diff --git a/models/ngspice/testing/.spiceinit b/models/ngspice/testing/.spiceinit
new file mode 100644
index 0000000..6fc9af8
--- /dev/null
+++ b/models/ngspice/testing/.spiceinit
@@ -0,0 +1,2 @@
+************
+set ngbehavior=hs
diff --git a/models/ngspice/testing/180MCU_SPICE_DATA/BJT/bjt_cv_npn.nl_out.xlsx b/models/ngspice/testing/180MCU_SPICE_DATA/BJT/bjt_cv_npn.nl_out.xlsx
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diff --git a/models/ngspice/testing/180MCU_SPICE_DATA/BJT/bjt_mm_pnp.nl_out.xlsx b/models/ngspice/testing/180MCU_SPICE_DATA/BJT/bjt_mm_pnp.nl_out.xlsx
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diff --git a/models/ngspice/testing/180MCU_SPICE_DATA/BJT/bjt_npn_beta_r.nl_out.xlsx b/models/ngspice/testing/180MCU_SPICE_DATA/BJT/bjt_npn_beta_r.nl_out.xlsx
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diff --git a/models/ngspice/testing/180MCU_SPICE_DATA/BJT/bjt_npn_flyback_f.nl_out.xlsx b/models/ngspice/testing/180MCU_SPICE_DATA/BJT/bjt_npn_flyback_f.nl_out.xlsx
new file mode 100644
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new file mode 100644
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diff --git a/models/ngspice/testing/180MCU_SPICE_DATA/BJT/bjt_npn_gummel_f.nl_out.xlsx b/models/ngspice/testing/180MCU_SPICE_DATA/BJT/bjt_npn_gummel_f.nl_out.xlsx
new file mode 100644
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new file mode 100644
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diff --git a/models/ngspice/testing/180MCU_SPICE_DATA/BJT/bjt_npn_icvc_f.nl_out.xlsx b/models/ngspice/testing/180MCU_SPICE_DATA/BJT/bjt_npn_icvc_f.nl_out.xlsx
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diff --git a/models/ngspice/testing/180MCU_SPICE_DATA/Cap/mimcap_fc.nl_out.xlsx b/models/ngspice/testing/180MCU_SPICE_DATA/Cap/mimcap_fc.nl_out.xlsx
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diff --git a/models/ngspice/testing/180MCU_SPICE_DATA/Cap/moscap_cv_6p0.nl_out.xlsx b/models/ngspice/testing/180MCU_SPICE_DATA/Cap/moscap_cv_6p0.nl_out.xlsx
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diff --git a/models/ngspice/testing/Makefile b/models/ngspice/testing/Makefile
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+++ b/models/ngspice/testing/Makefile
@@ -0,0 +1,182 @@
+# Copyright 2022 Efabless Corporation
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#      http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+#=================================================================
+# ------------------------ models_ngspice ------------------------
+#=================================================================
+
+SHELL := /bin/bash
+Testing_DIR ?= $(shell pwd)
+run_folder  := $(shell date +'run_%Y_%m_%d_%H:%M:%S')
+
+
+.DEFAULT_GOAL := all
+
+all : test-models_ngspice
+
+test-models_ngspice: smoke-test models-MOS  models-BJT models-diode models-MOSCAP models-MIMCAP models-RES 
+
+#================================
+#---------- Create Run ----------
+#================================
+
+.ONESHELL:
+Add_run-dir:
+	@cd $(Testing_DIR)
+	@ [ ! -d "$(run_folder)/" ] && cp -rf $(Testing_DIR)/regression $(Testing_DIR)/$(run_folder)
+
+#================================
+#---------- smoke-test ----------
+#================================
+
+.ONESHELL:
+smoke-test:
+	@cd $(Testing_DIR)/smoke_test
+	@python3 ng_smoke_test.py
+
+
+#================================
+# ---------- models-MOS----------
+#================================
+
+.ONESHELL:
+models-MOS: Add_run-dir
+	@cd $(Testing_DIR)/$(run_folder)/mos_iv_vgs
+	@echo "========== Runing models_ngspice-MOS regression ==========" |& tee -a ../run_log.log 
+	@python3 models_regression.py |& tee -a ../run_log.log 
+# @cd ../mos_iv_vbs
+# @python3 models_regression.py |& tee -a ../run_log.log  
+
+# .ONESHELL:
+# clean-models-MOS:
+# 	@echo "==== Cleaning models-MOS old runs ===="
+# 	@cd $(Testing_DIR)/$(run_folder)/mos_iv_vgs && rm -rf nmos_* pmos_*
+
+#================================
+# ---------- models-BJT----------
+#================================
+
+.ONESHELL:
+models-BJT: Add_run-dir
+	@cd $(Testing_DIR)/$(run_folder)/bjt_cj
+	@echo "========== Runing models_ngspice-BJT regression ==========" |& tee -a ../run_log.log 
+	@python3 models_regression.py |& tee -a ../run_log.log
+
+
+# .ONESHELL:
+# clean-models-BJT:
+# 	@echo "==== Cleaning models-BJT old runs ===="
+# 	@cd $(Testing_DIR)/$(run_folder)/bjt_cj && rm -rf vnpn_* vpnp_*
+
+#================================
+# --------- models-diode --------
+#================================
+
+.ONESHELL:
+models-diode: Add_run-dir
+	@cd $(Testing_DIR)/$(run_folder)/diode
+	@echo "========== Runing models_ngspice-didoe regression ==========" |& tee -a ../run_log.log 
+	@python3 models_regression.py |& tee -a ../run_log.log
+
+
+# .ONESHELL:
+# clean-models-diode:
+# 	@echo "==== Cleaning models-diode old runs ===="
+# 	@cd $(Testing_DIR)/$(run_folder)/diode && rm -rf np_* pn_* nwp* dnw* sc_*
+
+#================================
+# -------- models-MOSCAP --------
+#================================
+
+.ONESHELL:
+models-MOSCAP: Add_run-dir
+	@cd $(Testing_DIR)/$(run_folder)/moscap_c
+	@echo "========== Runing models_ngspice-MOSCAP regression ==========" |& tee -a ../run_log.log 
+	@python3 models_regression.py |& tee -a ../run_log.log
+
+
+# .ONESHELL:
+# clean-models-MOSCAP:
+# 	@echo "==== Cleaning models-MOSCAP old runs ===="
+# 	@cd $(Testing_DIR)/$(run_folder)/moscap_c && rm -rf nmoscap_* pmoscap_*	
+
+#================================
+# -------- models-MIMCAP --------
+#================================
+
+.ONESHELL:
+models-MIMCAP: Add_run-dir
+	@cd $(Testing_DIR)/$(run_folder)/mimcap_c
+	@echo "========== Runing models_ngspice-MIMCAP regression ==========" |& tee -a ../run_log.log 
+	@python3 models_regression.py |& tee -a ../run_log.log
+
+
+# .ONESHELL:
+# clean-models-MIMCAP:
+# 	@echo "==== Cleaning models-MIMCAP old runs ===="
+# 	@cd $(Testing_DIR)/$(run_folder)/mimcap_c && rm -rf mim*		
+
+
+#================================
+# --------- models-RES ----------
+#================================
+
+.ONESHELL:
+models-RES: Add_run-dir
+	@cd $(Testing_DIR)/$(run_folder)/resistor_r
+	@echo "========== Runing models_ngspice-RES regression ==========" |& tee -a ../run_log.log 
+	@python3 models_regression.py |& tee -a ../run_log.log
+
+
+# .ONESHELL:
+# clean-models-RES:
+# 	@echo "==== Cleaning models-RES old runs ===="
+# 	@cd $(Testing_DIR)/$(run_folder)/resistor_r && rm -rf nplus* pplus* npoly* ppoly* rm* tm* nwell
+
+
+
+# #===============================
+# # --------- Clean ALL ----------
+# #===============================
+
+# .ONESHELL:
+# clean: clean-models-MOS clean-models-BJT clean-models-diode clean-models-MOSCAP clean-models-MIMCAP clean-models-RES
+# 	@echo "==== Cleaning all runs is done ===="
+
+
+#==========================
+# --------- HELP ----------
+#==========================
+
+# Help Target
+help:
+	@echo "\n ==== The following are some of the valid targets for this Makefile ====\n"
+	@echo "... all                  (the default if no target is provided)"
+	@echo "... smoke-test           (To run smoke test for    an inverter)"
+	@echo "... test-models_ngspice  (To run regression for all    devices)"
+	@echo "... models-MOS           (To run regression for MOS    devices)"
+	@echo "... models-BJT           (To run regression for BJT    devices)"
+	@echo "... models-diode         (To run regression for diode  devices)"
+	@echo "... models-MOSCAP        (To run regression for MOSCAP devices)"
+	@echo "... models-MIMCAP        (To run regression for MIMCAP devices)"
+	@echo "... models-RES           (To run regression for RES    devices)"
+# @echo "... clean-models-MOS     (To clean old runs for MOS    devices)"
+# @echo "... clean-models-BJT     (To clean old runs for BJT    devices)"
+# @echo "... clean-models-diode   (To clean old runs for diode  devices)"
+# @echo "... clean-models-MOSCAP  (To clean old runs for MOSCAP devices)"
+# @echo "... clean-models-MIMCAP  (To clean old runs for MIMCAP devices)"
+# @echo "... clean-models-RES     (To run regression for RES    devices)"
+# @echo "... clean                (To clean all old runs)               "
+   
+.PHONY : help
diff --git a/models/ngspice/testing/README.md b/models/ngspice/testing/README.md
new file mode 100644
index 0000000..2205747
--- /dev/null
+++ b/models/ngspice/testing/README.md
@@ -0,0 +1,51 @@
+# Globalfoundries 180nm MCU models-ngspice regression
+
+Explains how to run GF180nm models-ngspice regression.
+
+## Folder Structure
+
+```text
+📦testing
+ ┣ 📜Makefile
+ ┣ 📜README.md
+ ┣ 📦regression
+ ┣ 📦smoke_test
+ ┣ 📦180MCU_SPICE_Models
+ ```
+
+## Prerequisites
+
+At a minimum:
+
+- Git 2.35+
+- Python 3.6+
+- ngspice-36+
+
+### On Ubuntu, you can just
+
+`apt install -y build-essential python3`
+
+- Check this [ngspice](http://ngspice.sourceforge.net/download.html) for ngspice installation.
+
+## Regression Usage
+
+To make a full test for GF180nm models-ngspice, you could use the following command in testing directory:
+
+```bash
+make all
+```
+
+- You could also check allowed targets in the Makefile, using the following command:
+
+    ```bash
+    make help
+    ```
+
+## **Regression Outputs**
+
+- The resulting files are in `regression/<device_folder>/` with name of `<device_name><options>` that contains:
+
+    1. A final report file of all results.
+    2. measured folder that contains measured data used in regression.
+    3. simulated folder that contains simulated data used in regression.
+    4. netlists folder that contains spice files used in simulation.
diff --git a/models/ngspice/testing/regression/.spiceinit b/models/ngspice/testing/regression/.spiceinit
new file mode 100644
index 0000000..6fc9af8
--- /dev/null
+++ b/models/ngspice/testing/regression/.spiceinit
@@ -0,0 +1,2 @@
+************
+set ngbehavior=hs
diff --git a/models/ngspice/testing/regression/bjt_beta/.spiceinit b/models/ngspice/testing/regression/bjt_beta/.spiceinit
new file mode 100644
index 0000000..6fc9af8
--- /dev/null
+++ b/models/ngspice/testing/regression/bjt_beta/.spiceinit
@@ -0,0 +1,2 @@
+************
+set ngbehavior=hs
diff --git a/models/ngspice/testing/regression/bjt_beta/device_netlists/npn.spice b/models/ngspice/testing/regression/bjt_beta/device_netlists/npn.spice
new file mode 100644
index 0000000..e25a8d2
--- /dev/null
+++ b/models/ngspice/testing/regression/bjt_beta/device_netlists/npn.spice
@@ -0,0 +1,29 @@
+*****************
+** main netlist
+*****************
+
+Vcp c 0 dc 3
+Vbp b 0 dc 1.2
+
+.temp {{temp}}
+.options tnom={{temp}}
+
+xq1 c b 0 0 {{device}}
+
+
+*****************
+** Analysis
+*****************
+
+.control
+set filetype=ascii
+
+dc Vbp 0.2 1.2 0.01 Vcp 1 3 1
+wrdata npn/simulated_Ic/{{i}}_simulated_{{device}}.csv -i(Vcp)
+wrdata npn/simulated_Ib/{{i}}_simulated_{{device}}.csv -i(Vbp)
+.endc
+
+.include "../../../design.ngspice"
+.lib "../../../sm141064.ngspice" bjt_typical
+
+.end
diff --git a/models/ngspice/testing/regression/bjt_beta/device_netlists/pnp.spice b/models/ngspice/testing/regression/bjt_beta/device_netlists/pnp.spice
new file mode 100644
index 0000000..d6a9414
--- /dev/null
+++ b/models/ngspice/testing/regression/bjt_beta/device_netlists/pnp.spice
@@ -0,0 +1,29 @@
+*****************
+** main netlist
+*****************
+
+Vcp c 0 dc -3
+Vbp b 0 dc -1.2
+
+.temp {{temp}}
+.options tnom={{temp}}
+
+xq1 c b 0 {{device}}
+
+
+*****************
+** Analysis
+*****************
+
+.control
+set filetype=ascii
+
+dc Vbp -0.2 -1.2 -0.01 Vcp -1 -3 -1
+wrdata pnp/simulated_Ic/{{i}}_simulated_{{device}}.csv i(Vcp)
+wrdata pnp/simulated_Ib/{{i}}_simulated_{{device}}.csv i(Vbp)
+.endc
+
+.include "../../../design.ngspice"
+.lib "../../../sm141064.ngspice" bjt_typical
+
+.end
diff --git a/models/ngspice/testing/regression/bjt_beta/device_netlists/run_npn_beta.spice b/models/ngspice/testing/regression/bjt_beta/device_netlists/run_npn_beta.spice
new file mode 100644
index 0000000..b21c115
--- /dev/null
+++ b/models/ngspice/testing/regression/bjt_beta/device_netlists/run_npn_beta.spice
@@ -0,0 +1,34 @@
+
+*****************
+** main netlist
+*****************
+
+Vcp c 0 dc 3
+*Ib 0 b 9u
+Vbp b 0 dc 1.2
+
+.temp 25
+.options tnom=25
+
+xq1 c b 0 0 vnpn_10x10
+
+
+*****************
+** Analysis
+*****************
+
+.control
+set filetype=ascii
+
+dc Vbp 0.2 1.2 0.01 Vcp 1 3 1
+print -i(Vcp)
+print -i(Vbp)
+wrdata result.csv -i(Vcp)
+wrdata result.csv -i(Vbp)
+.endc
+
+.include "../../../design.ngspice"
+.lib "../../../sm141064.ngspice" bjt_typical
+
+.end
+
diff --git a/models/ngspice/testing/regression/bjt_beta/models_regression.py b/models/ngspice/testing/regression/bjt_beta/models_regression.py
new file mode 100644
index 0000000..6d8c5f2
--- /dev/null
+++ b/models/ngspice/testing/regression/bjt_beta/models_regression.py
@@ -0,0 +1,243 @@
+"""
+Usage:
+  models_regression.py [--num_cores=<num>]
+
+  -h, --help             Show help text.
+  -v, --version          Show version.
+  --num_cores=<num>      Number of cores to be used by simulator
+"""
+
+from cmath import inf
+from re import T
+from docopt import docopt
+import pandas as pd 
+import numpy as np
+import os 
+from jinja2 import Template
+import concurrent.futures
+import shutil
+import warnings
+warnings.simplefilter(action='ignore', category=FutureWarning)
+
+def call_simulator(file_name):
+    """Call simulation commands to perform simulation.
+    Args:
+        file_name (str): Netlist file name.
+    """
+    os.system(f"ngspice -b -a {file_name} -o {file_name}.log > {file_name}.log")
+
+def ext_measured(device,vb,step,Id_sim,list_devices,vc):
+
+    # Get dimensions used for each device 
+    dimensions = pd.read_csv(f"{device}/{device}.csv",usecols=["corners"])
+    loops = dimensions["corners"].count()
+
+    # Extracting measured values for each Device 
+    for i in range (loops):
+        k = i
+        if i >= len(list_devices):
+            while k >= len(list_devices):
+                k = k - len(list_devices)
+
+        # Special case for 1st measured values 
+        if i == 0 :
+            if device == "pnp":
+                temp_vb = vb
+                vb = "-vb "
+            # measured Id_sim 0
+            col_list = [f"{vb}",f"{vc}{step[0]}",f"{vc}{step[1]}",f"{vc}{step[2]}"]
+            df_measured = pd.read_csv(f"{device}/{device}.csv",usecols=col_list)
+            df_measured.columns = [f"{vb}",f"{vc}{step[0]}",f"{vc}{step[1]}",f"{vc}{step[2]}"]
+            df_measured.to_csv(f"{device}/measured_{Id_sim[0]}/{i}_measured_{list_devices[k]}.csv", index = False)
+
+            if device == "pnp":
+                vb = temp_vb
+
+            # measured Id_sim 1
+            col_list = [f"{vb}",f"{vc}{step[0]}.{2*i+1}",f"{vc}{step[1]}.{2*i+1}",f"{vc}{step[2]}.{2*i+1}"]
+            df_measured = pd.read_csv(f"{device}/{device}.csv",usecols=col_list)
+            df_measured.columns = [f"{vb}",f"{vc}{step[0]}",f"{vc}{step[1]}",f"{vc}{step[2]}"]        
+            df_measured.to_csv(f"{device}/measured_{Id_sim[1]}/{i}_measured_{list_devices[k]}.csv", index = False)
+        else:
+            # measured Id_sim 0
+            col_list = [f"{vb}",f"{vc}{step[0]}.{2*i}",f"{vc}{step[1]}.{2*i}",f"{vc}{step[2]}.{2*i}"]
+            df_measured = pd.read_csv(f"{device}/{device}.csv",usecols=col_list)
+            df_measured.columns = [f"{vb}",f"{vc}{step[0]}",f"{vc}{step[1]}",f"{vc}{step[2]}"]        
+            df_measured.to_csv(f"{device}/measured_{Id_sim[0]}/{i}_measured_{list_devices[k]}.csv", index = False)
+
+            # measured Id_sim 1
+            col_list = [f"{vb}",f"{vc}{step[0]}.{2*i+1}",f"{vc}{step[1]}.{2*i+1}",f"{vc}{step[2]}.{2*i+1}"]
+            df_measured = pd.read_csv(f"{device}/{device}.csv",usecols=col_list)
+            df_measured.columns = [f"{vb}",f"{vc}{step[0]}",f"{vc}{step[1]}",f"{vc}{step[2]}"]        
+            df_measured.to_csv(f"{device}/measured_{Id_sim[1]}/{i}_measured_{list_devices[k]}.csv", index = False)
+
+def ext_simulated(device,vc,step,sweep,Id_sim,list_devices,ib):
+
+    # Get dimensions used for each device 
+    dimensions = pd.read_csv(f"{device}/{device}.csv",usecols=["corners"])
+    loops = dimensions["corners"].count()
+    temp_range = int(loops/4) 
+    netlist_tmp = f"./device_netlists/{device}.spice"
+    for i in range (loops):
+        if i in range (0,temp_range):               temp = 25
+        elif i in range (temp_range,2*temp_range):  temp = -40
+        elif i in range (2*temp_range,3*temp_range):temp = 125
+        else:                                       temp = 175 
+
+        k = i
+        if i >= len(list_devices):
+            while k >= len(list_devices):
+                k = k - len(list_devices)
+
+        with open(netlist_tmp) as f:
+            tmpl = Template(f.read())
+            os.makedirs(f"{device}/{device}_netlists_sim",exist_ok=True)
+            with open(f"{device}/{device}_netlists_sim/{i}_{device}_netlist_{list_devices[k]}.spice", "w") as netlist:
+                netlist.write(tmpl.render(device = list_devices[k], i = i , temp = temp ))
+            netlist_path  = f"{device}/{device}_netlists_sim/{i}_{device}_netlist_{list_devices[k]}.spice" 
+
+            # Running ngspice for each netlist 
+            with concurrent.futures.ProcessPoolExecutor(max_workers=workers_count) as executor:
+                executor.submit(call_simulator, netlist_path)
+
+        # Writing simulated data 0
+        df_simulated = pd.read_csv(f"{device}/simulated_{Id_sim[0]}/{i}_simulated_{list_devices[k]}.csv",header=None, delimiter=r"\s+")
+
+        # empty array to append in it shaped (sweep, number of trials + 1)
+        new_array = np.empty((sweep, 1+int(df_simulated.shape[0]/sweep)))  
+        new_array[:, 0] = df_simulated.iloc[:sweep, 0]
+        times = int(df_simulated.shape[0]/sweep)
+
+        for j in range(times):
+            new_array[:, (j+1)] = df_simulated.iloc[j*sweep:(j+1)*sweep, 1]
+
+        # Writing final simulated data 0
+        df_simulated = pd.DataFrame(new_array)
+        df_simulated.to_csv(f"{device}/simulated_{Id_sim[0]}/{i}_simulated_{list_devices[k]}.csv",index= False)    
+        df_simulated.columns = [f"{vc}",f"{ib}{step[0]}",f"{ib}{step[1]}",f"{ib}{step[2]}"]
+        df_simulated.to_csv(f"{device}/simulated_{Id_sim[0]}/{i}_simulated_{list_devices[k]}.csv",index= False)
+
+
+        # Writing simulated data 1
+        df_simulated = pd.read_csv(f"{device}/simulated_{Id_sim[1]}/{i}_simulated_{list_devices[k]}.csv",header=None, delimiter=r"\s+")
+
+        # empty array to append in it shaped (sweep, number of trials + 1)
+        new_array = np.empty((sweep, 1+int(df_simulated.shape[0]/sweep)))  
+        new_array[:, 0] = df_simulated.iloc[:sweep, 0]
+        times = int(df_simulated.shape[0]/sweep)
+
+        for j in range(times):
+            new_array[:, (j+1)] = df_simulated.iloc[j*sweep:(j+1)*sweep, 1]
+
+        # Writing final simulated data 1
+        df_simulated = pd.DataFrame(new_array)
+        df_simulated.to_csv(f"{device}/simulated_{Id_sim[1]}/{i}_simulated_{list_devices[k]}.csv",index= False)    
+        df_simulated.columns = [f"{vc}",f"{ib}{step[0]}",f"{ib}{step[1]}",f"{ib}{step[2]}"]
+        df_simulated.to_csv(f"{device}/simulated_{Id_sim[1]}/{i}_simulated_{list_devices[k]}.csv",index= False)
+
+def error_cal(device,vb,step,Id_sim,list_devices,vc):
+
+    df_final = pd.DataFrame()
+    # Get dimensions used for each device 
+    dimensions = pd.read_csv(f"{device}/{device}.csv",usecols=["corners"])
+    loops = dimensions["corners"].count()
+    temp_range = int(loops/4) 
+    for i in range (loops):
+        if i in range (0,temp_range):               temp = 25
+        elif i in range (temp_range,2*temp_range):  temp = -40
+        elif i in range (2*temp_range,3*temp_range):temp = 125
+        else:                                       temp = 175 
+
+        k = i
+        if i >= len(list_devices):
+            while k >= len(list_devices):
+                k = k - len(list_devices)
+
+        measured  = pd.read_csv(f"{device}/measured_{Id_sim}/{i}_measured_{list_devices[k]}.csv")
+        simulated = pd.read_csv(f"{device}/simulated_{Id_sim}/{i}_simulated_{list_devices[k]}.csv")
+
+        error_1 = round (100 * abs((abs(measured.iloc[0:, 1]) - abs(simulated.iloc[0:, 1]))/abs(measured.iloc[:, 1])),6)
+        error_2 = round (100 * abs((abs(measured.iloc[0:, 2]) - abs(simulated.iloc[0:, 2]))/abs(measured.iloc[:, 2])),6)
+        error_3 = round (100 * abs((abs(measured.iloc[0:, 3]) - abs(simulated.iloc[0:, 3]))/abs(measured.iloc[:, 3])),6)
+
+        df_error = pd.DataFrame(data=[measured.iloc[:, 0],error_1,error_2,error_3]).transpose()
+        df_error.replace([np.inf, -np.inf], df_error.max().nlargest(2).iloc[1], inplace=True)
+        df_error.to_csv(f"{device}/error_{Id_sim}/{i}_{device}_error_{list_devices[k]}.csv",index= False)
+
+        # Mean error 
+        mean_error = (df_error[f"{vc}{step[0]}"].mean() + df_error[f"{vc}{step[1]}"].mean() + df_error[f"{vc}{step[2]}"].mean())/6
+        # Max error 
+        max_error = df_error[[f"{vc}{step[0]}",f"{vc}{step[1]}",f"{vc}{step[2]}"]].max().max()
+        # Max error location 
+        max_index = max((df_error == max_error).idxmax())
+        max_location_vc = (df_error == max_error).idxmax(axis=1)[max_index]
+        if Id_sim == "Ic":
+            if i == 0 :
+                if device == "pnp":
+                    temp_vb = vb
+                    vb = "-vb "
+            else:
+                if device == "pnp":
+                    vb = temp_vb
+        max_location_vb = df_error[f"{vb}"][max_index]
+
+        df_final_ = {'Run no.': f'{i}', 'Temp': f'{temp}', 'Device name': f'{device}', 'device': f'{list_devices[k]}','Simulated_Val':f'{Id_sim}','Mean error%':f'{"{:.2f}".format(mean_error)}', 'Max error%':f'{"{:.2f}".format(max_error)} @ {max_location_vc} & Vc (V) = {max_location_vb}'}
+        df_final = df_final.append(df_final_, ignore_index = True)
+
+    # Max mean error 
+    print (df_final)   
+    df_final.to_csv (f"{device}/Final_report_{Id_sim}.csv", index = False)
+    out_report = pd.read_csv (f"{device}/Final_report_{Id_sim}.csv")
+    print ("\n",f"Max. mean error = {out_report['Mean error%'].max()}%")    
+    print ("=====================================================================================================================================================")
+
+def main():
+
+    devices = ["npn","pnp"]
+    list_devices = [["vnpn_10x10" , "vnpn_5x5" , "vnpn_0p54x16" , "vnpn_0p54x8" , "vnpn_0p54x4", "vnpn_0p54x2"],
+                    ["vpnp_0p42x10" , "vpnp_0p42x5", "vpnp_10x10" , "vpnp_5x5"]]
+    vb = ["vbp ","-vb (V)"]
+    vc = ["vcp =","vc =-"]
+    Id_sim  = ["Ic","Ib"]
+    sweep = 101
+    step = [1, 2, 3]
+
+    for i, device in enumerate(devices): 
+        # Folder structure of measured values 
+        dirpath = f"{device}"
+        if os.path.exists(dirpath) and os.path.isdir(dirpath):
+            shutil.rmtree(dirpath)
+        os.makedirs(f"{device}/measured_{Id_sim[0]}",exist_ok=False)
+        os.makedirs(f"{device}/measured_{Id_sim[1]}",exist_ok=False)
+
+        # From xlsx to csv 
+        read_file = pd.read_excel (f"../../180MCU_SPICE_DATA/BJT/bjt_{device}_beta_f.nl_out.xlsx")
+        read_file.to_csv (f"{device}/{device}.csv", index = False, header=True)
+
+        # Folder structure of simulated values
+        os.makedirs(f"{device}/simulated_{Id_sim[0]}",exist_ok=False)
+        os.makedirs(f"{device}/error_{Id_sim[0]}",exist_ok=False)
+        os.makedirs(f"{device}/simulated_{Id_sim[1]}",exist_ok=False)
+        os.makedirs(f"{device}/error_{Id_sim[1]}",exist_ok=False)
+
+        # =========== Simulate ==============      
+        ext_measured (device,vb[i],step,Id_sim,list_devices[i],vc[i])
+
+        ext_simulated(device,vb[i],step,sweep,Id_sim,list_devices[i],vc[i])
+
+        # ============ Results ============= 
+        error_cal    (device,vb[i],step,Id_sim[0],list_devices[i],vc[i])
+        error_cal    (device,vb[i],step,Id_sim[1],list_devices[i],vc[i])
+
+# ================================================================
+# -------------------------- MAIN --------------------------------
+# ================================================================
+
+if __name__ == "__main__":
+
+    # Args
+    arguments     = docopt(__doc__, version='comparator: 0.1')
+    workers_count = os.cpu_count()*2 if arguments["--num_cores"] == None else int(arguments["--num_cores"])
+
+    # Calling main function 
+    main()
diff --git a/models/ngspice/testing/regression/bjt_cj/.spiceinit b/models/ngspice/testing/regression/bjt_cj/.spiceinit
new file mode 100644
index 0000000..7779a4c
--- /dev/null
+++ b/models/ngspice/testing/regression/bjt_cj/.spiceinit
@@ -0,0 +1,2 @@
+* user provided init file
+set ngbehavior=hs
diff --git a/models/ngspice/testing/regression/bjt_cj/device_netlists/.spiceinit b/models/ngspice/testing/regression/bjt_cj/device_netlists/.spiceinit
new file mode 100644
index 0000000..7779a4c
--- /dev/null
+++ b/models/ngspice/testing/regression/bjt_cj/device_netlists/.spiceinit
@@ -0,0 +1,2 @@
+* user provided init file
+set ngbehavior=hs
diff --git a/models/ngspice/testing/regression/bjt_cj/device_netlists/damping_test.spice b/models/ngspice/testing/regression/bjt_cj/device_netlists/damping_test.spice
new file mode 100644
index 0000000..cf16aa3
--- /dev/null
+++ b/models/ngspice/testing/regression/bjt_cj/device_netlists/damping_test.spice
@@ -0,0 +1,43 @@
+***************************
+** CV netlist generation **
+***************************
+* Copyright 2022 Efabless Corporation
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*      http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+
+Vb b 0 dc -3.3
+
+.temp 25
+.options tnom=25
+      
+
+xq1 0 b 0 0 vnpn_10x10
+
+
+.DC Vb 0 -3.3 -0.1
+
+.control
+
+save all @q.xq1.q0[cpi]
+run 
+print  @q.xq1.q0[cpi]   
+
+.endc
+
+** library calling
+
+.include "../../../../design.ngspice"
+.lib "../../../../sm141064.ngspice" bjt_typical
+
+
+.end
diff --git a/models/ngspice/testing/regression/bjt_cj/device_netlists/npn_CBJ.spice b/models/ngspice/testing/regression/bjt_cj/device_netlists/npn_CBJ.spice
new file mode 100644
index 0000000..5b9e251
--- /dev/null
+++ b/models/ngspice/testing/regression/bjt_cj/device_netlists/npn_CBJ.spice
@@ -0,0 +1,44 @@
+***************************
+** CV netlist generation **
+***************************
+* Copyright 2022 Efabless Corporation
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*      http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+Vb b 0 dc -3.3
+
+.temp {{temp}}
+.options tnom={{temp}}
+      
+
+xq1 0 b 0 0 {{device}}
+
+
+.DC Vb 0 -3.3 -0.1
+
+.control
+
+save all @q.xq1.q0[cmu]
+run 
+print  @q.xq1.q0[cmu]
+
+wrdata {{device}}_{{cv_sim}}_{{corner}}_T{{temp}}/simulated_{{cv_sim}}/1_simulated_{{device}}.csv @q.xq1.q0[cmu]*1.0e15
+
+.endc
+
+** library calling
+
+.include "../../../design.ngspice"
+.lib "../../../sm141064.ngspice" bjt_{{corner}}
+
+
+.end
diff --git a/models/ngspice/testing/regression/bjt_cj/device_netlists/npn_CSJ.spice b/models/ngspice/testing/regression/bjt_cj/device_netlists/npn_CSJ.spice
new file mode 100644
index 0000000..0a09963
--- /dev/null
+++ b/models/ngspice/testing/regression/bjt_cj/device_netlists/npn_CSJ.spice
@@ -0,0 +1,44 @@
+***************************
+** CV netlist generation **
+***************************
+* Copyright 2022 Efabless Corporation
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*      http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+Vb b 0 dc -3.3
+
+.temp {{temp}}
+.options tnom={{temp}}
+      
+
+xq1 0 0 0 b {{device}}
+
+
+.DC Vb 0 -3.3 -0.1
+
+.control
+
+save all @q.xq1.q0[csub]
+run 
+print  @q.xq1.q0[csub]
+
+wrdata {{device}}_{{cv_sim}}_{{corner}}_T{{temp}}/simulated_{{cv_sim}}/2_simulated_{{device}}.csv @q.xq1.q0[csub]*1.0e15
+
+.endc
+
+** library calling
+
+.include "../../../design.ngspice"
+.lib "../../../sm141064.ngspice" bjt_{{corner}}
+
+
+.end
diff --git a/models/ngspice/testing/regression/bjt_cj/device_netlists/npn_EBJ.spice b/models/ngspice/testing/regression/bjt_cj/device_netlists/npn_EBJ.spice
new file mode 100644
index 0000000..e735dbc
--- /dev/null
+++ b/models/ngspice/testing/regression/bjt_cj/device_netlists/npn_EBJ.spice
@@ -0,0 +1,44 @@
+***************************
+** CV netlist generation **
+***************************
+* Copyright 2022 Efabless Corporation
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*      http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+Vb b 0 dc -3.3
+
+.temp {{temp}}
+.options tnom={{temp}}
+      
+
+xq1 0 b 0 0 {{device}}
+
+
+.DC Vb 0 -3.3 -0.1
+
+.control
+
+save all @q.xq1.q0[cpi]
+run 
+print  @q.xq1.q0[cpi]
+
+wrdata {{device}}_{{cv_sim}}_{{corner}}_T{{temp}}/simulated_{{cv_sim}}/0_simulated_{{device}}.csv @q.xq1.q0[cpi]*1.0e15
+
+.endc
+
+** library calling
+
+.include "../../../design.ngspice"
+.lib "../../../sm141064.ngspice" bjt_{{corner}}
+
+
+.end
diff --git a/models/ngspice/testing/regression/bjt_cj/device_netlists/pnp_CBJ.spice b/models/ngspice/testing/regression/bjt_cj/device_netlists/pnp_CBJ.spice
new file mode 100644
index 0000000..9d1a0ee
--- /dev/null
+++ b/models/ngspice/testing/regression/bjt_cj/device_netlists/pnp_CBJ.spice
@@ -0,0 +1,44 @@
+***************************
+** CV netlist generation **
+***************************
+* Copyright 2022 Efabless Corporation
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*      http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+Vb b 0 dc -3.3
+
+.temp {{temp}}
+.options tnom={{temp}}
+      
+
+xq1 b 0 0 {{device}}
+
+
+.DC Vb 0 -3.3 -0.1
+
+.control
+
+save all @q.xq1.q0[cmu]
+run 
+print  @q.xq1.q0[cmu]
+
+wrdata {{device}}_{{cv_sim}}_{{corner}}_T{{temp}}/simulated_{{cv_sim}}/1_simulated_{{device}}.csv @q.xq1.q0[cmu]*1.0e15
+
+.endc
+
+** library calling
+
+.include "../../../design.ngspice"
+.lib "../../../sm141064.ngspice" bjt_{{corner}}
+
+
+.end
diff --git a/models/ngspice/testing/regression/bjt_cj/device_netlists/pnp_EBJ.spice b/models/ngspice/testing/regression/bjt_cj/device_netlists/pnp_EBJ.spice
new file mode 100644
index 0000000..521b223
--- /dev/null
+++ b/models/ngspice/testing/regression/bjt_cj/device_netlists/pnp_EBJ.spice
@@ -0,0 +1,44 @@
+***************************
+** CV netlist generation **
+***************************
+* Copyright 2022 Efabless Corporation
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*      http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+Vb b 0 dc -3.3
+
+.temp {{temp}}
+.options tnom={{temp}}
+      
+
+xq1 0 0 b {{device}}
+
+
+.DC Vb 0 -3.3 -0.1
+
+.control
+
+save all @q.xq1.q0[cpi]
+run 
+print  @q.xq1.q0[cpi]
+
+wrdata {{device}}_{{cv_sim}}_{{corner}}_T{{temp}}/simulated_{{cv_sim}}/0_simulated_{{device}}.csv @q.xq1.q0[cpi]*1.0e15
+
+.endc
+
+** library calling
+
+.include "../../../design.ngspice"
+.lib "../../../sm141064.ngspice" bjt_{{corner}}
+
+
+.end
diff --git a/models/ngspice/testing/regression/bjt_cj/models_regression.py b/models/ngspice/testing/regression/bjt_cj/models_regression.py
new file mode 100644
index 0000000..aeba47a
--- /dev/null
+++ b/models/ngspice/testing/regression/bjt_cj/models_regression.py
@@ -0,0 +1,202 @@
+# Copyright 2022 Efabless Corporation
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#      http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+"""
+Usage:
+  models_regression.py [--num_cores=<num>]
+
+  -h, --help             Show help text.
+  -v, --version          Show version.
+  --num_cores=<num>      Number of cores to be used by simulator
+"""
+
+from re import T
+from docopt import docopt
+import pandas as pd 
+import numpy as np
+import os 
+from jinja2 import Template
+import concurrent.futures
+import shutil
+import warnings
+warnings.simplefilter(action='ignore', category=FutureWarning)
+
+def call_simulator(file_name):
+    """Call simulation commands to perform simulation.
+    Args:
+        file_name (str): Netlist file name.
+    """
+    os.system(f"ngspice -b -a {file_name} -o {file_name}.log > {file_name}.log")
+
+def ext_measured(device,vn,d_in, cv_sim, corner,start,dirpath):
+    
+    # Get dimensions used for each device 
+    if "vnpn" in device:
+        loops = 3
+    else:
+        loops = 2 
+        
+    # Extracting measured values for each W & L 
+    for i in range (start,loops+start):
+
+        # Special case for 1st measured values 
+        if i == 0 :
+            # measured Id
+            col_list = [f"{vn}",f"{d_in}_{corner}"]
+            df_measured = pd.read_csv(f"{dirpath}/{device}.csv",usecols=col_list)
+            df_measured.columns = [f"{vn}",f"{d_in}_{corner}"]
+            df_measured.to_csv(f"{dirpath}/measured_{cv_sim}/{i-start}_measured_{device}.csv", index = False)
+        else:
+            # measured Id
+            col_list = [f"{vn}",f"{d_in}_{corner}.{i}"]
+            df_measured = pd.read_csv(f"{dirpath}/{device}.csv",usecols=col_list)
+            df_measured.columns = [f"{vn}",f"{d_in}_{corner}"]        
+            df_measured.to_csv(f"{dirpath}/measured_{cv_sim}/{i-start}_measured_{device}.csv", index = False)
+
+def ext_simulated(device,vn,d_in,cv_sim, corner,temp,dirpath,cap):
+    
+    # Get dimensions used for each device 
+    netlist_tmp = f"./device_netlists/{cap}.spice"
+    
+    if "EBJ" in cap: i = 0 
+    elif "CBJ" in cap: i = 1
+    else: i =2 
+    
+    with open(netlist_tmp) as f:
+        tmpl = Template(f.read())
+        os.makedirs(f"{dirpath}/{device}_netlists_{cv_sim}",exist_ok=True)
+        with open(f"{dirpath}/{device}_netlists_{cv_sim}/{i}_{device}_netlist_{device}.spice", "w") as netlist:
+            netlist.write(tmpl.render(device = device, i = i , temp = temp, cv_sim = cv_sim , corner = corner ))
+        netlist_path  = f"{dirpath}/{device}_netlists_{cv_sim}/{i}_{device}_netlist_{device}.spice" 
+        # Running ngspice for each netlist 
+        with concurrent.futures.ProcessPoolExecutor(max_workers=workers_count) as executor:
+            executor.submit(call_simulator, netlist_path)
+        
+        # Writing simulated data 
+        df_simulated = pd.read_csv(f"{dirpath}/simulated_{cv_sim}/{i}_simulated_{device}.csv",header=None, delimiter=r"\s+")
+        df_simulated.to_csv(f"{dirpath}/simulated_{cv_sim}/{i}_simulated_{device}.csv",index= False)    
+        df_simulated.columns = [f"{vn}",f"{d_in}_{corner}"]
+        df_simulated.to_csv(f"{dirpath}/simulated_{cv_sim}/{i}_simulated_{device}.csv",index= False)    
+
+def error_cal(device,vn,d_in,cv_sim, corner,temp,dirpath):
+    
+    # Get dimensions used for each device 
+    loops = 2    
+    df_final = pd.DataFrame()
+    for i in range (0,loops):
+        if i == 0  : cap = "EBJ" 
+        elif i == 1 : cap = "CBJ"
+        else : cap = "CSJ"
+        
+        measured  = pd.read_csv(f"{dirpath}/measured_{cv_sim}/{i}_measured_{device}.csv")
+        simulated = pd.read_csv(f"{dirpath}/simulated_{cv_sim}/{i}_simulated_{device}.csv")
+
+        error_1 = round (100 * abs((abs(measured.iloc[:, 1]) - abs(simulated.iloc[:, 1]))/abs(measured.iloc[:, 1])),6)  
+
+        df_error = pd.DataFrame(data=[measured.iloc[:, 0],error_1]).transpose()        
+        df_error.to_csv(f"{dirpath}/error_{cv_sim}/{i}_{device}_error_{device}.csv",index= False)
+        
+        # Mean error 
+        mean_error = (df_error[f"{d_in}_{corner}"].mean())
+        # Max error 
+        max_error = df_error[f"{d_in}_{corner}"].max()
+        # Max error location 
+        max_index = max((df_error == max_error).idxmax())
+        max_location_vgs = (df_error == max_error).idxmax(axis=1)[max_index]
+        max_location_vds = df_error[f"{vn}"][max_index]
+
+        df_final_ = {'Run no.': f'{i}', 'Temp': f'{temp}', 'Device name': f'{device}', 'corner': f'{corner}' , 'Junction': f'{cap}', 'Simulated_Val':f'{cv_sim}','Mean error%':f'{"{:.2f}".format(mean_error)}', 'Max error%':f'{"{:.2f}".format(max_error)} @ {max_location_vgs} & vn (V) = {max_location_vds}'}
+        df_final = df_final.append(df_final_, ignore_index = True)
+    # Max mean error 
+    print (df_final)   
+    df_final.to_csv (f"{dirpath}/Final_report_{cv_sim}.csv", index = False)
+    out_report = pd.read_csv (f"{dirpath}/Final_report_{cv_sim}.csv")
+    print ("\n",f"Max. mean error = {out_report['Mean error%'].max()}%")    
+    print ("=====================================================================================================================================================")
+
+def main():
+
+    corners = ["typical","ff","ss"]
+    temps   = [ 25 , -40 , 175 ]
+    measure = ["cv","Vj", "bjt", 31]
+    cv_sim, bjt_vn, bjt_in = measure[0], measure[1], measure[2] 
+    
+    #vnpn
+    npn_devices = ["vnpn_10x10" , "vnpn_5x5" , "vnpn_0p54x16" , "vnpn_0p54x8" , "vnpn_0p54x4" , "vnpn_0p54x2"]
+    npn_start = 0 
+    
+    for corner in corners:
+        for temp in temps:
+            for device in npn_devices: 
+                # Folder structure of measured values
+                dirpath = f"{device}_{cv_sim}_{corner}_T{temp}"
+                if os.path.exists(dirpath) and os.path.isdir(dirpath):
+                    shutil.rmtree(dirpath)
+                os.makedirs(f"{dirpath}/measured_{cv_sim}",exist_ok=False)
+
+                # From xlsx to csv 
+                read_file = pd.read_excel (f"../../180MCU_SPICE_DATA/BJT/{bjt_in}_{cv_sim}_npn.nl_out.xlsx")
+                read_file.to_csv (f"{dirpath}/{device}.csv", index = False, header=True)
+
+                # Folder structure of simulated values 
+                os.makedirs(f"{dirpath}/simulated_{cv_sim}",exist_ok=False)
+                os.makedirs(f"{dirpath}/error_{cv_sim}",exist_ok=False)
+                ext_measured (device,bjt_vn,bjt_in, cv_sim, corner,npn_start,dirpath)
+                ext_simulated(device,bjt_vn,bjt_in,cv_sim, corner,temp,dirpath,"npn_EBJ")
+                ext_simulated(device,bjt_vn,bjt_in,cv_sim, corner,temp,dirpath,"npn_CBJ")
+                # ext_simulated(device,bjt_vn,bjt_in,cv_sim, corner,temp,dirpath,"npn_CSJ")
+                error_cal    (device,bjt_vn,bjt_in,cv_sim, corner,temp,dirpath)
+                
+                npn_start = npn_start + 3
+        npn_start = 0
+
+    # vpnp
+    pnp_devices = ["vpnp_0p42x10" , "vpnp_0p42x5" , "vpnp_10x10" , "vpnp_5x5"]
+    pnp_start = 0 
+    
+    for corner in corners:
+        for temp in temps:
+            for device in pnp_devices: 
+                # Folder structure of measured values
+                dirpath = f"{device}_{cv_sim}_{corner}_T{temp}"
+                if os.path.exists(dirpath) and os.path.isdir(dirpath):
+                    shutil.rmtree(dirpath)
+                os.makedirs(f"{dirpath}/measured_{cv_sim}",exist_ok=False)
+
+                # From xlsx to csv 
+                read_file = pd.read_excel (f"../../180MCU_SPICE_DATA/BJT/{bjt_in}_{cv_sim}_pnp.nl_out.xlsx")
+                read_file.to_csv (f"{dirpath}/{device}.csv", index = False, header=True)
+
+                # Folder structure of simulated values 
+                os.makedirs(f"{dirpath}/simulated_{cv_sim}",exist_ok=False)
+                os.makedirs(f"{dirpath}/error_{cv_sim}",exist_ok=False)
+                ext_measured (device,bjt_vn,bjt_in, cv_sim, corner,pnp_start,dirpath)
+                ext_simulated(device,bjt_vn,bjt_in,cv_sim, corner,temp,dirpath,"pnp_EBJ")
+                ext_simulated(device,bjt_vn,bjt_in,cv_sim, corner,temp,dirpath,"pnp_CBJ")
+                error_cal    (device,bjt_vn,bjt_in,cv_sim, corner,temp,dirpath)
+                
+                pnp_start = pnp_start + 2
+        pnp_start = 0
+        
+# # ================================================================
+# -------------------------- MAIN --------------------------------
+# ================================================================
+        
+if __name__ == "__main__":
+    
+    # Args 
+    arguments     = docopt(__doc__, version='comparator: 0.1')
+    workers_count = os.cpu_count()*2 if arguments["--num_cores"] == None else int(arguments["--num_cores"])
+    
+    # Calling main function 
+    main()
diff --git a/models/ngspice/testing/regression/bjt_iv/.spiceinit b/models/ngspice/testing/regression/bjt_iv/.spiceinit
new file mode 100644
index 0000000..6fc9af8
--- /dev/null
+++ b/models/ngspice/testing/regression/bjt_iv/.spiceinit
@@ -0,0 +1,2 @@
+************
+set ngbehavior=hs
diff --git a/models/ngspice/testing/regression/bjt_iv/device_netlists/npn.spice b/models/ngspice/testing/regression/bjt_iv/device_netlists/npn.spice
new file mode 100644
index 0000000..792e40c
--- /dev/null
+++ b/models/ngspice/testing/regression/bjt_iv/device_netlists/npn.spice
@@ -0,0 +1,29 @@
+*****************
+** main netlist
+*****************
+
+Vcp c 0 dc 6
+Ib 0 b 9u
+
+.temp {{temp}}
+.options tnom={{temp}}
+
+xq1 c b 0 0 {{device}}
+
+
+*****************
+** Analysis
+*****************
+
+.control
+set filetype=ascii
+
+dc Vcp 0 6 0.1 Ib 1u 9u 2u
+print -i(Vcp)
+wrdata npn/simulated_IcVc/{{i}}_simulated_{{device}}.csv -i(Vcp)
+.endc
+
+.include "../../../design.ngspice"
+.lib "../../../sm141064.ngspice" bjt_typical
+
+.end
diff --git a/models/ngspice/testing/regression/bjt_iv/device_netlists/pnp.spice b/models/ngspice/testing/regression/bjt_iv/device_netlists/pnp.spice
new file mode 100644
index 0000000..0233ac6
--- /dev/null
+++ b/models/ngspice/testing/regression/bjt_iv/device_netlists/pnp.spice
@@ -0,0 +1,29 @@
+*****************
+** main netlist
+*****************
+
+Vcp c 0 dc -3
+Ib 0 b -9u
+
+.temp {{temp}}
+.options tnom={{temp}}
+
+xq1 c b 0 {{device}}
+
+
+*****************
+** Analysis
+*****************
+
+.control
+set filetype=ascii
+
+dc Vcp 0 -3 -0.1 Ib -1u -9u -2u
+print -i(Vcp)
+wrdata pnp/simulated_IcVc/{{i}}_simulated_{{device}}.csv i(Vcp)
+.endc
+
+.include "../../../design.ngspice"
+.lib "../../../sm141064.ngspice" bjt_typical
+
+.end
diff --git a/models/ngspice/testing/regression/bjt_iv/device_netlists/run_npn_vcic.spice b/models/ngspice/testing/regression/bjt_iv/device_netlists/run_npn_vcic.spice
new file mode 100644
index 0000000..48f9bb3
--- /dev/null
+++ b/models/ngspice/testing/regression/bjt_iv/device_netlists/run_npn_vcic.spice
@@ -0,0 +1,30 @@
+
+*****************
+** main netlist
+*****************
+
+Vcp c 0 dc 6
+Ib 0 b 9u
+
+.temp 25
+.options tnom=25
+
+xq1 c b 0 0 vnpn_10x10
+
+
+*****************
+** Analysis
+*****************
+
+.control
+set filetype=ascii
+
+dc Vcp 0 6 0.1 Ib 1u 9u 2u
+print -i(Vcp)
+wrdata result.csv -i(Vcp)
+.endc
+
+.include "../../../design.ngspice"
+.lib "../../../sm141064.ngspice" bjt_typical
+
+.end
diff --git a/models/ngspice/testing/regression/bjt_iv/models_regression.py b/models/ngspice/testing/regression/bjt_iv/models_regression.py
new file mode 100644
index 0000000..a6630d0
--- /dev/null
+++ b/models/ngspice/testing/regression/bjt_iv/models_regression.py
@@ -0,0 +1,208 @@
+"""
+Usage:
+  models_regression.py [--num_cores=<num>]
+
+  -h, --help             Show help text.
+  -v, --version          Show version.
+  --num_cores=<num>      Number of cores to be used by simulator
+"""
+
+from re import T
+from docopt import docopt
+import pandas as pd 
+import numpy as np
+import os 
+from jinja2 import Template
+import concurrent.futures
+import shutil
+import warnings
+warnings.simplefilter(action='ignore', category=FutureWarning)
+
+def call_simulator(file_name):
+    """Call simulation commands to perform simulation.
+    Args:
+        file_name (str): Netlist file name.
+    """
+    os.system(f"ngspice -b -a {file_name} -o {file_name}.log > {file_name}.log")
+
+def ext_measured(device,vc,step,Id_sim,list_devices,ib):
+
+    # Get dimensions used for each device 
+    dimensions = pd.read_csv(f"{device}/{device}.csv",usecols=["corners"])
+    loops = dimensions["corners"].count()
+
+    # Extracting measured values for each Device 
+    for i in range (loops):
+        k = i
+        if i >= len(list_devices):
+            while k >= len(list_devices):
+                k = k - len(list_devices)
+
+        # Special case for 1st measured values 
+        if i == 0 :
+            if device == "pnp":
+                temp_vc = vc
+                vc = "-vc "
+            # measured Id_sim
+            col_list = [f"{vc}",f"{ib}{step[0]}",f"{ib}{step[1]}",f"{ib}{step[2]}",f"{ib}{step[3]}",f"{ib}{step[4]}"]
+            df_measured = pd.read_csv(f"{device}/{device}.csv",usecols=col_list)
+            df_measured.columns = [f"{vc}",f"{ib}{step[0]}",f"{ib}{step[1]}",f"{ib}{step[2]}",f"{ib}{step[3]}",f"{ib}{step[4]}"]
+            df_measured.to_csv(f"{device}/measured_{Id_sim}/{i}_measured_{list_devices[k]}.csv", index = False)
+        else:
+            if device == "pnp":
+                vc = temp_vc
+            # measured Id_sim
+            col_list = [f"{vc}",f"{ib}{step[0]}.{i}",f"{ib}{step[1]}.{i}",f"{ib}{step[2]}.{i}",f"{ib}{step[3]}.{i}",f"{ib}{step[4]}.{i}"]
+            df_measured = pd.read_csv(f"{device}/{device}.csv",usecols=col_list)
+            df_measured.columns = [f"{vc}",f"{ib}{step[0]}",f"{ib}{step[1]}",f"{ib}{step[2]}",f"{ib}{step[3]}",f"{ib}{step[4]}"]        
+            df_measured.to_csv(f"{device}/measured_{Id_sim}/{i}_measured_{list_devices[k]}.csv", index = False)
+
+def ext_simulated(device,vc,step,sweep,Id_sim,list_devices,ib):
+
+    # Get dimensions used for each device 
+    dimensions = pd.read_csv(f"{device}/{device}.csv",usecols=["corners"])
+    loops = dimensions["corners"].count()
+    temp_range = int(loops/4) 
+    netlist_tmp = f"./device_netlists/{device}.spice"
+    for i in range (loops):
+        if i in range (0,temp_range):               temp = 25
+        elif i in range (temp_range,2*temp_range):  temp = -40
+        elif i in range (2*temp_range,3*temp_range):temp = 125
+        else:                                       temp = 175 
+
+        k = i
+        if i >= len(list_devices):
+            while k >= len(list_devices):
+                k = k - len(list_devices)
+
+        with open(netlist_tmp) as f:
+            tmpl = Template(f.read())
+            os.makedirs(f"{device}/{device}_netlists_{Id_sim}",exist_ok=True)
+            with open(f"{device}/{device}_netlists_{Id_sim}/{i}_{device}_netlist_{list_devices[k]}.spice", "w") as netlist:
+                netlist.write(tmpl.render(device = list_devices[k], i = i , temp = temp ))
+            netlist_path  = f"{device}/{device}_netlists_{Id_sim}/{i}_{device}_netlist_{list_devices[k]}.spice" 
+
+            # Running ngspice for each netlist 
+            with concurrent.futures.ProcessPoolExecutor(max_workers=workers_count) as executor:
+                executor.submit(call_simulator, netlist_path)
+
+            # Writing simulated data 
+            df_simulated = pd.read_csv(f"{device}/simulated_{Id_sim}/{i}_simulated_{list_devices[k]}.csv",header=None, delimiter=r"\s+")
+
+            # empty array to append in it shaped (sweep, number of trials + 1)
+            new_array = np.empty((sweep, 1+int(df_simulated.shape[0]/sweep)))  
+            new_array[:, 0] = df_simulated.iloc[:sweep, 0]
+            times = int(df_simulated.shape[0]/sweep)
+
+            for j in range(times):
+                new_array[:, (j+1)] = df_simulated.iloc[j*sweep:(j+1)*sweep, 1]
+
+            # Writing final simulated data                 
+            df_simulated = pd.DataFrame(new_array)
+            df_simulated.to_csv(f"{device}/simulated_{Id_sim}/{i}_simulated_{list_devices[k]}.csv",index= False)    
+            df_simulated.columns = [f"{vc}",f"{ib}{step[0]}",f"{ib}{step[1]}",f"{ib}{step[2]}",f"{ib}{step[3]}",f"{ib}{step[4]}"]
+            df_simulated.to_csv(f"{device}/simulated_{Id_sim}/{i}_simulated_{list_devices[k]}.csv",index= False)
+
+def error_cal(device,vc,step,Id_sim,list_devices,ib):
+
+    df_final = pd.DataFrame()
+    # Get dimensions used for each device 
+    dimensions = pd.read_csv(f"{device}/{device}.csv",usecols=["corners"])
+    loops = dimensions["corners"].count()
+    temp_range = int(loops/4) 
+    for i in range (loops):
+        if i in range (0,temp_range):               temp = 25
+        elif i in range (temp_range,2*temp_range):  temp = -40
+        elif i in range (2*temp_range,3*temp_range):temp = 125
+        else:                                       temp = 175 
+
+        k = i
+        if i >= len(list_devices):
+            while k >= len(list_devices):
+                k = k - len(list_devices)
+
+        measured  = pd.read_csv(f"{device}/measured_{Id_sim}/{i}_measured_{list_devices[k]}.csv")
+        simulated = pd.read_csv(f"{device}/simulated_{Id_sim}/{i}_simulated_{list_devices[k]}.csv")
+
+        error_1 = round (100 * abs((abs(measured.iloc[0:, 1]) - abs(simulated.iloc[0:, 1]))/abs(measured.iloc[:, 1])),6)  
+        error_2 = round (100 * abs((abs(measured.iloc[0:, 2]) - abs(simulated.iloc[0:, 2]))/abs(measured.iloc[:, 2])),6)
+        error_3 = round (100 * abs((abs(measured.iloc[0:, 3]) - abs(simulated.iloc[0:, 3]))/abs(measured.iloc[:, 3])),6) 
+        error_4 = round (100 * abs((abs(measured.iloc[0:, 4]) - abs(simulated.iloc[0:, 4]))/abs(measured.iloc[:, 4])),6) 
+        error_5 = round (100 * abs((abs(measured.iloc[0:, 5]) - abs(simulated.iloc[0:, 5]))/abs(measured.iloc[:, 5])),6)
+
+        df_error = pd.DataFrame(data=[measured.iloc[:, 0],error_1,error_2,error_3,error_4,error_5]).transpose()        
+        df_error.to_csv(f"{device}/error_{Id_sim}/{i}_{device}_error_{list_devices[k]}.csv",index= False)
+
+        # Mean error 
+        mean_error = (df_error[f"{ib}{step[0]}"].mean() + df_error[f"{ib}{step[1]}"].mean() + df_error[f"{ib}{step[2]}"].mean() + 
+                      df_error[f"{ib}{step[3]}"].mean() + df_error[f"{ib}{step[4]}"].mean())/6
+        # Max error 
+        max_error = df_error[[f"{ib}{step[0]}",f"{ib}{step[1]}",f"{ib}{step[2]}",f"{ib}{step[3]}",f"{ib}{step[4]}"]].max().max()
+        # Max error location 
+        max_index = max((df_error == max_error).idxmax())
+        max_location_ib = (df_error == max_error).idxmax(axis=1)[max_index]
+        if i == 0 :
+            if device == "pnp":
+                temp_vc = vc
+                vc = "-vc "
+        else:
+            if device == "pnp":
+                vc = temp_vc
+        max_location_vc = df_error[f"{vc}"][max_index]
+
+        df_final_ = {'Run no.': f'{i}', 'Temp': f'{temp}', 'Device name': f'{device}', 'device': f'{list_devices[k]}','Simulated_Val':f'{Id_sim}','Mean error%':f'{"{:.2f}".format(mean_error)}', 'Max error%':f'{"{:.2f}".format(max_error)} @ {max_location_ib} & Vc (V) = {max_location_vc}'}
+        df_final = df_final.append(df_final_, ignore_index = True)
+
+    # Max mean error 
+    print (df_final)   
+    df_final.to_csv (f"{device}/Final_report_{Id_sim}.csv", index = False)
+    out_report = pd.read_csv (f"{device}/Final_report_{Id_sim}.csv")
+    print ("\n",f"Max. mean error = {out_report['Mean error%'].max()}%")    
+    print ("=====================================================================================================================================================")
+
+def main():
+
+    devices = ["npn","pnp"]
+    list_devices = [["vnpn_10x10" , "vnpn_5x5" , "vnpn_0p54x16" , "vnpn_0p54x8" , "vnpn_0p54x4", "vnpn_0p54x2"],
+                    ["vpnp_0p42x10" , "vpnp_0p42x5", "vpnp_10x10" , "vpnp_5x5"]]
+    vc = ["vcp ","-vc (A)"]
+    ib = ["ibp =","ib =-"]
+    Id_sim  = "IcVc"
+    sweep = [61,31] 
+    step = [ "1.000E-06" ,  "3.000E-06" ,  "5.000E-06" ,  "7.000E-06" ,  "9.000E-06"] 
+
+    for i, device in enumerate(devices): 
+        # Folder structure of measured values 
+        dirpath = f"{device}"
+        if os.path.exists(dirpath) and os.path.isdir(dirpath):
+            shutil.rmtree(dirpath)
+        os.makedirs(f"{device}/measured_{Id_sim}",exist_ok=False)
+
+        # From xlsx to csv 
+        read_file = pd.read_excel (f"../../180MCU_SPICE_DATA/BJT/bjt_{device}_icvc_f.nl_out.xlsx")
+        read_file.to_csv (f"{device}/{device}.csv", index = False, header=True)
+
+        # Folder structure of simulated values 
+        os.makedirs(f"{device}/simulated_{Id_sim}",exist_ok=False)
+        os.makedirs(f"{device}/error_{Id_sim}",exist_ok=False)
+
+        # =========== Simulate ==============      
+        ext_measured (device,vc[i],step,Id_sim,list_devices[i],ib[i])
+
+        ext_simulated(device,vc[i],step,sweep[i],Id_sim,list_devices[i],ib[i])
+
+        # ============ Results ============= 
+        error_cal    (device,vc[i],step,Id_sim,list_devices[i],ib[i])
+
+# ================================================================
+# -------------------------- MAIN --------------------------------
+# ================================================================
+
+if __name__ == "__main__":
+
+    # Args
+    arguments     = docopt(__doc__, version='comparator: 0.1')
+    workers_count = os.cpu_count()*2 if arguments["--num_cores"] == None else int(arguments["--num_cores"])
+
+    # Calling main function 
+    main()
diff --git a/models/ngspice/testing/regression/diode/.spiceinit b/models/ngspice/testing/regression/diode/.spiceinit
new file mode 100644
index 0000000..7779a4c
--- /dev/null
+++ b/models/ngspice/testing/regression/diode/.spiceinit
@@ -0,0 +1,2 @@
+* user provided init file
+set ngbehavior=hs
diff --git a/models/ngspice/testing/regression/diode/0_measured_data/dnwps_cv.nl_out.xlsx b/models/ngspice/testing/regression/diode/0_measured_data/dnwps_cv.nl_out.xlsx
new file mode 100644
index 0000000..cdcbf27
--- /dev/null
+++ b/models/ngspice/testing/regression/diode/0_measured_data/dnwps_cv.nl_out.xlsx
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diff --git a/models/ngspice/testing/regression/diode/0_measured_data/dnwps_iv.nl_out.xlsx b/models/ngspice/testing/regression/diode/0_measured_data/dnwps_iv.nl_out.xlsx
new file mode 100644
index 0000000..d9d62db
--- /dev/null
+++ b/models/ngspice/testing/regression/diode/0_measured_data/dnwps_iv.nl_out.xlsx
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diff --git a/models/ngspice/testing/regression/diode/0_measured_data/dnwpw_cv.nl_out.xlsx b/models/ngspice/testing/regression/diode/0_measured_data/dnwpw_cv.nl_out.xlsx
new file mode 100644
index 0000000..82a005e
--- /dev/null
+++ b/models/ngspice/testing/regression/diode/0_measured_data/dnwpw_cv.nl_out.xlsx
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diff --git a/models/ngspice/testing/regression/diode/0_measured_data/dnwpw_iv.nl_out.xlsx b/models/ngspice/testing/regression/diode/0_measured_data/dnwpw_iv.nl_out.xlsx
new file mode 100644
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+++ b/models/ngspice/testing/regression/diode/0_measured_data/dnwpw_iv.nl_out.xlsx
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diff --git a/models/ngspice/testing/regression/diode/0_measured_data/np_3p3_cv.nl_out.xlsx b/models/ngspice/testing/regression/diode/0_measured_data/np_3p3_cv.nl_out.xlsx
new file mode 100644
index 0000000..aea9c00
--- /dev/null
+++ b/models/ngspice/testing/regression/diode/0_measured_data/np_3p3_cv.nl_out.xlsx
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diff --git a/models/ngspice/testing/regression/diode/0_measured_data/np_3p3_iv.nl_out.xlsx b/models/ngspice/testing/regression/diode/0_measured_data/np_3p3_iv.nl_out.xlsx
new file mode 100644
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--- /dev/null
+++ b/models/ngspice/testing/regression/diode/0_measured_data/np_3p3_iv.nl_out.xlsx
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diff --git a/models/ngspice/testing/regression/diode/0_measured_data/np_6p0_cv.nl_out.xlsx b/models/ngspice/testing/regression/diode/0_measured_data/np_6p0_cv.nl_out.xlsx
new file mode 100644
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--- /dev/null
+++ b/models/ngspice/testing/regression/diode/0_measured_data/np_6p0_cv.nl_out.xlsx
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diff --git a/models/ngspice/testing/regression/diode/0_measured_data/np_6p0_iv.nl_out.xlsx b/models/ngspice/testing/regression/diode/0_measured_data/np_6p0_iv.nl_out.xlsx
new file mode 100644
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diff --git a/models/ngspice/testing/regression/diode/0_measured_data/nwp_3p3_cv.nl_out.xlsx b/models/ngspice/testing/regression/diode/0_measured_data/nwp_3p3_cv.nl_out.xlsx
new file mode 100644
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--- /dev/null
+++ b/models/ngspice/testing/regression/diode/0_measured_data/nwp_3p3_cv.nl_out.xlsx
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diff --git a/models/ngspice/testing/regression/diode/0_measured_data/nwp_3p3_iv.nl_out.xlsx b/models/ngspice/testing/regression/diode/0_measured_data/nwp_3p3_iv.nl_out.xlsx
new file mode 100644
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diff --git a/models/ngspice/testing/regression/diode/0_measured_data/nwp_6p0_cv.nl_out.xlsx b/models/ngspice/testing/regression/diode/0_measured_data/nwp_6p0_cv.nl_out.xlsx
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new file mode 100644
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diff --git a/models/ngspice/testing/regression/diode/0_measured_data/pn_3p3_cv.nl_out.xlsx b/models/ngspice/testing/regression/diode/0_measured_data/pn_3p3_cv.nl_out.xlsx
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diff --git a/models/ngspice/testing/regression/diode/0_measured_data/pn_3p3_iv.nl_out.xlsx b/models/ngspice/testing/regression/diode/0_measured_data/pn_3p3_iv.nl_out.xlsx
new file mode 100644
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diff --git a/models/ngspice/testing/regression/diode/0_measured_data/pn_6p0_cv.nl_out.xlsx b/models/ngspice/testing/regression/diode/0_measured_data/pn_6p0_cv.nl_out.xlsx
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diff --git a/models/ngspice/testing/regression/diode/0_measured_data/sc_diode_cv.nl_out.xlsx b/models/ngspice/testing/regression/diode/0_measured_data/sc_diode_cv.nl_out.xlsx
new file mode 100644
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--- /dev/null
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diff --git a/models/ngspice/testing/regression/diode/0_measured_data/sc_diode_iv.nl_out.xlsx b/models/ngspice/testing/regression/diode/0_measured_data/sc_diode_iv.nl_out.xlsx
new file mode 100644
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diff --git a/models/ngspice/testing/regression/diode/device_netlists/cv.spice b/models/ngspice/testing/regression/diode/device_netlists/cv.spice
new file mode 100644
index 0000000..c53922b
--- /dev/null
+++ b/models/ngspice/testing/regression/diode/device_netlists/cv.spice
@@ -0,0 +1,55 @@
+***************************
+** CV netlist generation **
+***************************
+* Copyright 2022 Efabless Corporation
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*      http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+Vn n 0 dc 1
+
+
+.temp {{temp}}
+.options tnom={{temp}}
+      
+
+dn n 0 {{device}} AREA = {{area}}p PJ = {{pj}}u 
+
+.control
+set filetype=ascii
+
+let vn_min  = 0
+let vn_step = -0.2
+let vn_max  = -3.2
+
+option TEMP={{temp}}
+
+save   @dn[cd]
+*******************
+** simulation part
+*******************
+DC Vn $&vn_min $&vn_max $&vn_step
+
+* ** parameters calculation
+
+print  @dn[cd]*1000000000000000
+    
+wrdata {{device}}_{{Id_sim}}_{{corner}}/simulated_{{Id_sim}}/{{i}}_simulated_A{{area}}_P{{pj}}.csv  @dn[cd]*1000000000000000
+
+.endc
+
+** library calling
+
+.include "../../../design.ngspice"
+.lib "../../../sm141064.ngspice" diode_{{corner}}
+
+
+.end
\ No newline at end of file
diff --git a/models/ngspice/testing/regression/diode/device_netlists/iv.spice b/models/ngspice/testing/regression/diode/device_netlists/iv.spice
new file mode 100644
index 0000000..e66427c
--- /dev/null
+++ b/models/ngspice/testing/regression/diode/device_netlists/iv.spice
@@ -0,0 +1,47 @@
+***************************
+** IV netlist generation **
+***************************
+* Copyright 2022 Efabless Corporation
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*      http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+Vn n 0 dc 1
+
+.temp {{temp}}
+.options tnom={{temp}}
+
+ 
+
+dn1 n 0 {{device}} AREA = {{area}}p PJ = {{pj}}u 
+
+**** begin architecture code
+
+
+.control
+set filetype=ascii
+
+dc Vn -12.13 1.13 0.13
+print abs(i(Vn))
+wrdata {{device}}_{{Id_sim}}_{{corner}}/simulated_{{Id_sim}}/{{i}}_simulated_A{{area}}_P{{pj}}.csv abs(i(Vn))
+.endc
+
+
+
+** library calling
+
+.include "../../../design.ngspice"
+.lib "../../../sm141064.ngspice" diode_{{corner}}
+
+**** end architecture code
+
+
+.end
diff --git a/models/ngspice/testing/regression/diode/models_regression.py b/models/ngspice/testing/regression/diode/models_regression.py
new file mode 100644
index 0000000..eddc91a
--- /dev/null
+++ b/models/ngspice/testing/regression/diode/models_regression.py
@@ -0,0 +1,196 @@
+# Copyright 2022 Efabless Corporation
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#      http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+"""
+Usage:
+  models_regression.py [--num_cores=<num>]
+
+  -h, --help             Show help text.
+  -v, --version          Show version.
+  --num_cores=<num>      Number of cores to be used by simulator
+"""
+
+from re import T
+from docopt import docopt
+import pandas as pd 
+import numpy as np
+import os 
+from jinja2 import Template
+import concurrent.futures
+import shutil
+import warnings
+warnings.simplefilter(action='ignore', category=FutureWarning)
+
+def call_simulator(file_name):
+    """Call simulation commands to perform simulation.
+    Args:
+        file_name (str): Netlist file name.
+    """
+    os.system(f"ngspice -b -a {file_name} -o {file_name}.log > {file_name}.log")
+
+def ext_measured(device,vn,d_in, Id_sim, corner):
+    
+    # Get dimensions used for each device 
+    dirpath = f"{device}_{Id_sim}_{corner}"
+    dimensions = pd.read_csv(f"{dirpath}/{device}.csv",usecols=["W (um)" , "L (um)"])
+    loops = dimensions["L (um)"].count()
+    
+    # Extracting measured values for each W & L 
+    for i in range (0,loops):
+        width  = dimensions["W (um)"].iloc[i]
+        length = dimensions["L (um)"].iloc[i]
+        
+        # Special case for 1st measured values 
+        if i == 0 :
+            # measured Id
+            col_list = [f"{vn}",f"{d_in}_{corner}"]
+            df_measured = pd.read_csv(f"{dirpath}/{device}.csv",usecols=col_list)
+            df_measured.columns = [f"{vn}",f"{d_in}_{corner}"]
+            df_measured.to_csv(f"{dirpath}/measured_{Id_sim}/{i}_measured_A{width}_P{length}.csv", index = False)
+        else:
+            # measured Id
+            col_list = [f"{vn}",f"{d_in}_{corner}.{i}"]
+            df_measured = pd.read_csv(f"{dirpath}/{device}.csv",usecols=col_list)
+            df_measured.columns = [f"{vn}",f"{d_in}_{corner}"]        
+            df_measured.to_csv(f"{dirpath}/measured_{Id_sim}/{i}_measured_A{width}_P{length}.csv", index = False)
+
+def ext_simulated(device,vn,d_in,vn_sweeps,Id_sim, corner):
+    
+    # Get dimensions used for each device 
+    dirpath = f"{device}_{Id_sim}_{corner}"
+    dimensions = pd.read_csv(f"{dirpath}/{device}.csv",usecols=["W (um)" , "L (um)"])
+    loops = dimensions["L (um)"].count()
+    netlist_tmp = f"./device_netlists/{Id_sim}.spice"
+    for i in range (0,loops):
+        width  = dimensions["W (um)"].iloc[int(i)]
+        length = dimensions["L (um)"].iloc[int(i)]
+
+        if i % 4 == 0: temp = -40 
+        elif i % 4 == 1: temp = 25 
+        elif i % 4 == 2: temp = 125
+        else:
+            temp = 175 
+        with open(netlist_tmp) as f:
+            tmpl = Template(f.read())
+            os.makedirs(f"{dirpath}/{device}_netlists_{Id_sim}",exist_ok=True)
+            with open(f"{dirpath}/{device}_netlists_{Id_sim}/{i}_{device}_netlist_A{width}_P{length}.spice", "w") as netlist:
+                netlist.write(tmpl.render(device = device, area = width, pj = length, i = i , temp = temp, Id_sim = Id_sim , corner = corner ))
+            netlist_path  = f"{dirpath}/{device}_netlists_{Id_sim}/{i}_{device}_netlist_A{width}_P{length}.spice" 
+            # Running ngspice for each netlist 
+            with concurrent.futures.ProcessPoolExecutor(max_workers=workers_count) as executor:
+                executor.submit(call_simulator, netlist_path)
+            
+            # Writing simulated data 
+            df_simulated = pd.read_csv(f"{dirpath}/simulated_{Id_sim}/{i}_simulated_A{width}_P{length}.csv",header=None, delimiter=r"\s+")
+            df_simulated.to_csv(f"{dirpath}/simulated_{Id_sim}/{i}_simulated_A{width}_P{length}.csv",index= False)    
+            
+            # empty array to append in it shaped (vn_sweeps, number of trials + 1)
+            new_array = np.empty((vn_sweeps, 1+int(df_simulated.shape[0]/vn_sweeps)))  
+            new_array[:, 0] = df_simulated.iloc[:vn_sweeps, 0]
+            times = int(df_simulated.shape[0]/vn_sweeps)
+
+            for j in range(times):
+                new_array[:, (j+1)] = df_simulated.iloc[j*vn_sweeps:(j+1)*vn_sweeps, 1]
+                
+            # Writing final simulated data                 
+            df_simulated = pd.DataFrame(new_array)
+            df_simulated.to_csv(f"{dirpath}/simulated_{Id_sim}/{i}_simulated_A{width}_P{length}.csv",index= False)    
+            df_simulated.columns = [f"{vn}",f"{d_in}_{corner}"]
+            df_simulated.to_csv(f"{dirpath}/simulated_{Id_sim}/{i}_simulated_A{width}_P{length}.csv",index= False)    
+
+def error_cal(device,vn,d_in,Id_sim, corner):
+    
+    # Get dimensions used for each device 
+    dirpath = f"{device}_{Id_sim}_{corner}"
+    dimensions = pd.read_csv(f"{dirpath}/{device}.csv",usecols=["W (um)" , "L (um)"])
+    loops = dimensions["L (um)"].count()    
+    df_final = pd.DataFrame()
+    for i in range (0,loops):  
+        width  = dimensions["W (um)"].iloc[int(i)]
+        length = dimensions["L (um)"].iloc[int(i)]
+        if i % 4 == 0: temp = -40 
+        elif i % 4 == 1: temp = 25 
+        elif i % 4 == 2: temp = 125
+        else:
+            temp = 175 
+             
+        measured  = pd.read_csv(f"{dirpath}/measured_{Id_sim}/{i}_measured_A{width}_P{length}.csv")
+        simulated = pd.read_csv(f"{dirpath}/simulated_{Id_sim}/{i}_simulated_A{width}_P{length}.csv")
+
+        error_1 = round (100 * abs((abs(measured.iloc[:, 1]) - abs(simulated.iloc[:, 1]))/abs(measured.iloc[:, 1])),6)  
+
+        df_error = pd.DataFrame(data=[measured.iloc[:, 0],error_1]).transpose()        
+        df_error.to_csv(f"{dirpath}/error_{Id_sim}/{i}_{device}_error_A{width}_P{length}.csv",index= False)
+        
+        # Mean error 
+        mean_error = (df_error[f"{d_in}_{corner}"].mean())/6
+        # Max error 
+        max_error = df_error[f"{d_in}_{corner}"].max()
+        # Max error location 
+        max_index = max((df_error == max_error).idxmax())
+        max_location_vgs = (df_error == max_error).idxmax(axis=1)[max_index]
+        max_location_vds = df_error[f"{vn}"][max_index]
+
+        df_final_ = {'Run no.': f'{i}', 'Temp': f'{temp}', 'Device name': f'{dirpath}', 'Area': f'{width}', 'Perimeter': f'{length}', 'Simulated_Val':f'{Id_sim}','Mean error%':f'{"{:.2f}".format(mean_error)}', 'Max error%':f'{"{:.2f}".format(max_error)} @ {max_location_vgs} & vn (V) = {max_location_vds}'}
+        df_final = df_final.append(df_final_, ignore_index = True)
+    # Max mean error 
+    print (df_final)   
+    df_final.to_csv (f"{dirpath}/Final_report_{Id_sim}.csv", index = False)
+    out_report = pd.read_csv (f"{dirpath}/Final_report_{Id_sim}.csv")
+    print ("\n",f"Max. mean error = {out_report['Mean error%'].max()}%")    
+    print ("=====================================================================================================================================================")
+
+def main():
+        
+    devices = ["dnwps","dnwpw","np_3p3","np_6p0", "nwp_3p3","nwp_6p0","pn_3p3","pn_6p0","sc_diode"]
+    corners = ["typical","ff","ss"]
+    measures = [["iv","Vn1 (V)", " |In1(A)| diode", 103],
+                 ["cv","Vj", "diode", 17]]
+
+    for device in devices: 
+        for measure in measures:
+            for corner in corners: 
+                # Folder structure of measured values
+                Id_sim, diode_vn, diode_in, no_of_vn_sweeps = measure[0], measure[1], measure[2], measure[3] 
+                dirpath = f"{device}_{Id_sim}_{corner}"
+                if os.path.exists(dirpath) and os.path.isdir(dirpath):
+                    shutil.rmtree(dirpath)
+                os.makedirs(f"{dirpath}/measured_{Id_sim}",exist_ok=False)
+
+                # From xlsx to csv 
+                read_file = pd.read_excel (f"./0_measured_data/{device}_{Id_sim}.nl_out.xlsx")
+                read_file.to_csv (f"{dirpath}/{device}.csv", index = False, header=True)
+
+                # Folder structure of simulated values 
+                os.makedirs(f"{dirpath}/simulated_{Id_sim}",exist_ok=False)
+                os.makedirs(f"{dirpath}/error_{Id_sim}",exist_ok=False)
+        
+                ext_measured (device,diode_vn,diode_in, Id_sim, corner)
+
+                ext_simulated(device,diode_vn,diode_in,no_of_vn_sweeps,Id_sim, corner)
+                error_cal    (device,diode_vn,diode_in,Id_sim, corner)
+
+
+    
+# # ================================================================
+# -------------------------- MAIN --------------------------------
+# ================================================================
+        
+if __name__ == "__main__":
+    
+    # Args 
+    arguments     = docopt(__doc__, version='comparator: 0.1')
+    workers_count = os.cpu_count()*2 if arguments["--num_cores"] == None else int(arguments["--num_cores"])
+    
+    # Calling main function 
+    main()
diff --git a/models/ngspice/testing/regression/mimcap_c/.spiceinit b/models/ngspice/testing/regression/mimcap_c/.spiceinit
new file mode 100644
index 0000000..7779a4c
--- /dev/null
+++ b/models/ngspice/testing/regression/mimcap_c/.spiceinit
@@ -0,0 +1,2 @@
+* user provided init file
+set ngbehavior=hs
diff --git a/models/ngspice/testing/regression/mimcap_c/device_netlists/.spiceinit b/models/ngspice/testing/regression/mimcap_c/device_netlists/.spiceinit
new file mode 100644
index 0000000..84222e2
--- /dev/null
+++ b/models/ngspice/testing/regression/mimcap_c/device_netlists/.spiceinit
@@ -0,0 +1,5 @@
+
+* user provided init file
+set ngbehavior=hs
+
+
diff --git a/models/ngspice/testing/regression/mimcap_c/device_netlists/mimcap.spice b/models/ngspice/testing/regression/mimcap_c/device_netlists/mimcap.spice
new file mode 100644
index 0000000..b2d8736
--- /dev/null
+++ b/models/ngspice/testing/regression/mimcap_c/device_netlists/mimcap.spice
@@ -0,0 +1,38 @@
+***************************
+** cap
+***************************
+* Copyright 2022 Efabless Corporation
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*      http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+.options noacct
+
+Ich 0 p dc 10u
+
+.temp 25
+.options tnom=25
+      
+xcn p 0 {{device}} c_length={{length}}u c_width={{width}}u
+
+.ic v(p)=0.0
+.tran 10ns 100us
+
+* .print tran v(p) cj=par('10.0e-6  * time / v(p)')
+
+.meas tran CV FIND par('(10.0e-6  * time / v(p))*1.0e15') AT=100us
+
+** library calling
+
+.include "../../../design.ngspice"
+.lib "../../../sm141064.ngspice" mimcap_{{corner}}
+.end
+
diff --git a/models/ngspice/testing/regression/mimcap_c/models_regression.py b/models/ngspice/testing/regression/mimcap_c/models_regression.py
new file mode 100644
index 0000000..ee4a895
--- /dev/null
+++ b/models/ngspice/testing/regression/mimcap_c/models_regression.py
@@ -0,0 +1,163 @@
+# Copyright 2022 Efabless Corporation
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#      http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+"""
+Usage:
+  models_regression.py [--num_cores=<num>]
+
+  -h, --help             Show help text.
+  -v, --version          Show version.
+  --num_cores=<num>      Number of cores to be used by simulator
+"""
+
+from re import T
+from docopt import docopt
+import pandas as pd 
+import numpy as np
+import os 
+from jinja2 import Template
+import concurrent.futures
+import shutil
+import warnings
+warnings.simplefilter(action='ignore', category=FutureWarning)
+
+def call_simulator(file_name):
+    """Call simulation commands to perform simulation.
+    Args:
+        file_name (str): Netlist file name.
+    """
+    os.system(f"ngspice -b -a {file_name} -o {file_name}.log > {file_name}.log")
+
+def ext_measured(device,vn,d_in, cv_sim, corner,start):
+    
+    # Get dimensions used for each device 
+    dirpath = f"{device}_{cv_sim}_{corner}"
+    
+    # Extracting measured values for each W & L 
+    for i in range (start,4+start):
+        if i == 0+start: width  = 100 ; length = 100
+        if i == 1+start: width  = 5   ; length = 5
+        if i == 2+start: width  = 100 ; length = 5
+        if i == 3+start: width  = 5   ; length = 100
+        
+        # measured cv
+        col_list = [f"{vn}",f"{d_in}"]
+        df_measured = pd.read_csv(f"{dirpath}/{device}.csv",usecols=col_list)
+        df_measured.loc[i:i].to_csv(f"{dirpath}/measured_{cv_sim}/{i-start}_measured_w{width}_l{length}.csv", index=False)
+
+def ext_simulated(device,vn,d_in,cv_sim, corner,start):
+    
+    # Get dimensions used for each device 
+    dirpath = f"{device}_{cv_sim}_{corner}"
+    netlist_tmp = f"./device_netlists/mimcap.spice"
+    
+    # Extracting measured values for each W & L 
+    for i in range (start,4+start):
+        if i == 0+start: width  = 100 ; length = 100
+        if i == 1+start: width  = 5   ; length = 5
+        if i == 2+start: width  = 100 ; length = 5
+        if i == 3+start: width  = 5   ; length = 100
+    
+        with open(netlist_tmp) as f:
+            tmpl = Template(f.read())
+            os.makedirs(f"{dirpath}/{device}_netlists_{cv_sim}",exist_ok=True)
+            with open(f"{dirpath}/{device}_netlists_{cv_sim}/{i-start}_{device}_netlist_w{width}_l{length}.spice", "w") as netlist:
+                netlist.write(tmpl.render(device = device, width = width, length = length , corner = corner ))
+            netlist_path  = f"{dirpath}/{device}_netlists_{cv_sim}/{i-start}_{device}_netlist_w{width}_l{length}.spice" 
+            # Running ngspice for each netlist 
+            with concurrent.futures.ProcessPoolExecutor(max_workers=workers_count) as executor:
+                executor.submit(call_simulator, netlist_path)
+            
+            # Writing simulated data 
+            df_simulated = pd.read_csv(f"{dirpath}/{device}_netlists_{cv_sim}/{i-start}_{device}_netlist_w{width}_l{length}.spice.log")
+            clean_data = str(df_simulated.loc[4]).replace("Compatibility modes selected: hs","").replace("\nName: 4, dtype: object","").split("=")
+            df_clean_ = {vn: [f"moscap_{corner}"],d_in: [clean_data[1]]}
+            df_clean = pd.DataFrame(df_clean_)            
+            df_clean.to_csv(f"{dirpath}/simulated_{cv_sim}/{i-start}_simulated_w{width}_l{length}.csv",index= False)    
+            
+def error_cal(device,vn,d_in,Id_sim, corner,start):
+    
+    # Get dimensions used for each device 
+    dirpath = f"{device}_{Id_sim}_{corner}"
+    df_final = pd.DataFrame()
+    for i in range (start,4+start):
+        if i == 0+start: width  = 100 ; length = 100
+        if i == 1+start: width  = 5   ; length = 5
+        if i == 2+start: width  = 100 ; length = 5
+        if i == 3+start: width  = 5   ; length = 100
+             
+        measured  = pd.read_csv(f"{dirpath}/measured_{Id_sim}/{i-start}_measured_w{width}_l{length}.csv")
+        simulated = pd.read_csv(f"{dirpath}/simulated_{Id_sim}/{i-start}_simulated_w{width}_l{length}.csv")
+
+        error_1 = round (100 * abs((abs(measured.iloc[:, 1]) - abs(simulated.iloc[:, 1]))/abs(measured.iloc[:, 1])),8)  
+
+        df_error = pd.DataFrame(data=[measured.iloc[:, 0],error_1]).transpose()        
+        df_error.to_csv(f"{dirpath}/error_{Id_sim}/{i-start}_{device}_error_w{width}_l{length}.csv",index= False)
+        
+        # Mean error 
+        mean_error = (df_error[f"{d_in}"].mean())
+        # Max error 
+        max_error = df_error[f"{d_in}"].max()
+
+        df_final_ = {'Run no.': f'{i-start}', 'Device name': f'{dirpath}', 'Width': f'{width}', 'Length': f'{length}', 'Simulated_Val':f'{Id_sim}','Mean error%':f'{"{:.2f}".format(mean_error)}', 'Max error%':f'{"{:.2f}".format(max_error)} '}
+        df_final = df_final.append(df_final_, ignore_index = True)
+    # Max mean error 
+    print (df_final)   
+    df_final.to_csv (f"{dirpath}/Final_report_{Id_sim}.csv", index = False)
+    out_report = pd.read_csv (f"{dirpath}/Final_report_{Id_sim}.csv")
+    print ("\n",f"Max. mean error = {out_report['Mean error%'].max()}%")    
+    print ("=====================================================================================================================================================")
+
+
+def main():
+
+    # mim
+    corners = ["ss" , "typical","ff"]        
+    devices = ["mim_1p5fF" , "mim_1p0fF" , "mim_2p0fF"]
+    measure = ["cv","corners", "CV (fF)"]
+    start = 0
+    for corner in corners: 
+        for device in devices: 
+            # Folder structure of measured values
+            cv_sim, cap_vn, cap_in = measure[0], measure[1], measure[2]
+            dirpath = f"{device}_{cv_sim}_{corner}"
+            if os.path.exists(dirpath) and os.path.isdir(dirpath):
+                shutil.rmtree(dirpath)
+            os.makedirs(f"{dirpath}/measured_{cv_sim}",exist_ok=False)
+
+            # From xlsx to csv
+            read_file = pd.read_excel (f"../../180MCU_SPICE_DATA/Cap/mimcap_fc.nl_out.xlsx")
+            read_file.to_csv (f"{dirpath}/{device}.csv", index = False, header=True)
+
+            # Folder structure of simulated values 
+            os.makedirs(f"{dirpath}/simulated_{cv_sim}",exist_ok=False)
+            os.makedirs(f"{dirpath}/error_{cv_sim}",exist_ok=False)
+    
+            ext_measured (device,cap_vn,cap_in, cv_sim, corner,start)
+            ext_simulated(device,cap_vn,cap_in,cv_sim, corner,start)
+            error_cal    (device,cap_vn,cap_in,cv_sim, corner,start)            
+            start = start + 4            
+        start = start + 24
+
+# # ================================================================
+# -------------------------- MAIN --------------------------------
+# ================================================================
+        
+if __name__ == "__main__":
+    
+    # Args 
+    arguments     = docopt(__doc__, version='comparator: 0.1')
+    workers_count = os.cpu_count()*2 if arguments["--num_cores"] == None else int(arguments["--num_cores"])
+    
+    # Calling main function 
+    main()
diff --git a/models/ngspice/testing/regression/mos_cv/.spiceinit b/models/ngspice/testing/regression/mos_cv/.spiceinit
new file mode 100644
index 0000000..0be699c
--- /dev/null
+++ b/models/ngspice/testing/regression/mos_cv/.spiceinit
@@ -0,0 +1,4 @@
+
+* user provided init file
+set ngbehavior=hs
+
diff --git a/models/ngspice/testing/regression/mos_cv/device_netlists_Cgc/nmos_3p3_cv.spice b/models/ngspice/testing/regression/mos_cv/device_netlists_Cgc/nmos_3p3_cv.spice
new file mode 100644
index 0000000..f381eff
--- /dev/null
+++ b/models/ngspice/testing/regression/mos_cv/device_netlists_Cgc/nmos_3p3_cv.spice
@@ -0,0 +1,74 @@
+***************************
+** nmos_3p3_cv
+***************************
+* Copyright 2022 Efabless Corporation
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*      http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+** library calling
+
+.include "../../../design.ngspice"
+.lib "../../../sm141064.ngspice" typical
+
+
+** Circuit Description **
+* power supply
+vds D_tn 0 dc=0
+vgs G_tn 0 dc=3.3
+vbs S_tn 0 dc=0
+
+.temp 25
+.options tnom=25
+
+*l_diff_min = 0.24
+* ad = int((nf+1)/2) * width/nf * 0.24       = 24u                         
+* pd = (int((nf+1)/2) * width/nf + 0.24)*2   = 200.48u                 
+
+* circuit
+mn D_tn G_tn S_tn S_tn nmos_3p3 W = {{width}}u L = {{length}}u nf={{nf}} ad= 24u pd=200.48u as=24u ps=200.48u
+
+.control
+set filetype=ascii
+
+let vgs_min  = -3.3
+let vgs_step = 0.1
+let vgs_max  = 3.3
+
+compose  vbs_vector   start=0          stop=-3.3          step=-0.825
+
+set appendwrite
+
+foreach t 25
+
+    let vbs_counter = 0
+    while vbs_counter < length(vbs_vector)
+        option TEMP=25
+        alter vbs = vbs_vector[vbs_counter]
+
+        save  @mn[vs] @mn[vgs] @mn[id] @mn[cgb]
+        *******************
+        ** simulation part
+        *******************
+        DC vgs $&vgs_min $&vgs_max $&vgs_step
+    
+        * ** parameters calculation
+	
+	print @mn[cgb]
+        
+        wrdata nmos_3p3_cv/simulated_Cgc/{{i}}_simulated_W{{width}}_L{{length}}.csv {@mn[cgb]*1e15} 
+        
+        reset
+        let vbs_counter = vbs_counter + 1
+    end
+end
+.endc
+.end
diff --git a/models/ngspice/testing/regression/mos_cv/device_netlists_Cgc/pmos_3p3_cv.spice b/models/ngspice/testing/regression/mos_cv/device_netlists_Cgc/pmos_3p3_cv.spice
new file mode 100644
index 0000000..f7d8b08
--- /dev/null
+++ b/models/ngspice/testing/regression/mos_cv/device_netlists_Cgc/pmos_3p3_cv.spice
@@ -0,0 +1,74 @@
+***************************
+** pmos_3p3_cv
+***************************
+* Copyright 2022 Efabless Corporation
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*      http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+** library calling
+
+.include "../../../design.ngspice"
+.lib "../../../sm141064.ngspice" typical
+
+
+** Circuit Description **
+* power supply
+vds D_tn 0 dc=0
+vgs G_tn 0 dc=3.3
+vbs S_tn 0 dc=0
+
+.temp 25
+.options tnom=25
+
+*l_diff_min = 0.24
+* ad = int((nf+1)/2) * width/nf * 0.24       = 24u                         
+* pd = (int((nf+1)/2) * width/nf + 0.24)*2   = 200.48u                 
+
+* circuit
+mn D_tn G_tn S_tn S_tn pmos_3p3 W = {{width}}u L = {{length}}u nf={{nf}} ad= 24u pd=200.48u as=24u ps=200.48u
+
+.control
+set filetype=ascii
+
+let vgs_min  = -3.3
+let vgs_step = 0.1
+let vgs_max  = 3.3
+
+compose  vbs_vector   start=0          stop=3.3          step=0.825
+
+set appendwrite
+
+foreach t 25
+
+    let vbs_counter = 0
+    while vbs_counter < length(vbs_vector)
+        option TEMP=25
+        alter vbs = vbs_vector[vbs_counter]
+
+        save  @mn[vs] @mn[vgs] @mn[id] @mn[cgb]
+        *******************
+        ** simulation part
+        *******************
+        DC vgs $&vgs_min $&vgs_max $&vgs_step
+    
+        * ** parameters calculation
+	
+	print @mn[cgb]
+        
+        wrdata pmos_3p3_cv/simulated_Cgc/{{i}}_simulated_W{{width}}_L{{length}}.csv {@mn[cgb]*1e15} 
+        
+        reset
+        let vbs_counter = vbs_counter + 1
+    end
+end
+.endc
+.end
diff --git a/models/ngspice/testing/regression/mos_cv/device_netlists_Cgd/nmos_3p3_cv.spice b/models/ngspice/testing/regression/mos_cv/device_netlists_Cgd/nmos_3p3_cv.spice
new file mode 100644
index 0000000..8d4ed65
--- /dev/null
+++ b/models/ngspice/testing/regression/mos_cv/device_netlists_Cgd/nmos_3p3_cv.spice
@@ -0,0 +1,74 @@
+***************************
+** nmos_3p3_cv
+***************************
+* Copyright 2022 Efabless Corporation
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*      http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+** library calling
+
+.include "../../../design.ngspice"
+.lib "../../../sm141064.ngspice" typical
+
+
+** Circuit Description **
+* power supply
+vds D_tn 0 dc=3.3
+vgs G_tn 0 dc=3.3
+vs S_tn 0 dc=0.2
+
+.temp 25
+.options tnom=25
+
+*l_diff_min = 0.24
+* ad = int((nf+1)/2) * width/nf * 0.24       = 24u                         
+* pd = (int((nf+1)/2) * width/nf + 0.24)*2   = 200.48u                 
+
+* circuit
+mn D_tn G_tn S_tn S_tn nmos_3p3 W = 200u L = 0.28u nf=20 ad= 24u pd=200.48u as=24u ps=200.48u
+
+.control
+set filetype=ascii
+
+let vds_min  = 0
+let vds_step = 0.1
+let vds_max  = 3.3
+
+compose  vgs_vector   start=0          stop=3.3          step=1
+
+set appendwrite
+
+foreach t 25
+
+    let vgs_counter = 0
+    while vgs_counter < length(vgs_vector)
+        option TEMP=25
+        alter vgs = vgs_vector[vgs_counter]
+
+        save  @mn[vds] @mn[vgs] @mn[id] @mn[cgd]
+        *******************
+        ** simulation part
+        *******************
+        DC vds $&vds_min $&vds_max $&vds_step
+    
+        * ** parameters calculation
+	
+	print @mn[cgd]
+        
+        wrdata nmos_3p3_cv/simulated_Cgd/{{i}}_simulated_W{{width}}_L{{length}}.csv {@mn[cgd]*1e15} 
+        
+        reset
+        let vgs_counter = vgs_counter + 1
+    end
+end
+.endc
+.end
diff --git a/models/ngspice/testing/regression/mos_cv/device_netlists_Cgd/pmos_3p3_cv.spice b/models/ngspice/testing/regression/mos_cv/device_netlists_Cgd/pmos_3p3_cv.spice
new file mode 100644
index 0000000..ae302a1
--- /dev/null
+++ b/models/ngspice/testing/regression/mos_cv/device_netlists_Cgd/pmos_3p3_cv.spice
@@ -0,0 +1,74 @@
+***************************
+** pmos_3p3_cv
+***************************
+* Copyright 2022 Efabless Corporation
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*      http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+** library calling
+
+.include "../../../design.ngspice"
+.lib "../../../sm141064.ngspice" typical
+
+
+** Circuit Description **
+* power supply
+vds D_tn 0 dc=-3.3
+vgs G_tn 0 dc=-3.3
+vs S_tn 0 dc=0.2
+
+.temp 25
+.options tnom=25
+
+*l_diff_min = 0.24
+* ad = int((nf+1)/2) * width/nf * 0.24       = 24u                         
+* pd = (int((nf+1)/2) * width/nf + 0.24)*2   = 200.48u                 
+
+* circuit
+mn D_tn G_tn S_tn S_tn pmos_3p3 W = 200u L = 0.28u nf=20 ad= 24u pd=200.48u as=24u ps=200.48u
+
+.control
+set filetype=ascii
+
+let vds_min  = 0
+let vds_step = -0.1
+let vds_max  = -3.3
+
+compose  vgs_vector   start=0          stop=-3.3          step=-1
+
+set appendwrite
+
+foreach t 25
+
+    let vgs_counter = 0
+    while vgs_counter < length(vgs_vector)
+        option TEMP=25
+        alter vgs = vgs_vector[vgs_counter]
+
+        save  @mn[vds] @mn[vgs] @mn[id] @mn[cgs]
+        *******************
+        ** simulation part
+        *******************
+        DC vds $&vds_min $&vds_max $&vds_step
+    
+        * ** parameters calculation
+	
+	print @mn[cgd]
+        
+        wrdata pmos_3p3_cv/simulated_Cgd/{{i}}_simulated_W{{width}}_L{{length}}.csv {@mn[cgd]*1e15} 
+        
+        reset
+        let vgs_counter = vgs_counter + 1
+    end
+end
+.endc
+.end
diff --git a/models/ngspice/testing/regression/mos_cv/device_netlists_Cgs/nmos_3p3_cv.spice b/models/ngspice/testing/regression/mos_cv/device_netlists_Cgs/nmos_3p3_cv.spice
new file mode 100644
index 0000000..6bb276f
--- /dev/null
+++ b/models/ngspice/testing/regression/mos_cv/device_netlists_Cgs/nmos_3p3_cv.spice
@@ -0,0 +1,74 @@
+***************************
+** nmos_3p3_cv
+***************************
+* Copyright 2022 Efabless Corporation
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*      http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+** library calling
+
+.include "../../../design.ngspice"
+.lib "../../../sm141064.ngspice" typical
+
+
+** Circuit Description **
+* power supply
+vds D_tn 0 dc=3.3
+vgs G_tn 0 dc=3.3
+vs S_tn 0 dc=0.1
+
+.temp 25
+.options tnom=25
+
+*l_diff_min = 0.24
+* ad = int((nf+1)/2) * width/nf * 0.24       = 24u                         
+* pd = (int((nf+1)/2) * width/nf + 0.24)*2   = 200.48u                 
+
+* circuit
+mn D_tn G_tn S_tn S_tn nmos_3p3 W = 200u L = 0.28u nf=20 ad= 24u pd=200.48u as=24u ps=200.48u
+
+.control
+set filetype=ascii
+
+let vds_min  = 0
+let vds_step = 0.1
+let vds_max  = 3.3
+
+compose  vgs_vector   start=0          stop=3.3          step=1
+
+set appendwrite
+
+foreach t 25
+
+    let vgs_counter = 0
+    while vgs_counter < length(vgs_vector)
+        option TEMP=25
+        alter vgs = vgs_vector[vgs_counter]
+
+        save  @mn[vds] @mn[vgs] @mn[id] @mn[cgs]
+        *******************
+        ** simulation part
+        *******************
+        DC vds $&vds_min $&vds_max $&vds_step
+    
+        * ** parameters calculation
+	
+	print @mn[cgs]
+        
+        wrdata nmos_3p3_cv/simulated_Cgs/{{i}}_simulated_W{{width}}_L{{length}}.csv {@mn[cgs]*1e15} 
+        
+        reset
+        let vgs_counter = vgs_counter + 1
+    end
+end
+.endc
+.end
diff --git a/models/ngspice/testing/regression/mos_cv/device_netlists_Cgs/pmos_3p3_cv.spice b/models/ngspice/testing/regression/mos_cv/device_netlists_Cgs/pmos_3p3_cv.spice
new file mode 100644
index 0000000..eaa97b0
--- /dev/null
+++ b/models/ngspice/testing/regression/mos_cv/device_netlists_Cgs/pmos_3p3_cv.spice
@@ -0,0 +1,74 @@
+***************************
+** pmos_3p3_cv
+***************************
+* Copyright 2022 Efabless Corporation
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*      http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+** library calling
+
+.include "../../../design.ngspice"
+.lib "../../../sm141064.ngspice" typical
+
+
+** Circuit Description **
+* power supply
+vds D_tn 0 dc=-3.3
+vgs G_tn 0 dc=-3.3
+vs S_tn 0 dc=0.1
+
+.temp 25
+.options tnom=25
+
+*l_diff_min = 0.24
+* ad = int((nf+1)/2) * width/nf * 0.24       = 24u                         
+* pd = (int((nf+1)/2) * width/nf + 0.24)*2   = 200.48u                 
+
+* circuit
+mn D_tn G_tn S_tn S_tn pmos_3p3 W = 200u L = 0.28u nf=20 ad= 24u pd=200.48u as=24u ps=200.48u
+
+.control
+set filetype=ascii
+
+let vds_min  = 0
+let vds_step = -0.1
+let vds_max  = -3.3
+
+compose  vgs_vector   start=0          stop=-3.3          step=-1
+
+set appendwrite
+
+foreach t 25
+
+    let vgs_counter = 0
+    while vgs_counter < length(vgs_vector)
+        option TEMP=25
+        alter vgs = vgs_vector[vgs_counter]
+
+        save  @mn[vds] @mn[vgs] @mn[id] @mn[cgs]
+        *******************
+        ** simulation part
+        *******************
+        DC vds $&vds_min $&vds_max $&vds_step
+    
+        * ** parameters calculation
+	
+	print @mn[cgs]
+        
+        wrdata pmos_3p3_cv/simulated_Cgs/{{i}}_simulated_W{{width}}_L{{length}}.csv {@mn[cgs]*1e15} 
+        
+        reset
+        let vgs_counter = vgs_counter + 1
+    end
+end
+.endc
+.end
diff --git a/models/ngspice/testing/regression/mos_cv/measured_data/3p3_cv.nl_out.xlsx b/models/ngspice/testing/regression/mos_cv/measured_data/3p3_cv.nl_out.xlsx
new file mode 100644
index 0000000..813635c
--- /dev/null
+++ b/models/ngspice/testing/regression/mos_cv/measured_data/3p3_cv.nl_out.xlsx
Binary files differ
diff --git a/models/ngspice/testing/regression/mos_cv/measured_data/3p3_sab_cv.nl_out.xlsx b/models/ngspice/testing/regression/mos_cv/measured_data/3p3_sab_cv.nl_out.xlsx
new file mode 100644
index 0000000..fd139e1
--- /dev/null
+++ b/models/ngspice/testing/regression/mos_cv/measured_data/3p3_sab_cv.nl_out.xlsx
Binary files differ
diff --git a/models/ngspice/testing/regression/mos_cv/measured_data/6p0_cv.nl_out.xlsx b/models/ngspice/testing/regression/mos_cv/measured_data/6p0_cv.nl_out.xlsx
new file mode 100644
index 0000000..a6d80ee
--- /dev/null
+++ b/models/ngspice/testing/regression/mos_cv/measured_data/6p0_cv.nl_out.xlsx
Binary files differ
diff --git a/models/ngspice/testing/regression/mos_cv/measured_data/6p0_nat_cv.nl_out.xlsx b/models/ngspice/testing/regression/mos_cv/measured_data/6p0_nat_cv.nl_out.xlsx
new file mode 100644
index 0000000..407129c
--- /dev/null
+++ b/models/ngspice/testing/regression/mos_cv/measured_data/6p0_nat_cv.nl_out.xlsx
Binary files differ
diff --git a/models/ngspice/testing/regression/mos_cv/measured_data/6p0_sab_cv.nl_out.xlsx b/models/ngspice/testing/regression/mos_cv/measured_data/6p0_sab_cv.nl_out.xlsx
new file mode 100644
index 0000000..1dbd85c
--- /dev/null
+++ b/models/ngspice/testing/regression/mos_cv/measured_data/6p0_sab_cv.nl_out.xlsx
Binary files differ
diff --git a/models/ngspice/testing/regression/mos_cv/models_regression.py b/models/ngspice/testing/regression/mos_cv/models_regression.py
new file mode 100644
index 0000000..f4cdf84
--- /dev/null
+++ b/models/ngspice/testing/regression/mos_cv/models_regression.py
@@ -0,0 +1,293 @@
+# Copyright 2022 Efabless Corporation
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#      http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+"""
+Usage:
+  models_regression.py [--num_cores=<num>]
+
+  -h, --help             Show help text.
+  -v, --version          Show version.
+  --num_cores=<num>      Number of cores to be used by simulator
+"""
+
+from re import T
+from docopt import docopt
+import pandas as pd 
+import numpy as np
+import os 
+from jinja2 import Template
+import concurrent.futures
+import shutil
+import warnings
+warnings.simplefilter(action='ignore', category=FutureWarning)
+
+def call_simulator(file_name):
+    """Call simulation commands to perform simulation.
+    Args:
+        file_name (str): Netlist file name.
+    """
+    os.system(f"ngspice -b -a {file_name} -o {file_name}.log > {file_name}.log")
+
+def ext_measured(device,sweep_x,sweep_y,sim_val):
+    
+    # Get dimensions used for each device 
+    dimensions = pd.read_csv(f"{device}/{device}.csv",usecols=["W (um)" , "L (um)"])
+    loops = int(dimensions["L (um)"].count()/2)
+    
+    # Extracting measured values for each W & L 
+    for i in range (0,loops):
+        width  = dimensions["W (um)"].iloc[int(i)]
+        length = dimensions["L (um)"].iloc[int(i)]
+        # Special case for 1st measured values 
+        if i == 0 :
+            # measured Cgc
+            if sim_val == "Cgc":
+                col_list = [sweep_x,sweep_y[0],sweep_y[1],sweep_y[2],sweep_y[3],sweep_y[4]]
+                df_measured = pd.read_csv(f"{device}/{device}.csv",usecols=col_list)                
+                df_measured.columns = [sweep_x,sweep_y[0],sweep_y[1],sweep_y[2],sweep_y[3],sweep_y[4]]
+            else:
+            # measured Cgs & Cgd  
+                if sim_val == "Cgs":
+                    col_list = [sweep_x,sweep_y[0],sweep_y[1],sweep_y[2],sweep_y[3]]   
+                else:
+                    col_list = [sweep_x,f"{sweep_y[0]}.1",f"{sweep_y[1]}.1",f"{sweep_y[2]}.1",f"{sweep_y[3]}.1"]
+                df_measured = pd.read_csv(f"{device}/{device}.csv",usecols=col_list)            
+                df_measured.columns = [sweep_x,sweep_y[0],sweep_y[1],sweep_y[2],sweep_y[3]]
+            df_measured.to_csv(f"{device}/measured_{sim_val}/{i}_measured_W{width}_L{length}.csv", index = False)
+        else:
+            # measured Cgc
+            if sim_val == "Cgc":    
+                col_list = [sweep_x,f"{sweep_y[0]}.{i}",f"{sweep_y[1]}.{i}",f"{sweep_y[2]}.{i}",f"{sweep_y[3]}.{i}",f"{sweep_y[4]}.{i}"]
+                df_measured = pd.read_csv(f"{device}/{device}.csv",usecols=col_list)            
+                df_measured.columns = [sweep_x,f"{sweep_y[0]}",f"{sweep_y[1]}",f"{sweep_y[2]}",f"{sweep_y[3]}",f"{sweep_y[4]}"]        
+            else:
+            # measured Cgs & Cgd 
+                cgs_index = 2*i
+                cgd_index = cgs_index + 1 
+                if sim_val == "Cgs":
+                    col_list = [sweep_x,f"{sweep_y[0]}.{cgs_index}",f"{sweep_y[1]}.{cgs_index}",f"{sweep_y[2]}.{cgs_index}",f"{sweep_y[3]}.{cgs_index}"]   
+                else: 
+                    col_list = [sweep_x,f"{sweep_y[0]}.{cgd_index}",f"{sweep_y[1]}.{cgd_index}",f"{sweep_y[2]}.{cgd_index}",f"{sweep_y[3]}.{cgd_index}"]                       
+                df_measured = pd.read_csv(f"{device}/{device}.csv",usecols=col_list)                
+                df_measured.columns = [sweep_x,f"{sweep_y[0]}",f"{sweep_y[1]}",f"{sweep_y[2]}",f"{sweep_y[3]}"]                                     
+                                
+            df_measured.to_csv(f"{device}/measured_{sim_val}/{i}_measured_W{width}_L{length}.csv", index = False)
+
+def ext_simulated(device,sweep_x,sweep_y,vds_sweep,sim_val):
+    
+    # Get dimensions used for each device 
+    dimensions = pd.read_csv(f"{device}/{device}.csv",usecols=["W (um)" , "L (um)"])
+    loops = int(dimensions["L (um)"].count()/2)
+
+    netlist_tmp = f"./device_netlists_{sim_val}/{device}.spice"
+    for i in range (0,loops):
+        width  = dimensions["W (um)"].iloc[int(i)]
+        length = dimensions["L (um)"].iloc[int(i)]
+        if i == 0:
+            nf = 20
+        else:
+            nf = 1
+        with open(netlist_tmp) as f:
+            tmpl = Template(f.read())
+            os.makedirs(f"{device}/{device}_netlists_{sim_val}",exist_ok=True)
+            with open(f"{device}/{device}_netlists_{sim_val}/{i}_{device}_netlist_W{width}_L{length}.spice", "w") as netlist:
+                netlist.write(tmpl.render(width = width,length = length,i = i, nf = nf ))
+            netlist_path  = f"{device}/{device}_netlists_{sim_val}/{i}_{device}_netlist_W{width}_L{length}.spice" 
+            # Running ngspice for each netlist 
+            with concurrent.futures.ProcessPoolExecutor(max_workers=workers_count) as executor:
+                executor.submit(call_simulator, netlist_path)
+            
+            # Writing simulated data 
+            df_simulated = pd.read_csv(f"{device}/simulated_{sim_val}/{i}_simulated_W{width}_L{length}.csv",header=None, delimiter=r"\s+")
+            df_simulated.to_csv(f"{device}/simulated_{sim_val}/{i}_simulated_W{width}_L{length}.csv",index= False)    
+            
+            # empty array to append in it shaped (vds_sweep, number of trials + 1)
+            new_array = np.empty((vds_sweep, 1+int(df_simulated.shape[0]/vds_sweep)))  
+            new_array[:, 0] = df_simulated.iloc[:vds_sweep, 0]
+            times = int(df_simulated.shape[0]/vds_sweep)
+
+            for j in range(times):
+                new_array[:, (j+1)] = df_simulated.iloc[j*vds_sweep:(j+1)*vds_sweep, 1]
+                
+            # Writing final simulated data                 
+            df_simulated = pd.DataFrame(new_array)
+            df_simulated.to_csv(f"{device}/simulated_{sim_val}/{i}_simulated_W{width}_L{length}.csv",index= False)
+            if sim_val == "Cgc":    
+                df_simulated.columns = [sweep_x,sweep_y[0],sweep_y[1],sweep_y[2],sweep_y[3],sweep_y[4]]
+            else: 
+                df_simulated.columns = [sweep_x,sweep_y[0],sweep_y[1],sweep_y[2],sweep_y[3]]
+            df_simulated.to_csv(f"{device}/simulated_{sim_val}/{i}_simulated_W{width}_L{length}.csv",index= False)    
+            
+def error_cal(device,sweep_x,sweep_y,sim_val):
+    
+    # Get dimensions used for each device 
+    dimensions = pd.read_csv(f"{device}/{device}.csv",usecols=["W (um)" , "L (um)"])
+    loops = int(dimensions["L (um)"].count()/2)
+    df_final = pd.DataFrame()
+    for i in range (0,loops):  
+        width  = dimensions["W (um)"].iloc[int(i)]
+        length = dimensions["L (um)"].iloc[int(i)]
+            
+        measured  = pd.read_csv(f"{device}/measured_{sim_val}/{i}_measured_W{width}_L{length}.csv")
+        simulated = pd.read_csv(f"{device}/simulated_{sim_val}/{i}_simulated_W{width}_L{length}.csv")
+
+        error_1 = round (100 * (abs(measured.iloc[:, 1]) - abs(simulated.iloc[:, 1]))/abs(measured.iloc[:, 1]),6)  
+        error_2 = round (100 * (abs(measured.iloc[:, 2]) - abs(simulated.iloc[:, 2]))/abs(measured.iloc[:, 2]),6)
+        error_3 = round (100 * (abs(measured.iloc[:, 3]) - abs(simulated.iloc[:, 3]))/abs(measured.iloc[:, 3]),6) 
+        error_4 = round (100 * (abs(measured.iloc[:, 4]) - abs(simulated.iloc[:, 4]))/abs(measured.iloc[:, 4]),6)         
+        if sim_val == "Cgc":
+            error_5 = round (100 * (abs(measured.iloc[:, 5]) - abs(simulated.iloc[:, 5]))/abs(measured.iloc[:, 5]),6) 
+            df_error = pd.DataFrame(data=[measured.iloc[:, 0],error_1,error_2,error_3,error_4,error_5]).transpose()        
+        else: 
+            df_error = pd.DataFrame(data=[measured.iloc[:, 0],error_1,error_2,error_3,error_4]).transpose()        
+        df_error.to_csv(f"{device}/error_{sim_val}/{i}_{device}_error_W{width}_L{length}.csv",index= False)
+
+        # Mean error 
+        if sim_val == "Cgc":
+            mean_error = (df_error[sweep_y[0]].mean() + df_error[sweep_y[1]].mean() + df_error[sweep_y[2]].mean() + 
+                          df_error[sweep_y[3]].mean() + df_error[sweep_y[4]].mean())/5
+        else: 
+            mean_error = (df_error[sweep_y[0]].mean() + df_error[sweep_y[1]].mean() + df_error[sweep_y[2]].mean() + 
+                          df_error[sweep_y[3]].mean())/4 
+        # Max error 
+        if sim_val == "Cgc":
+            max_error = df_error[[sweep_y[0],sweep_y[1],sweep_y[2],sweep_y[3],sweep_y[4]]].max().max()
+        else:
+            max_error = df_error[[sweep_y[0],sweep_y[1],sweep_y[2],sweep_y[3]]].max().max()
+        # Max error location 
+        max_index = max((df_error == max_error).idxmax())
+        max_location_sweep_y = (df_error == max_error).idxmax(axis=1)[max_index]
+        max_location_sweep_x = df_error[sweep_x][max_index]
+
+        df_final_ = {'Run no.': f'{i}', 'Temp': f'25', 'Device name': f'{device}', 'Width': f'{width}', 'Length': f'{length}', 'Simulated_Val':f'{sim_val}','Mean error%':f'{"{:.2f}".format(mean_error)}', 'Max error%':f'{"{:.2f}".format(max_error)} @ {max_location_sweep_y} & {sweep_x}= {max_location_sweep_x}'}
+        df_final = df_final.append(df_final_, ignore_index = True)
+    # Max mean error 
+    print (df_final)   
+    df_final.to_csv (f"{device}/Final_report_{sim_val}.csv", index = False)
+    out_report = pd.read_csv (f"{device}/Final_report_{sim_val}.csv")
+    print ("\n",f"Max. mean error = {out_report['Mean error%'].max()}%")    
+    print ("=====================================================================================================================================================")
+
+def main():
+        
+    devices = ["nmos_3p3_cv" , "pmos_3p3_cv" ]
+    measured_data = ["3p3_cv"]
+    nmos_vds = "Vds (V)"
+    pmos_vds = "-Vds (V)"
+    nmos_vgs = "Vgs (V)"
+    pmos_vgs = "-Vgs (V)"
+    nmos_rds = "Rds"
+    cgc_sim  = "Cgc"
+    cgs_sim  = "Cgs"
+    cgd_sim  = "Cgd"
+    Rds_sim = "Rds"
+    mos_3p3_vbs_sweep = 67 
+    mos_3p3_vgs_sweep = 34 
+
+    mos_6p0_vgs_sweep = 133 
+  
+    nmos3p3_vgs = ["Vgs=0"   , "Vgs=1.1"  , "Vgs=2.2"  , "Vgs=3.3" ] 
+    pmos3p3_vgs = ["Vgs=-0"  , "Vgs=-1.1" , "Vgs=-2.2" , "Vgs=-3.3"] 
+    # pmos3p3_vgs = [-0.8 , -1.3 , -1.8 , -2.3 , -2.8 , -3.3] 
+    # nmos6p0_vgs = [ 1 ,  2 ,  3 ,  4 ,  5 ,  6] 
+    # pmos6p0_vgs = [-1 , -2 , -3 , -4 , -5 , -6] 
+    # nmos6p0_nat_vgs = [ 0.25 ,  1.4 , 2.55 , 3.7 , 4.85 , 6]
+
+    nmos3p3_vbs = ["Vbs=0"  , "Vbs=-0.825" , "Vbs=-1.65" , "Vbs=-2.475" , "Vbs=-3.3"] 
+    pmos3p3_vbs = ["Vbs=-0" , "Vbs=0.825"  , "Vbs=1.65"  , "Vbs=2.475"  , "Vbs=3.3" ] 
+    # nmos6p0_vbs = [ 0 , -0.75 , -1.5 ,  -2.25 ,  -3] 
+    # pmos6p0_vbs = [ 0 ,  0.75 ,  1.5 ,   2.25 ,   3] 
+    # nmos6p0_nat_vbs = [ 0 ,  -0.75 , -1.5 , -2.25 , -3]
+
+    for device in devices: 
+        # Folder structure of measured values 
+        dirpath = f"{device}"
+        if os.path.exists(dirpath) and os.path.isdir(dirpath):
+            shutil.rmtree(dirpath)
+        os.makedirs(f"{device}/measured_{cgc_sim}",exist_ok=False)
+        os.makedirs(f"{device}/measured_{cgs_sim}",exist_ok=False)
+        os.makedirs(f"{device}/measured_{cgd_sim}",exist_ok=False)
+        
+        # From xlsx to csv 
+        read_file = pd.read_excel (f"./measured_data/{measured_data[0]}.nl_out.xlsx")
+        read_file.to_csv (f"{device}/{device}.csv", index = False, header=True)
+
+        # Folder structure of simulated values 
+        os.makedirs(f"{device}/simulated_{cgc_sim}",exist_ok=False)
+        os.makedirs(f"{device}/simulated_{cgs_sim}",exist_ok=False)
+        os.makedirs(f"{device}/simulated_{cgd_sim}",exist_ok=False)
+        os.makedirs(f"{device}/error_{cgc_sim}",exist_ok=False)
+        os.makedirs(f"{device}/error_{cgs_sim}",exist_ok=False)
+        os.makedirs(f"{device}/error_{cgd_sim}",exist_ok=False)
+
+
+    # =========== nmos_3p3_cv ==============      
+    # Cgc 
+    ext_measured ("nmos_3p3_cv",nmos_vgs,nmos3p3_vbs,cgc_sim)
+    ext_simulated("nmos_3p3_cv",nmos_vgs,nmos3p3_vbs,mos_3p3_vbs_sweep,cgc_sim)
+    error_cal    ("nmos_3p3_cv",nmos_vgs,nmos3p3_vbs,cgc_sim)
+
+    # Cgs
+    ext_measured ("nmos_3p3_cv",nmos_vds,nmos3p3_vgs,cgs_sim)
+    ext_simulated("nmos_3p3_cv",nmos_vds,nmos3p3_vgs,mos_3p3_vgs_sweep,cgs_sim)
+    error_cal    ("nmos_3p3_cv",nmos_vds,nmos3p3_vgs,cgs_sim)
+
+    # Cgd
+    ext_measured ("nmos_3p3_cv",nmos_vds,nmos3p3_vgs,cgd_sim)
+    ext_simulated("nmos_3p3_cv",nmos_vds,nmos3p3_vgs,mos_3p3_vgs_sweep,cgd_sim)
+    error_cal    ("nmos_3p3_cv",nmos_vds,nmos3p3_vgs,cgd_sim)
+    
+    
+    # =========== nmos_3p3_cv ==============      
+    # Cgc
+    ext_measured ("pmos_3p3_cv",pmos_vgs,pmos3p3_vbs,cgc_sim)
+    ext_simulated("pmos_3p3_cv",pmos_vgs,pmos3p3_vbs,mos_3p3_vbs_sweep,cgc_sim)
+    error_cal    ("pmos_3p3_cv",pmos_vgs,pmos3p3_vbs,cgc_sim)
+    
+    # Cgs
+    ext_measured ("pmos_3p3_cv",pmos_vgs,pmos3p3_vgs,cgs_sim)
+    ext_simulated("pmos_3p3_cv",pmos_vgs,pmos3p3_vgs,mos_3p3_vgs_sweep,cgs_sim)
+    error_cal    ("pmos_3p3_cv",pmos_vgs,pmos3p3_vgs,cgs_sim)
+     
+    # Cgd   
+    ext_measured ("pmos_3p3_cv",pmos_vgs,pmos3p3_vgs,cgd_sim)
+    ext_simulated("pmos_3p3_cv",pmos_vgs,pmos3p3_vgs,mos_3p3_vgs_sweep,cgd_sim)
+    error_cal    ("pmos_3p3_cv",pmos_vgs,pmos3p3_vgs,cgd_sim)
+            
+    # =========== pmos_3p3_iv ==============      
+
+
+    # =========== nmos_6p0_iv ==============      
+
+         
+    # =========== pmos_6p0_iv ==============      
+      
+          
+    # ============ nmos_3p3_sab_iv =============                                # Error in ngspice 
+
+
+    # ============ nmos_6p0_nat_iv =============              
+ 
+ 
+# # ================================================================
+# -------------------------- MAIN --------------------------------
+# ================================================================
+        
+if __name__ == "__main__":
+    
+    # Args 
+    arguments     = docopt(__doc__, version='comparator: 0.1')
+    workers_count = os.cpu_count()*2 if arguments["--num_cores"] == None else int(arguments["--num_cores"])
+    
+    # Calling main function 
+    main()
diff --git a/models/ngspice/testing/regression/mos_iv_vbs/.spiceinit b/models/ngspice/testing/regression/mos_iv_vbs/.spiceinit
new file mode 100644
index 0000000..0be699c
--- /dev/null
+++ b/models/ngspice/testing/regression/mos_iv_vbs/.spiceinit
@@ -0,0 +1,4 @@
+
+* user provided init file
+set ngbehavior=hs
+
diff --git a/models/ngspice/testing/regression/mos_iv_vbs/device_netlists_Id/nmos_3p3_iv.spice b/models/ngspice/testing/regression/mos_iv_vbs/device_netlists_Id/nmos_3p3_iv.spice
new file mode 100644
index 0000000..47ce6c1
--- /dev/null
+++ b/models/ngspice/testing/regression/mos_iv_vbs/device_netlists_Id/nmos_3p3_iv.spice
@@ -0,0 +1,48 @@
+***************************
+** nmos_3p3_t_id
+***************************
+* Copyright 2022 Efabless Corporation
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*      http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+* power supply
+Vds D_tn 0 dc=0.05
+Vgs G_tn 0 dc=3.3
+Vbs B_tn 0 dc=0
+
+.temp {{temp}}
+.options tnom={{temp}}
+
+xmn1 D_tn G_tn 0 B_tn nmos_3p3 W = {{width}}u L = {{length}}u
+
+**** begin architecture code
+
+
+.control
+set filetype=ascii
+
+dc Vgs 0 3.3 0.05 Vbs 0 -3.3 -0.825
+print -i(Vds)
+wrdata nmos_3p3_iv/simulated_Id/{{i}}_simulated_W{{width}}_L{{length}}.csv -i(Vds)
+.endc
+
+
+
+** library calling
+
+.include "../../../design.ngspice"
+.lib "../../../sm141064.ngspice" typical
+
+**** end architecture code
+
+
+.end
diff --git a/models/ngspice/testing/regression/mos_iv_vbs/device_netlists_Id/nmos_6p0_iv.spice b/models/ngspice/testing/regression/mos_iv_vbs/device_netlists_Id/nmos_6p0_iv.spice
new file mode 100644
index 0000000..0551cd7
--- /dev/null
+++ b/models/ngspice/testing/regression/mos_iv_vbs/device_netlists_Id/nmos_6p0_iv.spice
@@ -0,0 +1,48 @@
+***************************
+** nmos_6p0_t_id
+***************************
+* Copyright 2022 Efabless Corporation
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*      http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+* power supply
+Vds D_tn 0 dc=0.05
+Vgs G_tn 0 dc=6
+Vbs S_tn 0 dc=0
+
+.temp {{temp}}
+.options tnom={{temp}}
+
+xmn1 D_tn G_tn 0 S_tn nmos_6p0 W = {{width}}u L = {{length}}u
+
+**** begin architecture code
+
+
+.control
+set filetype=ascii
+
+dc Vgs 0 6 0.05 Vbs 0 -3 -0.75
+print -i(Vds)
+wrdata nmos_6p0_iv/simulated_Id/{{i}}_simulated_W{{width}}_L{{length}}.csv -i(Vds)
+.endc
+
+
+
+** library calling
+
+.include "../../../design.ngspice"
+.lib "../../../sm141064.ngspice" typical
+
+**** end architecture code
+
+
+.end
diff --git a/models/ngspice/testing/regression/mos_iv_vbs/device_netlists_Id/nmos_6p0_nat_iv.spice b/models/ngspice/testing/regression/mos_iv_vbs/device_netlists_Id/nmos_6p0_nat_iv.spice
new file mode 100644
index 0000000..3c50e5f
--- /dev/null
+++ b/models/ngspice/testing/regression/mos_iv_vbs/device_netlists_Id/nmos_6p0_nat_iv.spice
@@ -0,0 +1,48 @@
+***************************
+** nmos_6p0_nat_t_id
+***************************
+* Copyright 2022 Efabless Corporation
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*      http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+* power supply
+Vds D_tn 0 dc=0.05
+Vgs G_tn 0 dc=6
+Vbs S_tn 0 dc=0
+
+.temp {{temp}}
+.options tnom={{temp}}
+
+xmn1 D_tn G_tn 0 S_tn nmos_6p0_nat W = {{width}}u L = {{length}}u
+
+**** begin architecture code
+
+
+.control
+set filetype=ascii
+
+dc Vgs -0.5 6 0.05 Vbs 0 -3 -0.75
+print -i(Vds)
+wrdata nmos_6p0_nat_iv/simulated_Id/{{i}}_simulated_W{{width}}_L{{length}}.csv -i(Vds)
+.endc
+
+
+
+** library calling
+
+.include "../../../design.ngspice"
+.lib "../../../sm141064.ngspice" typical
+
+**** end architecture code
+
+
+.end
diff --git a/models/ngspice/testing/regression/mos_iv_vbs/device_netlists_Id/pmos_3p3_iv.spice b/models/ngspice/testing/regression/mos_iv_vbs/device_netlists_Id/pmos_3p3_iv.spice
new file mode 100644
index 0000000..5a4a87a
--- /dev/null
+++ b/models/ngspice/testing/regression/mos_iv_vbs/device_netlists_Id/pmos_3p3_iv.spice
@@ -0,0 +1,48 @@
+***************************
+** pmos_3p3_t_id
+***************************
+* Copyright 2022 Efabless Corporation
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*      http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+* power supply
+Vds D_tn 0 dc=-0.05
+Vgs G_tn 0 dc=-3.3
+Vbs S_tn 0 dc=0
+
+.temp {{temp}}
+.options tnom={{temp}}
+
+xmn1 D_tn G_tn 0 S_tn pmos_3p3 W = {{width}}u L = {{length}}u
+
+**** begin architecture code
+
+
+.control
+set filetype=ascii
+
+dc Vgs 0 -3.3 -0.05 Vbs 0 3.3 0.825
+print -i(Vds)
+wrdata pmos_3p3_iv/simulated_Id/{{i}}_simulated_W{{width}}_L{{length}}.csv -i(Vds)
+.endc
+
+
+
+** library calling
+
+.include "../../../design.ngspice"
+.lib "../../../sm141064.ngspice" typical
+
+**** end architecture code
+
+
+.end
diff --git a/models/ngspice/testing/regression/mos_iv_vbs/device_netlists_Id/pmos_6p0_iv.spice b/models/ngspice/testing/regression/mos_iv_vbs/device_netlists_Id/pmos_6p0_iv.spice
new file mode 100644
index 0000000..e2237f2
--- /dev/null
+++ b/models/ngspice/testing/regression/mos_iv_vbs/device_netlists_Id/pmos_6p0_iv.spice
@@ -0,0 +1,50 @@
+***************************
+** pmos_6p0_t_id
+***************************
+* Copyright 2022 Efabless Corporation
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*      http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+* power supply
+Vds D_tn 0 dc=-0.05
+Vgs G_tn 0 dc=-6
+Vbs S_tn 0 dc=0
+
+
+.temp {{temp}}
+.options tnom={{temp}}
+
+xmn1 D_tn G_tn 0 S_tn pmos_6p0 W = {{width}}u L = {{length}}u
+
+**** begin architecture code
+
+
+.control
+set filetype=ascii
+
+dc Vgs 0 -6 -0.05 Vbs 0 3 0.75
+print -i(Vds)
+wrdata pmos_6p0_iv/simulated_Id/{{i}}_simulated_W{{width}}_L{{length}}.csv -i(Vds)
+.endc
+
+
+
+** library calling
+
+.include "../../../design.ngspice"
+.lib "../../../sm141064.ngspice" typical
+
+
+**** end architecture code
+
+
+.end
diff --git a/models/ngspice/testing/regression/mos_iv_vbs/models_regression.py b/models/ngspice/testing/regression/mos_iv_vbs/models_regression.py
new file mode 100644
index 0000000..675229e
--- /dev/null
+++ b/models/ngspice/testing/regression/mos_iv_vbs/models_regression.py
@@ -0,0 +1,237 @@
+# Copyright 2022 Efabless Corporation
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#      http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+"""
+Usage:
+  models_regression.py [--num_cores=<num>]
+
+  -h, --help             Show help text.
+  -v, --version          Show version.
+  --num_cores=<num>      Number of cores to be used by simulator
+"""
+
+from re import T
+from docopt import docopt
+import pandas as pd 
+import numpy as np
+import os 
+from jinja2 import Template
+import concurrent.futures
+import shutil
+import warnings
+warnings.simplefilter(action='ignore', category=FutureWarning)
+
+def call_simulator(file_name):
+    """Call simulation commands to perform simulation.
+    Args:
+        file_name (str): Netlist file name.
+    """
+    os.system(f"ngspice -b -a {file_name} -o {file_name}.log > {file_name}.log")
+
+def ext_measured(device,vgs,vbs):
+    
+    # Get dimensions used for each device 
+    dimensions = pd.read_csv(f"{device}/{device}.csv",usecols=["W (um)" , "L (um)"])
+    loops = dimensions["L (um)"].count()
+    
+    # Extracting measured values for each W & L 
+    for i in range (0,loops*2,2):
+        width  = dimensions["W (um)"].iloc[int(i/2)]
+        length = dimensions["L (um)"].iloc[int(i/2)]
+        
+        # Special case for 1st measured values 
+        if i == 0 :
+            # measured Id
+            if device in ["pmos_3p3_iv" , "pmos_6p0_iv"]:
+                col_list = ['-vgs ',f"vbs ={vbs[0]}",f"vbs ={vbs[1]}",f"vbs ={vbs[2]}",f"vbs ={vbs[3]}",f"vbs ={vbs[4]}"]
+            else:
+                col_list = ['vgs ',f"vbs ={vbs[0]}",f"vbs ={vbs[1]}",f"vbs ={vbs[2]}",f"vbs ={vbs[3]}",f"vbs ={vbs[4]}"]                
+            df_measured = pd.read_csv(f"{device}/{device}.csv",usecols=col_list)
+            df_measured.columns = [f"{vgs}",f"vbs ={vbs[0]}",f"vbs ={vbs[1]}",f"vbs ={vbs[2]}",f"vbs ={vbs[3]}",f"vbs ={vbs[4]}"]
+            df_measured.to_csv(f"{device}/measured_Id/{int(i/2)}_measured_W{width}_L{length}.csv", index = False)
+        else:
+            # measured Id
+            col_list = [f"{vgs}",f"vbs ={vbs[0]}.{i}",f"vbs ={vbs[1]}.{i}",f"vbs ={vbs[2]}.{i}",f"vbs ={vbs[3]}.{i}",f"vbs ={vbs[4]}.{i}"]
+            df_measured = pd.read_csv(f"{device}/{device}.csv",usecols=col_list)
+            df_measured.columns = [f"{vgs}",f"vbs ={vbs[0]}",f"vbs ={vbs[1]}",f"vbs ={vbs[2]}",f"vbs ={vbs[3]}",f"vbs ={vbs[4]}"]        
+            df_measured.to_csv(f"{device}/measured_Id/{int(i/2)}_measured_W{width}_L{length}.csv", index = False)
+
+
+def ext_simulated(device,vgs,vbs,vbs_sweep,sim_val):
+    
+    # Get dimensions used for each device 
+    dimensions = pd.read_csv(f"{device}/{device}.csv",usecols=["W (um)" , "L (um)"])
+    loops = dimensions["L (um)"].count()
+    temp_range = int(loops/3) 
+    netlist_tmp = f"./device_netlists_{sim_val}/{device}.spice"
+    for i in range (0,loops):
+        width  = dimensions["W (um)"].iloc[int(i)]
+        length = dimensions["L (um)"].iloc[int(i)]
+        AD = float(width) * 0.24
+        PD = 2 * (float(width) + 0.24)
+        AS = AD 
+        PS = PD 
+        if i in range (0,temp_range): temp = 25 
+        elif i in range (temp_range,2*temp_range): temp = -40 
+        else:
+            temp = 125 
+        with open(netlist_tmp) as f:
+            tmpl = Template(f.read())
+            os.makedirs(f"{device}/{device}_netlists_{sim_val}",exist_ok=True)
+            with open(f"{device}/{device}_netlists_{sim_val}/{i}_{device}_netlist_W{width}_L{length}.spice", "w") as netlist:
+                netlist.write(tmpl.render(width = width,length = length,i = i , temp = temp , AD = AD , PD = PD , AS = AS , PS = PD ))
+            netlist_path  = f"{device}/{device}_netlists_{sim_val}/{i}_{device}_netlist_W{width}_L{length}.spice" 
+            # Running ngspice for each netlist 
+            with concurrent.futures.ProcessPoolExecutor(max_workers=workers_count) as executor:
+                executor.submit(call_simulator, netlist_path)
+            
+            # Writing simulated data 
+            df_simulated = pd.read_csv(f"{device}/simulated_{sim_val}/{i}_simulated_W{width}_L{length}.csv",header=None, delimiter=r"\s+")
+            df_simulated.to_csv(f"{device}/simulated_{sim_val}/{i}_simulated_W{width}_L{length}.csv",index= False)    
+            
+            # empty array to append in it shaped (vbs_sweep, number of trials + 1)
+            new_array = np.empty((vbs_sweep, 1+int(df_simulated.shape[0]/vbs_sweep)))  
+            new_array[:, 0] = df_simulated.iloc[:vbs_sweep, 0]
+            times = int(df_simulated.shape[0]/vbs_sweep)
+
+            for j in range(times):
+                new_array[:, (j+1)] = df_simulated.iloc[j*vbs_sweep:(j+1)*vbs_sweep, 1]
+                
+            # Writing final simulated data                 
+            df_simulated = pd.DataFrame(new_array)
+            df_simulated.to_csv(f"{device}/simulated_{sim_val}/{i}_simulated_W{width}_L{length}.csv",index= False)    
+            df_simulated.columns = [f"{vgs}",f"vbs ={vbs[0]}",f"vbs ={vbs[1]}",f"vbs ={vbs[2]}",f"vbs ={vbs[3]}",f"vbs ={vbs[4]}"]
+            df_simulated.to_csv(f"{device}/simulated_{sim_val}/{i}_simulated_W{width}_L{length}.csv",index= False)    
+
+def error_cal(device,vgs,vbs,sim_val):
+    
+    # Get dimensions used for each device 
+    dimensions = pd.read_csv(f"{device}/{device}.csv",usecols=["W (um)" , "L (um)"])
+    loops = dimensions["L (um)"].count()
+    temp_range = int(loops/3)     
+    df_final = pd.DataFrame()
+    for i in range (0,loops):  
+        width  = dimensions["W (um)"].iloc[int(i)]
+        length = dimensions["L (um)"].iloc[int(i)]
+        if i in range (0,temp_range): temp = 25             
+        elif i in range (temp_range,2*temp_range): temp = -40             
+        else: temp = 125
+             
+        measured  = pd.read_csv(f"{device}/measured_{sim_val}/{i}_measured_W{width}_L{length}.csv")
+        simulated = pd.read_csv(f"{device}/simulated_{sim_val}/{i}_simulated_W{width}_L{length}.csv")
+
+        error_1 = round (100 * abs((abs(measured.iloc[:, 1]) - abs(simulated.iloc[:, 1]))/abs(measured.iloc[:, 1])),6)  
+        error_2 = round (100 * abs((abs(measured.iloc[:, 2]) - abs(simulated.iloc[:, 2]))/abs(measured.iloc[:, 2])),6)
+        error_3 = round (100 * abs((abs(measured.iloc[:, 3]) - abs(simulated.iloc[:, 3]))/abs(measured.iloc[:, 3])),6) 
+        error_4 = round (100 * abs((abs(measured.iloc[:, 4]) - abs(simulated.iloc[:, 4]))/abs(measured.iloc[:, 4])),6) 
+        error_5 = round (100 * abs((abs(measured.iloc[:, 5]) - abs(simulated.iloc[:, 5]))/abs(measured.iloc[:, 5])),6) 
+
+        df_error = pd.DataFrame(data=[measured.iloc[:, 0],error_1,error_2,error_3,error_4,error_5]).transpose()        
+        df_error.to_csv(f"{device}/error_{sim_val}/{i}_{device}_error_W{width}_L{length}.csv",index= False)
+        
+        # Mean error 
+        mean_error = (df_error[f"vbs ={vbs[0]}"].mean() + df_error[f"vbs ={vbs[1]}"].mean() + df_error[f"vbs ={vbs[2]}"].mean() + 
+                      df_error[f"vbs ={vbs[3]}"].mean() + df_error[f"vbs ={vbs[4]}"].mean())/6
+        # Max error 
+        max_error = df_error[[f"vbs ={vbs[0]}",f"vbs ={vbs[1]}",f"vbs ={vbs[2]}",f"vbs ={vbs[3]}",f"vbs ={vbs[4]}"]].max().max()
+        # Max error location 
+        max_index = max((df_error == max_error).idxmax())
+        max_location_vbs = (df_error == max_error).idxmax(axis=1)[max_index]
+        max_location_vgs = df_error[f"{vgs}"][max_index]
+
+        df_final_ = {'Run no.': f'{i}', 'Temp': f'{temp}', 'Device name': f'{device}', 'Width': f'{width}', 'Length': f'{length}', 'Simulated_Val':f'{sim_val}','Mean error%':f'{"{:.2f}".format(mean_error)}', 'Max error%':f'{"{:.2f}".format(max_error)} @ {max_location_vgs} & vbs (V) = {max_location_vbs}'}
+        df_final = df_final.append(df_final_, ignore_index = True)
+    # Max mean error 
+    print (df_final)   
+    df_final.to_csv (f"{device}/Final_report_{sim_val}.csv", index = False)
+    out_report = pd.read_csv (f"{device}/Final_report_{sim_val}.csv")
+    print ("\n",f"Max. mean error = {out_report['Mean error%'].max()}%")    
+    print ("=====================================================================================================================================================")
+
+def main():
+        
+    devices = ["nmos_3p3_iv" , "pmos_3p3_iv" , "nmos_6p0_iv" , "pmos_6p0_iv" , "nmos_6p0_nat_iv"] #"nmos_3p3_sab_iv"
+    nmos_vgs = "vgs (V)"
+    pmos_vgs = "-vgs (V)"
+    nmos_rds = "Rds"
+    Id_sim  = "Id"
+    Rds_sim = "Rds"
+    mos_3p3_vbs_sweep = 67 
+    mos_6p0_vbs_sweep = 121 
+    mos_6p0_nat_vbs_sweep = 131     
+    nmos3p3_vbs = [0 , -0.825 , -1.65 ,  -2.48 ,  -3.3] 
+    pmos3p3_vbs = [0 ,  0.825 ,  1.65 ,   2.48 ,   3.3] 
+    nmos6p0_vbs = [ 0 , -0.75 , -1.5 ,  -2.25 ,  -3] 
+    pmos6p0_vbs = [ 0 ,  0.75 ,  1.5 ,   2.25 ,   3] 
+    nmos6p0_nat_vbs = [ 0 ,  -0.75 , -1.5 , -2.25 , -3]
+
+    for device in devices: 
+        # Folder structure of measured values 
+        dirpath = f"{device}"
+        if os.path.exists(dirpath) and os.path.isdir(dirpath):
+            shutil.rmtree(dirpath)
+        os.makedirs(f"{device}/measured_{Id_sim}",exist_ok=False)
+        # os.makedirs(f"{device}/measured_{Rds_sim}",exist_ok=False)
+
+        # From xlsx to csv 
+        read_file = pd.read_excel (f"../../180MCU_SPICE_DATA/MOS/{device}.nl_out.xlsx")
+        read_file.to_csv (f"{device}/{device}.csv", index = False, header=True)
+
+        # Folder structure of simulated values 
+        os.makedirs(f"{device}/simulated_{Id_sim}",exist_ok=False)
+        # os.makedirs(f"{device}/simulated_{Rds_sim}",exist_ok=False)
+        os.makedirs(f"{device}/error_{Id_sim}",exist_ok=False)
+        # os.makedirs(f"{device}/error_{Rds_sim}",exist_ok=False)
+
+    # =========== nmos_3p3_iv ==============      
+    ext_measured ("nmos_3p3_iv",nmos_vgs,nmos3p3_vbs)
+    ext_simulated("nmos_3p3_iv",nmos_vgs,nmos3p3_vbs,mos_3p3_vbs_sweep,Id_sim)
+    error_cal    ("nmos_3p3_iv",nmos_vgs,nmos3p3_vbs,Id_sim)
+
+    # =========== pmos_3p3_iv ==============      
+    ext_measured ("pmos_3p3_iv",pmos_vgs,pmos3p3_vbs)
+    ext_simulated("pmos_3p3_iv",pmos_vgs,pmos3p3_vbs,mos_3p3_vbs_sweep,Id_sim)
+    error_cal    ("pmos_3p3_iv",pmos_vgs,pmos3p3_vbs,Id_sim)
+
+    # =========== nmos_6p0_iv ==============      
+    ext_measured ("nmos_6p0_iv",nmos_vgs,nmos6p0_vbs)   
+    ext_simulated("nmos_6p0_iv",nmos_vgs,nmos6p0_vbs,mos_6p0_vbs_sweep,Id_sim)
+    error_cal    ("nmos_6p0_iv",nmos_vgs,nmos6p0_vbs,Id_sim)    
+         
+    # =========== pmos_6p0_iv ==============      
+    ext_measured ("pmos_6p0_iv",pmos_vgs,pmos6p0_vbs)
+    ext_simulated("pmos_6p0_iv",pmos_vgs,pmos6p0_vbs,mos_6p0_vbs_sweep,Id_sim)
+    error_cal    ("pmos_6p0_iv",pmos_vgs,pmos6p0_vbs,Id_sim) 
+          
+    # ============ nmos_3p3_sab_iv =============                                # Error in ngspice 
+    # ext_measured ("nmos_3p3_sab_iv",nmos_vgs,nmos3p3_vbs)    
+    # ext_simulated("nmos_3p3_sab_iv",nmos_vgs,nmos3p3_vbs,mos_3p3_vbs_sweep,Id_sim)
+    # error_cal    ("nmos_3p3_sab_iv",nmos_vgs,nmos3p3_vbs,Rds_sim)
+
+    # ============ nmos_6p0_nat_iv =============              
+    ext_measured ("nmos_6p0_nat_iv",nmos_vgs,nmos6p0_nat_vbs)
+    ext_simulated("nmos_6p0_nat_iv",nmos_vgs,nmos6p0_nat_vbs,mos_6p0_nat_vbs_sweep,Id_sim)
+    error_cal    ("nmos_6p0_nat_iv",nmos_vgs,nmos6p0_nat_vbs,Id_sim)     
+
+# # ================================================================
+# -------------------------- MAIN --------------------------------
+# ================================================================
+        
+if __name__ == "__main__":
+    
+    # Args 
+    arguments     = docopt(__doc__, version='comparator: 0.1')
+    workers_count = os.cpu_count()*2 if arguments["--num_cores"] == None else int(arguments["--num_cores"])
+    
+    # Calling main function 
+    main()
\ No newline at end of file
diff --git a/models/ngspice/testing/regression/mos_iv_vgs/.spiceinit b/models/ngspice/testing/regression/mos_iv_vgs/.spiceinit
new file mode 100644
index 0000000..0be699c
--- /dev/null
+++ b/models/ngspice/testing/regression/mos_iv_vgs/.spiceinit
@@ -0,0 +1,4 @@
+
+* user provided init file
+set ngbehavior=hs
+
diff --git a/models/ngspice/testing/regression/mos_iv_vgs/0_man_error_debugging/nmos_3p3/Id/48_W0.22_L0.5_id/48_W0.22_L0.5.ods b/models/ngspice/testing/regression/mos_iv_vgs/0_man_error_debugging/nmos_3p3/Id/48_W0.22_L0.5_id/48_W0.22_L0.5.ods
new file mode 100644
index 0000000..9a12f21
--- /dev/null
+++ b/models/ngspice/testing/regression/mos_iv_vgs/0_man_error_debugging/nmos_3p3/Id/48_W0.22_L0.5_id/48_W0.22_L0.5.ods
Binary files differ
diff --git a/models/ngspice/testing/regression/mos_iv_vgs/0_man_error_debugging/nmos_3p3/Id/48_W0.22_L0.5_id/48_measured_W0.22_L0.5.csv b/models/ngspice/testing/regression/mos_iv_vgs/0_man_error_debugging/nmos_3p3/Id/48_W0.22_L0.5_id/48_measured_W0.22_L0.5.csv
new file mode 100644
index 0000000..b656307
--- /dev/null
+++ b/models/ngspice/testing/regression/mos_iv_vgs/0_man_error_debugging/nmos_3p3/Id/48_W0.22_L0.5_id/48_measured_W0.22_L0.5.csv
@@ -0,0 +1,68 @@
+vds (V),vgs =0.8_mea,vgs =1.3_mea,vgs =1.8_mea,vgs =2.3_mea,vgs =2.8_mea,vgs =3.3_mea
+0,0,0,0,0,0,0
+0.05,0.000000394808,0.00000250744,0.00000415488,0.00000540081,0.00000635234,0.0000070844
+0.1,0.000000599289,0.00000469955,0.00000796984,0.0000104601,0.0000123724,0.0000138509
+0.15,0.000000675551,0.00000659522,0.0000114625,0.0000151936,0.0000180738,0.0000203114
+0.2,0.000000703823,0.00000821193,0.0000146493,0.000019616,0.0000234695,0.000026477
+0.25,0.000000719359,0.00000956596,0.0000175456,0.0000237412,0.0000285717,0.0000323583
+0.3,0.00000073047,0.0000106727,0.0000201655,0.0000275821,0.0000333918,0.0000379655
+0.35,0.000000739448,0.0000115474,0.0000225223,0.0000311509,0.000037941,0.0000433083
+0.4,0.000000747171,0.0000122074,0.000024628,0.0000344592,0.0000422294,0.0000483957
+0.45,0.000000754064,0.0000126791,0.0000264939,0.0000375176,0.0000462669,0.0000532366
+0.5,0.000000760366,0.0000130039,0.0000281296,0.000040336,0.0000500628,0.0000578394
+0.55,0.000000766223,0.0000132304,0.0000295432,0.0000429238,0.0000536257,0.0000622118
+0.6,0.000000771734,0.0000133967,0.0000307404,0.000045289,0.0000569639,0.0000663615
+0.65,0.000000776969,0.0000135258,0.000031726,0.0000474388,0.000060085,0.0000702956
+0.7,0.000000781977,0.000013631,0.0000325086,0.0000493786,0.0000629959,0.0000740209
+0.75,0.000000786795,0.0000137197,0.0000331103,0.0000511113,0.0000657028,0.0000775436
+0.8,0.000000791454,0.0000137967,0.0000335682,0.0000526365,0.000068211,0.0000808698
+0.85,0.000000795976,0.0000138648,0.0000339219,0.0000539506,0.0000705243,0.0000840048
+0.9,0.00000080038,0.0000139261,0.0000342032,0.0000550503,0.0000726444,0.0000869533
+0.95,0.00000080468,0.000013982,0.0000344339,0.0000559425,0.0000745699,0.0000897193
+1,0.000000808889,0.0000140335,0.0000346285,0.0000566516,0.0000762953,0.0000923055
+1.05,0.000000813017,0.0000140813,0.0000347963,0.0000572141,0.0000778115,0.0000947128
+1.1,0.000000817074,0.000014126,0.0000349439,0.0000576666,0.0000791096,0.0000969396
+1.15,0.000000821066,0.0000141682,0.0000350756,0.0000580386,0.0000801907,0.0000989809
+1.2,0.000000825,0.0000142081,0.0000351946,0.0000583513,0.0000810732,0.000100827
+1.25,0.000000828881,0.000014246,0.0000353034,0.0000586196,0.0000817895,0.000102465
+1.3,0.000000832715,0.0000142822,0.0000354036,0.000058854,0.0000823753,0.000103883
+1.35,0.000000836505,0.0000143169,0.0000354967,0.0000590619,0.0000828619,0.000105083
+1.4,0.000000840256,0.0000143502,0.0000355836,0.0000592486,0.0000832735,0.000106079
+1.45,0.00000084397,0.0000143823,0.0000356653,0.0000594181,0.0000836278,0.000106901
+1.5,0.000000847651,0.0000144134,0.0000357424,0.0000595734,0.0000839377,0.000107584
+1.55,0.000000851301,0.0000144434,0.0000358154,0.0000597167,0.0000842125,0.000108158
+1.6,0.000000854924,0.0000144725,0.000035885,0.0000598498,0.0000844591,0.000108648
+1.65,0.00000085852,0.0000145008,0.0000359513,0.0000599743,0.0000846827,0.000109072
+1.7,0.000000862094,0.0000145284,0.0000360149,0.0000600912,0.0000848871,0.000109444
+1.75,0.000000865647,0.0000145552,0.0000360759,0.0000602015,0.0000850756,0.000109776
+1.8,0.00000086918,0.0000145814,0.0000361346,0.000060306,0.0000852504,0.000110073
+1.85,0.000000872698,0.000014607,0.0000361912,0.0000604053,0.0000854135,0.000110344
+1.9,0.000000876202,0.0000146321,0.0000362458,0.0000605,0.0000855663,0.000110591
+1.95,0.000000879694,0.0000146567,0.0000362988,0.0000605906,0.0000857103,0.000110819
+2,0.000000883178,0.0000146808,0.0000363501,0.0000606774,0.0000858464,0.00011103
+2.05,0.000000886656,0.0000147045,0.0000364,0.0000607608,0.0000859756,0.000111227
+2.1,0.000000890133,0.0000147278,0.0000364485,0.0000608412,0.0000860985,0.000111412
+2.15,0.000000893611,0.0000147508,0.0000364957,0.0000609187,0.0000862159,0.000111586
+2.2,0.000000897095,0.0000147734,0.0000365418,0.0000609936,0.0000863281,0.000111751
+2.25,0.000000900589,0.0000147958,0.0000365868,0.0000610661,0.0000864358,0.000111907
+2.3,0.000000904098,0.000014818,0.0000366308,0.0000611364,0.0000865394,0.000112055
+2.35,0.000000907628,0.00001484,0.000036674,0.0000612047,0.0000866391,0.000112196
+2.4,0.000000911185,0.0000148619,0.0000367164,0.0000612711,0.0000867353,0.000112331
+2.45,0.000000914776,0.0000148837,0.0000367581,0.0000613359,0.0000868283,0.000112461
+2.5,0.000000918408,0.0000149056,0.0000367992,0.0000613991,0.0000869184,0.000112585
+2.55,0.000000922089,0.0000149275,0.0000368398,0.0000614608,0.0000870057,0.000112705
+2.6,0.000000925828,0.0000149496,0.0000368801,0.0000615213,0.0000870905,0.000112821
+2.65,0.000000929635,0.0000149719,0.0000369202,0.0000615808,0.0000871731,0.000112932
+2.7,0.000000933521,0.0000149945,0.0000369601,0.0000616392,0.0000872535,0.00011304
+2.75,0.000000937496,0.0000150176,0.0000370002,0.0000616969,0.0000873321,0.000113145
+2.8,0.000000941573,0.0000150412,0.0000370404,0.000061754,0.000087409,0.000113246
+2.85,0.000000945765,0.0000150655,0.0000370811,0.0000618108,0.0000874844,0.000113345
+2.9,0.000000950086,0.0000150906,0.0000371225,0.0000618673,0.0000875586,0.000113441
+2.95,0.000000954551,0.0000151167,0.0000371646,0.000061924,0.0000876318,0.000113535
+3,0.000000959177,0.0000151438,0.000037208,0.0000619811,0.0000877043,0.000113627
+3.05,0.00000096398,0.0000151723,0.0000372527,0.0000620388,0.0000877763,0.000113717
+3.1,0.00000096898,0.0000152021,0.0000372991,0.0000620976,0.0000878482,0.000113805
+3.15,0.000000974195,0.0000152337,0.0000373475,0.0000621577,0.0000879203,0.000113893
+3.2,0.000000979646,0.0000152671,0.0000373982,0.0000622196,0.000087993,0.000113979
+3.25,0.000000985354,0.0000153025,0.0000374518,0.0000622838,0.0000880667,0.000114066
+3.3,0.000000991344,0.0000153403,0.0000375085,0.0000623507,0.000088142,0.000114152
diff --git a/models/ngspice/testing/regression/mos_iv_vgs/0_man_error_debugging/nmos_3p3/Id/48_W0.22_L0.5_id/48_simulated_W0.22_L0.5.csv b/models/ngspice/testing/regression/mos_iv_vgs/0_man_error_debugging/nmos_3p3/Id/48_W0.22_L0.5_id/48_simulated_W0.22_L0.5.csv
new file mode 100644
index 0000000..559bf1d
--- /dev/null
+++ b/models/ngspice/testing/regression/mos_iv_vgs/0_man_error_debugging/nmos_3p3/Id/48_W0.22_L0.5_id/48_simulated_W0.22_L0.5.csv
@@ -0,0 +1,68 @@
+vds (V),vgs =0.8,vgs =1.3,vgs =1.8,vgs =2.3,vgs =2.8,vgs =3.3
+0.0,-0.0,-0.0,-0.0,-0.0,-0.0,-0.0
+0.05,3.22975818e-07,2.43157729e-06,4.09284118e-06,5.34817009e-06,6.3062549e-06,7.04303691e-06
+0.1,4.73071201e-07,4.55021762e-06,7.84708646e-06,1.03557458e-05,1.22809248e-05,1.37688149e-05
+0.15,5.22055208e-07,6.374768e-06,1.1280361e-05,1.50384049e-05,1.79376507e-05,2.01890947e-05
+0.2,5.40679521e-07,7.92268471e-06,1.44090676e-05,1.9410865e-05,2.32893288e-05,2.6315059e-05
+0.25,5.51695359e-07,9.21026143e-06,1.72484754e-05,2.348695e-05,2.83481576e-05,3.21573459e-05
+0.3,5.59915347e-07,1.02530145e-05,1.9812787e-05,2.72796465e-05,3.31256801e-05,3.77260797e-05
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diff --git a/models/ngspice/testing/regression/mos_iv_vgs/0_man_error_debugging/nmos_3p3/Id/49_W0.22_L0.28_id/49_W0.22_L0.28.ods b/models/ngspice/testing/regression/mos_iv_vgs/0_man_error_debugging/nmos_3p3/Id/49_W0.22_L0.28_id/49_W0.22_L0.28.ods
new file mode 100644
index 0000000..46c102b
--- /dev/null
+++ b/models/ngspice/testing/regression/mos_iv_vgs/0_man_error_debugging/nmos_3p3/Id/49_W0.22_L0.28_id/49_W0.22_L0.28.ods
Binary files differ
diff --git a/models/ngspice/testing/regression/mos_iv_vgs/0_man_error_debugging/nmos_3p3/Id/49_W0.22_L0.28_id/49_measured_W0.22_L0.28.csv b/models/ngspice/testing/regression/mos_iv_vgs/0_man_error_debugging/nmos_3p3/Id/49_W0.22_L0.28_id/49_measured_W0.22_L0.28.csv
new file mode 100644
index 0000000..7a22f99
--- /dev/null
+++ b/models/ngspice/testing/regression/mos_iv_vgs/0_man_error_debugging/nmos_3p3/Id/49_W0.22_L0.28_id/49_measured_W0.22_L0.28.csv
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diff --git a/models/ngspice/testing/regression/mos_iv_vgs/0_man_error_debugging/nmos_3p3/Id/49_W0.22_L0.28_id/49_simulated_W0.22_L0.28.csv b/models/ngspice/testing/regression/mos_iv_vgs/0_man_error_debugging/nmos_3p3/Id/49_W0.22_L0.28_id/49_simulated_W0.22_L0.28.csv
new file mode 100644
index 0000000..0b15593
--- /dev/null
+++ b/models/ngspice/testing/regression/mos_iv_vgs/0_man_error_debugging/nmos_3p3/Id/49_W0.22_L0.28_id/49_simulated_W0.22_L0.28.csv
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diff --git a/models/ngspice/testing/regression/mos_iv_vgs/0_man_error_debugging/nmos_3p3/Rds/0_W10_L10.0_rds/0_measured_W10_L10.0.ods b/models/ngspice/testing/regression/mos_iv_vgs/0_man_error_debugging/nmos_3p3/Rds/0_W10_L10.0_rds/0_measured_W10_L10.0.ods
new file mode 100644
index 0000000..e64e374
--- /dev/null
+++ b/models/ngspice/testing/regression/mos_iv_vgs/0_man_error_debugging/nmos_3p3/Rds/0_W10_L10.0_rds/0_measured_W10_L10.0.ods
Binary files differ
diff --git a/models/ngspice/testing/regression/mos_iv_vgs/0_man_error_debugging/pmos_3p3/Rds_large_signal/0_measured_W10_L10.0.csv b/models/ngspice/testing/regression/mos_iv_vgs/0_man_error_debugging/pmos_3p3/Rds_large_signal/0_measured_W10_L10.0.csv
new file mode 100644
index 0000000..69951e8
--- /dev/null
+++ b/models/ngspice/testing/regression/mos_iv_vgs/0_man_error_debugging/pmos_3p3/Rds_large_signal/0_measured_W10_L10.0.csv
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diff --git a/models/ngspice/testing/regression/mos_iv_vgs/0_man_error_debugging/pmos_3p3/Rds_large_signal/0_simulated_W10_L10.0.csv b/models/ngspice/testing/regression/mos_iv_vgs/0_man_error_debugging/pmos_3p3/Rds_large_signal/0_simulated_W10_L10.0.csv
new file mode 100644
index 0000000..c264eca
--- /dev/null
+++ b/models/ngspice/testing/regression/mos_iv_vgs/0_man_error_debugging/pmos_3p3/Rds_large_signal/0_simulated_W10_L10.0.csv
@@ -0,0 +1,68 @@
+,-vds (V),vgs =-0.8,vgs =-1.3,vgs =-1.8,vgs =-2.3,vgs =-2.8,vgs =-3.3
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diff --git a/models/ngspice/testing/regression/mos_iv_vgs/0_man_error_debugging/pmos_3p3/Rds_large_signal/diff_table.csv b/models/ngspice/testing/regression/mos_iv_vgs/0_man_error_debugging/pmos_3p3/Rds_large_signal/diff_table.csv
new file mode 100644
index 0000000..b68d5f3
--- /dev/null
+++ b/models/ngspice/testing/regression/mos_iv_vgs/0_man_error_debugging/pmos_3p3/Rds_large_signal/diff_table.csv
@@ -0,0 +1,80 @@
+,0,1,2,3,4,5
+0,100.0,,,,,
+1,99.999996,1294.909461,85.475612,38.740399,23.432232,15.866543
+2,99.999999,1847.174246,84.908885,36.961743,21.96087,14.680282
+3,100.0,2226.549972,84.225108,35.045737,20.417247,13.452003
+4,100.0,2297.804937,83.364891,32.975091,18.796291,12.1775
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+13,100.0,62.593966,25.605994,2.179907,0.567963,1.747341
+14,100.0,70.839982,50.404868,3.825284,3.446882,3.637579
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+58,100.0,82.81556,99.058792,99.396209,99.425173,99.337314
+59,100.0,82.125288,98.96284,99.408575,99.436947,99.351606
+60,100.0,81.018143,98.945327,99.398579,99.449453,99.366766
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+62,100.0,77.891034,98.99414,99.40249,99.453908,99.399688
+63,100.0,75.844852,98.977992,99.392881,99.468246,99.403744
+64,100.0,72.455346,98.961854,99.383274,99.459829,99.415196
+65,100.0,68.974428,98.857872,99.398721,99.463339,99.434369
+66,100.0,67.176881,98.751218,99.389502,99.467215,99.440052
+67,,,,,,
+68,,,,,,
+69,,,,,,
+70,,,,,,
+71,,,,,,
+72,,,,,,
+73,,,,,,
+74,,,,,,
+75,,,,,,
+76,,,,,,
+77,,,,,,
+78,,,,,,
diff --git a/models/ngspice/testing/regression/mos_iv_vgs/0_man_error_debugging/pmos_3p3/Rds_large_signal/get_diff.py b/models/ngspice/testing/regression/mos_iv_vgs/0_man_error_debugging/pmos_3p3/Rds_large_signal/get_diff.py
new file mode 100644
index 0000000..811fe74
--- /dev/null
+++ b/models/ngspice/testing/regression/mos_iv_vgs/0_man_error_debugging/pmos_3p3/Rds_large_signal/get_diff.py
@@ -0,0 +1,14 @@
+import pandas as pd
+
+measured  = pd.read_csv('0_measured_W10_L10.0.csv')
+simulated = pd.read_csv('0_simulated_W10_L10.0.csv')
+
+error_1 = round (100 * (abs(measured.iloc[:, 1]) - abs(simulated.iloc[:, 1]))/abs(measured.iloc[:, 1]),6)  
+error_2 = round (100 * (abs(measured.iloc[:, 2]) - abs(simulated.iloc[:, 2]))/abs(measured.iloc[:, 2]),6)
+error_3 = round (100 * (abs(measured.iloc[:, 3]) - abs(simulated.iloc[:, 3]))/abs(measured.iloc[:, 3]),6) 
+error_4 = round (100 * (abs(measured.iloc[:, 4]) - abs(simulated.iloc[:, 4]))/abs(measured.iloc[:, 4]),6) 
+error_5 = round (100 * (abs(measured.iloc[:, 5]) - abs(simulated.iloc[:, 5]))/abs(measured.iloc[:, 5]),6) 
+error_6 = round (100 * (abs(measured.iloc[:, 6]) - abs(simulated.iloc[:, 6]))/abs(measured.iloc[:, 6]),6) 
+
+df = pd.DataFrame(data=[error_1,error_2,error_3,error_4,error_5,error_6]).transpose()
+df.to_csv("diff_table.csv")
\ No newline at end of file
diff --git a/models/ngspice/testing/regression/mos_iv_vgs/0_man_error_debugging/pmos_3p3/Rds_large_signal/rds_calc.py b/models/ngspice/testing/regression/mos_iv_vgs/0_man_error_debugging/pmos_3p3/Rds_large_signal/rds_calc.py
new file mode 100644
index 0000000..dbf119a
--- /dev/null
+++ b/models/ngspice/testing/regression/mos_iv_vgs/0_man_error_debugging/pmos_3p3/Rds_large_signal/rds_calc.py
@@ -0,0 +1,14 @@
+import pandas as pd
+
+
+df = pd.read_csv ("../../../pmos_3p3_iv/simulated_Id/0_simulated_W10_L10.0.csv")
+
+df["vgs =-0.8"] = df["-vds (V)"]/df["vgs =-0.8"]
+df["vgs =-1.3"] = df["-vds (V)"]/df["vgs =-1.3"]
+df["vgs =-1.8"] = df["-vds (V)"]/df["vgs =-1.8"]
+df["vgs =-2.3"] = df["-vds (V)"]/df["vgs =-2.3"]
+df["vgs =-2.8"] = df["-vds (V)"]/df["vgs =-2.8"]
+df["vgs =-3.3"] = df["-vds (V)"]/df["vgs =-3.3"]
+
+df.to_csv ("0_simulated_W10_L10.0.csv")
+
diff --git a/models/ngspice/testing/regression/mos_iv_vgs/device_netlists_Id/nmos_3p3_iv.spice b/models/ngspice/testing/regression/mos_iv_vgs/device_netlists_Id/nmos_3p3_iv.spice
new file mode 100644
index 0000000..524d1f9
--- /dev/null
+++ b/models/ngspice/testing/regression/mos_iv_vgs/device_netlists_Id/nmos_3p3_iv.spice
@@ -0,0 +1,48 @@
+***************************
+** nmos_3p3_t_id
+***************************
+* Copyright 2022 Efabless Corporation
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*      http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+Vds D_tn 0 dc 3.3
+Vgs G_tn 0 3.3
+
+.temp {{temp}}
+.options tnom={{temp}}
+ 
+
+xmn1 D_tn G_tn 0 0 nmos_3p3 W = {{width}}u L = {{length}}u ad={{AD}}u pd={{PD}}u as={{AS}}u ps={{PS}}u
+
+**** begin architecture code
+
+
+.control
+set filetype=ascii
+
+dc Vds 0 3.3 0.05 Vgs 0.8 3.3 0.5
+print -i(Vds)
+wrdata nmos_3p3_iv/simulated_Id/{{i}}_simulated_W{{width}}_L{{length}}.csv -i(Vds)
+.endc
+
+
+
+** library calling
+
+.include "../../../design.ngspice"
+.lib "../../../sm141064.ngspice" typical
+
+
+**** end architecture code
+
+
+.end
diff --git a/models/ngspice/testing/regression/mos_iv_vgs/device_netlists_Id/nmos_3p3_sab_iv.spice b/models/ngspice/testing/regression/mos_iv_vgs/device_netlists_Id/nmos_3p3_sab_iv.spice
new file mode 100644
index 0000000..a22503c
--- /dev/null
+++ b/models/ngspice/testing/regression/mos_iv_vgs/device_netlists_Id/nmos_3p3_sab_iv.spice
@@ -0,0 +1,47 @@
+***************************
+** nmos_3p3_t_id
+***************************
+* Copyright 2022 Efabless Corporation
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*      http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+Vds D_tn 0 dc 3.3
+Vgs G_tn 0 3.3
+
+.temp {{temp}}
+.options tnom={{temp}}
+
+xmn1 D_tn G_tn 0 0 nmos_3p3_sab W = {{width}}u L = {{length}}u ad={{AD}}u pd={{PD}}u as={{AS}}u ps={{PS}}u
+
+**** begin architecture code
+
+
+.control
+set filetype=ascii
+
+dc Vds 0 3.3 0.05 Vgs 0.8 3.3 0.5
+print -i(Vds)
+wrdata nmos_3p3_sab_iv/simulated_Id/{{i}}_simulated_W{{width}}_L{{length}}.csv -i(Vds)
+.endc
+
+
+
+** library calling
+
+.include "../../../design.ngspice"
+.lib "../../../sm141064.ngspice" typical
+
+
+**** end architecture code
+
+
+.end
diff --git a/models/ngspice/testing/regression/mos_iv_vgs/device_netlists_Id/nmos_6p0_iv.spice b/models/ngspice/testing/regression/mos_iv_vgs/device_netlists_Id/nmos_6p0_iv.spice
new file mode 100644
index 0000000..c1842a2
--- /dev/null
+++ b/models/ngspice/testing/regression/mos_iv_vgs/device_netlists_Id/nmos_6p0_iv.spice
@@ -0,0 +1,46 @@
+***************************
+** nmos_6p0_t_id
+***************************
+* Copyright 2022 Efabless Corporation
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*      http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+Vds D_tn 0 dc 6.6
+Vgs G_tn 0 6
+
+.temp {{temp}}
+.options tnom={{temp}}
+
+xmn1 D_tn G_tn 0 0 nmos_6p0 W = {{width}}u L = {{length}}u ad={{AD}}u pd={{PD}}u as={{AS}}u ps={{PS}}u
+
+**** begin architecture code
+
+
+.control
+set filetype=ascii
+
+dc Vds 0 6.6 0.05 Vgs 1 6 1
+print -i(Vds)
+wrdata nmos_6p0_iv/simulated_Id/{{i}}_simulated_W{{width}}_L{{length}}.csv -i(Vds)
+.endc
+
+
+
+** library calling
+
+.include "../../../design.ngspice"
+.lib "../../../sm141064.ngspice" typical
+
+**** end architecture code
+
+
+.end
diff --git a/models/ngspice/testing/regression/mos_iv_vgs/device_netlists_Id/nmos_6p0_nat_iv.spice b/models/ngspice/testing/regression/mos_iv_vgs/device_netlists_Id/nmos_6p0_nat_iv.spice
new file mode 100644
index 0000000..5a93ceb
--- /dev/null
+++ b/models/ngspice/testing/regression/mos_iv_vgs/device_netlists_Id/nmos_6p0_nat_iv.spice
@@ -0,0 +1,46 @@
+***************************
+** nmos_6p0_nat_t_id
+***************************
+* Copyright 2022 Efabless Corporation
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*      http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+Vds D_tn 0 dc 6.6
+Vgs G_tn 0 6
+
+.temp {{temp}}
+.options tnom={{temp}}
+
+xmn1 D_tn G_tn 0 0 nmos_6p0_nat W = {{width}}u L = {{length}}u ad={{AD}}u pd={{PD}}u as={{AS}}u ps={{PS}}u
+
+**** begin architecture code
+
+
+.control
+set filetype=ascii
+
+dc Vds 0 6.6 0.05 Vgs 0.25 6 1.15
+print -i(Vds)
+wrdata nmos_6p0_nat_iv/simulated_Id/{{i}}_simulated_W{{width}}_L{{length}}.csv -i(Vds)
+.endc
+
+
+
+** library calling
+
+.include "../../../design.ngspice"
+.lib "../../../sm141064.ngspice" typical
+
+**** end architecture code
+
+
+.end
diff --git a/models/ngspice/testing/regression/mos_iv_vgs/device_netlists_Id/nmos_6p0_sab_iv.spice b/models/ngspice/testing/regression/mos_iv_vgs/device_netlists_Id/nmos_6p0_sab_iv.spice
new file mode 100644
index 0000000..7bcdab8
--- /dev/null
+++ b/models/ngspice/testing/regression/mos_iv_vgs/device_netlists_Id/nmos_6p0_sab_iv.spice
@@ -0,0 +1,47 @@
+***************************
+** nmos_3p3_t_id
+***************************
+* Copyright 2022 Efabless Corporation
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*      http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+Vds D_tn 0 dc 6.6
+Vgs G_tn 0 6
+
+.temp {{temp}}
+.options tnom={{temp}}
+
+xmn1 D_tn G_tn 0 0 nmos_6p0_sab W = {{width}}u L = {{length}}u ad={{AD}}u pd={{PD}}u as={{AS}}u ps={{PS}}u
+
+**** begin architecture code
+
+
+.control
+set filetype=ascii
+
+dc Vds 0 6.6 0.05 Vgs 1 6 1
+print -i(Vds)
+wrdata nmos_6p0_sab_iv/simulated_Id/{{i}}_simulated_W{{width}}_L{{length}}.csv -i(Vds)
+.endc
+
+
+
+** library calling
+
+.include "../../../design.ngspice"
+.lib "../../../sm141064.ngspice" typical
+
+
+**** end architecture code
+
+
+.end
diff --git a/models/ngspice/testing/regression/mos_iv_vgs/device_netlists_Id/pmos_3p3_iv.spice b/models/ngspice/testing/regression/mos_iv_vgs/device_netlists_Id/pmos_3p3_iv.spice
new file mode 100644
index 0000000..90099fe
--- /dev/null
+++ b/models/ngspice/testing/regression/mos_iv_vgs/device_netlists_Id/pmos_3p3_iv.spice
@@ -0,0 +1,46 @@
+***************************
+** pmos_3p3_t_id
+***************************
+* Copyright 2022 Efabless Corporation
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*      http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+Vds D_tn 0 dc -3.3
+Vgs G_tn 0 -3.3
+
+.temp {{temp}}
+.options tnom={{temp}}
+
+xmn1 D_tn G_tn 0 0 pmos_3p3 W = {{width}}u L = {{length}}u ad={{AD}}u pd={{PD}}u as={{AS}}u ps={{PS}}u
+
+**** begin architecture code
+
+
+.control
+set filetype=ascii
+
+dc Vds -0 -3.3 -0.05 Vgs -0.8 -3.3 -0.5
+print -i(Vds)
+wrdata pmos_3p3_iv/simulated_Id/{{i}}_simulated_W{{width}}_L{{length}}.csv -i(Vds)
+.endc
+
+
+
+** library calling
+
+.include "../../../design.ngspice"
+.lib "../../../sm141064.ngspice" typical
+
+**** end architecture code
+
+
+.end
diff --git a/models/ngspice/testing/regression/mos_iv_vgs/device_netlists_Id/pmos_3p3_sab_iv.spice b/models/ngspice/testing/regression/mos_iv_vgs/device_netlists_Id/pmos_3p3_sab_iv.spice
new file mode 100644
index 0000000..aaa16ab
--- /dev/null
+++ b/models/ngspice/testing/regression/mos_iv_vgs/device_netlists_Id/pmos_3p3_sab_iv.spice
@@ -0,0 +1,47 @@
+***************************
+** nmos_3p3_t_id
+***************************
+* Copyright 2022 Efabless Corporation
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*      http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+Vds D_tn 0 dc -3.3
+Vgs G_tn 0 -3.3
+
+.temp {{temp}}
+.options tnom={{temp}}
+
+xmn1 D_tn G_tn 0 0 pmos_3p3_sab W = {{width}}u L = {{length}}u ad={{AD}}u pd={{PD}}u as={{AS}}u ps={{PS}}u
+
+**** begin architecture code
+
+
+.control
+set filetype=ascii
+
+dc Vds 0 -3.3 -0.05 Vgs -0.8 -3.3 -0.5
+print -i(Vds)
+wrdata pmos_3p3_sab_iv/simulated_Id/{{i}}_simulated_W{{width}}_L{{length}}.csv -i(Vds)
+.endc
+
+
+
+** library calling
+
+.include "../../../design.ngspice"
+.lib "../../../sm141064.ngspice" typical
+
+
+**** end architecture code
+
+
+.end
diff --git a/models/ngspice/testing/regression/mos_iv_vgs/device_netlists_Id/pmos_6p0_iv.spice b/models/ngspice/testing/regression/mos_iv_vgs/device_netlists_Id/pmos_6p0_iv.spice
new file mode 100644
index 0000000..d4d2cca
--- /dev/null
+++ b/models/ngspice/testing/regression/mos_iv_vgs/device_netlists_Id/pmos_6p0_iv.spice
@@ -0,0 +1,47 @@
+***************************
+** pmos_6p0_t_id
+***************************
+* Copyright 2022 Efabless Corporation
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*      http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+Vds D_tn 0 dc -6.6
+Vgs G_tn 0 -6
+
+.temp {{temp}}
+.options tnom={{temp}}
+
+xmn1 D_tn G_tn 0 0 pmos_6p0 W = {{width}}u L = {{length}}u ad={{AD}}u pd={{PD}}u as={{AS}}u ps={{PS}}u
+
+**** begin architecture code
+
+
+.control
+set filetype=ascii
+
+dc Vds 0 -6.6 -0.05 Vgs -1 -6 -1
+print -i(Vds)
+wrdata pmos_6p0_iv/simulated_Id/{{i}}_simulated_W{{width}}_L{{length}}.csv -i(Vds)
+.endc
+
+
+
+** library calling
+
+.include "../../../design.ngspice"
+.lib "../../../sm141064.ngspice" typical
+
+
+**** end architecture code
+
+
+.end
diff --git a/models/ngspice/testing/regression/mos_iv_vgs/device_netlists_Id/pmos_6p0_sab_iv.spice b/models/ngspice/testing/regression/mos_iv_vgs/device_netlists_Id/pmos_6p0_sab_iv.spice
new file mode 100644
index 0000000..10ef8b1
--- /dev/null
+++ b/models/ngspice/testing/regression/mos_iv_vgs/device_netlists_Id/pmos_6p0_sab_iv.spice
@@ -0,0 +1,47 @@
+***************************
+** nmos_3p3_t_id
+***************************
+* Copyright 2022 Efabless Corporation
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*      http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+Vds D_tn 0 dc -6.6
+Vgs G_tn 0 -6
+
+.temp {{temp}}
+.options tnom={{temp}}
+
+xmn1 D_tn G_tn 0 0 pmos_6p0_sab W = {{width}}u L = {{length}}u ad={{AD}}u pd={{PD}}u as={{AS}}u ps={{PS}}u
+
+**** begin architecture code
+
+
+.control
+set filetype=ascii
+
+dc Vds 0 -6.6 -0.05 Vgs -1 -6 -1
+print -i(Vds)
+wrdata pmos_6p0_sab_iv/simulated_Id/{{i}}_simulated_W{{width}}_L{{length}}.csv -i(Vds)
+.endc
+
+
+
+** library calling
+
+.include "../../../design.ngspice"
+.lib "../../../sm141064.ngspice" typical
+
+
+**** end architecture code
+
+
+.end
diff --git a/models/ngspice/testing/regression/mos_iv_vgs/device_netlists_Rds/nmos_3p3_iv.spice b/models/ngspice/testing/regression/mos_iv_vgs/device_netlists_Rds/nmos_3p3_iv.spice
new file mode 100644
index 0000000..aeaf953
--- /dev/null
+++ b/models/ngspice/testing/regression/mos_iv_vgs/device_netlists_Rds/nmos_3p3_iv.spice
@@ -0,0 +1,68 @@
+***************************
+** nmos_3p3_t_id
+***************************
+* Copyright 2022 Efabless Corporation
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*      http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+
+** library calling
+
+.include "../../../design.ngspice"
+.lib "../../../sm141064.ngspice" typical
+
+
+** Circuit Description **
+* power supply
+vds D_tn 0 dc=3.3
+vgs G_tn 0 dc=3.3
+
+.temp {{temp}}
+.options tnom={{temp}}
+
+* circuit
+mn D_tn G_tn 0 0 nmos_3p3 W = {{width}}u L = {{length}}u
+
+.control
+set filetype=ascii
+
+let vds_min  = 0
+let vds_step = 0.05
+let vds_max  = 3.3
+
+compose  vgs_vector   start=0.8          stop=3.3          step=0.5
+
+set appendwrite
+
+foreach t {{temp}}
+
+    let vgs_counter = 0
+    while vgs_counter < length(vgs_vector)
+        option TEMP=$t
+        alter vgs = vgs_vector[vgs_counter]
+
+        save  @mn[vds] @mn[vgs] @mn[vth] @mn[id] @mn[gm] @mn[gmbs] @mn[gds] @mn[cgg] @mn[cgs] @mn[cgd] @mn[cdd] @mn[cdb] @mn[cgb] @mn[csb]
+        *******************
+        ** simulation part
+        *******************
+        DC vds $&vds_min $&vds_max $&vds_step
+    
+        * ** parameters calculation
+        let Rds = 1/@mn[gds]
+        print Rds
+        wrdata nmos_3p3_iv/simulated_Rds/{{i}}_simulated_W{{width}}_L{{length}}.csv Rds 
+        reset
+        let vgs_counter = vgs_counter + 1
+    end
+end
+.endc
+.end
diff --git a/models/ngspice/testing/regression/mos_iv_vgs/device_netlists_Rds/nmos_3p3_sab_iv.spice b/models/ngspice/testing/regression/mos_iv_vgs/device_netlists_Rds/nmos_3p3_sab_iv.spice
new file mode 100644
index 0000000..dfefba2
--- /dev/null
+++ b/models/ngspice/testing/regression/mos_iv_vgs/device_netlists_Rds/nmos_3p3_sab_iv.spice
@@ -0,0 +1,68 @@
+***************************
+** nmos_3p3_t_id
+***************************
+* Copyright 2022 Efabless Corporation
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*      http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+
+** library calling
+
+.include "../../../design.ngspice"
+.lib "../../../sm141064.ngspice" typical
+
+
+** Circuit Description **
+* power supply
+vds D_tn 0 dc=3.3
+vgs G_tn 0 dc=3.3
+
+.temp {{temp}}
+.options tnom={{temp}}
+
+* circuit
+xmn1 D_tn G_tn 0 0 nmos_3p3_sab W = {{width}}u L = {{length}}u 
+
+.control
+set filetype=ascii
+
+let vds_min  = 0
+let vds_step = 0.05
+let vds_max  = 3.3
+
+compose  vgs_vector   start=0.8          stop=3.3          step=0.5
+
+set appendwrite
+
+foreach t {{temp}}
+
+    let vgs_counter = 0
+    while vgs_counter < length(vgs_vector)
+        option TEMP=$t
+        alter vgs = vgs_vector[vgs_counter]
+
+        save  all @m.xmn1.m0[gds]
+        *******************
+        ** simulation part
+        *******************
+        DC vds $&vds_min $&vds_max $&vds_step
+    
+        * ** parameters calculation
+        let Rds = 1/@m.xmn1.m0[gds]
+        print Rds
+        wrdata nmos_3p3_sab_iv/simulated_Rds/{{i}}_simulated_W{{width}}_L{{length}}.csv Rds 
+        reset
+        let vgs_counter = vgs_counter + 1
+    end
+end
+.endc
+.end
diff --git a/models/ngspice/testing/regression/mos_iv_vgs/device_netlists_Rds/nmos_6p0_iv.spice b/models/ngspice/testing/regression/mos_iv_vgs/device_netlists_Rds/nmos_6p0_iv.spice
new file mode 100644
index 0000000..ba3d9a9
--- /dev/null
+++ b/models/ngspice/testing/regression/mos_iv_vgs/device_netlists_Rds/nmos_6p0_iv.spice
@@ -0,0 +1,68 @@
+***************************
+** nmos_6p0_t_id
+***************************
+* Copyright 2022 Efabless Corporation
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*      http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+
+** library calling
+
+.include "../../../design.ngspice"
+.lib "../../../sm141064.ngspice" typical
+
+
+** Circuit Description **
+* power supply
+vds D_tn 0 dc=6.6
+vgs G_tn 0 dc=6
+
+.temp {{temp}}
+.options tnom={{temp}}
+
+* circuit
+mn D_tn G_tn 0 0 nmos_6p0 W = {{width}}u L = {{length}}u
+
+.control
+set filetype=ascii
+
+let vds_min  = 0
+let vds_step = 0.05
+let vds_max  = 6.6
+
+compose  vgs_vector   start=1          stop=6          step=1
+
+set appendwrite
+
+foreach t {{temp}}
+
+    let vgs_counter = 0
+    while vgs_counter < length(vgs_vector)
+        option TEMP=$t
+        alter vgs = vgs_vector[vgs_counter]
+
+        save  @mn[vds] @mn[vgs] @mn[vth] @mn[id] @mn[gm] @mn[gmbs] @mn[gds] @mn[cgg] @mn[cgs] @mn[cgd] @mn[cdd] @mn[cdb] @mn[cgb] @mn[csb]
+        *******************
+        ** simulation part
+        *******************
+        DC vds $&vds_min $&vds_max $&vds_step
+    
+        * ** parameters calculation
+        let Rds = 1/@mn[gds]
+        print Rds
+        wrdata nmos_6p0_iv/simulated_Rds/{{i}}_simulated_W{{width}}_L{{length}}.csv @mn[gds] 
+        reset
+        let vgs_counter = vgs_counter + 1
+    end
+end
+.endc
+.end
diff --git a/models/ngspice/testing/regression/mos_iv_vgs/device_netlists_Rds/nmos_6p0_nat_iv.spice b/models/ngspice/testing/regression/mos_iv_vgs/device_netlists_Rds/nmos_6p0_nat_iv.spice
new file mode 100644
index 0000000..2ea4dc8
--- /dev/null
+++ b/models/ngspice/testing/regression/mos_iv_vgs/device_netlists_Rds/nmos_6p0_nat_iv.spice
@@ -0,0 +1,68 @@
+***************************
+** nmos_6p0_nat_id
+***************************
+* Copyright 2022 Efabless Corporation
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*      http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+
+** library calling
+
+.include "../../../design.ngspice"
+.lib "../../../sm141064.ngspice" typical
+
+
+** Circuit Description **
+* power supply
+vds D_tn 0 dc=6.6
+vgs G_tn 0 dc=6
+
+.temp {{temp}}
+.options tnom={{temp}}
+
+* circuit
+mn D_tn G_tn 0 0 nmos_6p0_nat W = {{width}}u L = {{length}}u
+
+.control
+set filetype=ascii
+
+let vds_min  = 0
+let vds_step = 0.05
+let vds_max  = 6.6
+
+compose  vgs_vector   start=0.25          stop=6          step=1.15
+
+set appendwrite
+
+foreach t {{temp}}
+
+    let vgs_counter = 0
+    while vgs_counter < length(vgs_vector)
+        option TEMP=$t
+        alter vgs = vgs_vector[vgs_counter]
+
+        save  @mn[vds] @mn[vgs] @mn[vth] @mn[id] @mn[gm] @mn[gmbs] @mn[gds] @mn[cgg] @mn[cgs] @mn[cgd] @mn[cdd] @mn[cdb] @mn[cgb] @mn[csb]
+        *******************
+        ** simulation part
+        *******************
+        DC vds $&vds_min $&vds_max $&vds_step
+    
+        * ** parameters calculation
+        let Rds = 1/@mn[gds]
+        print Rds
+        wrdata nmos_6p0_nat_iv/simulated_Rds/{{i}}_simulated_W{{width}}_L{{length}}.csv Rds 
+        reset
+        let vgs_counter = vgs_counter + 1
+    end
+end
+.endc
+.end
diff --git a/models/ngspice/testing/regression/mos_iv_vgs/device_netlists_Rds/nmos_6p0_sab_iv.spice b/models/ngspice/testing/regression/mos_iv_vgs/device_netlists_Rds/nmos_6p0_sab_iv.spice
new file mode 100644
index 0000000..e7d46fc
--- /dev/null
+++ b/models/ngspice/testing/regression/mos_iv_vgs/device_netlists_Rds/nmos_6p0_sab_iv.spice
@@ -0,0 +1,68 @@
+***************************
+** nmos_3p3_t_id
+***************************
+* Copyright 2022 Efabless Corporation
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*      http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+
+** library calling
+
+.include "../../../design.ngspice"
+.lib "../../../sm141064.ngspice" typical
+
+
+** Circuit Description **
+* power supply
+vds D_tn 0 dc=6.6
+vgs G_tn 0 dc=6
+
+.temp {{temp}}
+.options tnom={{temp}}
+
+* circuit
+xmn1 D_tn G_tn 0 0 nmos_6p0_sab W = {{width}}u L = {{length}}u 
+
+.control
+set filetype=ascii
+
+let vds_min  = 0
+let vds_step = 0.05
+let vds_max  = 6.6
+
+compose  vgs_vector   start=1          stop=6          step=1
+
+set appendwrite
+
+foreach t {{temp}}
+
+    let vgs_counter = 0
+    while vgs_counter < length(vgs_vector)
+        option TEMP=$t
+        alter vgs = vgs_vector[vgs_counter]
+
+        save  all @m.xmn1.m0[gds]
+        *******************
+        ** simulation part
+        *******************
+        DC vds $&vds_min $&vds_max $&vds_step
+    
+        * ** parameters calculation
+        let Rds = @m.xmn1.m0[gds]
+        print Rds
+        wrdata nmos_6p0_sab_iv/simulated_Rds/{{i}}_simulated_W{{width}}_L{{length}}.csv Rds 
+        reset
+        let vgs_counter = vgs_counter + 1
+    end
+end
+.endc
+.end
diff --git a/models/ngspice/testing/regression/mos_iv_vgs/device_netlists_Rds/pmos_3p3_iv.spice b/models/ngspice/testing/regression/mos_iv_vgs/device_netlists_Rds/pmos_3p3_iv.spice
new file mode 100644
index 0000000..56e3016
--- /dev/null
+++ b/models/ngspice/testing/regression/mos_iv_vgs/device_netlists_Rds/pmos_3p3_iv.spice
@@ -0,0 +1,68 @@
+***************************
+** pmos_3p3_t_id
+***************************
+* Copyright 2022 Efabless Corporation
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*      http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+
+** library calling
+
+.include "../../../design.ngspice"
+.lib "../../../sm141064.ngspice" typical
+
+
+** Circuit Description **
+* power supply
+vds D_tn 0 dc=-3.3
+vgs G_tn 0 dc=-3.3
+
+.temp {{temp}}
+.options tnom={{temp}}
+
+* circuit
+mn D_tn G_tn 0 0 pmos_3p3 W = {{width}}u L = {{length}}u
+
+.control
+set filetype=ascii
+
+let vds_min  =  0
+let vds_step = -0.05
+let vds_max  = -3.3
+
+compose  vgs_vector   start=-0.8          stop=-3.3          step=-0.5
+
+set appendwrite
+
+foreach t {{temp}}
+
+    let vgs_counter = 0
+    while vgs_counter < length(vgs_vector)
+        option TEMP=$t
+        alter vgs = vgs_vector[vgs_counter]
+
+        save  @mn[vds] @mn[vgs] @mn[vth] @mn[id] @mn[gm] @mn[gmbs] @mn[gds] @mn[cgg] @mn[cgs] @mn[cgd] @mn[cdd] @mn[cdb] @mn[cgb] @mn[csb]
+        *******************
+        ** simulation part
+        *******************
+        DC vds $&vds_min $&vds_max $&vds_step
+    
+        * ** parameters calculation
+        let Rds = 1/@mn[gds]
+        print Rds
+        wrdata pmos_3p3_iv/simulated_Rds/{{i}}_simulated_W{{width}}_L{{length}}.csv Rds 
+        reset
+        let vgs_counter = vgs_counter + 1
+    end
+end
+.endc
+.end
diff --git a/models/ngspice/testing/regression/mos_iv_vgs/device_netlists_Rds/pmos_3p3_sab_iv.spice b/models/ngspice/testing/regression/mos_iv_vgs/device_netlists_Rds/pmos_3p3_sab_iv.spice
new file mode 100644
index 0000000..0d50993
--- /dev/null
+++ b/models/ngspice/testing/regression/mos_iv_vgs/device_netlists_Rds/pmos_3p3_sab_iv.spice
@@ -0,0 +1,68 @@
+***************************
+** nmos_3p3_t_id
+***************************
+* Copyright 2022 Efabless Corporation
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*      http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+
+** library calling
+
+.include "../../../design.ngspice"
+.lib "../../../sm141064.ngspice" typical
+
+
+** Circuit Description **
+* power supply
+vds D_tn 0 dc=-3.3
+vgs G_tn 0 dc=-3.3
+
+.temp {{temp}}
+.options tnom={{temp}}
+
+* circuit
+xmn1 D_tn G_tn 0 0 pmos_3p3_sab W = {{width}}u L = {{length}}u 
+
+.control
+set filetype=ascii
+
+let vds_min  =  0
+let vds_step = -0.05
+let vds_max  = -3.3
+
+compose  vgs_vector   start=-0.8          stop=-3.3          step=-0.5
+
+set appendwrite
+
+foreach t {{temp}}
+
+    let vgs_counter = 0
+    while vgs_counter < length(vgs_vector)
+        option TEMP=$t
+        alter vgs = vgs_vector[vgs_counter]
+
+        save  all @m.xmn1.m0[gds]
+        *******************
+        ** simulation part
+        *******************
+        DC vds $&vds_min $&vds_max $&vds_step
+    
+        * ** parameters calculation
+        let Rds = 1/@m.xmn1.m0[gds]
+        print Rds
+        wrdata pmos_3p3_sab_iv/simulated_Rds/{{i}}_simulated_W{{width}}_L{{length}}.csv Rds 
+        reset
+        let vgs_counter = vgs_counter + 1
+    end
+end
+.endc
+.end
diff --git a/models/ngspice/testing/regression/mos_iv_vgs/device_netlists_Rds/pmos_6p0_iv.spice b/models/ngspice/testing/regression/mos_iv_vgs/device_netlists_Rds/pmos_6p0_iv.spice
new file mode 100644
index 0000000..de3e491
--- /dev/null
+++ b/models/ngspice/testing/regression/mos_iv_vgs/device_netlists_Rds/pmos_6p0_iv.spice
@@ -0,0 +1,68 @@
+***************************
+** pmos_6p0_t_id
+***************************
+* Copyright 2022 Efabless Corporation
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*      http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+
+** library calling
+
+.include "../../../design.ngspice"
+.lib "../../../sm141064.ngspice" typical
+
+
+** Circuit Description **
+* power supply
+vds D_tn 0 dc=-6.6
+vgs G_tn 0 dc=-6
+
+.temp {{temp}}
+.options tnom={{temp}}
+
+* circuit
+mn D_tn G_tn 0 0 pmos_6p0 W = {{width}}u L = {{length}}u
+
+.control
+set filetype=ascii
+
+let vds_min  =  0
+let vds_step = -0.05
+let vds_max  = -6.6
+
+compose  vgs_vector   start=-1          stop=-6          step=-1
+
+set appendwrite
+
+foreach t {{temp}}
+
+    let vgs_counter = 0
+    while vgs_counter < length(vgs_vector)
+        option TEMP=$t
+        alter vgs = vgs_vector[vgs_counter]
+
+        save  @mn[vds] @mn[vgs] @mn[vth] @mn[id] @mn[gm] @mn[gmbs] @mn[gds] @mn[cgg] @mn[cgs] @mn[cgd] @mn[cdd] @mn[cdb] @mn[cgb] @mn[csb]
+        *******************
+        ** simulation part
+        *******************
+        DC vds $&vds_min $&vds_max $&vds_step
+    
+        * ** parameters calculation
+        let Rds = 1/@mn[gds]
+        print Rds
+        wrdata pmos_6p0_iv/simulated_Rds/{{i}}_simulated_W{{width}}_L{{length}}.csv @mn[gds]
+        reset
+        let vgs_counter = vgs_counter + 1
+    end
+end
+.endc
+.end
diff --git a/models/ngspice/testing/regression/mos_iv_vgs/device_netlists_Rds/pmos_6p0_sab_iv.spice b/models/ngspice/testing/regression/mos_iv_vgs/device_netlists_Rds/pmos_6p0_sab_iv.spice
new file mode 100644
index 0000000..780a169
--- /dev/null
+++ b/models/ngspice/testing/regression/mos_iv_vgs/device_netlists_Rds/pmos_6p0_sab_iv.spice
@@ -0,0 +1,68 @@
+***************************
+** nmos_3p3_t_id
+***************************
+* Copyright 2022 Efabless Corporation
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*      http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+
+** library calling
+
+.include "../../../design.ngspice"
+.lib "../../../sm141064.ngspice" typical
+
+
+** Circuit Description **
+* power supply
+vds D_tn 0 dc=-6.6
+vgs G_tn 0 dc=-6
+
+.temp {{temp}}
+.options tnom={{temp}}
+
+* circuit
+xmn1 D_tn G_tn 0 0 pmos_6p0_sab W = {{width}}u L = {{length}}u 
+
+.control
+set filetype=ascii
+
+let vds_min  =  0
+let vds_step = -0.05
+let vds_max  = -6.6
+
+compose  vgs_vector   start=-1          stop=-6          step=-1
+
+set appendwrite
+
+foreach t {{temp}}
+
+    let vgs_counter = 0
+    while vgs_counter < length(vgs_vector)
+        option TEMP=$t
+        alter vgs = vgs_vector[vgs_counter]
+
+        save  all @m.xmn1.m0[gds]
+        *******************
+        ** simulation part
+        *******************
+        DC vds $&vds_min $&vds_max $&vds_step
+    
+        * ** parameters calculation
+        let Rds = @m.xmn1.m0[gds]
+        print Rds
+        wrdata pmos_6p0_sab_iv/simulated_Rds/{{i}}_simulated_W{{width}}_L{{length}}.csv Rds 
+        reset
+        let vgs_counter = vgs_counter + 1
+    end
+end
+.endc
+.end
diff --git a/models/ngspice/testing/regression/mos_iv_vgs/models_regression.py b/models/ngspice/testing/regression/mos_iv_vgs/models_regression.py
new file mode 100644
index 0000000..76815a2
--- /dev/null
+++ b/models/ngspice/testing/regression/mos_iv_vgs/models_regression.py
@@ -0,0 +1,294 @@
+# Copyright 2022 Efabless Corporation
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#      http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+"""
+Usage:
+  models_regression.py [--num_cores=<num>]
+
+  -h, --help             Show help text.
+  -v, --version          Show version.
+  --num_cores=<num>      Number of cores to be used by simulator
+"""
+
+from re import T
+from docopt import docopt
+import pandas as pd 
+import numpy as np
+import os 
+from jinja2 import Template
+import concurrent.futures
+import shutil
+import warnings
+warnings.simplefilter(action='ignore', category=FutureWarning)
+
+def call_simulator(file_name):
+    """Call simulation commands to perform simulation.
+    Args:
+        file_name (str): Netlist file name.
+    """
+    os.system(f"ngspice -b -a {file_name} -o {file_name}.log > {file_name}.log")
+
+def ext_measured(device,vds,vgs):
+    
+    # Get dimensions used for each device 
+    dimensions = pd.read_csv(f"{device}/{device}.csv",usecols=["W (um)" , "L (um)"])
+    loops = dimensions["L (um)"].count()
+    
+    # Extracting measured values for each W & L 
+    for i in range (0,loops*2,2):
+        width  = dimensions["W (um)"].iloc[int(i/2)]
+        length = dimensions["L (um)"].iloc[int(i/2)]
+        
+        # Special case for 1st measured values 
+        if i == 0 :
+            # measured Id
+            col_list = [f"{vds}",f"vgs ={vgs[0]}",f"vgs ={vgs[1]}",f"vgs ={vgs[2]}",f"vgs ={vgs[3]}",f"vgs ={vgs[4]}",f"vgs ={vgs[5]}"]
+            df_measured = pd.read_csv(f"{device}/{device}.csv",usecols=col_list)
+            df_measured.columns = [f"{vds}",f"vgs ={vgs[0]}",f"vgs ={vgs[1]}",f"vgs ={vgs[2]}",f"vgs ={vgs[3]}",f"vgs ={vgs[4]}",f"vgs ={vgs[5]}"]
+            df_measured.to_csv(f"{device}/measured_Id/{int(i/2)}_measured_W{width}_L{length}.csv", index = False)
+            # measured Rds
+            col_list = [f"{vds}",f"vgs ={vgs[0]}.{i+1}",f"vgs ={vgs[1]}.{i+1}",f"vgs ={vgs[2]}.{i+1}",f"vgs ={vgs[3]}.{i+1}",f"vgs ={vgs[4]}.{i+1}",f"vgs ={vgs[5]}.{i+1}"]
+            df_measured = pd.read_csv(f"{device}/{device}.csv",usecols=col_list)
+            df_measured.columns = [f"{vds}",f"vgs ={vgs[0]}",f"vgs ={vgs[1]}",f"vgs ={vgs[2]}",f"vgs ={vgs[3]}",f"vgs ={vgs[4]}",f"vgs ={vgs[5]}"]
+            df_measured.to_csv(f"{device}/measured_Rds/{int(i/2)}_measured_W{width}_L{length}.csv", index = False)
+        else:
+            # measured Id
+            col_list = [f"{vds}",f"vgs ={vgs[0]}.{i}",f"vgs ={vgs[1]}.{i}",f"vgs ={vgs[2]}.{i}",f"vgs ={vgs[3]}.{i}",f"vgs ={vgs[4]}.{i}",f"vgs ={vgs[5]}.{i}"]
+            df_measured = pd.read_csv(f"{device}/{device}.csv",usecols=col_list)
+            df_measured.columns = [f"{vds}",f"vgs ={vgs[0]}",f"vgs ={vgs[1]}",f"vgs ={vgs[2]}",f"vgs ={vgs[3]}",f"vgs ={vgs[4]}",f"vgs ={vgs[5]}"]        
+            df_measured.to_csv(f"{device}/measured_Id/{int(i/2)}_measured_W{width}_L{length}.csv", index = False)
+            # measured Rds
+            col_list = [f"{vds}",f"vgs ={vgs[0]}.{i+1}",f"vgs ={vgs[1]}.{i+1}",f"vgs ={vgs[2]}.{i+1}",f"vgs ={vgs[3]}.{i+1}",f"vgs ={vgs[4]}.{i+1}",f"vgs ={vgs[5]}.{i+1}"]
+            df_measured = pd.read_csv(f"{device}/{device}.csv",usecols=col_list)
+            df_measured.columns = [f"{vds}",f"vgs ={vgs[0]}",f"vgs ={vgs[1]}",f"vgs ={vgs[2]}",f"vgs ={vgs[3]}",f"vgs ={vgs[4]}",f"vgs ={vgs[5]}"]
+            df_measured.to_csv(f"{device}/measured_Rds/{int(i/2)}_measured_W{width}_L{length}.csv", index = False)
+
+def ext_simulated(device,vds,vgs,vds_sweep,sim_val):
+    
+    # Get dimensions used for each device 
+    dimensions = pd.read_csv(f"{device}/{device}.csv",usecols=["W (um)" , "L (um)"])
+    loops = dimensions["L (um)"].count()
+    temp_range = int(loops/3) 
+    netlist_tmp = f"./device_netlists_{sim_val}/{device}.spice"
+    for i in range (0,loops):
+        width  = dimensions["W (um)"].iloc[int(i)]
+        length = dimensions["L (um)"].iloc[int(i)]
+        AD = float(width) * 0.24
+        PD = 2 * (float(width) + 0.24)
+        AS = AD 
+        PS = PD 
+        if i in range (0,temp_range): temp = 25 
+        elif i in range (temp_range,2*temp_range): temp = -40 
+        else:
+            temp = 125 
+        with open(netlist_tmp) as f:
+            tmpl = Template(f.read())
+            os.makedirs(f"{device}/{device}_netlists_{sim_val}",exist_ok=True)
+            with open(f"{device}/{device}_netlists_{sim_val}/{i}_{device}_netlist_W{width}_L{length}.spice", "w") as netlist:
+                netlist.write(tmpl.render(width = width,length = length,i = i , temp = temp , AD = AD , PD = PD , AS = AS , PS = PD ))
+            netlist_path  = f"{device}/{device}_netlists_{sim_val}/{i}_{device}_netlist_W{width}_L{length}.spice" 
+            # Running ngspice for each netlist 
+            with concurrent.futures.ProcessPoolExecutor(max_workers=workers_count) as executor:
+                executor.submit(call_simulator, netlist_path)
+            
+            # Writing simulated data 
+            df_simulated = pd.read_csv(f"{device}/simulated_{sim_val}/{i}_simulated_W{width}_L{length}.csv",header=None, delimiter=r"\s+")
+            df_simulated.to_csv(f"{device}/simulated_{sim_val}/{i}_simulated_W{width}_L{length}.csv",index= False)    
+            
+            # empty array to append in it shaped (vds_sweep, number of trials + 1)
+            new_array = np.empty((vds_sweep, 1+int(df_simulated.shape[0]/vds_sweep)))  
+            new_array[:, 0] = df_simulated.iloc[:vds_sweep, 0]
+            times = int(df_simulated.shape[0]/vds_sweep)
+
+            for j in range(times):
+                new_array[:, (j+1)] = df_simulated.iloc[j*vds_sweep:(j+1)*vds_sweep, 1]
+                
+            # Writing final simulated data                 
+            df_simulated = pd.DataFrame(new_array)
+            df_simulated.to_csv(f"{device}/simulated_{sim_val}/{i}_simulated_W{width}_L{length}.csv",index= False)    
+            df_simulated.columns = [f"{vds}",f"vgs ={vgs[0]}",f"vgs ={vgs[1]}",f"vgs ={vgs[2]}",f"vgs ={vgs[3]}",f"vgs ={vgs[4]}",f"vgs ={vgs[5]}"]
+            df_simulated.to_csv(f"{device}/simulated_{sim_val}/{i}_simulated_W{width}_L{length}.csv",index= False)    
+
+def error_cal(device,vds,vgs,sim_val):
+    
+    # Get dimensions used for each device 
+    dimensions = pd.read_csv(f"{device}/{device}.csv",usecols=["W (um)" , "L (um)"])
+    loops = dimensions["L (um)"].count()
+    temp_range = int(loops/3)     
+    df_final = pd.DataFrame()
+    for i in range (0,loops):  
+        width  = dimensions["W (um)"].iloc[int(i)]
+        length = dimensions["L (um)"].iloc[int(i)]
+        if i in range (0,temp_range): temp = 25             
+        elif i in range (temp_range,2*temp_range): temp = -40             
+        else: temp = 125
+             
+        measured  = pd.read_csv(f"{device}/measured_{sim_val}/{i}_measured_W{width}_L{length}.csv")
+        simulated = pd.read_csv(f"{device}/simulated_{sim_val}/{i}_simulated_W{width}_L{length}.csv")
+
+        error_1 = round (100 * abs((abs(measured.iloc[1:, 1]) - abs(simulated.iloc[1:, 1]))/abs(measured.iloc[:, 1])),6)  
+        error_2 = round (100 * abs((abs(measured.iloc[1:, 2]) - abs(simulated.iloc[1:, 2]))/abs(measured.iloc[:, 2])),6)
+        error_3 = round (100 * abs((abs(measured.iloc[1:, 3]) - abs(simulated.iloc[1:, 3]))/abs(measured.iloc[:, 3])),6) 
+        error_4 = round (100 * abs((abs(measured.iloc[1:, 4]) - abs(simulated.iloc[1:, 4]))/abs(measured.iloc[:, 4])),6) 
+        error_5 = round (100 * abs((abs(measured.iloc[1:, 5]) - abs(simulated.iloc[1:, 5]))/abs(measured.iloc[:, 5])),6) 
+        error_6 = round (100 * abs((abs(measured.iloc[1:, 6]) - abs(simulated.iloc[1:, 6]))/abs(measured.iloc[:, 6])),6) 
+
+        df_error = pd.DataFrame(data=[measured.iloc[:, 0],error_1,error_2,error_3,error_4,error_5,error_6]).transpose()        
+        df_error.to_csv(f"{device}/error_{sim_val}/{i}_{device}_error_W{width}_L{length}.csv",index= False)
+        
+        # Mean error 
+        mean_error = (df_error[f"vgs ={vgs[0]}"].mean() + df_error[f"vgs ={vgs[1]}"].mean() + df_error[f"vgs ={vgs[2]}"].mean() + 
+                      df_error[f"vgs ={vgs[3]}"].mean() + df_error[f"vgs ={vgs[4]}"].mean() + df_error[f"vgs ={vgs[5]}"].mean())/6
+        # Max error 
+        max_error = df_error[[f"vgs ={vgs[0]}",f"vgs ={vgs[1]}",f"vgs ={vgs[2]}",f"vgs ={vgs[3]}",f"vgs ={vgs[4]}",f"vgs ={vgs[5]}" ]].max().max()
+        # Max error location 
+        max_index = max((df_error == max_error).idxmax())
+        max_location_vgs = (df_error == max_error).idxmax(axis=1)[max_index]
+        max_location_vds = df_error[f"{vds}"][max_index]
+
+        df_final_ = {'Run no.': f'{i}', 'Temp': f'{temp}', 'Device name': f'{device}', 'Width': f'{width}', 'Length': f'{length}', 'Simulated_Val':f'{sim_val}','Mean error%':f'{"{:.2f}".format(mean_error)}', 'Max error%':f'{"{:.2f}".format(max_error)} @ {max_location_vgs} & Vds (V) = {max_location_vds}'}
+        df_final = df_final.append(df_final_, ignore_index = True)
+    # Max mean error 
+    print (df_final)   
+    df_final.to_csv (f"{device}/Final_report_{sim_val}.csv", index = False)
+    out_report = pd.read_csv (f"{device}/Final_report_{sim_val}.csv")
+    print ("\n",f"Max. mean error = {out_report['Mean error%'].max()}%")    
+    print ("=====================================================================================================================================================")
+
+def main():
+        
+    devices = ["nmos_3p3_iv" , "pmos_3p3_iv" , "nmos_6p0_iv" , "pmos_6p0_iv" , "nmos_6p0_nat_iv", "nmos_3p3_sab_iv", "pmos_3p3_sab_iv" , "nmos_6p0_sab_iv" , "pmos_6p0_sab_iv"] 
+    nmos_vds = "vds (V)"
+    pmos_vds = "-vds (V)"
+    nmos_rds = "Rds"
+    Id_sim  = "Id"
+    Rds_sim = "Rds"
+    mos_3p3_vgs_sweep = 67 
+    mos_6p0_vgs_sweep = 133 
+    nmos3p3_vgs = [ 0.8 ,  1.3 ,  1.8 ,  2.3 ,  2.8 ,  3.3] 
+    pmos3p3_vgs = [-0.8 , -1.3 , -1.8 , -2.3 , -2.8 , -3.3] 
+    nmos6p0_vgs = [ 1 ,  2 ,  3 ,  4 ,  5 ,  6] 
+    pmos6p0_vgs = [-1 , -2 , -3 , -4 , -5 , -6] 
+    nmos6p0_nat_vgs = [ 0.25 ,  1.4 , 2.55 , 3.7 , 4.85 , 6]
+
+    for device in devices: 
+        # Folder structure of measured values 
+        dirpath = f"{device}"
+        if os.path.exists(dirpath) and os.path.isdir(dirpath):
+            shutil.rmtree(dirpath)
+        os.makedirs(f"{device}/measured_{Id_sim}",exist_ok=False)
+        os.makedirs(f"{device}/measured_{Rds_sim}",exist_ok=False)
+
+        # From xlsx to csv 
+        read_file = pd.read_excel (f"../../180MCU_SPICE_DATA/MOS/{device}.nl_out.xlsx")
+        read_file.to_csv (f"{device}/{device}.csv", index = False, header=True)
+
+        # Folder structure of simulated values 
+        os.makedirs(f"{device}/simulated_{Id_sim}",exist_ok=False)
+        os.makedirs(f"{device}/simulated_{Rds_sim}",exist_ok=False)
+        os.makedirs(f"{device}/error_{Id_sim}",exist_ok=False)
+        os.makedirs(f"{device}/error_{Rds_sim}",exist_ok=False)
+
+    # =========== nmos_3p3_iv ==============      
+    ext_measured ("nmos_3p3_iv",nmos_vds,nmos3p3_vgs)
+
+    ext_simulated("nmos_3p3_iv",nmos_vds,nmos3p3_vgs,mos_3p3_vgs_sweep,Id_sim)
+    error_cal    ("nmos_3p3_iv",nmos_vds,nmos3p3_vgs,Id_sim)
+
+    ext_simulated("nmos_3p3_iv",nmos_vds,nmos3p3_vgs,mos_3p3_vgs_sweep,Rds_sim)
+    error_cal    ("nmos_3p3_iv",nmos_vds,nmos3p3_vgs,Rds_sim)
+
+    # =========== pmos_3p3_iv ==============      
+    ext_measured ("pmos_3p3_iv",pmos_vds,pmos3p3_vgs)
+
+    ext_simulated("pmos_3p3_iv",pmos_vds,pmos3p3_vgs,mos_3p3_vgs_sweep,Id_sim)
+    error_cal    ("pmos_3p3_iv",pmos_vds,pmos3p3_vgs,Id_sim)
+    
+    ext_simulated("pmos_3p3_iv",pmos_vds,pmos3p3_vgs,mos_3p3_vgs_sweep,Rds_sim)    
+    error_cal    ("pmos_3p3_iv",pmos_vds,pmos3p3_vgs,Rds_sim)
+
+    # =========== nmos_6p0_iv ==============      
+    ext_measured ("nmos_6p0_iv",nmos_vds,nmos6p0_vgs)
+   
+    ext_simulated("nmos_6p0_iv",nmos_vds,nmos6p0_vgs,mos_6p0_vgs_sweep,Id_sim)
+    error_cal    ("nmos_6p0_iv",nmos_vds,nmos6p0_vgs,Id_sim)    
+    
+    ext_simulated("nmos_6p0_iv",nmos_vds,nmos6p0_vgs,mos_6p0_vgs_sweep,Rds_sim)
+    error_cal    ("nmos_6p0_iv",nmos_vds,nmos6p0_vgs,Rds_sim)    
+         
+    # =========== pmos_6p0_iv ==============      
+    ext_measured ("pmos_6p0_iv",pmos_vds,pmos6p0_vgs)
+
+    ext_simulated("pmos_6p0_iv",pmos_vds,pmos6p0_vgs,mos_6p0_vgs_sweep,Id_sim)
+    error_cal    ("pmos_6p0_iv",pmos_vds,pmos6p0_vgs,Id_sim) 
+    
+    ext_simulated("pmos_6p0_iv",pmos_vds,pmos6p0_vgs,mos_6p0_vgs_sweep,Rds_sim)    
+    error_cal    ("pmos_6p0_iv",pmos_vds,pmos6p0_vgs,Rds_sim)              
+
+    # ============ nmos_6p0_nat_iv =============              
+    ext_measured ("nmos_6p0_nat_iv",nmos_vds,nmos6p0_nat_vgs)
+
+    ext_simulated("nmos_6p0_nat_iv",nmos_vds,nmos6p0_nat_vgs,mos_6p0_vgs_sweep,Id_sim)
+    error_cal    ("nmos_6p0_nat_iv",nmos_vds,nmos6p0_nat_vgs,Id_sim)     
+    
+    ext_simulated("nmos_6p0_nat_iv",nmos_vds,nmos6p0_nat_vgs,mos_6p0_vgs_sweep,Rds_sim)    
+    error_cal    ("nmos_6p0_nat_iv",nmos_vds,nmos6p0_nat_vgs,Rds_sim)    
+    
+    # ============ nmos_3p3_sab_iv =============                                
+    ext_measured ("nmos_3p3_sab_iv",nmos_vds,nmos3p3_vgs)
+    
+    ext_simulated("nmos_3p3_sab_iv",nmos_vds,nmos3p3_vgs,mos_3p3_vgs_sweep,Id_sim)
+    error_cal    ("nmos_3p3_sab_iv",nmos_vds,nmos3p3_vgs,Id_sim)
+    
+    ext_simulated("nmos_3p3_sab_iv",nmos_vds,nmos3p3_vgs,mos_3p3_vgs_sweep,Rds_sim)
+    error_cal    ("nmos_3p3_sab_iv",nmos_vds,nmos3p3_vgs,Rds_sim)
+
+    # =========== pmos_3p3_sab_iv ==============      
+    ext_measured ("pmos_3p3_sab_iv",pmos_vds,pmos3p3_vgs)
+
+    ext_simulated("pmos_3p3_sab_iv",pmos_vds,pmos3p3_vgs,mos_3p3_vgs_sweep,Id_sim)
+    error_cal    ("pmos_3p3_sab_iv",pmos_vds,pmos3p3_vgs,Id_sim)
+    
+    ext_simulated("pmos_3p3_sab_iv",pmos_vds,pmos3p3_vgs,mos_3p3_vgs_sweep,Rds_sim)    
+    error_cal    ("pmos_3p3_sab_iv",pmos_vds,pmos3p3_vgs,Rds_sim)
+
+    # =========== nmos_6p0_sab_iv ==============      
+    ext_measured ("nmos_6p0_sab_iv",nmos_vds,nmos6p0_vgs)
+   
+    ext_simulated("nmos_6p0_sab_iv",nmos_vds,nmos6p0_vgs,mos_6p0_vgs_sweep,Id_sim)
+    error_cal    ("nmos_6p0_sab_iv",nmos_vds,nmos6p0_vgs,Id_sim)    
+    
+    ext_simulated("nmos_6p0_sab_iv",nmos_vds,nmos6p0_vgs,mos_6p0_vgs_sweep,Rds_sim)
+    error_cal    ("nmos_6p0_sab_iv",nmos_vds,nmos6p0_vgs,Rds_sim)    
+         
+    # =========== pmos_6p0_sab_iv ==============      
+    ext_measured ("pmos_6p0_sab_iv",pmos_vds,pmos6p0_vgs)
+
+    ext_simulated("pmos_6p0_sab_iv",pmos_vds,pmos6p0_vgs,mos_6p0_vgs_sweep,Id_sim)
+    error_cal    ("pmos_6p0_sab_iv",pmos_vds,pmos6p0_vgs,Id_sim) 
+    
+    ext_simulated("pmos_6p0_sab_iv",pmos_vds,pmos6p0_vgs,mos_6p0_vgs_sweep,Rds_sim)    
+    error_cal    ("pmos_6p0_sab_iv",pmos_vds,pmos6p0_vgs,Rds_sim) 
+    
+# # ================================================================
+# -------------------------- MAIN --------------------------------
+# ================================================================
+        
+if __name__ == "__main__":
+    
+    # Args 
+    arguments     = docopt(__doc__, version='comparator: 0.1')
+    workers_count = os.cpu_count()*2 if arguments["--num_cores"] == None else int(arguments["--num_cores"])
+    
+    # Calling main function 
+    main()
diff --git a/models/ngspice/testing/regression/moscap_c/.spiceinit b/models/ngspice/testing/regression/moscap_c/.spiceinit
new file mode 100644
index 0000000..7779a4c
--- /dev/null
+++ b/models/ngspice/testing/regression/moscap_c/.spiceinit
@@ -0,0 +1,2 @@
+* user provided init file
+set ngbehavior=hs
diff --git a/models/ngspice/testing/regression/moscap_c/device_netlists/.spiceinit b/models/ngspice/testing/regression/moscap_c/device_netlists/.spiceinit
new file mode 100644
index 0000000..84222e2
--- /dev/null
+++ b/models/ngspice/testing/regression/moscap_c/device_netlists/.spiceinit
@@ -0,0 +1,5 @@
+
+* user provided init file
+set ngbehavior=hs
+
+
diff --git a/models/ngspice/testing/regression/moscap_c/device_netlists/moscap.spice b/models/ngspice/testing/regression/moscap_c/device_netlists/moscap.spice
new file mode 100644
index 0000000..6150abb
--- /dev/null
+++ b/models/ngspice/testing/regression/moscap_c/device_netlists/moscap.spice
@@ -0,0 +1,38 @@
+***************************
+** cap
+***************************
+* Copyright 2022 Efabless Corporation
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*      http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+.options noacct
+
+Ich 0 p dc 10u
+
+.temp 25
+.options tnom=25
+      
+xcn p 0 {{device}} c_length={{length}}u c_width={{width}}u
+
+.ic v(p)=0.0
+.tran 10ns 100us
+
+* .print tran v(p) cj=par('10.0e-6  * time / v(p)')
+
+.meas tran CV FIND par('(10.0e-6  * time / v(p))*1.0e15') AT=100us
+
+** library calling
+
+.include "../../../design.ngspice"
+.lib "../../../sm141064.ngspice" moscap_{{corner}}
+.end
+
diff --git a/models/ngspice/testing/regression/moscap_c/models_regression.py b/models/ngspice/testing/regression/moscap_c/models_regression.py
new file mode 100644
index 0000000..dc0c019
--- /dev/null
+++ b/models/ngspice/testing/regression/moscap_c/models_regression.py
@@ -0,0 +1,191 @@
+# Copyright 2022 Efabless Corporation
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#      http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+"""
+Usage:
+  models_regression.py [--num_cores=<num>]
+
+  -h, --help             Show help text.
+  -v, --version          Show version.
+  --num_cores=<num>      Number of cores to be used by simulator
+"""
+
+from re import T
+from docopt import docopt
+import pandas as pd 
+import numpy as np
+import os 
+from jinja2 import Template
+import concurrent.futures
+import shutil
+import warnings
+warnings.simplefilter(action='ignore', category=FutureWarning)
+
+def call_simulator(file_name):
+    """Call simulation commands to perform simulation.
+    Args:
+        file_name (str): Netlist file name.
+    """
+    os.system(f"ngspice -b -a {file_name} -o {file_name}.log > {file_name}.log")
+
+def ext_measured(device,vn,d_in, cv_sim, corner,start):
+    
+    # Get dimensions used for each device 
+    dirpath = f"{device}_{cv_sim}_{corner}"
+    
+    # Extracting measured values for each W & L 
+    for i in range (start,4+start):
+        if i == 0+start: width  = 50 ; length = 50
+        if i == 1+start: width  = 1  ; length = 1
+        if i == 2+start: width  = 50 ; length = 1
+        if i == 3+start: width  = 1  ; length = 50
+                                            
+        # measured cv
+        col_list = [f"{vn}",f"{d_in}"]
+        df_measured = pd.read_csv(f"{dirpath}/{device}.csv",usecols=col_list)
+        df_measured.loc[i:i].to_csv(f"{dirpath}/measured_{cv_sim}/{i-start}_measured_w{width}_l{length}.csv", index=False)
+
+def ext_simulated(device,vn,d_in,cv_sim, corner,start):
+    
+    # Get dimensions used for each device 
+    dirpath = f"{device}_{cv_sim}_{corner}"
+    netlist_tmp = f"./device_netlists/moscap.spice"
+    
+    # Extracting measured values for each W & L 
+    for i in range (start,4+start):
+        if i == 0+start: width  = 50 ; length = 50
+        if i == 1+start: width  = 1  ; length = 1
+        if i == 2+start: width  = 50 ; length = 1
+        if i == 3+start: width  = 1  ; length = 50
+    
+        with open(netlist_tmp) as f:
+            tmpl = Template(f.read())
+            os.makedirs(f"{dirpath}/{device}_netlists_{cv_sim}",exist_ok=True)
+            with open(f"{dirpath}/{device}_netlists_{cv_sim}/{i-start}_{device}_netlist_w{width}_l{length}.spice", "w") as netlist:
+                netlist.write(tmpl.render(device = device, width = width, length = length , corner = corner ))
+            netlist_path  = f"{dirpath}/{device}_netlists_{cv_sim}/{i-start}_{device}_netlist_w{width}_l{length}.spice" 
+            # Running ngspice for each netlist 
+            with concurrent.futures.ProcessPoolExecutor(max_workers=workers_count) as executor:
+                executor.submit(call_simulator, netlist_path)
+            
+            # Writing simulated data 
+            df_simulated = pd.read_csv(f"{dirpath}/{device}_netlists_{cv_sim}/{i-start}_{device}_netlist_w{width}_l{length}.spice.log")
+            clean_data = str(df_simulated.loc[4]).replace("Compatibility modes selected: hs","").replace("\nName: 4, dtype: object","").split("=")
+            df_clean_ = {vn: [f"moscap_{corner}"],d_in: [clean_data[1]]}
+            df_clean = pd.DataFrame(df_clean_)            
+            df_clean.to_csv(f"{dirpath}/simulated_{cv_sim}/{i-start}_simulated_w{width}_l{length}.csv",index= False)    
+            
+def error_cal(device,vn,d_in,Id_sim, corner,start):
+    
+    # Get dimensions used for each device 
+    dirpath = f"{device}_{Id_sim}_{corner}"
+    df_final = pd.DataFrame()
+    for i in range (start,4+start):
+        if i == 0+start: width  = 50 ; length = 50
+        if i == 1+start: width  = 1  ; length = 1
+        if i == 2+start: width  = 50 ; length = 1
+        if i == 3+start: width  = 1  ; length = 50
+             
+        measured  = pd.read_csv(f"{dirpath}/measured_{Id_sim}/{i-start}_measured_w{width}_l{length}.csv")
+        simulated = pd.read_csv(f"{dirpath}/simulated_{Id_sim}/{i-start}_simulated_w{width}_l{length}.csv")
+
+        error_1 = round (100 * abs((abs(measured.iloc[:, 1]) - abs(simulated.iloc[:, 1]))/abs(measured.iloc[:, 1])),8)  
+
+        df_error = pd.DataFrame(data=[measured.iloc[:, 0],error_1]).transpose()        
+        df_error.to_csv(f"{dirpath}/error_{Id_sim}/{i-start}_{device}_error_w{width}_l{length}.csv",index= False)
+        
+        # Mean error 
+        mean_error = (df_error[f"{d_in}"].mean())
+        # Max error 
+        max_error = df_error[f"{d_in}"].max()
+
+        df_final_ = {'Run no.': f'{i-start}', 'Device name': f'{dirpath}', 'Width': f'{width}', 'Length': f'{length}', 'Simulated_Val':f'{Id_sim}','Mean error%':f'{"{:.2f}".format(mean_error)}', 'Max error%':f'{"{:.2f}".format(max_error)} '}
+        df_final = df_final.append(df_final_, ignore_index = True)
+    # Max mean error 
+    print (df_final)   
+    df_final.to_csv (f"{dirpath}/Final_report_{Id_sim}.csv", index = False)
+    out_report = pd.read_csv (f"{dirpath}/Final_report_{Id_sim}.csv")
+    print ("\n",f"Max. mean error = {out_report['Mean error%'].max()}%")    
+    print ("=====================================================================================================================================================")
+
+
+def main():
+
+    # 3p3
+    corners = ["typical","ff","ss"]        
+    devices = ["nmoscap_3p3" , "pmoscap_3p3" , "nmoscap_3p3_b" , "pmoscap_3p3_b"]
+    measure = ["cv","corners", "CV (fF)"]
+    start = 0
+    for corner in corners: 
+        for device in devices: 
+            # Folder structure of measured values
+            cv_sim, cap_vn, cap_in = measure[0], measure[1], measure[2]
+            dirpath = f"{device}_{cv_sim}_{corner}"
+            if os.path.exists(dirpath) and os.path.isdir(dirpath):
+                shutil.rmtree(dirpath)
+            os.makedirs(f"{dirpath}/measured_{cv_sim}",exist_ok=False)
+
+            # From xlsx to csv
+            read_file = pd.read_excel (f"../../180MCU_SPICE_DATA/Cap/moscap_cv_3p3.nl_out.xlsx")
+            read_file.to_csv (f"{dirpath}/{device}.csv", index = False, header=True)
+
+            # Folder structure of simulated values 
+            os.makedirs(f"{dirpath}/simulated_{cv_sim}",exist_ok=False)
+            os.makedirs(f"{dirpath}/error_{cv_sim}",exist_ok=False)
+    
+            ext_measured (device,cap_vn,cap_in, cv_sim, corner,start)
+            ext_simulated(device,cap_vn,cap_in,cv_sim, corner,start)
+            error_cal    (device,cap_vn,cap_in,cv_sim, corner,start)            
+            start = start + 4            
+        start = start + 32
+
+    # 6p0 
+    corners = ["typical","ff","ss"]        
+    devices = ["nmoscap_6p0" , "pmoscap_6p0" , "nmoscap_6p0_b" , "pmoscap_6p0_b"]
+    measure = ["cv","corners", "CV (fF)"]
+    start = 0
+    for corner in corners: 
+        for device in devices: 
+            # Folder structure of measured values
+            cv_sim, cap_vn, cap_in = measure[0], measure[1], measure[2]
+            dirpath = f"{device}_{cv_sim}_{corner}"
+            if os.path.exists(dirpath) and os.path.isdir(dirpath):
+                shutil.rmtree(dirpath)
+            os.makedirs(f"{dirpath}/measured_{cv_sim}",exist_ok=False)
+
+            # From xlsx to csv
+            read_file = pd.read_excel (f"../../180MCU_SPICE_DATA/Cap/moscap_cv_6p0.nl_out.xlsx")
+            read_file.to_csv (f"{dirpath}/{device}.csv", index = False, header=True)
+
+            # Folder structure of simulated values 
+            os.makedirs(f"{dirpath}/simulated_{cv_sim}",exist_ok=False)
+            os.makedirs(f"{dirpath}/error_{cv_sim}",exist_ok=False)
+    
+            ext_measured (device,cap_vn,cap_in, cv_sim, corner,start)
+            ext_simulated(device,cap_vn,cap_in,cv_sim, corner,start)
+            error_cal    (device,cap_vn,cap_in,cv_sim, corner,start)            
+            start = start + 4            
+        start = start + 32
+
+# # ================================================================
+# -------------------------- MAIN --------------------------------
+# ================================================================
+        
+if __name__ == "__main__":
+    
+    # Args 
+    arguments     = docopt(__doc__, version='comparator: 0.1')
+    workers_count = os.cpu_count()*2 if arguments["--num_cores"] == None else int(arguments["--num_cores"])
+    
+    # Calling main function 
+    main()
diff --git a/models/ngspice/testing/regression/resistor_r/.spiceinit b/models/ngspice/testing/regression/resistor_r/.spiceinit
new file mode 100644
index 0000000..7779a4c
--- /dev/null
+++ b/models/ngspice/testing/regression/resistor_r/.spiceinit
@@ -0,0 +1,2 @@
+* user provided init file
+set ngbehavior=hs
diff --git a/models/ngspice/testing/regression/resistor_r/device_netlists/.spiceinit b/models/ngspice/testing/regression/resistor_r/device_netlists/.spiceinit
new file mode 100644
index 0000000..84222e2
--- /dev/null
+++ b/models/ngspice/testing/regression/resistor_r/device_netlists/.spiceinit
@@ -0,0 +1,5 @@
+
+* user provided init file
+set ngbehavior=hs
+
+
diff --git a/models/ngspice/testing/regression/resistor_r/device_netlists/2term_res_a.spice b/models/ngspice/testing/regression/resistor_r/device_netlists/2term_res_a.spice
new file mode 100644
index 0000000..1f39ae3
--- /dev/null
+++ b/models/ngspice/testing/regression/resistor_r/device_netlists/2term_res_a.spice
@@ -0,0 +1,44 @@
+**************************
+** res
+**************************
+* Copyright 2022 Efabless Corporation
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*      http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+
+Vn n 0 DC {{sign}}3.3
+
+.temp 25
+.options tnom=25
+      
+r1 n p 1M
+xrn p 0 {{device}} r_width={{width}}u r_length={{length}}u
+
+
+.print dc Rs=par('(1M*V(p)/(V(n)-V(p)))/{{length}}u*{{width}}u')
+
+
+.control
+set filetype=ascii
+set appendwrite
+
+DC Vn {{sign}}3.3 {{sign}}3.3 0.1
+wrdata {{device}}_r_{{corner}}/simulated_r/{{i}}_simulated_w{{width}}_l{{length}}.csv Rs 
+
+.endc
+
+** library calling
+
+.include "../../../design.ngspice"
+.lib "../../../sm141064.ngspice" res_{{corner}}
+
+.end
diff --git a/models/ngspice/testing/regression/resistor_r/device_netlists/2term_res_b.spice b/models/ngspice/testing/regression/resistor_r/device_netlists/2term_res_b.spice
new file mode 100644
index 0000000..21db7ab
--- /dev/null
+++ b/models/ngspice/testing/regression/resistor_r/device_netlists/2term_res_b.spice
@@ -0,0 +1,44 @@
+**************************
+** res
+**************************
+* Copyright 2022 Efabless Corporation
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*      http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+
+Vn n 0 DC {{sign}}3.3
+
+.temp {{temp}}
+.options tnom={{temp}}
+      
+r1 n p 1M
+xrn p 0 {{device}} r_width={{width}}u r_length={{length}}u
+
+
+.print dc Rs=par('(1M*V(p)/(V(n)-V(p)))/{{length}}u*{{width}}u')
+
+
+.control
+set filetype=ascii
+set appendwrite
+
+DC Vn {{sign}}3.3 {{sign}}3.3 0.1
+wrdata {{device}}_r_{{corner}}_temp/simulated_r/{{i}}_simulated_w{{width}}_l{{length}}.csv Rs 
+
+.endc
+
+** library calling
+
+.include "../../../design.ngspice"
+.lib "../../../sm141064.ngspice" res_{{corner}}
+
+.end
diff --git a/models/ngspice/testing/regression/resistor_r/device_netlists/3term_res_a.spice b/models/ngspice/testing/regression/resistor_r/device_netlists/3term_res_a.spice
new file mode 100644
index 0000000..8653599
--- /dev/null
+++ b/models/ngspice/testing/regression/resistor_r/device_netlists/3term_res_a.spice
@@ -0,0 +1,44 @@
+**************************
+** res
+**************************
+* Copyright 2022 Efabless Corporation
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*      http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+
+Vn n 0 DC {{sign}}3.3
+
+.temp 25
+.options tnom=25
+      
+r1 n p 1M
+xrn p 0 0 {{device}} r_width={{width}}u r_length={{length}}u
+
+
+.print dc Rs=par('(1M*V(p)/(V(n)-V(p)))/{{length}}u*{{width}}u')
+
+
+.control
+set filetype=ascii
+set appendwrite
+
+DC Vn {{sign}}3.3 {{sign}}3.3 0.1
+wrdata {{device}}_r_{{corner}}/simulated_r/{{i}}_simulated_w{{width}}_l{{length}}.csv Rs 
+
+.endc
+
+** library calling
+
+.include "../../../design.ngspice"
+.lib "../../../sm141064.ngspice" res_{{corner}}
+
+.end
diff --git a/models/ngspice/testing/regression/resistor_r/device_netlists/3term_res_b.spice b/models/ngspice/testing/regression/resistor_r/device_netlists/3term_res_b.spice
new file mode 100644
index 0000000..120aa9d
--- /dev/null
+++ b/models/ngspice/testing/regression/resistor_r/device_netlists/3term_res_b.spice
@@ -0,0 +1,44 @@
+**************************
+** res
+**************************
+* Copyright 2022 Efabless Corporation
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*      http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+
+Vn n 0 DC {{sign}}3.3
+
+.temp {{temp}}
+.options tnom={{temp}}
+      
+r1 n p 1M
+xrn p 0 0 {{device}} r_width={{width}}u r_length={{length}}u
+
+
+.print dc Rs=par('(1M*V(p)/(V(n)-V(p)))/{{length}}u*{{width}}u')
+
+
+.control
+set filetype=ascii
+set appendwrite
+
+DC Vn {{sign}}3.3 {{sign}}3.3 0.1
+wrdata {{device}}_r_{{corner}}_temp/simulated_r/{{i}}_simulated_w{{width}}_l{{length}}.csv Rs 
+
+.endc
+
+** library calling
+
+.include "../../../design.ngspice"
+.lib "../../../sm141064.ngspice" res_{{corner}}
+
+.end
diff --git a/models/ngspice/testing/regression/resistor_r/models_regression.py b/models/ngspice/testing/regression/resistor_r/models_regression.py
new file mode 100644
index 0000000..f166171
--- /dev/null
+++ b/models/ngspice/testing/regression/resistor_r/models_regression.py
@@ -0,0 +1,323 @@
+# Copyright 2022 Efabless Corporation
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#      http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+"""
+Usage:
+  models_regression.py [--num_cores=<num>]
+
+  -h, --help             Show help text.
+  -v, --version          Show version.
+  --num_cores=<num>      Number of cores to be used by simulator
+"""
+
+from re import T
+from docopt import docopt
+import pandas as pd 
+import numpy as np
+import os 
+from jinja2 import Template
+import concurrent.futures
+import shutil
+import warnings
+warnings.simplefilter(action='ignore', category=FutureWarning)
+
+def call_simulator(file_name):
+    """Call simulation commands to perform simulation.
+    Args:
+        file_name (str): Netlist file name.
+    """
+    os.system(f"ngspice -b -a {file_name} -o {file_name}.log > {file_name}.log")
+
+def ext_measured_a(device,vn,d_in, r_sim, corner):
+    
+    # Get dimensions used for each device 
+    dirpath = f"{device}_{r_sim}_{corner}"
+    dimensions = pd.read_csv(f"{dirpath}/{device}.csv",usecols=["w (um)" , "l (um)"])
+    loops = dimensions["l (um)"].count()
+    
+    # Extracting measured values for each W & L 
+    for i in range (0,loops):
+        width  = dimensions["w (um)"].iloc[i]
+        length = dimensions["l (um)"].iloc[i]
+                                      
+        # measured r   
+        col_list = [f"{vn}",f"{d_in}_{corner} Rev9 "]
+        df_measured = pd.read_csv(f"{dirpath}/{device}.csv",usecols=col_list)
+        df_measured.columns = [f"{vn}","value"]
+        df_measured.loc[i:i].to_csv(f"{dirpath}/measured_{r_sim}/{i}_measured_w{width}_l{length}.csv", index=False)
+
+def ext_measured_b(device,vn,d_in, r_sim, corner):
+    
+    # Get dimensions used for each device 
+    dirpath = f"{device}_{r_sim}_{corner}_temp"
+    dimensions = pd.read_csv(f"{dirpath}/{device}.csv",usecols=["Temperature (C)" , "l (um)"])
+    if "rm" in device or "tm" in device:        
+        loops = dimensions["l (um)"].count()
+    else:
+        loops = 11
+    
+    # Extracting measured values for each W & L 
+    for i in range (0,loops):
+        temp   = dimensions["Temperature (C)"].iloc[i]
+        length = dimensions["l (um)"].iloc[i]
+        if "rm" in device or "tm" in device or "_u" in device:        
+            width  = length
+        else:
+            width  = length/2
+                                                  
+        # measured r   
+        col_list = [f"{vn}",f"{d_in}_{corner} Rev9 "]
+        df_measured = pd.read_csv(f"{dirpath}/{device}.csv",usecols=col_list)
+        df_measured.columns = [f"{vn}","value"]
+        df_measured.loc[i:i].to_csv(f"{dirpath}/measured_{r_sim}/{i}_measured_w{width}_l{length}.csv", index=False)
+
+def ext_simulated_a(device,vn,d_in,r_sim, corner,sign):
+    
+    if "rm" in device or "tm" in device:
+        netlist_tmp = f"./device_netlists/2term_res_a.spice"
+    else:
+        netlist_tmp = f"./device_netlists/3term_res_a.spice"        
+
+    # Get dimensions used for each device 
+    dirpath = f"{device}_{r_sim}_{corner}"
+    dimensions = pd.read_csv(f"{dirpath}/{device}.csv",usecols=["w (um)" , "l (um)"])
+    loops = dimensions["l (um)"].count()
+    temp = 25 
+    # Extracting measured values for each W & L 
+    for i in range (0,loops):
+        width  = dimensions["w (um)"].iloc[i]
+        length = dimensions["l (um)"].iloc[i]
+      
+        with open(netlist_tmp) as f:
+            tmpl = Template(f.read())
+            os.makedirs(f"{dirpath}/{device}_netlists_{r_sim}",exist_ok=True)
+            with open(f"{dirpath}/{device}_netlists_{r_sim}/{i}_{device}_netlist_w{width}_l{length}.spice", "w") as netlist:
+                netlist.write(tmpl.render(device = device, width = width, length = length , corner = corner, i = i , sign = sign))
+            netlist_path  = f"{dirpath}/{device}_netlists_{r_sim}/{i}_{device}_netlist_w{width}_l{length}.spice" 
+            # Running ngspice for each netlist 
+            with concurrent.futures.ProcessPoolExecutor(max_workers=workers_count) as executor:
+                executor.submit(call_simulator, netlist_path)
+            
+            # Writing simulated data 
+            df_simulated = pd.read_csv(f"{dirpath}/simulated_r/{i}_simulated_w{width}_l{length}.csv",header=None, delimiter=r"\s+")
+            df_simulated.to_csv(f"{dirpath}/simulated_r/{i}_simulated_w{width}_l{length}.csv",index= False)    
+
+            # Writing final simulated data                 
+            df_simulated.columns = [f"{vn}","value"]
+            df_simulated.to_csv(f"{dirpath}/simulated_r/{i}_simulated_w{width}_l{length}.csv",index= False) 
+
+def ext_simulated_b(device,vn,d_in,r_sim, corner,sign):
+    
+    if "rm" in device or "tm" in device:
+        netlist_tmp = f"./device_netlists/2term_res_b.spice"
+    else:
+        netlist_tmp = f"./device_netlists/3term_res_b.spice"        
+
+    # Get dimensions used for each device 
+    dirpath = f"{device}_{r_sim}_{corner}_temp"
+    dimensions = pd.read_csv(f"{dirpath}/{device}.csv",usecols=["Temperature (C)" , "l (um)"])
+    if "rm" in device or "tm" in device:        
+        loops = dimensions["l (um)"].count()
+    else:
+        loops = 11
+            
+    # Extracting measured values for each W & L 
+    for i in range (0,loops):
+        temp   = dimensions["Temperature (C)"].iloc[i]
+        length = dimensions["l (um)"].iloc[i]
+        if "rm" in device or "tm" in device or "_u" in device:        
+            width  = length
+        else:
+            width  = length/2            
+        
+        with open(netlist_tmp) as f:
+            tmpl = Template(f.read())
+            os.makedirs(f"{dirpath}/{device}_netlists_{r_sim}",exist_ok=True)
+            with open(f"{dirpath}/{device}_netlists_{r_sim}/{i}_{device}_netlist_w{width}_l{length}.spice", "w") as netlist:
+                netlist.write(tmpl.render(device = device, temp = temp , width = width, length = length , corner = corner, i = i , sign = sign))
+            netlist_path  = f"{dirpath}/{device}_netlists_{r_sim}/{i}_{device}_netlist_w{width}_l{length}.spice" 
+            # Running ngspice for each netlist 
+            with concurrent.futures.ProcessPoolExecutor(max_workers=workers_count) as executor:
+                executor.submit(call_simulator, netlist_path)
+            
+            # Writing simulated data 
+            df_simulated = pd.read_csv(f"{dirpath}/simulated_r/{i}_simulated_w{width}_l{length}.csv",header=None, delimiter=r"\s+")
+            df_simulated.to_csv(f"{dirpath}/simulated_r/{i}_simulated_w{width}_l{length}.csv",index= False)    
+
+            # Writing final simulated data                 
+            df_simulated.columns = [f"{vn}","value"]
+            df_simulated.to_csv(f"{dirpath}/simulated_r/{i}_simulated_w{width}_l{length}.csv",index= False) 
+                  
+def error_cal_a(device,vn,d_in,r_sim, corner):
+    
+    df_final = pd.DataFrame()
+    # Get dimensions used for each device 
+    dirpath = f"{device}_{r_sim}_{corner}"
+    dimensions = pd.read_csv(f"{dirpath}/{device}.csv",usecols=["w (um)" , "l (um)"])
+    loops = dimensions["l (um)"].count()
+    temp = 25 
+    # Extracting measured values for each W & L 
+    for i in range (0,loops):
+        width  = dimensions["w (um)"].iloc[i]
+        length = dimensions["l (um)"].iloc[i]
+             
+        measured  = pd.read_csv(f"{dirpath}/measured_{r_sim}/{i}_measured_w{width}_l{length}.csv")
+        simulated = pd.read_csv(f"{dirpath}/simulated_{r_sim}/{i}_simulated_w{width}_l{length}.csv")
+
+        error_1 = round (100 * abs((abs(measured.iloc[:, 1]) - abs(simulated.iloc[:, 1]))/abs(measured.iloc[:, 1])),8)  
+
+        df_error = pd.DataFrame(data=[measured.iloc[:, 0],error_1]).transpose()        
+        df_error.to_csv(f"{dirpath}/error_{r_sim}/{i}_{device}_error_w{width}_l{length}.csv",index= False)
+        
+        # Mean error 
+        mean_error = (df_error[f"value"].mean())
+        # Max error 
+        max_error = df_error[f"value"].max()
+
+        df_final_ = {'Run no.': f'{i}', 'Device name': f'{dirpath}', 'Temperature': temp, 'Width': f'{width}', 'Length': f'{length}', 'Simulated_Val':f'{r_sim}','Mean error%':f'{"{:.2f}".format(mean_error)}', 'Max error%':f'{"{:.2f}".format(max_error)} '}
+        df_final = df_final.append(df_final_, ignore_index = True)
+    # Max mean error 
+    print (df_final)   
+    df_final.to_csv (f"{dirpath}/Final_report_{r_sim}.csv", index = False)
+    out_report = pd.read_csv (f"{dirpath}/Final_report_{r_sim}.csv")
+    print ("\n",f"Max. mean error = {out_report['Mean error%'].max()}%")    
+    print ("=====================================================================================================================================================")
+
+def error_cal_b(device,vn,d_in,r_sim, corner):
+    
+    df_final = pd.DataFrame()
+    # Get dimensions used for each device 
+    dirpath = f"{device}_{r_sim}_{corner}_temp"
+    dimensions = pd.read_csv(f"{dirpath}/{device}.csv",usecols=["Temperature (C)" , "l (um)"])
+    if "rm" in device or "tm" in device:        
+        loops = dimensions["l (um)"].count()
+    else:
+        loops = 11
+        
+    # Extracting measured values for each W & L 
+    for i in range (0,loops):
+        temp   = dimensions["Temperature (C)"].iloc[i]
+        length = dimensions["l (um)"].iloc[i]
+        if "rm" in device or "tm" in device or "_u" in device:        
+            width  = length
+        else:
+            width  = length/2   
+                         
+        measured  = pd.read_csv(f"{dirpath}/measured_{r_sim}/{i}_measured_w{width}_l{length}.csv")
+        simulated = pd.read_csv(f"{dirpath}/simulated_{r_sim}/{i}_simulated_w{width}_l{length}.csv")
+
+        error_1 = round (100 * abs((abs(measured.iloc[:, 1]) - abs(simulated.iloc[:, 1]))/abs(measured.iloc[:, 1])),8)  
+
+        df_error = pd.DataFrame(data=[measured.iloc[:, 0],error_1]).transpose()        
+        df_error.to_csv(f"{dirpath}/error_{r_sim}/{i}_{device}_error_w{width}_l{length}.csv",index= False)
+        
+        # Mean error 
+        mean_error = (df_error[f"value"].mean())
+        # Max error 
+        max_error = df_error[f"value"].max()
+
+        df_final_ = {'Run no.': f'{i}', 'Device name': f'{dirpath}', 'Temperature': temp, 'Width': f'{width}', 'Length': f'{length}', 'Simulated_Val':f'{r_sim}','Mean error%':f'{"{:.2f}".format(mean_error)}', 'Max error%':f'{"{:.2f}".format(max_error)} '}
+        df_final = df_final.append(df_final_, ignore_index = True)
+    # Max mean error 
+    print (df_final)   
+    df_final.to_csv (f"{dirpath}/Final_report_{r_sim}.csv", index = False)
+    out_report = pd.read_csv (f"{dirpath}/Final_report_{r_sim}.csv")
+    print ("\n",f"Max. mean error = {out_report['Mean error%'].max()}%")    
+    print ("=====================================================================================================================================================")
+
+def main():
+
+    # res W&L var. 
+    corners_a  = ["typical","ff","ss"]        
+    
+    devices_a  = ["nplus_u" , "pplus_u" , "nplus_s" , "pplus_s" , "npolyf_u" , "ppolyf_u" , "npolyf_s" , "ppolyf_s" , "ppolyf_u_1k" , "ppolyf_u_2k" , "ppolyf_u_1k_6p0" ,
+                  "ppolyf_u_2k_6p0" , "ppolyf_u_3k" , "rm1" , "rm2" , "rm3" , "tm6k" , "tm9k" , "tm11k" , "tm30k" , "nwell"]
+    
+    dev_data_a = ["RES01a-wl-nplus_u.nl_out"     ,"RES02a-wl-pplus_u.nl_out"       ,"RES03a-wl-nplus_s.nl_out"       , "RES04a-wl-pplus_s.nl_out"     , 
+                  "RES06a-wl-npolyf_u.nl_out"    ,"RES07a-wl-ppolyf_u.nl_out"      ,"RES08a-wl-npolyf_s.nl_out"      , "RES09a-wl-ppolyf_s.nl_out"    , "RES10a-wl-ppolyf_u_1k.nl_out", 
+                  "RES11a-wl-ppolyf_u_2k.nl_out" ,"RES12a-wl-ppolyf_u_1k_6p0.nl_o" ,"RES13a-wl-ppolyf_u_2k_6p0.nl_o" , "RES14a-wl-ppolyf_u_3k.nl_out" , 
+                  "RES15a-wl-rm1.nl_out"         , "RES16a-wl-rm2.nl_out"          , "RES17a-wl-rm3.nl_out"          , "RES18a-wl-tm6k.nl_out"        , "RES19a-wl-tm9k.nl_out" ,
+                  "RES20a-wl-tm11k.nl_out"       , "RES21a-wl-tm30k.nl_out" ,"RES05a-wl-nwell.nl_out"]
+    
+    sign_a     = ["+" , "-" , "+" , "-" , "+" , "+" , "-" , "+" , "-" , "-" , "-" , "-" , "-" , "-" , "+" , "+" , "+" , "+" , "+" , "+", "+", ""]
+    measure_a  = ["r","corners", "res"]
+   
+    for corner in corners_a: 
+        for i,device in enumerate(devices_a): 
+            # Folder structure of measured values
+            r_sim, res_vn, res_in = measure_a[0], measure_a[1], measure_a[2]
+            dirpath = f"{device}_{r_sim}_{corner}"
+            if os.path.exists(dirpath) and os.path.isdir(dirpath):
+                shutil.rmtree(dirpath)
+            os.makedirs(f"{dirpath}/measured_{r_sim}",exist_ok=False)
+
+            # From xlsx to csv
+            read_file = pd.read_excel (f"../../180MCU_SPICE_DATA/Resistor/{dev_data_a[i]}.xlsx")
+            read_file.to_csv (f"{dirpath}/{device}.csv", index = False, header=True)
+
+            # Folder structure of simulated values 
+            os.makedirs(f"{dirpath}/simulated_{r_sim}",exist_ok=False)
+            os.makedirs(f"{dirpath}/error_{r_sim}",exist_ok=False)
+    
+            ext_measured_a (device,res_vn,res_in, r_sim, corner)
+            ext_simulated_a(device,res_vn,res_in,r_sim, corner,sign_a[i])
+            error_cal_a    (device,res_vn,res_in,r_sim, corner)            
+
+
+    # res temp_var
+    corners_b  = ["typical","ff","ss"]        
+    devices_b  = ["nplus_u" , "nplus_s", "pplus_u" , "pplus_s" , "nwell" , "npolyf_u" , "ppolyf_u" , "npolyf_s" , "ppolyf_s" , "ppolyf_u_1k" , "ppolyf_u_2k" , "ppolyf_u_1k_6p0" , "ppolyf_u_2k_6p0" , "ppolyf_u_3k" ,
+                  "rm1" , "rm2", "rm3" , "tm6k" , "tm9k" , "tm11k", "tm30k"]
+    dev_data_b = ["RES01b-temp-nplus_u.nl_out" , "RES03b-temp-nplus_s.nl_out", "RES02b-temp-pplus_u.nl_out" , "RES04b-temp-pplus_s.nl_out" , "RES05b-temp-nwell.nl_out" ,
+                  "RES06b-temp-npolyf_u.nl_out" , "RES07b-temp-ppolyf_u.nl_out" ,  "RES08b-temp-npolyf_s.nl_out" , "RES09b-temp-ppolyf_s.nl_out" , "RES10b-temp-ppolyf_u_1k.nl_out" ,
+                  "RES11b-temp-ppolyf_u_2k.nl_out" , "RES12b-temp-ppolyf_u_1k_6p0.nl" , "RES13b-temp-ppolyf_u_2k_6p0.nl" , "RES14b-temp-ppolyf_u_3k.nl_out" ,   
+                  "RES15b-temp-rm1.nl_out", "RES16b-temp-rm2.nl_out" , "RES17b-temp-rm3.nl_out" ,
+                  "RES18b-temp-tm6k.nl_out", "RES19b-temp-tm9k.nl_out" , "RES20b-temp-tm11k.nl_out", "RES21b-temp-tm30k.nl_out"]
+    
+    sign_b     = ["+" , "+", "-" , "-" , "+" , "+" , "-" ,"+" , "-" , "-" , "-" , "-" , "-" , "-" , "+" , "+" , "+" , "+" , "+" , "+", "+"]
+    measure_b  = ["r","corners", "res"]
+   
+    for corner in corners_b: 
+        for i,device in enumerate(devices_b): 
+            # Folder structure of measured values
+            r_sim, res_vn, res_in = measure_b[0], measure_b[1], measure_b[2]
+            dirpath = f"{device}_{r_sim}_{corner}_temp"
+            if os.path.exists(dirpath) and os.path.isdir(dirpath):
+                shutil.rmtree(dirpath)
+            os.makedirs(f"{dirpath}/measured_{r_sim}",exist_ok=False)
+
+            # From xlsx to csv
+            read_file = pd.read_excel (f"../../180MCU_SPICE_DATA/Resistor/{dev_data_b[i]}.xlsx")
+            read_file.to_csv (f"{dirpath}/{device}.csv", index = False, header=True)
+
+            # Folder structure of simulated values 
+            os.makedirs(f"{dirpath}/simulated_{r_sim}",exist_ok=False)
+            os.makedirs(f"{dirpath}/error_{r_sim}",exist_ok=False)
+    
+            ext_measured_b (device,res_vn,res_in, r_sim, corner)
+            ext_simulated_b(device,res_vn,res_in,r_sim, corner,sign_b[i])
+            error_cal_b    (device,res_vn,res_in,r_sim, corner)  
+
+
+# # ================================================================
+# -------------------------- MAIN --------------------------------
+# ================================================================
+        
+if __name__ == "__main__":
+    
+    # Args 
+    arguments     = docopt(__doc__, version='comparator: 0.1')
+    workers_count = os.cpu_count()*2 if arguments["--num_cores"] == None else int(arguments["--num_cores"])
+    
+    # Calling main function 
+    main()
diff --git a/models/ngspice/testing/sc_regression/gf180mcu_fd_sc_mcu7t5v0/.spiceinit b/models/ngspice/testing/sc_regression/gf180mcu_fd_sc_mcu7t5v0/.spiceinit
new file mode 100644
index 0000000..6fc9af8
--- /dev/null
+++ b/models/ngspice/testing/sc_regression/gf180mcu_fd_sc_mcu7t5v0/.spiceinit
@@ -0,0 +1,2 @@
+************
+set ngbehavior=hs
diff --git a/models/ngspice/testing/sc_regression/gf180mcu_fd_sc_mcu7t5v0/device_netlists/.spiceinit b/models/ngspice/testing/sc_regression/gf180mcu_fd_sc_mcu7t5v0/device_netlists/.spiceinit
new file mode 100644
index 0000000..6fc9af8
--- /dev/null
+++ b/models/ngspice/testing/sc_regression/gf180mcu_fd_sc_mcu7t5v0/device_netlists/.spiceinit
@@ -0,0 +1,2 @@
+************
+set ngbehavior=hs
diff --git a/models/ngspice/testing/sc_regression/gf180mcu_fd_sc_mcu7t5v0/device_netlists/gf180mcu_fd_sc_mcu7t5v0__inv_1.spice b/models/ngspice/testing/sc_regression/gf180mcu_fd_sc_mcu7t5v0/device_netlists/gf180mcu_fd_sc_mcu7t5v0__inv_1.spice
new file mode 100644
index 0000000..9a49154
--- /dev/null
+++ b/models/ngspice/testing/sc_regression/gf180mcu_fd_sc_mcu7t5v0/device_netlists/gf180mcu_fd_sc_mcu7t5v0__inv_1.spice
@@ -0,0 +1,46 @@
+* Copyright 2022 GlobalFoundries PDK Authors
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*      http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+
+* Sources
+Vin I 0 dc pulse(0 5 100p 1p 1p 100p 200p)
+Vdd VDD 0 dc {{volt}}
+
+* Main circuit
+X1 I ZN VDD VDD 0 0 gf180mcu_fd_sc_mcu7t5v0__inv_1
+
+* Temperature set
+.temp {{temp}}
+.options tnom={{temp}}
+
+* Analyses
+.control
+tran 1p 200p
+meas tran high_in FIND V(ZN) AT=100p
+meas tran low_in  FIND V(ZN) AT=200p
+
+wrdata inv/simulated/inv_{{process}}_{{temp}}c_{{volt}}v.csv {high_in} {low_in}
+
+.endc
+
+* Libraries calling
+.include "../../../design.ngspice"
+.lib "../../../sm141064.ngspice" {{process}}
+
+.SUBCKT gf180mcu_fd_sc_mcu7t5v0__inv_1 I ZN VDD VNW VPW VSS
+xM_i_0 ZN I VSS VPW nmos_6p0 W=8.2e-07 L=6e-07
+xM_i_1 ZN I VDD VNW pmos_6p0 W=1.22e-06 L=5e-07
+.ENDS
+
+
+.end
diff --git a/models/ngspice/testing/sc_regression/gf180mcu_fd_sc_mcu7t5v0/device_netlists/gf180mcu_fd_sc_mcu7t5v0__inv_1_run.spice b/models/ngspice/testing/sc_regression/gf180mcu_fd_sc_mcu7t5v0/device_netlists/gf180mcu_fd_sc_mcu7t5v0__inv_1_run.spice
new file mode 100644
index 0000000..76b31f6
--- /dev/null
+++ b/models/ngspice/testing/sc_regression/gf180mcu_fd_sc_mcu7t5v0/device_netlists/gf180mcu_fd_sc_mcu7t5v0__inv_1_run.spice
@@ -0,0 +1,46 @@
+* Copyright 2022 GlobalFoundries PDK Authors
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*      http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+
+* Sources
+Vin I 0 dc pulse(0 5 100p 1p 1p 100p 200p)
+Vdd VDD 0 dc 5
+
+* Main circuit
+X1 I ZN VDD VDD 0 0 gf180mcu_fd_sc_mcu7t5v0__inv_1
+
+* Temperature set
+.temp 25
+.options tnom=25
+
+* Analyses
+.control
+tran 1p 200p
+meas tran high_in FIND V(ZN) AT=100p
+meas tran low_in  FIND V(ZN) AT=200p
+
+wrdata inv/inv_simulated.csv {high_in} {low_in}
+
+.endc
+
+* Libraries calling
+.include "../../../../design.ngspice"
+.lib "../../../../sm141064.ngspice" typical
+
+.SUBCKT gf180mcu_fd_sc_mcu7t5v0__inv_1 I ZN VDD VNW VPW VSS
+xM_i_0 ZN I VSS VPW nmos_6p0 W=8.2e-07 L=6e-07
+xM_i_1 ZN I VDD VNW pmos_6p0 W=1.22e-06 L=5e-07
+.ENDS
+
+
+.end
diff --git a/models/ngspice/testing/sc_regression/gf180mcu_fd_sc_mcu7t5v0/device_netlists/gf180mcu_fd_sc_mcu7t5v0__nand2_1.spice b/models/ngspice/testing/sc_regression/gf180mcu_fd_sc_mcu7t5v0/device_netlists/gf180mcu_fd_sc_mcu7t5v0__nand2_1.spice
new file mode 100644
index 0000000..56e4523
--- /dev/null
+++ b/models/ngspice/testing/sc_regression/gf180mcu_fd_sc_mcu7t5v0/device_netlists/gf180mcu_fd_sc_mcu7t5v0__nand2_1.spice
@@ -0,0 +1,50 @@
+* Copyright 2022 GlobalFoundries PDK Authors
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*      http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+
+* Sources
+Vdd VDD 0 dc {{volt}}
+Vin1 I1 0 dc pulse(0 5 200p 1p 1p 200p 400p)
+Vin2 I2 0 dc pulse(0 5 400p 1p 1p 400p 800p)
+
+* Main circuit
+X1 I1 I2 ZN VDD VDD 0 0 gf180mcu_fd_sc_mcu7t5v0__nand2_1
+
+* Temperature set
+.temp {{temp}}
+.options tnom={{temp}}
+
+* Analyses
+.control
+tran 1p 800p
+meas tran o0 FIND V(ZN) AT=200p
+meas tran o1  FIND V(ZN) AT=400p
+meas tran o2 FIND V(ZN) AT=600p
+meas tran o3  FIND V(ZN) AT=800p
+
+wrdata nand2/simulated/nand2_{{process}}_{{temp}}c_{{volt}}v.csv {o0} {o1} {o2} {o3}
+.endc
+
+* Libraries calling
+.include "../../../design.ngspice"
+.lib "../../../sm141064.ngspice" {{process}}
+
+.SUBCKT gf180mcu_fd_sc_mcu7t5v0__nand2_1 A1 A2 ZN VDD VNW VPW VSS
+xM_i_1 net_0 A2 VSS VPW nmos_6p0 W=8.2e-07 L=6e-07
+xM_i_0 ZN A1 net_0 VPW nmos_6p0 W=8.2e-07 L=6e-07
+xM_i_3 ZN A2 VDD VNW pmos_6p0 W=1.13e-06 L=5e-07
+xM_i_2 VDD A1 ZN VNW pmos_6p0 W=1.13e-06 L=5e-07
+.ENDS
+
+
+.end
diff --git a/models/ngspice/testing/sc_regression/gf180mcu_fd_sc_mcu7t5v0/device_netlists/gf180mcu_fd_sc_mcu7t5v0__nand2_1_run.spice b/models/ngspice/testing/sc_regression/gf180mcu_fd_sc_mcu7t5v0/device_netlists/gf180mcu_fd_sc_mcu7t5v0__nand2_1_run.spice
new file mode 100644
index 0000000..ff981f9
--- /dev/null
+++ b/models/ngspice/testing/sc_regression/gf180mcu_fd_sc_mcu7t5v0/device_netlists/gf180mcu_fd_sc_mcu7t5v0__nand2_1_run.spice
@@ -0,0 +1,50 @@
+* Copyright 2022 GlobalFoundries PDK Authors
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*      http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+
+* Sources
+Vdd VDD 0 dc 5
+Vin1 I1 0 dc pulse(0 5 200p 1p 1p 200p 400p)
+Vin2 I2 0 dc pulse(0 5 400p 1p 1p 400p 800p)
+
+* Main circuit
+X1 I1 I2 ZN VDD VDD 0 0 gf180mcu_fd_sc_mcu7t5v0__nand2_1
+
+* Temperature set
+.temp 25
+.options tnom=25
+
+* Analyses
+.control
+tran 1p 800p
+meas tran o0 FIND V(ZN) AT=200p
+meas tran o1  FIND V(ZN) AT=400p
+meas tran o2 FIND V(ZN) AT=600p
+meas tran o3  FIND V(ZN) AT=800p
+
+wrdata nand2/nand2_simulated.csv {o0} {o1} {o2} {o3}
+.endc
+
+* Libraries calling
+.include "../../../../design.ngspice"
+.lib "../../../../sm141064.ngspice" typical
+
+.SUBCKT gf180mcu_fd_sc_mcu7t5v0__nand2_1 A1 A2 ZN VDD VNW VPW VSS
+xM_i_1 net_0 A2 VSS VPW nmos_6p0 W=8.2e-07 L=6e-07
+xM_i_0 ZN A1 net_0 VPW nmos_6p0 W=8.2e-07 L=6e-07
+xM_i_3 ZN A2 VDD VNW pmos_6p0 W=1.13e-06 L=5e-07
+xM_i_2 VDD A1 ZN VNW pmos_6p0 W=1.13e-06 L=5e-07
+.ENDS
+
+
+.end
diff --git a/models/ngspice/testing/sc_regression/gf180mcu_fd_sc_mcu7t5v0/device_netlists/gf180mcu_fd_sc_mcu7t5v0__or3_1.spice b/models/ngspice/testing/sc_regression/gf180mcu_fd_sc_mcu7t5v0/device_netlists/gf180mcu_fd_sc_mcu7t5v0__or3_1.spice
new file mode 100644
index 0000000..f269c03
--- /dev/null
+++ b/models/ngspice/testing/sc_regression/gf180mcu_fd_sc_mcu7t5v0/device_netlists/gf180mcu_fd_sc_mcu7t5v0__or3_1.spice
@@ -0,0 +1,59 @@
+* Copyright 2022 GlobalFoundries PDK Authors
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*      http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+
+* Sources
+Vdd VDD 0 dc {{volt}}
+Vin1 I1 0 dc pulse(0 5 200p 1p 1p 200p 400p)
+Vin2 I2 0 dc pulse(0 5 400p 1p 1p 400p 800p)
+Vin3 I3 0 dc pulse(0 5 800p 1p 1p 800p 1600p)
+
+* Main circuit
+X1 I1 I2 I3 ZN VDD VDD 0 0 gf180mcu_fd_sc_mcu7t5v0__or3_1
+
+* Temperature set
+.temp {{temp}}
+.options tnom={{temp}}
+
+* Analyses
+.control
+tran 1p 1600p
+meas tran o0 FIND V(ZN) AT=200p
+meas tran o1 FIND V(ZN) AT=400p
+meas tran o2 FIND V(ZN) AT=600p
+meas tran o3 FIND V(ZN) AT=800p
+meas tran o4 FIND V(ZN) AT=1000p
+meas tran o5 FIND V(ZN) AT=1200p
+meas tran o6 FIND V(ZN) AT=1400p
+meas tran o7 FIND V(ZN) AT=1600p
+
+wrdata or3/simulated/or3_{{process}}_{{temp}}c_{{volt}}v.csv {o0} {o1} {o2} {o3} {o4} {o5} {o6} {o7}
+.endc
+
+* Libraries calling
+.include "../../../design.ngspice"
+.lib "../../../sm141064.ngspice" {{process}}
+
+.SUBCKT gf180mcu_fd_sc_mcu7t5v0__or3_1 A1 A2 A3 Z VDD VNW VPW VSS
+M_i_2 VSS A1 Z_neg VPW nmos_6p0 W=4e-07 L=6e-07
+M_i_3 Z_neg A2 VSS VPW nmos_6p0 W=4e-07 L=6e-07
+M_i_4 VSS A3 Z_neg VPW nmos_6p0 W=4e-07 L=6e-07
+M_i_0 Z Z_neg VSS VPW nmos_6p0 W=8.2e-07 L=6e-07
+M_i_5 net_0 A1 Z_neg VNW pmos_6p0 W=5.6e-07 L=5e-07
+M_i_6 net_1 A2 net_0 VNW pmos_6p0 W=5.6e-07 L=5e-07
+M_i_7 VDD A3 net_1 VNW pmos_6p0 W=5.6e-07 L=5e-07
+M_i_1 Z Z_neg VDD VNW pmos_6p0 W=1.22e-06 L=5e-07
+.ENDS
+
+
+.end
diff --git a/models/ngspice/testing/sc_regression/gf180mcu_fd_sc_mcu7t5v0/device_netlists/gf180mcu_fd_sc_mcu7t5v0__or3_1_run.spice b/models/ngspice/testing/sc_regression/gf180mcu_fd_sc_mcu7t5v0/device_netlists/gf180mcu_fd_sc_mcu7t5v0__or3_1_run.spice
new file mode 100644
index 0000000..24a5c05
--- /dev/null
+++ b/models/ngspice/testing/sc_regression/gf180mcu_fd_sc_mcu7t5v0/device_netlists/gf180mcu_fd_sc_mcu7t5v0__or3_1_run.spice
@@ -0,0 +1,59 @@
+* Copyright 2022 GlobalFoundries PDK Authors
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*      http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+
+* Sources
+Vdd VDD 0 dc 5
+Vin1 I1 0 dc pulse(0 5 200p 1p 1p 200p 400p)
+Vin2 I2 0 dc pulse(0 5 400p 1p 1p 400p 800p)
+Vin3 I3 0 dc pulse(0 5 800p 1p 1p 800p 1600p)
+
+* Main circuit
+X1 I1 I2 I3 ZN VDD VDD 0 0 gf180mcu_fd_sc_mcu7t5v0__or3_1
+
+* Temperature set
+.temp 25
+.options tnom=25
+
+* Analyses
+.control
+tran 1p 1600p
+meas tran o0 FIND V(ZN) AT=200p
+meas tran o1 FIND V(ZN) AT=400p
+meas tran o2 FIND V(ZN) AT=600p
+meas tran o3 FIND V(ZN) AT=800p
+meas tran o4 FIND V(ZN) AT=1000p
+meas tran o5 FIND V(ZN) AT=1200p
+meas tran o6 FIND V(ZN) AT=1400p
+meas tran o7 FIND V(ZN) AT=1600p
+
+wrdata or3/or3_simulated.csv {o0} {o1} {o2} {o3} {o4} {o5} {o6} {o7}
+.endc
+
+* Libraries calling
+.include "../../../../design.ngspice"
+.lib "../../../../sm141064.ngspice" typical
+
+.SUBCKT gf180mcu_fd_sc_mcu7t5v0__or3_1 A1 A2 A3 Z VDD VNW VPW VSS
+M_i_2 VSS A1 Z_neg VPW nmos_6p0 W=4e-07 L=6e-07
+M_i_3 Z_neg A2 VSS VPW nmos_6p0 W=4e-07 L=6e-07
+M_i_4 VSS A3 Z_neg VPW nmos_6p0 W=4e-07 L=6e-07
+M_i_0 Z Z_neg VSS VPW nmos_6p0 W=8.2e-07 L=6e-07
+M_i_5 net_0 A1 Z_neg VNW pmos_6p0 W=5.6e-07 L=5e-07
+M_i_6 net_1 A2 net_0 VNW pmos_6p0 W=5.6e-07 L=5e-07
+M_i_7 VDD A3 net_1 VNW pmos_6p0 W=5.6e-07 L=5e-07
+M_i_1 Z Z_neg VDD VNW pmos_6p0 W=1.22e-06 L=5e-07
+.ENDS
+
+
+.end
diff --git a/models/ngspice/testing/sc_regression/gf180mcu_fd_sc_mcu7t5v0/models_regression.py b/models/ngspice/testing/sc_regression/gf180mcu_fd_sc_mcu7t5v0/models_regression.py
new file mode 100644
index 0000000..154994b
--- /dev/null
+++ b/models/ngspice/testing/sc_regression/gf180mcu_fd_sc_mcu7t5v0/models_regression.py
@@ -0,0 +1,140 @@
+"""
+Usage:
+  models_regression.py [--num_cores=<num>]
+
+  -h, --help             Show help text.
+  -v, --version          Show version.
+  --num_cores=<num>      Number of cores to be used by simulator
+"""
+
+from cmath import inf
+from re import L, T
+from docopt import docopt
+import pandas as pd 
+import numpy as np
+import os 
+from jinja2 import Template
+import concurrent.futures
+import shutil
+import warnings
+warnings.simplefilter(action='ignore', category=FutureWarning)
+
+def call_simulator(file_name):
+    """Call simulation commands to perform simulation.
+    Args:
+        file_name (str): Netlist file name.
+    """
+    os.system(f"ngspice -b -a {file_name} -o {file_name}.log > {file_name}.log")
+
+def ext_measured(device, table):
+
+    # Generate CSVs with truth tables
+    df = pd.DataFrame(data=table)
+    df.set_index(df.columns[0])
+    new_header = df.iloc[0]
+    df = df[1:]
+    df.columns = new_header
+    df.to_csv(f"{device}/{device}_measured.csv", index = False)
+
+def ext_simulated(device, processes, volts, temps):
+
+    # Get all corners simulated
+    for process in processes:
+        for volt in volts:
+            for temp in temps:
+                with open(f"device_netlists/gf180mcu_fd_sc_mcu7t5v0__{device}_1.spice") as f:
+                    tmpl = Template(f.read())
+                netlist_path  = f"{device}/{device}_netlists/{device}_{process}_{temp}c_{volt}v.spice"
+                with open(netlist_path, "w") as netlist:
+                    netlist.write(tmpl.render(process = process, volt = volt , temp = temp ))
+
+                # Running ngspice for each netlist 
+                with concurrent.futures.ProcessPoolExecutor(max_workers=workers_count) as executor:
+                    executor.submit(call_simulator, netlist_path)
+
+                df_simulated = pd.read_csv(f"{device}/simulated/{device}_{process}_{temp}c_{volt}v.csv",header=None, delimiter=r"\s+")
+                results = []
+                for i in df_simulated.columns:
+                    if df_simulated.iloc[0, i] > 2.5:
+                        results.append(1)
+                    else:
+                        results.append(0)
+                df_measured = pd.read_csv(f"{device}/{device}_measured.csv",header=0)
+                df = df_measured
+                df_measured.drop(df_measured.columns[len(df_measured.columns)-1], axis=1, inplace=True)
+                df_measured['output'] = results[1::2]
+                df_measured.to_csv(f"{device}/simulated/{device}_{process}_{temp}c_{volt}v.csv",index= False)
+
+def error_cal(device, processes, volts, temps):
+
+    print (f"\nSimulation results of {device}")
+    measured  = pd.read_csv(f"{device}/{device}_measured.csv")
+    for process in processes:
+        for volt in volts:
+            for temp in temps:
+                simulated = pd.read_csv(f"{device}/simulated/{device}_{process}_{temp}c_{volt}v.csv")
+
+                res = (measured == simulated).all().all()
+                print ("{:^5s} in PVT of {:^7s}, {:^3s}V, {:^3s}C functional simulation = {}".format(device, process, volt, temp, res))    
+    print ("================================================================================================\n")
+
+def main():
+
+    devices = ["inv","nand2","or3"]
+
+    # Generate truth tables data
+    inv_table = [["input","output"],
+                 [0,1],
+                 [1,0]]
+
+    nand2_table = [["input1","input2","output"],
+                   [0,0,1],
+                   [0,1,1],
+                   [1,0,1],
+                   [1,1,0]]
+
+    or3_table = [["input1","input2","input3","output"],
+                 [0,0,0,0],
+                 [0,0,1,1],
+                 [0,1,0,1],
+                 [0,1,1,1],
+                 [1,0,0,1],
+                 [1,0,1,1],
+                 [1,1,0,1],
+                 [1,1,1,1]]
+
+    tables = [inv_table,nand2_table,or3_table]
+
+    processes   = ["typical","ff","ss"]
+    volts       = ["5", "4.5", "5.5"]
+    temps       = ["25", "-40", "125"]
+
+    for i, device in enumerate(devices): 
+        # Folder structure of measured values
+        if os.path.exists(device) and os.path.isdir(device):
+            shutil.rmtree(device)
+        os.makedirs(device)
+
+        # Folder structure of simulated values
+        os.makedirs(f"{device}/{device}_netlists",exist_ok=True)
+        os.makedirs(f"{device}/simulated",exist_ok=True)
+        
+        ext_measured (device, tables[i])
+        # =========== Simulate ==============
+        ext_simulated(device, processes, volts, temps)
+
+        # ============ Results ==============
+        error_cal    (device, processes, volts, temps)
+
+# ================================================================
+# -------------------------- MAIN --------------------------------
+# ================================================================
+
+if __name__ == "__main__":
+
+    # Args
+    arguments     = docopt(__doc__, version='comparator: 0.1')
+    workers_count = os.cpu_count()*2 if arguments["--num_cores"] == None else int(arguments["--num_cores"])
+
+    # Calling main function 
+    main()
diff --git a/models/ngspice/testing/smoke_test/.spiceinit b/models/ngspice/testing/smoke_test/.spiceinit
new file mode 100644
index 0000000..6fc9af8
--- /dev/null
+++ b/models/ngspice/testing/smoke_test/.spiceinit
@@ -0,0 +1,2 @@
+************
+set ngbehavior=hs
diff --git a/models/ngspice/testing/smoke_test/inv_ng.spice b/models/ngspice/testing/smoke_test/inv_ng.spice
new file mode 100644
index 0000000..5a3b4c9
--- /dev/null
+++ b/models/ngspice/testing/smoke_test/inv_ng.spice
@@ -0,0 +1,44 @@
+**.subckt INV_tb
+* Copyright 2022 Efabless Corporation
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*      http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+Vdd Vdd 0 3.3
+Vin Vin 0 dc pulse(0 3.3 0 1p 1p 100p 200p)
+X1 Vdd Vout Vin 0 INV
+
+
+.temp {{temp}}
+.options tnom={{temp}}
+
+
+.control
+tran 1p 400p
+meas tran tphl TRIG v(Vin) VAL={0.5*3.3} RISE=2 TARG v(Vout) VAL={0.5*3.3} FALL=2
+meas tran tplh TRIG v(Vin) VAL={0.5*3.3} FALL=1 TARG v(Vout) VAL={0.5*3.3} RISE=1
+print {(tplh+tphl)/2}
+wrdata {{run_path}}/simulation/inv_W{{width}}_L{{length}}_T{{temp}}_{{corner}}.csv {(tplh+tphl)/2}
+.endc
+
+
+.include "../../design.ngspice"
+.lib "../../sm141064.ngspice" {{corner}}
+
+
+.subckt INV  VDD Vout Vin GND
+XM1 Vout Vin GND GND nmos_3p3 W={{width}}u L={{length}}u 
+*ad={{AD}}u pd={{PD}}u as={{AS}}u ps={{PS}}u
+XM2 Vout Vin VDD VDD pmos_3p3 W = {{width_p}}u L = {{length}}u 
+*ad={{AD_p}}u pd={{PD_p}}u as={{AD_p}}u ps={{PD_p}}u
+.ends
+
+.end
\ No newline at end of file
diff --git a/models/ngspice/testing/smoke_test/ng_smoke_test.py b/models/ngspice/testing/smoke_test/ng_smoke_test.py
new file mode 100644
index 0000000..23128ee
--- /dev/null
+++ b/models/ngspice/testing/smoke_test/ng_smoke_test.py
@@ -0,0 +1,120 @@
+# Copyright 2022 Efabless Corporation
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#      http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+"""
+Usage:
+  smoke_test.py [--num_cores=<num>]
+
+  -h, --help             Show help text.
+  -v, --version          Show version.
+  --num_cores=<num>      Number of cores to be used by simulator
+"""
+
+import re
+from docopt import docopt
+import pandas as pd 
+import os 
+from jinja2 import Template
+import concurrent.futures
+import itertools
+import datetime
+import warnings
+import subprocess
+
+warnings.simplefilter(action='ignore', category=FutureWarning)
+
+def call_simulator(file_name):
+    """Call simulation commands to perform simulation.
+    Args:
+        file_name (str): Netlist file name.
+    """
+    p = subprocess.Popen(f"ngspice -b -a {file_name} > {file_name}.log 2>&1", shell=True, executable='/bin/bash')
+    p.wait()
+
+def get_sizes(models_path):
+    with open(models_path, "r") as f:
+        device_model = f.read()
+        dimensions = re.findall(f"\.model  nmos_3p3.*\n.*\n\+lmin.*= (.*\S).*\n.*\n\+wmin.*= (.*\S)", device_model)
+    return dimensions[0:16]
+
+def get_results(run_path, sizes, temp, corner):
+    netlist_tmp = f"./inv_ng.spice"
+    width  = float(sizes[1]) * 1000000
+    width_p = width * 1.5
+    length = float(sizes[0])  * 1000000
+    # AD = width * 0.24
+    # AD_p = AD * 1.5
+    # PD = 2 * (width + 0.24)
+    # PD_p = width + PD 
+    # AS = AD 
+    # PS = PD 
+    with open(netlist_tmp) as f:
+        tmpl = Template(f.read())
+
+    os.makedirs(f"{run_path}/netlists",exist_ok=True)
+    os.makedirs(f"{run_path}/simulation",exist_ok=True)
+    netlist_path  = f"{run_path}/netlists/inv_W{width}_L{length}_T{temp}_{corner}.spice"
+    with open(netlist_path, "w") as netlist:
+        netlist.write(tmpl.render(corner = corner, width = width,length = length, temp = temp , run_path = run_path, width_p = width_p))#, AD = AD , PD = PD , AS = AS , PS = PS, AD_p = AD_p, PD_p = PD_p ))
+    
+    call_simulator(netlist_path)
+    
+    # Writing simulated data 
+    df_simulated = pd.read_csv(f"{run_path}/simulation/inv_W{width}_L{length}_T{temp}_{corner}.csv",header=None, delimiter=r"\s+")
+    return [f"W{width}_L{length}_T{temp}_{corner}",df_simulated.iloc[-1, -1]]  
+
+def main():
+        
+    models_path = "../../sm141064.ngspice"
+    temps = ["25","-40","125"]
+    corners = ["typical","ff","ss","fs","sf"]#,"stat"]
+
+    time = f"{datetime.datetime.now()}".replace(" ", "_")
+    run_path = f"../run_smoke_{time}"
+    os.makedirs(run_path,exist_ok=True)
+
+    sizes = get_sizes(models_path)
+    results = []
+
+    all_combs = list(itertools.product(sizes, temps, corners))
+
+    with concurrent.futures.ThreadPoolExecutor(max_workers=workers_count) as executor:
+        # Start the load operations and mark each future with its URL
+        future_list = [executor.submit(get_results, run_path, comb[0], comb[1], comb[2]) for comb in all_combs]
+        for future in concurrent.futures.as_completed(future_list):
+            try:
+                results.append(future.result())
+            except Exception as exc:
+                print('Generated an exception: %s' % (exc))
+
+
+    df_results = pd.DataFrame(results)    
+    df_results.columns = ["run","tpd_result"]
+    df_results.to_csv(f"{run_path}/final_results.csv",index= False)
+
+    print (df_results)
+    
+
+    
+# # ================================================================
+# -------------------------- MAIN --------------------------------
+# ================================================================
+        
+if __name__ == "__main__":
+    
+    # Args 
+    arguments     = docopt(__doc__, version='smoke_test: 0.1')
+    workers_count = os.cpu_count()*2 if arguments["--num_cores"] == None else int(arguments["--num_cores"])
+    
+    # Calling main function 
+    main()
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diff --git a/models/xyce/testing/180MCU_SPICE_DATA/Resistor/efuse.nl_out.xlsx b/models/xyce/testing/180MCU_SPICE_DATA/Resistor/efuse.nl_out.xlsx
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diff --git a/models/xyce/testing/Makefile b/models/xyce/testing/Makefile
new file mode 100644
index 0000000..7cc3ce2
--- /dev/null
+++ b/models/xyce/testing/Makefile
@@ -0,0 +1,183 @@
+# Copyright 2022 Efabless Corporation
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#      http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+
+#=================================================================
+# ------------------------ models_xyce ------------------------
+#=================================================================
+
+SHELL := /bin/bash
+Testing_DIR ?= $(shell pwd)
+run_folder  := $(shell date +'run_%Y_%m_%d_%H:%M:%S')
+
+
+.DEFAULT_GOAL := all
+
+all : test-models_xyce
+
+test-models_xyce: smoke-test models-MOS  models-BJT models-diode models-MOSCAP models-MIMCAP models-RES 
+
+#================================
+#---------- Create Run ----------
+#================================
+
+.ONESHELL:
+Add_run-dir:
+	@cd $(Testing_DIR)
+	@ [ ! -d "$(run_folder)/" ] && cp -rf $(Testing_DIR)/regression $(Testing_DIR)/$(run_folder)
+
+#================================
+#---------- smoke-test ----------
+#================================
+
+.ONESHELL:
+smoke-test:
+	@cd $(Testing_DIR)/smoke_test
+	@python3 xyce_smoke_test.py
+
+
+#================================
+# ---------- models-MOS----------
+#================================
+
+.ONESHELL:
+models-MOS: Add_run-dir
+	@cd $(Testing_DIR)/$(run_folder)/mos_iv_vgs
+	@echo "========== Runing models_xyce-MOS regression ==========" |& tee -a ../run_log.log 
+	@ python3 models_regression.py |& tee -a ../run_log.log  
+# @cd ../mos_iv_vbs
+# @ python3 models_regression.py |& tee -a ../run_log.log  
+
+# .ONESHELL:
+# clean-models-MOS:
+# 	@echo "==== Cleaning models-MOS old runs ===="
+# 	@cd $(Testing_DIR)/$(run_folder)/mos_iv_vgs && rm -rf nmos_* pmos_*
+
+#================================
+# ---------- models-BJT----------
+#================================
+
+.ONESHELL:
+models-BJT: Add_run-dir
+	@cd $(Testing_DIR)/$(run_folder)/bjt_cj
+	@echo "========== Runing models_xyce-BJT regression ==========" |& tee -a ../run_log.log 
+	@ python3 models_regression.py |& tee -a ../run_log.log
+
+
+# .ONESHELL:
+# clean-models-BJT:
+# 	@echo "==== Cleaning models-BJT old runs ===="
+# 	@cd $(Testing_DIR)/$(run_folder)/bjt_cj && rm -rf vnpn_* vpnp_*
+
+#================================
+# --------- models-diode --------
+#================================
+
+.ONESHELL:
+models-diode: Add_run-dir
+	@cd $(Testing_DIR)/$(run_folder)/diode
+	@echo "========== Runing models_xyce-diode regression ==========" |& tee -a ../run_log.log 
+	@ python3 models_regression.py |& tee -a ../run_log.log
+
+
+# .ONESHELL:
+# clean-models-diode:
+# 	@echo "==== Cleaning models-diode old runs ===="
+# 	@cd $(Testing_DIR)/$(run_folder)/diode && rm -rf np_* pn_* nwp* dnw* sc_*
+
+#================================
+# -------- models-MOSCAP --------
+#================================
+
+.ONESHELL:
+models-MOSCAP: Add_run-dir
+	@cd $(Testing_DIR)/$(run_folder)/moscap_c
+	@echo "========== Runing models_xyce-MOSCAP regression ==========" |& tee -a ../run_log.log 
+	@ python3 models_regression.py |& tee -a ../run_log.log
+
+
+# .ONESHELL:
+# clean-models-MOSCAP:
+# 	@echo "==== Cleaning models-MOSCAP old runs ===="
+# 	@cd $(Testing_DIR)/$(run_folder)/moscap_c && rm -rf nmoscap_* pmoscap_*	
+
+#================================
+# -------- models-MIMCAP --------
+#================================
+
+.ONESHELL:
+models-MIMCAP: Add_run-dir
+	@cd $(Testing_DIR)/$(run_folder)/mimcap_c
+	@echo "========== Runing models_xyce-MIMCAP regression ==========" |& tee -a ../run_log.log 
+	@ python3 models_regression.py |& tee -a ../run_log.log
+
+
+# .ONESHELL:
+# clean-models-MIMCAP:
+# 	@echo "==== Cleaning models-MIMCAP old runs ===="
+# 	@cd $(Testing_DIR)/$(run_folder)/mimcap_c && rm -rf mim*		
+
+
+#================================
+# --------- models-RES ----------
+#================================
+
+.ONESHELL:
+models-RES: Add_run-dir
+	@cd $(Testing_DIR)/$(run_folder)/resistor_r
+	@echo "========== Runing models_xyce-RES regression ==========" |& tee -a ../run_log.log 
+	@ python3 models_regression.py |& tee -a ../run_log.log
+
+
+# .ONESHELL:
+# clean-models-RES:
+# 	@echo "==== Cleaning models-RES old runs ===="
+# 	@cd $(Testing_DIR)/$(run_folder)/resistor_r && rm -rf nplus* pplus* npoly* ppoly* rm* tm* nwell
+
+
+#===============================
+# --------- Clean ALL ----------
+#===============================
+
+# .ONESHELL:
+# clean: clean-models-MOS clean-models-BJT clean-models-diode clean-models-MOSCAP clean-models-MIMCAP clean-models-RES
+# 	@echo "==== Cleaning all runs is done ===="
+
+
+#==========================
+# --------- HELP ----------
+#==========================
+
+# Help Target
+help:
+	@echo "\n ==== The following are some of the valid targets for this Makefile ====\n"
+	@echo "... all                  (the default if no target is provided)"
+	@echo "... smoke-test           (To run smoke test for    an inverter)"
+	@echo "... test-models_xyce     (To run regression for all    devices)"
+	@echo "... models-MOS           (To run regression for MOS    devices)"
+	@echo "... models-BJT           (To run regression for BJT    devices)"
+	@echo "... models-diode         (To run regression for diode  devices)"
+	@echo "... models-MOSCAP        (To run regression for MOSCAP devices)"
+	@echo "... models-MIMCAP        (To run regression for MIMCAP devices)"
+	@echo "... models-RES           (To run regression for RES    devices)"
+# @echo "... clean-models-MOS     (To clean old runs for MOS    devices)"
+# @echo "... clean-models-BJT     (To clean old runs for BJT    devices)"
+# @echo "... clean-models-diode   (To clean old runs for diode  devices)"
+# @echo "... clean-models-MOSCAP  (To clean old runs for MOSCAP devices)"
+# @echo "... clean-models-MIMCAP  (To clean old runs for MIMCAP devices)"
+# @echo "... clean-models-RES     (To run regression for RES    devices)"
+	
+# @echo "... clean                (To clean all old runs)               "
+   
+.PHONY : help
\ No newline at end of file
diff --git a/models/xyce/testing/README.md b/models/xyce/testing/README.md
new file mode 100644
index 0000000..063cc25
--- /dev/null
+++ b/models/xyce/testing/README.md
@@ -0,0 +1,51 @@
+# Globalfoundries 180nm MCU models-xyce regression
+
+Explains how to run GF180nm models-xyce regression.
+
+## Folder Structure
+
+```text
+📦testing
+ ┣ 📜Makefile
+ ┣ 📜README.md
+ ┣ 📦regression
+ ┣ 📦smoke_test
+ ┣ 📦180MCU_SPICE_Models
+ ```
+
+## Prerequisites
+
+At a minimum:
+
+- Git 2.35+
+- Python 3.6+
+- Xyce 7.5+
+
+### On Ubuntu, you can just
+
+`apt install -y build-essential python3`
+
+- Check this [xyce](https://xyce.sandia.gov/documentation-tutorials/building-guide/) for Xyce installation.
+
+## Regression Usage
+
+To make a full test for GF180nm models-xyce, you could use the following command in testing directory:
+
+```bash
+make all
+```
+
+- You could also check allowed targets in the Makefile, using the following command:
+
+    ```bash
+    make help
+    ```
+
+## **Regression Outputs**
+
+- The resulting files are in `regression/<device_folder>/` with name of `<device_name><options>` that contains:
+
+    1. A final report file of all results.
+    2. measured folder that contains measured data used in regression.
+    3. simulated folder that contains simulated data used in regression.
+    4. netlists folder that contains spice files used in simulation.
diff --git a/models/xyce/testing/regression/bjt_beta/device_netlists/npn.spice b/models/xyce/testing/regression/bjt_beta/device_netlists/npn.spice
new file mode 100644
index 0000000..ad9e216
--- /dev/null
+++ b/models/xyce/testing/regression/bjt_beta/device_netlists/npn.spice
@@ -0,0 +1,26 @@
+*****************
+** main netlist
+*****************
+
+Vcp c 0 dc 3
+Vbp b 0 dc 1.2
+
+xq1 c b 0 0 {{device}}
+
+
+*****************
+** Analysis
+*****************
+
+.DC Vbp 0.2 1.2 0.01 Vcp 1 3 1
+.STEP TEMP {{temp}} -60 200
+.print DC FORMAT=CSV file=npn/simulated_Ic/{{i}}_simulated_{{device}}.csv Vbp
+.print DC FORMAT=CSV file=npn/simulated_Ic/{{i}}_simulated_{{device}}.csv {-I(Vcp)}
+.print DC FORMAT=CSV file=npn/simulated_Ib/{{i}}_simulated_{{device}}.csv Vbp
+.print DC FORMAT=CSV file=npn/simulated_Ib/{{i}}_simulated_{{device}}.csv {-I(Vbp)}
+
+
+.include "../../../design.xyce"
+.lib "../../../sm141064.xyce" bjt_typical
+
+.end
diff --git a/models/xyce/testing/regression/bjt_beta/device_netlists/pnp.spice b/models/xyce/testing/regression/bjt_beta/device_netlists/pnp.spice
new file mode 100644
index 0000000..f238b9c
--- /dev/null
+++ b/models/xyce/testing/regression/bjt_beta/device_netlists/pnp.spice
@@ -0,0 +1,26 @@
+*****************
+** main netlist
+*****************
+
+Vcp c 0 dc -3
+Vbp b 0 dc -1.2
+
+xq1 c b 0 {{device}}
+
+
+*****************
+** Analysis
+*****************
+
+.DC Vbp -0.2 -1.2 -0.01 Vcp -1 -3 -1
+.STEP TEMP {{temp}} -60 200
+.print DC FORMAT=CSV file=pnp/simulated_Ic/{{i}}_simulated_{{device}}.csv Vbp
+.print DC FORMAT=CSV file=pnp/simulated_Ic/{{i}}_simulated_{{device}}.csv {I(Vcp)}
+.print DC FORMAT=CSV file=pnp/simulated_Ib/{{i}}_simulated_{{device}}.csv Vbp
+.print DC FORMAT=CSV file=pnp/simulated_Ib/{{i}}_simulated_{{device}}.csv {I(Vbp)}
+
+
+.include "../../../design.xyce"
+.lib "../../../sm141064.xyce" bjt_typical
+
+.end
diff --git a/models/xyce/testing/regression/bjt_beta/device_netlists/run_npn_beta.spice b/models/xyce/testing/regression/bjt_beta/device_netlists/run_npn_beta.spice
new file mode 100644
index 0000000..60e160e
--- /dev/null
+++ b/models/xyce/testing/regression/bjt_beta/device_netlists/run_npn_beta.spice
@@ -0,0 +1,25 @@
+
+*****************
+** main netlist
+*****************
+
+Vcp c 0 dc 3
+Vbp b 0 dc 1.2
+
+xq1 c b 0 0 vnpn_10x10
+
+
+*****************
+** Analysis
+*****************
+.DC Vbp 0.2 1.2 0.01 Vcp 1 3 1
+.STEP TEMP 25 -60 200
+.print DC FORMAT=CSV file=result0.csv Vbp
+.print DC FORMAT=CSV file=result0.csv {-I(Vbp)}
+.print DC FORMAT=CSV file=result1.csv Vbp
+.print DC FORMAT=CSV file=result1.csv {-I(Vcp)}
+
+.include "../../../../design.xyce"
+.lib "../../../../sm141064.xyce" bjt_typical
+
+.end
diff --git a/models/xyce/testing/regression/bjt_beta/models_regression.py b/models/xyce/testing/regression/bjt_beta/models_regression.py
new file mode 100644
index 0000000..9bdc7cd
--- /dev/null
+++ b/models/xyce/testing/regression/bjt_beta/models_regression.py
@@ -0,0 +1,243 @@
+"""
+Usage:
+  models_regression.py [--num_cores=<num>]
+
+  -h, --help             Show help text.
+  -v, --version          Show version.
+  --num_cores=<num>      Number of cores to be used by simulator
+"""
+
+from cmath import inf
+from re import T
+from docopt import docopt
+import pandas as pd 
+import numpy as np
+import os 
+from jinja2 import Template
+import concurrent.futures
+import shutil
+import warnings
+warnings.simplefilter(action='ignore', category=FutureWarning)
+
+def call_simulator(file_name):
+    """Call simulation commands to perform simulation.
+    Args:
+        file_name (str): Netlist file name.
+    """
+    os.system(f"Xyce -hspice-ext all {file_name} -l {file_name}.log")
+
+def ext_measured(device,vb,step,Id_sim,list_devices,vc):
+
+    # Get dimensions used for each device 
+    dimensions = pd.read_csv(f"{device}/{device}.csv",usecols=["corners"])
+    loops = dimensions["corners"].count()
+
+    # Extracting measured values for each Device 
+    for i in range (loops):
+        k = i
+        if i >= len(list_devices):
+            while k >= len(list_devices):
+                k = k - len(list_devices)
+
+        # Special case for 1st measured values 
+        if i == 0 :
+            if device == "pnp":
+                temp_vb = vb
+                vb = "-vb "
+            # measured Id_sim 0
+            col_list = [f"{vb}",f"{vc}{step[0]}",f"{vc}{step[1]}",f"{vc}{step[2]}"]
+            df_measured = pd.read_csv(f"{device}/{device}.csv",usecols=col_list)
+            df_measured.columns = [f"{vb}",f"{vc}{step[0]}",f"{vc}{step[1]}",f"{vc}{step[2]}"]
+            df_measured.to_csv(f"{device}/measured_{Id_sim[0]}/{i}_measured_{list_devices[k]}.csv", index = False)
+
+            if device == "pnp":
+                vb = temp_vb
+
+            # measured Id_sim 1
+            col_list = [f"{vb}",f"{vc}{step[0]}.{2*i+1}",f"{vc}{step[1]}.{2*i+1}",f"{vc}{step[2]}.{2*i+1}"]
+            df_measured = pd.read_csv(f"{device}/{device}.csv",usecols=col_list)
+            df_measured.columns = [f"{vb}",f"{vc}{step[0]}",f"{vc}{step[1]}",f"{vc}{step[2]}"]        
+            df_measured.to_csv(f"{device}/measured_{Id_sim[1]}/{i}_measured_{list_devices[k]}.csv", index = False)
+        else:
+            # measured Id_sim 0
+            col_list = [f"{vb}",f"{vc}{step[0]}.{2*i}",f"{vc}{step[1]}.{2*i}",f"{vc}{step[2]}.{2*i}"]
+            df_measured = pd.read_csv(f"{device}/{device}.csv",usecols=col_list)
+            df_measured.columns = [f"{vb}",f"{vc}{step[0]}",f"{vc}{step[1]}",f"{vc}{step[2]}"]        
+            df_measured.to_csv(f"{device}/measured_{Id_sim[0]}/{i}_measured_{list_devices[k]}.csv", index = False)
+
+            # measured Id_sim 1
+            col_list = [f"{vb}",f"{vc}{step[0]}.{2*i+1}",f"{vc}{step[1]}.{2*i+1}",f"{vc}{step[2]}.{2*i+1}"]
+            df_measured = pd.read_csv(f"{device}/{device}.csv",usecols=col_list)
+            df_measured.columns = [f"{vb}",f"{vc}{step[0]}",f"{vc}{step[1]}",f"{vc}{step[2]}"]        
+            df_measured.to_csv(f"{device}/measured_{Id_sim[1]}/{i}_measured_{list_devices[k]}.csv", index = False)
+
+def ext_simulated(device,vc,step,sweep,Id_sim,list_devices,ib):
+
+    # Get dimensions used for each device 
+    dimensions = pd.read_csv(f"{device}/{device}.csv",usecols=["corners"])
+    loops = dimensions["corners"].count()
+    temp_range = int(loops/4) 
+    netlist_tmp = f"./device_netlists/{device}.spice"
+    for i in range (loops):
+        if i in range (0,temp_range):               temp = 25
+        elif i in range (temp_range,2*temp_range):  temp = -40
+        elif i in range (2*temp_range,3*temp_range):temp = 125
+        else:                                       temp = 175 
+
+        k = i
+        if i >= len(list_devices):
+            while k >= len(list_devices):
+                k = k - len(list_devices)
+
+        with open(netlist_tmp) as f:
+            tmpl = Template(f.read())
+            os.makedirs(f"{device}/{device}_netlists_sim",exist_ok=True)
+            with open(f"{device}/{device}_netlists_sim/{i}_{device}_netlist_{list_devices[k]}.spice", "w") as netlist:
+                netlist.write(tmpl.render(device = list_devices[k], i = i , temp = temp ))
+            netlist_path  = f"{device}/{device}_netlists_sim/{i}_{device}_netlist_{list_devices[k]}.spice" 
+
+            # Running ngspice for each netlist 
+            with concurrent.futures.ProcessPoolExecutor(max_workers=workers_count) as executor:
+                executor.submit(call_simulator, netlist_path)
+
+        # Writing simulated data 0
+        df_simulated = pd.read_csv(f"{device}/simulated_{Id_sim[0]}/{i}_simulated_{list_devices[k]}.csv",header=0)
+
+        # empty array to append in it shaped (sweep, number of trials + 1)
+        new_array = np.empty((sweep, 1+int(df_simulated.shape[0]/sweep)))  
+        new_array[:, 0] = df_simulated.iloc[:sweep, 0]
+        times = int(df_simulated.shape[0]/sweep)
+
+        for j in range(times):
+            new_array[:, (j+1)] = df_simulated.iloc[j*sweep:(j+1)*sweep, 1]
+
+        # Writing final simulated data 0
+        df_simulated = pd.DataFrame(new_array)
+        df_simulated.to_csv(f"{device}/simulated_{Id_sim[0]}/{i}_simulated_{list_devices[k]}.csv",index= False)    
+        df_simulated.columns = [f"{vc}",f"{ib}{step[0]}",f"{ib}{step[1]}",f"{ib}{step[2]}"]
+        df_simulated.to_csv(f"{device}/simulated_{Id_sim[0]}/{i}_simulated_{list_devices[k]}.csv",index= False)
+
+
+        # Writing simulated data 1
+        df_simulated = pd.read_csv(f"{device}/simulated_{Id_sim[1]}/{i}_simulated_{list_devices[k]}.csv",header=0)
+
+        # empty array to append in it shaped (sweep, number of trials + 1)
+        new_array = np.empty((sweep, 1+int(df_simulated.shape[0]/sweep)))  
+        new_array[:, 0] = df_simulated.iloc[:sweep, 0]
+        times = int(df_simulated.shape[0]/sweep)
+
+        for j in range(times):
+            new_array[:, (j+1)] = df_simulated.iloc[j*sweep:(j+1)*sweep, 1]
+
+        # Writing final simulated data 1
+        df_simulated = pd.DataFrame(new_array)
+        df_simulated.to_csv(f"{device}/simulated_{Id_sim[1]}/{i}_simulated_{list_devices[k]}.csv",index= False)    
+        df_simulated.columns = [f"{vc}",f"{ib}{step[0]}",f"{ib}{step[1]}",f"{ib}{step[2]}"]
+        df_simulated.to_csv(f"{device}/simulated_{Id_sim[1]}/{i}_simulated_{list_devices[k]}.csv",index= False)
+
+def error_cal(device,vb,step,Id_sim,list_devices,vc):
+
+    df_final = pd.DataFrame()
+    # Get dimensions used for each device 
+    dimensions = pd.read_csv(f"{device}/{device}.csv",usecols=["corners"])
+    loops = dimensions["corners"].count()
+    temp_range = int(loops/4) 
+    for i in range (loops):
+        if i in range (0,temp_range):               temp = 25
+        elif i in range (temp_range,2*temp_range):  temp = -40
+        elif i in range (2*temp_range,3*temp_range):temp = 125
+        else:                                       temp = 175 
+
+        k = i
+        if i >= len(list_devices):
+            while k >= len(list_devices):
+                k = k - len(list_devices)
+
+        measured  = pd.read_csv(f"{device}/measured_{Id_sim}/{i}_measured_{list_devices[k]}.csv")
+        simulated = pd.read_csv(f"{device}/simulated_{Id_sim}/{i}_simulated_{list_devices[k]}.csv")
+
+        error_1 = round (100 * abs((abs(measured.iloc[0:, 1]) - abs(simulated.iloc[0:, 1]))/abs(measured.iloc[:, 1])),6)
+        error_2 = round (100 * abs((abs(measured.iloc[0:, 2]) - abs(simulated.iloc[0:, 2]))/abs(measured.iloc[:, 2])),6)
+        error_3 = round (100 * abs((abs(measured.iloc[0:, 3]) - abs(simulated.iloc[0:, 3]))/abs(measured.iloc[:, 3])),6)
+
+        df_error = pd.DataFrame(data=[measured.iloc[:, 0],error_1,error_2,error_3]).transpose()
+        df_error.replace([np.inf, -np.inf], df_error.max().nlargest(2).iloc[1], inplace=True)
+        df_error.to_csv(f"{device}/error_{Id_sim}/{i}_{device}_error_{list_devices[k]}.csv",index= False)
+
+        # Mean error 
+        mean_error = (df_error[f"{vc}{step[0]}"].mean() + df_error[f"{vc}{step[1]}"].mean() + df_error[f"{vc}{step[2]}"].mean())/6
+        # Max error 
+        max_error = df_error[[f"{vc}{step[0]}",f"{vc}{step[1]}",f"{vc}{step[2]}"]].max().max()
+        # Max error location 
+        max_index = max((df_error == max_error).idxmax())
+        max_location_vc = (df_error == max_error).idxmax(axis=1)[max_index]
+        if Id_sim == "Ic":
+            if i == 0 :
+                if device == "pnp":
+                    temp_vb = vb
+                    vb = "-vb "
+            else:
+                if device == "pnp":
+                    vb = temp_vb
+        max_location_vb = df_error[f"{vb}"][max_index]
+
+        df_final_ = {'Run no.': f'{i}', 'Temp': f'{temp}', 'Device name': f'{device}', 'device': f'{list_devices[k]}','Simulated_Val':f'{Id_sim}','Mean error%':f'{"{:.2f}".format(mean_error)}', 'Max error%':f'{"{:.2f}".format(max_error)} @ {max_location_vc} & Vc (V) = {max_location_vb}'}
+        df_final = df_final.append(df_final_, ignore_index = True)
+
+    # Max mean error 
+    print (df_final)   
+    df_final.to_csv (f"{device}/Final_report_{Id_sim}.csv", index = False)
+    out_report = pd.read_csv (f"{device}/Final_report_{Id_sim}.csv")
+    print ("\n",f"Max. mean error = {out_report['Mean error%'].max()}%")    
+    print ("=====================================================================================================================================================")
+
+def main():
+
+    devices = ["npn","pnp"]
+    list_devices = [["vnpn_10x10" , "vnpn_5x5" , "vnpn_0p54x16" , "vnpn_0p54x8" , "vnpn_0p54x4", "vnpn_0p54x2"],
+                    ["vpnp_0p42x10" , "vpnp_0p42x5", "vpnp_10x10" , "vpnp_5x5"]]
+    vb = ["vbp ","-vb (V)"]
+    vc = ["vcp =","vc =-"]
+    Id_sim  = ["Ic","Ib"]
+    sweep = 101
+    step = [1, 2, 3]
+
+    for i, device in enumerate(devices): 
+        # Folder structure of measured values 
+        dirpath = f"{device}"
+        if os.path.exists(dirpath) and os.path.isdir(dirpath):
+            shutil.rmtree(dirpath)
+        os.makedirs(f"{device}/measured_{Id_sim[0]}",exist_ok=False)
+        os.makedirs(f"{device}/measured_{Id_sim[1]}",exist_ok=False)
+
+        # From xlsx to csv 
+        read_file = pd.read_excel (f"../../180MCU_SPICE_DATA/BJT/bjt_{device}_beta_f.nl_out.xlsx")
+        read_file.to_csv (f"{device}/{device}.csv", index = False, header=True)
+
+        # Folder structure of simulated values
+        os.makedirs(f"{device}/simulated_{Id_sim[0]}",exist_ok=False)
+        os.makedirs(f"{device}/error_{Id_sim[0]}",exist_ok=False)
+        os.makedirs(f"{device}/simulated_{Id_sim[1]}",exist_ok=False)
+        os.makedirs(f"{device}/error_{Id_sim[1]}",exist_ok=False)
+
+        # =========== Simulate ==============      
+        ext_measured (device,vb[i],step,Id_sim,list_devices[i],vc[i])
+
+        ext_simulated(device,vb[i],step,sweep,Id_sim,list_devices[i],vc[i])
+
+        # ============ Results ============= 
+        error_cal    (device,vb[i],step,Id_sim[0],list_devices[i],vc[i])
+        error_cal    (device,vb[i],step,Id_sim[1],list_devices[i],vc[i])
+
+# ================================================================
+# -------------------------- MAIN --------------------------------
+# ================================================================
+
+if __name__ == "__main__":
+
+    # Args
+    arguments     = docopt(__doc__, version='comparator: 0.1')
+    workers_count = os.cpu_count()*2 if arguments["--num_cores"] == None else int(arguments["--num_cores"])
+
+    # Calling main function 
+    main()
diff --git a/models/xyce/testing/regression/bjt_cj/device_netlists/cv.spice b/models/xyce/testing/regression/bjt_cj/device_netlists/cv.spice
new file mode 100644
index 0000000..92eed52
--- /dev/null
+++ b/models/xyce/testing/regression/bjt_cj/device_netlists/cv.spice
@@ -0,0 +1,28 @@
+*Xyce Common Source Circuit
+** library calling
+
+
+
+*****************
+** main netlist
+*****************
+.param volt = 0
+V1 in 0 dc {volt} ac 1
+{{Iopen}}
+
+R1 in out 1G
+xq1 {{connection}} {{device}}
+
+.meas AC freq when Vdb(out)=-3 PRECISION=15
+
+*****************
+** Analysis
+*****************
+.ac dec 10 1 10G
+.step volt 0 -3.0 -0.1
+.STEP TEMP {{temp}} -60 200
+
+.include "../../../../../design.xyce"
+.lib "../../../../../sm141064.xyce" bjt_{{corner}}
+
+.end
\ No newline at end of file
diff --git a/models/xyce/testing/regression/bjt_cj/device_netlists/run_npn_cv.spice b/models/xyce/testing/regression/bjt_cj/device_netlists/run_npn_cv.spice
new file mode 100644
index 0000000..3b6d488
--- /dev/null
+++ b/models/xyce/testing/regression/bjt_cj/device_netlists/run_npn_cv.spice
@@ -0,0 +1,28 @@
+*Xyce Common Source Circuit
+** library calling
+
+
+
+*****************
+** main netlist
+*****************
+.param volt = -3.0
+V1 in 0 dc {volt} ac 1
+*Iopen open 0 0
+
+R1 in out 1G
+xq1 0 out 0 0 vnpn_10x10
+
+.meas AC freq when Vdb(out)=-3 PRECISION=15
+
+*****************
+** Analysis
+*****************
+.ac dec 10 1 10G
+.STEP volt 0 -3.0 -0.1
+.STEP TEMP 25 -60 200
+
+.include "../../../../design.xyce"
+.lib "../../../../sm141064.xyce" bjt_typical
+
+.end
diff --git a/models/xyce/testing/regression/bjt_cj/device_netlists/run_pnp_cv.spice b/models/xyce/testing/regression/bjt_cj/device_netlists/run_pnp_cv.spice
new file mode 100644
index 0000000..d64aa7e
--- /dev/null
+++ b/models/xyce/testing/regression/bjt_cj/device_netlists/run_pnp_cv.spice
@@ -0,0 +1,28 @@
+*Xyce Common Source Circuit
+** library calling
+
+
+
+*****************
+** main netlist
+*****************
+.param volt = 0
+V1 in 0 dc {volt} ac 1
+* Iopen 0 open 0
+
+R1 in out 1G
+xq1 out 0 0 vpnp_0p42x10
+
+.meas AC freq when Vdb(out)=-3 PRECISION=15
+
+*****************
+** Analysis
+*****************
+.ac dec 10 1 10G
+.STEP volt 0 -3.0 -0.1
+* .STEP TEMP 25 -60 200
+
+.include "../../../../design.xyce"
+.lib "../../../../sm141064.xyce" bjt_typical
+
+.end
\ No newline at end of file
diff --git a/models/xyce/testing/regression/bjt_cj/models_regression.py b/models/xyce/testing/regression/bjt_cj/models_regression.py
new file mode 100644
index 0000000..3954d94
--- /dev/null
+++ b/models/xyce/testing/regression/bjt_cj/models_regression.py
@@ -0,0 +1,257 @@
+"""
+Usage:
+  models_regression.py [--num_cores=<num>]
+
+  -h, --help             Show help text.
+  -v, --version          Show version.
+  --num_cores=<num>      Number of cores to be used by simulator
+"""
+
+from re import T
+from docopt import docopt
+import pandas as pd 
+import numpy as np
+import os 
+from jinja2 import Template
+import concurrent.futures
+import shutil
+import warnings
+warnings.simplefilter(action='ignore', category=FutureWarning)
+
+def call_simulator(file_name):
+    """Call simulation commands to perform simulation.
+    Args:
+        file_name (str): Netlist file name.
+    """
+    os.system(f"Xyce -hspice-ext all {file_name} -l {file_name}.log")
+
+def ext_measured(device,vn,d_in, cv_sim, corner,start,dirpath):
+    
+    # Get dimensions used for each device 
+    if "vnpn" in device:
+        loops = 3
+    else:
+        loops = 2 
+        
+    # Extracting measured values for each W & L 
+    for i in range (start,loops+start):
+
+        # Special case for 1st measured values 
+        if i == 0 :
+            # measured Id
+            col_list = [f"{vn}",f"{d_in}_{corner}"]
+            df_measured = pd.read_csv(f"{dirpath}/{device}.csv",usecols=col_list)
+            df_measured.columns = [f"{vn}",f"{d_in}_{corner}"]
+            df_measured.to_csv(f"{dirpath}/measured_{cv_sim}/{i-start}_measured_{device}.csv", index = False)
+        else:
+            # measured Id
+            col_list = [f"{vn}",f"{d_in}_{corner}.{i}"]
+            df_measured = pd.read_csv(f"{dirpath}/{device}.csv",usecols=col_list)
+            df_measured.columns = [f"{vn}",f"{d_in}_{corner}"]        
+            df_measured.to_csv(f"{dirpath}/measured_{cv_sim}/{i-start}_measured_{device}.csv", index = False)
+
+def ext_simulated(device,vn,d_in,cv_sim, corner,temp,dirpath,cap):
+    
+    # Get dimensions used for each device 
+    netlist_tmp = f"./device_netlists/cv.spice"
+    
+    if "EBJ" in cap: 
+        i = 0
+        if "vnpn" in device:
+            connection = "0 out 0 0"
+        else:
+            connection = "0 0 out" 
+        Iopen = ""
+    elif "CBJ" in cap: 
+        i = 1
+        if "vnpn" in device:
+            connection = "0 out open 0"
+            Iopen = "Iopen open 0 0"
+        else:
+            connection = "out 0 0" 
+            Iopen = ""
+    else: 
+        i =2
+        connection = "0 0 open out"
+        Iopen = "Iopen open 0 0"
+    
+    with open(netlist_tmp) as f:
+        tmpl = Template(f.read())
+        os.makedirs(f"{dirpath}/{device}_netlists_{cv_sim}",exist_ok=True)
+        with open(f"{dirpath}/{device}_netlists_{cv_sim}/{i}_{device}_netlist_{device}.spice", "w") as netlist:
+            netlist.write(tmpl.render(device = device, i = i , Iopen = Iopen , connection = connection , temp = temp, cv_sim = cv_sim , corner = corner ))
+        netlist_path  = f"{dirpath}/{device}_netlists_{cv_sim}/{i}_{device}_netlist_{device}.spice" 
+        # Running ngspice for each netlist 
+        with concurrent.futures.ProcessPoolExecutor(max_workers=workers_count) as executor:
+            executor.submit(call_simulator, netlist_path)
+
+        # Writing simulated data 
+        df_simulated = []
+        # Writing simulated data 
+        for j in range(len([x for x in os.listdir(f"{dirpath}/{device}_netlists_{cv_sim}") if f"{i}_{device}_netlist_{device}.spice.ma" in x])):
+            with open(f"{dirpath}/{device}_netlists_{cv_sim}/{i}_{device}_netlist_{device}.spice.ma{j}") as f:
+                caps = 1000000/(float(next(f).replace("FREQ = ", ""))*2*np.pi)
+                df_simulated.append(caps) 
+        
+        # zero array to append in it shaped (vn_sweeps, number of trials + 1)
+        new_array = np.zeros((len(df_simulated), 2))
+        new_array[:len(df_simulated), 0] = df_simulated
+        new_array[:len(df_simulated), 1] = df_simulated
+
+        # Writing final simulated data                 
+        df_simulated = pd.DataFrame(new_array)
+        if "npn_EBJ" in cap:
+            df_cbj = pd.read_csv(f"{dirpath}/simulated_{cv_sim}/1_simulated_{device}.csv")
+            diff   = df_simulated.iloc[:, 1] - df_cbj.iloc[:, 1] 
+            df_simulated = pd.DataFrame(data=[df_simulated.iloc[:, 0],diff]).transpose()
+            df_simulated.columns = [f"{vn}",f"{d_in}_{corner}"]
+            df_simulated.to_csv(f"{dirpath}/simulated_{cv_sim}/{i}_simulated_{device}.csv",index= False)
+        elif "pnp_CBJ" in cap:
+            df_ebj = pd.read_csv(f"{dirpath}/simulated_{cv_sim}/0_simulated_{device}.csv")
+            diff   = df_simulated.iloc[:, 1] - (2*df_ebj.iloc[:, 1]) 
+            df_simulated = pd.DataFrame(data=[df_simulated.iloc[:, 0],diff]).transpose()
+            df_simulated.columns = [f"{vn}",f"{d_in}_{corner}"]
+            df_simulated.to_csv(f"{dirpath}/simulated_{cv_sim}/{i}_simulated_{device}.csv",index= False)
+        else:
+            df_simulated.columns = [f"{vn}",f"{d_in}_{corner}"]
+            df_simulated.to_csv(f"{dirpath}/simulated_{cv_sim}/{i}_simulated_{device}.csv",index= False)
+           
+
+def error_cal(device,vn,d_in,cv_sim, corner,temp,dirpath):
+    
+    # Get dimensions used for each device
+    if "vnpn" in device:
+        loops = 3
+    else:
+        loops = 2     
+    df_final = pd.DataFrame()
+    for i in range (0,loops):
+        if i == 0  : cap = "EBJ" 
+        elif i == 1 : cap = "CBJ"
+        else : cap = "CSJ"
+        
+        measured  = pd.read_csv(f"{dirpath}/measured_{cv_sim}/{i}_measured_{device}.csv")
+        simulated = pd.read_csv(f"{dirpath}/simulated_{cv_sim}/{i}_simulated_{device}.csv")
+
+        error_1 = round (100 * abs((abs(measured.iloc[:, 1]) - abs(simulated.iloc[:, 1]))/abs(measured.iloc[:, 1])),6)  
+
+        df_error = pd.DataFrame(data=[measured.iloc[:, 0],error_1]).transpose()        
+        df_error.to_csv(f"{dirpath}/error_{cv_sim}/{i}_{device}_error_{device}.csv",index= False)
+        
+        # Mean error 
+        mean_error = (df_error[f"{d_in}_{corner}"].mean())
+        # Max error 
+        max_error = df_error[f"{d_in}_{corner}"].max()
+        # Max error location 
+        max_index = max((df_error == max_error).idxmax())
+        max_location_vgs = (df_error == max_error).idxmax(axis=1)[max_index]
+        max_location_vds = df_error[f"{vn}"][max_index]
+
+        df_final_ = {'Run no.': f'{i}', 'Temp': f'{temp}', 'Device name': f'{device}', 'corner': f'{corner}' , 'Junction': f'{cap}', 'Simulated_Val':f'{cv_sim}','Mean error%':f'{"{:.2f}".format(mean_error)}', 'Max error%':f'{"{:.2f}".format(max_error)} @ {max_location_vgs} & vn (V) = {max_location_vds}'}
+        df_final = df_final.append(df_final_, ignore_index = True)
+    # Max mean error 
+    print (df_final)   
+    df_final.to_csv (f"{dirpath}/Final_report_{cv_sim}.csv", index = False)
+    out_report = pd.read_csv (f"{dirpath}/Final_report_{cv_sim}.csv")
+    print ("\n",f"Max. mean error = {out_report['Mean error%'].max()}%")    
+    print ("=====================================================================================================================================================")
+
+def main():
+
+    corners = ["typical","ff","ss"]
+    temps   = [ 25 , -40 , 175 ]
+    measure = ["cv","Vj", "bjt", 31]
+    cv_sim, bjt_vn, bjt_in = measure[0], measure[1], measure[2] 
+    
+    #vnpn
+    npn_devices = ["vnpn_10x10" , "vnpn_5x5" , "vnpn_0p54x16" , "vnpn_0p54x8" , "vnpn_0p54x4" , "vnpn_0p54x2"]
+    npn_start = 0 
+    
+    for corner in corners:
+        for temp in temps:
+            for device in npn_devices: 
+                # Folder structure of measured values
+                dirpath = f"{device}_{cv_sim}_{corner}_T{temp}"
+                if os.path.exists(dirpath) and os.path.isdir(dirpath):
+                    shutil.rmtree(dirpath)
+                os.makedirs(f"{dirpath}/measured_{cv_sim}",exist_ok=False)
+
+                # From xlsx to csv 
+                read_file = pd.read_excel (f"../../180MCU_SPICE_DATA/BJT/{bjt_in}_{cv_sim}_npn.nl_out.xlsx")
+                read_file.to_csv (f"{dirpath}/{device}.csv", index = False, header=True)
+
+                # Folder structure of simulated values 
+                os.makedirs(f"{dirpath}/simulated_{cv_sim}",exist_ok=False)
+                os.makedirs(f"{dirpath}/error_{cv_sim}",exist_ok=False)
+                ext_measured (device,bjt_vn,bjt_in, cv_sim, corner,npn_start,dirpath)
+                ext_simulated(device,bjt_vn,bjt_in,cv_sim, corner,temp,dirpath,"npn_CBJ")
+                ext_simulated(device,bjt_vn,bjt_in,cv_sim, corner,temp,dirpath,"npn_EBJ")
+                ext_simulated(device,bjt_vn,bjt_in,cv_sim, corner,temp,dirpath,"npn_CSJ")
+
+                npn_start = npn_start + 3
+        npn_start = 0
+
+    # vpnp
+    pnp_devices = ["vpnp_0p42x10" , "vpnp_0p42x5" , "vpnp_10x10" , "vpnp_5x5"]
+    pnp_start = 0 
+    
+    for corner in corners:
+        for temp in temps:
+            for device in pnp_devices: 
+                # Folder structure of measured values
+                dirpath = f"{device}_{cv_sim}_{corner}_T{temp}"
+                if os.path.exists(dirpath) and os.path.isdir(dirpath):
+                    shutil.rmtree(dirpath)
+                os.makedirs(f"{dirpath}/measured_{cv_sim}",exist_ok=False)
+
+                # From xlsx to csv 
+                read_file = pd.read_excel (f"../../180MCU_SPICE_DATA/BJT/{bjt_in}_{cv_sim}_pnp.nl_out.xlsx")
+                read_file.to_csv (f"{dirpath}/{device}.csv", index = False, header=True)
+
+                # Folder structure of simulated values 
+                os.makedirs(f"{dirpath}/simulated_{cv_sim}",exist_ok=False)
+                os.makedirs(f"{dirpath}/error_{cv_sim}",exist_ok=False)
+                ext_measured (device,bjt_vn,bjt_in, cv_sim, corner,pnp_start,dirpath)
+                ext_simulated(device,bjt_vn,bjt_in,cv_sim, corner,temp,dirpath,"pnp_EBJ")
+                ext_simulated(device,bjt_vn,bjt_in,cv_sim, corner,temp,dirpath,"pnp_CBJ")
+                error_cal    (device,bjt_vn,bjt_in,cv_sim, corner,temp,dirpath)
+                
+                pnp_start = pnp_start + 2
+        pnp_start = 0
+
+    for corner in corners:
+        for temp in temps:
+            for device in npn_devices: 
+                # Folder structure of measured values
+                dirpath = f"{device}_{cv_sim}_{corner}_T{temp}"
+                error_cal    (device,bjt_vn,bjt_in,cv_sim, corner,temp,dirpath)
+                
+                npn_start = npn_start + 3
+        npn_start = 0
+
+    # vpnp
+    pnp_devices = ["vpnp_0p42x10" , "vpnp_0p42x5" , "vpnp_10x10" , "vpnp_5x5"]
+    pnp_start = 0 
+    
+    for corner in corners:
+        for temp in temps:
+            for device in pnp_devices: 
+                # Folder structure of measured values
+                dirpath = f"{device}_{cv_sim}_{corner}_T{temp}"
+                error_cal    (device,bjt_vn,bjt_in,cv_sim, corner,temp,dirpath)
+                
+                pnp_start = pnp_start + 2
+        pnp_start = 0
+        
+# # ================================================================
+# -------------------------- MAIN --------------------------------
+# ================================================================
+        
+if __name__ == "__main__":
+    
+    # Args 
+    arguments     = docopt(__doc__, version='comparator: 0.1')
+    workers_count = os.cpu_count()*2 if arguments["--num_cores"] == None else int(arguments["--num_cores"])
+    
+    # Calling main function 
+    main()
diff --git a/models/xyce/testing/regression/bjt_iv/device_netlists/npn.spice b/models/xyce/testing/regression/bjt_iv/device_netlists/npn.spice
new file mode 100644
index 0000000..7bac45c
--- /dev/null
+++ b/models/xyce/testing/regression/bjt_iv/device_netlists/npn.spice
@@ -0,0 +1,26 @@
+*Xyce Common Source Circuit
+** library calling
+
+
+
+*****************
+** main netlist
+*****************
+
+Vcp c 0 dc 6
+Ib 0 b 9u
+
+xq1 c b 0 0 {{device}}
+
+
+*****************
+** Analysis
+*****************
+.DC Vcp 0 6 0.1 Ib 1u 9u 2u
+.STEP TEMP {{temp}} -60 200
+.print DC FORMAT=CSV file=npn/simulated_IcVc/{{i}}_simulated_{{device}}.csv {-I(Vcp)}
+
+.include "../../../../../design.xyce"
+.lib "../../../../../sm141064.xyce" bjt_typical
+
+.end
diff --git a/models/xyce/testing/regression/bjt_iv/device_netlists/pnp.spice b/models/xyce/testing/regression/bjt_iv/device_netlists/pnp.spice
new file mode 100644
index 0000000..76d695f
--- /dev/null
+++ b/models/xyce/testing/regression/bjt_iv/device_netlists/pnp.spice
@@ -0,0 +1,26 @@
+*Xyce Common Source Circuit
+** library calling
+
+
+
+*****************
+** main netlist
+*****************
+
+Vcp c 0 dc -6
+Ib 0 b -9u
+
+xq1 c b 0 {{device}}
+
+
+*****************
+** Analysis
+*****************
+.DC Vcp 0 -3 -0.1 Ib -1u -9u -2u
+.STEP TEMP {{temp}} -60 200
+.print DC FORMAT=CSV file=pnp/simulated_IcVc/{{i}}_simulated_{{device}}.csv {I(Vcp)}
+
+.include "../../../../../design.xyce"
+.lib "../../../../../sm141064.xyce" bjt_typical
+
+.end
diff --git a/models/xyce/testing/regression/bjt_iv/device_netlists/run_npn_vcic.spice b/models/xyce/testing/regression/bjt_iv/device_netlists/run_npn_vcic.spice
new file mode 100644
index 0000000..f76470a
--- /dev/null
+++ b/models/xyce/testing/regression/bjt_iv/device_netlists/run_npn_vcic.spice
@@ -0,0 +1,26 @@
+*Xyce Common Source Circuit
+** library calling
+
+
+
+*****************
+** main netlist
+*****************
+
+Vcp c 0 dc 6
+Ib 0 b 9u
+
+xq1 c b 0 0 vnpn_10x10
+
+
+*****************
+** Analysis
+*****************
+.DC Vcp 0 6 0.1 Ib 1u 9u 2u
+.STEP TEMP 25 -60 200
+.print DC FORMAT=CSV file=result.csv {-I(Vcp)}
+
+.include "../../design.xyce"
+.lib "../../sm141064.xyce" bjt_typical
+
+.end
diff --git a/models/xyce/testing/regression/bjt_iv/models_regression.py b/models/xyce/testing/regression/bjt_iv/models_regression.py
new file mode 100644
index 0000000..5fe2163
--- /dev/null
+++ b/models/xyce/testing/regression/bjt_iv/models_regression.py
@@ -0,0 +1,208 @@
+"""
+Usage:
+  models_regression.py [--num_cores=<num>]
+
+  -h, --help             Show help text.
+  -v, --version          Show version.
+  --num_cores=<num>      Number of cores to be used by simulator
+"""
+
+from re import T
+from docopt import docopt
+import pandas as pd 
+import numpy as np
+import os 
+from jinja2 import Template
+import concurrent.futures
+import shutil
+import warnings
+warnings.simplefilter(action='ignore', category=FutureWarning)
+
+def call_simulator(file_name):
+    """Call simulation commands to perform simulation.
+    Args:
+        file_name (str): Netlist file name.
+    """
+    os.system(f"Xyce -hspice-ext all {file_name} -l {file_name}.log")
+
+def ext_measured(device,vc,step,Id_sim,list_devices,ib):
+
+    # Get dimensions used for each device 
+    dimensions = pd.read_csv(f"{device}/{device}.csv",usecols=["corners"])
+    loops = dimensions["corners"].count()
+
+    # Extracting measured values for each Device 
+    for i in range (loops):
+        k = i
+        if i >= len(list_devices):
+            while k >= len(list_devices):
+                k = k - len(list_devices)
+
+        # Special case for 1st measured values 
+        if i == 0 :
+            if device == "pnp":
+                temp_vc = vc
+                vc = "-vc "
+            # measured Id_sim
+            col_list = [f"{vc}",f"{ib}{step[0]}",f"{ib}{step[1]}",f"{ib}{step[2]}",f"{ib}{step[3]}",f"{ib}{step[4]}"]
+            df_measured = pd.read_csv(f"{device}/{device}.csv",usecols=col_list)
+            df_measured.columns = [f"{vc}",f"{ib}{step[0]}",f"{ib}{step[1]}",f"{ib}{step[2]}",f"{ib}{step[3]}",f"{ib}{step[4]}"]
+            df_measured.to_csv(f"{device}/measured_{Id_sim}/{i}_measured_{list_devices[k]}.csv", index = False)
+        else:
+            if device == "pnp":
+                vc = temp_vc
+            # measured Id_sim
+            col_list = [f"{vc}",f"{ib}{step[0]}.{i}",f"{ib}{step[1]}.{i}",f"{ib}{step[2]}.{i}",f"{ib}{step[3]}.{i}",f"{ib}{step[4]}.{i}"]
+            df_measured = pd.read_csv(f"{device}/{device}.csv",usecols=col_list)
+            df_measured.columns = [f"{vc}",f"{ib}{step[0]}",f"{ib}{step[1]}",f"{ib}{step[2]}",f"{ib}{step[3]}",f"{ib}{step[4]}"]        
+            df_measured.to_csv(f"{device}/measured_{Id_sim}/{i}_measured_{list_devices[k]}.csv", index = False)
+
+def ext_simulated(device,vc,step,sweep,Id_sim,list_devices,ib):
+
+    # Get dimensions used for each device 
+    dimensions = pd.read_csv(f"{device}/{device}.csv",usecols=["corners"])
+    loops = dimensions["corners"].count()
+    temp_range = int(loops/4) 
+    netlist_tmp = f"./device_netlists/{device}.spice"
+    for i in range (loops):
+        if i in range (0,temp_range):               temp = 25
+        elif i in range (temp_range,2*temp_range):  temp = -40
+        elif i in range (2*temp_range,3*temp_range):temp = 125
+        else:                                       temp = 175 
+
+        k = i
+        if i >= len(list_devices):
+            while k >= len(list_devices):
+                k = k - len(list_devices)
+
+        with open(netlist_tmp) as f:
+            tmpl = Template(f.read())
+            os.makedirs(f"{device}/{device}_netlists_{Id_sim}",exist_ok=True)
+            with open(f"{device}/{device}_netlists_{Id_sim}/{i}_{device}_netlist_{list_devices[k]}.spice", "w") as netlist:
+                netlist.write(tmpl.render(device = list_devices[k], i = i , temp = temp ))
+            netlist_path  = f"{device}/{device}_netlists_{Id_sim}/{i}_{device}_netlist_{list_devices[k]}.spice" 
+
+            # Running Xyce for each netlist 
+            with concurrent.futures.ProcessPoolExecutor(max_workers=workers_count) as executor:
+                executor.submit(call_simulator, netlist_path)
+
+            # Writing simulated data 
+            df_simulated = pd.read_csv(f"{device}/simulated_{Id_sim}/{i}_simulated_{list_devices[k]}.csv",header=0)   
+
+            # empty array to append in it shaped (sweep, number of trials + 1)
+            new_array = np.empty((sweep, 1+int(df_simulated.shape[0]/sweep)))  
+            new_array[:, 0] = df_simulated.iloc[:sweep, 0]
+            times = int(df_simulated.shape[0]/sweep)
+
+            for j in range(times):
+                new_array[:, (j+1)] = df_simulated.iloc[j*sweep:(j+1)*sweep, 0]
+
+            # Writing final simulated data                 
+            df_simulated = pd.DataFrame(new_array)
+            df_simulated.to_csv(f"{device}/simulated_{Id_sim}/{i}_simulated_{list_devices[k]}.csv",index= False)    
+            df_simulated.columns = [f"{vc}",f"{ib}{step[0]}",f"{ib}{step[1]}",f"{ib}{step[2]}",f"{ib}{step[3]}",f"{ib}{step[4]}"]
+            df_simulated.to_csv(f"{device}/simulated_{Id_sim}/{i}_simulated_{list_devices[k]}.csv",index= False)
+
+def error_cal(device,vc,step,Id_sim,list_devices,ib):
+
+    df_final = pd.DataFrame()
+    # Get dimensions used for each device 
+    dimensions = pd.read_csv(f"{device}/{device}.csv",usecols=["corners"])
+    loops = dimensions["corners"].count()
+    temp_range = int(loops/4) 
+    for i in range (loops):
+        if i in range (0,temp_range):               temp = 25
+        elif i in range (temp_range,2*temp_range):  temp = -40
+        elif i in range (2*temp_range,3*temp_range):temp = 125
+        else:                                       temp = 175 
+
+        k = i
+        if i >= len(list_devices):
+            while k >= len(list_devices):
+                k = k - len(list_devices)
+
+        measured  = pd.read_csv(f"{device}/measured_{Id_sim}/{i}_measured_{list_devices[k]}.csv")
+        simulated = pd.read_csv(f"{device}/simulated_{Id_sim}/{i}_simulated_{list_devices[k]}.csv")
+
+        error_1 = round (100 * abs((abs(measured.iloc[0:, 1]) - abs(simulated.iloc[0:, 1]))/abs(measured.iloc[:, 1])),6)  
+        error_2 = round (100 * abs((abs(measured.iloc[0:, 2]) - abs(simulated.iloc[0:, 2]))/abs(measured.iloc[:, 2])),6)
+        error_3 = round (100 * abs((abs(measured.iloc[0:, 3]) - abs(simulated.iloc[0:, 3]))/abs(measured.iloc[:, 3])),6) 
+        error_4 = round (100 * abs((abs(measured.iloc[0:, 4]) - abs(simulated.iloc[0:, 4]))/abs(measured.iloc[:, 4])),6) 
+        error_5 = round (100 * abs((abs(measured.iloc[0:, 5]) - abs(simulated.iloc[0:, 5]))/abs(measured.iloc[:, 5])),6)
+
+        df_error = pd.DataFrame(data=[measured.iloc[:, 0],error_1,error_2,error_3,error_4,error_5]).transpose()        
+        df_error.to_csv(f"{device}/error_{Id_sim}/{i}_{device}_error_{list_devices[k]}.csv",index= False)
+
+        # Mean error 
+        mean_error = (df_error[f"{ib}{step[0]}"].mean() + df_error[f"{ib}{step[1]}"].mean() + df_error[f"{ib}{step[2]}"].mean() + 
+                      df_error[f"{ib}{step[3]}"].mean() + df_error[f"{ib}{step[4]}"].mean())/6
+        # Max error 
+        max_error = df_error[[f"{ib}{step[0]}",f"{ib}{step[1]}",f"{ib}{step[2]}",f"{ib}{step[3]}",f"{ib}{step[4]}"]].max().max()
+        # Max error location 
+        max_index = max((df_error == max_error).idxmax())
+        max_location_ib = (df_error == max_error).idxmax(axis=1)[max_index]
+        if i == 0 :
+            if device == "pnp":
+                temp_vc = vc
+                vc = "-vc "
+        else:
+            if device == "pnp":
+                vc = temp_vc
+        max_location_vc = df_error[f"{vc}"][max_index]
+
+        df_final_ = {'Run no.': f'{i}', 'Temp': f'{temp}', 'Device name': f'{device}', 'device': f'{list_devices[k]}','Simulated_Val':f'{Id_sim}','Mean error%':f'{"{:.2f}".format(mean_error)}', 'Max error%':f'{"{:.2f}".format(max_error)} @ {max_location_ib} & Vc (V) = {max_location_vc}'}
+        df_final = df_final.append(df_final_, ignore_index = True)
+
+    # Max mean error 
+    print (df_final)   
+    df_final.to_csv (f"{device}/Final_report_{Id_sim}.csv", index = False)
+    out_report = pd.read_csv (f"{device}/Final_report_{Id_sim}.csv")
+    print ("\n",f"Max. mean error = {out_report['Mean error%'].max()}%")    
+    print ("=====================================================================================================================================================")
+
+def main():
+
+    devices = ["npn","pnp"]
+    list_devices = [["vnpn_10x10" , "vnpn_5x5" , "vnpn_0p54x16" , "vnpn_0p54x8" , "vnpn_0p54x4", "vnpn_0p54x2"],
+                    ["vpnp_0p42x10" , "vpnp_0p42x5", "vpnp_10x10" , "vpnp_5x5"]]
+    vc = ["vcp ","-vc (A)"]
+    ib = ["ibp =","ib =-"]
+    Id_sim  = "IcVc"
+    sweep = [61,31] 
+    step = [ "1.000E-06" ,  "3.000E-06" ,  "5.000E-06" ,  "7.000E-06" ,  "9.000E-06"] 
+
+    for i, device in enumerate(devices): 
+        # Folder structure of measured values 
+        dirpath = f"{device}"
+        if os.path.exists(dirpath) and os.path.isdir(dirpath):
+            shutil.rmtree(dirpath)
+        os.makedirs(f"{device}/measured_{Id_sim}",exist_ok=False)
+
+        # From xlsx to csv 
+        read_file = pd.read_excel (f"../../180MCU_SPICE_DATA/BJT/bjt_{device}_icvc_f.nl_out.xlsx")
+        read_file.to_csv (f"{device}/{device}.csv", index = False, header=True)
+
+        # Folder structure of simulated values 
+        os.makedirs(f"{device}/simulated_{Id_sim}",exist_ok=False)
+        os.makedirs(f"{device}/error_{Id_sim}",exist_ok=False)
+
+        # =========== Simulate ==============      
+        ext_measured (device,vc[i],step,Id_sim,list_devices[i],ib[i])
+
+        ext_simulated(device,vc[i],step,sweep[i],Id_sim,list_devices[i],ib[i])
+
+        # ============ Results ============= 
+        error_cal    (device,vc[i],step,Id_sim,list_devices[i],ib[i])
+
+# ================================================================
+# -------------------------- MAIN --------------------------------
+# ================================================================
+
+if __name__ == "__main__":
+
+    # Args
+    arguments     = docopt(__doc__, version='comparator: 0.1')
+    workers_count = os.cpu_count()*2 if arguments["--num_cores"] == None else int(arguments["--num_cores"])
+
+    # Calling main function 
+    main()
diff --git a/models/xyce/testing/regression/diode/device_netlists/cv.spice b/models/xyce/testing/regression/diode/device_netlists/cv.spice
new file mode 100644
index 0000000..d5797e8
--- /dev/null
+++ b/models/xyce/testing/regression/diode/device_netlists/cv.spice
@@ -0,0 +1,28 @@
+*Xyce Common Source Circuit
+** library calling
+
+
+*****************
+** main netlist
+*****************
+.param volt = -3.3
+V1 in 0 dc {volt} ac 1
+R1 in out 1G
+dn1 out 0 np_3p3 AREA={10u*10u}
+
+.meas AC freq when Vdb(out)=-3
+*.meas AC C param = {1/(2*3.141592653589793238*freq*1000000000)}
+
+*****************
+** Analysis
+*****************
+*.control
+.ac dec 10 1 10G
+.step volt -12.13 1.13 0.13
+
+.include "../../design.xyce"
+.lib "../../sm141064.xyce" diode_typical
+
+.end
+
+
diff --git a/models/xyce/testing/regression/diode/device_netlists/iv.spice b/models/xyce/testing/regression/diode/device_netlists/iv.spice
new file mode 100644
index 0000000..2ed78b2
--- /dev/null
+++ b/models/xyce/testing/regression/diode/device_netlists/iv.spice
@@ -0,0 +1,28 @@
+*Xyce Common Source Circuit
+** library calling
+
+
+*****************
+** main netlist
+*****************
+Vn n 0 dc 1
+
+
+dn1 n 0 {{device}} AREA={{area}}p
+* PJ=40u
+
+
+*****************
+** Analysis
+*****************
+.DC Vn -12.13 1.13 0.13
+.STEP TEMP {{temp}} -60 200
+.print DC FORMAT=CSV file={{device}}_{{Id_sim}}_{{corner}}/simulated_{{Id_sim}}/{{i}}_simulated_A{{area}}_P{{pj}}.csv {abs(I(dn1))}
+* .print DC FORMAT=CSV file=result.csv {N(dn1:is)}
+
+
+
+.include "../../../../../design.xyce"
+.lib "../../../../../sm141064.xyce" diode_{{corner}}
+
+.end
\ No newline at end of file
diff --git a/models/xyce/testing/regression/diode/device_netlists/run_np_3p3_iv_independently.spice b/models/xyce/testing/regression/diode/device_netlists/run_np_3p3_iv_independently.spice
new file mode 100644
index 0000000..62580c1
--- /dev/null
+++ b/models/xyce/testing/regression/diode/device_netlists/run_np_3p3_iv_independently.spice
@@ -0,0 +1,28 @@
+*Xyce Common Source Circuit
+** library calling
+
+
+*****************
+** main netlist
+*****************
+Vn n 0 dc 1
+
+
+dn1 n 0 sc_diode AREA={10u*10u}
+* PJ=40u
+
+
+*****************
+** Analysis
+*****************
+.DC Vn -12.13 1.13 0.13
+.STEP TEMP LIST -40 25 125 175
+.print DC FORMAT=CSV file=result.csv {abs(I(dn1))}
+* .print DC FORMAT=CSV file=result.csv {N(dn1:is)}
+
+
+
+.include "../../../../design.xyce"
+.lib "../../../../sm141064.xyce" diode_typical
+
+.end
diff --git a/models/xyce/testing/regression/diode/models_regression.py b/models/xyce/testing/regression/diode/models_regression.py
new file mode 100644
index 0000000..983702e
--- /dev/null
+++ b/models/xyce/testing/regression/diode/models_regression.py
@@ -0,0 +1,187 @@
+"""
+Usage:
+  models_regression.py [--num_cores=<num>]
+
+  -h, --help             Show help text.
+  -v, --version          Show version.
+  --num_cores=<num>      Number of cores to be used by simulator
+"""
+
+from re import T
+from docopt import docopt
+import pandas as pd 
+import numpy as np
+import os 
+from jinja2 import Template
+import concurrent.futures
+import shutil
+import warnings
+warnings.simplefilter(action='ignore', category=FutureWarning)
+
+def call_simulator(file_name):
+    """Call simulation commands to perform simulation.
+    Args:
+        file_name (str): Netlist file name.
+    """
+    os.system(f"Xyce -hspice-ext all {file_name} -l {file_name}.log")
+
+def ext_measured(device,vn,d_in, Id_sim, corner):
+    
+    # Get dimensions used for each device 
+    dirpath = f"{device}_{Id_sim}_{corner}"
+    dimensions = pd.read_csv(f"{dirpath}/{device}.csv",usecols=["W (um)" , "L (um)"])
+    loops = dimensions["L (um)"].count()
+    
+    # Extracting measured values for each W & L 
+    for i in range (0,loops):
+        width  = dimensions["W (um)"].iloc[i]
+        length = dimensions["L (um)"].iloc[i]
+        
+        # Special case for 1st measured values 
+        if i == 0 :
+            # measured Id
+            col_list = [f"{vn}",f"{d_in}_{corner}"]
+            df_measured = pd.read_csv(f"{dirpath}/{device}.csv",usecols=col_list)
+            df_measured.columns = [f"{vn}",f"{d_in}_{corner}"]
+            df_measured.to_csv(f"{dirpath}/measured_{Id_sim}/{i}_measured_A{width}_P{length}.csv", index = False)
+        else:
+            # measured Id
+            col_list = [f"{vn}",f"{d_in}_{corner}.{i}"]
+            df_measured = pd.read_csv(f"{dirpath}/{device}.csv",usecols=col_list)
+            df_measured.columns = [f"{vn}",f"{d_in}_{corner}"]        
+            df_measured.to_csv(f"{dirpath}/measured_{Id_sim}/{i}_measured_A{width}_P{length}.csv", index = False)
+
+def ext_simulated(device,vn,d_in,vn_sweeps,Id_sim, corner):
+    
+    # Get dimensions used for each device 
+    dirpath = f"{device}_{Id_sim}_{corner}"
+    dimensions = pd.read_csv(f"{dirpath}/{device}.csv",usecols=["W (um)" , "L (um)"])
+    loops = dimensions["L (um)"].count()
+    netlist_tmp = f"./device_netlists/{Id_sim}.spice"
+    for i in range (0,loops):
+        width  = dimensions["W (um)"].iloc[int(i)]
+        length = dimensions["L (um)"].iloc[int(i)]
+
+        if i % 4 == 0: temp = -40 
+        elif i % 4 == 1: temp = 25 
+        elif i % 4 == 2: temp = 125
+        else:
+            temp = 175 
+        with open(netlist_tmp) as f:
+            tmpl = Template(f.read())
+            os.makedirs(f"{dirpath}/{device}_netlists_{Id_sim}",exist_ok=True)
+            with open(f"{dirpath}/{device}_netlists_{Id_sim}/{i}_{device}_netlist_A{width}_P{length}.spice", "w") as netlist:
+                netlist.write(tmpl.render(device = device, area = width, pj = length, i = i , temp = temp, Id_sim = Id_sim , corner = corner ))
+            netlist_path  = f"{dirpath}/{device}_netlists_{Id_sim}/{i}_{device}_netlist_A{width}_P{length}.spice" 
+            # Running ngspice for each netlist 
+            with concurrent.futures.ProcessPoolExecutor(max_workers=workers_count) as executor:
+                executor.submit(call_simulator, netlist_path)
+            
+            # Writing simulated data 
+            df_simulated = pd.read_csv(f"{dirpath}/simulated_{Id_sim}/{i}_simulated_A{width}_P{length}.csv",header=0)
+            #df_simulated.to_csv(f"{dirpath}/simulated_{Id_sim}/{i}_simulated_A{width}_P{length}.csv",index= False)    
+            
+            # zero array to append in it shaped (vn_sweeps, number of trials + 1)
+            new_array = np.zeros((vn_sweeps, 2))
+            new_array[:len(df_simulated.index), 0] = df_simulated.iloc[:, 0]
+            
+            new_array[:len(df_simulated.index), 1] = df_simulated.iloc[:, 0]
+                
+            # Writing final simulated data                 
+            df_simulated = pd.DataFrame(new_array)
+            df_simulated.to_csv(f"{dirpath}/simulated_{Id_sim}/{i}_simulated_A{width}_P{length}.csv",index= False)    
+            df_simulated.columns = [f"{vn}",f"{d_in}_{corner}"]
+            df_simulated.to_csv(f"{dirpath}/simulated_{Id_sim}/{i}_simulated_A{width}_P{length}.csv",index= False)    
+
+def error_cal(device,vn,d_in,Id_sim, corner):
+    
+    # Get dimensions used for each device 
+    dirpath = f"{device}_{Id_sim}_{corner}"
+    dimensions = pd.read_csv(f"{dirpath}/{device}.csv",usecols=["W (um)" , "L (um)"])
+    loops = dimensions["L (um)"].count()    
+    df_final = pd.DataFrame()
+    for i in range (0,loops):  
+        width  = dimensions["W (um)"].iloc[int(i)]
+        length = dimensions["L (um)"].iloc[int(i)]
+        if i % 4 == 0: temp = -40 
+        elif i % 4 == 1: temp = 25 
+        elif i % 4 == 2: temp = 125
+        else:
+            temp = 175 
+             
+        measured  = pd.read_csv(f"{dirpath}/measured_{Id_sim}/{i}_measured_A{width}_P{length}.csv")
+        simulated = pd.read_csv(f"{dirpath}/simulated_{Id_sim}/{i}_simulated_A{width}_P{length}.csv")
+
+        error_1 = round (100 * abs((abs(measured.iloc[:, 1]) - abs(simulated.iloc[:, 1]))/abs(measured.iloc[:, 1])),6)  
+
+        df_error = pd.DataFrame(data=[measured.iloc[:, 0],error_1]).transpose()        
+        df_error.to_csv(f"{dirpath}/error_{Id_sim}/{i}_{device}_error_A{width}_P{length}.csv",index= False)
+        
+        # Mean error 
+        mean_error = (df_error[f"{d_in}_{corner}"].mean())/6
+        # Max error 
+        max_error = df_error[f"{d_in}_{corner}"].max()
+        # Max error location 
+        max_index = max((df_error == max_error).idxmax())
+        max_location_vgs = (df_error == max_error).idxmax(axis=1)[max_index]
+        max_location_vds = df_error[f"{vn}"][max_index]
+
+        df_final_ = {'Run no.': f'{i}', 'Temp': f'{temp}', 'Device name': f'{dirpath}', 'Area': f'{width}', 'Perimeter': f'{length}', 'Simulated_Val':f'{Id_sim}','Mean error%':f'{"{:.2f}".format(mean_error)}', 'Max error%':f'{"{:.2f}".format(max_error)} @ {max_location_vgs} & vn (V) = {max_location_vds}'}
+        df_final = df_final.append(df_final_, ignore_index = True)
+    # Max mean error 
+    print (df_final)   
+    df_final.to_csv (f"{dirpath}/Final_report_{Id_sim}.csv", index = False)
+    out_report = pd.read_csv (f"{dirpath}/Final_report_{Id_sim}.csv")
+    print ("\n",f"Max. mean error = {out_report['Mean error%'].max()}%")    
+    print ("=====================================================================================================================================================")
+
+def main():
+        
+    devices = ["np_3p3","dnwpw","dnwps","np_6p0", "nwp_3p3","nwp_6p0","pn_3p3","pn_6p0","sc_diode"]
+    corners = ["typical","ff","ss"]
+    measures = [["iv","Vn1 (V)", " |In1(A)| diode", 103]]#,
+                # ["cv","Vj", "diode", 17]]
+
+    for device in devices: 
+        for measure in measures:
+            for corner in corners: 
+                # Folder structure of measured values
+                Id_sim, diode_vn, diode_in, no_of_vn_sweeps = measure[0], measure[1], measure[2], measure[3] 
+                dirpath = f"{device}_{Id_sim}_{corner}"
+                if os.path.exists(dirpath) and os.path.isdir(dirpath):
+                    shutil.rmtree(dirpath)
+                os.makedirs(f"{dirpath}/measured_{Id_sim}",exist_ok=False)
+
+                # From xlsx to csv 
+                read_file = pd.read_excel (f"../../180MCU_SPICE_DATA/Diode/{device}_{Id_sim}.nl_out.xlsx")
+                read_file.to_csv (f"{dirpath}/{device}.csv", index = False, header=True)
+
+                # Folder structure of simulated values 
+                os.makedirs(f"{dirpath}/simulated_{Id_sim}",exist_ok=False)
+                os.makedirs(f"{dirpath}/error_{Id_sim}",exist_ok=False)
+        
+                ext_measured (device,diode_vn,diode_in, Id_sim, corner)
+
+                ext_simulated(device,diode_vn,diode_in,no_of_vn_sweeps,Id_sim, corner)
+                
+    for device in devices: 
+        for measure in measures:
+            for corner in corners: 
+                # Folder structure of measured values
+                Id_sim, diode_vn, diode_in, no_of_vn_sweeps = measure[0], measure[1], measure[2], measure[3] 
+                error_cal    (device,diode_vn,diode_in,Id_sim, corner)
+
+
+    
+# ================================================================
+# -------------------------- MAIN --------------------------------
+# ================================================================
+        
+if __name__ == "__main__":
+    
+    # Args 
+    arguments     = docopt(__doc__, version='comparator: 0.1')
+    workers_count = os.cpu_count()*2 if arguments["--num_cores"] == None else int(arguments["--num_cores"])
+    
+    # Calling main function 
+    main()
diff --git a/models/xyce/testing/regression/mimcap_c/device_netlists/mimcap.spice b/models/xyce/testing/regression/mimcap_c/device_netlists/mimcap.spice
new file mode 100644
index 0000000..491a56f
--- /dev/null
+++ b/models/xyce/testing/regression/mimcap_c/device_netlists/mimcap.spice
@@ -0,0 +1,30 @@
+*Xyce Common Source Circuit
+** library calling
+
+
+*****************
+** main netlist
+*****************
+.param volt = -3.0
+V1 in 0 dc {volt} ac 1
+R1 in out 1G
+xcn out 0 {{device}} c_length={{length}}u c_width={{width}}u l={{length}}u w={{width}}u
+
+.meas AC freq when Vdb(out)=-3 PRECISION=15
+
+
+
+
+*****************
+** Analysis
+*****************
+
+.ac dec 10 1 10G
+.step volt {{voltage}}
+
+.include "../../../../../design.xyce"
+.lib "../../../../../sm141064.xyce" mimcap_{{corner}}
+
+.end
+
+
diff --git a/models/xyce/testing/regression/mimcap_c/models_regression.py b/models/xyce/testing/regression/mimcap_c/models_regression.py
new file mode 100644
index 0000000..625e5ac
--- /dev/null
+++ b/models/xyce/testing/regression/mimcap_c/models_regression.py
@@ -0,0 +1,181 @@
+"""
+Usage:
+  models_regression.py [--num_cores=<num>]
+
+  -h, --help             Show help text.
+  -v, --version          Show version.
+  --num_cores=<num>      Number of cores to be used by simulator
+"""
+
+from re import T
+from docopt import docopt
+import pandas as pd 
+import numpy as np
+import os 
+from jinja2 import Template
+import concurrent.futures
+import shutil
+import warnings
+warnings.simplefilter(action='ignore', category=FutureWarning)
+
+def call_simulator(file_name):
+    """Call simulation commands to perform simulation.
+    Args:
+        file_name (str): Netlist file name.
+    """
+    os.system(f"Xyce -hspice-ext all {file_name} -l {file_name}.log")
+
+def ext_measured(device,vn,d_in, cv_sim, corner,start):
+    
+    # Get dimensions used for each device 
+    dirpath = f"{device}_{cv_sim}_{corner}"
+    
+    # Extracting measured values for each W & L 
+    for i in range (start,4+start):
+        if i == 0+start: width  = 100 ; length = 100
+        if i == 1+start: width  = 5   ; length = 5
+        if i == 2+start: width  = 100 ; length = 5
+        if i == 3+start: width  = 5   ; length = 100
+
+        if i == 0 :                       
+            # measured cv
+            col_list = [f"Vj",f"mimcap_{corner}"]
+            df_measured = pd.read_csv(f"{dirpath}/{device}.csv",usecols=col_list)
+            df_measured.to_csv(f"{dirpath}/measured_{cv_sim}/{i-start}_measured_w{width}_l{length}.csv", index=False)
+        else:
+            # measured cv
+            col_list = [f"Vj",f"mimcap_{corner}.{i}"]
+            df_measured = pd.read_csv(f"{dirpath}/{device}.csv",usecols=col_list)
+            df_measured.columns = [f"Vj",f"mimcap_{corner}"]
+            df_measured.to_csv(f"{dirpath}/measured_{cv_sim}/{i-start}_measured_w{width}_l{length}.csv", index=False)
+
+def ext_simulated(device,vn,d_in,cv_sim, corner,start,voltage):
+    
+    # Get dimensions used for each device 
+    dirpath = f"{device}_{cv_sim}_{corner}"
+    netlist_tmp = f"./device_netlists/mimcap.spice"
+    
+    # Extracting measured values for each W & L 
+    for i in range (start,4+start):
+        if i == 0+start: width  = 100 ; length = 100
+        if i == 1+start: width  = 5   ; length = 5
+        if i == 2+start: width  = 100 ; length = 5
+        if i == 3+start: width  = 5   ; length = 100
+    
+        with open(netlist_tmp) as f:
+            tmpl = Template(f.read())
+            os.makedirs(f"{dirpath}/{device}_netlists_{cv_sim}",exist_ok=True)
+            with open(f"{dirpath}/{device}_netlists_{cv_sim}/{i-start}_{device}_netlist_w{width}_l{length}.spice", "w") as netlist:
+                netlist.write(tmpl.render(device = device, width = width, length = length , corner = corner , voltage = voltage))
+            netlist_path  = f"{dirpath}/{device}_netlists_{cv_sim}/{i-start}_{device}_netlist_w{width}_l{length}.spice" 
+            # Running ngspice for each netlist 
+            with concurrent.futures.ProcessPoolExecutor(max_workers=workers_count) as executor:
+                executor.submit(call_simulator, netlist_path)
+            
+        # Writing simulated data 
+        df_simulated = []
+        # Writing simulated data 
+        for j in range(len([x for x in os.listdir(f"{dirpath}/{device}_netlists_{cv_sim}") if f"{i-start}_{device}_netlist_w{width}_l{length}.spice.ma" in x])):
+            with open(f"{dirpath}/{device}_netlists_{cv_sim}/{i-start}_{device}_netlist_w{width}_l{length}.spice.ma{j}") as f:
+                cap = 1000000/(float(next(f).replace("FREQ = ", ""))*2*np.pi)
+                df_simulated.append(cap) 
+        
+        # zero array to append in it shaped (vn_sweeps, number of trials + 1)
+        new_array = np.zeros((len(df_simulated), 2))
+        new_array[:len(df_simulated), 0] = df_simulated
+        new_array[:len(df_simulated), 1] = df_simulated
+
+        # Writing final simulated data                 
+        df_simulated = pd.DataFrame(new_array)   
+        df_simulated.columns = [f"Vj",f"mimcap_{corner}"]
+        df_simulated.to_csv(f"{dirpath}/simulated_{cv_sim}/{i-start}_simulated_w{width}_l{length}.csv",index= False)     
+            
+def error_cal(device,vn,d_in,Id_sim, corner,start):
+    
+    # Get dimensions used for each device 
+    dirpath = f"{device}_{Id_sim}_{corner}"
+    df_final = pd.DataFrame()
+    for i in range (start,4+start):
+        if i == 0+start: width  = 100 ; length = 100
+        if i == 1+start: width  = 5   ; length = 5
+        if i == 2+start: width  = 100 ; length = 5
+        if i == 3+start: width  = 5   ; length = 100
+             
+        measured  = pd.read_csv(f"{dirpath}/measured_{Id_sim}/{i-start}_measured_w{width}_l{length}.csv")
+        simulated = pd.read_csv(f"{dirpath}/simulated_{Id_sim}/{i-start}_simulated_w{width}_l{length}.csv")
+
+        error_1 = round (100 * abs((abs(measured.iloc[:, 1]) - abs(simulated.iloc[:, 1]))/abs(measured.iloc[:, 1])),8)  
+
+        df_error = pd.DataFrame(data=[measured.iloc[:, 0],error_1]).transpose()        
+        df_error.to_csv(f"{dirpath}/error_{Id_sim}/{i-start}_{device}_error_w{width}_l{length}.csv",index= False)
+        
+        # Mean error 
+        mean_error = (df_error[f"mimcap_{corner}"].mean())
+        # Max error 
+        max_error = df_error[f"mimcap_{corner}"].max()
+
+        df_final_ = {'Run no.': f'{i-start}', 'Device name': f'{dirpath}', 'Width': f'{width}', 'Length': f'{length}', 'Simulated_Val':f'{Id_sim}','Mean error%':f'{"{:.2f}".format(mean_error)}', 'Max error%':f'{"{:.2f}".format(max_error)} '}
+        df_final = df_final.append(df_final_, ignore_index = True)
+    
+    # Max mean error 
+    print (df_final)   
+    df_final.to_csv (f"{dirpath}/Final_report_{Id_sim}.csv", index = False)
+    out_report = pd.read_csv (f"{dirpath}/Final_report_{Id_sim}.csv")
+    print ("\n",f"Max. mean error = {out_report['Mean error%'].max()}%")    
+    print ("=====================================================================================================================================================")
+
+
+def main():
+
+    # 3p3
+    corners = ["ss" , "typical","ff"]        
+    devices = ["mim_1p5fF" , "mim_1p0fF" , "mim_2p0fF"]
+    measure = ["cv","corners", "CV (fF)"]
+    voltage = ["-3.0 3.0 0.1"]
+    start = 0
+    for corner in corners: 
+        for device in devices: 
+            # Folder structure of measured values
+            cv_sim, cap_vn, cap_in = measure[0], measure[1], measure[2]
+            dirpath = f"{device}_{cv_sim}_{corner}"
+            if os.path.exists(dirpath) and os.path.isdir(dirpath):
+                shutil.rmtree(dirpath)
+            os.makedirs(f"{dirpath}/measured_{cv_sim}",exist_ok=False)
+
+            # From xlsx to csv
+            read_file = pd.read_excel (f"../../180MCU_SPICE_DATA/Cap/mimcap_fc.nl_out.xlsx")
+            read_file.to_csv (f"{dirpath}/{device}.csv", index = False, header=True)
+
+            # Folder structure of simulated values 
+            os.makedirs(f"{dirpath}/simulated_{cv_sim}",exist_ok=False)
+            os.makedirs(f"{dirpath}/error_{cv_sim}",exist_ok=False)
+    
+            ext_measured (device,cap_vn,cap_in, cv_sim, corner,start)
+            ext_simulated(device,cap_vn,cap_in,cv_sim, corner,start,voltage[0])
+            error_cal    (device,cap_vn,cap_in,cv_sim, corner,start)            
+            start = start + 4            
+        start = 0
+
+    
+    for corner in corners: 
+        for device in devices: 
+            # Folder structure of measured values
+            cv_sim, cap_vn, cap_in = measure[0], measure[1], measure[2]
+            error_cal    (device,cap_vn,cap_in,cv_sim, corner,start)            
+            start = start + 4            
+        start = 0
+
+    
+
+# # ================================================================
+# -------------------------- MAIN --------------------------------
+# ================================================================
+        
+if __name__ == "__main__":
+    
+    # Args 
+    arguments     = docopt(__doc__, version='comparator: 0.1')
+    workers_count = os.cpu_count()*2 if arguments["--num_cores"] == None else int(arguments["--num_cores"])
+    
+    # Calling main function 
+    main()
diff --git a/models/xyce/testing/regression/mos_cv/device_netlists_Cgc/nmos_3p3_cv.spice b/models/xyce/testing/regression/mos_cv/device_netlists_Cgc/nmos_3p3_cv.spice
new file mode 100644
index 0000000..87c6de8
--- /dev/null
+++ b/models/xyce/testing/regression/mos_cv/device_netlists_Cgc/nmos_3p3_cv.spice
@@ -0,0 +1,62 @@
+***************************
+** nmos_3p3_cv
+***************************
+
+** library calling
+
+.include "../../180MCU_SPICE_hspice/design.xyce"
+.lib "../../180MCU_SPICE_hspice/sm141064.xyce" typical
+
+
+** Circuit Description **
+* power supply
+vds D_tn 0 dc=0
+vgs G_tn 0 dc=3.3
+vbs S_tn 0 dc=0
+
+.temp 25
+.options tnom=25
+
+*l_diff_min = 0.24
+* ad = int((nf+1)/2) * width/nf * 0.24       = 24u                         
+* pd = (int((nf+1)/2) * width/nf + 0.24)*2   = 200.48u                 
+
+* circuit
+mn D_tn G_tn S_tn S_tn nmos_3p3 W = {{width}}u L = {{length}}u nf={{nf}} ad= 24u pd=200.48u as=24u ps=200.48u
+
+.control
+set filetype=ascii
+
+let vgs_min  = -3.3
+let vgs_step = 0.1
+let vgs_max  = 3.3
+
+compose  vbs_vector   start=0          stop=-3.3          step=-0.825
+
+set appendwrite
+
+foreach t 25
+
+    let vbs_counter = 0
+    while vbs_counter < length(vbs_vector)
+        option TEMP=25
+        alter vbs = vbs_vector[vbs_counter]
+
+        save  @mn[vs] @mn[vgs] @mn[id] @mn[cgb]
+        *******************
+        ** simulation part
+        *******************
+        DC vgs $&vgs_min $&vgs_max $&vgs_step
+    
+        * ** parameters calculation
+	
+	print @mn[cgb]
+        
+        wrdata nmos_3p3_cv/simulated_Cgc/{{i}}_simulated_W{{width}}_L{{length}}.csv @mn[cgb] 
+        
+        reset
+        let vbs_counter = vbs_counter + 1
+    end
+end
+.endc
+.end
diff --git a/models/xyce/testing/regression/mos_cv/device_netlists_Cgc/pmos_3p3_cv.spice b/models/xyce/testing/regression/mos_cv/device_netlists_Cgc/pmos_3p3_cv.spice
new file mode 100644
index 0000000..377a4b1
--- /dev/null
+++ b/models/xyce/testing/regression/mos_cv/device_netlists_Cgc/pmos_3p3_cv.spice
@@ -0,0 +1,62 @@
+***************************
+** pmos_3p3_cv
+***************************
+
+** library calling
+
+.include "../../180MCU_SPICE_hspice/design.xyce"
+.lib "../../180MCU_SPICE_hspice/sm141064.xyce" typical
+
+
+** Circuit Description **
+* power supply
+vds D_tn 0 dc=0
+vgs G_tn 0 dc=3.3
+vbs S_tn 0 dc=0
+
+.temp 25
+.options tnom=25
+
+*l_diff_min = 0.24
+* ad = int((nf+1)/2) * width/nf * 0.24       = 24u                         
+* pd = (int((nf+1)/2) * width/nf + 0.24)*2   = 200.48u                 
+
+* circuit
+mn D_tn G_tn S_tn S_tn pmos_3p3 W = {{width}}u L = {{length}}u nf={{nf}} ad= 24u pd=200.48u as=24u ps=200.48u
+
+.control
+set filetype=ascii
+
+let vgs_min  = -3.3
+let vgs_step = 0.1
+let vgs_max  = 3.3
+
+compose  vbs_vector   start=0          stop=3.3          step=0.825
+
+set appendwrite
+
+foreach t 25
+
+    let vbs_counter = 0
+    while vbs_counter < length(vbs_vector)
+        option TEMP=25
+        alter vbs = vbs_vector[vbs_counter]
+
+        save  @mn[vs] @mn[vgs] @mn[id] @mn[cgb]
+        *******************
+        ** simulation part
+        *******************
+        DC vgs $&vgs_min $&vgs_max $&vgs_step
+    
+        * ** parameters calculation
+	
+	print @mn[cgb]
+        
+        wrdata pmos_3p3_cv/simulated_Cgc/{{i}}_simulated_W{{width}}_L{{length}}.csv @mn[cgb] 
+        
+        reset
+        let vbs_counter = vbs_counter + 1
+    end
+end
+.endc
+.end
diff --git a/models/xyce/testing/regression/mos_cv/device_netlists_Cgd/nmos_3p3_cv.spice b/models/xyce/testing/regression/mos_cv/device_netlists_Cgd/nmos_3p3_cv.spice
new file mode 100644
index 0000000..f85c481
--- /dev/null
+++ b/models/xyce/testing/regression/mos_cv/device_netlists_Cgd/nmos_3p3_cv.spice
@@ -0,0 +1,62 @@
+***************************
+** nmos_3p3_cv
+***************************
+
+** library calling
+
+.include "../../180MCU_SPICE_hspice/design.xyce"
+.lib "../../180MCU_SPICE_hspice/sm141064.xyce" typical
+
+
+** Circuit Description **
+* power supply
+vds D_tn 0 dc=3.3
+vgs G_tn 0 dc=3.3
+vs S_tn 0 dc=0.2
+
+.temp 25
+.options tnom=25
+
+*l_diff_min = 0.24
+* ad = int((nf+1)/2) * width/nf * 0.24       = 24u                         
+* pd = (int((nf+1)/2) * width/nf + 0.24)*2   = 200.48u                 
+
+* circuit
+mn D_tn G_tn S_tn S_tn nmos_3p3 W = 200u L = 0.28u nf=20 ad= 24u pd=200.48u as=24u ps=200.48u
+
+.control
+set filetype=ascii
+
+let vds_min  = 0
+let vds_step = 0.1
+let vds_max  = 3.3
+
+compose  vgs_vector   start=0          stop=3.3          step=1
+
+set appendwrite
+
+foreach t 25
+
+    let vgs_counter = 0
+    while vgs_counter < length(vgs_vector)
+        option TEMP=25
+        alter vgs = vgs_vector[vgs_counter]
+
+        save  @mn[vds] @mn[vgs] @mn[id] @mn[cgd]
+        *******************
+        ** simulation part
+        *******************
+        DC vds $&vds_min $&vds_max $&vds_step
+    
+        * ** parameters calculation
+	
+	print @mn[cgd]
+        
+        wrdata nmos_3p3_cv/simulated_Cgd/{{i}}_simulated_W{{width}}_L{{length}}.csv @mn[cgd] 
+        
+        reset
+        let vgs_counter = vgs_counter + 1
+    end
+end
+.endc
+.end
diff --git a/models/xyce/testing/regression/mos_cv/device_netlists_Cgd/pmos_3p3_cv.spice b/models/xyce/testing/regression/mos_cv/device_netlists_Cgd/pmos_3p3_cv.spice
new file mode 100644
index 0000000..4e35ebc
--- /dev/null
+++ b/models/xyce/testing/regression/mos_cv/device_netlists_Cgd/pmos_3p3_cv.spice
@@ -0,0 +1,62 @@
+***************************
+** pmos_3p3_cv
+***************************
+
+** library calling
+
+.include "../../180MCU_SPICE_hspice/design.xyce"
+.lib "../../180MCU_SPICE_hspice/sm141064.xyce" typical
+
+
+** Circuit Description **
+* power supply
+vds D_tn 0 dc=-3.3
+vgs G_tn 0 dc=-3.3
+vs S_tn 0 dc=0.2
+
+.temp 25
+.options tnom=25
+
+*l_diff_min = 0.24
+* ad = int((nf+1)/2) * width/nf * 0.24       = 24u                         
+* pd = (int((nf+1)/2) * width/nf + 0.24)*2   = 200.48u                 
+
+* circuit
+mn D_tn G_tn S_tn S_tn pmos_3p3 W = 200u L = 0.28u nf=20 ad= 24u pd=200.48u as=24u ps=200.48u
+
+.control
+set filetype=ascii
+
+let vds_min  = 0
+let vds_step = -0.1
+let vds_max  = -3.3
+
+compose  vgs_vector   start=0          stop=-3.3          step=-1
+
+set appendwrite
+
+foreach t 25
+
+    let vgs_counter = 0
+    while vgs_counter < length(vgs_vector)
+        option TEMP=25
+        alter vgs = vgs_vector[vgs_counter]
+
+        save  @mn[vds] @mn[vgs] @mn[id] @mn[cgs]
+        *******************
+        ** simulation part
+        *******************
+        DC vds $&vds_min $&vds_max $&vds_step
+    
+        * ** parameters calculation
+	
+	print @mn[cgd]
+        
+        wrdata pmos_3p3_cv/simulated_Cgd/{{i}}_simulated_W{{width}}_L{{length}}.csv @mn[cgd] 
+        
+        reset
+        let vgs_counter = vgs_counter + 1
+    end
+end
+.endc
+.end
diff --git a/models/xyce/testing/regression/mos_cv/device_netlists_Cgs/nmos_3p3_cv.spice b/models/xyce/testing/regression/mos_cv/device_netlists_Cgs/nmos_3p3_cv.spice
new file mode 100644
index 0000000..9358ece
--- /dev/null
+++ b/models/xyce/testing/regression/mos_cv/device_netlists_Cgs/nmos_3p3_cv.spice
@@ -0,0 +1,62 @@
+***************************
+** nmos_3p3_cv
+***************************
+
+** library calling
+
+.include "../../180MCU_SPICE_hspice/design.xyce"
+.lib "../../180MCU_SPICE_hspice/sm141064.xyce" typical
+
+
+** Circuit Description **
+* power supply
+vds D_tn 0 dc=3.3
+vgs G_tn 0 dc=3.3
+vs S_tn 0 dc=0.1
+
+.temp 25
+.options tnom=25
+
+*l_diff_min = 0.24
+* ad = int((nf+1)/2) * width/nf * 0.24       = 24u                         
+* pd = (int((nf+1)/2) * width/nf + 0.24)*2   = 200.48u                 
+
+* circuit
+mn D_tn G_tn S_tn S_tn nmos_3p3 W = 200u L = 0.28u nf=20 ad= 24u pd=200.48u as=24u ps=200.48u
+
+.control
+set filetype=ascii
+
+let vds_min  = 0
+let vds_step = 0.1
+let vds_max  = 3.3
+
+compose  vgs_vector   start=0          stop=3.3          step=1
+
+set appendwrite
+
+foreach t 25
+
+    let vgs_counter = 0
+    while vgs_counter < length(vgs_vector)
+        option TEMP=25
+        alter vgs = vgs_vector[vgs_counter]
+
+        save  @mn[vds] @mn[vgs] @mn[id] @mn[cgs]
+        *******************
+        ** simulation part
+        *******************
+        DC vds $&vds_min $&vds_max $&vds_step
+    
+        * ** parameters calculation
+	
+	print @mn[cgs]
+        
+        wrdata nmos_3p3_cv/simulated_Cgs/{{i}}_simulated_W{{width}}_L{{length}}.csv @mn[cgs] 
+        
+        reset
+        let vgs_counter = vgs_counter + 1
+    end
+end
+.endc
+.end
diff --git a/models/xyce/testing/regression/mos_cv/device_netlists_Cgs/pmos_3p3_cv.spice b/models/xyce/testing/regression/mos_cv/device_netlists_Cgs/pmos_3p3_cv.spice
new file mode 100644
index 0000000..c01b53e
--- /dev/null
+++ b/models/xyce/testing/regression/mos_cv/device_netlists_Cgs/pmos_3p3_cv.spice
@@ -0,0 +1,62 @@
+***************************
+** pmos_3p3_cv
+***************************
+
+** library calling
+
+.include "../../180MCU_SPICE_hspice/design.xyce"
+.lib "../../180MCU_SPICE_hspice/sm141064.xyce" typical
+
+
+** Circuit Description **
+* power supply
+vds D_tn 0 dc=-3.3
+vgs G_tn 0 dc=-3.3
+vs S_tn 0 dc=0.1
+
+.temp 25
+.options tnom=25
+
+*l_diff_min = 0.24
+* ad = int((nf+1)/2) * width/nf * 0.24       = 24u                         
+* pd = (int((nf+1)/2) * width/nf + 0.24)*2   = 200.48u                 
+
+* circuit
+mn D_tn G_tn S_tn S_tn pmos_3p3 W = 200u L = 0.28u nf=20 ad= 24u pd=200.48u as=24u ps=200.48u
+
+.control
+set filetype=ascii
+
+let vds_min  = 0
+let vds_step = -0.1
+let vds_max  = -3.3
+
+compose  vgs_vector   start=0          stop=-3.3          step=-1
+
+set appendwrite
+
+foreach t 25
+
+    let vgs_counter = 0
+    while vgs_counter < length(vgs_vector)
+        option TEMP=25
+        alter vgs = vgs_vector[vgs_counter]
+
+        save  @mn[vds] @mn[vgs] @mn[id] @mn[cgs]
+        *******************
+        ** simulation part
+        *******************
+        DC vds $&vds_min $&vds_max $&vds_step
+    
+        * ** parameters calculation
+	
+	print @mn[cgs]
+        
+        wrdata pmos_3p3_cv/simulated_Cgs/{{i}}_simulated_W{{width}}_L{{length}}.csv @mn[cgs] 
+        
+        reset
+        let vgs_counter = vgs_counter + 1
+    end
+end
+.endc
+.end
diff --git a/models/xyce/testing/regression/mos_cv/measured_data/3p3_cv.nl_out.xlsx b/models/xyce/testing/regression/mos_cv/measured_data/3p3_cv.nl_out.xlsx
new file mode 100644
index 0000000..813635c
--- /dev/null
+++ b/models/xyce/testing/regression/mos_cv/measured_data/3p3_cv.nl_out.xlsx
Binary files differ
diff --git a/models/xyce/testing/regression/mos_cv/measured_data/3p3_sab_cv.nl_out.xlsx b/models/xyce/testing/regression/mos_cv/measured_data/3p3_sab_cv.nl_out.xlsx
new file mode 100644
index 0000000..fd139e1
--- /dev/null
+++ b/models/xyce/testing/regression/mos_cv/measured_data/3p3_sab_cv.nl_out.xlsx
Binary files differ
diff --git a/models/xyce/testing/regression/mos_cv/measured_data/6p0_cv.nl_out.xlsx b/models/xyce/testing/regression/mos_cv/measured_data/6p0_cv.nl_out.xlsx
new file mode 100644
index 0000000..a6d80ee
--- /dev/null
+++ b/models/xyce/testing/regression/mos_cv/measured_data/6p0_cv.nl_out.xlsx
Binary files differ
diff --git a/models/xyce/testing/regression/mos_cv/measured_data/6p0_nat_cv.nl_out.xlsx b/models/xyce/testing/regression/mos_cv/measured_data/6p0_nat_cv.nl_out.xlsx
new file mode 100644
index 0000000..407129c
--- /dev/null
+++ b/models/xyce/testing/regression/mos_cv/measured_data/6p0_nat_cv.nl_out.xlsx
Binary files differ
diff --git a/models/xyce/testing/regression/mos_cv/measured_data/6p0_sab_cv.nl_out.xlsx b/models/xyce/testing/regression/mos_cv/measured_data/6p0_sab_cv.nl_out.xlsx
new file mode 100644
index 0000000..1dbd85c
--- /dev/null
+++ b/models/xyce/testing/regression/mos_cv/measured_data/6p0_sab_cv.nl_out.xlsx
Binary files differ
diff --git a/models/xyce/testing/regression/mos_cv/models_regression.py b/models/xyce/testing/regression/mos_cv/models_regression.py
new file mode 100644
index 0000000..d31986d
--- /dev/null
+++ b/models/xyce/testing/regression/mos_cv/models_regression.py
@@ -0,0 +1,280 @@
+"""
+Usage:
+  models_regression.py [--num_cores=<num>]
+
+  -h, --help             Show help text.
+  -v, --version          Show version.
+  --num_cores=<num>      Number of cores to be used by simulator
+"""
+
+from re import T
+from docopt import docopt
+import pandas as pd 
+import numpy as np
+import os 
+from jinja2 import Template
+import concurrent.futures
+import shutil
+import warnings
+warnings.simplefilter(action='ignore', category=FutureWarning)
+
+def call_simulator(file_name):
+    """Call simulation commands to perform simulation.
+    Args:
+        file_name (str): Netlist file name.
+    """
+    os.system(f"ngspice -b -a {file_name} -o {file_name}.log > {file_name}.log")
+
+def ext_measured(device,sweep_x,sweep_y,sim_val):
+    
+    # Get dimensions used for each device 
+    dimensions = pd.read_csv(f"{device}/{device}.csv",usecols=["W (um)" , "L (um)"])
+    loops = int(dimensions["L (um)"].count()/2)
+    
+    # Extracting measured values for each W & L 
+    for i in range (0,loops):
+        width  = dimensions["W (um)"].iloc[int(i)]
+        length = dimensions["L (um)"].iloc[int(i)]
+        # Special case for 1st measured values 
+        if i == 0 :
+            # measured Cgc
+            if sim_val == "Cgc":
+                col_list = [sweep_x,sweep_y[0],sweep_y[1],sweep_y[2],sweep_y[3],sweep_y[4]]
+                df_measured = pd.read_csv(f"{device}/{device}.csv",usecols=col_list)                
+                df_measured.columns = [sweep_x,sweep_y[0],sweep_y[1],sweep_y[2],sweep_y[3],sweep_y[4]]
+            else:
+            # measured Cgs & Cgd  
+                if sim_val == "Cgs":
+                    col_list = [sweep_x,sweep_y[0],sweep_y[1],sweep_y[2],sweep_y[3]]   
+                else:
+                    col_list = [sweep_x,f"{sweep_y[0]}.1",f"{sweep_y[1]}.1",f"{sweep_y[2]}.1",f"{sweep_y[3]}.1"]
+                df_measured = pd.read_csv(f"{device}/{device}.csv",usecols=col_list)            
+                df_measured.columns = [sweep_x,sweep_y[0],sweep_y[1],sweep_y[2],sweep_y[3]]
+            df_measured.to_csv(f"{device}/measured_{sim_val}/{i}_measured_W{width}_L{length}.csv", index = False)
+        else:
+            # measured Cgc
+            if sim_val == "Cgc":    
+                col_list = [sweep_x,f"{sweep_y[0]}.{i}",f"{sweep_y[1]}.{i}",f"{sweep_y[2]}.{i}",f"{sweep_y[3]}.{i}",f"{sweep_y[4]}.{i}"]
+                df_measured = pd.read_csv(f"{device}/{device}.csv",usecols=col_list)            
+                df_measured.columns = [sweep_x,f"{sweep_y[0]}",f"{sweep_y[1]}",f"{sweep_y[2]}",f"{sweep_y[3]}",f"{sweep_y[4]}"]        
+            else:
+            # measured Cgs & Cgd 
+                cgs_index = 2*i
+                cgd_index = cgs_index + 1 
+                if sim_val == "Cgs":
+                    col_list = [sweep_x,f"{sweep_y[0]}.{cgs_index}",f"{sweep_y[1]}.{cgs_index}",f"{sweep_y[2]}.{cgs_index}",f"{sweep_y[3]}.{cgs_index}"]   
+                else: 
+                    col_list = [sweep_x,f"{sweep_y[0]}.{cgd_index}",f"{sweep_y[1]}.{cgd_index}",f"{sweep_y[2]}.{cgd_index}",f"{sweep_y[3]}.{cgd_index}"]                       
+                df_measured = pd.read_csv(f"{device}/{device}.csv",usecols=col_list)                
+                df_measured.columns = [sweep_x,f"{sweep_y[0]}",f"{sweep_y[1]}",f"{sweep_y[2]}",f"{sweep_y[3]}"]                                     
+                                
+            df_measured.to_csv(f"{device}/measured_{sim_val}/{i}_measured_W{width}_L{length}.csv", index = False)
+
+def ext_simulated(device,sweep_x,sweep_y,vds_sweep,sim_val):
+    
+    # Get dimensions used for each device 
+    dimensions = pd.read_csv(f"{device}/{device}.csv",usecols=["W (um)" , "L (um)"])
+    loops = int(dimensions["L (um)"].count()/2)
+
+    netlist_tmp = f"./device_netlists_{sim_val}/{device}.spice"
+    for i in range (0,loops):
+        width  = dimensions["W (um)"].iloc[int(i)]
+        length = dimensions["L (um)"].iloc[int(i)]
+        if i == 0:
+            nf = 20
+        else:
+            nf = 1
+        with open(netlist_tmp) as f:
+            tmpl = Template(f.read())
+            os.makedirs(f"{device}/{device}_netlists_{sim_val}",exist_ok=True)
+            with open(f"{device}/{device}_netlists_{sim_val}/{i}_{device}_netlist_W{width}_L{length}.spice", "w") as netlist:
+                netlist.write(tmpl.render(width = width,length = length,i = i, nf = nf ))
+            netlist_path  = f"{device}/{device}_netlists_{sim_val}/{i}_{device}_netlist_W{width}_L{length}.spice" 
+            # Running ngspice for each netlist 
+            with concurrent.futures.ProcessPoolExecutor(max_workers=workers_count) as executor:
+                executor.submit(call_simulator, netlist_path)
+            
+            # Writing simulated data 
+            df_simulated = pd.read_csv(f"{device}/simulated_{sim_val}/{i}_simulated_W{width}_L{length}.csv",header=None, delimiter=r"\s+")
+            df_simulated.to_csv(f"{device}/simulated_{sim_val}/{i}_simulated_W{width}_L{length}.csv",index= False)    
+            
+            # empty array to append in it shaped (vds_sweep, number of trials + 1)
+            new_array = np.empty((vds_sweep, 1+int(df_simulated.shape[0]/vds_sweep)))  
+            new_array[:, 0] = df_simulated.iloc[:vds_sweep, 0]
+            times = int(df_simulated.shape[0]/vds_sweep)
+
+            for j in range(times):
+                new_array[:, (j+1)] = df_simulated.iloc[j*vds_sweep:(j+1)*vds_sweep, 1]
+                
+            # Writing final simulated data                 
+            df_simulated = pd.DataFrame(new_array)
+            df_simulated.to_csv(f"{device}/simulated_{sim_val}/{i}_simulated_W{width}_L{length}.csv",index= False)
+            if sim_val == "Cgc":    
+                df_simulated.columns = [sweep_x,sweep_y[0],sweep_y[1],sweep_y[2],sweep_y[3],sweep_y[4]]
+            else: 
+                df_simulated.columns = [sweep_x,sweep_y[0],sweep_y[1],sweep_y[2],sweep_y[3]]
+            df_simulated.to_csv(f"{device}/simulated_{sim_val}/{i}_simulated_W{width}_L{length}.csv",index= False)    
+            
+def error_cal(device,sweep_x,sweep_y,sim_val):
+    
+    # Get dimensions used for each device 
+    dimensions = pd.read_csv(f"{device}/{device}.csv",usecols=["W (um)" , "L (um)"])
+    loops = int(dimensions["L (um)"].count()/2)
+    df_final = pd.DataFrame()
+    for i in range (0,loops):  
+        width  = dimensions["W (um)"].iloc[int(i)]
+        length = dimensions["L (um)"].iloc[int(i)]
+            
+        measured  = pd.read_csv(f"{device}/measured_{sim_val}/{i}_measured_W{width}_L{length}.csv")
+        simulated = pd.read_csv(f"{device}/simulated_{sim_val}/{i}_simulated_W{width}_L{length}.csv")
+
+        error_1 = round (100 * (abs(measured.iloc[:, 1]) - abs(simulated.iloc[:, 1]))/abs(measured.iloc[:, 1]),6)  
+        error_2 = round (100 * (abs(measured.iloc[:, 2]) - abs(simulated.iloc[:, 2]))/abs(measured.iloc[:, 2]),6)
+        error_3 = round (100 * (abs(measured.iloc[:, 3]) - abs(simulated.iloc[:, 3]))/abs(measured.iloc[:, 3]),6) 
+        error_4 = round (100 * (abs(measured.iloc[:, 4]) - abs(simulated.iloc[:, 4]))/abs(measured.iloc[:, 4]),6)         
+        if sim_val == "Cgc":
+            error_5 = round (100 * (abs(measured.iloc[:, 5]) - abs(simulated.iloc[:, 5]))/abs(measured.iloc[:, 5]),6) 
+            df_error = pd.DataFrame(data=[measured.iloc[:, 0],error_1,error_2,error_3,error_4,error_5]).transpose()        
+        else: 
+            df_error = pd.DataFrame(data=[measured.iloc[:, 0],error_1,error_2,error_3,error_4]).transpose()        
+        df_error.to_csv(f"{device}/error_{sim_val}/{i}_{device}_error_W{width}_L{length}.csv",index= False)
+
+        # Mean error 
+        if sim_val == "Cgc":
+            mean_error = (df_error[sweep_y[0]].mean() + df_error[sweep_y[1]].mean() + df_error[sweep_y[2]].mean() + 
+                          df_error[sweep_y[3]].mean() + df_error[sweep_y[4]].mean())/5
+        else: 
+            mean_error = (df_error[sweep_y[0]].mean() + df_error[sweep_y[1]].mean() + df_error[sweep_y[2]].mean() + 
+                          df_error[sweep_y[3]].mean())/4 
+        # Max error 
+        if sim_val == "Cgc":
+            max_error = df_error[[sweep_y[0],sweep_y[1],sweep_y[2],sweep_y[3],sweep_y[4]]].max().max()
+        else:
+            max_error = df_error[[sweep_y[0],sweep_y[1],sweep_y[2],sweep_y[3]]].max().max()
+        # Max error location 
+        max_index = max((df_error == max_error).idxmax())
+        max_location_sweep_y = (df_error == max_error).idxmax(axis=1)[max_index]
+        max_location_sweep_x = df_error[sweep_x][max_index]
+
+        df_final_ = {'Run no.': f'{i}', 'Temp': f'25', 'Device name': f'{device}', 'Width': f'{width}', 'Length': f'{length}', 'Simulated_Val':f'{sim_val}','Mean error%':f'{"{:.2f}".format(mean_error)}', 'Max error%':f'{"{:.2f}".format(max_error)} @ {max_location_sweep_y} & {sweep_x}= {max_location_sweep_x}'}
+        df_final = df_final.append(df_final_, ignore_index = True)
+    # Max mean error 
+    print (df_final)   
+    df_final.to_csv (f"{device}/Final_report_{sim_val}.csv", index = False)
+    out_report = pd.read_csv (f"{device}/Final_report_{sim_val}.csv")
+    print ("\n",f"Max. mean error = {out_report['Mean error%'].max()}%")    
+    print ("=====================================================================================================================================================")
+
+def main():
+        
+    devices = ["nmos_3p3_cv" , "pmos_3p3_cv" ]
+    measured_data = ["3p3_cv"]
+    nmos_vds = "Vds (V)"
+    pmos_vds = "-Vds (V)"
+    nmos_vgs = "Vgs (V)"
+    pmos_vgs = "-Vgs (V)"
+    nmos_rds = "Rds"
+    cgc_sim  = "Cgc"
+    cgs_sim  = "Cgs"
+    cgd_sim  = "Cgd"
+    Rds_sim = "Rds"
+    mos_3p3_vbs_sweep = 67 
+    mos_3p3_vgs_sweep = 34 
+
+    mos_6p0_vgs_sweep = 133 
+  
+    nmos3p3_vgs = ["Vgs=0"   , "Vgs=1.1"  , "Vgs=2.2"  , "Vgs=3.3" ] 
+    pmos3p3_vgs = ["Vgs=-0"  , "Vgs=-1.1" , "Vgs=-2.2" , "Vgs=-3.3"] 
+    # pmos3p3_vgs = [-0.8 , -1.3 , -1.8 , -2.3 , -2.8 , -3.3] 
+    # nmos6p0_vgs = [ 1 ,  2 ,  3 ,  4 ,  5 ,  6] 
+    # pmos6p0_vgs = [-1 , -2 , -3 , -4 , -5 , -6] 
+    # nmos6p0_nat_vgs = [ 0.25 ,  1.4 , 2.55 , 3.7 , 4.85 , 6]
+
+    nmos3p3_vbs = ["Vbs=0"  , "Vbs=-0.825" , "Vbs=-1.65" , "Vbs=-2.475" , "Vbs=-3.3"] 
+    pmos3p3_vbs = ["Vbs=-0" , "Vbs=0.825"  , "Vbs=1.65"  , "Vbs=2.475"  , "Vbs=3.3" ] 
+    # nmos6p0_vbs = [ 0 , -0.75 , -1.5 ,  -2.25 ,  -3] 
+    # pmos6p0_vbs = [ 0 ,  0.75 ,  1.5 ,   2.25 ,   3] 
+    # nmos6p0_nat_vbs = [ 0 ,  -0.75 , -1.5 , -2.25 , -3]
+
+    for device in devices: 
+        # Folder structure of measured values 
+        dirpath = f"{device}"
+        if os.path.exists(dirpath) and os.path.isdir(dirpath):
+            shutil.rmtree(dirpath)
+        os.makedirs(f"{device}/measured_{cgc_sim}",exist_ok=False)
+        os.makedirs(f"{device}/measured_{cgs_sim}",exist_ok=False)
+        os.makedirs(f"{device}/measured_{cgd_sim}",exist_ok=False)
+        
+        # From xlsx to csv 
+        read_file = pd.read_excel (f"./measured_data/{measured_data[0]}.nl_out.xlsx")
+        read_file.to_csv (f"{device}/{device}.csv", index = False, header=True)
+
+        # Folder structure of simulated values 
+        os.makedirs(f"{device}/simulated_{cgc_sim}",exist_ok=False)
+        os.makedirs(f"{device}/simulated_{cgs_sim}",exist_ok=False)
+        os.makedirs(f"{device}/simulated_{cgd_sim}",exist_ok=False)
+        os.makedirs(f"{device}/error_{cgc_sim}",exist_ok=False)
+        os.makedirs(f"{device}/error_{cgs_sim}",exist_ok=False)
+        os.makedirs(f"{device}/error_{cgd_sim}",exist_ok=False)
+
+
+    # =========== nmos_3p3_cv ==============      
+    # Cgc 
+    ext_measured ("nmos_3p3_cv",nmos_vgs,nmos3p3_vbs,cgc_sim)
+    ext_simulated("nmos_3p3_cv",nmos_vgs,nmos3p3_vbs,mos_3p3_vbs_sweep,cgc_sim)
+    error_cal    ("nmos_3p3_cv",nmos_vgs,nmos3p3_vbs,cgc_sim)
+
+    # Cgs
+    ext_measured ("nmos_3p3_cv",nmos_vds,nmos3p3_vgs,cgs_sim)
+    ext_simulated("nmos_3p3_cv",nmos_vds,nmos3p3_vgs,mos_3p3_vgs_sweep,cgs_sim)
+    error_cal    ("nmos_3p3_cv",nmos_vds,nmos3p3_vgs,cgs_sim)
+
+    # Cgd
+    ext_measured ("nmos_3p3_cv",nmos_vds,nmos3p3_vgs,cgd_sim)
+    ext_simulated("nmos_3p3_cv",nmos_vds,nmos3p3_vgs,mos_3p3_vgs_sweep,cgd_sim)
+    error_cal    ("nmos_3p3_cv",nmos_vds,nmos3p3_vgs,cgd_sim)
+    
+    
+    # =========== nmos_3p3_cv ==============      
+    # Cgc
+    ext_measured ("pmos_3p3_cv",pmos_vgs,pmos3p3_vbs,cgc_sim)
+    ext_simulated("pmos_3p3_cv",pmos_vgs,pmos3p3_vbs,mos_3p3_vbs_sweep,cgc_sim)
+    error_cal    ("pmos_3p3_cv",pmos_vgs,pmos3p3_vbs,cgc_sim)
+    
+    # Cgs
+    ext_measured ("pmos_3p3_cv",pmos_vgs,pmos3p3_vgs,cgs_sim)
+    ext_simulated("pmos_3p3_cv",pmos_vgs,pmos3p3_vgs,mos_3p3_vgs_sweep,cgs_sim)
+    error_cal    ("pmos_3p3_cv",pmos_vgs,pmos3p3_vgs,cgs_sim)
+     
+    # Cgd   
+    ext_measured ("pmos_3p3_cv",pmos_vgs,pmos3p3_vgs,cgd_sim)
+    ext_simulated("pmos_3p3_cv",pmos_vgs,pmos3p3_vgs,mos_3p3_vgs_sweep,cgd_sim)
+    error_cal    ("pmos_3p3_cv",pmos_vgs,pmos3p3_vgs,cgd_sim)
+            
+    # =========== pmos_3p3_iv ==============      
+
+
+    # =========== nmos_6p0_iv ==============      
+
+         
+    # =========== pmos_6p0_iv ==============      
+      
+          
+    # ============ nmos_3p3_sab_iv =============                                # Error in ngspice 
+
+
+    # ============ nmos_6p0_nat_iv =============              
+ 
+ 
+# # ================================================================
+# -------------------------- MAIN --------------------------------
+# ================================================================
+        
+if __name__ == "__main__":
+    
+    # Args 
+    arguments     = docopt(__doc__, version='comparator: 0.1')
+    workers_count = os.cpu_count()*2 if arguments["--num_cores"] == None else int(arguments["--num_cores"])
+    
+    # Calling main function 
+    main()
diff --git a/models/xyce/testing/regression/mos_iv_vbs/device_netlists_Id/nmos_3p3_iv_vbs.spice b/models/xyce/testing/regression/mos_iv_vbs/device_netlists_Id/nmos_3p3_iv_vbs.spice
new file mode 100644
index 0000000..0d09520
--- /dev/null
+++ b/models/xyce/testing/regression/mos_iv_vbs/device_netlists_Id/nmos_3p3_iv_vbs.spice
@@ -0,0 +1,25 @@
+*Xyce Common Source Circuit
+** library calling
+
+
+*****************
+** main netlist
+*****************
+Vds D_tn 0 dc 0.05
+Vgs G_tn 0 dc 3.3
+Vbs S_tn 0 dc 0
+
+xmn1 D_tn G_tn 0 S_tn nmos_3p3 W=10u L=10u ad=2.4u pd=20.48u as=2.4u ps=20.48u
+
+
+*****************
+** Analysis
+*****************
+.dc Vgs 0 3.3 0.05 Vbs 0 -3.3 -0.825
+.STEP TEMP -40 -60 200
+.print DC FORMAT=CSV file=result.csv {-I(Vds)}
+
+.include "../../../../design.xyce"
+.lib "../../../../sm141064.xyce" typical
+
+.end
diff --git a/models/xyce/testing/regression/mos_iv_vbs/models_regression.py b/models/xyce/testing/regression/mos_iv_vbs/models_regression.py
new file mode 100644
index 0000000..3a85b3e
--- /dev/null
+++ b/models/xyce/testing/regression/mos_iv_vbs/models_regression.py
@@ -0,0 +1,224 @@
+"""
+Usage:
+  models_regression.py [--num_cores=<num>]
+
+  -h, --help             Show help text.
+  -v, --version          Show version.
+  --num_cores=<num>      Number of cores to be used by simulator
+"""
+
+from re import T
+from docopt import docopt
+import pandas as pd 
+import numpy as np
+import os 
+from jinja2 import Template
+import concurrent.futures
+import shutil
+import warnings
+warnings.simplefilter(action='ignore', category=FutureWarning)
+
+def call_simulator(file_name):
+    """Call simulation commands to perform simulation.
+    Args:
+        file_name (str): Netlist file name.
+    """
+    os.system(f"ngspice -b -a {file_name} -o {file_name}.log > {file_name}.log")
+
+def ext_measured(device,vgs,vbs):
+    
+    # Get dimensions used for each device 
+    dimensions = pd.read_csv(f"{device}/{device}.csv",usecols=["W (um)" , "L (um)"])
+    loops = dimensions["L (um)"].count()
+    
+    # Extracting measured values for each W & L 
+    for i in range (0,loops*2,2):
+        width  = dimensions["W (um)"].iloc[int(i/2)]
+        length = dimensions["L (um)"].iloc[int(i/2)]
+        
+        # Special case for 1st measured values 
+        if i == 0 :
+            # measured Id
+            if device in ["pmos_3p3_iv" , "pmos_6p0_iv"]:
+                col_list = ['-vgs ',f"vbs ={vbs[0]}",f"vbs ={vbs[1]}",f"vbs ={vbs[2]}",f"vbs ={vbs[3]}",f"vbs ={vbs[4]}"]
+            else:
+                col_list = ['vgs ',f"vbs ={vbs[0]}",f"vbs ={vbs[1]}",f"vbs ={vbs[2]}",f"vbs ={vbs[3]}",f"vbs ={vbs[4]}"]                
+            df_measured = pd.read_csv(f"{device}/{device}.csv",usecols=col_list)
+            df_measured.columns = [f"{vgs}",f"vbs ={vbs[0]}",f"vbs ={vbs[1]}",f"vbs ={vbs[2]}",f"vbs ={vbs[3]}",f"vbs ={vbs[4]}"]
+            df_measured.to_csv(f"{device}/measured_Id/{int(i/2)}_measured_W{width}_L{length}.csv", index = False)
+        else:
+            # measured Id
+            col_list = [f"{vgs}",f"vbs ={vbs[0]}.{i}",f"vbs ={vbs[1]}.{i}",f"vbs ={vbs[2]}.{i}",f"vbs ={vbs[3]}.{i}",f"vbs ={vbs[4]}.{i}"]
+            df_measured = pd.read_csv(f"{device}/{device}.csv",usecols=col_list)
+            df_measured.columns = [f"{vgs}",f"vbs ={vbs[0]}",f"vbs ={vbs[1]}",f"vbs ={vbs[2]}",f"vbs ={vbs[3]}",f"vbs ={vbs[4]}"]        
+            df_measured.to_csv(f"{device}/measured_Id/{int(i/2)}_measured_W{width}_L{length}.csv", index = False)
+
+
+def ext_simulated(device,vgs,vbs,vbs_sweep,sim_val):
+    
+    # Get dimensions used for each device 
+    dimensions = pd.read_csv(f"{device}/{device}.csv",usecols=["W (um)" , "L (um)"])
+    loops = dimensions["L (um)"].count()
+    temp_range = int(loops/3) 
+    netlist_tmp = f"./device_netlists_{sim_val}/{device}.spice"
+    for i in range (0,loops):
+        width  = dimensions["W (um)"].iloc[int(i)]
+        length = dimensions["L (um)"].iloc[int(i)]
+        AD = float(width) * 0.24
+        PD = 2 * (float(width) + 0.24)
+        AS = AD 
+        PS = PD 
+        if i in range (0,temp_range): temp = 25 
+        elif i in range (temp_range,2*temp_range): temp = -40 
+        else:
+            temp = 125 
+        with open(netlist_tmp) as f:
+            tmpl = Template(f.read())
+            os.makedirs(f"{device}/{device}_netlists_{sim_val}",exist_ok=True)
+            with open(f"{device}/{device}_netlists_{sim_val}/{i}_{device}_netlist_W{width}_L{length}.spice", "w") as netlist:
+                netlist.write(tmpl.render(width = width,length = length,i = i , temp = temp , AD = AD , PD = PD , AS = AS , PS = PD ))
+            netlist_path  = f"{device}/{device}_netlists_{sim_val}/{i}_{device}_netlist_W{width}_L{length}.spice" 
+            # Running ngspice for each netlist 
+            with concurrent.futures.ProcessPoolExecutor(max_workers=workers_count) as executor:
+                executor.submit(call_simulator, netlist_path)
+            
+            # Writing simulated data 
+            df_simulated = pd.read_csv(f"{device}/simulated_{sim_val}/{i}_simulated_W{width}_L{length}.csv",header=None, delimiter=r"\s+")
+            df_simulated.to_csv(f"{device}/simulated_{sim_val}/{i}_simulated_W{width}_L{length}.csv",index= False)    
+            
+            # empty array to append in it shaped (vbs_sweep, number of trials + 1)
+            new_array = np.empty((vbs_sweep, 1+int(df_simulated.shape[0]/vbs_sweep)))  
+            new_array[:, 0] = df_simulated.iloc[:vbs_sweep, 0]
+            times = int(df_simulated.shape[0]/vbs_sweep)
+
+            for j in range(times):
+                new_array[:, (j+1)] = df_simulated.iloc[j*vbs_sweep:(j+1)*vbs_sweep, 1]
+                
+            # Writing final simulated data                 
+            df_simulated = pd.DataFrame(new_array)
+            df_simulated.to_csv(f"{device}/simulated_{sim_val}/{i}_simulated_W{width}_L{length}.csv",index= False)    
+            df_simulated.columns = [f"{vgs}",f"vbs ={vbs[0]}",f"vbs ={vbs[1]}",f"vbs ={vbs[2]}",f"vbs ={vbs[3]}",f"vbs ={vbs[4]}"]
+            df_simulated.to_csv(f"{device}/simulated_{sim_val}/{i}_simulated_W{width}_L{length}.csv",index= False)    
+
+def error_cal(device,vgs,vbs,sim_val):
+    
+    # Get dimensions used for each device 
+    dimensions = pd.read_csv(f"{device}/{device}.csv",usecols=["W (um)" , "L (um)"])
+    loops = dimensions["L (um)"].count()
+    temp_range = int(loops/3)     
+    df_final = pd.DataFrame()
+    for i in range (0,loops):  
+        width  = dimensions["W (um)"].iloc[int(i)]
+        length = dimensions["L (um)"].iloc[int(i)]
+        if i in range (0,temp_range): temp = 25             
+        elif i in range (temp_range,2*temp_range): temp = -40             
+        else: temp = 125
+             
+        measured  = pd.read_csv(f"{device}/measured_{sim_val}/{i}_measured_W{width}_L{length}.csv")
+        simulated = pd.read_csv(f"{device}/simulated_{sim_val}/{i}_simulated_W{width}_L{length}.csv")
+
+        error_1 = round (100 * abs((abs(measured.iloc[:, 1]) - abs(simulated.iloc[:, 1]))/abs(measured.iloc[:, 1])),6)  
+        error_2 = round (100 * abs((abs(measured.iloc[:, 2]) - abs(simulated.iloc[:, 2]))/abs(measured.iloc[:, 2])),6)
+        error_3 = round (100 * abs((abs(measured.iloc[:, 3]) - abs(simulated.iloc[:, 3]))/abs(measured.iloc[:, 3])),6) 
+        error_4 = round (100 * abs((abs(measured.iloc[:, 4]) - abs(simulated.iloc[:, 4]))/abs(measured.iloc[:, 4])),6) 
+        error_5 = round (100 * abs((abs(measured.iloc[:, 5]) - abs(simulated.iloc[:, 5]))/abs(measured.iloc[:, 5])),6) 
+
+        df_error = pd.DataFrame(data=[measured.iloc[:, 0],error_1,error_2,error_3,error_4,error_5]).transpose()        
+        df_error.to_csv(f"{device}/error_{sim_val}/{i}_{device}_error_W{width}_L{length}.csv",index= False)
+        
+        # Mean error 
+        mean_error = (df_error[f"vbs ={vbs[0]}"].mean() + df_error[f"vbs ={vbs[1]}"].mean() + df_error[f"vbs ={vbs[2]}"].mean() + 
+                      df_error[f"vbs ={vbs[3]}"].mean() + df_error[f"vbs ={vbs[4]}"].mean())/6
+        # Max error 
+        max_error = df_error[[f"vbs ={vbs[0]}",f"vbs ={vbs[1]}",f"vbs ={vbs[2]}",f"vbs ={vbs[3]}",f"vbs ={vbs[4]}"]].max().max()
+        # Max error location 
+        max_index = max((df_error == max_error).idxmax())
+        max_location_vbs = (df_error == max_error).idxmax(axis=1)[max_index]
+        max_location_vgs = df_error[f"{vgs}"][max_index]
+
+        df_final_ = {'Run no.': f'{i}', 'Temp': f'{temp}', 'Device name': f'{device}', 'Width': f'{width}', 'Length': f'{length}', 'Simulated_Val':f'{sim_val}','Mean error%':f'{"{:.2f}".format(mean_error)}', 'Max error%':f'{"{:.2f}".format(max_error)} @ {max_location_vgs} & vbs (V) = {max_location_vbs}'}
+        df_final = df_final.append(df_final_, ignore_index = True)
+    # Max mean error 
+    print (df_final)   
+    df_final.to_csv (f"{device}/Final_report_{sim_val}.csv", index = False)
+    out_report = pd.read_csv (f"{device}/Final_report_{sim_val}.csv")
+    print ("\n",f"Max. mean error = {out_report['Mean error%'].max()}%")    
+    print ("=====================================================================================================================================================")
+
+def main():
+        
+    devices = ["nmos_3p3_iv" , "pmos_3p3_iv" , "nmos_6p0_iv" , "pmos_6p0_iv" , "nmos_6p0_nat_iv"] #"nmos_3p3_sab_iv"
+    nmos_vgs = "vgs (V)"
+    pmos_vgs = "-vgs (V)"
+    nmos_rds = "Rds"
+    Id_sim  = "Id"
+    Rds_sim = "Rds"
+    mos_3p3_vbs_sweep = 67 
+    mos_6p0_vbs_sweep = 121 
+    mos_6p0_nat_vbs_sweep = 131     
+    nmos3p3_vbs = [0 , -0.825 , -1.65 ,  -2.48 ,  -3.3] 
+    pmos3p3_vbs = [0 ,  0.825 ,  1.65 ,   2.48 ,   3.3] 
+    nmos6p0_vbs = [ 0 , -0.75 , -1.5 ,  -2.25 ,  -3] 
+    pmos6p0_vbs = [ 0 ,  0.75 ,  1.5 ,   2.25 ,   3] 
+    nmos6p0_nat_vbs = [ 0 ,  -0.75 , -1.5 , -2.25 , -3]
+
+    for device in devices: 
+        # Folder structure of measured values 
+        dirpath = f"{device}"
+        if os.path.exists(dirpath) and os.path.isdir(dirpath):
+            shutil.rmtree(dirpath)
+        os.makedirs(f"{device}/measured_{Id_sim}",exist_ok=False)
+        # os.makedirs(f"{device}/measured_{Rds_sim}",exist_ok=False)
+
+        # From xlsx to csv 
+        read_file = pd.read_excel (f"../../180MCU_SPICE_DATA/MOS/{device}.nl_out.xlsx")
+        read_file.to_csv (f"{device}/{device}.csv", index = False, header=True)
+
+        # Folder structure of simulated values 
+        os.makedirs(f"{device}/simulated_{Id_sim}",exist_ok=False)
+        # os.makedirs(f"{device}/simulated_{Rds_sim}",exist_ok=False)
+        os.makedirs(f"{device}/error_{Id_sim}",exist_ok=False)
+        # os.makedirs(f"{device}/error_{Rds_sim}",exist_ok=False)
+
+    # =========== nmos_3p3_iv ==============      
+    ext_measured ("nmos_3p3_iv",nmos_vgs,nmos3p3_vbs)
+    ext_simulated("nmos_3p3_iv",nmos_vgs,nmos3p3_vbs,mos_3p3_vbs_sweep,Id_sim)
+    error_cal    ("nmos_3p3_iv",nmos_vgs,nmos3p3_vbs,Id_sim)
+
+    # =========== pmos_3p3_iv ==============      
+    ext_measured ("pmos_3p3_iv",pmos_vgs,pmos3p3_vbs)
+    ext_simulated("pmos_3p3_iv",pmos_vgs,pmos3p3_vbs,mos_3p3_vbs_sweep,Id_sim)
+    error_cal    ("pmos_3p3_iv",pmos_vgs,pmos3p3_vbs,Id_sim)
+
+    # =========== nmos_6p0_iv ==============      
+    ext_measured ("nmos_6p0_iv",nmos_vgs,nmos6p0_vbs)   
+    ext_simulated("nmos_6p0_iv",nmos_vgs,nmos6p0_vbs,mos_6p0_vbs_sweep,Id_sim)
+    error_cal    ("nmos_6p0_iv",nmos_vgs,nmos6p0_vbs,Id_sim)    
+         
+    # =========== pmos_6p0_iv ==============      
+    ext_measured ("pmos_6p0_iv",pmos_vgs,pmos6p0_vbs)
+    ext_simulated("pmos_6p0_iv",pmos_vgs,pmos6p0_vbs,mos_6p0_vbs_sweep,Id_sim)
+    error_cal    ("pmos_6p0_iv",pmos_vgs,pmos6p0_vbs,Id_sim) 
+          
+    # ============ nmos_3p3_sab_iv =============                                # Error in ngspice 
+    # ext_measured ("nmos_3p3_sab_iv",nmos_vgs,nmos3p3_vbs)    
+    # ext_simulated("nmos_3p3_sab_iv",nmos_vgs,nmos3p3_vbs,mos_3p3_vbs_sweep,Id_sim)
+    # error_cal    ("nmos_3p3_sab_iv",nmos_vgs,nmos3p3_vbs,Rds_sim)
+
+    # ============ nmos_6p0_nat_iv =============              
+    ext_measured ("nmos_6p0_nat_iv",nmos_vgs,nmos6p0_nat_vbs)
+    ext_simulated("nmos_6p0_nat_iv",nmos_vgs,nmos6p0_nat_vbs,mos_6p0_nat_vbs_sweep,Id_sim)
+    error_cal    ("nmos_6p0_nat_iv",nmos_vgs,nmos6p0_nat_vbs,Id_sim)     
+
+# # ================================================================
+# -------------------------- MAIN --------------------------------
+# ================================================================
+        
+if __name__ == "__main__":
+    
+    # Args 
+    arguments     = docopt(__doc__, version='comparator: 0.1')
+    workers_count = os.cpu_count()*2 if arguments["--num_cores"] == None else int(arguments["--num_cores"])
+    
+    # Calling main function 
+    main()
\ No newline at end of file
diff --git a/models/xyce/testing/regression/mos_iv_vgs/device_netlists_Id/nmos_3p3_iv.spice b/models/xyce/testing/regression/mos_iv_vgs/device_netlists_Id/nmos_3p3_iv.spice
new file mode 100644
index 0000000..4e307ff
--- /dev/null
+++ b/models/xyce/testing/regression/mos_iv_vgs/device_netlists_Id/nmos_3p3_iv.spice
@@ -0,0 +1,25 @@
+*Xyce Common Source Circuit
+** library calling
+
+* .OPTIONS DEVICE TEMP=-40
+
+*****************
+** main netlist
+*****************
+Vds D_tn 0 dc 3.3
+Vgs G_tn 0 dc 3.3
+
+
+xmn1 D_tn G_tn 0 0 nmos_3p3 W={{width}}u L={{length}}u ad={{AD}}u pd={{PD}}u as={{AS}}u ps={{PS}}u
+
+*****************
+** Analysis
+*****************
+.DC Vds 0 3.3 0.05 Vgs 0.8 3.3 0.5
+.STEP TEMP {{temp}} -60 200
+.print DC FORMAT=CSV file=nmos_3p3_iv/simulated_Id/{{i}}_simulated_W{{width}}_L{{length}}.csv {-I(Vds)}
+
+.include "../../../../../design.xyce"
+.lib "../../../../../sm141064.xyce" typical
+
+.end
\ No newline at end of file
diff --git a/models/xyce/testing/regression/mos_iv_vgs/device_netlists_Id/nmos_3p3_sab_iv.spice b/models/xyce/testing/regression/mos_iv_vgs/device_netlists_Id/nmos_3p3_sab_iv.spice
new file mode 100644
index 0000000..4a01057
--- /dev/null
+++ b/models/xyce/testing/regression/mos_iv_vgs/device_netlists_Id/nmos_3p3_sab_iv.spice
@@ -0,0 +1,25 @@
+*Xyce Common Source Circuit
+** library calling
+
+* .OPTIONS DEVICE TEMP=-40
+
+*****************
+** main netlist
+*****************
+Vds D_tn 0 dc 3.3
+Vgs G_tn 0 dc 3.3
+
+
+xmn1 D_tn G_tn 0 0 nmos_3p3_sab W={{width}}u L={{length}}u ad={{AD}}u pd={{PD}}u as={{AS}}u ps={{PS}}u
+
+*****************
+** Analysis
+*****************
+.DC Vds 0 3.3 0.05 Vgs 0.8 3.3 0.5
+.STEP TEMP {{temp}} -60 200
+.print DC FORMAT=CSV file=nmos_3p3_sab_iv/simulated_Id/{{i}}_simulated_W{{width}}_L{{length}}.csv {-I(Vds)}
+
+.include "../../../../../design.xyce"
+.lib "../../../../../sm141064.xyce" typical
+
+.end
\ No newline at end of file
diff --git a/models/xyce/testing/regression/mos_iv_vgs/device_netlists_Id/nmos_6p0_iv.spice b/models/xyce/testing/regression/mos_iv_vgs/device_netlists_Id/nmos_6p0_iv.spice
new file mode 100644
index 0000000..889d85b
--- /dev/null
+++ b/models/xyce/testing/regression/mos_iv_vgs/device_netlists_Id/nmos_6p0_iv.spice
@@ -0,0 +1,25 @@
+*Xyce Common Source Circuit
+** library calling
+
+* .OPTIONS DEVICE TEMP=-40
+
+*****************
+** main netlist
+*****************
+Vds D_tn 0 dc 3.3
+Vgs G_tn 0 dc 3.3
+
+
+xmn1 D_tn G_tn 0 0 nmos_6p0 W={{width}}u L={{length}}u ad={{AD}}u pd={{PD}}u as={{AS}}u ps={{PS}}u
+
+*****************
+** Analysis
+*****************
+.DC Vds 0 6.6 0.05 Vgs 1 6 1
+.STEP TEMP {{temp}} -60 200
+.print DC FORMAT=CSV file=nmos_6p0_iv/simulated_Id/{{i}}_simulated_W{{width}}_L{{length}}.csv {-I(Vds)}
+
+.include "../../../../../design.xyce"
+.lib "../../../../../sm141064.xyce" typical
+
+.end
\ No newline at end of file
diff --git a/models/xyce/testing/regression/mos_iv_vgs/device_netlists_Id/nmos_6p0_nat_iv.spice b/models/xyce/testing/regression/mos_iv_vgs/device_netlists_Id/nmos_6p0_nat_iv.spice
new file mode 100644
index 0000000..688a445
--- /dev/null
+++ b/models/xyce/testing/regression/mos_iv_vgs/device_netlists_Id/nmos_6p0_nat_iv.spice
@@ -0,0 +1,25 @@
+*Xyce Common Source Circuit
+** library calling
+
+* .OPTIONS DEVICE TEMP=-40
+
+*****************
+** main netlist
+*****************
+Vds D_tn 0 dc 3.3
+Vgs G_tn 0 dc 3.3
+
+
+xmn1 D_tn G_tn 0 0 nmos_6p0_nat W={{width}}u L={{length}}u ad={{AD}}u pd={{PD}}u as={{AS}}u ps={{PS}}u
+
+*****************
+** Analysis
+*****************
+.DC Vds 0 6.6 0.05 Vgs 0.25 6 1.15
+.STEP TEMP {{temp}} -60 200
+.print DC FORMAT=CSV file=nmos_6p0_nat_iv/simulated_Id/{{i}}_simulated_W{{width}}_L{{length}}.csv {-I(Vds)}
+
+.include "../../../../../design.xyce"
+.lib "../../../../../sm141064.xyce" typical
+
+.end
\ No newline at end of file
diff --git a/models/xyce/testing/regression/mos_iv_vgs/device_netlists_Id/nmos_6p0_sab_iv.spice b/models/xyce/testing/regression/mos_iv_vgs/device_netlists_Id/nmos_6p0_sab_iv.spice
new file mode 100644
index 0000000..ba9ec40
--- /dev/null
+++ b/models/xyce/testing/regression/mos_iv_vgs/device_netlists_Id/nmos_6p0_sab_iv.spice
@@ -0,0 +1,25 @@
+*Xyce Common Source Circuit
+** library calling
+
+* .OPTIONS DEVICE TEMP=-40
+
+*****************
+** main netlist
+*****************
+Vds D_tn 0 dc 3.3
+Vgs G_tn 0 dc 3.3
+
+
+xmn1 D_tn G_tn 0 0 nmos_6p0_sab W={{width}}u L={{length}}u ad={{AD}}u pd={{PD}}u as={{AS}}u ps={{PS}}u
+
+*****************
+** Analysis
+*****************
+.DC Vds 0 6.6 0.05 Vgs 1 6 1
+.STEP TEMP {{temp}} -60 200
+.print DC FORMAT=CSV file=nmos_6p0_sab_iv/simulated_Id/{{i}}_simulated_W{{width}}_L{{length}}.csv {-I(Vds)}
+
+.include "../../../../../design.xyce"
+.lib "../../../../../sm141064.xyce" typical
+
+.end
\ No newline at end of file
diff --git a/models/xyce/testing/regression/mos_iv_vgs/device_netlists_Id/pmos_3p3_iv.spice b/models/xyce/testing/regression/mos_iv_vgs/device_netlists_Id/pmos_3p3_iv.spice
new file mode 100644
index 0000000..65ec777
--- /dev/null
+++ b/models/xyce/testing/regression/mos_iv_vgs/device_netlists_Id/pmos_3p3_iv.spice
@@ -0,0 +1,25 @@
+*Xyce Common Source Circuit
+** library calling
+
+* .OPTIONS DEVICE TEMP=-40
+
+*****************
+** main netlist
+*****************
+Vds D_tn 0 dc -3.3
+Vgs G_tn 0 dc -3.3
+
+
+xmn1 D_tn G_tn 0 0 pmos_3p3 W={{width}}u L={{length}}u ad={{AD}}u pd={{PD}}u as={{AS}}u ps={{PS}}u
+
+*****************
+** Analysis
+*****************
+.DC Vds 0 -3.3 -0.05 Vgs -0.8 -3.3 -0.5
+.STEP TEMP {{temp}} -60 200
+.print DC FORMAT=CSV file=pmos_3p3_iv/simulated_Id/{{i}}_simulated_W{{width}}_L{{length}}.csv {-I(Vds)}
+
+.include "../../../../../design.xyce"
+.lib "../../../../../sm141064.xyce" typical
+
+.end
\ No newline at end of file
diff --git a/models/xyce/testing/regression/mos_iv_vgs/device_netlists_Id/pmos_3p3_sab_iv.spice b/models/xyce/testing/regression/mos_iv_vgs/device_netlists_Id/pmos_3p3_sab_iv.spice
new file mode 100644
index 0000000..8c95a4e
--- /dev/null
+++ b/models/xyce/testing/regression/mos_iv_vgs/device_netlists_Id/pmos_3p3_sab_iv.spice
@@ -0,0 +1,25 @@
+*Xyce Common Source Circuit
+** library calling
+
+* .OPTIONS DEVICE TEMP=-40
+
+*****************
+** main netlist
+*****************
+Vds D_tn 0 dc -3.3
+Vgs G_tn 0 dc -3.3
+
+
+xmn1 D_tn G_tn 0 0 pmos_3p3_sab W={{width}}u L={{length}}u ad={{AD}}u pd={{PD}}u as={{AS}}u ps={{PS}}u
+
+*****************
+** Analysis
+*****************
+.DC Vds 0 -3.3 -0.05 Vgs -0.8 -3.3 -0.5
+.STEP TEMP {{temp}} -60 200
+.print DC FORMAT=CSV file=pmos_3p3_sab_iv/simulated_Id/{{i}}_simulated_W{{width}}_L{{length}}.csv {-I(Vds)}
+
+.include "../../../../../design.xyce"
+.lib "../../../../../sm141064.xyce" typical
+
+.end
\ No newline at end of file
diff --git a/models/xyce/testing/regression/mos_iv_vgs/device_netlists_Id/pmos_6p0_iv.spice b/models/xyce/testing/regression/mos_iv_vgs/device_netlists_Id/pmos_6p0_iv.spice
new file mode 100644
index 0000000..4cb584c
--- /dev/null
+++ b/models/xyce/testing/regression/mos_iv_vgs/device_netlists_Id/pmos_6p0_iv.spice
@@ -0,0 +1,25 @@
+*Xyce Common Source Circuit
+** library calling
+
+* .OPTIONS DEVICE TEMP=-40
+
+*****************
+** main netlist
+*****************
+Vds D_tn 0 dc -3.3
+Vgs G_tn 0 dc -3.3
+
+
+xmn1 D_tn G_tn 0 0 pmos_6p0 W={{width}}u L={{length}}u ad={{AD}}u pd={{PD}}u as={{AS}}u ps={{PS}}u
+
+*****************
+** Analysis
+*****************
+.DC Vds 0 -6.6 -0.05 Vgs -1 -6 -1
+.STEP TEMP {{temp}} -60 200
+.print DC FORMAT=CSV file=pmos_6p0_iv/simulated_Id/{{i}}_simulated_W{{width}}_L{{length}}.csv {-I(Vds)}
+
+.include "../../../../../design.xyce"
+.lib "../../../../../sm141064.xyce" typical
+
+.end
\ No newline at end of file
diff --git a/models/xyce/testing/regression/mos_iv_vgs/device_netlists_Id/pmos_6p0_sab_iv.spice b/models/xyce/testing/regression/mos_iv_vgs/device_netlists_Id/pmos_6p0_sab_iv.spice
new file mode 100644
index 0000000..eb914ad
--- /dev/null
+++ b/models/xyce/testing/regression/mos_iv_vgs/device_netlists_Id/pmos_6p0_sab_iv.spice
@@ -0,0 +1,25 @@
+*Xyce Common Source Circuit
+** library calling
+
+* .OPTIONS DEVICE TEMP=-40
+
+*****************
+** main netlist
+*****************
+Vds D_tn 0 dc -3.3
+Vgs G_tn 0 dc -3.3
+
+
+xmn1 D_tn G_tn 0 0 pmos_6p0_sab W={{width}}u L={{length}}u ad={{AD}}u pd={{PD}}u as={{AS}}u ps={{PS}}u
+
+*****************
+** Analysis
+*****************
+.DC Vds 0 -6.6 -0.05 Vgs -1 -6 -1
+.STEP TEMP {{temp}} -60 200
+.print DC FORMAT=CSV file=pmos_6p0_sab_iv/simulated_Id/{{i}}_simulated_W{{width}}_L{{length}}.csv {-I(Vds)}
+
+.include "../../../../../design.xyce"
+.lib "../../../../../sm141064.xyce" typical
+
+.end
\ No newline at end of file
diff --git a/models/xyce/testing/regression/mos_iv_vgs/device_netlists_Id/run_nmos_3p3_iv_independently.spice b/models/xyce/testing/regression/mos_iv_vgs/device_netlists_Id/run_nmos_3p3_iv_independently.spice
new file mode 100644
index 0000000..993faeb
--- /dev/null
+++ b/models/xyce/testing/regression/mos_iv_vgs/device_netlists_Id/run_nmos_3p3_iv_independently.spice
@@ -0,0 +1,25 @@
+*Xyce Common Source Circuit
+** library calling
+
+* .OPTIONS DEVICE TEMP=-40
+
+*****************
+** main netlist
+*****************
+Vds D_tn 0 dc 3.3
+Vgs G_tn 0 dc 3.3
+
+
+xmn1 D_tn G_tn 0 0 nmos_3p3_sab W=10u L=10u ad=2.4u pd=20.48u as=2.4u ps=20.48u
+
+*****************
+** Analysis
+*****************
+.DC Vds 0 3.3 0.05 Vgs 0.8 3.3 0.5
+.STEP TEMP 25 -60 200
+.print DC FORMAT=CSV file=result.csv {-I(Vds)}
+
+.include "../../../../design.xyce"
+.lib "../../../../sm141064.xyce" typical
+
+.end
\ No newline at end of file
diff --git a/models/xyce/testing/regression/mos_iv_vgs/device_netlists_Rds/nmos_3p3_iv.spice b/models/xyce/testing/regression/mos_iv_vgs/device_netlists_Rds/nmos_3p3_iv.spice
new file mode 100644
index 0000000..ccc637a
--- /dev/null
+++ b/models/xyce/testing/regression/mos_iv_vgs/device_netlists_Rds/nmos_3p3_iv.spice
@@ -0,0 +1,27 @@
+*Xyce Common Source Circuit
+** library calling
+
+
+
+*****************
+** main netlist
+*****************
+Vds D_tn 0 dc 3.3
+Vgs G_tn 0 dc 3.3
+
+
+xmn1 D_tn G_tn 0 0 nmos_3p3 W={{width}}u L={{length}}u ad={{AD}}u pd={{PD}}u as={{AS}}u ps={{PS}}u
+
+
+
+*****************
+** Analysis
+*****************
+.DC Vds 0 3.3 0.05 Vgs 0.8 3.3 0.5
+.STEP TEMP {{temp}} -60 200
+.print DC FORMAT=CSV file=nmos_3p3_iv/simulated_Rds/{{i}}_simulated_W{{width}}_L{{length}}.csv {1/N(xmn1:m0:gds)}
+
+.include "../../../../../design.xyce"
+.lib "../../../../../sm141064.xyce" typical
+
+.end
\ No newline at end of file
diff --git a/models/xyce/testing/regression/mos_iv_vgs/device_netlists_Rds/nmos_3p3_sab_iv.spice b/models/xyce/testing/regression/mos_iv_vgs/device_netlists_Rds/nmos_3p3_sab_iv.spice
new file mode 100644
index 0000000..009c02c
--- /dev/null
+++ b/models/xyce/testing/regression/mos_iv_vgs/device_netlists_Rds/nmos_3p3_sab_iv.spice
@@ -0,0 +1,27 @@
+*Xyce Common Source Circuit
+** library calling
+
+
+
+*****************
+** main netlist
+*****************
+Vds D_tn 0 dc 3.3
+Vgs G_tn 0 dc 3.3
+
+
+xmn1 D_tn G_tn 0 0 nmos_3p3_sab W={{width}}u L={{length}}u ad={{AD}}u pd={{PD}}u as={{AS}}u ps={{PS}}u
+
+
+
+*****************
+** Analysis
+*****************
+.DC Vds 0 3.3 0.05 Vgs 0.8 3.3 0.5
+.STEP TEMP {{temp}} -60 200
+.print DC FORMAT=CSV file=nmos_3p3_sab_iv/simulated_Rds/{{i}}_simulated_W{{width}}_L{{length}}.csv {1/N(xmn1:m0:gds)}
+
+.include "../../../../../design.xyce"
+.lib "../../../../../sm141064.xyce" typical
+
+.end
\ No newline at end of file
diff --git a/models/xyce/testing/regression/mos_iv_vgs/device_netlists_Rds/nmos_6p0_iv.spice b/models/xyce/testing/regression/mos_iv_vgs/device_netlists_Rds/nmos_6p0_iv.spice
new file mode 100644
index 0000000..5b4fad8
--- /dev/null
+++ b/models/xyce/testing/regression/mos_iv_vgs/device_netlists_Rds/nmos_6p0_iv.spice
@@ -0,0 +1,27 @@
+*Xyce Common Source Circuit
+** library calling
+
+
+
+*****************
+** main netlist
+*****************
+Vds D_tn 0 dc 3.3
+Vgs G_tn 0 dc 3.3
+
+
+xmn1 D_tn G_tn 0 0 nmos_6p0 W={{width}}u L={{length}}u ad={{AD}}u pd={{PD}}u as={{AS}}u ps={{PS}}u
+
+
+
+*****************
+** Analysis
+*****************
+.DC Vds 0 6.6 0.05 Vgs 1 6 1
+.STEP TEMP {{temp}} -60 200
+.print DC FORMAT=CSV file=nmos_6p0_iv/simulated_Rds/{{i}}_simulated_W{{width}}_L{{length}}.csv {N(xmn1:m0:gds)}
+
+.include "../../../../../design.xyce"
+.lib "../../../../../sm141064.xyce" typical
+
+.end
\ No newline at end of file
diff --git a/models/xyce/testing/regression/mos_iv_vgs/device_netlists_Rds/nmos_6p0_nat_iv.spice b/models/xyce/testing/regression/mos_iv_vgs/device_netlists_Rds/nmos_6p0_nat_iv.spice
new file mode 100644
index 0000000..a83c949
--- /dev/null
+++ b/models/xyce/testing/regression/mos_iv_vgs/device_netlists_Rds/nmos_6p0_nat_iv.spice
@@ -0,0 +1,27 @@
+*Xyce Common Source Circuit
+** library calling
+
+
+
+*****************
+** main netlist
+*****************
+Vds D_tn 0 dc 3.3
+Vgs G_tn 0 dc 3.3
+
+
+xmn1 D_tn G_tn 0 0 nmos_6p0_nat W={{width}}u L={{length}}u ad={{AD}}u pd={{PD}}u as={{AS}}u ps={{PS}}u
+
+
+
+*****************
+** Analysis
+*****************
+.DC Vds 0 6.6 0.05 Vgs 0.25 6 1.15
+.STEP TEMP {{temp}} -60 200
+.print DC FORMAT=CSV file=nmos_6p0_nat_iv/simulated_Rds/{{i}}_simulated_W{{width}}_L{{length}}.csv {1/N(xmn1:m0:gds)}
+
+.include "../../../../../design.xyce"
+.lib "../../../../../sm141064.xyce" typical
+
+.end
\ No newline at end of file
diff --git a/models/xyce/testing/regression/mos_iv_vgs/device_netlists_Rds/nmos_6p0_sab_iv.spice b/models/xyce/testing/regression/mos_iv_vgs/device_netlists_Rds/nmos_6p0_sab_iv.spice
new file mode 100644
index 0000000..de6c2b4
--- /dev/null
+++ b/models/xyce/testing/regression/mos_iv_vgs/device_netlists_Rds/nmos_6p0_sab_iv.spice
@@ -0,0 +1,27 @@
+*Xyce Common Source Circuit
+** library calling
+
+
+
+*****************
+** main netlist
+*****************
+Vds D_tn 0 dc 3.3
+Vgs G_tn 0 dc 3.3
+
+
+xmn1 D_tn G_tn 0 0 nmos_6p0_sab W={{width}}u L={{length}}u ad={{AD}}u pd={{PD}}u as={{AS}}u ps={{PS}}u
+
+
+
+*****************
+** Analysis
+*****************
+.DC Vds 0 6.6 0.05 Vgs 1 6 1
+.STEP TEMP {{temp}} -60 200
+.print DC FORMAT=CSV file=nmos_6p0_sab_iv/simulated_Rds/{{i}}_simulated_W{{width}}_L{{length}}.csv {N(xmn1:m0:gds)}
+
+.include "../../../../../design.xyce"
+.lib "../../../../../sm141064.xyce" typical
+
+.end
\ No newline at end of file
diff --git a/models/xyce/testing/regression/mos_iv_vgs/device_netlists_Rds/pmos_3p3_iv.spice b/models/xyce/testing/regression/mos_iv_vgs/device_netlists_Rds/pmos_3p3_iv.spice
new file mode 100644
index 0000000..3104bbe
--- /dev/null
+++ b/models/xyce/testing/regression/mos_iv_vgs/device_netlists_Rds/pmos_3p3_iv.spice
@@ -0,0 +1,27 @@
+*Xyce Common Source Circuit
+** library calling
+
+
+
+*****************
+** main netlist
+*****************
+Vds D_tn 0 dc -3.3
+Vgs G_tn 0 dc -3.3
+
+
+xmn1 D_tn G_tn 0 0 pmos_3p3 W={{width}}u L={{length}}u ad={{AD}}u pd={{PD}}u as={{AS}}u ps={{PS}}u
+
+
+
+*****************
+** Analysis
+*****************
+.DC Vds 0 -3.3 -0.05 Vgs -0.8 -3.3 -0.5
+.STEP TEMP {{temp}} -60 200
+.print DC FORMAT=CSV file=pmos_3p3_iv/simulated_Rds/{{i}}_simulated_W{{width}}_L{{length}}.csv {1/N(xmn1:m0:gds)}
+
+.include "../../../../../design.xyce"
+.lib "../../../../../sm141064.xyce" typical
+
+.end
\ No newline at end of file
diff --git a/models/xyce/testing/regression/mos_iv_vgs/device_netlists_Rds/pmos_3p3_sab_iv.spice b/models/xyce/testing/regression/mos_iv_vgs/device_netlists_Rds/pmos_3p3_sab_iv.spice
new file mode 100644
index 0000000..15a279a
--- /dev/null
+++ b/models/xyce/testing/regression/mos_iv_vgs/device_netlists_Rds/pmos_3p3_sab_iv.spice
@@ -0,0 +1,27 @@
+*Xyce Common Source Circuit
+** library calling
+
+
+
+*****************
+** main netlist
+*****************
+Vds D_tn 0 dc -3.3
+Vgs G_tn 0 dc -3.3
+
+
+xmn1 D_tn G_tn 0 0 pmos_3p3_sab W={{width}}u L={{length}}u ad={{AD}}u pd={{PD}}u as={{AS}}u ps={{PS}}u
+
+
+
+*****************
+** Analysis
+*****************
+.DC Vds 0 -3.3 -0.05 Vgs -0.8 -3.3 -0.5
+.STEP TEMP {{temp}} -60 200
+.print DC FORMAT=CSV file=pmos_3p3_sab_iv/simulated_Rds/{{i}}_simulated_W{{width}}_L{{length}}.csv {1/N(xmn1:m0:gds)}
+
+.include "../../../../../design.xyce"
+.lib "../../../../../sm141064.xyce" typical
+
+.end
\ No newline at end of file
diff --git a/models/xyce/testing/regression/mos_iv_vgs/device_netlists_Rds/pmos_6p0_iv.spice b/models/xyce/testing/regression/mos_iv_vgs/device_netlists_Rds/pmos_6p0_iv.spice
new file mode 100644
index 0000000..08035f6
--- /dev/null
+++ b/models/xyce/testing/regression/mos_iv_vgs/device_netlists_Rds/pmos_6p0_iv.spice
@@ -0,0 +1,27 @@
+*Xyce Common Source Circuit
+** library calling
+
+
+
+*****************
+** main netlist
+*****************
+Vds D_tn 0 dc -3.3
+Vgs G_tn 0 dc -3.3
+
+
+xmn1 D_tn G_tn 0 0 pmos_6p0 W={{width}}u L={{length}}u ad={{AD}}u pd={{PD}}u as={{AS}}u ps={{PS}}u
+
+
+
+*****************
+** Analysis
+*****************
+.DC Vds 0 -6.6 -0.05 Vgs -1 -6 -1
+.STEP TEMP {{temp}} -60 200
+.print DC FORMAT=CSV file=pmos_6p0_iv/simulated_Rds/{{i}}_simulated_W{{width}}_L{{length}}.csv {N(xmn1:m0:gds)}
+
+.include "../../../../../design.xyce"
+.lib "../../../../../sm141064.xyce" typical
+
+.end
\ No newline at end of file
diff --git a/models/xyce/testing/regression/mos_iv_vgs/device_netlists_Rds/pmos_6p0_sab_iv.spice b/models/xyce/testing/regression/mos_iv_vgs/device_netlists_Rds/pmos_6p0_sab_iv.spice
new file mode 100644
index 0000000..d1bea5b
--- /dev/null
+++ b/models/xyce/testing/regression/mos_iv_vgs/device_netlists_Rds/pmos_6p0_sab_iv.spice
@@ -0,0 +1,27 @@
+*Xyce Common Source Circuit
+** library calling
+
+
+
+*****************
+** main netlist
+*****************
+Vds D_tn 0 dc -3.3
+Vgs G_tn 0 dc -3.3
+
+
+xmn1 D_tn G_tn 0 0 pmos_6p0_sab W={{width}}u L={{length}}u ad={{AD}}u pd={{PD}}u as={{AS}}u ps={{PS}}u
+
+
+
+*****************
+** Analysis
+*****************
+.DC Vds 0 -6.6 -0.05 Vgs -1 -6 -1
+.STEP TEMP {{temp}} -60 200
+.print DC FORMAT=CSV file=pmos_6p0_sab_iv/simulated_Rds/{{i}}_simulated_W{{width}}_L{{length}}.csv {N(xmn1:m0:gds)}
+
+.include "../../../../../design.xyce"
+.lib "../../../../../sm141064.xyce" typical
+
+.end
\ No newline at end of file
diff --git a/models/xyce/testing/regression/mos_iv_vgs/device_netlists_Rds/run_nmos_3p3_rds_independently.spice b/models/xyce/testing/regression/mos_iv_vgs/device_netlists_Rds/run_nmos_3p3_rds_independently.spice
new file mode 100644
index 0000000..4b90836
--- /dev/null
+++ b/models/xyce/testing/regression/mos_iv_vgs/device_netlists_Rds/run_nmos_3p3_rds_independently.spice
@@ -0,0 +1,27 @@
+*Xyce Common Source Circuit
+** library calling
+
+
+
+*****************
+** main netlist
+*****************
+Vds D_tn 0 dc 3.3
+Vgs G_tn 0 dc 3.3
+
+
+xmn1 D_tn G_tn 0 0 nmos_3p3 W=10u L=10u ad=2.4u pd=20.48u as=2.4u ps=20.48u
+
+
+
+*****************
+** Analysis
+*****************
+.DC Vds 0 3.3 0.05 Vgs 0.8 3.3 0.5
+.STEP TEMP -40 -40 -40
+.print DC FORMAT=CSV file=result.csv {1/N(xmn1:m0:gds)}
+
+.include "../../design.xyce"
+.lib "../../sm141064.xyce" typical
+
+.end
\ No newline at end of file
diff --git a/models/xyce/testing/regression/mos_iv_vgs/models_regression.py b/models/xyce/testing/regression/mos_iv_vgs/models_regression.py
new file mode 100644
index 0000000..e59763d
--- /dev/null
+++ b/models/xyce/testing/regression/mos_iv_vgs/models_regression.py
@@ -0,0 +1,287 @@
+"""
+Usage:
+  models_regression.py [--num_cores=<num>]
+
+  -h, --help             Show help text.
+  -v, --version          Show version.
+  --num_cores=<num>      Number of cores to be used by simulator
+"""
+
+from re import T
+from docopt import docopt
+import pandas as pd 
+import numpy as np
+import os 
+from jinja2 import Template
+import concurrent.futures
+import shutil
+import warnings
+warnings.simplefilter(action='ignore', category=FutureWarning)
+
+def call_simulator(file_name):
+    """Call simulation commands to perform simulation.
+    Args:
+        file_name (str): Netlist file name.
+    """
+    os.system(f"Xyce {file_name} -l {file_name}.log")
+
+def ext_measured(device,vds,vgs):
+    
+    # Get dimensions used for each device 
+    dimensions = pd.read_csv(f"{device}/{device}.csv",usecols=["W (um)" , "L (um)"])
+    loops = dimensions["L (um)"].count()
+    
+    # Extracting measured values for each W & L 
+    for i in range (0,loops*2,2):
+        width  = dimensions["W (um)"].iloc[int(i/2)]
+        length = dimensions["L (um)"].iloc[int(i/2)]
+        
+        # Special case for 1st measured values 
+        if i == 0 :
+            # measured Id
+            col_list = [f"{vds}",f"vgs ={vgs[0]}",f"vgs ={vgs[1]}",f"vgs ={vgs[2]}",f"vgs ={vgs[3]}",f"vgs ={vgs[4]}",f"vgs ={vgs[5]}"]
+            df_measured = pd.read_csv(f"{device}/{device}.csv",usecols=col_list)
+            df_measured.columns = [f"{vds}",f"vgs ={vgs[0]}",f"vgs ={vgs[1]}",f"vgs ={vgs[2]}",f"vgs ={vgs[3]}",f"vgs ={vgs[4]}",f"vgs ={vgs[5]}"]
+            df_measured.to_csv(f"{device}/measured_Id/{int(i/2)}_measured_W{width}_L{length}.csv", index = False)
+            # measured Rds
+            col_list = [f"{vds}",f"vgs ={vgs[0]}.{i+1}",f"vgs ={vgs[1]}.{i+1}",f"vgs ={vgs[2]}.{i+1}",f"vgs ={vgs[3]}.{i+1}",f"vgs ={vgs[4]}.{i+1}",f"vgs ={vgs[5]}.{i+1}"]
+            df_measured = pd.read_csv(f"{device}/{device}.csv",usecols=col_list)
+            df_measured.columns = [f"{vds}",f"vgs ={vgs[0]}",f"vgs ={vgs[1]}",f"vgs ={vgs[2]}",f"vgs ={vgs[3]}",f"vgs ={vgs[4]}",f"vgs ={vgs[5]}"]
+            df_measured.to_csv(f"{device}/measured_Rds/{int(i/2)}_measured_W{width}_L{length}.csv", index = False)
+        else:
+            # measured Id
+            col_list = [f"{vds}",f"vgs ={vgs[0]}.{i}",f"vgs ={vgs[1]}.{i}",f"vgs ={vgs[2]}.{i}",f"vgs ={vgs[3]}.{i}",f"vgs ={vgs[4]}.{i}",f"vgs ={vgs[5]}.{i}"]
+            df_measured = pd.read_csv(f"{device}/{device}.csv",usecols=col_list)
+            df_measured.columns = [f"{vds}",f"vgs ={vgs[0]}",f"vgs ={vgs[1]}",f"vgs ={vgs[2]}",f"vgs ={vgs[3]}",f"vgs ={vgs[4]}",f"vgs ={vgs[5]}"]        
+            df_measured.to_csv(f"{device}/measured_Id/{int(i/2)}_measured_W{width}_L{length}.csv", index = False)
+            # measured Rds
+            col_list = [f"{vds}",f"vgs ={vgs[0]}.{i+1}",f"vgs ={vgs[1]}.{i+1}",f"vgs ={vgs[2]}.{i+1}",f"vgs ={vgs[3]}.{i+1}",f"vgs ={vgs[4]}.{i+1}",f"vgs ={vgs[5]}.{i+1}"]
+            df_measured = pd.read_csv(f"{device}/{device}.csv",usecols=col_list)
+            df_measured.columns = [f"{vds}",f"vgs ={vgs[0]}",f"vgs ={vgs[1]}",f"vgs ={vgs[2]}",f"vgs ={vgs[3]}",f"vgs ={vgs[4]}",f"vgs ={vgs[5]}"]
+            df_measured.to_csv(f"{device}/measured_Rds/{int(i/2)}_measured_W{width}_L{length}.csv", index = False)
+
+def ext_simulated(device,vds,vgs,vds_sweep,sim_val):
+    
+    # Get dimensions used for each device 
+    dimensions = pd.read_csv(f"{device}/{device}.csv",usecols=["W (um)" , "L (um)"])
+    loops = dimensions["L (um)"].count()
+    temp_range = int(loops/3) 
+    netlist_tmp = f"./device_netlists_{sim_val}/{device}.spice"
+    for i in range (0,loops):
+        width  = dimensions["W (um)"].iloc[int(i)]
+        length = dimensions["L (um)"].iloc[int(i)]
+        AD = float(width) * 0.24
+        PD = 2 * (float(width) + 0.24)
+        AS = AD 
+        PS = PD 
+        if i in range (0,temp_range): temp = 25 
+        elif i in range (temp_range,2*temp_range): temp = -40 
+        else:
+            temp = 125 
+        with open(netlist_tmp) as f:
+            tmpl = Template(f.read())
+            os.makedirs(f"{device}/{device}_netlists_{sim_val}",exist_ok=True)
+            with open(f"{device}/{device}_netlists_{sim_val}/{i}_{device}_netlist_W{width}_L{length}.spice", "w") as netlist:
+                netlist.write(tmpl.render(width = width,length = length,i = i , temp = temp , AD = AD , PD = PD , AS = AS , PS = PD ))
+            netlist_path  = f"{device}/{device}_netlists_{sim_val}/{i}_{device}_netlist_W{width}_L{length}.spice" 
+            if ("sab" not in netlist_path) and ("Rds" not in netlist_path):
+                netlist_path = "-hspice-ext all " + netlist_path
+            # Running ngspice for each netlist 
+            with concurrent.futures.ProcessPoolExecutor(max_workers=workers_count) as executor:
+                executor.submit(call_simulator, netlist_path)
+            
+            # Writing simulated data 
+            df_simulated = pd.read_csv(f"{device}/simulated_{sim_val}/{i}_simulated_W{width}_L{length}.csv",header=0)   
+            
+            # empty array to append in it shaped (vds_sweep, number of trials + 1)
+            new_array = np.empty((vds_sweep, 1+int(df_simulated.shape[0]/vds_sweep)))  
+            new_array[:, 0] = df_simulated.iloc[:vds_sweep, 0]
+            times = int(df_simulated.shape[0]/vds_sweep)
+
+            for j in range(times):
+                new_array[:, (j+1)] = df_simulated.iloc[j*vds_sweep:(j+1)*vds_sweep, 0]
+                
+            # Writing final simulated data                 
+            df_simulated = pd.DataFrame(new_array)
+            df_simulated.to_csv(f"{device}/simulated_{sim_val}/{i}_simulated_W{width}_L{length}.csv",index= False)    
+            df_simulated.columns = [f"{vds}",f"vgs ={vgs[0]}",f"vgs ={vgs[1]}",f"vgs ={vgs[2]}",f"vgs ={vgs[3]}",f"vgs ={vgs[4]}",f"vgs ={vgs[5]}"]
+            df_simulated.to_csv(f"{device}/simulated_{sim_val}/{i}_simulated_W{width}_L{length}.csv",index= False)
+
+def error_cal(device,vds,vgs,sim_val):
+    
+    # Get dimensions used for each device 
+    dimensions = pd.read_csv(f"{device}/{device}.csv",usecols=["W (um)" , "L (um)"])
+    loops = dimensions["L (um)"].count()
+    temp_range = int(loops/3)     
+    df_final = pd.DataFrame()
+    for i in range (0,loops):  
+        width  = dimensions["W (um)"].iloc[int(i)]
+        length = dimensions["L (um)"].iloc[int(i)]
+        if i in range (0,temp_range): temp = 25             
+        elif i in range (temp_range,2*temp_range): temp = -40             
+        else: temp = 125
+             
+        measured  = pd.read_csv(f"{device}/measured_{sim_val}/{i}_measured_W{width}_L{length}.csv")
+        simulated = pd.read_csv(f"{device}/simulated_{sim_val}/{i}_simulated_W{width}_L{length}.csv")
+
+        error_1 = round (100 * abs((abs(measured.iloc[1:, 1]) - abs(simulated.iloc[1:, 1]))/abs(measured.iloc[:, 1])),6)  
+        error_2 = round (100 * abs((abs(measured.iloc[1:, 2]) - abs(simulated.iloc[1:, 2]))/abs(measured.iloc[:, 2])),6)
+        error_3 = round (100 * abs((abs(measured.iloc[1:, 3]) - abs(simulated.iloc[1:, 3]))/abs(measured.iloc[:, 3])),6) 
+        error_4 = round (100 * abs((abs(measured.iloc[1:, 4]) - abs(simulated.iloc[1:, 4]))/abs(measured.iloc[:, 4])),6) 
+        error_5 = round (100 * abs((abs(measured.iloc[1:, 5]) - abs(simulated.iloc[1:, 5]))/abs(measured.iloc[:, 5])),6) 
+        error_6 = round (100 * abs((abs(measured.iloc[1:, 6]) - abs(simulated.iloc[1:, 6]))/abs(measured.iloc[:, 6])),6) 
+
+        df_error = pd.DataFrame(data=[measured.iloc[:, 0],error_1,error_2,error_3,error_4,error_5,error_6]).transpose()        
+        df_error.to_csv(f"{device}/error_{sim_val}/{i}_{device}_error_W{width}_L{length}.csv",index= False)
+        
+        # Mean error 
+        mean_error = (df_error[f"vgs ={vgs[0]}"].mean() + df_error[f"vgs ={vgs[1]}"].mean() + df_error[f"vgs ={vgs[2]}"].mean() + 
+                      df_error[f"vgs ={vgs[3]}"].mean() + df_error[f"vgs ={vgs[4]}"].mean() + df_error[f"vgs ={vgs[5]}"].mean())/6
+        # Max error 
+        max_error = df_error[[f"vgs ={vgs[0]}",f"vgs ={vgs[1]}",f"vgs ={vgs[2]}",f"vgs ={vgs[3]}",f"vgs ={vgs[4]}",f"vgs ={vgs[5]}" ]].max().max()
+        # Max error location 
+        max_index = max((df_error == max_error).idxmax())
+        max_location_vgs = (df_error == max_error).idxmax(axis=1)[max_index]
+        max_location_vds = df_error[f"{vds}"][max_index]
+
+        df_final_ = {'Run no.': f'{i}', 'Temp': f'{temp}', 'Device name': f'{device}', 'Width': f'{width}', 'Length': f'{length}', 'Simulated_Val':f'{sim_val}','Mean error%':f'{"{:.2f}".format(mean_error)}', 'Max error%':f'{"{:.2f}".format(max_error)} @ {max_location_vgs} & Vds (V) = {max_location_vds}'}
+        df_final = df_final.append(df_final_, ignore_index = True)
+
+    # Max mean error 
+    print (df_final)   
+    df_final.to_csv (f"{device}/Final_report_{sim_val}.csv", index = False)
+    out_report = pd.read_csv (f"{device}/Final_report_{sim_val}.csv")
+    print ("\n",f"Max. mean error = {out_report['Mean error%'].max()}%")    
+    print ("=====================================================================================================================================================")
+
+def main():
+        
+    devices = ["nmos_3p3_iv" , "pmos_3p3_iv" , "nmos_6p0_iv" , "pmos_6p0_iv" , "nmos_6p0_nat_iv", "nmos_3p3_sab_iv", "pmos_3p3_sab_iv" , "nmos_6p0_sab_iv" , "pmos_6p0_sab_iv"]
+    nmos_vds = "vds (V)"
+    pmos_vds = "-vds (V)"
+    nmos_rds = "Rds"
+    Id_sim  = "Id"
+    Rds_sim = "Rds"
+    mos_3p3_vgs_sweep = 67 
+    mos_6p0_vgs_sweep = 133 
+    nmos3p3_vgs = [ 0.8 ,  1.3 ,  1.8 ,  2.3 ,  2.8 ,  3.3] 
+    pmos3p3_vgs = [-0.8 , -1.3 , -1.8 , -2.3 , -2.8 , -3.3] 
+    nmos6p0_vgs = [ 1 ,  2 ,  3 ,  4 ,  5 ,  6] 
+    pmos6p0_vgs = [-1 , -2 , -3 , -4 , -5 , -6] 
+    nmos6p0_nat_vgs = [ 0.25 ,  1.4 , 2.55 , 3.7 , 4.85 , 6]
+
+    for device in devices: 
+        # Folder structure of measured values 
+        dirpath = f"{device}"
+        if os.path.exists(dirpath) and os.path.isdir(dirpath):
+            shutil.rmtree(dirpath)
+        os.makedirs(f"{device}/measured_{Id_sim}",exist_ok=False)
+        os.makedirs(f"{device}/measured_{Rds_sim}",exist_ok=False)
+
+        # From xlsx to csv 
+        read_file = pd.read_excel (f"../../180MCU_SPICE_DATA/MOS/{device}.nl_out.xlsx")
+        read_file.to_csv (f"{device}/{device}.csv", index = False, header=True)
+
+        # Folder structure of simulated values 
+        os.makedirs(f"{device}/simulated_{Id_sim}",exist_ok=False)
+        os.makedirs(f"{device}/simulated_{Rds_sim}",exist_ok=False)
+        os.makedirs(f"{device}/error_{Id_sim}",exist_ok=False)
+        os.makedirs(f"{device}/error_{Rds_sim}",exist_ok=False)
+
+    # =========== nmos_3p3_iv ==============      
+    ext_measured ("nmos_3p3_iv",nmos_vds,nmos3p3_vgs)
+
+    ext_simulated("nmos_3p3_iv",nmos_vds,nmos3p3_vgs,mos_3p3_vgs_sweep,Id_sim)
+
+    ext_simulated("nmos_3p3_iv",nmos_vds,nmos3p3_vgs,mos_3p3_vgs_sweep,Rds_sim)
+
+    # =========== pmos_3p3_iv ==============      
+    ext_measured ("pmos_3p3_iv",pmos_vds,pmos3p3_vgs)
+
+    ext_simulated("pmos_3p3_iv",pmos_vds,pmos3p3_vgs,mos_3p3_vgs_sweep,Id_sim)
+    
+    ext_simulated("pmos_3p3_iv",pmos_vds,pmos3p3_vgs,mos_3p3_vgs_sweep,Rds_sim)    
+
+    # =========== nmos_6p0_iv ==============      
+    ext_measured ("nmos_6p0_iv",nmos_vds,nmos6p0_vgs)
+   
+    ext_simulated("nmos_6p0_iv",nmos_vds,nmos6p0_vgs,mos_6p0_vgs_sweep,Id_sim)
+        
+    ext_simulated("nmos_6p0_iv",nmos_vds,nmos6p0_vgs,mos_6p0_vgs_sweep,Rds_sim)
+
+    # =========== pmos_6p0_iv ==============      
+    ext_measured ("pmos_6p0_iv",pmos_vds,pmos6p0_vgs)
+
+    ext_simulated("pmos_6p0_iv",pmos_vds,pmos6p0_vgs,mos_6p0_vgs_sweep,Id_sim)
+
+    ext_simulated("pmos_6p0_iv",pmos_vds,pmos6p0_vgs,mos_6p0_vgs_sweep,Rds_sim)    
+    
+    # ============ nmos_6p0_nat_iv =============              
+    ext_measured ("nmos_6p0_nat_iv",nmos_vds,nmos6p0_nat_vgs)
+
+    ext_simulated("nmos_6p0_nat_iv",nmos_vds,nmos6p0_nat_vgs,mos_6p0_vgs_sweep,Id_sim)
+    
+    ext_simulated("nmos_6p0_nat_iv",nmos_vds,nmos6p0_nat_vgs,mos_6p0_vgs_sweep,Rds_sim) 
+
+    # ============ nmos_3p3_sab_iv =============                                
+    ext_measured ("nmos_3p3_sab_iv",nmos_vds,nmos3p3_vgs)
+    
+    ext_simulated("nmos_3p3_sab_iv",nmos_vds,nmos3p3_vgs,mos_3p3_vgs_sweep,Id_sim)
+
+    ext_simulated("nmos_3p3_sab_iv",nmos_vds,nmos3p3_vgs,mos_3p3_vgs_sweep,Rds_sim)
+    
+    # =========== pmos_3p3_sab_iv ==============      
+    ext_measured ("pmos_3p3_sab_iv",pmos_vds,pmos3p3_vgs)
+
+    ext_simulated("pmos_3p3_sab_iv",pmos_vds,pmos3p3_vgs,mos_3p3_vgs_sweep,Id_sim)
+    
+    ext_simulated("pmos_3p3_sab_iv",pmos_vds,pmos3p3_vgs,mos_3p3_vgs_sweep,Rds_sim)    
+
+    # =========== nmos_6p0_sab_iv ==============      
+    ext_measured ("nmos_6p0_sab_iv",nmos_vds,nmos6p0_vgs)
+   
+    ext_simulated("nmos_6p0_sab_iv",nmos_vds,nmos6p0_vgs,mos_6p0_vgs_sweep,Id_sim)
+        
+    ext_simulated("nmos_6p0_sab_iv",nmos_vds,nmos6p0_vgs,mos_6p0_vgs_sweep,Rds_sim)
+
+    # =========== pmos_6p0_sab_iv ==============      
+    ext_measured ("pmos_6p0_sab_iv",pmos_vds,pmos6p0_vgs)
+
+    ext_simulated("pmos_6p0_sab_iv",pmos_vds,pmos6p0_vgs,mos_6p0_vgs_sweep,Id_sim)
+
+    ext_simulated("pmos_6p0_sab_iv",pmos_vds,pmos6p0_vgs,mos_6p0_vgs_sweep,Rds_sim)    
+    
+       
+         
+    # ============ Results ============= 
+    error_cal    ("nmos_3p3_iv",nmos_vds,nmos3p3_vgs,Id_sim)
+    error_cal    ("nmos_3p3_iv",nmos_vds,nmos3p3_vgs,Rds_sim)
+    error_cal    ("pmos_3p3_iv",pmos_vds,pmos3p3_vgs,Id_sim)
+    error_cal    ("pmos_3p3_iv",pmos_vds,pmos3p3_vgs,Rds_sim)
+    error_cal    ("nmos_6p0_iv",nmos_vds,nmos6p0_vgs,Id_sim)
+    error_cal    ("nmos_6p0_iv",nmos_vds,nmos6p0_vgs,Rds_sim)
+    error_cal    ("pmos_6p0_iv",pmos_vds,pmos6p0_vgs,Id_sim)
+    error_cal    ("pmos_6p0_iv",pmos_vds,pmos6p0_vgs,Rds_sim)
+    error_cal    ("nmos_6p0_nat_iv",nmos_vds,nmos6p0_nat_vgs,Id_sim)
+    error_cal    ("nmos_6p0_nat_iv",nmos_vds,nmos6p0_nat_vgs,Rds_sim)
+    error_cal    ("nmos_3p3_sab_iv",nmos_vds,nmos3p3_vgs,Rds_sim)
+    error_cal    ("nmos_3p3_sab_iv",nmos_vds,nmos3p3_vgs,Id_sim)
+    error_cal    ("pmos_3p3_sab_iv",pmos_vds,pmos3p3_vgs,Id_sim)
+    error_cal    ("pmos_3p3_sab_iv",pmos_vds,pmos3p3_vgs,Rds_sim)
+    error_cal    ("nmos_6p0_sab_iv",nmos_vds,nmos6p0_vgs,Id_sim)
+    error_cal    ("nmos_6p0_sab_iv",nmos_vds,nmos6p0_vgs,Rds_sim)
+    error_cal    ("pmos_6p0_sab_iv",pmos_vds,pmos6p0_vgs,Id_sim)
+    error_cal    ("pmos_6p0_sab_iv",pmos_vds,pmos6p0_vgs,Rds_sim)
+    
+# # ================================================================
+# -------------------------- MAIN --------------------------------
+# ================================================================
+        
+if __name__ == "__main__":
+    
+    # Args 
+    arguments     = docopt(__doc__, version='comparator: 0.1')
+    workers_count = os.cpu_count()*2 if arguments["--num_cores"] == None else int(arguments["--num_cores"])
+    
+    # Calling main function 
+    main()
diff --git a/models/xyce/testing/regression/moscap_c/device_netlists/moscap.spice b/models/xyce/testing/regression/moscap_c/device_netlists/moscap.spice
new file mode 100644
index 0000000..132247d
--- /dev/null
+++ b/models/xyce/testing/regression/moscap_c/device_netlists/moscap.spice
@@ -0,0 +1,30 @@
+*Xyce Common Source Circuit
+** library calling
+
+
+*****************
+** main netlist
+*****************
+.param volt = -3.3
+V1 in 0 dc {volt} ac 1
+R1 in out 1G
+xcn out 0 {{device}} c_length={{length}}u c_width={{width}}u l={{length}}u w={{width}}u
+
+.meas AC freq when Vdb(out)=-3 PRECISION=15
+
+
+
+
+*****************
+** Analysis
+*****************
+
+.ac dec 10 1 10G
+.step volt {{voltage}}
+
+.include "../../../../../design.xyce"
+.lib "../../../../../sm141064.xyce" moscap_{{corner}}
+
+.end
+
+
diff --git a/models/xyce/testing/regression/moscap_c/device_netlists/run_nmoscap_3p3_independently.spice b/models/xyce/testing/regression/moscap_c/device_netlists/run_nmoscap_3p3_independently.spice
new file mode 100644
index 0000000..97c50cf
--- /dev/null
+++ b/models/xyce/testing/regression/moscap_c/device_netlists/run_nmoscap_3p3_independently.spice
@@ -0,0 +1,28 @@
+*Xyce Common Source Circuit
+** library calling
+
+
+*****************
+** main netlist
+*****************
+Ich 0 p dc 10u
+
+
+xcn p 0 nmoscap_3p3 L=50u W=50u
+* PJ=40u
+
+
+*****************
+** Analysis
+*****************
+.ic v(p)=0.0
+.tran 10ns 2000us
+
+.meas tran CV FIND par('(10.0e-6  * time / v(p))*1.0e15') AT=2000us
+
+
+
+.include "../../design.xyce"
+.lib "../../sm141064.xyce" moscap_typical
+
+.end
\ No newline at end of file
diff --git a/models/xyce/testing/regression/moscap_c/models_regression.py b/models/xyce/testing/regression/moscap_c/models_regression.py
new file mode 100644
index 0000000..731da96
--- /dev/null
+++ b/models/xyce/testing/regression/moscap_c/models_regression.py
@@ -0,0 +1,224 @@
+"""
+Usage:
+  models_regression.py [--num_cores=<num>]
+
+  -h, --help             Show help text.
+  -v, --version          Show version.
+  --num_cores=<num>      Number of cores to be used by simulator
+"""
+
+from re import T
+from docopt import docopt
+import pandas as pd 
+import numpy as np
+import os 
+from jinja2 import Template
+import concurrent.futures
+import shutil
+import warnings
+warnings.simplefilter(action='ignore', category=FutureWarning)
+
+def call_simulator(file_name):
+    """Call simulation commands to perform simulation.
+    Args:
+        file_name (str): Netlist file name.
+    """
+    os.system(f"Xyce -hspice-ext all {file_name} -l {file_name}.log")
+
+def ext_measured(device,vn,d_in, cv_sim, corner,start):
+    
+    # Get dimensions used for each device 
+    dirpath = f"{device}_{cv_sim}_{corner}"
+    
+    # Extracting measured values for each W & L 
+    for i in range (start,4+start):
+        if i == 0+start: width  = 50 ; length = 50
+        if i == 1+start: width  = 1  ; length = 1
+        if i == 2+start: width  = 50 ; length = 1
+        if i == 3+start: width  = 1  ; length = 50
+
+        if i == 0 :                       
+            # measured cv
+            col_list = [f"Vj",f"moscap_{corner}"]
+            df_measured = pd.read_csv(f"{dirpath}/{device}.csv",usecols=col_list)
+            df_measured.to_csv(f"{dirpath}/measured_{cv_sim}/{i-start}_measured_w{width}_l{length}.csv", index=False)
+        else:
+            # measured cv
+            col_list = [f"Vj",f"moscap_{corner}.{i}"]
+            df_measured = pd.read_csv(f"{dirpath}/{device}.csv",usecols=col_list)
+            df_measured.columns = [f"Vj",f"moscap_{corner}"]
+            df_measured.to_csv(f"{dirpath}/measured_{cv_sim}/{i-start}_measured_w{width}_l{length}.csv", index=False)
+
+def ext_simulated(device,vn,d_in,cv_sim, corner,start,voltage):
+    
+    # Get dimensions used for each device 
+    dirpath = f"{device}_{cv_sim}_{corner}"
+    netlist_tmp = f"./device_netlists/moscap.spice"
+    
+    # Extracting measured values for each W & L 
+    for i in range (start,4+start):
+        if i == 0+start: width  = 50 ; length = 50
+        if i == 1+start: width  = 1  ; length = 1
+        if i == 2+start: width  = 50 ; length = 1
+        if i == 3+start: width  = 1  ; length = 50
+    
+        with open(netlist_tmp) as f:
+            tmpl = Template(f.read())
+            os.makedirs(f"{dirpath}/{device}_netlists_{cv_sim}",exist_ok=True)
+            with open(f"{dirpath}/{device}_netlists_{cv_sim}/{i-start}_{device}_netlist_w{width}_l{length}.spice", "w") as netlist:
+                netlist.write(tmpl.render(device = device, width = width, length = length , corner = corner , voltage = voltage))
+            netlist_path  = f"{dirpath}/{device}_netlists_{cv_sim}/{i-start}_{device}_netlist_w{width}_l{length}.spice" 
+            # Running ngspice for each netlist 
+            with concurrent.futures.ProcessPoolExecutor(max_workers=workers_count) as executor:
+                executor.submit(call_simulator, netlist_path)
+            
+        # Writing simulated data 
+        df_simulated = []
+        # Writing simulated data 
+        for j in range(len([x for x in os.listdir(f"{dirpath}/{device}_netlists_{cv_sim}") if f"{i-start}_{device}_netlist_w{width}_l{length}.spice.ma" in x])):
+            with open(f"{dirpath}/{device}_netlists_{cv_sim}/{i-start}_{device}_netlist_w{width}_l{length}.spice.ma{j}") as f:
+                cap = 1000000/(float(next(f).replace("FREQ = ", ""))*2*np.pi)
+                df_simulated.append(cap) 
+        
+        # zero array to append in it shaped (vn_sweeps, number of trials + 1)
+        new_array = np.zeros((len(df_simulated), 2))
+        new_array[:len(df_simulated), 0] = df_simulated
+        new_array[:len(df_simulated), 1] = df_simulated
+
+        # Writing final simulated data                 
+        df_simulated = pd.DataFrame(new_array)   
+        df_simulated.columns = [f"Vj",f"moscap_{corner}"]
+        df_simulated.to_csv(f"{dirpath}/simulated_{cv_sim}/{i-start}_simulated_w{width}_l{length}.csv",index= False)     
+            
+def error_cal(device,vn,d_in,Id_sim, corner,start):
+    
+    # Get dimensions used for each device 
+    dirpath = f"{device}_{Id_sim}_{corner}"
+    df_final = pd.DataFrame()
+    for i in range (start,4+start):
+        if i == 0+start: width  = 50 ; length = 50
+        if i == 1+start: width  = 1  ; length = 1
+        if i == 2+start: width  = 50 ; length = 1
+        if i == 3+start: width  = 1  ; length = 50
+             
+        measured  = pd.read_csv(f"{dirpath}/measured_{Id_sim}/{i-start}_measured_w{width}_l{length}.csv")
+        simulated = pd.read_csv(f"{dirpath}/simulated_{Id_sim}/{i-start}_simulated_w{width}_l{length}.csv")
+
+        error_1 = round (100 * abs((abs(measured.iloc[:, 1]) - abs(simulated.iloc[:, 1]))/abs(measured.iloc[:, 1])),8)  
+
+        df_error = pd.DataFrame(data=[measured.iloc[:, 0],error_1]).transpose()        
+        df_error.to_csv(f"{dirpath}/error_{Id_sim}/{i-start}_{device}_error_w{width}_l{length}.csv",index= False)
+        
+        # Mean error 
+        mean_error = (df_error[f"moscap_{corner}"].mean())
+        # Max error 
+        max_error = df_error[f"moscap_{corner}"].max()
+
+        df_final_ = {'Run no.': f'{i-start}', 'Device name': f'{dirpath}', 'Width': f'{width}', 'Length': f'{length}', 'Simulated_Val':f'{Id_sim}','Mean error%':f'{"{:.2f}".format(mean_error)}', 'Max error%':f'{"{:.2f}".format(max_error)} '}
+        df_final = df_final.append(df_final_, ignore_index = True)
+    
+    # Max mean error 
+    print (df_final)   
+    df_final.to_csv (f"{dirpath}/Final_report_{Id_sim}.csv", index = False)
+    out_report = pd.read_csv (f"{dirpath}/Final_report_{Id_sim}.csv")
+    print ("\n",f"Max. mean error = {out_report['Mean error%'].max()}%")    
+    print ("=====================================================================================================================================================")
+
+
+def main():
+
+    # 3p3
+    corners = ["typical","ff","ss"]        
+    devices = ["nmoscap_3p3" , "pmoscap_3p3" , "nmoscap_3p3_b" , "pmoscap_3p3_b"]
+    measure = ["cv","corners", "CV (fF)"]
+    voltage = ["-3.3 3.3 0.1","-6.6 6.0 0.1"]
+    start = 0
+    for corner in corners: 
+        for device in devices: 
+            # Folder structure of measured values
+            cv_sim, cap_vn, cap_in = measure[0], measure[1], measure[2]
+            dirpath = f"{device}_{cv_sim}_{corner}"
+            if os.path.exists(dirpath) and os.path.isdir(dirpath):
+                shutil.rmtree(dirpath)
+            os.makedirs(f"{dirpath}/measured_{cv_sim}",exist_ok=False)
+
+            # From xlsx to csv
+            read_file = pd.read_excel (f"../../180MCU_SPICE_DATA/Cap/moscap_cv_3p3.nl_out.xlsx")
+            read_file.to_csv (f"{dirpath}/{device}.csv", index = False, header=True)
+
+            # Folder structure of simulated values 
+            os.makedirs(f"{dirpath}/simulated_{cv_sim}",exist_ok=False)
+            os.makedirs(f"{dirpath}/error_{cv_sim}",exist_ok=False)
+    
+            ext_measured (device,cap_vn,cap_in, cv_sim, corner,start)
+            ext_simulated(device,cap_vn,cap_in,cv_sim, corner,start,voltage[0])
+            error_cal    (device,cap_vn,cap_in,cv_sim, corner,start)            
+            start = start + 4            
+        start = 0
+
+    # 6p0 
+    corners = ["typical","ff","ss"]        
+    devices = ["nmoscap_6p0" , "pmoscap_6p0" , "nmoscap_6p0_b" , "pmoscap_6p0_b"]
+    measure = ["cv","corners", "CV (fF)"]
+    start = 0
+    for corner in corners: 
+        for device in devices: 
+            # Folder structure of measured values
+            cv_sim, cap_vn, cap_in = measure[0], measure[1], measure[2]
+            dirpath = f"{device}_{cv_sim}_{corner}"
+            if os.path.exists(dirpath) and os.path.isdir(dirpath):
+                shutil.rmtree(dirpath)
+            os.makedirs(f"{dirpath}/measured_{cv_sim}",exist_ok=False)
+
+            # From xlsx to csv
+            read_file = pd.read_excel (f"../../180MCU_SPICE_DATA/Cap/moscap_cv_6p0.nl_out.xlsx")
+            read_file.to_csv (f"{dirpath}/{device}.csv", index = False, header=True)
+
+            # Folder structure of simulated values 
+            os.makedirs(f"{dirpath}/simulated_{cv_sim}",exist_ok=False)
+            os.makedirs(f"{dirpath}/error_{cv_sim}",exist_ok=False)
+    
+            ext_measured (device,cap_vn,cap_in, cv_sim, corner,start)
+            ext_simulated(device,cap_vn,cap_in,cv_sim, corner,start,voltage[1])
+            error_cal    (device,cap_vn,cap_in,cv_sim, corner,start)            
+            start = start + 4            
+        start = 0
+
+        # 3p3
+    corners = ["typical","ff","ss"]        
+    devices = ["nmoscap_3p3" , "pmoscap_3p3" , "nmoscap_3p3_b" , "pmoscap_3p3_b"]
+    measure = ["cv","corners", "CV (fF)"]
+    start = 0
+    for corner in corners: 
+        for device in devices: 
+            # Folder structure of measured values
+            cv_sim, cap_vn, cap_in = measure[0], measure[1], measure[2]
+            error_cal    (device,cap_vn,cap_in,cv_sim, corner,start)            
+            start = start + 4            
+        start = 0
+
+    # 6p0 
+    corners = ["typical","ff","ss"]        
+    devices = ["nmoscap_6p0" , "pmoscap_6p0" , "nmoscap_6p0_b" , "pmoscap_6p0_b"]
+    measure = ["cv","corners", "CV (fF)"]
+    start = 0
+    for corner in corners: 
+        for device in devices: 
+            # Folder structure of measured values
+            cv_sim, cap_vn, cap_in = measure[0], measure[1], measure[2]
+            error_cal    (device,cap_vn,cap_in,cv_sim, corner,start)            
+            start = start + 4            
+        start = 0
+
+# # ================================================================
+# -------------------------- MAIN --------------------------------
+# ================================================================
+        
+if __name__ == "__main__":
+    
+    # Args 
+    arguments     = docopt(__doc__, version='comparator: 0.1')
+    workers_count = os.cpu_count()*2 if arguments["--num_cores"] == None else int(arguments["--num_cores"])
+    
+    # Calling main function 
+    main()
diff --git a/models/xyce/testing/regression/resistor_r/device_netlists/2term_res_a.spice b/models/xyce/testing/regression/resistor_r/device_netlists/2term_res_a.spice
new file mode 100644
index 0000000..a5f7272
--- /dev/null
+++ b/models/xyce/testing/regression/resistor_r/device_netlists/2term_res_a.spice
@@ -0,0 +1,25 @@
+*Xyce Common Source Circuit
+** library calling
+
+
+*****************
+** main netlist
+*****************
+Vn n 0 DC 1
+
+xrn n 0 {{device}} L={{width}}u W={{length}}u
+
+
+*****************
+** Analysis
+*****************
+.OP
+.STEP TEMP 25 -60 200
+.print DC FORMAT=CSV file={{device}}_r_{{corner}}/simulated_r/{{i}}_simulated_w{{width}}_l{{length}}.csv {(V(n)*{{length}}u)/(-I(Vn)*{{width}}u)}
+
+
+
+.include "../../../../../design.xyce"
+.lib "../../../../../sm141064.xyce" res_{{corner}}
+
+.end
\ No newline at end of file
diff --git a/models/xyce/testing/regression/resistor_r/device_netlists/2term_res_b.spice b/models/xyce/testing/regression/resistor_r/device_netlists/2term_res_b.spice
new file mode 100644
index 0000000..82ccc77
--- /dev/null
+++ b/models/xyce/testing/regression/resistor_r/device_netlists/2term_res_b.spice
@@ -0,0 +1,25 @@
+*Xyce Common Source Circuit
+** library calling
+
+
+*****************
+** main netlist
+*****************
+Vn n 0 DC 1
+
+xrn n 0 {{device}} L={{width}}u W={{length}}u
+
+
+*****************
+** Analysis
+*****************
+.OP
+.STEP TEMP {{temp}} -60 200
+.print DC FORMAT=CSV file={{device}}_r_{{corner}}_temp/simulated_r/{{i}}_simulated_w{{width}}_l{{length}}.csv {(V(n)*{{length}}u)/(-I(Vn)*{{width}}u)}
+
+
+
+.include "../../../../../design.xyce"
+.lib "../../../../../sm141064.xyce" res_{{corner}}
+
+.end
\ No newline at end of file
diff --git a/models/xyce/testing/regression/resistor_r/device_netlists/3term_res_a.spice b/models/xyce/testing/regression/resistor_r/device_netlists/3term_res_a.spice
new file mode 100644
index 0000000..ad0f4eb
--- /dev/null
+++ b/models/xyce/testing/regression/resistor_r/device_netlists/3term_res_a.spice
@@ -0,0 +1,25 @@
+*Xyce Common Source Circuit
+** library calling
+
+
+*****************
+** main netlist
+*****************
+Vn n 0 DC 1
+
+xrn n 0 0 {{device}} L={{width}}u W={{length}}u
+
+
+*****************
+** Analysis
+*****************
+.OP
+.STEP TEMP 25 -60 200
+.print DC FORMAT=CSV file={{device}}_r_{{corner}}/simulated_r/{{i}}_simulated_w{{width}}_l{{length}}.csv {(V(n)*{{length}}u)/(-I(Vn)*{{width}}u)}
+
+
+
+.include "../../../../../design.xyce"
+.lib "../../../../../sm141064.xyce" res_{{corner}}
+
+.end
\ No newline at end of file
diff --git a/models/xyce/testing/regression/resistor_r/device_netlists/3term_res_b.spice b/models/xyce/testing/regression/resistor_r/device_netlists/3term_res_b.spice
new file mode 100644
index 0000000..b7af642
--- /dev/null
+++ b/models/xyce/testing/regression/resistor_r/device_netlists/3term_res_b.spice
@@ -0,0 +1,25 @@
+*Xyce Common Source Circuit
+** library calling
+
+
+*****************
+** main netlist
+*****************
+Vn n 0 DC 1
+
+xrn n 0 0 {{device}} L={{width}}u W={{length}}u
+
+
+*****************
+** Analysis
+*****************
+.OP
+.STEP TEMP {{temp}} -60 200
+.print DC FORMAT=CSV file={{device}}_r_{{corner}}_temp/simulated_r/{{i}}_simulated_w{{width}}_l{{length}}.csv {(V(n)*{{length}}u)/(-I(Vn)*{{width}}u)}
+
+
+
+.include "../../../../../design.xyce"
+.lib "../../../../../sm141064.xyce" res_{{corner}}
+
+.end
\ No newline at end of file
diff --git a/models/xyce/testing/regression/resistor_r/device_netlists/run_2term_res.spice b/models/xyce/testing/regression/resistor_r/device_netlists/run_2term_res.spice
new file mode 100644
index 0000000..d7e0b81
--- /dev/null
+++ b/models/xyce/testing/regression/resistor_r/device_netlists/run_2term_res.spice
@@ -0,0 +1,28 @@
+*Xyce Common Source Circuit
+** library calling
+
+
+*****************
+** main netlist
+*****************
+Vn n 0 dc 1
+
+r1 n p 1M
+xrn p 0 rm1 L=100u W=100u
+* PJ=40u
+
+* .print dc Rs=par('(1M*V(p)/(V(n)-V(p)))/100u*100u')
+
+*****************
+** Analysis
+*****************
+.OP
+
+.print DC FORMAT=CSV file=result.csv {(1M*V(p)/(V(n)-V(p)))/100u*100u}
+
+
+
+.include "../../../../design.xyce"
+.lib "../../../../sm141064.xyce" res_typical
+
+.end
\ No newline at end of file
diff --git a/models/xyce/testing/regression/resistor_r/device_netlists/run_3term_res.spice b/models/xyce/testing/regression/resistor_r/device_netlists/run_3term_res.spice
new file mode 100644
index 0000000..c1853ca
--- /dev/null
+++ b/models/xyce/testing/regression/resistor_r/device_netlists/run_3term_res.spice
@@ -0,0 +1,28 @@
+*Xyce Common Source Circuit
+** library calling
+
+
+*****************
+** main netlist
+*****************
+Vn n 0 dc 1
+
+*r1 n p 1MEG
+xrn n 0 0 ppolyf_s L=50u W=150u
+* PJ=40u
+
+* .print dc Rs=par('(1M*V(p)/(V(n)-V(p)))/100u*100u')
+
+*****************
+** Analysis
+*****************
+.OP
+* .DC Vn 1 1 0.1
+* .print DC FORMAT=CSV file=result.csv {(1MEG*V(p)/(V(n)-V(p)))/50u*150u}
+.print DC FORMAT=CSV file=result.csv {(V(n)*150u)/(-I(Vn)*50u)}
+
+
+.include "../../../../design.xyce"
+.lib "../../../../sm141064.xyce" res_typical
+
+.end
\ No newline at end of file
diff --git a/models/xyce/testing/regression/resistor_r/models_regression.py b/models/xyce/testing/regression/resistor_r/models_regression.py
new file mode 100644
index 0000000..92d38b4
--- /dev/null
+++ b/models/xyce/testing/regression/resistor_r/models_regression.py
@@ -0,0 +1,324 @@
+"""
+Usage:
+  models_regression.py [--num_cores=<num>]
+
+  -h, --help             Show help text.
+  -v, --version          Show version.
+  --num_cores=<num>      Number of cores to be used by simulator
+"""
+
+from fileinput import filename
+from re import T
+from docopt import docopt
+import pandas as pd 
+import numpy as np
+import os 
+from jinja2 import Template
+import concurrent.futures
+import shutil
+import warnings
+warnings.simplefilter(action='ignore', category=FutureWarning)
+
+def call_simulator(file_name):
+    """Call simulation commands to perform simulation.
+    Args:
+        file_name (str): Netlist file name.
+    """
+    os.system(f"Xyce -hspice-ext all {file_name} -l {file_name}.log")
+
+def ext_measured_a(device,vn,d_in, r_sim, corner):
+    
+    # Get dimensions used for each device 
+    dirpath = f"{device}_{r_sim}_{corner}"
+    dimensions = pd.read_csv(f"{dirpath}/{device}.csv",usecols=["w (um)" , "l (um)"])
+    loops = dimensions["l (um)"].count()
+    
+    # Extracting measured values for each W & L 
+    for i in range (0,loops):
+        width  = dimensions["w (um)"].iloc[i]
+        length = dimensions["l (um)"].iloc[i]
+                                      
+        # measured r   
+        col_list = [f"{vn}",f"{d_in}_{corner} Rev9 "]
+        df_measured = pd.read_csv(f"{dirpath}/{device}.csv",usecols=col_list)
+        df_measured.columns = [f"{vn}","value"]
+        df_measured.loc[i:i].to_csv(f"{dirpath}/measured_{r_sim}/{i}_measured_w{width}_l{length}.csv", index=False)
+
+def ext_measured_b(device,vn,d_in, r_sim, corner):
+    
+    # Get dimensions used for each device 
+    dirpath = f"{device}_{r_sim}_{corner}_temp"
+    dimensions = pd.read_csv(f"{dirpath}/{device}.csv",usecols=["Temperature (C)" , "l (um)"])
+    if "rm" in device or "tm" in device:        
+        loops = dimensions["l (um)"].count()
+    else:
+        loops = 11
+    
+    # Extracting measured values for each W & L 
+    for i in range (0,loops):
+        temp   = dimensions["Temperature (C)"].iloc[i]
+        length = dimensions["l (um)"].iloc[i]
+        if "rm" in device or "tm" in device or "_u" in device:        
+            width  = length
+        else:
+            width  = length/2
+                                                  
+        # measured r   
+        col_list = [f"{vn}",f"{d_in}_{corner} Rev9 "]
+        df_measured = pd.read_csv(f"{dirpath}/{device}.csv",usecols=col_list)
+        df_measured.columns = [f"{vn}","value"]
+        df_measured.loc[i:i].to_csv(f"{dirpath}/measured_{r_sim}/{i}_measured_w{width}_l{length}.csv", index=False)
+
+def ext_simulated_a(device,vn,d_in,r_sim, corner,sign):
+    
+    if "rm" in device or "tm" in device:
+        netlist_tmp = f"./device_netlists/2term_res_a.spice"
+    else:
+        netlist_tmp = f"./device_netlists/3term_res_a.spice"        
+
+    # Get dimensions used for each device 
+    dirpath = f"{device}_{r_sim}_{corner}"
+    dimensions = pd.read_csv(f"{dirpath}/{device}.csv",usecols=["w (um)" , "l (um)"])
+    loops = dimensions["l (um)"].count()
+    temp = 25 
+    # Extracting measured values for each W & L 
+    for i in range (0,loops):
+        width  = dimensions["w (um)"].iloc[i]
+        length = dimensions["l (um)"].iloc[i]
+      
+        with open(netlist_tmp) as f:
+            tmpl = Template(f.read())
+            os.makedirs(f"{dirpath}/{device}_netlists_{r_sim}",exist_ok=True)
+            with open(f"{dirpath}/{device}_netlists_{r_sim}/{i}_{device}_netlist_w{width}_l{length}.spice", "w") as netlist:
+                netlist.write(tmpl.render(device = device, width = width, length = length , corner = corner, i = i , sign = sign))
+            netlist_path  = f"{dirpath}/{device}_netlists_{r_sim}/{i}_{device}_netlist_w{width}_l{length}.spice" 
+            # Running ngspice for each netlist 
+            with concurrent.futures.ProcessPoolExecutor(max_workers=workers_count) as executor:
+                executor.submit(call_simulator, netlist_path)
+            
+            # Writing simulated data 
+            df_simulated = pd.read_csv(f"{dirpath}/simulated_r/{i}_simulated_w{width}_l{length}.csv",header=0)
+            # df_simulated.to_csv(f"{dirpath}/simulated_r/{i}_simulated_w{width}_l{length}.csv",index= False)    
+
+            # Writing final simulated data                 
+            df_simulated.columns = [f"value"]#,"value"]
+            df_simulated.to_csv(f"{dirpath}/simulated_r/{i}_simulated_w{width}_l{length}.csv",index= False) 
+
+def ext_simulated_b(device,vn,d_in,r_sim, corner,sign):
+    
+    if "rm" in device or "tm" in device:
+        netlist_tmp = f"./device_netlists/2term_res_b.spice"
+    else:
+        netlist_tmp = f"./device_netlists/3term_res_b.spice"        
+
+    # Get dimensions used for each device 
+    dirpath = f"{device}_{r_sim}_{corner}_temp"
+    dimensions = pd.read_csv(f"{dirpath}/{device}.csv",usecols=["Temperature (C)" , "l (um)"])
+    if "rm" in device or "tm" in device:        
+        loops = dimensions["l (um)"].count()
+    else:
+        loops = 11
+            
+    # Extracting measured values for each W & L 
+    for i in range (0,loops):
+        temp   = dimensions["Temperature (C)"].iloc[i]
+        length = dimensions["l (um)"].iloc[i]
+        if "rm" in device or "tm" in device or "_u" in device:        
+            width  = length
+        else:
+            width  = length/2            
+        
+        with open(netlist_tmp) as f:
+            tmpl = Template(f.read())
+            os.makedirs(f"{dirpath}/{device}_netlists_{r_sim}",exist_ok=True)
+            with open(f"{dirpath}/{device}_netlists_{r_sim}/{i}_{device}_netlist_w{width}_l{length}.spice", "w") as netlist:
+                netlist.write(tmpl.render(device = device, temp = temp , width = width, length = length , corner = corner, i = i , sign = sign))
+            netlist_path  = f"{dirpath}/{device}_netlists_{r_sim}/{i}_{device}_netlist_w{width}_l{length}.spice" 
+            # Running ngspice for each netlist 
+            with concurrent.futures.ProcessPoolExecutor(max_workers=workers_count) as executor:
+                executor.submit(call_simulator, netlist_path)
+            
+            # Writing simulated data 
+            df_simulated = pd.read_csv(f"{dirpath}/simulated_r/{i}_simulated_w{width}_l{length}.csv",header=0)
+            df_simulated.to_csv(f"{dirpath}/simulated_r/{i}_simulated_w{width}_l{length}.csv",index= False)    
+
+            # Writing final simulated data                 
+            df_simulated.columns = [f"value"]#,"value"]
+            df_simulated.to_csv(f"{dirpath}/simulated_r/{i}_simulated_w{width}_l{length}.csv",index= False) 
+                  
+def error_cal_a(device,vn,d_in,r_sim, corner):
+    
+    df_final = pd.DataFrame()
+    # Get dimensions used for each device 
+    dirpath = f"{device}_{r_sim}_{corner}"
+    dimensions = pd.read_csv(f"{dirpath}/{device}.csv",usecols=["w (um)" , "l (um)"])
+    loops = dimensions["l (um)"].count()
+    temp = 25 
+    # Extracting measured values for each W & L 
+    for i in range (0,loops):
+        width  = dimensions["w (um)"].iloc[i]
+        length = dimensions["l (um)"].iloc[i]
+             
+        measured  = pd.read_csv(f"{dirpath}/measured_{r_sim}/{i}_measured_w{width}_l{length}.csv")
+        simulated = pd.read_csv(f"{dirpath}/simulated_{r_sim}/{i}_simulated_w{width}_l{length}.csv")
+
+        error_1 = round (100 * abs((abs(measured.iloc[:, 1]) - abs(simulated.iloc[:, 0]))/abs(measured.iloc[:, 1])),8)  
+
+        df_error = pd.DataFrame(data=[measured.iloc[:, 0],error_1]).transpose()        
+        df_error.to_csv(f"{dirpath}/error_{r_sim}/{i}_{device}_error_w{width}_l{length}.csv",index= False)
+        
+        # Mean error 
+        mean_error = (df_error[f"value"].mean())
+        # Max error 
+        max_error = df_error[f"value"].max()
+
+        df_final_ = {'Run no.': f'{i}', 'Device name': f'{dirpath}', 'Temperature': temp, 'Width': f'{width}', 'Length': f'{length}', 'Simulated_Val':f'{r_sim}','Mean error%':f'{"{:.2f}".format(mean_error)}', 'Max error%':f'{"{:.2f}".format(max_error)} '}
+        df_final = df_final.append(df_final_, ignore_index = True)
+    # Max mean error 
+    print (df_final)   
+    df_final.to_csv (f"{dirpath}/Final_report_{r_sim}.csv", index = False)
+    out_report = pd.read_csv (f"{dirpath}/Final_report_{r_sim}.csv")
+    print ("\n",f"Max. mean error = {out_report['Mean error%'].max()}%")    
+    print ("=====================================================================================================================================================")
+
+def error_cal_b(device,vn,d_in,r_sim, corner):
+    
+    df_final = pd.DataFrame()
+    # Get dimensions used for each device 
+    dirpath = f"{device}_{r_sim}_{corner}_temp"
+    dimensions = pd.read_csv(f"{dirpath}/{device}.csv",usecols=["Temperature (C)" , "l (um)"])
+    if "rm" in device or "tm" in device:        
+        loops = dimensions["l (um)"].count()
+    else:
+        loops = 11
+        
+    # Extracting measured values for each W & L 
+    for i in range (0,loops):
+        temp   = dimensions["Temperature (C)"].iloc[i]
+        length = dimensions["l (um)"].iloc[i]
+        if "rm" in device or "tm" in device or "_u" in device:        
+            width  = length
+        else:
+            width  = length/2   
+                         
+        measured  = pd.read_csv(f"{dirpath}/measured_{r_sim}/{i}_measured_w{width}_l{length}.csv")
+        simulated = pd.read_csv(f"{dirpath}/simulated_{r_sim}/{i}_simulated_w{width}_l{length}.csv")
+
+        error_1 = round (100 * abs((abs(measured.iloc[:, 1]) - abs(simulated.iloc[:, 0]))/abs(measured.iloc[:, 1])),8)  
+
+        df_error = pd.DataFrame(data=[measured.iloc[:, 0],error_1]).transpose()        
+        df_error.to_csv(f"{dirpath}/error_{r_sim}/{i}_{device}_error_w{width}_l{length}.csv",index= False)
+        
+        # Mean error 
+        mean_error = (df_error[f"value"].mean())
+        # Max error 
+        max_error = df_error[f"value"].max()
+
+        df_final_ = {'Run no.': f'{i}', 'Device name': f'{dirpath}', 'Temperature': temp, 'Width': f'{width}', 'Length': f'{length}', 'Simulated_Val':f'{r_sim}','Mean error%':f'{"{:.2f}".format(mean_error)}', 'Max error%':f'{"{:.2f}".format(max_error)} '}
+        df_final = df_final.append(df_final_, ignore_index = True)
+    # Max mean error 
+    print (df_final)   
+    df_final.to_csv (f"{dirpath}/Final_report_{r_sim}.csv", index = False)
+    out_report = pd.read_csv (f"{dirpath}/Final_report_{r_sim}.csv")
+    print ("\n",f"Max. mean error = {out_report['Mean error%'].max()}%")    
+    print ("=====================================================================================================================================================")
+
+def main():
+
+    # res W&L var. 
+    corners_a  = ["typical","ff","ss"]        
+    
+    devices_a  = ["nplus_u" , "pplus_u" , "nplus_s" , "pplus_s" , "npolyf_u" , "ppolyf_u" , "npolyf_s" , "ppolyf_s" , "ppolyf_u_1k" , "ppolyf_u_2k" , "ppolyf_u_1k_6p0" ,
+                  "ppolyf_u_2k_6p0" , "ppolyf_u_3k" , "rm1" , "rm2" , "rm3" , "tm6k" , "tm9k" , "tm11k" , "tm30k" , "nwell"]
+    
+    dev_data_a = ["RES01a-wl-nplus_u.nl_out"     ,"RES02a-wl-pplus_u.nl_out"       ,"RES03a-wl-nplus_s.nl_out"       , "RES04a-wl-pplus_s.nl_out"     , 
+                  "RES06a-wl-npolyf_u.nl_out"    ,"RES07a-wl-ppolyf_u.nl_out"      ,"RES08a-wl-npolyf_s.nl_out"      , "RES09a-wl-ppolyf_s.nl_out"    , "RES10a-wl-ppolyf_u_1k.nl_out", 
+                  "RES11a-wl-ppolyf_u_2k.nl_out" ,"RES12a-wl-ppolyf_u_1k_6p0.nl_o" ,"RES13a-wl-ppolyf_u_2k_6p0.nl_o" , "RES14a-wl-ppolyf_u_3k.nl_out" , 
+                  "RES15a-wl-rm1.nl_out"         , "RES16a-wl-rm2.nl_out"          , "RES17a-wl-rm3.nl_out"          , "RES18a-wl-tm6k.nl_out"        , "RES19a-wl-tm9k.nl_out" ,
+                  "RES20a-wl-tm11k.nl_out"       , "RES21a-wl-tm30k.nl_out" ,"RES05a-wl-nwell.nl_out"]
+    
+    sign_a     = ["+" , "-" , "+" , "-" , "+" , "+" , "-" , "+" , "-" , "-" , "-" , "-" , "-" , "-" , "+" , "+" , "+" , "+" , "+" , "+", "+", ""]
+    measure_a  = ["r","corners", "res"]
+   
+    for corner in corners_a: 
+        for i,device in enumerate(devices_a): 
+            # Folder structure of measured values
+            r_sim, res_vn, res_in = measure_a[0], measure_a[1], measure_a[2]
+            dirpath = f"{device}_{r_sim}_{corner}"
+            if os.path.exists(dirpath) and os.path.isdir(dirpath):
+                shutil.rmtree(dirpath)
+            os.makedirs(f"{dirpath}/measured_{r_sim}",exist_ok=False)
+
+            # From xlsx to csv
+            read_file = pd.read_excel (f"../../180MCU_SPICE_DATA/Resistor/{dev_data_a[i]}.xlsx")
+            read_file.to_csv (f"{dirpath}/{device}.csv", index = False, header=True)
+
+            # Folder structure of simulated values 
+            os.makedirs(f"{dirpath}/simulated_{r_sim}",exist_ok=False)
+            os.makedirs(f"{dirpath}/error_{r_sim}",exist_ok=False)
+    
+            ext_measured_a (device,res_vn,res_in, r_sim, corner)
+            ext_simulated_a(device,res_vn,res_in,r_sim, corner,sign_a[i])
+            error_cal_a    (device,res_vn,res_in,r_sim, corner)            
+
+
+    # res temp_var
+    corners_b  = ["typical","ff","ss"]        
+    devices_b  = ["nplus_u" , "nplus_s", "pplus_u" , "pplus_s" , "nwell" , "npolyf_u" , "ppolyf_u" , "npolyf_s" , "ppolyf_s" , "ppolyf_u_1k" , "ppolyf_u_2k" , "ppolyf_u_1k_6p0" , "ppolyf_u_2k_6p0" , "ppolyf_u_3k" ,
+                  "rm1" , "rm2", "rm3" , "tm6k" , "tm9k" , "tm11k", "tm30k"]
+    dev_data_b = ["RES01b-temp-nplus_u.nl_out" , "RES03b-temp-nplus_s.nl_out", "RES02b-temp-pplus_u.nl_out" , "RES04b-temp-pplus_s.nl_out" , "RES05b-temp-nwell.nl_out" ,
+                  "RES06b-temp-npolyf_u.nl_out" , "RES07b-temp-ppolyf_u.nl_out" ,  "RES08b-temp-npolyf_s.nl_out" , "RES09b-temp-ppolyf_s.nl_out" , "RES10b-temp-ppolyf_u_1k.nl_out" ,
+                  "RES11b-temp-ppolyf_u_2k.nl_out" , "RES12b-temp-ppolyf_u_1k_6p0.nl" , "RES13b-temp-ppolyf_u_2k_6p0.nl" , "RES14b-temp-ppolyf_u_3k.nl_out" ,   
+                  "RES15b-temp-rm1.nl_out", "RES16b-temp-rm2.nl_out" , "RES17b-temp-rm3.nl_out" ,
+                  "RES18b-temp-tm6k.nl_out", "RES19b-temp-tm9k.nl_out" , "RES20b-temp-tm11k.nl_out", "RES21b-temp-tm30k.nl_out"]
+    
+    sign_b     = ["+" , "+", "-" , "-" , "+" , "+" , "-" ,"+" , "-" , "-" , "-" , "-" , "-" , "-" , "+" , "+" , "+" , "+" , "+" , "+", "+"]
+    measure_b  = ["r","corners", "res"]
+   
+    for corner in corners_b: 
+        for i,device in enumerate(devices_b): 
+            # Folder structure of measured values
+            r_sim, res_vn, res_in = measure_b[0], measure_b[1], measure_b[2]
+            dirpath = f"{device}_{r_sim}_{corner}_temp"
+            if os.path.exists(dirpath) and os.path.isdir(dirpath):
+                shutil.rmtree(dirpath)
+            os.makedirs(f"{dirpath}/measured_{r_sim}",exist_ok=False)
+
+            # From xlsx to csv
+            read_file = pd.read_excel (f"../../180MCU_SPICE_DATA/Resistor/{dev_data_b[i]}.xlsx")
+            read_file.to_csv (f"{dirpath}/{device}.csv", index = False, header=True)
+
+            # Folder structure of simulated values 
+            os.makedirs(f"{dirpath}/simulated_{r_sim}",exist_ok=False)
+            os.makedirs(f"{dirpath}/error_{r_sim}",exist_ok=False)
+    
+            ext_measured_b (device,res_vn,res_in, r_sim, corner)
+            ext_simulated_b(device,res_vn,res_in,r_sim, corner,sign_b[i])
+            error_cal_b    (device,res_vn,res_in,r_sim, corner)  
+
+    for corner in corners_a: 
+        for i,device in enumerate(devices_a): 
+            # Folder structure of measured values
+            r_sim, res_vn, res_in = measure_a[0], measure_a[1], measure_a[2]
+            error_cal_a    (device,res_vn,res_in,r_sim, corner)            
+
+   
+    for corner in corners_b: 
+        for i,device in enumerate(devices_b): 
+            # Folder structure of measured values
+            r_sim, res_vn, res_in = measure_b[0], measure_b[1], measure_b[2]
+            error_cal_b    (device,res_vn,res_in,r_sim, corner)
+
+
+# # ================================================================
+# -------------------------- MAIN --------------------------------
+# ================================================================
+        
+if __name__ == "__main__":
+    
+    # Args 
+    arguments     = docopt(__doc__, version='comparator: 0.1')
+    workers_count = os.cpu_count()*2 if arguments["--num_cores"] == None else int(arguments["--num_cores"])
+    
+    # Calling main function 
+    main()
diff --git a/models/xyce/testing/sc_regression/gf180mcu_fd_sc_mcu7t5v0/device_netlists/gf180mcu_fd_sc_mcu7t5v0__inv_1.spice b/models/xyce/testing/sc_regression/gf180mcu_fd_sc_mcu7t5v0/device_netlists/gf180mcu_fd_sc_mcu7t5v0__inv_1.spice
new file mode 100644
index 0000000..9eb17df
--- /dev/null
+++ b/models/xyce/testing/sc_regression/gf180mcu_fd_sc_mcu7t5v0/device_netlists/gf180mcu_fd_sc_mcu7t5v0__inv_1.spice
@@ -0,0 +1,43 @@
+* Copyright 2022 GlobalFoundries PDK Authors
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*      http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+
+* Sources
+Vin I 0 dc pulse(0 5 100p 1p 1p 100p 200p)
+Vdd VDD 0 dc {{volt}}
+
+* Main circuit
+X1 I ZN VDD VDD 0 0 gf180mcu_fd_sc_mcu7t5v0__inv_1
+
+* Temperature set
+.STEP TEMP {{temp}} -60 200
+
+* Analyses
+.tran 1p 200p
+.meas tran high_in FIND V(ZN) AT=100p
+.meas tran low_in  FIND V(ZN) AT=200p
+
+.print TRAN FORMAT=CSV file=inv/simulated/inv_{{process}}_{{temp}}c_{{volt}}v.csv high_in low_in
+
+
+* Libraries calling
+.include "../../../../../design.xyce"
+.lib "../../../../../sm141064.xyce" {{process}}
+
+.SUBCKT gf180mcu_fd_sc_mcu7t5v0__inv_1 I ZN VDD VNW VPW VSS
+xM_i_0 ZN I VSS VPW nmos_6p0 W=8.2e-07 L=6e-07
+xM_i_1 ZN I VDD VNW pmos_6p0 W=1.22e-06 L=5e-07
+.ENDS
+
+
+.end
diff --git a/models/xyce/testing/sc_regression/gf180mcu_fd_sc_mcu7t5v0/device_netlists/gf180mcu_fd_sc_mcu7t5v0__inv_1_run.spice b/models/xyce/testing/sc_regression/gf180mcu_fd_sc_mcu7t5v0/device_netlists/gf180mcu_fd_sc_mcu7t5v0__inv_1_run.spice
new file mode 100644
index 0000000..c4bd339
--- /dev/null
+++ b/models/xyce/testing/sc_regression/gf180mcu_fd_sc_mcu7t5v0/device_netlists/gf180mcu_fd_sc_mcu7t5v0__inv_1_run.spice
@@ -0,0 +1,42 @@
+* Copyright 2022 GlobalFoundries PDK Authors
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*      http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+
+* Sources
+Vin I 0 dc pulse(0 5 100p 1p 1p 100p 200p)
+Vdd VDD 0 dc 5
+
+* Main circuit
+X1 I ZN VDD VDD 0 0 gf180mcu_fd_sc_mcu7t5v0__inv_1
+
+* Temperature set
+.STEP TEMP 25 -60 200
+
+* Analyses
+.tran 1p 200p
+.meas tran high_in FIND V(ZN) AT=100p
+.meas tran low_in  FIND V(ZN) AT=200p
+.print TRAN FORMAT=CSV file=inv_simulated.csv {high_in} {low_in}
+
+
+* Libraries calling
+.include "../../../../design.xyce"
+.lib "../../../../sm141064.xyce" typical
+
+.SUBCKT gf180mcu_fd_sc_mcu7t5v0__inv_1 I ZN VDD VNW VPW VSS
+xM_i_0 ZN I VSS VPW nmos_6p0 W=8.2e-07 L=6e-07
+xM_i_1 ZN I VDD VNW pmos_6p0 W=1.22e-06 L=5e-07
+.ENDS
+
+
+.end
diff --git a/models/xyce/testing/sc_regression/gf180mcu_fd_sc_mcu7t5v0/device_netlists/gf180mcu_fd_sc_mcu7t5v0__nand2_1.spice b/models/xyce/testing/sc_regression/gf180mcu_fd_sc_mcu7t5v0/device_netlists/gf180mcu_fd_sc_mcu7t5v0__nand2_1.spice
new file mode 100644
index 0000000..53ce93d
--- /dev/null
+++ b/models/xyce/testing/sc_regression/gf180mcu_fd_sc_mcu7t5v0/device_netlists/gf180mcu_fd_sc_mcu7t5v0__nand2_1.spice
@@ -0,0 +1,47 @@
+* Copyright 2022 GlobalFoundries PDK Authors
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*      http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+
+* Sources
+Vdd VDD 0 dc {{volt}}
+Vin1 I1 0 dc pulse(0 5 200p 1p 1p 200p 400p)
+Vin2 I2 0 dc pulse(0 5 400p 1p 1p 400p 800p)
+
+* Main circuit
+X1 I1 I2 ZN VDD VDD 0 0 gf180mcu_fd_sc_mcu7t5v0__nand2_1
+
+* Temperature set
+.STEP TEMP {{temp}} -60 200
+
+* Analyses
+.tran 1p 800p
+.meas tran o0 FIND V(ZN) AT=200p
+.meas tran o1  FIND V(ZN) AT=400p
+.meas tran o2 FIND V(ZN) AT=600p
+.meas tran o3  FIND V(ZN) AT=800p
+.print TRAN FORMAT=CSV file=nand2/simulated/nand2_{{process}}_{{temp}}c_{{volt}}v.csv o0 o1 o2 o3
+
+
+* Libraries calling
+.include "../../../../../design.xyce"
+.lib "../../../../../sm141064.xyce" {{process}}
+
+.SUBCKT gf180mcu_fd_sc_mcu7t5v0__nand2_1 A1 A2 ZN VDD VNW VPW VSS
+xM_i_1 net_0 A2 VSS VPW nmos_6p0 W=8.2e-07 L=6e-07
+xM_i_0 ZN A1 net_0 VPW nmos_6p0 W=8.2e-07 L=6e-07
+xM_i_3 ZN A2 VDD VNW pmos_6p0 W=1.13e-06 L=5e-07
+xM_i_2 VDD A1 ZN VNW pmos_6p0 W=1.13e-06 L=5e-07
+.ENDS
+
+
+.end
diff --git a/models/xyce/testing/sc_regression/gf180mcu_fd_sc_mcu7t5v0/device_netlists/gf180mcu_fd_sc_mcu7t5v0__nand2_1_run.spice b/models/xyce/testing/sc_regression/gf180mcu_fd_sc_mcu7t5v0/device_netlists/gf180mcu_fd_sc_mcu7t5v0__nand2_1_run.spice
new file mode 100644
index 0000000..6f7509c
--- /dev/null
+++ b/models/xyce/testing/sc_regression/gf180mcu_fd_sc_mcu7t5v0/device_netlists/gf180mcu_fd_sc_mcu7t5v0__nand2_1_run.spice
@@ -0,0 +1,48 @@
+* Copyright 2022 GlobalFoundries PDK Authors
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*      http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+
+* Sources
+Vdd VDD 0 dc 5
+Vin1 I1 0 dc pulse(0 5 200p 1p 1p 200p 400p)
+Vin2 I2 0 dc pulse(0 5 400p 1p 1p 400p 800p)
+
+* Main circuit
+X1 I1 I2 ZN VDD VDD 0 0 gf180mcu_fd_sc_mcu7t5v0__nand2_1
+
+* Temperature set
+.temp 25
+.options tnom=25
+
+* Analyses
+.tran 1p 800p
+.meas tran o0 FIND V(ZN) AT=200p
+.meas tran o1  FIND V(ZN) AT=400p
+.meas tran o2 FIND V(ZN) AT=600p
+.meas tran o3  FIND V(ZN) AT=800p
+.print TRAN FORMAT=CSV file=nand2_simulated.csv o0 o1 o2 o3
+
+
+* Libraries calling
+.include "../../../../design.xyce"
+.lib "../../../../sm141064.xyce" typical
+
+.SUBCKT gf180mcu_fd_sc_mcu7t5v0__nand2_1 A1 A2 ZN VDD VNW VPW VSS
+xM_i_1 net_0 A2 VSS VPW nmos_6p0 W=8.2e-07 L=6e-07
+xM_i_0 ZN A1 net_0 VPW nmos_6p0 W=8.2e-07 L=6e-07
+xM_i_3 ZN A2 VDD VNW pmos_6p0 W=1.13e-06 L=5e-07
+xM_i_2 VDD A1 ZN VNW pmos_6p0 W=1.13e-06 L=5e-07
+.ENDS
+
+
+.end
diff --git a/models/xyce/testing/sc_regression/gf180mcu_fd_sc_mcu7t5v0/device_netlists/gf180mcu_fd_sc_mcu7t5v0__or3_1.spice b/models/xyce/testing/sc_regression/gf180mcu_fd_sc_mcu7t5v0/device_netlists/gf180mcu_fd_sc_mcu7t5v0__or3_1.spice
new file mode 100644
index 0000000..01a7534
--- /dev/null
+++ b/models/xyce/testing/sc_regression/gf180mcu_fd_sc_mcu7t5v0/device_netlists/gf180mcu_fd_sc_mcu7t5v0__or3_1.spice
@@ -0,0 +1,56 @@
+* Copyright 2022 GlobalFoundries PDK Authors
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*      http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+
+* Sources
+Vdd VDD 0 dc {{volt}}
+Vin1 I1 0 dc pulse(0 5 200p 1p 1p 200p 400p)
+Vin2 I2 0 dc pulse(0 5 400p 1p 1p 400p 800p)
+Vin3 I3 0 dc pulse(0 5 800p 1p 1p 800p 1600p)
+
+* Main circuit
+X1 I1 I2 I3 ZN VDD VDD 0 0 gf180mcu_fd_sc_mcu7t5v0__or3_1
+
+* Temperature set
+.STEP TEMP {{temp}} -60 200
+
+* Analyses
+.tran 1p 1600p
+.meas tran o0 FIND V(ZN) AT=200p
+.meas tran o1 FIND V(ZN) AT=400p
+.meas tran o2 FIND V(ZN) AT=600p
+.meas tran o3 FIND V(ZN) AT=800p
+.meas tran o4 FIND V(ZN) AT=1000p
+.meas tran o5 FIND V(ZN) AT=1200p
+.meas tran o6 FIND V(ZN) AT=1400p
+.meas tran o7 FIND V(ZN) AT=1600p
+.print TRAN FORMAT=CSV file=or3/simulated/or3_{{process}}_{{temp}}c_{{volt}}v.csv o0 o1 o2 o3 o4 o5 o6 o7
+
+
+* Libraries calling
+.include "../../../../../design.xyce"
+.lib "../../../../../sm141064.xyce" {{process}}
+
+.SUBCKT gf180mcu_fd_sc_mcu7t5v0__or3_1 A1 A2 A3 Z VDD VNW VPW VSS
+M_i_2 VSS A1 Z_neg VPW nmos_6p0 W=4e-07 L=6e-07
+M_i_3 Z_neg A2 VSS VPW nmos_6p0 W=4e-07 L=6e-07
+M_i_4 VSS A3 Z_neg VPW nmos_6p0 W=4e-07 L=6e-07
+M_i_0 Z Z_neg VSS VPW nmos_6p0 W=8.2e-07 L=6e-07
+M_i_5 net_0 A1 Z_neg VNW pmos_6p0 W=5.6e-07 L=5e-07
+M_i_6 net_1 A2 net_0 VNW pmos_6p0 W=5.6e-07 L=5e-07
+M_i_7 VDD A3 net_1 VNW pmos_6p0 W=5.6e-07 L=5e-07
+M_i_1 Z Z_neg VDD VNW pmos_6p0 W=1.22e-06 L=5e-07
+.ENDS
+
+
+.end
diff --git a/models/xyce/testing/sc_regression/gf180mcu_fd_sc_mcu7t5v0/device_netlists/gf180mcu_fd_sc_mcu7t5v0__or3_1_run.spice b/models/xyce/testing/sc_regression/gf180mcu_fd_sc_mcu7t5v0/device_netlists/gf180mcu_fd_sc_mcu7t5v0__or3_1_run.spice
new file mode 100644
index 0000000..bfa90e9
--- /dev/null
+++ b/models/xyce/testing/sc_regression/gf180mcu_fd_sc_mcu7t5v0/device_netlists/gf180mcu_fd_sc_mcu7t5v0__or3_1_run.spice
@@ -0,0 +1,59 @@
+* Copyright 2022 GlobalFoundries PDK Authors
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*      http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+
+* Sources
+Vdd VDD 0 dc 5
+Vin1 I1 0 dc pulse(0 5 200p 1p 1p 200p 400p)
+Vin2 I2 0 dc pulse(0 5 400p 1p 1p 400p 800p)
+Vin3 I3 0 dc pulse(0 5 800p 1p 1p 800p 1600p)
+
+* Main circuit
+X1 I1 I2 I3 ZN VDD VDD 0 0 gf180mcu_fd_sc_mcu7t5v0__or3_1
+
+* Temperature set
+.temp 25
+.options tnom=25
+
+* Analyses
+.control
+tran 1p 1600p
+meas tran o0 FIND V(ZN) AT=200p
+meas tran o1 FIND V(ZN) AT=400p
+meas tran o2 FIND V(ZN) AT=600p
+meas tran o3 FIND V(ZN) AT=800p
+meas tran o4 FIND V(ZN) AT=1000p
+meas tran o5 FIND V(ZN) AT=1200p
+meas tran o6 FIND V(ZN) AT=1400p
+meas tran o7 FIND V(ZN) AT=1600p
+
+wrdata or3/or3_simulated.csv {o0} {o1} {o2} {o3} {o4} {o5} {o6} {o7}
+.endc
+
+* Libraries calling
+.include "../../../../design.xyce"
+.lib "../../../../sm141064.xyce" typical
+
+.SUBCKT gf180mcu_fd_sc_mcu7t5v0__or3_1 A1 A2 A3 Z VDD VNW VPW VSS
+M_i_2 VSS A1 Z_neg VPW nmos_6p0 W=4e-07 L=6e-07
+M_i_3 Z_neg A2 VSS VPW nmos_6p0 W=4e-07 L=6e-07
+M_i_4 VSS A3 Z_neg VPW nmos_6p0 W=4e-07 L=6e-07
+M_i_0 Z Z_neg VSS VPW nmos_6p0 W=8.2e-07 L=6e-07
+M_i_5 net_0 A1 Z_neg VNW pmos_6p0 W=5.6e-07 L=5e-07
+M_i_6 net_1 A2 net_0 VNW pmos_6p0 W=5.6e-07 L=5e-07
+M_i_7 VDD A3 net_1 VNW pmos_6p0 W=5.6e-07 L=5e-07
+M_i_1 Z Z_neg VDD VNW pmos_6p0 W=1.22e-06 L=5e-07
+.ENDS
+
+
+.end
diff --git a/models/xyce/testing/sc_regression/gf180mcu_fd_sc_mcu7t5v0/models_regression.py b/models/xyce/testing/sc_regression/gf180mcu_fd_sc_mcu7t5v0/models_regression.py
new file mode 100644
index 0000000..c61d72a
--- /dev/null
+++ b/models/xyce/testing/sc_regression/gf180mcu_fd_sc_mcu7t5v0/models_regression.py
@@ -0,0 +1,140 @@
+"""
+Usage:
+  models_regression.py [--num_cores=<num>]
+
+  -h, --help             Show help text.
+  -v, --version          Show version.
+  --num_cores=<num>      Number of cores to be used by simulator
+"""
+
+from cmath import inf
+from re import L, T
+from docopt import docopt
+import pandas as pd 
+import numpy as np
+import os 
+from jinja2 import Template
+import concurrent.futures
+import shutil
+import warnings
+warnings.simplefilter(action='ignore', category=FutureWarning)
+
+def call_simulator(file_name):
+    """Call simulation commands to perform simulation.
+    Args:
+        file_name (str): Netlist file name.
+    """
+    os.system(f"Xyce -hspice-ext all {file_name} -l {file_name}.log")
+
+def ext_measured(device, table):
+
+    # Generate CSVs with truth tables
+    df = pd.DataFrame(data=table)
+    df.set_index(df.columns[0])
+    new_header = df.iloc[0]
+    df = df[1:]
+    df.columns = new_header
+    df.to_csv(f"{device}/{device}_measured.csv", index = False)
+
+def ext_simulated(device, processes, volts, temps):
+
+    # Get all corners simulated
+    for process in processes:
+        for volt in volts:
+            for temp in temps:
+                with open(f"device_netlists/gf180mcu_fd_sc_mcu7t5v0__{device}_1.spice") as f:
+                    tmpl = Template(f.read())
+                netlist_path  = f"{device}/{device}_netlists/{device}_{process}_{temp}c_{volt}v.spice"
+                with open(netlist_path, "w") as netlist:
+                    netlist.write(tmpl.render(process = process, volt = volt , temp = temp ))
+
+                # Running ngspice for each netlist 
+                with concurrent.futures.ProcessPoolExecutor(max_workers=workers_count) as executor:
+                    executor.submit(call_simulator, netlist_path)
+
+                df_simulated = pd.read_csv(f"{device}/simulated/{device}_{process}_{temp}c_{volt}v.csv",header=0)
+                results = []
+                for i, col in enumerate(df_simulated.columns):
+                    if df_simulated.iloc[-1].iloc[i] > 2.5:
+                        results.append(1)
+                    else:
+                        results.append(0)
+                df_measured = pd.read_csv(f"{device}/{device}_measured.csv",header=0)
+                df = df_measured
+                df_measured.drop(df_measured.columns[len(df_measured.columns)-1], axis=1, inplace=True)
+                df_measured['output'] = results[1:]
+                df_measured.to_csv(f"{device}/simulated/{device}_{process}_{temp}c_{volt}v.csv",index= False)
+
+def error_cal(device, processes, volts, temps):
+
+    print (f"\n\nSimulation results of {device}")
+    measured  = pd.read_csv(f"{device}/{device}_measured.csv")
+    for process in processes:
+        for volt in volts:
+            for temp in temps:
+                simulated = pd.read_csv(f"{device}/simulated/{device}_{process}_{temp}c_{volt}v.csv")
+
+                res = (measured == simulated).all().all()
+                print ("{:^5s} in PVT of {:^7s}, {:^3s}V, {:^3s}C functional simulation = {}".format(device, process, volt, temp, res))    
+    print ("================================================================================================\n")
+
+def main():
+
+    devices = ["inv","nand2","or3"]
+
+    # Generate truth tables data
+    inv_table = [["input","output"],
+                 [0,1],
+                 [1,0]]
+
+    nand2_table = [["input1","input2","output"],
+                   [0,0,1],
+                   [0,1,1],
+                   [1,0,1],
+                   [1,1,0]]
+
+    or3_table = [["input1","input2","input3","output"],
+                 [0,0,0,0],
+                 [0,0,1,1],
+                 [0,1,0,1],
+                 [0,1,1,1],
+                 [1,0,0,1],
+                 [1,0,1,1],
+                 [1,1,0,1],
+                 [1,1,1,1]]
+
+    tables = [inv_table,nand2_table,or3_table]
+
+    processes   = ["typical","ff","ss"]
+    volts       = ["5", "4.5", "5.5"]
+    temps       = ["25", "-40", "125"]
+
+    for i, device in enumerate(devices): 
+        # Folder structure of measured values
+        if os.path.exists(device) and os.path.isdir(device):
+            shutil.rmtree(device)
+        os.makedirs(device)
+
+        # Folder structure of simulated values
+        os.makedirs(f"{device}/{device}_netlists",exist_ok=True)
+        os.makedirs(f"{device}/simulated",exist_ok=True)
+        
+        ext_measured (device, tables[i])
+        # =========== Simulate ==============
+        ext_simulated(device, processes, volts, temps)
+
+        # ============ Results ==============
+        error_cal    (device, processes, volts, temps)
+
+# ================================================================
+# -------------------------- MAIN --------------------------------
+# ================================================================
+
+if __name__ == "__main__":
+
+    # Args
+    arguments     = docopt(__doc__, version='comparator: 0.1')
+    workers_count = os.cpu_count()*2 if arguments["--num_cores"] == None else int(arguments["--num_cores"])
+
+    # Calling main function 
+    main()
diff --git a/models/xyce/testing/smoke_test/inv_xyce.spice b/models/xyce/testing/smoke_test/inv_xyce.spice
new file mode 100644
index 0000000..ada6d54
--- /dev/null
+++ b/models/xyce/testing/smoke_test/inv_xyce.spice
@@ -0,0 +1,26 @@
+** INV_tb
+Vdd Vdd 0 3.3
+Vin Vin 0 dc pulse(0 3.3 0 50p 50p 150p 300p)
+X1 Vdd Vout Vin 0 INV
+
+.measure tran tphl TRIG v(Vin) VAL={0.5*3.3} RISE=2 TARG v(Vout) VAL={0.5*3.3} FALL=2
+.measure tran tplh TRIG v(Vin) VAL={0.5*3.3} FALL=1 TARG v(Vout) VAL={0.5*3.3} RISE=1
+.measure tran tpd param = {(tplh+tphl)/2}
+
+.STEP TEMP {{temp}} -60 200
+.tran 5p 800p
+.print tran FORMAT=CSV file={{run_path}}/simulation/inv_W{{width}}_L{{length}}_T{{temp}}_{{corner}}.csv {tpd}
+
+
+.include "../../design.xyce"
+.lib "../../sm141064.xyce" {{corner}}
+
+
+.subckt INV  VDD Vout Vin GND
+XM1 Vout Vin GND GND nmos_3p3 W={{width}}u L={{length}}u 
+*ad={{AD}}u pd={{PD}}u as={{AS}}u ps={{PS}}u
+XM2 Vout Vin VDD VDD pmos_3p3 W={{width_p}}u L={{length}}u 
+*ad={{AD_p}}u pd={{PD_p}}u as={{AD_p}}u ps={{PD_p}}u
+.ends
+
+.end
diff --git a/models/xyce/testing/smoke_test/xyce_smoke_test.py b/models/xyce/testing/smoke_test/xyce_smoke_test.py
new file mode 100644
index 0000000..129157f
--- /dev/null
+++ b/models/xyce/testing/smoke_test/xyce_smoke_test.py
@@ -0,0 +1,102 @@
+"""
+Usage:
+  smoke_test.py [--num_cores=<num>]
+
+  -h, --help             Show help text.
+  -v, --version          Show version.
+  --num_cores=<num>      Number of cores to be used by simulator
+"""
+
+import re
+from docopt import docopt
+import pandas as pd 
+import os 
+from jinja2 import Template
+import concurrent.futures
+import datetime
+import warnings
+warnings.simplefilter(action='ignore', category=FutureWarning)
+
+def call_simulator(file_name):
+    """Call simulation commands to perform simulation.
+    Args:
+        file_name (str): Netlist file name.
+    """
+    os.system(f"Xyce -hspice-ext all {file_name} -l {file_name}.log")
+
+def get_sizes(models_path):
+    sizes = []
+    with open(models_path, "r") as f:
+        device_model = f.read()
+        # for j, corner in enumerate(corners):
+        for i in range(16):
+            data = device_model.split(f".MODEL nmos_3p3.{i} NMOS")
+            data = data[1].split("+ LEVEL=14")
+            dimensions = re.findall("LMAX=([0-9e.-]+)[\w+\s=.{}-]+LMIN=([0-9e.-]+)[\w+\s=.{}-]+WMAX=([0-9e.-]+)[\w+\s=.{}-]+WMIN=([0-9e.-]+)[\w+\s=.{}-]+", data[0])
+            sizes.append(dimensions)
+    return sizes
+
+def get_results(run_path,sizes,temp,corner):
+    netlist_tmp = f"./inv_xyce.spice"
+    width  = float(sizes[0][3]) * 1000000
+    width_p = width * 1.5
+    length = float(sizes[0][1])  * 1000000
+    # AD = width * 0.24
+    # AD_p = AD * 1.5
+    # PD = 2 * (width + 0.24)
+    # PD_p = width + PD 
+    # AS = AD 
+    # PS = PD 
+    with open(netlist_tmp) as f:
+        tmpl = Template(f.read())
+        os.makedirs(f"{run_path}/netlists",exist_ok=True)
+        os.makedirs(f"{run_path}/simulation",exist_ok=True)
+        netlist_path  = f"{run_path}/netlists/inv_W{width}_L{length}_T{temp}_{corner}.spice"
+        with open(netlist_path, "w") as netlist:
+            netlist.write(tmpl.render(corner = corner, width = width,length = length, temp = temp , run_path = run_path, width_p = width_p))#, AD = AD , PD = PD , AS = AS , PS = PS, AD_p = AD_p, PD_p = PD_p ))
+        # Running ngspice for each netlist 
+        with concurrent.futures.ProcessPoolExecutor(max_workers=workers_count) as executor:
+            executor.submit(call_simulator, netlist_path)
+        
+        # Writing simulated data 
+        df_simulated = pd.read_csv(f"{run_path}/simulation/inv_W{width}_L{length}_T{temp}_{corner}.csv",header=0)
+    return [f"W{width}_L{length}_T{temp}_{corner}",df_simulated["{TPD}"].iloc[-1]]  
+
+def main():
+        
+    models_path = "../../sm141064.xyce"
+    temps = ["25","-40","125"]
+    corners = ["typical","ff","ss","fs","sf"]#,"stat"]
+
+    time = f"{datetime.datetime.now()}".replace(" ", "_")
+    run_path = f"../run_smoke_{time}"
+    os.makedirs(run_path,exist_ok=True)
+
+    sizes = get_sizes(models_path)
+    results = []
+
+    for corner in corners:
+        for temp in temps:
+            for size in sizes:
+                results.append(get_results(run_path, size, temp, corner))
+
+    df_results = pd.DataFrame(results)    
+    df_results.columns = ["run","tpd_result"]
+    df_results.to_csv(f"{run_path}/final_results.csv",index= False)
+
+    print (df_results)
+    
+
+    
+# # ================================================================
+# -------------------------- MAIN --------------------------------
+# ================================================================
+        
+if __name__ == "__main__":
+    
+    # Args 
+    arguments     = docopt(__doc__, version='smoke_test: 0.1')
+    workers_count = os.cpu_count()*2 if arguments["--num_cores"] == None else int(arguments["--num_cores"])
+    
+    # Calling main function 
+    main()