| # 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() |
