| """ |
| 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() |
