Skip to content

Commit

Permalink
apply black and flake8
Browse files Browse the repository at this point in the history
  • Loading branch information
@Mohamed-Gomaa1
Mohamed-Gomaa1 committed Jan 9, 2023
1 parent 6223d66 commit 398874a
Showing 1 changed file with 70 additions and 84 deletions.
154 changes: 70 additions & 84 deletions models/xyce/testing/regression/bjt_iv/models_regression.py
View file
Original file line number Diff line number Diff line change
Expand Up @@ -18,10 +18,19 @@
import warnings
import multiprocessing as mp
import glob

PASS_THRESH = 2.0
warnings.simplefilter(action="ignore", category=FutureWarning)
pd.options.mode.chained_assignment = None # default='warn'
MOS=["ibp=1.000E-06", "ibp=3.000E-06", "ibp=5.000E-06", "ibp=7.000E-06", "ibp=9.000E-06"]
MOS = [
"ibp=1.000E-06",
"ibp=3.000E-06",
"ibp=5.000E-06",
"ibp=7.000E-06",
"ibp=9.000E-06",
]


def call_simulator(file_name):
"""Call simulation commands to perform simulation.
Args:
Expand All @@ -30,7 +39,7 @@ def call_simulator(file_name):
os.system(f"Xyce -hspice-ext all {file_name} -l {file_name}.log 2>/dev/null")


def ext_measured(dirpath,device, vc, step, list_devices, ib):
def ext_measured(dirpath, device, vc, step, list_devices, ib):

# Get dimensions used for each device
dimensions = pd.read_csv(f"{dirpath}/{device}.csv", usecols=["corners"])
Expand Down Expand Up @@ -90,7 +99,7 @@ def ext_measured(dirpath,device, vc, step, list_devices, ib):
]
all_dfs.append(df_measured)
dfs = pd.concat(all_dfs, axis=1)
dfs.drop_duplicates(inplace=True)
dfs.drop_duplicates(inplace=True)
return dfs


Expand All @@ -115,8 +124,6 @@ def run_sim(dirpath, device, list_devices, temp=25):
info["temp"] = temp
info["dev"] = list_devices



temp_str = temp
list_devices_str = list_devices

Expand All @@ -130,13 +137,7 @@ def run_sim(dirpath, device, list_devices, temp=25):
tmpl = Template(f.read())
os.makedirs(f"{dirpath}/{device}_netlists", exist_ok=True)
with open(netlist_path, "w") as netlist:
netlist.write(
tmpl.render(
device=list_devices_str,
temp=temp_str

)
)
netlist.write(tmpl.render(device=list_devices_str, temp=temp_str))

# Running ngspice for each netlist
try:
Expand All @@ -155,7 +156,7 @@ def run_sim(dirpath, device, list_devices, temp=25):
return info


def run_sims( dirpath, list_devices,device, num_workers=mp.cpu_count()):
def run_sims(dirpath, list_devices, device, num_workers=mp.cpu_count()):
"""passing netlists to run_sim function
and storing the results csv files into dataframes
Expand All @@ -171,22 +172,19 @@ def run_sims( dirpath, list_devices,device, num_workers=mp.cpu_count()):
df1 = pd.read_csv(f"{dirpath}/{device}.csv", usecols=["corners"])
loops = (df1["corners"]).count()
temp_range = int(loops / 4)
df=pd.DataFrame()
df["dev"]=df1["corners"].dropna()
df["dev"][0:temp_range]=list_devices
df["dev"][temp_range:2*temp_range]=list_devices
df["dev"][2*temp_range:3*temp_range]=list_devices
df["dev"][3*temp_range:4*temp_range]=list_devices
df["temp"]=25
df["temp"][temp_range :2 * temp_range]=-40
df["temp"][2*temp_range :3 * temp_range]=125
df["temp"][3*temp_range :]=-175

df = pd.DataFrame()
df["dev"] = df1["corners"].dropna()
df["dev"][0:temp_range] = list_devices
df["dev"][temp_range : 2 * temp_range] = list_devices
df["dev"][2 * temp_range : 3 * temp_range] = list_devices
df["dev"][3 * temp_range : 4 * temp_range] = list_devices
df["temp"] = 25
df["temp"][temp_range : 2 * temp_range] = -40
df["temp"][2 * temp_range : 3 * temp_range] = 125
df["temp"][3 * temp_range :] = -175

results = []
with concurrent.futures.ThreadPoolExecutor(
max_workers=num_workers
) as executor:
with concurrent.futures.ThreadPoolExecutor(max_workers=num_workers) as executor:
futures_list = []
for j, row in df.iterrows():
futures_list.append(
Expand All @@ -206,7 +204,7 @@ def run_sims( dirpath, list_devices,device, num_workers=mp.cpu_count()):
except Exception as exc:
print("Test case generated an exception: %s" % (exc))
sf = glob.glob(f"{dirpath}/simulated/*.csv")

# sweeping on all generated cvs files
for i in range(len(sf)):
sdf = pd.read_csv(
Expand All @@ -217,22 +215,16 @@ def run_sims( dirpath, list_devices,device, num_workers=mp.cpu_count()):
sweep = int(sdf[0].count() / len(MOS))
new_array = np.empty((sweep, 1 + int(sdf.shape[0] / sweep)))

new_array[:, 0] = sdf.iloc[1:sweep+1, 0]
new_array[:, 0] = sdf.iloc[1 : sweep + 1, 0]
times = int(sdf.shape[0] / sweep)

for j in range(times):
new_array[:, (j + 1)] = sdf.iloc[(j * sweep)+1: ((j + 1) * sweep)+1 , 0]
new_array[:, (j + 1)] = sdf.iloc[(j * sweep) + 1 : ((j + 1) * sweep) + 1, 0]

# Writing final simulated data 1
sdf = pd.DataFrame(new_array)
sdf.rename(
columns={
1: "ibp1",
2: "ibp2",
3: "ibp3",
4: "ibp4",
5: "ibp5"
},
columns={1: "ibp1", 2: "ibp2", 3: "ibp3", 4: "ibp4", 5: "ibp5"},
inplace=True,
)
sdf.to_csv(sf[i], index=False)
Expand All @@ -242,14 +234,8 @@ def run_sims( dirpath, list_devices,device, num_workers=mp.cpu_count()):
return df



def error_cal(
sim_df: pd.DataFrame,
meas_df: pd.DataFrame,
device: str,
step,
ib,
vc
sim_df: pd.DataFrame, meas_df: pd.DataFrame, device: str, step, ib, vc
) -> None:
"""error function calculates the error between measured, simulated data
Expand All @@ -262,35 +248,37 @@ def error_cal(
"""
merged_dfs = list()
meas_df.to_csv(f"mos_iv_reg/{device}/{device}_measured.csv", index=False, header=True)
meas_df=pd.read_csv(f"mos_iv_reg/{device}/{device}_measured.csv")
for i in range (len(sim_df)):
t=sim_df["temp"].iloc[i]
dev=sim_df["dev"].iloc[i]
sim_path= f"mos_iv_reg/{device}/simulated/t{t}_simulated_{dev}.csv"
meas_df.to_csv(
f"mos_iv_reg/{device}/{device}_measured.csv", index=False, header=True
)
meas_df = pd.read_csv(f"mos_iv_reg/{device}/{device}_measured.csv")
for i in range(len(sim_df)):
t = sim_df["temp"].iloc[i]
dev = sim_df["dev"].iloc[i]
sim_path = f"mos_iv_reg/{device}/simulated/t{t}_simulated_{dev}.csv"

simulated_data = pd.read_csv(sim_path)
if i==0:
if i == 0:
measured_data = meas_df[
[
f"{ib}{step[0]}",
f"{ib}{step[1]}",
f"{ib}{step[2]}",
f"{ib}{step[3]}",
f"{ib}{step[4]}",

]
].copy()

measured_data.rename(
columns={
f"{ib}{step[0]}":"m_ibp1",
f"{ib}{step[1]}":"m_ibp2",
f"{ib}{step[2]}":"m_ibp3",
f"{ib}{step[3]}":"m_ibp4",
f"{ib}{step[4]}":"m_ibp5"},
inplace=True
)
columns={
f"{ib}{step[0]}": "m_ibp1",
f"{ib}{step[1]}": "m_ibp2",
f"{ib}{step[2]}": "m_ibp3",
f"{ib}{step[3]}": "m_ibp4",
f"{ib}{step[4]}": "m_ibp5",
},
inplace=True,
)
else:
measured_data = meas_df[
[
Expand All @@ -299,27 +287,27 @@ def error_cal(
f"{ib}{step[2]}.{i}",
f"{ib}{step[3]}.{i}",
f"{ib}{step[4]}.{i}",

]
].copy()

measured_data.rename(
columns={
f"{ib}{step[0]}.{i}":"m_ibp1",
f"{ib}{step[1]}.{i}":"m_ibp2",
f"{ib}{step[2]}.{i}":"m_ibp3",
f"{ib}{step[3]}.{i}":"m_ibp4",
f"{ib}{step[4]}.{i}":"m_ibp5"}
,inplace=True
)
measured_data["vcp"]=meas_df[f"{vc}"]
simulated_data["vcp"]=meas_df[f"{vc}"]
simulated_data["device"]=sim_df["dev"].iloc[i]
measured_data["device"]=sim_df["dev"].iloc[i]
simulated_data["temp"]=sim_df["temp"].iloc[i]
measured_data["temp"]=sim_df["temp"].iloc[i]
columns={
f"{ib}{step[0]}.{i}": "m_ibp1",
f"{ib}{step[1]}.{i}": "m_ibp2",
f"{ib}{step[2]}.{i}": "m_ibp3",
f"{ib}{step[3]}.{i}": "m_ibp4",
f"{ib}{step[4]}.{i}": "m_ibp5",
},
inplace=True,
)
measured_data["vcp"] = meas_df[f"{vc}"]
simulated_data["vcp"] = meas_df[f"{vc}"]
simulated_data["device"] = sim_df["dev"].iloc[i]
measured_data["device"] = sim_df["dev"].iloc[i]
simulated_data["temp"] = sim_df["temp"].iloc[i]
measured_data["temp"] = sim_df["temp"].iloc[i]
result_data = simulated_data.merge(measured_data, how="left")

result_data["step1_error"] = (
np.abs(result_data["ibp1"] - result_data["m_ibp1"])
* 100.0
Expand Down Expand Up @@ -359,9 +347,7 @@ def error_cal(
merged_dfs.append(result_data)
merged_out = pd.concat(merged_dfs)
merged_out.fillna(0, inplace=True)
merged_out.to_csv(
f"mos_iv_reg/{device}/error_analysis.csv", index=False
)
merged_out.to_csv(f"mos_iv_reg/{device}/error_analysis.csv", index=False)
return merged_out


Expand Down Expand Up @@ -405,13 +391,12 @@ def main():
# Folder structure of simulated values
os.makedirs(f"{dirpath}/simulated", exist_ok=False)


# =========== Simulate ==============
df=ext_measured(dirpath,device, vc[i], step, list_devices[i], ib[i])
sims=run_sims( dirpath,list_devices[i], device, num_workers=mp.cpu_count())
df = ext_measured(dirpath, device, vc[i], step, list_devices[i], ib[i])

sims = run_sims(dirpath, list_devices[i], device, num_workers=mp.cpu_count())
# ============ Results =============
merged_all=error_cal(sims,df,device,step,ib[i],vc[i])
merged_all = error_cal(sims, df, device, step, ib[i], vc[i])

for dev in list_devices[i]:
min_error_total = float()
Expand Down Expand Up @@ -463,6 +448,7 @@ def main():

print("\n\n")


# ================================================================
# -------------------------- MAIN --------------------------------
# ================================================================
Expand Down

0 comments on commit 398874a

Please sign in to comment.