In this example, we run a DC simulation of Qorvo SiC transistor.
This is the same code saved in the 10_DC.py, with more interactive descriptions.
After running below block of code, we have the simulation result in a Pandas DataFrame df.
from PyQSPICE import clsQSPICE as pqs
import math
import pandas as pd
import matplotlib as mpl
import matplotlib.pyplot as plt
pqs.chdir(".")
run = pqs("UJ3N065080")
run.InitPlot()
run.qsch2cir()
run.cir2qraw()
df = run.LoadQRAW(["Id(J1)"])
print(df) V2 Id(J1) Step
0 0.000000 1.160000e-12 0
1 0.002000 3.885333e-03 0
2 0.004001 7.770666e-03 0
3 0.006001 1.165600e-02 0
4 0.008002 1.554133e-02 0
... ... ... ...
29995 9.991998 9.254473e+01 5
29996 9.993999 9.255042e+01 5
29997 9.995999 9.255612e+01 5
29998 9.998000 9.256181e+01 5
29999 10.000000 9.256751e+01 5
[30000 rows x 3 columns]
As you can see the last "print()" command, this df has the drain-voltage V2 and the drain-currnet Id(J1), plus the index of .STEP simulations.
# Prepare a blank plotting area
plt.close("all")
fig, ax = plt.subplots(tight_layout=True)
# Plot DC curves of all ".STEP"
for i in range(run.sim['Nstep']):
df[df.Step == i].plot(ax=ax, x=run.sim['Xlbl'], y="Id(J1)", label="Step-" + str(i))
# Axis setup = begin =
ax.set_xlim(run.sim['Xmin'],run.sim['Xmax'])
ax.set_ylim(0,80)
ax.set_ylabel('Drain Current (A)', fontsize=14)
ax.set_xlabel('$V_{DS}$ (V)', fontsize=14)
ax.minorticks_on()
ax.grid(which='major', linewidth="0.5")
ax.grid(which='minor', linewidth="0.35")
# Axis setup = end =
# Legend
ax.text(0.1, 70, run.sim['StepInfo'])
plt.legend(ncol=1, loc="center left",fancybox=True)
# Save the Plot in PNG file
plt.savefig(run.path['base'] + "_plt.png", format='png', bbox_inches='tight')
plt.show()
plt.close('all')