In [1]:
# PyPlot_C5_inverter.py
from PyLTSpice.LTSpice_RawRead import RawRead as RawRead
import matplotlib.pyplot as plt
import numpy as np
LTR = RawRead("./spiceout/C5_inverter_TRAN_ngsp_bin.raw")
print(LTR.get_trace_names())
print("\n")
print(LTR.get_raw_property())
print("\n")
steps = LTR.get_steps()
num_steps = len(steps)
print('number of sweeps in the simulation:', num_steps)
# objects containing the data
t = LTR.get_trace('time')
Vo = LTR.get_trace('v(out)')
Vi = LTR.get_trace('v(in)')
t_delay = LTR.get_trace('t_delay')
t_rise = LTR.get_trace('t_rise')
t_fall = LTR.get_trace('t_fall')
# extract the data from the objects
if num_steps == 1:
time = t.get_time_axis(0)
Vout = Vo.get_wave(0)
Vin = Vi.get_wave(0)
tdelay = t_delay.get_wave(0)
trise = t_rise.get_wave(0)
tfall = t_fall.get_wave(0)
# spice measurements are the first value of the data vector
trise = trise[0]*1e12 # units: ps
tfall = tfall[0]*1e12 # units: ps
tdelay = tdelay[0]*1e12 # units: ps
print('trise: ',round(trise,4), 'ps')
print('tfall: ',round(tfall,4), 'ps')
print('tdelay: ', round(tdelay,4), 'ps')
str_1 = 'rise time (10%% to 90%%) --> t$_{RISE}$ = %.4f ps' % trise
str_2 = 'fall time (90%% to 10%%) --> t$_{FALL}$ = %.4f ps' % tfall
str_3 = 'delay time (50%% to 50%%) --> t$_{DELAY}$ = %.4f ps' % tdelay
fig1 = plt.figure()
plt.title("C5 CMOS inverter: transient analysis" )
plt.ylabel("voltage (V)")
plt.xlabel("time (ns)")
plt.plot(time*1e9,Vin, label="v$_{in}$(t)")
plt.plot(time*1e9,Vout, label="v$_{out}$(t)")
plt.annotate(str_1+'\n'+str_2+'\n'+str_3,
xy=(3,3),ha='left', va='top', color='darkblue', fontsize=10,
bbox=dict(facecolor='lemonchiffon', edgecolor='black',boxstyle='round,pad=1'))
plt.legend(bbox_to_anchor=(1, 0.5), loc="center left",frameon=True,fontsize=12)
plt.tight_layout();
plt.savefig("Plot_TRAN_ngsp.pdf")
# ------------------------------------------------
LTR = RawRead("./spiceout/C5_inverter_VTC_ngsp_bin.raw")
print(LTR.get_trace_names())
print("\n")
print(LTR.get_raw_property())
print("\n")
steps = LTR.get_steps()
num_steps = len(steps)
print('number of sweeps in the simulation:', num_steps)
# objects contaonong the data
Vo = LTR.get_trace('v(out)')
Vi = LTR.get_trace('v(in)')
DVo = LTR.get_trace('v(dvout)')
vsw = LTR.get_trace('vsw')
vih = LTR.get_trace('vih')
vil = LTR.get_trace('vil')
voh = LTR.get_trace('voh')
vol = LTR.get_trace('vol')
# extract the data from the objects
if num_steps == 1:
Vout = Vo.get_wave(0)
Vin = Vi.get_wave(0)
DVout = DVo.get_wave(0)
Vsw = vsw.get_wave(0)
Vih = vih.get_wave(0)
Voh = voh.get_wave(0)
Vil = vil.get_wave(0)
Vol = vol.get_wave(0)
# spice measurements are the first value of the data vector
vsw = Vsw[0]
vih = Vih[0]
voh = Voh[0]
vil = Vil[0]
vol = Vol[0]
print('Vsw: ',round(vsw,4), 'V')
print('Vih: ',round(vih,4), 'V')
print('Voh: ',round(voh,4), 'V')
print('Vil: ',round(vil,4), 'V')
print('Vol: ',round(vol,4), 'V')
str_1 = "V$_{SW}$ = %.4f V" %vsw
str_2 = "V$_{IL}$ = %.4f V" %vil
str_3 = "V$_{OH}$ = %.4f V" %voh
str_4 = "V$_{IH}$ = %.4f V" %vih
str_5 = "V$_{OL}$ = %.4f V" %vol
# compute max DC gain and corresponding bias voltage VIN
maxgain = abs(min(DVout))
tupla = np.where(DVout == min(DVout))
index = tupla[0][0]
VIN = Vin[index]
print("The max DC gain is %.4f(V/V) at VIN=%.4f(V)" % (maxgain,VIN))
str_6 = "The max DC gain is"
str_7 = "%.2f V/V " % maxgain
str_8 = "at V$_{IN}$=%.2f V" % VIN
fig2 = plt.figure()
plt.subplot(211) # 2 plots - col 1, row 1
plt.grid(True, which="both", axis="x")
plt.title("C5 CMOS inverter: DC voltage characteristic" )
plt.ylabel("Voltage (V)")
plt.xlabel("V$_{in}$ (V)")
plt.plot(Vin, Vout, label="V$_{out}$",linewidth=2.0)
plt.plot(Vin, Vin, label="V$_{in}$")
plt.xlim((0,5))
plt.ylim((-0.5,5.5))
plt.yticks(np.arange(0,5.1, step=1))
plt.yticks(fontsize=8)
plt.xticks(fontsize=8)
plt.annotate(str_1+'\n'+str_2+'\n'+str_3+'\n'+str_4+'\n'+str_5+'\n', xy=(0.2,4.5),ha='left', va='top',
color='tab:purple',fontsize=10)
plt.legend(loc="center right",frameon=True,fontsize=11)
plt.subplot(212) # 2 plots - plot col 1, row 2
plt.grid(True, which="both", axis="x")
plt.title("C5 CMOS inverter: DC gain" )
plt.ylabel("$\dfrac{dV_{out}}{dV_{in}}$",rotation=90)
plt.yticks(fontsize=8,rotation=0)
plt.xticks(fontsize=8)
plt.xlabel("V$_{in}$ (V)")
plt.plot(Vin, DVout, linewidth=2, color='teal')
plt.xlim((0,5))
plt.annotate(str_6+'\n'+str_7+'\n'+str_8, xy=(0.5,-4),ha='left', va='top',
color='indigo',fontsize=10)
fig2.tight_layout()
plt.savefig("Plot_VTC_ngsp.pdf")
plt.show()
Found Numpy. WIll be used for storing data
Normal access
['time', 't_delay', 't_fall', 't_rise', 'v(in)', 'v(out)']
{'Filename': './spiceout/C5_inverter_TRAN_ngsp_bin.raw', 'Title': ' *** spice deck for cell c5_inverter_tran_ngsp{sch} from library c5_cmoslib', 'Date': ' Wed Nov 10 00:02:40 2021', 'Plotname': ' Transient Analysis', 'Flags': ' real', 'No. Variables': 6, 'No. Points': 3041, 'Variables': ['time', 't_delay', 't_fall', 't_rise', 'v(in)', 'v(out)']}
number of sweeps in the simulation: 1
trise: 220.9172 ps
tfall: 206.2974 ps
tdelay: 38.3503 ps
Normal access
['v(v-sweep)', 'v(in)', 'v(out)', 'v(dvout)', 'vsw', 'vil', 'vih', 'voh', 'vol']
{'Filename': './spiceout/C5_inverter_VTC_ngsp_bin.raw', 'Title': ' *** spice deck for cell c5_inverter_vtc_ngsp{sch} from library c5_cmoslib', 'Date': ' Wed Nov 10 12:38:43 2021', 'Plotname': ' DC transfer characteristic', 'Flags': ' real', 'No. Variables': 9, 'No. Points': 5001, 'Variables': ['v(v-sweep)', 'v(in)', 'v(out)', 'v(dvout)', 'vsw', 'vil', 'vih', 'voh', 'vol']}
number of sweeps in the simulation: 1
Vsw: 2.4591 V
Vih: 2.858 V
Voh: 4.4045 V
Vil: 1.9659 V
Vol: 0.5603 V
The max DC gain is 16.7198(V/V) at VIN=2.4720(V)
