def make_thd_plot(thdplot, sinplot, voltages):
thdplot.set_ylabel("thd (dB)")
thdplot.set_xlabel("control current (mA)")
thdplot.set_title("total harmonic distortion")
sinplot.set_xticks([], [])
#sinplot.set_yticks([],[])
#sinplot.set_title("sine shape at cc = 1mA")
#for voltage in np.arange(3,18, 1):
for voltage in voltages:
printall(ns.cmd("alter v1 %f" % voltage))
printall(ns.cmd("alter v2 %f" % voltage))
y = []
x = my_logspace(0.01, 1, 8)
for current in x:
printall(ns.cmd("alter i1 %fm" % current))
y.append(calc_thd(300))
printall(ns.cmd("alter i1 40u"))
_, signal, time = simulate_waveform(300,
n_periods=1,
steps_per_period=64)
thdplot.plot(x / 1000, np.log10(y) * 10, label="+/- %fV" % voltage)
sinplot.plot(time, signal)
thdplot.set_xscale('log')
fmt_mA = ticker.EngFormatter(unit='A')
fmt_dB = ticker.FormatStrFormatter('%.0f dB')
thdplot.xaxis.set_major_formatter(fmt_mA)
thdplot.yaxis.set_major_formatter(fmt_dB)
def test_cmd(self):
self.assertEqual(ns.cmd('print planck'), ['planck = 6.626200e-34'])
self.assertEqual(ns.cmd('print' + ' ' * 200 + 'kelvin'),
['kelvin = -2.73150e+02'])
# Command too long
self.assertRaises(ValueError, ns.cmd, 'print' + ' ' * 2000 + 'kelvin')
def test_cmd(self):
self.assertEqual(ns.cmd('print planck'),
['planck = 6.626200e-34'])
self.assertEqual(ns.cmd('print' + ' ' * 200 + 'kelvin'),
['kelvin = -2.73150e+02'])
# Command too long
self.assertRaises(ValueError, ns.cmd, 'print' + ' ' * 2000 + 'kelvin')
def sim():
tb = testbench(common_emitter_amplifer())
circuit = Builder(tb).compile()
circuit.to_spice('common_emitter_amplifier.sp')
ng.source('common_emitter_amplifier.sp')
ng.cmd('tran 50us 10ms')
print('\n'.join(ng.vector_names()))
time, tp1 = map(ng.vector, ['time', 'V(VOUT)'])
plt.plot(time, tp1, label='VOUT')
plt.legend()
plt.show()
def test_default_codemodels(self):
"""Test presence of one model from each default .cm library"""
required_models = {'spice2poly', 'sine', 'd_nor', 'aswitch',
'd_to_real'}
existing_models = {line.partition(' ')[0]
for line in ns.cmd('devhelp')[1:]}
self.assertEqual(required_models, required_models & existing_models)
def plot_bode(outfile):
plt.clf()
printall(ns.cmd("alter c6 100u"))
#printall(ns.cmd("alter v1 3"))
#printall(ns.cmd("alter v2 3"))
gains = [500**(1 / n) for n in range(3, 0, -1)]
impedances = [1000, 10 * 1000, 100 * 1000, 1000 * 1000, 10 * 1000 * 1000]
currents_mA = [0] + list(my_logspace(0.0001, 10, 5 if DRAFT_MODE else 16))
_, plots = plt.subplots(
len(gains),
len(impedances) + 1,
gridspec_kw={'width_ratios': [3] * len(impedances) + [1]})
fmt_Hz = ticker.EngFormatter(unit='Hz')
fmt_dB = ticker.EngFormatter(unit='dB')
ohmfmt = ticker.EngFormatter(unit="Ω")
for y, gain in enumerate(gains):
for x, impedance_ohms in enumerate(impedances):
update_amplifier(impedance_ohms, gain)
plot_single_bode_family(plots[y][x], currents_mA)
plots[y][x].set_ylim(10 * math.log10(gain / 500) - 55,
10 * math.log10(gain / 500) + 5)
plots[y][x].xaxis.set_major_formatter(fmt_Hz)
plots[y][x].yaxis.set_major_formatter(fmt_dB)
if x == 0:
plots[y][x].text(0,
0.5,
'gain = %.1f×\n\n\n\n' % gain,
fontsize=10,
horizontalalignment='right',
verticalalignment='center',
transform=plots[y][x].transAxes,
rotation='vertical')
if y == 0:
plots[y][x].text(0.5,
1.0,
'impedance = %s\n' %
ohmfmt.format_data(impedance_ohms),
fontsize=10,
horizontalalignment='center',
verticalalignment='baseline',
transform=plots[y][x].transAxes)
if y == len(gains) - 1:
plots[y][x].set_xlabel("Frequency")
for p in plots:
p[-1].axis(False)
fmt = ticker.EngFormatter(unit="A")
make_legend([fmt.format_data(c / 1000) for c in currents_mA], plots[0][-1])
plt.gcf().set_size_inches(20, 11)
if outfile is not None:
plt.savefig(outfile)
def update_amplifier(impedance_ohms, factor):
factor /= PREGAIN
if not TWO_STAGE_AMP:
r78 = impedance_ohms
r910 = r78 * factor
printall(ns.cmd("alter r7 %f" % r78))
printall(ns.cmd("alter r8 %f" % r78))
printall(ns.cmd("alter r9 %f" % r910))
printall(ns.cmd("alter r10 %f" % r910))
else:
factor_sqrt = math.sqrt(factor)
r78 = impedance_ohms
r910 = r78 * factor_sqrt
printall(ns.cmd("alter r7 %f" % r78))
printall(ns.cmd("alter r8 %f" % r78))
printall(ns.cmd("alter r9 %f" % r910))
printall(ns.cmd("alter r10 %f" % r910))
printall(ns.cmd("alter r101 %f" % r78))
printall(ns.cmd("alter r102 %f" % r910))
def simulate_waveform(freq, n_periods=2, t_skip_ms=25, steps_per_period=200):
period = 1 / freq
timestep = period / steps_per_period
# set the input frequency
printall(ns.cmd("let tmp = @v4[sin]"))
printall(ns.cmd("let tmp[2] = %f" % freq))
printall(ns.cmd("alter @v4[sin] = tmp"))
skip_periods = math.ceil(t_skip_ms / 1000 * freq)
actual_t_skip_ms = skip_periods / freq * 1000
t_run_ms = actual_t_skip_ms + n_periods / freq * 1000
ns.destroy()
print("tran %fu %fm %fm" %
(timestep * 1000000, t_run_ms, actual_t_skip_ms))
ns.cmd("tran %fu %fm %fm" %
(timestep * 1000000, t_run_ms, actual_t_skip_ms))
return ns.vector('signal_in'), ns.vector('signal_out'), (
ns.vector('time') - actual_t_skip_ms / 1000)
def plot_bode2(outfile):
plt.clf()
printall(ns.cmd("alter c6 100u"))
currents_mA = [0] + list(my_logspace(0.0001, 0.1, 5 if DRAFT_MODE else 16))
headroom = 1 # set to 2.5 possibly
update_amplifier(10000, 500 / headroom)
if DRAFT_MODE:
xlen, ylen = 3, 2
else:
xlen, ylen = 7, 5
max_resonance_gain = 1 / 25 * headroom
resonance_gains = list(
np.arange(0, max_resonance_gain, max_resonance_gain / (xlen * ylen)))
_, plots = plt.subplots(xlen, ylen)
fmt_Hz = ticker.EngFormatter(unit='Hz')
fmt_dB = ticker.EngFormatter(unit='dB')
ohmfmt = ticker.EngFormatter(unit="Ω")
for i, resonance_gain in enumerate(resonance_gains):
x = i % ylen
y = int(i / ylen)
print("\n######\n####### %s\n######\n" % resonance_gain)
printall(ns.cmd("alter r122 %f" % (100000 * resonance_gain)))
plot_single_bode_family(plots[y][x], currents_mA)
plots[y][x].set_ylim(-55, 15)
plots[y][x].xaxis.set_major_formatter(fmt_Hz)
plots[y][x].yaxis.set_major_formatter(fmt_dB)
plots[y][x].set_title("gain = %7.5f" % resonance_gain, y=1.0, pad=-14)
plt.gcf().set_size_inches(20, 11)
if outfile is not None:
plt.savefig(outfile)
def calc_attenuation_and_phase(freq,
control_current_mA,
n_periods=2,
t_skip_ms=25,
steps_per_period=200,
debug=False):
# set the control current
printall(ns.cmd("alter i1 %fm" % control_current_mA))
signal_in, signal_out, time = simulate_waveform(freq, n_periods, t_skip_ms,
steps_per_period)
amplitude_in = np.max(signal_in) - np.min(signal_in)
amplitude_out = np.max(signal_out) - np.min(signal_out)
zeros = zero_crossings(signal_out)
if len(zeros) >= 3:
pmax = int((zeros[0] + zeros[1]) / 2)
pmin = int((zeros[1] + zeros[2]) / 2)
print(pmax, pmin)
if signal_out[pmax] < signal_out[pmin]:
pmin, pmax = pmax, pmin
period = ((time[pmax] * freq - 1 / 4) % 1.0) * math.pi * 2
if period > math.pi:
period -= 2 * math.pi
else:
period = np.nan
attenuation_db = math.log10(amplitude_out / amplitude_in) * 10
print(attenuation_db, period)
if debug:
plt.plot(time, signal_in)
plt.plot(time, signal_out)
plt.pause(3)
return attenuation_db, period
def run_sim(varactor_voltage):
ngspyce.cmd(f'alterparam varactor_bias_voltage = {varactor_voltage}')
ngspyce.cmd('reset')
# ngspyce.cmd('stop after 10000')
step_ps = 1 #not always obeyed - ngspice sets its own timestep.
sim_duration = 100000
n_steps = sim_duration / step_ps
# ngspyce.cmd(" ")
ngspyce.cmd(f'tran {step_ps}p {sim_duration}ps uic')
timesteps = ngspyce.vector('time')
v_collector = ngspyce.vector('v(E1)')
v_base = ngspyce.vector('v(Base)')
varactor_bias = ngspyce.vector('v(Vvaractor)')
output = ngspyce.vector('v(output)')
stable_running_point = -1 * len(v_collector) // 3
v_collector_trimmed = v_collector[
stable_running_point:] # lots of noise on startup. we want to trim that out of the FFT.
spectrum = np.fft.fft(v_collector_trimmed)
spectrum_freqs = np.fft.fftfreq(
len(v_collector_trimmed),
d=(timesteps[-1] - timesteps[stable_running_point]) /
len(v_collector_trimmed))
spectrum_begin_indice = np.abs(spectrum_freqs - 100e6).argmin()
spectrum_end_indice = np.abs(spectrum_freqs - 25e9).argmin()
#normalize
spectrum_norm = np.linalg.norm(
spectrum[spectrum_begin_indice:spectrum_end_indice].clip(min=0))
if (spectrum_norm):
fft_cleaned = spectrum[spectrum_begin_indice:spectrum_end_indice].clip(
min=0) / spectrum_norm
else:
fft_cleaned = np.zeros_like(
spectrum[spectrum_begin_indice:spectrum_end_indice])
spectrum_freqs = spectrum_freqs[spectrum_begin_indice:spectrum_end_indice]
fft_cleaned = fft_cleaned[:int(
600)] # trim all spectra to the same length 2ps,800, 5ps, 600
spectrum_freqs = spectrum_freqs[:int(600)]
return [
np.array(np.abs(fft_cleaned)),
np.array(spectrum_freqs), timesteps, v_collector, v_base,
varactor_bias, output
]
import ngspyce
import numpy as np
from matplotlib import pyplot as plt
ngspyce.source('quad.net')
#trrandom(2 2m 0 10m 0)
ngspyce.cmd('tran 1m 20m')
print('\n'.join(ngspyce.vector_names()))
time, vsin, vcos = map(ngspyce.vector, ['time', 'Vsin', 'Vcos'])
#np.savetxt('vcos.txt', vcos)
#np.savetxt('vsin.txt', vsin)
#np.savetxt('time.txt', time)
#exit()
plt.plot(time, vcos, label='Vcos')
plt.plot(time, vsin, label='Vsin')
plt.legend()
plt.show()
# Plot the frequency response of an RC low-pass filter
import ngspyce
from matplotlib import pyplot as plt
import numpy as np
# Reat netlist
ngspyce.cmd('source lowpass.net')
# Calculate small-signal transfer function between 10kHz and 100MHz, with 5
# points per decade
ngspyce.cmd('ac dec 5 10k 100meg')
# Read results
freq = np.abs(ngspyce.vector('frequency'))
vout = ngspyce.vector('vout')
# And plot them
fig = plt.figure()
fig.suptitle('Frequency response of an RC low-pass filter')
ax = fig.add_subplot(1,2,1)
ax.semilogx(freq, 20*np.log10(np.abs(vout)))
ax.set_xlabel('Frequency [Hz]')
ax.set_ylabel('Magnitude [dB]')
ax = fig.add_subplot(1,2,2)
ax.semilogx(freq, np.angle(vout,True))
ax.set_xlabel('Frequency [Hz]')
ax.set_ylabel('Phase [degrees]')
# Plot output voltages of an operational amplifier quadrature oscillator
import ngspyce
import numpy as np
from matplotlib import pyplot as plt
# Load netlist
ngspyce.cmd(b'source quad.net')
# Simulate 10 ms
ngspyce.cmd(b'tran 12n 10m 1n')
# Read results
time, vsin, vcos = map(ngspyce.vector, ['time','Vsin','Vcos'])
# And plot them
plt.plot(time*1e3, vcos, label='Vcos')
plt.plot(time*1e3, vsin, label='Vsin')
plt.title('Quadrature op-amp oscillator output voltage')
plt.xlabel('Time [ms]')
plt.ylabel('Voltage [V]')
plt.savefig('quad.png')
plt.show()
"""
Plot output voltages of an operational amplifier quadrature oscillator
"""
import ngspyce
import numpy as np
from matplotlib import pyplot as plt
# Load netlist
ngspyce.source('quad.net')
# Simulate 10 ms
ngspyce.cmd('tran 12n 10m 1n')
# Read results
time, vsin, vcos = map(ngspyce.vector, ['time', 'Vsin', 'Vcos'])
# And plot them
plt.plot(time * 1e3, vcos, label='Vcos')
plt.plot(time * 1e3, vsin, label='Vsin')
plt.title('Quadrature op-amp oscillator output voltage')
plt.xlabel('Time [ms]')
plt.ylabel('Voltage [V]')
plt.savefig('quad.png')
plt.show()
def test_vector(self):
ns.cmd('let myvector = unitvec(4)')
self.assertEqual(list(ns.vector('myvector')), [1, 1, 1, 1])
def test_vector_names(self):
ns.cmd('set curplot = new')
names = list('abdf')
for name in names:
ns.cmd('let {} = 0'.format(name))
self.assertEqual(sorted(ns.vector_names()), names)
def set_input_amplitude(amplitude):
printall(ns.cmd("let tmp = @v4[sin]"))
printall(ns.cmd("let tmp[1] = %f" % amplitude))
printall(ns.cmd("alter @v4[sin] = tmp"))
"""
Plot output voltages of an operational amplifier quadrature oscillator
"""
import ngspyce
import numpy as np
from matplotlib import pyplot as plt
# Load netlist
ngspyce.source('quad.net')
# Simulate 10 ms
ngspyce.cmd('tran 12n 10m 1n')
# Read results
time, vsin, vcos = map(ngspyce.vector, ['time', 'Vsin', 'Vcos'])
# And plot them
plt.plot(time*1e3, vcos, label='Vcos')
plt.plot(time*1e3, vsin, label='Vsin')
plt.title('Quadrature op-amp oscillator output voltage')
plt.xlabel('Time [ms]')
plt.ylabel('Voltage [V]')
plt.savefig('quad.png')
plt.show()
"""
Plot the output characteristics for the BC337 NPN transistor
"""
import ngspyce
import numpy as np
from matplotlib import pyplot as plt
# Load netlist
ngspyce.source('npn.net')
# Sweep both base and collector current
ngspyce.cmd('dc vcc 0 2 .05 vbb .7 1.2 .1')
# Load simulation results into numpy arrays
vb, vc, Ivcc = map(ngspyce.vector, ['Vb', 'Vc', 'I(Vcc)'])
# Correct the sign for collector current
ic = -Ivcc
plt.figure()
# Plot one line per base voltage
series = np.unique(vb)
for _vb in series:
plt.plot(vc[vb == _vb],
ic[vb == _vb],
'-',
label='Vb = {:.1f}'.format(_vb))
plt.legend()
plt.title('Output characteristics for BC337')
import ngspyce
import numpy as np
from matplotlib import pyplot as plt
ngspyce.cmd(b'source quad.net')
#trrandom(2 2m 0 10m 0)
ngspyce.cmd(b'tran 1m 20m')
print('\n'.join(ngspyce.vectorNames()))
vcos, vsin, time = ngspyce.vectors(['Vcos','Vsin','time']).values()
#np.savetxt('vcos.txt', vcos)
#np.savetxt('vsin.txt', vsin)
#np.savetxt('time.txt', time)
#exit()
plt.plot(time,vcos, label='Vcos')
plt.plot(time,vsin, label='Vsin')
plt.legend()
plt.show()
# Plot the output characteristics for the BC337 NPN transistor
import ngspyce
import numpy as np
from matplotlib import pyplot as plt
# Load netlist
ngspyce.cmd(b'source npn.net')
# Sweep both base and collector current
ngspyce.cmd(b'dc vcc 0 2 .05 vbb .7 1.2 .1')
# Load simulation results into numpy arrays
vb, vc, Ivcc = map(ngspyce.vector, ['Vb', 'Vc', 'I(Vcc)'])
# Correct the sign for collector current
ic = -Ivcc
plt.figure()
# Plot one line per base voltage
series = np.unique(vb)
for _vb in series:
plt.plot(vc[vb==_vb], ic[vb==_vb], '-', label='Vb = {}'.format(_vb))
plt.legend()
plt.title('Output characteristics for BC337')
plt.xlabel('Collector-emitter voltage [V]')
plt.ylabel('Collector current [A]')
plt.savefig('bc337.png')
plt.show()
"""
Plot the output characteristics for the BC337 NPN transistor
"""
import ngspyce
import numpy as np
from matplotlib import pyplot as plt
# Load netlist
ngspyce.source('npn.net')
# Sweep both base and collector current
ngspyce.cmd('dc vcc 0 2 .02 vbb .7 1.2 .1')
# Load simulation results into numpy arrays
vb, vc, Ivcc = map(ngspyce.vector, ['Vb', 'Vc', 'I(Vcc)'])
# Correct the sign for collector current
ic = -Ivcc
plt.figure()
# Plot one line per base voltage
series = np.unique(vb)
for _vb in series:
plt.plot(vc[vb == _vb], ic[vb == _vb], '-',
label='Vb = {:.1f}'.format(_vb))
plt.legend(loc='center right')
plt.title('Output characteristics for BC337')
plt.xlabel('Collector-emitter voltage [V]')
plt.ylabel('Collector current [A]')
