def simulate(self):
self.netlist.to_spice('optimize.sp')
ngspyce.source('optimize.sp')
ngspyce.ac(**self.sim_params)
fs = np.abs(ngspyce.vector('frequency'))
vs = ngspyce.vector('vout')
return fs, vs
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
]
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)
Plot the frequency response of an RC low-pass filter
"""
import ngspyce
from matplotlib import pyplot as plt
import numpy as np
# Read netlist
ngspyce.source('lowpass.net')
# Calculate small-signal transfer function between 1 kHz and 10 MHz, with 5
# points per decade
ngspyce.ac(mode='dec', npoints=7, fstart=1e3, fstop=10e6)
# Read results
freq = np.abs(ngspyce.vector('frequency'))
vout = ngspyce.vector('vout')
# And plot them
fig, (ax1, ax2) = plt.subplots(2, sharex=True)
fig.suptitle('Frequency response of an RC low-pass filter')
ax1.semilogx(freq, 20 * np.log10(np.abs(vout)))
ax1.set_ylabel('Magnitude [dB]')
ax1.grid(True, which='both')
ax2.semilogx(freq, np.angle(vout, True))
ax2.set_xlabel('Frequency [Hz]')
ax2.set_ylabel('Phase [degrees]')
ax2.grid(True, which='both')
ax2.margins(x=0)
# 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]')
def test_vector(self):
ns.cmd('let myvector = unitvec(4)')
self.assertEqual(list(ns.vector('myvector')), [1, 1, 1, 1])
def _test_sweep(self, *args):
ns.dc('va', *args)
self.assertEqualNdarray(ns.vector('a'),
ns.linear_sweep(*args))
def test_altermod(self):
ns.circ(['r n 0 rmodel', '.model rmodel R res = 3'])
ns.alter_model('r', res=4)
ns.operating_point()
self.assertEqual(ns.vector('@r[resistance]'), 4)
def test_alter(self):
ns.circ('r n 0 1')
ns.alter('r', resistance=2, temp=3)
ns.operating_point() # Necessary for resistance to be calculated
self.assertEqual(ns.vector('@r[resistance]'), 2)
self.assertEqual(ns.vector('@r[temp]'), 3)
