def graficar(self, archivo, filtro, f_infty):
if filtro == 'Circuito_Pasa_Bajas'.lower():
titulo = 'Circuito pasa bajas con frecuencia de cero dB en '
else:
titulo = 'Circuito pasa altas con frecuencia de cero dB en '
l = ltspice.Ltspice(os.getcwd() + '/' + archivo)
# Make sure that the .raw file is located in the correct path
l.parse()
f = l.get_frequency()
V_in = abs(l.get_data('V(in)'))
V_out = abs((l.get_data('V(out)')))
H = 20 * np.log10(V_out) - 20 * np.log10(V_in)
f = np.multiply(f, 1e-6)
#plt.figure()
plt.semilogx(f, H, f,
np.ones(len(H)) * -3, f,
np.ones(len(H)) * -10.3, f,
np.ones(len(H)) * -30)
plt.legend(['H', '-3dB', '-10,3 dB', '-30dB'])
plt.ylabel('Magnitud [dB]')
plt.xlabel('frecuencia [MHz]')
#plt.title(titulo+str(f_infty)+' Hz')
#plt.xlim([60,100])
#plt.ylim([-2,2])
plt.grid(True)
plt.xticks(
np.concatenate(
(np.arange(10, 100, step=10), np.arange(100, 300, step=100))))
plt.savefig(os.getcwd() + '/' + filtro + '_' + str(f_infty) + '_Hz' +
'.png')
def graficar(self,archivo,tipoFiltro,orden):
'''
Esta función permite graficar los resultados
- Archivo: Documento .raw que se genera por el simulador
- tipoFiltro: Tipo de filtro
- orden: Orden del filtro
'''
l = ltspice.Ltspice(os.getcwd()+'/'+archivo)
# Make sure that the .raw file is located in the correct path
l.parse()
f= l.get_frequency()*1e-6
V_in =abs(l.get_data('V(in)'))
V_out =abs(l.get_data('V(out)'))
H=20*np.log10(V_out)-20*np.log10(V_in)
plt.figure()
plt.semilogx(f,H ,f,np.ones(len(H))*-6,f,np.ones(len(H))*-30,f,np.ones(len(H))*-73.87)
plt.ylabel('Magnitud [dB]')
plt.xlabel('frecuencia [MHz]')
plt.axvline(x=200, ymin=-3, ymax=3,c='m')
plt.legend(['H','-6dB','-30dB','-73.87dB','200 MHz'])
plt.grid(True)
plt.title(tipoFiltro+' con orden '+str(orden))
plt.xticks(np.concatenate((np.arange(10,100,step=10),np.arange(100,400,step=100))))
plt.savefig(os.getcwd()+'/'+tipoFiltro.replace(' ','_').lower()+'_Orden_'+str(orden)+'.png')
plt.show()
def getData(sim_raw, variables):
l = ltspice.Ltspice(os.path.dirname(__file__) + sim_raw)
# Make sure that the .raw file is located in the correct path
#l = ltspice.Ltspice('C:/Users/user/Desktop/python_spice/root_con/practice_optpy.raw' )
tryParse(l)
v_sim = l.getData(variables[0])
i_sim = l.getData(variables[1])
simulation = ModelPv(v_sim, i_sim)
os.system('ltspice_end.bat')
return simulation
def getData(dir):
l = ltspice.Ltspice(dir)
# Make sure that the .raw file is located in the correct path
l.parse()
time = l.getTime()
V_source = l.getData('V(source)')
V = l.getData('V(cap)')
I = l.getData('I(R1)')
return time, V, I
for run in runList_:
queue.put((LTSpicePath, run))
queue.join()
end = time()
elapsed = end - start
print('elapsed: ', elapsed)
return (runList_,indexlist)
(runs, indexlist) = execRuns(16)
import ltspice
import struct
outdata = [None] * len(runs)
for r in range(len(runs)):
outdata[r] = ltspice.Ltspice('{}.raw'.format(runs[r]))
outdata[r].parse()
totalpoints = 0
for dat in outdata:
totalpoints += dat._point_num
##totalpoints = outdata[0]._point_num
# TODO: this only works for TRANS...
out = open('outdata.raw','w', encoding='UTF16', newline='')
out.write('Title: * {}\n'.format('i forgot what the input file was'))
out.write('Date: {}\n'.format(outdata[0].date.strip()))
out.write('Plotname: {}\n'.format(outdata[0].plot_name.strip())) # TODO: copying this name might not always work
out.write('Flags: {}\n'.format(outdata[0].flags.strip())) # TODO: copying this name might not always work
out.write('No. Variables: {}\n'.format(outdata[0]._variable_num))
out.write('No. Points: {}\n'.format(totalpoints))
import ltspice
import matplotlib.pyplot as plt
import numpy as np
import os
file_path = 'inv_example.raw'
l = ltspice.Ltspice(file_path)
l.parse()
time = l.get_time()
V0 = l.get_data('V(N003)')
V1 = l.get_data('V(N004)')
plt.plot(time, V0)
plt.plot(time, V1)
plt.show()
'R2 N002 N003 ' + r_2 + ' \n'
'V1 N002 N004 SINE(0 177 60 0 0 90) \n'
'.model D D \n'
'.lib C:\\Users\\user\\Documents\\LTspiceXVII\\lib\\cmp\\standard.dio \n'
'.options maxstep=1.25-5 \n'
'.tran 0 512e-4 0 0.417e-6 \n'
'.backanno \n'
'.end \n')
#%% Create new netlist
newNetCall(netlist, code)
#%%Get info
#l = ltspice.Ltspice('C:/Users/user/Desktop/python_spice/root_con/practice_optpy.raw' )
l = ltspice.Ltspice(os.path.dirname(__file__) + sim_raw)
# Make sure that the .raw file is located in the correct path
l.parse()
time = l.getTime()
#v_1 = l.getData('V(V1)')
v_na = l.getData('V(n002)')
v_nb = l.getData('V(n004)')
i_in = l.getData('I(R2)')
simulation = Modelo(time, v_na - v_nb, i_in)
#%% Plotting signals
#plt.plot(time, v_1)
plt.plot(simulation.t, simulation.v)
plt.plot(time, simulation.i * 1000)
#plt.xlim((0, 1e-3))
import ltspice
import matplotlib.pyplot as plt
import numpy as np
import os
l = ltspice.Ltspice(os.path.dirname(__file__) + '/rectifier.raw')
l.parse()
time = l.get_time()
V_source = l.get_data('V(source)')
V_cap_max = []
plt.plot(time, V_source)
for i in range(l.case_count): # Iteration in simulation cases
time = l.get_time(i)
# Case count starts from zero
# Each case has different time point numbers
V_cap = l.get_data('V(cap,pgnd)', i)
V_cap_max.append(max(V_cap))
plt.plot(time, V_cap)
print(V_cap_max)
plt.xlim((0, 1e-3))
plt.ylim((-15, 15))
plt.grid()
plt.savefig('rectifier.png')
plt.show()
import os
import ltspice
import matplotlib.pyplot as plt
import numpy as np
filePath = os.path.join(os.path.dirname(__file__), "voltage-clamp-simple.raw")
print("loading", filePath)
assert os.path.isfile(filePath)
l = ltspice.Ltspice(filePath)
l.parse()
print("NAMES:", ", ".join(l.getVariableNames()))
times = l.getTime() * 1e3 # ms
Vcell = l.getData('V(n003)') * 1e3 # mV
Vcommand = l.getData('V(vcmd)') * 1e3 # mV
Iclamp = l.getData('I(Rf)') * 1e12 # pA
ax1 = plt.subplot(211)
plt.grid(ls='--', alpha=.5)
plt.plot(times, Iclamp, 'r-')
plt.ylabel("Current (pA)")
plt.subplot(212, sharex=ax1)
plt.grid(ls='--', alpha=.5)
plt.plot(times, Vcell, label="Cell")
plt.plot(times, Vcommand, label="Clamp")
plt.ylabel("Potential (mV)")
plt.xlabel("Time (milliseconds)")
plt.legend()
# %%
lts "circuito sencillo.net"
# %% [markdown]
# Al ejecutar esta simulación, se genera un fichero `.raw` con los resultados. Es muy parecido al `outfile` que hemos empleado antes con Ahkab. Para leer este fichero, tenemos que usar el paquete [ltspice de Python](https://github.com/DongHoonPark/ltspice_pytool), el cual podéis instalar directamente desde Jupyter:
# %%
get_ipython().system('pip install ltspice')
# %% [markdown]
# Ahora ya podemos leer este fichero `.raw` y pintar una recta de voltaje muy parecida a la que obtuvimos anteriormente con Ahkab:
# %%
l = ltspice.Ltspice("circuito sencillo.raw")
l.parse()
tiempo = l.get_time()
voltaje = l.get_data('V(1)')
corriente = l.get_data('I(V1)')
# Podemos pintar la corrente en función del tiempo
# plt.plot(tiempo, corriente)
# O el voltaje
plt.plot(tiempo, voltaje)
# %% [markdown]
# ** En resumen: ** hemos usado dos *compiladores* Spice distintos para hacer el mismo ejercicio. De igual manera podríamos haber usado [Ngspice](http://ngspice.sourceforge.net) u otro. De hecho, podíamos haber usado Ahkab en modo comando. Si tenemos correctamente instalado este framework, en princpio podemos invocarlo [directamente desde línea de comandos](https://ahkab.readthedocs.io/en/latest/help/Command-Line-Help.html):
# %%
get_ipython().system('ahkab "circuito sencillo.sp"')
import os
import ltspice
import matplotlib.pyplot as plt
import numpy as np
import scipy.interpolate
np.set_printoptions(suppress=True)
l = ltspice.Ltspice(os.path.dirname(__file__) + "/voltage-clamp-simple.raw")
l.parse()
times = l.getTime() * 1e3 # ms
Iclamp = l.getData('I(Rf)') * 1e12 # pA
plt.figure(figsize=(6, 3))
plt.title("Irregularly Spaced Data")
plt.plot(times, Iclamp, '.-')
plt.savefig(os.path.dirname(__file__) + "/voltage-clamp-simple-fig3.png")
plt.show()
# interpolate data for 20 kHz sample rate
f = scipy.interpolate.interp1d(times, Iclamp)
pointCount = int((times[-1] - times[0]) * 20) + 1
times = np.linspace(times[0], times[-1], pointCount)
Iclamp = f(times)
plt.figure(figsize=(6, 3))
plt.grid(ls='--', alpha=.5)
plt.title("Interpolated 20kHz Signal")
plt.plot(times, Iclamp)
plt.savefig(os.path.dirname(__file__) + "/voltage-clamp-simple-fig4.png")
import os
import ltspice
import matplotlib.pyplot as plt
import numpy as np
import scipy.interpolate
np.set_printoptions(suppress=True)
# read data from LTSpice simulation file
l = ltspice.Ltspice(
os.path.dirname(__file__) +
f"/../models/single-electrode-advanced/voltage-clamp.raw")
l.parse()
times = l.getTime() * 1e3 # ms
Iclamp = l.getData('I(Rf)') * 1e12 # pA
# interpolate data for 20 kHz sample rate
f = scipy.interpolate.interp1d(times, Iclamp)
pointCount = int((times[-1] - times[0]) * 20) + 1
times = np.linspace(times[0], times[-1], pointCount)
Iclamp = f(times)
plt.figure(figsize=(6, 3))
plt.grid(ls='--', alpha=.5)
plt.title("Interpolated 20kHz Signal")
plt.plot(times, Iclamp)
plt.savefig(os.path.dirname(__file__) + "/mt1.png")
plt.show()
#%% Create new netlist
f_id = open(netlist, 'w')
f_id.write(code)
f_id.close()
#%%Simulation
os.system('ltspice_call.bat')
time.sleep(5)
os.system('ltspice_end.bat')
#%%Get info
#l = ltspice.Ltspice('C:/Users/user/Desktop/python_spice/root_con/practice_optpy.raw' )
l = ltspice.Ltspice(os.path.dirname(__file__) + '/practice_optpy.raw')
# Make sure that the .raw file is located in the correct path
l.parse()
time = l.getTime()
V_source = l.getData('V(source)')
V_cap = l.getData('V(cap)')
I_ser = l.getData('I(R1)')
#%% Plotting signals
plt.plot(time, V_source)
plt.plot(time, V_cap)
plt.plot(time, I_ser)
#plt.xlim((0, 1e-3))
#plt.ylim((-10, 10))
parser.add_argument('graph_file',
metavar='graph_path',
type=str,
help="Graph file to be plot to")
parser.add_argument('values',
metavar='exprs',
type=str,
nargs='+',
help="Expresions to be ploted")
args = parser.parse_args()
if (not os.path.exists(args.raw_file)):
print('invalid raw file: file not find!', file=sys.stderr)
raw = ltspice.Ltspice(args.raw_file)
raw.parse()
print(len(raw.variables), 'variable found')
time = raw.get_time()
graph_datas = []
for need_exps in args.values:
if (not need_exps in raw.variables):
print('"%s" did not contains "%s"' % (args.raw_file, need_exps))
graph_datas.append({
"name":
need_exps,
## Writing the netlist to a file
print('Writing the .net file for LTspice XVII...')
file = NETLIST_PATH
with open(file, mode='w') as f:
f.write(netlist)
## Executing LTspice XVII in batch mode
## (Possibly, handling of error is needed.)
print('Running LTspice XVII...')
subprocess.call([LTSPICE_PATH, '-b', file])
print('LTspice XVII simulation successfully completed!')
## Loading the simulation results
print('Loading the resulting .raw file...')
l = ltspice.Ltspice(file.replace('.net', '.raw'))
l.parse()
time = l.getTime()
## Node and branch settings
node = range(N_STAGES + 1)
xt = [n / N_STAGES * LENGTH for n in node]
branch = range(N_STAGES)
xb = [(n + 0.5) / N_STAGES * LENGTH for n in branch]
## Obtaining waveform: Signal source
v_source = l.getData('V(1)')
## Obtaining waveform: Node voltages
vn, vn_interp = [], []
for i in node:
import ltspice
import matplotlib.pyplot as plt
import numpy as np
import os
l = ltspice.Ltspice(os.path.dirname(__file__) + '/01_RC_circuit.raw')
# Make sure that the .raw file is located in the correct path
l.parse()
time = l.getTime()
V_source = l.getData('V(source)')
V_cap = l.getData('V(cap)')
plt.plot(time, V_source)
plt.plot(time, V_cap)
plt.xlim((0, 1e-3))
plt.ylim((-10, 10))
plt.grid()
plt.show()
def graficar(self,archivo,Rs,RL):
# Obtenención de datos
l = ltspice.Ltspice(os.getcwd()+'/'+archivo)
l.parse()
unidadesFrecuencia='MHz'
unidadesFrecuenciaFactor=1e-6
f= l.get_frequency()*unidadesFrecuenciaFactor
v_in =l.get_data('V(in)')
i_vin=l.get_data('i(vin)')
v_out =l.get_data('V(out)')
# Operaciones
H=20*np.log10(abs(v_out/v_in))
H_angle=(np.angle(v_out/v_in))*180/math.pi
dB_corte=20*np.log10(1/(2**0.5))
nMax=self.posicionMagnitudMaxima(H)
f_resonancia=f[nMax]
nOmegaLow=self.posicionPrimerCoicidenciaSentidoPositivo(H,H[nMax]+dB_corte)
f_low=f[nOmegaLow]
nOmegaHigh=self.posicionPrimerCoicidenciaSentidoNegativo(H,H[nMax]+dB_corte)
f_high=f[nOmegaHigh]
Q=f_resonancia/(f_high-f_low)
print('f_o: ',f_resonancia,unidadesFrecuencia)
print(f'Q={Q} {unidadesFrecuencia}/{unidadesFrecuencia}')
# Configuración de texto
conf_left = {'fontsize':12,'horizontalalignment':'left','verticalalignment':'top'}
conf_right= {'fontsize':12,'horizontalalignment':'right','verticalalignment':'top'}
conf_center= {'fontsize':12,'horizontalalignment':'center','verticalalignment':'baseline'}
## Factor de calidad
fig, axs = plt.subplots(2, 1)
axs[0].semilogx(f,H,f,np.ones(len(H))*(H[nMax]+dB_corte))
axs[1].semilogx(f,H_angle)
axs[0].set_xticks((np.arange(70,110,step=10)))
axs[1].set_xticks((np.arange(70,110,step=10)))
axs[0].text(f[nMax],H[nMax]\
,f'({f[nMax].round(3)} [{unidadesFrecuencia}],{H[nMax].round(3)}[dB])',conf_center)
#H_c_low=H[nOmegaLow]+(H[0]-H[nOmegaLow])/8
axs[0].text(f[nOmegaLow],H[nOmegaLow]\
,f'({f[nOmegaLow].round(3)} [{unidadesFrecuencia}],{H[nOmegaLow].round(3)}[dB])',conf_right)
#H_c_high=H[nOmegaHigh]+(H[0]-H[nOmegaHigh])/8
axs[0].text(f[nOmegaHigh],H[nOmegaHigh]\
,f'({f[nOmegaHigh].round(3)} [{unidadesFrecuencia}],{H[nOmegaHigh].round(3)}[dB])',conf_left)
H_m=H[nMax]+(H[0]-H[nMax])/2
axs[0].text(f[nMax],H_m\
,f'Q={Q.round(3)}',conf_center)
axs[1].text(f[nMax],H_angle[nMax]*0.97\
,f'({f[nMax].round(3)} [{unidadesFrecuencia}],{H_angle[nMax].round(3)}[$^0 $])',conf_left)
axs[0].set_xlabel(f'frecuencia [{unidadesFrecuencia}]')
axs[1].set_xlabel(f'frecuencia [{unidadesFrecuencia}]')
axs[0].set_ylabel('Magnitud [dB]')
axs[1].set_ylabel('Arg(H) [$^0 $]')
axs[0].legend(['H','-3 [dB]'],loc="lower right")
axs[0].grid(True)
axs[1].grid(True)
plt.show()
## Impedancia de entrada del amplificador
Z_in_amplificador=abs(v_in/i_vin)-Rs
Z_in_amplificador_fase=np.angle(v_in/i_vin)*180/math.pi
fig, axs = plt.subplots(2, 1)
axs[0].semilogx(f, Z_in_amplificador)
axs[1].semilogx(f, Z_in_amplificador_fase)
axs[0].set_xticks((np.arange(70,110,step=10)))
axs[1].set_xticks((np.arange(70,110,step=10)))
axs[0].text(f[nMax],Z_in_amplificador[nMax]*0.97\
,f'({f[nMax].round(3)} [{unidadesFrecuencia}],{Z_in_amplificador[nMax].round(3)}[$\Omega $])',conf_left)
axs[1].text(f[nMax],Z_in_amplificador_fase[nMax]*0.97\
,f'({f[nMax].round(3)} [{unidadesFrecuencia}],{Z_in_amplificador_fase[nMax].round(3)}[$^0 $])',conf_left)
axs[0].set_xlabel(f'frecuencia [{unidadesFrecuencia}]')
axs[1].set_xlabel(f'frecuencia [{unidadesFrecuencia}]')
axs[0].set_ylabel('|Z|')
axs[1].set_ylabel('Arg(Z) [$^0 $]')
axs[0].grid(True)
axs[1].grid(True)
plt.show()
## Potencia
S_fuente=v_in*np.conj(i_vin) #[VA] Potencia aparente
S_carga=v_out*np.conj(v_out/RL) #[VA] Potencia aparente
P_fuente=np.real(S_fuente) #[W] Potencia real
P_carga=np.real(S_carga) #[[W]] Potencia real
Q_fuente=np.imag(S_fuente) #[W] Potencia real
Q_carga=np.imag(S_carga) #[[W]] Potencia real
H_P=P_carga/P_fuente
H_Q=Q_carga/Q_fuente
fig, axs = plt.subplots(2, 1)
axs[0].semilogx(f, H_P)
axs[1].semilogx(f, H_Q)
axs[0].set_xticks((np.arange(70,110,step=10)))
axs[1].set_xticks((np.arange(70,110,step=10)))
axs[0].text(f[nMax],H_P[nMax]\
,f'({f[nMax].round(3)} [{unidadesFrecuencia}],{H_P[nMax].round(3)} [W/W])',conf_left)
axs[1].text(f[nMax],H_Q[nMax]\
,f'({f[nMax].round(3)} [{unidadesFrecuencia}],{H_Q[nMax].round(3)} [VAR/VAR])',conf_left)
axs[0].set_xlabel(f'frecuencia [{unidadesFrecuencia}]')
axs[1].set_xlabel(f'frecuencia [{unidadesFrecuencia}]')
axs[0].set_ylabel('Pout/Pin [W/W]')
axs[1].set_ylabel('Pout/Pin [VAR/VAR]')
axs[0].grid(True)
axs[1].grid(True)
plt.show()
import os
import ltspice
import matplotlib.pyplot as plt
import numpy as np
base = os.path.dirname(__file__)
fp = f"{base}\\fft.fft"
lt = ltspice.Ltspice(fp)
lt.parse()
vars = lt.getVariableNames()
print(f"FFT Variables: {vars}")
f = lt.getFrequencies()
fig, ax = plt.subplots()
for var in ('V(ip)', 'V(op)'):
res = 20 * np.log10(lt.getData(var))
ax.semilogx(f, res, label=var)
fig.legend()
plt.show()
import ltspice
import matplotlib.pyplot as plt
import numpy as np
import os
l = ltspice.Ltspice(os.path.dirname(__file__) + '/rc.raw')
l.parse()
time = l.get_time()
V_source = l.get_data('V(source)')
V_cap = l.get_data('V(cap)')
plt.plot(time, V_source)
plt.plot(time, V_cap)
plt.xlim((0, 1e-3))
plt.ylim((-10, 10))
plt.grid()
plt.savefig("rc.png")
plt.show()
# read data from the LTSpice .raw file
import ltspice
l = ltspice.Ltspice("voltage-clamp.raw")
l.parse()
# obtain data by its identifier and scale it as desired
times = l.getTime() * 1e3 # ms
Vcell = l.getData('V(n007)') * 1e3 # mV
Vcommand = l.getData('V(n006)') * 1e3 # mV
Iclamp = l.getData('I(Rf)') * 1e12 # pA
# plot scaled simulation data
import matplotlib.pyplot as plt
ax1 = plt.subplot(211)
plt.grid(ls='--', alpha=.5)
plt.plot(times, Iclamp, 'r-')
plt.ylabel("Current (pA)")
plt.subplot(212, sharex=ax1)
plt.grid(ls='--', alpha=.5)
plt.plot(times, Vcell, label="Cell")
plt.plot(times, Vcommand, label="Clamp")
plt.ylabel("Potential (mV)")
plt.xlabel("Time (milliseconds)")
plt.legend()
plt.margins(0, .1)
plt.tight_layout()
plt.savefig("voltage-clamp-simple-fig1.png")
#plt.show()
import ltspice
import matplotlib.pyplot as plt
import numpy as np
import os
l = ltspice.Ltspice(os.path.dirname(__file__)+'/energy_calc.raw')
l.parse()
energy_R1 = []
for i in range(l.case_count): # Iteration in simulation cases
time = l.get_time(i)
I_R1 = l.get_data('I(R1)',i)
R1 = 1
power_R1 = R1 * I_R1 * I_R1 # Calc dissipated power from R1 from 0 to 5ms
a = ltspice.integrate(time, power_R1, [0, 5e-3])
energy_R1.append(a)
cond = np.linspace(1e-3, 10e-3, 10) #Simulation condition written in .asc file
plt.xlabel("RL circuit inductance (H)")
plt.ylabel("Energy (J)")
plt.grid()
plt.plot(cond, energy_R1)
plt.savefig('energy_calc.png')
plt.show()
def readRaw(self):
if Config.simulator == "LTSPICE":
raw = ltspice.Ltspice(Config.TEMP_DIR + self.filename + ".raw")
raw.parse()
data = dict()
for var in raw.getVariableNames():
if var == "time":
data["time"] = raw.getTime()
else:
data[var] = raw.getData(var)
del raw
return data
elif Config.simulator == "NGSPICE_WRDATA":
read = pd.read_csv(Config.TEMP_DIR + "output.m", delimiter="\s+")
d = dict()
for col in read.columns:
d[col] = np.array(read[col], dtype=np.float64)
return d
elif Config.simulator == "NGSPICE":
# shameless rip from
# https://gist.github.com/snmishra/27dcc624b639c2626137
BSIZE_SP = 512
MDATA_LIST = [
b'title', b'date', b'plotname', b'flags', b'no. variables',
b'no. points', b'dimensions', b'command', b'option'
]
try:
fp = open(Config.TEMP_DIR + self.filename + ".raw", 'rb')
except:
print("NO RAW FILE")
return {"None": [None]}
plot = {}
count = 0
arrs = []
plots = []
while (True):
try:
mdata = fp.readline(BSIZE_SP).split(b':', maxsplit=1)
except:
raise
if len(mdata) == 2:
if mdata[0].lower() in MDATA_LIST:
plot[mdata[0].lower()] = mdata[1].strip()
if mdata[0].lower() == b'variables':
nvars = int(plot[b'no. variables'])
npoints = int(plot[b'no. points'])
plot['varnames'] = []
plot['varunits'] = []
for varn in range(nvars):
varspec = (fp.readline(BSIZE_SP).strip().decode(
'ascii').split())
assert (varn == int(varspec[0]))
plot['varnames'].append(varspec[1])
plot['varunits'].append(varspec[2])
if mdata[0].lower() == b'binary':
dtype = [
np.complex_
if b'complex' in plot.get(b'flags') else np.float_
] * nvars
rowdtype = np.dtype({
"names": plot["varnames"],
"formats": dtype
})
# We should have all the metadata by now
arrs.append(
np.fromfile(fp, dtype=rowdtype, count=npoints))
plots.append(plot)
fp.readline() # Read to the end of line
else:
break
d = dict()
for i, var in enumerate(plots[0]["varnames"]):
name = var
# capitalize V or I
if "v(" in var:
name = "V" + var[1:]
if "i(" in var:
name = "I" + var[1:]
d[name] = list()
for data in arrs[0]:
d[name].append(data[i].real)
d[name] = np.array(d[name])
return d
