def _smithchart_recalc(self, new=False):
for sset in self.__ssets:
dname = self.__sset_dname[sset]
fcol = self.__sset_fdcol[sset]
rcol = self.__sset_rdcol[sset]
icol = self.__sset_idcol[sset]
fdata = self.__sset_fdata[sset]
rdata = self.__sset_rdata[sset]
idata = self.__sset_idata[sset]
dsmith = Data()
dsmith.read_inline(fcol, fdata, rcol, rdata, icol, idata)
# if input data is admittance or impedance, convert to s-parameter
if new:
self.add_curve(dsmith, rcol, icol, dname=dname)
else:
curve = "%s_:_%s_%s_vs_%s" % (dname, rcol, icol, fcol)
self._curve_xdata[curve] = dsmith.get(rcol)
self._curve_ydata[curve] = dsmith.get(icol)
from decida.Data import Data
import numpy as np
Iin_avg_array = []
stop_vo_array = []
final_vo_array = []
tend = 550e-6
for i in range(1):
input_file = "tb.tr" + str(i)
d = Data()
d.read_hspice(input_file)
#d.names()
time = d.get('TIME')
vout = d.get('v(vout))')
Iin = d.get('i(vvin))')
stop_recycle = d.get('v(stop_recycle))')
zcd = d.get('v(zcd))')
Iin_avg = np.sum((time[1:] - time[:-1]) * (Iin[1:] + Iin[:-1]) / 2) / tend
Iin_avg_array.append(Iin_avg)
for j in range(len(time)):
if time[j] > 1e-6 and stop_recycle[j] > 0.6 and zcd[j] > 0.6:
stop_vo_array.append(vout[j])
break
final_vo_array.append(vout[-1])
output_filename = "extracted_result.txt"
with open(output_filename, "w") as f:
f.write("Iin_avg\tstop_vo\tfinal_vo\n")
for i in range(len(Iin_avg_array)):
f.write("%e\t%f\t%f\n" %
(Iin_avg_array[i], stop_vo_array[i], final_vo_array[i]))
f.close()