def stitch_s2p_list(s2p_list):
# A temporary list to hold stitched files.
stitched_s2p_list = []
# Recursive end condition.
# Once list is one element long, stitching is complete.
if len(s2p_list) == 1:
return s2p_list
# For every element in s2p_list...
for i in range(0, len(s2p_list)):
# For every other element in s2p_list...
if i % 2 == 1:
# Take the prior element.
s2p_1 = s2p_list[i - 1]
# Take the current element.
s2p_2 = s2p_list[i]
# Stitch the two elements together.
stitched_s2p = rf.stitch(s2p_1, s2p_2)
# Append the stitched .s2p file to temporary list.
stitched_s2p_list.append(stitched_s2p)
# If the length of s2p_list is odd and the current element is the last in the list....
if len(s2p_list) % 2 != 0 and i == len(s2p_list) - 1:
# Append the element to the temporary list.
stitched_s2p_list.append(s2p_list[i])
# Recursively stitch temporary list until all elements are stitched together.
return stitch_s2p_list(stitched_s2p_list)
def test_stitch(self):
tmp = self.ntwk1.copy()
tmp.f = tmp.f + tmp.f[0]
c = rf.stitch(self.ntwk1, tmp)
def test_stitch(self):
tmp = self.ntwk1.copy()
tmp.f = tmp.f+ tmp.f[0]
c = rf.stitch(self.ntwk1, tmp)
os.mkdir(out_dir)
#Creates a dictionary to load all of the s2p data into in network format from python package scikit-rf, and then stitch them all together into one s2p. Can omit these steps if you didn't take your data in multiple frequency sweeps.
C = {}
for f in fnames:
C[int(f.split('.')[0].split('_')[-1])] = rf.Network(main_dir + '/' + f)
i = 0
for key in C.keys():
if i == 0:
net = C[key]
i = i + 1
continue
else:
net = rf.stitch(net, C[key])
#Extracts just the information from the s2p data that you need for fitting and puts them into np arrays
mag = net.s21.s_mag[:, 0, 0]
freq = net.frequency.f
real = net.s21.s_re[:, 0, 0]
imag = net.s21.s_im[:, 0, 0]
#Finds the peaks for chunking up individual peaks out of the full frequency sweep
freqs, pks = pk.get_peaks(freq, mag, f_delta=100e3, res_num=62)
#Loops through found peaks, fits only +/- 400kHz around the peak with the fitting code then plots and saves it.
results = {}
for fr in freqs:
f_start = fr - 200e3
f_stop = fr + 200e3
import skrf as rf
from pylab import *
import os
data_folder='results'
touchstone_file_lf = os.path.join(data_folder,'t520_10u_lfF.s1p')
touchstone_file = os.path.join(data_folder,'t520_10uF.s1p')
baseline= os.path.join(data_folder,'T520B476M010ATE035.s2p')
# Network 1
zmeas_lf = rf.Network(touchstone_file_lf)
zmeas=rf.Network(touchstone_file)
full_ntwk=rf.stitch(zmeas_lf[2:], zmeas)
full_ntwk.name='T520B_47uF10V_meas'
# Network 2
model_ntwk=rf.Network(baseline)
model_ntwk.name="T520B_47uF10V_model"
# Saving Network 1
full_ntwk.write_touchstone('T520B_47uF10V_meas.s1p','./results/',False,True)
# Plotting
rf.stylely() # matplotlib custom style from skrf.mplstyle
figure(figsize=(8,6))
loglog()
model_ntwk.plot_z_mag(m=0,n=0,marker='x', markevery=1, label='model')
full_ntwk.plot_z_mag(marker='+', markevery=1,label='measured')
title('Kemet T520B 47uF 10V' )
