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Commit 00489685 authored by Markus Mirz's avatar Markus Mirz
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updated dpsim tools

parent 20ab9a9b
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Showing with 310 additions and 303 deletions
dataprocessing/plotdpsim.py
View file @ 00489685
......@@ -3,6 +3,7 @@ from .plottools import *
from .calc import *
import matplotlib
import matplotlib.pyplot as plt
from scipy.interpolate import interp1d
matplotlib.rcParams.update({'font.size': 8})
def plot_dpsim_abs_diff(filename1, label1, node1, filename2, label2, node2):
......@@ -143,8 +144,297 @@ def plot_dpsim_abs_single(filename, node):
plt.grid(True)
plt.show()
def main():
plot_dpsim_single()
if __name__ == "__main__":
main()
\ No newline at end of file
def plotNodeVoltageInterpDpRef(filenameRef, filenameDP, node):
node = node - 1
dfRef = pd.read_csv(filenameRef, header=None)
dfDP = pd.read_csv(filenameDP, header=None)
if (dfRef.shape[1] - 1) < node or node < 0:
print('Node not available')
exit()
if (dfDP.shape[1] - 1) / 2 < node or node < 0:
print('Node not available')
exit()
# Ref
timeRef = np.array(dfRef.ix[:, 0])
voltageRef = np.array(dfRef.ix[:, node + 1])
# DP interpolated
timeDP = np.array(dfDP.ix[:, 0])
voltageReDP = np.array(dfDP.ix[:, node + 1])
voltageImDP = np.array(dfDP.ix[:, int((dfDP.shape[1] - 1) / 2 + node + 1)])
interpTime = np.arange(dfDP.ix[0, 0], dfDP.ix[dfDP.shape[0] - 1, 0], 0.00005)
fVoltageRe = interp1d(timeDP, voltageReDP)
fVoltageIm = interp1d(timeDP, voltageImDP)
interpVoltageRe = fVoltageRe(interpTime)
interpVoltageIm = fVoltageIm(interpTime)
voltageShiftDPInterp = interpVoltageRe * np.cos(2 * np.pi * 50 * interpTime) - interpVoltageIm * np.sin(
2 * np.pi * 50 * interpTime)
voltageAbsDP = np.sqrt(voltageReDP ** 2 + voltageImDP ** 2)
fig, ax1 = plt.subplots()
ax1.plot(timeRef, voltageRef, 'm:', label='Ref')
ax1.plot(interpTime, voltageShiftDPInterp, 'b--', label='DP interp')
ax1.plot(timeDP, voltageAbsDP, 'r-', label='DP abs')
# Now add the legend with some customizations.
legend = ax1.legend(loc='lower right', shadow=True)
# The frame is matplotlib.patches.Rectangle instance surrounding the legend.
frame = legend.get_frame()
frame.set_facecolor('0.90')
ax1.set_xlabel('time [s]')
ax1.set_ylabel('mag [V]')
ax1.grid(True)
plt.show()
def plotNodeVoltageDpEmtRef(filenameRef, filenameDP, filenameEMT, node):
node = node - 1
dfRef = pd.read_csv(filenameRef, header=None)
dfEMT = pd.read_csv(filenameEMT, header=None)
dfDP = pd.read_csv(filenameDP, header=None)
if (dfRef.shape[1] - 1) < node or node < 0:
print('Node not available')
exit()
if (dfEMT.shape[1] - 1) < node or node < 0:
print('Node not available')
exit()
if (dfDP.shape[1] - 1) / 2 < node or node < 0:
print('Node not available')
exit()
# Ref
timeRef = np.array(dfRef.ix[:, 0])
voltageRef = np.array(dfRef.ix[:, node + 1])
# EMT
timeEMT = np.array(dfEMT.ix[:, 0])
voltageEMT = np.array(dfEMT.ix[:, node + 1])
# DP
timeDP = np.array(dfDP.ix[:, 0])
voltageReDP = np.array(dfDP.ix[:, node + 1])
voltageImDP = np.array(dfDP.ix[:, int((dfDP.shape[1] - 1) / 2 + node + 1)])
voltageAbsDP = np.sqrt(voltageReDP ** 2 + voltageImDP ** 2)
voltageShiftDP = voltageReDP * np.cos(2 * np.pi * 50 * timeDP) - voltageImDP * np.sin(2 * np.pi * 50 * timeDP)
fig, ax1 = plt.subplots()
ax1.plot(timeRef, voltageRef, 'm:', label='Ref')
ax1.plot(timeEMT, voltageEMT, 'g--', label='EMT')
ax1.plot(timeDP, voltageShiftDP, 'b--', label='DP shift')
ax1.plot(timeDP, voltageAbsDP, 'r-', label='DP abs')
# Now add the legend with some customizations.
legend = ax1.legend(loc='lower right', shadow=True)
# The frame is matplotlib.patches.Rectangle instance surrounding the legend.
frame = legend.get_frame()
frame.set_facecolor('0.90')
ax1.set_xlabel('time [s]')
ax1.set_ylabel('mag [V]')
ax1.grid(True)
plt.show()
def plotNodeVoltageDpEmt(filenameDP, filenameEMT, node):
node = node - 1
dfEMT = pd.read_csv(filenameEMT, header=None)
dfDP = pd.read_csv(filenameDP, header=None)
if (dfEMT.shape[1] - 1) < node or node < 0:
print('Node not available')
exit()
if (dfDP.shape[1] - 1) / 2 < node or node < 0:
print('Node not available')
exit()
# EMT
timeEMT = np.array(dfEMT.ix[:, 0])
voltageEMT = np.array(dfEMT.ix[:, node + 1])
# DP
timeDP = np.array(dfDP.ix[:, 0])
voltageReDP = np.array(dfDP.ix[:, node + 1])
voltageImDP = np.array(dfDP.ix[:, int((dfDP.shape[1] - 1) / 2 + node + 1)])
voltageAbsDP = np.sqrt(voltageReDP ** 2 + voltageImDP ** 2)
voltageShiftDP = voltageReDP * np.cos(2 * np.pi * 50 * timeDP) - voltageImDP * np.sin(2 * np.pi * 50 * timeDP)
fig, ax1 = plt.subplots()
ax1.plot(timeEMT, voltageEMT, 'g--', label='EMT')
ax1.plot(timeDP, voltageShiftDP, 'b--', label='DP shift')
ax1.plot(timeDP, voltageAbsDP, 'r-', label='DP abs')
# Now add the legend with some customizations.
legend = ax1.legend(loc='lower right', shadow=True)
# The frame is matplotlib.patches.Rectangle instance surrounding the legend.
frame = legend.get_frame()
frame.set_facecolor('0.90')
ax1.set_xlabel('time [s]')
ax1.set_ylabel('mag [V]')
ax1.grid(True)
plt.show()
def plotEmtNodeResults(filename, node):
node = node - 1
df = pd.read_csv(filename, header=None)
print(df.shape)
if (df.shape[1] - 1) < node or node < 0:
print('Node not available')
exit()
time = np.array(df.ix[:, 0])
voltage = np.array(df.ix[:, node + 1])
fig, ax1 = plt.subplots()
ax1.plot(time, voltage, 'b-')
# plt.yticks(np.arange(-10, 10, 1.0))
ax1.set_xlabel('time [s]')
ax1.set_ylabel('mag [V] or [A]')
ax1.grid(True)
plt.show()
def plotNodeResults(filename, node):
node = node - 1
df = pd.read_csv(filename, header=None)
print(df.shape)
if (df.shape[1] - 1) / 2 < node or node < 0:
print('Node not available')
exit()
time = np.array(df.ix[:, 0])
voltageRe = np.array(df.ix[:, node + 1])
voltageIm = np.array(df.ix[:, int((df.shape[1] - 1) / 2 + node + 1)])
voltage = np.sqrt(voltageRe ** 2 + voltageIm ** 2)
voltageEmt = voltageRe * np.cos(2 * np.pi * 50 * time) - voltageIm * np.sin(2 * np.pi * 50 * time)
fig, ax1 = plt.subplots()
ax1.plot(time, voltageEmt, 'b-', time, voltage, 'r-')
# plt.yticks(np.arange(-10, 10, 1.0))
ax1.set_xlabel('time [s]')
ax1.set_ylabel('mag [V] or [A]')
ax1.grid(True)
plt.show()
def plotInterpolatedNodeResults(filename, node):
node = node - 1
df = pd.read_csv(filename, header=None)
print(df.shape)
if (df.shape[1] - 1) / 2 < node or node < 0:
print('Node not available')
exit()
time = np.array(df.ix[:, 0])
voltageRe = np.array(df.ix[:, node + 1])
voltageIm = np.array(df.ix[:, int((df.shape[1] - 1) / 2 + node + 1)])
interpTime = np.arange(df.ix[0, 0], df.ix[df.shape[0] - 1, 0], 0.00005)
fVoltageRe = interp1d(time, voltageRe)
fVoltageIm = interp1d(time, voltageIm)
interpVoltageRe = fVoltageRe(interpTime)
interpVoltageIm = fVoltageIm(interpTime)
voltageMeas = np.sqrt(voltageRe ** 2 + voltageIm ** 2)
voltage = np.sqrt(interpVoltageRe ** 2 + interpVoltageIm ** 2)
voltageEmt = interpVoltageRe * np.cos(2 * np.pi * 50 * interpTime) - interpVoltageIm * np.sin(
2 * np.pi * 50 * interpTime)
fig, ax1 = plt.subplots()
ax1.plot(interpTime, voltageEmt, 'b-')
ax1.plot(time, voltageMeas, 'r-')
ax1.set_xlabel('time [s]')
ax1.set_ylabel('mag [V] or [A]')
ax1.grid(True)
plt.show()
def plotResultsInterfacedInductor(filename, node):
node = node - 1
df = pd.read_csv(filename, header=None)
print(df.shape)
if (df.shape[1] - 1) / 2 < node or node < 0:
print('Voltage not available')
exit()
time = np.array(df.ix[:, 0])
voltageRe = np.array(df.ix[:, node + 1])
voltageIm = np.array(df.ix[:, int((df.shape[1] - 1) / 2 + node + 1)])
voltage = np.sqrt(voltageRe ** 2 + voltageIm ** 2)
voltageEmt = voltageRe * np.cos(2 * np.pi * 50 * time) - voltageIm * np.sin(2 * np.pi * 50 * time)
fig, ax1 = plt.subplots()
ax1.plot(time, voltageEmt, 'b-', time, voltage, 'r-')
plt.yticks(np.arange(-10, 10, 1.0))
ax1.set_xlabel('time [s]')
ax1.set_ylabel('voltage [V]')
ax1.grid(True)
plt.show()
def plotResultsSynGenUnitTest(filename, node1, node2, node3):
node1 = node1 - 1
node2 = node2 - 1
node3 = node3 - 1
df = pd.read_csv(filename, header=None)
print(df.shape)
if (df.shape[1] - 1) / 2 < node1 or node1 < 0 or \
(df.shape[1] - 1) / 2 < node2 or node2 < 0 or \
(df.shape[1] - 1) / 2 < node3 or node3 < 0:
print('Voltage not available')
exit()
time = np.array(df.ix[:, 0])
mag1 = np.array(df.ix[:, node1 + 1])
mag2 = np.array(df.ix[:, node2 + 1])
mag3 = np.array(df.ix[:, node3 + 1])
fig, ax1 = plt.subplots()
ax1.plot(time, mag1, 'b-', time, mag2, 'r-', time, mag3, 'g-')
# ax1.plot(time, voltageEmt, 'b-', time, voltage, 'r-')
# plt.yticks(np.arange(-10, 10, 1.0))
ax1.set_xlabel('time [s]')
ax1.set_ylabel('Magnitude')
ax1.grid(True)
plt.show()
def plotResultsSynGenUnitTestVar(filename, varNum):
df = pd.read_csv(filename, header=None)
print(df.shape)
if (df.shape[1]) < varNum or varNum < 0:
print('Variable not available')
exit()
time = np.array(df.ix[:, 0])
mag = np.array(df.ix[:, varNum])
fig, ax1 = plt.subplots()
ax1.plot(time, mag, 'b-')
# plt.yticks(np.arange(-10, 10, 1.0))
ax1.set_xlabel('time [s]')
ax1.set_ylabel('Magnitude')
ax1.grid(True)
plt.show()
dataprocessing/plotdpsim_deprecated.py deleted 100644 → 0
View file @ 20ab9a9b
import numpy as np
import matplotlib.pyplot as plt
import pandas as pd
from scipy.interpolate import interp1d
def plotNodeVoltageInterpDpRef(filenameRef, filenameDP, node):
node = node - 1
dfRef = pd.read_csv(filenameRef, header=None)
dfDP = pd.read_csv(filenameDP, header=None)
if (dfRef.shape[1] - 1) < node or node < 0:
print('Node not available')
exit()
if (dfDP.shape[1] - 1) / 2 < node or node < 0:
print('Node not available')
exit()
# Ref
timeRef = np.array(dfRef.ix[:,0])
voltageRef = np.array(dfRef.ix[:,node + 1])
#DP interpolated
timeDP = np.array(dfDP.ix[:,0])
voltageReDP = np.array(dfDP.ix[:,node + 1])
voltageImDP = np.array(dfDP.ix[:, int((dfDP.shape[1] - 1) / 2 + node + 1)])
interpTime = np.arange(dfDP.ix[0, 0], dfDP.ix[ dfDP.shape[0] - 1, 0], 0.00005)
fVoltageRe = interp1d(timeDP, voltageReDP)
fVoltageIm = interp1d(timeDP, voltageImDP)
interpVoltageRe = fVoltageRe(interpTime)
interpVoltageIm = fVoltageIm(interpTime)
voltageShiftDPInterp = interpVoltageRe*np.cos(2*np.pi*50*interpTime) - interpVoltageIm*np.sin(2*np.pi*50*interpTime)
voltageAbsDP = np.sqrt(voltageReDP**2+voltageImDP**2)
fig, ax1 = plt.subplots()
ax1.plot(timeRef, voltageRef, 'm:', label='Ref')
ax1.plot(interpTime, voltageShiftDPInterp, 'b--', label='DP interp')
ax1.plot(timeDP, voltageAbsDP, 'r-', label='DP abs')
# Now add the legend with some customizations.
legend = ax1.legend(loc='lower right', shadow=True)
# The frame is matplotlib.patches.Rectangle instance surrounding the legend.
frame = legend.get_frame()
frame.set_facecolor('0.90')
ax1.set_xlabel('time [s]')
ax1.set_ylabel('mag [V]')
ax1.grid(True)
plt.show()
def plotNodeVoltageDpEmtRef(filenameRef, filenameDP, filenameEMT, node):
node = node - 1
dfRef = pd.read_csv(filenameRef, header=None)
dfEMT = pd.read_csv(filenameEMT, header=None)
dfDP = pd.read_csv(filenameDP, header=None)
if (dfRef.shape[1] - 1) < node or node < 0:
print('Node not available')
exit()
if (dfEMT.shape[1] - 1) < node or node < 0:
print('Node not available')
exit()
if (dfDP.shape[1] - 1) / 2 < node or node < 0:
print('Node not available')
exit()
# Ref
timeRef = np.array(dfRef.ix[:,0])
voltageRef = np.array(dfRef.ix[:,node + 1])
# EMT
timeEMT = np.array(dfEMT.ix[:,0])
voltageEMT = np.array(dfEMT.ix[:,node + 1])
#DP
timeDP = np.array(dfDP.ix[:,0])
voltageReDP = np.array(dfDP.ix[:,node + 1])
voltageImDP = np.array(dfDP.ix[:, int((dfDP.shape[1] - 1) / 2 + node + 1)])
voltageAbsDP = np.sqrt(voltageReDP**2+voltageImDP**2)
voltageShiftDP = voltageReDP*np.cos(2*np.pi*50*timeDP) - voltageImDP*np.sin(2*np.pi*50*timeDP)
fig, ax1 = plt.subplots()
ax1.plot(timeRef, voltageRef, 'm:', label='Ref')
ax1.plot(timeEMT, voltageEMT, 'g--', label='EMT')
ax1.plot(timeDP, voltageShiftDP, 'b--', label='DP shift')
ax1.plot(timeDP, voltageAbsDP, 'r-', label='DP abs')
# Now add the legend with some customizations.
legend = ax1.legend(loc='lower right', shadow=True)
# The frame is matplotlib.patches.Rectangle instance surrounding the legend.
frame = legend.get_frame()
frame.set_facecolor('0.90')
ax1.set_xlabel('time [s]')
ax1.set_ylabel('mag [V]')
ax1.grid(True)
plt.show()
def plotNodeVoltageDpEmt(filenameDP, filenameEMT, node):
node = node - 1
dfEMT = pd.read_csv(filenameEMT, header=None)
dfDP = pd.read_csv(filenameDP, header=None)
if (dfEMT.shape[1] - 1) < node or node < 0:
print('Node not available')
exit()
if (dfDP.shape[1] - 1) / 2 < node or node < 0:
print('Node not available')
exit()
# EMT
timeEMT = np.array(dfEMT.ix[:,0])
voltageEMT = np.array(dfEMT.ix[:,node + 1])
#DP
timeDP = np.array(dfDP.ix[:,0])
voltageReDP = np.array(dfDP.ix[:,node + 1])
voltageImDP = np.array(dfDP.ix[:, int((dfDP.shape[1] - 1) / 2 + node + 1)])
voltageAbsDP = np.sqrt(voltageReDP**2+voltageImDP**2)
voltageShiftDP = voltageReDP*np.cos(2*np.pi*50*timeDP) - voltageImDP*np.sin(2*np.pi*50*timeDP)
fig, ax1 = plt.subplots()
ax1.plot(timeEMT, voltageEMT, 'g--', label='EMT')
ax1.plot(timeDP, voltageShiftDP, 'b--', label='DP shift')
ax1.plot(timeDP, voltageAbsDP, 'r-', label='DP abs')
# Now add the legend with some customizations.
legend = ax1.legend(loc='lower right', shadow=True)
# The frame is matplotlib.patches.Rectangle instance surrounding the legend.
frame = legend.get_frame()
frame.set_facecolor('0.90')
ax1.set_xlabel('time [s]')
ax1.set_ylabel('mag [V]')
ax1.grid(True)
plt.show()
def plotEmtNodeResults(filename, node):
node = node - 1
df = pd.read_csv(filename, header=None)
print(df.shape)
if (df.shape[1] - 1) < node or node < 0:
print('Node not available')
exit()
time = np.array(df.ix[:,0])
voltage = np.array(df.ix[:,node + 1])
fig, ax1 = plt.subplots()
ax1.plot(time, voltage, 'b-')
#plt.yticks(np.arange(-10, 10, 1.0))
ax1.set_xlabel('time [s]')
ax1.set_ylabel('mag [V] or [A]')
ax1.grid(True)
plt.show()
def plotNodeResults(filename, node):
node = node - 1
df = pd.read_csv(filename, header=None)
print(df.shape)
if (df.shape[1] - 1) / 2 < node or node < 0:
print('Node not available')
exit()
time = np.array(df.ix[:,0])
voltageRe = np.array(df.ix[:,node + 1])
voltageIm = np.array(df.ix[:, int((df.shape[1] - 1) / 2 + node + 1)])
voltage = np.sqrt(voltageRe**2+voltageIm**2)
voltageEmt = voltageRe*np.cos(2*np.pi*50*time) - voltageIm*np.sin(2*np.pi*50*time)
fig, ax1 = plt.subplots()
ax1.plot(time, voltageEmt, 'b-', time, voltage, 'r-')
#plt.yticks(np.arange(-10, 10, 1.0))
ax1.set_xlabel('time [s]')
ax1.set_ylabel('mag [V] or [A]')
ax1.grid(True)
plt.show()
def plotInterpolatedNodeResults(filename, node):
node = node - 1
df = pd.read_csv(filename, header=None)
print(df.shape)
if (df.shape[1] - 1) / 2 < node or node < 0:
print('Node not available')
exit()
time = np.array(df.ix[:,0])
voltageRe = np.array(df.ix[:,node + 1])
voltageIm = np.array(df.ix[:, int((df.shape[1] - 1) / 2 + node + 1)])
interpTime = np.arange(df.ix[0, 0], df.ix[ df.shape[0] - 1, 0], 0.00005)
fVoltageRe = interp1d(time, voltageRe)
fVoltageIm = interp1d(time, voltageIm)
interpVoltageRe = fVoltageRe(interpTime)
interpVoltageIm = fVoltageIm(interpTime)
voltageMeas = np.sqrt(voltageRe**2+voltageIm**2)
voltage = np.sqrt(interpVoltageRe**2+interpVoltageIm**2)
voltageEmt = interpVoltageRe*np.cos(2*np.pi*50*interpTime) - interpVoltageIm*np.sin(2*np.pi*50*interpTime)
fig, ax1 = plt.subplots()
ax1.plot(interpTime, voltageEmt, 'b-')
ax1.plot(time, voltageMeas, 'r-')
ax1.set_xlabel('time [s]')
ax1.set_ylabel('mag [V] or [A]')
ax1.grid(True)
plt.show()
def plotResultsInterfacedInductor(filename, node):
node = node - 1
df = pd.read_csv(filename, header=None)
print(df.shape)
if (df.shape[1] - 1) / 2 < node or node < 0:
print('Voltage not available')
exit()
time = np.array(df.ix[:,0])
voltageRe = np.array(df.ix[:,node + 1])
voltageIm = np.array(df.ix[:, int((df.shape[1] - 1) / 2 + node + 1)])
voltage = np.sqrt(voltageRe**2+voltageIm**2)
voltageEmt = voltageRe*np.cos(2*np.pi*50*time) - voltageIm*np.sin(2*np.pi*50*time)
fig, ax1 = plt.subplots()
ax1.plot(time, voltageEmt, 'b-', time, voltage, 'r-')
plt.yticks(np.arange(-10, 10, 1.0))
ax1.set_xlabel('time [s]')
ax1.set_ylabel('voltage [V]')
ax1.grid(True)
plt.show()
def plotResultsSynGenUnitTest(filename, node1, node2, node3):
node1 = node1 - 1
node2 = node2 - 1
node3 = node3 - 1
df = pd.read_csv(filename, header=None)
print(df.shape)
if (df.shape[1] - 1) / 2 < node1 or node1 < 0 or \
(df.shape[1] - 1) / 2 < node2 or node2 < 0 or \
(df.shape[1] - 1) / 2 < node3 or node3 < 0:
print('Voltage not available')
exit()
time = np.array(df.ix[:,0])
mag1 = np.array(df.ix[:,node1 + 1])
mag2 = np.array(df.ix[:,node2 + 1])
mag3 = np.array(df.ix[:,node3 + 1])
fig, ax1 = plt.subplots()
ax1.plot(time, mag1, 'b-', time, mag2, 'r-', time, mag3, 'g-')
#ax1.plot(time, voltageEmt, 'b-', time, voltage, 'r-')
#plt.yticks(np.arange(-10, 10, 1.0))
ax1.set_xlabel('time [s]')
ax1.set_ylabel('Magnitude')
ax1.grid(True)
plt.show()
def plotResultsSynGenUnitTestVar(filename, varNum):
df = pd.read_csv(filename, header=None)
print(df.shape)
if (df.shape[1]) < varNum or varNum < 0:
print('Variable not available')
exit()
time = np.array(df.ix[:,0])
mag = np.array(df.ix[:,varNum])
fig, ax1 = plt.subplots()
ax1.plot(time, mag, 'b-')
#plt.yticks(np.arange(-10, 10, 1.0))
ax1.set_xlabel('time [s]')
ax1.set_ylabel('Magnitude')
ax1.grid(True)
plt.show()
dataprocessing/plottools.py
View file @ 00489685
......@@ -20,3 +20,5 @@ def plot_timeseries(figure_id, timeseries, plt_linestyle='-'):
def set_time_series_labels(timeseries_list, time_series_labels):
for ts in timeseries_list:
ts.label = time_series_labels[timeseries_list.index(ts)]
dataprocessing/timeseries.py
View file @ 00489685
import numpy as np
import cmath
class TimeSeries:
"""Stores data from different simulation sources.
......@@ -44,19 +45,23 @@ class TimeSeries:
return ts_abs
def abs(self, name):
""" Calculate absolute value of complex variable.
Assumes the same time steps for both timeseries.
""" Calculate absolute value of complex time series.
"""
ts_abs = TimeSeries(name, self.time, self.values.abs())
abs_values = []
for value in self.values:
abs_values.append(np.abs(value))
ts_abs = TimeSeries(name, self.time, abs_values)
return ts_abs
def complex_phase(name, ts_real, ts_imag):
""" Calculate absolute value of complex variable.
Assumes the same time steps for both timeseries.
def phase(self, name):
""" Calculate absolute value of complex time series.
"""
ts_complex = np.vectorize(complex)(ts_real.values, ts_imag.values)
ts_abs = TimeSeries(name, ts_real.time, ts_complex.phase())
return ts_abs
phase_values = []
for value in self.values:
phase_values.append(np.angle(value, deg=True))
ts_abs = TimeSeries