added tools and scripts for comparing modelica and plecs results

ebf92baa · Jan Dinkelbach · 75954496 · ebf92baa · ebf92baa · ebf92baa
Commit ebf92baa authored 7 years ago by Jan Dinkelbach
--- a/.gitignore
+++ b/.gitignore
+# ignore results 
+*.csv
+*.mat
+
+# ignore symbolic links
+*.egg-info
+
+# ignore compiled python files
+*.pyc
+
+# ignore logging files
+*.log
+
+# ignore generated dymola files
+buildlog.txt
+dsfinal.txt
+dsin.txt
+dslog.txt
+dsmodel*
+dymosim*
+
+# ignore matlab dumping file
+*.mdmp
+
+# ignore spyder project
+.spyderproject
+.spyproject
+
+# ignore pycharm files
+.idea
+__pycache__
+
+# ignore jupyter notebook files
+.ipynb_checkpoints
\ No newline at end of file
--- a/CompareModelicaPLECS.py
+++ b/CompareModelicaPLECS.py
+from ReadTools import *
+from PlotTools import *
+import matplotlib.pyplot as plt
+import numpy as np
+
+### --- Read in section --- ###
+# Stator currents
+stator_currents_mo = read_time_series_Modelica(r'\\tsclient\N\Diss\jdi\Documents\MachineModeling\results\Modelica3hpMachine.mat', ['inductionMachineSquirrelCage.i[1]', 'inductionMachineSquirrelCage.i[2]', 'inductionMachineSquirrelCage.i[3]'])
+stator_currents_pls = read_time_series_PLECS(r'\\tsclient\N\Diss\jdi\Documents\MachineModeling\results\PLECS3hpMachineStatorCurrents.csv')
+
+# Rotor currents
+rotor_currents_mo = read_time_series_Modelica(r'\\tsclient\N\Diss\jdi\Documents\MachineModeling\results\Modelica3hpMachine.mat', ['inductionMachineSquirrelCage.i_qd0r[1]', 'inductionMachineSquirrelCage.i_qd0r[2]'])
+rotor_currents_pls = read_time_series_PLECS(r'\\tsclient\N\Diss\jdi\Documents\MachineModeling\results\PLECS3hpMachineRotorCurrentsDqRRFs.csv')
+rotor_currents_pls[1].values = -rotor_currents_pls[1].values # transformation DQ0->QD0
+
+# Torque and speed
+torque_speed_mo = read_time_series_Modelica(r'\\tsclient\N\Diss\jdi\Documents\MachineModeling\results\Modelica3hpMachine.mat', ['inductionMachineSquirrelCage.T_e', 'inductionMachineSquirrelCage.omega_rm'])
+torque_speed_pls = read_time_series_PLECS(r'\\tsclient\N\Diss\jdi\Documents\MachineModeling\results\PLECS3hpMachineTorqueSpeed.csv')
+torque_speed_mo[1].values = torque_speed_mo[1].values/2/np.pi*60 # transformation to r/min
+
+### --- Plot section --- ###
+# Stator currents
+figure_id = 1
+plt.figure(figure_id)
+plt.title("Stator currents")
+set_time_series_labels(stator_currents_mo, ['Modelica: Ias [A]', 'Modelica: Ibs [A]', 'Modelica: Ics [A]'])
+plot_in_subplots(figure_id, stator_currents_mo)
+set_time_series_labels(stator_currents_pls, ['PLECS: Ias [A]', 'PLECS: Ibs [A]', 'PLECS: Ics [A]'])
+plot_in_subplots(figure_id, stator_currents_pls, plt_linestyle='--')
+plt.xlabel('Time [s]')
+plt.show(block=False)
+
+# Rotor currents
+figure_id = 2
+plt.figure(figure_id)
+plt.title("Rotor currents (in synchronously rotating reference frame)")
+set_time_series_labels(rotor_currents_mo, ['Modelica: Iqr\' [A]', 'Modelica: Idr\' [A]'])
+plot_in_subplots(figure_id, rotor_currents_mo)
+set_time_series_labels(rotor_currents_pls, ['PLECS: Iqr\' [A]', 'PLECS: Idr\' [A]'])
+plot_in_subplots(figure_id, rotor_currents_pls, plt_linestyle='--')
+plt.xlabel('Time [s]')
+plt.show(block=False)
+
+# Torque and speed
+figure_id = 3
+plt.figure(figure_id)
+plt.title("Rotor currents (in synchronously rotating reference frame)")
+set_time_series_labels(torque_speed_mo, ['Modelica: Torque [Nm]', 'Modelica: Speed [r/min]'])
+plot_in_subplots(figure_id, torque_speed_mo)
+set_time_series_labels(torque_speed_pls, ['PLECS: Torque [Nm]', 'PLECS: Speed [r/min]'])
+plot_in_subplots(figure_id, torque_speed_pls, plt_linestyle='--')
+plt.xlabel('Time [s]')
+plt.show()
\ No newline at end of file
--- a/PlotTools.py
+++ b/PlotTools.py
-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 plotDpDiff(filename1, node1, filename2, node2):
-    node1 = node1 - 1
-    node2 = node2 - 1
-    df1 = pd.read_csv(filename1, header=None)
-    df2 = pd.read_csv(filename2, header=None)
-
-    if (df1.shape[1] - 1) / 2 < node1 or node1 < 0:
-        print('Node 1 not available')
-        exit()
-
-    if (df2.shape[1] - 1) / 2 < node2 or node2 < 0:
-        print('Node 2 not available')
-        exit()
-
-    # this assumes same timestep for both runs
-    time = np.array(df1.ix[:,0])
-    re1 = np.array(df1.ix[:,node1 + 1])
-    re2 = np.array(df2.ix[:,node2 + 1])
-    im1 = np.array(df1.ix[:,int((df1.shape[1] - 1) / 2 + node1 + 1)])
-    im2 = np.array(df2.ix[:,int((df2.shape[1] - 1) / 2 + node2 + 1)])
-    abs1 = np.sqrt(re1**2+im1**2)
-    abs2 = np.sqrt(re2**2+im2**2)
-    diff = np.sqrt((re1-re2)**2+(im1-im2)**2)
-
-    fig, ax = plt.subplots()
-    ax.plot(time, abs1, 'b-', time, abs2, 'r-', time, diff, 'g-')
-    ax.set_xlabel('time [s]')
-    ax.set_ylabel('mag [V]')
-    ax.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):
+import numpy as np

-	df = pd.read_csv(filename, header=None)
-	print(df.shape)

-	if (df.shape[1]) < varNum or varNum < 0:
-		print('Variable not available')
-		exit()
+def plot_in_subplots(figure_id, time_series, plt_linestyle='-'):
+    plt.figure(figure_id)
+    for ts in time_series:
+        plt.subplot(len(time_series), 1, time_series.index(ts) + 1)
+        plt.plot(ts.time, ts.values, linestyle=plt_linestyle, label=ts.label)
+        plt.gca().autoscale(axis='x', tight=True)
+        plt.legend()

-	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()
+def set_time_series_labels(time_series, time_series_labels):
+    for ts in time_series:
+        ts.label = time_series_labels[time_series.index(ts)]
\ No newline at end of file
--- a/PlotToolsDPsim.py
+++ b/PlotToolsDPsim.py
+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 plotDpDiff(filename1, node1, filename2, node2):
+    node1 = node1 - 1
+    node2 = node2 - 1
+    df1 = pd.read_csv(filename1, header=None)
+    df2 = pd.read_csv(filename2, header=None)
+
+    if (df1.shape[1] - 1) / 2 < node1 or node1 < 0:
+        print('Node 1 not available')
+        exit()
+
+    if (df2.shape[1] - 1) / 2 < node2 or node2 < 0:
+        print('Node 2 not available')
+        exit()
+
+    # this assumes same timestep for both runs
+    time = np.array(df1.ix[:,0])
+    re1 = np.array(df1.ix[:,node1 + 1])
+    re2 = np.array(df2.ix[:,node2 + 1])
+    im1 = np.array(df1.ix[:,int((df1.shape[1] - 1) / 2 + node1 + 1)])
+    im2 = np.array(df2.ix[:,int((df2.shape[1] - 1) / 2 + node2 + 1)])
+    abs1 = np.sqrt(re1**2+im1**2)
+    abs2 = np.sqrt(re2**2+im2**2)
+    diff = np.sqrt((re1-re2)**2+(im1-im2)**2)
+
+    fig, ax = plt.subplots()
+    ax.plot(time, abs1, 'b-', time, abs2, 'r-', time, diff, 'g-')
+    ax.set_xlabel('time [s]')
+    ax.set_ylabel('mag [V]')
+    ax.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()
--- a/ReadTools.py
+++ b/ReadTools.py
+import numpy as np
+from modelicares import SimRes
+import pandas as pd
+
+
+class TimeSeries:
+    def __init__(self, name, time, values, label=""):
+        self.time = np.array(time)
+        self.values = np.array(values)
+        self.name = name
+        self.label = name
+
+def read_time_series_Modelica(filename, time_series_names=None):
+    sim = SimRes(filename)
+    times_series = []
+    if time_series_names is None:
+        # No trajectory names specified, thus read in all
+        print('TBD')
+    else:
+        # Read in specified time series
+        for name in time_series_names:
+            times_series.append(TimeSeries(name, sim(name).times(), sim(name).values()))
+    return times_series
+
+
+def read_time_series_PLECS(filename, time_series_names=None):
+    pd_df = pd.read_csv(filename)
+    times_series = []
+    if time_series_names is None:
+        # No trajectory names specified, thus read in all
+        time_series_names = list(pd_df.columns.values)
+        time_series_names.remove('Time')
+        for name in time_series_names:
+            times_series.append(TimeSeries(name, pd_df['Time'].values, pd_df[name].values))
+    else:
+        # Read in specified time series
+        for name in time_series_names:
+            times_series.append(TimeSeries(name, pd_df['Time'].values, pd_df[name].values))
+    return times_series
\ No newline at end of file