update

dataprocessing/calc.py

@@ -9,6 +9,13 @@ def diff(name, ts1, ts2):
     ts_diff = TimeSeries(name, ts1.time, (ts1.values - ts2.values))
     return ts_diff
 
+def scale_ts(name, ts, factor):
+    """ Scale timeseries.
+    Assumes the same time steps for both timeseries.
+    """
+    ts_scaled = TimeSeries(name, ts.time, ts.values * factor)
+    return ts_scaled
+
 def complex_abs(name, real, imag):
     """ Calculate absolute value of complex variable.
     Assumes the same time steps for both timeseries.

dataprocessing/plotdpsim.py

@@ -22,22 +22,27 @@ def plot_dpsim_abs_diff(filename1, node1, filename2, node2):
 
     # this assumes same timestep for both simulations
     ts_abs1 = complex_abs('node ' + str(node1) + 'abs', ts_dpsim1[node1], ts_dpsim1[node1 + im_offset1])
+    ts_abs1 = scale_ts(ts_abs1.name, ts_abs1, 0.001)
     ts_abs1.label = 'reference'
     ts_abs2 = complex_abs('node ' + str(node2) + 'abs', ts_dpsim2[node1], ts_dpsim2[node1 + im_offset2])
+    ts_abs2 = scale_ts(ts_abs2.name, ts_abs2, 0.001)
     ts_abs2.label = 'local co-sim'
     ts_diff = diff('diff', ts_abs1, ts_abs2)
     ts_diff.label = 'difference'
 
     figure_id = 1
-    plt.figure(figure_id)
+    #plt.figure(figure_id)
+    plt.figure(figure_id, figsize=(12 / 2.54, 6 / 2.54), facecolor='w', edgecolor='k')
     plot_single_ts(figure_id, ts_abs1)
     plot_single_ts(figure_id, ts_abs2)
     plot_single_ts(figure_id, ts_diff)
     plt.xlabel('Time [s]')
-    plt.ylabel('Voltage [V]')
+    plt.ylabel('Voltage [kV]')
     plt.grid(True)
+    plt.tight_layout()
     plt.show()
 
+
 def plot_dpsim_abs_single(filename, node):
     ts_dpsim = read_time_series_DPsim(filename)
 

dataprocessing/plottools.py

@@ -17,15 +17,6 @@ def plot_in_subplots(figure_id, time_series, plt_linestyle='-'):
         plt.gca().autoscale(axis='x', tight=True)
         plt.legend()
 
-def plot_in_oneplot(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()
-
-
 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