updating dpsim reader and removing deprecated parts

dataprocessing/readtools.py

@@ -73,115 +73,6 @@ def read_timeseries_simulink(filename, timeseries_names=None):
 
     return timeseries_list
 
-def read_timeseries_dpsim_real(filename, timeseries_names=None):
-    """Reads real time series data from DPsim log file which may have a header.
-    Timeseries names are assigned according to the header names if available.
-    :param filename: name of the csv file that has the data
-    :param timeseries_names: column names which should be read
-    :return: list of Timeseries objects
-    """
-    timeseries_list = []
-    pd_df = pd.read_csv(filename)
-
-    if timeseries_names is None:
-        # No column names specified, thus read in all and strip spaces
-        pd_df.rename(columns=lambda x: x.strip(), inplace=True)
-        timeseries_names = list(pd_df.columns.values)
-        timeseries_names.remove('time')
-    #else:
-    #    # Read in specified column names
-    #    pd_df = pd.read_csv(filename, names=timeseries_names)
-
-    # store columns of interest in list of timeseries
-    # note: timestamps must be given in first column of csv file
-    timestamps = pd_df.iloc[:, 0]
-    for name in timeseries_names:
-        timeseries_list.append(TimeSeries(name, timestamps, pd_df[name].values))
-
-    print('DPsim results column names: ' + str(timeseries_names))
-    print('DPsim results number: ' + str(len(timeseries_list)))
-    print('DPsim results timestamps number: ' + str(len(timestamps)))
-
-    return timeseries_list
-
-
-def read_timeseries_dpsim_cmpl(filename, timeseries_names=None):
-    """Reads complex time series data from DPsim log file. Real and
-    imaginary part are stored in one complex variable.
-    :param filename: name of the csv file that has the data
-    :param timeseries_names: column name which should be read
-    :return: list of Timeseries objects
-    """
-    pd_df = pd.read_csv(filename)
-    timeseries_list = []
-
-    if timeseries_names is None:
-        # No column names specified, thus read in all and strip off spaces
-        pd_df.rename(columns=lambda x: x.strip(), inplace=True)
-        column_names = list(pd_df.columns.values)
-
-        # Remove timestamps column name and store separately
-        column_names.remove('time')
-        timestamps = pd_df.iloc[:, 0]
-        # Calculate number of network nodes since array is [real, imag]
-        node_number = int(len(column_names) / 2)
-        node_index = 1
-        for column in column_names:
-            if node_index <= node_number:
-                ts_name = 'n' + str(node_index)
-                timeseries_list.append(
-                    TimeSeries(ts_name, timestamps, np.vectorize(complex)(pd_df.iloc[:, node_index], pd_df.iloc[:, node_index + node_number])))
-            else:
-                break
-            node_index = node_index + 1
-    else:
-        # Read in specified time series
-        print('cannot read specified columns yet')
-
-    print('DPsim results column names: ' + str(column_names))
-    print('DPsim results number: ' + str(len(timeseries_list)))
-
-    return timeseries_list
-
-
-def read_timeseries_dpsim_cmpl_separate(filename, timeseries_names=None):
-    """Deprecated - Reads complex time series data from DPsim log file. Real and
-    imaginary part are stored separately.
-    :param filename: name of the csv file that has the data
-    :param timeseries_names: column name which should be read
-    :return: list of Timeseries objects
-    """
-    pd_df = pd.read_csv(filename, header=None)
-    timeseries_list = []
-
-    if timeseries_names is None:
-        # No trajectory names specified, thus read in all
-        column_names = list(pd_df.columns.values)
-        # Remove timestamps column name and store separately
-        column_names.remove(0)
-        timestamps = pd_df.iloc[:, 0]
-        # Calculate number of network nodes since array is [real, imag]
-        node_number = int(len(column_names) / 2)
-        node_index = 1
-        for column in column_names:
-            if node_index <= node_number:
-                node_name = 'node ' + str(node_index) + ' Re'
-                timeseries_list.append(TimeSeries(node_name, timestamps, pd_df.iloc[:, column]))
-            else:
-                node_name = 'node ' + str(node_index - node_number) + ' Im'
-                timeseries_list.append(TimeSeries(node_name, timestamps, pd_df.iloc[:, column]))
-
-            node_index = node_index + 1
-    else:
-        # Read in specified time series
-        print('no column names specified yet')
-
-    print('DPsim results file length:')
-    print(len(timeseries_list))
-    for result in timeseries_list:
-        print(result.name)
-    return timeseries_list
-
 def read_timeseries_dpsim(filename, timeseries_names=None):
     """Reads complex time series data from DPsim log file. Real and
     imaginary part are stored in one complex variable.
@@ -213,17 +104,17 @@ def read_timeseries_dpsim(filename, timeseries_names=None):
                 #print("Found complex variable: " + tmp)
             elif not imaginary_string in column:
                 real_result_columns.append(column)
-                #print("Found real variable: " + column)
- 
+                #print("Found real variable: " + column)       
+        
+        for column in real_result_columns:                
+            timeseries_list.append(
+                TimeSeries(column, timestamps, pd_df[column]))
+
         for column in cmpl_result_columns:                
             timeseries_list.append(
                 TimeSeries(column, timestamps, 
                     np.vectorize(complex)(pd_df[column + real_string], 
                     pd_df[column + imaginary_string])))
-        
-        for column in real_result_columns:                
-            timeseries_list.append(
-                TimeSeries(column, timestamps, pd_df[column]))
            
     else:
         # Read in specified time series