Commit bb192aa8 authored by Markus Mirz's avatar Markus Mirz
Browse files

updating dpsim reader and removing deprecated parts

parent 6bcb2b4e
...@@ -73,115 +73,6 @@ def read_timeseries_simulink(filename, timeseries_names=None): ...@@ -73,115 +73,6 @@ def read_timeseries_simulink(filename, timeseries_names=None):
return timeseries_list 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): def read_timeseries_dpsim(filename, timeseries_names=None):
"""Reads complex time series data from DPsim log file. Real and """Reads complex time series data from DPsim log file. Real and
imaginary part are stored in one complex variable. imaginary part are stored in one complex variable.
...@@ -213,17 +104,17 @@ def read_timeseries_dpsim(filename, timeseries_names=None): ...@@ -213,17 +104,17 @@ def read_timeseries_dpsim(filename, timeseries_names=None):
#print("Found complex variable: " + tmp) #print("Found complex variable: " + tmp)
elif not imaginary_string in column: elif not imaginary_string in column:
real_result_columns.append(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: for column in cmpl_result_columns:
timeseries_list.append( timeseries_list.append(
TimeSeries(column, timestamps, TimeSeries(column, timestamps,
np.vectorize(complex)(pd_df[column + real_string], np.vectorize(complex)(pd_df[column + real_string],
pd_df[column + imaginary_string]))) pd_df[column + imaginary_string])))
for column in real_result_columns:
timeseries_list.append(
TimeSeries(column, timestamps, pd_df[column]))
else: else:
# Read in specified time series # Read in specified time series
......
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