def load_diode_data(
diode_data_file,
apply_lowpass
):
"""
Loads in diode data from a tdms file given the location
Parameters
----------
diode_data_file : str
Location of diode data file
apply_lowpass : bool
Determines whether or not a lowpass filter is applied
Returns
-------
pandas.core.frame.DataFrame
Dataframe of diode data, with time stamps removed if they are present
"""
# import data
data = TdmsFile(diode_data_file).as_dataframe()
for key in data.keys():
# remove time column
if 'diode' not in key.replace('diodes', '').lower():
data = data.drop(key, axis=1)
if apply_lowpass:
data = data.apply(_diode_filter)
return data
def load_diode_data(diode_data_file, apply_lowpass):
"""
Loads in diode data from a tdms file given the location
Parameters
----------
diode_data_file : str
Location of diode data file
apply_lowpass : bool
Determines whether or not a lowpass filter is applied
Returns
-------
pandas.core.frame.DataFrame
Dataframe of diode data, with time stamps removed if they are present
"""
# import data
tf = TdmsFile(diode_data_file)
diode_channels = tf.group_channels("diodes")
if len(diode_channels) == 0 or \
len(diode_channels[0].data) > 0:
# diodes.tdms has data
data = TdmsFile(diode_data_file).as_dataframe()
for key in data.keys():
# remove time column
if "diode" not in key.replace("diodes", "").lower():
data = data.drop(key, axis=1)
if apply_lowpass:
# noinspection PyTypeChecker
data = data.apply(_diode_filter)
else:
# empty tdms file
data = pd.DataFrame(columns=[c.path for c in diode_channels],
data=np.array([[np.NaN] * 50
for _ in diode_channels]).T)
return data
