pygwb.preprocessing.preprocessing_data_channel_name
- pygwb.preprocessing.preprocessing_data_channel_name(IFO: str, t0: int, tf: int, data_type: str, channel: str, new_sample_rate: int, cutoff_frequency: float, segment_duration: int, number_cropped_seconds: int = 2, window_downsampling: str = 'hamming', ftype: str = 'fir', time_shift: int = 0, local_data_path: str = '', frametype: str = '', input_sample_rate: int = 16384)[source]
Function doing the pre-processing of the data to be used in the remainder of the code.
- Parameters:
IFO (
str
) – Interferometer name for which to retrieve the data.t0 (
int
) – GPS time of the start of the data taking.tf (
int
) – GPS time of the end of the data taking.data_type (
str
) – String indicating the type of data to be read, either ‘public’, ‘private’ or ‘local’.channel (
str
) – Name of the channel (e.g.: “L1:GWOSC-4KHZ_R1_STRAIN”).frametype (
str
) – Frame type that contains the channel, only used if data_type=private (e.g.: “L1_HOFT_C00”).new_sample_rate (
int
) – Sampling rate of the downsampled-timeseries in Hz.cutoff_frequency (
float
) – Frequency (in Hz) from which to start applying the high pass filter.segment_duration (
int
) – Duration (in seconds) of each segment (argument of set_start_time).number_cropped_seconds (
int
, optional) – Number of seconds to remove at the beginning and end of the high-passed data. Default is 2.window_downsampling (
str
, optional) – Type of window used to downsample. Default is “hamming”.ftype (
str
, optional) – Type of filter to use in the downsampling. Default is “fir”.time_shift (
int
, optional) – Value of the time shift (in seconds). Default is 0.local_data_path (
str
, optional) – Path where local gwf frame file is stored. Default is an empty string.input_sample_rate (
int
, optional.) – Sampling rate of the timeseries to be read in Hz. Default is 16384 Hz.
- Returns:
- pre_processed_data:
gwpy.timeseries.TimeSeries
Timeseries containing the filtered and high passed data (shifted if time_shift>0).
- pre_processed_data: