backscatter.fitacf.filtering module

class backscatter.fitacf.filtering.Filtering

Bases: object

This class contains static methods relating to the filtering of bad data from the consideration of fitting.

static filter_bad_acfs(raw_data, ranges, noise_pwr)

Removes bad ACFs entirely from analysis

Removes ACFs which are deemed to be pure noise, or ACFs with too few power lags left

Parameters:

• raw_data – a dictionary of raw data parameters

• range_list – A list of Range objects with data points

• noise_pwr – minimum power for which an ACF is pure noise

static filter_bad_fits(ranges)

static filter_inf_lags(range_list)

static filter_low_pwr_lags(raw_data, range_list)

Removes low power lags from fitting

Prunes off low power lags determined by cutoff criteria. Once a cutoff lag is determined, all subsequent lags in the list are removed

Parameters:

• raw_data – a dictionary of raw data parameters

• range_list – A list of Range objects with data points

static filter_tx_overlapped_lags(raw_data, lags, range_list)

Remove data points affected by TX overlapped lags

Parameters:

• raw_data – a dictionary of raw data parameters

• lags – list of lag dictionaries

• range_list – A list of Range objects with data points

static mark_bad_samples(raw_data)

Mark the samples that are blacked out by TX overlap

Parameters:

raw_data – a dictionary of raw data parameters