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gravitools.math

calculate_allan_dev(ds, taus='octave', measurement_rate=None)

Calculate the overlapped Allan deviation of a time series.

Parameters:

  • ds (Series) –

    Time series of frequency input data.

  • taus (array or str, default: 'octave' ) –

    Time differences (tau), in seconds, for which the Allan deviation is calculated. Specify "all", "octave" or "decade" for automatic generation. See allantools.oadev documentation.

  • measurement_rate (float, default: None ) –

    Sampling rate of the input data, in Hz. Specify None to calculate from average interval.

Returns:

  • Series –

    Allan deviation at different taus

interval_means(series, interval, min_count=None, name=None, err='sem')

Calculate interval means of a time series

See pandas.DataFrame.resample.

Parameters:

  • series (Series) –

    Input time series.

  • interval (str) –

    Resampling interval, e. g. "1h".

  • min_count (int | float, default: None ) –

    Minimum number of samples required in each interval. For intervals with fewer samples, the mean value is set to NaN. A fractional value 0 < min_count < 1 is interpreted as a fraction of the maximum number of samples.

  • name (str, default: None ) –

    Prefix of the output dataframe's columns. If unspecified, the input series' name attribute is used, or "y", if it does not have a name.

  • err (str, default: 'sem' ) –

    Statistical function to use for error column. Options are "sem" (standard error of the mean) and "std" (standard deviation).

Returns:

  • DataFrame –

    Time series of mean value, standard error of the mean (SEM), and count of samples per interval.

truncate(x, digits=0)

Truncate a float number to specified digits

weighted_mean(values, errors)

Weighted mean, standard deviation and standard error of the mean