`tape.timeseries`#

Module Contents#

Represent and analyze Rubin TimeSeries data

class TimeSeries(data=None)[source]#

Represent and analyze Rubin TimeSeries data

from_dict(data_dict, time_label='time', flux_label='flux', err_label='flux_err', band_label='band')[source]#

Build dataframe from a python dictionary

Parameters:

data_dict (dict) – Dictionary contaning the data.
time_label (str) – Name for column containing time information.
flux_label (str) – Name for column containing signal (flux, magnitude, etc) information.
err_label (str) – Name for column containing error information.
band_label (str) – Name for column containing filter information.

dropna(**kwargs)[source]#: Handle NaN values, wrapper for pandas.DataFrame.dropna

from_dataframe(data, object_id, time_label='time', flux_label='flux', err_label='flux_err', band_label='band')[source]#

Loader function for inputing data from a dataframe.

Parameters:

data (pandas.DataFrame) – The data for the time serires.
object_id (str) – The ID of the current object.
time_label (str) – Name for column containing time information.
flux_label (str) – Name for column containing signal (flux, magnitude, etc) information.
err_label (str) – Name for column containing error information.
band_label (str) – Name for column containing filter information.

stetson_J(band=None)[source]#

Compute the stetsonJ statistic on data from one or several bands

Parameters:: band (str or list of str) – Single band descriptor, or list of such descriptors.
Returns:: stetsonJ – StetsonJ statistic for each of input bands.
Return type:: dict

Note

In case that no value for band is passed, the function is executed on all available bands.

sf2(sf_method='basic', argument_container=None)[source]#

Compute the structure function squared statistic on data

Parameters:

bins (numpy.array or list) – Manually provided bins, if not provided then bins are computed using the method kwarg
band_to_calc (str or list of str) – Single band descriptor, or list of such descriptors.
method ('str') – The binning method to apply, choices of ‘size’; which seeks an even distribution of samples per bin using quantiles, ‘length’; which creates bins of equal length in time and ‘loglength’; which creates bins of equal length in log time.
sthresh ('int') – Target number of samples per bin.

Returns:

stetsonJ – Structure function squared statistic for each of input bands.

Return type:

dict

Note

In case that no value for band_to_calc is passed, the function is executed on all available bands.