base_timeseries#

class arte.dataelab.base_timeseries.BaseTimeSeries(data, time_vector=None, astropy_unit=None, data_label=None, axes=None)#

Bases: TimeSeries

Generic time series.

A time series holds:

  • N samples of numeric data of arbitrary type and dimensions, with an optional astropy unit.

  • sampling time for each sample

  • optionally, a data label for plots and displays

Data is accessed with the get_data() method. Derived classes can define specialized arguments to return data subsets, e.g. get_data(quadrant=2) Basic arithmetic operations (sum, div, etc) are supported. Astropy units, if present, will be enforced.

Parameters:

  • data_loader (instance of DataLoader or derived class, or numpy array, or filename (string or pathlib instance)) – time series data [time, data_d0 [, data_d1…]]

  • time_vector (instance of DataLoader or derived class, or numpy_array, or None) – time vector data. If None, a default counter from 0 to N-1 samples will be assigned

  • astropy_unit (astropy unit or None) – if possible, astropy unit to use with the data.

  • data_label (string or None) – human-readable label for plot (e.g.: “Surface modal coefficients” )

  • axes (sequence or None) – sequence of axes names, optional

Attributes:
axes

Data series shape

delta_time

Property with the interval between samples.

If no interval can be determined (time vector too short), returns 1 with the correct unit if applicable.

ensemble_mean

Mean over ensemble dimensions (chainable property).

ensemble_median

Median over ensemble dimensions (chainable property).

ensemble_ptp

Peak-to-peak over ensemble dimensions (chainable property).

ensemble_rms

RMS over ensemble dimensions (chainable property).

ensemble_std

Standard deviation over ensemble dimensions (chainable property).

shape

Data series shape

TODO depending on the data loader, it could be found without loading the entire data array

time_mean

Mean over time dimension (chainable property).

time_median

Median over time dimension (chainable property).

time_ptp

Peak-to-peak over time dimension (chainable property).

time_rms

RMS over time dimension (chainable property).

time_std

Standard deviation over time dimension (chainable property).

value

Extract final value(s) from TimeSeries (convenience accessor).

Methods

astropy_unit()

Data unit as an astropy unit

data_label()

Override to return a string with a readable unit name

data_unit()

Data unit string (for plots)

ensemble_size()

Number of distinct series in this time ensemble

filename()

Data filename (full path)

filter(*args, **kwargs)

Create filtered TimeSeries by applying ensemble and/or time selection.

get_data(*args[, times, axes])

Retrieve time series data with optional filtering and indexing.

get_display(*args[, times])

Display cube for the specified time interval

get_display_axes()

Display cube axes names as a list of 3 strings

get_ensemble_average(*args[, times])

Average across series at each sampling time

get_ensemble_median(*args[, times])

Median across series at each sampling time

get_ensemble_ptp(*args[, times])

Peak-to-peak (max - min) across series at each sampling time

get_ensemble_rms(*args[, times])

Root-Mean-Square across series at each sampling time (legacy method).

get_ensemble_std(*args[, times])

Standard deviation across series at each sampling time

get_index_of(*args, **kwargs)

Return a selection index

get_time_average(*args[, times])

Average value over time for each series

get_time_median(*args[, times])

Median over time for each series

get_time_ptp(*args[, times])

Peak-to-peak (max - min) over time for each series

get_time_rms(*args[, times])

Root-Mean-Square value over time for each series

get_time_std(*args[, times])

Standard deviation over time for each series

get_time_vector()

Return the series time vector

help([search, prefix])

Interactive help

imshow(*args[, cut_wings, title, xlabel, ylabel])

Display a 2d image.

movie(*args[, interval])

Display data as a movie

plot(*args[, cut_wings, title, xlabel, ylabel])

Plot timeseries

plot_cumulative_spectra(*args[, from_freq, ...])

Plot cumulative PSD

plot_hist(*args[, from_t, to_t, overplot, ...])

Plot histogram.

plot_spectra(*args[, from_freq, to_freq, ...])

Plot PSD

power(*args[, from_freq, to_freq, ...])

Compute Power Spectral Density using Welch's method.

savegif(filename, *args[, interval, loop])

Save data as an animated GIF

tile(*args[, rowlength])

Display data as a tiled 2d frame

time_size()

Number of time samples in this time ensemble

with_times(times)

Filter to specific time interval (convenience alias for filter(times=...)).

frequency

last_cut_frequency
astropy_unit()#

Data unit as an astropy unit

data_label()#

Override to return a string with a readable unit name

data_unit()#

Data unit string (for plots)

filename()#

Data filename (full path)

get_display(*args, times=None, **kwargs)#

Display cube for the specified time interval

get_display_axes()#

Display cube axes names as a list of 3 strings

get_index_of(*args, **kwargs)#

Return a selection index

Parameters:

  • *args (tuple) – user-defined arguments for data selection

  • **kwargs (dict, optional) – extra user-defined arguments for data selection

Returns:

index – indexes to select a data subset. If None, all data is selected. An integer, a list of integers or a slice will select those rows. If the data is multidimensional, a tuple can be returned where each element will select data across a single dimension. For a detailed explanation, see the “Advanced indexing” topic at https://numpy.org/doc/stable/user/basics.indexing.html#advanced-indexing

Return type:

None, integer, list of integers, slice objects, or a tuple of the previous possibilities.

imshow(*args, cut_wings=0, title='', xlabel='', ylabel='', **kwargs)#

Display a 2d image.

cut_wings=x means that colorbar is saturated for array values below x percentile and above 100-x percentile. Default is 0, i.e. all data are displayed; values below 0 are forced to 0, values above 50 are set to 50.

movie(*args, interval=0.1, **kwargs)#

Display data as a movie

plot(*args, cut_wings=0, title='', xlabel='', ylabel='', **kwargs)#

Plot timeseries

plot_cumulative_spectra(*args, from_freq=None, to_freq=None, segment_factor=None, label=None, plot_to=None, overplot=False, plot_rms=False, lineary=False, **kwargs)#

Plot cumulative PSD

plot_hist(*args, from_t=None, to_t=None, overplot=None, plot_to=None, label=None, **kwargs)#

Plot histogram. TODO: does not work, rewrite

plot_spectra(*args, from_freq=None, to_freq=None, segment_factor=None, overplot=False, label=None, plot_to=None, lineary=False, linearx=False, **kwargs)#

Plot PSD

savegif(filename, *args, interval=0.1, loop=0, **kwargs)#

Save data as an animated GIF

property shape#

Data series shape

TODO depending on the data loader, it could be found without loading the entire data array

tile(*args, rowlength=10, **kwargs)#

Display data as a tiled 2d frame