Tsallis¶
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class
turbustat.statistics.
Tsallis
(img, header=None, lags=None, distance=None)[source] [edit on github]¶ Bases:
turbustat.statistics.base_statistic.BaseStatisticMixIn
The Tsallis Distribution (see Tofflemire et al., 2011)
Parameters: - img : numpy.ndarray or astropy.io.fits.PrimaryHDU or astropy.io.fits.ImageHDU or spectral_cube.Projection or spectral_cube.Slice
2D image.
- header : FITS header, optional
The image header. Needed for the pixel scale.
- lags :
Quantity
, optional Give the spatial lag values to compute the distribution at. The default lag sizes are powers of 2 up to half the image size (so for a 128 by 128 image, the lags will be [1, 2, 4, 8, 16, 32, 64]).
- distance :
Quantity
, optional Physical distance to the region in the data.
Attributes Summary
data
distance
header
lag_arrays
Arrays of the image computed at different lags. lag_distribs
Histogram bins and values compute from lag_arrays
.lags
Lag values to calculate the statistics at. need_header_flag
no_data_flag
tsallis_chisq
Reduced chi-squared values for the fit at each lag value. tsallis_params
Parameters of the Tsallis distribution fit at each lag value. tsallis_stderrs
Standard errors of the Tsallis distribution fit at each lag value. tsallis_table
Return the fit parameters, standard error, and chi-squared values as an Table
.Methods Summary
fit_tsallis
([sigma_clip])Fit the Tsallis distributions. input_data_header
(data, header[, need_copy])Check if the header is given separately from the data type. load_beam
([beam])Try loading the beam from the header or a given object. load_results
(pickle_file)Load in a saved pickle file. make_tsallis
([periodic, num_bins])Calculate the Tsallis distribution at each lag. plot_fit
([save_name, color, fit_color])Plot the distributions and fits to the Tsallis function. plot_parameters
([save_name])Plot the fit parameters as a function of lag. run
([verbose, num_bins, periodic, …])Run all steps. save_results
(output_name[, keep_data])Save the results of the SCF to avoid re-computing. Attributes Documentation
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data
¶
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distance
¶
-
header
¶
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lag_arrays
¶ Arrays of the image computed at different lags.
-
lag_distribs
¶ Histogram bins and values compute from
lag_arrays
. The histogram values are in log10.
-
lags
¶ Lag values to calculate the statistics at.
-
need_header_flag
= True¶
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no_data_flag
= False¶
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tsallis_chisq
¶ Reduced chi-squared values for the fit at each lag value.
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tsallis_params
¶ Parameters of the Tsallis distribution fit at each lag value.
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tsallis_stderrs
¶ Standard errors of the Tsallis distribution fit at each lag value.
Methods Documentation
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fit_tsallis
(sigma_clip=5)[source] [edit on github]¶ Fit the Tsallis distributions.
Parameters: - sigma_clip : float
Sets the sigma value to clip data at. If
None
, no clipping is performed on the data. Defaults to 5.
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input_data_header
(data, header, need_copy=False) [edit on github]¶ Check if the header is given separately from the data type.
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load_beam
(beam=None) [edit on github]¶ Try loading the beam from the header or a given object.
Parameters: - beam :
Beam
, optional The beam.
- beam :
-
static
load_results
(pickle_file) [edit on github]¶ Load in a saved pickle file.
Parameters: - pickle_file : str
Name of filename to load in.
Returns: - self : Save statistic class
Statistic instance with saved results.
Examples
Load saved results. >>> stat = Statistic.load_results(“stat_saved.pkl”) # doctest: +SKIP
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make_tsallis
(periodic=True, num_bins=None)[source] [edit on github]¶ Calculate the Tsallis distribution at each lag. We standardize each distribution such that it has a mean of zero and variance of one before fitting.
If the lag values are fractions of a pixel when converted to pixel units, the lag is rounded down to the next smallest integer value.
Parameters: - periodic : bool, optional
Use for simulations with periodic boundaries.
- num_bins : int, optional
Number of bins to use in the histograms. Defaults to the square-root of the number of finite points in the image.
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plot_fit
(save_name=None, color='r', fit_color='k')[source] [edit on github]¶ Plot the distributions and fits to the Tsallis function.
Parameters: - save_name : str, optional
Save name for the figure. Enables saving the plot.
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plot_parameters
(save_name=None, **kwargs)[source] [edit on github]¶ Plot the fit parameters as a function of lag.
Parameters: - save_name : str,optional
Save name for the figure. Enables saving the plot.
- kwargs : passed to
errorbar
.
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run
(verbose=False, num_bins=None, periodic=True, sigma_clip=5, save_name=None)[source] [edit on github]¶ Run all steps.
Parameters: - verbose : bool, optional
Enables plotting.
- num_bins : int, optional
Sets the number of bins to use in the lag histograms. Passed to
make_tsallis
.- periodic : bool, optional
Treat periodic boundaries. Passed to
make_tsallis
. Enabled by default.- sigma_clip : float
Sets the sigma value to clip data at. Passed to
fit_tsallis()
.- save_name : str,optional
Save the figure when a file name is given.
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save_results
(output_name, keep_data=False) [edit on github]¶ Save the results of the SCF to avoid re-computing. The pickled file will not include the data cube by default.
Parameters: - output_name : str
Name of the outputted pickle file.
- keep_data : bool, optional
Save the data cube in the pickle file when enabled.