Preprocessing¶

class muse_origin.Preprocessing(orig, idx, param)[source]¶

Bases: muse_origin.Step

Preparation of the data for the following steps:

Continuum subtraction with a DCT filter (the continuum cube is stored in cube_dct)
Standardization of the data (stored in cube_std).
Computation of the local maxima and minima of the std cube (cube_std_local_max and cube_std_local_min).
Segmentation based on the continuum (segmap_cont).
Segmentation based on the residual image (ima_std), merged with the previous one which gives segmap_merged.

Parameters

dct_orderint: The number of atom to keep for the DCT decomposition, defaults to 10.
dct_approxbool: If True, the DCT computation does not take the variance into account for the computation of the DCT coefficients. Defaults to False.
pfasegcontfloat: PFA for the segmentation based on the continuum, defaults to 0.01
pfasegresfloat: PFA for the segmentation based on the residual, defaults to 0.01
local_max_sizeint: Connectivity of contiguous voxels per axis, for the maximum filter, defaults to 3.
binsstr: Method for computing bins for the segmentation of the continuum and of the residual images (see numpy.histogram_bin_edges), defaults to ‘fd’.

Returns

self.cube_stdCube: Standardized data for the PCA.
self.cont_dctCube: Continuum estimated with a DCT.
self.ima_stdImage: White-light image of standardized data cube.
self.ima_dctImage: White-light image of DCT continuum cube.
self.cube_std_local_maxCube: Local maxima from cube_std.
self.cube_std_local_minCube: Local maxima from minus cube_std.
self.segmap_contImage: Segmentation map computed on the white-light image.
self.segmap_mergedImage: Segmentation map merged with the cont one and another one computed on the residual.

Attributes Summary

`cont_dct`
`cube_std`
`cube_std_local_max`
`cube_std_local_min`
`desc`
`ima_dct`
`ima_std`
`name`
`require`
`segmap_cont`
`segmap_merged`
`status`	Processing status (`muse_origin.Status`):

Methods Summary

`__call__`(self, \args, \\*kwargs)	Run a step, calling its `run` method.
`dump`(self, outpath)	Save the attributes that have been created by the steps, and unload them to free memory.
`load`(self, outpath)	Recreate attributes of a step, not really loading them as just the file is set, and files are loaded in memory only if needed.
`run`(self, orig[, dct_order, dct_approx, …])
`store_cube`(self, name, data, \\kwargs)	Create a MPDAF Cube and store it as an attribute.
`store_image`(self, name, data, \\kwargs)	Create a MPDAF Image and store it as an attribute.

Attributes Documentation

cont_dct = None¶

cube_std = None¶

cube_std_local_max = None¶

cube_std_local_min = None¶

desc = 'Preprocessing'¶

ima_dct = None¶

ima_std = None¶

name = 'preprocessing'¶

require = None¶

segmap_cont = None¶

segmap_merged = None¶

status¶

Processing status (muse_origin.Status):

NOTRUN: The step has not been run.
RUN: The step has been run but not saved.
DUMP: The step has been run and its outputs saved to disk.
FAILED: The step has been run but it failed.

Methods Documentation

__call__(self, *args, **kwargs)¶

Run a step, calling its run method.

This method is the one that is called from the ORIGIN object. It calls the run method of the step and also does a few additional things like storing the parameters, execution time and date.

dump(self, outpath)¶: Save the attributes that have been created by the steps, and unload them to free memory.

load(self, outpath)¶: Recreate attributes of a step, not really loading them as just the file is set, and files are loaded in memory only if needed.

run(self, orig, dct_order=10, dct_approx=False, pfasegcont=0.01, pfasegres=0.01, local_max_size=3, bins='fd')[source]¶

store_cube(self, name, data, **kwargs)¶: Create a MPDAF Cube and store it as an attribute.

store_image(self, name, data, **kwargs)¶: Create a MPDAF Image and store it as an attribute.