fosanalysis.preprocessing.masking.ZSOD Class Reference

Abstract base class for outlier detection by different kinds of z-scores. More...

Inheritance diagram for fosanalysis.preprocessing.masking.ZSOD:

Public Member Functions
	__init__ (self, float threshold=3.5, str timespace="1d_space", *args, **kwargs)
	Construct an instance of the class.
Public Member Functions inherited from fosanalysis.preprocessing.masking.AnomalyMasker
np.array	run (self, np.array x, np.array y, np.array z, bool make_copy=True, str timespace=None, bool identify_only=False, *args, **kwargs)
	Mask strain reading anomalies with NaNs.
Public Member Functions inherited from fosanalysis.utils.base.Task
	__init__ (self, *args, **kwargs)
Public Member Functions inherited from fosanalysis.utils.base.Base
	__init__ (self, *args, **kwargs)
	Construct the object and warn about unused/unknown arguments.

Public Attributes
	threshold = threshold
	Relative height threshold above which a pixel is flagged as SRA.

Protected Member Functions
np.array	_get_outlier_mask (self, np.array z_score)
	Mask entries as SRA, whose z-scores exceed threshold.
np.array	_get_z_score (self, np.array z)
	Calculate the z-score for the given array.
tuple	_run_1d (self, np.array x, np.array z, np.array SRA_array, *args, **kwargs)
	Estimate which entries are strain reading anomalies in 1D.
tuple	_run_2d (self, np.array x, np.array y, np.array z, np.array SRA_array, *args, **kwargs)
	Estimate which entries are strain reading anomalies in 2D.
Protected Member Functions inherited from fosanalysis.preprocessing.masking.AnomalyMasker
tuple	_map_2d (self, np.array x, np.array y, np.array z, np.array SRA_array, str timespace=None, *args, **kwargs)
	Estimate, which entries are strain reading anomalies, in 2D.

Detailed Description

Abstract base class for outlier detection by different kinds of z-scores.

After calculating the z-score by the given _get_z_score(), SRAs are identified by comparing the strain increments to a threshold. The algorithms only make sense for sufficient measuring values (not NaN). An overview of all z-score calculations can be found at https://towardsdatascience.com/removing-spikes-from-raman-spectra-8a9fdda0ac22

Definition at line 579 of file masking.py.

Constructor & Destructor Documentation

__init__()

fosanalysis.preprocessing.masking.ZSOD.__init__	(		self,
		float	threshold = 3.5,
		str	timespace = "1d_space",
		*	args,
		**	kwargs )

Construct an instance of the class.

Parameters

threshold

Relative height threshold above which a pixel is flagged as SRA.

Defaults to 3.5.

Parameters

timespace
*args	Additional positional arguments, will be passed to the superconstructor.
**kwargs	Additional keyword arguments, will be passed to the superconstructor.

Definition at line 588 of file masking.py.

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Member Function Documentation

_get_outlier_mask()

np.array fosanalysis.preprocessing.masking.ZSOD._get_outlier_mask ( self, np.array z_score )

protected

Mask entries as SRA, whose z-scores exceed threshold.

Parameters

z_score

Array containing the z-score values.

Returns

Boolean array with values as outlier mask.

Definition at line 628 of file masking.py.

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_get_z_score()

np.array fosanalysis.preprocessing.masking.ZSOD._get_z_score ( self, np.array z )

protected

Calculate the z-score for the given array.

Sub-classes need to provide a meaningful implementation.

Reimplemented in fosanalysis.preprocessing.masking.ModifiedZscoreDetection, fosanalysis.preprocessing.masking.SlidingModifiedZscore, fosanalysis.preprocessing.masking.WhitakerAndHayes, and fosanalysis.preprocessing.masking.ZscoreOutlierDetection.

Definition at line 637 of file masking.py.

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_run_1d()

tuple fosanalysis.preprocessing.masking.ZSOD._run_1d ( self, np.array x, np.array z, np.array SRA_array, * args, ** kwargs )

protected

Estimate which entries are strain reading anomalies in 1D.

This operation might be applied to on a 2D array by _map_2d(). This function is called, if:

• the z is 1D or
• timespace is set to "1d_space" or "1d_time".

  Parameters

  x	Array of coordinate positions. Dependent on timespace it may hold: x: sensor coordinates, (timespace = "1d_space") y: time data (timespace = "1d_time") indices, if none of both previous options match the z's shape.
  z	Array of strain data in accordance to x and y.
  *args	Additional positional arguments to customize the behaviour.
  **kwargs	Additional keyword arguments to customize the behaviour.

  Returns

  Returns a tuple like (x, z). They correspond to the input variables of the same name. Each of those might be changed.

  Parameters

  SRA_array

  Array of boolean values indicating SRAs by True and a valid entries by False. This function returns the SRA_array instead of the z array.

Reimplemented from fosanalysis.preprocessing.masking.AnomalyMasker.

Definition at line 603 of file masking.py.

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_run_2d()

tuple fosanalysis.preprocessing.masking.ZSOD._run_2d ( self, np.array x, np.array y, np.array z, np.array SRA_array, * args, ** kwargs )

protected

Estimate which entries are strain reading anomalies in 2D.

Needs to be reimplemented by sub-classes. This function is only called, if z is 2D and timespace is "2D".

Parameters

x	Array of measuring point positions.
y	Array of time stamps.
z	Array of strain data in accordance to x and y.
*args	Additional positional arguments to customize the behaviour.
**kwargs	Additional keyword arguments to customize the behaviour.

Returns

Returns a tuple like (x, y, z). They correspond to the input variables of the same name. Each of those might be changed.

Parameters

SRA_array

Array of boolean values indicating SRAs by True and a valid entries by False. This function returns the SRA_array instead of the z array.

Reimplemented from fosanalysis.preprocessing.masking.AnomalyMasker.

Definition at line 615 of file masking.py.

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Member Data Documentation

threshold

fosanalysis.preprocessing.masking.ZSOD.threshold = threshold

Relative height threshold above which a pixel is flagged as SRA.

Defaults to 3.5.

Definition at line 602 of file masking.py.

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The documentation for this class was generated from the following file:

• src/fosanalysis/preprocessing/masking.py