fosanalysis.preprocessing.resizing.Aggregate Class Reference

Change the dimension of an array using aggregate functions (such as mean, median, min or max). More...

Inheritance diagram for fosanalysis.preprocessing.resizing.Aggregate:

Public Member Functions
	__init__ (self, str or callable method, module=np, str timespace="1d_space", *args, **kwargs)
	Construct an instance of the class.
np.array	reduce (self, np.array data, int axis, *args, **kwargs)
	Reduce the given array using the kernel funcition.
np.array	run (self, np.array x, np.array y, np.array z, str timespace=None, bool make_copy=True, *args, **kwargs)
	Reduce a 2D array to a 1D array using aggregate functions.
	setup (self, str or callable method, module=np)
	Set the kernel method for data processing, which can be either a string representing function name in a given namespace module or a custom callable function.
Public Member Functions inherited from fosanalysis.preprocessing.base.Base
	__init__ (self, *args, **kwargs)
	Construct an instance of the class.
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
	kernel = method if callable(method) else getattr(module, method)
	Callable function used to aggregate the data.
	method = method
	Could be either a callable (function object) or a string representing a function name in the namespace of module.
	module = module
	A Python module or namespace in which method is looked up when method is not a callable.
	timespace = timespace
	Setting, how to compact the 2d array.

Detailed Description

Change the dimension of an array using aggregate functions (such as mean, median, min or max).

It can be used to reduce 2D to 1D strain data.

Definition at line 34 of file resizing.py.

Constructor & Destructor Documentation

__init__()

fosanalysis.preprocessing.resizing.Aggregate.__init__	(		self,
		str or callable	method,
			module = np,
		str	timespace = "1d_space",
		*	args,
		**	kwargs )

Construct an instance of the class.

Parameters

method	A string or callable representing the method.
module	The module (default is numpy).
timespace	Setting, how to compact the 2d array. For more, see timespace.
*args	Additional positional arguments, will be passed to the superconstructor.
**kwargs	Additional keyword arguments, will be passed to the superconstructor.

Definition at line 40 of file resizing.py.

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Member Function Documentation

reduce()

np.array fosanalysis.preprocessing.resizing.Aggregate.reduce	(		self,
		np.array	data,
		int	axis,
		*	args,
		**	kwargs )

Reduce the given array using the kernel funcition.

Parameters

data	Array of data with functional data according to data.
axis	Axis in which the data should be consolidated. This is in accordance with the numpy axis definitions.
*args	Additional positional arguments, passed to kernel.
**kwargs	Additional keyword arguments, passed to kernel.

Returns

Returns an array, where multiple readings are combined to one single array.

Definition at line 136 of file resizing.py.

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run()

np.array fosanalysis.preprocessing.resizing.Aggregate.run	(		self,
		np.array	x,
		np.array	y,
		np.array	z,
		str	timespace = None,
		bool	make_copy = True,
		*	args,
		**	kwargs )

Reduce a 2D array to a 1D array using aggregate functions.

The aggregate function is implemented in reduce(). The array of the crushed axis is set to np.array(None).

Parameters

x	Array of measuring point positions.
y	Array of time stamps.
z	Array of strain data in accordance to x and y.
timespace	Setting, how to compact the 2d array. For more, see timespace.
make_copy	Switch, whether a deepcopy of the passed data should be done. Defaults to True.
*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. The resulting shape of the return values depending on timespace is as follows:

"timespace"	x	y	z
"1d_space"	x	np.array(None)	1d array, same size as x
"1d_time"	np.array(None)	y	1d array, same size as y
"2d"	np.array(None)	np.array(None)	np.array(float)

Reimplemented from fosanalysis.preprocessing.base.Base.

Definition at line 90 of file resizing.py.

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setup()

fosanalysis.preprocessing.resizing.Aggregate.setup	(		self,
		str or callable	method,
			module = np )

Set the kernel method for data processing, which can be either a string representing function name in a given namespace module or a custom callable function.

If "method" is a string, retrieve the corresponding function from the specified module. If "method" is a custom callable function, directly set it as the processing method.

Parameters

method

Could be either a callable (function object) or a string representing a function name in the namespace of module.

Parameters

module

A Python module or namespace in which method is looked up when method is not a callable.

Defaults to Numpy (np).

Definition at line 69 of file resizing.py.

Member Data Documentation

kernel

fosanalysis.preprocessing.resizing.Aggregate.kernel = method if callable(method) else getattr(module, method)

Callable function used to aggregate the data.

Use setup to set it.

Definition at line 89 of file resizing.py.

method

fosanalysis.preprocessing.resizing.Aggregate.method = method

Could be either a callable (function object) or a string representing a function name in the namespace of module.

Definition at line 83 of file resizing.py.

module

fosanalysis.preprocessing.resizing.Aggregate.module = module

A Python module or namespace in which method is looked up when method is not a callable.

Defaults to Numpy (np).

Definition at line 86 of file resizing.py.

timespace

fosanalysis.preprocessing.resizing.Aggregate.timespace = timespace

Setting, how to compact the 2d array.

Available options:

• "1d_space": (default): Reduce the temporal component and keep the spatial component by aggregating several readings into a single reading. Results in a 1D array of the same size as x.
• "1d_time": Reduce the spatial component and keep the temporal component by aggregating several time series into a single time series. Results in a 1D array of the same size as y.
• "2d": Compact data into a single value. Both spatial and temporal component are reduced. Results in a 0D array with a single element.

Definition at line 67 of file resizing.py.

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

• src/fosanalysis/preprocessing/resizing.py