var

Find the variance of values in the input. More...

Functions
AFAPI array	var (const array &in, const bool isbiased=false, const dim_t dim=-1)
	C++ Interface for variance. More...
AFAPI array	var (const array &in, const array &weights, const dim_t dim=-1)
	C++ Interface for variance of weighted inputs. More...
template<typename T >
AFAPI T	var (const array &in, const bool isbiased=false)
	C++ Interface for variance of all elements. More...
template<typename T >
AFAPI T	var (const array &in, const array &weights)
	C++ Interface for variance of all elements in weighted input. More...
AFAPI af_err	af_var (af_array *out, const af_array in, const bool isbiased, const dim_t dim)
	C Interface for variance. More...
AFAPI af_err	af_var_weighted (af_array *out, const af_array in, const af_array weights, const dim_t dim)
	C Interface for variance of weighted input array. More...
AFAPI af_err	af_var_all (double *realVal, double *imagVal, const af_array in, const bool isbiased)
	C Interface for variance of all elements. More...
AFAPI af_err	af_var_all_weighted (double *realVal, double *imagVal, const af_array in, const af_array weights)
	C Interface for variance of all elements in weighted input. More...

Detailed Description

Find the variance of values in the input.

This function performs the operation across all batches present in the input simultaneously.

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Function Documentation

AFAPI af_err af_var	(	af_array *	out,
		const af_array	in,
		const bool	isbiased,
		const dim_t	dim
	)

C Interface for variance.

Parameters

[out]	out	will contain the variance of the input array along dimension dim
[in]	in	is the input array
[in]	isbiased	is boolean denoting Population variance (false) or Sample Variance (true)
[in]	dim	the dimension along which the variance is extracted

Returns

AF_SUCCESS if the operation is successful, otherwise an appropriate error code is returned.

AFAPI af_err af_var_all	(	double *	realVal,
		double *	imagVal,
		const af_array	in,
		const bool	isbiased
	)

C Interface for variance of all elements.

Parameters

[out]	realVal	will contain the real part of variance of the entire input array
[out]	imagVal	will contain the imaginary part of variance of the entire input array
[in]	in	is the input array
[in]	isbiased	is boolean denoting Population variance (false) or Sample Variance (true)

Returns

AF_SUCCESS if the operation is successful, otherwise an appropriate error code is returned.

AFAPI af_err af_var_all_weighted	(	double *	realVal,
		double *	imagVal,
		const af_array	in,
		const af_array	weights
	)

C Interface for variance of all elements in weighted input.

Parameters

[out]	realVal	will contain the real part of variance of the entire weighted input array
[out]	imagVal	will contain the imaginary part of variance of the entire weighted input array
[in]	in	is the input array
[in]	weights	is used to scale input in before getting variance

Returns

AF_SUCCESS if the operation is successful, otherwise an appropriate error code is returned.

AFAPI af_err af_var_weighted	(	af_array *	out,
		const af_array	in,
		const af_array	weights,
		const dim_t	dim
	)

C Interface for variance of weighted input array.

Parameters

[out]	out	will contain the variance of the input array along dimension dim
[in]	in	is the input array
[in]	weights	is used to scale input in before getting variance
[in]	dim	the dimension along which the variance is extracted

Returns

AF_SUCCESS if the operation is successful, otherwise an appropriate error code is returned.

AFAPI array af::var	(	const array &	in,
		const bool	isbiased = false,
		const dim_t	dim = -1
	)

C++ Interface for variance.

Parameters

[in]	in	is the input array
[in]	isbiased	is boolean denoting Population variance (false) or Sample Variance (true)
[in]	dim	the dimension along which the variance is extracted

Returns

the variance of the input array along dimension dim

Note

dim is -1 by default. -1 denotes the first non-singleton dimension.

Examples:

machine_learning/naive_bayes.cpp.

AFAPI array af::var	(	const array &	in,
		const array &	weights,
		const dim_t	dim = -1
	)

C++ Interface for variance of weighted inputs.

Parameters

[in]	in	is the input array
[in]	weights	is used to scale input in before getting variance
[in]	dim	the dimension along which the variance is extracted

Returns

the variance of the weighted input array along dimension dim

Note

dim is -1 by default. -1 denotes the first non-singleton dimension.

AFAPI T af::var	(	const array &	in,
		const bool	isbiased = false
	)

C++ Interface for variance of all elements.

Parameters

[in]	in	is the input array
[in]	isbiased	is boolean denoting Population variance (false) or Sample Variance (true)

Returns

variance of the entire input array

AFAPI T af::var	(	const array &	in,
		const array &	weights
	)

C++ Interface for variance of all elements in weighted input.

Parameters

[in]	in	is the input array
[in]	weights	is used to scale input in before getting variance

Returns

variance of the entire input array