Functions

AFAPI array mean (const array &in, const dim_t dim=-1)
 C++ Interface for mean. More...
 
AFAPI array mean (const array &in, const array &weights, const dim_t dim=-1)
 C++ Interface for mean of weighted inputs. More...
 
template<typename T >
AFAPImean (const array &in)
 C++ Interface for mean of all elements. More...
 
template<typename T >
AFAPImean (const array &in, const array &weights)
 C++ Interface for mean of all elements in weighted input. More...
 
AFAPI af_err af_mean (af_array *out, const af_array in, const dim_t dim)
 C Interface for mean. More...
 
AFAPI af_err af_mean_weighted (af_array *out, const af_array in, const af_array weights, const dim_t dim)
 C Interface for mean of weighted input array. More...
 
AFAPI af_err af_mean_all (double *real, double *imag, const af_array in)
 C Interface for mean of all elements. More...
 
AFAPI af_err af_mean_all_weighted (double *real, double *imag, const af_array in, const af_array weights)
 C Interface for mean of all elements in weighted input. More...
 

Detailed Description

Find the mean of values in the input

This function performs the operation across all dimensions of the input array.


Function Documentation

◆ af_mean()

AFAPI af_err af_mean ( af_array out,
const af_array  in,
const dim_t  dim 
)

C Interface for mean.

Parameters
[out]outwill contain the mean of the input array along dimension dim
[in]inis the input array
[in]dimthe dimension along which the mean is extracted
Returns
AF_SUCCESS if the operation is successful, otherwise an appropriate error code is returned.

◆ af_mean_all()

AFAPI af_err af_mean_all ( double *  real,
double *  imag,
const af_array  in 
)

C Interface for mean of all elements.

Parameters
[out]realwill contain the real part of mean of the entire input array
[out]imagwill contain the imaginary part of mean of the entire input array
[in]inis the input array
Returns
AF_SUCCESS if the operation is successful, otherwise an appropriate error code is returned.

◆ af_mean_all_weighted()

AFAPI af_err af_mean_all_weighted ( double *  real,
double *  imag,
const af_array  in,
const af_array  weights 
)

C Interface for mean of all elements in weighted input.

Parameters
[out]realwill contain the real part of mean of the entire weighted input array
[out]imagwill contain the imaginary part of mean of the entire weighted input array
[in]inis the input array
[in]weightsis used to scale input in before getting mean
Returns
AF_SUCCESS if the operation is successful, otherwise an appropriate error code is returned.

◆ af_mean_weighted()

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

C Interface for mean of weighted input array.

Parameters
[out]outwill contain the mean of the input array along dimension dim
[in]inis the input array
[in]weightsis used to scale input in before getting mean
[in]dimthe dimension along which the mean is extracted
Returns
AF_SUCCESS if the operation is successful, otherwise an appropriate error code is returned.

◆ mean() [1/4]

AFAPI T af::mean ( const array in)

C++ Interface for mean of all elements.

Parameters
[in]inis the input array
Returns
mean of the entire input array

◆ mean() [2/4]

AFAPI T af::mean ( const array in,
const array weights 
)

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

Parameters
[in]inis the input array
[in]weightsis used to scale input in before getting mean
Returns
mean of the entire weighted input array

◆ mean() [3/4]

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

C++ Interface for mean of weighted inputs.

Parameters
[in]inis the input array
[in]weightsis used to scale input in before getting mean
[in]dimthe dimension along which the mean is extracted
Returns
the mean of the weighted input array along dimension dim
Note
dim is -1 by default. -1 denotes the first non-singleton dimension.

◆ mean() [4/4]

AFAPI array af::mean ( const array in,
const dim_t  dim = -1 
)

C++ Interface for mean.

Parameters
[in]inis the input array
[in]dimthe dimension along which the mean is extracted
Returns
the mean of the input array along dimension dim
Note
dim is -1 by default. -1 denotes the first non-singleton dimension.
Examples
financial/heston_model.cpp, image_processing/adaptive_thresholding.cpp, and machine_learning/naive_bayes.cpp.