A high-performance general-purpose compute library

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Namespaces | Functions
statistics.h File Reference
`#include <af/defines.h>`

Go to the source code of this file.

## Namespaces
namespace | af

## Functions
AFAPI array | mean (const array &in, const dim_t dim=-1)
| C++ Interface for mean.
AFAPI array | mean (const array &in, const array &weights, const dim_t dim=-1)
| C++ Interface for mean of weighted inputs.
AFAPI array | var (const array &in, const bool isbiased=false, const dim_t dim=-1)
| C++ Interface for variance.
AFAPI array | var (const array &in, const af_var_bias bias, const dim_t dim=-1)
| C++ Interface for variance.
AFAPI array | var (const array &in, const array &weights, const dim_t dim=-1)
| C++ Interface for variance of weighted inputs.
AFAPI void | meanvar (array &mean, array &var, const array &in, const array &weights, const af_var_bias bias=AF_VARIANCE_POPULATION, const dim_t dim=-1)
| C++ Interface for mean and variance.
AFAPI array | stdev (const array &in, const dim_t dim=-1)
| C++ Interface for standard deviation.
AFAPI array | stdev (const array &in, const af_var_bias bias, const dim_t dim=-1)
| C++ Interface for standard deviation.
AFAPI array | cov (const array &X, const array &Y, const bool isbiased=false)
| C++ Interface for covariance.
AFAPI array | cov (const array &X, const array &Y, const af_var_bias bias)
| C++ Interface for covariance.
AFAPI array | median (const array &in, const dim_t dim=-1)
| C++ Interface for median.
template<typename T >
AFAPI T | mean (const array &in)
| C++ Interface for mean of all elements.
template<typename T >
AFAPI T | mean (const array &in, const array &weights)
| C++ Interface for mean of all elements in weighted input.
template<typename T >
AFAPI T | var (const array &in, const bool isbiased=false)
| C++ Interface for variance of all elements.
template<typename T >
AFAPI T | var (const array &in, const af_var_bias bias)
| C++ Interface for variance of all elements.
template<typename T >
AFAPI T | var (const array &in, const array &weights)
| C++ Interface for variance of all elements in weighted input.
template<typename T >
AFAPI T | stdev (const array &in)
| C++ Interface for standard deviation of all elements.
template<typename T >
AFAPI T | stdev (const array &in, const af_var_bias bias)
| C++ Interface for standard deviation of all elements.
template<typename T >
AFAPI T | median (const array &in)
| C++ Interface for median of all elements.
template<typename T >
AFAPI T | corrcoef (const array &X, const array &Y)
| C++ Interface for correlation coefficient.
AFAPI void | topk (array &values, array &indices, const array &in, const int k, const int dim=-1, const topkFunction order=AF_TOPK_MAX)
| C++ Interface for finding top k elements along a given dimension.
AFAPI af_err | af_mean (af_array *out, const af_array in, const dim_t dim)
| C Interface for mean.
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.
AFAPI af_err | af_var (af_array *out, const af_array in, const bool isbiased, const dim_t dim)
| C Interface for variance.
AFAPI af_err | af_var_v2 (af_array *out, const af_array in, const af_var_bias bias, const dim_t dim)
| C Interface for variance.
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.
AFAPI af_err | af_meanvar (af_array *mean, af_array *var, const af_array in, const af_array weights, const af_var_bias bias, const dim_t dim)
| C Interface for mean and variance.
AFAPI af_err | af_stdev (af_array *out, const af_array in, const dim_t dim)
| C Interface for standard deviation.
AFAPI af_err | af_stdev_v2 (af_array *out, const af_array in, const af_var_bias bias, const dim_t dim)
| C Interface for standard deviation.
AFAPI af_err | af_cov (af_array *out, const af_array X, const af_array Y, const bool isbiased)
| C Interface for covariance.
AFAPI af_err | af_cov_v2 (af_array *out, const af_array X, const af_array Y, const af_var_bias bias)
| C Interface for covariance.
AFAPI af_err | af_median (af_array *out, const af_array in, const dim_t dim)
| C Interface for median.
AFAPI af_err | af_mean_all (double *real, double *imag, const af_array in)
| C Interface for mean of all elements.
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.
AFAPI af_err | af_var_all (double *realVal, double *imagVal, const af_array in, const bool isbiased)
| C Interface for variance of all elements.
AFAPI af_err | af_var_all_v2 (double *realVal, double *imagVal, const af_array in, const af_var_bias bias)
| C Interface for variance of all elements.
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.
AFAPI af_err | af_stdev_all (double *real, double *imag, const af_array in)
| C Interface for standard deviation of all elements.
AFAPI af_err | af_stdev_all_v2 (double *real, double *imag, const af_array in, const af_var_bias bias)
| C Interface for standard deviation of all elements.
AFAPI af_err | af_median_all (double *realVal, double *imagVal, const af_array in)
| C Interface for median.
AFAPI af_err | af_corrcoef (double *realVal, double *imagVal, const af_array X, const af_array Y)
| C Interface for correlation coefficient.
AFAPI af_err | af_topk (af_array *values, af_array *indices, const af_array in, const int k, const int dim, const af_topk_function order)
| C Interface for finding top k elements along a given dimension.

## Function Documentation

## ◆ af_meanvar()

AFAPI af_err af_meanvar | ( | af_array * | mean,
|  | af_array * | var,
|  | const af_array | in,
|  | const af_array | weights,
|  | const af_var_bias | bias,
|  | const dim_t | dim )

C Interface for mean and variance.

Parameters

  [out] | mean | The mean of the input array along `dim` dimension
  [out] | var | The variance of the input array along the `dim` dimension
  [in] | in | The input array
  [in] | weights | The weights to scale the input array before calculating the mean and varience. If empty, the input is not scaled
  [in] | bias | The type of bias used for variance calculation
  [in] | dim | The dimension along which the variance and mean are calculated. Default is -1 meaning the first non-zero dim