pprz_stat.h File Reference

Statistics functions. More...

#include "std.h"

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Functions
int32_t	mean_i (int32_t *array, uint32_t n_elements)
	Compute the mean value of an array This is implemented using floats to handle scaling of all variables.
int32_t	variance_i (int32_t *array, uint32_t n_elements)
	Compute the variance of an array of values (integer).
int32_t	covariance_i (int32_t *array1, int32_t *array2, uint32_t n_elements)
	Compute the covariance of two arrays V(X) = E[(X-E[X])(Y-E[Y])] = E[XY] - E[X]E[Y] where E[X] is the expected value of X This is implemented using floats to handle scaling of all variables.
float	sum_f (float *array, uint32_t n_elements)
	Compute the sum array elements.
float	mean_f (float *arr, uint32_t n_elements)
	Compute the mean value of an array (float)
float	variance_f (float *array, uint32_t n_elements)
	Compute the variance of an array of values (float).
float	covariance_f (float *array1, float *array2, uint32_t n_elements)
	Compute the covariance of two arrays V(X) = E[(X-E[X])(Y-E[Y])] = E[XY] - E[X]E[Y] where E[X] is the expected value of X.

Detailed Description

Statistics functions.

Definition in file pprz_stat.h.

Function Documentation

covariance_f()

float covariance_f ( float *  arr1, float *  arr2, uint32_t  n_elements  )

extern

Compute the covariance of two arrays V(X) = E[(X-E[X])(Y-E[Y])] = E[XY] - E[X]E[Y] where E[X] is the expected value of X.

Parameters

[in]	*array1	The first array
[in]	*array2	The second array
[in]	n_elements	Number of elements in the arrays

Returns

covariance

Definition at line 152 of file pprz_stat.c.

References foo.

Referenced by cloud_sensor_callback(), set_cov_div(), set_cov_div(), set_cov_flow(), and variance_f().

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covariance_i()

int32_t covariance_i ( int32_t *  array1, int32_t *  array2, uint32_t  n_elements  )

extern

Compute the covariance of two arrays V(X) = E[(X-E[X])(Y-E[Y])] = E[XY] - E[X]E[Y] where E[X] is the expected value of X This is implemented using floats to handle scaling of all variables.

Parameters

[in]	*array1	The first array
[in]	*array2	The second array
[in]	n_elements	Number of elements in the arrays

Returns

covariance

Definition at line 78 of file pprz_stat.c.

References foo.

Referenced by variance_i().

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mean_f()

float mean_f ( float *  array, uint32_t  n_elements  )

extern

Compute the mean value of an array (float)

Parameters

[in]	*array	The array
[in]	n_elements	Number of elements in the array

Returns

mean

Definition at line 122 of file pprz_stat.c.

References array, foo, and sum_f().

Referenced by cloud_sensor_callback().

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mean_i()

int32_t mean_i ( int32_t *  array, uint32_t  n_elements  )

extern

Compute the mean value of an array This is implemented using floats to handle scaling of all variables.

Parameters

[in]	*array	The array
[in]	n_elements	Number of elements in the array

Returns

mean

Definition at line 39 of file pprz_stat.c.

References array, and foo.

sum_f()

float sum_f ( float *  array, uint32_t  n_elements  )

extern

Compute the sum array elements.

Parameters

[in]	*array	The first array
[in]	n_elements	Number of elements in the arrays

Returns

array sum

Compute the sum array elements.

Parameters

[in]	*array	The array
[in]	n_elements	Number of elements in the arrays

Returns

array sum

Definition at line 106 of file pprz_stat.c.

References array, and foo.

Referenced by mean_f().

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variance_f()

float variance_f ( float *  array, uint32_t  n_elements  )

extern

Compute the variance of an array of values (float).

The variance is a measure of how far a set of numbers is spread out V(X) = E[(X-E[X])^2] = E[X^2] - E[X]^2 where E[X] is the expected value of X

Parameters

array	Pointer to an array of float
n_elements	Number of values in the array

Returns

variance

Definition at line 139 of file pprz_stat.c.

References array, covariance_f(), and foo.

Referenced by baro_cb(), cloud_sensor_callback(), and cloud_sensor_init().

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variance_i()

int32_t variance_i ( int32_t *  array, uint32_t  n_elements  )

extern

Compute the variance of an array of values (integer).

The variance is a measure of how far a set of numbers is spread out V(X) = E[(X-E[X])^2] = E[X^2] - E[X]^2 where E[X] is the expected value of X This is implemented using floats to handle scaling of all variables

Parameters

array	pointer to an array of integer
n_elements	number of elements in the array

Returns

variance

Definition at line 64 of file pprz_stat.c.

References array, covariance_i(), and foo.

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