tatami_stats::sums Namespace Reference

Functions for computing dimension-wise sums. More...

Classes
struct	Options
	Summation options. More...
class	RunningDense
	Running sums from dense data. More...
class	RunningSparse
	Running sums from sparse data. More...

Functions
template<typename Output_ = double, typename Value_ , typename Index_ >
Output_	direct (const Value_ *ptr, Index_ num, bool skip_nan)
template<typename Value_ , typename Index_ , typename Output_ >
void	apply (bool row, const tatami::Matrix< Value_, Index_ > &mat, Output_ *output, const Options &sopt)
template<typename Output_ = double, typename Value_ , typename Index_ >
std::vector< Output_ >	by_column (const tatami::Matrix< Value_, Index_ > &mat, const Options &sopt)
template<typename Output_ = double, typename Value_ , typename Index_ >
std::vector< Output_ >	by_row (const tatami::Matrix< Value_, Index_ > &mat, const Options &sopt)

Detailed Description

Functions for computing dimension-wise sums.

Function Documentation

direct()

template<typename Output_ = double, typename Value_ , typename Index_ >

Output_ tatami_stats::sums::direct	(	const Value_ *	ptr,
		Index_	num,
		bool	skip_nan )

Compute the sum across an objective vector using naive accumulation. This is best used with a sufficiently high-precision Output_, hence the default of double.

Template Parameters

Output_	Type of the output data.
Value_	Type of the input data.
Index_	Type of the row/column index.

Parameters

[in]	ptr	Pointer to an array of length num, containing the values of the objective vector.
	num	Size of the array at ptr. This may be less than the length of the objective vector for sparse data.
	skip_nan	See Options::skip_nan.

Returns

The sum.

apply()

template<typename Value_ , typename Index_ , typename Output_ >

void tatami_stats::sums::apply	(	bool	row,
		const tatami::Matrix< Value_, Index_ > &	mat,
		Output_ *	output,
		const Options &	sopt )

Compute sums for each element of a chosen dimension of a tatami::Matrix. This is done using direct(), RunningDense or RunningSparse, depending on the requested dimension in row and the preferred dimension for access in p. Note that all sums are obtained using naive accumulation, so it is best to use a sufficiently high-precision Output_ to mitigate round-off errors.

Template Parameters

Value_	Type of the matrix value, should be numeric.
Index_	Type of the row/column indices.
Output_	Type of the output value.

Parameters

	row	Whether to compute the sum for each row. If false, the sum is computed for each column instead.
	mat	Instance of a tatami::Matrix.
[out]	output	Pointer to an array of length equal to the number of rows (if row = true) or columns (otherwise). On output, this will contain the row/column variances.
	sopt	Summation options.

by_column()

template<typename Output_ = double, typename Value_ , typename Index_ >

std::vector< Output_ > tatami_stats::sums::by_column	(	const tatami::Matrix< Value_, Index_ > &	mat,
		const Options &	sopt )

Wrapper around apply() for column sums.

Template Parameters

Value_	Type of the matrix value, should be summable.
Index_	Type of the row/column indices.
Output_	Type of the output value.

Parameters

mat	Instance of a tatami::Matrix.
sopt	Summation options.

Returns

Vector containing the sum for each column.

by_row()

template<typename Output_ = double, typename Value_ , typename Index_ >

std::vector< Output_ > tatami_stats::sums::by_row	(	const tatami::Matrix< Value_, Index_ > &	mat,
		const Options &	sopt )

Wrapper around apply() for row sums.

Template Parameters

Output_	Type of the output value.
Value_	Type of the matrix value, should be summable.
Index_	Type of the row/column indices.

Parameters

mat	Instance of a tatami::Matrix.
sopt	Summation options.

Returns

Vector containing the sum of each row.