verbose.m File Reference

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Functions
function	verbose (in cmat, in dim, in weight, in checked)
	Return a MATLAB double, cell, or table matrix whose rows or columns are unrolled according to a prespecified weight. More...

Function Documentation

verbose()

function verbose	(	in	cmat,
		in	dim,
		in	weight,
		in	checked
	)

Return a MATLAB double, cell, or table matrix whose rows or columns are unrolled according to a prespecified weight.

Parameters

[in]	cmat	: The input compact MATLAB double, cell, or table matrix that is to be unrolled along an axis.
[in]	dim	: The input scalar MATLAB integer that can be either 1 or 2 representing the axis along with the array must be unrolled. An input value of 1 implies unrolling along the rows of the input cmat, that is, unrolling the cmat columns.
[in]	weight	: The input MATLAB matrix of integer values of size size(cmat, dim) containing the set of weights to used for unrolling the input cmat.
[in]	checked	: The input scalar Python Boolean value. If true, the condition ~all(rem(weight, 1) == 0) || any(weight < 0) will be asserted. This can be useful for debugging, but can slow down the runtime performance. (optional, default = false)

Returns

vmat : The output MATLAB matrix of the same type and kind as the input cmat, containing the cmat that is unrolled along the specified axis dim using the input weights.

Possible calling interfaces ⛓

vmat = pm.array.verbose(cmat, dim, weight)
vmat = pm.array.verbose(cmat, dim, weight, checked)

Warning

Negative weights lead to a runtime error.
Any entry corresponding to a zero weight is ignored in the output vmat.

Example usage ⛓

cd(fileparts(mfilename('fullpath'))); % Change working directory to source code directory.
addpath('../../../'); % Add the ParaMonte library root directory to the search path.
 
cmat = randi([0, 9], 3, 5)
pm.array.verbose(cmat, 1, [0, 2, 1])
pm.array.verbose(cmat, 2, [2, 0, 1, 3, 1])

Example output ⛓

cmat =
     8     9     2     9     9
     9     6     5     1     4
     1     0     9     9     8
ans =
     9     6     5     1     4
     9     6     5     1     4
     1     0     9     9     8
ans =
     8     8     2     9     9     9     9
     9     9     5     1     1     1     4
     1     1     9     9     9     9     8

Final Remarks ⛓

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For details on the naming conventions, see this page.
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Copyright

Computational Data Science Lab

Author:

Joshua Alexander Osborne, May 21 2024, 4:24 PM, University of Texas at Arlington
Fatemeh Bagheri, May 20 2024, 1:25 PM, NASA Goddard Space Flight Center (GSFC), Washington, D.C.
Amir Shahmoradi, May 16 2016, 9:03 AM, Oden Institute for Computational Engineering and Sciences (ICES), UT Austin