All files / pcorrdistmat/lib index.js

100% Statements 81/81
100% Branches 1/1
100% Functions 0/0
100% Lines 81/81

Press n or j to go to the next uncovered block, b, p or k for the previous block.

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 821x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x  
/**
* @license Apache-2.0
*
* Copyright (c) 2018 The Stdlib Authors.
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
*    http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
 
'use strict';
 
/**
* Compute a sample Pearson product-moment correlation distance matrix incrementally.
*
* @module @stdlib/stats/incr/pcorrdistmat
*
* @example
* var Float64Array = require( '@stdlib/array/float64' );
* var ndarray = require( '@stdlib/ndarray/ctor' );
* var incrpcorrdistmat = require( '@stdlib/stats/incr/pcorrdistmat' );
*
* // Create an output correlation distance matrix:
* var buffer = new Float64Array( 4 );
* var shape = [ 2, 2 ];
* var strides = [ 2, 1 ];
* var offset = 0;
* var order = 'row-major';
*
* var dist = ndarray( 'float64', buffer, shape, strides, offset, order );
*
* // Create a correlation distance matrix accumulator:
* var accumulator = incrpcorrdistmat( dist );
*
* var out = accumulator();
* // returns null
*
* // Create a data vector:
* buffer = new Float64Array( 2 );
* shape = [ 2 ];
* strides = [ 1 ];
*
* var vec = ndarray( 'float64', buffer, shape, strides, offset, order );
*
* // Provide data to the accumulator:
* vec.set( 0, 2.0 );
* vec.set( 1, 1.0 );
*
* out = accumulator( vec );
* // returns <ndarray>
*
* var bool = ( out === dist );
* // returns true
*
* vec.set( 0, -5.0 );
* vec.set( 1, 3.14 );
*
* out = accumulator( vec );
* // returns <ndarray>
*
* // Retrieve the distance matrix:
* out = accumulator();
* // returns <ndarray>
*/
 
// MODULES //
 
var main = require( './main.js' );
 
 
// EXPORTS //
 
module.exports = main;