Returns an accumulator function which incrementally computes a sample Pearson product-moment correlation distance matrix.
order of the correlation distance matrix or a square 2-dimensional output ndarray for storing the correlation distance matrix
mean values
accumulator function
var Float64Array = require( `@stdlib/array/float64` );
var ndarray = require( `@stdlib/ndarray/ctor` );
// 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 correlation distance matrix:
out = accumulator();
// returns <ndarray>
If provided a data vector, the accumulator function returns an updated sample correlation distance matrix. If not provided a data vector, the accumulator function returns the current sample correlation distance matrix.
data vector
must provide a 1-dimensional ndarray
vector length must match correlation distance matrix dimensions
sample correlation distance matrix or null