StackGenVis: Alignment of Data, Algorithms, and Models for Stacking Ensemble Learning Using Performance Metrics https://doi.org/10.1109/TVCG.2020.3030352
You can not select more than 25 topics Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
 
 
 
 
StackGenVis/frontend/node_modules/ndarray-gradient
Angelos Chatzimparmpas e069030893 fix the frontend 3 years ago
..
example fix the frontend 3 years ago
test fix the frontend 3 years ago
.npmignore fix the frontend 3 years ago
LICENSE fix the frontend 3 years ago
README.md fix the frontend 3 years ago
fdg.js fix the frontend 3 years ago
package.json fix the frontend 3 years ago

README.md

ndarray-gradient

Computes the gradient of an ndarray using a 2-point central finite difference template.

Example

var pack = require('ndarray-pack')
var pool = require('ndarray-scratch')
var grad = require('ndarray-gradient')
var show = require('ndarray-show')

var X = pack([[0, 0, 0],
              [0, 1, 0],
              [0, 0, 0]])

//Compute gradient of X
var dX = grad(pool.zero([3,3,2]), X)

console.log('grad(X) = \n', show(dX))

Output:

grad(X) =
   0.000    0.000    0.000
  -0.500    0.000    0.500
   0.000    0.000    0.000

   0.000   -0.500    0.000
   0.000    0.000    0.000
   0.000    0.500    0.000

Install

npm install ndarray-gradient

API

require('ndarray-gradient')(dst, src[, bc])

Computes the gradient of src storing the result into dst.

  • dst is an array of gradient values. The shape of dst must be the shape of src with one additional dimension for the components of the gradient

  • src is the array to differentiate

  • bc is an array of boundary conditions. The boundary conditions are encoded as string values and must be one of the following values:

    • 'clamp' (Default) clamp boundary edges to boundary
    • 'mirror' mirror values across the boundary
    • 'wrap' wrap values across boundary

Returns dst

Credits

(c) 2014 Mikola Lysenko. MIT License