A suite to track Project Diva score statistics and ratings / D4DJ event data.
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.
 
 
 
 
 
 
projectdivar/server/node_modules/pxls/test.js

177 lines
4.6 KiB

'use strict'
var pxls = require('./')
var Ndarray = require('ndarray')
var t = require('tape')
var zeros = require('ndarray-scratch').zeros
var isBrowser = require('is-browser')
t('4-channel array', t => {
t.deepEqual(pxls([0,0,0,1, 1,1,1,1]), [0,0,0,255, 255,255,255,255])
t.deepEqual(pxls([[0,0,0,1], [1,1,1,1]]), [0,0,0,255, 255,255,255,255])
t.deepEqual(pxls([[[0,0,0,1], [1,1,1,1]]]), [0,0,0,255, 255,255,255,255])
t.deepEqual(pxls([[0,0,0,1, 1,1,1,1]]), [0,0,0,255, 255,255,255,255])
t.end()
})
t('3-channel array', t => {
t.deepEqual(pxls([0,0,1, 1,1,1], 3), [0,0,255,255, 255,255,255,255])
t.deepEqual(pxls([[0,0,0,1], [1,1,1,1]]), [0,0,0,255, 255,255,255,255])
t.deepEqual(pxls([[[0,0,0,1], [1,1,1,1]]]), [0,0,0,255, 255,255,255,255])
t.deepEqual(pxls([[0,0,0,1, 1,1,1,1]]), [0,0,0,255, 255,255,255,255])
t.end()
})
t('1-channel array', t => {
t.deepEqual(pxls([0,1], 1), [0,0,0,255, 255,255,255,255])
t.deepEqual(pxls([0,.5], 1), [0,0,0,255, 127,127,127,255])
t.deepEqual(pxls([0,255], 1), [0,0,0,255, 255,255,255,255])
t.end()
})
t('shapes', t => {
t.deepEqual(pxls([0,0,0,1, 1,1,1,1], [1,1]), [0,0,0,255, 255,255,255,255])
t.deepEqual(pxls([0,0,0, 1,1,1, 1,1,0], [3,1]), [0,0,0,255, 255,255,255,255, 255,255,0,255])
t.deepEqual(pxls([0,0,0, 1,1,1, 1,1,0], [1,3]), [0,0,0,255, 255,255,255,255, 255,255,0,255])
t.end()
})
t('4-channel ndarray', t => {
var x = zeros([5, 3])
t.deepEqual(pxls(x), [
0,0,0,255, 0,0,0,255, 0,0,0,255, 0,0,0,255, 0,0,0,255,
0,0,0,255, 0,0,0,255, 0,0,0,255, 0,0,0,255, 0,0,0,255,
0,0,0,255, 0,0,0,255, 0,0,0,255, 0,0,0,255, 0,0,0,255
])
t.end()
})
t('3-channel ndarray', t => {
var x = zeros([3, 5, 3])
t.deepEqual(pxls(x), [
0,0,0,255, 0,0,0,255, 0,0,0,255,
0,0,0,255, 0,0,0,255, 0,0,0,255,
0,0,0,255, 0,0,0,255, 0,0,0,255,
0,0,0,255, 0,0,0,255, 0,0,0,255,
0,0,0,255, 0,0,0,255, 0,0,0,255
])
t.end()
})
t('1-channel ndarray', t => {
var x = zeros([3, 5, 1])
t.deepEqual(pxls(x), [
0,0,0,255, 0,0,0,255, 0,0,0,255,
0,0,0,255, 0,0,0,255, 0,0,0,255,
0,0,0,255, 0,0,0,255, 0,0,0,255,
0,0,0,255, 0,0,0,255, 0,0,0,255,
0,0,0,255, 0,0,0,255, 0,0,0,255
])
t.end()
})
t('ImageData or alike', t => {
var data
if (isBrowser) {
data = document.createElement('canvas').getContext('2d').createImageData(3,5)
}
else {
data = {
data: new Uint8ClampedArray(3 * 5 * 4),
width: 3,
height: 5
}
}
t.deepEqual(pxls(data), [
0,0,0,0, 0,0,0,0, 0,0,0,0,
0,0,0,0, 0,0,0,0, 0,0,0,0,
0,0,0,0, 0,0,0,0, 0,0,0,0,
0,0,0,0, 0,0,0,0, 0,0,0,0,
0,0,0,0, 0,0,0,0, 0,0,0,0
])
t.end()
})
t('DOM containers', t => {
if (!isBrowser) return t.end()
var context = document.createElement('canvas').getContext('2d')
context.canvas.width = 3
context.canvas.height = 5
var fix = [
0,0,0,0, 0,0,0,0, 0,0,0,0,
0,0,0,0, 0,0,0,0, 0,0,0,0,
0,0,0,0, 0,0,0,0, 0,0,0,0,
0,0,0,0, 0,0,0,0, 0,0,0,0,
0,0,0,0, 0,0,0,0, 0,0,0,0
]
context.canvas.toBlob(async function (blob) {
let file = new File([blob], 'x.png')
let bmpromise = createImageBitmap(blob)
let bm = await bmpromise
let canvas = context.canvas
let idata = context.getImageData(0,0,canvas.width,canvas.height)
t.deepEqual(pxls(idata), fix)
t.deepEqual(pxls(idata.data), fix)
t.deepEqual(pxls(canvas), fix)
t.deepEqual(pxls(context), fix)
t.deepEqual(pxls(bm), fix)
let im = new Image()
im.src = canvas.toDataURL()
im.onload = function () {
t.deepEqual(pxls(im), fix)
t.end()
}
})
})
t('playing aroung', t => {
t.deepEqual(pxls([0,0,0,0,1,1,1,1]), [0,0,0,0,255,255,255,255])
t.deepEqual(pxls([0,0,0,0,255,255,255,255]), [0,0,0,0,255,255,255,255])
t.deepEqual(pxls([0,255],1), [0,0,0,255,255,255,255,255])
// bad step
t.deepEqual(pxls([0,0,1,1,0,0,1,1], 2), [0,0,255,255, 0,0,255,255])
t.end()
})
t('readme', t => {
t.deepEqual(pxls([[0,0,0], [1,1,1]]), [0,0,0,255, 255,255,255,255])
t.deepEqual(pxls([0, 1], 1), [0,0,0,255, 255,255,255,255])
t.deepEqual(pxls([0,0,0, 1,1,1], [2,1]), [0,0,0,255, 255,255,255,255])
t.deepEqual(pxls(new Ndarray([0,1], [2,1])), [0,0,0,255, 255,255,255,255])
t.deepEqual(pxls(new Ndarray([0,0,0,1,1,1], [2,1,3])), [0,0,0,255, 255,255,255,255])
t.end()
})
t('arraybuffer, buffer', t => {
var b = new Uint8Array([0,0,0,1,0,0,0,1])
t.deepEqual(b, [0,0,0,1,0,0,0,1])
t.deepEqual(pxls(b.buffer), [0,0,0,1,0,0,0,1])
t.deepEqual(pxls(Buffer.from(b.buffer)), [0,0,0,1,0,0,0,1])
t.end()
})
t('float array', t => {
var arr = new Float32Array([0,0,1,1])
t.deepEqual(pxls(arr), [0,0,255,255])
t.end()
})
t('regl')