@d4c/numjs
Version:
Like NumPy, in TypeScript and JavaScript
1,137 lines • 88.2 kB
JavaScript
"use strict";
import cwise from "cwise";
import ops from "ndarray-ops";
import ndFFT from "ndarray-fft";
import gemm from "ndarray-gemm";
import ndPool from "typedarray-pool";
import ndarray from "ndarray";
import util from "util";
import CONF from "./config";
import * as errors from "./errors";
import _ from "./utils";
/**
* Multidimensional, homogeneous array of fixed-size items
*
* The number of dimensions and items in an array is defined by its shape, which is a tuple of N positive
* integers that specify the sizes of each dimension. The type of items in the array is specified by a separate
* data-type object (dtype), one of which is associated with each NdArray.
*/
export class NdArray {
constructor(...args) {
if (args.length === 1) {
this.selection = args[0];
}
else if (args.length === 0) {
throw new errors.ValueError("Required argument 'data' not found");
}
else {
this.selection = ndarray.apply(null, args);
}
}
/**
* @property NdArray#size - Number of elements in the array.
*/
get size() {
return this.selection.size;
}
/**
* The shape of the array
*
* @name NdArray#shape
* @readonly
*/
get shape() {
return this.selection.shape;
}
/**
* Number of array dimensions.
*
* @name NdArray#ndim
* @readonly
*/
get ndim() {
return this.selection.shape.length;
}
/**
* Data-type of the array’s elements.
*/
get dtype() {
return this.selection.dtype;
}
set dtype(dtype) {
const T = _.getType(dtype);
if (T !== _.getType(this.dtype)) {
this.selection = ndarray(new T(this.selection.data), this.selection.shape, this.selection.stride, this.selection.offset);
}
}
/**
* Permute the dimensions of the array.
*
* @name NdArray#T
* @readonly
*/
get T() {
return this.transpose();
}
get(...args) {
const n = args.length;
for (let i = 0; i < n; i++) {
if (args[i] < 0) {
args[i] += this.shape[i];
}
}
return this.selection.get.apply(this.selection, args);
}
set(...args) {
return this.selection.set.apply(this.selection, args);
}
slice(...args) {
const d = this.ndim;
const hi = new Array(d);
const lo = new Array(d);
const step = new Array(d);
const tShape = this.shape;
for (let i = 0; i < d; i++) {
let arg = args[i];
if (typeof arg === "undefined") {
break;
}
if (arg === null) {
continue;
}
if (_.isNumber(arg)) {
lo[i] = arg < 0 ? arg + tShape[i] : arg;
hi[i] = null;
step[i] = 1;
}
else if (arg.length === 4 &&
arg[1] === null &&
arg[2] === null) {
// pattern: a[start::step]
const s = arg[0] < 0 ? arg[0] + tShape[i] : arg[0];
lo[i] = s;
hi[i] = null;
step[i] = arg[3] || 1;
}
else {
// pattern start:end:step
const start = arg[0] < 0 ? arg[0] + tShape[i] : arg[0];
const end = arg[1] < 0 ? arg[1] + tShape[i] : arg[1];
lo[i] = end ? start : 0;
hi[i] = end ? end - start : start;
step[i] = arg[2] || 1;
}
}
const slo = this.selection.lo.apply(this.selection, lo);
const shi = slo.hi.apply(slo, hi);
const sstep = shi.step.apply(shi, step);
return new NdArray(sstep);
}
/**
* Return a subarray by fixing a particular axis
* @param axis a array whose element could be `null` or `number`
*
* @example
* ```typescript
* arr = nj.arange(4*4).reshape(4,4)
* // array([[ 0, 1, 2, 3],
* // [ 4, 5, 6, 7],
* // [ 8, 9, 10, 11],
* // [ 12, 13, 14, 15]])
*
* arr.pick(1)
* // array([ 4, 5, 6, 7])
*
* arr.pick(null, 1)
* // array([ 1, 5, 9, 13])
* ```
**/
pick(...axis) {
return new NdArray(this.selection.pick.apply(this.selection, arguments));
}
/**
* Return a shifted view of the array. Think of it as taking the upper left corner of the image and dragging it inward
*
* @example
* ```typescript
* arr = nj.arange(4*4).reshape(4,4)
* // array([[ 0, 1, 2, 3],
* // [ 4, 5, 6, 7],
* // [ 8, 9, 10, 11],
* // [ 12, 13, 14, 15]])
* arr.lo(1,1)
* // array([[ 5, 6, 7],
* // [ 9, 10, 11],
* // [ 13, 14, 15]])
* ```
**/
lo(...args) {
return new NdArray(this.selection.lo.apply(this.selection, args));
}
/**
* Return a sliced view of the array.
*
* @example
* ```typescript
* arr = nj.arange(4*4).reshape(4,4)
* // array([[ 0, 1, 2, 3],
* // [ 4, 5, 6, 7],
* // [ 8, 9, 10, 11],
* // [ 12, 13, 14, 15]])
*
* arr.hi(3,3)
* // array([[ 0, 1, 2],
* // [ 4, 5, 6],
* // [ 8, 9, 10]])
*
* arr.lo(1,1).hi(2,2)
* // array([[ 5, 6],
* // [ 9, 10]])
* ```
*/
hi(...args) {
return new NdArray(this.selection.hi.apply(this.selection, args));
}
step(...args) {
return new NdArray(this.selection.step.apply(this.selection, args));
}
/**
* Return a copy of the array collapsed into one dimension using row-major order (C-style)
*/
flatten() {
if (this.ndim === 1) {
// already flattened
return new NdArray(this.selection);
}
const T = _.getType(this.dtype);
let arr = _.flatten(this.tolist(), true);
if (!(arr instanceof T)) {
arr = new T(arr);
}
return new NdArray(arr, [this.size]);
}
reshape(...args) {
if (arguments.length === 0) {
throw new errors.ValueError("function takes at least one argument (0 given)");
}
let shape;
if (arguments.length === 1 &&
_.isNumber(arguments[0]) &&
arguments[0] === -1) {
shape = [_.shapeSize(this.shape)];
}
if (arguments.length === 1) {
if (_.isNumber(arguments[0])) {
shape = [arguments[0]];
}
else {
// grimmer refactor note: original logic does not check if it is an array
shape = arguments[0];
}
}
if (arguments.length > 1) {
shape = [].slice.call(arguments);
}
if (shape.filter(function (s) {
return s === -1;
}).length > 1) {
throw new errors.ValueError("can only specify one unknown dimension");
}
const currentShapeSize = _.shapeSize(shape);
shape = shape.map(function (s) {
return s === -1 ? (-1 * this.size) / currentShapeSize : s;
}.bind(this));
if (this.size !== _.shapeSize(shape)) {
throw new errors.ValueError("total size of new array must be unchanged");
}
const selfShape = this.selection.shape;
const selfOffset = this.selection.offset;
const selfStride = this.selection.stride;
const selfDim = selfShape.length;
const d = shape.length;
let stride;
let offset;
let i;
let sz;
if (selfDim === d) {
let sameShapes = true;
for (i = 0; i < d; ++i) {
if (selfShape[i] !== shape[i]) {
sameShapes = false;
break;
}
}
if (sameShapes) {
return new NdArray(this.selection.data, selfShape, selfStride, selfOffset);
}
}
else if (selfDim === 1) {
// 1d view
stride = new Array(d);
for (i = d - 1, sz = 1; i >= 0; --i) {
stride[i] = sz;
sz *= shape[i];
}
offset = selfOffset;
for (i = 0; i < d; ++i) {
if (stride[i] < 0) {
offset -= (shape[i] - 1) * stride[i];
}
}
return new NdArray(this.selection.data, shape, stride, offset);
}
const minDim = Math.min(selfDim, d);
let areCompatible = true;
for (i = 0; i < minDim; i++) {
if (selfShape[i] !== shape[i]) {
areCompatible = false;
break;
}
}
if (areCompatible) {
stride = new Array(d);
for (i = 0; i < d; i++) {
stride[i] = selfStride[i] || 1;
}
offset = selfOffset;
return new NdArray(this.selection.data, shape, stride, offset);
}
return this.flatten().reshape(shape);
}
transpose(...args) {
let axes;
if (args.length === 0) {
const d = this.ndim;
axes = new Array(d);
for (let i = 0; i < d; i++) {
axes[i] = d - i - 1;
}
}
else if (args.length > 1) {
axes = args;
}
else {
axes = args[0];
}
return new NdArray(this.selection.transpose.apply(this.selection, axes));
}
/**
* Dot product of two arrays.
*/
dot(x) {
x = x instanceof NdArray ? x : createArray(x, this.dtype);
const tShape = this.shape;
const xShape = x.shape;
if (tShape.length === 2 && xShape.length === 2 && tShape[1] === xShape[0]) {
// matrix/matrix
const T = _.getType(this.dtype);
const c = new NdArray(new T(tShape[0] * xShape[1]), [
tShape[0],
xShape[1],
]);
gemm(c.selection, this.selection, x.selection);
return c;
}
else if (tShape.length === 1 &&
xShape.length === 2 &&
tShape[0] === xShape[0]) {
// vector/matrix
return this.reshape([tShape[0], 1]).T.dot(x).reshape(xShape[1]);
}
else if (tShape.length === 2 &&
xShape.length === 1 &&
tShape[1] === xShape[0]) {
// matrix/vector
return this.dot(x.reshape([xShape[0], 1])).reshape(tShape[0]);
}
else if (tShape.length === 1 &&
xShape.length === 1 &&
tShape[0] === xShape[0]) {
// vector/vector
return this.reshape([tShape[0], 1])
.T.dot(x.reshape([xShape[0], 1]))
.reshape([1]);
}
else {
throw new errors.ValueError("cannot compute the matrix product of given arrays");
}
}
/**
* Assign `x` to the array, element-wise.
*/
assign(x, copy = true) {
if (arguments.length === 1) {
copy = true;
}
const arr = copy ? this.clone() : this;
if (_.isNumber(x)) {
ops.assigns(arr.selection, x);
return arr;
}
x = createArray(x, this.dtype);
ops.assign(arr.selection, x.selection);
return arr;
}
/**
* Add `x` to the array, element-wise.
*/
add(x, copy = true) {
if (arguments.length === 1) {
copy = true;
}
const arr = copy ? this.clone() : this;
if (_.isNumber(x)) {
ops.addseq(arr.selection, x);
return arr;
}
x = createArray(x, this.dtype);
ops.addeq(arr.selection, x.selection);
return arr;
}
/**
* Subtract `x` to the array, element-wise.
*/
subtract(x, copy = true) {
if (arguments.length === 1) {
copy = true;
}
const arr = copy ? this.clone() : this;
if (_.isNumber(x)) {
ops.subseq(arr.selection, x);
return arr;
}
x = createArray(x, this.dtype);
ops.subeq(arr.selection, x.selection);
return arr;
}
/**
* Multiply array by `x`, element-wise.
*/
multiply(x, copy = true) {
if (arguments.length === 1) {
copy = true;
}
const arr = copy ? this.clone() : this;
if (_.isNumber(x)) {
ops.mulseq(arr.selection, x);
return arr;
}
x = createArray(x, this.dtype);
ops.muleq(arr.selection, x.selection);
return arr;
}
/**
* Divide array by `x`, element-wise.
*/
divide(x, copy = true) {
if (arguments.length === 1) {
copy = true;
}
const arr = copy ? this.clone() : this;
if (_.isNumber(x)) {
ops.divseq(arr.selection, x);
return arr;
}
x = createArray(x, this.dtype);
ops.diveq(arr.selection, x.selection);
return arr;
}
/**
* Raise array elements to powers from given array, element-wise.
*
* @param x
* @param copy - set to false to modify the array rather than create a new one
*/
pow(x, copy = true) {
if (arguments.length === 1) {
copy = true;
}
const arr = copy ? this.clone() : this;
if (_.isNumber(x)) {
ops.powseq(arr.selection, x);
return arr;
}
x = createArray(x, this.dtype);
ops.poweq(arr.selection, x.selection);
return arr;
}
/**
* Calculate the exponential of all elements in the array, element-wise.
*
* @param copy - set to false to modify the array rather than create a new one
*/
exp(copy = true) {
if (arguments.length === 0) {
copy = true;
}
const arr = copy ? this.clone() : this;
ops.expeq(arr.selection);
return arr;
}
/**
* Calculate the natural logarithm of all elements in the array, element-wise.
*
* @param copy - set to false to modify the array rather than create a new one
*/
log(copy = true) {
if (arguments.length === 0) {
copy = true;
}
const arr = copy ? this.clone() : this;
ops.logeq(arr.selection);
return arr;
}
/**
* Calculate the positive square-root of all elements in the array, element-wise.
*
* @param copy set to false to modify the array rather than create a new one
*/
sqrt(copy = true) {
if (arguments.length === 0) {
copy = true;
}
const arr = copy ? this.clone() : this;
ops.sqrteq(arr.selection);
return arr;
}
/**
* Return the maximum value of the array
*/
max() {
if (this.selection.size === 0) {
return null;
}
return ops.sup(this.selection);
}
/**
* Return the minimum value of the array
*/
min() {
if (this.selection.size === 0) {
return null;
}
return ops.inf(this.selection);
}
/**
* Sum of array elements.
*/
sum() {
return ops.sum(this.selection);
}
/**
* Returns the standard deviation, a measure of the spread of a distribution, of the array elements.
*
* @param {object} options default {ddof:0}
*/
std(options) {
if (!(options === null || options === void 0 ? void 0 : options.ddof)) {
options = { ddof: 0 };
}
const squares = this.clone();
ops.powseq(squares.selection, 2);
const mean = this.mean();
const shapeSize = _.shapeSize(this.shape);
const letiance = ops.sum(squares.selection) / (shapeSize - options.ddof) -
(mean * mean * shapeSize) / (shapeSize - options.ddof);
return letiance > 0 ? Math.sqrt(Math.abs(letiance)) : 0;
}
/**
* Return the arithmetic mean of array elements.
*/
mean() {
return ops.sum(this.selection) / _.shapeSize(this.shape);
}
/**
* Return element-wise remainder of division.
*/
mod(x, copy = true) {
if (arguments.length === 1) {
copy = true;
}
const arr = copy ? this.clone() : this;
if (_.isNumber(x)) {
ops.modseq(arr.selection, x);
return arr;
}
x = createArray(x, this.dtype);
ops.modeq(arr.selection, x.selection);
return arr;
}
/**
* Converts {NdArray} to a native JavaScript {Array}
*/
tolist() {
return unpackArray(this.selection);
}
valueOf() {
return this.tolist();
}
/**
* Stringify the array to make it readable in the console, by a human.
*/
[util.inspect.custom]() {
return this.toString();
}
/**
* Stringify the array to make it readable by a human.
*/
toString() {
const nChars = formatNumber(this.max()).length;
const reg1 = /\]\,(\s*)\[/g;
const spacer1 = "],\n$1 [";
const reg3 = /\]\,(\s+)...\,(\s+)\[/g;
const spacer3 = "],\n$2 ...\n$2 [";
const reg2 = /\[\s+\[/g;
const spacer2 = "[[";
function formatArray(k, v) {
if (_.isString(v)) {
return v;
}
if (_.isNumber(v)) {
const s = formatNumber(v);
return new Array(Math.max(0, nChars - s.length + 2)).join(" ") + s;
}
k = k || 0;
let arr;
const th = CONF.printThreshold;
const hth = (th / 2) | 0;
if (v.length > th) {
arr = [].concat(v.slice(0, hth), [" ..."], v.slice(v.length - hth));
}
else {
arr = v;
}
return (new Array(k + 1).join(" ") +
"[" +
arr
.map(function (i, ii) {
return formatArray(ii === 0 && k === 0 ? 1 : k + 1, i);
})
.join(",") +
"]");
}
let base = JSON.stringify(this.tolist(), formatArray)
.replace(reg1, spacer1)
.replace(reg2, spacer2)
.replace(reg2, spacer2)
.replace(reg3, spacer3)
.slice(2, -1);
switch (this.dtype) {
case "array":
return "array([" + base + ")";
default:
return "array([" + base + ", dtype=" + this.dtype + ")";
}
}
/**
* Stringify object to JSON
*/
toJSON() {
return JSON.stringify(this.tolist());
}
/**
* Create a full copy of the array
*/
clone() {
const s = this.selection;
if (typeof s.data.slice === "undefined") {
return new NdArray(ndarray([].slice.apply(s.data), s.shape, s.stride, s.offset)); // for legacy browsers
}
return new NdArray(ndarray(s.data.slice(), s.shape, s.stride, s.offset));
}
/**
* Return true if two arrays have the same shape and elements, false otherwise.
*/
equal(array) {
array = createArray(array);
if (this.size !== array.size || this.ndim !== array.ndim) {
return false;
}
const d = this.ndim;
for (let i = 0; i < d; i++) {
if (this.shape[i] !== array.shape[i]) {
return false;
}
}
return ops.equals(this.selection, array.selection);
}
/**
* Round array to the to the nearest integer.
*/
round(copy = true) {
if (arguments.length === 0) {
copy = true;
}
const arr = copy ? this.clone() : this;
ops.roundeq(arr.selection);
return arr;
}
/**
* Return the inverse of the array, element-wise.
*/
negative() {
const c = this.clone();
ops.neg(c.selection, this.selection);
return c;
}
diag() {
const d = this.ndim;
if (d === 1) {
// input is a vector => return a diagonal matrix
const T = _.getType(this.dtype);
const shape = [this.shape[0], this.shape[0]];
const arr = new NdArray(new T(_.shapeSize(shape)), shape);
if (arr.dtype === "array") {
ops.assigns(arr.selection, 0);
}
for (let i = 0; i < this.shape[0]; i++)
arr.set(i, i, this.get(i));
return arr;
}
const mshape = this.shape;
const mstride = this.selection.stride;
let nshape = 1 << 30;
let nstride = 0;
for (let i = 0; i < d; ++i) {
nshape = Math.min(nshape, mshape[i]) | 0;
nstride += mstride[i];
}
return new NdArray(this.selection.data, [nshape], [nstride], this.selection.offset);
}
iteraxis(axis, cb) {
const shape = this.shape;
if (axis === -1) {
axis = shape.length - 1;
}
if (axis < 0 || axis > shape.length - 1) {
throw new errors.ValueError("invalid axis");
}
for (let i = 0; i < shape[axis]; i++) {
const loc = new Array(axis + 1);
for (let ii = 0; ii < axis + 1; ii++) {
loc[ii] = ii === axis ? i : null;
}
const subArr = this.selection.pick.apply(this.selection, loc);
const xi = createArray(unpackArray(subArr), this.dtype);
cb(xi, i);
}
}
/**
* Returns the discrete, linear convolution of the array using the given filter.
*
* @note: Arrays must have the same dimensions and `filter` must be smaller than the array.
* @note: The convolution product is only given for points where the signals overlap completely. Values outside the signal boundary have no effect. This behaviour is known as the 'valid' mode.
* @note: Use optimized code for 3x3, 3x3x1, 5x5, 5x5x1 filters, FFT otherwise.
*/
convolve(filter) {
filter = NdArray.new(filter);
const ndim = this.ndim;
if (ndim !== filter.ndim) {
throw new errors.ValueError("arrays must have the same dimensions");
}
const outShape = new Array(ndim);
const step = new Array(ndim);
const ts = this.selection;
const tShape = this.shape;
const fs = filter.selection;
const fShape = filter.shape;
for (let i = 0; i < ndim; i++) {
const l = tShape[i] - fShape[i] + 1;
if (l < 0) {
throw new errors.ValueError("filter cannot be greater than the array");
}
outShape[i] = l;
step[i] = -1;
}
if (ndim === 2 && fShape[0] === 3 && fShape[1] === 3) {
const out3x3 = new NdArray(new Float32Array(_.shapeSize(tShape)), tShape);
doConvolve3x3(out3x3.selection, // c
ts, // x
fs.get(0, 0), // fa
fs.get(0, 1), // fb
fs.get(0, 2), // fc
fs.get(1, 0), // fd
fs.get(1, 1), // fe
fs.get(1, 2), // ff
fs.get(2, 0), // fg
fs.get(2, 1), // fh
fs.get(2, 2) // fi
);
return out3x3.lo(1, 1).hi(outShape[0], outShape[1]);
}
else if (ndim === 3 &&
fShape[2] === 1 &&
tShape[2] === 1 &&
fShape[0] === 3 &&
fShape[1] === 3) {
const out3x3x1 = new NdArray(new Float32Array(_.shapeSize(tShape)), tShape);
doConvolve3x3(out3x3x1.selection.pick(null, null, 0), // c
ts.pick(null, null, 0), // x
fs.get(0, 0, 0), // fa
fs.get(0, 1, 0), // fb
fs.get(0, 2, 0), // fc
fs.get(1, 0, 0), // fd
fs.get(1, 1, 0), // fe
fs.get(1, 2, 0), // ff
fs.get(2, 0, 0), // fg
fs.get(2, 1, 0), // fh
fs.get(2, 2, 0) // fi
);
return out3x3x1.lo(1, 1).hi(outShape[0], outShape[1]);
}
else if (ndim === 2 && fShape[0] === 5 && fShape[1] === 5) {
const out5x5 = new NdArray(new Float32Array(_.shapeSize(tShape)), tShape);
doConvolve5x5(out5x5.selection, // c
ts, // x
fs.get(0, 0), // fa
fs.get(0, 1), // fb
fs.get(0, 2), // fc
fs.get(0, 3), // fd
fs.get(0, 4), // fe
fs.get(1, 0), // ff
fs.get(1, 1), // fg
fs.get(1, 2), // fh
fs.get(1, 3), // fi
fs.get(1, 4), // fj
fs.get(2, 0), // fk
fs.get(2, 1), // fl
fs.get(2, 2), // fm
fs.get(2, 3), // fn
fs.get(2, 4), // fo
fs.get(3, 0), // fp
fs.get(3, 1), // fq
fs.get(3, 2), // fr
fs.get(3, 3), // fs
fs.get(3, 4), // ft
fs.get(4, 0), // fu
fs.get(4, 1), // fv
fs.get(4, 2), // fw
fs.get(4, 3), // fx
fs.get(4, 4) // fy
);
return out5x5.lo(2, 2).hi(outShape[0], outShape[1]);
}
else if (ndim === 3 &&
fShape[2] === 1 &&
tShape[2] === 1 &&
fShape[0] === 5 &&
fShape[1] === 5) {
const out5x5x1 = new NdArray(new Float32Array(_.shapeSize(tShape)), tShape);
doConvolve5x5(out5x5x1.selection, // c
ts, // x
fs.get(0, 0, 0), // fa
fs.get(0, 1, 0), // fb
fs.get(0, 2, 0), // fc
fs.get(0, 3, 0), // fd
fs.get(0, 4, 0), // fe
fs.get(1, 0, 0), // ff
fs.get(1, 1, 0), // fg
fs.get(1, 2, 0), // fh
fs.get(1, 3, 0), // fi
fs.get(1, 4, 0), // fj
fs.get(2, 0, 0), // fk
fs.get(2, 1, 0), // fl
fs.get(2, 2, 0), // fm
fs.get(2, 3, 0), // fn
fs.get(2, 4, 0), // fo
fs.get(3, 0, 0), // fp
fs.get(3, 1, 0), // fq
fs.get(3, 2, 0), // fr
fs.get(3, 3, 0), // fs
fs.get(3, 4, 0), // ft
fs.get(4, 0, 0), // fu
fs.get(4, 1, 0), // fv
fs.get(4, 2, 0), // fw
fs.get(4, 3, 0), // fx
fs.get(4, 4, 0) // fy
);
return out5x5x1.lo(2, 2).hi(outShape[0], outShape[1]);
}
else {
return this.fftconvolve(filter);
}
}
fftconvolve(filter) {
filter = NdArray.new(filter);
if (this.ndim !== filter.ndim) {
throw new errors.ValueError("arrays must have the same dimensions");
}
const as = this.selection;
const bs = filter.selection;
const d = this.ndim;
let nsize = 1;
const nstride = new Array(d);
const nshape = new Array(d);
const oshape = new Array(d);
let i;
for (i = d - 1; i >= 0; --i) {
nshape[i] = as.shape[i];
nstride[i] = nsize;
nsize *= nshape[i];
oshape[i] = as.shape[i] - bs.shape[i] + 1;
}
const T = _.getType(as.dtype);
const out = new NdArray(new T(_.shapeSize(oshape)), oshape);
const outs = out.selection;
const xT = ndPool.mallocDouble(nsize);
const x = ndarray(xT, nshape, nstride, 0);
ops.assigns(x, 0);
ops.assign(x.hi.apply(x, as.shape), as);
const yT = ndPool.mallocDouble(nsize);
const y = ndarray(yT, nshape, nstride, 0);
ops.assigns(y, 0);
// FFT x/y
ndFFT(1, x, y);
const uT = ndPool.mallocDouble(nsize);
const u = ndarray(uT, nshape, nstride, 0);
ops.assigns(u, 0);
ops.assign(u.hi.apply(u, bs.shape), bs);
const vT = ndPool.mallocDouble(nsize);
const v = ndarray(vT, nshape, nstride, 0);
ops.assigns(v, 0);
ndFFT(1, u, v);
doConjMuleq(x, y, u, v);
ndFFT(-1, x, y);
const outShape = new Array(d);
const outOffset = new Array(d);
let needZeroFill = false;
for (i = 0; i < d; ++i) {
if (outs.shape[i] > nshape[i]) {
needZeroFill = true;
}
outOffset[i] = bs.shape[i] - 1;
outShape[i] = Math.min(outs.shape[i], nshape[i] - outOffset[i]);
}
let croppedX;
if (needZeroFill) {
ops.assign(outs, 0.0);
}
croppedX = x.lo.apply(x, outOffset);
croppedX = croppedX.hi.apply(croppedX, outShape);
ops.assign(outs.hi.apply(outs, outShape), croppedX);
ndPool.freeDouble(xT);
ndPool.freeDouble(yT);
ndPool.freeDouble(uT);
ndPool.freeDouble(vT);
return out;
}
static new(arr, dtype) {
return createArray(arr, dtype);
}
}
/* istanbul ignore next */
const doConjMuleq = cwise({
args: ["array", "array", "array", "array"],
body: function (xi, yi, ui, vi) {
const a = ui;
const b = vi;
const c = xi;
const d = yi;
const k1 = c * (a + b);
xi = k1 - b * (c + d);
yi = k1 + a * (d - c);
},
});
/* istanbul ignore next */
const doConvolve3x3 = cwise({
args: [
"array",
"array",
"scalar",
"scalar",
"scalar",
"scalar",
"scalar",
"scalar",
"scalar",
"scalar",
"scalar",
{ offset: [-1, -1], array: 1 },
{ offset: [-1, 0], array: 1 },
{ offset: [-1, 1], array: 1 },
{ offset: [0, -1], array: 1 },
// {offset:[ 9, 0], array:1}, // useless since available already
{ offset: [0, 1], array: 1 },
{ offset: [1, -1], array: 1 },
{ offset: [1, 0], array: 1 },
{ offset: [1, 1], array: 1 }, // xi
],
body: function (c, xe, fa, fb, fc, fd, fe, ff, fg, fh, fi, xa, xb, xc, xd, xf, xg, xh, xi) {
c =
xa * fi +
xb * fh +
xc * fg +
xd * ff +
xe * fe +
xf * fd +
xg * fc +
xh * fb +
xi * fa;
},
});
/* istanbul ignore next */
const doConvolve5x5 = cwise({
args: [
"index",
"array",
"array",
"scalar",
"scalar",
"scalar",
"scalar",
"scalar",
"scalar",
"scalar",
"scalar",
"scalar",
"scalar",
"scalar",
"scalar",
"scalar",
"scalar",
"scalar",
"scalar",
"scalar",
"scalar",
"scalar",
"scalar",
"scalar",
"scalar",
"scalar",
"scalar",
"scalar",
{ offset: [-2, -2], array: 1 },
{ offset: [-2, -1], array: 1 },
{ offset: [-2, 0], array: 1 },
{ offset: [-2, 1], array: 1 },
{ offset: [-2, 2], array: 1 },
{ offset: [-1, -2], array: 1 },
{ offset: [-1, -1], array: 1 },
{ offset: [-1, 0], array: 1 },
{ offset: [-1, 1], array: 1 },
{ offset: [-1, 2], array: 1 },
{ offset: [0, -2], array: 1 },
{ offset: [0, -1], array: 1 },
// {offset:[ 0, 0], array:1},
{ offset: [0, 1], array: 1 },
{ offset: [0, 2], array: 1 },
{ offset: [1, -2], array: 1 },
{ offset: [1, -1], array: 1 },
{ offset: [1, 0], array: 1 },
{ offset: [1, 1], array: 1 },
{ offset: [1, 2], array: 1 },
{ offset: [2, -2], array: 1 },
{ offset: [2, -1], array: 1 },
{ offset: [2, 0], array: 1 },
{ offset: [2, 1], array: 1 },
{ offset: [2, 2], array: 1 }, // xy
],
body: function (index, c, xm, fa, fb, fc, fd, fe, ff, fg, fh, fi, fj, fk, fl, fm, fn, fo, fp, fq, fr, fs, ft, fu, fv, fw, fx, fy, xa, xb, xc, xd, xe, xf, xg, xh, xi, xj, xk, xl, xn, xo, xp, xq, xr, xs, xt, xu, xv, xw, xx, xy) {
c =
index[0] < 2 || index[1] < 2
? 0
: xa * fy +
xb * fx +
xc * fw +
xd * fv +
xe * fu +
xf * ft +
xg * fs +
xh * fr +
xi * fq +
xj * fp +
xk * fo +
xl * fn +
xm * fm +
xn * fl +
xo * fk +
xp * fj +
xq * fi +
xr * fh +
xs * fg +
xt * ff +
xu * fe +
xv * fd +
xw * fc +
xx * fb +
xy * fa;
},
});
function createArray(arr, dtype) {
if (arr instanceof NdArray) {
return arr;
}
let T;
// this condition is to fix https://github.com/grimmer0125/numjs/pull/9
if (dtype) {
T = _.getType(dtype);
}
if (_.isNumber(arr)) {
if (T && T !== Array) {
return new NdArray(new T([arr]), [1]);
}
else {
return new NdArray([arr], [1]);
}
}
const shape = _.getShape(arr);
if (shape.length > 1) {
arr = _.flatten(arr, true);
}
if (T && !(arr instanceof T)) {
// below is to fix https://github.com/grimmer0125/numjs/pull/9
if (arr instanceof Array) {
arr = new T(arr);
}
else if (T === Array) {
arr = Array.from(arr);
}
else {
throw new errors.ValueError("Passed TypedArray and (Typed) dtype are not the same types, not support these conversions yet");
}
}
return new NdArray(arr, shape);
}
// NdArray.new = createArray;
/* utils */
function initNativeArray(shape, i) {
i = i || 0;
const c = shape[i] | 0;
if (c <= 0) {
return [];
}
const result = new Array(c);
let j;
if (i === shape.length - 1) {
for (j = 0; j < c; ++j) {
result[j] = 0;
}
}
else {
for (j = 0; j < c; ++j) {
result[j] = initNativeArray(shape, i + 1);
}
}
return result;
}
/* istanbul ignore next */
const doUnpack = cwise({
args: ["array", "scalar", "index"],
body: function unpackCwise(arr, a, idx) {
let v = a;
let i;
for (i = 0; i < idx.length - 1; ++i) {
v = v[idx[i]];
}
v[idx[idx.length - 1]] = arr;
},
});
function unpackArray(arr) {
const result = initNativeArray(arr.shape, 0);
doUnpack(arr, result);
return result;
}
function formatNumber(v) {
return String(Number((v || 0).toFixed(CONF.nFloatingValues)));
}
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