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Hello, npyjs
// adapted from https://github.com/jhuapl-boss/npyjs
class npyjs {
constructor(opts) {
if (opts) {
throw [
"No arguments accepted to npyjs constructor.",
"For usage, go to https://github.com/jhuapl-boss/npyjs."
].join(" ");
}
this.dtypes = {
"<u1": {
name: "uint8",
size: 8,
arrayConstructor: Uint8Array
},
"|u1": {
name: "uint8",
size: 8,
arrayConstructor: Uint8Array
},
"|i1": {
name: "int8",
size: 8,
arrayConstructor: Int8Array
},
"<u4": {
name: "uint32",
size: 32,
arrayConstructor: Int32Array
},
"<i4": {
name: "int32",
size: 32,
arrayConstructor: Int32Array
},
"<u8": {
name: "uint64",
size: 64,
arrayConstructor: BigUint64Array
},
"<i8": {
name: "int64",
size: 64,
arrayConstructor: BigInt64Array
},
"<f4": {
name: "float32",
size: 32,
arrayConstructor: Float32Array
},
"<f8": {
name: "float64",
size: 64,
arrayConstructor: Float64Array
}
};
}
parse(arrayBufferContents) {
// const version = arrayBufferContents.slice(6, 8); // Uint8-encoded
const headerLength = new DataView(
arrayBufferContents.slice(8, 10)
).getUint8(0);
const offsetBytes = 10 + headerLength;
const hcontents = new TextDecoder("utf-8").decode(
new Uint8Array(arrayBufferContents.slice(10, 10 + headerLength))
);
const header = JSON.parse(
hcontents
.replace(/'/g, '"')
.replace("False", "false")
.replace("(", "[")
.replace(/,*\),*/g, "]")
);
const shape = header.shape;
const dtype = this.dtypes[header.descr];
const nums = new dtype["arrayConstructor"](
arrayBufferContents,
offsetBytes
);
return {
dtype: dtype.name,
data: nums,
shape
};
}
}
FileAttachment("10-float32.npy")
.arrayBuffer()
.then(d => new npyjs().parse(d))
import { file } from "@jashkenas/inputs"
viewof f = file()
f.arrayBuffer().then(d => new npyjs().parse(d))
fetch(
"https://rawcdn.githack.com/aplbrain/npyjs/ba60a3a529f3210dd07d2ed05ab628939e18b6a7/test/data/4x4x4x4x4-float32.npy"
)
.then(d => d.arrayBuffer())
.then(d => new npyjs().parse(d))
// aplbrain/npyjs is licensed under the Apache License 2.0
LICENSE = "apache-2.0"
Purpose-built for displays of data
Observable is your go-to platform for exploring data and creating expressive data visualizations. Use reactive JavaScript notebooks for prototyping and a collaborative canvas for visual data exploration and dashboard creation.
