mirror of
https://github.com/chanzuckerberg/cellxgene.git
synced 2026-10-03 01:38:11 +08:00
binary wire format with flatbuffers (#509)
* first flatbuffer schema * do not lint auto-generated files * add flatbuffers package * add flatbuffer module * wire up /data/X/T route * use flatbuffers for matrix data fetc * clarity and comments * add flatbuffer layout route * clean up obsolete code * fix tests * move flake8 config to setup.cfg * add comments * lint * rework layout routes for fbs * add more type support to fbs * lint * add flatbuffer support for annotations * function name improvements * fix botched merge with master * remove unused import * route cleanup for flatbuffers * rename function for clarity * add missing globals to Jest tests * fix client JS tests * fix routes for Python tests * comments for clarity * non-finite floating point hardening * more non-finite number handling * lint * fix tests for summarizeAnnotations * harden diffexp calculation against FP errors * cleanup unused code * lint * add encoding tests for flatbuffers * application type specified as strings * fix spelling error * improve variable names * add note about documentation gap * rename FBS DataFrame to Matrix
This commit is contained in:
@@ -0,0 +1,75 @@
|
||||
import { flatbuffers } from "flatbuffers";
|
||||
import { NetEncoding } from "./matrix_generated";
|
||||
|
||||
const utf8Decoder = new TextDecoder("utf-8");
|
||||
|
||||
/*
|
||||
Matrix flatbuffer decoding support. See fbs/matrix.fbs
|
||||
*/
|
||||
|
||||
/*
|
||||
Decode NetEncoding.TypedArray
|
||||
*/
|
||||
function decodeTypedArray(uType, uValF, inplace = false) {
|
||||
if (uType === NetEncoding.TypedArray.NONE) {
|
||||
return null;
|
||||
}
|
||||
|
||||
// Convert to a JS class that supports this type
|
||||
const TypeClass = NetEncoding[NetEncoding.TypedArray[uType]];
|
||||
// Create a TypedArray that references the underlying buffer
|
||||
let arr = uValF(new TypeClass()).dataArray();
|
||||
if (uType === NetEncoding.TypedArray.JSONEncodedArray) {
|
||||
const json = utf8Decoder.decode(arr);
|
||||
arr = JSON.parse(json);
|
||||
} else if (!inplace) {
|
||||
/* force copy to release underlying FBS buffer */
|
||||
arr = new arr.constructor(arr);
|
||||
}
|
||||
return arr;
|
||||
}
|
||||
|
||||
/*
|
||||
Parameter: Uint8Array or ArrayBuffer containing raw flatbuffer Matrix
|
||||
Returns: object containing decoded Matrix:
|
||||
{
|
||||
nRows: num,
|
||||
nCols: num,
|
||||
columns: [
|
||||
each column, which will be a TypedArray or Array
|
||||
]
|
||||
colIdx: []|null
|
||||
}
|
||||
*/
|
||||
function decodeMatrixFBS(arrayBuffer, inplace = false) {
|
||||
const bb = new flatbuffers.ByteBuffer(new Uint8Array(arrayBuffer));
|
||||
const df = NetEncoding.Matrix.getRootAsMatrix(bb);
|
||||
|
||||
const nRows = df.nRows();
|
||||
const nCols = df.nCols();
|
||||
|
||||
/* decode columns */
|
||||
const columnsLength = df.columnsLength();
|
||||
const columns = Array(columnsLength).fill(null);
|
||||
for (let c = 0; c < columnsLength; c += 1) {
|
||||
const col = df.columns(c);
|
||||
columns[c] = decodeTypedArray(col.uType(), col.u.bind(col), inplace);
|
||||
}
|
||||
|
||||
/* decode col_idx */
|
||||
const colIdx = decodeTypedArray(
|
||||
df.colIndexType(),
|
||||
df.colIndex.bind(df),
|
||||
inplace
|
||||
);
|
||||
|
||||
return {
|
||||
nRows,
|
||||
nCols,
|
||||
columns,
|
||||
colIdx,
|
||||
rowIdx: null
|
||||
};
|
||||
}
|
||||
|
||||
export default decodeMatrixFBS;
|
||||
Reference in New Issue
Block a user