fork/cellxgene
1
0
Fork 0
mirror of https://github.com/chanzuckerberg/cellxgene.git synced 2026-09-29 19:48:11 +08:00
Code Issues Packages Projects Releases Wiki Activity

add multi-layout support to back-end (#766)

Browse Source 
* add multi-layout support to back-end

* remove obsolete code

* temporary code to apply heuristic choice of default layout

* fix tests

* update python tests

* more py lint

* PR review changes

* more PR lint

* PR lint
This commit is contained in:
Bruce Martin
2019-05-16 14:49:22 -07:00
committed by GitHub
parent d6040f687a
commit efa1709158
10 changed files with 93 additions and 60 deletions
Download Patch File Download Diff File Expand all files Collapse all files
client/__tests__/util/stateManager/sampleResponses.js
+1 -23
View File
@@ -162,29 +162,7 @@ const aLayoutFBSResponse = (() => {
new Float32Array(nObs).fill(Math.random()),
new Float32Array(nObs).fill(Math.random())
];
const builder = new flatbuffers.Builder(1024);
const cols = _.map(coords, carr => {
const cdv = NetEncoding.Float32Array.createDataVector(builder, carr);
NetEncoding.Float32Array.startFloat32Array(builder);
NetEncoding.Float32Array.addData(builder, cdv);
const floatArr = NetEncoding.Float32Array.endFloat32Array(builder);
NetEncoding.Column.startColumn(builder);
NetEncoding.Column.addUType(builder, NetEncoding.TypedArray.Float32Array);
NetEncoding.Column.addU(builder, floatArr);
return NetEncoding.Column.endColumn(builder);
});
const columns = NetEncoding.Matrix.createColumnsVector(builder, cols);
NetEncoding.Matrix.startMatrix(builder);
NetEncoding.Matrix.addNRows(builder, nObs);
NetEncoding.Matrix.addNCols(builder, coords.length);
NetEncoding.Matrix.addColumns(builder, columns);
const matrix = NetEncoding.Matrix.endMatrix(builder);
builder.finish(matrix);
return builder.asUint8Array();
return encodeMatrix(coords, ["umap_0", "umap_1"]);
})();
const aDataObsResponse = {
client/src/util/stateManager/universe.js
+21 -3
View File
@@ -78,6 +78,7 @@ function AnnotationsFBSToDataframe(arrayBuffer) {
The application has strong assumptions that all scalar data will be
stored as a float32 or float64 (regardless of underlying data types).
For example, clipping of value ranges (eg, user-selected percentiles)
depends on the ability to use NaN in any numeric type.
All float data from the server is left as is. All non-float is promoted
to an appropriate float.
@@ -98,13 +99,30 @@ function AnnotationsFBSToDataframe(arrayBuffer) {
function LayoutFBSToDataframe(arrayBuffer) {
const fbs = decodeMatrixFBS(arrayBuffer, true);
if (fbs.columns.length !== 2 || !fbs.columns.every(isFpTypedArray)) {
if (fbs.columns.length < 2 || !fbs.columns.every(isFpTypedArray)) {
// We have strong assumptions about the shape & type of layout data.
throw new Error("Unexpected layout data type returned from server");
}
/*
TODO: XXX
TEMPORARY CODE AND COMMENT to support the progressive implementation
of multi-layout support. For now, we search for one of the following
in the layouts and use it if we find it: umap, then tsne, then pca,
then whatever is first in the list.
*/
let layoutIndex = 0;
["umap", "tsne", "pca"].some(name => {
const idx = fbs.colIdx.indexOf(`${name}_0`);
if (idx !== -1) {
layoutIndex = idx;
}
return idx !== -1;
});
const df = new Dataframe.Dataframe(
[fbs.nRows, fbs.nCols],
fbs.columns,
[fbs.nRows, 2],
[fbs.columns[layoutIndex], fbs.columns[layoutIndex + 1]],
null,
new Dataframe.KeyIndex(["X", "Y"])
);