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visium-beta
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54d4de431c |
@@ -0,0 +1,20 @@
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# Cellxgene Visium Beta
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## How it works
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1. Launch `cellxgene` as normal.
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1. If the loaded dataset has spatial information available, the image data will be loaded on startup.
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1. On the toolbar, next to the Zoom icon, a `Toggle image` button will now appear. Click on it and the image will be added as an underlay.
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1. You can now use any `cellxgene` functionality and the image will still be present. If you pan and zoom, the image will also be panned and zoomed.
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1. If you want to hide the image, you can click on `Toggle image` again
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In order for the image to be displayed with the correct size and alignment, the H5AD needs to have a few requirements. See the following section to learn more.
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## h5ad requirements
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1. The spatial embedding layer should be contained in `obsm` and be named `X_spatial`. Other layers can exist, but only this one will have the spatial feature enabled.
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2. A `spatial` dict needs to be defined in the `uns` dictionary.
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3. Inside the `spatial` dict, an `images` dict must be defined.
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4. The `images` dict must contain a `hires` key, which should reference an image encoded as an RGB matrix (i.e., a three-dimensional matrix of size `height x width x 3` where the final dimension has the RGB values for each pixel)
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5. The `images` dict must contain a `scalefactors` dict. This should in turn contain a `tissue_hires_scalef` key, which should reference a floating point number.
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Moreover, in order to have the image correctly aligned with the dots, the following must be true:
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1. `tissue_hires_scalef` should represent the ratio between the embedding layer `X_spatial` and the image matrix. In particular, if you multiply `X_spatial` by `tissue_hires_scalef`, you should obtain an array of points that ovelap the tissue image if you plot them in a plane.
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@@ -8,6 +8,7 @@ import {
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import { loadUserColorConfig } from "../util/stateManager/colorHelpers";
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import * as selnActions from "./selection";
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import * as annoActions from "./annotation";
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import * as spatialActions from "./spatial";
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import * as viewActions from "./viewStack";
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import * as embActions from "./embedding";
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import * as genesetActions from "./geneset";
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@@ -272,4 +273,5 @@ export default {
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genesetDelete: genesetActions.genesetDelete,
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genesetAddGenes: genesetActions.genesetAddGenes,
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genesetDeleteGenes: genesetActions.genesetDeleteGenes,
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requestSpatialMetadata: spatialActions.requestSpatialMetadata,
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};
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@@ -0,0 +1,35 @@
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import * as globals from "../globals";
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export const requestSpatialMetadata = () => async (dispatch) => {
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dispatch({ type: "request spatial metadata started" });
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try {
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const res = await fetch(
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`${globals.API.prefix}${globals.API.version}spatial/meta`,
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{
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method: "GET",
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headers: new Headers({
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Accept: "application/json",
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"Content-Type": "application/json",
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}),
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credentials: "include",
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}
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);
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if (!res.ok || res.headers.get("Content-Type") !== "application/json") {
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return null; // TODO need a dispatch //dispatchDiffExpErrors(dispatch, res);
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}
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const response = await res.json();
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/* then send the success case action through */
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return dispatch({
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type: "request spatial metadata success",
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data: response,
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});
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} catch (error) {
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return dispatch({
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type: "request spatial metadata error",
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error,
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});
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}
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};
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@@ -23,6 +23,8 @@ class App extends React.Component {
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componentDidMount() {
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const { dispatch } = this.props;
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dispatch(actions.requestSpatialMetadata());
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/* listen for url changes, fire one when we start the app up */
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window.addEventListener("popstate", this._onURLChanged);
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this._onURLChanged();
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@@ -16,10 +16,11 @@ import actions from "../../actions";
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import { getDiscreteCellEmbeddingRowIndex } from "../../util/stateManager/viewStackHelpers";
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@connect((state) => ({
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layoutChoice: state.layoutChoice, // TODO: really should clean up naming, s/layout/embedding/g
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schema: state.annoMatrix?.schema,
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crossfilter: state.obsCrossfilter,
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}))
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imageUnderlay: state.imageUnderlay,
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layoutChoice: state.layoutChoice, // TODO: really should clean up naming, s/layout/embedding/g
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schema: state.annoMatrix?.schema,
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crossfilter: state.obsCrossfilter,
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}))
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class Embedding extends React.PureComponent {
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constructor(props) {
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super(props);
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@@ -27,8 +28,18 @@ class Embedding extends React.PureComponent {
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}
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handleLayoutChoiceChange = (e) => {
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const { dispatch } = this.props;
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const { dispatch, imageUnderlay } = this.props;
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dispatch(actions.layoutChoiceAction(e.currentTarget.value));
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// if we just switched off spatial, if the image is on, turn it off
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if (
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imageUnderlay.isActive &&
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e.target.value !== globals.spatialEmbeddingKeyword
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) {
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dispatch({
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type: "toggle image underlay",
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});
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}
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};
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render() {
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@@ -0,0 +1,62 @@
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export default function drawSpatialImageRegl(regl) {
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return regl({
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frag: `
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precision mediump float;
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// our texture
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uniform sampler2D u_image;
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// the texCoords passed in from the vertex shader.
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varying vec2 v_texCoord;
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void main() {
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gl_FragColor = texture2D(u_image, v_texCoord);
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}`,
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vert: `
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attribute vec2 a_position;
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attribute vec2 a_texCoord;
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uniform vec2 u_resolution;
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uniform mat3 projView;
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varying vec2 v_texCoord;
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void main() {
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// convert the rectangle from pixels to 0.0 to 1.0
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vec3 pos = vec3(a_position, 1.);
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vec2 zeroToOne = pos.xy / u_resolution;
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// convert from 0->1 to 0->2
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vec2 zeroToTwo = zeroToOne * 2.0;
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// convert from 0->2 to -1->+1 (clipspace)
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vec2 clipSpace = zeroToTwo - 1.0;
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vec3 pos2 = projView * vec3(clipSpace, 1.);
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gl_Position = vec4(pos2.xy , 0, 1);
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// pass the texCoord to the fragment shader
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// The GPU will interpolate this value between points.
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v_texCoord = a_texCoord;
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}`,
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attributes: {
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a_texCoord: [0.0, 0.0, 1.0, 0.0, 0.0, 1.0, 0.0, 1.0, 1.0, 0.0, 1.0, 1.0],
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a_position: regl.prop("rectCoords"),
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},
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uniforms: {
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projView: regl.prop("projView"),
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u_image: regl.prop("spatialImageAsTexture"),
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color: [1, 0, 0, 1],
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u_resolution: [regl.prop("imageWidth"), regl.prop("imageHeight")],
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image_width: regl.prop("imageWidth"),
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// translate:
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},
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count: 6,
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});
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}
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@@ -14,6 +14,7 @@ import {
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createColorTable,
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createColorQuery,
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} from "../../util/stateManager/colorHelpers";
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import _drawSpatialImage from "./drawSpatialImageRegl";
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import * as globals from "../../globals";
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import GraphOverlayLayer from "./overlays/graphOverlayLayer";
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@@ -77,6 +78,8 @@ function createModelTF() {
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colors: state.colors,
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pointDilation: state.pointDilation,
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genesets: state.genesets.genesets,
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spatial: state.spatial.metadata,
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imageUnderlay: state.imageUnderlay,
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}))
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class Graph extends React.Component {
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static createReglState(canvas) {
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@@ -87,6 +90,7 @@ class Graph extends React.Component {
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const camera = _camera(canvas);
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const regl = _regl(canvas);
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const drawPoints = _drawPoints(regl);
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const drawSpatialImage = _drawSpatialImage(regl);
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// preallocate webgl buffers
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const pointBuffer = regl.buffer();
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@@ -100,6 +104,7 @@ class Graph extends React.Component {
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||||
pointBuffer,
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colorBuffer,
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flagBuffer,
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drawSpatialImage,
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||||
};
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||||
}
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||||
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@@ -232,6 +237,8 @@ class Graph extends React.Component {
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||||
pointBuffer: null,
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colorBuffer: null,
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flagBuffer: null,
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drawSpatialImage: null,
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spatial: null,
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||||
|
||||
// component rendering derived state - these must stay synchronized
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// with the reducer state they were generated from.
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@@ -317,7 +324,10 @@ class Graph extends React.Component {
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if (e.type !== "wheel") e.preventDefault();
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if (camera.handleEvent(e, projectionTF)) {
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this.renderCanvas();
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this.setState((state) => ({ ...state, updateOverlay: !state.updateOverlay }));
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this.setState((state) => ({
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...state,
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updateOverlay: !state.updateOverlay,
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}));
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||||
}
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||||
};
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@@ -509,6 +519,14 @@ class Graph extends React.Component {
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||||
return { toolSVG: newToolSVG, tool, container };
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||||
};
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loadTextureFromUrl = (src) =>
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new Promise((resolve, reject) => {
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const img = new Image();
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||||
img.onload = () => resolve(img);
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||||
img.onerror = reject;
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||||
img.src = src;
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||||
});
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||||
fetchAsyncProps = async (props) => {
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const {
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annoMatrix,
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||||
@@ -517,6 +535,8 @@ class Graph extends React.Component {
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||||
crossfilter,
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||||
pointDilation,
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viewport,
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||||
spatial,
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imageUnderlay,
|
||||
} = props.watchProps;
|
||||
const { modelTF } = this.state;
|
||||
|
||||
@@ -524,7 +544,8 @@ class Graph extends React.Component {
|
||||
annoMatrix,
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||||
layoutChoice,
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||||
colorsProp,
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||||
pointDilation
|
||||
pointDilation,
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||||
imageUnderlay
|
||||
);
|
||||
|
||||
const { currentDimNames } = layoutChoice;
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||||
@@ -551,6 +572,10 @@ class Graph extends React.Component {
|
||||
pointDilationLabel
|
||||
);
|
||||
|
||||
this.spatialImage = await this.loadTextureFromUrl(
|
||||
"/api/v0.2/spatial/image"
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);
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||||
|
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const { width, height } = viewport;
|
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return {
|
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positions,
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||||
@@ -558,6 +583,8 @@ class Graph extends React.Component {
|
||||
flags,
|
||||
width,
|
||||
height,
|
||||
spatial,
|
||||
imageUnderlay,
|
||||
};
|
||||
};
|
||||
|
||||
@@ -721,6 +748,7 @@ class Graph extends React.Component {
|
||||
flagBuffer,
|
||||
camera,
|
||||
projectionTF,
|
||||
drawSpatialImage,
|
||||
} = this.state;
|
||||
this.renderPoints(
|
||||
regl,
|
||||
@@ -729,12 +757,14 @@ class Graph extends React.Component {
|
||||
pointBuffer,
|
||||
flagBuffer,
|
||||
camera,
|
||||
projectionTF
|
||||
projectionTF,
|
||||
drawSpatialImage
|
||||
);
|
||||
});
|
||||
|
||||
updateReglAndRender(asyncProps, prevAsyncProps) {
|
||||
const { positions, colors, flags, height, width } = asyncProps;
|
||||
const { positions, colors, flags, height, width, imageUnderlay } =
|
||||
asyncProps;
|
||||
this.cachedAsyncProps = asyncProps;
|
||||
const { pointBuffer, colorBuffer, flagBuffer } = this.state;
|
||||
let needToRenderCanvas = false;
|
||||
@@ -754,6 +784,9 @@ class Graph extends React.Component {
|
||||
flagBuffer({ data: flags, dimension: 1 });
|
||||
needToRenderCanvas = true;
|
||||
}
|
||||
if (imageUnderlay !== prevAsyncProps?.imageUnderlay) {
|
||||
needToRenderCanvas = true;
|
||||
}
|
||||
if (needToRenderCanvas) this.renderCanvas();
|
||||
}
|
||||
|
||||
@@ -797,20 +830,25 @@ class Graph extends React.Component {
|
||||
pointBuffer,
|
||||
flagBuffer,
|
||||
camera,
|
||||
projectionTF
|
||||
projectionTF,
|
||||
drawSpatialImage
|
||||
) {
|
||||
const { annoMatrix } = this.props;
|
||||
const { annoMatrix, spatial, imageUnderlay } = this.props;
|
||||
if (!this.reglCanvas || !annoMatrix) return;
|
||||
|
||||
const { schema } = annoMatrix;
|
||||
const cameraTF = camera.view();
|
||||
const projView = mat3.multiply(mat3.create(), projectionTF, cameraTF);
|
||||
const { width, height } = this.reglCanvas;
|
||||
const imW = spatial.data.imageWidth;
|
||||
const imH = spatial.data.imageHeight;
|
||||
|
||||
regl.poll();
|
||||
regl.clear({
|
||||
depth: 1,
|
||||
color: [1, 1, 1, 1],
|
||||
color: [0, 0, 0, 0],
|
||||
});
|
||||
|
||||
drawPoints({
|
||||
distance: camera.distance(),
|
||||
color: colorBuffer,
|
||||
@@ -821,6 +859,19 @@ class Graph extends React.Component {
|
||||
nPoints: schema.dataframe.nObs,
|
||||
minViewportDimension: Math.min(width, height),
|
||||
});
|
||||
if (imageUnderlay?.isActive) {
|
||||
drawSpatialImage({
|
||||
projView,
|
||||
imageWidth: imW,
|
||||
imageHeight: imH,
|
||||
rectCoords: [0, 0, imW, 0, 0, imH, 0, imH, imW, 0, imW, imH],
|
||||
spatialImageAsTexture: regl.texture({
|
||||
data: this.spatialImage,
|
||||
wrapS: "clamp",
|
||||
wrapT: "clamp",
|
||||
}),
|
||||
});
|
||||
}
|
||||
regl._gl.flush();
|
||||
}
|
||||
|
||||
@@ -832,6 +883,8 @@ class Graph extends React.Component {
|
||||
layoutChoice,
|
||||
pointDilation,
|
||||
crossfilter,
|
||||
spatial,
|
||||
imageUnderlay,
|
||||
} = this.props;
|
||||
const { modelTF, projectionTF, camera, viewport, regl } = this.state;
|
||||
const cameraTF = camera?.view()?.slice();
|
||||
@@ -902,6 +955,8 @@ class Graph extends React.Component {
|
||||
pointDilation,
|
||||
crossfilter,
|
||||
viewport,
|
||||
spatial,
|
||||
imageUnderlay,
|
||||
}}
|
||||
>
|
||||
<Async.Pending initial>
|
||||
@@ -951,32 +1006,29 @@ const ErrorLoading = ({ displayName, error, width, height }) => {
|
||||
);
|
||||
};
|
||||
|
||||
const StillLoading = ({ displayName, width, height }) =>
|
||||
const StillLoading = ({ displayName, width, height }) => (
|
||||
/*
|
||||
Render a busy/loading indicator
|
||||
*/
|
||||
(
|
||||
<div
|
||||
style={{
|
||||
position: "fixed",
|
||||
fontWeight: 500,
|
||||
top: height / 2,
|
||||
width,
|
||||
}}
|
||||
>
|
||||
<div
|
||||
style={{
|
||||
position: "fixed",
|
||||
fontWeight: 500,
|
||||
top: height / 2,
|
||||
width,
|
||||
display: "flex",
|
||||
justifyContent: "center",
|
||||
justifyItems: "center",
|
||||
alignItems: "center",
|
||||
}}
|
||||
>
|
||||
<div
|
||||
style={{
|
||||
display: "flex",
|
||||
justifyContent: "center",
|
||||
justifyItems: "center",
|
||||
alignItems: "center",
|
||||
}}
|
||||
>
|
||||
<Button minimal loading intent="primary" />
|
||||
<span style={{ fontStyle: "italic" }}>Loading {displayName}</span>
|
||||
</div>
|
||||
<Button minimal loading intent="primary" />
|
||||
<span style={{ fontStyle: "italic" }}>Loading {displayName}</span>
|
||||
</div>
|
||||
)
|
||||
;
|
||||
|
||||
</div>
|
||||
);
|
||||
export default Graph;
|
||||
|
||||
@@ -28,6 +28,8 @@ import { getEmbSubsetView } from "../../util/stateManager/viewStackHelpers";
|
||||
subsetPossible,
|
||||
subsetResetPossible,
|
||||
graphInteractionMode: state.controls.graphInteractionMode,
|
||||
imageUnderlay: state.imageUnderlay,
|
||||
layoutChoice: state.layoutChoice, // TODO: really should clean up naming, s/layout/embedding/g
|
||||
clipPercentileMin: Math.round(100 * (annoMatrix?.clipRange?.[0] ?? 0)),
|
||||
clipPercentileMax: Math.round(100 * (annoMatrix?.clipRange?.[1] ?? 1)),
|
||||
userDefinedGenes: state.controls.userDefinedGenes,
|
||||
@@ -206,6 +208,8 @@ class MenuBar extends React.PureComponent {
|
||||
colorAccessor,
|
||||
subsetPossible,
|
||||
subsetResetPossible,
|
||||
imageUnderlay,
|
||||
layoutChoice,
|
||||
} = this.props;
|
||||
const { pendingClipPercentiles } = this.state;
|
||||
|
||||
@@ -268,6 +272,29 @@ class MenuBar extends React.PureComponent {
|
||||
disabled={!isColoredByCategorical}
|
||||
/>
|
||||
</Tooltip>
|
||||
{layoutChoice?.available?.includes(globals.spatialEmbeddingKeyword) && (
|
||||
<ButtonGroup className={styles.menubarButton}>
|
||||
<Tooltip
|
||||
content={"Toggle image"}
|
||||
position="bottom"
|
||||
hoverOpenDelay={globals.tooltipHoverOpenDelay}
|
||||
>
|
||||
<AnchorButton
|
||||
type="button"
|
||||
data-testid="toggle-image-underlay"
|
||||
icon={"media"}
|
||||
intent={imageUnderlay.isActive ? "primary" : "none"}
|
||||
active={imageUnderlay.isActive}
|
||||
onClick={() => {
|
||||
dispatch({
|
||||
type: "toggle image underlay",
|
||||
});
|
||||
}}
|
||||
/>
|
||||
</Tooltip>
|
||||
</ButtonGroup>
|
||||
)}
|
||||
|
||||
<ButtonGroup className={styles.menubarButton}>
|
||||
<Tooltip
|
||||
content={selectionTooltip}
|
||||
|
||||
@@ -2,6 +2,9 @@ import { Colors } from "@blueprintjs/core";
|
||||
import { dispatchNetworkErrorMessageToUser } from "./util/actionHelpers";
|
||||
import ENV_DEFAULT from "../../environment.default.json";
|
||||
|
||||
// visium embedding word, spatial image underlay
|
||||
export const spatialEmbeddingKeyword = "spatial";
|
||||
|
||||
/* overflow category values are created using this string */
|
||||
export const overflowCategoryLabel = ": all other labels";
|
||||
|
||||
|
||||
@@ -0,0 +1,14 @@
|
||||
const imageUnderlay = (state = { isActive: false }, action) => {
|
||||
switch (action.type) {
|
||||
case "toggle image underlay":
|
||||
return {
|
||||
...state,
|
||||
isActive: !state.isActive,
|
||||
};
|
||||
|
||||
default:
|
||||
return state;
|
||||
}
|
||||
};
|
||||
|
||||
export default imageUnderlay;
|
||||
@@ -11,6 +11,7 @@ import continuousSelection from "./continuousSelection";
|
||||
import graphSelection from "./graphSelection";
|
||||
import colors from "./colors";
|
||||
import differential from "./differential";
|
||||
import spatial from "./spatial";
|
||||
import layoutChoice from "./layoutChoice";
|
||||
import controls from "./controls";
|
||||
import annotations from "./annotations";
|
||||
@@ -19,6 +20,7 @@ import genesetsUI from "./genesetsUI";
|
||||
import autosave from "./autosave";
|
||||
import centroidLabels from "./centroidLabels";
|
||||
import pointDialation from "./pointDilation";
|
||||
import imageUnderlay from "./imageUnderlay";
|
||||
import { gcMiddleware as annoMatrixGC } from "../annoMatrix";
|
||||
|
||||
import undoableConfig from "./undoableConfig";
|
||||
@@ -38,7 +40,9 @@ const Reducer = undoable(
|
||||
["colors", colors],
|
||||
["controls", controls],
|
||||
["differential", differential],
|
||||
["spatial", spatial],
|
||||
["centroidLabels", centroidLabels],
|
||||
["imageUnderlay", imageUnderlay],
|
||||
["pointDilation", pointDialation],
|
||||
["autosave", autosave],
|
||||
]),
|
||||
@@ -51,6 +55,7 @@ const Reducer = undoable(
|
||||
"colors",
|
||||
"controls",
|
||||
"differential",
|
||||
"spatial",
|
||||
"layoutChoice",
|
||||
"centroidLabels",
|
||||
"genesets",
|
||||
|
||||
@@ -0,0 +1,34 @@
|
||||
const Spatial = (
|
||||
state = {
|
||||
loading: null,
|
||||
error: null,
|
||||
metadata: null,
|
||||
},
|
||||
action
|
||||
) => {
|
||||
switch (action.type) {
|
||||
case "request spatial metadata started":
|
||||
return {
|
||||
...state,
|
||||
loading: true,
|
||||
error: null,
|
||||
};
|
||||
case "request spatial metadata success":
|
||||
return {
|
||||
...state,
|
||||
error: null,
|
||||
loading: false,
|
||||
metadata: action,
|
||||
};
|
||||
case "request spatial metadata error":
|
||||
return {
|
||||
...state,
|
||||
loading: false,
|
||||
error: action.data,
|
||||
};
|
||||
default:
|
||||
return state;
|
||||
}
|
||||
};
|
||||
|
||||
export default Spatial;
|
||||
@@ -52,6 +52,9 @@ const skipOnActions = new Set([
|
||||
"geneset: disable add new genes mode",
|
||||
"geneset: activate rename geneset mode",
|
||||
"geneset: disable rename geneset mode",
|
||||
|
||||
/* spatial */
|
||||
"toggle image underlay",
|
||||
]);
|
||||
|
||||
/*
|
||||
|
||||
@@ -190,6 +190,16 @@ class SummarizeVarAPI(Resource):
|
||||
def post(self, data_adaptor):
|
||||
return common_rest.summarize_var_post(request, data_adaptor)
|
||||
|
||||
class SpatialImageAPI(Resource):
|
||||
@rest_get_data_adaptor
|
||||
def get(self, data_adaptor):
|
||||
return common_rest.spatial_image_get(request, data_adaptor)
|
||||
|
||||
class SpatialMetaAPI(Resource):
|
||||
@rest_get_data_adaptor
|
||||
def get(self, data_adaptor):
|
||||
return data_adaptor.get_spatial_metadata()
|
||||
|
||||
|
||||
def get_api_base_resources(bp_base):
|
||||
"""Add resources that are accessed from the api url"""
|
||||
@@ -222,6 +232,9 @@ def get_api_dataroot_resources(bp_dataroot):
|
||||
# Computation routes
|
||||
add_resource(DiffExpObsAPI, "/diffexp/obs")
|
||||
add_resource(LayoutObsAPI, "/layout/obs")
|
||||
# Spatial routes
|
||||
add_resource(SpatialImageAPI, "/spatial/image")
|
||||
add_resource(SpatialMetaAPI, "/spatial/meta")
|
||||
return api
|
||||
|
||||
|
||||
|
||||
+40
-2
@@ -4,8 +4,9 @@ import sys
|
||||
from http import HTTPStatus
|
||||
import zlib
|
||||
import json
|
||||
import numpy as np
|
||||
|
||||
from flask import make_response, jsonify, current_app, abort
|
||||
from flask import make_response, jsonify, current_app, abort, send_file
|
||||
from werkzeug.urls import url_unquote
|
||||
|
||||
from server.common.config.client_config import get_client_config
|
||||
@@ -293,7 +294,7 @@ def layout_obs_get(request, data_adaptor):
|
||||
|
||||
try:
|
||||
return make_response(
|
||||
data_adaptor.layout_to_fbs_matrix(fields), HTTPStatus.OK, {"Content-Type": "application/octet-stream"}
|
||||
data_adaptor.layout_to_fbs_matrix(fields, data_adaptor.get_spatial()), HTTPStatus.OK, {"Content-Type": "application/octet-stream"}
|
||||
)
|
||||
except (KeyError, DatasetAccessError) as e:
|
||||
return abort_and_log(HTTPStatus.BAD_REQUEST, str(e), include_exc_info=True)
|
||||
@@ -397,3 +398,40 @@ def summarize_var_post(request, data_adaptor):
|
||||
|
||||
key = request.args.get("key", default=None)
|
||||
return summarize_var_helper(request, data_adaptor, key, request.get_data())
|
||||
|
||||
def spatial_image_get(request, data_adaptor):
|
||||
import io
|
||||
import matplotlib.pyplot
|
||||
|
||||
resolution = "hires"
|
||||
spatial = data_adaptor.get_spatial()
|
||||
|
||||
if len(list(spatial)) == 0:
|
||||
return abort_and_log(HTTPStatus.BAD_REQUEST, "uns does not have spatial information")
|
||||
|
||||
library_id = list(spatial)[0]
|
||||
if len(spatial) > 1:
|
||||
current_app.logger.warning(f"More than one library found under uns.spatial, using library '{library_id}'")
|
||||
|
||||
if "images" not in spatial[library_id]:
|
||||
return abort_and_log(HTTPStatus.BAD_REQUEST, "spatial information does not contain images")
|
||||
|
||||
if resolution not in spatial[library_id]["images"]:
|
||||
return abort_and_log(HTTPStatus.BAD_REQUEST, f"spatial information does not contain requested resolution '{resolution}'")
|
||||
|
||||
response_image = io.BytesIO()
|
||||
img = spatial[library_id]["images"][resolution]
|
||||
matplotlib.pyplot.imsave(response_image, img)
|
||||
response_image.seek(0)
|
||||
|
||||
try:
|
||||
return send_file(response_image, attachment_filename=f"{library_id}-{resolution}.png", mimetype="image/png")
|
||||
except (KeyError, DatasetAccessError) as e:
|
||||
return abort_and_log(HTTPStatus.BAD_REQUEST, str(e), include_exc_info=True)
|
||||
except PrepareError:
|
||||
return abort_and_log(
|
||||
HTTPStatus.NOT_IMPLEMENTED,
|
||||
f"No spatial image available {request.path}",
|
||||
loglevel=logging.ERROR,
|
||||
include_exc_info=True,
|
||||
)
|
||||
|
||||
@@ -274,6 +274,43 @@ class AnndataAdaptor(DataAdaptor):
|
||||
df = df[fields]
|
||||
return encode_matrix_fbs(df, col_idx=df.columns)
|
||||
|
||||
def get_spatial(self):
|
||||
return self.data.uns["spatial"]
|
||||
|
||||
def get_spatial_metadata(self):
|
||||
spatial = self.get_spatial()
|
||||
|
||||
resolution = "hires"
|
||||
|
||||
if len(list(spatial)) == 0:
|
||||
raise Exception("uns does not have spatial information")
|
||||
|
||||
library_id = list(spatial)[0]
|
||||
|
||||
if "images" not in spatial[library_id]:
|
||||
raise Exception("spatial information does not contain images")
|
||||
|
||||
if resolution not in spatial[library_id]["images"]:
|
||||
raise Exception(f"spatial information does not contain requested resolution '{resolution}'")
|
||||
|
||||
scaleref = spatial[library_id]["scalefactors"][f"tissue_{resolution}_scalef"]
|
||||
(h, w, _) = spatial[library_id]["images"][resolution].shape
|
||||
|
||||
A = self.data.obsm["X_spatial"]
|
||||
min = np.nanmin(A, axis=0)
|
||||
max = np.nanmax(A, axis=0)
|
||||
scale = np.amax(max - min)
|
||||
translate = 0.5 - ((max - min) / scale / 2)
|
||||
|
||||
return {
|
||||
"imageWidth": w,
|
||||
"imageHeight": h,
|
||||
"scaleref": scaleref,
|
||||
"inverseScale": int(scale),
|
||||
"inverseTranslate": translate.tolist(),
|
||||
"inverseMin": min.tolist(),
|
||||
}
|
||||
|
||||
def get_embedding_names(self):
|
||||
"""
|
||||
Return pre-computed embeddings.
|
||||
|
||||
@@ -340,31 +340,57 @@ class DataAdaptor(metaclass=ABCMeta):
|
||||
pass
|
||||
|
||||
@staticmethod
|
||||
def normalize_embedding(embedding):
|
||||
def normalize_embedding(embedding, spatial = None):
|
||||
"""Normalize embedding layout to meet client assumptions.
|
||||
Embedding is an ndarray, shape (n_obs, n)., where n is normally 2
|
||||
Embedding is an ndarray, shape (n_obs, n)., where n is normally 2.
|
||||
Note: if spatial data is available, the normalization will be done
|
||||
according to the size of the underlying image
|
||||
"""
|
||||
|
||||
# scale isotropically
|
||||
try:
|
||||
min = np.nanmin(embedding, axis=0)
|
||||
max = np.nanmax(embedding, axis=0)
|
||||
except RuntimeError:
|
||||
# indicates entire array was NaN, which should propagate
|
||||
min = np.NaN
|
||||
max = np.NaN
|
||||
if spatial is not None:
|
||||
|
||||
scale = np.amax(max - min)
|
||||
normalized_layout = (embedding - min) / scale
|
||||
# TODO: sync with the code in spatial_data_get
|
||||
resolution = "hires"
|
||||
|
||||
# translate to center on both axis
|
||||
translate = 0.5 - ((max - min) / scale / 2)
|
||||
normalized_layout = normalized_layout + translate
|
||||
if len(list(spatial)) == 0:
|
||||
raise Exception("uns does not have spatial information")
|
||||
|
||||
library_id = list(spatial)[0]
|
||||
|
||||
if "images" not in spatial[library_id]:
|
||||
raise Exception("spatial information does not contain images")
|
||||
|
||||
if resolution not in spatial[library_id]["images"]:
|
||||
raise Exception(f"spatial information does not contain requested resolution '{resolution}'")
|
||||
|
||||
scaleref = spatial[library_id]["scalefactors"][f"tissue_{resolution}_scalef"]
|
||||
(h, w, _) = spatial[library_id]["images"][resolution].shape
|
||||
|
||||
A = embedding * scaleref
|
||||
A = np.column_stack([A[:, 0] / w, A[:, 1] / h])
|
||||
normalized_layout = A.astype(dtype=np.float32)
|
||||
|
||||
else:
|
||||
|
||||
# scale isotropically
|
||||
try:
|
||||
min = np.nanmin(embedding, axis=0)
|
||||
max = np.nanmax(embedding, axis=0)
|
||||
except RuntimeError:
|
||||
# indicates entire array was NaN, which should propagate
|
||||
min = np.NaN
|
||||
max = np.NaN
|
||||
|
||||
scale = np.amax(max - min)
|
||||
normalized_layout = (embedding - min) / scale
|
||||
|
||||
# translate to center on both axis
|
||||
translate = 0.5 - ((max - min) / scale / 2)
|
||||
normalized_layout = normalized_layout + translate
|
||||
|
||||
normalized_layout = normalized_layout.astype(dtype=np.float32)
|
||||
return normalized_layout
|
||||
|
||||
def layout_to_fbs_matrix(self, fields):
|
||||
def layout_to_fbs_matrix(self, fields, spatial = None):
|
||||
"""
|
||||
return specified embeddings as a flatbuffer, using the cellxgene matrix fbs encoding.
|
||||
|
||||
@@ -380,7 +406,7 @@ class DataAdaptor(metaclass=ABCMeta):
|
||||
with ServerTiming.time("layout.query"):
|
||||
for ename in embeddings:
|
||||
embedding = self.get_embedding_array(ename, 2)
|
||||
normalized_layout = DataAdaptor.normalize_embedding(embedding)
|
||||
normalized_layout = DataAdaptor.normalize_embedding(embedding, ename == "spatial" and spatial)
|
||||
layout_data.append(pd.DataFrame(normalized_layout, columns=[f"{ename}_0", f"{ename}_1"]))
|
||||
|
||||
with ServerTiming.time("layout.encode"):
|
||||
|
||||
@@ -14,6 +14,7 @@ flatten-dict>=0.2.0
|
||||
fsspec>=0.4.4,<0.8.0
|
||||
gunicorn>=20.0.4
|
||||
h5py>=3.0.0
|
||||
matplotlib>=3.5.0
|
||||
numba>=0.51.2
|
||||
numpy>=1.17.5
|
||||
packaging>=20.0
|
||||
|
||||
Reference in New Issue
Block a user