Merge pull request #107 from jku-vds-lab/ch/prepDemoVersion

add dummy embedding controller in case we are in demo mode
jku-vds-lab · Oct 17, 2023 · 7a119fd · 7a119fd
2 parents 79adde3 + 422d071
commit 7a119fd
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Showing 3 changed files with 74 additions and 42 deletions.
diff --git a/.env b/.env
@@ -1,2 +1,2 @@
 # REACT_APP_CIME_BACKEND_URL=https://reaction-optimization.caleydoapp.org/
-# REACT_APP_CIME_BACKEND_URL=/api/reaction_cime
+# REACT_APP_CIME_BACKEND_URL=/api/reaction_cime
diff --git a/src/Overrides/Embeddings/DummyEmbeddingController.ts b/src/Overrides/Embeddings/DummyEmbeddingController.ts
@@ -0,0 +1,16 @@
+import { EmbeddingController } from 'projection-space-explorer';
+
+export class DummyEmbeddingController extends EmbeddingController {
+  init() {
+    // console.log('init');
+  }
+
+  override terminate() {
+    // console.log('terminate');
+  }
+
+  override supportsPause() {
+    // console.log('supportsPause');
+    return false;
+  }
+}
diff --git a/src/ReactionCIMEApp.tsx b/src/ReactionCIMEApp.tsx
@@ -15,9 +15,9 @@ import {
 import { connect, ConnectedProps, useDispatch } from 'react-redux';
 import HelpIcon from '@mui/icons-material/Help';
 import { IconButton, Tooltip } from '@mui/material';
-import { useVisynAppContext } from 'visyn_core/app';
+import { useVisynAppContext, VisynApp, VisynHeader } from 'visyn_core/app';
 import { Anchor, useMantineTheme } from '@mantine/core';
-import { VisynApp, VisynHeader } from 'visyn_core/app';
+
 import { BrowserRouter, useSearchParams } from 'react-router-dom';
 import { IClientConfig } from 'visyn_core/base';
 import { LineUpContext } from './LineUpContext';
@@ -41,6 +41,7 @@ import bayerLogo from './assets/bayer_logo.svg';
 import { BackendCSVLoader } from './Overrides/Dataset/BackendCSVLoader';
 import { TabDocumentation } from './Utility/TabDocumentation';
 import { BuildInfoContent, BuildInfoLogos } from './Utility/HeaderCustomization';
+import { DummyEmbeddingController } from './Overrides/Embeddings/DummyEmbeddingController';
 
 PluginRegistry.getInstance().registerPlugin(new ReactionsPlugin());
 
@@ -63,6 +64,7 @@ type PropsFromRedux = ConnectedProps<typeof connector>;
 type Props = PropsFromRedux;
 
 const ApplicationWrapper = connector(({ setMouseMoveFn, setMouseClickFn, resetViews }: Props) => {
+  const { clientConfig } = useVisynAppContext();
   const loadedDataset = usePSESelector((state) => state.dataset);
   const [searchParams, setSearchParams] = useSearchParams();
   const dispatch = useDispatch();
@@ -76,6 +78,46 @@ const ApplicationWrapper = connector(({ setMouseMoveFn, setMouseClickFn, resetVi
     }
   };
 
+  const embeddings = [
+    {
+      id: 'umapRemote',
+      name: 'UMAP',
+      settings: { nneighbors: true },
+      embController: new RemoteEmbeddingController('umap', startProjection),
+      description:
+        'Performs Uniform Manifold Approximation (UMAP) on the whole dataset using the chosen feature columns. This projects the high-dimensional dataset to a two-dimensional space that will then be shown as a scatterplot.',
+      tooltip:
+        'Performs Uniform Manifold Approximation (UMAP) on the whole dataset using the chosen feature columns. This method scales better than t-SNE with an increasing number of points.',
+    },
+    {
+      id: 'tsneRemote',
+      name: 't-SNE',
+      settings: { perplexity: true },
+      embController: new RemoteEmbeddingController('tsne', startProjection),
+      description:
+        'Performs t-distributed stochastic neighbor embedding (t-SNE) on the whole dataset using the chosen feature columns. This projects the high-dimensional dataset to a two-dimensional space that will then be shown as a scatterplot.',
+      tooltip: 'Performs t-distributed stochastic neighbor embedding (t-SNE) on the whole dataset using the chosen feature columns.',
+    },
+    {
+      id: 'pcaRemote',
+      name: 'PCA',
+      settings: {},
+      embController: new RemoteEmbeddingController('pca', startProjection),
+      description:
+        'Performs principal component analysis (PCA) on the whole dataset using the chosen feature columns. This linearly projects the high-dimensional dataset to a two-dimensional space that will then be shown as a scatterplot.',
+      tooltip: 'Performs principal component analysis (PCA) on the whole dataset using the chosen feature columns.',
+    },
+    {
+      id: 'rmOverlap',
+      name: 'Overlap removal',
+      settings: { hideSettings: true },
+      embController: new RemoteEmbeddingController('rmOverlap', startProjection),
+      tooltip: 'Removes overlapping points by moving them to the nearest non-overlapping position. This helps to reduce visual clutter.',
+      description:
+        'Removes overlapping points of the current projection by moving them to the nearest non-overlapping position. This is particularly useful for large datasets after a projection like t-SNE or UMAP has been triggered to reduce visual clutter.',
+    },
+  ];
+
   const onLoadProject = React.useCallback(
     (tableId: string) => {
       new BackendCSVLoader().resolvePath(
@@ -132,45 +174,19 @@ const ApplicationWrapper = connector(({ setMouseMoveFn, setMouseClickFn, resetVi
         baseUrl: ReactionCIMEBackendFromEnv.baseUrl,
       }}
       features={{
-        embeddings: [
-          {
-            id: 'umapRemote',
-            name: 'UMAP',
-            settings: { nneighbors: true },
-            embController: new RemoteEmbeddingController('umap', startProjection),
-            description:
-              'Performs Uniform Manifold Approximation (UMAP) on the whole dataset using the chosen feature columns. This projects the high-dimensional dataset to a two-dimensional space that will then be shown as a scatterplot.',
-            tooltip:
-              'Performs Uniform Manifold Approximation (UMAP) on the whole dataset using the chosen feature columns. This method scales better than t-SNE with an increasing number of points.',
-          },
-          {
-            id: 'tsneRemote',
-            name: 't-SNE',
-            settings: { perplexity: true },
-            embController: new RemoteEmbeddingController('tsne', startProjection),
-            description:
-              'Performs t-distributed stochastic neighbor embedding (t-SNE) on the whole dataset using the chosen feature columns. This projects the high-dimensional dataset to a two-dimensional space that will then be shown as a scatterplot.',
-            tooltip: 'Performs t-distributed stochastic neighbor embedding (t-SNE) on the whole dataset using the chosen feature columns.',
-          },
-          {
-            id: 'pcaRemote',
-            name: 'PCA',
-            settings: {},
-            embController: new RemoteEmbeddingController('pca', startProjection),
-            description:
-              'Performs principal component analysis (PCA) on the whole dataset using the chosen feature columns. This linearly projects the high-dimensional dataset to a two-dimensional space that will then be shown as a scatterplot.',
-            tooltip: 'Performs principal component analysis (PCA) on the whole dataset using the chosen feature columns.',
-          },
-          {
-            id: 'rmOverlap',
-            name: 'Overlap removal',
-            settings: { hideSettings: true },
-            embController: new RemoteEmbeddingController('rmOverlap', startProjection),
-            tooltip: 'Removes overlapping points by moving them to the nearest non-overlapping position. This helps to reduce visual clutter.',
-            description:
-              'Removes overlapping points of the current projection by moving them to the nearest non-overlapping position. This is particularly useful for large datasets after a projection like t-SNE or UMAP has been triggered to reduce visual clutter.',
-          },
-        ],
+        embeddings: clientConfig.publicVersion
+          ? [
+              {
+                id: 'noProjection',
+                name: 'Dummy Projection',
+                settings: { hideSettings: true },
+                embController: new DummyEmbeddingController(),
+                description:
+                  'Performs a projection on the whole dataset using the chosen feature columns. This projects the high-dimensional dataset to a two-dimensional space that will then be shown as a scatterplot. Projections are disabled in the Demo version.',
+                tooltip: 'Performs a Projection on the whole dataset using the chosen feature columns.',
+              },
+            ]
+          : embeddings,
         showVisibleProjections: false,
         showTrailSettings: false,
         enableFeatureWeighing: true,