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

* 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

client/src/util/stateManager/universe.js

@@ -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"])
   );