Checkpoint

client/src/components/graph/drawSpatialImageRegl.js

@@ -56,15 +56,15 @@ export default function drawSpatialImageRegl(regl) {
       a_position: [
         0,
         0,
-        0 + 2000,
+        0 + 1921,
         0,
         0,
         0 + 2000,
         0,
         0 + 2000,
-        0 + 2000,
+        0 + 1921,
         0,
-        0 + 2000,
+        0 + 1921,
         0 + 2000,
       ],
     },
@@ -73,7 +73,8 @@ export default function drawSpatialImageRegl(regl) {
       projView: regl.prop("projView"),
       u_image: regl.prop("spatialImageAsTexture"),
       color: [1, 0, 0, 1],
-      u_resolution: [2000, 2000],
+      u_resolution: [1921, 2000],
+      //   translate:
     },
 
     count: 6,

client/src/components/graph/graph.js

@@ -122,6 +122,7 @@ class Graph extends React.Component {
       positions[2 * i] = p[0];
       positions[2 * i + 1] = p[1];
     }
+    console.log({ transformed: positions });
     return positions;
   });
 
@@ -759,6 +760,7 @@ class Graph extends React.Component {
     const { positions, colors, flags, height, width } = asyncProps;
     this.cachedAsyncProps = asyncProps;
     const { pointBuffer, colorBuffer, flagBuffer } = this.state;
+    console.log({ pos2: positions });
     let needToRenderCanvas = false;
 
     if (height !== prevAsyncProps?.height || width !== prevAsyncProps?.width) {

server/common/rest.py

@@ -420,7 +420,7 @@ def spatial_image_get(request, data_adaptor):
         return abort_and_log(HTTPStatus.BAD_REQUEST, f"spatial information does not contain requested resolution '{resolution}'")
 
     response_image = io.BytesIO()
-    img = np.flipud(spatial[library_id]["images"][resolution])
+    img = spatial[library_id]["images"][resolution]
     matplotlib.pyplot.imsave(response_image, img)
     response_image.seek(0)
 

server/data_common/data_adaptor.py

@@ -363,7 +363,10 @@ class DataAdaptor(metaclass=ABCMeta):
 
         print(f"scale {scale}, translate {translate}")
 
-        normalized_layout = normalized_layout.astype(dtype=np.float32)
+        A = embedding * 0.17011142
+        A = np.column_stack([A[:, 0] / 1921, A[:, 1] / 2000])
+
+        normalized_layout = A.astype(dtype=np.float32)
         return normalized_layout
 
     def layout_to_fbs_matrix(self, fields):