Add support for int8 int16, float16 float32 float64 buffer arrays

Signed-off-by: martinRenou <[email protected]>

Author: martinRenou

ipycanvas/utils.py

@@ -41,11 +41,18 @@ def binary_image(ar):
 
 def array_to_binary(ar):
     """Turn a NumPy array into a binary buffer."""
+    # Unsupported int64 array JavaScript side
     if ar.dtype == np.int64:
         ar = ar.astype(np.int32)
 
-    if not ar.flags["C_CONTIGUOUS"]:  # make sure it's contiguous
+    # Unsupported float16 array JavaScript side
+    if ar.dtype == np.float16:
+        ar = ar.astype(np.float32)
+
+    # make sure it's contiguous
+    if not ar.flags["C_CONTIGUOUS"]:
         ar = np.ascontiguousarray(ar)
+
     return {'shape': ar.shape, 'dtype': str(ar.dtype)}, memoryview(ar)
 
 

src/utils.ts

@@ -1,8 +1,20 @@
 function getTypedArray(dataview: any, metadata: any) {
   switch (metadata.dtype) {
+    case 'int8':
+      return new Int8Array(dataview.buffer);
+      break;
+    case 'int16':
+      return new Int16Array(dataview.buffer);
+      break;
     case 'int32':
       return new Int32Array(dataview.buffer);
       break;
+    case 'float32':
+      return new Float32Array(dataview.buffer);
+      break;
+    case 'float64':
+      return new Float64Array(dataview.buffer);
+      break;
     default:
       throw 'Unknown dtype ' + metadata.dtype;
       break;