add some better tests for indexing

Author: pattonw

explore.ipynb

@@ -40,13 +40,13 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "[[[ 0.44273075 -0.17070776 -0.7056614 ]\n",
-      "  [ 0.99363405 -0.7815089   1.3557754 ]\n",
-      "  [ 0.5848475   0.59523624 -1.4611949 ]]\n",
+      "[[[-0.03777862  0.34548774 -0.67263967]\n",
+      "  [ 0.3058082   0.29156172 -0.9545453 ]\n",
+      "  [ 0.70072883 -1.5905756   0.06846493]]\n",
       "\n",
-      " [[ 0.09116387 -1.4376557   0.5421799 ]\n",
-      "  [ 1.1627685   1.9053004   1.2552763 ]\n",
-      "  [ 0.2825793  -0.8584084  -1.4131508 ]]]\n"
+      " [[ 0.41885415  0.04308635 -0.457416  ]\n",
+      "  [-1.1773857  -0.15212785  1.2121304 ]\n",
+      "  [ 1.3966681  -0.16751394 -2.1650443 ]]]\n"
      ]
     }
    ],
@@ -57,36 +57,32 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": 5,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "[[[ 0.09116387 -1.4376557   0.5421799 ]\n",
-      "  [ 1.1627685   1.9053004   1.2552763 ]\n",
-      "  [ 0.2825793  -0.8584084  -1.4131508 ]]]\n"
+      "[[ 0.41885415  0.04308635 -0.457416  ]]\n"
      ]
     }
    ],
    "source": [
-    "array_sliced = Array(ds, (0, 0), (1, 1), adapter=slice(1,2))\n",
+    "array_sliced = Array(ds, (0, 0), (1, 1), adapter=(slice(1,2), 0, slice(None)))\n",
     "print(array_sliced[array_sliced.roi])"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": 6,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "[[[10.091164  8.562345 10.54218 ]\n",
-      "  [11.162768 11.9053   11.255277]\n",
-      "  [10.282579  9.141592  8.586849]]]\n"
+      "[[10.418854 10.043086  9.542584]]\n"
      ]
     }
    ],
@@ -97,30 +93,28 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": 7,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "[[[ 0.44273075 -0.17070776 -0.7056614 ]\n",
-      "  [ 0.99363405 -0.7815089   1.3557754 ]\n",
-      "  [ 0.5848475   0.59523624 -1.4611949 ]]\n",
-      "\n",
-      " [[10.091164    8.562345   10.54218   ]\n",
-      "  [11.162768   11.9053     11.255277  ]\n",
-      "  [10.282579    9.141592    8.586849  ]]]\n"
+      "[10.418854 10.043086]\n",
+      "['d1']\n"
      ]
     }
    ],
    "source": [
-    "print(ds[:])"
+    "array_sliced.adapt(np.s_[0])\n",
+    "array_sliced.adapt(np.s_[:2])\n",
+    "print(array_sliced[array_sliced.roi])\n",
+    "print(array_sliced.axis_names)"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
+   "execution_count": 8,
    "metadata": {},
    "outputs": [
     {
@@ -133,8 +127,8 @@
       "  [False False False]]\n",
       "\n",
       " [[ True  True  True]\n",
-      "  [ True  True  True]\n",
-      "  [ True  True  True]]]\n"
+      "  [False False False]\n",
+      "  [False False False]]]\n"
      ]
     }
    ],
@@ -146,7 +140,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
+   "execution_count": 9,
    "metadata": {},
    "outputs": [
     {
@@ -156,8 +150,8 @@
      "traceback": [
       "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
       "\u001b[0;31mRuntimeError\u001b[0m                              Traceback (most recent call last)",
-      "Cell \u001b[0;32mIn[8], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m \u001b[43mthresholded\u001b[49m\u001b[43m[\u001b[49m\u001b[43mthresholded\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mroi\u001b[49m\u001b[43m]\u001b[49m \u001b[38;5;241m=\u001b[39m thresholded[thresholded\u001b[38;5;241m.\u001b[39mroi] \u001b[38;5;241m+\u001b[39m \u001b[38;5;241m10\u001b[39m\n",
-      "File \u001b[0;32m~/Work/Packages/funlib.persistence/funlib/persistence/arrays/array.py:211\u001b[0m, in \u001b[0;36mArray.__setitem__\u001b[0;34m(self, key, value)\u001b[0m\n\u001b[1;32m    209\u001b[0m     da\u001b[38;5;241m.\u001b[39mstore(\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mdata[roi_slices], \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_source_data, regions\u001b[38;5;241m=\u001b[39mroi_slices)\n\u001b[1;32m    210\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[0;32m--> 211\u001b[0m     \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mRuntimeError\u001b[39;00m(\n\u001b[1;32m    212\u001b[0m         \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mThis array is not writeable since you have applied a custom callable \u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m    213\u001b[0m         \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124madapter that may or may not be invertable.\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m    214\u001b[0m     )\n",
+      "Cell \u001b[0;32mIn[9], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m \u001b[43mthresholded\u001b[49m\u001b[43m[\u001b[49m\u001b[43mthresholded\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mroi\u001b[49m\u001b[43m]\u001b[49m \u001b[38;5;241m=\u001b[39m thresholded[thresholded\u001b[38;5;241m.\u001b[39mroi] \u001b[38;5;241m+\u001b[39m \u001b[38;5;241m10\u001b[39m\n",
+      "File \u001b[0;32m~/Work/Packages/funlib.persistence/funlib/persistence/arrays/array.py:314\u001b[0m, in \u001b[0;36mArray.__setitem__\u001b[0;34m(self, key, value)\u001b[0m\n\u001b[1;32m    311\u001b[0m         da\u001b[38;5;241m.\u001b[39mstore(\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mdata[key], \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_source_data, regions\u001b[38;5;241m=\u001b[39mregion_slices)\n\u001b[1;32m    313\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[0;32m--> 314\u001b[0m     \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mRuntimeError\u001b[39;00m(\n\u001b[1;32m    315\u001b[0m         \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mThis array is not writeable since you have applied a custom callable \u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m    316\u001b[0m         \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124madapter that may or may not be invertable.\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m    317\u001b[0m     )\n",
       "\u001b[0;31mRuntimeError\u001b[0m: This array is not writeable since you have applied a custom callable adapter that may or may not be invertable."
      ]
     }

tests/test_array.py

@@ -20,34 +20,11 @@ def test_constructor():
     with pytest.raises(AssertionError):
         Array(data, offset, (1, 1))
 
-    # ROI not multiple of voxel size
-    # This is fine!
-    # with pytest.raises(AssertionError):
     Array(data, offset, (1, 1, 3))
-    # with pytest.raises(AssertionError):
     Array(data, offset, (1, 1, 4))
 
-    # ROI begin doesn't align with voxel size
-    # This is fine!
-    # with pytest.raises(AssertionError):
     Array(data, (1, 1, 1), (1, 1, 2))
 
-    # ROI shape doesn't align with voxel size
-    # No longer possible, we only specify the offset
-    # roi = Roi((0, 0, 0), (11, 11, 11))
-    # with pytest.raises(AssertionError):
-    #     Array(data, roi, (1, 1, 2))
-
-    # ROI outside of provided data
-    # No longer possible, we only provide the offset
-    # roi = Roi((0, 0, 0), (20, 20, 20))
-    # with pytest.raises(AssertionError):
-    #     Array(data, roi, (1, 1, 1))
-    # with pytest.raises(AssertionError):
-    #     Array(data, roi, (2, 2, 1))
-    # with pytest.raises(AssertionError):
-    #     Array(data, roi, (2, 2, 2), data_offset=(0, 0, 2))
-
 def test_dtype():
     for dtype in [np.float32, np.uint8, np.uint64]:
         assert Array(np.zeros((1,), dtype=dtype), (0,), (1,)).dtype == dtype
@@ -222,3 +199,20 @@ def test_adapters():
 
     a = Array(np.arange(0, 10*10).reshape(10, 2, 5), (0, 0), (1, 1), adapter=lambda x: x + 0.5)
     assert a.dtype == float
+
+def test_slicing():
+    a = Array(np.arange(0, 4*4).reshape(4, 2, 2), (0, 0), (1, 1))
+    
+    a.adapt(np.s_[0:3, 1, :])
+    assert a.shape == (3, 2)
+    assert a.axis_names == ["c0^", "d1"]
+    assert a.units == [""]
+
+    a.adapt(np.s_[2, :])
+    assert a.shape == (2,)
+    assert a.axis_names == ["d1"]
+    assert a.units == [""]
+
+    a[:] = 42
+
+    assert all([x == 42 for x in a._source_data[2, 1, :]]), a._source_data