Add image class

docs/source/_toc.yml

@@ -16,6 +16,11 @@ parts:
 
   - caption: Advanced
     chapters:
+    - file: advanced/labels/index
+      sections:
+      - file: advanced/labels/adding_labels
+      - file: advanced/labels/labels_metadata
+
     - file: advanced/sharding
     - file: advanced/build_custom_pyramid
     - file: advanced/write_hcs_plate
@@ -30,6 +35,7 @@ parts:
     chapters:
     - file: api
       sections:
+      - file: api/image
       - file: api/writer
       - file: api/reader
       - file: api/io

docs/source/advanced/build_custom_pyramid.ipynb

@@ -11,7 +11,7 @@
         "\n",
         "Multi-resolution pyramids are an integral part of ome-zarr image data\n",
         "and enable fast rendering of large images.\n",
-        "The entrypoints to writing ome-zarr images in ome-zarr-py ({py:func}`ome_zarr.writer.write_image` and {py:func}`ome_zarr.writer.write_labels`)\n",
+        "The entrypoints to writing ome-zarr images in ome-zarr-py ({py:func}`ome_zarr.classes.image.NgffMultiscales`, {py:func}`ome_zarr.writer.write_image` and {py:func}`ome_zarr.writer.write_labels`)\n",
         "build these pyramids under the hood as delayed dask arrays based on the settings for the scaling functions and scale factors.\n",
         "\n",
         "In this example, the downsampling will be applied in all spatial dimensions *except the z dimension*, which will be left at a scale factor of 1.\n",
@@ -20,36 +20,78 @@
     },
     {
       "cell_type": "code",
-      "execution_count": 16,
+      "execution_count": 1,
       "id": "642955b1",
       "metadata": {},
+      "outputs": [],
+      "source": [
+        "import numpy as np\n",
+        "\n",
+        "from ome_zarr import NgffImage, NgffMultiscales\n",
+        "from ome_zarr.writer import write_image\n",
+        "\n",
+        "scale_factors = [2, 4, 8]\n",
+        "rng = np.random.default_rng(0)\n",
+        "data = rng.poisson(lam=10, size=(64, 64, 64)).astype(np.uint8)"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 2,
+      "id": "a8f0defa",
+      "metadata": {},
       "outputs": [
         {
           "data": {
             "text/plain": [
               "[]"
             ]
           },
-          "execution_count": 16,
+          "execution_count": 2,
           "metadata": {},
           "output_type": "execute_result"
         }
       ],
       "source": [
-        "import numpy as np\n",
-        "\n",
-        "from ome_zarr.writer import write_image\n",
-        "\n",
-        "scale_factors = [2, 4, 8]\n",
-        "rng = np.random.default_rng(0)\n",
-        "data = rng.poisson(lam=10, size=(64, 64, 64)).astype(np.uint8)\n",
-        "\n",
         "write_image(\n",
         "    data,\n",
         "    \"test_ngff_image.ome.zarr\",\n",
         "    axes=\"zyx\",\n",
         "    scale_factors=scale_factors,\n",
-        "    )"
+        ")"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "id": "c3f7a5aa",
+      "metadata": {},
+      "source": [
+        "Or, if you choose to work with the {py:class}`ome_zarr.classes.image.NgffMultiscales` and {py:class}`ome_zarr.classes.image.NgffImage` classes directly,\n",
+        "they accept the same arguments:"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 3,
+      "id": "d0315903",
+      "metadata": {},
+      "outputs": [
+        {
+          "data": {
+            "text/plain": [
+              "[]"
+            ]
+          },
+          "execution_count": 3,
+          "metadata": {},
+          "output_type": "execute_result"
+        }
+      ],
+      "source": [
+        "ngff_image = NgffImage(data, axes=\"zyx\")\n",
+        "ngff_multiscales = NgffMultiscales(ngff_image, scale_factors=scale_factors)\n",
+        "\n",
+        "ngff_multiscales.to_ome_zarr(\"test_ngff_image_multiscales.ome.zarr\")"
       ]
     },
     {
@@ -66,7 +108,7 @@
     },
     {
       "cell_type": "code",
-      "execution_count": 17,
+      "execution_count": 4,
       "id": "60dcd278",
       "metadata": {},
       "outputs": [
@@ -76,7 +118,7 @@
               "[]"
             ]
           },
-          "execution_count": 17,
+          "execution_count": 4,
           "metadata": {},
           "output_type": "execute_result"
         }
@@ -108,7 +150,7 @@
     },
     {
       "cell_type": "code",
-      "execution_count": 18,
+      "execution_count": 5,
       "id": "877ab60d",
       "metadata": {},
       "outputs": [
@@ -136,7 +178,7 @@
     },
     {
       "cell_type": "code",
-      "execution_count": 19,
+      "execution_count": 6,
       "id": "859ca482",
       "metadata": {},
       "outputs": [
@@ -146,7 +188,7 @@
               "[]"
             ]
           },
-          "execution_count": 19,
+          "execution_count": 6,
           "metadata": {},
           "output_type": "execute_result"
         }
@@ -161,6 +203,38 @@
         ")\n"
       ]
     },
+    {
+      "cell_type": "markdown",
+      "id": "9b33ad31",
+      "metadata": {},
+      "source": [
+        "Again, the {py:class}`ome_zarr.NgffMultiscales` accepts the same argument:"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 7,
+      "id": "84c73869",
+      "metadata": {},
+      "outputs": [
+        {
+          "data": {
+            "text/plain": [
+              "[]"
+            ]
+          },
+          "execution_count": 7,
+          "metadata": {},
+          "output_type": "execute_result"
+        }
+      ],
+      "source": [
+        "ngff_image = NgffImage(data, axes=\"zyx\")\n",
+        "ngff_multiscales = NgffMultiscales(ngff_image, scale_factors=scale_factors, method=\"nearest\")\n",
+        "\n",
+        "ngff_multiscales.to_ome_zarr(\"test_ngff_image_multiscales.ome.zarr\")"
+      ]
+    },
     {
       "cell_type": "markdown",
       "id": "893a1b3b",
@@ -188,7 +262,7 @@
   ],
   "metadata": {
     "kernelspec": {
-      "display_name": "ngff-spec",
+      "display_name": "ome-zarr (3.12.12)",
       "language": "python",
       "name": "python3"
     },