fix minor issues for docs creation

fractal-analytics-platform · Oct 9, 2024 · 44d05fc · 44d05fc
1 parent a11e12c
commit 44d05fc
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Showing 4 changed files with 23 additions and 25 deletions.
diff --git a/docs/notebooks/basic_usage.ipynb b/docs/notebooks/basic_usage.ipynb
@@ -93,7 +93,7 @@
    "source": [
     "print(\"List of Labels: \", ngff_image.label.list())\n",
     "\n",
-    "label_nuclei = ngff_image.label.get(\"nuclei\", path=\"0\")\n",
+    "label_nuclei = ngff_image.label.get_label(\"nuclei\", path=\"0\")\n",
     "print(f\"{label_nuclei.shape=}\")\n",
     "print(f\"{label_nuclei.pixel_size=}\")"
    ]
@@ -131,7 +131,7 @@
    "outputs": [],
    "source": [
     "# Loading a table\n",
-    "feature_table = ngff_image.table.get(\"regionprops_DAPI\")\n",
+    "feature_table = ngff_image.table.get_table(\"regionprops_DAPI\")\n",
     "feature_table.table"
    ]
   },
@@ -142,7 +142,7 @@
    "outputs": [],
    "source": [
     "# Loading a roi table\n",
-    "roi_table = ngff_image.table.get(\"FOV_ROI_table\")\n",
+    "roi_table = ngff_image.table.get_table(\"FOV_ROI_table\")\n",
     "\n",
     "print(f\"{roi_table.list_field_indexes=}\")\n",
     "print(f\"{roi_table.get_roi(\"FOV_1\")=}\")\n",
@@ -199,7 +199,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.12.6"
+   "version": "3.12.7"
   }
  },
  "nbformat": 4,

diff --git a/docs/notebooks/image.ipynb b/docs/notebooks/image.ipynb
@@ -68,10 +68,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "# Get image as a zarr.Array\n",
-    "array = image.array\n",
-    "print(f\"{array}\")\n",
-    "\n",
+    "# Get image as a dask array\n",
     "dask_array = image.on_disk_dask_array\n",
     "dask_array"
    ]
@@ -82,7 +79,7 @@
    "source": [
     "Note, directly accessing the `.on_disk_array` or `.on_disk_dask_array` attributes will load the image as stored in the file.\n",
     "\n",
-    "Since in principle the images can have different axes order. A safer way to access the image data is to use the `.array` method, which will return the image data in canonical order (TCZYX)."
+    "Since in principle the images can have different axes order. A safer way to access the image data is to use the `.get_array()` method, which will return the image data in canonical order (TCZYX)."
    ]
   },
   {
@@ -91,7 +88,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "image_numpy = image.array(c=0, x=slice(0, 250), y=slice(0, 250), preserve_dimensions=False, mode=\"numpy\")\n",
+    "image_numpy = image.get_array(c=0, x=slice(0, 250), y=slice(0, 250), preserve_dimensions=False, mode=\"numpy\")\n",
     "\n",
     "print(f\"{image_numpy.shape=}\")"
    ]
@@ -111,11 +108,11 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "roi_table = ngff_image.table.get(\"FOV_ROI_table\")\n",
+    "roi_table = ngff_image.table.get_table(\"FOV_ROI_table\")\n",
     "roi = roi_table.get_roi(\"FOV_1\")\n",
     "print(f\"{roi=}\")\n",
     "\n",
-    "image_roi_1 = image.array_from_roi(roi=roi, c=0, preserve_dimensions=True, mode=\"dask\")\n",
+    "image_roi_1 = image.get_array_from_roi(roi=roi, c=0, preserve_dimensions=True, mode=\"dask\")\n",
     "image_roi_1"
    ]
   },
@@ -138,10 +135,10 @@
     "print(f\"{image_2.pixel_size=}\")\n",
     "\n",
     "# Get roi for higher resolution image\n",
-    "image_1_roi_1 = image.array_from_roi(roi=roi, c=0, preserve_dimensions=False)\n",
+    "image_1_roi_1 = image.get_array_from_roi(roi=roi, c=0, preserve_dimensions=False)\n",
     "\n",
     "# Get roi for lower resolution image\n",
-    "image_2_roi_1 = image_2.array_from_roi(roi=roi, c=0, preserve_dimensions=False)\n",
+    "image_2_roi_1 = image_2.get_array_from_roi(roi=roi, c=0, preserve_dimensions=False)\n",
     "\n",
     "# Plot the two images side by side\n",
     "fig, axs = plt.subplots(1, 2, figsize=(10, 5))\n",
@@ -168,15 +165,15 @@
     "import numpy as np\n",
     "\n",
     "# Get a small slice of the image\n",
-    "small_slice = image.array(x=slice(1000, 2000), y=slice(1000, 2000))\n",
+    "small_slice = image.get_array(x=slice(1000, 2000), y=slice(1000, 2000))\n",
     "\n",
     "# Set the sample slice to zeros\n",
     "zeros_slice = np.zeros_like(small_slice)\n",
     "image.set_array(patch=zeros_slice, x=slice(1000, 2000), y=slice(1000, 2000))\n",
     "\n",
     "\n",
     "# Load the image from disk and show the edited image\n",
-    "nuclei = ngff_image.label.get(\"nuclei\")\n",
+    "nuclei = ngff_image.label.get_label(\"nuclei\")\n",
     "fig, axs = plt.subplots(1, 2, figsize=(10, 5))\n",
     "axs[0].imshow(image.on_disk_array[0, 0], cmap=\"gray\")\n",
     "axs[1].imshow(nuclei.on_disk_array[0])\n",
@@ -237,8 +234,8 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "label_0 = ngff_image.label.get(\"new_label\", path=\"0\")\n",
-    "label_2 = ngff_image.label.get(\"new_label\", path=\"2\")\n",
+    "label_0 = ngff_image.label.get_label(\"new_label\", path=\"0\")\n",
+    "label_2 = ngff_image.label.get_label(\"new_label\", path=\"2\")\n",
     "\n",
     "label_before_consolidation = label_2.on_disk_array[...]\n",
     "\n",
@@ -280,12 +277,12 @@
     "print(f\"List of feature table: {ngff_image.table.list(type='feature_table')}\")\n",
     "\n",
     "\n",
-    "nuclei = ngff_image.label.get('nuclei')\n",
+    "nuclei = ngff_image.label.get_label('nuclei')\n",
     "\n",
     "# Create a table with random features for each nuclei in each ROI\n",
     "list_of_records = []\n",
     "for roi in roi_table.list_rois:\n",
-    "    nuclei_in_roi = nuclei.array_from_roi(roi, mode='numpy')\n",
+    "    nuclei_in_roi = nuclei.get_array_from_roi(roi, mode='numpy')\n",
     "    for nuclei_id in np.unique(nuclei_in_roi)[1:]:\n",
     "        list_of_records.append(\n",
     "            {\"label\": nuclei_id,\n",
@@ -298,7 +295,7 @@
     "\n",
     "# Create a new feature table\n",
     "feat_table = ngff_image.table.new(name='new_feature_table',\n",
-    "                     region='../nuclei',\n",
+    "                     label_image='../nuclei',\n",
     "                     table_type='feature_table',\n",
     "                     overwrite=True)\n",
     "\n",

diff --git a/docs/notebooks/processing.ipynb b/docs/notebooks/processing.ipynb
@@ -82,7 +82,7 @@
     "print(\"MIP image loaded with shape:\", mip_image.shape)\n",
     "\n",
     "# Get a ROI table\n",
-    "roi_table = ngff_image.table.get(\"FOV_ROI_table\")\n",
+    "roi_table = ngff_image.table.get_table(\"FOV_ROI_table\")\n",
     "print(\"ROI table loaded with\", len(roi_table.list_rois), \"ROIs\")\n",
     "\n",
     "# For each ROI in the table\n",
@@ -91,7 +91,7 @@
     "# - set the data in the MIP image\n",
     "for roi in roi_table.list_rois:\n",
     "    print(f\" - Processing ROI {roi.infos.get(\"field_index\")}\")\n",
-    "    patch = source_image.array_from_roi(roi)\n",
+    "    patch = source_image.get_array_from_roi(roi)\n",
     "    mip_patch = patch.max(axis=1, keepdims=True)\n",
     "    mip_image.set_array_from_roi(patch=mip_patch, roi=roi)\n",
     "    \n",
@@ -124,12 +124,12 @@
     "# Get the MIP image at a lower resolution\n",
     "mip_image_2 = mip_ngff.get_image(path=\"2\")\n",
     "\n",
-    "image_before_consolidation = mip_image_2.array(c=0, z=0)\n",
+    "image_before_consolidation = mip_image_2.get_array(c=0, z=0)\n",
     "\n",
     "# Consolidate the pyramid\n",
     "mip_image.consolidate()\n",
     "\n",
-    "image_after_consolidation = mip_image_2.array(c=0, z=0)\n",
+    "image_after_consolidation = mip_image_2.get_array(c=0, z=0)\n",
     "\n",
     "fig, axs = plt.subplots(2, 1, figsize=(10, 5))\n",
     "axs[0].set_title(\"Before consolidation\")\n",

diff --git a/pyproject.toml b/pyproject.toml
@@ -54,6 +54,7 @@ test = ["zarr<3", "pytest", "pytest-cov"]
 dev2 = [
     "zarr<3",
     "fractal-tasks-core==1.3.1",
+    "scikit-image",
     "matplotlib",
     "ipython",
     "pytest",