From 70910f2d0591f3e17ca7023a80933254eaf8aa58 Mon Sep 17 00:00:00 2001 From: s214735 <s214735@dtu.dk> Date: Thu, 23 Jan 2025 14:43:23 +0100 Subject: [PATCH] some changes and some new additions --- docs/notebooks/local_thickness.ipynb | 50 +++-- docs/notebooks/ome_zarr.ipynb | 203 +++++++++--------- ...om DOI.ipynb => references from DOI.ipynb} | 0 qim3d/examples/blobs_256x256.png | Bin 0 -> 18957 bytes qim3d/io/_loading.py | 7 +- qim3d/viz/_data_exploration.py | 2 +- 6 files changed, 130 insertions(+), 132 deletions(-) rename docs/notebooks/{References from DOI.ipynb => references from DOI.ipynb} (100%) create mode 100644 qim3d/examples/blobs_256x256.png diff --git a/docs/notebooks/local_thickness.ipynb b/docs/notebooks/local_thickness.ipynb index 28701af3..66bff284 100644 --- a/docs/notebooks/local_thickness.ipynb +++ b/docs/notebooks/local_thickness.ipynb @@ -39,30 +39,34 @@ }, { "cell_type": "code", - "execution_count": 1, + "execution_count": null, "metadata": {}, "outputs": [ { - "ename": "ValueError", - "evalue": "\"Invalid path. Did you mean '../../qim3d/examples/fly_150x256x256.tif'?\"", - "output_type": "error", - "traceback": [ - "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", - "\u001b[0;31mValueError\u001b[0m Traceback (most recent call last)", - "Cell \u001b[0;32mIn[1], line 3\u001b[0m\n\u001b[1;32m 1\u001b[0m \u001b[38;5;28;01mimport\u001b[39;00m \u001b[38;5;21;01mqim3d\u001b[39;00m\n\u001b[1;32m 2\u001b[0m \u001b[38;5;66;03m# Load 2D image of blobs\u001b[39;00m\n\u001b[0;32m----> 3\u001b[0m img \u001b[38;5;241m=\u001b[39m \u001b[43mqim3d\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mio\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mload\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43m../../qim3d/examples/blobs_256x256.png\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mprogress_bar\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43;01mFalse\u001b[39;49;00m\u001b[43m)\u001b[49m\n\u001b[1;32m 5\u001b[0m \u001b[38;5;66;03m# Compute the local thickness of the blobs\u001b[39;00m\n\u001b[1;32m 6\u001b[0m img_lt \u001b[38;5;241m=\u001b[39m qim3d\u001b[38;5;241m.\u001b[39mprocessing\u001b[38;5;241m.\u001b[39mlocal_thickness(img, visualize\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mTrue\u001b[39;00m)\n", - "File \u001b[0;32m~/qim3d/qim3d/io/_loading.py:841\u001b[0m, in \u001b[0;36mload\u001b[0;34m(path, virtual_stack, dataset_name, return_metadata, contains, progress_bar, force_load, dim_order, **kwargs)\u001b[0m\n\u001b[1;32m 839\u001b[0m data \u001b[38;5;241m=\u001b[39m loader\u001b[38;5;241m.\u001b[39mload(path)\n\u001b[1;32m 840\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[0;32m--> 841\u001b[0m data \u001b[38;5;241m=\u001b[39m \u001b[43mloader\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mload\u001b[49m\u001b[43m(\u001b[49m\u001b[43mpath\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 843\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mlog_memory_info\u001b[39m(data):\n\u001b[1;32m 844\u001b[0m mem \u001b[38;5;241m=\u001b[39m Memory()\n", - "File \u001b[0;32m~/qim3d/qim3d/io/_loading.py:730\u001b[0m, in \u001b[0;36mDataLoader.load\u001b[0;34m(self, path)\u001b[0m\n\u001b[1;32m 728\u001b[0m suggestion \u001b[38;5;241m=\u001b[39m similar_paths[\u001b[38;5;241m0\u001b[39m] \u001b[38;5;66;03m# Get the closest match\u001b[39;00m\n\u001b[1;32m 729\u001b[0m message \u001b[38;5;241m=\u001b[39m \u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mInvalid path. Did you mean \u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;132;01m{\u001b[39;00msuggestion\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124m?\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[0;32m--> 730\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mValueError\u001b[39;00m(\u001b[38;5;28mrepr\u001b[39m(message))\n\u001b[1;32m 731\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[1;32m 732\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mValueError\u001b[39;00m(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mInvalid path\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n", - "\u001b[0;31mValueError\u001b[0m: \"Invalid path. Did you mean '../../qim3d/examples/fly_150x256x256.tif'?\"" + "name": "stderr", + "output_type": "stream", + "text": [ + "Input image is not binary. It will be binarized using Otsu's method with threshold: 69\n" ] + }, + { + "data": { + "image/png": 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+ "text/plain": [ + "<Figure size 1500x500 with 4 Axes>" + ] + }, + "metadata": {}, + "output_type": "display_data" } ], "source": [ "import qim3d\n", - "# Load 2D image of blobs\n", - "img = qim3d.io.load('../../qim3d/examples/blobs_256x256.png', progress_bar=False)\n", + "# Load 2D grayscale image of blobs\n", + "img = qim3d.io.load('../../qim3d/examples/blobs_256x256.png', progress_bar=False, log_memory=False)\n", "\n", "# Compute the local thickness of the blobs\n", - "img_lt = qim3d.processing.local_thickness(img, visualize=True)" + "img_lt = qim3d.processing.local_thickness(img, visualize=True, )" ] }, { @@ -77,7 +81,7 @@ }, { "cell_type": "code", - "execution_count": 60, + "execution_count": 2, "metadata": {}, "outputs": [ { @@ -90,7 +94,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "27daffa813ab472ba65368e3dbcb4d23", + "model_id": "488cb932d2e14df6b8934028b6f71203", "version_major": 2, "version_minor": 0 }, @@ -133,7 +137,7 @@ }, { "cell_type": "code", - "execution_count": 59, + "execution_count": 3, "metadata": {}, "outputs": [ { @@ -182,7 +186,7 @@ }, { "cell_type": "code", - "execution_count": 67, + "execution_count": 4, "metadata": {}, "outputs": [ { @@ -195,7 +199,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "64f9869d3f2147a9b6c6609722b9cf6f", + "model_id": "320731d6e08e43279cc982bfb700989b", "version_major": 2, "version_minor": 0 }, @@ -203,7 +207,7 @@ "interactive(children=(IntSlider(value=64, description='Slice', max=127), Output()), layout=Layout(align_items=…" ] }, - "execution_count": 67, + "execution_count": 4, "metadata": {}, "output_type": "execute_result" } @@ -234,13 +238,13 @@ }, { "cell_type": "code", - "execution_count": 68, + "execution_count": 5, "metadata": {}, "outputs": [ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "59e2ec8c08d14a52bc2e4e44b9b515e3", + "model_id": "6d870255e7fb4103ac373cfcb0c22a9a", "version_major": 2, "version_minor": 0 }, @@ -254,7 +258,7 @@ ], "source": [ "# Compute the local thickness of cement (input: binary mask)\n", - "mask_lt = qim3d.processing.local_thickness(mask, visualize=True, axis=0)\n" + "mask_lt = qim3d.processing.local_thickness(mask, visualize=True, axis=0)" ] } ], diff --git a/docs/notebooks/ome_zarr.ipynb b/docs/notebooks/ome_zarr.ipynb index 12aecab3..ec0562b0 100644 --- a/docs/notebooks/ome_zarr.ipynb +++ b/docs/notebooks/ome_zarr.ipynb @@ -15,7 +15,7 @@ }, { "cell_type": "code", - "execution_count": 49, + "execution_count": 1, "metadata": {}, "outputs": [ { @@ -66,7 +66,7 @@ " | \n", " | qim3d.viz.slicer_orthogonal(data, color_map=\"magma\")\n", " | ```\n", - " | \n", + " | \n", " | \n", " | Methods defined here:\n", " | \n", @@ -89,19 +89,20 @@ "import qim3d\n", "\n", "downloader = qim3d.io.Downloader()\n", - "help(downloader)\n" + "\n", + "help(downloader)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "After deciding to use the coral data, we fetch the data. We use the 'load_file' argument to load it while downloading it. Additionally, we can use the vizualisation tool `slicer_orthogonal` too explore the volume from three different axes." + "After deciding to use the okinawa crab volume, we fetch the data. We use the 'load_file' argument to load it while downloading it. Additionally, we can use the vizualisation tool `slicer_orthogonal` too explore the volume from three different axes." ] }, { "cell_type": "code", - "execution_count": 50, + "execution_count": 9, "metadata": {}, "outputs": [ { @@ -109,20 +110,20 @@ "output_type": "stream", "text": [ "File already downloaded:\n", - "/home/s214735/qim3d/docs/notebooks/Corals/Coral2_DOWNSAMPLED.tif\n", + "/home/s214735/qim3d/docs/notebooks/Crab/OkinawaCrab.tif\n", "\n", - "Loading Coral2_DOWNSAMPLED.tif\n" + "Loading OkinawaCrab.tif\n" ] }, { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "0745beff9bb54c64bf716f73168629f2", + "model_id": "c8510c263d2842e39e5067531823f451", "version_major": 2, "version_minor": 0 }, "text/plain": [ - "Loading: 0%| | 0.00B/153MB [00:00<?, ?B/s]" + "Loading: 0%| | 0.00B/1.86GB [00:00<?, ?B/s]" ] }, "metadata": {}, @@ -132,30 +133,13 @@ "name": "stderr", "output_type": "stream", "text": [ - "Loaded shape: (500, 400, 400)\n", + "Loaded shape: (995, 1014, 992)\n", "Using virtual stack\n" ] - }, - { - "data": { - "application/vnd.jupyter.widget-view+json": { - "model_id": "7179fe74113a4a98a2870334e1216b41", - "version_major": 2, - "version_minor": 0 - }, - "text/plain": [ - "HBox(children=(interactive(children=(IntSlider(value=250, description='Z', max=499), Output()), layout=Layout(…" - ] - }, - "execution_count": 50, - "metadata": {}, - "output_type": "execute_result" } ], "source": [ - "vol = downloader.Corals.Coral2_DOWNSAMPLED(load_file=True)\n", - "\n", - "qim3d.viz.slicer_orthogonal(vol, color_map=\"magma\")" + "vol = downloader.Crab.OkinawaCrab(load_file=True)" ] }, { @@ -164,36 +148,36 @@ "source": [ "Attempting to visualize the volume in a three-dimensional space will require a lot of computing power due to the size of the volume. However using the OME-Zarr data type, we can visualize it in chunks. Additionally we can save it in the .zarr format.\n", "\n", - "First we export the file using the `export_ome_zarr` method." + "First we export the file using the `export_ome_zarr` method. We set the downsample rate to 3, such that we have different scales of the volume." ] }, { "cell_type": "code", - "execution_count": 81, + "execution_count": 3, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ - "Exporting data to OME-Zarr format at coral.zarr\n", + "Exporting data to OME-Zarr format at crab.zarr\n", "Number of scales: 3\n", "Calculating the multi-scale pyramid\n", - "- Scale 0: (500, 400, 400)\n", - "- Scale 1: (250, 200, 200)\n", - "- Scale 2: (125, 100, 100)\n", + "- Scale 0: (995, 1014, 992)\n", + "- Scale 1: (332, 338, 331)\n", + "- Scale 2: (111, 113, 110)\n", "Writing data to disk\n" ] }, { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "2196a3a7db3c4b059d86a9e050608ad2", + "model_id": "c1e38c07b2d14b9b81f653dd085f157c", "version_major": 2, "version_minor": 0 }, "text/plain": [ - "Saving: 0%| | 0.00/166 [00:00<?, ?Chunks/s]" + "Saving: 0%| | 0.00/1.08k [00:00<?, ?Chunks/s]" ] }, "metadata": {}, @@ -210,10 +194,9 @@ ], "source": [ "qim3d.io.export_ome_zarr(\n", - " 'coral.zarr',\n", + " 'crab.zarr',\n", " vol,\n", - " chunk_size=200,\n", - " downsample_rate=2,\n", + " downsample_rate=3,\n", " replace=True)" ] }, @@ -221,18 +204,18 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "We can then use the `chunks` method to visualize the chunks from the volume. Here we have both options for exploring the volume slices or the entire 3D object." + "We can then use the `chunks` method to visualize the chunks from the volume. Here we have both options for exploring the volume slices or the entire 3D object. Additionally we can change the view dimension and the scale of the volume." ] }, { "cell_type": "code", - "execution_count": 52, + "execution_count": 4, "metadata": {}, "outputs": [ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "2af896bb7a0b453e9de1cc7767265dae", + "model_id": "36481522fd0b444c9940c1c028596544", "version_major": 2, "version_minor": 0 }, @@ -245,111 +228,119 @@ } ], "source": [ - "qim3d.viz.chunks('coral.zarr')" + "qim3d.viz.chunks('crab.zarr')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "After looking at the object, we see that some of it is obstructed by background noise. Therefore we attempt to remove that with a threshold, followed by another export and visualization of the volume:" + "If we wish to continue working on a downsampled version of the volume, we can load it back in using `import_ome_zarr`. Here we use the `scale` argument to decide what scale we with to import. By writing 'lowest', we can get the lowest resolution, and by writing 0 or 'highest' we can get the highest resolution. In this case we want the volume at scale 1 along with the highest resolution:" ] }, { "cell_type": "code", - "execution_count": 82, + "execution_count": 5, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ - "Exporting data to OME-Zarr format at coral_threshold.zarr\n", - "Number of scales: 3\n", - "Calculating the multi-scale pyramid\n", - "- Scale 0: (500, 400, 400)\n", - "- Scale 1: (250, 200, 200)\n", - "- Scale 2: (125, 100, 100)\n", - "Writing data to disk\n" - ] - }, - { - "data": { - "application/vnd.jupyter.widget-view+json": { - "model_id": "756f4bb77ec140bd85d3986e20b7942a", - "version_major": 2, - "version_minor": 0 - }, - "text/plain": [ - "Saving: 0%| | 0.00/83.0 [00:00<?, ?Chunks/s]" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ + "/home/s214735/miniconda3/envs/qim3d-env/lib/python3.11/site-packages/zarr/creation.py:614: UserWarning: ignoring keyword argument 'read_only'\n", + " compressor, fill_value = _kwargs_compat(compressor, fill_value, kwargs)\n", + "Data contains 3 scales:\n", + "- Scale 0: (995, 1014, 992)\n", + "- Scale 1: (332, 338, 331)\n", + "- Scale 2: (111, 113, 110)\n", "\n", - "All done!\n" + "Loading scale 1 with shape (332, 338, 331)\n", + "Data contains 3 scales:\n", + "- Scale 0: (995, 1014, 992)\n", + "- Scale 1: (332, 338, 331)\n", + "- Scale 2: (111, 113, 110)\n", + "\n", + "Loading scale 0 with shape (995, 1014, 992)\n" ] - }, + } + ], + "source": [ + "vol_lowscale = qim3d.io.import_ome_zarr('crab.zarr', scale=1)\n", + "vol_highscale = qim3d.io.import_ome_zarr('crab.zarr', scale='highest')" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Now we can visually inspect the volume at different scales. In this case, we can separate the first 256 voxels:" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [], + "source": [ + "vol_low = vol_lowscale[0:256, 0:256, 0:256]\n", + "vol_high = vol_highscale[256:512, 256:512, 256:512]" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Then we can visualize the volume along the three primary axes." + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "2200dadf1af24cf89fa60d9eefd6c8b2", + "model_id": "d4bd61011d794f14b4b8487666b2c8ea", "version_major": 2, "version_minor": 0 }, "text/plain": [ - "VBox(children=(HTML(value='<h2>Chunk Explorer</h2>'), HBox(children=(VBox(children=(Dropdown(description='OME-…" + "HBox(children=(interactive(children=(IntSlider(value=128, description='Z', max=255), Output()), _dom_classes=(…" ] }, + "execution_count": 7, "metadata": {}, - "output_type": "display_data" + "output_type": "execute_result" } ], "source": [ - "vol_t = vol > 30000\n", - "\n", - "qim3d.io.export_ome_zarr(\n", - " 'coral_threshold.zarr',\n", - " vol_t,\n", - " chunk_size=200,\n", - " downsample_rate=2,\n", - " replace=True)\n", - "\n", - "qim3d.viz.chunks('coral_threshold.zarr')" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "For next time the volume is to be used, we can import it easily using the `import_ome_zarr` method:" + "qim3d.viz.slicer_orthogonal(vol_low)" ] }, { "cell_type": "code", - "execution_count": 83, + "execution_count": 8, "metadata": {}, "outputs": [ { - "name": "stderr", - "output_type": "stream", - "text": [ - "Data contains 3 scales:\n", - "- Scale 0: (500, 400, 400)\n", - "- Scale 1: (250, 200, 200)\n", - "- Scale 2: (125, 100, 100)\n", - "\n", - "Loading scale 0 with shape (500, 400, 400)\n" - ] + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "927a9b89fe0f4e3598f6aad61451c254", + "version_major": 2, + "version_minor": 0 + }, + "text/plain": [ + "HBox(children=(interactive(children=(IntSlider(value=128, description='Z', max=255), Output()), _dom_classes=(…" + ] + }, + "execution_count": 8, + "metadata": {}, + "output_type": "execute_result" } ], "source": [ - "vol_t = qim3d.io.import_ome_zarr('coral_threshold.zarr')" + "qim3d.viz.slicer_orthogonal(vol_high)" ] } ], diff --git a/docs/notebooks/References from DOI.ipynb b/docs/notebooks/references from DOI.ipynb similarity index 100% rename from docs/notebooks/References from DOI.ipynb rename to docs/notebooks/references from DOI.ipynb diff --git a/qim3d/examples/blobs_256x256.png b/qim3d/examples/blobs_256x256.png new file mode 100644 index 0000000000000000000000000000000000000000..78dff8c93b55f07105044ac3b6934215d7c48d99 GIT binary patch literal 18957 zcmeAS@N?(olHy`uVBq!ia0y~yV2op6U`*s-U|?X7&6&H8fx+{Nr;B4q#hkZ$Bl}Y# 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memmap object if not isinstance( @@ -861,7 +863,8 @@ def load( log.info("Using virtual stack") else: log.warning("Virtual stack is not supported for this file format") - log_memory_info(data) + if log_memory: + log_memory_info(data) return data diff --git a/qim3d/viz/_data_exploration.py b/qim3d/viz/_data_exploration.py index 3544af79..eeae0b58 100644 --- a/qim3d/viz/_data_exploration.py +++ b/qim3d/viz/_data_exploration.py @@ -389,7 +389,7 @@ def slicer( continuous_update=True, ) slicer_obj = widgets.interactive(_slicer, slice_positions=position_slider) - slicer_obj.layout = widgets.Layout(align_items="flex-start") + #slicer_obj.layout = widgets.Layout(align_items="flex-start") return slicer_obj -- GitLab