From c8d275f84ac940232441afdbaab01b7955b92aff Mon Sep 17 00:00:00 2001 From: Demetris Roumis Date: Fri, 22 Nov 2024 12:24:23 -0800 Subject: [PATCH 01/35] volume example draft --- volumetric_imaging/anaconda-project.yml | 50 +++ volumetric_imaging/volumetric_imaging.ipynb | 446 ++++++++++++++++++++ 2 files changed, 496 insertions(+) create mode 100644 volumetric_imaging/anaconda-project.yml create mode 100644 volumetric_imaging/volumetric_imaging.ipynb diff --git a/volumetric_imaging/anaconda-project.yml b/volumetric_imaging/anaconda-project.yml new file mode 100644 index 000000000..470759e29 --- /dev/null +++ b/volumetric_imaging/anaconda-project.yml @@ -0,0 +1,50 @@ +name: volumetric_imaging +description: Display 3D image and segmentation data in a Jupyter notebook. + +examples_config: + created: 2024-11-22 + maintainers: + - "droumis" + labels: + - "panel" + categories: + - Neuroscience + title: "Volumetric Imaging" + deployments: + - command: notebook + # - command: dashboard + +user_fields: [examples_config] + +channels: +- conda-forge +- nodefaults + +packages: &pkgs +- notebook>=6.5.2,<7 # required +- python=3.11 +- panel +- jupyterlab +- pip +- pip: + - neuroglancer + +dependencies: *pkgs + +commands: + lab: + unix: jupyter lab volumetric_imaging.ipynb + windows: jupyter lab volumetric_imaging.ipynb + notebook: + notebook: volumetric_imaging.ipynb + dashboard: + unix: panel serve --rest-session-info --session-history -1 volumetric_imaging.ipynb --show + supports_http_options: true + +variables: {} + +platforms: +- linux-64 +- osx-64 +- win-64 +- osx-arm64 diff --git a/volumetric_imaging/volumetric_imaging.ipynb b/volumetric_imaging/volumetric_imaging.ipynb new file mode 100644 index 000000000..ffecf0556 --- /dev/null +++ b/volumetric_imaging/volumetric_imaging.ipynb @@ -0,0 +1,446 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "id": "3b7c8ca4-49bc-4673-9547-5571738972d6", + "metadata": { + "ExecuteTime": { + "end_time": "2024-03-29T17:25:02.532910Z", + "start_time": "2024-03-29T17:25:02.529856Z" + } + }, + "source": [ + "# Volumetric Imaging\n", + "\n", + "## Overview\n", + "\n", + "[Neuroglancer](https://github.com/google/neuroglancer) by Google is a WebGL-based viewer for volumetric data. It is capable of displaying arbitrary (non-axis-aligned) cross-sectional views of volumetric data, as well as 3D meshes and line-segment-based models (skeletons). It is commonly used to display massive datasets from techniques like electron microscopy (EM) in the field of neuroscience.\n", + "\n", + "Volumetric imaging techniques, such as EM, allow researchers to explore the fine structural details of biological specimens at nanometer resolutions. However, handling and visualizing these massive datasets pose significant challenges due to their size and complexity.\n", + "\n", + "While Neuroglancer provides a powerful browser-based tool for exploring very large volumes, it is typically used as a standalone application. Researchers often utilize Jupyter Notebooks to conduct reproducible research and encapsulate visualizations alongside code and text. Using [Panel](https://panel.holoviz.org/), we can integrate the Neuroglancer interface within the context of a research notebook or a larger HoloViz application.\n", + "\n", + "In this workflow, we will demonstrate how to embed Neuroglancer within a Panel application, highlighting how HoloViz tools can seamlessly integrate with third-party applications to create interactive and reproducible visualizations.\n", + "\n", + "### Use Cases\n", + "\n", + "- **Exploring Large Volumetric Datasets:** Integrate Neuroglancer within a Jupyter Notebook to explore volumetric data without leaving the notebook environment.\n", + "- **Combining Multiple Visualization Tools:** Use HoloViz Panel to combine Neuroglancer with other HoloViz components or custom plots.\n", + "- **Reproducible Research:** Embed the visualization directly within your code and documentation for easy sharing and collaboration.\n", + "\n", + "---\n", + "\n", + "## Prerequisites\n", + "\n", + "| Topic | Type | Notes |\n", + "| --- | --- | --- |\n", + "| [Panel Documentation](https://panel.holoviz.org/) | Prerequisite | Familiarity with Panel for building interactive apps |\n", + "\n", + "---" + ] + }, + { + "cell_type": "markdown", + "id": "a2f77667-f42b-42f6-a13d-5abbe589d7ea", + "metadata": { + "ExecuteTime": { + "end_time": "2024-03-29T17:25:02.532910Z", + "start_time": "2024-03-29T17:25:02.529856Z" + } + }, + "source": [ + "## Imports and Configuration" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "80f2ec05-50e3-4678-9323-09244ba5cde6", + "metadata": {}, + "outputs": [], + "source": [ + "import panel as pn\n", + "import neuroglancer\n", + "\n", + "pn.extension()" + ] + }, + { + "cell_type": "markdown", + "id": "64a50727-8c91-4d88-a82d-626e5a7715ba", + "metadata": {}, + "source": [ + "## Defining the `NeuroglancerNB` Class\n", + "\n", + "To embed Neuroglancer within a Panel application, we'll define a custom class `NeuroglancerNB`. This class creates a Panel viewable object that includes the Neuroglancer viewer embedded within an iframe, along with controls to load a Neuroglancer state from a URL, display the current state JSON, and generate shareable links." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "081e6201-bc6c-4afd-ab2a-f7e21de3d4c7", + "metadata": {}, + "outputs": [], + "source": [ + "class NeuroglancerNB(pn.viewable.Viewer):\n", + " \"\"\"\n", + " A HoloViz Panel app for visualizing and interacting with Neuroglancer viewers\n", + " within a Jupyter Notebook.\n", + "\n", + " This app supports loading from a parameterized Neuroglancer URL or an existing\n", + " `neuroglancer.viewer.Viewer` instance.\n", + " \"\"\"\n", + "\n", + " # Demo URL for loading an example dataset\n", + " DEMO_URL = \"https://neuroglancer-demo.appspot.com/#!%7B%22dimensions%22%3A%7B%22x%22%3A%5B6.000000000000001e-9%2C%22m%22%5D%2C%22y%22%3A%5B6.000000000000001e-9%2C%22m%22%5D%2C%22z%22%3A%5B3.0000000000000004e-8%2C%22m%22%5D%7D%2C%22position%22%3A%5B5029.42333984375%2C6217.5849609375%2C1182.5%5D%2C%22crossSectionScale%22%3A3.7621853549999242%2C%22projectionOrientation%22%3A%5B-0.05179581791162491%2C-0.8017329573631287%2C0.0831851214170456%2C-0.5895944833755493%5D%2C%22projectionScale%22%3A4699.372698097029%2C%22layers%22%3A%5B%7B%22type%22%3A%22image%22%2C%22source%22%3A%22precomputed%3A%2F%2Fgs%3A%2F%2Fneuroglancer-public-data%2Fkasthuri2011%2Fimage%22%2C%22tab%22%3A%22source%22%2C%22name%22%3A%22original-image%22%7D%2C%7B%22type%22%3A%22image%22%2C%22source%22%3A%22precomputed%3A%2F%2Fgs%3A%2F%2Fneuroglancer-public-data%2Fkasthuri2011%2Fimage_color_corrected%22%2C%22tab%22%3A%22source%22%2C%22name%22%3A%22corrected-image%22%7D%2C%7B%22type%22%3A%22segmentation%22%2C%22source%22%3A%22precomputed%3A%2F%2Fgs%3A%2F%2Fneuroglancer-public-data%2Fkasthuri2011%2Fground_truth%22%2C%22tab%22%3A%22source%22%2C%22selectedAlpha%22%3A0.63%2C%22notSelectedAlpha%22%3A0.14%2C%22segments%22%3A%5B%223208%22%2C%224901%22%2C%2213%22%2C%224965%22%2C%224651%22%2C%222282%22%2C%223189%22%2C%223758%22%2C%2215%22%2C%224027%22%2C%223228%22%2C%22444%22%2C%223207%22%2C%223224%22%2C%223710%22%5D%2C%22name%22%3A%22ground_truth%22%7D%5D%2C%22layout%22%3A%224panel%22%7D\"\n", + "\n", + " def __init__(\n", + " self,\n", + " source=None,\n", + " aspect_ratio=2.75,\n", + " show_state=False,\n", + " load_demo=False,\n", + " **params,\n", + " ):\n", + " \"\"\"\n", + " Initialize the NeuroglancerNB class.\n", + "\n", + " Args:\n", + " source (str or neuroglancer.viewer.Viewer, optional): Source for the initial state of the viewer,\n", + " which can be a URL string or an existing neuroglancer.viewer.Viewer instance.\n", + " If None, a new viewer will be initialized without a predefined state.\n", + " aspect_ratio (float, optional): The width to height ratio for the window-responsive Neuroglancer viewer.\n", + " Default is 2.75.\n", + " show_state (bool, optional): Provides a collapsible card widget under the viewer that displays the viewer's state.\n", + " Useful for debugging. Default is False.\n", + " load_demo (bool, optional): If True, loads the demo dataset upon initialization. Default is False.\n", + " **params: Additional parameters passed to the parent class.\n", + " \"\"\"\n", + " super().__init__(**params)\n", + "\n", + " # Determine if a source was provided\n", + " self.source_not_provided = False if source else True\n", + " self.show_state = show_state\n", + "\n", + " # Initialize the Neuroglancer viewer\n", + " self.viewer = (\n", + " source\n", + " if isinstance(source, neuroglancer.viewer.Viewer)\n", + " else neuroglancer.Viewer()\n", + " )\n", + "\n", + " # Set up the UI components\n", + " self._setup_ui_components(aspect_ratio=aspect_ratio)\n", + "\n", + " # Configure the viewer\n", + " self._configure_viewer()\n", + "\n", + " # Set up callbacks for interactivity\n", + " self._setup_callbacks()\n", + "\n", + " # If a source URL is provided, initialize the viewer from the URL\n", + " if source and not isinstance(source, neuroglancer.viewer.Viewer):\n", + " self._initialize_viewer_from_url(source)\n", + "\n", + " # Load the demo dataset if requested\n", + " if load_demo:\n", + " self.demo_button.clicks += 1\n", + "\n", + " def _initialize_viewer_from_url(self, source: str):\n", + " \"\"\"Initialize the viewer state from a URL.\"\"\"\n", + " self.url_input.value = source\n", + " self._load_state_from_url(source)\n", + "\n", + " def _setup_ui_components(self, aspect_ratio):\n", + " \"\"\"Set up the UI components for the application.\"\"\"\n", + " # Text input for the Neuroglancer URL\n", + " self.url_input = pn.widgets.TextInput(\n", + " placeholder=\"Enter a Neuroglancer URL and click Load\",\n", + " name=\"Input URL\",\n", + " width=700,\n", + " )\n", + "\n", + " # Buttons for loading and demo dataset\n", + " self.load_button = pn.widgets.Button(\n", + " name=\"Load\", button_type=\"primary\", width=75\n", + " )\n", + " self.demo_button = pn.widgets.Button(\n", + " name=\"Demo\", button_type=\"warning\", width=75\n", + " )\n", + "\n", + " # JSON pane to display the viewer state\n", + " self.json_pane = pn.pane.JSON(\n", + " {}, theme=\"light\", depth=2, name=\"Viewer State\", height=800, width=350\n", + " )\n", + "\n", + " # Markdown panes to display shareable and local URLs\n", + " self.shareable_url_pane = pn.pane.Markdown(\"**Shareable URL:**\")\n", + " self.local_url_pane = pn.pane.Markdown(\"**Local URL:**\")\n", + "\n", + " # HTML pane to embed the Neuroglancer viewer via iframe\n", + " self.iframe = pn.pane.HTML(\n", + " sizing_mode=\"stretch_both\",\n", + " aspect_ratio=aspect_ratio,\n", + " min_height=800,\n", + " styles={\"resize\": \"both\", \"overflow\": \"hidden\"},\n", + " )\n", + "\n", + " def _configure_viewer(self):\n", + " \"\"\"Configure the Neuroglancer viewer.\"\"\"\n", + " # Update the local URL and iframe content\n", + " self._update_local_url()\n", + " self._update_iframe_with_local_url()\n", + "\n", + " def _setup_callbacks(self):\n", + " \"\"\"Set up callbacks for interactivity.\"\"\"\n", + " self.load_button.on_click(self._on_load_button_clicked)\n", + " self.demo_button.on_click(self._on_demo_button_clicked)\n", + "\n", + " # Callback for when the viewer state changes\n", + " self.viewer.shared_state.add_changed_callback(self._on_viewer_state_changed)\n", + "\n", + " def _on_demo_button_clicked(self, event):\n", + " \"\"\"Load the demo dataset when the Demo button is clicked.\"\"\"\n", + " self.url_input.value = self.DEMO_URL\n", + " self._load_state_from_url(self.url_input.value)\n", + "\n", + " def _on_load_button_clicked(self, event):\n", + " \"\"\"Load the viewer state from the provided URL.\"\"\"\n", + " self._load_state_from_url(self.url_input.value)\n", + "\n", + " def _load_state_from_url(self, url):\n", + " \"\"\"Load the viewer state from a URL.\"\"\"\n", + " try:\n", + " new_state = self._parse_state_from_url(url)\n", + " self.viewer.set_state(new_state)\n", + " except Exception as e:\n", + " print(f\"Error loading Neuroglancer state: {e}\")\n", + "\n", + " def _parse_state_from_url(self, url):\n", + " \"\"\"Parse the viewer state from a Neuroglancer URL.\"\"\"\n", + " return neuroglancer.parse_url(url)\n", + "\n", + " def _on_viewer_state_changed(self):\n", + " \"\"\"Update the UI when the viewer state changes.\"\"\"\n", + " self._update_shareable_url()\n", + " self._update_json_pane()\n", + "\n", + " def _update_shareable_url(self):\n", + " \"\"\"Update the shareable URL pane.\"\"\"\n", + " shareable_url = neuroglancer.to_url(self.viewer.state)\n", + " self.shareable_url_pane.object = self._generate_dropdown_markup(\n", + " \"Shareable URL\", shareable_url\n", + " )\n", + "\n", + " def _update_local_url(self):\n", + " \"\"\"Update the local URL pane.\"\"\"\n", + " self.local_url_pane.object = self._generate_dropdown_markup(\n", + " \"Local URL\", self.viewer.get_viewer_url()\n", + " )\n", + "\n", + " def _update_iframe_with_local_url(self):\n", + " \"\"\"Embed the viewer in the iframe.\"\"\"\n", + " iframe_style = (\n", + " 'frameborder=\"0\" scrolling=\"no\" marginheight=\"0\" marginwidth=\"0\" '\n", + " 'style=\"width:100%; height:100%; min-width:500px; min-height:500px;\"'\n", + " )\n", + " self.iframe.object = (\n", + " f''\n", + " )\n", + "\n", + " def _update_json_pane(self):\n", + " \"\"\"Update the JSON pane with the current viewer state.\"\"\"\n", + " self.json_pane.object = self.viewer.state.to_json()\n", + "\n", + " def _generate_dropdown_markup(self, title, url):\n", + " \"\"\"Generate HTML markup for dropdown links.\"\"\"\n", + " return f\"\"\"\n", + "
\n", + " {title}:\n", + " {url}\n", + "
\n", + " \"\"\"\n", + "\n", + " def __panel__(self):\n", + " \"\"\"Define how the class is rendered in a Panel application.\"\"\"\n", + " # Layout for controls (only visible if no source is provided)\n", + " controls_layout = pn.Column(\n", + " pn.Row(self.demo_button, self.load_button),\n", + " pn.Row(self.url_input),\n", + " visible=self.source_not_provided,\n", + " )\n", + " # Layout for URL links\n", + " links_layout = pn.Column(self.local_url_pane, self.shareable_url_pane)\n", + "\n", + " state_widget = pn.Card(\n", + " self.json_pane,\n", + " title=\"State\",\n", + " collapsed=False,\n", + " visible=self.show_state,\n", + " styles={\"background\": \"WhiteSmoke\"},\n", + " max_width=350\n", + " )\n", + " # Combine all components into a single layout\n", + " return pn.Column(\n", + " controls_layout,\n", + " links_layout,\n", + " pn.Row(state_widget, self.iframe))\n" + ] + }, + { + "cell_type": "markdown", + "id": "4dac819c-c3e9-4a51-be83-bf54b28f62b2", + "metadata": {}, + "source": [ + "## Approach 1: Launching a New Viewer and Loading State from URL\n" + ] + }, + { + "cell_type": "markdown", + "id": "58f1de1e-d307-4e6a-8f49-ec7f4a04cc24", + "metadata": {}, + "source": [ + "In this workflow, we'll initialize a new Neuroglancer viewer and load a dataset using a parameterized URL. This allows us to explore different datasets by simply changing the URL.\n", + "\n", + "To launch an empty viewer, simply omit the `source` input. You can then use the GUI to insert and load from a parameterized URL to set the state of the new viewer. Click the **Demo** button or pass `load_demo=True` to insert an example URL dataset. You can find other demo links on the [Neuroglancer repository](https://github.com/google/neuroglancer#examples).\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "b5fb5bf4-83af-4180-b061-a7eac0f5ad6a", + "metadata": {}, + "outputs": [], + "source": [ + "ng_app = NeuroglancerNB(show_state=True, load_demo=True)" + ] + }, + { + "cell_type": "markdown", + "id": "3f41e92d-1e9c-4fc5-8e7b-649f758df098", + "metadata": {}, + "source": [ + "### Usage Instructions:\n", + "\n", + "1. **Load the Demo Dataset:**\n", + " - Since we passed `load_demo=True`, we'll skip this step, but otherwise you could have clicked the **Demo** button to load the example dataset.\n", + "\n", + "2. **Explore the Viewer:**\n", + " - Use the mouse and keyboard to navigate through the volumetric data.\n", + " - Adjust cross-sectional views, zoom, and rotate the 3D view.\n", + "\n", + "3. **View the Viewer State:**\n", + " - Click on the **State** card to expand and view the JSON representation of the current viewer state.\n", + " \n", + "5. **Load a Custom Dataset:**\n", + " - Enter a Neuroglancer URL in the **Input URL** field.\n", + " - Click **Load** to visualize the dataset.\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "28700ea9-6eed-4d4c-9028-0c2ba8058d75", + "metadata": {}, + "outputs": [], + "source": [ + "ng_app" + ] + }, + { + "cell_type": "markdown", + "id": "afa26a39-e22f-4ae8-880e-559350e1bfc9", + "metadata": {}, + "source": [ + "## Approach 2: Displaying a Pre-specified Viewer" + ] + }, + { + "cell_type": "markdown", + "id": "2717e7f4-f098-4ba8-87a5-1e673496d740", + "metadata": {}, + "source": [ + "Alternatively, you can provide a pre-configured `neuroglancer.viewer.Viewer` object as the `source` to display that viewer in the notebook. This allows you to set up the viewer programmatically and then embed it.\n", + "\n", + "- We create a Neuroglancer `Viewer` instance.\n", + "- Within a transaction (`viewer.txn()`), we add layers to the viewer:\n", + " - An image layer from a precomputed data source.\n", + " - A segmentation layer.\n", + "- We then pass this configured viewer to our `NeuroglancerNB` class.\n", + "- The viewer is embedded within the Panel app and displayed in the notebook.\n", + "\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "27bbb3a0-270c-4f8b-ac16-b60a764f1cfc", + "metadata": {}, + "outputs": [], + "source": [ + "# Create a Neuroglancer viewer and configure it\n", + "viewer = neuroglancer.Viewer()\n", + "\n", + "with viewer.txn() as s:\n", + " # Add an image layer from a precomputed data source\n", + " s.layers[\"image\"] = neuroglancer.ImageLayer(\n", + " source=\"precomputed://gs://neuroglancer-janelia-flyem-hemibrain/emdata/clahe_yz/jpeg\",\n", + " )\n", + " # Add a segmentation layer\n", + " s.layers[\"segmentation\"] = neuroglancer.SegmentationLayer(\n", + " source=\"precomputed://gs://neuroglancer-janelia-flyem-hemibrain/v1.1/segmentation\",\n", + " )\n", + "\n", + "# Embed the viewer within the Panel app\n", + "ng_app_2 = NeuroglancerNB(source=viewer, show_state=True)\n", + "\n", + "# Display the app\n", + "ng_app_2" + ] + }, + { + "cell_type": "markdown", + "id": "1247343e-44b5-46a8-a05d-511d1a392e9d", + "metadata": {}, + "source": [ + "## Next Steps\n", + "\n", + "- **Explore Your Own Datasets:** Modify the code to load and visualize your own volumetric datasets.\n", + "- **Extend the Application:** Integrate additional HoloViews plots or other Panel components to create a more comprehensive application. For instance, you might add controls for adjusting visualization parameters.\n", + "- **Share and Collaborate:** Use the shareable URLs generated by the app to share specific views or states with collaborators. Embedding the application in a notebook ensures that your analysis and visualizations are reproducible and shareable.\n", + "\n", + "---\n", + "\n", + "## Resources\n", + "\n", + "| Resource | Description |\n", + "| --- | --- |\n", + "| [Neuroglancer GitHub Repository](https://github.com/google/neuroglancer) | Neuroglancer source code and documentation |\n", + "| [Neuroglancer Python Integration](https://github.com/google/neuroglancer/tree/master/python) | Python interface for controlling Neuroglancer |\n", + "\n", + "---\n" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.11.10" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} From 84e97c36c13ec7f436883fcb3e8c32d5eef3b178 Mon Sep 17 00:00:00 2001 From: Demetris Roumis Date: Sat, 23 Nov 2024 12:14:43 -0800 Subject: [PATCH 02/35] lock --- volumetric_imaging/anaconda-project-lock.yml | 417 +++++++++++++++++++ 1 file changed, 417 insertions(+) create mode 100644 volumetric_imaging/anaconda-project-lock.yml diff --git a/volumetric_imaging/anaconda-project-lock.yml b/volumetric_imaging/anaconda-project-lock.yml new file mode 100644 index 000000000..75221c719 --- /dev/null +++ b/volumetric_imaging/anaconda-project-lock.yml @@ -0,0 +1,417 @@ +# This is an Anaconda project lock file. +# The lock file locks down exact versions of all your dependencies. +# +# In most cases, this file is automatically maintained by the `anaconda-project` command or GUI tools. +# It's best to keep this file in revision control (such as git or svn). +# The file is in YAML format, please see http://www.yaml.org/start.html for more. +# + +# +# Set to false to ignore locked versions. +# +locking_enabled: true + +# +# A key goes in here for each env spec. +# +env_specs: + default: + locked: true + env_spec_hash: 9416c0a974d1a3397dd9a05e428fac41c98afeac + platforms: + - linux-64 + - osx-64 + - osx-arm64 + - win-64 + packages: + all: + - anyio=4.6.2.post1=pyhd8ed1ab_0 + - argon2-cffi=23.1.0=pyhd8ed1ab_0 + - arrow=1.3.0=pyhd8ed1ab_0 + - asttokens=2.4.1=pyhd8ed1ab_0 + - async-lru=2.0.4=pyhd8ed1ab_0 + - attrs=24.2.0=pyh71513ae_0 + - babel=2.16.0=pyhd8ed1ab_0 + - beautifulsoup4=4.12.3=pyha770c72_0 + - bleach=6.2.0=pyhd8ed1ab_0 + - bokeh=3.6.1=pyhd8ed1ab_0 + - cached-property=1.5.2=hd8ed1ab_1 + - cached_property=1.5.2=pyha770c72_1 + - certifi=2024.8.30=pyhd8ed1ab_0 + - charset-normalizer=3.4.0=pyhd8ed1ab_0 + - colorama=0.4.6=pyhd8ed1ab_0 + - comm=0.2.2=pyhd8ed1ab_0 + - decorator=5.1.1=pyhd8ed1ab_0 + - defusedxml=0.7.1=pyhd8ed1ab_0 + - entrypoints=0.4=pyhd8ed1ab_0 + - exceptiongroup=1.2.2=pyhd8ed1ab_0 + - executing=2.1.0=pyhd8ed1ab_0 + - fqdn=1.5.1=pyhd8ed1ab_0 + - h11=0.14.0=pyhd8ed1ab_0 + - h2=4.1.0=pyhd8ed1ab_0 + - hpack=4.0.0=pyh9f0ad1d_0 + - httpcore=1.0.7=pyh29332c3_1 + - httpx=0.27.2=pyhd8ed1ab_0 + - hyperframe=6.0.1=pyhd8ed1ab_0 + - idna=3.10=pyhd8ed1ab_0 + - importlib-metadata=8.5.0=pyha770c72_0 + - importlib_resources=6.4.5=pyhd8ed1ab_0 + - ipython_genutils=0.2.0=pyhd8ed1ab_1 + - isoduration=20.11.0=pyhd8ed1ab_0 + - jedi=0.19.2=pyhff2d567_0 + - jinja2=3.1.4=pyhd8ed1ab_0 + - json5=0.9.28=pyhff2d567_0 + - jsonschema-specifications=2024.10.1=pyhd8ed1ab_0 + - jsonschema-with-format-nongpl=4.23.0=hd8ed1ab_0 + - jsonschema=4.23.0=pyhd8ed1ab_0 + - jupyter-lsp=2.2.5=pyhd8ed1ab_0 + - jupyter_client=7.4.9=pyhd8ed1ab_0 + - jupyter_events=0.10.0=pyhd8ed1ab_0 + - jupyter_server=2.14.2=pyhd8ed1ab_0 + - jupyter_server_terminals=0.5.3=pyhd8ed1ab_0 + - jupyterlab=4.3.1=pyhff2d567_0 + - jupyterlab_pygments=0.3.0=pyhd8ed1ab_1 + - jupyterlab_server=2.27.3=pyhd8ed1ab_0 + - linkify-it-py=2.0.3=pyhd8ed1ab_0 + - markdown-it-py=3.0.0=pyhd8ed1ab_0 + - markdown=3.6=pyhd8ed1ab_0 + - matplotlib-inline=0.1.7=pyhd8ed1ab_0 + - mdit-py-plugins=0.4.2=pyhd8ed1ab_0 + - mdurl=0.1.2=pyhd8ed1ab_0 + - mistune=3.0.2=pyhd8ed1ab_0 + - nbclassic=1.1.0=pyhd8ed1ab_0 + - nbclient=0.10.0=pyhd8ed1ab_0 + - nbconvert-core=7.16.4=pyhd8ed1ab_1 + - nbformat=5.10.4=pyhd8ed1ab_0 + - nest-asyncio=1.6.0=pyhd8ed1ab_0 + - notebook-shim=0.2.4=pyhd8ed1ab_0 + - notebook=6.5.7=pyha770c72_0 + - overrides=7.7.0=pyhd8ed1ab_0 + - packaging=24.2=pyhff2d567_1 + - pandocfilters=1.5.0=pyhd8ed1ab_0 + - panel=1.5.4=pyhd8ed1ab_0 + - param=2.1.1=pyhff2d567_0 + - parso=0.8.4=pyhd8ed1ab_0 + - pickleshare=0.7.5=py_1003 + - pip=24.3.1=pyh8b19718_0 + - pkgutil-resolve-name=1.3.10=pyhd8ed1ab_1 + - platformdirs=4.3.6=pyhd8ed1ab_0 + - prometheus_client=0.21.0=pyhd8ed1ab_0 + - prompt-toolkit=3.0.48=pyha770c72_0 + - pure_eval=0.2.3=pyhd8ed1ab_0 + - pycparser=2.22=pyhd8ed1ab_0 + - pygments=2.18.0=pyhd8ed1ab_0 + - python-dateutil=2.9.0.post0=pyhff2d567_0 + - python-fastjsonschema=2.20.0=pyhd8ed1ab_0 + - python-json-logger=2.0.7=pyhd8ed1ab_0 + - python-tzdata=2024.2=pyhd8ed1ab_0 + - python_abi=3.11=5_cp311 + - pytz=2024.1=pyhd8ed1ab_0 + - pyviz_comms=3.0.3=pyhd8ed1ab_0 + - referencing=0.35.1=pyhd8ed1ab_0 + - requests=2.32.3=pyhd8ed1ab_0 + - rfc3339-validator=0.1.4=pyhd8ed1ab_0 + - rfc3986-validator=0.1.1=pyh9f0ad1d_0 + - setuptools=75.6.0=pyhff2d567_0 + - six=1.16.0=pyh6c4a22f_0 + - sniffio=1.3.1=pyhd8ed1ab_0 + - soupsieve=2.5=pyhd8ed1ab_1 + - stack_data=0.6.2=pyhd8ed1ab_0 + - tinycss2=1.4.0=pyhd8ed1ab_0 + - tomli=2.1.0=pyhff2d567_0 + - tqdm=4.67.0=pyhd8ed1ab_0 + - traitlets=5.14.3=pyhd8ed1ab_0 + - types-python-dateutil=2.9.0.20241003=pyhff2d567_0 + - typing-extensions=4.12.2=hd8ed1ab_0 + - typing_extensions=4.12.2=pyha770c72_0 + - typing_utils=0.1.0=pyhd8ed1ab_0 + - tzdata=2024b=hc8b5060_0 + - uc-micro-py=1.0.3=pyhd8ed1ab_0 + - uri-template=1.3.0=pyhd8ed1ab_0 + - urllib3=2.2.3=pyhd8ed1ab_0 + - wcwidth=0.2.13=pyhd8ed1ab_0 + - webcolors=24.8.0=pyhd8ed1ab_0 + - webencodings=0.5.1=pyhd8ed1ab_2 + - websocket-client=1.8.0=pyhd8ed1ab_0 + - wheel=0.45.1=pyhd8ed1ab_0 + - xyzservices=2024.9.0=pyhd8ed1ab_0 + - zipp=3.21.0=pyhd8ed1ab_0 + unix: + - ipython=8.29.0=pyh707e725_0 + - jupyter_core=5.7.2=pyh31011fe_1 + - pexpect=4.9.0=pyhd8ed1ab_0 + - ptyprocess=0.7.0=pyhd3deb0d_0 + - pysocks=1.7.1=pyha2e5f31_6 + osx: + - appnope=0.1.4=pyhd8ed1ab_0 + - ipykernel=6.29.5=pyh57ce528_0 + - send2trash=1.8.3=pyh31c8845_0 + - terminado=0.18.1=pyh31c8845_0 + linux-64: + - _libgcc_mutex=0.1=conda_forge + - _openmp_mutex=4.5=2_gnu + - argon2-cffi-bindings=21.2.0=py311h9ecbd09_5 + - brotli-python=1.1.0=py311hfdbb021_2 + - bzip2=1.0.8=h4bc722e_7 + - ca-certificates=2024.8.30=hbcca054_0 + - cffi=1.17.1=py311hf29c0ef_0 + - contourpy=1.3.1=py311hd18a35c_0 + - debugpy=1.8.9=py311hfdbb021_0 + - freetype=2.12.1=h267a509_2 + - ipykernel=6.29.5=pyh3099207_0 + - jsonpointer=3.0.0=py311h38be061_1 + - keyutils=1.6.1=h166bdaf_0 + - krb5=1.21.3=h659f571_0 + - lcms2=2.16=hb7c19ff_0 + - ld_impl_linux-64=2.43=h712a8e2_2 + - lerc=4.0.0=h27087fc_0 + - libblas=3.9.0=25_linux64_openblas + - libcblas=3.9.0=25_linux64_openblas + - libdeflate=1.22=hb9d3cd8_0 + - libedit=3.1.20191231=he28a2e2_2 + - libexpat=2.6.4=h5888daf_0 + - libffi=3.4.2=h7f98852_5 + - libgcc-ng=14.2.0=h69a702a_1 + - libgcc=14.2.0=h77fa898_1 + - libgfortran5=14.2.0=hd5240d6_1 + - libgfortran=14.2.0=h69a702a_1 + - libgomp=14.2.0=h77fa898_1 + - libjpeg-turbo=3.0.0=hd590300_1 + - liblapack=3.9.0=25_linux64_openblas + - libnsl=2.0.1=hd590300_0 + - libopenblas=0.3.28=pthreads_h94d23a6_1 + - libpng=1.6.44=hadc24fc_0 + - libsodium=1.0.20=h4ab18f5_0 + - libsqlite=3.47.0=hadc24fc_1 + - libstdcxx-ng=14.2.0=h4852527_1 + - libstdcxx=14.2.0=hc0a3c3a_1 + - libtiff=4.7.0=he137b08_1 + - libuuid=2.38.1=h0b41bf4_0 + - libwebp-base=1.4.0=hd590300_0 + - libxcb=1.17.0=h8a09558_0 + - libxcrypt=4.4.36=hd590300_1 + - libzlib=1.3.1=hb9d3cd8_2 + - markupsafe=3.0.2=py311h2dc5d0c_0 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psutil=6.1.0=py311hae2e1ce_0 + - pthread-stubs=0.4=hd74edd7_1002 + - pyobjc-core=10.3.1=py311h09e6bbd_1 + - pyobjc-framework-cocoa=10.3.1=py311h09e6bbd_1 + - python=3.11.10=hc51fdd5_3_cpython + - pyyaml=6.0.2=py311h460d6c5_1 + - pyzmq=26.2.0=py311h730b646_3 + - readline=8.2=h92ec313_1 + - rpds-py=0.21.0=py311h3ff9189_0 + - tk=8.6.13=h5083fa2_1 + - tornado=6.4.1=py311h460d6c5_1 + - xorg-libxau=1.0.11=hd74edd7_1 + - xorg-libxdmcp=1.1.5=hd74edd7_0 + - xz=5.2.6=h57fd34a_0 + - yaml=0.2.5=h3422bc3_2 + - zeromq=4.3.5=hc1bb282_7 + - zstandard=0.23.0=py311ha60cc69_1 + - zstd=1.5.6=hb46c0d2_0 + win-64: + - _openmp_mutex=4.5=2_gnu + - argon2-cffi-bindings=21.2.0=py311he736701_5 + - brotli-python=1.1.0=py311hda3d55a_2 + - bzip2=1.0.8=h2466b09_7 + - ca-certificates=2024.8.30=h56e8100_0 + - cffi=1.17.1=py311he736701_0 + - contourpy=1.3.1=py311h3257749_0 + - cpython=3.11.10=py311hd8ed1ab_3 + - debugpy=1.8.9=py311hda3d55a_0 + - freetype=2.12.1=hdaf720e_2 + - intel-openmp=2024.2.1=h57928b3_1083 + - 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psutil=6.1.0=py311he736701_0 + - pthread-stubs=0.4=h0e40799_1002 + - pysocks=1.7.1=pyh0701188_6 + - python=3.11.10=hce54a09_3_cpython + - pywin32=307=py311hda3d55a_3 + - pywinpty=2.0.14=py311hda3d55a_0 + - pyyaml=6.0.2=py311he736701_1 + - pyzmq=26.2.0=py311h484c95c_3 + - rpds-py=0.21.0=py311h533ab2d_0 + - send2trash=1.8.3=pyh5737063_0 + - tbb=2021.7.0=h91493d7_0 + - terminado=0.18.1=pyh5737063_0 + - tk=8.6.13=h5226925_1 + - tornado=6.4.1=py311he736701_1 + - ucrt=10.0.22621.0=h57928b3_1 + - vc14_runtime=14.42.34433=he29a5d6_23 + - vc=14.3=ha32ba9b_23 + - vs2015_runtime=14.42.34433=hdffcdeb_23 + - win_inet_pton=1.1.0=pyh7428d3b_7 + - winpty=0.4.3=4 + - xorg-libxau=1.0.11=h0e40799_1 + - xorg-libxdmcp=1.1.5=h0e40799_0 + - xz=5.2.6=h8d14728_0 + - yaml=0.2.5=h8ffe710_2 + - zeromq=4.3.5=ha9f60a1_7 + - zstandard=0.23.0=py311h53056dc_1 + - zstd=1.5.6=h0ea2cb4_0 + pip: + - atomicwrites==1.4.1 + - cachetools==5.5.0 + - fasteners==0.19 + - google-apitools==0.5.32 + - google-auth==2.36.0 + - 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z^%vOsV9l%_H_)Om2AXf=XdVQ_v3fl?LJ{~5&qBBSlC&w*lGVpILT_D#sS!LQx1Zz^ z-5lCaJ8yWVhPb+36CUDZ;1d5(B#*8{RqF1Dn?G_G|7GJL)WqG&PZS2^4GtfZCGx~PRDMp9q@8Ue1-wvOF-DJYr8=> z?izX{SVc08nF>u>O#ST@o}M_copS6a+vbrF$)L`xF-bdT<^?X>_cRXbkzI`1la@4X zvg?=$x6}#u9wGB`GovQqh-lvFT!=}DG-A|DB$b4V&JJ*_4ltmL0>UhvoAkiW26UCy z|8=kYfBSrB%YV%m{_8XJ@BJUi%D;6h|6Trv3hv()D*s;ohhN`+eftvr*A@S#u\n", + "\n", + "---\n", + "\n", "## Overview\n", "\n", "[Neuroglancer](https://github.com/google/neuroglancer) by Google is a WebGL-based viewer for volumetric data. It is capable of displaying arbitrary (non-axis-aligned) cross-sectional views of volumetric data, as well as 3D meshes and line-segment-based models (skeletons). It is commonly used to display massive datasets from techniques like electron microscopy (EM) in the field of neuroscience.\n", From 4b127fd26d137746af9328e35e4be1836fbf89e0 Mon Sep 17 00:00:00 2001 From: Demetris Roumis Date: Sat, 23 Nov 2024 12:48:20 -0800 Subject: [PATCH 04/35] set no data ingestion --- volumetric_imaging/anaconda-project.yml | 1 + 1 file changed, 1 insertion(+) diff --git a/volumetric_imaging/anaconda-project.yml b/volumetric_imaging/anaconda-project.yml index 470759e29..005325266 100644 --- a/volumetric_imaging/anaconda-project.yml +++ b/volumetric_imaging/anaconda-project.yml @@ -13,6 +13,7 @@ examples_config: deployments: - command: notebook # - command: dashboard + no_data_ingestion: true user_fields: [examples_config] From fb8c16ac73c0f5f55d7ea2f7942c686dca248973 Mon Sep 17 00:00:00 2001 From: Demetris Roumis Date: Sat, 23 Nov 2024 12:48:44 -0800 Subject: [PATCH 05/35] revise intro --- volumetric_imaging/volumetric_imaging.ipynb | 45 +++++++++++++-------- 1 file changed, 29 insertions(+), 16 deletions(-) diff --git a/volumetric_imaging/volumetric_imaging.ipynb b/volumetric_imaging/volumetric_imaging.ipynb index e5d288316..fd9c4b41a 100644 --- a/volumetric_imaging/volumetric_imaging.ipynb +++ b/volumetric_imaging/volumetric_imaging.ipynb @@ -2,13 +2,8 @@ "cells": [ { "cell_type": "markdown", - "id": "3b7c8ca4-49bc-4673-9547-5571738972d6", - "metadata": { - "ExecuteTime": { - "end_time": "2024-03-29T17:25:02.532910Z", - "start_time": "2024-03-29T17:25:02.529856Z" - } - }, + "id": "761f808c-7539-4050-9f1e-d13eaf57af24", + "metadata": {}, "source": [ "# Volumetric Imaging\n", "\n", @@ -22,19 +17,37 @@ "\n", "## Overview\n", "\n", - "[Neuroglancer](https://github.com/google/neuroglancer) by Google is a WebGL-based viewer for volumetric data. It is capable of displaying arbitrary (non-axis-aligned) cross-sectional views of volumetric data, as well as 3D meshes and line-segment-based models (skeletons). It is commonly used to display massive datasets from techniques like electron microscopy (EM) in the field of neuroscience.\n", + "**Volumetric imaging** refers to techniques that capture data in three dimensions, allowing researchers to visualize and analyze the internal structures of objects, including depth and spatial relationships. Unlike traditional 2D imaging, volumetric imaging provides a more comprehensive view of specimens.\n", + "\n", + "One of the most powerful volumetric imaging techniques is **electron microscopy** ([EM](https://en.wikipedia.org/wiki/Electron_microscope)). EM uses a beam of electrons to create high-resolution images at the nanometer scale, enabling the exploration of fine structural details of biological specimens such as cells, tissues, and molecular structures. However, handling and visualizing the massive datasets generated by EM poses significant challenges due to their size and complexity.\n", "\n", - "Volumetric imaging techniques, such as EM, allow researchers to explore the fine structural details of biological specimens at nanometer resolutions. However, handling and visualizing these massive datasets pose significant challenges due to their size and complexity.\n", + "### Introducing Neuroglancer\n", "\n", - "While Neuroglancer provides a powerful browser-based tool for exploring very large volumes, it is typically used as a standalone application. Researchers often utilize Jupyter Notebooks to conduct reproducible research and encapsulate visualizations alongside code and text. Using [Panel](https://panel.holoviz.org/), we can integrate the Neuroglancer interface within the context of a research notebook or a larger HoloViz application.\n", + "[Neuroglancer](https://github.com/google/neuroglancer) by Google is a WebGL-based viewer designed specifically for volumetric data, offering efficient handling of large-scale datasets through data streaming. Its key features include:\n", "\n", - "In this workflow, we will demonstrate how to embed Neuroglancer within a Panel application, highlighting how HoloViz tools can seamlessly integrate with third-party applications to create interactive and reproducible visualizations.\n", + "- **Interactive Visualization:** Smooth, real-time navigation through volumetric data.\n", + "- **Customizable Layers:** Support for raw images, segmented regions, and annotations.\n", + "- **Web-Based Interface:** Accessible directly from browsers without the need for specialized software.\n", "\n", - "### Use Cases\n", + "Originally developed for neuroscience, Neuroglancer empowers researchers to explore complex 3D structures by tracing neural pathways, identifying cellular components, and annotating regions of interest.\n", "\n", - "- **Exploring Large Volumetric Datasets:** Integrate Neuroglancer within a Jupyter Notebook to explore volumetric data without leaving the notebook environment.\n", - "- **Combining Multiple Visualization Tools:** Use HoloViz Panel to combine Neuroglancer with other HoloViz components or custom plots.\n", - "- **Reproducible Research:** Embed the visualization directly within your code and documentation for easy sharing and collaboration.\n", + "### Integrating Neuroglancer with Jupyter Notebooks\n", + "\n", + "While Neuroglancer is a powerful tool for exploring large volumes, it is typically used as a standalone application. Researchers often utilize **Jupyter Notebooks** to conduct reproducible research and combine code, data analysis, and visualizations.\n", + "\n", + "By integrating Neuroglancer within Jupyter Notebooks using [HoloViz Panel](https://panel.holoviz.org/), researchers can:\n", + "\n", + "- **Consolidate Workflow:** Keep code, data analysis, and visualization in a single environment.\n", + "- **Enhance Reproducibility:** Share notebooks that include both computational steps and interactive visualizations.\n", + "- **Facilitate Collaboration:** Allow collaborators to interact with the same data and visualizations within the notebook.\n", + "\n", + "### Using HoloViz for the Integration\n", + "\n", + "In this workflow, we will demonstrate how to embed Neuroglancer within a Panel application, highlighting how HoloViz tools can seamlessly extend third-party applications. By using Panel, we can:\n", + "\n", + "- Embed the Neuroglancer viewer directly within a notebook cell.\n", + "- Create interactive widgets and controls to manipulate and report the state of the viewer.\n", + "- Combine Neuroglancer views alongside other visualizations.\n", "\n", "---\n", "\n", @@ -44,7 +57,7 @@ "| --- | --- | --- |\n", "| [Panel Documentation](https://panel.holoviz.org/) | Prerequisite | Familiarity with Panel for building interactive apps |\n", "\n", - "---" + "---\n" ] }, { From 88091c287a14c7c12e56f5998b2d1e34d667ac5f Mon Sep 17 00:00:00 2001 From: Demetris Roumis Date: Mon, 25 Nov 2024 11:49:07 -0800 Subject: [PATCH 06/35] reduce thumbnail size --- .../thumbnails/volumetric_imaging.png | Bin 1404748 -> 476164 bytes 1 file changed, 0 insertions(+), 0 deletions(-) diff --git a/volumetric_imaging/thumbnails/volumetric_imaging.png b/volumetric_imaging/thumbnails/volumetric_imaging.png index 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z^%vOsV9l%_H_)Om2AXf=XdVQ_v3fl?LJ{~5&qBBSlC&w*lGVpILT_D#sS!LQx1Zz^ z-5lCaJ8yWVhPb+36CUDZ;1d5(B#*8{RqF1Dn?G_G|7GJL)WqG&PZS2^4GtfZCGx~PRDMp9q@8Ue1-wvOF-DJYr8=> z?izX{SVc08nF>u>O#ST@o}M_copS6a+vbrF$)L`xF-bdT<^?X>_cRXbkzI`1la@4X zvg?=$x6}#u9wGB`GovQqh-lvFT!=}DG-A|DB$b4V&JJ*_4ltmL0>UhvoAkiW26UCy z|8=kYfBSrB%YV%m{_8XJ@BJUi%D;6h|6Trv3hv()D*s;ohhN`+eftvr*A@S#u Date: Wed, 4 Dec 2024 00:37:25 +0200 Subject: [PATCH 07/35] minor cleanup --- volumetric_imaging/volumetric_imaging.ipynb | 112 ++++---------------- 1 file changed, 22 insertions(+), 90 deletions(-) diff --git a/volumetric_imaging/volumetric_imaging.ipynb b/volumetric_imaging/volumetric_imaging.ipynb index fd9c4b41a..36924c178 100644 --- a/volumetric_imaging/volumetric_imaging.ipynb +++ b/volumetric_imaging/volumetric_imaging.ipynb @@ -112,7 +112,6 @@ " `neuroglancer.viewer.Viewer` instance.\n", " \"\"\"\n", "\n", - " # Demo URL for loading an example dataset\n", " DEMO_URL = \"https://neuroglancer-demo.appspot.com/#!%7B%22dimensions%22%3A%7B%22x%22%3A%5B6.000000000000001e-9%2C%22m%22%5D%2C%22y%22%3A%5B6.000000000000001e-9%2C%22m%22%5D%2C%22z%22%3A%5B3.0000000000000004e-8%2C%22m%22%5D%7D%2C%22position%22%3A%5B5029.42333984375%2C6217.5849609375%2C1182.5%5D%2C%22crossSectionScale%22%3A3.7621853549999242%2C%22projectionOrientation%22%3A%5B-0.05179581791162491%2C-0.8017329573631287%2C0.0831851214170456%2C-0.5895944833755493%5D%2C%22projectionScale%22%3A4699.372698097029%2C%22layers%22%3A%5B%7B%22type%22%3A%22image%22%2C%22source%22%3A%22precomputed%3A%2F%2Fgs%3A%2F%2Fneuroglancer-public-data%2Fkasthuri2011%2Fimage%22%2C%22tab%22%3A%22source%22%2C%22name%22%3A%22original-image%22%7D%2C%7B%22type%22%3A%22image%22%2C%22source%22%3A%22precomputed%3A%2F%2Fgs%3A%2F%2Fneuroglancer-public-data%2Fkasthuri2011%2Fimage_color_corrected%22%2C%22tab%22%3A%22source%22%2C%22name%22%3A%22corrected-image%22%7D%2C%7B%22type%22%3A%22segmentation%22%2C%22source%22%3A%22precomputed%3A%2F%2Fgs%3A%2F%2Fneuroglancer-public-data%2Fkasthuri2011%2Fground_truth%22%2C%22tab%22%3A%22source%22%2C%22selectedAlpha%22%3A0.63%2C%22notSelectedAlpha%22%3A0.14%2C%22segments%22%3A%5B%223208%22%2C%224901%22%2C%2213%22%2C%224965%22%2C%224651%22%2C%222282%22%2C%223189%22%2C%223758%22%2C%2215%22%2C%224027%22%2C%223228%22%2C%22444%22%2C%223207%22%2C%223224%22%2C%223710%22%5D%2C%22name%22%3A%22ground_truth%22%7D%5D%2C%22layout%22%3A%224panel%22%7D\"\n", "\n", " def __init__(\n", @@ -124,64 +123,53 @@ " **params,\n", " ):\n", " \"\"\"\n", - " Initialize the NeuroglancerNB class.\n", - "\n", - " Args:\n", - " source (str or neuroglancer.viewer.Viewer, optional): Source for the initial state of the viewer,\n", - " which can be a URL string or an existing neuroglancer.viewer.Viewer instance.\n", - " If None, a new viewer will be initialized without a predefined state.\n", - " aspect_ratio (float, optional): The width to height ratio for the window-responsive Neuroglancer viewer.\n", - " Default is 2.75.\n", - " show_state (bool, optional): Provides a collapsible card widget under the viewer that displays the viewer's state.\n", - " Useful for debugging. Default is False.\n", - " load_demo (bool, optional): If True, loads the demo dataset upon initialization. Default is False.\n", - " **params: Additional parameters passed to the parent class.\n", + " Initializes the NeuroglancerNB app.\n", + "\n", + " Parameters\n", + " ----------\n", + " source : str or neuroglancer.viewer.Viewer, optional\n", + " Source for the initial state of the viewer, which can be a URL string or an existing `neuroglancer.viewer.Viewer` instance.\n", + " If None, a new viewer will be initialized without a predefined state.\n", + " aspect_ratio : float, optional\n", + " The width-to-height ratio for the window-responsive Neuroglancer viewer. Default is 2.75.\n", + " show_state : bool, optional\n", + " Provides a collapsible card widget under the viewer that displays the viewer's state.\n", + " Useful for debugging. Default is False.\n", + " load_demo : bool, optional\n", + " If True, loads the demo dataset upon initialization. Default is False.\n", + " **params\n", + " Additional parameters passed to the parent class.\n", " \"\"\"\n", " super().__init__(**params)\n", - "\n", - " # Determine if a source was provided\n", " self.source_not_provided = False if source else True\n", " self.show_state = show_state\n", - "\n", - " # Initialize the Neuroglancer viewer\n", " self.viewer = (\n", " source\n", " if isinstance(source, neuroglancer.viewer.Viewer)\n", " else neuroglancer.Viewer()\n", " )\n", "\n", - " # Set up the UI components\n", " self._setup_ui_components(aspect_ratio=aspect_ratio)\n", - "\n", - " # Configure the viewer\n", " self._configure_viewer()\n", - "\n", - " # Set up callbacks for interactivity\n", " self._setup_callbacks()\n", "\n", - " # If a source URL is provided, initialize the viewer from the URL\n", " if source and not isinstance(source, neuroglancer.viewer.Viewer):\n", " self._initialize_viewer_from_url(source)\n", "\n", - " # Load the demo dataset if requested\n", " if load_demo:\n", " self.demo_button.clicks += 1\n", "\n", " def _initialize_viewer_from_url(self, source: str):\n", - " \"\"\"Initialize the viewer state from a URL.\"\"\"\n", " self.url_input.value = source\n", " self._load_state_from_url(source)\n", "\n", " def _setup_ui_components(self, aspect_ratio):\n", - " \"\"\"Set up the UI components for the application.\"\"\"\n", - " # Text input for the Neuroglancer URL\n", " self.url_input = pn.widgets.TextInput(\n", " placeholder=\"Enter a Neuroglancer URL and click Load\",\n", " name=\"Input URL\",\n", " width=700,\n", " )\n", "\n", - " # Buttons for loading and demo dataset\n", " self.load_button = pn.widgets.Button(\n", " name=\"Load\", button_type=\"primary\", width=75\n", " )\n", @@ -189,16 +177,13 @@ " name=\"Demo\", button_type=\"warning\", width=75\n", " )\n", "\n", - " # JSON pane to display the viewer state\n", " self.json_pane = pn.pane.JSON(\n", " {}, theme=\"light\", depth=2, name=\"Viewer State\", height=800, width=350\n", " )\n", "\n", - " # Markdown panes to display shareable and local URLs\n", " self.shareable_url_pane = pn.pane.Markdown(\"**Shareable URL:**\")\n", " self.local_url_pane = pn.pane.Markdown(\"**Local URL:**\")\n", "\n", - " # HTML pane to embed the Neuroglancer viewer via iframe\n", " self.iframe = pn.pane.HTML(\n", " sizing_mode=\"stretch_both\",\n", " aspect_ratio=aspect_ratio,\n", @@ -207,30 +192,22 @@ " )\n", "\n", " def _configure_viewer(self):\n", - " \"\"\"Configure the Neuroglancer viewer.\"\"\"\n", - " # Update the local URL and iframe content\n", " self._update_local_url()\n", " self._update_iframe_with_local_url()\n", "\n", " def _setup_callbacks(self):\n", - " \"\"\"Set up callbacks for interactivity.\"\"\"\n", " self.load_button.on_click(self._on_load_button_clicked)\n", " self.demo_button.on_click(self._on_demo_button_clicked)\n", - "\n", - " # Callback for when the viewer state changes\n", " self.viewer.shared_state.add_changed_callback(self._on_viewer_state_changed)\n", "\n", " def _on_demo_button_clicked(self, event):\n", - " \"\"\"Load the demo dataset when the Demo button is clicked.\"\"\"\n", " self.url_input.value = self.DEMO_URL\n", " self._load_state_from_url(self.url_input.value)\n", "\n", " def _on_load_button_clicked(self, event):\n", - " \"\"\"Load the viewer state from the provided URL.\"\"\"\n", " self._load_state_from_url(self.url_input.value)\n", "\n", " def _load_state_from_url(self, url):\n", - " \"\"\"Load the viewer state from a URL.\"\"\"\n", " try:\n", " new_state = self._parse_state_from_url(url)\n", " self.viewer.set_state(new_state)\n", @@ -238,29 +215,24 @@ " print(f\"Error loading Neuroglancer state: {e}\")\n", "\n", " def _parse_state_from_url(self, url):\n", - " \"\"\"Parse the viewer state from a Neuroglancer URL.\"\"\"\n", " return neuroglancer.parse_url(url)\n", "\n", " def _on_viewer_state_changed(self):\n", - " \"\"\"Update the UI when the viewer state changes.\"\"\"\n", " self._update_shareable_url()\n", " self._update_json_pane()\n", "\n", " def _update_shareable_url(self):\n", - " \"\"\"Update the shareable URL pane.\"\"\"\n", " shareable_url = neuroglancer.to_url(self.viewer.state)\n", " self.shareable_url_pane.object = self._generate_dropdown_markup(\n", " \"Shareable URL\", shareable_url\n", " )\n", "\n", " def _update_local_url(self):\n", - " \"\"\"Update the local URL pane.\"\"\"\n", " self.local_url_pane.object = self._generate_dropdown_markup(\n", " \"Local URL\", self.viewer.get_viewer_url()\n", " )\n", "\n", " def _update_iframe_with_local_url(self):\n", - " \"\"\"Embed the viewer in the iframe.\"\"\"\n", " iframe_style = (\n", " 'frameborder=\"0\" scrolling=\"no\" marginheight=\"0\" marginwidth=\"0\" '\n", " 'style=\"width:100%; height:100%; min-width:500px; min-height:500px;\"'\n", @@ -270,11 +242,9 @@ " )\n", "\n", " def _update_json_pane(self):\n", - " \"\"\"Update the JSON pane with the current viewer state.\"\"\"\n", " self.json_pane.object = self.viewer.state.to_json()\n", "\n", " def _generate_dropdown_markup(self, title, url):\n", - " \"\"\"Generate HTML markup for dropdown links.\"\"\"\n", " return f\"\"\"\n", "

    \n", " {title}:\n", @@ -283,14 +253,12 @@ " \"\"\"\n", "\n", " def __panel__(self):\n", - " \"\"\"Define how the class is rendered in a Panel application.\"\"\"\n", - " # Layout for controls (only visible if no source is provided)\n", + " # only visible if no source is provided\n", " controls_layout = pn.Column(\n", " pn.Row(self.demo_button, self.load_button),\n", " pn.Row(self.url_input),\n", " visible=self.source_not_provided,\n", " )\n", - " # Layout for URL links\n", " links_layout = pn.Column(self.local_url_pane, self.shareable_url_pane)\n", "\n", " state_widget = pn.Card(\n", @@ -301,7 +269,6 @@ " styles={\"background\": \"WhiteSmoke\"},\n", " max_width=350\n", " )\n", - " # Combine all components into a single layout\n", " return pn.Column(\n", " controls_layout,\n", " links_layout,\n", @@ -323,49 +290,19 @@ "source": [ "In this workflow, we'll initialize a new Neuroglancer viewer and load a dataset using a parameterized URL. This allows us to explore different datasets by simply changing the URL.\n", "\n", - "To launch an empty viewer, simply omit the `source` input. You can then use the GUI to insert and load from a parameterized URL to set the state of the new viewer. Click the **Demo** button or pass `load_demo=True` to insert an example URL dataset. You can find other demo links on the [Neuroglancer repository](https://github.com/google/neuroglancer#examples).\n" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "b5fb5bf4-83af-4180-b061-a7eac0f5ad6a", - "metadata": {}, - "outputs": [], - "source": [ - "ng_app = NeuroglancerNB(show_state=True, load_demo=True)" - ] - }, - { - "cell_type": "markdown", - "id": "3f41e92d-1e9c-4fc5-8e7b-649f758df098", - "metadata": {}, - "source": [ - "### Usage Instructions:\n", - "\n", - "1. **Load the Demo Dataset:**\n", - " - Since we passed `load_demo=True`, we'll skip this step, but otherwise you could have clicked the **Demo** button to load the example dataset.\n", + "Either use `NeuroglancerNB(source=)` or just run `NeuroglancerNB()` and input the URL in the GUI:\n", "\n", - "2. **Explore the Viewer:**\n", - " - Use the mouse and keyboard to navigate through the volumetric data.\n", - " - Adjust cross-sectional views, zoom, and rotate the 3D view.\n", - "\n", - "3. **View the Viewer State:**\n", - " - Click on the **State** card to expand and view the JSON representation of the current viewer state.\n", - " \n", - "5. **Load a Custom Dataset:**\n", - " - Enter a Neuroglancer URL in the **Input URL** field.\n", - " - Click **Load** to visualize the dataset.\n" + "To use a demo URL, either `load_demo=True` or click the **Demo** button. You can find other demo links on the [Neuroglancer repository](https://github.com/google/neuroglancer#examples).\n" ] }, { "cell_type": "code", "execution_count": null, - "id": "28700ea9-6eed-4d4c-9028-0c2ba8058d75", + "id": "b5fb5bf4-83af-4180-b061-a7eac0f5ad6a", "metadata": {}, "outputs": [], "source": [ - "ng_app" + "NeuroglancerNB(show_state=True, load_demo=True)" ] }, { @@ -399,7 +336,6 @@ "metadata": {}, "outputs": [], "source": [ - "# Create a Neuroglancer viewer and configure it\n", "viewer = neuroglancer.Viewer()\n", "\n", "with viewer.txn() as s:\n", @@ -412,11 +348,7 @@ " source=\"precomputed://gs://neuroglancer-janelia-flyem-hemibrain/v1.1/segmentation\",\n", " )\n", "\n", - "# Embed the viewer within the Panel app\n", - "ng_app_2 = NeuroglancerNB(source=viewer, show_state=True)\n", - "\n", - "# Display the app\n", - "ng_app_2" + "NeuroglancerNB(source=viewer, show_state=True)" ] }, { From 6fb4f4e5a293ce575c3b33ab4a79a9d4a975ad24 Mon Sep 17 00:00:00 2001 From: Demetris Roumis Date: Wed, 4 Dec 2024 01:03:07 +0200 Subject: [PATCH 08/35] add video preview --- volumetric_imaging/volumetric_imaging.ipynb | 31 +++++++++++++++++---- 1 file changed, 26 insertions(+), 5 deletions(-) diff --git a/volumetric_imaging/volumetric_imaging.ipynb b/volumetric_imaging/volumetric_imaging.ipynb index 36924c178..3c6fd3b00 100644 --- a/volumetric_imaging/volumetric_imaging.ipynb +++ b/volumetric_imaging/volumetric_imaging.ipynb @@ -2,7 +2,7 @@ "cells": [ { "cell_type": "markdown", - "id": "761f808c-7539-4050-9f1e-d13eaf57af24", + "id": "cc47db48-cd14-4874-a377-e4c13de91cdd", "metadata": {}, "source": [ "# Volumetric Imaging\n", @@ -13,8 +13,29 @@ " align=\"center\" \n", " style=\"border: 2px solid #ccc; border-radius: 8px; padding: 5px; width: 100%; box-shadow: 0px 4px 8px rgba(0,0,0,0.1);\">\n", "\n", - "---\n", - "\n", + "---" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "ef81c950-38e8-4c18-aec0-63ce70c34b1f", + "metadata": {}, + "outputs": [], + "source": [ + "from IPython.display import HTML\n", + "HTML(\"\"\"\n", + "
    \n", + " \n", + "
    \n", + "\"\"\")" + ] + }, + { + "cell_type": "markdown", + "id": "e3b92a30-50eb-4d00-ad83-0354c947f767", + "metadata": {}, + "source": [ "## Overview\n", "\n", "**Volumetric imaging** refers to techniques that capture data in three dimensions, allowing researchers to visualize and analyze the internal structures of objects, including depth and spatial relationships. Unlike traditional 2D imaging, volumetric imaging provides a more comprehensive view of specimens.\n", @@ -57,7 +78,7 @@ "| --- | --- | --- |\n", "| [Panel Documentation](https://panel.holoviz.org/) | Prerequisite | Familiarity with Panel for building interactive apps |\n", "\n", - "---\n" + "---" ] }, { @@ -76,7 +97,7 @@ { "cell_type": "code", "execution_count": null, - "id": "80f2ec05-50e3-4678-9323-09244ba5cde6", + "id": "c83a8253-e6da-485d-96cd-ce0e783ac00d", "metadata": {}, "outputs": [], "source": [ From 31604a180a90b6124daf903f0ea6e35841c253d3 Mon Sep 17 00:00:00 2001 From: Demetris Roumis Date: Thu, 5 Dec 2024 23:59:46 +0200 Subject: [PATCH 09/35] use params and reduce num of methods --- volumetric_imaging/volumetric_imaging.ipynb | 201 +++++++++----------- 1 file changed, 93 insertions(+), 108 deletions(-) diff --git a/volumetric_imaging/volumetric_imaging.ipynb b/volumetric_imaging/volumetric_imaging.ipynb index 3c6fd3b00..48307af87 100644 --- a/volumetric_imaging/volumetric_imaging.ipynb +++ b/volumetric_imaging/volumetric_imaging.ipynb @@ -120,107 +120,83 @@ { "cell_type": "code", "execution_count": null, - "id": "081e6201-bc6c-4afd-ab2a-f7e21de3d4c7", + "id": "ed82c0c5-1e5d-4acc-ad91-e3052c273c2d", "metadata": {}, "outputs": [], "source": [ + "import param\n", + "import panel as pn\n", + "import neuroglancer\n", + "\n", "class NeuroglancerNB(pn.viewable.Viewer):\n", " \"\"\"\n", " A HoloViz Panel app for visualizing and interacting with Neuroglancer viewers\n", " within a Jupyter Notebook.\n", - "\n", - " This app supports loading from a parameterized Neuroglancer URL or an existing\n", - " `neuroglancer.viewer.Viewer` instance.\n", " \"\"\"\n", - "\n", + " \n", + " source = param.Parameter(default=None, doc=\"\"\"\n", + " Source for the initial state of the viewer, which can be a URL string \n", + " or an existing neuroglancer.viewer.Viewer instance.\n", + " \"\"\")\n", + " height = param.Number(default=600, doc=\"height of the viewer.\")\n", + " width = param.Number(default=800, doc=\"width of the viewer.\")\n", + " show_state = param.Boolean(default=False, doc=\"Show the viewer state for debugging.\")\n", + " load_demo = param.Boolean(default=False, doc=\"Load the demo dataset on initialization.\")\n", + " \n", " DEMO_URL = \"https://neuroglancer-demo.appspot.com/#!%7B%22dimensions%22%3A%7B%22x%22%3A%5B6.000000000000001e-9%2C%22m%22%5D%2C%22y%22%3A%5B6.000000000000001e-9%2C%22m%22%5D%2C%22z%22%3A%5B3.0000000000000004e-8%2C%22m%22%5D%7D%2C%22position%22%3A%5B5029.42333984375%2C6217.5849609375%2C1182.5%5D%2C%22crossSectionScale%22%3A3.7621853549999242%2C%22projectionOrientation%22%3A%5B-0.05179581791162491%2C-0.8017329573631287%2C0.0831851214170456%2C-0.5895944833755493%5D%2C%22projectionScale%22%3A4699.372698097029%2C%22layers%22%3A%5B%7B%22type%22%3A%22image%22%2C%22source%22%3A%22precomputed%3A%2F%2Fgs%3A%2F%2Fneuroglancer-public-data%2Fkasthuri2011%2Fimage%22%2C%22tab%22%3A%22source%22%2C%22name%22%3A%22original-image%22%7D%2C%7B%22type%22%3A%22image%22%2C%22source%22%3A%22precomputed%3A%2F%2Fgs%3A%2F%2Fneuroglancer-public-data%2Fkasthuri2011%2Fimage_color_corrected%22%2C%22tab%22%3A%22source%22%2C%22name%22%3A%22corrected-image%22%7D%2C%7B%22type%22%3A%22segmentation%22%2C%22source%22%3A%22precomputed%3A%2F%2Fgs%3A%2F%2Fneuroglancer-public-data%2Fkasthuri2011%2Fground_truth%22%2C%22tab%22%3A%22source%22%2C%22selectedAlpha%22%3A0.63%2C%22notSelectedAlpha%22%3A0.14%2C%22segments%22%3A%5B%223208%22%2C%224901%22%2C%2213%22%2C%224965%22%2C%224651%22%2C%222282%22%2C%223189%22%2C%223758%22%2C%2215%22%2C%224027%22%2C%223228%22%2C%22444%22%2C%223207%22%2C%223224%22%2C%223710%22%5D%2C%22name%22%3A%22ground_truth%22%7D%5D%2C%22layout%22%3A%224panel%22%7D\"\n", "\n", - " def __init__(\n", - " self,\n", - " source=None,\n", - " aspect_ratio=2.75,\n", - " show_state=False,\n", - " load_demo=False,\n", - " **params,\n", - " ):\n", - " \"\"\"\n", - " Initializes the NeuroglancerNB app.\n", - "\n", - " Parameters\n", - " ----------\n", - " source : str or neuroglancer.viewer.Viewer, optional\n", - " Source for the initial state of the viewer, which can be a URL string or an existing `neuroglancer.viewer.Viewer` instance.\n", - " If None, a new viewer will be initialized without a predefined state.\n", - " aspect_ratio : float, optional\n", - " The width-to-height ratio for the window-responsive Neuroglancer viewer. Default is 2.75.\n", - " show_state : bool, optional\n", - " Provides a collapsible card widget under the viewer that displays the viewer's state.\n", - " Useful for debugging. Default is False.\n", - " load_demo : bool, optional\n", - " If True, loads the demo dataset upon initialization. Default is False.\n", - " **params\n", - " Additional parameters passed to the parent class.\n", - " \"\"\"\n", + " def __init__(self, **params):\n", " super().__init__(**params)\n", - " self.source_not_provided = False if source else True\n", - " self.show_state = show_state\n", - " self.viewer = (\n", - " source\n", - " if isinstance(source, neuroglancer.viewer.Viewer)\n", - " else neuroglancer.Viewer()\n", - " )\n", "\n", - " self._setup_ui_components(aspect_ratio=aspect_ratio)\n", - " self._configure_viewer()\n", - " self._setup_callbacks()\n", + " self.source_not_provided = (self.source is None)\n", + " self.viewer = (self.source if isinstance(self.source, neuroglancer.viewer.Viewer)\n", + " else neuroglancer.Viewer())\n", "\n", - " if source and not isinstance(source, neuroglancer.viewer.Viewer):\n", - " self._initialize_viewer_from_url(source)\n", - "\n", - " if load_demo:\n", - " self.demo_button.clicks += 1\n", - "\n", - " def _initialize_viewer_from_url(self, source: str):\n", - " self.url_input.value = source\n", - " self._load_state_from_url(source)\n", - "\n", - " def _setup_ui_components(self, aspect_ratio):\n", + " # Setup UI\n", " self.url_input = pn.widgets.TextInput(\n", " placeholder=\"Enter a Neuroglancer URL and click Load\",\n", " name=\"Input URL\",\n", - " width=700,\n", - " )\n", - "\n", - " self.load_button = pn.widgets.Button(\n", - " name=\"Load\", button_type=\"primary\", width=75\n", - " )\n", - " self.demo_button = pn.widgets.Button(\n", - " name=\"Demo\", button_type=\"warning\", width=75\n", - " )\n", - "\n", - " self.json_pane = pn.pane.JSON(\n", - " {}, theme=\"light\", depth=2, name=\"Viewer State\", height=800, width=350\n", + " width=self.width,\n", " )\n", - "\n", + " self.load_button = pn.widgets.Button(name=\"Load\", button_type=\"primary\", width=75)\n", + " self.demo_button = pn.widgets.Button(name=\"Demo\", button_type=\"warning\", width=75)\n", + " self.json_pane = pn.pane.JSON({}, theme=\"light\", depth=2, name=\"Viewer State\", \n", + " sizing_mode='stretch_both')\n", " self.shareable_url_pane = pn.pane.Markdown(\"**Shareable URL:**\")\n", " self.local_url_pane = pn.pane.Markdown(\"**Local URL:**\")\n", "\n", " self.iframe = pn.pane.HTML(\n", - " sizing_mode=\"stretch_both\",\n", - " aspect_ratio=aspect_ratio,\n", - " min_height=800,\n", + " # sizing_mode=\"stretch_both\",\n", + " # aspect_ratio=self.aspect_ratio,\n", + " height=self.height,\n", + " width=self.width,\n", " styles={\"resize\": \"both\", \"overflow\": \"hidden\"},\n", " )\n", "\n", - " def _configure_viewer(self):\n", - " self._update_local_url()\n", - " self._update_iframe_with_local_url()\n", + " # Configure viewer and UI\n", + " local_url = self.viewer.get_viewer_url()\n", + " self.local_url_pane.object = self._generate_dropdown_markup(\"Local URL\", local_url)\n", + " iframe_style = ('frameborder=\"0\" scrolling=\"no\" marginheight=\"0\" marginwidth=\"0\" '\n", + " 'style=\"width:100%; height:100%; min-width:500px; min-height:500px;\"')\n", + " self.iframe.object = f''\n", "\n", - " def _setup_callbacks(self):\n", + " # UI Actions\n", " self.load_button.on_click(self._on_load_button_clicked)\n", " self.demo_button.on_click(self._on_demo_button_clicked)\n", " self.viewer.shared_state.add_changed_callback(self._on_viewer_state_changed)\n", "\n", + " # If a source URL was provided, initialize the viewer from it\n", + " if self.source and not isinstance(self.source, neuroglancer.viewer.Viewer):\n", + " self._initialize_viewer_from_url(self.source)\n", + "\n", + " # Load the demo if requested\n", + " if self.load_demo:\n", + " self.demo_button.clicks += 1\n", + "\n", + " def _initialize_viewer_from_url(self, source: str):\n", + " self.url_input.value = source\n", + " self._load_state_from_url(source)\n", + "\n", " def _on_demo_button_clicked(self, event):\n", " self.url_input.value = self.DEMO_URL\n", " self._load_state_from_url(self.url_input.value)\n", @@ -230,39 +206,15 @@ "\n", " def _load_state_from_url(self, url):\n", " try:\n", - " new_state = self._parse_state_from_url(url)\n", + " new_state = neuroglancer.parse_url(url)\n", " self.viewer.set_state(new_state)\n", " except Exception as e:\n", " print(f\"Error loading Neuroglancer state: {e}\")\n", "\n", - " def _parse_state_from_url(self, url):\n", - " return neuroglancer.parse_url(url)\n", - "\n", " def _on_viewer_state_changed(self):\n", - " self._update_shareable_url()\n", - " self._update_json_pane()\n", - "\n", - " def _update_shareable_url(self):\n", + " # Update shareable URL and JSON pane\n", " shareable_url = neuroglancer.to_url(self.viewer.state)\n", - " self.shareable_url_pane.object = self._generate_dropdown_markup(\n", - " \"Shareable URL\", shareable_url\n", - " )\n", - "\n", - " def _update_local_url(self):\n", - " self.local_url_pane.object = self._generate_dropdown_markup(\n", - " \"Local URL\", self.viewer.get_viewer_url()\n", - " )\n", - "\n", - " def _update_iframe_with_local_url(self):\n", - " iframe_style = (\n", - " 'frameborder=\"0\" scrolling=\"no\" marginheight=\"0\" marginwidth=\"0\" '\n", - " 'style=\"width:100%; height:100%; min-width:500px; min-height:500px;\"'\n", - " )\n", - " self.iframe.object = (\n", - " f''\n", - " )\n", - "\n", - " def _update_json_pane(self):\n", + " self.shareable_url_pane.object = self._generate_dropdown_markup(\"Shareable URL\", shareable_url)\n", " self.json_pane.object = self.viewer.state.to_json()\n", "\n", " def _generate_dropdown_markup(self, title, url):\n", @@ -274,7 +226,6 @@ " \"\"\"\n", "\n", " def __panel__(self):\n", - " # only visible if no source is provided\n", " controls_layout = pn.Column(\n", " pn.Row(self.demo_button, self.load_button),\n", " pn.Row(self.url_input),\n", @@ -283,17 +234,19 @@ " links_layout = pn.Column(self.local_url_pane, self.shareable_url_pane)\n", "\n", " state_widget = pn.Card(\n", - " self.json_pane,\n", - " title=\"State\",\n", - " collapsed=False,\n", - " visible=self.show_state,\n", - " styles={\"background\": \"WhiteSmoke\"},\n", - " max_width=350\n", - " )\n", + " self.json_pane,\n", + " title=\"State\",\n", + " collapsed=False,\n", + " visible=self.show_state,\n", + " styles={\"background\": \"WhiteSmoke\"},\n", + " max_width=350\n", + " )\n", + "\n", " return pn.Column(\n", " controls_layout,\n", " links_layout,\n", - " pn.Row(state_widget, self.iframe))\n" + " pn.Row(state_widget, self.iframe)\n", + " )" ] }, { @@ -394,6 +347,38 @@ "\n", "---\n" ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "ccf0e62d-1171-428b-8d7c-ea7ae153663d", + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "25eb2b65-03ad-4ee0-9e06-76ff8c669b55", + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "65c8cb83-5cf3-42ba-8987-aa3e4d51da6c", + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "6d4ce38e-7f95-4c10-97a4-2a36eb77f5bd", + "metadata": {}, + "outputs": [], + "source": [] } ], "metadata": { From 7f9ac3fb224ff0d227374dbf2b912f5dbe9c8896 Mon Sep 17 00:00:00 2001 From: Demetris Roumis Date: Fri, 6 Dec 2024 00:23:07 +0200 Subject: [PATCH 10/35] add static previews and install instructions for colab --- volumetric_imaging/assets/approach1.png | Bin 0 -> 855579 bytes volumetric_imaging/assets/approach2.png | Bin 0 -> 1150039 bytes volumetric_imaging/volumetric_imaging.ipynb | 91 ++++++++++++-------- 3 files changed, 55 insertions(+), 36 deletions(-) create mode 100644 volumetric_imaging/assets/approach1.png create mode 100644 volumetric_imaging/assets/approach2.png diff --git a/volumetric_imaging/assets/approach1.png b/volumetric_imaging/assets/approach1.png new file mode 100644 index 0000000000000000000000000000000000000000..89699226ca35d57f9a47b43d41a6636633b8d666 GIT binary patch literal 855579 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z)RA_@m}xS*QvLAFS1F}0KYRH8N1smH&DY=m7;E(T_`7eV5MO-$@Pm)f-F8<;Chvx~ z&qXs$6aI7n0Dzl3e*Dw<`MJC%8mjkL&e`Gd`{4v4AqXo5000000Pz3t=+Prq)%@{> z>v!K~hyNP^0N}QW=&&CFXH5bC00000+!HN%Y_GSxj%X490RDY#G!jiX00000008$f zoxJ%vqDcS%_z&H6UNZkt0RR91004mdf!!LRZWRCkZljbU1l3&fu(`Xzy#oLM00000 z-g;`%T8k9{0D!+_t<_q$Hq2L>yDMz#1^@s6004lujV3QI*H{q%0C-coM-0PwQx^H! z6~vSP000000C4wcaK_lC#26(2000000NgE_eDL7C zCr_RlW3Vm&0B~T8S?&(YJwi(PDw?cHVK0?8V@ecx0{{R3006+>_#It}QR{c_)zJU| N002ovPDHLkV1h?t-#Y*R literal 0 HcmV?d00001 diff --git a/volumetric_imaging/volumetric_imaging.ipynb b/volumetric_imaging/volumetric_imaging.ipynb index 48307af87..475a77098 100644 --- a/volumetric_imaging/volumetric_imaging.ipynb +++ b/volumetric_imaging/volumetric_imaging.ipynb @@ -94,6 +94,17 @@ "## Imports and Configuration" ] }, + { + "cell_type": "code", + "execution_count": 49, + "id": "414a6f44-89d3-4a5b-b91d-56e99a601c61", + "metadata": {}, + "outputs": [], + "source": [ + "# For google colab, uncomment and run to install packages:\n", + "# !pip install panel neuroglancer jupyter_bokeh" + ] + }, { "cell_type": "code", "execution_count": null, @@ -276,7 +287,23 @@ "metadata": {}, "outputs": [], "source": [ - "NeuroglancerNB(show_state=True, load_demo=True)" + "# NeuroglancerNB(show_state=True, load_demo=True)" + ] + }, + { + "cell_type": "markdown", + "id": "9ab67ed5-625f-4be7-8c86-a5657c86a065", + "metadata": {}, + "source": [ + "\"Panel\n", + "\n", + "**Here's a static snapshot of what the previous cell produces. 👉**\n", + "\n", + "

    \n" ] }, { @@ -306,7 +333,7 @@ { "cell_type": "code", "execution_count": null, - "id": "27bbb3a0-270c-4f8b-ac16-b60a764f1cfc", + "id": "1d178d1c-7f5b-4be2-b000-26157cb28416", "metadata": {}, "outputs": [], "source": [ @@ -320,9 +347,33 @@ " # Add a segmentation layer\n", " s.layers[\"segmentation\"] = neuroglancer.SegmentationLayer(\n", " source=\"precomputed://gs://neuroglancer-janelia-flyem-hemibrain/v1.1/segmentation\",\n", - " )\n", + " )" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "26d8d75a-4512-4d92-8c96-a5f974fc72c7", + "metadata": {}, + "outputs": [], + "source": [ + "# NeuroglancerNB(source=viewer, show_state=True)" + ] + }, + { + "cell_type": "markdown", + "id": "94b0e8a2-4fa3-44b0-b7a4-8b43f9ad081f", + "metadata": {}, + "source": [ + "\"Panel\n", + "\n", + "**Here's a static snapshot of what the previous cell produces. 👉**\n", "\n", - "NeuroglancerNB(source=viewer, show_state=True)" + "
    \n" ] }, { @@ -347,38 +398,6 @@ "\n", "---\n" ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "ccf0e62d-1171-428b-8d7c-ea7ae153663d", - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "25eb2b65-03ad-4ee0-9e06-76ff8c669b55", - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "65c8cb83-5cf3-42ba-8987-aa3e4d51da6c", - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "6d4ce38e-7f95-4c10-97a4-2a36eb77f5bd", - "metadata": {}, - "outputs": [], - "source": [] } ], "metadata": { From 7fdc7b28602d25289bf74263aaea6b8286125c58 Mon Sep 17 00:00:00 2001 From: Demetris Roumis Date: Fri, 6 Dec 2024 00:27:44 +0200 Subject: [PATCH 11/35] remove notebook command and attempt colab command --- volumetric_imaging/anaconda-project.yml | 8 +++++--- 1 file changed, 5 insertions(+), 3 deletions(-) diff --git a/volumetric_imaging/anaconda-project.yml b/volumetric_imaging/anaconda-project.yml index 005325266..e731ca127 100644 --- a/volumetric_imaging/anaconda-project.yml +++ b/volumetric_imaging/anaconda-project.yml @@ -11,7 +11,7 @@ examples_config: - Neuroscience title: "Volumetric Imaging" deployments: - - command: notebook + # - command: notebook # - command: dashboard no_data_ingestion: true @@ -38,10 +38,12 @@ commands: windows: jupyter lab volumetric_imaging.ipynb notebook: notebook: volumetric_imaging.ipynb - dashboard: - unix: panel serve --rest-session-info --session-history -1 volumetric_imaging.ipynb --show + colab: + # unix: panel serve --rest-session-info --session-history -1 volumetric_imaging.ipynb --show + unix: open https://colab.research.google.com/github/holoviz-topics/volumetric_imaging/blob/main/volumetric_imaging.ipynb supports_http_options: true + variables: {} platforms: From 11e33d0c16125edf914d4ec2828be069fe868c49 Mon Sep 17 00:00:00 2001 From: Demetris Roumis Date: Fri, 6 Dec 2024 00:32:48 +0200 Subject: [PATCH 12/35] min pin --- volumetric_imaging/anaconda-project.yml | 8 ++++---- 1 file changed, 4 insertions(+), 4 deletions(-) diff --git a/volumetric_imaging/anaconda-project.yml b/volumetric_imaging/anaconda-project.yml index e731ca127..882642786 100644 --- a/volumetric_imaging/anaconda-project.yml +++ b/volumetric_imaging/anaconda-project.yml @@ -22,13 +22,13 @@ channels: - nodefaults packages: &pkgs -- notebook>=6.5.2,<7 # required +- notebook>=6.5.2 - python=3.11 -- panel -- jupyterlab +- panel>=1.5.4 # auto min pinned 2024-12-06 +- jupyterlab>=4.3.1 # auto min pinned 2024-12-06 - pip - pip: - - neuroglancer + - neuroglancer>=2.40.1 # auto min pinned 2024-12-06 dependencies: *pkgs From 66bf76854771a1eb3dacab0ba7c157eff04a5cb0 Mon Sep 17 00:00:00 2001 From: Demetris Roumis Date: Fri, 6 Dec 2024 00:34:17 +0200 Subject: [PATCH 13/35] restore dashboard command to resolve ae5 deploy error --- volumetric_imaging/anaconda-project.yml | 4 +++- 1 file changed, 3 insertions(+), 1 deletion(-) diff --git a/volumetric_imaging/anaconda-project.yml b/volumetric_imaging/anaconda-project.yml index 882642786..c16840ba2 100644 --- a/volumetric_imaging/anaconda-project.yml +++ b/volumetric_imaging/anaconda-project.yml @@ -38,8 +38,10 @@ commands: windows: jupyter lab volumetric_imaging.ipynb notebook: notebook: volumetric_imaging.ipynb + dashboard: + unix: panel serve --rest-session-info --session-history -1 volumetric_imaging.ipynb --show + supports_http_options: true colab: - # unix: panel serve --rest-session-info --session-history -1 volumetric_imaging.ipynb --show unix: open https://colab.research.google.com/github/holoviz-topics/volumetric_imaging/blob/main/volumetric_imaging.ipynb supports_http_options: true From f8b69304e7476c22f62f3a87b71bb08004995085 Mon Sep 17 00:00:00 2001 From: Demetris Roumis Date: Fri, 22 Nov 2024 12:24:23 -0800 Subject: [PATCH 14/35] volume example draft --- volumetric_imaging/anaconda-project.yml | 50 +++ volumetric_imaging/volumetric_imaging.ipynb | 446 ++++++++++++++++++++ 2 files changed, 496 insertions(+) create mode 100644 volumetric_imaging/anaconda-project.yml create mode 100644 volumetric_imaging/volumetric_imaging.ipynb diff --git a/volumetric_imaging/anaconda-project.yml b/volumetric_imaging/anaconda-project.yml new file mode 100644 index 000000000..470759e29 --- /dev/null +++ b/volumetric_imaging/anaconda-project.yml @@ -0,0 +1,50 @@ +name: volumetric_imaging +description: Display 3D image and segmentation data in a Jupyter notebook. + +examples_config: + created: 2024-11-22 + maintainers: + - "droumis" + labels: + - "panel" + categories: + - Neuroscience + title: "Volumetric Imaging" + deployments: + - command: notebook + # - command: dashboard + +user_fields: [examples_config] + +channels: +- conda-forge +- nodefaults + +packages: &pkgs +- notebook>=6.5.2,<7 # required +- python=3.11 +- panel +- jupyterlab +- pip +- pip: + - neuroglancer + +dependencies: *pkgs + +commands: + lab: + unix: jupyter lab volumetric_imaging.ipynb + windows: jupyter lab volumetric_imaging.ipynb + notebook: + notebook: volumetric_imaging.ipynb + dashboard: + unix: panel serve --rest-session-info --session-history -1 volumetric_imaging.ipynb --show + supports_http_options: true + +variables: {} + +platforms: +- linux-64 +- osx-64 +- win-64 +- osx-arm64 diff --git a/volumetric_imaging/volumetric_imaging.ipynb b/volumetric_imaging/volumetric_imaging.ipynb new file mode 100644 index 000000000..ffecf0556 --- /dev/null +++ b/volumetric_imaging/volumetric_imaging.ipynb @@ -0,0 +1,446 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "id": "3b7c8ca4-49bc-4673-9547-5571738972d6", + "metadata": { + "ExecuteTime": { + "end_time": "2024-03-29T17:25:02.532910Z", + "start_time": "2024-03-29T17:25:02.529856Z" + } + }, + "source": [ + "# Volumetric Imaging\n", + "\n", + "## Overview\n", + "\n", + "[Neuroglancer](https://github.com/google/neuroglancer) by Google is a WebGL-based viewer for volumetric data. It is capable of displaying arbitrary (non-axis-aligned) cross-sectional views of volumetric data, as well as 3D meshes and line-segment-based models (skeletons). It is commonly used to display massive datasets from techniques like electron microscopy (EM) in the field of neuroscience.\n", + "\n", + "Volumetric imaging techniques, such as EM, allow researchers to explore the fine structural details of biological specimens at nanometer resolutions. However, handling and visualizing these massive datasets pose significant challenges due to their size and complexity.\n", + "\n", + "While Neuroglancer provides a powerful browser-based tool for exploring very large volumes, it is typically used as a standalone application. Researchers often utilize Jupyter Notebooks to conduct reproducible research and encapsulate visualizations alongside code and text. Using [Panel](https://panel.holoviz.org/), we can integrate the Neuroglancer interface within the context of a research notebook or a larger HoloViz application.\n", + "\n", + "In this workflow, we will demonstrate how to embed Neuroglancer within a Panel application, highlighting how HoloViz tools can seamlessly integrate with third-party applications to create interactive and reproducible visualizations.\n", + "\n", + "### Use Cases\n", + "\n", + "- **Exploring Large Volumetric Datasets:** Integrate Neuroglancer within a Jupyter Notebook to explore volumetric data without leaving the notebook environment.\n", + "- **Combining Multiple Visualization Tools:** Use HoloViz Panel to combine Neuroglancer with other HoloViz components or custom plots.\n", + "- **Reproducible Research:** Embed the visualization directly within your code and documentation for easy sharing and collaboration.\n", + "\n", + "---\n", + "\n", + "## Prerequisites\n", + "\n", + "| Topic | Type | Notes |\n", + "| --- | --- | --- |\n", + "| [Panel Documentation](https://panel.holoviz.org/) | Prerequisite | Familiarity with Panel for building interactive apps |\n", + "\n", + "---" + ] + }, + { + "cell_type": "markdown", + "id": "a2f77667-f42b-42f6-a13d-5abbe589d7ea", + "metadata": { + "ExecuteTime": { + "end_time": "2024-03-29T17:25:02.532910Z", + "start_time": "2024-03-29T17:25:02.529856Z" + } + }, + "source": [ + "## Imports and Configuration" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "80f2ec05-50e3-4678-9323-09244ba5cde6", + "metadata": {}, + "outputs": [], + "source": [ + "import panel as pn\n", + "import neuroglancer\n", + "\n", + "pn.extension()" + ] + }, + { + "cell_type": "markdown", + "id": "64a50727-8c91-4d88-a82d-626e5a7715ba", + "metadata": {}, + "source": [ + "## Defining the `NeuroglancerNB` Class\n", + "\n", + "To embed Neuroglancer within a Panel application, we'll define a custom class `NeuroglancerNB`. This class creates a Panel viewable object that includes the Neuroglancer viewer embedded within an iframe, along with controls to load a Neuroglancer state from a URL, display the current state JSON, and generate shareable links." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "081e6201-bc6c-4afd-ab2a-f7e21de3d4c7", + "metadata": {}, + "outputs": [], + "source": [ + "class NeuroglancerNB(pn.viewable.Viewer):\n", + " \"\"\"\n", + " A HoloViz Panel app for visualizing and interacting with Neuroglancer viewers\n", + " within a Jupyter Notebook.\n", + "\n", + " This app supports loading from a parameterized Neuroglancer URL or an existing\n", + " `neuroglancer.viewer.Viewer` instance.\n", + " \"\"\"\n", + "\n", + " # Demo URL for loading an example dataset\n", + " DEMO_URL = \"https://neuroglancer-demo.appspot.com/#!%7B%22dimensions%22%3A%7B%22x%22%3A%5B6.000000000000001e-9%2C%22m%22%5D%2C%22y%22%3A%5B6.000000000000001e-9%2C%22m%22%5D%2C%22z%22%3A%5B3.0000000000000004e-8%2C%22m%22%5D%7D%2C%22position%22%3A%5B5029.42333984375%2C6217.5849609375%2C1182.5%5D%2C%22crossSectionScale%22%3A3.7621853549999242%2C%22projectionOrientation%22%3A%5B-0.05179581791162491%2C-0.8017329573631287%2C0.0831851214170456%2C-0.5895944833755493%5D%2C%22projectionScale%22%3A4699.372698097029%2C%22layers%22%3A%5B%7B%22type%22%3A%22image%22%2C%22source%22%3A%22precomputed%3A%2F%2Fgs%3A%2F%2Fneuroglancer-public-data%2Fkasthuri2011%2Fimage%22%2C%22tab%22%3A%22source%22%2C%22name%22%3A%22original-image%22%7D%2C%7B%22type%22%3A%22image%22%2C%22source%22%3A%22precomputed%3A%2F%2Fgs%3A%2F%2Fneuroglancer-public-data%2Fkasthuri2011%2Fimage_color_corrected%22%2C%22tab%22%3A%22source%22%2C%22name%22%3A%22corrected-image%22%7D%2C%7B%22type%22%3A%22segmentation%22%2C%22source%22%3A%22precomputed%3A%2F%2Fgs%3A%2F%2Fneuroglancer-public-data%2Fkasthuri2011%2Fground_truth%22%2C%22tab%22%3A%22source%22%2C%22selectedAlpha%22%3A0.63%2C%22notSelectedAlpha%22%3A0.14%2C%22segments%22%3A%5B%223208%22%2C%224901%22%2C%2213%22%2C%224965%22%2C%224651%22%2C%222282%22%2C%223189%22%2C%223758%22%2C%2215%22%2C%224027%22%2C%223228%22%2C%22444%22%2C%223207%22%2C%223224%22%2C%223710%22%5D%2C%22name%22%3A%22ground_truth%22%7D%5D%2C%22layout%22%3A%224panel%22%7D\"\n", + "\n", + " def __init__(\n", + " self,\n", + " source=None,\n", + " aspect_ratio=2.75,\n", + " show_state=False,\n", + " load_demo=False,\n", + " **params,\n", + " ):\n", + " \"\"\"\n", + " Initialize the NeuroglancerNB class.\n", + "\n", + " Args:\n", + " source (str or neuroglancer.viewer.Viewer, optional): Source for the initial state of the viewer,\n", + " which can be a URL string or an existing neuroglancer.viewer.Viewer instance.\n", + " If None, a new viewer will be initialized without a predefined state.\n", + " aspect_ratio (float, optional): The width to height ratio for the window-responsive Neuroglancer viewer.\n", + " Default is 2.75.\n", + " show_state (bool, optional): Provides a collapsible card widget under the viewer that displays the viewer's state.\n", + " Useful for debugging. Default is False.\n", + " load_demo (bool, optional): If True, loads the demo dataset upon initialization. Default is False.\n", + " **params: Additional parameters passed to the parent class.\n", + " \"\"\"\n", + " super().__init__(**params)\n", + "\n", + " # Determine if a source was provided\n", + " self.source_not_provided = False if source else True\n", + " self.show_state = show_state\n", + "\n", + " # Initialize the Neuroglancer viewer\n", + " self.viewer = (\n", + " source\n", + " if isinstance(source, neuroglancer.viewer.Viewer)\n", + " else neuroglancer.Viewer()\n", + " )\n", + "\n", + " # Set up the UI components\n", + " self._setup_ui_components(aspect_ratio=aspect_ratio)\n", + "\n", + " # Configure the viewer\n", + " self._configure_viewer()\n", + "\n", + " # Set up callbacks for interactivity\n", + " self._setup_callbacks()\n", + "\n", + " # If a source URL is provided, initialize the viewer from the URL\n", + " if source and not isinstance(source, neuroglancer.viewer.Viewer):\n", + " self._initialize_viewer_from_url(source)\n", + "\n", + " # Load the demo dataset if requested\n", + " if load_demo:\n", + " self.demo_button.clicks += 1\n", + "\n", + " def _initialize_viewer_from_url(self, source: str):\n", + " \"\"\"Initialize the viewer state from a URL.\"\"\"\n", + " self.url_input.value = source\n", + " self._load_state_from_url(source)\n", + "\n", + " def _setup_ui_components(self, aspect_ratio):\n", + " \"\"\"Set up the UI components for the application.\"\"\"\n", + " # Text input for the Neuroglancer URL\n", + " self.url_input = pn.widgets.TextInput(\n", + " placeholder=\"Enter a Neuroglancer URL and click Load\",\n", + " name=\"Input URL\",\n", + " width=700,\n", + " )\n", + "\n", + " # Buttons for loading and demo dataset\n", + " self.load_button = pn.widgets.Button(\n", + " name=\"Load\", button_type=\"primary\", width=75\n", + " )\n", + " self.demo_button = pn.widgets.Button(\n", + " name=\"Demo\", button_type=\"warning\", width=75\n", + " )\n", + "\n", + " # JSON pane to display the viewer state\n", + " self.json_pane = pn.pane.JSON(\n", + " {}, theme=\"light\", depth=2, name=\"Viewer State\", height=800, width=350\n", + " )\n", + "\n", + " # Markdown panes to display shareable and local URLs\n", + " self.shareable_url_pane = pn.pane.Markdown(\"**Shareable URL:**\")\n", + " self.local_url_pane = pn.pane.Markdown(\"**Local URL:**\")\n", + "\n", + " # HTML pane to embed the Neuroglancer viewer via iframe\n", + " self.iframe = pn.pane.HTML(\n", + " sizing_mode=\"stretch_both\",\n", + " aspect_ratio=aspect_ratio,\n", + " min_height=800,\n", + " styles={\"resize\": \"both\", \"overflow\": \"hidden\"},\n", + " )\n", + "\n", + " def _configure_viewer(self):\n", + " \"\"\"Configure the Neuroglancer viewer.\"\"\"\n", + " # Update the local URL and iframe content\n", + " self._update_local_url()\n", + " self._update_iframe_with_local_url()\n", + "\n", + " def _setup_callbacks(self):\n", + " \"\"\"Set up callbacks for interactivity.\"\"\"\n", + " self.load_button.on_click(self._on_load_button_clicked)\n", + " self.demo_button.on_click(self._on_demo_button_clicked)\n", + "\n", + " # Callback for when the viewer state changes\n", + " self.viewer.shared_state.add_changed_callback(self._on_viewer_state_changed)\n", + "\n", + " def _on_demo_button_clicked(self, event):\n", + " \"\"\"Load the demo dataset when the Demo button is clicked.\"\"\"\n", + " self.url_input.value = self.DEMO_URL\n", + " self._load_state_from_url(self.url_input.value)\n", + "\n", + " def _on_load_button_clicked(self, event):\n", + " \"\"\"Load the viewer state from the provided URL.\"\"\"\n", + " self._load_state_from_url(self.url_input.value)\n", + "\n", + " def _load_state_from_url(self, url):\n", + " \"\"\"Load the viewer state from a URL.\"\"\"\n", + " try:\n", + " new_state = self._parse_state_from_url(url)\n", + " self.viewer.set_state(new_state)\n", + " except Exception as e:\n", + " print(f\"Error loading Neuroglancer state: {e}\")\n", + "\n", + " def _parse_state_from_url(self, url):\n", + " \"\"\"Parse the viewer state from a Neuroglancer URL.\"\"\"\n", + " return neuroglancer.parse_url(url)\n", + "\n", + " def _on_viewer_state_changed(self):\n", + " \"\"\"Update the UI when the viewer state changes.\"\"\"\n", + " self._update_shareable_url()\n", + " self._update_json_pane()\n", + "\n", + " def _update_shareable_url(self):\n", + " \"\"\"Update the shareable URL pane.\"\"\"\n", + " shareable_url = neuroglancer.to_url(self.viewer.state)\n", + " self.shareable_url_pane.object = self._generate_dropdown_markup(\n", + " \"Shareable URL\", shareable_url\n", + " )\n", + "\n", + " def _update_local_url(self):\n", + " \"\"\"Update the local URL pane.\"\"\"\n", + " self.local_url_pane.object = self._generate_dropdown_markup(\n", + " \"Local URL\", self.viewer.get_viewer_url()\n", + " )\n", + "\n", + " def _update_iframe_with_local_url(self):\n", + " \"\"\"Embed the viewer in the iframe.\"\"\"\n", + " iframe_style = (\n", + " 'frameborder=\"0\" scrolling=\"no\" marginheight=\"0\" marginwidth=\"0\" '\n", + " 'style=\"width:100%; height:100%; min-width:500px; min-height:500px;\"'\n", + " )\n", + " self.iframe.object = (\n", + " f''\n", + " )\n", + "\n", + " def _update_json_pane(self):\n", + " \"\"\"Update the JSON pane with the current viewer state.\"\"\"\n", + " self.json_pane.object = self.viewer.state.to_json()\n", + "\n", + " def _generate_dropdown_markup(self, title, url):\n", + " \"\"\"Generate HTML markup for dropdown links.\"\"\"\n", + " return f\"\"\"\n", + " \n", + " \"\"\"\n", + "\n", + " def __panel__(self):\n", + " \"\"\"Define how the class is rendered in a Panel application.\"\"\"\n", + " # Layout for controls (only visible if no source is provided)\n", + " controls_layout = pn.Column(\n", + " pn.Row(self.demo_button, self.load_button),\n", + " pn.Row(self.url_input),\n", + " visible=self.source_not_provided,\n", + " )\n", + " # Layout for URL links\n", + " links_layout = pn.Column(self.local_url_pane, self.shareable_url_pane)\n", + "\n", + " state_widget = pn.Card(\n", + " self.json_pane,\n", + " title=\"State\",\n", + " collapsed=False,\n", + " visible=self.show_state,\n", + " styles={\"background\": \"WhiteSmoke\"},\n", + " max_width=350\n", + " )\n", + " # Combine all components into a single layout\n", + " return pn.Column(\n", + " controls_layout,\n", + " links_layout,\n", + " pn.Row(state_widget, self.iframe))\n" + ] + }, + { + "cell_type": "markdown", + "id": "4dac819c-c3e9-4a51-be83-bf54b28f62b2", + "metadata": {}, + "source": [ + "## Approach 1: Launching a New Viewer and Loading State from URL\n" + ] + }, + { + "cell_type": "markdown", + "id": "58f1de1e-d307-4e6a-8f49-ec7f4a04cc24", + "metadata": {}, + "source": [ + "In this workflow, we'll initialize a new Neuroglancer viewer and load a dataset using a parameterized URL. This allows us to explore different datasets by simply changing the URL.\n", + "\n", + "To launch an empty viewer, simply omit the `source` input. You can then use the GUI to insert and load from a parameterized URL to set the state of the new viewer. Click the **Demo** button or pass `load_demo=True` to insert an example URL dataset. You can find other demo links on the [Neuroglancer repository](https://github.com/google/neuroglancer#examples).\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "b5fb5bf4-83af-4180-b061-a7eac0f5ad6a", + "metadata": {}, + "outputs": [], + "source": [ + "ng_app = NeuroglancerNB(show_state=True, load_demo=True)" + ] + }, + { + "cell_type": "markdown", + "id": "3f41e92d-1e9c-4fc5-8e7b-649f758df098", + "metadata": {}, + "source": [ + "### Usage Instructions:\n", + "\n", + "1. **Load the Demo Dataset:**\n", + " - Since we passed `load_demo=True`, we'll skip this step, but otherwise you could have clicked the **Demo** button to load the example dataset.\n", + "\n", + "2. **Explore the Viewer:**\n", + " - Use the mouse and keyboard to navigate through the volumetric data.\n", + " - Adjust cross-sectional views, zoom, and rotate the 3D view.\n", + "\n", + "3. **View the Viewer State:**\n", + " - Click on the **State** card to expand and view the JSON representation of the current viewer state.\n", + " \n", + "5. **Load a Custom Dataset:**\n", + " - Enter a Neuroglancer URL in the **Input URL** field.\n", + " - Click **Load** to visualize the dataset.\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "28700ea9-6eed-4d4c-9028-0c2ba8058d75", + "metadata": {}, + "outputs": [], + "source": [ + "ng_app" + ] + }, + { + "cell_type": "markdown", + "id": "afa26a39-e22f-4ae8-880e-559350e1bfc9", + "metadata": {}, + "source": [ + "## Approach 2: Displaying a Pre-specified Viewer" + ] + }, + { + "cell_type": "markdown", + "id": "2717e7f4-f098-4ba8-87a5-1e673496d740", + "metadata": {}, + "source": [ + "Alternatively, you can provide a pre-configured `neuroglancer.viewer.Viewer` object as the `source` to display that viewer in the notebook. This allows you to set up the viewer programmatically and then embed it.\n", + "\n", + "- We create a Neuroglancer `Viewer` instance.\n", + "- Within a transaction (`viewer.txn()`), we add layers to the viewer:\n", + " - An image layer from a precomputed data source.\n", + " - A segmentation layer.\n", + "- We then pass this configured viewer to our `NeuroglancerNB` class.\n", + "- The viewer is embedded within the Panel app and displayed in the notebook.\n", + "\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "27bbb3a0-270c-4f8b-ac16-b60a764f1cfc", + "metadata": {}, + "outputs": [], + "source": [ + "# Create a Neuroglancer viewer and configure it\n", + "viewer = neuroglancer.Viewer()\n", + "\n", + "with viewer.txn() as s:\n", + " # Add an image layer from a precomputed data source\n", + " s.layers[\"image\"] = neuroglancer.ImageLayer(\n", + " source=\"precomputed://gs://neuroglancer-janelia-flyem-hemibrain/emdata/clahe_yz/jpeg\",\n", + " )\n", + " # Add a segmentation layer\n", + " s.layers[\"segmentation\"] = neuroglancer.SegmentationLayer(\n", + " source=\"precomputed://gs://neuroglancer-janelia-flyem-hemibrain/v1.1/segmentation\",\n", + " )\n", + "\n", + "# Embed the viewer within the Panel app\n", + "ng_app_2 = NeuroglancerNB(source=viewer, show_state=True)\n", + "\n", + "# Display the app\n", + "ng_app_2" + ] + }, + { + "cell_type": "markdown", + "id": "1247343e-44b5-46a8-a05d-511d1a392e9d", + "metadata": {}, + "source": [ + "## Next Steps\n", + "\n", + "- **Explore Your Own Datasets:** Modify the code to load and visualize your own volumetric datasets.\n", + "- **Extend the Application:** Integrate additional HoloViews plots or other Panel components to create a more comprehensive application. For instance, you might add controls for adjusting visualization parameters.\n", + "- **Share and Collaborate:** Use the shareable URLs generated by the app to share specific views or states with collaborators. Embedding the application in a notebook ensures that your analysis and visualizations are reproducible and shareable.\n", + "\n", + "---\n", + "\n", + "## Resources\n", + "\n", + "| Resource | Description |\n", + "| --- | --- |\n", + "| [Neuroglancer GitHub Repository](https://github.com/google/neuroglancer) | Neuroglancer source code and documentation |\n", + "| [Neuroglancer Python Integration](https://github.com/google/neuroglancer/tree/master/python) | Python interface for controlling Neuroglancer |\n", + "\n", + "---\n" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.11.10" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} From 92a1e52e5bc25f723d8a5d256e1ef7003d7d8599 Mon Sep 17 00:00:00 2001 From: Demetris Roumis Date: Sat, 23 Nov 2024 12:14:43 -0800 Subject: [PATCH 15/35] lock --- volumetric_imaging/anaconda-project-lock.yml | 417 +++++++++++++++++++ 1 file changed, 417 insertions(+) create mode 100644 volumetric_imaging/anaconda-project-lock.yml diff --git a/volumetric_imaging/anaconda-project-lock.yml b/volumetric_imaging/anaconda-project-lock.yml new file mode 100644 index 000000000..75221c719 --- /dev/null +++ b/volumetric_imaging/anaconda-project-lock.yml @@ -0,0 +1,417 @@ +# This is an Anaconda project lock file. +# The lock file locks down exact versions of all your dependencies. +# +# In most cases, this file is automatically maintained by the `anaconda-project` command or GUI tools. +# It's best to keep this file in revision control (such as git or svn). +# The file is in YAML format, please see http://www.yaml.org/start.html for more. +# + +# +# Set to false to ignore locked versions. +# +locking_enabled: true + +# +# A key goes in here for each env spec. +# +env_specs: + default: + locked: true + env_spec_hash: 9416c0a974d1a3397dd9a05e428fac41c98afeac + platforms: + - linux-64 + - osx-64 + - osx-arm64 + - win-64 + packages: + all: + - anyio=4.6.2.post1=pyhd8ed1ab_0 + - argon2-cffi=23.1.0=pyhd8ed1ab_0 + - arrow=1.3.0=pyhd8ed1ab_0 + - asttokens=2.4.1=pyhd8ed1ab_0 + - async-lru=2.0.4=pyhd8ed1ab_0 + - attrs=24.2.0=pyh71513ae_0 + - babel=2.16.0=pyhd8ed1ab_0 + - beautifulsoup4=4.12.3=pyha770c72_0 + - bleach=6.2.0=pyhd8ed1ab_0 + - bokeh=3.6.1=pyhd8ed1ab_0 + - cached-property=1.5.2=hd8ed1ab_1 + - cached_property=1.5.2=pyha770c72_1 + - certifi=2024.8.30=pyhd8ed1ab_0 + - charset-normalizer=3.4.0=pyhd8ed1ab_0 + - colorama=0.4.6=pyhd8ed1ab_0 + - comm=0.2.2=pyhd8ed1ab_0 + - decorator=5.1.1=pyhd8ed1ab_0 + - defusedxml=0.7.1=pyhd8ed1ab_0 + - entrypoints=0.4=pyhd8ed1ab_0 + - exceptiongroup=1.2.2=pyhd8ed1ab_0 + - executing=2.1.0=pyhd8ed1ab_0 + - fqdn=1.5.1=pyhd8ed1ab_0 + - h11=0.14.0=pyhd8ed1ab_0 + - h2=4.1.0=pyhd8ed1ab_0 + - hpack=4.0.0=pyh9f0ad1d_0 + - httpcore=1.0.7=pyh29332c3_1 + - httpx=0.27.2=pyhd8ed1ab_0 + - hyperframe=6.0.1=pyhd8ed1ab_0 + - idna=3.10=pyhd8ed1ab_0 + - importlib-metadata=8.5.0=pyha770c72_0 + - importlib_resources=6.4.5=pyhd8ed1ab_0 + - ipython_genutils=0.2.0=pyhd8ed1ab_1 + - isoduration=20.11.0=pyhd8ed1ab_0 + - jedi=0.19.2=pyhff2d567_0 + - jinja2=3.1.4=pyhd8ed1ab_0 + - json5=0.9.28=pyhff2d567_0 + - jsonschema-specifications=2024.10.1=pyhd8ed1ab_0 + - jsonschema-with-format-nongpl=4.23.0=hd8ed1ab_0 + - jsonschema=4.23.0=pyhd8ed1ab_0 + - jupyter-lsp=2.2.5=pyhd8ed1ab_0 + - jupyter_client=7.4.9=pyhd8ed1ab_0 + - jupyter_events=0.10.0=pyhd8ed1ab_0 + - jupyter_server=2.14.2=pyhd8ed1ab_0 + - jupyter_server_terminals=0.5.3=pyhd8ed1ab_0 + - jupyterlab=4.3.1=pyhff2d567_0 + - jupyterlab_pygments=0.3.0=pyhd8ed1ab_1 + - jupyterlab_server=2.27.3=pyhd8ed1ab_0 + - linkify-it-py=2.0.3=pyhd8ed1ab_0 + - markdown-it-py=3.0.0=pyhd8ed1ab_0 + - markdown=3.6=pyhd8ed1ab_0 + - matplotlib-inline=0.1.7=pyhd8ed1ab_0 + - mdit-py-plugins=0.4.2=pyhd8ed1ab_0 + - mdurl=0.1.2=pyhd8ed1ab_0 + - mistune=3.0.2=pyhd8ed1ab_0 + - nbclassic=1.1.0=pyhd8ed1ab_0 + - nbclient=0.10.0=pyhd8ed1ab_0 + - nbconvert-core=7.16.4=pyhd8ed1ab_1 + - nbformat=5.10.4=pyhd8ed1ab_0 + - nest-asyncio=1.6.0=pyhd8ed1ab_0 + - notebook-shim=0.2.4=pyhd8ed1ab_0 + - notebook=6.5.7=pyha770c72_0 + - overrides=7.7.0=pyhd8ed1ab_0 + - packaging=24.2=pyhff2d567_1 + - pandocfilters=1.5.0=pyhd8ed1ab_0 + - panel=1.5.4=pyhd8ed1ab_0 + - param=2.1.1=pyhff2d567_0 + - parso=0.8.4=pyhd8ed1ab_0 + - pickleshare=0.7.5=py_1003 + - pip=24.3.1=pyh8b19718_0 + - pkgutil-resolve-name=1.3.10=pyhd8ed1ab_1 + - platformdirs=4.3.6=pyhd8ed1ab_0 + - prometheus_client=0.21.0=pyhd8ed1ab_0 + - prompt-toolkit=3.0.48=pyha770c72_0 + - pure_eval=0.2.3=pyhd8ed1ab_0 + - pycparser=2.22=pyhd8ed1ab_0 + - pygments=2.18.0=pyhd8ed1ab_0 + - python-dateutil=2.9.0.post0=pyhff2d567_0 + - python-fastjsonschema=2.20.0=pyhd8ed1ab_0 + - python-json-logger=2.0.7=pyhd8ed1ab_0 + - python-tzdata=2024.2=pyhd8ed1ab_0 + - python_abi=3.11=5_cp311 + - pytz=2024.1=pyhd8ed1ab_0 + - pyviz_comms=3.0.3=pyhd8ed1ab_0 + - referencing=0.35.1=pyhd8ed1ab_0 + - requests=2.32.3=pyhd8ed1ab_0 + - rfc3339-validator=0.1.4=pyhd8ed1ab_0 + - rfc3986-validator=0.1.1=pyh9f0ad1d_0 + - setuptools=75.6.0=pyhff2d567_0 + - six=1.16.0=pyh6c4a22f_0 + - sniffio=1.3.1=pyhd8ed1ab_0 + - soupsieve=2.5=pyhd8ed1ab_1 + - stack_data=0.6.2=pyhd8ed1ab_0 + - tinycss2=1.4.0=pyhd8ed1ab_0 + - tomli=2.1.0=pyhff2d567_0 + - tqdm=4.67.0=pyhd8ed1ab_0 + - traitlets=5.14.3=pyhd8ed1ab_0 + - types-python-dateutil=2.9.0.20241003=pyhff2d567_0 + - typing-extensions=4.12.2=hd8ed1ab_0 + - typing_extensions=4.12.2=pyha770c72_0 + - typing_utils=0.1.0=pyhd8ed1ab_0 + - tzdata=2024b=hc8b5060_0 + - uc-micro-py=1.0.3=pyhd8ed1ab_0 + - uri-template=1.3.0=pyhd8ed1ab_0 + - urllib3=2.2.3=pyhd8ed1ab_0 + - wcwidth=0.2.13=pyhd8ed1ab_0 + - webcolors=24.8.0=pyhd8ed1ab_0 + - webencodings=0.5.1=pyhd8ed1ab_2 + - websocket-client=1.8.0=pyhd8ed1ab_0 + - wheel=0.45.1=pyhd8ed1ab_0 + - xyzservices=2024.9.0=pyhd8ed1ab_0 + - zipp=3.21.0=pyhd8ed1ab_0 + unix: + - ipython=8.29.0=pyh707e725_0 + - jupyter_core=5.7.2=pyh31011fe_1 + - pexpect=4.9.0=pyhd8ed1ab_0 + - ptyprocess=0.7.0=pyhd3deb0d_0 + - pysocks=1.7.1=pyha2e5f31_6 + osx: + - appnope=0.1.4=pyhd8ed1ab_0 + - ipykernel=6.29.5=pyh57ce528_0 + - send2trash=1.8.3=pyh31c8845_0 + - terminado=0.18.1=pyh31c8845_0 + linux-64: + - _libgcc_mutex=0.1=conda_forge + - _openmp_mutex=4.5=2_gnu + - argon2-cffi-bindings=21.2.0=py311h9ecbd09_5 + - brotli-python=1.1.0=py311hfdbb021_2 + - bzip2=1.0.8=h4bc722e_7 + - ca-certificates=2024.8.30=hbcca054_0 + - cffi=1.17.1=py311hf29c0ef_0 + - contourpy=1.3.1=py311hd18a35c_0 + - debugpy=1.8.9=py311hfdbb021_0 + - freetype=2.12.1=h267a509_2 + - ipykernel=6.29.5=pyh3099207_0 + - jsonpointer=3.0.0=py311h38be061_1 + - keyutils=1.6.1=h166bdaf_0 + - krb5=1.21.3=h659f571_0 + - lcms2=2.16=hb7c19ff_0 + - ld_impl_linux-64=2.43=h712a8e2_2 + - lerc=4.0.0=h27087fc_0 + - libblas=3.9.0=25_linux64_openblas + - libcblas=3.9.0=25_linux64_openblas + - libdeflate=1.22=hb9d3cd8_0 + - libedit=3.1.20191231=he28a2e2_2 + - libexpat=2.6.4=h5888daf_0 + - libffi=3.4.2=h7f98852_5 + - libgcc-ng=14.2.0=h69a702a_1 + - libgcc=14.2.0=h77fa898_1 + - libgfortran5=14.2.0=hd5240d6_1 + - libgfortran=14.2.0=h69a702a_1 + - libgomp=14.2.0=h77fa898_1 + - libjpeg-turbo=3.0.0=hd590300_1 + - liblapack=3.9.0=25_linux64_openblas + - libnsl=2.0.1=hd590300_0 + - libopenblas=0.3.28=pthreads_h94d23a6_1 + - libpng=1.6.44=hadc24fc_0 + - libsodium=1.0.20=h4ab18f5_0 + - libsqlite=3.47.0=hadc24fc_1 + - libstdcxx-ng=14.2.0=h4852527_1 + - libstdcxx=14.2.0=hc0a3c3a_1 + - libtiff=4.7.0=he137b08_1 + - libuuid=2.38.1=h0b41bf4_0 + - libwebp-base=1.4.0=hd590300_0 + - libxcb=1.17.0=h8a09558_0 + - libxcrypt=4.4.36=hd590300_1 + - libzlib=1.3.1=hb9d3cd8_2 + - markupsafe=3.0.2=py311h2dc5d0c_0 + - ncurses=6.5=he02047a_1 + - numpy=2.1.3=py311h71ddf71_0 + - openjpeg=2.5.2=h488ebb8_0 + - openssl=3.4.0=hb9d3cd8_0 + - pandas=2.2.3=py311h7db5c69_1 + - pillow=11.0.0=py311h49e9ac3_0 + - psutil=6.1.0=py311h9ecbd09_0 + - pthread-stubs=0.4=hb9d3cd8_1002 + - python=3.11.10=hc5c86c4_3_cpython + - pyyaml=6.0.2=py311h9ecbd09_1 + - pyzmq=26.2.0=py311h7deb3e3_3 + - readline=8.2=h8228510_1 + - rpds-py=0.21.0=py311h9e33e62_0 + - send2trash=1.8.3=pyh0d859eb_0 + - terminado=0.18.1=pyh0d859eb_0 + - tk=8.6.13=noxft_h4845f30_101 + - tornado=6.4.1=py311h9ecbd09_1 + - xorg-libxau=1.0.11=hb9d3cd8_1 + - xorg-libxdmcp=1.1.5=hb9d3cd8_0 + - xz=5.2.6=h166bdaf_0 + - yaml=0.2.5=h7f98852_2 + - zeromq=4.3.5=h3b0a872_7 + - zstandard=0.23.0=py311hbc35293_1 + - zstd=1.5.6=ha6fb4c9_0 + osx-64: + - argon2-cffi-bindings=21.2.0=py311h3336109_5 + - brotli-python=1.1.0=py311hd89902b_2 + - bzip2=1.0.8=hfdf4475_7 + - ca-certificates=2024.8.30=h8857fd0_0 + - cffi=1.17.1=py311h137bacd_0 + - contourpy=1.3.1=py311h4e34fa0_0 + - debugpy=1.8.9=py311hc356e98_0 + - freetype=2.12.1=h60636b9_2 + - jsonpointer=3.0.0=py311h6eed73b_1 + - krb5=1.21.3=h37d8d59_0 + - lcms2=2.16=ha2f27b4_0 + - lerc=4.0.0=hb486fe8_0 + - libblas=3.9.0=25_osx64_openblas + - libcblas=3.9.0=25_osx64_openblas + - libcxx=19.1.4=hf95d169_0 + - libdeflate=1.22=h00291cd_0 + - libedit=3.1.20191231=h0678c8f_2 + - libexpat=2.6.4=h240833e_0 + - libffi=3.4.2=h0d85af4_5 + - libgfortran5=13.2.0=h2873a65_3 + - libgfortran=5.0.0=13_2_0_h97931a8_3 + - libjpeg-turbo=3.0.0=h0dc2134_1 + - liblapack=3.9.0=25_osx64_openblas + - libopenblas=0.3.28=openmp_hbf64a52_1 + - libpng=1.6.44=h4b8f8c9_0 + - libsodium=1.0.20=hfdf4475_0 + - libsqlite=3.47.0=h2f8c449_1 + - libtiff=4.7.0=h583c2ba_1 + - libwebp-base=1.4.0=h10d778d_0 + - libxcb=1.17.0=hf1f96e2_0 + - libzlib=1.3.1=hd23fc13_2 + - llvm-openmp=19.1.4=ha54dae1_0 + - markupsafe=3.0.2=py311h8b4e8a7_0 + - ncurses=6.5=hf036a51_1 + - numpy=2.1.3=py311h14ed71f_0 + - openjpeg=2.5.2=h7310d3a_0 + - openssl=3.4.0=hd471939_0 + - pandas=2.2.3=py311haeb46be_1 + - pillow=11.0.0=py311h1f68098_0 + - psutil=6.1.0=py311h1314207_0 + - pthread-stubs=0.4=h00291cd_1002 + - pyobjc-core=10.3.1=py311hd6939f8_1 + - pyobjc-framework-cocoa=10.3.1=py311hd6939f8_1 + - python=3.11.10=ha513fb2_3_cpython + - pyyaml=6.0.2=py311h3336109_1 + - pyzmq=26.2.0=py311h4d3da15_3 + - readline=8.2=h9e318b2_1 + - rpds-py=0.21.0=py311h3b9c2be_0 + - tk=8.6.13=h1abcd95_1 + - tornado=6.4.1=py311h3336109_1 + - xorg-libxau=1.0.11=h00291cd_1 + - xorg-libxdmcp=1.1.5=h00291cd_0 + - xz=5.2.6=h775f41a_0 + - yaml=0.2.5=h0d85af4_2 + - zeromq=4.3.5=h7130eaa_7 + - zstandard=0.23.0=py311hdf6fcd6_1 + - zstd=1.5.6=h915ae27_0 + osx-arm64: + - argon2-cffi-bindings=21.2.0=py311h460d6c5_5 + - brotli-python=1.1.0=py311h3f08180_2 + - bzip2=1.0.8=h99b78c6_7 + - ca-certificates=2024.8.30=hf0a4a13_0 + - cffi=1.17.1=py311h3a79f62_0 + - contourpy=1.3.1=py311h210dab8_0 + - debugpy=1.8.9=py311h155a34a_0 + - freetype=2.12.1=hadb7bae_2 + - jsonpointer=3.0.0=py311h267d04e_1 + - krb5=1.21.3=h237132a_0 + - lcms2=2.16=ha0e7c42_0 + - lerc=4.0.0=h9a09cb3_0 + - libblas=3.9.0=25_osxarm64_openblas + - libcblas=3.9.0=25_osxarm64_openblas + - libcxx=19.1.4=ha82da77_0 + - libdeflate=1.22=hd74edd7_0 + - libedit=3.1.20191231=hc8eb9b7_2 + - libexpat=2.6.4=h286801f_0 + - libffi=3.4.2=h3422bc3_5 + - libgfortran5=13.2.0=hf226fd6_3 + - libgfortran=5.0.0=13_2_0_hd922786_3 + - libjpeg-turbo=3.0.0=hb547adb_1 + - liblapack=3.9.0=25_osxarm64_openblas + - libopenblas=0.3.28=openmp_hf332438_1 + - libpng=1.6.44=hc14010f_0 + - libsodium=1.0.20=h99b78c6_0 + - libsqlite=3.47.0=hbaaea75_1 + - libtiff=4.7.0=hfce79cd_1 + - libwebp-base=1.4.0=h93a5062_0 + - libxcb=1.17.0=hdb1d25a_0 + - libzlib=1.3.1=h8359307_2 + - llvm-openmp=19.1.4=hdb05f8b_0 + - markupsafe=3.0.2=py311h56c23cb_0 + - ncurses=6.5=h7bae524_1 + - numpy=2.1.3=py311h649a571_0 + - openjpeg=2.5.2=h9f1df11_0 + - openssl=3.4.0=h39f12f2_0 + - pandas=2.2.3=py311h9cb3ce9_1 + - pillow=11.0.0=py311h3894ae9_0 + - psutil=6.1.0=py311hae2e1ce_0 + - pthread-stubs=0.4=hd74edd7_1002 + - pyobjc-core=10.3.1=py311h09e6bbd_1 + - pyobjc-framework-cocoa=10.3.1=py311h09e6bbd_1 + - python=3.11.10=hc51fdd5_3_cpython + - pyyaml=6.0.2=py311h460d6c5_1 + - pyzmq=26.2.0=py311h730b646_3 + - readline=8.2=h92ec313_1 + - rpds-py=0.21.0=py311h3ff9189_0 + - tk=8.6.13=h5083fa2_1 + - tornado=6.4.1=py311h460d6c5_1 + - xorg-libxau=1.0.11=hd74edd7_1 + - xorg-libxdmcp=1.1.5=hd74edd7_0 + - xz=5.2.6=h57fd34a_0 + - yaml=0.2.5=h3422bc3_2 + - zeromq=4.3.5=hc1bb282_7 + - zstandard=0.23.0=py311ha60cc69_1 + - zstd=1.5.6=hb46c0d2_0 + win-64: + - _openmp_mutex=4.5=2_gnu + - argon2-cffi-bindings=21.2.0=py311he736701_5 + - brotli-python=1.1.0=py311hda3d55a_2 + - bzip2=1.0.8=h2466b09_7 + - ca-certificates=2024.8.30=h56e8100_0 + - cffi=1.17.1=py311he736701_0 + - contourpy=1.3.1=py311h3257749_0 + - cpython=3.11.10=py311hd8ed1ab_3 + - debugpy=1.8.9=py311hda3d55a_0 + - freetype=2.12.1=hdaf720e_2 + - intel-openmp=2024.2.1=h57928b3_1083 + - ipykernel=6.29.5=pyh4bbf305_0 + - ipython=8.29.0=pyh7428d3b_0 + - jsonpointer=3.0.0=py311h1ea47a8_1 + - jupyter_core=5.7.2=pyh5737063_1 + - krb5=1.21.3=hdf4eb48_0 + - lcms2=2.16=h67d730c_0 + - lerc=4.0.0=h63175ca_0 + - libblas=3.9.0=25_win64_mkl + - libcblas=3.9.0=25_win64_mkl + - libdeflate=1.22=h2466b09_0 + - libexpat=2.6.4=he0c23c2_0 + - libffi=3.4.2=h8ffe710_5 + - libgcc=14.2.0=h1383e82_1 + - libgomp=14.2.0=h1383e82_1 + - libjpeg-turbo=3.0.0=hcfcfb64_1 + - liblapack=3.9.0=25_win64_mkl + - libpng=1.6.44=h3ca93ac_0 + - libsodium=1.0.20=hc70643c_0 + - libsqlite=3.47.0=h2466b09_1 + - libtiff=4.7.0=hfc51747_1 + - libwebp-base=1.4.0=hcfcfb64_0 + - libwinpthread=12.0.0.r4.gg4f2fc60ca=h57928b3_8 + - libxcb=1.17.0=h0e4246c_0 + - libzlib=1.3.1=h2466b09_2 + - markupsafe=3.0.2=py311h5082efb_0 + - mkl=2024.2.2=h66d3029_14 + - numpy=2.1.3=py311h35ffc71_0 + - openjpeg=2.5.2=h3d672ee_0 + - openssl=3.4.0=h2466b09_0 + - pandas=2.2.3=py311hcf9f919_1 + - pillow=11.0.0=py311h4fbf6a9_0 + - psutil=6.1.0=py311he736701_0 + - pthread-stubs=0.4=h0e40799_1002 + - pysocks=1.7.1=pyh0701188_6 + - python=3.11.10=hce54a09_3_cpython + - pywin32=307=py311hda3d55a_3 + - pywinpty=2.0.14=py311hda3d55a_0 + - pyyaml=6.0.2=py311he736701_1 + - pyzmq=26.2.0=py311h484c95c_3 + - rpds-py=0.21.0=py311h533ab2d_0 + - send2trash=1.8.3=pyh5737063_0 + - tbb=2021.7.0=h91493d7_0 + - terminado=0.18.1=pyh5737063_0 + - tk=8.6.13=h5226925_1 + - tornado=6.4.1=py311he736701_1 + - ucrt=10.0.22621.0=h57928b3_1 + - vc14_runtime=14.42.34433=he29a5d6_23 + - vc=14.3=ha32ba9b_23 + - vs2015_runtime=14.42.34433=hdffcdeb_23 + - win_inet_pton=1.1.0=pyh7428d3b_7 + - winpty=0.4.3=4 + - xorg-libxau=1.0.11=h0e40799_1 + - xorg-libxdmcp=1.1.5=h0e40799_0 + - xz=5.2.6=h8d14728_0 + - yaml=0.2.5=h8ffe710_2 + - zeromq=4.3.5=ha9f60a1_7 + - zstandard=0.23.0=py311h53056dc_1 + - zstd=1.5.6=h0ea2cb4_0 + pip: + - atomicwrites==1.4.1 + - cachetools==5.5.0 + - fasteners==0.19 + - google-apitools==0.5.32 + - google-auth==2.36.0 + - httplib2==0.22.0 + - neuroglancer==2.40.1 + - oauth2client==4.1.3 + - pyasn1==0.6.1 + - pyasn1-modules==0.4.1 + - pyparsing==3.2.0 + - rsa==4.9 From 1630a3d6a7801efbd6c553e61044f1eae2438c44 Mon Sep 17 00:00:00 2001 From: Demetris Roumis Date: Sat, 23 Nov 2024 12:20:29 -0800 Subject: [PATCH 16/35] add assets and thumbs --- .../assets/volumetric_imaging_header.png | Bin 0 -> 2607413 bytes .../thumbnails/volumetric_imaging.png | Bin 0 -> 1404748 bytes volumetric_imaging/volumetric_imaging.ipynb | 8 ++++++++ 3 files changed, 8 insertions(+) create mode 100644 volumetric_imaging/assets/volumetric_imaging_header.png create mode 100644 volumetric_imaging/thumbnails/volumetric_imaging.png diff --git a/volumetric_imaging/assets/volumetric_imaging_header.png b/volumetric_imaging/assets/volumetric_imaging_header.png new file mode 100644 index 0000000000000000000000000000000000000000..e650215bcf37076d7cace5f494e49a8f64720abd GIT binary patch literal 2607413 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z^%vOsV9l%_H_)Om2AXf=XdVQ_v3fl?LJ{~5&qBBSlC&w*lGVpILT_D#sS!LQx1Zz^ z-5lCaJ8yWVhPb+36CUDZ;1d5(B#*8{RqF1Dn?G_G|7GJL)WqG&PZS2^4GtfZCGx~PRDMp9q@8Ue1-wvOF-DJYr8=> z?izX{SVc08nF>u>O#ST@o}M_copS6a+vbrF$)L`xF-bdT<^?X>_cRXbkzI`1la@4X zvg?=$x6}#u9wGB`GovQqh-lvFT!=}DG-A|DB$b4V&JJ*_4ltmL0>UhvoAkiW26UCy z|8=kYfBSrB%YV%m{_8XJ@BJUi%D;6h|6Trv3hv()D*s;ohhN`+eftvr*A@S#u\n", + "\n", + "---\n", + "\n", "## Overview\n", "\n", "[Neuroglancer](https://github.com/google/neuroglancer) by Google is a WebGL-based viewer for volumetric data. It is capable of displaying arbitrary (non-axis-aligned) cross-sectional views of volumetric data, as well as 3D meshes and line-segment-based models (skeletons). It is commonly used to display massive datasets from techniques like electron microscopy (EM) in the field of neuroscience.\n", From 7e52cee732c1104481718a886d77ed4c3154e093 Mon Sep 17 00:00:00 2001 From: Demetris Roumis Date: Sat, 23 Nov 2024 12:48:20 -0800 Subject: [PATCH 17/35] set no data ingestion --- volumetric_imaging/anaconda-project.yml | 1 + 1 file changed, 1 insertion(+) diff --git a/volumetric_imaging/anaconda-project.yml b/volumetric_imaging/anaconda-project.yml index 470759e29..005325266 100644 --- a/volumetric_imaging/anaconda-project.yml +++ b/volumetric_imaging/anaconda-project.yml @@ -13,6 +13,7 @@ examples_config: deployments: - command: notebook # - command: dashboard + no_data_ingestion: true user_fields: [examples_config] From a0a24e9a518d672a55a81e56e6931bc73deb1f86 Mon Sep 17 00:00:00 2001 From: Demetris Roumis Date: Sat, 23 Nov 2024 12:48:44 -0800 Subject: [PATCH 18/35] revise intro --- volumetric_imaging/volumetric_imaging.ipynb | 45 +++++++++++++-------- 1 file changed, 29 insertions(+), 16 deletions(-) diff --git a/volumetric_imaging/volumetric_imaging.ipynb b/volumetric_imaging/volumetric_imaging.ipynb index e5d288316..fd9c4b41a 100644 --- a/volumetric_imaging/volumetric_imaging.ipynb +++ b/volumetric_imaging/volumetric_imaging.ipynb @@ -2,13 +2,8 @@ "cells": [ { "cell_type": "markdown", - "id": "3b7c8ca4-49bc-4673-9547-5571738972d6", - "metadata": { - "ExecuteTime": { - "end_time": "2024-03-29T17:25:02.532910Z", - "start_time": "2024-03-29T17:25:02.529856Z" - } - }, + "id": "761f808c-7539-4050-9f1e-d13eaf57af24", + "metadata": {}, "source": [ "# Volumetric Imaging\n", "\n", @@ -22,19 +17,37 @@ "\n", "## Overview\n", "\n", - "[Neuroglancer](https://github.com/google/neuroglancer) by Google is a WebGL-based viewer for volumetric data. It is capable of displaying arbitrary (non-axis-aligned) cross-sectional views of volumetric data, as well as 3D meshes and line-segment-based models (skeletons). It is commonly used to display massive datasets from techniques like electron microscopy (EM) in the field of neuroscience.\n", + "**Volumetric imaging** refers to techniques that capture data in three dimensions, allowing researchers to visualize and analyze the internal structures of objects, including depth and spatial relationships. Unlike traditional 2D imaging, volumetric imaging provides a more comprehensive view of specimens.\n", + "\n", + "One of the most powerful volumetric imaging techniques is **electron microscopy** ([EM](https://en.wikipedia.org/wiki/Electron_microscope)). EM uses a beam of electrons to create high-resolution images at the nanometer scale, enabling the exploration of fine structural details of biological specimens such as cells, tissues, and molecular structures. However, handling and visualizing the massive datasets generated by EM poses significant challenges due to their size and complexity.\n", "\n", - "Volumetric imaging techniques, such as EM, allow researchers to explore the fine structural details of biological specimens at nanometer resolutions. However, handling and visualizing these massive datasets pose significant challenges due to their size and complexity.\n", + "### Introducing Neuroglancer\n", "\n", - "While Neuroglancer provides a powerful browser-based tool for exploring very large volumes, it is typically used as a standalone application. Researchers often utilize Jupyter Notebooks to conduct reproducible research and encapsulate visualizations alongside code and text. Using [Panel](https://panel.holoviz.org/), we can integrate the Neuroglancer interface within the context of a research notebook or a larger HoloViz application.\n", + "[Neuroglancer](https://github.com/google/neuroglancer) by Google is a WebGL-based viewer designed specifically for volumetric data, offering efficient handling of large-scale datasets through data streaming. Its key features include:\n", "\n", - "In this workflow, we will demonstrate how to embed Neuroglancer within a Panel application, highlighting how HoloViz tools can seamlessly integrate with third-party applications to create interactive and reproducible visualizations.\n", + "- **Interactive Visualization:** Smooth, real-time navigation through volumetric data.\n", + "- **Customizable Layers:** Support for raw images, segmented regions, and annotations.\n", + "- **Web-Based Interface:** Accessible directly from browsers without the need for specialized software.\n", "\n", - "### Use Cases\n", + "Originally developed for neuroscience, Neuroglancer empowers researchers to explore complex 3D structures by tracing neural pathways, identifying cellular components, and annotating regions of interest.\n", "\n", - "- **Exploring Large Volumetric Datasets:** Integrate Neuroglancer within a Jupyter Notebook to explore volumetric data without leaving the notebook environment.\n", - "- **Combining Multiple Visualization Tools:** Use HoloViz Panel to combine Neuroglancer with other HoloViz components or custom plots.\n", - "- **Reproducible Research:** Embed the visualization directly within your code and documentation for easy sharing and collaboration.\n", + "### Integrating Neuroglancer with Jupyter Notebooks\n", + "\n", + "While Neuroglancer is a powerful tool for exploring large volumes, it is typically used as a standalone application. Researchers often utilize **Jupyter Notebooks** to conduct reproducible research and combine code, data analysis, and visualizations.\n", + "\n", + "By integrating Neuroglancer within Jupyter Notebooks using [HoloViz Panel](https://panel.holoviz.org/), researchers can:\n", + "\n", + "- **Consolidate Workflow:** Keep code, data analysis, and visualization in a single environment.\n", + "- **Enhance Reproducibility:** Share notebooks that include both computational steps and interactive visualizations.\n", + "- **Facilitate Collaboration:** Allow collaborators to interact with the same data and visualizations within the notebook.\n", + "\n", + "### Using HoloViz for the Integration\n", + "\n", + "In this workflow, we will demonstrate how to embed Neuroglancer within a Panel application, highlighting how HoloViz tools can seamlessly extend third-party applications. By using Panel, we can:\n", + "\n", + "- Embed the Neuroglancer viewer directly within a notebook cell.\n", + "- Create interactive widgets and controls to manipulate and report the state of the viewer.\n", + "- Combine Neuroglancer views alongside other visualizations.\n", "\n", "---\n", "\n", @@ -44,7 +57,7 @@ "| --- | --- | --- |\n", "| [Panel Documentation](https://panel.holoviz.org/) | Prerequisite | Familiarity with Panel for building interactive apps |\n", "\n", - "---" + "---\n" ] }, { From d0ea5753a1f1d1d72ffddd258017e96bf0ab91ee Mon Sep 17 00:00:00 2001 From: Demetris Roumis Date: Mon, 25 Nov 2024 11:49:07 -0800 Subject: [PATCH 19/35] reduce thumbnail size --- .../thumbnails/volumetric_imaging.png | Bin 1404748 -> 476164 bytes 1 file changed, 0 insertions(+), 0 deletions(-) diff --git a/volumetric_imaging/thumbnails/volumetric_imaging.png b/volumetric_imaging/thumbnails/volumetric_imaging.png index 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z^%vOsV9l%_H_)Om2AXf=XdVQ_v3fl?LJ{~5&qBBSlC&w*lGVpILT_D#sS!LQx1Zz^ z-5lCaJ8yWVhPb+36CUDZ;1d5(B#*8{RqF1Dn?G_G|7GJL)WqG&PZS2^4GtfZCGx~PRDMp9q@8Ue1-wvOF-DJYr8=> z?izX{SVc08nF>u>O#ST@o}M_copS6a+vbrF$)L`xF-bdT<^?X>_cRXbkzI`1la@4X zvg?=$x6}#u9wGB`GovQqh-lvFT!=}DG-A|DB$b4V&JJ*_4ltmL0>UhvoAkiW26UCy z|8=kYfBSrB%YV%m{_8XJ@BJUi%D;6h|6Trv3hv()D*s;ohhN`+eftvr*A@S#u Date: Wed, 4 Dec 2024 00:37:25 +0200 Subject: [PATCH 20/35] minor cleanup --- volumetric_imaging/volumetric_imaging.ipynb | 112 ++++---------------- 1 file changed, 22 insertions(+), 90 deletions(-) diff --git a/volumetric_imaging/volumetric_imaging.ipynb b/volumetric_imaging/volumetric_imaging.ipynb index fd9c4b41a..36924c178 100644 --- a/volumetric_imaging/volumetric_imaging.ipynb +++ b/volumetric_imaging/volumetric_imaging.ipynb @@ -112,7 +112,6 @@ " `neuroglancer.viewer.Viewer` instance.\n", " \"\"\"\n", "\n", - " # Demo URL for loading an example dataset\n", " DEMO_URL = \"https://neuroglancer-demo.appspot.com/#!%7B%22dimensions%22%3A%7B%22x%22%3A%5B6.000000000000001e-9%2C%22m%22%5D%2C%22y%22%3A%5B6.000000000000001e-9%2C%22m%22%5D%2C%22z%22%3A%5B3.0000000000000004e-8%2C%22m%22%5D%7D%2C%22position%22%3A%5B5029.42333984375%2C6217.5849609375%2C1182.5%5D%2C%22crossSectionScale%22%3A3.7621853549999242%2C%22projectionOrientation%22%3A%5B-0.05179581791162491%2C-0.8017329573631287%2C0.0831851214170456%2C-0.5895944833755493%5D%2C%22projectionScale%22%3A4699.372698097029%2C%22layers%22%3A%5B%7B%22type%22%3A%22image%22%2C%22source%22%3A%22precomputed%3A%2F%2Fgs%3A%2F%2Fneuroglancer-public-data%2Fkasthuri2011%2Fimage%22%2C%22tab%22%3A%22source%22%2C%22name%22%3A%22original-image%22%7D%2C%7B%22type%22%3A%22image%22%2C%22source%22%3A%22precomputed%3A%2F%2Fgs%3A%2F%2Fneuroglancer-public-data%2Fkasthuri2011%2Fimage_color_corrected%22%2C%22tab%22%3A%22source%22%2C%22name%22%3A%22corrected-image%22%7D%2C%7B%22type%22%3A%22segmentation%22%2C%22source%22%3A%22precomputed%3A%2F%2Fgs%3A%2F%2Fneuroglancer-public-data%2Fkasthuri2011%2Fground_truth%22%2C%22tab%22%3A%22source%22%2C%22selectedAlpha%22%3A0.63%2C%22notSelectedAlpha%22%3A0.14%2C%22segments%22%3A%5B%223208%22%2C%224901%22%2C%2213%22%2C%224965%22%2C%224651%22%2C%222282%22%2C%223189%22%2C%223758%22%2C%2215%22%2C%224027%22%2C%223228%22%2C%22444%22%2C%223207%22%2C%223224%22%2C%223710%22%5D%2C%22name%22%3A%22ground_truth%22%7D%5D%2C%22layout%22%3A%224panel%22%7D\"\n", "\n", " def __init__(\n", @@ -124,64 +123,53 @@ " **params,\n", " ):\n", " \"\"\"\n", - " Initialize the NeuroglancerNB class.\n", - "\n", - " Args:\n", - " source (str or neuroglancer.viewer.Viewer, optional): Source for the initial state of the viewer,\n", - " which can be a URL string or an existing neuroglancer.viewer.Viewer instance.\n", - " If None, a new viewer will be initialized without a predefined state.\n", - " aspect_ratio (float, optional): The width to height ratio for the window-responsive Neuroglancer viewer.\n", - " Default is 2.75.\n", - " show_state (bool, optional): Provides a collapsible card widget under the viewer that displays the viewer's state.\n", - " Useful for debugging. Default is False.\n", - " load_demo (bool, optional): If True, loads the demo dataset upon initialization. Default is False.\n", - " **params: Additional parameters passed to the parent class.\n", + " Initializes the NeuroglancerNB app.\n", + "\n", + " Parameters\n", + " ----------\n", + " source : str or neuroglancer.viewer.Viewer, optional\n", + " Source for the initial state of the viewer, which can be a URL string or an existing `neuroglancer.viewer.Viewer` instance.\n", + " If None, a new viewer will be initialized without a predefined state.\n", + " aspect_ratio : float, optional\n", + " The width-to-height ratio for the window-responsive Neuroglancer viewer. Default is 2.75.\n", + " show_state : bool, optional\n", + " Provides a collapsible card widget under the viewer that displays the viewer's state.\n", + " Useful for debugging. Default is False.\n", + " load_demo : bool, optional\n", + " If True, loads the demo dataset upon initialization. Default is False.\n", + " **params\n", + " Additional parameters passed to the parent class.\n", " \"\"\"\n", " super().__init__(**params)\n", - "\n", - " # Determine if a source was provided\n", " self.source_not_provided = False if source else True\n", " self.show_state = show_state\n", - "\n", - " # Initialize the Neuroglancer viewer\n", " self.viewer = (\n", " source\n", " if isinstance(source, neuroglancer.viewer.Viewer)\n", " else neuroglancer.Viewer()\n", " )\n", "\n", - " # Set up the UI components\n", " self._setup_ui_components(aspect_ratio=aspect_ratio)\n", - "\n", - " # Configure the viewer\n", " self._configure_viewer()\n", - "\n", - " # Set up callbacks for interactivity\n", " self._setup_callbacks()\n", "\n", - " # If a source URL is provided, initialize the viewer from the URL\n", " if source and not isinstance(source, neuroglancer.viewer.Viewer):\n", " self._initialize_viewer_from_url(source)\n", "\n", - " # Load the demo dataset if requested\n", " if load_demo:\n", " self.demo_button.clicks += 1\n", "\n", " def _initialize_viewer_from_url(self, source: str):\n", - " \"\"\"Initialize the viewer state from a URL.\"\"\"\n", " self.url_input.value = source\n", " self._load_state_from_url(source)\n", "\n", " def _setup_ui_components(self, aspect_ratio):\n", - " \"\"\"Set up the UI components for the application.\"\"\"\n", - " # Text input for the Neuroglancer URL\n", " self.url_input = pn.widgets.TextInput(\n", " placeholder=\"Enter a Neuroglancer URL and click Load\",\n", " name=\"Input URL\",\n", " width=700,\n", " )\n", "\n", - " # Buttons for loading and demo dataset\n", " self.load_button = pn.widgets.Button(\n", " name=\"Load\", button_type=\"primary\", width=75\n", " )\n", @@ -189,16 +177,13 @@ " name=\"Demo\", button_type=\"warning\", width=75\n", " )\n", "\n", - " # JSON pane to display the viewer state\n", " self.json_pane = pn.pane.JSON(\n", " {}, theme=\"light\", depth=2, name=\"Viewer State\", height=800, width=350\n", " )\n", "\n", - " # Markdown panes to display shareable and local URLs\n", " self.shareable_url_pane = pn.pane.Markdown(\"**Shareable URL:**\")\n", " self.local_url_pane = pn.pane.Markdown(\"**Local URL:**\")\n", "\n", - " # HTML pane to embed the Neuroglancer viewer via iframe\n", " self.iframe = pn.pane.HTML(\n", " sizing_mode=\"stretch_both\",\n", " aspect_ratio=aspect_ratio,\n", @@ -207,30 +192,22 @@ " )\n", "\n", " def _configure_viewer(self):\n", - " \"\"\"Configure the Neuroglancer viewer.\"\"\"\n", - " # Update the local URL and iframe content\n", " self._update_local_url()\n", " self._update_iframe_with_local_url()\n", "\n", " def _setup_callbacks(self):\n", - " \"\"\"Set up callbacks for interactivity.\"\"\"\n", " self.load_button.on_click(self._on_load_button_clicked)\n", " self.demo_button.on_click(self._on_demo_button_clicked)\n", - "\n", - " # Callback for when the viewer state changes\n", " self.viewer.shared_state.add_changed_callback(self._on_viewer_state_changed)\n", "\n", " def _on_demo_button_clicked(self, event):\n", - " \"\"\"Load the demo dataset when the Demo button is clicked.\"\"\"\n", " self.url_input.value = self.DEMO_URL\n", " self._load_state_from_url(self.url_input.value)\n", "\n", " def _on_load_button_clicked(self, event):\n", - " \"\"\"Load the viewer state from the provided URL.\"\"\"\n", " self._load_state_from_url(self.url_input.value)\n", "\n", " def _load_state_from_url(self, url):\n", - " \"\"\"Load the viewer state from a URL.\"\"\"\n", " try:\n", " new_state = self._parse_state_from_url(url)\n", " self.viewer.set_state(new_state)\n", @@ -238,29 +215,24 @@ " print(f\"Error loading Neuroglancer state: {e}\")\n", "\n", " def _parse_state_from_url(self, url):\n", - " \"\"\"Parse the viewer state from a Neuroglancer URL.\"\"\"\n", " return neuroglancer.parse_url(url)\n", "\n", " def _on_viewer_state_changed(self):\n", - " \"\"\"Update the UI when the viewer state changes.\"\"\"\n", " self._update_shareable_url()\n", " self._update_json_pane()\n", "\n", " def _update_shareable_url(self):\n", - " \"\"\"Update the shareable URL pane.\"\"\"\n", " shareable_url = neuroglancer.to_url(self.viewer.state)\n", " self.shareable_url_pane.object = self._generate_dropdown_markup(\n", " \"Shareable URL\", shareable_url\n", " )\n", "\n", " def _update_local_url(self):\n", - " \"\"\"Update the local URL pane.\"\"\"\n", " self.local_url_pane.object = self._generate_dropdown_markup(\n", " \"Local URL\", self.viewer.get_viewer_url()\n", " )\n", "\n", " def _update_iframe_with_local_url(self):\n", - " \"\"\"Embed the viewer in the iframe.\"\"\"\n", " iframe_style = (\n", " 'frameborder=\"0\" scrolling=\"no\" marginheight=\"0\" marginwidth=\"0\" '\n", " 'style=\"width:100%; height:100%; min-width:500px; min-height:500px;\"'\n", @@ -270,11 +242,9 @@ " )\n", "\n", " def _update_json_pane(self):\n", - " \"\"\"Update the JSON pane with the current viewer state.\"\"\"\n", " self.json_pane.object = self.viewer.state.to_json()\n", "\n", " def _generate_dropdown_markup(self, title, url):\n", - " \"\"\"Generate HTML markup for dropdown links.\"\"\"\n", " return f\"\"\"\n", "

      \n", " {title}:\n", @@ -283,14 +253,12 @@ " \"\"\"\n", "\n", " def __panel__(self):\n", - " \"\"\"Define how the class is rendered in a Panel application.\"\"\"\n", - " # Layout for controls (only visible if no source is provided)\n", + " # only visible if no source is provided\n", " controls_layout = pn.Column(\n", " pn.Row(self.demo_button, self.load_button),\n", " pn.Row(self.url_input),\n", " visible=self.source_not_provided,\n", " )\n", - " # Layout for URL links\n", " links_layout = pn.Column(self.local_url_pane, self.shareable_url_pane)\n", "\n", " state_widget = pn.Card(\n", @@ -301,7 +269,6 @@ " styles={\"background\": \"WhiteSmoke\"},\n", " max_width=350\n", " )\n", - " # Combine all components into a single layout\n", " return pn.Column(\n", " controls_layout,\n", " links_layout,\n", @@ -323,49 +290,19 @@ "source": [ "In this workflow, we'll initialize a new Neuroglancer viewer and load a dataset using a parameterized URL. This allows us to explore different datasets by simply changing the URL.\n", "\n", - "To launch an empty viewer, simply omit the `source` input. You can then use the GUI to insert and load from a parameterized URL to set the state of the new viewer. Click the **Demo** button or pass `load_demo=True` to insert an example URL dataset. You can find other demo links on the [Neuroglancer repository](https://github.com/google/neuroglancer#examples).\n" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "b5fb5bf4-83af-4180-b061-a7eac0f5ad6a", - "metadata": {}, - "outputs": [], - "source": [ - "ng_app = NeuroglancerNB(show_state=True, load_demo=True)" - ] - }, - { - "cell_type": "markdown", - "id": "3f41e92d-1e9c-4fc5-8e7b-649f758df098", - "metadata": {}, - "source": [ - "### Usage Instructions:\n", - "\n", - "1. **Load the Demo Dataset:**\n", - " - Since we passed `load_demo=True`, we'll skip this step, but otherwise you could have clicked the **Demo** button to load the example dataset.\n", + "Either use `NeuroglancerNB(source=)` or just run `NeuroglancerNB()` and input the URL in the GUI:\n", "\n", - "2. **Explore the Viewer:**\n", - " - Use the mouse and keyboard to navigate through the volumetric data.\n", - " - Adjust cross-sectional views, zoom, and rotate the 3D view.\n", - "\n", - "3. **View the Viewer State:**\n", - " - Click on the **State** card to expand and view the JSON representation of the current viewer state.\n", - " \n", - "5. **Load a Custom Dataset:**\n", - " - Enter a Neuroglancer URL in the **Input URL** field.\n", - " - Click **Load** to visualize the dataset.\n" + "To use a demo URL, either `load_demo=True` or click the **Demo** button. You can find other demo links on the [Neuroglancer repository](https://github.com/google/neuroglancer#examples).\n" ] }, { "cell_type": "code", "execution_count": null, - "id": "28700ea9-6eed-4d4c-9028-0c2ba8058d75", + "id": "b5fb5bf4-83af-4180-b061-a7eac0f5ad6a", "metadata": {}, "outputs": [], "source": [ - "ng_app" + "NeuroglancerNB(show_state=True, load_demo=True)" ] }, { @@ -399,7 +336,6 @@ "metadata": {}, "outputs": [], "source": [ - "# Create a Neuroglancer viewer and configure it\n", "viewer = neuroglancer.Viewer()\n", "\n", "with viewer.txn() as s:\n", @@ -412,11 +348,7 @@ " source=\"precomputed://gs://neuroglancer-janelia-flyem-hemibrain/v1.1/segmentation\",\n", " )\n", "\n", - "# Embed the viewer within the Panel app\n", - "ng_app_2 = NeuroglancerNB(source=viewer, show_state=True)\n", - "\n", - "# Display the app\n", - "ng_app_2" + "NeuroglancerNB(source=viewer, show_state=True)" ] }, { From 37bb551b126b9b0446837501558c8099166ca566 Mon Sep 17 00:00:00 2001 From: Demetris Roumis Date: Wed, 4 Dec 2024 01:03:07 +0200 Subject: [PATCH 21/35] add video preview --- volumetric_imaging/volumetric_imaging.ipynb | 31 +++++++++++++++++---- 1 file changed, 26 insertions(+), 5 deletions(-) diff --git a/volumetric_imaging/volumetric_imaging.ipynb b/volumetric_imaging/volumetric_imaging.ipynb index 36924c178..3c6fd3b00 100644 --- a/volumetric_imaging/volumetric_imaging.ipynb +++ b/volumetric_imaging/volumetric_imaging.ipynb @@ -2,7 +2,7 @@ "cells": [ { "cell_type": "markdown", - "id": "761f808c-7539-4050-9f1e-d13eaf57af24", + "id": "cc47db48-cd14-4874-a377-e4c13de91cdd", "metadata": {}, "source": [ "# Volumetric Imaging\n", @@ -13,8 +13,29 @@ " align=\"center\" \n", " style=\"border: 2px solid #ccc; border-radius: 8px; padding: 5px; width: 100%; box-shadow: 0px 4px 8px rgba(0,0,0,0.1);\">\n", "\n", - "---\n", - "\n", + "---" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "ef81c950-38e8-4c18-aec0-63ce70c34b1f", + "metadata": {}, + "outputs": [], + "source": [ + "from IPython.display import HTML\n", + "HTML(\"\"\"\n", + "
      \n", + " \n", + "
      \n", + "\"\"\")" + ] + }, + { + "cell_type": "markdown", + "id": "e3b92a30-50eb-4d00-ad83-0354c947f767", + "metadata": {}, + "source": [ "## Overview\n", "\n", "**Volumetric imaging** refers to techniques that capture data in three dimensions, allowing researchers to visualize and analyze the internal structures of objects, including depth and spatial relationships. Unlike traditional 2D imaging, volumetric imaging provides a more comprehensive view of specimens.\n", @@ -57,7 +78,7 @@ "| --- | --- | --- |\n", "| [Panel Documentation](https://panel.holoviz.org/) | Prerequisite | Familiarity with Panel for building interactive apps |\n", "\n", - "---\n" + "---" ] }, { @@ -76,7 +97,7 @@ { "cell_type": "code", "execution_count": null, - "id": "80f2ec05-50e3-4678-9323-09244ba5cde6", + "id": "c83a8253-e6da-485d-96cd-ce0e783ac00d", "metadata": {}, "outputs": [], "source": [ From 30b52e9430473b1a1fd7eab2ad4c6bae8e1147f8 Mon Sep 17 00:00:00 2001 From: Demetris Roumis Date: Thu, 5 Dec 2024 23:59:46 +0200 Subject: [PATCH 22/35] use params and reduce num of methods --- volumetric_imaging/volumetric_imaging.ipynb | 201 +++++++++----------- 1 file changed, 93 insertions(+), 108 deletions(-) diff --git a/volumetric_imaging/volumetric_imaging.ipynb b/volumetric_imaging/volumetric_imaging.ipynb index 3c6fd3b00..48307af87 100644 --- a/volumetric_imaging/volumetric_imaging.ipynb +++ b/volumetric_imaging/volumetric_imaging.ipynb @@ -120,107 +120,83 @@ { "cell_type": "code", "execution_count": null, - "id": "081e6201-bc6c-4afd-ab2a-f7e21de3d4c7", + "id": "ed82c0c5-1e5d-4acc-ad91-e3052c273c2d", "metadata": {}, "outputs": [], "source": [ + "import param\n", + "import panel as pn\n", + "import neuroglancer\n", + "\n", "class NeuroglancerNB(pn.viewable.Viewer):\n", " \"\"\"\n", " A HoloViz Panel app for visualizing and interacting with Neuroglancer viewers\n", " within a Jupyter Notebook.\n", - "\n", - " This app supports loading from a parameterized Neuroglancer URL or an existing\n", - " `neuroglancer.viewer.Viewer` instance.\n", " \"\"\"\n", - "\n", + " \n", + " source = param.Parameter(default=None, doc=\"\"\"\n", + " Source for the initial state of the viewer, which can be a URL string \n", + " or an existing neuroglancer.viewer.Viewer instance.\n", + " \"\"\")\n", + " height = param.Number(default=600, doc=\"height of the viewer.\")\n", + " width = param.Number(default=800, doc=\"width of the viewer.\")\n", + " show_state = param.Boolean(default=False, doc=\"Show the viewer state for debugging.\")\n", + " load_demo = param.Boolean(default=False, doc=\"Load the demo dataset on initialization.\")\n", + " \n", " DEMO_URL = \"https://neuroglancer-demo.appspot.com/#!%7B%22dimensions%22%3A%7B%22x%22%3A%5B6.000000000000001e-9%2C%22m%22%5D%2C%22y%22%3A%5B6.000000000000001e-9%2C%22m%22%5D%2C%22z%22%3A%5B3.0000000000000004e-8%2C%22m%22%5D%7D%2C%22position%22%3A%5B5029.42333984375%2C6217.5849609375%2C1182.5%5D%2C%22crossSectionScale%22%3A3.7621853549999242%2C%22projectionOrientation%22%3A%5B-0.05179581791162491%2C-0.8017329573631287%2C0.0831851214170456%2C-0.5895944833755493%5D%2C%22projectionScale%22%3A4699.372698097029%2C%22layers%22%3A%5B%7B%22type%22%3A%22image%22%2C%22source%22%3A%22precomputed%3A%2F%2Fgs%3A%2F%2Fneuroglancer-public-data%2Fkasthuri2011%2Fimage%22%2C%22tab%22%3A%22source%22%2C%22name%22%3A%22original-image%22%7D%2C%7B%22type%22%3A%22image%22%2C%22source%22%3A%22precomputed%3A%2F%2Fgs%3A%2F%2Fneuroglancer-public-data%2Fkasthuri2011%2Fimage_color_corrected%22%2C%22tab%22%3A%22source%22%2C%22name%22%3A%22corrected-image%22%7D%2C%7B%22type%22%3A%22segmentation%22%2C%22source%22%3A%22precomputed%3A%2F%2Fgs%3A%2F%2Fneuroglancer-public-data%2Fkasthuri2011%2Fground_truth%22%2C%22tab%22%3A%22source%22%2C%22selectedAlpha%22%3A0.63%2C%22notSelectedAlpha%22%3A0.14%2C%22segments%22%3A%5B%223208%22%2C%224901%22%2C%2213%22%2C%224965%22%2C%224651%22%2C%222282%22%2C%223189%22%2C%223758%22%2C%2215%22%2C%224027%22%2C%223228%22%2C%22444%22%2C%223207%22%2C%223224%22%2C%223710%22%5D%2C%22name%22%3A%22ground_truth%22%7D%5D%2C%22layout%22%3A%224panel%22%7D\"\n", "\n", - " def __init__(\n", - " self,\n", - " source=None,\n", - " aspect_ratio=2.75,\n", - " show_state=False,\n", - " load_demo=False,\n", - " **params,\n", - " ):\n", - " \"\"\"\n", - " Initializes the NeuroglancerNB app.\n", - "\n", - " Parameters\n", - " ----------\n", - " source : str or neuroglancer.viewer.Viewer, optional\n", - " Source for the initial state of the viewer, which can be a URL string or an existing `neuroglancer.viewer.Viewer` instance.\n", - " If None, a new viewer will be initialized without a predefined state.\n", - " aspect_ratio : float, optional\n", - " The width-to-height ratio for the window-responsive Neuroglancer viewer. Default is 2.75.\n", - " show_state : bool, optional\n", - " Provides a collapsible card widget under the viewer that displays the viewer's state.\n", - " Useful for debugging. Default is False.\n", - " load_demo : bool, optional\n", - " If True, loads the demo dataset upon initialization. Default is False.\n", - " **params\n", - " Additional parameters passed to the parent class.\n", - " \"\"\"\n", + " def __init__(self, **params):\n", " super().__init__(**params)\n", - " self.source_not_provided = False if source else True\n", - " self.show_state = show_state\n", - " self.viewer = (\n", - " source\n", - " if isinstance(source, neuroglancer.viewer.Viewer)\n", - " else neuroglancer.Viewer()\n", - " )\n", "\n", - " self._setup_ui_components(aspect_ratio=aspect_ratio)\n", - " self._configure_viewer()\n", - " self._setup_callbacks()\n", + " self.source_not_provided = (self.source is None)\n", + " self.viewer = (self.source if isinstance(self.source, neuroglancer.viewer.Viewer)\n", + " else neuroglancer.Viewer())\n", "\n", - " if source and not isinstance(source, neuroglancer.viewer.Viewer):\n", - " self._initialize_viewer_from_url(source)\n", - "\n", - " if load_demo:\n", - " self.demo_button.clicks += 1\n", - "\n", - " def _initialize_viewer_from_url(self, source: str):\n", - " self.url_input.value = source\n", - " self._load_state_from_url(source)\n", - "\n", - " def _setup_ui_components(self, aspect_ratio):\n", + " # Setup UI\n", " self.url_input = pn.widgets.TextInput(\n", " placeholder=\"Enter a Neuroglancer URL and click Load\",\n", " name=\"Input URL\",\n", - " width=700,\n", - " )\n", - "\n", - " self.load_button = pn.widgets.Button(\n", - " name=\"Load\", button_type=\"primary\", width=75\n", - " )\n", - " self.demo_button = pn.widgets.Button(\n", - " name=\"Demo\", button_type=\"warning\", width=75\n", - " )\n", - "\n", - " self.json_pane = pn.pane.JSON(\n", - " {}, theme=\"light\", depth=2, name=\"Viewer State\", height=800, width=350\n", + " width=self.width,\n", " )\n", - "\n", + " self.load_button = pn.widgets.Button(name=\"Load\", button_type=\"primary\", width=75)\n", + " self.demo_button = pn.widgets.Button(name=\"Demo\", button_type=\"warning\", width=75)\n", + " self.json_pane = pn.pane.JSON({}, theme=\"light\", depth=2, name=\"Viewer State\", \n", + " sizing_mode='stretch_both')\n", " self.shareable_url_pane = pn.pane.Markdown(\"**Shareable URL:**\")\n", " self.local_url_pane = pn.pane.Markdown(\"**Local URL:**\")\n", "\n", " self.iframe = pn.pane.HTML(\n", - " sizing_mode=\"stretch_both\",\n", - " aspect_ratio=aspect_ratio,\n", - " min_height=800,\n", + " # sizing_mode=\"stretch_both\",\n", + " # aspect_ratio=self.aspect_ratio,\n", + " height=self.height,\n", + " width=self.width,\n", " styles={\"resize\": \"both\", \"overflow\": \"hidden\"},\n", " )\n", "\n", - " def _configure_viewer(self):\n", - " self._update_local_url()\n", - " self._update_iframe_with_local_url()\n", + " # Configure viewer and UI\n", + " local_url = self.viewer.get_viewer_url()\n", + " self.local_url_pane.object = self._generate_dropdown_markup(\"Local URL\", local_url)\n", + " iframe_style = ('frameborder=\"0\" scrolling=\"no\" marginheight=\"0\" marginwidth=\"0\" '\n", + " 'style=\"width:100%; height:100%; min-width:500px; min-height:500px;\"')\n", + " self.iframe.object = f''\n", "\n", - " def _setup_callbacks(self):\n", + " # UI Actions\n", " self.load_button.on_click(self._on_load_button_clicked)\n", " self.demo_button.on_click(self._on_demo_button_clicked)\n", " self.viewer.shared_state.add_changed_callback(self._on_viewer_state_changed)\n", "\n", + " # If a source URL was provided, initialize the viewer from it\n", + " if self.source and not isinstance(self.source, neuroglancer.viewer.Viewer):\n", + " self._initialize_viewer_from_url(self.source)\n", + "\n", + " # Load the demo if requested\n", + " if self.load_demo:\n", + " self.demo_button.clicks += 1\n", + "\n", + " def _initialize_viewer_from_url(self, source: str):\n", + " self.url_input.value = source\n", + " self._load_state_from_url(source)\n", + "\n", " def _on_demo_button_clicked(self, event):\n", " self.url_input.value = self.DEMO_URL\n", " self._load_state_from_url(self.url_input.value)\n", @@ -230,39 +206,15 @@ "\n", " def _load_state_from_url(self, url):\n", " try:\n", - " new_state = self._parse_state_from_url(url)\n", + " new_state = neuroglancer.parse_url(url)\n", " self.viewer.set_state(new_state)\n", " except Exception as e:\n", " print(f\"Error loading Neuroglancer state: {e}\")\n", "\n", - " def _parse_state_from_url(self, url):\n", - " return neuroglancer.parse_url(url)\n", - "\n", " def _on_viewer_state_changed(self):\n", - " self._update_shareable_url()\n", - " self._update_json_pane()\n", - "\n", - " def _update_shareable_url(self):\n", + " # Update shareable URL and JSON pane\n", " shareable_url = neuroglancer.to_url(self.viewer.state)\n", - " self.shareable_url_pane.object = self._generate_dropdown_markup(\n", - " \"Shareable URL\", shareable_url\n", - " )\n", - "\n", - " def _update_local_url(self):\n", - " self.local_url_pane.object = self._generate_dropdown_markup(\n", - " \"Local URL\", self.viewer.get_viewer_url()\n", - " )\n", - "\n", - " def _update_iframe_with_local_url(self):\n", - " iframe_style = (\n", - " 'frameborder=\"0\" scrolling=\"no\" marginheight=\"0\" marginwidth=\"0\" '\n", - " 'style=\"width:100%; height:100%; min-width:500px; min-height:500px;\"'\n", - " )\n", - " self.iframe.object = (\n", - " f''\n", - " )\n", - "\n", - " def _update_json_pane(self):\n", + " self.shareable_url_pane.object = self._generate_dropdown_markup(\"Shareable URL\", shareable_url)\n", " self.json_pane.object = self.viewer.state.to_json()\n", "\n", " def _generate_dropdown_markup(self, title, url):\n", @@ -274,7 +226,6 @@ " \"\"\"\n", "\n", " def __panel__(self):\n", - " # only visible if no source is provided\n", " controls_layout = pn.Column(\n", " pn.Row(self.demo_button, self.load_button),\n", " pn.Row(self.url_input),\n", @@ -283,17 +234,19 @@ " links_layout = pn.Column(self.local_url_pane, self.shareable_url_pane)\n", "\n", " state_widget = pn.Card(\n", - " self.json_pane,\n", - " title=\"State\",\n", - " collapsed=False,\n", - " visible=self.show_state,\n", - " styles={\"background\": \"WhiteSmoke\"},\n", - " max_width=350\n", - " )\n", + " self.json_pane,\n", + " title=\"State\",\n", + " collapsed=False,\n", + " visible=self.show_state,\n", + " styles={\"background\": \"WhiteSmoke\"},\n", + " max_width=350\n", + " )\n", + "\n", " return pn.Column(\n", " controls_layout,\n", " links_layout,\n", - " pn.Row(state_widget, self.iframe))\n" + " pn.Row(state_widget, self.iframe)\n", + " )" ] }, { @@ -394,6 +347,38 @@ "\n", "---\n" ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "ccf0e62d-1171-428b-8d7c-ea7ae153663d", + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "25eb2b65-03ad-4ee0-9e06-76ff8c669b55", + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "65c8cb83-5cf3-42ba-8987-aa3e4d51da6c", + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "6d4ce38e-7f95-4c10-97a4-2a36eb77f5bd", + "metadata": {}, + "outputs": [], + "source": [] } ], "metadata": { From 9414f3ab96283119a3ba87e74def0a4f409d8e8a Mon Sep 17 00:00:00 2001 From: Demetris Roumis Date: Fri, 6 Dec 2024 00:23:07 +0200 Subject: [PATCH 23/35] add static previews and install instructions for colab --- volumetric_imaging/assets/approach1.png | Bin 0 -> 855579 bytes volumetric_imaging/assets/approach2.png | Bin 0 -> 1150039 bytes volumetric_imaging/volumetric_imaging.ipynb | 91 ++++++++++++-------- 3 files changed, 55 insertions(+), 36 deletions(-) create mode 100644 volumetric_imaging/assets/approach1.png create mode 100644 volumetric_imaging/assets/approach2.png diff --git a/volumetric_imaging/assets/approach1.png b/volumetric_imaging/assets/approach1.png new file mode 100644 index 0000000000000000000000000000000000000000..89699226ca35d57f9a47b43d41a6636633b8d666 GIT binary patch literal 855579 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z)RA_@m}xS*QvLAFS1F}0KYRH8N1smH&DY=m7;E(T_`7eV5MO-$@Pm)f-F8<;Chvx~ z&qXs$6aI7n0Dzl3e*Dw<`MJC%8mjkL&e`Gd`{4v4AqXo5000000Pz3t=+Prq)%@{> z>v!K~hyNP^0N}QW=&&CFXH5bC00000+!HN%Y_GSxj%X490RDY#G!jiX00000008$f zoxJ%vqDcS%_z&H6UNZkt0RR91004mdf!!LRZWRCkZljbU1l3&fu(`Xzy#oLM00000 z-g;`%T8k9{0D!+_t<_q$Hq2L>yDMz#1^@s6004lujV3QI*H{q%0C-coM-0PwQx^H! z6~vSP000000C4wcaK_lC#26(2000000NgE_eDL7C zCr_RlW3Vm&0B~T8S?&(YJwi(PDw?cHVK0?8V@ecx0{{R3006+>_#It}QR{c_)zJU| N002ovPDHLkV1h?t-#Y*R literal 0 HcmV?d00001 diff --git a/volumetric_imaging/volumetric_imaging.ipynb b/volumetric_imaging/volumetric_imaging.ipynb index 48307af87..475a77098 100644 --- a/volumetric_imaging/volumetric_imaging.ipynb +++ b/volumetric_imaging/volumetric_imaging.ipynb @@ -94,6 +94,17 @@ "## Imports and Configuration" ] }, + { + "cell_type": "code", + "execution_count": 49, + "id": "414a6f44-89d3-4a5b-b91d-56e99a601c61", + "metadata": {}, + "outputs": [], + "source": [ + "# For google colab, uncomment and run to install packages:\n", + "# !pip install panel neuroglancer jupyter_bokeh" + ] + }, { "cell_type": "code", "execution_count": null, @@ -276,7 +287,23 @@ "metadata": {}, "outputs": [], "source": [ - "NeuroglancerNB(show_state=True, load_demo=True)" + "# NeuroglancerNB(show_state=True, load_demo=True)" + ] + }, + { + "cell_type": "markdown", + "id": "9ab67ed5-625f-4be7-8c86-a5657c86a065", + "metadata": {}, + "source": [ + "\"Panel\n", + "\n", + "**Here's a static snapshot of what the previous cell produces. 👉**\n", + "\n", + "

      \n" ] }, { @@ -306,7 +333,7 @@ { "cell_type": "code", "execution_count": null, - "id": "27bbb3a0-270c-4f8b-ac16-b60a764f1cfc", + "id": "1d178d1c-7f5b-4be2-b000-26157cb28416", "metadata": {}, "outputs": [], "source": [ @@ -320,9 +347,33 @@ " # Add a segmentation layer\n", " s.layers[\"segmentation\"] = neuroglancer.SegmentationLayer(\n", " source=\"precomputed://gs://neuroglancer-janelia-flyem-hemibrain/v1.1/segmentation\",\n", - " )\n", + " )" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "26d8d75a-4512-4d92-8c96-a5f974fc72c7", + "metadata": {}, + "outputs": [], + "source": [ + "# NeuroglancerNB(source=viewer, show_state=True)" + ] + }, + { + "cell_type": "markdown", + "id": "94b0e8a2-4fa3-44b0-b7a4-8b43f9ad081f", + "metadata": {}, + "source": [ + "\"Panel\n", + "\n", + "**Here's a static snapshot of what the previous cell produces. 👉**\n", "\n", - "NeuroglancerNB(source=viewer, show_state=True)" + "
      \n" ] }, { @@ -347,38 +398,6 @@ "\n", "---\n" ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "ccf0e62d-1171-428b-8d7c-ea7ae153663d", - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "25eb2b65-03ad-4ee0-9e06-76ff8c669b55", - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "65c8cb83-5cf3-42ba-8987-aa3e4d51da6c", - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "6d4ce38e-7f95-4c10-97a4-2a36eb77f5bd", - "metadata": {}, - "outputs": [], - "source": [] } ], "metadata": { From 63be18fae2750b2922b7bf3c66dbe1c45797093d Mon Sep 17 00:00:00 2001 From: Demetris Roumis Date: Fri, 6 Dec 2024 00:27:44 +0200 Subject: [PATCH 24/35] remove notebook command and attempt colab command --- volumetric_imaging/anaconda-project.yml | 8 +++++--- 1 file changed, 5 insertions(+), 3 deletions(-) diff --git a/volumetric_imaging/anaconda-project.yml b/volumetric_imaging/anaconda-project.yml index 005325266..e731ca127 100644 --- a/volumetric_imaging/anaconda-project.yml +++ b/volumetric_imaging/anaconda-project.yml @@ -11,7 +11,7 @@ examples_config: - Neuroscience title: "Volumetric Imaging" deployments: - - command: notebook + # - command: notebook # - command: dashboard no_data_ingestion: true @@ -38,10 +38,12 @@ commands: windows: jupyter lab volumetric_imaging.ipynb notebook: notebook: volumetric_imaging.ipynb - dashboard: - unix: panel serve --rest-session-info --session-history -1 volumetric_imaging.ipynb --show + colab: + # unix: panel serve --rest-session-info --session-history -1 volumetric_imaging.ipynb --show + unix: open https://colab.research.google.com/github/holoviz-topics/volumetric_imaging/blob/main/volumetric_imaging.ipynb supports_http_options: true + variables: {} platforms: From 9337621a747a983f49499113d2e6082a4dccc8dc Mon Sep 17 00:00:00 2001 From: Demetris Roumis Date: Fri, 6 Dec 2024 00:32:48 +0200 Subject: [PATCH 25/35] min pin --- volumetric_imaging/anaconda-project.yml | 8 ++++---- 1 file changed, 4 insertions(+), 4 deletions(-) diff --git a/volumetric_imaging/anaconda-project.yml b/volumetric_imaging/anaconda-project.yml index e731ca127..882642786 100644 --- a/volumetric_imaging/anaconda-project.yml +++ b/volumetric_imaging/anaconda-project.yml @@ -22,13 +22,13 @@ channels: - nodefaults packages: &pkgs -- notebook>=6.5.2,<7 # required +- notebook>=6.5.2 - python=3.11 -- panel -- jupyterlab +- panel>=1.5.4 # auto min pinned 2024-12-06 +- jupyterlab>=4.3.1 # auto min pinned 2024-12-06 - pip - pip: - - neuroglancer + - neuroglancer>=2.40.1 # auto min pinned 2024-12-06 dependencies: *pkgs From d39360758961838c6a22462cccbbba4e7e31332c Mon Sep 17 00:00:00 2001 From: Demetris Roumis Date: Fri, 6 Dec 2024 00:34:17 +0200 Subject: [PATCH 26/35] restore dashboard command to resolve ae5 deploy error --- volumetric_imaging/anaconda-project.yml | 4 +++- 1 file changed, 3 insertions(+), 1 deletion(-) diff --git a/volumetric_imaging/anaconda-project.yml b/volumetric_imaging/anaconda-project.yml index 882642786..c16840ba2 100644 --- a/volumetric_imaging/anaconda-project.yml +++ b/volumetric_imaging/anaconda-project.yml @@ -38,8 +38,10 @@ commands: windows: jupyter lab volumetric_imaging.ipynb notebook: notebook: volumetric_imaging.ipynb + dashboard: + unix: panel serve --rest-session-info --session-history -1 volumetric_imaging.ipynb --show + supports_http_options: true colab: - # unix: panel serve --rest-session-info --session-history -1 volumetric_imaging.ipynb --show unix: open https://colab.research.google.com/github/holoviz-topics/volumetric_imaging/blob/main/volumetric_imaging.ipynb supports_http_options: true From 98aac872cca359cbffe6b40b2cefce003eef7c39 Mon Sep 17 00:00:00 2001 From: Demetris Roumis Date: Fri, 6 Dec 2024 00:37:25 +0200 Subject: [PATCH 27/35] minor cleanup --- volumetric_imaging/volumetric_imaging.ipynb | 2 -- 1 file changed, 2 deletions(-) diff --git a/volumetric_imaging/volumetric_imaging.ipynb b/volumetric_imaging/volumetric_imaging.ipynb index 475a77098..e0f4ca54a 100644 --- a/volumetric_imaging/volumetric_imaging.ipynb +++ b/volumetric_imaging/volumetric_imaging.ipynb @@ -177,8 +177,6 @@ " self.local_url_pane = pn.pane.Markdown(\"**Local URL:**\")\n", "\n", " self.iframe = pn.pane.HTML(\n", - " # sizing_mode=\"stretch_both\",\n", - " # aspect_ratio=self.aspect_ratio,\n", " height=self.height,\n", " width=self.width,\n", " styles={\"resize\": \"both\", \"overflow\": \"hidden\"},\n", From 23aca17db3f65a8d1ce350533bb6e8ee1efb359c Mon Sep 17 00:00:00 2001 From: Demetris Roumis Date: Fri, 6 Dec 2024 01:13:12 +0200 Subject: [PATCH 28/35] remove colab --- volumetric_imaging/anaconda-project.yml | 6 +----- volumetric_imaging/volumetric_imaging.ipynb | 11 ----------- 2 files changed, 1 insertion(+), 16 deletions(-) diff --git a/volumetric_imaging/anaconda-project.yml b/volumetric_imaging/anaconda-project.yml index c16840ba2..77f7788ea 100644 --- a/volumetric_imaging/anaconda-project.yml +++ b/volumetric_imaging/anaconda-project.yml @@ -12,7 +12,7 @@ examples_config: title: "Volumetric Imaging" deployments: # - command: notebook - # - command: dashboard + - command: dashboard no_data_ingestion: true user_fields: [examples_config] @@ -41,10 +41,6 @@ commands: dashboard: unix: panel serve --rest-session-info --session-history -1 volumetric_imaging.ipynb --show supports_http_options: true - colab: - unix: open https://colab.research.google.com/github/holoviz-topics/volumetric_imaging/blob/main/volumetric_imaging.ipynb - supports_http_options: true - variables: {} diff --git a/volumetric_imaging/volumetric_imaging.ipynb b/volumetric_imaging/volumetric_imaging.ipynb index e0f4ca54a..1ef3c7228 100644 --- a/volumetric_imaging/volumetric_imaging.ipynb +++ b/volumetric_imaging/volumetric_imaging.ipynb @@ -94,17 +94,6 @@ "## Imports and Configuration" ] }, - { - "cell_type": "code", - "execution_count": 49, - "id": "414a6f44-89d3-4a5b-b91d-56e99a601c61", - "metadata": {}, - "outputs": [], - "source": [ - "# For google colab, uncomment and run to install packages:\n", - "# !pip install panel neuroglancer jupyter_bokeh" - ] - }, { "cell_type": "code", "execution_count": null, From e22bd9f1a46e6337c603bf641207564b081c8f4e Mon Sep 17 00:00:00 2001 From: Demetris Roumis Date: Fri, 6 Dec 2024 01:13:16 +0200 Subject: [PATCH 29/35] relock --- volumetric_imaging/anaconda-project-lock.yml | 246 ++++++++++--------- 1 file changed, 131 insertions(+), 115 deletions(-) diff --git a/volumetric_imaging/anaconda-project-lock.yml b/volumetric_imaging/anaconda-project-lock.yml index 75221c719..103a4e5d3 100644 --- a/volumetric_imaging/anaconda-project-lock.yml +++ b/volumetric_imaging/anaconda-project-lock.yml @@ -17,7 +17,7 @@ locking_enabled: true env_specs: default: locked: true - env_spec_hash: 9416c0a974d1a3397dd9a05e428fac41c98afeac + env_spec_hash: d394747b111fb937e4709cee44a9d55e485797b9 platforms: - linux-64 - osx-64 @@ -26,126 +26,124 @@ env_specs: packages: all: - anyio=4.6.2.post1=pyhd8ed1ab_0 - - argon2-cffi=23.1.0=pyhd8ed1ab_0 + - argon2-cffi=23.1.0=pyhd8ed1ab_1 - arrow=1.3.0=pyhd8ed1ab_0 - - asttokens=2.4.1=pyhd8ed1ab_0 + - asttokens=3.0.0=pyhd8ed1ab_1 - async-lru=2.0.4=pyhd8ed1ab_0 - attrs=24.2.0=pyh71513ae_0 - - babel=2.16.0=pyhd8ed1ab_0 - - beautifulsoup4=4.12.3=pyha770c72_0 - - bleach=6.2.0=pyhd8ed1ab_0 - - bokeh=3.6.1=pyhd8ed1ab_0 + - babel=2.16.0=pyhd8ed1ab_1 + - beautifulsoup4=4.12.3=pyha770c72_1 + - bleach=6.2.0=pyhd8ed1ab_1 + - bokeh=3.6.2=pyhd8ed1ab_0 - cached-property=1.5.2=hd8ed1ab_1 - cached_property=1.5.2=pyha770c72_1 - certifi=2024.8.30=pyhd8ed1ab_0 - - charset-normalizer=3.4.0=pyhd8ed1ab_0 - - colorama=0.4.6=pyhd8ed1ab_0 + - charset-normalizer=3.4.0=pyhd8ed1ab_1 + - colorama=0.4.6=pyhd8ed1ab_1 - comm=0.2.2=pyhd8ed1ab_0 - - decorator=5.1.1=pyhd8ed1ab_0 + - decorator=5.1.1=pyhd8ed1ab_1 - defusedxml=0.7.1=pyhd8ed1ab_0 - - entrypoints=0.4=pyhd8ed1ab_0 - - exceptiongroup=1.2.2=pyhd8ed1ab_0 + - entrypoints=0.4=pyhd8ed1ab_1 + - exceptiongroup=1.2.2=pyhd8ed1ab_1 - executing=2.1.0=pyhd8ed1ab_0 - - fqdn=1.5.1=pyhd8ed1ab_0 - - h11=0.14.0=pyhd8ed1ab_0 - - h2=4.1.0=pyhd8ed1ab_0 - - hpack=4.0.0=pyh9f0ad1d_0 + - fqdn=1.5.1=pyhd8ed1ab_1 + - h11=0.14.0=pyhd8ed1ab_1 + - h2=4.1.0=pyhd8ed1ab_1 + - hpack=4.0.0=pyhd8ed1ab_1 - httpcore=1.0.7=pyh29332c3_1 - - httpx=0.27.2=pyhd8ed1ab_0 - - hyperframe=6.0.1=pyhd8ed1ab_0 - - idna=3.10=pyhd8ed1ab_0 - - importlib-metadata=8.5.0=pyha770c72_0 - - importlib_resources=6.4.5=pyhd8ed1ab_0 - - ipython_genutils=0.2.0=pyhd8ed1ab_1 + - httpx=0.28.0=pyhd8ed1ab_0 + - hyperframe=6.0.1=pyhd8ed1ab_1 + - idna=3.10=pyhd8ed1ab_1 + - importlib-metadata=8.5.0=pyha770c72_1 + - importlib_resources=6.4.5=pyhd8ed1ab_1 - isoduration=20.11.0=pyhd8ed1ab_0 - - jedi=0.19.2=pyhff2d567_0 - - jinja2=3.1.4=pyhd8ed1ab_0 - - json5=0.9.28=pyhff2d567_0 + - jedi=0.19.2=pyhd8ed1ab_1 + - jinja2=3.1.4=pyhd8ed1ab_1 + - json5=0.10.0=pyhd8ed1ab_1 - jsonschema-specifications=2024.10.1=pyhd8ed1ab_0 - jsonschema-with-format-nongpl=4.23.0=hd8ed1ab_0 - jsonschema=4.23.0=pyhd8ed1ab_0 - jupyter-lsp=2.2.5=pyhd8ed1ab_0 - - jupyter_client=7.4.9=pyhd8ed1ab_0 + - jupyter_client=8.6.3=pyhd8ed1ab_0 - jupyter_events=0.10.0=pyhd8ed1ab_0 - - jupyter_server=2.14.2=pyhd8ed1ab_0 - - jupyter_server_terminals=0.5.3=pyhd8ed1ab_0 - - jupyterlab=4.3.1=pyhff2d567_0 - - jupyterlab_pygments=0.3.0=pyhd8ed1ab_1 + - jupyter_server=2.14.2=pyhd8ed1ab_1 + - jupyter_server_terminals=0.5.3=pyhd8ed1ab_1 + - jupyterlab=4.3.2=pyhd8ed1ab_0 + - jupyterlab_pygments=0.3.0=pyhd8ed1ab_2 - jupyterlab_server=2.27.3=pyhd8ed1ab_0 - linkify-it-py=2.0.3=pyhd8ed1ab_0 - - markdown-it-py=3.0.0=pyhd8ed1ab_0 + - markdown-it-py=3.0.0=pyhd8ed1ab_1 - markdown=3.6=pyhd8ed1ab_0 - - matplotlib-inline=0.1.7=pyhd8ed1ab_0 + - matplotlib-inline=0.1.7=pyhd8ed1ab_1 - mdit-py-plugins=0.4.2=pyhd8ed1ab_0 - - mdurl=0.1.2=pyhd8ed1ab_0 - - mistune=3.0.2=pyhd8ed1ab_0 - - nbclassic=1.1.0=pyhd8ed1ab_0 - - nbclient=0.10.0=pyhd8ed1ab_0 - - nbconvert-core=7.16.4=pyhd8ed1ab_1 - - nbformat=5.10.4=pyhd8ed1ab_0 - - nest-asyncio=1.6.0=pyhd8ed1ab_0 - - notebook-shim=0.2.4=pyhd8ed1ab_0 - - notebook=6.5.7=pyha770c72_0 + - mdurl=0.1.2=pyhd8ed1ab_1 + - mistune=3.0.2=pyhd8ed1ab_1 + - nbclient=0.10.1=pyhd8ed1ab_0 + - nbconvert-core=7.16.4=pyhff2d567_2 + - nbformat=5.10.4=pyhd8ed1ab_1 + - nest-asyncio=1.6.0=pyhd8ed1ab_1 + - notebook-shim=0.2.4=pyhd8ed1ab_1 + - notebook=7.3.1=pyhd8ed1ab_0 - overrides=7.7.0=pyhd8ed1ab_0 - - packaging=24.2=pyhff2d567_1 + - packaging=24.2=pyhd8ed1ab_2 - pandocfilters=1.5.0=pyhd8ed1ab_0 - panel=1.5.4=pyhd8ed1ab_0 - param=2.1.1=pyhff2d567_0 - - parso=0.8.4=pyhd8ed1ab_0 - - pickleshare=0.7.5=py_1003 + - parso=0.8.4=pyhd8ed1ab_1 + - pickleshare=0.7.5=pyhd8ed1ab_1004 - pip=24.3.1=pyh8b19718_0 - - pkgutil-resolve-name=1.3.10=pyhd8ed1ab_1 - - platformdirs=4.3.6=pyhd8ed1ab_0 - - prometheus_client=0.21.0=pyhd8ed1ab_0 - - prompt-toolkit=3.0.48=pyha770c72_0 + - pkgutil-resolve-name=1.3.10=pyhd8ed1ab_2 + - platformdirs=4.3.6=pyhd8ed1ab_1 + - prometheus_client=0.21.1=pyhd8ed1ab_0 + - prompt-toolkit=3.0.48=pyha770c72_1 - pure_eval=0.2.3=pyhd8ed1ab_0 - - pycparser=2.22=pyhd8ed1ab_0 - - pygments=2.18.0=pyhd8ed1ab_0 - - python-dateutil=2.9.0.post0=pyhff2d567_0 - - python-fastjsonschema=2.20.0=pyhd8ed1ab_0 + - pycparser=2.22=pyh29332c3_1 + - pygments=2.18.0=pyhd8ed1ab_1 + - python-dateutil=2.9.0.post0=pyhff2d567_1 + - python-fastjsonschema=2.21.1=pyhd8ed1ab_0 - python-json-logger=2.0.7=pyhd8ed1ab_0 - - python-tzdata=2024.2=pyhd8ed1ab_0 + - python-tzdata=2024.2=pyhd8ed1ab_1 - python_abi=3.11=5_cp311 - pytz=2024.1=pyhd8ed1ab_0 - pyviz_comms=3.0.3=pyhd8ed1ab_0 - - referencing=0.35.1=pyhd8ed1ab_0 - - requests=2.32.3=pyhd8ed1ab_0 + - referencing=0.35.1=pyhd8ed1ab_1 + - requests=2.32.3=pyhd8ed1ab_1 - rfc3339-validator=0.1.4=pyhd8ed1ab_0 - rfc3986-validator=0.1.1=pyh9f0ad1d_0 - - setuptools=75.6.0=pyhff2d567_0 - - six=1.16.0=pyh6c4a22f_0 - - sniffio=1.3.1=pyhd8ed1ab_0 + - setuptools=75.6.0=pyhff2d567_1 + - six=1.17.0=pyhd8ed1ab_0 + - sniffio=1.3.1=pyhd8ed1ab_1 - soupsieve=2.5=pyhd8ed1ab_1 - stack_data=0.6.2=pyhd8ed1ab_0 - tinycss2=1.4.0=pyhd8ed1ab_0 - - tomli=2.1.0=pyhff2d567_0 - - tqdm=4.67.0=pyhd8ed1ab_0 - - traitlets=5.14.3=pyhd8ed1ab_0 - - types-python-dateutil=2.9.0.20241003=pyhff2d567_0 - - typing-extensions=4.12.2=hd8ed1ab_0 - - typing_extensions=4.12.2=pyha770c72_0 - - typing_utils=0.1.0=pyhd8ed1ab_0 + - tomli=2.2.1=pyhd8ed1ab_1 + - tqdm=4.67.1=pyhd8ed1ab_0 + - traitlets=5.14.3=pyhd8ed1ab_1 + - types-python-dateutil=2.9.0.20241003=pyhd8ed1ab_1 + - typing-extensions=4.12.2=hd8ed1ab_1 + - typing_extensions=4.12.2=pyha770c72_1 + - typing_utils=0.1.0=pyhd8ed1ab_1 - tzdata=2024b=hc8b5060_0 - uc-micro-py=1.0.3=pyhd8ed1ab_0 - - uri-template=1.3.0=pyhd8ed1ab_0 - - urllib3=2.2.3=pyhd8ed1ab_0 - - wcwidth=0.2.13=pyhd8ed1ab_0 - - webcolors=24.8.0=pyhd8ed1ab_0 - - webencodings=0.5.1=pyhd8ed1ab_2 - - websocket-client=1.8.0=pyhd8ed1ab_0 - - wheel=0.45.1=pyhd8ed1ab_0 - - xyzservices=2024.9.0=pyhd8ed1ab_0 - - zipp=3.21.0=pyhd8ed1ab_0 + - uri-template=1.3.0=pyhd8ed1ab_1 + - urllib3=2.2.3=pyhd8ed1ab_1 + - wcwidth=0.2.13=pyhd8ed1ab_1 + - webcolors=24.11.1=pyhd8ed1ab_0 + - webencodings=0.5.1=pyhd8ed1ab_3 + - websocket-client=1.8.0=pyhd8ed1ab_1 + - wheel=0.45.1=pyhd8ed1ab_1 + - xyzservices=2024.9.0=pyhd8ed1ab_1 + - zipp=3.21.0=pyhd8ed1ab_1 unix: - - ipython=8.29.0=pyh707e725_0 + - ipython=8.30.0=pyh707e725_0 - jupyter_core=5.7.2=pyh31011fe_1 - - pexpect=4.9.0=pyhd8ed1ab_0 - - ptyprocess=0.7.0=pyhd3deb0d_0 - - pysocks=1.7.1=pyha2e5f31_6 + - pexpect=4.9.0=pyhd8ed1ab_1 + - ptyprocess=0.7.0=pyhd8ed1ab_1 + - pysocks=1.7.1=pyha55dd90_7 osx: - - appnope=0.1.4=pyhd8ed1ab_0 + - appnope=0.1.4=pyhd8ed1ab_1 - ipykernel=6.29.5=pyh57ce528_0 - - send2trash=1.8.3=pyh31c8845_0 + - send2trash=1.8.3=pyh31c8845_1 - terminado=0.18.1=pyh31c8845_0 linux-64: - _libgcc_mutex=0.1=conda_forge @@ -178,6 +176,8 @@ env_specs: - libgomp=14.2.0=h77fa898_1 - libjpeg-turbo=3.0.0=hd590300_1 - liblapack=3.9.0=25_linux64_openblas + - liblzma-devel=5.6.3=hb9d3cd8_1 + - liblzma=5.6.3=hb9d3cd8_1 - libnsl=2.0.1=hd590300_0 - libopenblas=0.3.28=pthreads_h94d23a6_1 - libpng=1.6.44=hadc24fc_0 @@ -191,7 +191,7 @@ env_specs: - libxcb=1.17.0=h8a09558_0 - libxcrypt=4.4.36=hd590300_1 - libzlib=1.3.1=hb9d3cd8_2 - - markupsafe=3.0.2=py311h2dc5d0c_0 + - markupsafe=3.0.2=py311h2dc5d0c_1 - ncurses=6.5=he02047a_1 - numpy=2.1.3=py311h71ddf71_0 - openjpeg=2.5.2=h488ebb8_0 @@ -200,18 +200,20 @@ env_specs: - pillow=11.0.0=py311h49e9ac3_0 - psutil=6.1.0=py311h9ecbd09_0 - pthread-stubs=0.4=hb9d3cd8_1002 - - python=3.11.10=hc5c86c4_3_cpython + - python=3.11.11=h9e4cc4f_1_cpython - pyyaml=6.0.2=py311h9ecbd09_1 - pyzmq=26.2.0=py311h7deb3e3_3 - readline=8.2=h8228510_1 - - rpds-py=0.21.0=py311h9e33e62_0 - - send2trash=1.8.3=pyh0d859eb_0 + - rpds-py=0.22.3=py311h9e33e62_0 + - send2trash=1.8.3=pyh0d859eb_1 - terminado=0.18.1=pyh0d859eb_0 - tk=8.6.13=noxft_h4845f30_101 - - tornado=6.4.1=py311h9ecbd09_1 + - tornado=6.4.2=py311h9ecbd09_0 - xorg-libxau=1.0.11=hb9d3cd8_1 - xorg-libxdmcp=1.1.5=hb9d3cd8_0 - - xz=5.2.6=h166bdaf_0 + - xz-gpl-tools=5.6.3=hbcc6ac9_1 + - xz-tools=5.6.3=hb9d3cd8_1 + - xz=5.6.3=hbcc6ac9_1 - yaml=0.2.5=h7f98852_2 - zeromq=4.3.5=h3b0a872_7 - zstandard=0.23.0=py311hbc35293_1 @@ -231,7 +233,7 @@ env_specs: - lerc=4.0.0=hb486fe8_0 - libblas=3.9.0=25_osx64_openblas - libcblas=3.9.0=25_osx64_openblas - - libcxx=19.1.4=hf95d169_0 + - libcxx=19.1.5=hf95d169_0 - libdeflate=1.22=h00291cd_0 - libedit=3.1.20191231=h0678c8f_2 - libexpat=2.6.4=h240833e_0 @@ -240,6 +242,8 @@ env_specs: - libgfortran=5.0.0=13_2_0_h97931a8_3 - libjpeg-turbo=3.0.0=h0dc2134_1 - liblapack=3.9.0=25_osx64_openblas + - liblzma-devel=5.6.3=hd471939_1 + - liblzma=5.6.3=hd471939_1 - libopenblas=0.3.28=openmp_hbf64a52_1 - libpng=1.6.44=h4b8f8c9_0 - libsodium=1.0.20=hfdf4475_0 @@ -248,8 +252,8 @@ env_specs: - libwebp-base=1.4.0=h10d778d_0 - libxcb=1.17.0=hf1f96e2_0 - libzlib=1.3.1=hd23fc13_2 - - llvm-openmp=19.1.4=ha54dae1_0 - - markupsafe=3.0.2=py311h8b4e8a7_0 + - llvm-openmp=19.1.5=ha54dae1_0 + - markupsafe=3.0.2=py311ha3cf9ac_1 - ncurses=6.5=hf036a51_1 - numpy=2.1.3=py311h14ed71f_0 - openjpeg=2.5.2=h7310d3a_0 @@ -258,18 +262,20 @@ env_specs: - pillow=11.0.0=py311h1f68098_0 - psutil=6.1.0=py311h1314207_0 - pthread-stubs=0.4=h00291cd_1002 - - pyobjc-core=10.3.1=py311hd6939f8_1 - - pyobjc-framework-cocoa=10.3.1=py311hd6939f8_1 - - python=3.11.10=ha513fb2_3_cpython + - pyobjc-core=10.3.2=py311hfbc4093_0 + - pyobjc-framework-cocoa=10.3.2=py311hfbc4093_0 + - python=3.11.11=h9ccd52b_1_cpython - pyyaml=6.0.2=py311h3336109_1 - pyzmq=26.2.0=py311h4d3da15_3 - readline=8.2=h9e318b2_1 - - rpds-py=0.21.0=py311h3b9c2be_0 + - rpds-py=0.22.3=py311h3b9c2be_0 - tk=8.6.13=h1abcd95_1 - - tornado=6.4.1=py311h3336109_1 + - tornado=6.4.2=py311h4d7f069_0 - xorg-libxau=1.0.11=h00291cd_1 - xorg-libxdmcp=1.1.5=h00291cd_0 - - xz=5.2.6=h775f41a_0 + - xz-gpl-tools=5.6.3=h357f2ed_1 + - xz-tools=5.6.3=hd471939_1 + - xz=5.6.3=h357f2ed_1 - yaml=0.2.5=h0d85af4_2 - zeromq=4.3.5=h7130eaa_7 - zstandard=0.23.0=py311hdf6fcd6_1 @@ -289,7 +295,7 @@ env_specs: - lerc=4.0.0=h9a09cb3_0 - libblas=3.9.0=25_osxarm64_openblas - libcblas=3.9.0=25_osxarm64_openblas - - libcxx=19.1.4=ha82da77_0 + - libcxx=19.1.5=ha82da77_0 - libdeflate=1.22=hd74edd7_0 - libedit=3.1.20191231=hc8eb9b7_2 - libexpat=2.6.4=h286801f_0 @@ -298,6 +304,8 @@ env_specs: - libgfortran=5.0.0=13_2_0_hd922786_3 - libjpeg-turbo=3.0.0=hb547adb_1 - liblapack=3.9.0=25_osxarm64_openblas + - liblzma-devel=5.6.3=h39f12f2_1 + - liblzma=5.6.3=h39f12f2_1 - libopenblas=0.3.28=openmp_hf332438_1 - libpng=1.6.44=hc14010f_0 - libsodium=1.0.20=h99b78c6_0 @@ -306,8 +314,8 @@ env_specs: - libwebp-base=1.4.0=h93a5062_0 - libxcb=1.17.0=hdb1d25a_0 - libzlib=1.3.1=h8359307_2 - - llvm-openmp=19.1.4=hdb05f8b_0 - - markupsafe=3.0.2=py311h56c23cb_0 + - llvm-openmp=19.1.5=hdb05f8b_0 + - markupsafe=3.0.2=py311h4921393_1 - ncurses=6.5=h7bae524_1 - numpy=2.1.3=py311h649a571_0 - openjpeg=2.5.2=h9f1df11_0 @@ -316,18 +324,20 @@ env_specs: - pillow=11.0.0=py311h3894ae9_0 - psutil=6.1.0=py311hae2e1ce_0 - pthread-stubs=0.4=hd74edd7_1002 - - pyobjc-core=10.3.1=py311h09e6bbd_1 - - pyobjc-framework-cocoa=10.3.1=py311h09e6bbd_1 - - python=3.11.10=hc51fdd5_3_cpython + - pyobjc-core=10.3.2=py311hab620ed_0 + - pyobjc-framework-cocoa=10.3.2=py311hab620ed_0 + - python=3.11.11=hc22306f_1_cpython - pyyaml=6.0.2=py311h460d6c5_1 - pyzmq=26.2.0=py311h730b646_3 - readline=8.2=h92ec313_1 - - rpds-py=0.21.0=py311h3ff9189_0 + - rpds-py=0.22.3=py311h3ff9189_0 - tk=8.6.13=h5083fa2_1 - - tornado=6.4.1=py311h460d6c5_1 + - tornado=6.4.2=py311h917b07b_0 - xorg-libxau=1.0.11=hd74edd7_1 - xorg-libxdmcp=1.1.5=hd74edd7_0 - - xz=5.2.6=h57fd34a_0 + - xz-gpl-tools=5.6.3=h9a6d368_1 + - xz-tools=5.6.3=h39f12f2_1 + - xz=5.6.3=h9a6d368_1 - yaml=0.2.5=h3422bc3_2 - zeromq=4.3.5=hc1bb282_7 - zstandard=0.23.0=py311ha60cc69_1 @@ -340,12 +350,12 @@ env_specs: - ca-certificates=2024.8.30=h56e8100_0 - cffi=1.17.1=py311he736701_0 - contourpy=1.3.1=py311h3257749_0 - - cpython=3.11.10=py311hd8ed1ab_3 + - cpython=3.11.11=py311hd8ed1ab_1 - debugpy=1.8.9=py311hda3d55a_0 - freetype=2.12.1=hdaf720e_2 - intel-openmp=2024.2.1=h57928b3_1083 - ipykernel=6.29.5=pyh4bbf305_0 - - ipython=8.29.0=pyh7428d3b_0 + - ipython=8.30.0=pyh7428d3b_0 - jsonpointer=3.0.0=py311h1ea47a8_1 - jupyter_core=5.7.2=pyh5737063_1 - krb5=1.21.3=hdf4eb48_0 @@ -358,8 +368,12 @@ env_specs: - libffi=3.4.2=h8ffe710_5 - libgcc=14.2.0=h1383e82_1 - libgomp=14.2.0=h1383e82_1 + - libhwloc=2.11.2=default_ha69328c_1001 + - libiconv=1.17=hcfcfb64_2 - libjpeg-turbo=3.0.0=hcfcfb64_1 - liblapack=3.9.0=25_win64_mkl + - liblzma-devel=5.6.3=h2466b09_1 + - liblzma=5.6.3=h2466b09_1 - libpng=1.6.44=h3ca93ac_0 - libsodium=1.0.20=hc70643c_0 - libsqlite=3.47.0=h2466b09_1 @@ -367,8 +381,9 @@ env_specs: - libwebp-base=1.4.0=hcfcfb64_0 - libwinpthread=12.0.0.r4.gg4f2fc60ca=h57928b3_8 - libxcb=1.17.0=h0e4246c_0 + - libxml2=2.13.5=h442d1da_0 - libzlib=1.3.1=h2466b09_2 - - markupsafe=3.0.2=py311h5082efb_0 + - markupsafe=3.0.2=py311h5082efb_1 - mkl=2024.2.2=h66d3029_14 - numpy=2.1.3=py311h35ffc71_0 - openjpeg=2.5.2=h3d672ee_0 @@ -377,27 +392,28 @@ env_specs: - pillow=11.0.0=py311h4fbf6a9_0 - psutil=6.1.0=py311he736701_0 - pthread-stubs=0.4=h0e40799_1002 - - pysocks=1.7.1=pyh0701188_6 - - python=3.11.10=hce54a09_3_cpython + - pysocks=1.7.1=pyh09c184e_7 + - python=3.11.11=h3f84c4b_1_cpython - pywin32=307=py311hda3d55a_3 - pywinpty=2.0.14=py311hda3d55a_0 - pyyaml=6.0.2=py311he736701_1 - pyzmq=26.2.0=py311h484c95c_3 - - rpds-py=0.21.0=py311h533ab2d_0 - - send2trash=1.8.3=pyh5737063_0 - - tbb=2021.7.0=h91493d7_0 + - rpds-py=0.22.3=py311h533ab2d_0 + - send2trash=1.8.3=pyh5737063_1 + - tbb=2021.13.0=h62715c5_1 - terminado=0.18.1=pyh5737063_0 - tk=8.6.13=h5226925_1 - - tornado=6.4.1=py311he736701_1 + - tornado=6.4.2=py311he736701_0 - ucrt=10.0.22621.0=h57928b3_1 - vc14_runtime=14.42.34433=he29a5d6_23 - vc=14.3=ha32ba9b_23 - vs2015_runtime=14.42.34433=hdffcdeb_23 - - win_inet_pton=1.1.0=pyh7428d3b_7 + - win_inet_pton=1.1.0=pyh7428d3b_8 - winpty=0.4.3=4 - xorg-libxau=1.0.11=h0e40799_1 - xorg-libxdmcp=1.1.5=h0e40799_0 - - xz=5.2.6=h8d14728_0 + - xz-tools=5.6.3=h2466b09_1 + - xz=5.6.3=h208afaa_1 - yaml=0.2.5=h8ffe710_2 - zeromq=4.3.5=ha9f60a1_7 - zstandard=0.23.0=py311h53056dc_1 From 686973903c5c1ee16e5330ee7d01fbbb098d59a7 Mon Sep 17 00:00:00 2001 From: Demetris Roumis Date: Fri, 6 Dec 2024 01:41:04 +0200 Subject: [PATCH 30/35] adjust assets and thumbnail --- .../assets/volumetric_imaging_header.png | Bin 2607413 -> 1634907 bytes .../thumbnails/volumetric_imaging.png | Bin 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