fish1-release/tutorials.html at main · VCG/fish1-release · GitHub

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    <title>Tutorials | Fish1 Release</title>

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  <body>
    <header class="site-header">
      <div class="branding">
        <a class="site-title" aria-label="Fish1 Release" href="/">
          Fish1 Release
        </a>
      </div>
    </header>

    <div class="content">
      <article class="feature-image">
        <header
          id="main"
          style="background-image: url('/assets/img/fish1_banner.png')"
        >
          <div class="title-padder">
            <h1 class="title">Tutorials</h1>
          </div>
        </header>

        <section class="post-content">
          <h2 id="tutorials">Programmatic Access to Fish1 Dataset</h2>

          <p>
            These tutorials guide you through using the
            <a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10402030/"
              >CAVE (Connectome Annotation and Versioning Engine)</a
            >
            to access and analyze the <strong>Fish1 dataset</strong>.
          </p>

          <p>
            The links below open in the Jupyter Notebook viewer (read-only). To
            execute code, download the notebooks from
            <a href="https://github.com/VCG/cave-scripts" target="_blank"
              >VCG/cave-scripts</a
            >
            or run them directly in
            <a href="https://colab.research.google.com" target="_blank"
              >Google Colab</a
            >.
          </p>
          <h3>Setup CAVE</h3>
          <p><strong>Local Machine</p></strong>
          <ul>
            <li>
              Download example notebooks from the repository:
              <img src="/assets/img/tutorials/github_download.png" alt="" />
            </li>
            <li>
              Install the CAVE client:
              Please refer to the <a href="https://github.com/VCG/cave-scripts" target="_blank">cave-scripts page</a> for more details.
              <!-- <pre><code class="language-python">pip install caveclient</code></pre> -->
            </li>
            <li>
              Configure your credentials following the
              <a
                href="https://github.com/seung-lab/CAVEclient"
                target="_blank"
                >CAVEclient documentation</a
              >.
            </li>
          </ul>

          <p><strong>Google Colab</strong></p>
          <ol>
            <li>
              Go to <strong>File → Open Notebook → GitHub</strong>  (at the left panel).
              <img src="/assets/img/tutorials/github_import.png" alt="" />
            </li>
            <li>
              Search for:
              <i>VCG/cave-scripts</i> and open
              <i>notebooks/fish1/Setup_CAVE.ipynb</i>.
            </li>
            <li>
              Add code cell and type command to install the CAVEclient package:
              <pre><code class="language-python">!pip install caveclient</code></pre>
            </li>
          </ol>

          <h3>Upload your Annotation Table</h3>

          <ul>
            <li>
              Choose a data <a href="https://global.brain-wire-test.org/schema/views/" target="_blank">schema</a> and <a
              href="https://nbviewer.org/github/VCG/cave-scripts/blob/master/notebooks/fish1/Create_Tables.ipynb" target="_blank"
              >create</a> an annotation table.
            </li>
            <li>
              <a
                href="https://nbviewer.org/github/VCG/cave-scripts/blob/master/notebooks/fish1/Upload_Data.ipynb" target="_blank"
                >Upload</a>
                your custom annotations to the table.
            </li>
          </ul>

          <h3>Query the Dataset</h3>
          <ul>
            <li>
              <a
                href="https://nbviewer.org/github/VCG/cave-scripts/blob/master/notebooks/fish1/Query_Materializtion.ipynb" target="_blank"
                >Query</a
              >
              data from materialized annotation table.
            </li>
            <li>
              Explore and analyze <a
              href="https://nbviewer.org/github/VCG/cave-scripts/blob/master/notebooks/fish1/Query_Synapses.ipynb" target="_blank"
              >synapses</a
            > querying by pre-synaptic or post-synaptic cells.
            </li>
          </ul>

          <h3>Use Cases</h3>
          <ul>
            <li>
              <a
              href="https://github.com/VCG/cave-scripts/blob/master/notebooks/fish1/Use_Cases.ipynb" target="_blank"
              >Lookup</a
            > Root ID by Coordinates
          <pre><code class="language-python">def get_latest_root_id(x, y, z):
    supervoxel_id = cv.download_point(pt=(x, y, z),
                                      size=1,
                                      agglomerate=False,
                                      coord_resolution=resolution)
    supervoxel_id = np.int64(supervoxel_id[0, 0, 0, 0])
    print(f"supervoxel_id: {supervoxel_id}")
    root_id = cggraph.get_root_id(supervoxel_id)
    print(f"root_id: {root_id}")
    is_latest = cggraph.is_latest_roots([root_id])
    if not is_latest:
        latest_root_id = cggraph.get_latest_roots(root_id)
        print(f"latest_root_id: {latest_root_id}")
    else:
        latest_root_id = root_id
        print("root_id is the latest")

    return supervoxel_id, root_id, latest_root_id</code></pre>
    <p>Example:</p>
    <pre><code class="language-python">supervoxel_id, root_id, latest_root_id = get_latest_root_id(37880, 22443, 4595)</code></pre>

          <div class="code-results">
            <code>Decompressing: 100%|██████████| 1/1 [00:00<00:00, 389.84it/s] <br />
              supervoxel_id: 82407780375333845 <br />
              root_id: 864691128652664051 <br />
              root_id is the latest</code>
          </div>
        </li>

          <!-- <li>Lookup Latest Root ID
          <pre><code class="language-python">
old_root_id = 123456789
latest_root = client.chunkedgraph.get_latest_roots([old_root_id])
print("Latest root ID:", latest_root[0])
          </code></pre>
          </li> -->
        </ul>


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