#holoviz anndata interface.md

 

.gitignore

/data/

hatch.toml

[envs.default]
installer = "uv"
dependencies = [
    # jupyter
    "ipykernel", "ipywidgets",
    # data stuff
    "scanpy", "numba>=0.60",
    # visualization
    "holoviews", "plotly",
]

playground.ipynb

{"cells":[{"cell_type":"code","execution_count":1,"metadata":{},"outputs":[],"source":["!hatch run true"]},{"cell_type":"code","execution_count":2,"metadata":{},"outputs":[],"source":["import holoviews as hv\n","import scanpy as sc"]},{"cell_type":"code","execution_count":3,"metadata":{},"outputs":[{"data":{"text/html":["<script type=\"esms-options\">{\"shimMode\": true}</script><style>*[data-root-id],\n","*[data-root-id] > * {\n","  box-sizing: border-box;\n","  font-family: var(--jp-ui-font-family);\n","  font-size: var(--jp-ui-font-size1);\n","  color: var(--vscode-editor-foreground, var(--jp-ui-font-color1));\n","}\n","\n","/* Override VSCode background color */\n",".cell-output-ipywidget-background:has(\n","    > .cell-output-ipywidget-background > .lm-Widget > *[data-root-id]\n","  ),\n",".cell-output-ipywidget-background:has(> .lm-Widget > *[data-root-id]) {\n","  background-color: transparent 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if (css_urls == null) css_urls = [];\n    if (js_urls == null) js_urls = [];\n    if (js_modules == null) js_modules = [];\n    if (js_exports == null) js_exports = {};\n\n    root._bokeh_onload_callbacks.push(callback);\n\n    if (root._bokeh_is_loading > 0) {\n      // Don't load bokeh if it is still initializing\n      console.debug(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n      return null;\n    } else if (js_urls.length === 0 && js_modules.length === 0 && Object.keys(js_exports).length === 0) {\n      // There is nothing to load\n      run_callbacks();\n      return null;\n    }\n\n    function on_load() {\n      root._bokeh_is_loading--;\n      if (root._bokeh_is_loading === 0) {\n        console.debug(\"Bokeh: all BokehJS libraries/stylesheets loaded\");\n        run_callbacks()\n      }\n    }\n    window._bokeh_on_load = on_load\n\n    function on_error(e) {\n      const src_el = e.srcElement\n      console.error(\"failed to load \" + (src_el.href || src_el.src));\n    }\n\n    const skip = [];\n    if (window.requirejs) {\n      window.requirejs.config({'packages': {}, 'paths': {}, 'shim': {}});\n      root._bokeh_is_loading = css_urls.length + 0;\n    } else {\n      root._bokeh_is_loading = css_urls.length + js_urls.length + js_modules.length + Object.keys(js_exports).length;\n    }\n\n    const existing_stylesheets = []\n    const links = document.getElementsByTagName('link')\n    for (let i = 0; i < links.length; i++) {\n      const link = links[i]\n      if (link.href != null) {\n        existing_stylesheets.push(link.href)\n      }\n    }\n    for (let i = 0; i < css_urls.length; i++) {\n      const url = css_urls[i];\n      const escaped = encodeURI(url)\n      if (existing_stylesheets.indexOf(escaped) !== -1) {\n        on_load()\n        continue;\n      }\n      const element = document.createElement(\"link\");\n      element.onload = on_load;\n      element.onerror = on_error;\n      element.rel = \"stylesheet\";\n   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library: \", url);\n      document.head.appendChild(element);\n    }\n    for (let i = 0; i < js_modules.length; i++) {\n      const url = js_modules[i];\n      const escaped = encodeURI(url)\n      if (skip.indexOf(escaped) !== -1 || existing_scripts.indexOf(escaped) !== -1) {\n        if (!window.requirejs) {\n          on_load();\n        }\n        continue;\n      }\n      var element = document.createElement('script');\n      element.onload = on_load;\n      element.onerror = on_error;\n      element.async = false;\n      element.src = url;\n      element.type = \"module\";\n      console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n      document.head.appendChild(element);\n    }\n    for (const name in js_exports) {\n      const url = js_exports[name];\n      const escaped = encodeURI(url)\n      if (skip.indexOf(escaped) >= 0 || root[name] != null) {\n        if (!window.requirejs) {\n          on_load();\n        }\n        continue;\n      }\n      var element = document.createElement('script');\n      element.onerror = on_error;\n      element.async = false;\n      element.type = \"module\";\n      console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n      element.textContent = `\n      import ${name} from \"${url}\"\n      window.${name} = ${name}\n      window._bokeh_on_load()\n      `\n      document.head.appendChild(element);\n    }\n    if (!js_urls.length && !js_modules.length) {\n      on_load()\n    }\n  };\n\n  function inject_raw_css(css) {\n    const element = document.createElement(\"style\");\n    element.appendChild(document.createTextNode(css));\n    document.body.appendChild(element);\n  }\n\n  const js_urls = [\"https://cdn.holoviz.org/panel/1.5.3/dist/bundled/reactiveesm/es-module-shims@^1.10.0/dist/es-module-shims.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-3.6.0.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-gl-3.6.0.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-widgets-3.6.0.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-tables-3.6.0.min.js\", \"https://cdn.holoviz.org/panel/1.5.3/dist/panel.min.js\"];\n  const js_modules = [];\n  const js_exports = {};\n  const css_urls = [];\n  const inline_js = [    function(Bokeh) {\n      Bokeh.set_log_level(\"info\");\n    },\nfunction(Bokeh) {} // ensure no trailing comma for IE\n  ];\n\n  function run_inline_js() {\n    if ((root.Bokeh !== undefined) || (force === true)) {\n      for (let i = 0; i < inline_js.length; i++) {\n        try {\n          inline_js[i].call(root, root.Bokeh);\n        } catch(e) {\n          if (!reloading) {\n            throw e;\n          }\n        }\n      }\n      // Cache old bokeh versions\n      if (Bokeh != undefined && !reloading) {\n        var NewBokeh = root.Bokeh;\n        if (Bokeh.versions === undefined) {\n          Bokeh.versions = new Map();\n        }\n        if (NewBokeh.version !== Bokeh.version) {\n  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root._bokeh_timeout) {\n      // If the timeout and bokeh was not successfully loaded we reset\n      // everything and try loading again\n      root._bokeh_timeout = Date.now() + 5000;\n      root._bokeh_is_initializing = false;\n      root._bokeh_onload_callbacks = undefined;\n      root._bokeh_is_loading = 0\n      console.log(\"Bokeh: BokehJS was loaded multiple times but one version failed to initialize.\");\n      load_or_wait();\n    } else if (root._bokeh_is_initializing || (typeof root._bokeh_is_initializing === \"undefined\" && root._bokeh_onload_callbacks !== undefined)) {\n      setTimeout(load_or_wait, 100);\n    } else {\n      root._bokeh_is_initializing = true\n      root._bokeh_onload_callbacks = []\n      const bokeh_loaded = root.Bokeh != null && (root.Bokeh.version === py_version || (root.Bokeh.versions !== undefined && root.Bokeh.versions.has(py_version)));\n      if (!reloading && !bokeh_loaded) {\n        if (root.Bokeh) {\n          root.Bokeh = undefined;\n     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auto()\n","\n","\n","@dataclass\n","class AnnDataProxy:\n","    adata: sc.AnnData\n","\n","    @overload\n","    def get(self, k: str, /, default: None = None) -> np.ndarray | None: ...\n","    @overload\n","    def get(self, k: str, /, default: np.ndarray | Raise) -> np.ndarray: ...\n","    def get(self, k: str, /, default: np.ndarray | Raise | None = None) -> np.ndarray | None:\n","        k_orig = k\n","        if \".\" not in k:\n","            if default is not Raise.Sentry and k not in self.adata.var_names:\n","                return default\n","            return self.adata[:, k].X.flatten()\n","        attr_name, k = k.split(\".\", 1)\n","        attr = getattr(self.adata, attr_name)\n","        if \".\" not in k:\n","            if default is not Raise.Sentry and k not in attr:\n","                return default\n","            return attr[k]\n","        k, i = k.split(\".\", 1)\n","        arr = attr[k]\n","        if \".\" not in i:\n","            if default is not Raise.Sentry and not (0 <= int(i) < arr.shape[1]):\n","                return default\n","            return arr[:, int(i)]\n","        raise KeyError(k_orig)\n","\n","    def __contains__(self, k: str) -> bool:\n","        return self.get(k) is not None\n","\n","    def __getitem__(self, k: str) -> object:\n","        return self.get(k, Raise.Sentry)\n","    \n","    def __len__(self) -> int:\n","        return len(self.adata)\n","\n","class AnnDataInterface(hv.core.Interface):\n","    types = (sc.AnnData,)\n","    datatype = \"anndata\"\n","\n","    @classmethod\n","    def init(cls, eltype, data: sc.AnnData | AnnDataProxy, kdims: list[str] | None, vdims: list[str] | None) -> tuple[AnnDataProxy, dict]:\n","        proxy = AnnDataProxy(data) if isinstance(data, sc.AnnData) else data\n","        return proxy, {'kdims': kdims, 'vdims': vdims}, {}\n","    \n","    @classmethod\n","    def values(\n","        cls,\n","        data: hv.Dataset,\n","        dim: hv.Dimension | str,\n","        expanded=True,\n","        flat=True,\n","        compute=True,\n","        keep_index=False,\n","    ) -> np.ndarray:\n","        dim = data.get_dimension(dim)\n","        proxy = cast(AnnDataProxy, data.data)\n","        return proxy[dim.name]\n","    \n","    @classmethod\n","    def dimension_type(cls, data: hv.Dataset, dim: hv.Dimension | str) -> np.dtype:\n","        dim = data.get_dimension(dim)\n","        proxy = cast(AnnDataProxy, data.data)\n","        return proxy[dim.name].dtype\n","\n","if AnnDataInterface.datatype not in hv.core.data.datatypes:\n","    hv.core.data.datatypes.append(AnnDataInterface.datatype)\n","hv.core.Interface.register(AnnDataInterface)"]},{"cell_type":"code","execution_count":6,"metadata":{},"outputs":[{"data":{},"metadata":{},"output_type":"display_data"},{"data":{"application/vnd.holoviews_exec.v0+json":"","text/html":["<div id='p1004'>\n","  <div id=\"ae765926-ccf9-422c-a2a0-0a27edc6a6e4\" data-root-id=\"p1004\" style=\"display: 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