{
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "\n# Zoom-level dependent labels\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "If there are many data points, their labels may be difficult to read. To selectively display\nlabels depending on the zoom level, use the :class:`plotly.graph_objects.FigureWidget` class and\nregister a callback.\n\n.. hint::\n\n   You will need to install the |anywidget| package to use\n   the :class:`plotly.graph_objects.FigureWidget` class. See\n   the [Plotly documentation](https://plotly.com/python/figurewidget)_ for details.\n\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "collapsed": false
      },
      "outputs": [],
      "source": [
        "import functools\n\nimport plotly\nimport plotly.graph_objects as go\nimport scipy\n\nfrom pdendro import attach_dendrogram\n\nX = plotly.data.iris()[[\"sepal_length\", \"sepal_width\", \"petal_length\", \"petal_width\"]]\nZ = scipy.cluster.hierarchy.linkage(X)\n\nfig = go.FigureWidget()\n_ = attach_dendrogram(fig, Z)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "The following code registers a callback to change labels on zooming:\n\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "collapsed": false
      },
      "outputs": [],
      "source": [
        "def update_ticks(axis, axis_range, all_ticktext, max_n_ticks):\n    \"\"\"Update ticks for limiting the number.\"\"\"\n    step = int(abs(axis_range[1]-axis_range[0])//max_n_ticks) + 1\n    axis.update(tickvals=list(range(0, len(all_ticktext), step)), ticktext=all_ticktext[::step])\n\n# axis for data point labels\naxis = fig.layout.xaxis\n\n# get all labels\nall_ticks = zip(axis.tickvals, axis.ticktext, strict=True)\nall_ticks = sorted(all_ticks, key=lambda item: item[0])\n_, all_ticktext = zip(*all_ticks, strict=True)\n\n# register a callback\ncallback = functools.partial(update_ticks, all_ticktext=all_ticktext, max_n_ticks=5)\naxis.on_change(callback, \"range\")\n\n# initialize\ncallback(axis, axis.range)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "The figure can be shown as follows:\n\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "collapsed": false
      },
      "outputs": [],
      "source": [
        "fig"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "<div class=\"alert alert-info\"><h4>Note</h4><p>The figure is not displayed in the documentation because\n   the :class:`plotly.graph_objects.FigureWidget` object can only be displayed in |jupyter|.\n   The following images illustrate the appearance at various zoom levels:\n\n   .. image:: /_galleries/examples/data_point_label/zoomed_out_figure.svg\n      :alt: zoomed-out figure\n      :align: center\n\n   .. image :: /_galleries/examples/data_point_label/zoomed_in_figure.svg\n      :alt: zoomed-in figure\n      :align: center</p></div>\n\n"
      ]
    }
  ],
  "metadata": {
    "kernelspec": {
      "display_name": "Python 3",
      "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": "3.14.4"
    }
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  "nbformat": 4,
  "nbformat_minor": 0
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