overlay_hists.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "2f3f9394-0609-43e4-9b73-3602fa4c4bb7",
   "metadata": {},
   "source": [
    "# Test Overlay.hist"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ba07e8bf-c7ac-4c49-b918-c256b8b28bf4",
   "metadata": {},
   "source": [
    "## Test NdOverlay"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "fbb18b35-4918-43fc-98b2-b783920df56d",
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import holoviews as hv\n",
    "\n",
    "hv.extension('bokeh')\n",
    "\n",
    "\n",
    "points_dct = {\n",
    "    'p1': hv.Points(np.random.randn(1000, 2), kdims=['x', 'y'], label='p1'),\n",
    "    'p2': hv.Points(np.random.randn(1000, 2) -5, kdims=['x', 'y'], label='p2')\n",
    "}\n",
    "nd_overlay = hv.NdOverlay(points_dct, kdims='cat')\n",
    "plot = nd_overlay.hist()\n",
    "print(repr(plot))\n",
    "plot"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5a68c4fe-8426-40fe-a92c-42e2877a4d91",
   "metadata": {},
   "source": [
    "### Test NdOverlay with given dimensions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "cb64434e-48c5-428f-8941-46444ff97116",
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import holoviews as hv\n",
    "\n",
    "hv.extension('bokeh')\n",
    "\n",
    "\n",
    "points_dct = {\n",
    "    'p1': hv.Points(np.random.randn(1000, 2), kdims=['x', 'y'], label='p1'),\n",
    "    'p2': hv.Points(np.random.randn(1000, 2) -5, kdims=['x', 'y'], label='p2')\n",
    "}\n",
    "nd_overlay = hv.NdOverlay(points_dct, kdims='cat')\n",
    "plot = nd_overlay.hist(dimension=['x','y'])\n",
    "print(repr(plot))\n",
    "plot"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0db7a4fc-4d71-452f-9e43-81d046cb92ea",
   "metadata": {},
   "source": [
    "### Test NdOverlay colormap"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "111e1319-22bb-4e51-b98e-7f79a299491f",
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import holoviews as hv\n",
    "\n",
    "hv.extension('bokeh')\n",
    "\n",
    "color_cycle = hv.Cycle(['green', 'purple', 'yellow'])\n",
    "\n",
    "\n",
    "points_dct = {\n",
    "    'p1': hv.Points(np.random.randn(1000, 2), kdims=['x', 'y'], label='p1'),\n",
    "    'p2': hv.Points(np.random.randn(1000, 2) -5, kdims=['x', 'y'], label='p2')\n",
    "}\n",
    "nd_overlay = hv.NdOverlay(points_dct, kdims='cat').options(hv.opts.Points(color=color_cycle))\n",
    "plot = nd_overlay.hist(dimension=['x','y']).opts(hv.opts.Histogram(color=color_cycle))\n",
    "print(repr(plot))\n",
    "plot"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0173496f-3571-4eaf-9bcb-ae53dcfe8e33",
   "metadata": {},
   "source": [
    "### Test NdOverlay without adjoint"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "d4f225c8-7a83-4ff4-b857-b40a5675655f",
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import holoviews as hv\n",
    "\n",
    "hv.extension('bokeh')\n",
    "\n",
    "\n",
    "points_dct = {\n",
    "    'p1': hv.Points(np.random.randn(1000, 2), kdims=['x', 'y'], label='p1'),\n",
    "    'p2': hv.Points(np.random.randn(1000, 2) -5, kdims=['x', 'y'], label='p2')\n",
    "}\n",
    "nd_overlay = hv.NdOverlay(points_dct, kdims='cat')\n",
    "plot = nd_overlay.hist(dimension=['x','y'], adjoin=False)\n",
    "print(repr(plot))\n",
    "plot"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "28b29f13-dd0b-4aad-b1d4-9175caa06aee",
   "metadata": {},
   "source": [
    "### Test NdOverlay with label index"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "13649114-4761-4052-a4cb-ec47259c3151",
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import holoviews as hv\n",
    "\n",
    "hv.extension('bokeh')\n",
    "\n",
    "\n",
    "points_dct = {\n",
    "    'p1': hv.Points(np.random.randn(1000, 2), kdims=['x', 'y'], label='p1'),\n",
    "    'p2': hv.Points(np.random.randn(1000, 2) -5, kdims=['x', 'y'], label='p2')\n",
    "}\n",
    "nd_overlay = hv.NdOverlay(points_dct, kdims='cat')\n",
    "plot = nd_overlay.hist(dimension=['x','y'], index='p2')\n",
    "print(repr(plot))\n",
    "plot"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e409ecea-f5e8-437e-b824-23a17a1ac8dc",
   "metadata": {},
   "source": [
    "### Test NdOverlay with integer index"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "a41ebb14-0740-4602-bcf2-866b4ded5d89",
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import holoviews as hv\n",
    "\n",
    "hv.extension('bokeh')\n",
    "\n",
    "\n",
    "points_dct = {\n",
    "    'p1': hv.Points(np.random.randn(1000, 2), kdims=['x', 'y'], label='p1'),\n",
    "    'p2': hv.Points(np.random.randn(1000, 2) -5, kdims=['x', 'y'], label='p2')\n",
    "}\n",
    "nd_overlay = hv.NdOverlay(points_dct, kdims='cat')\n",
    "plot = nd_overlay.hist(dimension=['x','y'], index=0)\n",
    "print(repr(plot))\n",
    "plot"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cc0144cc-2d43-42de-9bb7-271fa38abe66",
   "metadata": {},
   "source": [
    "### Test NdOverlay with single dimension"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "7f8b17c3-8cc8-44c0-85a4-6eae38cd397e",
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import holoviews as hv\n",
    "\n",
    "hv.extension('bokeh')\n",
    "\n",
    "\n",
    "points_dct = {\n",
    "    'p1': hv.Points(np.random.randn(1000, 2), kdims=['x', 'y'], label='p1'),\n",
    "    'p2': hv.Points(np.random.randn(1000, 2) -5, kdims=['x', 'y'], label='p2')\n",
    "}\n",
    "nd_overlay = hv.NdOverlay(points_dct, kdims='cat')\n",
    "plot = nd_overlay.hist(dimension='x')\n",
    "print(repr(plot))\n",
    "plot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "28c8e631-2952-4d9f-94e1-8cadb5f6fe8c",
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import holoviews as hv\n",
    "\n",
    "hv.extension('bokeh')\n",
    "\n",
    "\n",
    "points_dct = {\n",
    "    'p1': hv.Points(np.random.randn(1000, 2), kdims=['x', 'y'], label='p1'),\n",
    "    'p2': hv.Points(np.random.randn(1000, 2) -5, kdims=['x', 'y'], label='p2')\n",
    "}\n",
    "nd_overlay = hv.NdOverlay(points_dct, kdims='cat')\n",
    "plot = nd_overlay.hist(dimension='y')\n",
    "print(repr(plot))\n",
    "plot"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f33e8286-8f9e-44f6-8ff4-2cec6a1dc2de",
   "metadata": {},
   "source": [
    "## Test Overlay"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "6d294a61-930e-46c0-b64b-5a1253cf7a64",
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import holoviews as hv\n",
    "\n",
    "hv.extension('bokeh')\n",
    "\n",
    "\n",
    "pts1 = hv.Points(np.random.randn(1000, 2) , kdims=['x', 'y'], label='p1l')\n",
    "pts2 = hv.Points(np.random.randn(1000, 2) - 5, kdims=['x', 'y'], label='p2l')\n",
    "pts_overlay = hv.Overlay([pts1, pts2])\n",
    "plot = pts_overlay.hist()\n",
    "print(repr(plot))\n",
    "plot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "bbed3441-a7db-478d-807f-807042db4521",
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import holoviews as hv\n",
    "\n",
    "hv.extension('bokeh')\n",
    "\n",
    "\n",
    "pts1 = hv.Points(np.random.randn(1000, 2) , kdims=['x', 'y'], label='p1l')\n",
    "pts2 = hv.Points(np.random.randn(1000, 2) - 5, kdims=['x', 'y'], label='p2l')\n",
    "pts_overlay = pts1 * pts2\n",
    "plot = pts_overlay.hist()\n",
    "print(repr(plot))\n",
    "plot"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b302dcf4-0cf6-41f8-985f-1f7e9520bd64",
   "metadata": {},
   "source": [
    "### Test Overlay with given dimensions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "c25d00f1-e8d1-4b32-8189-a719b575569b",
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import holoviews as hv\n",
    "\n",
    "hv.extension('bokeh')\n",
    "\n",
    "\n",
    "pts1 = hv.Points(np.random.randn(1000, 2) , kdims=['x', 'y'], label='p1l')\n",
    "pts2 = hv.Points(np.random.randn(1000, 2) - 5, kdims=['x', 'y'], label='p2l')\n",
    "pts_overlay = pts1 * pts2\n",
    "plot = pts_overlay.hist(dimension=['x','y'])\n",
    "print(repr(plot))\n",
    "plot"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0060f122-fd21-463a-b641-788cd3a2f5fc",
   "metadata": {},
   "source": [
    "### Test Overlay colormap"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "e112116f-07c5-47e0-aaa1-65c328a0499b",
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import holoviews as hv\n",
    "\n",
    "hv.extension('bokeh')\n",
    "\n",
    "color_cycle = hv.Cycle(['green', 'purple', 'yellow'])\n",
    "\n",
    "pts1 = hv.Points(np.random.randn(1000, 2) , kdims=['x', 'y'], label='p1l')\n",
    "pts2 = hv.Points(np.random.randn(1000, 2) - 5, kdims=['x', 'y'], label='p2l')\n",
    "pts_overlay = (pts1 * pts2).options(hv.opts.Points(color=color_cycle))\n",
    "plot = pts_overlay.hist(dimension=['x','y']).opts(hv.opts.Histogram(color=color_cycle))\n",
    "print(repr(plot))\n",
    "plot"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "89cc800f-2d22-4bd5-8975-31cf2a6d36d2",
   "metadata": {},
   "source": [
    "### Test overlay single dimension"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "d8cafa3c-c4d3-45ac-ac2a-30d6eafba311",
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import holoviews as hv\n",
    "\n",
    "hv.extension('bokeh')\n",
    "\n",
    "\n",
    "pts1 = hv.Points(np.random.randn(1000, 2) , kdims=['x', 'y'], label='p1l')\n",
    "pts2 = hv.Points(np.random.randn(1000, 2) - 5, kdims=['x', 'y'], label='p2l')\n",
    "pts_overlay = pts1 * pts2\n",
    "plot = pts_overlay.hist(dimension='x')\n",
    "print(repr(plot))\n",
    "plot"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ae50d792-6e16-41fc-94da-d2a83e258dab",
   "metadata": {},
   "source": [
    "## Test regular element"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "267a4d15-61af-48b4-8445-7a47762ce3bc",
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import holoviews as hv\n",
    "\n",
    "hv.extension('bokeh')\n",
    "\n",
    "\n",
    "pts = hv.Points(np.random.randn(1000, 2), kdims=['x', 'y'], label='p1')\n",
    "pts.hist(dimension=['x','y'])"
   ]
  }
 ],
 "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": "3.9.6"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}