docs/source/notebooks/custom-dot-t-functionality.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "727140f5-5fc0-4db9-8f55-d1c455dc9f79",
   "metadata": {
    "nbsphinx": "hidden",
    "tags": [
     "nbconvert-hide"
    ]
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "c:\\users\\chsta\\documents\\github\\arpes\\arpes\\config.py:54: UserWarning: Could not find local configuration file. If you don't have one, you can safely ignore this message.\n",
      "  warnings.warn(msg)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Activating auto-logging. Current session state plus future input saved.\n",
      "Filename       : logs\\unnamed_2021-07-26_10-39-44.log\n",
      "Mode           : backup\n",
      "Output logging : False\n",
      "Raw input log  : False\n",
      "Timestamping   : False\n",
      "State          : active\n"
     ]
    }
   ],
   "source": [
    "\"\"\"nbconvert header\n",
    "\n",
    "We are just configuring to hide some unnecessary warnings.\n",
    "\"\"\"\n",
    "\n",
    "import arpes.config\n",
    "arpes.config.DOCS_BUILD = True"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "da1daf9f-92b4-4828-97f4-de4e76294899",
   "metadata": {},
   "source": [
    "# Non-ARPES Specific `xarray` Extensions\n",
    "\n",
    "Whereas `.S` contains extensions specific to ARPES, general extensions to the `xarray` methods provided by PyARPES are found on the `.G` extension.\n",
    "\n",
    "This extension is available on both `xr.Dataset` and `xr.DataArray` instances. For more detail, consult the docstrings and source for `arpes.xarray_extensions.GenericAccessorTools`.\n",
    "\n",
    "## Iteration\n",
    "\n",
    "### Iteration along one or more dimensions\n",
    "\n",
    "`iterate_axis` allows iteration along one or more axes in the dataset. The produced value is a generator (you can think of this like a list) that contains pairs of coordinate values for the dimensions specified for iteration, and a cut of the data at those specific coordinates. As an example for ARPES, this allows you to iterate along either EDCs or MDCs by using `.iterate_axis('phi')` or `.iterate_axis('eV')` respectively.\n",
    "\n",
    "Here is an example."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "83ff3232-a06f-4343-96f2-0fc3decab496",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[0.37454012, 0.95071431, 0.73199394],\n",
       "       [0.59865848, 0.15601864, 0.15599452],\n",
       "       [0.05808361, 0.86617615, 0.60111501]])"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Set the random seed so that you get the same numbers\n",
    "import numpy as np\n",
    "np.random.seed(42)\n",
    "\n",
    "\n",
    "import xarray as xr\n",
    "import arpes.xarray_extensions # so .G is in scope\n",
    "\n",
    "test_data = xr.DataArray(\n",
    "    np.random.random((3,3)), \n",
    "    coords={\"X\": [0, 1, 2], \"Y\": [-5, -4, -3]},\n",
    "    dims=[\"X\", \"Y\"]\n",
    ")\n",
    "test_data.values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "fa2a289a-5413-40c5-a3c1-91cc997b696a",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Constant X\n",
      "{'X': 0} [0.37454012 0.95071431 0.73199394]\n",
      "{'X': 1} [0.59865848 0.15601864 0.15599452]\n",
      "{'X': 2} [0.05808361 0.86617615 0.60111501]\n",
      "\n",
      "Constant Y\n",
      "{'Y': -5} [0.37454012 0.59865848 0.05808361]\n",
      "{'Y': -4} [0.95071431 0.15601864 0.86617615]\n",
      "{'Y': -3} [0.73199394 0.15599452 0.60111501]\n"
     ]
    }
   ],
   "source": [
    "print(\"Constant X\")\n",
    "for coordinate, constant_x_cut in test_data.G.iterate_axis(\"X\"):\n",
    "    print(coordinate, constant_x_cut.values)\n",
    "    \n",
    "print(\"\\nConstant Y\")\n",
    "for coordinate, constant_y_cut in test_data.G.iterate_axis(\"Y\"):\n",
    "    print(coordinate, constant_y_cut.values)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "182a3227-955e-4373-a079-2e514c81cb7f",
   "metadata": {},
   "source": [
    "### Iteration only across coordinates\n",
    "\n",
    "`iter_coords` allows you to iterate across only the coordinates of a `DataArray`, without also iterating across the data values. This can be useful if you would like to transform the coordinates before selection, or would only like access to the coordinates."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "d3c35d6a-7ea3-43a9-9050-30476d14cbca",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{'X': 0, 'Y': -5}\n",
      "{'X': 0, 'Y': -4}\n",
      "{'X': 0, 'Y': -3}\n",
      "{'X': 1, 'Y': -5}\n",
      "{'X': 1, 'Y': -4}\n",
      "{'X': 1, 'Y': -3}\n",
      "{'X': 2, 'Y': -5}\n",
      "{'X': 2, 'Y': -4}\n",
      "{'X': 2, 'Y': -3}\n"
     ]
    }
   ],
   "source": [
    "for coordinate in test_data.G.iter_coords():\n",
    "    print(coordinate)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f88f2238-40b2-43f4-8817-1ef33e9c924d",
   "metadata": {},
   "source": [
    "You can also iterate simultaneously over the coordinates and their indices in the data with `enumerate_iter_coords`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "f3bb1324-35a5-46a0-a753-c6907efc34d2",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(0, 0) {'X': 0, 'Y': -5}\n",
      "(0, 1) {'X': 0, 'Y': -4}\n",
      "(0, 2) {'X': 0, 'Y': -3}\n",
      "(1, 0) {'X': 1, 'Y': -5}\n",
      "(1, 1) {'X': 1, 'Y': -4}\n",
      "(1, 2) {'X': 1, 'Y': -3}\n",
      "(2, 0) {'X': 2, 'Y': -5}\n",
      "(2, 1) {'X': 2, 'Y': -4}\n",
      "(2, 2) {'X': 2, 'Y': -3}\n"
     ]
    }
   ],
   "source": [
    "for index, coordinate in test_data.G.enumerate_iter_coords():\n",
    "    print(index, coordinate)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a3bc154c-a87c-4c89-80ad-b4dd654505f7",
   "metadata": {},
   "source": [
    "## Raveling/Flattening\n",
    "\n",
    "It is sometimes necessary to have access to the data in a flat format where each of the coordinates has the full size of the data. The most common usecase is in preparing an isosurface plot, but this functionality is also used internally in the coordinate conversion code.\n",
    "\n",
    "The return value is a dictionary, with keys equal to all the dimension names, plus a special key \"data\" for the values of the array."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "2a4b0761-9b2d-42bb-9aa4-e2f652d20379",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<mpl_toolkits.mplot3d.art3d.Poly3DCollection at 0x1e0b33d1130>"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
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      "text/plain": [
       "<Figure size 648x648 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "from arpes.io import example_data\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "data = example_data.temperature_dependence.spectrum.sel(\n",
    "    eV=slice(-0.08, 0.05), phi=slice(-0.22, None)).sum(\"eV\")\n",
    "\n",
    "raveled = data.G.ravel()\n",
    "fig = plt.figure(figsize=(9,9))\n",
    "ax = fig.gca(projection=\"3d\")\n",
    "\n",
    "ax.plot_trisurf(\n",
    "    raveled[\"temperature\"], # use temperature as the X coordinates\n",
    "    raveled[\"phi\"],         # use phi as the Y coordinates\n",
    "    data.values.T.ravel()   # use the intensity as the Z coordinate\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c11f119b-3987-455a-b72d-5c2bf53c7bc7",
   "metadata": {},
   "source": [
    "## Coordinate manipulation\n",
    "\n",
    "You can also get a flat representation of the coordinates and data of a one dimensional dataset using `to_arrays`. This is especially valuable since the result can be [* splatted](https://docs.python.org/3/tutorial/controlflow.html#unpacking-argument-lists) into an invocation of a scatter plot."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "43c401cf-1ad4-4f9e-8243-6fc5774a330c",
   "metadata": {},
   "outputs": [
    {
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       "  --xr-font-color3: rgba(255, 255, 255, 0.38);\n",
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       "  --xr-background-color: #111111;\n",
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       "  --xr-background-color-row-odd: #313131;\n",
       "}\n",
       "\n",
       ".xr-wrap {\n",
       "  display: block;\n",
       "  min-width: 300px;\n",
       "  max-width: 700px;\n",
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       "\n",
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       "}\n",
       "\n",
       ".xr-header > div,\n",
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       "  margin-bottom: 0;\n",
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       "\n",
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       "\n",
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       "  color: var(--xr-font-color2);\n",
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       "\n",
       ".xr-sections {\n",
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       "\n",
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       "\n",
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       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-section-item input + label {\n",
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       "\n",
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       "\n",
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       "\n",
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       "\n",
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       "\n",
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       "\n",
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       "\n",
       ".xr-array-wrap {\n",
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       "\n",
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       "\n",
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       "\n",
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       ".xr-array-data {\n",
       "  padding: 0 5px !important;\n",
       "  grid-column: 2;\n",
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       "\n",
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       "  display: none;\n",
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       "\n",
       ".xr-array-in:checked ~ .xr-array-data,\n",
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       "\n",
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       "\n",
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       "\n",
       ".xr-attrs dt,\n",
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       "}\n",
       "\n",
       ".xr-attrs dt {\n",
       "  font-weight: normal;\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-attrs dt:hover span {\n",
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       "\n",
       ".xr-attrs dd {\n",
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       "\n",
       ".xr-icon-database,\n",
       ".xr-icon-file-text2 {\n",
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       "  fill: currentColor;\n",
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray (Y: 3)&gt;\n",
       "array([1.03128222, 1.97290909, 1.48910347])\n",
       "Coordinates:\n",
       "  * Y        (Y) int32 -5 -4 -3</pre><div class='xr-wrap' hidden><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'></div><ul class='xr-dim-list'><li><span class='xr-has-index'>Y</span>: 3</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-10319045-d760-4bf2-97cf-a78cbf1232c6' class='xr-array-in' type='checkbox' checked><label for='section-10319045-d760-4bf2-97cf-a78cbf1232c6' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>1.031 1.973 1.489</span></div><div class='xr-array-data'><pre>array([1.03128222, 1.97290909, 1.48910347])</pre></div></div></li><li class='xr-section-item'><input id='section-67e2540f-dc05-4d24-9d18-1e3253b6e459' class='xr-section-summary-in' type='checkbox'  checked><label for='section-67e2540f-dc05-4d24-9d18-1e3253b6e459' class='xr-section-summary' >Coordinates: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>Y</span></div><div class='xr-var-dims'>(Y)</div><div class='xr-var-dtype'>int32</div><div class='xr-var-preview xr-preview'>-5 -4 -3</div><input id='attrs-cf7c32bc-89d2-49ca-9c15-98d32eb971a7' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-cf7c32bc-89d2-49ca-9c15-98d32eb971a7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f96736c9-2690-4235-8c28-01b125b80b10' class='xr-var-data-in' type='checkbox'><label for='data-f96736c9-2690-4235-8c28-01b125b80b10' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([-5, -4, -3])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-d6790d93-8d78-4c00-a9d5-7f1ad785c67d' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-d6790d93-8d78-4c00-a9d5-7f1ad785c67d' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.DataArray (Y: 3)>\n",
       "array([1.03128222, 1.97290909, 1.48910347])\n",
       "Coordinates:\n",
       "  * Y        (Y) int32 -5 -4 -3"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "one_dim = test_data.sum(\"X\")\n",
    "one_dim"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "68823581-cffd-4289-bb7c-e79d8d122257",
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    {
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       "(array([-5, -4, -3]), array([1.03128222, 1.97290909, 1.48910347]))"
      ]
     },
     "execution_count": 8,
     "metadata": {},
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  {
   "cell_type": "markdown",
   "id": "9f822816-4894-4f68-b51c-56996dbe4262",
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    "## Functional Programming Primitives: `filter` and `map`\n",
    "\n",
    "You can `filter` or conditionally remove some of a datasets contents. To do this over coordinates on a dataset according to a function/sieve which accepts the coordinate and data value, you can use `filter_coord`. The sieving function should accept two arguments, the coordinate and the cut at that coordinate respectively. You can specify which coordinate or coordinates are iterated across when filtering using the `coordinate_name` paramter.\n",
    "\n",
    "As a simple, example, we can remove all the odd valued coordinates along Y:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "4a229aef-c0a8-4f37-9fdf-878290dc61aa",
   "metadata": {},
   "outputs": [
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       "\n",
       ".xr-section-summary-in:checked + label > span {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-section-summary,\n",
       ".xr-section-inline-details {\n",
       "  padding-top: 4px;\n",
       "  padding-bottom: 4px;\n",
       "}\n",
       "\n",
       ".xr-section-inline-details {\n",
       "  grid-column: 2 / -1;\n",
       "}\n",
       "\n",
       ".xr-section-details {\n",
       "  display: none;\n",
       "  grid-column: 1 / -1;\n",
       "  margin-bottom: 5px;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-array-wrap {\n",
       "  grid-column: 1 / -1;\n",
       "  display: grid;\n",
       "  grid-template-columns: 20px auto;\n",
       "}\n",
       "\n",
       ".xr-array-wrap > label {\n",
       "  grid-column: 1;\n",
       "  vertical-align: top;\n",
       "}\n",
       "\n",
       ".xr-preview {\n",
       "  color: var(--xr-font-color3);\n",
       "}\n",
       "\n",
       ".xr-array-preview,\n",
       ".xr-array-data {\n",
       "  padding: 0 5px !important;\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-array-data,\n",
       ".xr-array-in:checked ~ .xr-array-preview {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-array-in:checked ~ .xr-array-data,\n",
       ".xr-array-preview {\n",
       "  display: inline-block;\n",
       "}\n",
       "\n",
       ".xr-dim-list {\n",
       "  display: inline-block !important;\n",
       "  list-style: none;\n",
       "  padding: 0 !important;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list li {\n",
       "  display: inline-block;\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list:before {\n",
       "  content: '(';\n",
       "}\n",
       "\n",
       ".xr-dim-list:after {\n",
       "  content: ')';\n",
       "}\n",
       "\n",
       ".xr-dim-list li:not(:last-child):after {\n",
       "  content: ',';\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-has-index {\n",
       "  font-weight: bold;\n",
       "}\n",
       "\n",
       ".xr-var-list,\n",
       ".xr-var-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-var-item > div,\n",
       ".xr-var-item label,\n",
       ".xr-var-item > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-even);\n",
       "  margin-bottom: 0;\n",
       "}\n",
       "\n",
       ".xr-var-item > .xr-var-name:hover span {\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-var-list > li:nth-child(odd) > div,\n",
       ".xr-var-list > li:nth-child(odd) > label,\n",
       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-odd);\n",
       "}\n",
       "\n",
       ".xr-var-name {\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-var-dims {\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-var-dtype {\n",
       "  grid-column: 3;\n",
       "  text-align: right;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-var-preview {\n",
       "  grid-column: 4;\n",
       "}\n",
       "\n",
       ".xr-var-name,\n",
       ".xr-var-dims,\n",
       ".xr-var-dtype,\n",
       ".xr-preview,\n",
       ".xr-attrs dt {\n",
       "  white-space: nowrap;\n",
       "  overflow: hidden;\n",
       "  text-overflow: ellipsis;\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-var-name:hover,\n",
       ".xr-var-dims:hover,\n",
       ".xr-var-dtype:hover,\n",
       ".xr-attrs dt:hover {\n",
       "  overflow: visible;\n",
       "  width: auto;\n",
       "  z-index: 1;\n",
       "}\n",
       "\n",
       ".xr-var-attrs,\n",
       ".xr-var-data {\n",
       "  display: none;\n",
       "  background-color: var(--xr-background-color) !important;\n",
       "  padding-bottom: 5px !important;\n",
       "}\n",
       "\n",
       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
       ".xr-var-data-in:checked ~ .xr-var-data {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       ".xr-var-data > table {\n",
       "  float: right;\n",
       "}\n",
       "\n",
       ".xr-var-name span,\n",
       ".xr-var-data,\n",
       ".xr-attrs {\n",
       "  padding-left: 25px !important;\n",
       "}\n",
       "\n",
       ".xr-attrs,\n",
       ".xr-var-attrs,\n",
       ".xr-var-data {\n",
       "  grid-column: 1 / -1;\n",
       "}\n",
       "\n",
       "dl.xr-attrs {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  display: grid;\n",
       "  grid-template-columns: 125px auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt,\n",
       ".xr-attrs dd {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  float: left;\n",
       "  padding-right: 10px;\n",
       "  width: auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt {\n",
       "  font-weight: normal;\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-attrs dt:hover span {\n",
       "  display: inline-block;\n",
       "  background: var(--xr-background-color);\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-attrs dd {\n",
       "  grid-column: 2;\n",
       "  white-space: pre-wrap;\n",
       "  word-break: break-all;\n",
       "}\n",
       "\n",
       ".xr-icon-database,\n",
       ".xr-icon-file-text2 {\n",
       "  display: inline-block;\n",
       "  vertical-align: middle;\n",
       "  width: 1em;\n",
       "  height: 1.5em !important;\n",
       "  stroke-width: 0;\n",
       "  stroke: currentColor;\n",
       "  fill: currentColor;\n",
       "}\n",
       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray (X: 3, Y: 1)&gt;\n",
       "array([[0.95071431],\n",
       "       [0.15601864],\n",
       "       [0.86617615]])\n",
       "Coordinates:\n",
       "  * X        (X) int32 0 1 2\n",
       "  * Y        (Y) int32 -4</pre><div class='xr-wrap' hidden><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'></div><ul class='xr-dim-list'><li><span class='xr-has-index'>X</span>: 3</li><li><span class='xr-has-index'>Y</span>: 1</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-fc43f5fe-40ed-478c-8e73-5a0fed48f682' class='xr-array-in' type='checkbox' checked><label for='section-fc43f5fe-40ed-478c-8e73-5a0fed48f682' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>0.9507 0.156 0.8662</span></div><div class='xr-array-data'><pre>array([[0.95071431],\n",
       "       [0.15601864],\n",
       "       [0.86617615]])</pre></div></div></li><li class='xr-section-item'><input id='section-31508ae8-13f9-46f5-a6db-698bf4ce8ba8' class='xr-section-summary-in' type='checkbox'  checked><label for='section-31508ae8-13f9-46f5-a6db-698bf4ce8ba8' class='xr-section-summary' >Coordinates: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>X</span></div><div class='xr-var-dims'>(X)</div><div class='xr-var-dtype'>int32</div><div class='xr-var-preview xr-preview'>0 1 2</div><input id='attrs-d47172d1-85d5-4a43-b593-8eeedd7ff5b8' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-d47172d1-85d5-4a43-b593-8eeedd7ff5b8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-705102e4-5ab4-4e47-a739-5d302b76e217' class='xr-var-data-in' type='checkbox'><label for='data-705102e4-5ab4-4e47-a739-5d302b76e217' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([0, 1, 2])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>Y</span></div><div class='xr-var-dims'>(Y)</div><div class='xr-var-dtype'>int32</div><div class='xr-var-preview xr-preview'>-4</div><input id='attrs-cb8d5c08-c504-4d75-8a11-5444aaded1ee' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-cb8d5c08-c504-4d75-8a11-5444aaded1ee' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4f96d0cf-52ef-43d0-b6aa-de68e4f2df8c' class='xr-var-data-in' type='checkbox'><label for='data-4f96d0cf-52ef-43d0-b6aa-de68e4f2df8c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([-4])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-4de1b2a5-be39-4cc4-9c1c-ca82dda2e241' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-4de1b2a5-be39-4cc4-9c1c-ca82dda2e241' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.DataArray (X: 3, Y: 1)>\n",
       "array([[0.95071431],\n",
       "       [0.15601864],\n",
       "       [0.86617615]])\n",
       "Coordinates:\n",
       "  * X        (X) int32 0 1 2\n",
       "  * Y        (Y) int32 -4"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "test_data.G.filter_coord(\"Y\", lambda y, _: y % 2 == 0)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5c5d18d6-eae8-404d-a1d7-ad1537a0d427",
   "metadata": {},
   "source": [
    "Functional programming can also be used to modify data. With `map` we can apply a function onto a `DataArray`'s values. You can use this to add one to all of the elements:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "29e213cc-c667-4742-9159-dfde160fa766",
   "metadata": {},
   "outputs": [
    {
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       "\n",
       ".xr-var-item > .xr-var-name:hover span {\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-var-list > li:nth-child(odd) > div,\n",
       ".xr-var-list > li:nth-child(odd) > label,\n",
       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-odd);\n",
       "}\n",
       "\n",
       ".xr-var-name {\n",
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       "\n",
       ".xr-var-dims {\n",
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       "\n",
       ".xr-var-dtype {\n",
       "  grid-column: 3;\n",
       "  text-align: right;\n",
       "  color: var(--xr-font-color2);\n",
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       "\n",
       ".xr-var-preview {\n",
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       "\n",
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       ".xr-var-dims,\n",
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       ".xr-preview,\n",
       ".xr-attrs dt {\n",
       "  white-space: nowrap;\n",
       "  overflow: hidden;\n",
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       "\n",
       ".xr-var-name:hover,\n",
       ".xr-var-dims:hover,\n",
       ".xr-var-dtype:hover,\n",
       ".xr-attrs dt:hover {\n",
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       "\n",
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       ".xr-var-data {\n",
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       "\n",
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       ".xr-var-data-in:checked ~ .xr-var-data {\n",
       "  display: block;\n",
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       "\n",
       ".xr-var-data > table {\n",
       "  float: right;\n",
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       "\n",
       ".xr-var-name span,\n",
       ".xr-var-data,\n",
       ".xr-attrs {\n",
       "  padding-left: 25px !important;\n",
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       "\n",
       ".xr-attrs,\n",
       ".xr-var-attrs,\n",
       ".xr-var-data {\n",
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       "\n",
       "dl.xr-attrs {\n",
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       "\n",
       ".xr-attrs dt,\n",
       ".xr-attrs dd {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  float: left;\n",
       "  padding-right: 10px;\n",
       "  width: auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt {\n",
       "  font-weight: normal;\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-attrs dt:hover span {\n",
       "  display: inline-block;\n",
       "  background: var(--xr-background-color);\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-attrs dd {\n",
       "  grid-column: 2;\n",
       "  white-space: pre-wrap;\n",
       "  word-break: break-all;\n",
       "}\n",
       "\n",
       ".xr-icon-database,\n",
       ".xr-icon-file-text2 {\n",
       "  display: inline-block;\n",
       "  vertical-align: middle;\n",
       "  width: 1em;\n",
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       "  stroke-width: 0;\n",
       "  stroke: currentColor;\n",
       "  fill: currentColor;\n",
       "}\n",
       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray (X: 3, Y: 3)&gt;\n",
       "array([[1.37454012, 1.95071431, 1.73199394],\n",
       "       [1.59865848, 1.15601864, 1.15599452],\n",
       "       [1.05808361, 1.86617615, 1.60111501]])\n",
       "Coordinates:\n",
       "  * X        (X) int32 0 1 2\n",
       "  * Y        (Y) int32 -5 -4 -3</pre><div class='xr-wrap' hidden><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'></div><ul class='xr-dim-list'><li><span class='xr-has-index'>X</span>: 3</li><li><span class='xr-has-index'>Y</span>: 3</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-7d885d67-40f1-49e3-a712-3ea71ece523a' class='xr-array-in' type='checkbox' checked><label for='section-7d885d67-40f1-49e3-a712-3ea71ece523a' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>1.375 1.951 1.732 1.599 1.156 1.156 1.058 1.866 1.601</span></div><div class='xr-array-data'><pre>array([[1.37454012, 1.95071431, 1.73199394],\n",
       "       [1.59865848, 1.15601864, 1.15599452],\n",
       "       [1.05808361, 1.86617615, 1.60111501]])</pre></div></div></li><li class='xr-section-item'><input id='section-7b0c62fc-edea-4a68-a55e-de25edfc11a7' class='xr-section-summary-in' type='checkbox'  checked><label for='section-7b0c62fc-edea-4a68-a55e-de25edfc11a7' class='xr-section-summary' >Coordinates: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>X</span></div><div class='xr-var-dims'>(X)</div><div class='xr-var-dtype'>int32</div><div class='xr-var-preview xr-preview'>0 1 2</div><input id='attrs-e92705a8-76d7-4c3d-8d91-2f4688b1fbec' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-e92705a8-76d7-4c3d-8d91-2f4688b1fbec' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-01535a34-55c2-4735-a133-e1b2d91398d6' class='xr-var-data-in' type='checkbox'><label for='data-01535a34-55c2-4735-a133-e1b2d91398d6' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([0, 1, 2])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>Y</span></div><div class='xr-var-dims'>(Y)</div><div class='xr-var-dtype'>int32</div><div class='xr-var-preview xr-preview'>-5 -4 -3</div><input id='attrs-687f7c3e-fa0f-456f-bf73-155367d84204' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-687f7c3e-fa0f-456f-bf73-155367d84204' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0bab1413-967a-4e81-8664-9f84f770996c' class='xr-var-data-in' type='checkbox'><label for='data-0bab1413-967a-4e81-8664-9f84f770996c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([-5, -4, -3])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-51c50464-bd74-4f36-8fd5-f32c0eb64939' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-51c50464-bd74-4f36-8fd5-f32c0eb64939' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.DataArray (X: 3, Y: 3)>\n",
       "array([[1.37454012, 1.95071431, 1.73199394],\n",
       "       [1.59865848, 1.15601864, 1.15599452],\n",
       "       [1.05808361, 1.86617615, 1.60111501]])\n",
       "Coordinates:\n",
       "  * X        (X) int32 0 1 2\n",
       "  * Y        (Y) int32 -5 -4 -3"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "test_data.G.map(lambda v: v + 1)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "620d8ec0-7b09-4195-8a62-59918b555d51",
   "metadata": {},
   "source": [
    "Additionally, we can simultaneously iterate and apply a function onto a specified dimension of the data with `map_axes`. Here we can use this to ensure that the rows along `Y` have unit norm."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "713b4b90-ff32-4a7e-96fa-47297b78ccea",
   "metadata": {},
   "outputs": [
    {
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       ".xr-var-attrs,\n",
       ".xr-var-data {\n",
       "  grid-column: 1 / -1;\n",
       "}\n",
       "\n",
       "dl.xr-attrs {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  display: grid;\n",
       "  grid-template-columns: 125px auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt,\n",
       ".xr-attrs dd {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  float: left;\n",
       "  padding-right: 10px;\n",
       "  width: auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt {\n",
       "  font-weight: normal;\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-attrs dt:hover span {\n",
       "  display: inline-block;\n",
       "  background: var(--xr-background-color);\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-attrs dd {\n",
       "  grid-column: 2;\n",
       "  white-space: pre-wrap;\n",
       "  word-break: break-all;\n",
       "}\n",
       "\n",
       ".xr-icon-database,\n",
       ".xr-icon-file-text2 {\n",
       "  display: inline-block;\n",
       "  vertical-align: middle;\n",
       "  width: 1em;\n",
       "  height: 1.5em !important;\n",
       "  stroke-width: 0;\n",
       "  stroke: currentColor;\n",
       "  fill: currentColor;\n",
       "}\n",
       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray (X: 3, Y: 3)&gt;\n",
       "array([[0.52859931, 0.73382829, 0.76253974],\n",
       "       [0.84490405, 0.12042618, 0.16250411],\n",
       "       [0.08197508, 0.66857578, 0.62619929]])\n",
       "Coordinates:\n",
       "  * X        (X) int32 0 1 2\n",
       "  * Y        (Y) int32 -5 -4 -3</pre><div class='xr-wrap' hidden><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'></div><ul class='xr-dim-list'><li><span class='xr-has-index'>X</span>: 3</li><li><span class='xr-has-index'>Y</span>: 3</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-59e52d3d-5634-4b4c-a81a-2ccae7698d23' class='xr-array-in' type='checkbox' checked><label for='section-59e52d3d-5634-4b4c-a81a-2ccae7698d23' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>0.5286 0.7338 0.7625 0.8449 0.1204 0.1625 0.08198 0.6686 0.6262</span></div><div class='xr-array-data'><pre>array([[0.52859931, 0.73382829, 0.76253974],\n",
       "       [0.84490405, 0.12042618, 0.16250411],\n",
       "       [0.08197508, 0.66857578, 0.62619929]])</pre></div></div></li><li class='xr-section-item'><input id='section-939df516-58c2-42c0-9b20-bc4840f6cdc9' class='xr-section-summary-in' type='checkbox'  checked><label for='section-939df516-58c2-42c0-9b20-bc4840f6cdc9' class='xr-section-summary' >Coordinates: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>X</span></div><div class='xr-var-dims'>(X)</div><div class='xr-var-dtype'>int32</div><div class='xr-var-preview xr-preview'>0 1 2</div><input id='attrs-3c2c66d7-e924-4dea-8902-ac559c106469' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-3c2c66d7-e924-4dea-8902-ac559c106469' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-757b0342-5b4c-4303-a6ac-3ae838e760c0' class='xr-var-data-in' type='checkbox'><label for='data-757b0342-5b4c-4303-a6ac-3ae838e760c0' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([0, 1, 2])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>Y</span></div><div class='xr-var-dims'>(Y)</div><div class='xr-var-dtype'>int32</div><div class='xr-var-preview xr-preview'>-5 -4 -3</div><input id='attrs-96e92f74-b953-43f2-8475-f194949ed862' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-96e92f74-b953-43f2-8475-f194949ed862' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1a38bdc0-66ec-4625-a13f-fa704d708269' class='xr-var-data-in' type='checkbox'><label for='data-1a38bdc0-66ec-4625-a13f-fa704d708269' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([-5, -4, -3])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-f9a3baf8-11a2-4ba1-b8bf-7574c4513d6d' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-f9a3baf8-11a2-4ba1-b8bf-7574c4513d6d' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.DataArray (X: 3, Y: 3)>\n",
       "array([[0.52859931, 0.73382829, 0.76253974],\n",
       "       [0.84490405, 0.12042618, 0.16250411],\n",
       "       [0.08197508, 0.66857578, 0.62619929]])\n",
       "Coordinates:\n",
       "  * X        (X) int32 0 1 2\n",
       "  * Y        (Y) int32 -5 -4 -3"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "test_data.G.map_axes(\"Y\", lambda v, c: v / np.linalg.norm(v))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1ff3aa89-a175-4bc3-a0f8-f534c286b475",
   "metadata": {},
   "source": [
    "## Shifting\n",
    "\n",
    "Suppose you have a bundle of spaghetti in your hand with varying lengths. You might want to align them so that they all meet in a flat plane at the tops of the strands. In general, you will have to shift each a different amount depending on the length of each strand, and its initial position in your hand.\n",
    "\n",
    "A similar problem presents itself in multidimensional data. You might want to shift 1D or 2D \"strands\" of data by differing amounts along an axis. One practical use case in ARPES is to [align the chemical potential](/fermi-edge-corrections) to take into account the spectrometer calibration and shape of the spectrometer entrance slit. Using the curve fitting data we explored in the previous section, we can align the data as a function of the temperature so that all the Fermi momenta are at the same index:\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "e0a7a5a2-7a6b-45b8-b0c7-0af58b057d8a",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Running on multiprocessing pool... this may take a while the first time.\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "94c2d27065e846948a4ca1c1a11a6871",
       "version_major": 2,
       "version_minor": 0
      },
      "text/html": [
       "<p>Failed to display Jupyter Widget of type <code>TqdmHBox</code>.</p>\n",
       "<p>\n",
       "  If you're reading this message in Jupyter Notebook or JupyterLab, it may mean\n",
       "  that the widgets JavaScript is still loading. If this message persists, it\n",
       "  likely means that the widgets JavaScript library is either not installed or\n",
       "  not enabled. See the <a href=\"https://ipywidgets.readthedocs.io/en/stable/user_install.html\">Jupyter\n",
       "  Widgets Documentation</a> for setup instructions.\n",
       "</p>\n",
       "<p>\n",
       "  If you're reading this message in another notebook frontend (for example, a static\n",
       "  rendering on GitHub or <a href=\"https://nbviewer.jupyter.org/\">NBViewer</a>),\n",
       "  it may mean that your frontend doesn't currently support widgets.\n",
       "</p>\n"
      ],
      "text/plain": [
       "Fitting on pool...:   0%|          | 0/34 [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Deserializing...\n",
      "Finished deserializing\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'Shifted to align Fermi angle')"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 936x360 with 4 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# first, get the same cut and fermi angles/momenta from the previous page\n",
    "# this is reproduced for clarity and so you can run the whole notebook\n",
    "# please feel free to skip...\n",
    "\n",
    "from arpes.fits.utilities import broadcast_model\n",
    "from arpes.fits.fit_models import LorentzianModel, AffineBackgroundModel\n",
    "\n",
    "temp_dep = example_data.temperature_dependence\n",
    "near_ef = temp_dep.sel(\n",
    "    eV=slice(-0.05, 0.05), \n",
    "    phi=slice(-0.2, None)\n",
    ").sum(\"eV\").spectrum\n",
    "\n",
    "phis = broadcast_model(\n",
    "    [AffineBackgroundModel, LorentzianModel], near_ef, \"temperature\",\n",
    ").F.p(\"b_center\")\n",
    "\n",
    "# ...to here\n",
    "fig, ax = plt.subplots(1, 2, figsize=(13, 5))\n",
    "near_ef.S.plot(ax=ax[0])\n",
    "near_ef.G.shift_by(phis - phis.mean(), shift_axis=\"phi\").S.plot(ax=ax[1])\n",
    "\n",
    "ax[0].set_title(\"Original data\")\n",
    "ax[1].set_title(\"Shifted to align Fermi angle\")"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "python3",
   "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": "3.8.8"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}