willirath/2024-05-23_xhist_binning_scalars.ipynb

## 2024-05-23_xhist_binning_scalars.ipynb
{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "98546625-627d-449f-8853-0030576e7ae6",
   "metadata": {},
   "outputs": [],
   "source": [
    "import xarray as xr\n",
    "import numpy as np\n",
    "from xhistogram.xarray import histogram as xhist"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "032ca7fc-4dda-4861-9f2d-b350a2c3514d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div><svg style=\"position: absolute; width: 0; height: 0; overflow: hidden\">\n",
       "<defs>\n",
       "<symbol id=\"icon-database\" viewBox=\"0 0 32 32\">\n",
       "<path d=\"M16 0c-8.837 0-16 2.239-16 5v4c0 2.761 7.163 5 16 5s16-2.239 16-5v-4c0-2.761-7.163-5-16-5z\"></path>\n",
       "<path d=\"M16 17c-8.837 0-16-2.239-16-5v6c0 2.761 7.163 5 16 5s16-2.239 16-5v-6c0 2.761-7.163 5-16 5z\"></path>\n",
       "<path d=\"M16 26c-8.837 0-16-2.239-16-5v6c0 2.761 7.163 5 16 5s16-2.239 16-5v-6c0 2.761-7.163 5-16 5z\"></path>\n",
       "</symbol>\n",
       "<symbol id=\"icon-file-text2\" viewBox=\"0 0 32 32\">\n",
       "<path d=\"M28.681 7.159c-0.694-0.947-1.662-2.053-2.724-3.116s-2.169-2.030-3.116-2.724c-1.612-1.182-2.393-1.319-2.841-1.319h-15.5c-1.378 0-2.5 1.121-2.5 2.5v27c0 1.378 1.122 2.5 2.5 2.5h23c1.378 0 2.5-1.122 2.5-2.5v-19.5c0-0.448-0.137-1.23-1.319-2.841zM24.543 5.457c0.959 0.959 1.712 1.825 2.268 2.543h-4.811v-4.811c0.718 0.556 1.584 1.309 2.543 2.268zM28 29.5c0 0.271-0.229 0.5-0.5 0.5h-23c-0.271 0-0.5-0.229-0.5-0.5v-27c0-0.271 0.229-0.5 0.5-0.5 0 0 15.499-0 15.5 0v7c0 0.552 0.448 1 1 1h7v19.5z\"></path>\n",
       "<path d=\"M23 26h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
       "<path d=\"M23 22h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
       "<path d=\"M23 18h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
       "</symbol>\n",
       "</defs>\n",
       "</svg>\n",
       "<style>/* CSS stylesheet for displaying xarray objects in jupyterlab.\n",
       " *\n",
       " */\n",
       "\n",
       ":root {\n",
       "  --xr-font-color0: var(--jp-content-font-color0, rgba(0, 0, 0, 1));\n",
       "  --xr-font-color2: var(--jp-content-font-color2, rgba(0, 0, 0, 0.54));\n",
       "  --xr-font-color3: var(--jp-content-font-color3, rgba(0, 0, 0, 0.38));\n",
       "  --xr-border-color: var(--jp-border-color2, #e0e0e0);\n",
       "  --xr-disabled-color: var(--jp-layout-color3, #bdbdbd);\n",
       "  --xr-background-color: var(--jp-layout-color0, white);\n",
       "  --xr-background-color-row-even: var(--jp-layout-color1, white);\n",
       "  --xr-background-color-row-odd: var(--jp-layout-color2, #eeeeee);\n",
       "}\n",
       "\n",
       "html[theme=dark],\n",
       "body[data-theme=dark],\n",
       "body.vscode-dark {\n",
       "  --xr-font-color0: rgba(255, 255, 255, 1);\n",
       "  --xr-font-color2: rgba(255, 255, 255, 0.54);\n",
       "  --xr-font-color3: rgba(255, 255, 255, 0.38);\n",
       "  --xr-border-color: #1F1F1F;\n",
       "  --xr-disabled-color: #515151;\n",
       "  --xr-background-color: #111111;\n",
       "  --xr-background-color-row-even: #111111;\n",
       "  --xr-background-color-row-odd: #313131;\n",
       "}\n",
       "\n",
       ".xr-wrap {\n",
       "  display: block !important;\n",
       "  min-width: 300px;\n",
       "  max-width: 700px;\n",
       "}\n",
       "\n",
       ".xr-text-repr-fallback {\n",
       "  /* fallback to plain text repr when CSS is not injected (untrusted notebook) */\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-header {\n",
       "  padding-top: 6px;\n",
       "  padding-bottom: 6px;\n",
       "  margin-bottom: 4px;\n",
       "  border-bottom: solid 1px var(--xr-border-color);\n",
       "}\n",
       "\n",
       ".xr-header > div,\n",
       ".xr-header > ul {\n",
       "  display: inline;\n",
       "  margin-top: 0;\n",
       "  margin-bottom: 0;\n",
       "}\n",
       "\n",
       ".xr-obj-type,\n",
       ".xr-array-name {\n",
       "  margin-left: 2px;\n",
       "  margin-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-obj-type {\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-sections {\n",
       "  padding-left: 0 !important;\n",
       "  display: grid;\n",
       "  grid-template-columns: 150px auto auto 1fr 20px 20px;\n",
       "}\n",
       "\n",
       ".xr-section-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-section-item input {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-section-item input + label {\n",
       "  color: var(--xr-disabled-color);\n",
       "}\n",
       "\n",
       ".xr-section-item input:enabled + label {\n",
       "  cursor: pointer;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-section-item input:enabled + label:hover {\n",
       "  color: var(--xr-font-color0);\n",
       "}\n",
       "\n",
       ".xr-section-summary {\n",
       "  grid-column: 1;\n",
       "  color: var(--xr-font-color2);\n",
       "  font-weight: 500;\n",
       "}\n",
       "\n",
       ".xr-section-summary > span {\n",
       "  display: inline-block;\n",
       "  padding-left: 0.5em;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:disabled + label {\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-section-summary-in + label:before {\n",
       "  display: inline-block;\n",
       "  content: '►';\n",
       "  font-size: 11px;\n",
       "  width: 15px;\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:disabled + label:before {\n",
       "  color: var(--xr-disabled-color);\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked + label:before {\n",
       "  content: '▼';\n",
       "}\n",
       "\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-index-preview {\n",
       "  grid-column: 2 / 5;\n",
       "  color: var(--xr-font-color2);\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",
       ".xr-index-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",
       ".xr-index-data-in:checked ~ .xr-index-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-index-name div,\n",
       ".xr-index-data,\n",
       ".xr-attrs {\n",
       "  padding-left: 25px !important;\n",
       "}\n",
       "\n",
       ".xr-attrs,\n",
       ".xr-var-attrs,\n",
       ".xr-var-data,\n",
       ".xr-index-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",
       ".xr-no-icon {\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.Dataset&gt;\n",
       "Dimensions:  (traj: 100000)\n",
       "Dimensions without coordinates: traj\n",
       "Data variables:\n",
       "    lon      (traj) float64 -59.34 -114.7 137.7 80.74 ... -118.5 -77.1 133.3\n",
       "    lat      (traj) float64 55.16 16.15 -89.94 35.98 ... 31.82 -23.65 88.59</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-b594b188-f5f7-44c9-b6be-221187772da5' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-b594b188-f5f7-44c9-b6be-221187772da5' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span>traj</span>: 100000</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-e6dfcca5-dfea-40b5-93c0-716c5309202d' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-e6dfcca5-dfea-40b5-93c0-716c5309202d' class='xr-section-summary'  title='Expand/collapse section'>Coordinates: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'></ul></div></li><li class='xr-section-item'><input id='section-220b8dc4-a7ae-4a78-95f8-c9f1916a7fe9' class='xr-section-summary-in' type='checkbox'  checked><label for='section-220b8dc4-a7ae-4a78-95f8-c9f1916a7fe9' class='xr-section-summary' >Data variables: <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>lon</span></div><div class='xr-var-dims'>(traj)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-59.34 -114.7 137.7 ... -77.1 133.3</div><input id='attrs-3770ddc0-9efe-4588-9750-9d310e156784' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-3770ddc0-9efe-4588-9750-9d310e156784' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5e90b19d-5ee4-47db-adc5-1784a3e5eefb' class='xr-var-data-in' type='checkbox'><label for='data-5e90b19d-5ee4-47db-adc5-1784a3e5eefb' 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([ -59.34373912, -114.67100833,  137.70650338, ..., -118.50592591,\n",
       "        -77.09521239,  133.3005635 ])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lat</span></div><div class='xr-var-dims'>(traj)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>55.16 16.15 -89.94 ... -23.65 88.59</div><input id='attrs-0d85994b-bdda-45a5-b4b9-e69270dfd103' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-0d85994b-bdda-45a5-b4b9-e69270dfd103' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-fb1d8876-d15d-44e1-b0ce-3a2286173b8d' class='xr-var-data-in' type='checkbox'><label for='data-fb1d8876-d15d-44e1-b0ce-3a2286173b8d' 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([ 55.15952543,  16.14672476, -89.93899841, ...,  31.81908742,\n",
       "       -23.65347653,  88.59322285])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-77926841-52c7-4eca-9507-030ce0c4b4c1' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-77926841-52c7-4eca-9507-030ce0c4b4c1' class='xr-section-summary'  title='Expand/collapse section'>Indexes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'></ul></div></li><li class='xr-section-item'><input id='section-d32b1726-9237-4e00-a0f2-8921ef484bc6' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-d32b1726-9237-4e00-a0f2-8921ef484bc6' 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.Dataset>\n",
       "Dimensions:  (traj: 100000)\n",
       "Dimensions without coordinates: traj\n",
       "Data variables:\n",
       "    lon      (traj) float64 -59.34 -114.7 137.7 80.74 ... -118.5 -77.1 133.3\n",
       "    lat      (traj) float64 55.16 16.15 -89.94 35.98 ... 31.82 -23.65 88.59"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "trajs = xr.Dataset(\n",
    "    {\n",
    "        \"lon\": ((\"traj\", ), np.random.uniform(-180, 180, size=(100_000, ))),\n",
    "        \"lat\": ((\"traj\", ), np.random.uniform(-90, 90, size=(100_000, ))),\n",
    "    }\n",
    ")\n",
    "trajs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "9ed6705e-a2f0-4b6a-aa6e-6b2bc5cde701",
   "metadata": {},
   "outputs": [],
   "source": [
    "trajs[\"z\"] = 500 + 50 * np.cos(np.deg2rad(trajs.lon)) + 10.0 * np.random.normal(size=(len(trajs.lon), ))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "76bb3aa1-46f6-4872-80be-28376e633d43",
   "metadata": {},
   "outputs": [],
   "source": [
    "# trajs.plot.scatter(x=\"lon\", y=\"lat\", hue=\"z\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "3eb72126-d1f1-438a-bcfc-3c0f5ede15c5",
   "metadata": {},
   "outputs": [],
   "source": [
    "z_mean = (\n",
    "    xhist(\n",
    "        trajs.lon, trajs.lat,\n",
    "        bins=[np.linspace(-180, 180, 11), np.linspace(-90, 90, 7)],\n",
    "        weights=trajs.z,\n",
    "    ) / xhist(\n",
    "        trajs.lon, trajs.lat,\n",
    "        bins=[np.linspace(-180, 180, 11), np.linspace(-90, 90, 7)],\n",
    "    )\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "85cd31ea-3ff5-4509-9409-9bcdb9c6204a",
   "metadata": {},
   "outputs": [],
   "source": [
    "z2_mean = (\n",
    "    xhist(\n",
    "        trajs.lon, trajs.lat,\n",
    "        bins=[np.linspace(-180, 180, 11), np.linspace(-90, 90, 7)],\n",
    "        weights=trajs.z ** 2,\n",
    "    ) / xhist(\n",
    "        trajs.lon, trajs.lat,\n",
    "        bins=[np.linspace(-180, 180, 11), np.linspace(-90, 90, 7)],\n",
    "    )\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "d5d377fe-19c1-4bfa-84c2-876888f88350",
   "metadata": {},
   "outputs": [],
   "source": [
    "z_std = (z2_mean - z_mean ** 2) ** 0.5"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "60a5055e-d21c-44d1-a537-ef35d2e67f1b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.QuadMesh at 0x7f10947cb7d0>"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "z_mean.T.plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "e89f79e7-f020-43fc-b089-ec238ae10f1d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.QuadMesh at 0x7f0ff73fa990>"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "z_std.T.plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "872139c4-49d2-4b32-a9ac-039ec574cb51",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "parcels",
   "language": "python",
   "name": "parcels"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.11.6"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}