{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Identifying temporal variation in EvoDevo data with MEFISTO"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This notebook demonstrates how temporal (or spatial) covariates can be used for multimodal data integration to learn smooth latent factors while benefiting from the multimodal `MuData` objects from `muon`.\n",
    "\n",
    "Please find more information about this method — *MEFISTO* — [on its website](https://biofam.github.io/MOFA2/MEFISTO) and [in the preprint](https://www.biorxiv.org/content/10.1101/2020.11.03.366674v1) by Britta Velten et al."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import scanpy as sc\n",
    "\n",
    "import muon as mu"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Set the working directory to the root of the repository\n",
    "import os\n",
    "os.chdir(\"../\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Load data\n",
    "\n",
    "First we will load the evodevo data containing normalized gene expression data for 5 species (groups) and 5 organs (views) as well as the developmental time information for each sample. The data can be downloaded [from here](https://figshare.com/s/242916198fde3353f3e6)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "datadir = \"data/evodevo\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/usr/local/lib/python3.8/site-packages/numpy/lib/arraysetops.py:583: FutureWarning: elementwise comparison failed; returning scalar instead, but in the future will perform elementwise comparison\n",
      "  mask |= (ar1 == a)\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>group</th>\n",
       "      <th>view</th>\n",
       "      <th>sample</th>\n",
       "      <th>feature</th>\n",
       "      <th>value</th>\n",
       "      <th>time</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Human</td>\n",
       "      <td>Brain</td>\n",
       "      <td>10wpc_Human</td>\n",
       "      <td>ENSG00000000457_Brain</td>\n",
       "      <td>8.573918</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Human</td>\n",
       "      <td>Brain</td>\n",
       "      <td>10wpc_Human</td>\n",
       "      <td>ENSG00000001084_Brain</td>\n",
       "      <td>8.875957</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Human</td>\n",
       "      <td>Brain</td>\n",
       "      <td>10wpc_Human</td>\n",
       "      <td>ENSG00000001167_Brain</td>\n",
       "      <td>11.265237</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Human</td>\n",
       "      <td>Brain</td>\n",
       "      <td>10wpc_Human</td>\n",
       "      <td>ENSG00000001461_Brain</td>\n",
       "      <td>7.374965</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Human</td>\n",
       "      <td>Brain</td>\n",
       "      <td>10wpc_Human</td>\n",
       "      <td>ENSG00000001561_Brain</td>\n",
       "      <td>7.311018</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3193836</th>\n",
       "      <td>Human</td>\n",
       "      <td>Testis</td>\n",
       "      <td>youngMidAge_Human</td>\n",
       "      <td>ENSG00000271503_Testis</td>\n",
       "      <td>1.178014</td>\n",
       "      <td>21</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3193837</th>\n",
       "      <td>Human</td>\n",
       "      <td>Testis</td>\n",
       "      <td>youngMidAge_Human</td>\n",
       "      <td>ENSG00000271601_Testis</td>\n",
       "      <td>1.178014</td>\n",
       "      <td>21</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3193838</th>\n",
       "      <td>Human</td>\n",
       "      <td>Testis</td>\n",
       "      <td>youngMidAge_Human</td>\n",
       "      <td>ENSG00000272442_Testis</td>\n",
       "      <td>4.476201</td>\n",
       "      <td>21</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3193839</th>\n",
       "      <td>Human</td>\n",
       "      <td>Testis</td>\n",
       "      <td>youngMidAge_Human</td>\n",
       "      <td>ENSG00000272886_Testis</td>\n",
       "      <td>1.178014</td>\n",
       "      <td>21</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3193840</th>\n",
       "      <td>Human</td>\n",
       "      <td>Testis</td>\n",
       "      <td>youngMidAge_Human</td>\n",
       "      <td>ENSG00000273079_Testis</td>\n",
       "      <td>8.311393</td>\n",
       "      <td>21</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>3193840 rows × 6 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "         group    view             sample                 feature      value  \\\n",
       "1        Human   Brain        10wpc_Human   ENSG00000000457_Brain   8.573918   \n",
       "2        Human   Brain        10wpc_Human   ENSG00000001084_Brain   8.875957   \n",
       "3        Human   Brain        10wpc_Human   ENSG00000001167_Brain  11.265237   \n",
       "4        Human   Brain        10wpc_Human   ENSG00000001461_Brain   7.374965   \n",
       "5        Human   Brain        10wpc_Human   ENSG00000001561_Brain   7.311018   \n",
       "...        ...     ...                ...                     ...        ...   \n",
       "3193836  Human  Testis  youngMidAge_Human  ENSG00000271503_Testis   1.178014   \n",
       "3193837  Human  Testis  youngMidAge_Human  ENSG00000271601_Testis   1.178014   \n",
       "3193838  Human  Testis  youngMidAge_Human  ENSG00000272442_Testis   4.476201   \n",
       "3193839  Human  Testis  youngMidAge_Human  ENSG00000272886_Testis   1.178014   \n",
       "3193840  Human  Testis  youngMidAge_Human  ENSG00000273079_Testis   8.311393   \n",
       "\n",
       "         time  \n",
       "1           7  \n",
       "2           7  \n",
       "3           7  \n",
       "4           7  \n",
       "5           7  \n",
       "...       ...  \n",
       "3193836    21  \n",
       "3193837    21  \n",
       "3193838    21  \n",
       "3193839    21  \n",
       "3193840    21  \n",
       "\n",
       "[3193840 rows x 6 columns]"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data = pd.read_csv(f\"{datadir}/evodevo.csv\", sep=\",\", index_col=0)\n",
    "data"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "First, we create a collection of AnnData objects from this dataframe, one for each organ.\n",
    "\n",
    "For instance, here's the data for the `'Brain'` view:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>feature</th>\n",
       "      <th>ENSG00000000457_Brain</th>\n",
       "      <th>ENSG00000001084_Brain</th>\n",
       "      <th>ENSG00000001167_Brain</th>\n",
       "      <th>ENSG00000001461_Brain</th>\n",
       "      <th>ENSG00000001561_Brain</th>\n",
       "      <th>ENSG00000001617_Brain</th>\n",
       "      <th>ENSG00000001629_Brain</th>\n",
       "      <th>ENSG00000001631_Brain</th>\n",
       "      <th>ENSG00000002549_Brain</th>\n",
       "      <th>ENSG00000002745_Brain</th>\n",
       "      <th>...</th>\n",
       "      <th>ENSG00000267909_Brain</th>\n",
       "      <th>ENSG00000268104_Brain</th>\n",
       "      <th>ENSG00000269058_Brain</th>\n",
       "      <th>ENSG00000270885_Brain</th>\n",
       "      <th>ENSG00000271092_Brain</th>\n",
       "      <th>ENSG00000271503_Brain</th>\n",
       "      <th>ENSG00000271601_Brain</th>\n",
       "      <th>ENSG00000272442_Brain</th>\n",
       "      <th>ENSG00000272886_Brain</th>\n",
       "      <th>ENSG00000273079_Brain</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>sample</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
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       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
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       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>10wpc_Human</th>\n",
       "      <td>8.573918</td>\n",
       "      <td>8.875957</td>\n",
       "      <td>11.265237</td>\n",
       "      <td>7.374965</td>\n",
       "      <td>7.311018</td>\n",
       "      <td>9.959839</td>\n",
       "      <td>10.542619</td>\n",
       "      <td>9.692082</td>\n",
       "      <td>9.180280</td>\n",
       "      <td>4.281878</td>\n",
       "      <td>...</td>\n",
       "      <td>7.221091</td>\n",
       "      <td>1.178014</td>\n",
       "      <td>1.178014</td>\n",
       "      <td>1.178014</td>\n",
       "      <td>1.178014</td>\n",
       "      <td>1.178014</td>\n",
       "      <td>1.178014</td>\n",
       "      <td>1.178014</td>\n",
       "      <td>1.178014</td>\n",
       "      <td>11.74615</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11wpc_Human</th>\n",
       "      <td>8.439675</td>\n",
       "      <td>8.737682</td>\n",
       "      <td>10.855314</td>\n",
       "      <td>8.066544</td>\n",
       "      <td>7.354726</td>\n",
       "      <td>10.431113</td>\n",
       "      <td>10.308780</td>\n",
       "      <td>9.242115</td>\n",
       "      <td>9.350255</td>\n",
       "      <td>3.363064</td>\n",
       "      <td>...</td>\n",
       "      <td>7.116983</td>\n",
       "      <td>1.178014</td>\n",
       "      <td>1.178014</td>\n",
       "      <td>1.178014</td>\n",
       "      <td>1.178014</td>\n",
       "      <td>1.178014</td>\n",
       "      <td>1.178014</td>\n",
       "      <td>1.421384</td>\n",
       "      <td>1.178014</td>\n",
       "      <td>11.28160</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12wpc_Human</th>\n",
       "      <td>8.399178</td>\n",
       "      <td>8.916387</td>\n",
       "      <td>12.555510</td>\n",
       "      <td>9.253555</td>\n",
       "      <td>8.763702</td>\n",
       "      <td>9.946536</td>\n",
       "      <td>11.530929</td>\n",
       "      <td>10.033949</td>\n",
       "      <td>9.278142</td>\n",
       "      <td>4.322361</td>\n",
       "      <td>...</td>\n",
       "      <td>4.000716</td>\n",
       "      <td>1.178014</td>\n",
       "      <td>1.178014</td>\n",
       "      <td>1.178014</td>\n",
       "      <td>1.178014</td>\n",
       "      <td>1.178014</td>\n",
       "      <td>1.178014</td>\n",
       "      <td>2.664630</td>\n",
       "      <td>1.178014</td>\n",
       "      <td>13.97646</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13wpc_Human</th>\n",
       "      <td>8.637347</td>\n",
       "      <td>8.831740</td>\n",
       "      <td>10.916489</td>\n",
       "      <td>9.190959</td>\n",
       "      <td>8.158240</td>\n",
       "      <td>10.279600</td>\n",
       "      <td>11.287268</td>\n",
       "      <td>9.510370</td>\n",
       "      <td>9.033614</td>\n",
       "      <td>4.784136</td>\n",
       "      <td>...</td>\n",
       "      <td>5.635512</td>\n",
       "      <td>1.178014</td>\n",
       "      <td>1.481758</td>\n",
       "      <td>1.178014</td>\n",
       "      <td>1.178014</td>\n",
       "      <td>1.178014</td>\n",
       "      <td>1.178014</td>\n",
       "      <td>1.776655</td>\n",
       "      <td>1.178014</td>\n",
       "      <td>12.47349</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16wpc_Human</th>\n",
       "      <td>8.525125</td>\n",
       "      <td>8.575862</td>\n",
       "      <td>11.271736</td>\n",
       "      <td>8.177629</td>\n",
       "      <td>7.857303</td>\n",
       "      <td>10.363036</td>\n",
       "      <td>11.402954</td>\n",
       "      <td>9.523244</td>\n",
       "      <td>8.833177</td>\n",
       "      <td>2.785827</td>\n",
       "      <td>...</td>\n",
       "      <td>6.119527</td>\n",
       "      <td>1.178014</td>\n",
       "      <td>1.178014</td>\n",
       "      <td>1.178014</td>\n",
       "      <td>1.178014</td>\n",
       "      <td>1.178014</td>\n",
       "      <td>1.178014</td>\n",
       "      <td>2.413222</td>\n",
       "      <td>1.178014</td>\n",
       "      <td>13.73805</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>senior_Human</th>\n",
       "      <td>8.437410</td>\n",
       "      <td>9.898419</td>\n",
       "      <td>8.216911</td>\n",
       "      <td>11.504150</td>\n",
       "      <td>9.958047</td>\n",
       "      <td>6.857990</td>\n",
       "      <td>9.623469</td>\n",
       "      <td>9.205518</td>\n",
       "      <td>9.884420</td>\n",
       "      <td>4.484028</td>\n",
       "      <td>...</td>\n",
       "      <td>3.862928</td>\n",
       "      <td>1.178014</td>\n",
       "      <td>2.254255</td>\n",
       "      <td>1.178014</td>\n",
       "      <td>1.178014</td>\n",
       "      <td>1.178014</td>\n",
       "      <td>1.178014</td>\n",
       "      <td>2.581292</td>\n",
       "      <td>1.178014</td>\n",
       "      <td>11.67438</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>teenager_Human</th>\n",
       "      <td>8.429526</td>\n",
       "      <td>9.949921</td>\n",
       "      <td>8.637132</td>\n",
       "      <td>11.680144</td>\n",
       "      <td>10.211024</td>\n",
       "      <td>6.452668</td>\n",
       "      <td>10.214713</td>\n",
       "      <td>9.604091</td>\n",
       "      <td>9.903370</td>\n",
       "      <td>5.265158</td>\n",
       "      <td>...</td>\n",
       "      <td>3.162686</td>\n",
       "      <td>1.178014</td>\n",
       "      <td>1.178014</td>\n",
       "      <td>1.178014</td>\n",
       "      <td>1.453269</td>\n",
       "      <td>1.178014</td>\n",
       "      <td>1.178014</td>\n",
       "      <td>3.016177</td>\n",
       "      <td>1.178014</td>\n",
       "      <td>12.54986</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>toddler_Human</th>\n",
       "      <td>8.333979</td>\n",
       "      <td>10.027861</td>\n",
       "      <td>8.693345</td>\n",
       "      <td>11.691258</td>\n",
       "      <td>9.731870</td>\n",
       "      <td>7.191969</td>\n",
       "      <td>10.286671</td>\n",
       "      <td>8.958592</td>\n",
       "      <td>10.120605</td>\n",
       "      <td>5.322412</td>\n",
       "      <td>...</td>\n",
       "      <td>5.152286</td>\n",
       "      <td>1.178014</td>\n",
       "      <td>1.648489</td>\n",
       "      <td>1.178014</td>\n",
       "      <td>1.178014</td>\n",
       "      <td>1.178014</td>\n",
       "      <td>1.178014</td>\n",
       "      <td>3.201100</td>\n",
       "      <td>1.178014</td>\n",
       "      <td>12.81460</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>youngAdult_Human</th>\n",
       "      <td>8.601354</td>\n",
       "      <td>10.237539</td>\n",
       "      <td>9.176577</td>\n",
       "      <td>12.092567</td>\n",
       "      <td>10.388409</td>\n",
       "      <td>6.998035</td>\n",
       "      <td>10.577031</td>\n",
       "      <td>9.812306</td>\n",
       "      <td>9.798473</td>\n",
       "      <td>5.154397</td>\n",
       "      <td>...</td>\n",
       "      <td>4.365919</td>\n",
       "      <td>1.178014</td>\n",
       "      <td>1.178014</td>\n",
       "      <td>1.178014</td>\n",
       "      <td>1.178014</td>\n",
       "      <td>1.178014</td>\n",
       "      <td>1.178014</td>\n",
       "      <td>3.330907</td>\n",
       "      <td>1.178014</td>\n",
       "      <td>12.69678</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>youngMidAge_Human</th>\n",
       "      <td>8.378206</td>\n",
       "      <td>9.924419</td>\n",
       "      <td>9.128045</td>\n",
       "      <td>11.684351</td>\n",
       "      <td>10.253423</td>\n",
       "      <td>6.914197</td>\n",
       "      <td>10.260315</td>\n",
       "      <td>9.917214</td>\n",
       "      <td>9.823436</td>\n",
       "      <td>4.722714</td>\n",
       "      <td>...</td>\n",
       "      <td>4.218114</td>\n",
       "      <td>1.178014</td>\n",
       "      <td>3.464638</td>\n",
       "      <td>1.178014</td>\n",
       "      <td>1.737065</td>\n",
       "      <td>1.178014</td>\n",
       "      <td>1.178014</td>\n",
       "      <td>3.069621</td>\n",
       "      <td>1.178014</td>\n",
       "      <td>12.59430</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>83 rows × 7696 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "feature            ENSG00000000457_Brain  ENSG00000001084_Brain  \\\n",
       "sample                                                            \n",
       "10wpc_Human                     8.573918               8.875957   \n",
       "11wpc_Human                     8.439675               8.737682   \n",
       "12wpc_Human                     8.399178               8.916387   \n",
       "13wpc_Human                     8.637347               8.831740   \n",
       "16wpc_Human                     8.525125               8.575862   \n",
       "...                                  ...                    ...   \n",
       "senior_Human                    8.437410               9.898419   \n",
       "teenager_Human                  8.429526               9.949921   \n",
       "toddler_Human                   8.333979              10.027861   \n",
       "youngAdult_Human                8.601354              10.237539   \n",
       "youngMidAge_Human               8.378206               9.924419   \n",
       "\n",
       "feature            ENSG00000001167_Brain  ENSG00000001461_Brain  \\\n",
       "sample                                                            \n",
       "10wpc_Human                    11.265237               7.374965   \n",
       "11wpc_Human                    10.855314               8.066544   \n",
       "12wpc_Human                    12.555510               9.253555   \n",
       "13wpc_Human                    10.916489               9.190959   \n",
       "16wpc_Human                    11.271736               8.177629   \n",
       "...                                  ...                    ...   \n",
       "senior_Human                    8.216911              11.504150   \n",
       "teenager_Human                  8.637132              11.680144   \n",
       "toddler_Human                   8.693345              11.691258   \n",
       "youngAdult_Human                9.176577              12.092567   \n",
       "youngMidAge_Human               9.128045              11.684351   \n",
       "\n",
       "feature            ENSG00000001561_Brain  ENSG00000001617_Brain  \\\n",
       "sample                                                            \n",
       "10wpc_Human                     7.311018               9.959839   \n",
       "11wpc_Human                     7.354726              10.431113   \n",
       "12wpc_Human                     8.763702               9.946536   \n",
       "13wpc_Human                     8.158240              10.279600   \n",
       "16wpc_Human                     7.857303              10.363036   \n",
       "...                                  ...                    ...   \n",
       "senior_Human                    9.958047               6.857990   \n",
       "teenager_Human                 10.211024               6.452668   \n",
       "toddler_Human                   9.731870               7.191969   \n",
       "youngAdult_Human               10.388409               6.998035   \n",
       "youngMidAge_Human              10.253423               6.914197   \n",
       "\n",
       "feature            ENSG00000001629_Brain  ENSG00000001631_Brain  \\\n",
       "sample                                                            \n",
       "10wpc_Human                    10.542619               9.692082   \n",
       "11wpc_Human                    10.308780               9.242115   \n",
       "12wpc_Human                    11.530929              10.033949   \n",
       "13wpc_Human                    11.287268               9.510370   \n",
       "16wpc_Human                    11.402954               9.523244   \n",
       "...                                  ...                    ...   \n",
       "senior_Human                    9.623469               9.205518   \n",
       "teenager_Human                 10.214713               9.604091   \n",
       "toddler_Human                  10.286671               8.958592   \n",
       "youngAdult_Human               10.577031               9.812306   \n",
       "youngMidAge_Human              10.260315               9.917214   \n",
       "\n",
       "feature            ENSG00000002549_Brain  ENSG00000002745_Brain  ...  \\\n",
       "sample                                                           ...   \n",
       "10wpc_Human                     9.180280               4.281878  ...   \n",
       "11wpc_Human                     9.350255               3.363064  ...   \n",
       "12wpc_Human                     9.278142               4.322361  ...   \n",
       "13wpc_Human                     9.033614               4.784136  ...   \n",
       "16wpc_Human                     8.833177               2.785827  ...   \n",
       "...                                  ...                    ...  ...   \n",
       "senior_Human                    9.884420               4.484028  ...   \n",
       "teenager_Human                  9.903370               5.265158  ...   \n",
       "toddler_Human                  10.120605               5.322412  ...   \n",
       "youngAdult_Human                9.798473               5.154397  ...   \n",
       "youngMidAge_Human               9.823436               4.722714  ...   \n",
       "\n",
       "feature            ENSG00000267909_Brain  ENSG00000268104_Brain  \\\n",
       "sample                                                            \n",
       "10wpc_Human                     7.221091               1.178014   \n",
       "11wpc_Human                     7.116983               1.178014   \n",
       "12wpc_Human                     4.000716               1.178014   \n",
       "13wpc_Human                     5.635512               1.178014   \n",
       "16wpc_Human                     6.119527               1.178014   \n",
       "...                                  ...                    ...   \n",
       "senior_Human                    3.862928               1.178014   \n",
       "teenager_Human                  3.162686               1.178014   \n",
       "toddler_Human                   5.152286               1.178014   \n",
       "youngAdult_Human                4.365919               1.178014   \n",
       "youngMidAge_Human               4.218114               1.178014   \n",
       "\n",
       "feature            ENSG00000269058_Brain  ENSG00000270885_Brain  \\\n",
       "sample                                                            \n",
       "10wpc_Human                     1.178014               1.178014   \n",
       "11wpc_Human                     1.178014               1.178014   \n",
       "12wpc_Human                     1.178014               1.178014   \n",
       "13wpc_Human                     1.481758               1.178014   \n",
       "16wpc_Human                     1.178014               1.178014   \n",
       "...                                  ...                    ...   \n",
       "senior_Human                    2.254255               1.178014   \n",
       "teenager_Human                  1.178014               1.178014   \n",
       "toddler_Human                   1.648489               1.178014   \n",
       "youngAdult_Human                1.178014               1.178014   \n",
       "youngMidAge_Human               3.464638               1.178014   \n",
       "\n",
       "feature            ENSG00000271092_Brain  ENSG00000271503_Brain  \\\n",
       "sample                                                            \n",
       "10wpc_Human                     1.178014               1.178014   \n",
       "11wpc_Human                     1.178014               1.178014   \n",
       "12wpc_Human                     1.178014               1.178014   \n",
       "13wpc_Human                     1.178014               1.178014   \n",
       "16wpc_Human                     1.178014               1.178014   \n",
       "...                                  ...                    ...   \n",
       "senior_Human                    1.178014               1.178014   \n",
       "teenager_Human                  1.453269               1.178014   \n",
       "toddler_Human                   1.178014               1.178014   \n",
       "youngAdult_Human                1.178014               1.178014   \n",
       "youngMidAge_Human               1.737065               1.178014   \n",
       "\n",
       "feature            ENSG00000271601_Brain  ENSG00000272442_Brain  \\\n",
       "sample                                                            \n",
       "10wpc_Human                     1.178014               1.178014   \n",
       "11wpc_Human                     1.178014               1.421384   \n",
       "12wpc_Human                     1.178014               2.664630   \n",
       "13wpc_Human                     1.178014               1.776655   \n",
       "16wpc_Human                     1.178014               2.413222   \n",
       "...                                  ...                    ...   \n",
       "senior_Human                    1.178014               2.581292   \n",
       "teenager_Human                  1.178014               3.016177   \n",
       "toddler_Human                   1.178014               3.201100   \n",
       "youngAdult_Human                1.178014               3.330907   \n",
       "youngMidAge_Human               1.178014               3.069621   \n",
       "\n",
       "feature            ENSG00000272886_Brain  ENSG00000273079_Brain  \n",
       "sample                                                           \n",
       "10wpc_Human                     1.178014               11.74615  \n",
       "11wpc_Human                     1.178014               11.28160  \n",
       "12wpc_Human                     1.178014               13.97646  \n",
       "13wpc_Human                     1.178014               12.47349  \n",
       "16wpc_Human                     1.178014               13.73805  \n",
       "...                                  ...                    ...  \n",
       "senior_Human                    1.178014               11.67438  \n",
       "teenager_Human                  1.178014               12.54986  \n",
       "toddler_Human                   1.178014               12.81460  \n",
       "youngAdult_Human                1.178014               12.69678  \n",
       "youngMidAge_Human               1.178014               12.59430  \n",
       "\n",
       "[83 rows x 7696 columns]"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "brain = data[data.view == 'Brain'].pivot(index='sample', columns='feature', values='value')\n",
    "brain"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'Brain': AnnData object with n_obs × n_vars = 83 × 7696,\n",
       " 'Cerebellum': AnnData object with n_obs × n_vars = 83 × 7696,\n",
       " 'Heart': AnnData object with n_obs × n_vars = 83 × 7696,\n",
       " 'Liver': AnnData object with n_obs × n_vars = 83 × 7696,\n",
       " 'Testis': AnnData object with n_obs × n_vars = 83 × 7696}"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "views = data.view.unique()\n",
    "data_list = [data[data.view == m].pivot(index='sample', columns='feature', values='value') for m in views]\n",
    "mods = {views[m]:sc.AnnData(data_list[m]) for m in range(len(views))}\n",
    "mods"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In addition, we keep the meta data for each sample, containing the developmental time points."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>time</th>\n",
       "      <th>species</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>sample</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>10wpc_Human</th>\n",
       "      <td>7</td>\n",
       "      <td>Human</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11wpc_Human</th>\n",
       "      <td>8</td>\n",
       "      <td>Human</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12wpc_Human</th>\n",
       "      <td>9</td>\n",
       "      <td>Human</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13wpc_Human</th>\n",
       "      <td>10</td>\n",
       "      <td>Human</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16wpc_Human</th>\n",
       "      <td>11</td>\n",
       "      <td>Human</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>senior_Human</th>\n",
       "      <td>23</td>\n",
       "      <td>Human</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>teenager_Human</th>\n",
       "      <td>19</td>\n",
       "      <td>Human</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>toddler_Human</th>\n",
       "      <td>17</td>\n",
       "      <td>Human</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>youngAdult_Human</th>\n",
       "      <td>20</td>\n",
       "      <td>Human</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>youngMidAge_Human</th>\n",
       "      <td>21</td>\n",
       "      <td>Human</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>83 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                   time species\n",
       "sample                         \n",
       "10wpc_Human           7   Human\n",
       "11wpc_Human           8   Human\n",
       "12wpc_Human           9   Human\n",
       "13wpc_Human          10   Human\n",
       "16wpc_Human          11   Human\n",
       "...                 ...     ...\n",
       "senior_Human         23   Human\n",
       "teenager_Human       19   Human\n",
       "toddler_Human        17   Human\n",
       "youngAdult_Human     20   Human\n",
       "youngMidAge_Human    21   Human\n",
       "\n",
       "[83 rows x 2 columns]"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "obs = (\n",
    "    data[['sample', 'time', 'group']]\n",
    "        .drop_duplicates()\n",
    "        .rename(columns = {'group' : 'species'})\n",
    "        .set_index('sample')\n",
    ")\n",
    "obs"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We now create a multimodal `MuData` object:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "mdata = mu.MuData(mods)\n",
    "mdata.obs = mdata.obs.join(obs)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This contains both the gene expression data,"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "MuData object with n_obs × n_vars = 83 × 38480\n",
      "  obs:\t'time', 'species'\n",
      "  5 modalities\n",
      "    Brain:\t83 x 7696\n",
      "    Cerebellum:\t83 x 7696\n",
      "    Heart:\t83 x 7696\n",
      "    Liver:\t83 x 7696\n",
      "    Testis:\t83 x 7696\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "AnnData object with n_obs × n_vars = 83 × 7696"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "print(mdata)\n",
    "mdata[\"Brain\"]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "as well as the sample-level information given by the developmental time points, which are not yet matched for different species."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>time</th>\n",
       "      <th>species</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>sample</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>10wpc_Human</th>\n",
       "      <td>7</td>\n",
       "      <td>Human</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11wpc_Human</th>\n",
       "      <td>8</td>\n",
       "      <td>Human</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12wpc_Human</th>\n",
       "      <td>9</td>\n",
       "      <td>Human</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13wpc_Human</th>\n",
       "      <td>10</td>\n",
       "      <td>Human</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16wpc_Human</th>\n",
       "      <td>11</td>\n",
       "      <td>Human</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>senior_Human</th>\n",
       "      <td>23</td>\n",
       "      <td>Human</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>teenager_Human</th>\n",
       "      <td>19</td>\n",
       "      <td>Human</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>toddler_Human</th>\n",
       "      <td>17</td>\n",
       "      <td>Human</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>youngAdult_Human</th>\n",
       "      <td>20</td>\n",
       "      <td>Human</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>youngMidAge_Human</th>\n",
       "      <td>21</td>\n",
       "      <td>Human</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>83 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                   time species\n",
       "sample                         \n",
       "10wpc_Human           7   Human\n",
       "11wpc_Human           8   Human\n",
       "12wpc_Human           9   Human\n",
       "13wpc_Human          10   Human\n",
       "16wpc_Human          11   Human\n",
       "...                 ...     ...\n",
       "senior_Human         23   Human\n",
       "teenager_Human       19   Human\n",
       "toddler_Human        17   Human\n",
       "youngAdult_Human     20   Human\n",
       "youngMidAge_Human    21   Human\n",
       "\n",
       "[83 rows x 2 columns]"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mdata.obs"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Integrate data"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**MEFISTO** can be run on a `MuData` object with `mu.tl.mofa` by specifying which variable (*covariate*) should be treated as *time*.\n",
    "\n",
    "- To incorporate the time information, we specify which metadata column to use as a covariate for MEFISTO — `'time'`.\n",
    "\n",
    "- We also specify `'species'` to be used as groups.\n",
    "\n",
    "- In addition, we tell the model that we want to learn an alignment of the time points from different species by setting `smooth_warping=True` and using `'Mouse'` as reference.\n",
    "\n",
    "- Using the underlying Gaussian process for each factor we can interpolate to unseen time points. This is enabled by providing `new_values`, which correspond to the covariate, i.e. time.\n",
    "\n",
    "For illustration, we only use a small number of training iterations."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "        #########################################################\n",
      "        ###           __  __  ____  ______                    ### \n",
      "        ###          |  \\/  |/ __ \\|  ____/\\    _             ### \n",
      "        ###          | \\  / | |  | | |__ /  \\ _| |_           ### \n",
      "        ###          | |\\/| | |  | |  __/ /\\ \\_   _|          ###\n",
      "        ###          | |  | | |__| | | / ____ \\|_|            ###\n",
      "        ###          |_|  |_|\\____/|_|/_/    \\_\\              ###\n",
      "        ###                                                   ### \n",
      "        ######################################################### \n",
      "       \n",
      " \n",
      "        \n",
      "Loaded view='Brain' group='Human' with N=23 samples and D=7696 features...\n",
      "Loaded view='Brain' group='Mouse' with N=14 samples and D=7696 features...\n",
      "Loaded view='Brain' group='Opossum' with N=15 samples and D=7696 features...\n",
      "Loaded view='Brain' group='Rabbit' with N=15 samples and D=7696 features...\n",
      "Loaded view='Brain' group='Rat' with N=16 samples and D=7696 features...\n",
      "Loaded view='Cerebellum' group='Human' with N=23 samples and D=7696 features...\n",
      "Loaded view='Cerebellum' group='Mouse' with N=14 samples and D=7696 features...\n",
      "Loaded view='Cerebellum' group='Opossum' with N=15 samples and D=7696 features...\n",
      "Loaded view='Cerebellum' group='Rabbit' with N=15 samples and D=7696 features...\n",
      "Loaded view='Cerebellum' group='Rat' with N=16 samples and D=7696 features...\n",
      "Loaded view='Heart' group='Human' with N=23 samples and D=7696 features...\n",
      "Loaded view='Heart' group='Mouse' with N=14 samples and D=7696 features...\n",
      "Loaded view='Heart' group='Opossum' with N=15 samples and D=7696 features...\n",
      "Loaded view='Heart' group='Rabbit' with N=15 samples and D=7696 features...\n",
      "Loaded view='Heart' group='Rat' with N=16 samples and D=7696 features...\n",
      "Loaded view='Liver' group='Human' with N=23 samples and D=7696 features...\n",
      "Loaded view='Liver' group='Mouse' with N=14 samples and D=7696 features...\n",
      "Loaded view='Liver' group='Opossum' with N=15 samples and D=7696 features...\n",
      "Loaded view='Liver' group='Rabbit' with N=15 samples and D=7696 features...\n",
      "Loaded view='Liver' group='Rat' with N=16 samples and D=7696 features...\n",
      "Loaded view='Testis' group='Human' with N=23 samples and D=7696 features...\n",
      "Loaded view='Testis' group='Mouse' with N=14 samples and D=7696 features...\n",
      "Loaded view='Testis' group='Opossum' with N=15 samples and D=7696 features...\n",
      "Loaded view='Testis' group='Rabbit' with N=15 samples and D=7696 features...\n",
      "Loaded view='Testis' group='Rat' with N=16 samples and D=7696 features...\n",
      "\n",
      "\n",
      "Model options:\n",
      "- Automatic Relevance Determination prior on the factors: True\n",
      "- Automatic Relevance Determination prior on the weights: True\n",
      "- Spike-and-slab prior on the factors: False\n",
      "- Spike-and-slab prior on the weights: True\n",
      "Likelihoods:\n",
      "- View 0 (Brain): gaussian\n",
      "- View 1 (Cerebellum): gaussian\n",
      "- View 2 (Heart): gaussian\n",
      "- View 3 (Liver): gaussian\n",
      "- View 4 (Testis): gaussian\n",
      "\n",
      "\n",
      "Loaded 1 covariate(s) for each sample...\n",
      "\n",
      "\n",
      "Smooth covariate framework is activated. This is not compatible with ARD prior on factors. Setting ard_factors to False...\n",
      "\n",
      "##\n",
      "## Warping set to True: aligning the covariates across groups\n",
      "##\n",
      "\n",
      "\n",
      "######################################\n",
      "## Training the model with seed 1 ##\n",
      "######################################\n",
      "\n",
      "\n",
      "Importing the dtw module. When using in academic works please cite:\n",
      "  T. Giorgino. Computing and Visualizing Dynamic Time Warping Alignments in R: The dtw Package.\n",
      "  J. Stat. Soft., doi:10.18637/jss.v031.i07.\n",
      "\n",
      "Covariates were aligned between groups.\n",
      "Optimising sigma node...\n",
      "\n",
      "\n",
      "#######################\n",
      "## Training finished ##\n",
      "#######################\n",
      "\n",
      "\n",
      "Warning: Output file models/mefisto_evodevo.hdf5 already exists, it will be replaced\n",
      "Saving model in models/mefisto_evodevo.hdf5...\n",
      "Saved MOFA embeddings in .obsm['X_mofa'] slot and their loadings in .varm['LFs'].\n"
     ]
    }
   ],
   "source": [
    "mu.tl.mofa(mdata, n_factors=5, \n",
    "           groups_label=\"species\",\n",
    "           smooth_covariate='time', smooth_warping=True,\n",
    "           smooth_kwargs={\"warping_ref\": \"Mouse\", \"new_values\": list(range(1, 15))},\n",
    "           outfile=\"models/mefisto_evodevo.hdf5\",\n",
    "           n_iterations=25)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Visualization in the factor space"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "import seaborn as sns\n",
    "palette = sns.color_palette(\"Set2\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's take a look at the decomposition learnt by the model."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "... storing 'species' as categorical\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "mu.pl.mofa(mdata, color=\"species\", palette=palette, size = 250)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "... storing 'species' as categorical\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "mu.pl.mofa(mdata, color=\"time\", size = 250)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "... storing 'species' as categorical\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "mu.pl.mofa(mdata, color=\"time_warped\", size = 250)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Latent factors versus common developmental time"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can plot the latent processes along the inferred common developmental time."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "mdata.obs[\"Factor1\"] = mdata.obsm[\"X_mofa\"][:,0]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Before alignment:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "... storing 'species' as categorical\n"
     ]
    },
    {
     "data": {
      "image/png": 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9Itrz+dOKj2tCDCSySEyIAFESh6P96UOozbWgKChRQ/zua7O7KNhby6HKFowGLWNyhjA8xb+Tn4qbPmNn/VtYnA3oFCM5MXOZMPQnaBStX/2r6tppbrUxNM5EXLTJ75hPVJvDxqoD37G5thS3qjI+PoXLMyf1Wut4WsJw1lUVc7C1+7GdZyeNIMEUGciQhegXkqCFCDAleuhxvd7ucLHyP4XUNVq62ooONnLm5BSmjfN+HCTAodZv2Fz9t66vnaqVwsb3UXEzOeE6n30tNier1xZTXt3W1TZieCwXnpmJNkCHnrhVlT/t/JxDbUcrQ22tO8yB1noennwRRp33ohV6jZbbxs1mXWUxOxrKMWi0TE/I7LXwhBADhdziFiLEFOyt7Zacj/hmewUWm+/KRUUNH3ps39/0GU637+eya/MPdUvOAHsPNpK/w3chh5Oxq7GiW3I+otHWQb4f9ZmNWj3np47ijvHncdPYcyU5i0FFErQQIeZQZYvHdpdLpeIHCfSHWh3VHtudqg2r03uVJofDxd7SnokSYHex58pPfaHCR+WoCg/FLIQ4lUiCFiLEGA3enzwZw3w/R1atwzy3OyMw6b1v/XK63Ljdnhdo2ewun2OejCST9+fqw8KjAjauEAOBJGghQszYXM+LyWKjjCQn+F441XRoBqq75z/rlrIZdHR4XyFtMupJjPdcxWl4SuAS5di4JFLCY3q0xxhMzEjIDNi4QgwEkqCFCDHpSVGcPTUVnU4D3287ios2csns7N7PmbamU7/nKmxNw3E7jDjaE2kqvoiOqqloNb77nj01rXPMY5iMOk6fGLha0hpFw63jzmXa0Ax0igYFhfFxKdw+fg4mnSFg4woxEMgqbiFC0Ph4MxlaPY7KDtBriUiPIzK894SVlxlHfkEaDYWLurWnJ0USbvK+IhogdVgki+ePZntRbdc2q/EjhmL2Y9yTEWUwcUPeGVynulFVFZ3Gv+1gQgx2kqCFCDHOJisNK3eg2l0oAHYXHd9W4GqxEXvJKJ99p40bRmVtG4cqW7vaos1hnDdzuF9jx0YZOee0tBMP/iRoFU3nKSNCCEAStBAhp2NrBaqHhVm2vfU4Gyzo4rwfHqLXabni/JGUVbVSXd9OlDmMrLRotBp5miXEQCMJWogQ46zv8HnNV4I+InVYJKnD5DQtIQYy+VgtRIB1WB1YrA6/X6/zspoa8Cs5B5PFaafB2n5cZ2oLITyTGbQQAVLXaGHNxlLKazoPF0kbFsl5MzKIjTb67Bc+KQlLQRWqo3tN47CcOJ/JO5gsTjtvFH/LlrpDuFQ3CUYzl2dOYuKQ4DzPFmIwkBm0EAFgs7t4+79FXckZ4HBVK2/9twiH0+2jJ+hiTcReOQ59Wuf+Y8WgJXxyEjE/HhnQmE/G3ws3sKn2IC6182ersbbxtz1fc6C1LsiRCTFwyQxaiAAoPFBPh7XnudltHQ72lTYwOtt3ZStDciTxV41HdblBo/S+/zmIqjta2NlY0aPdjcrair1kjvS/ipcQ4ihJ0EIEQHOb3fu1Vu/XfkgJUBWpvlRva/d+zer9mhDCt9D/1y/EAJQQ5/1ZcUKIPkc+UakRMZ17mD1IN3s//1sI4ZskaCECIDcjhiGxPVdcJ8aHk5XqvUDEQBRlMHF2Uk6P9gidgTkpofvcXIhQJ7e4hQgArUbDwvNH8s32CvaVNqIoMHJ4HDMmJIX08+QTtTBrCkONkXxVVUybw8bImER+nD6WIUbfxT2EEN5JghYiQExGHbOnpzN7enqwQwk4jaIwO2Uks2XGLHrhUt1srT3EptpSLE4H6ZGxnJ2US6JJyov+kNziFkII0S/sLid/2rGWvxdtoKChnH0tNawpL+KRLR+xte7wSX3v/Px8brvttm5tTz/9NKtWrTqp7xtM/ZagHQ4HS5cu5ZprruGKK65gzZo1/TW0EEKIEPDx4V0UNVf3aHeqbl4t2kC7wxaEqEJXv93iXr16NTExMTz11FM0NTVx6aWXMmfOnP4aXgghRBCpqsrXVfu9Xre7XeTXHAzIY5LbbruNZ599FoAzzjiD9evXc/fdd6PT6aioqMButzNv3jzWrl1LZWUlf/3rX0lJSeHBBx+kqqqKmpoaZs+ezW233cbdd9+NwWCgvLycmpoannjiCcaMGdPnMUM/zqAvuOACbrnlFqDzf5RWKzVfRehzud1s2lHJq+/s5G9vbueT9QdoaZNP+UIcL5vLSYvD6vM1NdZWn9d7s3HjRhYvXtz13wcffODz9SkpKbzyyitkZWVRVlbGSy+9xPnnn8/nn39OZWUlEydO5OWXX+btt99mxYoVXf2Sk5N5+eWXWbx4MStXrjypmH3ptxl0REQEAG1tbdx8883ceuutHl+3cuXKrh+4sbGxv8ITwqNPvj5I4YGGrq93FddTWtHC4vmjMRn1QYxMiIHFoNURrtPT4fReOCbWcHJnBMyYMaNrpgydz6B/6NhCLqNHjwYgKiqKrKysrj/b7XZiYmLYsWMHGzduxGw2Y7cfPWBo1KjOuuzDhg1j69atJxWzL/26SKyyspJrr72WSy65hPnz53t8zaJFi1i1ahWrVq0iNja2P8MTopuGZku35HxEW4eDgr39c8Z0h7MBh8t7+UkhBgqNojAjIcv39cTMPh+3rq6O2tpaAMrLy2lubu665mvL46pVq4iMjOSZZ55hyZIlWK3WruTeX1sl+20GXVdXx5IlS3jwwQeZOXNmfw0rxAmr9lGXubo+sEdYVrZvY2vNa7TYy1DQkhY5g6mJNxCmlRrPYuD6cfo49jZXU9be1K1dAa7Knkq0oe/LqcbGxhIZGcnChQvJzs4mNTXVr34zZ87kjjvuYNu2bRgMBjIyMqipqenz+HxR1H4q3PrYY4/x8ccfd91GAHjppZcwGr2X3luwYMGAXiIvBraKmjZWfFzo8drk0Ymcc1pgSik22Ur5pPRu3Gr3YhuJ4WOZnfZQQMYUwl8n+3vZ6nTwVVUx+TUHsbgcZJjjmJ08kpzooX0Y5eDQbzPo+++/n/vvv7+/hhPipCUnmEmMD+8xk9ZqFSaMCNwvk32Nn/RIzgDVHTtptB4k1jg8YGMLEWhGnZ65qaOYmzoq2KGEPDmoRAgfLp2TS3ZaDEceOcXHGLl0di6x0d7v/JysNof322jtPq4JIQYXOepTCB8iTHoumZ2DxebE6XQTGWEI+JhxxiyqOrb3aFdQiJHZsxCnDJlBC+EHU5iuX5IzQG7MjwjT9jyXeHjUOZj1Cf0SgxAi+GQGLUSICdfHMzf9MXbUvUlVRwEGTQRZ0bPJi/O8NVEIMThJghYiBEUakjg9+ZZghyFEn1PdLtS936IW5oPNgpKYgTLhXJTYxGCHFnLkFrcQQoh+oTrsuP/9R9SPXoSS7VC+F3Xrp7j/+SDqvi0n9b3z8/MZOXIkH374Ybf2+fPnc/fdd5/U9w4WSdBCCCH6hbrpQzjs4WwBlxP3x39HtbSd1PfPysrqlqCLioqwWCwn9T2DSRK0EEKIgFNVFXXHOu8vcNpR92w8qTHy8vKoqKigtbWz6Mbq1au7jpVevXo1l19+OVdffTX33HMPDoeDVatWdZ3XbbPZmD17NgCvv/46CxcuZNGiRTz22GNA51HVN954I4sXL+bGG2+ksrLypGL1hyRoIYQQgeewQkeL79c0nfw+//PPP5///ve/qKpKQUEBkyZNoqmpiT//+c+89tpr/Otf/yIyMtJnFapVq1bxwAMPsHLlSrKysnA6nTz55JMsXryY5cuXc8MNN3gsxNHXfC4S8/UDLFq0qM+DEUIIMUjpwyAsHGw+ir9EnnyBpPnz5/Pwww+TlpbG1KlTAXC73eTk5GA2mwE47bTT+Prrr5kwYUJXv2NPvX788cd55ZVX+MMf/sDEiRNRVZW9e/fyt7/9jb///e+oqopOF/g11j5HKCkpYe3atVx88cUBD0SIQLPanVgsTqIiDWg1/XPzyG13Yj/YBIqCISMGjUHqoItTk6JoUEafjvrdZ55foNGijDr5QkppaWl0dHSwfPlybr/9dg4fPoyiKOzfv5+Ojg7Cw8PZtGkTmZmZhIWFdVW62rVrV9f3ePPNN/nd735HWFgYN9xwA9999x1ZWVksWbKEyZMns3//fjZv3nzSsfbGZ4K+5557KCkpYdasWYwfPz7gwQgRCA6nm8/zD1FYUo/LrRJu1DFzQjIT8gJ76IelsJaWT4pR7S4AlDAt0ReOwJgbH9BxhQhVysyLUQ8XQl3ZD6+gnHsNijmmT8aZN28e7733HpmZmRw+fJjY2Fh+/OMfc+2116LRaEhPT+fOO+/EZrPxr3/9i6uvvpoxY8YQEREBwMiRI7nmmmuIiIggMTGRCRMmcNddd/Hwww9js9mwWq3cd999fRKrL71Ws2poaMBisZCSkhLwYH5IqlmJvvDJ1wfYtb++R/v8c7LJzQhMzXFXi5Xal7aA+wf/vHQahv5iKtp+OpVMiL52sr+XVbsFtWAdauHGo/ugJ52HkpLbh1EODr3eRI+Li+Pll1/mhhtu6I94hOhTFquTPQcaPF77rrAmYAnasru2Z3IGcLqxFtYRMSU5IOMKEeoUgwll6o9g6o+CHUrI8+sp95dffsl1112HVivPz8TA0m5x4PaUKIHWNnvAxlXtLuwGCwdHbqQ2qRhQSKjIZXjhDFR7z1KSQgjxQ34l6MbGRs466yxSU1NRFAVFUVixYkWgYxPipMVEhWEM02K1uXpcGzYkImDj6odHss30b9qjjt5aL8vaRnNsBednLAvYuEKIwcOvBP3CCy8EOg4hAkKn1TB9XBJfftt9UYpep2HauGEBG7cqZg/tlp7PvVtja6iJ3EsqpwVsbCHE4OBXgtZqtSxbtoz9+/czfPhw7rnnnkDHJUSfmTJmGBHhBrbtqaa1w0HSkAimj09iaFx4wMZssh30eq3RepBUsyRoIYRvfiXo+++/n6uvvprTTjuNTZs2cd999/Haa68FOjYh+kxeZhx5mXH9Np5Z770yj69rQgx2brfK3tJGCkvqsTlcJMZHMGHkUGKjjMEOLeT4laBtNhtz5swB4LzzzuPVV18NaFBCDHQZUWeyo+5NrK6mbu3huiGkR84ITlBCBJnD6ebdNfs4XNXa1VZe3cb2whrmzco66V0Vhw8f5g9/+ANNTU04HA7y8vK48847u04QG2j8Ok7J5XJRVFQEdFYHURQloEEJEUosziaKGj9kZ93b1Fv3+9VHrzExO+0hEkxjvm9RGBY+ntlpD6LVyB5ocWratKOyW3I+wuVW+fjrA1hsJ77DwWq18j//8z/ceOONLF++nBUrVjBhwgTuuOOOkwk5qPyaQT/wwAPce++91NTUkJiY2FXdQ4jBrqx1E+srn8OtOgDYUb+S7Og5nJb4y14/qEaHpTIn/WFsrlYUFAzagfkpXoi+oKoqO/bWer3udLrZU1LP5FEn9gjoiy++4LTTTut2vvZll13Gv/71L+666y6gsyJVR0cHTz75JNnZ2bzyyit8+OGH6HQ6pk6dytKlS9myZQtPPvkkOp0Ok8nEn/70J2pra7nnnnvQ6XS43W6eeeYZDh06xIoVK3j22WcBOOOMM1i/fj133303Op2OiooK7HY78+bNY+3atVRWVvLXv/6V9PR0v38mv2bQVVVV/Pvf/+arr77i7bffpqSk5HjeNyEGJKfbysaqv3Ql5yP2N6+hvO1bv79PmDZSkrM45TmcbjqsvmfITS22E/7+hw8f9pj8UlNT2bx5M2lpafzzn//kpptu4qmnnqKoqIiPP/6YFStWsGLFCkpLS1m7di2fffYZF154If/3f//H1VdfTUtLCxs2bGD8+PG8+uqr3HTTTV3lLL1JSUnhlVdeISsri7KyMl566SXOP/98Pv/88+P6mXzOoNeuXcvWrVv58MMP+e6774DOqiBr1qxh3rx5xzWQEANNZft2HG7PlXcOtW4gNVJWYgvhL71OQ5hBi83e80yCIyIj9Cf8/RMTEykoKOjRXlpaytSpU5kxo3Ptx6RJk1i2bBklJSVMmDABvb5zzKlTp7Jv3z5+9atf8cILL/Czn/2MxMRExo8fzxVXXMFLL73EjTfeSGRkJLfddluPcY49NXv06NEAREVFkZWV1fVnu/34DkfyOYPOy8sjKyuLsLAwsrKyyMzMJCcnhz/+8Y/HNYgQA5P3Y+pVH9eEED0pisLobO+FYjSKwqisEy8kM2fOHDZs2NAtSb/11lvExsai0Wi6qlVt3bqV3NxcsrKyKCgowOl0oqoqmzdvJjMzk9WrV3PZZZexfPlycnNzefPNN1mzZg1Tpkzhtdde44ILLuDvf/97t0pY5eXlNDc3d/tZ+4LPGXRSUhKXXXYZs2bNoqioiNNPP53XX389KIUzhOhvwyImoMOAk56fetMipwchosBrsnWwvno/tZY2Us2xnJ6YRbhOFrWJvjFzQjKHq1qpa7T0uHbu9DTM4Sf+dy0iIoIXXniBZcuW0dTUhMvlYuTIkfzxj39k2bJlrFu3jjVr1uB2u3n88cdJS0vjwgsv5Oqrr8btdjNlyhTOO+88CgoKuP/++zGZTGg0Gh555BFUVeWuu+7i+eefx+12c8899zBy5EgiIyNZuHAh2dnZpKamnsxb41Gv1awArr/+eq699lrOPfdc3n//fT744AP+9re/9XkwPyTVrEQwqQ47u9/+EzsmfouqcXe1J5blcFbSQvSjJwcxur53sLWe53Z8jsV19Jl7XFg4S8fPJc4YuGNRxcBysr+X7Q4XBXtrKSxpwGZ3kRgfzqTRCaQkRPZhlN3dfffdzJs3j1mzZgVsjEDwaxW3xWLh3HPPBWD+/Pm89dZbAQ1KiFDg3FFAfNlMZtSPoTqlCKfOTnzNcGIaUrAmlA66BL1y/5ZuyRmgwdbBe6UFXD9yZpCiEoONQa9l6phhTB0TuKN2Bwu/ErRer2f9+vVMmDCBHTt2oNH4tfhbiJChNteh7lwHrY2QlI0yeiaKPsxnH0dT52IWoyWKjOLuC8KclsF127fdYaOktc7jtYKG8n6ORoi+9cQTTwQ7hBPiV4J+7LHHePLJJ3nsscfIycnhkUceCXRcQvQZ9dBu3O/+GZzfP0vevQH1u8/QLLoLxeT9tpouOwu2FHm8pk0ITB3pYNEqGjQouD0sfjNopMysEMHgV4LOyMjgr3/9a9fXNTU1AQtIiL6kqiruNf93NDkf0VCJuukjlLMXee1ryBiKPq4IR8MPLiguTOcMrtvbRp2eCfGpfFd/uMe1aQnD+z8gIYR/B5U899xzzJgxgylTpjBmzBiuv/76QMclhEdOl5vmNhsOp7v3FwM0Vnf+54Fasr3X7rHXTMeYHQlK58xSF6cl9qqJ6ANYCStYrs6ZSmpETLe2UTHDmJ8+LjgBCXGK82sGvXbtWtatW8eyZcu4/vrr+d3vfhfouIToYdOOSr7dVYXV5sKg1zIpL4HTJyX73nOo83HwgR/bhzQmPTELJqA6XKguFY3Rr38yA1K0wcT9ky5kT1PV99usYsiOGhrssMQgo7pVrEV1WPfU4rY50SeaCZ+UhC7WFOzQQo5fM+ihQ4diMBhob28nIyMDh8PReych+tB3e2r4ems5Vlvnwi27w0X+jkryCyp99lOi4iEl1/O1Uf5XlVL02kGdnI9QFIXRsUmcnZwryVn0OdXhovGtnTR/UIRtfwOOshY6tlRQ9+pWrHs9L1L0V35+PjNnzmTx4sUsXryYBQsWcPPNN3s9vevuu+9m3bp13drKysq48sore7z2xRdfpKCgAJvN1q+7mPxK0MOGDePtt9/GZDLxzDPP0NLSEui4hOhm6x7Pt6m3FdbQ21Z+zY+WQExCtzZlxFSUSef1WXxCiN615ZdhP9Tc84JLpfmjvbgtJzf5mzFjBsuXL2f58uWsWrUKvV5/3Odfe/KLX/yC8ePHU1tbGzoJ+sjCsEceeYTs7Gx++9vfkpCQwDPPPNMvwQlxREub50P0O6zOXp9HKzEJaK77PZpLb0aZsxjNTx9C8+Nfo2gH/4xYiFChqiqW7VXerzvcWHZ7r3Z1vOx2OzU1NURHR3Pfffdxww03MH/+/K7qUwBvvPEGP/vZz/jpT39KaWkpAA0NDfzqV79i4cKF/OUvfwGOzrZfeOEFiouL+X//7//1WZy++EzQGzdu7HyRRsOzzz6L2Wxm8eLF5OTk9EtwQhyRGO/5JKvYKCMGfe/bgBSNBiVrApoJ56Ak+F/uTQjRN1SHC3eH7xmyq6nnEaDHY+PGjSxevJh58+axYMEC5s6dS1paGhMnTuTll1/m7bffZsWKFV2vnzx5Mq+99ho///nPeeqppwDo6OjgqaeeYsWKFXz11VcUFhZ2vf5Xv/oVOTk5/OY3vzmpOP3lM0Efe+vQjxNBhQiYmROS8bQWbObE5P4PRghx3BS9FiXM94dpjdn34UG9OXKL+/XXX0ev15OamkpMTAw7duzgjjvuYNmyZd2eSU+dOhXorHB14MABoLNIVGRkJFqtlnHjxnW1B4PPBH3s6ti+qM7hdrt58MEHWbRoEYsXL+66pSBEbzJTo7l87gjSkyIJN+pISTRz6ewc8jLjgh2aEMIPiqJgGpvo/QUaBdOYBO/Xj0NsbCxPPfUU999/P//4xz+IjIzkmWeeYcmSJVit1q4J55HKV99++y25uZ2LSffv3097eztOp5OCgoKudui8m+x2+7nFsw/4fAi3a9currrqKlRVpbi4uOvPiqJ0u03gr88++wy73c7KlSvZtm0bTzzxBM8///wJBy8Gpur6dsqqWokw6clOj0Wv8+/o2LQhRlKTayGsHGITURIzAhypEKIvmU9Px36oCWdtzzrrUXOy0Jr77gjdnJwcFi9ezJ49ezh48CDbtm3DYDCQkZHRddjW9u3bufbaa1EUhWXLlqGqKtHR0dx22200NDQwb968bo904+PjcTgcPPXUUyxdurTPYvXGZzWr8nLvZ/CeSMnJxx9/nPHjx3PRRRcBcNZZZ/HVV195fb1Usxpc3G6Vj786QNHBo0dzhRt1LJg7goReDv5QWxtxv/kHaD7mFDtzLJqFS1FifXwqF0L0qZP9vey2O7Fsr8KyuxbV5kI/zEz45GQMqVF9GOXg4HMG3dd1n9va2jCbzV1fa7VanE4nOt3RMFauXMnKlSsBaGxs7NPxRXDt2FfbLTlD5yrsj9eV8LNLx/rsq371dvfkDNDWiPvLlWgvvbmvQxVCBIjGoCPitFQiTuv7+smDTb/uMzGbzbS3t3d97Xa7uyVngEWLFrFoUef5yAsWLOjP8ESAFR744aHWneqbrdQ2dDDUxyxaLd7q+cKBAlSnA8XXiWFA+9YKmrcfwOZoIjI6hagzMjGkRvsduxBC9Ld+TdCTJ09m7dq1zJs3j23btjFixIj+HF4EmcvlfSeA09XLwgtvixSV3p9fN6/fz3ft/6RqehGq1oXBGs7wjdMZd/piDMmBKxIvhBAno18LO8+dOxeDwcBVV13F448/zj333NOfw4sgy06L8dhuDtd73ed8hDJympdvOtHn7Nltd7HVupzKjN2o2u+PCTV2sHfcWkr2/NevuIUQIhj6dQat0WiklvQpbNKoBEoO1VNZb+1q02pg7szhaDS+t/EpZ12OWn0Qao8phxibiOacq33262iqozp5j8drB80byONyv+MXQoj+JGcdin6jd7RzefXrFFuiKNcnE+7uYLStiOjGyyH1LJ99FVMkmp88CCXbcdeVo4kb1jl77uW4ToexA1Xj+fa51dR6wj+LEOLEuFUXh1s3UtryFXZ3B3HGLHJjfkSkISnYoYUcSdCi36hb/ou2uYaR1DDSXny0/au3UUfN6HWhl7WwjvaNKs76GLQxEGGpI3zCMJ99oswp6F3hOLQ9913Gm+TIWiH6k9NtY135E1R37Oxqq7XsYV/TJ5yedCtpkdNP+Hvn5+dz6623du1bbm9vJzU1laeffhqDoef+6oqKCgoLC5k9e/YJjxlo/foMWpza1EO7PV+wtkGN71PlLHtqaf5wL876zkTrarLS8t9iOrb5Ljep1RgYm3hFz3Y1jLFpi/wLXAjRJ3Y3vNMtOR/hVp18U/lnbK6Tu6t1PNWsNm7cyNatXnaHhAiZQYv+Y/SxEMxo9n4NaN942GN7W34ZpgnDfB5Fmxc/H5M+jr2NH9HhqCfelMuY+MuJNcpJZEL0F1VV2d/0mdfrLtXGwZavGBk7r0/G+2E1q6qqKmpqapg9ezY333wzL774IlarlUmTJjFnzpw+GbOvSYIW/UYZexZqqYdZdHIOSpzvW9VHZs4/5G6xoTrcKAbfh/BnRJ1BRtQZfscqhOhbTtWK1eWhFvQx2uzey1H640g1q/r6ejQaDVdeeWVXNauFCxdis9mYNWsWt912G7/4xS8oKSkJ2eQMkqBFP9KMnIa7rhz12/+Ay9nZmJiB5qJf9tpXFx+Os64Dl9aBzdiGwRqBzmVAExmGopcnNUKEOp0Shl4TgcPd7vU1Jl38SY0xY8YMnn32WRobG1myZEm3alYbN27EbDZ3q2YV6iRBi36lOeMy1ElzoOoAhEejDBvuV7/waSlsL15OWfZ3OPV2tE49yQfHMzHpp31SaU0IEViKoiEz+mz2Nn7k+TpaMqNn9clYR6pZXXvttVxzzTVERkbyyCOPUFpayptvvomqqv1emepESIIW/U4Jj4KsCcfV51DStxzU5Xd97dI5OJyzhej4bMaxsK9DFEIEwLj4hdR07KLJ9sNFoQpTEpdg0sX22Vi9VbMaMWIEzz//PGPGjOkq4BRqfFazCjapZiWOWF3yv7Q7anq0h2kjuSz77yh+HPkphDh5J/t72eG2UNz0GaUtX+FwdxBrzGJkzDyGhuf1YZSDg8ygxYDQ4ajz2G5zteJUbegVUz9HJIQ4EXqNiVFx8xkVNz/YoYQ8mXaIASHOmO2xPcqQgl4jyVkIMfjIDFocN9XppiO/CFthFYpOwTg5E9M4//cUO6rbsJc1o4kwYMyJR9H1/jlx3JBFfFm2DJVjF3UojBsih40IIQYnSdDiuKhulYaX1+JoCQM6j+a0/ecw9r1lRF/ue5+x6lZp/mgv1j21qKgoKLRGGIi9YjT6BN8HlSRFTGB22oPsbniPZtshIg3JjIq7mKSIiX30kwVGk62D7Q3lKMDE+FSiDDLbF0L4RxK0OC7WDQXfJ+fuLCVuwivr0Sd538doKaiiqnobJWdsoDmuAoMtnOSD48j+UEPC9VN7HTshfAwJ4WNOKv7+9GXFPlaUfIv7+3WYK/dv4Zqc0zhjmOfb9UIIcSx5Bi2Oi21vhZcrCvbvPJd1PKL64A62z3yH5vgKUDrrMh/My2dP0kc4atr6Ptggqu5o4V/7N3clZwCn6ub/9m2iweb9oAYhhDhCErQ4LorW+8Z+Red7x17p0G9wa1092iszdmFx+D4CcKD5tq4UT++GG5UttYf6PR4hxMAjt7jFcQmflIblk2ag++ldClaM06f47Nse0+ixXdW4sca0EEVKX4UZdA4fJxT5unZEdUcL7x/awZ7GKsL1Bs5IzGJu6ii0st9biFOG/GsXx8U5YjRbo7Q4jsnPHRr4NikCTbTvU4Bioj2v9FbQEBnmu1jGQDMh3vuHjYk+rgE02jr4w/ZP2VxbSpvTRo2llXcObuf/9m3q6zCFECFMErQ4LruK6yg0GngnPowvo/WsidHzXnwYRS49h6t813LNG3IxGnpWncqMPqdPj/gLBZmRQ5idPKJH+wVpo0mOiPHZ94uKvbQ5bT3av6k+QJ3V/2f1bjW0zxkWQvgmt7hPYWplCWphPricKNkTYfjYXgtP1DdZAHBqFMrDtD2upQ2L9No33pjN2an3sr3uDRqs+zFoIsiOOW/Q7mVelD2VSfFpbK0/jILC1KHpZEcN7bXfoXYvjwJQKWtrZEgvtbO31ZfxfmkBZe1NxBhMzEnJY25KnhQVEWKAkQR9inLnf4i6fhV2dKiKhrCCL1BGzYQLbvD5izw22uj1WpyPa0cMixjPsIjxuNx2NIqu387QbnNY+ab6AI32DrIihzApPg2tpvex3aqbNeVFfFN9AKvLwZjYJOaljyU2LNyvcUfEJDIiJvG4Yh0SFuH9msl3ct7VWMELu9d1LVBrslv494HvsLuc/Dhj3HHFIYQILknQpyC1uY7Wbz4h33QROtcwNChYtY1M3PsFiaN2wfCxXvuOzR3Clt3VWKzObu2J8eE+Z88/pNUYTjj+41XSUsf/t3MtFpcDgDUUkWGO47ZxczDp9D77/nNvPt/UHOj6el1VMTsbK7hv0oWY9T33g/eFc5JHsKG6BOcPblGPjE4kNcL3o4BPDu/xuHp8TUUhP0objV7T8xGDECI0yTPoU5CrpIDvdJcyvi2B0RY3eRYXE9uiOKDMp33vTp99w416Fp4/kuEpUQBoNQqjs+NZcN6IkL2FunxffldyPqK0rYFPynb77FdtaWHjMcn5iAZbB19XFfdpjMdKiYjhf8ecTXJ4NABaRcNpQzP45aizeu1b2eF5u1qH00Gz3dKncQohAktm0KegQw0GRnj4XZ1pU9hfH09vlZqHxJpYcN4IXC43iqKg0YRmYgaosbRS4SVpbas7zKXDvf+0pa0NHmejAAda6/sgOu9Gxybx0JSLaLZbCNPoMPYy0z8iKTyalmZrj/ZwnZ5oOWZUiAFFZtCnILsl1uv/eK0t2u/v41ZsuLH3TVABouD9w0NvM/44H8+Z43w8J+5L0QaT38kZ4PzUUR5/4tnJI+X2thADjMygT0Hm6HDA80phU2Tvi58arQfYWvMPaiy7UdCSFjmNyQlLMOli+jbQPjDUZCbDHEdpW0OPa1OH+q7AlROdQLo5lkNt3d8rnaJhVlJOn8bZV8bGJfPLUWfxwaEdXau4Z6eM5PyUUcEOTQhxnCRBn4KSp6RSlV9OR2Qt1SlFuDUuhlRlEVufRtK0VJ99Lc4mPj/8CHZ3535cFReHWr+hxV7JBRl/CMnn0D8bMYM/7Vzb7RlsXkwic1Pyeu37v6PPZvm+fHY1VqICiaZIrsyaQlK4/3ca+tukIWlMGpKGy+32a6W6ECI0SYIe4FRVxVHegrvdgT4lCq2599XRmnA9NfMOsUf7TldbWfY2UjqmMSvtTJ99S5rXdiXnYzXZDlLVUUBSRG9PsPtfSkQMj02dz5a6QzTaOsiMHMKoWP9OLosJC+emsefSYrdgczkZYjSH5IcQTyQ5CzGwSYIewJyNFpre2YOzvqOzQaMQcVoKkbOG++zX7qijUPtej/by8E1Ute9gWIT3/bKt9kqv19rsVeBHglZVlRaHFZNWj0HbP38FDVodMxOzTri/1HEWQvQ3SdADWNP7hUeTM4BbpT2/DH2iGePIIV77VbRtQcXzMZBlbZt8JuiYMO/PbWPC0nuNeWvdYd45uI0aSyt6jZYZCZlcmTW53xK1EEIMFHIPrA+52u3YDjR2T5oB4qhpw1ntua6wZWe1z74axXsy1Ci+V/pmRZ9DuC6+R3uCaQxDw30vRCpuruHFPV9TY+k8s9vhdvFVVTH/3Jfvs58QQpyKJEH3AVVVaVlbQu0Lm2l8exd1r2yl4c2duC2O3juf6Ji2nnWVj3D/4JSvH0o1n4ZW8bx1JyPS9zNogzaCOemPkBF5JjrFSJg2kpGxFzEr9a5eY15TUYTqYWfxt7Wdz4aFEEIcJfcV+4BlexUd31Z0a7OXNtH832JiLwnM9hb9MDOKxonq7vm/0BDv7XiNTmG6KKYP+182Vv0Ft9r5IUJBYeyQRcSbet8+ZNYncHryLccds7dKTCoq9db2Xs+3bnPY2FBdQkV7EwmmKM4cliXPhoUQg5Yk6D7Qsb3KY7ttXz3uDgeacP8PmvB/0AYi1HzaOB2OOZpCSxMmeyEw0Wf3jKgzSAwfy+G2fNyqg5SIqZgN/hV1aLFb+ejwTgrqyzFotExLGM7c1FG9HoSRFtFzTzGAXqMlKTzKZ98aSytPF3zWbavUZ+WF3D5+dq/nUwshxEAkCboPeL2lrILb5uw1QTtKK+hYtwNXqwtdrJ7w2ZPQJXpf5AVAcz0mzV50aiNWdQRu1YReqcKoFKG0pfkVt1EXTW7M+X699giry8HTBZ9SbTla+/m90gIOttbzP2PO9tl3buoovq07hM3V/f06J2kEEb0UnnjnwLYeZ0m3O228XfIdt46bfVw/gxBCDASSoPuAIS0a666aHu2aqDC0Mb5LMNq27aHx02qg8+hIeztY/rmduAW56LN9rIoekgxaHXpXLXqlttslJbH31dQnKr/6YLfkfMT2hnIOttYzPLLnArIjksKjuXP8eXxQuoN9LbVE643MSsrl3OQRvY5b0FDusb2wqQq7yymrwIUQg478VusD5plp2EoaUC3HzAwViDons9dDLVq/OAB0v72rEkbrf3cQ92vviVYJj0KZcC7q1k+7XzCYUCYf36z4eBxs814korcEDZBujut1pu2JQavF6ey5NUyraNAMkINDhBDiePRbgm5tbWXp0qW0tbXhcDi4++67mTRpUn8NH1C6WBNDrp1I+5ZKHFWtaKPCCJ+UhCHZ93NVV0sLTofn19jbei/G4DhzAdttbaTsLyDcYac8dii6mZeQF+vfs+QT4atIRLwxcAUkpg3N5IvKvT3apwxNRydFIIQQg1C/JehXX32VGTNmcN1111FSUsIdd9zBO++803vHfuaoasN2sBFNmA5j3hA0Jv8WeGmjjESdm3lcYymGMMAF9EwwGqX3LVqvFuVz2JpOTOQ4tG4tFoOF+oNl3JQ4nMyoXp5h03l7eFNNKU7VxYS4VCYNSet1NnrGsCw+LduDzd39OXKiKZIxsUm9jnmiLh0+gfL2Jva1HH2UMNwcx5VZkwM2phBCBFO/JejrrrsOg6HznGiXy0VYmO9FQf1NVVVa/luMpeDoIR+tXx4g5uI8wrLieu9fUYx74/tQdRCi4lAmzUEzxveeYo0xDGNMK9ammB7XjMne9zlD55alykI78W1HYzPZTCRXJvPpvr38YorvBP3uwe18fHhX19f5NQeZHJ/Gz0ed6TNJx4VFcNPYc3ijeHNXneWR0YlcO2I6GiVw2+pNOj13TjiPfc01VLQ3kxgeycjoxAFzLrYQQhyvgCTot956i9dee61b27Jlyxg/fjy1tbUsXbqUe++912PflStXsnLlSgAaGz2XRAwE2976bskZQHW4afpoLwm/moai85581MoS3G89BUdWJ1vbUD95FbelDc3UC3yOa//RNGpW7SXhmAlzeRhkX3CGz37ljc1EtfW8Pa5RNTSXu2GK9761llb+c0xyPmJr/WF2NVYwLi7F59i50Qk8NOUi6qxt6DVaovtxL3JudAK50Qn9Np4QQgRLQBL0woULWbhwYY/2oqIibr/9dn77298ybdo0j30XLVrEokWLAFiwYEEgwvPIUljrsV21OLGVNmHM9j6Ldm/68GhyPrbvpo9RJ85B0Xm/Tf7lnkYOxxqJcbiJdKk06RRadRpqdtVy4VmRXvuFOcNQvt//rI+oRKPvwN6ajOoyYXT4vjuxs7HCw3lenXY09J6gjxhiNPv1OiGEEMev325xFxcXc8stt/Dcc8+Rl9d7Hd5+5+vwLdX3yVxUl3put7ZBaz14KW1od7g4XNW5ZalJr6HpmDy+/3CTzyFT4qLQGpqJGfEuBnPnQSmqW0db+UwS9L5n7WFa7x8YwmS7khBChIR++238zDPPYLfb+f3vfw+A2Wzm+eef76/he2UcEY9tX88tREqYFkN6jO/O0UPAwwlZ6AwQHu21m6KARlFwe/gA0Fst38gIA0njPsKlP3qKmaJxEpn2FblRkwDve4snxaeyQqvrcWCIAkxPGO5zXCGEEP2j3xJ0KCVjT4x5Q7Huq8e295gkrVGIOj8HjcH3Nh7NlPNxl+/r0a6MPRMlzPvzWb1OS3Z6DPtKGwE3itaO6goDFPJ6WZjWZCvFpT/k8Vqd62vgLK99TToDv8g7k78Xrsfi6nz4rVM0LMyaLMdmCiFEiBh09zNVVcVW3IC1qA4A48ghhOXE9braV9EoxFych720uWublWn0ULTRvk8CA1ByJqPMvQ71m/c6Z9L6MJRxs1DOuqLXvueclkqT9jOUmG/QGtpx2qLQt5zD6RN97xG3uzwXngCwuXqe9PVDY+OSeXL6ZexsqMChuhgbm4RZ3/vPKoQQon8MugTd8p99WHYe3Str3VOLaVwi0Rfk9tpXURTChscQNjzmuMfVjDsL24gZNFTXYY6JJDLKvwVUh60fo0v4rOtrXVgL6tDVVFjSyTR4P3ErzpiNXmPC4bb0uDYsYrxfY4dpdUwZGrhjQYUQQpy4QZWg7eUt3ZLzEZYd1ZjGJ/Z6spfV7mTbnhpKK1oIM2gZkzOE3Az/bvnmF1SweWcVdocbRYERGbHMPX04Br332+Nu1UVh4wcer+1pWE1mtPcErdMYmTDkJ3xb8/du7WZ9IiNiLvQrZiGEEKFrUCVo2wHv+6ZtJY0+E7TN7mLlx4XUN1m72krKmpk+PokzJvnedrR7fx3rvztaD1pVoehgI1qthgvO9H66mMPdgc3V7PFam6PS55gAubE/IiosheKmz7C5mkkwjSE39keEab1vzxJCCDEwDKoE7WsxV28LvXbuq+2WnI/YvLOKiXkJRPg48nOblz3UhQcaOOe0NIxhnt9mgyaCcF08Hc6eq8ejw/y79ZwYPpbE8LF+vVYIIcTAEbizGYPAOGooaD0sBtMqndd8OLIf+YfcbpXyat+Lrtotns/NdrtVLDYvtaIBRdEwJv5yT1e8tAshhDhVDKoZtDYyjJiLRtL8n32o9s6zrBWDlugLctFG+j5dy2T0/laYjL4LZiQPjWCfrYnwxG3oIypx2aPoqJ5IGMlEm32PmxMzlw6ni90Nq3G7G9BqEpk0dCGp5tN89hNCCDG4DaoEDZ3bqgyZMdgPNAFgyIzt9fY2wLjcoewq7nmrOTbKSGqi7xXZE8aE0Rj3D7SGozPt8ITtDNf+Eo3G9/aukpY6/r63BZvraGGNzQ3V3Dm+hWHhvhe1CSGEGLwG1S3uIzQGHcaRQzCOHOJXcgZITjBz3swMwvSgC69CG9bEkFgTl87O6XUPdYXzg27JGUDRuKjXrULt5ZjQN0u29DjRq9Vh473S7X7FLYQQYnAadDNoVVVh37eoe7cAoIyYArlT/SpLGD1sL8nTXsPq6lwNPtQ0CkP4TYDvAzyq2gs8trc5qmhzVBFp8Fwn2eK0c6C156wdYFdD76u4hRBCDF6DL0H/52XUPd8c/XrvZpRRM1EuvNFnvwZrCd9U/n+ouLvaai17WFf+JBcOf9pnX0Xx9pxZQa8J99pPp9GiUzQ4VXePa1K0QgghTm2D6ha3Wr6vW3Luat/zDWpFsc++xU3/7Zacj2iylVJrKfLZt8mR7bG9xZGMQev9ObJeo2Wql5O8ZiZm+RxTCCHE4Da4EvTBnd6vHfB+DcDi9H7IicXZ4LPv7uZkKi3p3apStjhi2dk8nlqr7y1aV2ZNJSeq+xawCfGpzM8Y57OfEEKIwW1w3Uf1UTkKo49rwBBTHhXtW3u0K2iIN/o+xztCZ6KodQqlHSOJ1DVhc4XT4oxDg0KEzuC7r97A0glzOdBaR42lldSIWFIiYnz2EUIIMfgNqgSt5E3Huv4DNoVNpNjQeYs4x17CNNs2TCOn++ybHX4W+61v0W7sfuhIjnUEEfohPvueNSyHN/ZvxuoyY3Ud3ZI1MT7V7wpRmZFDyIz0PY4QQohTx6BK0Gp4DO+kXkd1G0Dn/eatpomUD53I1eHR+FrHbdjzHXM2hFGUpVA11IneoZBZpiejsho1pxklItpr31lJOVRbW/iiYh+u7xd8jYoZxk9zp/XdDyeEEOKUMqgS9P7DTdTaW4jJXYsxdi8A1sYR1JaeS0lZEznp3itT2Q/uwGjXMKHQyITCY6+4oHwfjJjqta+iKFyZNYULUkdzuL2RuLAIksK9J3QhhBCiN4MqQVfVNxM/agU609EFX6b4QvTh1VTVZftM0JVuF97KUzQoCvF+jB9lMDHG4PtZtxBCCOGPwbWKO2Jnt+R8hM7UiBrhexX3lmEZHturw0wcjJZnw0IIIfrXoErQ5pgmH9c8110+wp2czYqMkVg0R48GrTBG8ELuBBLkTGwhhBD9bFDd4o41eq+hHGtK89n3nKQRPFa5n/z4YWS1NWPR6jhojmZUzDDSzN5vjQshhBCBMKhm0OmRM4nU9zz3OlKfRJp5hs++CaZIbhl3Likxw9gTHU95VBxnJGbzy1FnBSpcIYQQwqtBNYPWavTMTnuI72qXU9aWD0CaeToThy5Gq/Fd0xkgO2ood008H6vTgU6jQafxrxKWEEII0dcGVYIGCNfHMyPpZoqbawHIiR6KVjm+GwVGXe/JXAghhAikQZeg9zRW8Y+939BktwAQYzBx3YiZjIodFuTIhBBCCP8NqmfQrXYrz+9e15WcAZrsFp7fvY5WuzWIkQkhhBDHZ1Al6E21B7G5nT3abW4nm2tLgxCREEIIcWIGVYJuddh8XJMZtBBCiIFjUCXokdGJXq/lxcgzaCGEEAPHoErQo2KHMSE+tUf7hPhURsZ4T95CCCFEqBl0q7h/OepM1leVsLXuEABThqRz+rCsIEclhBBCHJ9Bl6C1ioZZSTnMSsoJdihCCCHECRtUt7iFEEKIwUIStBBCCBGCJEELIYQQIUgStBBCCBGCJEELIYQQISikV3GXl5dz7rnnEhsbG+xQQl5jY6O8T36Q98k/8j7571R7r8rLy4MdwilDUVVVDXYQvixYsIBVq1YFO4yQJ++Tf+R98o+8T/6T90oEitziFkIIIUKQJGghhBAiBIV8gl60aFGwQxgQ5H3yj7xP/pH3yX/yXolACfln0EIIIcSpKORn0EIIIcSpKGS3Wbndbh5++GGKioowGAw89thjZGRkBDuskHTZZZdhNpsBSE1N5fHHHw9yRKFl+/btPP300yxfvpzS0lLuvvtuFEUhNzeXhx56CI1GPqdC9/dp9+7d/PKXv2T48OEAXH311cybNy+4AQaZw+Hg3nvvpby8HLvdzq9//WtycnLk75MImJBN0J999hl2u52VK1eybds2nnjiCZ5//vlghxVybDYbqqqyfPnyYIcSkl566SVWr16NyWQC4PHHH+fWW29l+vTpPPjgg6xZs4a5c+cGOcrg++H7tGvXLq6//nqWLFkS5MhCx+rVq4mJieGpp56iqamJSy+9lLy8PPn7JAImZD/qbdmyhbPOOguAiRMnsnPnziBHFJoKCwuxWCwsWbKEa6+9lm3btgU7pJCSnp7On//8566vd+3axbRp0wCYNWsWGzZsCFZoIeWH79POnTv54osv+MlPfsK9995LW1tbEKMLDRdccAG33HILAKqqotVq5e+TCKiQTdBtbW1dt20BtFotTqcziBGFJqPRyA033MDLL7/M7373O+688055n47xox/9CJ3u6I0iVVVRFAWAiIgIWltbgxVaSPnh+zR+/Hh++9vf8vrrr5OWlsZf/vKXIEYXGiIiIjCbzbS1tXHzzTdz6623yt8nEVAhm6DNZjPt7e1dX7vd7m6/QESnzMxMLr74YhRFITMzk5iYGGpra4MdVsg69vlge3s7UVFRQYwmdM2dO5exY8d2/Xn37t1Bjig0VFZWcu2113LJJZcwf/58+fskAipkE/TkyZNZt24dANu2bWPEiBFBjig0vf322zzxxBMAVFdX09bWxtChQ4McVegaPXo0+fn5AKxbt46pU6cGOaLQdMMNN1BQUADAN998w5gxY4IcUfDV1dWxZMkSli5dyhVXXAHI3ycRWCG7D/rIKu69e/eiqirLli0jOzs72GGFHLvdzj333ENFRQWKonDnnXcyefLkYIcVUsrKyrj99tt58803OXDgAA888AAOh4OsrCwee+wxtFptsEMMCce+T7t27eLRRx9Fr9czZMgQHn300W6PnE5Fjz32GB9//DFZWVldbffddx+PPfaY/H0SARGyCVoIIYQ4lYXsLW4hhBDiVCYJWgghhAhBkqCFEEKIECQJWgghhAhBkqCFEEKIECQnfwhxkmw2G6tXr0ar1RIdHc2cOXOCHZIQYhCQBC3ESaqtreWtt97izTffDHYoQohBRBK0ECfphRdeoLi4mLy8PB566CGysrJ48cUX0ev1VFVVcdVVV7Fx40YKCwu59tprueaaa9i0aRPPPvssWq2WtLQ0HnnkEfR6fbB/FCFECJEELcRJ+tWvfsXevXu7qq8BVFVV8e6777Jr1y5uueUWPv30U6qrq/nNb37D1VdfzQMPPMAbb7xBfHw8zz33HO+88w5XXnllEH8KIUSokQQtRADk5uai1+uJjIwkPT0dg8FAdHQ0NpuNhoYGampquPXWWwGwWq2cfvrpwQ1YCBFyJEELcZI0Gg1ut7tb25EShJ7ExsYybNgw/vrXvxIZGcmaNWsIDw8PdJhCiAFGErQQJyk+Ph6Hw4HVavXr9RqNhvvuu49f/OIXqKpKREQEf/jDHwIcpRBioJFiGUIIIUQIkoNKhBBCiBAkCVoIIYQIQZKghRBCiBAkCVoIIYQIQZKghRBCiBAkCVoIIYQIQZKghRBCiBAkCVoIIYQIQf8/n0kmDegX1OwAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 609.84x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import seaborn as sns\n",
    "sc.pl.scatter(mdata, x=\"time\", y=\"Factor1\", color=\"species\", \n",
    "              palette=palette, size=200)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "After alignment:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 609.84x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sc.pl.scatter(mdata, x=\"time_warped\", y=\"Factor1\", color=\"species\", \n",
    "              palette=palette, size=200)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Alignment"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can also take a look at the learnt alignemnt."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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fZM3YISHRxPm1fl8LNHozITJRM3Zi1AD8Da2vPCYEhDEoSPsD3+UxKU4Xg02MSiTQ5PzDoPAM3ZKg//3vf/POO++wcuVK4uLiumNIITrMx9vA7OnJJMQEoiig1ykMTgwjbWqS21XCUUkDuXaUH1FKJQBeqpkxgZVcfu0v3I87JJKgK5LQBzed5ekCvAiY0h+/se6LWIwddTPJ9TMwmpvOIP3rIrhQ9wfiEie6jT3XDAmJ5veDL6bvj2euAUZvru43nGv6jXAbOy12MLMTRxPy45l2pE8ANw4azwUR7ouTzE+6kKkxKfjom65W9A8I47ahlxLnr31SoVMUbh96KRdGJmBQdCgoDA3py93DL8PPqL0SO9Dkzd3DL2NISDQKYNTpmRDZn1tTL3H7t5gQEMafUn9BP/+mEyNfg4npsUOYO6BtFdJEz1FUd8tR2ykvL4+77rqL999/nwkTJhAdHU1gYNNZxwUXXMBtt92mGZ+WlkZGRkZXTE2Is2a3O1AUBZ3O/e07P2c1m9EbDeh0ri9Pu6Ja7WDQtem2oTM5HA7sVjNGr/PjDMlit2HU6c/6dVJVFavDjknjjNsVh6piVx0Y2/F7tasOVFXF0I5Ym8OOoijtukXK6rCjV3TozvJ1OpO8N3efLrsPOjY2ltWrVwOwfXvvu8VDnF/0+vZfbDJ2YFGkYjz7N3AAnU6H7jxJzkC7EiyAoijtjtUpCjqlfb8fvaLDxVfZbrUnqZ/Wng8ToufIXepCCCGEB5IELYQQQnggSdBCCCGEB5IELYQQQnggSdBCCCGEB5JqVuKccqqsjroGK9Hhfvh4O981yxmHQ6WguBab3UFMlD9GQ9tXs6pWC+QfBr0RYpJQdG3/XNtQW05x0T68vUOIih3e5jiAWmsxVeZcAkx9CDS5vwe6M6iqSnZNKQ02KwMCI/AxtP01tjnsHKkqASApKOKsVhs32Cwcqy7Fx2AkMSD8rG+XEqI3kgQtzgk1dRbWfn2UUz/uU63XKVwwrA8TR7pPXIUltXzybTbVdU37VHuZ9Ey5MJ7BiWFuYx2Z21DXvQPmH/d2DghFd+UfUPoOdBu764e/c8TrKxx6O9RBwK4+TO6/iMAQ5zuFNY+p2thW9Donqjeg/rjvc4z/WCZE34ZR13W3ThXUVfL6oe841VANgJfewHUJI7m07yC3sfvLC/jn4a3U/FjQIdDozY3J40kN6es2dn1+Fh8d34PZ0VTgoo9PIDcPuZhoN1tnCtHbySVucU745NtjzckZwO5Q2bqnkMPHyzXjrDYHH60/2pycAcwWO59/l0OZm4IXankR6udv/JScAWrKcXz0EqrVrBl7LOtLsnz/25ScT4f6FfFd9lLNOIADZf/iePW3zckZIL/2e3YXr3Qb214OVeXVgxuakzOA2W5j1bHvOfrjWbEr1ZYGXj+0sTk5Q1NJw9cPbqTaTbWkI1XFpGfvbE7O0FSQ4tWDG3B0zR5KQpwzJEELj1de1UBBSZ3Tvn1HtEs3ZudW0tDYuvSgqsKBY61L/7V4zMFN4HBSPaqxFvXoD5qxOTVfO22v8s+ntOiwZuyxKuc1o3OqN2BXW5e/7AyHq05R0ljrtG/TqWOasdtLTmB18jpZHHZ2lBzXjN1U5PzYxQ01HHFTRlGI3k4StPB4DWbXtX0bNfo6GkuD8w8FTcEafYBFcV3u0NyoXR7QYndeAtCumrE7nJeT7Kg6q+vj1rm5WlCr0a91XIBam0asRp8Q5wNJ0MLjRYb64WVyvuAoPlq7qpRWv7tY4p1XPAJQNPoAIhTnlY0MVi8io1M1Y6N8hzltD/UegEnvpxnbXklBES73dk4J7qMZO1ijPyVEO9bVsQ2KjqRA7SpNQvR2kqCFxzMadFw8pvXCqiB/L8YMidKMDQ3yZmRK6zf62Ch/kvoFa8YqSaMhLqV1+4hLUMK0Fz+lJv0an4bWxx+iXoPRy3WtYoDh4XNbLQbTK0ZGRvyPZlxHBJp8mBnX+oNDnF8IF/UZoBmbHBzFqLDWVepGh8e5LYU4qc8AYv2CW7XPjB9KgEm75rYQvV2XVbPqKKmYIn4ur6iGvYdLqG+0EhMVwMjkiDbfanX4eDmHssux2R0MiAtmaFI4hjYUwFBtVtT9G1GP7QGDASXlQnTJ49o0ZkNtOYeOfEiJPQsvAkgKn05MQttiay2nyKr8lCrzSQKM0QwKuYIgr64v1bqvPJ/Np7JpsFkZEhLN5D4D8W7DrVYO1cGWUznsKs1FUWB0eDzjIxPQtaHiUqPNyoaioxysKMTHYGRiVCLDQrvntjJx9uS9uftIghZCCNFm8t7cfeQStxBCCOGBJEELIYQQHkgStBBCCOGBJEELIYQQHkgStBBCCOGBJEELIYQQHkiqWYlu1WC2cfBoKRXVZsJDfBicGOZyl7DOpBafRM3cBjYLSuII6Jfa5pKGhXV7KKjdiU4x0C9wEqHeiV08WyGE6MIEvWfPHpYuXcrKlSs5ceIE9957L4qikJSUxMMPP4zuLGrqit6hrLKBD/6bRf0ZxSt27C9izoxkAv29umxcx87/on67uvlndfd6lCETYfpCzSStqirbil4lp/qb5rbMio8ZGTGfwaFXd9l8hRACuugS94oVK1i8eDFmc9Nm908++SR33HEH7733Hqqqsm7duq4YVni4b3bktkjO0FTneeOu/C4bU62pQN34r9btBzfD8f2asUX1e1sk59P2lLxLvVW7EpYQQnRUlyTo+Ph4XnrppeafDxw4wLhxTVscTp48mc2bN3fFsMKDWW0OThRUO+07drKyy8ZVc/Y6LxkJqMe0S0bm1+5wHoeD/NrvOzw3IYTQ0iWXuKdPn05eXl7zz6qqNl9K9PPzo6bGeTm99PR00tPTAaioqOiKqYkeoiig0yk4HK13ltXr2/ZdcLvoNb7f1mv/+esU1/06Xdv2ABdCiPbqli+Cz/y+ua6ujsBA52X+5syZQ0ZGBhkZGYSEhHTH1EQ3Meh1DIwPdtqX0j+0y8ZVBowCg8l5X/KFmrH9Ai5y2q5XTMT6X9DhuQkhhJZuSdBDhgxh27ZtAGzYsIGxY8d2x7DCw1w6Lp7wkJZlFPuE+3HR6K6rXKR4+6G74nctk7SioEy8FqWvdhnFMJ8khofPReGnM3y9YmR89J/w0gd01ZSFEALoptusFi1axIMPPsiyZctITExk+vTp3TGs8DB+PkbmXzWEnPwqKqoaCQ/xJT46oM23O7WXkjQGXWwy6tFdYLOiJA5HCYpoU2xqWBr9AidRULuz6cw5YJwkZyFEt5Byk0IIIdqso+/N9TYLm4qOsb+iAFWF1NBoJkUNwM/YdbdanqvkZmQhhBDdorihhkd3fcqanB/IrDxFVtUpMnJ28+iuTzlV7/wuj7batm0bd955Z4u2pUuXntMnepKghRBCdIu3Dm+lwlzfqr3S0sA/Dm/pgRl5NtnqUwghRJcrqKviaHWJy/6cmjJyayuI8+/8O3juvPNOnn/+eQAuuugiNm3axL333ovBYKCgoACLxcLMmTP5+uuvKSws5NVXXyUmJoaHHnqIoqIiiouLmTJlCnfeeSf33nsvJpOJ/Px8iouLeeqpp0hNTe30OYOcQQshhOgGJY3O979o+ZjaDo2xdetW5s+f3/zff/7zH83Hx8TE8Oabb5KYmEheXh4rVqxg2rRprF+/nsLCQkaOHMkbb7zBmjVrWLVqVXNc3759eeONN5g/f37z3h1dQc6ghRBCdLkQL982PMbH7WO0jB8/vvlMGZq+g/65M9dFDxkyBIDAwEASExOb/99isRAcHMy+ffvYunUr/v7+WCyW5rjBgwcD0KdPH3bt2tWhOWuRM2ghhBBdLt4/lDg/15ev+/oG0T8gvNPHLS0tpaSk6dJ6fn4+VVVVzX1at3hmZGQQEBDAc889x8KFC2lsbGxO7l19a+hpLs+g58+f73ISb7/9dpdNSAhXsjauwS9zKz7mBsrC+hI8eTaRMYPcxlkddr7IO8j24hNYHXaGhcZwZfxQAk3ebmOrK2s4vH4/AfkWHDqo7+/LsMtHYjK53+qzqL6KT07u50hVCQEmLy7uk8Tk6IFteq6HK0/xed5B8usqifQJYFrsYIaFtm1Dlx3Fx1lfcJhycx0JAWHMjBtKv4Cu261NiLaan3QhL+xfR73N2qLdR29kwSDtnf3aKyQkhICAAGbPns2AAQOIjY1tU9yECRO4++672b17NyaTiX79+lFcXNwlc3TF5X3Q2dnZALzyyitcdtlljBkzhr179/L111/zxBNPdPnE5D5ocaZDn7zOoKyWxSvq9QbMcxYR3ke7PvPLB75hX3lBi7YonwDuHzUDb73rRGtuNJP9xlZC6lvu510Y4WDUjZM1xyxpqOWJ3Z9Tb7O0aJ8RO4Tr+o/UjD1UUcT/O/A1jjP+aSrAwuSJjItM0Ixdl5/J6uyWl9yMOj1/GTGVeH9J0qLjOvreXNpYy/qCLPaXFwIqqSF9uSwmmXBv/86bZC/h8hJ3YmIiiYmJlJaWMnPmTKKiopg6dWqLIhhCdIe6mgoSjuxs1e5rt1G66UPN2Jya0lbJGeBUQw3bio9rxmZuz2qVnAGiS3TkHD6pGftV/qFWyRlgXUEWdVazZux/Tu5rkZwBVODjk/vQ2lfI6rDz6ckDTts/c9IuRE8I9/bn14ljeHTsL3l07FXMGTBGkrMLbfoO+oMPPiArK4tVq1ZhNEoVH9G9yguOYHI4nPb5lxdqxh6vKXfZd6JGu6aztcj1qtOqPO3Y47XOx7U67OTXVWrHuphXcUMNDXar0z6AssY6am3Ok//xWqlfLcS5xm2CXrp0KZmZmTzzzDPk5OQ4XRUnRFfyC43GeXqGRl/nldFOC/Pyc9kXqtEHoAt0vfWgV7B2rKtxFSDU202si34/gwkvjRKZgSZvDIrzf9LunqsQwvO4TdARERFcdtllTJs2jeuuuw5fX/dL5YXoTKERcZyIjGvV7gBMo6dqxg4NjSbSp3VxCy+9gYv6aFez6n/BQMz61h8NKr3tJI3Qjr2k76AWVbBOGxYa4/Zy3qV9k522/yI6Cb2LBAzgazAxPqq/074pLo4phPBcbhP0smXL+Oijj1i9ejWHDh3ivvvu6455CdFCzHV3cazvAOw/3llQ6eXN8YuuIX7wBM04naLj9qGXkhIc9dOxfIO5LfUSt/dlhoQF4/hlAmX+9ua2olAHobOHYtC3/m76TIOCIlmYPIHQH8fQKQoXRPRjYbL2fAEu7TuIa/qNwPfHEpleegPTYgdzVb9hbmN/M2Ask/sMbD6TDjR6M3fAWMZExLuNFUJ4FrfVrK6//nreffdd5s+fz8qVK/n1r3/N6tWru3xisopbOFNXU05DXSUhEfHoNS73OlNlacDqsLdrQUpJcRlGo5HgEO1L6j/nUB2UNtbhZzCddbUeq8NOubmOIJOP5mpzZxpsFqqtjYR5+WHQaX+YEOJsdPS9WW2sR92/EfX4PlBVlIRhKEMnofjIQrGfc3sGbbfbMZvNKIqC3W5Hp5O9TUTP8QsIJbxP4lknZ4Agk0+7V4tGRIaddXKGpjP4SJ+AdpXSM+r0RPkEnnVyBvAxmIjyCZTkLDyKWnEKx8qHUTeshpOHIDcTdeMHOFb+FbWiqEPH3rZtG8nJyXzyySct2q+66iruvffeDh27p7jNtjfccANpaWkcOXKE2bNnM2/evO6YlxBCiF7G8cU/wNmdFbUVOD57o8PHT0xMbJGgs7KyaGho6PBxe4rb05ArrriCiRMncvLkSWJjYwkJ6fxKI0IIIXo3tawA8o+4fkBRNmpJLkpE6wWhbZWSkkJOTg41NTUEBASwdu1arrrqKgoLC1m7di1vvfUWJpOJhIQEHn30UT7++GOys7P585//jNls5oorrmD9+vW8++67fPTRR+h0OoYNG8bixYspLCzkwQcfxGw24+XlxZIlS4iOjm73XNvC7Rn0rl27WLBgAbfccgs33XQThw4d6tIJCSGE6IUq27BNZlse48a0adP44osvUFWVvXv3MmrUKCorK3nppZd46623eP/99wkICNCsQpWRkcGDDz5Ieno6iYmJ2Gw2nn766ea1WDfddFO33HLsNkE/9thjPPfcc3z33Xc89dRTPPLII10+KSGEEL1MW+o8d0It6KuuuopPP/2UHTt2MHbsWAAcDgcDBw7E379pDcoFF1zAkSMtz+bPXC/95JNP8t577/E///M/FBQUoKoqhw8f5m9/+xvz58/nlVdeoays6zf/cXuJOyAggIEDmzb4HzRoEN7e7gsMCCGEEGdSovpBRByU5Dp/QFgMSrT2vvptERcXR319PStXruSuu+4iNzcXRVE4duwY9fX1+Pr6sn37dvr374+Xl1dzpasDB37aDnf16tU88sgjeHl5cdNNN/HDDz+QmJjIwoULGT16NMeOHWPHjh2uptBp3CbosLAwHnjgAcaPH8+BAwdwOBzNlwbmzJnT5RMUnslqs1NRbcbPx4ifz9mtMlYbapsWigRFoHSw/uvZqCw5js1mJjQqSe5GEKIH6KbdiGPNc2Cub9nh5YNu2o2dNs7MmTP597//Tf/+/cnNzSUkJIRf/vKXLFiwAJ1OR3x8fPP3zu+//z5z584lNTUVP7+mHfeSk5OZN28efn5+REVFMWLECBYtWsRf//pXzGYzjY2NPPDAA502X1fc3gf98ssvu+z705/+1OaBrFYr9957L/n5+eh0OpYsWcKAAa53Y5L7oD3X9weK2La3ELPFjqLAoIRQpk7oh8mofUuParehfpOOun8D2G1gMKGMugxl0q+6tL5qRfExNuf+P6r9m4pm+DQEMzrwRuITL+qyMYXorTp8H3RVKeoPX6Hm7AN+vA969OUoQRGdN8lewu0ZdE5ODs8991yHB/r222+x2WysWrWKTZs28cILL/DSSy91+Liie2XmlLPh+58qmqkqZOWUo1Pgiou1L0+pm/+Numf9Tw02C+qOz8DHH2XsjC6Zr91m4ZuCJ2n0/6lIe4NPJVsaXyaoLJ6gsPavGBVCnD0lKBzlkt/AJb/p6al4PLfX+axWK5mZmZjNZiwWCxZL6xJ6bdG/f3/sdjsOh4Pa2loMhrPfaEL0vD2ZzldZZuVU0NBocxmnOhyoe79x3rd7vdP2znAieyONPlWt2h16G0dOfNpl4wohREe16Qz6j3/8Y/PPiqKwbt26sx7I19eX/Px8rrjiCioqKnj99ddbPSY9Pb35++2KioqzHkN0vdp65x/QHKpKfaMVH28Xf1I2c+vvnZoPWtk5k3OivrEUXGzi1eDounGFEKKj3Cbojz/+uFMG+uc//8mkSZO4++67KSws5IYbbuDjjz/Gy+und885c+Y0LzxLS0vrlHFF54qO9KfKSa1jX28DwQGut7NUTD4QFgNl+U4Oql0ZqiMiw4ZC7RqnfeHeg7psXCGE6Ci3CXrdunW89957WK1WVFWlsrKyXUk7MDAQo7FptW9QUBA2mw273e4mSniacUOjyc6twmJt+bubMKIver32Nya6SWk41r7c9MX1aXoDuonXdsFMm0TGpNJnRypFgQdatPvXRTAwtWu+9xZCiM7gNkG/8MILPProo6xatYoLL7yQTZs2tWugG2+8kfvvv5958+ZhtVq58847pbb0OSg8xIe5M1PYsb+IotI6/H2NjEqJYkB8sNtYZcBIdLPuwbHzv1BxCsJj0I2d0Sn3PmqZPHoxB/ank2vbhl1nJVodzrDkuRi78RYvIUSTRouN/UdKOZ5fhapCQkwQQ5PC8fGSdUk/5/YViYyMZNSoUaxatYq0tDQ+/PDDdg3k5+fHiy++2K5Y4VnCgn2YMal/u2KVuGT0ccmdPCNter2B4SOuZzjXd+u4QoiWKqobWfPFYWrqflrLkltUww+HTjF7WjIhQR3bCCs3N5dnnnmGyspKrFYrKSkp/PnPf27eQexc43YVt9FoZMeOHdhsNjZu3CiLt4QQQrTLF5uOt0jOp9XWW/nsu5wOHbuxsZE//vGP/O53v2PlypWsWrWKESNGcPfdd3fouD3J7Rn0I488QnZ2Nrfccgsvvvgit9xyS3fMSwghRC9SVtlAfnGty/6i0jpKyuuJCG3fV5/ffPMNF1xwASNGjGhuu+6663j//fdZtGgRAIWFhdTX1/P0008zYMAA3nzzTT755BMMBgNjx47lnnvuYefOnTz99NMYDAZ8fHx48cUXKSkp4b777sNgMOBwOHjuuec4efIkq1at4vnnnwfgoosuYtOmTdx7770YDAYKCgqwWCzMnDmTr7/+msLCQl599VXi4+Pb/JzcnkG/8sor2O12+vfvz0svvcSVV155tq+bEEKI81xljblTHuNKbm6u0+QXGxvLjh07iIuL4+233+bWW2/l2WefJSsri88++4xVq1axatUqTpw4wddff81XX33FFVdcwTvvvMPcuXOprq5m8+bNDB8+nH/84x/ceuut1NTUaM4lJiaGN998k8TERPLy8lixYgXTpk1j/fqz2/PBbYK+9tpr2bJlC9dffz2LFi1q1z3QQgghzm/+vu737G/LY1yJiooiLy+vVfuJEycYO3Ys48ePB2DUqFHk5OSQnZ3NiBEjMBqNKIrC2LFjOXLkCDfffDPFxcXccMMNfP755xgMBmbNmkVgYCC/+93vePfdd9HrW29rfOau2UOGDAGa7l46XWwqMDDwrDf6cpugR48ezcKFC7n++us5fvy4lJsUQghx1qLC/IgIdX3nRFiwD9ER7V/Mddlll7F582b27t3b3PbBBx8QEhKCTqdrrla1a9cukpKSSExMZO/evdhsNlRVZceOHfTv35+1a9dy3XXXsXLlSpKSkli9ejXr1q1jzJgxvPXWW8yYMYO///3vLSph5efnU1X1046FnVVbwO130FdffTV6vZ6rrrqKJUuWMGiQbO4ghBDi7E2bmMCaLw5jtrTcR8HLqGfaxH4dOrafnx+vv/46TzzxBJWVldjtdpKTk1m2bBlPPPEEGzZsYN26dTgcDp588kni4uK44oormDt3Lg6HgzFjxnD55Zezd+9eFi9ejI+PDzqdjkcffRRVVVm0aBGvvfYaDoeD++67j+TkZAICApg9ezYDBgwgNja2Q/N3xm01q08++YSNGzdSWFhISkoKkyZN4uKLL+70ifycVLPqeqfK6jieX42XSc+ghBB8vdt2eclut5O/cTP2k6UQ6E3fyy7GK6Btn3zNlga+P/Af6hoLCfCJY+zQX2I0tG1cc0M12ce+osFaSVTIMGISLmhTnBCi83T0vbmq1swPh4rJyasCVBJighg9OIogjZ0IO+ree+9l5syZTJ48ucvG6Apuz6CvvPJKpk2bxtatW1m+fDmffvopGzdu7I65iS701ZYT7D1c0vzzhu/z+OUvEkmMC9aMM9fUUvrGV5is4UAEnIKKI1tgRh/6DBumGVtwKput+U9g9qsCXygDinZ/weSBDxIW3FcztjD3B76rWobN2AhGyDJ/RuT3yVwy8iH0BlMbn7UQoqcF+XtxyQVxXHKBVJJzx+130DfffDO/+tWv2LJlC3feeScbNmzojnmJLnT0ZEWL5Axgszv47LscrDbt7VcLMr5Ebw3/WasP6pfH3Y67M3t5U3I+Q2NAKVsPrtCMczgcbCt7rSk5n6E4IItDB+UqixBC21NPPXXOnT1DGxL0HXfcwdq1a/nLX/7C6NGjm7/8fvnll7t8cqJrZB13vtmM2WLnREG1ZqxPqfOzVcUeQln2MZdxDY111AZnO+2rCzysOWZp4UEafJzPOdeyQzNWCCHOVW4TdEpKitP27du3d/pkRDfRWHagvSIBUF2vTlTtDtd9DhVchKqK9qCq6vq4KBp9QghxDnOboF1xs7ZMeLCB8SFO201GHf36BmrGNoQ2Om1XdZWEJyW5jPP19cev0vkOOn5V2uUmI/qm4t3ofF59DaM1Y4UQ4lzV7gTdWfd5ie43KCGE5ITQFm06ReHy8f0wGVvfgH+mqOsuRdX//HKzGcfkPm7HHRa3EGNDy9XeXvVBjBl4k2acTqdnbMDv0NtarvYOrUkgdfBst+MKITyHo9FG3Y48ytP3UZ6+j7rteTgarD09LY8k9b3OQ4qicOUvEhk2KJzjBdV4GXWkJIYR5O/+NgffkBBMt04n98tvUQpqcPgbiLxsAv4REW5j+8cMITz4eXYe/IgGaxF+XrGMHXwtvr7ub9GKS5xAaPVAjmZ/TqO9ksjAofQbPRmdTvsDhRDCc9gqGihP34/jjC09LSerqNtZQOicYRg0NjJxZ9u2bdxxxx3NO3fV1dURGxvL0qVLMZlar51xdutVXl4ed911F6tXr27x2OXLlzN+/HiSk5NZu3Yts2d3z4lBuxO0XOI+98VHBxIfrX1J2xmD0UT/mVPbNWaAXzCXXHBju2L9AiMYMXJ+u2KFED2v6rMjLZLzaY5aC1WfHibsf0Y4iWq78ePHNxevALj77rtZv349M2bM6NBxf//73wNNCfyDDz7wnARtt9vJyMigoKCA8ePHk5SURGhoKM8880x3zE8IIUQvYCutx5rv+i4Ra2EN1uJajJGdU7vZYrFQXFxMUFAQDzzwAEVFRRQXFzNlyhTuvPNOAN577z3eeOMN7HY7jz/+OHq9nvLycm6++WbKysq45JJL+L//+7/ms+0vvviCo0eP8vLLL/OnP/2pU+apxe130A899BAFBQVs3ryZurq65rJd0dHRXT45IYQQvYOtssHtY+yVzhehttXWrVuZP38+M2fOJC0tjalTpxIXF8fIkSN54403WLNmDatWrWp+/OjRo3nrrbf43//9X5599lkA6uvrefbZZ1m1ahUbN24kMzOz+fE333wzAwcO7JbkDG1I0CdPnuT222/Hy8uLKVOmuC2zJYQQQvycvg1beeo6uN3n+PHjWblyJe+++y5Go5HY2FiCg4PZt28fd999N0888USLilJjx44FfqpwBU23FgcEBKDX6xk2bFhze09wm6Dtdjvl5eUA1NbWotO1e+G3EEKI85Qxyh9DpJ/LfkO4L6bogE4ZKyQkhGeffZbFixfzz3/+k4CAAJ577jkWLlxIY2Nj8xqq05Wvvv/+e5J+vE302LFj1NXVYbPZ2Lt3b3M7gE6nw+Hovr0X3H4HfccddzB37lxKSkqYM2cO999/f3fMSwghRC8TND2J8tX7UM0ttxRWvPQEznC9j0J7DBw4kPnz53Po0CGOHz/O7t27MZlM9OvXj+LiYgD27NnDggULUBSFJ554AlVVCQoK4s4776S8vJyZM2c2rwoHCAsLw2q18uyzz3LPPfd06nydcVvN6rTy8nJCQ0PdP7CTSDUrIYTwPB19b7ZVNVK/swBzTgWo4JUYgu/ovhiCvTtxlr2D2zPoVatWkZ6ejtn809L4Tz/9tEsnJbpeXXkZxR9vwKtMj6q3Yx3gS8Ivp/f0tIQQvZwhyJvAKYk9PY1zgtsE/fbbb7N8+XKCgoI6PNjf/vY31q9fj9VqZe7cud12L5loqaGykup/bMXH8ePmInbQH4LjRRkk/C6tZycnhBACaEOCTk5OJjo6Gr2+Yzs2bdu2jR9++IH333+fhoYG3nzzzQ4dT7Rf0Wcb8HG0/rrCuyKcipMnCInv1wOzEkIIcSa3CXr8+PFcfvnlxMXFoaoqiqLw9ttvn/VA3333HYMGDeL//u//qK2t5S9/+Uu7Jiw6zlhqc9Gjo2pvpiRoIYTwAG4TdHp6Oi+88AIBAR1b/l5RUUFBQQGvv/46eXl53HLLLXz++ectim6kp6eTnp7e/HjRNexGFYOL/QB0ga5vgxBCCNF93CboqKgohg0b1uH7n4ODg0lMTMRkMpGYmIiXlxfl5eWEhYU1P2bOnDnMmTMHaFopKLqG4YIEWF9Hq9vglRr6XtS+PbaFEKItLPY6jlWtp7DuB0Al2m8kiUFT8NJ3zj3QvYnbBG2xWLjmmmtISkpqPtt97rnnznqgMWPG8Pbbb/Pb3/6W4uJiGhoaCA4OPuvjiI6LGTOGnNzP8DliApp27lF1leivHIhBLwXOhBBdo8ZSyPrcR6i3lTW3narfT1bFp0yJe5hAU992H/tsq1kVFBSQmZnJlClT2j1mV3P7bvyHP/yhUwa69NJL2bFjB7NmzUJVVR566KEOLzwT7df/2iuw1NdTvHsPej9fokdM6ukpCSF6uW1Fr7ZIzqc12MrZWvgy0/o90aHjn001q61bt5KdnX1uJuivv/6aSy+91Ok+pOPGjWvXYLIwzLOYfH2JnTihp6chhDgPVJlzKWnIdNlf1niEisbjhHgndMp4WtWsbrvtNpYvX05jYyOjRo3isssu65QxO5vLBF1VVQXAI488wh//+Mfm9jM3LBFCCCHaotZ6qk2P6UiCPl3NqqysDJ1Ox69//evmalazZ8/GbDYzefJk7rzzTn7/+9+TnZ3tsckZNBK01Wplzpw5+Pj4sHHjRgAcDgc2m42777672yYohBDi3OdjcL9VtG8bHqPl9CXuiooKFi5c2KKa1datW/H3929RzcrTuUzQ11xzDRMmTOBvf/sbN998M9BUyePMVddCCCFEW4R6JxLslUCl+bjT/iBTHGE+nVMw43Q1qwULFjBv3jwCAgJ49NFHOXHiBKtXr0ZV1W6vTNUeLhO0yWQiNjaWJUuWdOd8hBBC9FIX9rmZ9blLsDrqWrQbdb5c2OeWTh3LXTWrQYMG8dprr5GamsqVV17ZqWN3ljZXs+puUs1KCCE8T0ffm2utxRyu+JSCuh9AVYn2H0Vy8Ez8TVGdOMveQW569RBWmx2bTcXH++x/JY21taCqeLdjtzezvQa9YsKg8zqrOFVVMdurMep90SvGsx5XCHF+8jdGMjryRkZzY09PxeNJgu5hZouNr7fnkpVTjt2hEhnqy+SxscRHB7qNrcjPZ/3XBzhhCwEg3lDBpZMHExYf5za2pP4Qu0reorzxGDrFQJz/eMZELWzTbj7HqzeyrzSdWuspjDofBgRdzoiIeegU+XMSQojO0rH9O0WH/eebbA4eK8PuaPqmobi8ng/XHaG8qkEzztrQyJovj3LCHgqKAorCSXsoa9bnYK6r04ytsRTxdd7jlDceA8Ch2jhR8x0b8591O9+Cuh/YUvhS8y0TVkcDmRUfs6v4rbY8XSGEEG0kCboHlZTXc6KwulW73a6yO7NEM/bwjt3UKK0LW9QpvmRt360Ze7TyC+xq6/vZSxoOUdZwVDM2q/w/QOtlC9lV67HYtT8YCCGEaDtJ0D2ossb1pi+VNS7KTZ3ur6rX6NOOrbUWueyr0ejT6rerFhps5ZqxQggh2k4SdA8KD/Fx2RcR4qsZGxHh+jvq8HDt75GDvRJc9oV4adeCdtVv1PniZ4zUjBVCCNF2kqB7UEigNymJrXfO8fYyMDJFO9kNGDuSCKpatYdRzaBxIzVjBwZPxUsf1Ko9zv9Cgry0F5gNDr3O6WKwlJCrznoluBBCCNckQfew6RclMGFEXwL8TJiMOpL6hTBnRjIBfq3Lo51JbzAw65qxDPerwEdtxFttZJhvObOuHoXBSWm1M/kYQrg8/lHiAyZg1PngawgjNexXTIi+3e18w32SuDT2IaJ8h2FQvAk0xTA28ncMDZ91Vs9bCCGENtmoRAghRJvJe3P3kTNoIYQQwgNJghZCCCE8kCRoIYQQwgNJghZCCCE8kCRoIYQQwgNJghZCCCE8kJQf6iSqqpJbVEN1rYWocF+3O4G1iLXbIGcfqrkeJX4wSkDrzUtcqa+rJ3v/cVCh/9AE/PzbPq4QQgjP1e0JuqysjLS0NN58800GDBjQ3cN3iZo6Cx+uO0JpxU8VqAb1C+GKyf3R67QvUqhFOTj+/RLUNe0Kpio6lHFXoLsoze24B7YfImBjCeGOpjHKNpWSPTGMYRNSO/BshBBCeIJuvcRttVp56KGH8Pb27s5hu9yXW463SM4Ah09UsPPAKc041eHA8fGrzcn5x0bUbZ+gZu/VjK0oqyRoQykmx0+/QpNDR+imckqKy87+SQghhPAo3Zqgn376aX7zm98QGdl7iirUN1g5nt+6ZCTAwWNuEmVeJtQ4rwClHtqsGXr8h2wMqtKqXa8q5P6Qoz2uEEIIj9dtCTojI4PQ0FAuvvhil49JT08nLS2NtLQ0KioqumtqHWKzO1z2Wax27WCrxWWXanFdihLAoXFs1eJ6TkIIIc4N3Zag//Wvf7F582bmz5/PoUOHWLRoESUlJS0eM2fOHDIyMsjIyCAkJKS7ptYhgf5ehAU7v2SfGBusHRw7CIzOK0ApicM1QyOS+7rsC03uoz2uEEIIj9dtCfrdd9/lnXfeYeXKlQwePJinn36aiIiI7hq+S106Lh6DvuVLGehv4sLh0Zpxipcvyi9+DfzsUnVMEkrqJM3Y+MQY8vq3/vXlxSv0HxTfpnkLIYTwXHKbVSeIjw5kwTWp7DtcQnWthT7hvqQmheNtcv/y6oZfghqZgHpgE5jroF8qSvI4FIPRbezYWRPJ2nOUmsxToIJ/ciSjR/SOlfFCCHG+65EEvXLlyp4YtksFB3hx8ZjYdsUqfRJQ+iS0KzZ5xEAYMbBdsUIIITyX7CQmhBBCeCBJ0EIIIYQHkgQthBBCeCBJ0EIIIYQHkgQthBBCeCBJ0EIIIYQH6nX3QVutdvYfLSPvVA0+XgaGJoXTJ9yvTbFFVTX8d/dRKqss+PkZmDK8P4kRbSv9WJyZSf3GAxgaFazBOsKnTyAgMqpNsXuzviW37BscSiMBhmTGpc7C19ffbZyqquTXfs/Jmi2Ag7iACcT6j0NRWu/RLYQQ4tzSqxK02WJn9eeZlJxRWWrfkRKmTUwgdWC4ZuyR4lI++uIYerse0FNdoZKRf5SLJ0VzYWKcZuzJbzZi2uHAm6aEbCiCurd3Y52VTGhCgmbs+m0rOBX8BYQ1/VzLUb448D1TU5/AzzdQM3bHqb9xrGpd888najaREDiZCdG3asYJIYTwfL3qEvfuzOIWyRlAVeGbHblYbdqFKz7bdjo5/0Sn6tj4fZ7bcU3f1wAtY1H9qP1sp2ZcZXUJJQHrW7U3BJ5i2750zdiyhiMtkvNpx6s3UFx/yO2chRBCeLZelaCP51c5bTdb7BSW1GnGWiqdXxbWNRgpq3UdW5Z9DFTnZ7qmOu3L1Jk5m3DobU77atXDmrGFdbs1+n7QjBVCCOH5elWCNhn17eoDUHXOSzSqqHgbXe+LbfT1BVyUd1S0z9pNRl+XfTqHSTPWoPNxPSeNPiGEEOeGXpWgUweGOW0PC/Z2u1AsrK/zhGgMc+Dn5TpZBvaJxuZV5rSvIcp1vWeAYYMuxdQQ4LQvKvAizdh+gRehU1p/cNChp1+gdiUsIYQQnq9XJehBCaGMTY3izEXMQQFe/PIX7is8zZs0DF1wy8vNqp+NeZcMdRsb8KtxqPqKFm0W31PEzZmpGWc0GBkS8AeMDT9dClccOsLKL+KCodqxPoYQJkbf3uJs2aB4Mz76VvyMvaOMpxBCnM8UVVXVnp6EM2lpaWRkZLQrtqbOQt6pGny9DcRHB57VbUcHCk6RfaqCviEBjEmIOatx87Zsw1pSgd+gBCJTUtocZ7FZ2H3oSyyWWpL6TSQqXHvV+JlsjkYK6/YAKn38RsjlbSFEl+rIe7M4O73qNqvTAvxMDE50frnbndS+UaT2bdv9yz8XO+HCdsWZDCbGDbuyXbEGnTdxAe0bVwghhOfqVZe4hRBCiN5CErQQQgjhgSRBCyGEEB5IErQQQgjhgSRBCyGEEB5IErQQQgjhgXrdbVb7y3bxffE7GJV8bKoX/qZxXN3/Dxh1rrfrPC3vyGr21/yHKp8G/BtNJJsuZmDqzW0a93DF52RVfEK9tYRQ74EMDZ9NtN+Ijj4dIYQQ56luO4O2Wq3cc889zJs3j1mzZrFuXetKTB11rCqT3SXP4qXLRac4MOkasNi+ZfWRJ93G5h1dw0b7B1T4NeDQQbWvhR2GdWTte9Ft7IGyD9lZ/Aa11iIc2CltzOLbvCc4Vb+/M56WEEKI81C3Jei1a9cSHBzMe++9x9///neWLFnS6WNsK1qDXmldHUpR91NYp1028mDVx+Bkw7FD6hbsducVpwDsDguZ5f9u1a7i4GDZR27nLIQQQjjTbQl6xowZ3H777QCoqoper11dqj0sjiKn7Yqiklt7VDO2yrveaXuDlx1L/SmXcfW2ciwO5+Uoq8wnNccUQgghXOm276D9/JqqSdXW1nLbbbdxxx13tHpMeno66enpAFRUVLTqd8egCwdaJ1NVhWi/BM1Yf7M3lYbGVu1eFh0mX9fFJ3wMIRh0PtgcDa36AkzRbucshBBCONOtq7gLCwtZsGAB11xzDVdddVWr/jlz5pCRkUFGRgYhISFnffwxEWk41NZPyUYScf4JmrGDfS932j7IPhK93nW5SYPOi6TgaU77UkKv1hxTCCGEcKXbEnRpaSkLFy7knnvuYdasWV0yxuDQ4SSF3ILZ0VQow64aQBnN7AGL3cYmpNzABbbL8GtsuqjgbdYxvHEMQ4Yvchs7PHwuQ8NmY9I31XYOMEYzIfp2YvzHdODZCCGEOJ91W7nJxx57jM8++4zExMTmthUrVuDt7e308R0taVZtqcJH74NR4+zXGYfDgdVcjtErGJ3u7L4BcKh2bI5GTHq/s4oTQohzhZSb7D7d9h304sWLWbzY/ZlsZwk0BbUrTqfT4eUT3r5YRS/JWQghRKeQncSEEEIIDyQJWgghhPBAkqCFEEIIDyQJWgghhPBAkqCFEEIID9QrE7S9uobGbbuxZGpv7+k0tsaMOacCW0XrncGEEEKI7tLryk3W/Gsdddl6mp5aLYbPDxM8ezSGmD6acapDpfrLYzTsK4If7wz3GhhK0JXJ6Eydv2+4EEIIoaVXnUE3btpJXbYXZ37usFkDqfxgl9vYuu15NOz9KTkDmI+WU/N1dhfMVAghhNDWqxJ0/Z5Cp+02ayCWrGOasQ17nVfCajhYgmpzdHhuQgghxNnoVQnaYXVS0Pl0X3Wtdmy9i5rPNgeqxd6RaQkhhBBnrVclaFOk86/UFawYBw/Qjo13vjWoIdwXna+xw3MTQgghzkavStB+08eh09W1bh+oovf314z1nxSP8vPFYDqFgEv6d+YUhRBCiDbpVau49aEhhP12HHVf7MBabEUxqfiOjMF7/CS3scZIf8IWjKR+ZwHWkjoMwd74ju6LMUo7sQshhBBdoVclaGhK0oG/mdauWEOID4GXa18KF0IIIbpDr7rELYQQQvQWkqCFEEIIDyQJWgghhPBAkqCFEEIIDyQJWgghhPBAHruKOz8/n7S0NCoqKggJCenp6Xg8eZ3aRl6ntpHXqW3Ox9cpPz+/p6dw3lBUVVXdP6znpKWlkZGR0dPT8HjyOrWNvE5tI69T28jrJLqSXOIWQgghPJAkaCGEEMIDeXyCnjNnTk9P4Zwgr1PbyOvUNvI6tY28TqIrefx30EIIIcT5yOPPoIUQQojzkcfeZuVwOPjrX/9KVlYWJpOJxx57jH79+vX0tDzSddddh/+P5TRjY2N58skne3hGnmXPnj0sXbqUlStXcuLECe69914URSEpKYmHH34YnU4+p0LL1+ngwYP84Q9/ICEhAYC5c+cyc+bMnp1gD7Nardx///3k5+djsVi45ZZbGDhwoPw9iS7jsQn6q6++wmKxkJ6ezu7du3nqqad47bXXenpaHsdsNqOqKitXruzpqXikFStWsHbtWnx8fAB48sknueOOO7jwwgt56KGHWLduHVOnTu3hWfa8n79OBw4c4Le//S0LFy7s4Zl5jrVr1xIcHMyzzz5LZWUl1157LSkpKfL3JLqMx37U27lzJxdffDEAI0eOZP/+/T08I8+UmZlJQ0MDCxcuZMGCBezevbunp+RR4uPjeemll5p/PnDgAOPGjQNg8uTJbN68uaem5lF+/jrt37+fb775huuvv57777+f2traHpydZ5gxYwa33347AKqqotfr5e9JdCmPTdC1tbXNl20B9Ho9NputB2fkmby9vbnpppt44403eOSRR/jzn/8sr9MZpk+fjsHw04UiVVVRFAUAPz8/ampqempqHuXnr9Pw4cP5y1/+wrvvvktcXByvvPJKD87OM/j5+eHv709tbS233XYbd9xxh/w9iS7lsQna39+furq65p8dDkeLNxDRpH///lx99dUoikL//v0JDg6mpKSkp6flsc78frCuro7AwMAenI3nmjp1KkOHDm3+/4MHD/bwjDxDYWEhCxYs4JprruGqq66SvyfRpTw2QY8ePZoNGzYAsHv3bgYNGtTDM/JMa9as4amnngLg1KlT1NbWEhER0cOz8lxDhgxh27ZtAGzYsIGxY8f28Iw800033cTevXsB2LJlC6mpqT08o55XWlrKwoULueeee5g1axYgf0+ia3nsfdCnV3EfPnwYVVV54oknGDBgQE9Py+NYLBbuu+8+CgoKUBSFP//5z4wePbqnp+VR8vLyuOuuu1i9ejU5OTk8+OCDWK1WEhMTeeyxx9Dr9T09RY9w5ut04MABlixZgtFoJDw8nCVLlrT4yul89Nhjj/HZZ5+RmJjY3PbAAw/w2GOPyd+T6BIem6CFEEKI85nHXuIWQgghzmeSoIUQQggPJAlaCCGE8ECSoIUQQggPJAlaCCGE8ECy84cQHWA2m1m7di16vZ6goCAuu+yynp6SEKKXkAQtRAeUlJTwwQcfsHr16p6eihCil5EELUQHvP766xw9epSUlBQefvhhEhMTWb58OUajkaKiIn7zm9+wdetWMjMzWbBgAfPmzWP79u08//zz6PV64uLiePTRRzEajT39VIQQHkYStBAdcPPNN3P48OHmymsARUVFfPTRRxw4cIDbb7+dL7/8klOnTvGnP/2JuXPn8uCDD/Lee+8RFhbGCy+8wIcffsivf/3rHnwWQghPJAlaiE6WlJSE0WgkICCA+Ph4TCYTQUFBmM1mysvLKS4u5o477gCgsbGRiRMn9uyEhRAeSRK0EB2g0+lwOBwt2k6XH3QmJCSEPn368OqrrxIQEMC6devw9fXt6mkKIc5BkqCF6ICwsDCsViuNjY1terxOp+OBBx7g97//Paqq4ufnxzPPPNPFsxRCnIukWIYQQgjhgWSjEiGEEMIDSYIWQgghPJAkaCGEEMIDSYIWQgghPJAkaCGEEMIDSYIWQgghPJAkaCGEEMIDSYIWQgghPND/B9Z8GBNrSBLPAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 609.84x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sc.pl.scatter(mdata, x=\"time\", y=\"time_warped\", color=\"species\", \n",
    "              palette=palette, size=200)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Further analyses"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Additionally we can take a look at the smoothness and sharedness of the factors, interpolate the factors or cluster the species based on the learnt group kernel of each latent factor.\n",
    "\n",
    "For that, we will use the [mofax](https://github.com/bioFAM/mofax) library that provides convenient loaders and plotting functions."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "MOFA+ model: mefisto evodevo\n",
       "Samples (cells): 83\n",
       "Features: 38480\n",
       "Groups: Human (23), Mouse (14), Opossum (15), Rabbit (15), Rat (16)\n",
       "Views: Brain (7696), Cerebellum (7696), Heart (7696), Liver (7696), Testis (7696)\n",
       "Factors: 5\n",
       "Expectations: Sigma, W, Z\n",
       "\n",
       "MEFISTO:\n",
       "Covariates available: time\n",
       "Interpolated factors for 14 new values"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import mofax\n",
    "model = mofax.mofa_model(\"models/mefisto_evodevo.hdf5\")\n",
    "model"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Interpolation\n",
    "\n",
    "Using the underlying Gaussian process for each factor we can interpolate to unseen time points for species that are missing data in these time points or intermediate time points."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 2160x288 with 5 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "mofax.plot_interpolated_factors(model, factors=range(model.nfactors),\n",
    "                                ncols=5, size=70);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Smoothness and sharedness of factors\n",
    "\n",
    "In addition to the factor values and the alignment the model also inferred an underlying Gaussian process that generated these values. By looking into it we can extract information on the smoothness of each factor, i.e. how smoothly it varies along developmental time, as well as the sharedness of each factor, i.e. how much the species (groups) show the same underlying developmental pattern and how the shape of their developmental trajectory related to a given developmental module (Factor) clusters between species.\n",
    "\n",
    "The scale parameters of the Gaussian process capture the smoothness of the model. We will visualize them with bar plots where more colour means more smoothness:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "mofax.plot_smoothness(model);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The group kernel of the Gaussian process can give us insights into the extent to which a temporal pattern is shared across species for the developmental module captured by each process:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 2160x288 with 10 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "mofax.plot_group_kernel(model, ncols=5);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can also plot _sharedness_ as a feature for each factor (fully coloured bar means fully shared):"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "mofax.plot_sharedness(model);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    " "
   ]
  }
 ],
 "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": "3.8.6"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}