ClusterBuster_testing.ipynb

{
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  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import seaborn as sns\n",
    "import streamlit as st\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns; sns.set()\n",
    "import numpy as np\n",
    "import plotly.graph_objects as go\n",
    "from sklearn.mixture import GaussianMixture\n",
    "import plotly.express as px\n",
    "\n",
    "from clusterbuster import parse_report, plot_clusters, gtype_gmm, calculate_maf, plot_hist_contour"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Some info on the values:\n",
    "\n",
    "R values are the intensities. R for a sample is the sum of normalized X and Y (R= X+ Y)\n",
    "Theta is the B allele frequency and is calculated by: (2/pi)*arctan(normalized Y/ normalized X)\n",
    "\n",
    "BAF = Y / (X + Y)\n",
    "LRR = log2( (X + Y)sampleOfInterest / (X+Y)baselineSample)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "# first, need to subset the huge report to just snps of interest\n",
    "# report = pd.read_csv('F4SEttehadieh_P1_Genotyping_Report.txt', engine='c', sep='\\t', dtype={'Chr':str, 'position':int})\n",
    "# split by chromosome\n",
    "# for chrom in report.Chr.unique():\n",
    "#     report[report.Chr==chrom].to_csv(f'data/chr{chrom}_report.csv', header=True, index=False)\n",
    "\n",
    "# report[report['GenTrain Score']<0.15]\n",
    "# snps_df = pd.read_csv('prototyping/snps_of_interest_first_data.txt', engine='c')\n",
    "# report[report.Name.isin(snps_df.Name)].to_csv('data/cb_test_snps.txt', sep='\\t', index=False)\n",
    "\n",
    "# check_header = pd.read_csv('../data/chr22_report.csv', nrows=0)\n",
    "# header_list = ['Index', 'Name', 'Address', 'Chr', 'Position', 'GenTrain Score','Frac A', 'Frac C', 'Frac G', 'Frac T']\n",
    "# all(elem in check_header.columns for elem in header_list)\n",
    "# check_header.columns\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "report_in = pd.read_csv('../data/chr22_report.csv', engine='c', dtype={'Chr':str, 'position':int})\n",
    "\n",
    "report = parse_report(report_in, flag_maf=0.01, flag_gentrain=0.5)\n",
    "# test_report.keys()\n",
    "cb_df = report['clusterbuster_df']\n",
    "snps_df = report['flagged_snps']\n",
    "flagged = snps_df[snps_df.maf_flag & snps_df.gentrain_flag]\n",
    "\n",
    "total_flagged = snps_df[snps_df.maf_flag | snps_df.gentrain_flag].reset_index()\n",
    "both_flagged = snps_df[snps_df.maf_flag & snps_df.gentrain_flag].reset_index()\n",
    "maf_flagged = snps_df.loc[snps_df.maf_flag].reset_index()\n",
    "gentrain_flagged = snps_df.loc[snps_df.gentrain_flag].reset_index()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "# selected from user input\n",
    "selected_snp = 'exm1601793'\n",
    "# selected_snp = 'JHU_22.27408320'\n",
    "\n",
    "geno_col = selected_snp + \".GType\"\n",
    "theta_col = selected_snp + \".Theta\"\n",
    "r_col = selected_snp + \".R\"\n",
    "\n",
    "gtypes = list(cb_df[geno_col].unique())\n",
    "\n",
    "snp_for_plot_df = cb_df[['IID', theta_col, r_col, geno_col]].copy()\n",
    "snp_for_plot_df.columns = snp_for_plot_df.columns.str.replace(f'{selected_snp}.', '', regex=False)\n",
    "\n",
    "df = snp_for_plot_df.copy()\n",
    "x_col, y_col = 'Theta', 'R'\n",
    "gtypes_list = list(df.GType.unique())\n",
    "\n",
    "df = snp_for_plot_df.copy()\n",
    "x_col, y_col, gtype_col = 'Theta', 'R', 'GType'\n",
    "gtypes_list = (df.GType.unique())\n",
    "\n",
    "clusters_fig = plot_clusters(df=df, x_col=x_col, y_col=y_col, gtype_col=gtype_col, snpid=selected_snp)\n",
    "\n",
    "\n",
    "# clusters_fig.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
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       "    <tr style=\"text-align: right;\">\n",
       "      <th>idx</th>\n",
       "      <th>Theta</th>\n",
       "      <th>R</th>\n",
       "      <th>GType</th>\n",
       "      <th>IID</th>\n",
       "      <th>gtype_out</th>\n",
       "      <th>original_gtype</th>\n",
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       "      <td>1</td>\n",
       "      <td>FS04821313_FO0000275_FUS_R495*_A01_17_A01</td>\n",
       "      <td>BB</td>\n",
       "      <td>BB</td>\n",
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       "      <th>1</th>\n",
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       "      <td>1</td>\n",
       "      <td>FS04821315_FO0000163_MAPT_R317W_G09_17_B12</td>\n",
       "      <td>BB</td>\n",
       "      <td>BB</td>\n",
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       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.959375</td>\n",
       "      <td>1.239037</td>\n",
       "      <td>1</td>\n",
       "      <td>FS04821316_FO0000176_ANG_K41I_A04_17_D01</td>\n",
       "      <td>BB</td>\n",
       "      <td>BB</td>\n",
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       "      <td>1</td>\n",
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       "      <td>1</td>\n",
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       "      <td>BB</td>\n",
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       "      <td>1</td>\n",
       "      <td>FS04821405_FO0000172_APP_A673T_D12_17_C09</td>\n",
       "      <td>BB</td>\n",
       "      <td>BB</td>\n",
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       "      <th>93</th>\n",
       "      <td>0.013725</td>\n",
       "      <td>1.494911</td>\n",
       "      <td>2</td>\n",
       "      <td>FS04821406_FO0000173_APP_A673T_F06_17_C10</td>\n",
       "      <td>AA</td>\n",
       "      <td>AA</td>\n",
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       "    <tr>\n",
       "      <th>94</th>\n",
       "      <td>0.964469</td>\n",
       "      <td>1.133834</td>\n",
       "      <td>1</td>\n",
       "      <td>FS04821407_FO0000174_APP_A673T_H08_17_C11</td>\n",
       "      <td>BB</td>\n",
       "      <td>BB</td>\n",
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       "      <td>0.826584</td>\n",
       "      <td>1</td>\n",
       "      <td>PositiveControl_1_NA_NA</td>\n",
       "      <td>BB</td>\n",
       "      <td>BB</td>\n",
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       "idx     Theta         R  GType                                         IID  \\\n",
       "0    0.978341  1.124041      1   FS04821313_FO0000275_FUS_R495*_A01_17_A01   \n",
       "1    0.950462  1.286430      1  FS04821314_FO0000152_MAPT_R317W_A08_17_B01   \n",
       "2    0.974167  1.143932      1  FS04821315_FO0000163_MAPT_R317W_G09_17_B12   \n",
       "3    0.959375  1.239037      1    FS04821316_FO0000176_ANG_K41I_A04_17_D01   \n",
       "4    0.954499  1.171495      1  FS04821317_FO0000188_SNCB_P123H_B08_17_E01   \n",
       "..        ...       ...    ...                                         ...   \n",
       "91   0.958348  1.160252      1   FS04821404_FO0000171_APP_A673T_D09_17_C08   \n",
       "92   0.952213  1.151133      1   FS04821405_FO0000172_APP_A673T_D12_17_C09   \n",
       "93   0.013725  1.494911      2   FS04821406_FO0000173_APP_A673T_F06_17_C10   \n",
       "94   0.964469  1.133834      1   FS04821407_FO0000174_APP_A673T_H08_17_C11   \n",
       "95   0.942691  0.826584      1                     PositiveControl_1_NA_NA   \n",
       "\n",
       "idx gtype_out original_gtype  \n",
       "0          BB             BB  \n",
       "1          BB             BB  \n",
       "2          BB             BB  \n",
       "3          BB             BB  \n",
       "4          BB             BB  \n",
       "..        ...            ...  \n",
       "91         BB             BB  \n",
       "92         BB             BB  \n",
       "93         AA             AA  \n",
       "94         BB             BB  \n",
       "95         BB             BB  \n",
       "\n",
       "[96 rows x 6 columns]"
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     "execution_count": 5,
     "metadata": {},
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   "source": [
    "# now train a gmm and plot reclustered variants\n",
    "# get genotypes and number for choosing number of components\n",
    "gtypes_for_gmm = list(cb_df[geno_col].unique())\n",
    "gtypes_for_gmm.remove('NC')\n",
    "n_components = len(gtypes_for_gmm)\n",
    "\n",
    "snp_for_gmm_df = cb_df[['IID', theta_col, r_col, geno_col]].copy()\n",
    "snp_for_gmm_df.columns = snp_for_gmm_df.columns.str.replace(f'{selected_snp}.','', regex=False)\n",
    "gmm_out = gtype_gmm(snp_theta_r_df=snp_for_gmm_df, n_components=n_components)\n",
    "\n",
    "gmm_plot_df = gmm_out['X']\n",
    "gmm_plot_df.loc[:,'GType'] = gmm_out['y_pred']\n",
    "gmm_plot_df.loc[:,'IID'] = gmm_out['IID']\n",
    "gmm = gmm_out['gmm']\n",
    "\n",
    "cluster_means = {gtype:gmm_plot_df.loc[gmm_plot_df.GType==gtype,'Theta'].mean() for gtype in gmm_plot_df.GType.unique()}\n",
    "\n",
    "gtype_order = ['AA','AB','BB']\n",
    "gtypes_for_gmm_ordered = [gtype for gtype in gtype_order if gtype in gtypes_for_gmm]\n",
    "ordered_cluster_means = dict(sorted(cluster_means.items(), key=lambda item: item[1]))\n",
    "gmm_gtype_map = {list(ordered_cluster_means.keys())[i]:gtype for i, gtype in enumerate(gtypes_for_gmm_ordered)}\n",
    "\n",
    "gmm_plot_df.loc[:,'gtype_out'] = gmm_plot_df.loc[:,'GType'].replace(gmm_gtype_map)\n",
    "gmm_plot_df.loc[:,'original_gtype'] = snp_for_gmm_df.loc[:,'GType']\n",
    "gmm_plot_df\n",
    "# recluster_fig = plot_hist_contour(gmm_plot_df, x_col='Theta', y_col='R', gtype_col='gtype_out')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "# fig = go.make_subplots(\n",
    "#     rows=1, cols=2,shared_xaxes=True, specs=[[{'type': 'scatterplot'}, {'type': 'polar'}],\n",
    "#                            [{'type': 'scene'}, {'type': 'ternary'}]])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {},
   "outputs": [],
   "source": [
    "d3 = px.colors.qualitative.D3\n",
    "\n",
    "cmap = {\n",
    "    'AA': d3[0],\n",
    "    'AB': d3[1],\n",
    "    'BA': d3[1],\n",
    "    'BB': d3[2],\n",
    "    'NC': d3[3]\n",
    "}\n",
    "\n",
    "# cluster_fig = go.Scatter(\n",
    "#         x=df[x_col], y=df[y_col], \n",
    "#         color=gtype_col, \n",
    "#         color_discrete_map=cmap, \n",
    "#         width=600, height=400,\n",
    "#         name='scatter')\n",
    "# cluster_fig.show()"
   ]
  },
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":{\"color\":\"#C8D4E3\"},\"line\":{\"color\":\"white\"}},\"type\":\"table\"}]},\"layout\":{\"annotationdefaults\":{\"arrowcolor\":\"#2a3f5f\",\"arrowhead\":0,\"arrowwidth\":1},\"autotypenumbers\":\"strict\",\"coloraxis\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"colorscale\":{\"diverging\":[[0,\"#8e0152\"],[0.1,\"#c51b7d\"],[0.2,\"#de77ae\"],[0.3,\"#f1b6da\"],[0.4,\"#fde0ef\"],[0.5,\"#f7f7f7\"],[0.6,\"#e6f5d0\"],[0.7,\"#b8e186\"],[0.8,\"#7fbc41\"],[0.9,\"#4d9221\"],[1,\"#276419\"]],\"sequential\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]],\"sequentialminus\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]]},\"colorway\":[\"#636efa\",\"#EF553B\",\"#00cc96\",\"#ab63fa\",\"#FFA15A\",\"#19d3f3\",\"#FF6692\",\"#B6E880\",\"#FF97FF\",\"#FECB52\"],\"font\":{\"color\":\"#2a3f5f\"},\"geo\":{\"bgcolor\":\"white\",\"lakecolor\":\"white\",\"landcolor\":\"#E5ECF6\",\"showlakes\":true,\"showland\":true,\"subunitcolor\":\"white\"},\"hoverlabel\":{\"align\":\"left\"},\"hovermode\":\"closest\",\"mapbox\":{\"style\":\"light\"},\"paper_bgcolor\":\"white\",\"plot_bgcolor\":\"#E5ECF6\",\"polar\":{\"angularaxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\"},\"bgcolor\":\"#E5ECF6\",\"radialaxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\"}},\"scene\":{\"xaxis\":{\"backgroundcolor\":\"#E5ECF6\",\"gridcolor\":\"white\",\"gridwidth\":2,\"linecolor\":\"white\",\"showbackground\":true,\"ticks\":\"\",\"zerolinecolor\":\"white\"},\"yaxis\":{\"backgroundcolor\":\"#E5ECF6\",\"gridcolor\":\"white\",\"gridwidth\":2,\"linecolor\":\"white\",\"showbackground\":true,\"ticks\":\"\",\"zerolinecolor\":\"white\"},\"zaxis\":{\"backgroundcolor\":\"#E5ECF6\",\"gridcolor\":\"white\",\"gridwidth\":2,\"linecolor\":\"white\",\"showbackground\":true,\"ticks\":\"\",\"zerolinecolor\":\"white\"}},\"shapedefaults\":{\"line\":{\"color\":\"#2a3f5f\"}},\"ternary\":{\"aaxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\"},\"baxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\"},\"bgcolor\":\"#E5ECF6\",\"caxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\"}},\"title\":{\"x\":0.05},\"xaxis\":{\"automargin\":true,\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\",\"title\":{\"standoff\":15},\"zerolinecolor\":\"white\",\"zerolinewidth\":2},\"yaxis\":{\"automargin\":true,\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\",\"title\":{\"standoff\":15},\"zerolinecolor\":\"white\",\"zerolinewidth\":2}}},\"xaxis\":{\"anchor\":\"y\",\"domain\":[0.0,0.7363],\"range\":[0,1],\"title\":{\"text\":\"Theta\"}},\"xaxis2\":{\"anchor\":\"y2\",\"domain\":[0.7413,1.0],\"matches\":\"x2\",\"showgrid\":true,\"showline\":false,\"showticklabels\":false,\"ticks\":\"\"},\"xaxis3\":{\"anchor\":\"y3\",\"domain\":[0.0,0.7363],\"matches\":\"x\",\"showgrid\":true,\"showticklabels\":false},\"xaxis4\":{\"anchor\":\"y4\",\"domain\":[0.7413,1.0],\"matches\":\"x2\",\"showgrid\":true,\"showline\":false,\"showticklabels\":false,\"ticks\":\"\"},\"yaxis\":{\"anchor\":\"x\",\"domain\":[0.0,0.7326],\"range\":[0,2],\"title\":{\"text\":\"R\"}},\"yaxis2\":{\"anchor\":\"x2\",\"domain\":[0.0,0.7326],\"matches\":\"y\",\"showgrid\":true,\"showticklabels\":false},\"yaxis3\":{\"anchor\":\"x3\",\"domain\":[0.7426,1.0],\"matches\":\"y3\",\"showgrid\":true,\"showline\":false,\"showticklabels\":false,\"ticks\":\"\"},\"yaxis4\":{\"anchor\":\"x4\",\"domain\":[0.7426,1.0],\"matches\":\"y3\",\"showgrid\":true,\"showline\":false,\"showticklabels\":false,\"ticks\":\"\"}},                        {\"responsive\": true}                    ).then(function(){\n",
       "                            \n",
       "var gd = document.getElementById('1fbbbca4-5b25-43ca-a0d0-2aeadafa549e');\n",
       "var x = new MutationObserver(function (mutations, observer) {{\n",
       "        var display = window.getComputedStyle(gd).display;\n",
       "        if (!display || display === 'none') {{\n",
       "            console.log([gd, 'removed!']);\n",
       "            Plotly.purge(gd);\n",
       "            observer.disconnect();\n",
       "        }}\n",
       "}});\n",
       "\n",
       "// Listen for the removal of the full notebook cells\n",
       "var notebookContainer = gd.closest('#notebook-container');\n",
       "if (notebookContainer) {{\n",
       "    x.observe(notebookContainer, {childList: true});\n",
       "}}\n",
       "\n",
       "// Listen for the clearing of the current output cell\n",
       "var outputEl = gd.closest('.output');\n",
       "if (outputEl) {{\n",
       "    x.observe(outputEl, {childList: true});\n",
       "}}\n",
       "\n",
       "                        })                };                });            </script>        </div>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "n_trace = len(gmm_plot_df['gtype_out'].unique())\n",
    "\n",
    "\n",
    "recluster_fig = px.density_contour(\n",
    "    gmm_plot_df,\n",
    "    x=x_col, y=y_col, \n",
    "    marginal_x=\"histogram\", \n",
    "    marginal_y=\"histogram\",\n",
    "    color=\"gtype_out\", \n",
    "    color_discrete_map=cmap,\n",
    "    range_x=[0,1],\n",
    "    range_y=[0,2]\n",
    "    )\n",
    "\n",
    "fig2 = px.scatter(gmm_plot_df, x=x_col, y=y_col, color='gtype_out', color_discrete_map=cmap, range_x=[0,1], range_y=[0,2])\n",
    "\n",
    "# fig2.update_xaxes(range=xlim, nticks=10)\n",
    "# fig2.update_yaxes(range=ylim, nticks=10)\n",
    "\n",
    "\n",
    "for i in range(n_trace):\n",
    "    recluster_fig.add_trace(fig2.data[i])\n",
    "recluster_fig.show()\n",
    "\n",
    "# for i in range(n_trace):\n",
    "#     fig2.add_trace(recluster_fig.data[i])\n",
    "# fig2.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [],
   "source": [
    "# from plotly.subplots import make_subplots\n",
    "# test_fig = make_subplots(rows=1, cols=2)\n",
    "\n",
    "# test_fig.add_trace(cluster_fig['data'], row=1, col=1)\n",
    "# test_fig.add_trace(fig2['data'], row=1, col=2)\n",
    "# test_fig.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Histogram({\n",
       "    'alignmentgroup': 'True',\n",
       "    'bingroup': 'x',\n",
       "    'hovertemplate': 'gtype_out=BB<br>Theta=%{x}<br>count=%{y}<extra></extra>',\n",
       "    'legendgroup': 'BB',\n",
       "    'marker': {'color': '#2CA02C'},\n",
       "    'name': 'BB',\n",
       "    'offsetgroup': 'BB',\n",
       "    'opacity': 0.5,\n",
       "    'showlegend': False,\n",
       "    'x': array([0.9783415, 0.9504623, 0.9741675, 0.9593747, 0.9544989, 0.9494527,\n",
       "                0.9554906, 0.9632757, 0.961739 , 0.97149  , 0.9681001, 0.9717402,\n",
       "                0.9579055, 0.9733081, 0.9618404, 0.9758378, 0.9630002, 0.9573405,\n",
       "                0.9550448, 0.9673235, 0.936164 , 0.9478692, 0.9509611, 0.9573662,\n",
       "                0.9576157, 0.9629935, 0.9517125, 0.9531431, 0.947571 , 0.9553232,\n",
       "                0.9494918, 0.9538915, 0.958737 , 0.9647852, 0.9591101, 0.9642828,\n",
       "                0.958279 , 0.9521781, 0.9593722, 0.9658979, 0.9572034, 0.9519868,\n",
       "                0.9630252, 0.9533402, 0.9655342, 0.9574209, 0.9643096, 0.9534758,\n",
       "                0.9594354, 0.9531994, 0.9329   , 0.9591395, 0.9555489, 0.9434448,\n",
       "                0.9563623, 0.9604501, 0.9473326, 0.9729456, 0.9757709, 0.9630159,\n",
       "                0.9571338, 0.9560378, 0.934392 , 0.9602152, 0.9701965, 0.9553831,\n",
       "                0.9556195, 0.9671876, 0.9583478, 0.9522132, 0.9644687, 0.9426908]),\n",
       "    'xaxis': 'x3',\n",
       "    'yaxis': 'y3'\n",
       "})"
      ]
     },
     "execution_count": 78,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "recluster_fig.data[1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[Histogram2dContour({\n",
       "     'contours': {'coloring': 'none'},\n",
       "     'hovertemplate': 'gtype_out=BB<br>Theta=%{x}<br>R=%{y}<br>count=%{z}<extra></extra>',\n",
       "     'legendgroup': 'BB',\n",
       "     'line': {'color': '#2CA02C'},\n",
       "     'name': 'BB',\n",
       "     'showlegend': True,\n",
       "     'x': array([0.9783415, 0.9504623, 0.9741675, 0.9593747, 0.9544989, 0.9494527,\n",
       "                 0.9554906, 0.9632757, 0.961739 , 0.97149  , 0.9681001, 0.9717402,\n",
       "                 0.9579055, 0.9733081, 0.9618404, 0.9758378, 0.9630002, 0.9573405,\n",
       "                 0.9550448, 0.9673235, 0.936164 , 0.9478692, 0.9509611, 0.9573662,\n",
       "                 0.9576157, 0.9629935, 0.9517125, 0.9531431, 0.947571 , 0.9553232,\n",
       "                 0.9494918, 0.9538915, 0.958737 , 0.9647852, 0.9591101, 0.9642828,\n",
       "                 0.958279 , 0.9521781, 0.9593722, 0.9658979, 0.9572034, 0.9519868,\n",
       "                 0.9630252, 0.9533402, 0.9655342, 0.9574209, 0.9643096, 0.9534758,\n",
       "                 0.9594354, 0.9531994, 0.9329   , 0.9591395, 0.9555489, 0.9434448,\n",
       "                 0.9563623, 0.9604501, 0.9473326, 0.9729456, 0.9757709, 0.9630159,\n",
       "                 0.9571338, 0.9560378, 0.934392 , 0.9602152, 0.9701965, 0.9553831,\n",
       "                 0.9556195, 0.9671876, 0.9583478, 0.9522132, 0.9644687, 0.9426908]),\n",
       "     'xaxis': 'x',\n",
       "     'xbingroup': 'x',\n",
       "     'y': array([1.124041 , 1.28643  , 1.143932 , 1.239037 , 1.171495 , 1.132143 ,\n",
       "                 1.104728 , 1.117225 , 1.161996 , 1.143396 , 1.193882 , 1.145939 ,\n",
       "                 1.214612 , 1.195241 , 1.174356 , 1.191462 , 1.180584 , 1.214954 ,\n",
       "                 1.168255 , 1.186066 , 1.20844  , 1.230156 , 1.087062 , 1.123863 ,\n",
       "                 1.155385 , 1.192624 , 1.082331 , 1.156006 , 1.124266 , 1.167745 ,\n",
       "                 1.162335 , 1.146031 , 1.197268 , 1.150787 , 1.106112 , 1.143792 ,\n",
       "                 1.178022 , 1.233601 , 1.1828   , 1.171732 , 1.179432 , 1.153898 ,\n",
       "                 1.110721 , 1.136749 , 1.172696 , 1.100838 , 1.145391 , 1.197685 ,\n",
       "                 1.151607 , 1.223667 , 1.110455 , 1.133145 , 1.23889  , 1.120863 ,\n",
       "                 1.157234 , 1.186532 , 1.256602 , 1.1367   , 1.182563 , 1.220313 ,\n",
       "                 1.195901 , 1.197863 , 1.166847 , 1.168691 , 1.144719 , 1.131924 ,\n",
       "                 1.163753 , 1.177838 , 1.160252 , 1.151133 , 1.133834 , 0.8265839]),\n",
       "     'yaxis': 'y',\n",
       "     'ybingroup': 'y'\n",
       " }),\n",
       " Histogram({\n",
       "     'alignmentgroup': 'True',\n",
       "     'bingroup': 'x',\n",
       "     'hovertemplate': 'gtype_out=BB<br>Theta=%{x}<br>count=%{y}<extra></extra>',\n",
       "     'legendgroup': 'BB',\n",
       "     'marker': {'color': '#2CA02C'},\n",
       "     'name': 'BB',\n",
       "     'offsetgroup': 'BB',\n",
       "     'opacity': 0.5,\n",
       "     'showlegend': False,\n",
       "     'x': array([0.9783415, 0.9504623, 0.9741675, 0.9593747, 0.9544989, 0.9494527,\n",
       "                 0.9554906, 0.9632757, 0.961739 , 0.97149  , 0.9681001, 0.9717402,\n",
       "                 0.9579055, 0.9733081, 0.9618404, 0.9758378, 0.9630002, 0.9573405,\n",
       "                 0.9550448, 0.9673235, 0.936164 , 0.9478692, 0.9509611, 0.9573662,\n",
       "                 0.9576157, 0.9629935, 0.9517125, 0.9531431, 0.947571 , 0.9553232,\n",
       "                 0.9494918, 0.9538915, 0.958737 , 0.9647852, 0.9591101, 0.9642828,\n",
       "                 0.958279 , 0.9521781, 0.9593722, 0.9658979, 0.9572034, 0.9519868,\n",
       "                 0.9630252, 0.9533402, 0.9655342, 0.9574209, 0.9643096, 0.9534758,\n",
       "                 0.9594354, 0.9531994, 0.9329   , 0.9591395, 0.9555489, 0.9434448,\n",
       "                 0.9563623, 0.9604501, 0.9473326, 0.9729456, 0.9757709, 0.9630159,\n",
       "                 0.9571338, 0.9560378, 0.934392 , 0.9602152, 0.9701965, 0.9553831,\n",
       "                 0.9556195, 0.9671876, 0.9583478, 0.9522132, 0.9644687, 0.9426908]),\n",
       "     'xaxis': 'x3',\n",
       "     'yaxis': 'y3'\n",
       " }),\n",
       " Histogram({\n",
       "     'alignmentgroup': 'True',\n",
       "     'bingroup': 'y',\n",
       "     'hovertemplate': 'gtype_out=BB<br>R=%{y}<br>count=%{x}<extra></extra>',\n",
       "     'legendgroup': 'BB',\n",
       "     'marker': {'color': '#2CA02C'},\n",
       "     'name': 'BB',\n",
       "     'offsetgroup': 'BB',\n",
       "     'opacity': 0.5,\n",
       "     'showlegend': False,\n",
       "     'xaxis': 'x2',\n",
       "     'y': array([1.124041 , 1.28643  , 1.143932 , 1.239037 , 1.171495 , 1.132143 ,\n",
       "                 1.104728 , 1.117225 , 1.161996 , 1.143396 , 1.193882 , 1.145939 ,\n",
       "                 1.214612 , 1.195241 , 1.174356 , 1.191462 , 1.180584 , 1.214954 ,\n",
       "                 1.168255 , 1.186066 , 1.20844  , 1.230156 , 1.087062 , 1.123863 ,\n",
       "                 1.155385 , 1.192624 , 1.082331 , 1.156006 , 1.124266 , 1.167745 ,\n",
       "                 1.162335 , 1.146031 , 1.197268 , 1.150787 , 1.106112 , 1.143792 ,\n",
       "                 1.178022 , 1.233601 , 1.1828   , 1.171732 , 1.179432 , 1.153898 ,\n",
       "                 1.110721 , 1.136749 , 1.172696 , 1.100838 , 1.145391 , 1.197685 ,\n",
       "                 1.151607 , 1.223667 , 1.110455 , 1.133145 , 1.23889  , 1.120863 ,\n",
       "                 1.157234 , 1.186532 , 1.256602 , 1.1367   , 1.182563 , 1.220313 ,\n",
       "                 1.195901 , 1.197863 , 1.166847 , 1.168691 , 1.144719 , 1.131924 ,\n",
       "                 1.163753 , 1.177838 , 1.160252 , 1.151133 , 1.133834 , 0.8265839]),\n",
       "     'yaxis': 'y2'\n",
       " }),\n",
       " Histogram2dContour({\n",
       "     'contours': {'coloring': 'none'},\n",
       "     'hovertemplate': 'gtype_out=AA<br>Theta=%{x}<br>R=%{y}<br>count=%{z}<extra></extra>',\n",
       "     'legendgroup': 'AA',\n",
       "     'line': {'color': '#1F77B4'},\n",
       "     'name': 'AA',\n",
       "     'showlegend': True,\n",
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       "                 0.01508966, 0.02031893, 0.01372548]),\n",
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       "     'xbingroup': 'x',\n",
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       "                 1.475467, 1.515514, 1.362646, 1.396757, 1.523173, 1.59149 , 1.614841,\n",
       "                 1.494911]),\n",
       "     'yaxis': 'y',\n",
       "     'ybingroup': 'y'\n",
       " }),\n",
       " Histogram({\n",
       "     'alignmentgroup': 'True',\n",
       "     'bingroup': 'x',\n",
       "     'hovertemplate': 'gtype_out=AA<br>Theta=%{x}<br>count=%{y}<extra></extra>',\n",
       "     'legendgroup': 'AA',\n",
       "     'marker': {'color': '#1F77B4'},\n",
       "     'name': 'AA',\n",
       "     'offsetgroup': 'AA',\n",
       "     'opacity': 0.5,\n",
       "     'showlegend': False,\n",
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       "                 0.02604505, 0.02846322, 0.05940904, 0.07457311, 0.1443147 , 0.01120784,\n",
       "                 0.01508966, 0.02031893, 0.01372548]),\n",
       "     'xaxis': 'x3',\n",
       "     'yaxis': 'y3'\n",
       " }),\n",
       " Histogram({\n",
       "     'alignmentgroup': 'True',\n",
       "     'bingroup': 'y',\n",
       "     'hovertemplate': 'gtype_out=AA<br>R=%{y}<br>count=%{x}<extra></extra>',\n",
       "     'legendgroup': 'AA',\n",
       "     'marker': {'color': '#1F77B4'},\n",
       "     'name': 'AA',\n",
       "     'offsetgroup': 'AA',\n",
       "     'opacity': 0.5,\n",
       "     'showlegend': False,\n",
       "     'xaxis': 'x2',\n",
       "     'y': array([1.453825, 1.507179, 1.54051 , 1.554099, 1.536457, 1.468724, 1.524307,\n",
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       "                 1.494911]),\n",
       "     'yaxis': 'y2'\n",
       " }),\n",
       " Histogram2dContour({\n",
       "     'contours': {'coloring': 'none'},\n",
       "     'hovertemplate': 'gtype_out=AB<br>Theta=%{x}<br>R=%{y}<br>count=%{z}<extra></extra>',\n",
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       "     'line': {'color': '#FF7F0E'},\n",
       "     'name': 'AB',\n",
       "     'showlegend': True,\n",
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       "                 0.2626661, 0.2459879, 0.4191646]),\n",
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       "     'xbingroup': 'x',\n",
       "     'y': array([1.315046, 1.362909, 1.437546, 1.358505, 1.39309 , 1.32721 , 1.400039,\n",
       "                 1.293814, 1.33464 ]),\n",
       "     'yaxis': 'y',\n",
       "     'ybingroup': 'y'\n",
       " }),\n",
       " Histogram({\n",
       "     'alignmentgroup': 'True',\n",
       "     'bingroup': 'x',\n",
       "     'hovertemplate': 'gtype_out=AB<br>Theta=%{x}<br>count=%{y}<extra></extra>',\n",
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       "     'name': 'AB',\n",
       "     'offsetgroup': 'AB',\n",
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       "                 0.2626661, 0.2459879, 0.4191646]),\n",
       "     'xaxis': 'x3',\n",
       "     'yaxis': 'y3'\n",
       " }),\n",
       " Histogram({\n",
       "     'alignmentgroup': 'True',\n",
       "     'bingroup': 'y',\n",
       "     'hovertemplate': 'gtype_out=AB<br>R=%{y}<br>count=%{x}<extra></extra>',\n",
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       " }),\n",
       " Scatter({\n",
       "     'hovertemplate': 'gtype_out=AA<br>Theta=%{x}<br>R=%{y}<extra></extra>',\n",
       "     'legendgroup': 'AA',\n",
       "     'marker': {'color': '#1F77B4', 'symbol': 'circle'},\n",
       "     'mode': 'markers',\n",
       "     'name': 'AA',\n",
       "     'orientation': 'v',\n",
       "     'showlegend': True,\n",
       "     'x': array([0.03372161, 0.01768242, 0.01934427, 0.02041522, 0.00777587, 0.01317158,\n",
       "                 0.02604505, 0.02846322, 0.05940904, 0.07457311, 0.1443147 , 0.01120784,\n",
       "                 0.01508966, 0.02031893, 0.01372548]),\n",
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       "     'y': array([1.453825, 1.507179, 1.54051 , 1.554099, 1.536457, 1.468724, 1.524307,\n",
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       " }),\n",
       " Scatter({\n",
       "     'hovertemplate': 'gtype_out=AB<br>Theta=%{x}<br>R=%{y}<extra></extra>',\n",
       "     'legendgroup': 'AB',\n",
       "     'marker': {'color': '#FF7F0E', 'symbol': 'circle'},\n",
       "     'mode': 'markers',\n",
       "     'name': 'AB',\n",
       "     'orientation': 'v',\n",
       "     'showlegend': True,\n",
       "     'x': array([0.3452697, 0.3765664, 0.385852 , 0.3814036, 0.4036807, 0.4202441,\n",
       "                 0.2626661, 0.2459879, 0.4191646]),\n",
       "     'xaxis': 'x',\n",
       "     'y': array([1.315046, 1.362909, 1.437546, 1.358505, 1.39309 , 1.32721 , 1.400039,\n",
       "                 1.293814, 1.33464 ]),\n",
       "     'yaxis': 'y'\n",
       " })]"
      ]
     },
     "execution_count": 64,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "figure2_traces"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {},
   "outputs": [
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{\"template\":{\"data\":{\"bar\":[{\"error_x\":{\"color\":\"#2a3f5f\"},\"error_y\":{\"color\":\"#2a3f5f\"},\"marker\":{\"line\":{\"color\":\"#E5ECF6\",\"width\":0.5},\"pattern\":{\"fillmode\":\"overlay\",\"size\":10,\"solidity\":0.2}},\"type\":\"bar\"}],\"barpolar\":[{\"marker\":{\"line\":{\"color\":\"#E5ECF6\",\"width\":0.5},\"pattern\":{\"fillmode\":\"overlay\",\"size\":10,\"solidity\":0.2}},\"type\":\"barpolar\"}],\"carpet\":[{\"aaxis\":{\"endlinecolor\":\"#2a3f5f\",\"gridcolor\":\"white\",\"linecolor\":\"white\",\"minorgridcolor\":\"white\",\"startlinecolor\":\"#2a3f5f\"},\"baxis\":{\"endlinecolor\":\"#2a3f5f\",\"gridcolor\":\"white\",\"linecolor\":\"white\",\"minorgridcolor\":\"white\",\"startlinecolor\":\"#2a3f5f\"},\"type\":\"carpet\"}],\"choropleth\":[{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"type\":\"choropleth\"}],\"contour\":[{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"colorscale\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]],\"type\":\"contour\"}],\"contourcarpet\":[{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"type\":\"contourcarpet\"}],\"heatmap\":[{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"colorscale\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]],\"type\":\"heatmap\"}],\"heatmapgl\":[{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"colorscale\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]],\"type\":\"heatmapgl\"}],\"histogram\":[{\"marker\":{\"pattern\":{\"fillmode\":\"overlay\",\"size\":10,\"solidity\":0.2}},\"type\":\"histogram\"}],\"histogram2d\":[{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"colorscale\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]],\"type\":\"histogram2d\"}],\"histogram2dcontour\":[{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"colorscale\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]],\"type\":\"histogram2dcontour\"}],\"mesh3d\":[{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"type\":\"mesh3d\"}],\"parcoords\":[{\"line\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"type\":\"parcoords\"}],\"pie\":[{\"automargin\":true,\"type\":\"pie\"}],\"scatter\":[{\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"type\":\"scatter\"}],\"scatter3d\":[{\"line\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"type\":\"scatter3d\"}],\"scattercarpet\":[{\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"type\":\"scattercarpet\"}],\"scattergeo\":[{\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"type\":\"scattergeo\"}],\"scattergl\":[{\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"type\":\"scattergl\"}],\"scattermapbox\":[{\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"type\":\"scattermapbox\"}],\"scatterpolar\":[{\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"type\":\"scatterpolar\"}],\"scatterpolargl\":[{\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"type\":\"scatterpolargl\"}],\"scatterternary\":[{\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"type\":\"scatterternary\"}],\"surface\":[{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"colorscale\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]],\"type\":\"surface\"}],\"table\":[{\"cells\":{\"fill\":{\"color\":\"#EBF0F8\"},\"line\":{\"color\":\"white\"}},\"header\":{\"fill\":{\"color\":\"#C8D4E3\"},\"line\":{\"color\":\"white\"}},\"type\":\"table\"}]},\"layout\":{\"annotationdefaults\":{\"arrowcolor\":\"#2a3f5f\",\"arrowhead\":0,\"arrowwidth\":1},\"autotypenumbers\":\"strict\",\"coloraxis\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"colorscale\":{\"diverging\":[[0,\"#8e0152\"],[0.1,\"#c51b7d\"],[0.2,\"#de77ae\"],[0.3,\"#f1b6da\"],[0.4,\"#fde0ef\"],[0.5,\"#f7f7f7\"],[0.6,\"#e6f5d0\"],[0.7,\"#b8e186\"],[0.8,\"#7fbc41\"],[0.9,\"#4d9221\"],[1,\"#276419\"]],\"sequential\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]],\"sequentialminus\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]]},\"colorway\":[\"#636efa\",\"#EF553B\",\"#00cc96\",\"#ab63fa\",\"#FFA15A\",\"#19d3f3\",\"#FF6692\",\"#B6E880\",\"#FF97FF\",\"#FECB52\"],\"font\":{\"color\":\"#2a3f5f\"},\"geo\":{\"bgcolor\":\"white\",\"lakecolor\":\"white\",\"landcolor\":\"#E5ECF6\",\"showlakes\":true,\"showland\":true,\"subunitcolor\":\"white\"},\"hoverlabel\":{\"align\":\"left\"},\"hovermode\":\"closest\",\"mapbox\":{\"style\":\"light\"},\"paper_bgcolor\":\"white\",\"plot_bgcolor\":\"#E5ECF6\",\"polar\":{\"angularaxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\"},\"bgcolor\":\"#E5ECF6\",\"radialaxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\"}},\"scene\":{\"xaxis\":{\"backgroundcolor\":\"#E5ECF6\",\"gridcolor\":\"white\",\"gridwidth\":2,\"linecolor\":\"white\",\"showbackground\":true,\"ticks\":\"\",\"zerolinecolor\":\"white\"},\"yaxis\":{\"backgroundcolor\":\"#E5ECF6\",\"gridcolor\":\"white\",\"gridwidth\":2,\"linecolor\":\"white\",\"showbackground\":true,\"ticks\":\"\",\"zerolinecolor\":\"white\"},\"zaxis\":{\"backgroundcolor\":\"#E5ECF6\",\"gridcolor\":\"white\",\"gridwidth\":2,\"linecolor\":\"white\",\"showbackground\":true,\"ticks\":\"\",\"zerolinecolor\":\"white\"}},\"shapedefaults\":{\"line\":{\"color\":\"#2a3f5f\"}},\"ternary\":{\"aaxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\"},\"baxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\"},\"bgcolor\":\"#E5ECF6\",\"caxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\"}},\"title\":{\"x\":0.05},\"xaxis\":{\"automargin\":true,\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\",\"title\":{\"standoff\":15},\"zerolinecolor\":\"white\",\"zerolinewidth\":2},\"yaxis\":{\"automargin\":true,\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\",\"title\":{\"standoff\":15},\"zerolinecolor\":\"white\",\"zerolinewidth\":2}}},\"xaxis\":{\"anchor\":\"y\",\"domain\":[0.0,0.45]},\"xaxis2\":{\"anchor\":\"y2\",\"domain\":[0.55,1.0]},\"yaxis\":{\"anchor\":\"x\",\"domain\":[0.0,1.0]},\"yaxis2\":{\"anchor\":\"x2\",\"domain\":[0.0,1.0]}},                        {\"responsive\": true}                    ).then(function(){\n",
       "                            \n",
       "var gd = document.getElementById('f60c58b3-4b5b-4d64-aa2b-0bd105712596');\n",
       "var x = new MutationObserver(function (mutations, observer) {{\n",
       "        var display = window.getComputedStyle(gd).display;\n",
       "        if (!display || display === 'none') {{\n",
       "            console.log([gd, 'removed!']);\n",
       "            Plotly.purge(gd);\n",
       "            observer.disconnect();\n",
       "        }}\n",
       "}});\n",
       "\n",
       "// Listen for the removal of the full notebook cells\n",
       "var notebookContainer = gd.closest('#notebook-container');\n",
       "if (notebookContainer) {{\n",
       "    x.observe(notebookContainer, {childList: true});\n",
       "}}\n",
       "\n",
       "// Listen for the clearing of the current output cell\n",
       "var outputEl = gd.closest('.output');\n",
       "if (outputEl) {{\n",
       "    x.observe(outputEl, {childList: true});\n",
       "}}\n",
       "\n",
       "                        })                };                });            </script>        </div>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import plotly.subplots as sp\n",
    "figure1_traces = []\n",
    "figure2_traces = []\n",
    "for trace in range(len(cluster_fig[\"data\"])):\n",
    "    figure1_traces.append(cluster_fig[\"data\"][trace])\n",
    "# for trace in range(len(fig2[\"data\"])):\n",
    "#     figure2_traces.append(fig2[\"data\"][trace])\n",
    "for trace in range(len(recluster_fig[\"data\"])):\n",
    "    figure2_traces.append(recluster_fig[\"data\"][trace])\n",
    "\n",
    "#Create a 1x2 subplot\n",
    "out_fig = sp.make_subplots(rows=1, cols=2)\n",
    "# Get the Express fig broken down as traces and add the traces to the proper plot within in the subplot\n",
    "for traces in figure1_traces:\n",
    "    out_fig.append_trace(traces, row=1, col=1)\n",
    "for traces in figure2_traces:\n",
    "    out_fig.append_trace(traces, row=1, col=2)\n",
    "\n",
    "\n",
    "# fig2 = px.scatter(gmm_plot_df, x=x_col, y=y_col, color='gtype_out', color_discrete_map=cmap)\n",
    "\n",
    "# fig2.update_xaxes(range=xlim, nticks=10)\n",
    "# fig2.update_yaxes(range=ylim, nticks=10)\n",
    "\n",
    "# out_fig.append_trace(recluster_fig, 1,2)\n",
    "# n_trace = len(gmm_plot_df['gtype_out'].unique())\n",
    "# for i in range(n_trace):\n",
    "#     out_fig.append_trace(recluster_fig.data[i], 1,2)\n",
    "# out_fig.append_trace()\n",
    "out_fig.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [],
   "source": [
    "# for trace in range(len(this_figure.data)):\n",
    "#     print(this_figure[0])\n",
    "for gtype in gmm_plot_df['gtype_out'].unique():\n",
    "    x = gmm_plot_df.loc[gmm_plot_df['gtype_out']==gtype, x_col]\n",
    "    y = gmm_plot_df.loc[gmm_plot_df['gtype_out']==gtype, y_col]\n",
    "    out_fig.append_trace(go.Histogram2dContour(\n",
    "        x = x,\n",
    "        y = y,\n",
    "        xaxis = 'x',\n",
    "        yaxis = 'y',\n",
    "    ), 1,2)\n",
    "\n",
    "    # out_fig.append_trace(go.Histogram(\n",
    "    #     y = y,\n",
    "    #     xaxis = 'x2',\n",
    "    #     ),\n",
    "    #     1,2)\n",
    "    # out_fig.append_trace(go.Histogram(\n",
    "    #     x = x,\n",
    "    #     yaxis = 'y2',\n",
    "    #     ),\n",
    "    #     1,2)\n",
    "\n",
    "\n",
    "    # out_fig.update_layout(\n",
    "    #     autosize = False,\n",
    "    #     xaxis = dict(\n",
    "    #         zeroline = False,\n",
    "    #         domain = [0,0.85],\n",
    "    #         showgrid = False\n",
    "    #     ),\n",
    "    #     yaxis = dict(\n",
    "    #         zeroline = False,\n",
    "    #         domain = [0,0.85],\n",
    "    #         showgrid = False\n",
    "    #     ),\n",
    "    #     xaxis2 = dict(\n",
    "    #         zeroline = False,\n",
    "    #         domain = [0.85,1],\n",
    "    #         showgrid = False\n",
    "    #     ),\n",
    "    #     yaxis2 = dict(\n",
    "    #         zeroline = False,\n",
    "    #         domain = [0.85,1],\n",
    "    #         showgrid = False\n",
    "    #     ),\n",
    "    #     height = 600,\n",
    "    #     width = 600,\n",
    "    #     bargap = 0,\n",
    "    #     hovermode = 'closest',\n",
    "    #     showlegend = False,\n",
    "    # )\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Scatter({\n",
       "    'hovertemplate': 'GType=BB<br>Theta=%{x}<br>R=%{y}<extra></extra>',\n",
       "    'legendgroup': 'BB',\n",
       "    'marker': {'color': '#2CA02C', 'symbol': 'circle'},\n",
       "    'mode': 'markers',\n",
       "    'name': 'BB',\n",
       "    'orientation': 'v',\n",
       "    'showlegend': True,\n",
       "    'x': array([0.9783415, 0.9504623, 0.9741675, 0.9593747, 0.9544989, 0.9494527,\n",
       "                0.9554906, 0.9632757, 0.961739 , 0.97149  , 0.9681001, 0.9717402,\n",
       "                0.9579055, 0.9733081, 0.9618404, 0.9758378, 0.9630002, 0.9573405,\n",
       "                0.9550448, 0.9673235, 0.936164 , 0.9478692, 0.9509611, 0.9573662,\n",
       "                0.9576157, 0.9629935, 0.9517125, 0.9531431, 0.947571 , 0.9553232,\n",
       "                0.9494918, 0.9538915, 0.958737 , 0.9647852, 0.9591101, 0.9642828,\n",
       "                0.958279 , 0.9521781, 0.9593722, 0.9658979, 0.9572034, 0.9519868,\n",
       "                0.9630252, 0.9533402, 0.9655342, 0.9574209, 0.9643096, 0.9534758,\n",
       "                0.9594354, 0.9531994, 0.9329   , 0.9591395, 0.9555489, 0.9434448,\n",
       "                0.9563623, 0.9604501, 0.9473326, 0.9729456, 0.9757709, 0.9630159,\n",
       "                0.9571338, 0.9560378, 0.934392 , 0.9602152, 0.9701965, 0.9553831,\n",
       "                0.9556195, 0.9671876, 0.9583478, 0.9522132, 0.9644687, 0.9426908]),\n",
       "    'xaxis': 'x',\n",
       "    'y': array([1.124041 , 1.28643  , 1.143932 , 1.239037 , 1.171495 , 1.132143 ,\n",
       "                1.104728 , 1.117225 , 1.161996 , 1.143396 , 1.193882 , 1.145939 ,\n",
       "                1.214612 , 1.195241 , 1.174356 , 1.191462 , 1.180584 , 1.214954 ,\n",
       "                1.168255 , 1.186066 , 1.20844  , 1.230156 , 1.087062 , 1.123863 ,\n",
       "                1.155385 , 1.192624 , 1.082331 , 1.156006 , 1.124266 , 1.167745 ,\n",
       "                1.162335 , 1.146031 , 1.197268 , 1.150787 , 1.106112 , 1.143792 ,\n",
       "                1.178022 , 1.233601 , 1.1828   , 1.171732 , 1.179432 , 1.153898 ,\n",
       "                1.110721 , 1.136749 , 1.172696 , 1.100838 , 1.145391 , 1.197685 ,\n",
       "                1.151607 , 1.223667 , 1.110455 , 1.133145 , 1.23889  , 1.120863 ,\n",
       "                1.157234 , 1.186532 , 1.256602 , 1.1367   , 1.182563 , 1.220313 ,\n",
       "                1.195901 , 1.197863 , 1.166847 , 1.168691 , 1.144719 , 1.131924 ,\n",
       "                1.163753 , 1.177838 , 1.160252 , 1.151133 , 1.133834 , 0.8265839]),\n",
       "    'yaxis': 'y'\n",
       "})"
      ]
     },
     "execution_count": 56,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "out_fig.data[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "def plot_hist_contour(df, x_col, y_col, gtype_col, xlim, ylim):\n",
    "\n",
    "    d3 = px.colors.qualitative.D3\n",
    "\n",
    "    cmap = {\n",
    "        'AA': d3[0],\n",
    "        'AB': d3[1],\n",
    "        'BA': d3[1],\n",
    "        'BB': d3[2],\n",
    "        'NC': d3[3]\n",
    "    }\n",
    "\n",
    "    n_trace = len(df[gtype_col].unique())\n",
    "\n",
    "\n",
    "    fig = px.density_contour(\n",
    "        df,\n",
    "        x=x_col, y=y_col, \n",
    "        marginal_x=\"histogram\", \n",
    "        marginal_y=\"histogram\",\n",
    "        color=\"gtype_out\", \n",
    "        color_discrete_map=cmap,\n",
    "        width=750, height=500\n",
    "        )\n",
    "\n",
    "\n",
    "    fig2 = px.scatter(df, x=x_col, y=y_col, color=gtype_col, color_discrete_map=cmap)\n",
    "    fig2.update_xaxes(range=xlim, nticks=10)\n",
    "    fig2.update_yaxes(range=ylim, nticks=10)\n",
    "   \n",
    "\n",
    "    for i in range(n_trace):\n",
    "        fig.add_trace(fig2.data[i])\n",
    "\n",
    "    return fig\n",
    "\n",
    "\n",
    "def plot_clusters(df, x_col, y_col, gtype_col, snpid):\n",
    "\n",
    "    d3 = px.colors.qualitative.D3\n",
    "\n",
    "    cmap = {\n",
    "        'AA': d3[0],\n",
    "        'AB': d3[1],\n",
    "        'BA': d3[1],\n",
    "        'BB': d3[2],\n",
    "        'NC': d3[3]\n",
    "    }\n",
    "\n",
    "    # gtypes_list = (df[gtype_col].unique())\n",
    "    xmin, xmax = df[x_col].min(), df[x_col].max()\n",
    "    ymin, ymax = df[y_col].min(), df[y_col].max()\n",
    "\n",
    "    xlim = [xmin-.1, xmax+.1]\n",
    "    ylim = [ymin-.1, ymax+.1]\n",
    "\n",
    "    fig = px.scatter(\n",
    "        df, \n",
    "        x=x_col, y=y_col, \n",
    "        color=gtype_col, \n",
    "        color_discrete_map=cmap, \n",
    "        width=600, height=400)\n",
    "\n",
    "    fig.update_xaxes(range=xlim, nticks=10)\n",
    "    fig.update_yaxes(range=ylim, nticks=10)\n",
    "\n",
    "    out_dict = {\n",
    "        'fig': fig,\n",
    "        'xlim': xlim,\n",
    "        'ylim': ylim\n",
    "    }\n",
    "\n",
    "    return out_dict"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 88,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'2'"
      ]
     },
     "execution_count": 88,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sample_ids = ['a','b','c']\n",
    "gene_list = ['snca','snca','snca']\n",
    "cnv_list = ['1','2','3']\n",
    "sample_id = 'b'\n",
    "gene = 'snca'\n",
    "\n",
    "\n",
    "cnv_table = pd.DataFrame(\n",
    "    {\n",
    "        'sample_id':sample_ids,\n",
    "        'gene':gene_list,\n",
    "        'cnv_type':cnv_list\n",
    "        }\n",
    "    )\n",
    "\n",
    "cnv_table[(cnv_table.sample_id==sample_id) & (cnv_table.gene==gene)].reset_index().cnv_type[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 204,
   "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>idx</th>\n",
       "      <th>Theta</th>\n",
       "      <th>R</th>\n",
       "      <th>GType</th>\n",
       "      <th>IID</th>\n",
       "      <th>gtype_out</th>\n",
       "      <th>original_gtype</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.978341</td>\n",
       "      <td>1.124041</td>\n",
       "      <td>1</td>\n",
       "      <td>FS04821313_FO0000275_FUS_R495*_A01_17_A01</td>\n",
       "      <td>BB</td>\n",
       "      <td>BB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.950462</td>\n",
       "      <td>1.286430</td>\n",
       "      <td>1</td>\n",
       "      <td>FS04821314_FO0000152_MAPT_R317W_A08_17_B01</td>\n",
       "      <td>BB</td>\n",
       "      <td>BB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.974167</td>\n",
       "      <td>1.143932</td>\n",
       "      <td>1</td>\n",
       "      <td>FS04821315_FO0000163_MAPT_R317W_G09_17_B12</td>\n",
       "      <td>BB</td>\n",
       "      <td>BB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.959375</td>\n",
       "      <td>1.239037</td>\n",
       "      <td>1</td>\n",
       "      <td>FS04821316_FO0000176_ANG_K41I_A04_17_D01</td>\n",
       "      <td>BB</td>\n",
       "      <td>BB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0.954499</td>\n",
       "      <td>1.171495</td>\n",
       "      <td>1</td>\n",
       "      <td>FS04821317_FO0000188_SNCB_P123H_B08_17_E01</td>\n",
       "      <td>BB</td>\n",
       "      <td>BB</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>91</th>\n",
       "      <td>0.958348</td>\n",
       "      <td>1.160252</td>\n",
       "      <td>1</td>\n",
       "      <td>FS04821404_FO0000171_APP_A673T_D09_17_C08</td>\n",
       "      <td>BB</td>\n",
       "      <td>BB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>92</th>\n",
       "      <td>0.952213</td>\n",
       "      <td>1.151133</td>\n",
       "      <td>1</td>\n",
       "      <td>FS04821405_FO0000172_APP_A673T_D12_17_C09</td>\n",
       "      <td>BB</td>\n",
       "      <td>BB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>93</th>\n",
       "      <td>0.013725</td>\n",
       "      <td>1.494911</td>\n",
       "      <td>2</td>\n",
       "      <td>FS04821406_FO0000173_APP_A673T_F06_17_C10</td>\n",
       "      <td>AA</td>\n",
       "      <td>AA</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>94</th>\n",
       "      <td>0.964469</td>\n",
       "      <td>1.133834</td>\n",
       "      <td>1</td>\n",
       "      <td>FS04821407_FO0000174_APP_A673T_H08_17_C11</td>\n",
       "      <td>BB</td>\n",
       "      <td>BB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>95</th>\n",
       "      <td>0.942691</td>\n",
       "      <td>0.826584</td>\n",
       "      <td>1</td>\n",
       "      <td>PositiveControl_1_NA_NA</td>\n",
       "      <td>BB</td>\n",
       "      <td>BB</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>96 rows × 6 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "idx     Theta         R  GType                                         IID  \\\n",
       "0    0.978341  1.124041      1   FS04821313_FO0000275_FUS_R495*_A01_17_A01   \n",
       "1    0.950462  1.286430      1  FS04821314_FO0000152_MAPT_R317W_A08_17_B01   \n",
       "2    0.974167  1.143932      1  FS04821315_FO0000163_MAPT_R317W_G09_17_B12   \n",
       "3    0.959375  1.239037      1    FS04821316_FO0000176_ANG_K41I_A04_17_D01   \n",
       "4    0.954499  1.171495      1  FS04821317_FO0000188_SNCB_P123H_B08_17_E01   \n",
       "..        ...       ...    ...                                         ...   \n",
       "91   0.958348  1.160252      1   FS04821404_FO0000171_APP_A673T_D09_17_C08   \n",
       "92   0.952213  1.151133      1   FS04821405_FO0000172_APP_A673T_D12_17_C09   \n",
       "93   0.013725  1.494911      2   FS04821406_FO0000173_APP_A673T_F06_17_C10   \n",
       "94   0.964469  1.133834      1   FS04821407_FO0000174_APP_A673T_H08_17_C11   \n",
       "95   0.942691  0.826584      1                     PositiveControl_1_NA_NA   \n",
       "\n",
       "idx gtype_out original_gtype  \n",
       "0          BB             BB  \n",
       "1          BB             BB  \n",
       "2          BB             BB  \n",
       "3          BB             BB  \n",
       "4          BB             BB  \n",
       "..        ...            ...  \n",
       "91         BB             BB  \n",
       "92         BB             BB  \n",
       "93         AA             AA  \n",
       "94         BB             BB  \n",
       "95         BB             BB  \n",
       "\n",
       "[96 rows x 6 columns]"
      ]
     },
     "execution_count": 204,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# d3 = px.colors.qualitative.D3\n",
    "# cmap = {\n",
    "#     'AA': d3[0],\n",
    "#     'AB': d3[1],\n",
    "#     'BA': d3[1],\n",
    "#     'BB': d3[2],\n",
    "#     'NC': d3[3]\n",
    "# }\n",
    "\n",
    "# fig = px.density_contour(gmm_plot_df, x='Theta', y='R', marginal_x=\"histogram\", marginal_y=\"histogram\",color=\"gtype_out\", color_discrete_map=cmap, opacity=.8)\n",
    "# fig2 = px.scatter(gmm_plot_df, x='Theta', y='R', color=\"gtype_out\", color_discrete_map=cmap)\n",
    "\n",
    "# fig.add_trace(fig2.data[0]), fig.add_trace(fig2.data[1]), fig.add_trace(fig2.data[2])\n",
    "# fig.data[0].colorscale='blues'\n",
    "# fig.data[0].contours['coloring']='fill'\n",
    "# fig.data[3].contours['coloring']='fill'\n",
    "# fig.data[6].contours['coloring']='fill'\n",
    "\n",
    "# fig.data[0].showlegend=False\n",
    "# fig.data[3].showlegend=False\n",
    "# fig.data[6].showlegend=False\n",
    "gmm_plot_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 91,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "h5 = '/home/dan_vitale/projects/genotools_streamlit/GP2_round1.QC.metrics.h5'\n",
    "\n",
    "df_qc = pd.read_hdf(h5, key='QC')\n",
    "df_ancestry_counts = pd.read_hdf(h5, key='ancestry_counts')\n",
    "df_ancestry_labels = pd.read_hdf(h5, key='ancestry_labels')\n",
    "df_confusion_matrix = pd.read_hdf(h5, key='confusion_matrix')\n",
    "df_new_samples_umap = pd.read_hdf(h5, key='new_samples_umap')\n",
    "df_projected_pcs = pd.read_hdf(h5, key='projected_pcs')\n",
    "df_ref_pcs = pd.read_hdf(h5, key='ref_pcs')\n",
    "df_ref_umap = pd.read_hdf(h5, key='ref_umap')\n",
    "df_total_umap = pd.read_hdf(h5, key='total_umap')\n",
    "\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 92,
   "metadata": {},
   "outputs": [],
   "source": [
    "\n",
    "df_qc.to_csv('data/df_qc.csv')\n",
    "df_ancestry_counts.to_csv('data/df_ancestry_counts.csv', index=False)\n",
    "df_ancestry_labels.to_csv('data/df_ancestry_labels.csv', index=False)\n",
    "df_projected_pcs.to_csv('data/df_projected_pcs.csv',index=False)\n",
    "df_ref_pcs.to_csv('data/df_ref_pcs.csv', index=False)\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 94,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['a', 'b']"
      ]
     },
     "execution_count": 94,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#  gwas = pd.read_csv('https://raw.githubusercontent.com/plotly/dash-bio-docs-files/master/manhattan_data.csv')\n",
    "test = ['a']\n",
    "test.append('b')\n",
    "test"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 215,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0 BB\n",
      "1 AA\n",
      "2 AB\n"
     ]
    },
    {
     "data": {
      "application/vnd.plotly.v1+json": {
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        "plotlyServerURL": "https://plot.ly"
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          ],
          [
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          [
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          [
           0.625,
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          ],
          [
           0.75,
           "rgb(33,113,181)"
          ],
          [
           0.875,
           "rgb(8,81,156)"
          ],
          [
           1,
           "rgb(8,48,107)"
          ]
         ],
         "reversescale": true,
         "type": "histogram2dcontour",
         "x": [],
         "xaxis": "x",
         "y": [],
         "yaxis": "y"
        },
        {
         "marker": {
          "color": "#2CA02C",
          "size": 3
         },
         "mode": "markers",
         "type": "scatter",
         "x": [],
         "xaxis": "x",
         "y": [],
         "yaxis": "y"
        },
        {
         "marker": {
          "color": "#2CA02C"
         },
         "type": "histogram",
         "xaxis": "x2",
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        {
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      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import plotly.graph_objects as go\n",
    "\n",
    "import numpy as np\n",
    "\n",
    "t = np.linspace(-1, 1.2, 2000)\n",
    "# x = (t**3) + (0.3 * np.random.randn(2000))\n",
    "# y = (t**6) + (0.3 * np.random.randn(2000))\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "d3 = px.colors.qualitative.D3\n",
    "\n",
    "fig = go.Figure()\n",
    "\n",
    "cmap = {\n",
    "    'AA': d3[0],\n",
    "    'AB': d3[1],\n",
    "    'BA': d3[1],\n",
    "    'BB': d3[2],\n",
    "    'NC': d3[3]\n",
    "}\n",
    "\n",
    "\n",
    "\n",
    "for i, gtype in enumerate(gtypes):\n",
    "    print(i, gtype)\n",
    "\n",
    "    x = gmm_plot_df.loc[gmm_plot_df.GType==gtype,'Theta']\n",
    "    y = gmm_plot_df.loc[gmm_plot_df.GType==gtype,'R']\n",
    "\n",
    "    fig.add_trace(go.Histogram2dContour(\n",
    "        x = x,\n",
    "        y = y,\n",
    "        colorscale = 'Blues',\n",
    "        reversescale = True,\n",
    "        xaxis = f'x',\n",
    "        yaxis = f'y'\n",
    "    ))\n",
    "\n",
    "    fig.add_trace(go.Scatter(\n",
    "            x = x,\n",
    "            y = y,\n",
    "            xaxis = f'x',\n",
    "            yaxis = f'y',\n",
    "            mode = 'markers',\n",
    "            marker = dict(\n",
    "                color = cmap[gtype],\n",
    "                size = 3\n",
    "            )\n",
    "        ))\n",
    "\n",
    "    fig.add_trace(go.Histogram(\n",
    "            y = y,\n",
    "            xaxis = f'x2',\n",
    "            marker = dict(\n",
    "                color = cmap[gtype]\n",
    "            )\n",
    "        ))\n",
    "\n",
    "    fig.add_trace(go.Histogram(\n",
    "            x = x,\n",
    "            yaxis = f'y2',\n",
    "            marker = dict(\n",
    "                color = cmap[gtype]\n",
    "            )\n",
    "        ))\n",
    "\n",
    "    fig.update_layout(\n",
    "        autosize = False,\n",
    "        xaxis = dict(\n",
    "            zeroline = False,\n",
    "            domain = [0,0.85],\n",
    "            showgrid = False\n",
    "        ),\n",
    "        yaxis = dict(\n",
    "            zeroline = False,\n",
    "            domain = [0,0.85],\n",
    "            showgrid = False\n",
    "        ),\n",
    "        xaxis2 = dict(\n",
    "            zeroline = False,\n",
    "            domain = [0.85,1],\n",
    "            showgrid = False\n",
    "        ),\n",
    "        yaxis2 = dict(\n",
    "            zeroline = False,\n",
    "            domain = [0.85,1],\n",
    "            showgrid = False\n",
    "        ),\n",
    "        height = 600,\n",
    "        width = 600,\n",
    "        bargap = 0,\n",
    "        hovermode = 'closest',\n",
    "        showlegend = False\n",
    "    )\n",
    "\n",
    "fig.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 85,
   "metadata": {},
   "outputs": [],
   "source": [
    "def plot_gmm(df, x_col, y_col, gtype_col, gmm, snpid, n_std=3):\n",
    "\n",
    "    d3 = px.colors.qualitative.D3\n",
    "\n",
    "    cmap = {\n",
    "        'AA': d3[0],\n",
    "        'AB': d3[1],\n",
    "        'BA': d3[1],\n",
    "        'BB': d3[2],\n",
    "        'NC': d3[3]\n",
    "    }\n",
    "\n",
    "    gtypes_list = (df[gtype_col].unique())\n",
    "\n",
    "    fig = go.Figure()\n",
    "\n",
    "    for gtype in gtypes_list:\n",
    "        df_ = df.loc[df[gtype_col]==gtype]\n",
    "        x = df_.loc[:, x_col]\n",
    "        y = df_.loc[:, y_col]\n",
    "        color = cmap[gtype]\n",
    "        fig.add_trace(\n",
    "            go.Scatter(\n",
    "                x=x, y=y, \n",
    "                mode=\"markers\",\n",
    "                name=gtype,\n",
    "                marker = {'color':color},\n",
    "                hovertemplate=\"Genotype=%s<br>Theta=%%{x}<br>R=%%{y}<extra></extra>\"% gtype\n",
    "                ))\n",
    "\n",
    "        # fig.update_layout(title_text=f'{snpid} Cluster Plot')\n",
    "        # fig.update_layout(legend_title_text = 'Genotype')\n",
    "        # fig.update_xaxes(title_text=x_col)\n",
    "        # fig.update_yaxes(title_text=y_col, tickangle=-90)\n",
    "\n",
    "        # fig.add_trace(go.Histogram2dContour(\n",
    "        # x = x,\n",
    "        # y = y,\n",
    "        # showlegend=False\n",
    "        # ))\n",
    "\n",
    "        \n",
    "        # for n_std in range(1, n_std):\n",
    "        #     fig.add_shape(type='path',\n",
    "        #     path=confidence_ellipse(x, y, n_std=1.96*n_std, size=100), \n",
    "        #     line_color=color,\n",
    "        #     fillcolor=color,\n",
    "        #     opacity=0.2)\n",
    "    \n",
    "    return fig"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 86,
   "metadata": {},
   "outputs": [
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   "source": [
    "plot_gmm(df=gmm_plot_df, x_col='Theta', y_col='R', gtype_col='gtype_out', gmm=gmm, snpid=selected_snp, n_std=5)"
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                       {\"responsive\": true}                    ).then(function(){\n",
       "                            \n",
       "var gd = document.getElementById('098d34c8-8f7a-4517-b01e-dba667ffa58d');\n",
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       "            console.log([gd, 'removed!']);\n",
       "            Plotly.purge(gd);\n",
       "            observer.disconnect();\n",
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       "}});\n",
       "\n",
       "// Listen for the removal of the full notebook cells\n",
       "var notebookContainer = gd.closest('#notebook-container');\n",
       "if (notebookContainer) {{\n",
       "    x.observe(notebookContainer, {childList: true});\n",
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      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import plotly.figure_factory as ff\n",
    "import numpy as np\n",
    "\n",
    "# Add histogram data\n",
    "x1 = np.random.randn(200)-2\n",
    "x2 = np.random.randn(200)\n",
    "x3 = np.random.randn(200)+2\n",
    "x4 = np.random.randn(200)+4\n",
    "\n",
    "# Group data together\n",
    "hist_data = [x1, x2, x3, x4]\n",
    "\n",
    "group_labels = ['Group 1', 'Group 2', 'Group 3', 'Group 4']\n",
    "\n",
    "# Create distplot with custom bin_size\n",
    "fig = ff.create_distplot(hist_data, group_labels, bin_size=[.1, .25, .5, 1])\n",
    "fig.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th>idx</th>\n",
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       "      <th>1KG_22_36681998.GType</th>\n",
       "      <th>1KG_22_38494134.GType</th>\n",
       "      <th>...</th>\n",
       "      <th>Variant61228.R</th>\n",
       "      <th>Variant61231.R</th>\n",
       "      <th>Variant61234.R</th>\n",
       "      <th>Variant61237.R</th>\n",
       "      <th>Variant61242.R</th>\n",
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       "      <th>Variant61252.R</th>\n",
       "      <th>Variant61253.R</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>FS04821313_FO0000275_FUS_R495*_A01_17_A01</td>\n",
       "      <td>BB</td>\n",
       "      <td>BB</td>\n",
       "      <td>BB</td>\n",
       "      <td>BB</td>\n",
       "      <td>AA</td>\n",
       "      <td>AA</td>\n",
       "      <td>AA</td>\n",
       "      <td>AA</td>\n",
       "      <td>AA</td>\n",
       "      <td>...</td>\n",
       "      <td>0.430500</td>\n",
       "      <td>0.361874</td>\n",
       "      <td>0.540405</td>\n",
       "      <td>0.626420</td>\n",
       "      <td>0.957749</td>\n",
       "      <td>0.733668</td>\n",
       "      <td>0.795464</td>\n",
       "      <td>0.701761</td>\n",
       "      <td>0.470309</td>\n",
       "      <td>0.569939</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>FS04821314_FO0000152_MAPT_R317W_A08_17_B01</td>\n",
       "      <td>BB</td>\n",
       "      <td>BB</td>\n",
       "      <td>BB</td>\n",
       "      <td>BB</td>\n",
       "      <td>AA</td>\n",
       "      <td>AA</td>\n",
       "      <td>AA</td>\n",
       "      <td>AA</td>\n",
       "      <td>AA</td>\n",
       "      <td>...</td>\n",
       "      <td>0.415114</td>\n",
       "      <td>0.329952</td>\n",
       "      <td>0.549609</td>\n",
       "      <td>0.571324</td>\n",
       "      <td>0.932040</td>\n",
       "      <td>0.671134</td>\n",
       "      <td>0.730768</td>\n",
       "      <td>0.735666</td>\n",
       "      <td>0.476564</td>\n",
       "      <td>0.603078</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>FS04821315_FO0000163_MAPT_R317W_G09_17_B12</td>\n",
       "      <td>BB</td>\n",
       "      <td>BB</td>\n",
       "      <td>BB</td>\n",
       "      <td>BB</td>\n",
       "      <td>AA</td>\n",
       "      <td>AA</td>\n",
       "      <td>AA</td>\n",
       "      <td>AA</td>\n",
       "      <td>AA</td>\n",
       "      <td>...</td>\n",
       "      <td>0.379468</td>\n",
       "      <td>0.420835</td>\n",
       "      <td>0.541583</td>\n",
       "      <td>0.608452</td>\n",
       "      <td>0.976639</td>\n",
       "      <td>0.641460</td>\n",
       "      <td>0.726527</td>\n",
       "      <td>0.748987</td>\n",
       "      <td>0.439781</td>\n",
       "      <td>0.518233</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>FS04821316_FO0000176_ANG_K41I_A04_17_D01</td>\n",
       "      <td>BB</td>\n",
       "      <td>BB</td>\n",
       "      <td>BB</td>\n",
       "      <td>BB</td>\n",
       "      <td>AA</td>\n",
       "      <td>AA</td>\n",
       "      <td>AA</td>\n",
       "      <td>AA</td>\n",
       "      <td>AA</td>\n",
       "      <td>...</td>\n",
       "      <td>0.462127</td>\n",
       "      <td>0.387539</td>\n",
       "      <td>0.521502</td>\n",
       "      <td>0.639255</td>\n",
       "      <td>0.965216</td>\n",
       "      <td>0.699769</td>\n",
       "      <td>0.735392</td>\n",
       "      <td>0.791597</td>\n",
       "      <td>0.410290</td>\n",
       "      <td>0.626747</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>FS04821317_FO0000188_SNCB_P123H_B08_17_E01</td>\n",
       "      <td>BB</td>\n",
       "      <td>BB</td>\n",
       "      <td>BB</td>\n",
       "      <td>BB</td>\n",
       "      <td>AA</td>\n",
       "      <td>AA</td>\n",
       "      <td>AA</td>\n",
       "      <td>AA</td>\n",
       "      <td>AA</td>\n",
       "      <td>...</td>\n",
       "      <td>0.469232</td>\n",
       "      <td>0.366763</td>\n",
       "      <td>0.586054</td>\n",
       "      <td>0.579106</td>\n",
       "      <td>1.041958</td>\n",
       "      <td>0.677856</td>\n",
       "      <td>0.758849</td>\n",
       "      <td>0.712157</td>\n",
       "      <td>0.468440</td>\n",
       "      <td>0.582567</td>\n",
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       "    <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>91</th>\n",
       "      <td>FS04821404_FO0000171_APP_A673T_D09_17_C08</td>\n",
       "      <td>BB</td>\n",
       "      <td>BB</td>\n",
       "      <td>BB</td>\n",
       "      <td>BB</td>\n",
       "      <td>AA</td>\n",
       "      <td>AA</td>\n",
       "      <td>AA</td>\n",
       "      <td>AA</td>\n",
       "      <td>AA</td>\n",
       "      <td>...</td>\n",
       "      <td>0.359078</td>\n",
       "      <td>0.360436</td>\n",
       "      <td>0.449827</td>\n",
       "      <td>0.581284</td>\n",
       "      <td>1.042775</td>\n",
       "      <td>0.702279</td>\n",
       "      <td>0.757134</td>\n",
       "      <td>0.718126</td>\n",
       "      <td>0.447970</td>\n",
       "      <td>0.575152</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>92</th>\n",
       "      <td>FS04821405_FO0000172_APP_A673T_D12_17_C09</td>\n",
       "      <td>BB</td>\n",
       "      <td>BB</td>\n",
       "      <td>BB</td>\n",
       "      <td>BB</td>\n",
       "      <td>AA</td>\n",
       "      <td>AA</td>\n",
       "      <td>AA</td>\n",
       "      <td>AA</td>\n",
       "      <td>AA</td>\n",
       "      <td>...</td>\n",
       "      <td>0.365155</td>\n",
       "      <td>0.359822</td>\n",
       "      <td>0.513683</td>\n",
       "      <td>0.557322</td>\n",
       "      <td>0.872211</td>\n",
       "      <td>0.649222</td>\n",
       "      <td>0.692903</td>\n",
       "      <td>0.726661</td>\n",
       "      <td>0.427236</td>\n",
       "      <td>0.530507</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>93</th>\n",
       "      <td>FS04821406_FO0000173_APP_A673T_F06_17_C10</td>\n",
       "      <td>BB</td>\n",
       "      <td>BB</td>\n",
       "      <td>BB</td>\n",
       "      <td>BB</td>\n",
       "      <td>AA</td>\n",
       "      <td>AA</td>\n",
       "      <td>AA</td>\n",
       "      <td>AA</td>\n",
       "      <td>AA</td>\n",
       "      <td>...</td>\n",
       "      <td>0.329993</td>\n",
       "      <td>0.388541</td>\n",
       "      <td>0.518266</td>\n",
       "      <td>0.577355</td>\n",
       "      <td>0.891683</td>\n",
       "      <td>0.711396</td>\n",
       "      <td>0.780114</td>\n",
       "      <td>0.710056</td>\n",
       "      <td>0.407510</td>\n",
       "      <td>0.513913</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>94</th>\n",
       "      <td>FS04821407_FO0000174_APP_A673T_H08_17_C11</td>\n",
       "      <td>BB</td>\n",
       "      <td>BB</td>\n",
       "      <td>BB</td>\n",
       "      <td>BB</td>\n",
       "      <td>AA</td>\n",
       "      <td>AA</td>\n",
       "      <td>AA</td>\n",
       "      <td>AA</td>\n",
       "      <td>AA</td>\n",
       "      <td>...</td>\n",
       "      <td>0.354541</td>\n",
       "      <td>0.322347</td>\n",
       "      <td>0.421428</td>\n",
       "      <td>0.515936</td>\n",
       "      <td>0.894079</td>\n",
       "      <td>0.712438</td>\n",
       "      <td>0.747326</td>\n",
       "      <td>0.663459</td>\n",
       "      <td>0.403457</td>\n",
       "      <td>0.479983</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>95</th>\n",
       "      <td>PositiveControl_1_NA_NA</td>\n",
       "      <td>BB</td>\n",
       "      <td>BB</td>\n",
       "      <td>BB</td>\n",
       "      <td>BB</td>\n",
       "      <td>AA</td>\n",
       "      <td>AA</td>\n",
       "      <td>AA</td>\n",
       "      <td>AA</td>\n",
       "      <td>AA</td>\n",
       "      <td>...</td>\n",
       "      <td>0.182542</td>\n",
       "      <td>0.116625</td>\n",
       "      <td>0.200661</td>\n",
       "      <td>0.187479</td>\n",
       "      <td>0.391974</td>\n",
       "      <td>0.271091</td>\n",
       "      <td>0.502401</td>\n",
       "      <td>0.301212</td>\n",
       "      <td>0.207442</td>\n",
       "      <td>0.140064</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>96 rows × 77986 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "idx                                         IID 1KG_22_19435270.GType  \\\n",
       "0     FS04821313_FO0000275_FUS_R495*_A01_17_A01                    BB   \n",
       "1    FS04821314_FO0000152_MAPT_R317W_A08_17_B01                    BB   \n",
       "2    FS04821315_FO0000163_MAPT_R317W_G09_17_B12                    BB   \n",
       "3      FS04821316_FO0000176_ANG_K41I_A04_17_D01                    BB   \n",
       "4    FS04821317_FO0000188_SNCB_P123H_B08_17_E01                    BB   \n",
       "..                                          ...                   ...   \n",
       "91    FS04821404_FO0000171_APP_A673T_D09_17_C08                    BB   \n",
       "92    FS04821405_FO0000172_APP_A673T_D12_17_C09                    BB   \n",
       "93    FS04821406_FO0000173_APP_A673T_F06_17_C10                    BB   \n",
       "94    FS04821407_FO0000174_APP_A673T_H08_17_C11                    BB   \n",
       "95                      PositiveControl_1_NA_NA                    BB   \n",
       "\n",
       "idx 1KG_22_19766749.GType 1KG_22_24530438.GType 1KG_22_24909316.GType  \\\n",
       "0                      BB                    BB                    BB   \n",
       "1                      BB                    BB                    BB   \n",
       "2                      BB                    BB                    BB   \n",
       "3                      BB                    BB                    BB   \n",
       "4                      BB                    BB                    BB   \n",
       "..                    ...                   ...                   ...   \n",
       "91                     BB                    BB                    BB   \n",
       "92                     BB                    BB                    BB   \n",
       "93                     BB                    BB                    BB   \n",
       "94                     BB                    BB                    BB   \n",
       "95                     BB                    BB                    BB   \n",
       "\n",
       "idx 1KG_22_26286764.GType 1KG_22_26298671.GType 1KG_22_30857665.GType  \\\n",
       "0                      AA                    AA                    AA   \n",
       "1                      AA                    AA                    AA   \n",
       "2                      AA                    AA                    AA   \n",
       "3                      AA                    AA                    AA   \n",
       "4                      AA                    AA                    AA   \n",
       "..                    ...                   ...                   ...   \n",
       "91                     AA                    AA                    AA   \n",
       "92                     AA                    AA                    AA   \n",
       "93                     AA                    AA                    AA   \n",
       "94                     AA                    AA                    AA   \n",
       "95                     AA                    AA                    AA   \n",
       "\n",
       "idx 1KG_22_36681998.GType 1KG_22_38494134.GType  ... Variant61228.R  \\\n",
       "0                      AA                    AA  ...       0.430500   \n",
       "1                      AA                    AA  ...       0.415114   \n",
       "2                      AA                    AA  ...       0.379468   \n",
       "3                      AA                    AA  ...       0.462127   \n",
       "4                      AA                    AA  ...       0.469232   \n",
       "..                    ...                   ...  ...            ...   \n",
       "91                     AA                    AA  ...       0.359078   \n",
       "92                     AA                    AA  ...       0.365155   \n",
       "93                     AA                    AA  ...       0.329993   \n",
       "94                     AA                    AA  ...       0.354541   \n",
       "95                     AA                    AA  ...       0.182542   \n",
       "\n",
       "idx Variant61231.R Variant61234.R Variant61237.R Variant61242.R  \\\n",
       "0         0.361874       0.540405       0.626420       0.957749   \n",
       "1         0.329952       0.549609       0.571324       0.932040   \n",
       "2         0.420835       0.541583       0.608452       0.976639   \n",
       "3         0.387539       0.521502       0.639255       0.965216   \n",
       "4         0.366763       0.586054       0.579106       1.041958   \n",
       "..             ...            ...            ...            ...   \n",
       "91        0.360436       0.449827       0.581284       1.042775   \n",
       "92        0.359822       0.513683       0.557322       0.872211   \n",
       "93        0.388541       0.518266       0.577355       0.891683   \n",
       "94        0.322347       0.421428       0.515936       0.894079   \n",
       "95        0.116625       0.200661       0.187479       0.391974   \n",
       "\n",
       "idx Variant61244.R Variant61245.R Variant61246.R Variant61252.R Variant61253.R  \n",
       "0         0.733668       0.795464       0.701761       0.470309       0.569939  \n",
       "1         0.671134       0.730768       0.735666       0.476564       0.603078  \n",
       "2         0.641460       0.726527       0.748987       0.439781       0.518233  \n",
       "3         0.699769       0.735392       0.791597       0.410290       0.626747  \n",
       "4         0.677856       0.758849       0.712157       0.468440       0.582567  \n",
       "..             ...            ...            ...            ...            ...  \n",
       "91        0.702279       0.757134       0.718126       0.447970       0.575152  \n",
       "92        0.649222       0.692903       0.726661       0.427236       0.530507  \n",
       "93        0.711396       0.780114       0.710056       0.407510       0.513913  \n",
       "94        0.712438       0.747326       0.663459       0.403457       0.479983  \n",
       "95        0.271091       0.502401       0.301212       0.207442       0.140064  \n",
       "\n",
       "[96 rows x 77986 columns]"
      ]
     },
     "execution_count": 49,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cb_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.model_selection import train_test_split\n",
    "from sklearn.mixture import GaussianMixture\n",
    "\n",
    "gtypes_map = {\n",
    "    'AA':'0',\n",
    "    'AB':'1',\n",
    "    'BA':'1',\n",
    "    'BB':'2',\n",
    "    }\n",
    "\n",
    "gtypes_map_rev = {\n",
    "    '0':'AA',\n",
    "    '1':'AB',\n",
    "    '2':'BB'\n",
    "}\n",
    "\n",
    "# samples to train and test on\n",
    "to_gmm_samples = snp_for_gmm_df.loc[snp_for_gmm_df[geno_col]!='NC']\n",
    "# to_gmm_samples.loc[:,'gtype'] = np.where(to_gmm_samples.loc[:, geno_col]=='BA', 'AB', to_gmm_samples.loc[:, geno_col])\n",
    "\n",
    "# samples to predict\n",
    "to_pred_samples = snp_for_gmm_df.loc[snp_for_gmm_df[geno_col]=='NC']\n",
    "\n",
    "X = to_gmm_samples.loc[:,[theta_col, r_col]]\n",
    "y = np.where(to_gmm_samples.loc[:, geno_col]=='BA', 'AB', to_gmm_samples.loc[:, geno_col])\n",
    "y = to_gmm_samples.loc[:,geno_col].replace(gtypes_map)\n",
    "\n",
    "x_pred = to_pred_samples.loc[:,[theta_col, r_col]]\n",
    "# n_classes = len(np.unique(y))\n",
    "classes = np.unique(y)\n",
    "\n",
    "gmm = GaussianMixture(\n",
    "        n_components=n_components,\n",
    "        covariance_type=\"diag\",\n",
    "        random_state = 10).fit(X)\n",
    "\n",
    "gmm.means_ = np.array([X[y == i].mean(axis=0) for i in classes])\n",
    "\n",
    "gmm.fit(X)\n",
    "y_pred = gmm.predict(x_pred)\n",
    "y_pred"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.896737899999998"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# import math\n",
    "# position = gmm.means_\n",
    "# covariances = gmm.covariances_\n",
    "# w = gmm.weights_\n",
    "\n",
    "# position[0][0]\n",
    "\n",
    "# def ellipse(x_center=0, y_center=0, ax1 = [1, 0],  ax2 = [0,1], a=1, b =1,  N=100):\n",
    "#    # x_center, y_center the coordinates of ellipse center\n",
    "#    # ax1 ax2 two orthonormal vectors representing the ellipse axis directions\n",
    "#    # a, b the ellipse parameters\n",
    "#    if np.linalg.norm(ax1) != 1 or np.linalg.norm(ax2) != 1:\n",
    "#        raise ValueError('ax1, ax2 must be unit vectors')\n",
    "#    if  abs(np.dot(ax1, ax2)) > 1e-06:\n",
    "#        raise ValueError('ax1, ax2 must be orthogonal vectors')\n",
    "#    #rotation matrix   \n",
    "#    R = np.array([ax1, ax2]).T\n",
    "#    if np.linalg.det(R) <0: \n",
    "#        raise ValueError(\"the det(R) must be positive to get a  positively oriented ellipse reference frame\")\n",
    "#    t = np.linspace(0, 2*math.pi, N)\n",
    "#    #ellipse parameterization with respect to a system of axes of directions a1, a2\n",
    "#    xs = a * math.cos(t)\n",
    "#    ys = b * math.sin(t)\n",
    "   \n",
    "#    # coordinate of the  ellipse points with respect to the system of axes [1, 0], [0,1] with origin (0,0)\n",
    "#    xp, yp = np.dot(R, [xs, ys])\n",
    "#    x = xp + x_center \n",
    "#    y = yp + y_center\n",
    "#    return x, y\n",
    "\n",
    "\n",
    "# ellipse(x_center=position[0], y_center=position[1])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "39\n"
     ]
    }
   ],
   "source": [
    "# snp_list = gtype_df.idx\n",
    "# snps_of_interest = list()\n",
    "# count=0\n",
    "# for snp in snp_list:\n",
    "#     if set(['NC','AA','BB']).issubset(list(GType_transposed_df[snp].unique())):\n",
    "#         vc = GType_transposed_df[snp].value_counts()\n",
    "#         # print(vc)\n",
    "#         snps_of_interest.append(snp)\n",
    "#         count+=1\n",
    "       \n",
    "# print(count)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "# # flag_df[(flag_df.maf>0.03) & (flag_df.maf<0.5)\n",
    "# snps_of_interest_df = pd.DataFrame({'snp':snps_of_interest})\n",
    "# snps_of_interest_df.loc[:,'snp'] = snps_of_interest_df.loc[:,'snp'].str.replace('.GType','',regex=False) \n",
    "# snps_of_interest_df.to_csv('../data/testing_snps_of_interest.csv', index=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Chop out to GType, Score and Theta dataframes.\n",
    "flag_maf=0.01\n",
    "flag_gentrain=0.5\n",
    "report = report_in.copy()\n",
    "Name_df = report[['Name']].copy()\n",
    "GType_df = report.loc[:, report.columns.str.endswith(\".GType\")]\n",
    "Theta_df = report.loc[:, report.columns.str.endswith(\".Theta\")]\n",
    "R_df = report.loc[:, report.columns.str.endswith(\".R\")]\n",
    "\n",
    "Name_df['Name.GType'] = Name_df.loc[:,'Name'] + \".GType\"\n",
    "Name_df['Name.Theta'] = Name_df.loc[:,'Name'] + \".Theta\"\n",
    "Name_df['Name.R'] = Name_df.loc[:,'Name'] + \".R\"\n",
    "\n",
    "# Merge names plus data types.\n",
    "Name_GType_df = pd.concat([Name_df, GType_df], axis=1).rename(columns={\"Name.GType\":\"idx\"}).drop(columns=['Name', 'Name.Theta', 'Name.R'])\n",
    "Name_GType_df.columns = Name_GType_df.columns.str.replace(\".GType\", \"\", regex=False)\n",
    "Name_GType_df_final = Name_GType_df.set_index('idx')\n",
    "\n",
    "Name_Theta_df = pd.concat([Name_df, Theta_df], axis=1).rename(columns={\"Name.Theta\": \"idx\"}).set_index('idx').drop(columns=['Name', 'Name.GType', 'Name.R'])\n",
    "Name_Theta_df.columns = Name_Theta_df.columns.str.replace(\".Theta\", \"\", regex=False)\n",
    "\n",
    "Name_R_df = pd.concat([Name_df, R_df], axis=1).rename(columns={\"Name.R\":\"idx\"}).set_index('idx').drop(columns=['Name', 'Name.Theta', 'Name.GType'])\n",
    "Name_R_df.columns = Name_R_df.columns.str.replace(\".R\", \"\", regex=False)\n",
    "\n",
    "#  Transpose the data frames and make the names of the variants plus the suffixes the columns.\n",
    "GType_transposed_df = Name_GType_df_final.transpose()\n",
    "Theta_transposed_df = Name_Theta_df.transpose()\n",
    "R_transposed_df = Name_R_df.transpose()\n",
    "\n",
    "# Smash everything together and get ready for plotting.\n",
    "temp_df = GType_transposed_df.merge(Theta_transposed_df, left_index=True, right_index=True)\n",
    "clusterbuster_df = temp_df.merge(R_transposed_df, left_index=True, right_index=True)\n",
    "clusterbuster_out = clusterbuster_df.reset_index().rename(columns={'index':'IID'})\n",
    "\n",
    "# get gentrain scores\n",
    "\n",
    "gtrain_scores_df = report_in.loc[:,['Name', 'Chr', 'Position','GenTrain Score','Frac A', 'Frac C', 'Frac G', 'Frac T']]\n",
    "gtrain_scores_df.columns = ['snpid','Chr','Position','gentrain_score','Frac_A','Frac_C','Frac_G','Frac_T']\n",
    "# calculate maf\n",
    "gtype_df = Name_GType_df.copy()\n",
    "gtype_df.loc[:,'snpid'] = gtype_df.loc[:,'idx'].str.replace(\".GType\", \"\", regex=False)\n",
    "gtype_to_maf = gtype_df.drop(columns=['idx'])\n",
    "maf_scores_df = calculate_maf(gtype_to_maf)\n",
    "flag_df = maf_scores_df.merge(gtrain_scores_df, how='inner', on='snpid')\n",
    "flag_df.loc[:,'maf_flag'] = np.where(flag_df.maf<flag_maf, True, False)\n",
    "flag_df.loc[:,'gentrain_flag'] = np.where(flag_df.gentrain_score<flag_gentrain, True, False)\n",
    "\n",
    "missing_df = pd.DataFrame()\n",
    "\n",
    "\n",
    "out_dict = {\n",
    "    'clusterbuster_df': clusterbuster_out,\n",
    "    'flagged_snps': flag_df, \n",
    "}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>FS04821313_FO0000275_FUS_R495*_A01_17_A01</th>\n",
       "      <th>FS04821314_FO0000152_MAPT_R317W_A08_17_B01</th>\n",
       "      <th>FS04821315_FO0000163_MAPT_R317W_G09_17_B12</th>\n",
       "      <th>FS04821316_FO0000176_ANG_K41I_A04_17_D01</th>\n",
       "      <th>FS04821317_FO0000188_SNCB_P123H_B08_17_E01</th>\n",
       "      <th>FS04821318_FO0000200_PFN1_C71G_A01_17_F01</th>\n",
       "      <th>FS04821319_FO0000212_HNRNPA1_D262N_A01_17_G01</th>\n",
       "      <th>FS04821320_FO0000224_CSF1R_E633K_A01_17_H01</th>\n",
       "      <th>FS04821321_FO0000276_FUS_R495*_A04_17_A02</th>\n",
       "      <th>FS04821322_FO0000153_MAPT_R317W_A10_17_B02</th>\n",
       "      <th>...</th>\n",
       "      <th>FS04821399_FO0000166_APP_A673T_A10_17_C03</th>\n",
       "      <th>FS04821400_FO0000167_APP_A673T_B02_17_C04</th>\n",
       "      <th>FS04821401_FO0000168_APP_A673T_B11_17_C05</th>\n",
       "      <th>FS04821402_FO0000169_APP_A673T_C03_17_C06</th>\n",
       "      <th>FS04821403_FO0000170_APP_A673T_C04_17_C07</th>\n",
       "      <th>FS04821404_FO0000171_APP_A673T_D09_17_C08</th>\n",
       "      <th>FS04821405_FO0000172_APP_A673T_D12_17_C09</th>\n",
       "      <th>FS04821406_FO0000173_APP_A673T_F06_17_C10</th>\n",
       "      <th>FS04821407_FO0000174_APP_A673T_H08_17_C11</th>\n",
       "      <th>PositiveControl_1_NA_NA</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>idx</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",
       "      <th></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",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>22:19263188-TC.Theta</th>\n",
       "      <td>0.016549</td>\n",
       "      <td>0.016549</td>\n",
       "      <td>0.034746</td>\n",
       "      <td>0.005748</td>\n",
       "      <td>0.013034</td>\n",
       "      <td>0.028882</td>\n",
       "      <td>0.036758</td>\n",
       "      <td>0.009955</td>\n",
       "      <td>0.027756</td>\n",
       "      <td>0.026663</td>\n",
       "      <td>...</td>\n",
       "      <td>0.017424</td>\n",
       "      <td>0.030915</td>\n",
       "      <td>0.026956</td>\n",
       "      <td>0.011431</td>\n",
       "      <td>0.021527</td>\n",
       "      <td>0.011655</td>\n",
       "      <td>0.035450</td>\n",
       "      <td>0.039059</td>\n",
       "      <td>0.029760</td>\n",
       "      <td>0.050559</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22:21354461-GA.Theta</th>\n",
       "      <td>0.958369</td>\n",
       "      <td>0.881275</td>\n",
       "      <td>0.842105</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.900391</td>\n",
       "      <td>0.901443</td>\n",
       "      <td>0.901834</td>\n",
       "      <td>0.950166</td>\n",
       "      <td>0.885677</td>\n",
       "      <td>0.955232</td>\n",
       "      <td>...</td>\n",
       "      <td>0.856874</td>\n",
       "      <td>0.896709</td>\n",
       "      <td>0.903836</td>\n",
       "      <td>0.946666</td>\n",
       "      <td>0.937902</td>\n",
       "      <td>0.927664</td>\n",
       "      <td>0.946430</td>\n",
       "      <td>0.931566</td>\n",
       "      <td>0.867493</td>\n",
       "      <td>0.524616</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22:21384250-AG.Theta</th>\n",
       "      <td>0.040352</td>\n",
       "      <td>0.093047</td>\n",
       "      <td>0.065083</td>\n",
       "      <td>0.079220</td>\n",
       "      <td>0.063334</td>\n",
       "      <td>0.056559</td>\n",
       "      <td>0.088066</td>\n",
       "      <td>0.097245</td>\n",
       "      <td>0.146142</td>\n",
       "      <td>0.121591</td>\n",
       "      <td>...</td>\n",
       "      <td>0.101050</td>\n",
       "      <td>0.109888</td>\n",
       "      <td>0.090588</td>\n",
       "      <td>0.062786</td>\n",
       "      <td>0.094529</td>\n",
       "      <td>0.121504</td>\n",
       "      <td>0.117310</td>\n",
       "      <td>0.072148</td>\n",
       "      <td>0.136329</td>\n",
       "      <td>0.434891</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22:21984279-CA.Theta</th>\n",
       "      <td>0.936341</td>\n",
       "      <td>0.912554</td>\n",
       "      <td>0.924742</td>\n",
       "      <td>0.921270</td>\n",
       "      <td>0.957253</td>\n",
       "      <td>0.954720</td>\n",
       "      <td>0.900188</td>\n",
       "      <td>0.946820</td>\n",
       "      <td>0.911227</td>\n",
       "      <td>0.937269</td>\n",
       "      <td>...</td>\n",
       "      <td>0.880905</td>\n",
       "      <td>0.919169</td>\n",
       "      <td>0.942667</td>\n",
       "      <td>0.971814</td>\n",
       "      <td>0.899858</td>\n",
       "      <td>0.977350</td>\n",
       "      <td>0.914369</td>\n",
       "      <td>0.905627</td>\n",
       "      <td>0.905158</td>\n",
       "      <td>0.607808</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22:24481101-AG.Theta</th>\n",
       "      <td>0.027583</td>\n",
       "      <td>0.029278</td>\n",
       "      <td>0.020352</td>\n",
       "      <td>0.033576</td>\n",
       "      <td>0.017459</td>\n",
       "      <td>0.029715</td>\n",
       "      <td>0.028005</td>\n",
       "      <td>0.025697</td>\n",
       "      <td>0.014463</td>\n",
       "      <td>0.022326</td>\n",
       "      <td>...</td>\n",
       "      <td>0.030915</td>\n",
       "      <td>0.023189</td>\n",
       "      <td>0.010187</td>\n",
       "      <td>0.016286</td>\n",
       "      <td>0.017335</td>\n",
       "      <td>0.018646</td>\n",
       "      <td>0.020970</td>\n",
       "      <td>0.031749</td>\n",
       "      <td>0.016931</td>\n",
       "      <td>0.029535</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>rs9625374.Theta</th>\n",
       "      <td>0.578136</td>\n",
       "      <td>0.577489</td>\n",
       "      <td>0.562329</td>\n",
       "      <td>0.567274</td>\n",
       "      <td>0.587530</td>\n",
       "      <td>0.578070</td>\n",
       "      <td>0.591982</td>\n",
       "      <td>0.696036</td>\n",
       "      <td>0.603432</td>\n",
       "      <td>0.613582</td>\n",
       "      <td>...</td>\n",
       "      <td>0.618050</td>\n",
       "      <td>0.568534</td>\n",
       "      <td>0.558752</td>\n",
       "      <td>0.603907</td>\n",
       "      <td>0.591012</td>\n",
       "      <td>0.579917</td>\n",
       "      <td>0.589297</td>\n",
       "      <td>0.626615</td>\n",
       "      <td>0.603600</td>\n",
       "      <td>0.019538</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>rs9626059.Theta</th>\n",
       "      <td>0.959312</td>\n",
       "      <td>0.956198</td>\n",
       "      <td>0.945253</td>\n",
       "      <td>0.927606</td>\n",
       "      <td>0.948385</td>\n",
       "      <td>0.953619</td>\n",
       "      <td>0.958424</td>\n",
       "      <td>0.931868</td>\n",
       "      <td>0.926692</td>\n",
       "      <td>0.931908</td>\n",
       "      <td>...</td>\n",
       "      <td>0.911472</td>\n",
       "      <td>0.917925</td>\n",
       "      <td>0.952390</td>\n",
       "      <td>0.973589</td>\n",
       "      <td>0.954016</td>\n",
       "      <td>0.950417</td>\n",
       "      <td>0.937735</td>\n",
       "      <td>0.960297</td>\n",
       "      <td>0.951617</td>\n",
       "      <td>0.920231</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>rs9628047.Theta</th>\n",
       "      <td>0.515638</td>\n",
       "      <td>0.536284</td>\n",
       "      <td>0.560650</td>\n",
       "      <td>0.539354</td>\n",
       "      <td>0.543270</td>\n",
       "      <td>0.538346</td>\n",
       "      <td>0.570527</td>\n",
       "      <td>0.482153</td>\n",
       "      <td>0.550294</td>\n",
       "      <td>0.578773</td>\n",
       "      <td>...</td>\n",
       "      <td>0.520268</td>\n",
       "      <td>0.537218</td>\n",
       "      <td>0.557735</td>\n",
       "      <td>0.506185</td>\n",
       "      <td>0.537496</td>\n",
       "      <td>0.575556</td>\n",
       "      <td>0.550700</td>\n",
       "      <td>0.554986</td>\n",
       "      <td>0.564009</td>\n",
       "      <td>0.518252</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>rs999458.Theta</th>\n",
       "      <td>0.563739</td>\n",
       "      <td>0.589696</td>\n",
       "      <td>0.563988</td>\n",
       "      <td>0.602818</td>\n",
       "      <td>0.587157</td>\n",
       "      <td>0.574342</td>\n",
       "      <td>0.544992</td>\n",
       "      <td>0.506885</td>\n",
       "      <td>0.604721</td>\n",
       "      <td>0.573953</td>\n",
       "      <td>...</td>\n",
       "      <td>0.554496</td>\n",
       "      <td>0.539772</td>\n",
       "      <td>0.603856</td>\n",
       "      <td>0.628461</td>\n",
       "      <td>0.593603</td>\n",
       "      <td>0.595947</td>\n",
       "      <td>0.583897</td>\n",
       "      <td>0.585212</td>\n",
       "      <td>0.561027</td>\n",
       "      <td>0.527736</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>variant.71844.Theta</th>\n",
       "      <td>0.956982</td>\n",
       "      <td>0.946473</td>\n",
       "      <td>0.967700</td>\n",
       "      <td>0.958387</td>\n",
       "      <td>0.960848</td>\n",
       "      <td>0.932864</td>\n",
       "      <td>0.920081</td>\n",
       "      <td>0.959149</td>\n",
       "      <td>0.921769</td>\n",
       "      <td>0.949190</td>\n",
       "      <td>...</td>\n",
       "      <td>0.941767</td>\n",
       "      <td>0.971319</td>\n",
       "      <td>0.953378</td>\n",
       "      <td>0.967243</td>\n",
       "      <td>0.944638</td>\n",
       "      <td>0.946361</td>\n",
       "      <td>0.959746</td>\n",
       "      <td>0.949609</td>\n",
       "      <td>0.956597</td>\n",
       "      <td>0.927436</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>336 rows × 96 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                      FS04821313_FO0000275_FUS_R495*_A01_17_A01  \\\n",
       "idx                                                               \n",
       "22:19263188-TC.Theta                                   0.016549   \n",
       "22:21354461-GA.Theta                                   0.958369   \n",
       "22:21384250-AG.Theta                                   0.040352   \n",
       "22:21984279-CA.Theta                                   0.936341   \n",
       "22:24481101-AG.Theta                                   0.027583   \n",
       "...                                                         ...   \n",
       "rs9625374.Theta                                        0.578136   \n",
       "rs9626059.Theta                                        0.959312   \n",
       "rs9628047.Theta                                        0.515638   \n",
       "rs999458.Theta                                         0.563739   \n",
       "variant.71844.Theta                                    0.956982   \n",
       "\n",
       "                      FS04821314_FO0000152_MAPT_R317W_A08_17_B01  \\\n",
       "idx                                                                \n",
       "22:19263188-TC.Theta                                    0.016549   \n",
       "22:21354461-GA.Theta                                    0.881275   \n",
       "22:21384250-AG.Theta                                    0.093047   \n",
       "22:21984279-CA.Theta                                    0.912554   \n",
       "22:24481101-AG.Theta                                    0.029278   \n",
       "...                                                          ...   \n",
       "rs9625374.Theta                                         0.577489   \n",
       "rs9626059.Theta                                         0.956198   \n",
       "rs9628047.Theta                                         0.536284   \n",
       "rs999458.Theta                                          0.589696   \n",
       "variant.71844.Theta                                     0.946473   \n",
       "\n",
       "                      FS04821315_FO0000163_MAPT_R317W_G09_17_B12  \\\n",
       "idx                                                                \n",
       "22:19263188-TC.Theta                                    0.034746   \n",
       "22:21354461-GA.Theta                                    0.842105   \n",
       "22:21384250-AG.Theta                                    0.065083   \n",
       "22:21984279-CA.Theta                                    0.924742   \n",
       "22:24481101-AG.Theta                                    0.020352   \n",
       "...                                                          ...   \n",
       "rs9625374.Theta                                         0.562329   \n",
       "rs9626059.Theta                                         0.945253   \n",
       "rs9628047.Theta                                         0.560650   \n",
       "rs999458.Theta                                          0.563988   \n",
       "variant.71844.Theta                                     0.967700   \n",
       "\n",
       "                      FS04821316_FO0000176_ANG_K41I_A04_17_D01  \\\n",
       "idx                                                              \n",
       "22:19263188-TC.Theta                                  0.005748   \n",
       "22:21354461-GA.Theta                                       NaN   \n",
       "22:21384250-AG.Theta                                  0.079220   \n",
       "22:21984279-CA.Theta                                  0.921270   \n",
       "22:24481101-AG.Theta                                  0.033576   \n",
       "...                                                        ...   \n",
       "rs9625374.Theta                                       0.567274   \n",
       "rs9626059.Theta                                       0.927606   \n",
       "rs9628047.Theta                                       0.539354   \n",
       "rs999458.Theta                                        0.602818   \n",
       "variant.71844.Theta                                   0.958387   \n",
       "\n",
       "                      FS04821317_FO0000188_SNCB_P123H_B08_17_E01  \\\n",
       "idx                                                                \n",
       "22:19263188-TC.Theta                                    0.013034   \n",
       "22:21354461-GA.Theta                                    0.900391   \n",
       "22:21384250-AG.Theta                                    0.063334   \n",
       "22:21984279-CA.Theta                                    0.957253   \n",
       "22:24481101-AG.Theta                                    0.017459   \n",
       "...                                                          ...   \n",
       "rs9625374.Theta                                         0.587530   \n",
       "rs9626059.Theta                                         0.948385   \n",
       "rs9628047.Theta                                         0.543270   \n",
       "rs999458.Theta                                          0.587157   \n",
       "variant.71844.Theta                                     0.960848   \n",
       "\n",
       "                      FS04821318_FO0000200_PFN1_C71G_A01_17_F01  \\\n",
       "idx                                                               \n",
       "22:19263188-TC.Theta                                   0.028882   \n",
       "22:21354461-GA.Theta                                   0.901443   \n",
       "22:21384250-AG.Theta                                   0.056559   \n",
       "22:21984279-CA.Theta                                   0.954720   \n",
       "22:24481101-AG.Theta                                   0.029715   \n",
       "...                                                         ...   \n",
       "rs9625374.Theta                                        0.578070   \n",
       "rs9626059.Theta                                        0.953619   \n",
       "rs9628047.Theta                                        0.538346   \n",
       "rs999458.Theta                                         0.574342   \n",
       "variant.71844.Theta                                    0.932864   \n",
       "\n",
       "                      FS04821319_FO0000212_HNRNPA1_D262N_A01_17_G01  \\\n",
       "idx                                                                   \n",
       "22:19263188-TC.Theta                                       0.036758   \n",
       "22:21354461-GA.Theta                                       0.901834   \n",
       "22:21384250-AG.Theta                                       0.088066   \n",
       "22:21984279-CA.Theta                                       0.900188   \n",
       "22:24481101-AG.Theta                                       0.028005   \n",
       "...                                                             ...   \n",
       "rs9625374.Theta                                            0.591982   \n",
       "rs9626059.Theta                                            0.958424   \n",
       "rs9628047.Theta                                            0.570527   \n",
       "rs999458.Theta                                             0.544992   \n",
       "variant.71844.Theta                                        0.920081   \n",
       "\n",
       "                      FS04821320_FO0000224_CSF1R_E633K_A01_17_H01  \\\n",
       "idx                                                                 \n",
       "22:19263188-TC.Theta                                     0.009955   \n",
       "22:21354461-GA.Theta                                     0.950166   \n",
       "22:21384250-AG.Theta                                     0.097245   \n",
       "22:21984279-CA.Theta                                     0.946820   \n",
       "22:24481101-AG.Theta                                     0.025697   \n",
       "...                                                           ...   \n",
       "rs9625374.Theta                                          0.696036   \n",
       "rs9626059.Theta                                          0.931868   \n",
       "rs9628047.Theta                                          0.482153   \n",
       "rs999458.Theta                                           0.506885   \n",
       "variant.71844.Theta                                      0.959149   \n",
       "\n",
       "                      FS04821321_FO0000276_FUS_R495*_A04_17_A02  \\\n",
       "idx                                                               \n",
       "22:19263188-TC.Theta                                   0.027756   \n",
       "22:21354461-GA.Theta                                   0.885677   \n",
       "22:21384250-AG.Theta                                   0.146142   \n",
       "22:21984279-CA.Theta                                   0.911227   \n",
       "22:24481101-AG.Theta                                   0.014463   \n",
       "...                                                         ...   \n",
       "rs9625374.Theta                                        0.603432   \n",
       "rs9626059.Theta                                        0.926692   \n",
       "rs9628047.Theta                                        0.550294   \n",
       "rs999458.Theta                                         0.604721   \n",
       "variant.71844.Theta                                    0.921769   \n",
       "\n",
       "                      FS04821322_FO0000153_MAPT_R317W_A10_17_B02  ...  \\\n",
       "idx                                                               ...   \n",
       "22:19263188-TC.Theta                                    0.026663  ...   \n",
       "22:21354461-GA.Theta                                    0.955232  ...   \n",
       "22:21384250-AG.Theta                                    0.121591  ...   \n",
       "22:21984279-CA.Theta                                    0.937269  ...   \n",
       "22:24481101-AG.Theta                                    0.022326  ...   \n",
       "...                                                          ...  ...   \n",
       "rs9625374.Theta                                         0.613582  ...   \n",
       "rs9626059.Theta                                         0.931908  ...   \n",
       "rs9628047.Theta                                         0.578773  ...   \n",
       "rs999458.Theta                                          0.573953  ...   \n",
       "variant.71844.Theta                                     0.949190  ...   \n",
       "\n",
       "                      FS04821399_FO0000166_APP_A673T_A10_17_C03  \\\n",
       "idx                                                               \n",
       "22:19263188-TC.Theta                                   0.017424   \n",
       "22:21354461-GA.Theta                                   0.856874   \n",
       "22:21384250-AG.Theta                                   0.101050   \n",
       "22:21984279-CA.Theta                                   0.880905   \n",
       "22:24481101-AG.Theta                                   0.030915   \n",
       "...                                                         ...   \n",
       "rs9625374.Theta                                        0.618050   \n",
       "rs9626059.Theta                                        0.911472   \n",
       "rs9628047.Theta                                        0.520268   \n",
       "rs999458.Theta                                         0.554496   \n",
       "variant.71844.Theta                                    0.941767   \n",
       "\n",
       "                      FS04821400_FO0000167_APP_A673T_B02_17_C04  \\\n",
       "idx                                                               \n",
       "22:19263188-TC.Theta                                   0.030915   \n",
       "22:21354461-GA.Theta                                   0.896709   \n",
       "22:21384250-AG.Theta                                   0.109888   \n",
       "22:21984279-CA.Theta                                   0.919169   \n",
       "22:24481101-AG.Theta                                   0.023189   \n",
       "...                                                         ...   \n",
       "rs9625374.Theta                                        0.568534   \n",
       "rs9626059.Theta                                        0.917925   \n",
       "rs9628047.Theta                                        0.537218   \n",
       "rs999458.Theta                                         0.539772   \n",
       "variant.71844.Theta                                    0.971319   \n",
       "\n",
       "                      FS04821401_FO0000168_APP_A673T_B11_17_C05  \\\n",
       "idx                                                               \n",
       "22:19263188-TC.Theta                                   0.026956   \n",
       "22:21354461-GA.Theta                                   0.903836   \n",
       "22:21384250-AG.Theta                                   0.090588   \n",
       "22:21984279-CA.Theta                                   0.942667   \n",
       "22:24481101-AG.Theta                                   0.010187   \n",
       "...                                                         ...   \n",
       "rs9625374.Theta                                        0.558752   \n",
       "rs9626059.Theta                                        0.952390   \n",
       "rs9628047.Theta                                        0.557735   \n",
       "rs999458.Theta                                         0.603856   \n",
       "variant.71844.Theta                                    0.953378   \n",
       "\n",
       "                      FS04821402_FO0000169_APP_A673T_C03_17_C06  \\\n",
       "idx                                                               \n",
       "22:19263188-TC.Theta                                   0.011431   \n",
       "22:21354461-GA.Theta                                   0.946666   \n",
       "22:21384250-AG.Theta                                   0.062786   \n",
       "22:21984279-CA.Theta                                   0.971814   \n",
       "22:24481101-AG.Theta                                   0.016286   \n",
       "...                                                         ...   \n",
       "rs9625374.Theta                                        0.603907   \n",
       "rs9626059.Theta                                        0.973589   \n",
       "rs9628047.Theta                                        0.506185   \n",
       "rs999458.Theta                                         0.628461   \n",
       "variant.71844.Theta                                    0.967243   \n",
       "\n",
       "                      FS04821403_FO0000170_APP_A673T_C04_17_C07  \\\n",
       "idx                                                               \n",
       "22:19263188-TC.Theta                                   0.021527   \n",
       "22:21354461-GA.Theta                                   0.937902   \n",
       "22:21384250-AG.Theta                                   0.094529   \n",
       "22:21984279-CA.Theta                                   0.899858   \n",
       "22:24481101-AG.Theta                                   0.017335   \n",
       "...                                                         ...   \n",
       "rs9625374.Theta                                        0.591012   \n",
       "rs9626059.Theta                                        0.954016   \n",
       "rs9628047.Theta                                        0.537496   \n",
       "rs999458.Theta                                         0.593603   \n",
       "variant.71844.Theta                                    0.944638   \n",
       "\n",
       "                      FS04821404_FO0000171_APP_A673T_D09_17_C08  \\\n",
       "idx                                                               \n",
       "22:19263188-TC.Theta                                   0.011655   \n",
       "22:21354461-GA.Theta                                   0.927664   \n",
       "22:21384250-AG.Theta                                   0.121504   \n",
       "22:21984279-CA.Theta                                   0.977350   \n",
       "22:24481101-AG.Theta                                   0.018646   \n",
       "...                                                         ...   \n",
       "rs9625374.Theta                                        0.579917   \n",
       "rs9626059.Theta                                        0.950417   \n",
       "rs9628047.Theta                                        0.575556   \n",
       "rs999458.Theta                                         0.595947   \n",
       "variant.71844.Theta                                    0.946361   \n",
       "\n",
       "                      FS04821405_FO0000172_APP_A673T_D12_17_C09  \\\n",
       "idx                                                               \n",
       "22:19263188-TC.Theta                                   0.035450   \n",
       "22:21354461-GA.Theta                                   0.946430   \n",
       "22:21384250-AG.Theta                                   0.117310   \n",
       "22:21984279-CA.Theta                                   0.914369   \n",
       "22:24481101-AG.Theta                                   0.020970   \n",
       "...                                                         ...   \n",
       "rs9625374.Theta                                        0.589297   \n",
       "rs9626059.Theta                                        0.937735   \n",
       "rs9628047.Theta                                        0.550700   \n",
       "rs999458.Theta                                         0.583897   \n",
       "variant.71844.Theta                                    0.959746   \n",
       "\n",
       "                      FS04821406_FO0000173_APP_A673T_F06_17_C10  \\\n",
       "idx                                                               \n",
       "22:19263188-TC.Theta                                   0.039059   \n",
       "22:21354461-GA.Theta                                   0.931566   \n",
       "22:21384250-AG.Theta                                   0.072148   \n",
       "22:21984279-CA.Theta                                   0.905627   \n",
       "22:24481101-AG.Theta                                   0.031749   \n",
       "...                                                         ...   \n",
       "rs9625374.Theta                                        0.626615   \n",
       "rs9626059.Theta                                        0.960297   \n",
       "rs9628047.Theta                                        0.554986   \n",
       "rs999458.Theta                                         0.585212   \n",
       "variant.71844.Theta                                    0.949609   \n",
       "\n",
       "                      FS04821407_FO0000174_APP_A673T_H08_17_C11  \\\n",
       "idx                                                               \n",
       "22:19263188-TC.Theta                                   0.029760   \n",
       "22:21354461-GA.Theta                                   0.867493   \n",
       "22:21384250-AG.Theta                                   0.136329   \n",
       "22:21984279-CA.Theta                                   0.905158   \n",
       "22:24481101-AG.Theta                                   0.016931   \n",
       "...                                                         ...   \n",
       "rs9625374.Theta                                        0.603600   \n",
       "rs9626059.Theta                                        0.951617   \n",
       "rs9628047.Theta                                        0.564009   \n",
       "rs999458.Theta                                         0.561027   \n",
       "variant.71844.Theta                                    0.956597   \n",
       "\n",
       "                      PositiveControl_1_NA_NA  \n",
       "idx                                            \n",
       "22:19263188-TC.Theta                 0.050559  \n",
       "22:21354461-GA.Theta                 0.524616  \n",
       "22:21384250-AG.Theta                 0.434891  \n",
       "22:21984279-CA.Theta                 0.607808  \n",
       "22:24481101-AG.Theta                 0.029535  \n",
       "...                                       ...  \n",
       "rs9625374.Theta                      0.019538  \n",
       "rs9626059.Theta                      0.920231  \n",
       "rs9628047.Theta                      0.518252  \n",
       "rs999458.Theta                       0.527736  \n",
       "variant.71844.Theta                  0.927436  \n",
       "\n",
       "[336 rows x 96 columns]"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Name_Theta_df[Name_Theta_df.isna(axis=1)]\n",
    "\n",
    "Name_Theta_df[Name_Theta_df.isnull().any(axis=1)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "ename": "NameError",
     "evalue": "name 'snps_list' is not defined",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mNameError\u001b[0m                                 Traceback (most recent call last)",
      "\u001b[0;32m/tmp/ipykernel_5611/2237056008.py\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m      1\u001b[0m \u001b[0;31m# Generate output report\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 2\u001b[0;31m \u001b[0;32mfor\u001b[0m \u001b[0msnp\u001b[0m \u001b[0;32min\u001b[0m \u001b[0msnps_list\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m      3\u001b[0m     \u001b[0mgeno_col\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0msnp\u001b[0m \u001b[0;34m+\u001b[0m \u001b[0;34m\".GType\"\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      4\u001b[0m     \u001b[0mtheta_col\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0msnp\u001b[0m \u001b[0;34m+\u001b[0m \u001b[0;34m\".Theta\"\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      5\u001b[0m     \u001b[0mr_col\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0msnp\u001b[0m \u001b[0;34m+\u001b[0m \u001b[0;34m\".R\"\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;31mNameError\u001b[0m: name 'snps_list' is not defined"
     ]
    }
   ],
   "source": [
    "# Generate output report\n",
    "for snp in snps_list:\n",
    "    geno_col = snp + \".GType\"\n",
    "    theta_col = snp + \".Theta\"\n",
    "    r_col = snp + \".R\"    \n",
    "\n",
    "    gtypes = list(cb_df[geno_col].unique())\n",
    "\n",
    "    snp_for_plot_df = cb_df[['IID', theta_col, r_col, geno_col]].copy()\n",
    "    snp_for_plot_df.columns = snp_for_plot_df.columns.str.replace(f'{snp}.', '', regex=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "\n",
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       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>idx</th>\n",
       "      <th>IID</th>\n",
       "      <th>1KG_22_19435270.GType</th>\n",
       "      <th>1KG_22_19766749.GType</th>\n",
       "      <th>1KG_22_24530438.GType</th>\n",
       "      <th>1KG_22_24909316.GType</th>\n",
       "      <th>1KG_22_26286764.GType</th>\n",
       "      <th>1KG_22_26298671.GType</th>\n",
       "      <th>1KG_22_30857665.GType</th>\n",
       "      <th>1KG_22_36681998.GType</th>\n",
       "      <th>1KG_22_38494134.GType</th>\n",
       "      <th>...</th>\n",
       "      <th>Variant61228.R</th>\n",
       "      <th>Variant61231.R</th>\n",
       "      <th>Variant61234.R</th>\n",
       "      <th>Variant61237.R</th>\n",
       "      <th>Variant61242.R</th>\n",
       "      <th>Variant61244.R</th>\n",
       "      <th>Variant61245.R</th>\n",
       "      <th>Variant61246.R</th>\n",
       "      <th>Variant61252.R</th>\n",
       "      <th>Variant61253.R</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>FS04821313_FO0000275_FUS_R495*_A01_17_A01</td>\n",
       "      <td>BB</td>\n",
       "      <td>BB</td>\n",
       "      <td>BB</td>\n",
       "      <td>BB</td>\n",
       "      <td>AA</td>\n",
       "      <td>AA</td>\n",
       "      <td>AA</td>\n",
       "      <td>AA</td>\n",
       "      <td>AA</td>\n",
       "      <td>...</td>\n",
       "      <td>0.430500</td>\n",
       "      <td>0.361874</td>\n",
       "      <td>0.540405</td>\n",
       "      <td>0.626420</td>\n",
       "      <td>0.957749</td>\n",
       "      <td>0.733668</td>\n",
       "      <td>0.795464</td>\n",
       "      <td>0.701761</td>\n",
       "      <td>0.470309</td>\n",
       "      <td>0.569939</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>FS04821314_FO0000152_MAPT_R317W_A08_17_B01</td>\n",
       "      <td>BB</td>\n",
       "      <td>BB</td>\n",
       "      <td>BB</td>\n",
       "      <td>BB</td>\n",
       "      <td>AA</td>\n",
       "      <td>AA</td>\n",
       "      <td>AA</td>\n",
       "      <td>AA</td>\n",
       "      <td>AA</td>\n",
       "      <td>...</td>\n",
       "      <td>0.415114</td>\n",
       "      <td>0.329952</td>\n",
       "      <td>0.549609</td>\n",
       "      <td>0.571324</td>\n",
       "      <td>0.932040</td>\n",
       "      <td>0.671134</td>\n",
       "      <td>0.730768</td>\n",
       "      <td>0.735666</td>\n",
       "      <td>0.476564</td>\n",
       "      <td>0.603078</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>FS04821315_FO0000163_MAPT_R317W_G09_17_B12</td>\n",
       "      <td>BB</td>\n",
       "      <td>BB</td>\n",
       "      <td>BB</td>\n",
       "      <td>BB</td>\n",
       "      <td>AA</td>\n",
       "      <td>AA</td>\n",
       "      <td>AA</td>\n",
       "      <td>AA</td>\n",
       "      <td>AA</td>\n",
       "      <td>...</td>\n",
       "      <td>0.379468</td>\n",
       "      <td>0.420835</td>\n",
       "      <td>0.541583</td>\n",
       "      <td>0.608452</td>\n",
       "      <td>0.976639</td>\n",
       "      <td>0.641460</td>\n",
       "      <td>0.726527</td>\n",
       "      <td>0.748987</td>\n",
       "      <td>0.439781</td>\n",
       "      <td>0.518233</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>FS04821316_FO0000176_ANG_K41I_A04_17_D01</td>\n",
       "      <td>BB</td>\n",
       "      <td>BB</td>\n",
       "      <td>BB</td>\n",
       "      <td>BB</td>\n",
       "      <td>AA</td>\n",
       "      <td>AA</td>\n",
       "      <td>AA</td>\n",
       "      <td>AA</td>\n",
       "      <td>AA</td>\n",
       "      <td>...</td>\n",
       "      <td>0.462127</td>\n",
       "      <td>0.387539</td>\n",
       "      <td>0.521502</td>\n",
       "      <td>0.639255</td>\n",
       "      <td>0.965216</td>\n",
       "      <td>0.699769</td>\n",
       "      <td>0.735392</td>\n",
       "      <td>0.791597</td>\n",
       "      <td>0.410290</td>\n",
       "      <td>0.626747</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>FS04821317_FO0000188_SNCB_P123H_B08_17_E01</td>\n",
       "      <td>BB</td>\n",
       "      <td>BB</td>\n",
       "      <td>BB</td>\n",
       "      <td>BB</td>\n",
       "      <td>AA</td>\n",
       "      <td>AA</td>\n",
       "      <td>AA</td>\n",
       "      <td>AA</td>\n",
       "      <td>AA</td>\n",
       "      <td>...</td>\n",
       "      <td>0.469232</td>\n",
       "      <td>0.366763</td>\n",
       "      <td>0.586054</td>\n",
       "      <td>0.579106</td>\n",
       "      <td>1.041958</td>\n",
       "      <td>0.677856</td>\n",
       "      <td>0.758849</td>\n",
       "      <td>0.712157</td>\n",
       "      <td>0.468440</td>\n",
       "      <td>0.582567</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>91</th>\n",
       "      <td>FS04821404_FO0000171_APP_A673T_D09_17_C08</td>\n",
       "      <td>BB</td>\n",
       "      <td>BB</td>\n",
       "      <td>BB</td>\n",
       "      <td>BB</td>\n",
       "      <td>AA</td>\n",
       "      <td>AA</td>\n",
       "      <td>AA</td>\n",
       "      <td>AA</td>\n",
       "      <td>AA</td>\n",
       "      <td>...</td>\n",
       "      <td>0.359078</td>\n",
       "      <td>0.360436</td>\n",
       "      <td>0.449827</td>\n",
       "      <td>0.581284</td>\n",
       "      <td>1.042775</td>\n",
       "      <td>0.702279</td>\n",
       "      <td>0.757134</td>\n",
       "      <td>0.718126</td>\n",
       "      <td>0.447970</td>\n",
       "      <td>0.575152</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>92</th>\n",
       "      <td>FS04821405_FO0000172_APP_A673T_D12_17_C09</td>\n",
       "      <td>BB</td>\n",
       "      <td>BB</td>\n",
       "      <td>BB</td>\n",
       "      <td>BB</td>\n",
       "      <td>AA</td>\n",
       "      <td>AA</td>\n",
       "      <td>AA</td>\n",
       "      <td>AA</td>\n",
       "      <td>AA</td>\n",
       "      <td>...</td>\n",
       "      <td>0.365155</td>\n",
       "      <td>0.359822</td>\n",
       "      <td>0.513683</td>\n",
       "      <td>0.557322</td>\n",
       "      <td>0.872211</td>\n",
       "      <td>0.649222</td>\n",
       "      <td>0.692903</td>\n",
       "      <td>0.726661</td>\n",
       "      <td>0.427236</td>\n",
       "      <td>0.530507</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>93</th>\n",
       "      <td>FS04821406_FO0000173_APP_A673T_F06_17_C10</td>\n",
       "      <td>BB</td>\n",
       "      <td>BB</td>\n",
       "      <td>BB</td>\n",
       "      <td>BB</td>\n",
       "      <td>AA</td>\n",
       "      <td>AA</td>\n",
       "      <td>AA</td>\n",
       "      <td>AA</td>\n",
       "      <td>AA</td>\n",
       "      <td>...</td>\n",
       "      <td>0.329993</td>\n",
       "      <td>0.388541</td>\n",
       "      <td>0.518266</td>\n",
       "      <td>0.577355</td>\n",
       "      <td>0.891683</td>\n",
       "      <td>0.711396</td>\n",
       "      <td>0.780114</td>\n",
       "      <td>0.710056</td>\n",
       "      <td>0.407510</td>\n",
       "      <td>0.513913</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>94</th>\n",
       "      <td>FS04821407_FO0000174_APP_A673T_H08_17_C11</td>\n",
       "      <td>BB</td>\n",
       "      <td>BB</td>\n",
       "      <td>BB</td>\n",
       "      <td>BB</td>\n",
       "      <td>AA</td>\n",
       "      <td>AA</td>\n",
       "      <td>AA</td>\n",
       "      <td>AA</td>\n",
       "      <td>AA</td>\n",
       "      <td>...</td>\n",
       "      <td>0.354541</td>\n",
       "      <td>0.322347</td>\n",
       "      <td>0.421428</td>\n",
       "      <td>0.515936</td>\n",
       "      <td>0.894079</td>\n",
       "      <td>0.712438</td>\n",
       "      <td>0.747326</td>\n",
       "      <td>0.663459</td>\n",
       "      <td>0.403457</td>\n",
       "      <td>0.479983</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>95</th>\n",
       "      <td>PositiveControl_1_NA_NA</td>\n",
       "      <td>BB</td>\n",
       "      <td>BB</td>\n",
       "      <td>BB</td>\n",
       "      <td>BB</td>\n",
       "      <td>AA</td>\n",
       "      <td>AA</td>\n",
       "      <td>AA</td>\n",
       "      <td>AA</td>\n",
       "      <td>AA</td>\n",
       "      <td>...</td>\n",
       "      <td>0.182542</td>\n",
       "      <td>0.116625</td>\n",
       "      <td>0.200661</td>\n",
       "      <td>0.187479</td>\n",
       "      <td>0.391974</td>\n",
       "      <td>0.271091</td>\n",
       "      <td>0.502401</td>\n",
       "      <td>0.301212</td>\n",
       "      <td>0.207442</td>\n",
       "      <td>0.140064</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>96 rows × 77986 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "idx                                         IID 1KG_22_19435270.GType  \\\n",
       "0     FS04821313_FO0000275_FUS_R495*_A01_17_A01                    BB   \n",
       "1    FS04821314_FO0000152_MAPT_R317W_A08_17_B01                    BB   \n",
       "2    FS04821315_FO0000163_MAPT_R317W_G09_17_B12                    BB   \n",
       "3      FS04821316_FO0000176_ANG_K41I_A04_17_D01                    BB   \n",
       "4    FS04821317_FO0000188_SNCB_P123H_B08_17_E01                    BB   \n",
       "..                                          ...                   ...   \n",
       "91    FS04821404_FO0000171_APP_A673T_D09_17_C08                    BB   \n",
       "92    FS04821405_FO0000172_APP_A673T_D12_17_C09                    BB   \n",
       "93    FS04821406_FO0000173_APP_A673T_F06_17_C10                    BB   \n",
       "94    FS04821407_FO0000174_APP_A673T_H08_17_C11                    BB   \n",
       "95                      PositiveControl_1_NA_NA                    BB   \n",
       "\n",
       "idx 1KG_22_19766749.GType 1KG_22_24530438.GType 1KG_22_24909316.GType  \\\n",
       "0                      BB                    BB                    BB   \n",
       "1                      BB                    BB                    BB   \n",
       "2                      BB                    BB                    BB   \n",
       "3                      BB                    BB                    BB   \n",
       "4                      BB                    BB                    BB   \n",
       "..                    ...                   ...                   ...   \n",
       "91                     BB                    BB                    BB   \n",
       "92                     BB                    BB                    BB   \n",
       "93                     BB                    BB                    BB   \n",
       "94                     BB                    BB                    BB   \n",
       "95                     BB                    BB                    BB   \n",
       "\n",
       "idx 1KG_22_26286764.GType 1KG_22_26298671.GType 1KG_22_30857665.GType  \\\n",
       "0                      AA                    AA                    AA   \n",
       "1                      AA                    AA                    AA   \n",
       "2                      AA                    AA                    AA   \n",
       "3                      AA                    AA                    AA   \n",
       "4                      AA                    AA                    AA   \n",
       "..                    ...                   ...                   ...   \n",
       "91                     AA                    AA                    AA   \n",
       "92                     AA                    AA                    AA   \n",
       "93                     AA                    AA                    AA   \n",
       "94                     AA                    AA                    AA   \n",
       "95                     AA                    AA                    AA   \n",
       "\n",
       "idx 1KG_22_36681998.GType 1KG_22_38494134.GType  ... Variant61228.R  \\\n",
       "0                      AA                    AA  ...       0.430500   \n",
       "1                      AA                    AA  ...       0.415114   \n",
       "2                      AA                    AA  ...       0.379468   \n",
       "3                      AA                    AA  ...       0.462127   \n",
       "4                      AA                    AA  ...       0.469232   \n",
       "..                    ...                   ...  ...            ...   \n",
       "91                     AA                    AA  ...       0.359078   \n",
       "92                     AA                    AA  ...       0.365155   \n",
       "93                     AA                    AA  ...       0.329993   \n",
       "94                     AA                    AA  ...       0.354541   \n",
       "95                     AA                    AA  ...       0.182542   \n",
       "\n",
       "idx Variant61231.R Variant61234.R Variant61237.R Variant61242.R  \\\n",
       "0         0.361874       0.540405       0.626420       0.957749   \n",
       "1         0.329952       0.549609       0.571324       0.932040   \n",
       "2         0.420835       0.541583       0.608452       0.976639   \n",
       "3         0.387539       0.521502       0.639255       0.965216   \n",
       "4         0.366763       0.586054       0.579106       1.041958   \n",
       "..             ...            ...            ...            ...   \n",
       "91        0.360436       0.449827       0.581284       1.042775   \n",
       "92        0.359822       0.513683       0.557322       0.872211   \n",
       "93        0.388541       0.518266       0.577355       0.891683   \n",
       "94        0.322347       0.421428       0.515936       0.894079   \n",
       "95        0.116625       0.200661       0.187479       0.391974   \n",
       "\n",
       "idx Variant61244.R Variant61245.R Variant61246.R Variant61252.R Variant61253.R  \n",
       "0         0.733668       0.795464       0.701761       0.470309       0.569939  \n",
       "1         0.671134       0.730768       0.735666       0.476564       0.603078  \n",
       "2         0.641460       0.726527       0.748987       0.439781       0.518233  \n",
       "3         0.699769       0.735392       0.791597       0.410290       0.626747  \n",
       "4         0.677856       0.758849       0.712157       0.468440       0.582567  \n",
       "..             ...            ...            ...            ...            ...  \n",
       "91        0.702279       0.757134       0.718126       0.447970       0.575152  \n",
       "92        0.649222       0.692903       0.726661       0.427236       0.530507  \n",
       "93        0.711396       0.780114       0.710056       0.407510       0.513913  \n",
       "94        0.712438       0.747326       0.663459       0.403457       0.479983  \n",
       "95        0.271091       0.502401       0.301212       0.207442       0.140064  \n",
       "\n",
       "[96 rows x 77986 columns]"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "clusterbuster_out"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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