Tutorial/TADGATE_usage.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "2b6ff25e",
   "metadata": {},
   "source": [
    "# Import packages"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "4e5a1fb4",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/dcdang/anaconda3/envs/TADGATE_test/lib/python3.8/site-packages/tqdm/auto.py:22: TqdmWarning: IProgress not found. Please update jupyter and ipywidgets. See https://ipywidgets.readthedocs.io/en/stable/user_install.html\n",
      "  from .autonotebook import tqdm as notebook_tqdm\n"
     ]
    }
   ],
   "source": [
    "import os\n",
    "import time\n",
    "import scipy\n",
    "import copy\n",
    "import pickle\n",
    "import torch\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "from tqdm import tqdm\n",
    "from scipy import signal\n",
    "import matplotlib.pyplot as plt\n",
    "import warnings\n",
    "warnings.filterwarnings('ignore')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "b337bedf",
   "metadata": {},
   "outputs": [],
   "source": [
    "import TADGATE"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "09596259",
   "metadata": {},
   "outputs": [],
   "source": [
    "from TADGATE import TADGATE_utils as TL\n",
    "from TADGATE import Plot_Function as PF\n",
    "from TADGATE import Call_TADs as CT\n",
    "from TADGATE import TADGATE_main"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "55bad54c",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "937ffa07",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Please download the data used in this tutorial from https://drive.google.com/drive/folders/1B6Hp3kUgmjkm-IIIQZ7A3WR3iwEgtb0O"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "df22b648",
   "metadata": {},
   "source": [
    "# Load Hi-C data"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "266168b3",
   "metadata": {},
   "source": [
    "## Load chromosome size of reference genome"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "270ba9a8",
   "metadata": {},
   "outputs": [],
   "source": [
    "# The users need to get the length of all chromosomes of the reference genome. We provide the chromosome size of hg19.\n",
    "# You can download the chromosome size of other reference or species from UCSC."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "f849b90f",
   "metadata": {},
   "outputs": [],
   "source": [
    "chrom_size_file = '/mnt/disk2/ddc/project/TADGATE/Data_for_packages/chrom_hg19_sizes.txt'\n",
    "chr_size = TL.load_chromosome_size(chrom_size_file)\n",
    "\n",
    "chrom_size_file_hg38 = '/mnt/disk2/ddc/project/TADGATE/Data_for_packages/chrom_hg38_sizes.txt'\n",
    "chr_size_hg38 = TL.load_chromosome_size(chrom_size_file_hg38)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "8aff28fa",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "3a64d735",
   "metadata": {},
   "source": [
    "## Load Hi-C contact maps"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2703b908",
   "metadata": {},
   "source": [
    "### Load dense or sparse Hi-C contact maps"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "ec9a4456",
   "metadata": {},
   "outputs": [],
   "source": [
    "cell_type = 'GM12878'\n",
    "resolution = 50000"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "f777dff4",
   "metadata": {},
   "outputs": [],
   "source": [
    "data_add_dense = '/mnt/disk2/ddc/project/TADGATE/Data_for_packages/GM12878_dense'\n",
    "data_add_sparse = '/mnt/disk2/ddc/project/TADGATE/Data_for_packages/GM12878_sparse'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "a29255af",
   "metadata": {},
   "outputs": [],
   "source": [
    "# We allow input in two forms of Hi-C contact map: \n",
    "# (1) N*N dense matrix, recording interactions between all bins. \n",
    "# (2) M*3 sparse matrix, recording the positions and values of non-zero interactions. Because the Hi-C matrix are \n",
    "# symmetric. Only the upper or lower triangular matrix need to be stored in the sparse matrix. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "a91af412",
   "metadata": {},
   "outputs": [],
   "source": [
    "data_add = data_add_dense"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "affc22a8",
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['GM12878_chr8_res_50000_dense.mat',\n",
       " 'GM12878_chr13_res_50000_dense.mat',\n",
       " 'GM12878_chr16_res_50000_dense.mat',\n",
       " 'GM12878_chrX_res_50000_dense.mat',\n",
       " 'GM12878_chr11_res_50000_dense.mat',\n",
       " 'GM12878_chr9_res_50000_dense.mat',\n",
       " 'GM12878_chr19_res_50000_dense.mat',\n",
       " 'GM12878_chr17_res_50000_dense.mat',\n",
       " 'GM12878_chr4_res_50000_dense.mat',\n",
       " 'GM12878_chr18_res_50000_dense.mat',\n",
       " 'GM12878_chr10_res_50000_dense.mat',\n",
       " 'GM12878_chr21_res_50000_dense.mat',\n",
       " 'GM12878_chr5_res_50000_dense.mat',\n",
       " 'GM12878_chr2_res_50000_dense.mat',\n",
       " 'GM12878_chr22_res_50000_dense.mat',\n",
       " 'GM12878_chr7_res_50000_dense.mat',\n",
       " 'GM12878_chr14_res_50000_dense.mat',\n",
       " 'GM12878_chr1_res_50000_dense.mat',\n",
       " 'GM12878_chr15_res_50000_dense.mat',\n",
       " 'GM12878_chr12_res_50000_dense.mat',\n",
       " 'GM12878_chr6_res_50000_dense.mat',\n",
       " 'GM12878_chr20_res_50000_dense.mat',\n",
       " 'GM12878_chr3_res_50000_dense.mat']"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Files = os.listdir(data_add)\n",
    "Files"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "4ce5f58b",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████| 25/25 [00:12<00:00,  2.08it/s]\n"
     ]
    }
   ],
   "source": [
    "hic_mat_all = {}\n",
    "for Chr in tqdm(chr_size.keys()):\n",
    "    if Chr in ['chrY', 'chrM']:\n",
    "        continue\n",
    "    file = cell_type + '_' + Chr + '_res_' + str(resolution) + '_dense.mat'\n",
    "    mat_file = data_add + '/' + file\n",
    "    chr_length = chr_size[Chr]\n",
    "    bin_name_use = TL.chr_cut(chr_length, Chr, resolution)\n",
    "    bin_num = len(bin_name_use)\n",
    "    mat_hic = TL.LoadHicMat(mat_file, bin_num, mat_type='dense')\n",
    "    # if sparse mat are used\n",
    "    #mat_hic = TL.LoadHicMat(mat_file, bin_num, mat_type='sparse', mat_half = True)\n",
    "    while np.max(mat_hic) <= 1000:\n",
    "        mat_hic = mat_hic * 10\n",
    "    while np.max(mat_hic) > 10000:\n",
    "        mat_hic = mat_hic * 0.1\n",
    "    hic_mat_all[Chr] = mat_hic"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "71815b0f",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "39abc434",
   "metadata": {},
   "source": [
    "### Load hic or mcool Hi-C contact maps"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "af30804d",
   "metadata": {},
   "outputs": [],
   "source": [
    "# We also allow input in .hic file produced by juicer tools or .mcool file produced by cooler,\n",
    "# Each file contains Hi-C data for all chromosomes at multiple resolutions.\n",
    "# The hicstraw and cooler package should be pre-installed."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "a1d3d30e",
   "metadata": {},
   "outputs": [],
   "source": [
    "def extract_mat_from_hic_or_mcool_file(input_file, resolution, target_chr_l, file_type, \n",
    "                                       data_type = 'observed', norm_type = 'NONE'):\n",
    "    hic_mat = {}\n",
    "    if file_type == 'mcool':\n",
    "        import cooler\n",
    "        cool_file = cooler.Cooler(input_file + '::/resolutions/' + str(resolution))\n",
    "        for Chr in target_chr_l:\n",
    "            cool_mat = cool_file.matrix(balance=False).fetch(Chr.split('r')[-1])\n",
    "            hic_mat[Chr] = cool_mat\n",
    "    if file_type == 'hic':\n",
    "        import hicstraw\n",
    "        hic_file = hicstraw.HiCFile(input_file)\n",
    "        #print('Genome:')\n",
    "        #print(hic_file.getGenomeID())\n",
    "        #print('Resolution')\n",
    "        #print(hic_file.getResolutions())\n",
    "        for chrom in hic_file.getChromosomes():\n",
    "            #print(chrom.name, chrom.length)\n",
    "            if 'chr' + chrom.name not in target_chr_l:\n",
    "                continue    \n",
    "            result = hicstraw.straw(data_type, norm_type, input_file_hic, chrom.name, chrom.name, \n",
    "                                    'BP', resolution) \n",
    "            bin_1_l = []\n",
    "            bin_2_l = []\n",
    "            count_l = []\n",
    "            for i in range(len(result)):\n",
    "                bin_1_l.append(result[i].binX)\n",
    "                bin_2_l.append(result[i].binY)\n",
    "                count_l.append(result[i].counts)\n",
    "            df_mat_sparse = pd.DataFrame()\n",
    "            df_mat_sparse['bin1'] = bin_1_l\n",
    "            df_mat_sparse['bin2'] = bin_2_l\n",
    "            df_mat_sparse['value'] = count_l\n",
    "            if (chrom.length / resolution) % resolution != 0:\n",
    "                bin_num = int(chrom.length / resolution) + 1\n",
    "            else:\n",
    "                bin_num = int(chrom.length / resolution)\n",
    "            df_mat_dense_chr = TL.get_dense_hic_mat(df_mat_sparse, length = bin_num, resolution = resolution)\n",
    "            hic_mat['chr' + chrom.name] = df_mat_dense_chr\n",
    "    return hic_mat"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "c8a3dffa",
   "metadata": {},
   "outputs": [],
   "source": [
    "# .hic and .mcool file for two single cell \n",
    "input_file_hic = '/mnt/disk2/ddc/project/TADGATE/Data_for_packages/GSM7682228_K562_cell_062.hic'\n",
    "input_file_cool = '/mnt/disk2/ddc/project/TADGATE/Data_for_packages/GSM7682483_GM12878_cell_213.mcool'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "94a98bfe",
   "metadata": {},
   "outputs": [],
   "source": [
    "target_chr_l = ['chr3']\n",
    "file_type = 'hic'\n",
    "hic_mat_K562_cell_062 = extract_mat_from_hic_or_mcool_file(input_file_hic, resolution, target_chr_l, file_type,\n",
    "                                                           data_type = 'observed', norm_type = 'NONE')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "2e7905f5",
   "metadata": {},
   "outputs": [],
   "source": [
    "target_chr_l = ['chr5']\n",
    "file_type = 'mcool'\n",
    "hic_mat_GM12878_cell_213 = extract_mat_from_hic_or_mcool_file(input_file_cool, resolution, target_chr_l, \n",
    "                                                              file_type)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "15bd38ec",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "c391e626",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "4cc536c4",
   "metadata": {},
   "source": [
    "# Run TADGATE"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5bba60a7",
   "metadata": {},
   "source": [
    "## Run model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 90,
   "id": "2f6a6282",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Set GPU name"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "5a38a05c",
   "metadata": {},
   "outputs": [],
   "source": [
    "device_gpu0 = torch.device('cuda:0' if torch.cuda.is_available() else 'cpu')\n",
    "device_gpu1 = torch.device('cuda:1' if torch.cuda.is_available() else 'cpu')\n",
    "device_gpu2 = torch.device('cuda:2' if torch.cuda.is_available() else 'cpu')\n",
    "device_gpu3 = torch.device('cuda:3' if torch.cuda.is_available() else 'cpu')\n",
    "\n",
    "device_cpu = torch.device('cpu')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "d74f7ba1",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Paramater settings: the meanings of paramaters can be found in function 'TADGATE_main.TADGATE_for_embedding'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "89042c7d",
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Help on function TADGATE_for_embedding in module TADGATE.TADGATE_main:\n",
      "\n",
      "TADGATE_for_embedding(hic_all, chr_size, resolution, graph_radius, split_size, device, layer_node1, layer_node2, lr, weight_decay, num_epoch, embed_attention=False, weight_use='No', weight_range=0, weight_rate=0, batch_use=False, num_batch_x=1, auto_expand=False, impute_func=False, impute_range=5, CNN_impute=False, RWR_impute=False, target_chr_l=[], scale_f=1, diag_cut=0, wd='all', save_model=False, seed=666, verbose=True, split_stop='')\n",
      "    Run TADGATE on all chromosomes.\n",
      "    :param hic_all:  dict, Hi-C contact maps for all chromosomes.\n",
      "    :param chr_size:  dict, chromosome sizes.\n",
      "    :param resolution:  int, Resolution of Hi-C contact map.\n",
      "    :param graph_radius:  int, Radius used to construct spatial network.\n",
      "    :param split_size:  int, Size of sub-matrices to split Hi-C contact maps into.\n",
      "    :param device:  str, Device to run TADGATE on.\n",
      "    :param layer_node1: int, number of nodes in first layer of autoencoder.\n",
      "    :param layer_node2: int, number of nodes in second layer of autoencoder.\n",
      "    :param lr:  float, Learning rate.\n",
      "    :param weight_decay: float, Weight decay.\n",
      "    :param num_epoch: int, Number of epochs to train TADGATE.\n",
      "    :param embed_attention: bool, whether to use attention mechanism in the embedding layer (second layer).\n",
      "    :param weight_use: str, Whether to use weight matrix or use different kind of weight. Choose from 'No', 'Fix', 'Auto'.\n",
      "    :param weight_range: int, the range near the diagonal to apply the weight matrix.\n",
      "    :param weight_rate:  float, the weight rate for the fixed weight matrix.\n",
      "    :param batch_use: bool, whether to use batch training.\n",
      "    :param num_batch_x: int, number of batch for batch training.\n",
      "    :param auto_expand:  bool, whether to expand the auto-learned weight rate.\n",
      "    :param impute_func: bool, whether to impute region near the diagnal of Hi-C contact map.\n",
      "    :param impute_range: int, the range near the diagonal to apply the impute function.\n",
      "    :param CNN_impute: bool or int, whether to use CNN to impute Hi-C contact map, if not False, use CNN_impute as padding size.\n",
      "    :param RWR_impute: bool or float, whether to use Restart random walk to impute Hi-C contact map. if not False, use RWR_impute as restart rate.\n",
      "    :param target_chr_l: list, List of chromosomes to run TADGATE on. If empty, run TADGATE on all chromosomes in hic_all.\n",
      "    :param scale_f: int, scale factor for node embedding scaling with dimension.\n",
      "    :param diag_cut: int, number of diagonals to cut inner. If not zero, diag_cut to wd will be zero. If zero, will use wd to cut out\n",
      "    :param wd:  int, number of diagonals to cut out, wd to window will be zero. window is determined by split_size and resolution.\n",
      "    :param seed: int, random seed.\n",
      "    :param verbose: bool, whether to print the training process.\n",
      "    :return: TADGATE_res_all: dict, TADGATE results for all chromosomes. For each chromosome,\n",
      "                ‘range’ for range of each split window, ‘mat_split’ for Hi-C contact map for each window,\n",
      "                ‘row_bad’ for bad rows for each window, ‘spatial_net’ for spatial network for each window,\n",
      "                ‘mat_mask’ for mask matrix or weight matrix,\n",
      "                ‘result’ for TADGATE results for each window.\n",
      "                Detials of ‘result’ are the same as res_all_record of TADGATE_specific_chr.\n",
      "\n"
     ]
    }
   ],
   "source": [
    "help(TADGATE_main.TADGATE_for_embedding)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "4a953793",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Paramaters\n",
    "graph_radius = 2\n",
    "split_size = 'all'\n",
    "device = device_gpu0 \n",
    "\n",
    "layer_node1 = 500\n",
    "layer_node2 = 100\n",
    "lr = 0.001\n",
    "weight_decay = 0.0001\n",
    "num_epoch = 500\n",
    "embed_attention = False\n",
    "\n",
    "weight_use = 'Fix'\n",
    "weight_rate = 0.3\n",
    "weight_range = int(10000000 / resolution)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "c55b347d",
   "metadata": {},
   "outputs": [],
   "source": [
    "target_chr_l = ['chr1', 'chr2', 'chr3', 'chr4', 'chr5']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "98fcf16c",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Run model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "ddadf8e5",
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "For chr1\n",
      "Hi-C map is splited into 1 sub-map\n",
      "Build spatial network...\n",
      "Get mask-matrix or weight-matrix...\n",
      "For No.0 sub-map\n",
      "Train TADGATE....\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████| 500/500 [00:31<00:00, 15.63it/s]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "For chr2\n",
      "Hi-C map is splited into 1 sub-map\n",
      "Build spatial network...\n",
      "Get mask-matrix or weight-matrix...\n",
      "For No.0 sub-map\n",
      "Train TADGATE....\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████| 500/500 [00:29<00:00, 16.97it/s]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "For chr3\n",
      "Hi-C map is splited into 1 sub-map\n",
      "Build spatial network...\n",
      "Get mask-matrix or weight-matrix...\n",
      "For No.0 sub-map\n",
      "Train TADGATE....\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████| 500/500 [00:20<00:00, 24.44it/s]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "For chr4\n",
      "Hi-C map is splited into 1 sub-map\n",
      "Build spatial network...\n",
      "Get mask-matrix or weight-matrix...\n",
      "For No.0 sub-map\n",
      "Train TADGATE....\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████| 500/500 [00:18<00:00, 26.42it/s]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "For chr5\n",
      "Hi-C map is splited into 1 sub-map\n",
      "Build spatial network...\n",
      "Get mask-matrix or weight-matrix...\n",
      "For No.0 sub-map\n",
      "Train TADGATE....\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████| 500/500 [00:17<00:00, 29.31it/s]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Total time 126.85149955749512s\n"
     ]
    }
   ],
   "source": [
    "TADGATE_res_all = TADGATE_main.TADGATE_for_embedding(hic_mat_all, chr_size, resolution, graph_radius, split_size,  device, layer_node1,\n",
    "                                                     layer_node2, lr, weight_decay, num_epoch, embed_attention = embed_attention, \n",
    "                                                     weight_use = weight_use, weight_range = weight_range, weight_rate = weight_rate,\n",
    "                                                     target_chr_l = target_chr_l)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "dc05870e",
   "metadata": {},
   "outputs": [],
   "source": [
    "Chr = 'chr1'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "8eaca254",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "dict_keys(['range', 'mat_split', 'row_bad', 'spatial_net', 'mat_mask', 'result'])"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "TADGATE_res_all[Chr].keys()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "8125d36e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "dict_keys(['loss', 'mat_imputed_sym', 'bin_rep', 'attention_map'])"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "TADGATE_res_all[Chr]['result'][0].keys()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "61987538",
   "metadata": {},
   "source": [
    "## Plot loss during training process"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "c74903ab",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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IMF94KBW4UGNCXmk1ooO7bsyfiKgjOhTwAQEB2L17N/R6Pby9vaFQKGyOf/XVV/Dx8enUAh2d2k2BsZF+SDtRjr2nKhjwROQwOhTwDz30ULvOW7Vq1TUV46zGR/lfCvgLWDAh8urfQETUDToU8GvWrEF4eDhGjhzJ8eYrtDzwtO90BRrNFigVDvWAMBH1UB0K+IULF2LdunUoKCjAgw8+iPvuu8+6rEBPNjhYAz8vFS7WmnD4TBVGR/DPhIik16Gu5ooVK1BcXIw///nP2LhxI3Q6He666y5s3bq1R/fo5XIZ4vv7AwB+OsnpkkTkGDo8lqBWqzFv3jxs27YNR48exdChQ/HYY48hIiICNTU1XVGjU7iJ69IQkYO5rsFiuVwOmUwGIQTMZnNn1eSUJgxoDvisM1UwNDRKXA0R0TUEvNFoxLp16zB16lQMHDgQOTk5eP/991FUVGR901NP1LeXJyIDvGC2CGTkc9kCIpJeh26yPvbYY0hJSYFOp8NDDz2EdevWWV/XR8BNAwJQcKEWe05dwLShrS+GRkTUXTr0Rie5XI6wsDCMHDmyzVf3OdJSAl31RqfW/HikBI/8KxORAV7Y9dTNXfqziKjnam+udagHf//997frnaw91bj+/lDIZSi4UIuzlXXo28tT6pKIqAfr8INOZJ/GXYkROl9kFlZiz8kLuHtsmNQlEVEPxkcuO9lNl2bTcD48EUmNAd/JWgJ+b/4FmC099+EvIpIeA76Txfb1hY/aDVV1jcg9p5e6HCLqwRjwncxNIbc+9LTjeJnE1RBRT8aA7wIJg5vfW7vtaKnElRBRT8aA7wKTowMhlwHHig04c7FO6nKIqIdiwHcBPy+Vdcng7cfYiyciaTDgu8i0Ic3DNAx4IpIKA76LtIzD7zt9Efp6ri5JRN2PAd9FIgK8MCDQG00WgdQ8zqYhou7HgO9CUy8N03yfUyxxJUTUEzHgu9DM2FAAwK7j5RymIaJux4DvQtHBPhgY5A2T2YKtuSVSl0NEPQwDvgvJZDLMGtEHAPBt1jmJqyGinoYB38XuuDRMk366AqWGBomrIaKehAHfxXR+nhgV3gtCABsPn5e6HCLqQRjw3WDWiOZe/IZDHKYhou7DgO8Gt8eEQqWQ48h5A5cQJqJuw4DvBn5eKkwfFgwAWLe/SOJqiKinYMB3k3ljdACA77LOo87UJHE1RNQTMOC7ybh+/gj390SNsQnfZfFmKxF1PUkDfvfu3Zg5cyZCQ0Mhk8nw7bff2hx/4IEHIJPJbLYZM2ZIU+x1kstluC8uHADwYVo+mswWiSsiIlcnacDX1tYiNjYWK1assHvOjBkzUFxcbN3WrVvXjRV2rnvHhcHfS4XCijqsP8gZNUTUtdyk/OGJiYlITExs8xy1Wo3g4OBuqqhrearc8Oik/njl+2P43x/zcHtsCDxVkv4VEJELc/gx+NTUVAQGBmLQoEFYuHAhKioq2jzfaDTCYDDYbI7kT/Hh6OPrgbJqI3YdL5e6HCJyYQ4d8DNmzMBnn32GHTt24LXXXkNaWhoSExNhNpvtfk9ycjK0Wq110+l03Vjx1bkrFbg9JgQA8H0ulxEmoq4jE0IIqYsAmhfm2rBhA2bPnm33nNOnT6N///7Yvn07pkyZ0uo5RqMRRqPR+tlgMECn00Gv10Oj0XR22dck95wet7+3Bwq5DFufnIioQG+pSyIiJ2IwGKDVaq+aaw7dg/+tfv36ISAgAKdOnbJ7jlqthkajsdkczbA+WkyJDoTZIrDsm2ypyyEiF+VUAX/27FlUVFQgJCRE6lKu29//MAxuchkOFFbiRGm11OUQkQuSNOBramqQlZWFrKwsAEBBQQGysrJQVFSEmpoaPP3008jIyMCvv/6KHTt2YNasWYiKisL06dOlLLtThGg9cEt0IADgHz/mSVwNEbkiSQP+wIEDGDlyJEaOHAkAWLJkCUaOHInnn38eCoUC2dnZuOOOOzBw4EAsWLAAo0aNwk8//QS1Wi1l2Z1m8dSBcJPLsPVIKbbwjU9E1Mkc5iZrV2nvzQipvLblOFam5iO2rxbfLZogdTlE5ARc8iarK1owIRIqhRyHz+rx5YEzUpdDRC6EAS+xAG81/mdKFADg5U1HcaHGeJXvICJqHwa8A1h4cxSGhmpQ3dCED1PzpS6HiFwEA94BKOQyLE4YCAD4ZE8BUvPKJK6IiFwBA95BTBkciHljwwAAL208ClMTlxMmouvDgHcQMpkMz94ajQBvFU5fqMV7O09KXRIROTkGvAPxcVfiudsGAwDe23kKh4oqJa6IiJwZA97B/GFkX9x5Qx8AwLJvclBvsr9yJhFRWxjwDmhZYjQCvNXIK63GX77NhYs/i0ZEXYQB74ACfdzx3ryRkMuAbw6e5QNQRHRNGPAOKr6/P5ZOGwQA+Ot3R3DkvF7iiojI2TDgHdjCSf1xS3QgTE0WLP4iC7XGJqlLIiInwoB3YHK5DG/8MQYB3mqcKK1B0tqDaDJzfjwRtQ8D3sH5e6vxyfzRcFfKkZpXjpc2HZW6JCJyEgx4JzBC54u35zavmf9ZeiFW7y2QuCIicgYMeCcxY1gwnpkRDQB4adNRbMo+L3FFROToGPBO5NFJ/XDfuDAIASz+Igs/nSyXuiQicmAMeCcik8nw4h3DcNvwEDSaBf7fvzLxy68XpS6LiBwUA97JKOQyvDk3FjcNCECdyYwHVu3HQa5ZQ0StYMA7IbWbAh//aTTi+/mj1mTG/E/34/CZKqnLIiIHw4B3Uh4qBT59YDTGRvih2tiEP326jyFPRDYY8E7MU+WGVQ+OwejwXjA0NOGef2bg5/wLUpdFRA6CAe/kvNVuWPPQWNzYv3m45oFVv2DrkRKpyyIiB8CAdwHeajesemAMpg0JgslswcJ/Z+KtbSe4rAFRD8eAdxHuSgU+uPcGzBurg0UA7+w4iTtX/oydx0ulLo2IJMKAdyFuCjmS74zBO3ePgI+7G7LP6vHQmgNI2V8kdWlEJAEGvAuaNaIPti+ZhDtiQwEAy9bnIOnzg9hfwIeiiHoSBryLCtK44527R2DWiOaQ35xTjLs+Ssd/DnMNG6KeggHvwmQyGV6bE4NHJ/WHUiEDAPzPukOY93EG6kx8eQiRq2PAuzh3pQLLEqOx+X9usu5LP12BB1f/grOVdRJWRkRdjQHfQwwM8kH236Zh6pAgAMC+gouY9EYqFq09CH19o8TVEVFXkAkhhNRFdCWDwQCtVgu9Xg+NRiN1OQ7hdHkNntuQi/TTFdZ9/Xp74eGb+mHuaB3kcpmE1RHR1bQ31yTtwe/evRszZ85EaGgoZDIZvv32W5vjQgg8//zzCAkJgYeHBxISEnDy5ElpinUh/Xp7Y90j4/DJ/aMR4K0CAJwur8Xy9Tn4r4/Sca6qXuIKiagzSBrwtbW1iI2NxYoVK1o9/vrrr+Pdd9/Fhx9+iH379sHLywvTp09HQ0NDN1fqmhKGBGH/swlY9cBo9PH1AABkFlZiwms78clPp1FvMktcoTTW7ivCuzvYkSDn5zBDNDKZDBs2bMDs2bMBNPfeQ0NDsXTpUjz11FMAAL1ej6CgIKxZswZ33313u67LIZr225VXhkWfH0TtpWDv28sDyxKjkTgsBIoeMmzTZLYg6rkfAAC7nroZkQFeEldE9HtOMUTTloKCApSUlCAhIcG6T6vVIi4uDunp6RJW5romDwrE/ucSsGTqQPh5qXC2sh6L1h7CHe/vwabs83CQvkCXqqg1Wb/uqf+DIdfhJnUB9pSUNK+IGBQUZLM/KCjIeqw1RqMRRqPR+tlgMHRNgS7KS+2G/5kyAPfHh2PVngJ8tPs0jpw3YNHaQ3hZcxSTBvbGbTGheOqrw7jzhj5YnjhY6pI7Vanh8vAfnxUgZ+ewPfhrlZycDK1Wa910Op3UJTklX08VlkwbhB8XT8SiyVHwVClQajDiywNnMX/VfpRXG/FR2ml88UsRzJa2e/amJgu+zjwLfZ3jT8cs0V8O+OoGBjw5N4cN+ODgYABAaantaoilpaXWY61Zvnw59Hq9dTtz5kyX1unqwv298NT0Qfh52S3407hwqBS2/2Se+SYHt/wjFc9tyMF3Wedw/jczcExNFry/8ySe+uowln6V1Y2VX5vS6iv+99fg+L+QiNrisEM0kZGRCA4Oxo4dOzBixAgAzcMt+/btw8KFC+1+n1qthlqt7qYqew5fTxVenj0Mz946GFuOFGNwiAbfZxfjw92nUVhRh8KKIny+rwhqNzkeGB+BCH8v7D5RjtS8ctQ3No9lbz9Whpyzegzvq0XS5wex+2Q5/j57GO6IDcV5fQNCte6QyaS9mVt2xRBNjZE9eHJuks6iqampwalTpwAAI0eOxJtvvonJkyfDz88PYWFheO211/Dqq6/i//7v/xAZGYm//vWvyM7OxtGjR+Hu7t6un8FZNF3rbGUdDhVVYeuREvx4tBSmpqu/ZGRQkA/ySqt/t//524fgwfERbYZ8ebURz3yTjVuiA3HfuPDrqn3vqQt4f+cp/P0Pw9C/tzcA4M9fH8aXB85az3lkYj88e6tr3Wcg59feXJM04FNTUzF58uTf7Z8/fz7WrFkDIQReeOEFfPzxx6iqqsKECRPwwQcfYODAge3+GQz47iOEwH8On8dPJy8gNa8cF2ouD3eE+3uisOLqa988OD4CJ0trMDDIB8/PHIIVu07hP1nn8cn80dD5eeKuj9Ktyx7fNjwETyYMwIAgn3bVd7HWBJWbHIUVtYgK9Magv2wBAAzvo8XGxycAAO5ftR+7T5TbfN9Ls4Zi3tgwKBUOO6JJPYxTBHx3YMBLw9RkQXVDI7QeSuSc02N4Hy2+PHAWx4oN2Hm8rMNPy8plzS80ae1/CKPCe+GO2FDMvzHCZr/ZInDg14sYFd4L+vpG3PxGKqovDbv894RIfLKnAADgJpfh5CuJ+Cy9EC/850irP/+FmUPw4PjIDtVM1FXam2sOOwZPzk3lJoe/d/O9kJFhvQAA98SFAQBeBtBotiBlfxHi+wegodGM29/b0+b1LAJ2h38yCyuRWVgJL7UbSg0NCNa4Y0SYL5K/P4btx8oAAHeO7GMNdwDWcAeAJovAV5ln7YY7ABw9b4DZIiR94KvO1IRdx8txS3QgPFQK636zRcDUZLHZRwSwB08OorzaiGPFBuw4VoqtR0pRUWtEo1lAJgOk/Bc6ISoAe05dAAAEeKvw3aIJ1mUdrqZE34BAH/U1L96We04Pd6UcUYE+EEIg4c005JfX4tlbo/HIxP7W8+76MB0ny6qR9ufJ0LgrAQCHz1QhKtAbXmr24VyR0z/JSj1Lbx81Jg7sjRdnDUPGs1Nw8pVbse/ZKdjyxER8cv9ojI3ww8uzh2FxwkB8szAeI3S+dq/lrrz+f9Zul0L5tpgQ674LNSY8uz4HFVfcW7BYBM5X1eN/t+ZhyPNb8Pm+QtSbzPgu6xzGJe/AyrR867m7T5Rj/cHLN3DbcrHWhNvf24OEN3fDbBEouFCL/PJaAEDG6Ys25+3/9SIq6xpxsLASALBqTwFmrdiL17Ycv/Y/AHIJ/PVODitI444gjTsGBfsgYYjtE83fJo2HoaER724/iVsGB2LHsTJEB/vgv0brUGpowMOfHYC/lwqPTY7CR2n5OFFag6KL7XvByYt3DMX0ocE4W1mHMD9Pm2NpJ8ox6u/bsWhyFB4cH4EHVv+CnHN66/HnNuTilc3HUHdpmYM3tubh4Zv6QS5rvoELNK/NP6yPts0aTpfXWL8uMTSg4EKt9XOxvgFzP0rH7JF9EKy9PJussq55mYWXNh0FAHyWXoiXZg1rV5vJNXGIhnqMqjoTfsgtwczYUBRX1ePDtNPwUitw4NdKmMwWPH/7EPTp5WGdMgk0zwy655/7UNdoxvShQXh9S16n1DJrRCjujw/HqHC/Vo9/l3UOT6RkAQCWTB2I7LN6bD9W+rvzBgZ540Tp5V8GfxoXjn9lFAIAVAo5TryS2Cn1kmPhLJpLGPDUWepNZjz19WFszi627gvSqBGi9UDWmapruuaH992AGcNCsPfUBbz6w3GMCu+FJ6YMwL8yCvHmthPXXXPO36bB59K4PLkOBvwlDHjqbEIIHCyqhEUAI3W+cFPI8dWBMzhRWg0/L7V17HtCVAAW3RKFuz/OaPN6Pu5uXbbuzTMzojFpYG8MCXX8f/sWi0BFrQm9ffgk+tUw4C9hwFN3K6qow2fpvyJpchR6ealw+EwVPt59GoOCfTA/PgKFF2tx98cZ1nH6tvh5qXDxiiWMh/fR4nxVPYxNFutSChp3N9wxIhThfl5IPVGGvacqbK7hrpRj0+MTEBXYvgfCpFBvMuO+T/chs7ASb88dgfj+/tiUXYx/7j6Nf/93HKICva9+kR6EAX8JA54cVb3JDFOTBV8cKMKu4+U4VmJAVV0jRoX3al6KIS4cWk8lyquNmPtxOqYODsLyS8smGBoaUXihDgE+KshlMgRpmm+2WiwCv1bUos70+2cLvNVuqDE2IVTrjvP6BgRp1JgyOAjD+2hRom/A5OhA1DQ04YZwX3goFV26LlDG6QqE+3siRNs85XTd/iIsX59jPa5SyGEyX37u4S+3DcaCCZGSr1XkKBjwlzDgqaf6PqcYn/x0Gtln9Wi6ypLOV1K5ydFktmBwiAYR/l7wUisQrPWAr4cS2kubu1KBXl5KyCBDgI8KaoUCnmqF3eUchBCQyWSoNTZh+7FSPJGSBU+VAk9MGYAmi8CHaflXHaZ6YsoAKBUy3D02DAHePXsYhwF/CQOeerp6kxkny6pRUWPCj0dLkF9ei+qGJgRp1Ki9NMxz9LzB+qrGayWXNf9yUMrl8PNWocksEKRR40KNCcX6egiBDv2iaUsfXw8MCPLGDWG94KaQYVw/fzSYzIgK8oaXyg1qNzncXHjtIAb8JQx4oquzWASqG5rgoVIgr6QaaqUc+wsuoqHRjHqTGSWGBujrG62bsdGCCzVGyGTNrznsaIr0C/BC/0BvbDt6eern7TEh6O2jRtaZKhwqqgIAxPbV4vBZvZ2r2KdUyKD1UEEhB3w9VPBSK+ChUsBDqYCHyg2eyubPnioF1G4KKN1kUCnkzb+gFHKoFHIo3eRQKWTWfcpLx1VXfK28dFx1aZ2klnP19Y2QyYDglqEzgU5d5oJr0RBRu8nlMmg9m6dTDu/b/BDWwHau0tlktsAigKp6E4yNFhibzLhY2wiFvPmhrN7eani7u+FCjQkR/p5Iz6/ALYMD4e+lRl5JNQYEeaOwohZ9e3nCXdm8nk5RRR1+rajFxIG9IYTAz/kVyD6rR0xfLb45eBbeajecq6xHtbEJTWYLTpbVwM9LhaKLdRACaDQL62qmpQZjW+V3KbWbHE0WAbNFwM9LBSEElAo5PFQKqBRymC0Cob4e+Pd/x3XJz2cPnohcRq2xqfl/FTUmVDc0wSIEquoaUWtqQkOjGXWm5q3e1GT92mS2oLHJgkazBSazBaYm0fy1zb7LXzdecdx0aZ8QzUNULSNQbnIZBHDV11kCQJifJ3b/+ffLpreFPXgi6nFaFlfz9Ou+aBNCWIO8ySJgEQIeSgVMZgtK9Ubr2kgVtSYo5DI0mi1oaDTD2GiBm0IOL3XXrQLKgCciug4ymQxuiubxdbcrslrtpkCY/+W1jAI17XsLXWdy3dvMREQ9HAOeiMhFMeCJiFwUA56IyEUx4ImIXBQDnojIRTHgiYhclMvPg295UNdgMEhcCRFR52jJs6stRODyAV9dXQ0A0Ol0EldCRNS5qqurodXaf4G7y69FY7FYcP78efj4+HToZQEGgwE6nQ5nzpxxyTVsXL19gOu30dXbB7h+G6+1fUIIVFdXIzQ0FHK5/ZF2l+/By+Vy9O3b95q/X6PRuOQ/rBau3j7A9dvo6u0DXL+N19K+tnruLXiTlYjIRTHgiYhcFAPeDrVajRdeeAFqtWu++9HV2we4fhtdvX2A67exq9vn8jdZiYh6KvbgiYhcFAOeiMhFMeCJiFwUA56IyEUx4FuxYsUKREREwN3dHXFxcdi/f7/UJbXb7t27MXPmTISGhkImk+Hbb7+1OS6EwPPPP4+QkBB4eHggISEBJ0+etDnn4sWLuPfee6HRaODr64sFCxagpqamG1thX3JyMsaMGQMfHx8EBgZi9uzZyMvLszmnoaEBSUlJ8Pf3h7e3N+bMmYPS0lKbc4qKinDbbbfB09MTgYGBePrpp9HU1NSdTWnVypUrERMTY33wJT4+Hj/88IP1uDO3rTWvvvoqZDIZnnzySes+Z2/j3/72N8hkMpstOjraerxb2yfIRkpKilCpVGLVqlXiyJEj4uGHHxa+vr6itLRU6tLa5fvvvxfPPfecWL9+vQAgNmzYYHP81VdfFVqtVnz77bfi8OHD4o477hCRkZGivr7ees6MGTNEbGysyMjIED/99JOIiooS8+bN6+aWtG769Oli9erVIjc3V2RlZYlbb71VhIWFiZqaGus5jz76qNDpdGLHjh3iwIEDYty4ceLGG2+0Hm9qahLDhg0TCQkJ4tChQ+L7778XAQEBYvny5VI0ycZ//vMfsXnzZnHixAmRl5cnnn32WaFUKkVubq4Qwrnb9lv79+8XERERIiYmRjzxxBPW/c7exhdeeEEMHTpUFBcXW7fy8nLr8e5sHwP+N8aOHSuSkpKsn81mswgNDRXJyckSVnVtfhvwFotFBAcHizfeeMO6r6qqSqjVarFu3TohhBBHjx4VAMQvv/xiPeeHH34QMplMnDt3rttqb6+ysjIBQKSlpQkhmtujVCrFV199ZT3n2LFjAoBIT08XQjT/EpTL5aKkpMR6zsqVK4VGoxFGo7F7G9AOvXr1Ep988olLta26uloMGDBAbNu2TUyaNMka8K7QxhdeeEHExsa2eqy728chmiuYTCZkZmYiISHBuk8ulyMhIQHp6ekSVtY5CgoKUFJSYtM+rVaLuLg4a/vS09Ph6+uL0aNHW89JSEiAXC7Hvn37ur3mq9Hr9QAAPz8/AEBmZiYaGxtt2hgdHY2wsDCbNg4fPhxBQUHWc6ZPnw6DwYAjR450Y/VtM5vNSElJQW1tLeLj412qbUlJSbjtttts2gK4zt/fyZMnERoain79+uHee+9FUVERgO5vn8svNtYRFy5cgNlstvmDBYCgoCAcP35coqo6T0lJCQC02r6WYyUlJQgMDLQ57ubmBj8/P+s5jsJiseDJJ5/E+PHjMWzYMADN9atUKvj6+tqc+9s2tvZn0HJMajk5OYiPj0dDQwO8vb2xYcMGDBkyBFlZWU7fNgBISUnBwYMH8csvv/zumCv8/cXFxWHNmjUYNGgQiouL8eKLL+Kmm25Cbm5ut7ePAU9OKykpCbm5udizZ4/UpXSqQYMGISsrC3q9Hl9//TXmz5+PtLQ0qcvqFGfOnMETTzyBbdu2wd3dXepyukRiYqL165iYGMTFxSE8PBxffvklPDw8urUWDtFcISAgAAqF4nd3tEtLSxEcHCxRVZ2npQ1ttS84OBhlZWU2x5uamnDx4kWH+jNYtGgRNm3ahF27dtksBx0cHAyTyYSqqiqb83/bxtb+DFqOSU2lUiEqKgqjRo1CcnIyYmNj8c4777hE2zIzM1FWVoYbbrgBbm5ucHNzQ1paGt599124ubkhKCjI6dv4W76+vhg4cCBOnTrV7X+HDPgrqFQqjBo1Cjt27LDus1gs2LFjB+Lj4yWsrHNERkYiODjYpn0GgwH79u2zti8+Ph5VVVXIzMy0nrNz505YLBbExcV1e82/JYTAokWLsGHDBuzcuRORkZE2x0eNGgWlUmnTxry8PBQVFdm0MScnx+YX2bZt26DRaDBkyJDuaUgHWCwWGI1Gl2jblClTkJOTg6ysLOs2evRo3Hvvvdavnb2Nv1VTU4P8/HyEhIR0/99hh28Ru7iUlBShVqvFmjVrxNGjR8UjjzwifH19be5oO7Lq6mpx6NAhcejQIQFAvPnmm+LQoUOisLBQCNE8TdLX11d89913Ijs7W8yaNavVaZIjR44U+/btE3v27BEDBgxwmGmSCxcuFFqtVqSmptpMQ6urq7Oe8+ijj4qwsDCxc+dOceDAAREfHy/i4+Otx1umoU2bNk1kZWWJLVu2iN69ezvENLtly5aJtLQ0UVBQILKzs8WyZcuETCYTP/74oxDCudtmz5WzaIRw/jYuXbpUpKamioKCArF3716RkJAgAgICRFlZmRCie9vHgG/Fe++9J8LCwoRKpRJjx44VGRkZUpfUbrt27RIAfrfNnz9fCNE8VfKvf/2rCAoKEmq1WkyZMkXk5eXZXKOiokLMmzdPeHt7C41GIx588EFRXV0tQWt+r7W2ARCrV6+2nlNfXy8ee+wx0atXL+Hp6Sn+8Ic/iOLiYpvr/PrrryIxMVF4eHiIgIAAsXTpUtHY2NjNrfm9hx56SISHhwuVSiV69+4tpkyZYg13IZy7bfb8NuCdvY1z584VISEhQqVSiT59+oi5c+eKU6dOWY93Z/u4XDARkYviGDwRkYtiwBMRuSgGPBGRi2LAExG5KAY8EZGLYsATEbkoBjwRkYtiwBNJLDU1FTKZ7HfrkxBdLwY8EZGLYsATEbkoBjz1eBaLBcnJyYiMjISHhwdiY2Px9ddfA7g8fLJ582bExMTA3d0d48aNQ25urs01vvnmGwwdOhRqtRoRERH4xz/+YXPcaDTimWeegU6ng1qtRlRUFD799FObczIzMzF69Gh4enrixhtv/N3LxIk67DrX1SFyen//+99FdHS02LJli8jPzxerV68WarVapKamWhdvGzx4sPjxxx9Fdna2uP3220VERIQwmUxCCCEOHDgg5HK5eOmll0ReXp5YvXq18PDwsFkA7a677hI6nU6sX79e5Ofni+3bt4uUlBQhxOUF4uLi4kRqaqo4cuSIuOmmm2xexEx0LRjw1KM1NDQIT09P8fPPP9vsX7BggZg3b541fFvCWIjm1TY9PDzEF198IYQQ4p577hFTp061+f6nn35aDBkyRAghRF5engAgtm3b1moNLT9j+/bt1n2bN28WAGyWcSbqKA7RUI926tQp1NXVYerUqfD29rZun332GfLz863nXfnCFz8/PwwaNAjHjh0DABw7dgzjx4+3ue748eNx8uRJmM1mZGVlQaFQYNKkSW3WEhMTY/06JCQEAH73di2ijuA7WalHq6mpAQBs3rwZffr0sTmmVqttQv5atfc9nEql0vq1TCYD0Hx/gOhasQdPPdqQIUOgVqtRVFSEqKgom02n01nPy8jIsH5dWVmJEydOYPDgwQCAwYMHY+/evTbX3bt3LwYOHAiFQoHhw4fDYrG4zIuzyXmwB089mo+PD5566iksXrwYFosFEyZMgF6vx969e6HRaBAeHg4AeOmll+Dv74+goCA899xzCAgIwOzZswEAS5cuxZgxY/Dyyy9j7ty5SE9Px/vvv48PPvgAABAREYH58+fjoYcewrvvvovY2FgUFhairKwMd911l1RNp55A6psARFKzWCzi7bffFoMGDRJKpVL07t1bTJ8+XaSlpVlvgG7cuFEMHTrU+hrHw4cP21zj66+/FkOGDBFKpVKEhYWJN954w+Z4fX29WLx4sfVVblFRUWLVqlVCiMs3WSsrK63nt7xTt6CgoKubTy6Mr+wjakNqaiomT56MyspK+Pr6Sl0OUYdwDJ6IyEUx4ImIXBSHaIiIXBR78ERELooBT0TkohjwREQuigFPROSiGPBERC6KAU9E5KIY8ERELooBT0TkohjwREQu6v8DUGy8GFkzRbsAAAAASUVORK5CYII=",
      "text/plain": [
       "<Figure size 400x300 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "PF.draw_loss_record(TADGATE_res_all[Chr]['result'][0]['loss'], )"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "96082dcb",
   "metadata": {},
   "source": [
    "## Plot comparison of original and imputed Hi-C contact map, attention map"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "52809fc3",
   "metadata": {},
   "outputs": [],
   "source": [
    "Chr = 'chr2'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "fca768cf",
   "metadata": {},
   "outputs": [],
   "source": [
    "mat_hic = copy.deepcopy(hic_mat_all[Chr])\n",
    "mat_imputed = copy.deepcopy(TADGATE_res_all[Chr]['result'][0]['mat_imputed_sym'])\n",
    "mat_att = copy.deepcopy(TADGATE_res_all[Chr]['result'][0]['attention_map'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "06403ec5",
   "metadata": {},
   "outputs": [],
   "source": [
    "bin_name_l = list(TADGATE_res_all[Chr]['mat_split'][0].obs_names)\n",
    "mat_list = [mat_hic, mat_imputed, mat_att]\n",
    "mat_para_list = [{'color': 'Reds', 'range':[10, 90], 'diag': False, 'net': False, 'value_type':'no-real'}, \n",
    "                 {'color': 'Reds', 'range':[0, 90], 'diag': False, 'net': False, 'value_type':'no-real'},\n",
    "                {'color': 'coolwarm', 'range':[0, 0.25], 'diag': True, 'net': False, 'value_type':'real'}]\n",
    "title_l = ['', 'Imputed map', 'Attention map']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "c603f0e1",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x700 with 6 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "st = 221 - 30\n",
    "ed = 221 + 30\n",
    "ori = 'h'\n",
    "fgsize = (12, 7)\n",
    "PF.draw_multi_mat_compare(st, ed, mat_list, mat_para_list, bin_name_l, Chr, resolution, fgsize = fgsize, title_l = title_l,\n",
    "                          bin_size = 20, save_name = '', ori = ori)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "549455b4",
   "metadata": {},
   "source": [
    "# Call TADs based on TADGATE results"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "27eda1f4",
   "metadata": {},
   "outputs": [],
   "source": [
    "# If Mclust are used, the R_HOME and R_USER need to be specified in advance. \n",
    "# If you don't use Mclust for clustering, we provide k-means as an alternative way, set cluster_method='K-means' in CT.TADGATE_call_TADs\n",
    "# Thus, the number of clusters are decided by paramater \"exp_length\".\n",
    "os.environ['R_HOME'] = \"/home/dcdang/anaconda3/envs/Renv/lib/R\"\n",
    "os.environ['R_USER'] = '/home/dcdang/anaconda3/envs/TADGATE/lib/python3.8/site-packages/rpy2'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "58e950ff",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Paramater settings: the meanings of paramaters can be found in function 'CT.TADGATE_call_TADs'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "9d4e9127",
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Help on function TADGATE_call_TADs in module TADGATE.Call_TADs:\n",
      "\n",
      "TADGATE_call_TADs(TADGATE_embed_all, chr_size, resolution, bd_weight_list=[1, 1, 1, 1], cluster_method='Mclust', window_range=5000000, wd_ci=5, wd_p=-1, dist=3, pvalue_cut=0.05, exp_length=500000, length_cut=3, contact_fold_cut=2, zero_ratio_cut=0.3, expand_check=1, filter_method='strict', target_chr_l=[])\n",
      "    Get the TADs based on the TADGATE embedding and attention map\n",
      "    :param TADGATE_embed_all:  dict, the TADGATE embedding and attention map for all chromosomes\n",
      "    :param chr_size: dict, the chromosome size for all chromosomes\n",
      "    :param resolution: int, the resolution of the Hi-C contact map\n",
      "    :param bd_weight_list: list, the weight list for different boundary score, [w_ori_CI, w_imp_CI, w_att_valley, w_clt_bd]\n",
      "    :param cluster_method: str, 'Mclust', 'K-means' or 'None', the clustering method used for bin clustering\n",
      "    :param window_range: int, the window size used for clustering, we split the genome into seperated windows and perform clustering in each window\n",
      "    :param wd_ci: int, the size of the diamond matrix, used in calculate contrast index\n",
      "    :param wd_p: int, the size of the diamond matrix, used in calculate contrast p-value, if set -1, use wd_ci to calculate p-value\n",
      "    :param dist: int, the distance range used to call CI peak, attention valley or boundary peak\n",
      "    :param pvalue_cut: float, the contrast p-value cut-off for boundary filtering\n",
      "    :param exp_length: int, the expected length of the domain\n",
      "    :param length_cut: int, the length cut-off for domain, below this cut-off, it will be considered as boundary\n",
      "    :param contact_fold_cut: float, the fold cut-off when comparing domain mean contact with the background,\n",
      "    :param zero_ratio_cut: float, the ratio cut-off of zero bins in the domain, above this cut-off, it will be considered as gap\n",
      "    :param expand_check: int, the expand range used to check whether the boundary peak can pass p-value cut-off\n",
      "    :param filter_method: str, 'strict' or 'relax', decide whether add p-value valley below 0.5 to candidate boundary\n",
      "    :param target_chr_l: list, the target chromosome list, if empty, all chromosomes will be used\n",
      "    :return: TADGATE_tads_mclust: dict, the TADs and boundary score profile for all target chromosomes.\n",
      "            \"TADs\" for the TADs range and type, \"cluster_bin_lb\" for the bin label after clustering and\n",
      "            it is set to -1 if no clustering is performed, \"bin_vote_bd_score\" for the final boundary score profile,\n",
      "            \"bin_domain_label\" for the domain label of each bin, \"CI_original\" for the contrast index of the original Hi-C map,\n",
      "            \"CI_imputed\" for the contrast index of the imputed Hi-C map, \"pvalue_original\" for the contrast p-value of the original\n",
      "            Hi-C map, \"pvalue_imputed\" for the contrast p-value of the imputed Hi-C map,  \"att_profile\" for the smoothed attention\n",
      "            profile, \"run_time\" for the running time of the whole process\n",
      "\n"
     ]
    }
   ],
   "source": [
    "help(CT.TADGATE_call_TADs)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "ef7f0df7",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Paramaters\n",
    "bd_weight_list = [1.5, 1.5, 1, 1]\n",
    "cluster_method = 'Mclust'\n",
    "window_range = 5000000\n",
    "wd_ci = 5\n",
    "wd_p = 5\n",
    "dist = 3\n",
    "pvalue_cut = 0.05\n",
    "exp_length = 500000\n",
    "length_cut = 3"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "2cec0db0",
   "metadata": {},
   "outputs": [],
   "source": [
    "target_chr_l = ['chr1', 'chr2', 'chr3', 'chr4', 'chr5']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "b9952242",
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "For chr1\n",
      "For sub-matrix 0...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "R[write to console]: Package 'mclust' version 6.0.1\n",
      "Type 'citation(\"mclust\")' for citing this R package in publications.\n",
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "20% bins done!\n",
      "20% bins done!\n",
      "20% bins done!\n",
      "20% bins done!\n",
      "Running time 17.761696815490723s\n",
      "For chr2\n",
      "For sub-matrix 0...\n",
      "20% bins done!\n",
      "20% bins done!\n",
      "20% bins done!\n",
      "20% bins done!\n",
      "Running time 16.554702281951904s\n",
      "For chr3\n",
      "For sub-matrix 0...\n",
      "20% bins done!\n",
      "20% bins done!\n",
      "20% bins done!\n",
      "20% bins done!\n",
      "Running time 13.355533361434937s\n",
      "For chr4\n",
      "For sub-matrix 0...\n",
      "20% bins done!\n",
      "20% bins done!\n",
      "20% bins done!\n",
      "20% bins done!\n",
      "Running time 13.133927345275879s\n",
      "For chr5\n",
      "For sub-matrix 0...\n",
      "20% bins done!\n",
      "20% bins done!\n",
      "20% bins done!\n",
      "20% bins done!\n",
      "Running time 12.057604551315308s\n"
     ]
    }
   ],
   "source": [
    "TADGATE_tads_all = CT.TADGATE_call_TADs(TADGATE_res_all, chr_size, resolution, bd_weight_list, \n",
    "                                        cluster_method, window_range, wd_ci, wd_p, dist, pvalue_cut, \n",
    "                                        exp_length, length_cut = 3, contact_fold_cut = 2, zero_ratio_cut = 0.3, \n",
    "                                        target_chr_l = target_chr_l)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "id": "960f0791",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "dict_keys(['TADs', 'cluster_bin_lb', 'bin_vote_bd_score', 'bin_domain_label', 'CI_original', 'CI_imputed', 'pvalue_original', 'pvalue_imputed', 'att_profile', 'run_time'])"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "TADGATE_tads_all['chr1'].keys()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "c329f2ed",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "9eb566ae",
   "metadata": {},
   "source": [
    "## Draw TADs identified by TADGATE"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "id": "578b56e4",
   "metadata": {},
   "outputs": [],
   "source": [
    "Chr = 'chr2'\n",
    "mat_hic = copy.deepcopy(TADGATE_res_all[Chr]['mat_split'][0].X)\n",
    "mat_imputed = copy.deepcopy(TADGATE_res_all[Chr]['result'][0]['mat_imputed_sym'])\n",
    "mat_att = copy.deepcopy(TADGATE_res_all[Chr]['result'][0]['attention_map'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "id": "32239022",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Extract TADs of chr2\n",
    "df_tad_res = TADGATE_tads_all[Chr]['TADs'][0]\n",
    "df_tad_res_only = df_tad_res[df_tad_res['type'] == 'domain']\n",
    "df_tad_res_only = df_tad_res_only.reset_index(drop = True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "id": "5389af07",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Extract multiple score profile calculated by TADGATE\n",
    "bin_vote_bd_score = TADGATE_tads_all[Chr]['bin_vote_bd_score'][0]\n",
    "CI_value_ori = TADGATE_tads_all[Chr]['CI_original'][0]\n",
    "pvalue_ori = TADGATE_tads_all[Chr]['pvalue_original'][0]\n",
    "CI_value_imp = TADGATE_tads_all[Chr]['CI_imputed'][0]\n",
    "pvalue_imp = TADGATE_tads_all[Chr]['pvalue_imputed'][0]\n",
    "att_profile_smooth = TADGATE_tads_all[Chr]['att_profile'][0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "id": "b8b60a70",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Find CI peaks or attention valleys\n",
    "dist = 3\n",
    "CI_peak_ori = signal.find_peaks(CI_value_ori, distance=dist)[0]\n",
    "CI_peak_imp = signal.find_peaks(CI_value_imp, distance=dist)[0]\n",
    "Att_valley = signal.find_peaks(-np.array(att_profile_smooth), distance=dist)[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "id": "c45bf3d8",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_value_multi = pd.DataFrame()\n",
    "df_value_multi['ori_pvalue'] = pvalue_ori\n",
    "df_value_multi['ori_CI'] = CI_value_ori\n",
    "df_value_multi['imp_pvalue'] = pvalue_imp\n",
    "df_value_multi['imp_CI'] = CI_value_imp\n",
    "df_value_multi['bin_vote_bd_score'] = bin_vote_bd_score\n",
    "df_value_multi['attention'] = att_profile_smooth"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "id": "e8b22d83",
   "metadata": {},
   "outputs": [],
   "source": [
    "value_peak_multi = {}\n",
    "value_peak_multi['ori_CI'] = CI_peak_ori\n",
    "value_peak_multi['imp_CI'] = CI_peak_imp\n",
    "value_peak_multi['attention'] = Att_valley"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "id": "b1bb41a0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 500x800 with 5 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Original Hi-C, TADs, original CI and original p-value\n",
    "st = 3500\n",
    "ed = 3560\n",
    "start_bin = 0\n",
    "TAD_l = TL.get_tad_list_in_target_ranges(st, ed, df_tad_res_only, resolution, start_bin, pos_type='bin')\n",
    "#TAD_l = [] \n",
    "value_l = [ 'ori_pvalue', 'ori_CI',]\n",
    "track_cut = [0.05, '']\n",
    "#value_peak_multi = ''\n",
    "save_name = ''\n",
    "PF.draw_map_multi_CI(mat_hic, Chr, st, ed, bin_name_l, df_value_multi, value_l, value_peak_multi, \n",
    "                     resolution, save_name = save_name, track_cut = track_cut,  bin_size = 10, \n",
    "                     TAD_l = TAD_l, color_multi = True, h_range = (10, 90), fgsize=(5, 8))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "id": "9945a4ef",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 500x800 with 5 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Imputed Hi-C, TADs, imputed CI and imputed p-value\n",
    "st = 3500\n",
    "ed = 3560\n",
    "start_bin = 0\n",
    "TAD_l = TL.get_tad_list_in_target_ranges(st, ed, df_tad_res_only, resolution, start_bin, pos_type='bin')\n",
    "#TAD_l = [] \n",
    "value_l = [ 'imp_pvalue', 'imp_CI',]\n",
    "track_cut = [0.05, '']\n",
    "#value_peak_multi = ''\n",
    "save_name = ''\n",
    "PF.draw_map_multi_CI(mat_imputed, Chr, st, ed, bin_name_l, df_value_multi, value_l, value_peak_multi, \n",
    "                     resolution, save_name = save_name, track_cut=track_cut, bin_size = 10, \n",
    "                     TAD_l = TAD_l, color_multi = True, h_range = (10, 90), fgsize=(5, 8))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "id": "d9ad1509",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 500x800 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Imputed Hi-C, TADs, attention\n",
    "st = 3500\n",
    "ed = 3560\n",
    "start_bin = 0\n",
    "TAD_l = TL.get_tad_list_in_target_ranges(st, ed, df_tad_res_only, resolution, start_bin, pos_type='bin')\n",
    "#TAD_l = [] \n",
    "value_l = ['attention']\n",
    "#value_peak_multi = ''\n",
    "save_name = ''\n",
    "PF.draw_map_multi_CI(mat_imputed, Chr, st, ed, bin_name_l, df_value_multi, value_l, value_peak_multi, \n",
    "                     resolution, save_name = save_name, track_cut = [''], bin_size = 10, \n",
    "                     TAD_l = TAD_l, color_multi = True, h_range = (10, 90), fgsize=(5, 8))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "id": "3a789fe6",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 500x800 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Imputed Hi-C, TADs, bin_vote_bd_score\n",
    "st = 3500\n",
    "ed = 3560\n",
    "start_bin = 0\n",
    "TAD_l = TL.get_tad_list_in_target_ranges(st, ed, df_tad_res_only, resolution, start_bin, pos_type='bin')\n",
    "#TAD_l = [] \n",
    "value_l = ['bin_vote_bd_score']\n",
    "#value_peak_multi = ''\n",
    "save_name = ''\n",
    "PF.draw_map_multi_CI(mat_imputed, Chr, st, ed, bin_name_l, df_value_multi, value_l, value_peak_multi, \n",
    "                     resolution, save_name = save_name, track_cut = [''], bin_size = 10, \n",
    "                     TAD_l = TAD_l, color_multi = True, h_range = (10, 90), fgsize=(5, 8))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "59423e96",
   "metadata": {},
   "source": [
    "## Draw attention vallys and attention peaks aggregrated Hi-C map"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "id": "91b50702",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 400x500 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Attention peak\n",
    "expand = 8\n",
    "pos_type = 'attention peak'\n",
    "map_type = 'Hi-C'\n",
    "dist = 5\n",
    "mat_combine, vec_combine, count_combine = PF.get_attention_valley_peak_nearby_map(TADGATE_res_all, TADGATE_tads_all, \n",
    "                                                                                  expand, pos_type, map_type, dist)\n",
    "\n",
    "mat_combine_mean = mat_combine / count_combine\n",
    "vec_combine_mean = vec_combine / count_combine\n",
    "mat_color = 'Reds'\n",
    "fgsize = (4, 5)\n",
    "save_name = ''\n",
    "PF.draw_map_profile(map_type, pos_type, mat_combine_mean, vec_combine_mean, resolution, mat_color,\n",
    "                    fgsize, save_name = '', tick_adj=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "id": "f7caf67b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 400x500 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Attention valley\n",
    "expand = 8\n",
    "pos_type = 'attention valley'\n",
    "map_type = 'Hi-C'\n",
    "dist = 5\n",
    "mat_combine, vec_combine, count_combine = PF.get_attention_valley_peak_nearby_map(TADGATE_res_all, TADGATE_tads_all, \n",
    "                                                                                  expand, pos_type, map_type, dist)\n",
    "\n",
    "mat_combine_mean = mat_combine / count_combine\n",
    "vec_combine_mean = vec_combine / count_combine\n",
    "mat_color = 'Blues'\n",
    "fgsize = (4, 5)\n",
    "save_name = ''\n",
    "PF.draw_map_profile(map_type, pos_type, mat_combine_mean, vec_combine_mean, resolution, mat_color,\n",
    "                 fgsize, save_name = '', tick_adj=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "f392db86",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "934089ce",
   "metadata": {},
   "source": [
    "## Draw TADs and bin embeddings learned by TADGATE"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "id": "8ca0f584",
   "metadata": {},
   "outputs": [],
   "source": [
    "embed_all = {}\n",
    "embed_all['TADGATE'] = TADGATE_res_all\n",
    "\n",
    "tads_res = {}\n",
    "tads_res['TADGATE'] = TADGATE_tads_all"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "id": "725104c8",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "19\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x420 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "Chr = 'chr1'\n",
    "st = 2250\n",
    "ed = 2297\n",
    "#st = 1253\n",
    "#ed = 1300\n",
    "method_rep = 'TADGATE'\n",
    "method = 'TADGATE'\n",
    "fgsize = (10, 4.2)\n",
    "save_name = ''\n",
    "for random_state in range(19, 20):\n",
    "    bin_lb, TAD_l, df_bin_scatter_use, color_use = PF.hic_tad_and_bin_rep_compare(random_state, Chr, st, ed, hic_mat_all, resolution, tads_res, embed_all, method_rep, method, \n",
    "                                                                                  rd_method = 'UMAP', rd_dim = True, fgsize = fgsize, col_num = 2, arrow_draw = False, \n",
    "                                                                                  save_name = save_name)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c7daf368",
   "metadata": {},
   "source": [
    "# Apply TADGATE to sparse Hi-C contact maps of tissues"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5427339e",
   "metadata": {},
   "source": [
    "## For Lung"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "id": "56f8d44c",
   "metadata": {},
   "outputs": [],
   "source": [
    "data_add_tissue = '/mnt/disk2/ddc/project/TADGATE/Data_for_packages' "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "id": "5bd50b81",
   "metadata": {},
   "outputs": [],
   "source": [
    "cell_type = 'Lung'\n",
    "resolution = 40000\n",
    "Chr = 'chr2'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "id": "357ca300",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Load Hi-c data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "id": "cf0d6fbf",
   "metadata": {},
   "outputs": [],
   "source": [
    "hic_mat_lung = {}\n",
    "mat_file = data_add_tissue + '/' + 'Lung_chr2_40kb_iced.mat'\n",
    "chr_length = chr_size[Chr]\n",
    "bin_name_use = TL.chr_cut(chr_length, Chr, resolution)\n",
    "bin_num = len(bin_name_use)\n",
    "mat_hic = TL.LoadHicMat(mat_file, bin_num, mat_type='dense')\n",
    "while np.max(mat_hic) <= 1000:\n",
    "    mat_hic = mat_hic * 10\n",
    "#while np.max(mat_hic) > 10000:\n",
    "    #mat_hic = mat_hic * 0.1\n",
    "hic_mat_lung[Chr] = mat_hic"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "id": "5d96606f",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Run TADGATE"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "3acc4f22",
   "metadata": {},
   "outputs": [],
   "source": [
    "# We suggest adjusting the mode of weight_use as well as weight_rate value for data with varying quality"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "id": "414b5f49",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Paramaters\n",
    "graph_radius = 2\n",
    "split_size = 'all'\n",
    "device = device_gpu0 \n",
    "\n",
    "layer_node1 = 500\n",
    "layer_node2 = 100\n",
    "lr = 0.001\n",
    "weight_decay = 0.0001\n",
    "num_epoch = 500\n",
    "embed_attention = False\n",
    "\n",
    "weight_use = 'Fix'\n",
    "weight_rate = 2.5\n",
    "weight_range = int(10000000 / resolution)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "id": "382b89dc",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "For chr2\n",
      "Hi-C map is splited into 1 sub-map\n",
      "Build spatial network...\n",
      "Get mask-matrix or weight-matrix...\n",
      "For No.0 sub-map\n",
      "Train TADGATE....\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████| 500/500 [00:43<00:00, 11.48it/s]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Total time 47.002543926239014s\n"
     ]
    }
   ],
   "source": [
    "TADGATE_res_lung = TADGATE_main.TADGATE_for_embedding(hic_mat_lung, chr_size, resolution, graph_radius, split_size,  device, layer_node1,\n",
    "                                                      layer_node2, lr, weight_decay, num_epoch, embed_attention = embed_attention, \n",
    "                                                      weight_use = weight_use, weight_range = weight_range, weight_rate = weight_rate,\n",
    "                                                      target_chr_l = [])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "id": "0d0143b3",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Call TADs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "id": "3c205b53",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Paramaters\n",
    "bd_weight_list = [1.5, 1.5, 1, 1]\n",
    "cluster_method = 'Mclust'\n",
    "window_range = 4000000\n",
    "wd_ci = 5\n",
    "wd_p = 5\n",
    "dist = 3\n",
    "pvalue_cut = 0.03\n",
    "exp_length = 400000\n",
    "length_cut = 3"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "id": "645142a9",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "For chr2\n",
      "For sub-matrix 0...\n",
      "20% bins done!\n",
      "20% bins done!\n",
      "20% bins done!\n",
      "20% bins done!\n",
      "Running time 21.341269731521606s\n"
     ]
    }
   ],
   "source": [
    "TADGATE_tads_lung = CT.TADGATE_call_TADs(TADGATE_res_lung, chr_size, resolution, bd_weight_list, \n",
    "                                         cluster_method, window_range, wd_ci, wd_p, dist, pvalue_cut, \n",
    "                                         exp_length, length_cut = 3, contact_fold_cut = 2, zero_ratio_cut = 0.3, \n",
    "                                         target_chr_l = [])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 85,
   "id": "edf027f8",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Compare original and imputed maps"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "id": "ae4c90f1",
   "metadata": {},
   "outputs": [],
   "source": [
    "mat_hic = copy.deepcopy(TADGATE_res_lung[Chr]['mat_split'][0].X)\n",
    "mat_imputed = copy.deepcopy(TADGATE_res_lung[Chr]['result'][0]['mat_imputed_sym'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "id": "8094ae44",
   "metadata": {},
   "outputs": [],
   "source": [
    "st = 1380\n",
    "ed = 1450\n",
    "mat_hic_whole, mat_imputed_whole, mat_combine_whole = PF.get_hic_map_original_and_imputed_compare(st, ed, mat_hic, mat_imputed, \n",
    "                                                                                                  QN = False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "id": "945bd668",
   "metadata": {},
   "outputs": [],
   "source": [
    "bin_name_l = list(TADGATE_res_lung[Chr]['mat_split'][0].obs_names)\n",
    "mat_list = [mat_hic_whole, mat_imputed_whole, mat_combine_whole]\n",
    "mat_para_list = []\n",
    "for i in range(3):\n",
    "    mat_para_list.append({'color': 'Reds', 'range':[0, 0.3], 'diag': False, 'net': False, 'value_type':'real', \n",
    "                          'tad_color':'#317FBA', 'tad_upper':True, 'tad_lower':False, 'norm_mat':False})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "id": "d80e59eb",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_tad_res = TADGATE_tads_lung[Chr]['TADs'][0]\n",
    "df_tad_res_only = df_tad_res[df_tad_res['type'] == 'domain']\n",
    "df_tad_res_only = df_tad_res_only.reset_index(drop = True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "id": "40c19062",
   "metadata": {},
   "outputs": [],
   "source": [
    "start_bin = 0\n",
    "tad_list_all = [[], []]\n",
    "TAD_l = TL.get_tad_list_in_target_ranges(st, ed, df_tad_res_only, resolution, start_bin, pos_type='bin')\n",
    "tad_list_all.append(TAD_l)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "id": "22d97154",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1500x400 with 6 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fgsize = (15, 4)\n",
    "col_num = 3\n",
    "title_l = ['', 'Imputed', 'Comparison']\n",
    "tad_list_l = tad_list_all\n",
    "bar_label = True\n",
    "save_name = ''\n",
    "PF.draw_multi_mat_compare_multi_row_with_TADs(st, ed, mat_list, mat_para_list, tad_list_l, bin_name_l, Chr, resolution, col_num,\n",
    "                                             title_name_l=title_l, fgsize=fgsize, bin_size=20, save_name=save_name, ori='h', \n",
    "                                             bar_label = bar_label)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "142d0a6e",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "417fe588",
   "metadata": {},
   "source": [
    "## For Psoas"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 83,
   "id": "90c50a0a",
   "metadata": {},
   "outputs": [],
   "source": [
    "cell_type = 'Psoas'\n",
    "resolution = 40000\n",
    "Chr = 'chr1'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 84,
   "id": "5141a210",
   "metadata": {},
   "outputs": [],
   "source": [
    "hic_mat_psoas = {}\n",
    "mat_file = data_add_tissue + '/' + 'Psoas_chr1_40kb_iced.mat'\n",
    "chr_length = chr_size[Chr]\n",
    "bin_name_use = TL.chr_cut(chr_length, Chr, resolution)\n",
    "bin_num = len(bin_name_use)\n",
    "mat_hic = TL.LoadHicMat(mat_file, bin_num, mat_type='dense')\n",
    "while np.max(mat_hic) <= 1000:\n",
    "    mat_hic = mat_hic * 10\n",
    "#while np.max(mat_hic) > 10000:\n",
    "    #mat_hic = mat_hic * 0.1\n",
    "hic_mat_psoas[Chr] = mat_hic"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 85,
   "id": "65c7fad3",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Run TADGATE"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 86,
   "id": "0a41139f",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Paramaters\n",
    "graph_radius = 2\n",
    "split_size = 'all'\n",
    "device = device_gpu0 \n",
    "\n",
    "layer_node1 = 500\n",
    "layer_node2 = 100\n",
    "lr = 0.001\n",
    "weight_decay = 0.0001\n",
    "num_epoch = 500\n",
    "embed_attention = False\n",
    "\n",
    "weight_use = 'Fix'\n",
    "weight_rate = 3.5\n",
    "weight_range = int(10000000 / resolution)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 87,
   "id": "8a311bf5",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "For chr1\n",
      "Hi-C map is splited into 1 sub-map\n",
      "Build spatial network...\n",
      "Get mask-matrix or weight-matrix...\n",
      "For No.0 sub-map\n",
      "Train TADGATE....\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████| 500/500 [00:52<00:00,  9.53it/s]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Total time 55.8348331451416s\n"
     ]
    }
   ],
   "source": [
    "TADGATE_res_psoas= TADGATE_main.TADGATE_for_embedding(hic_mat_psoas, chr_size, resolution, graph_radius, split_size,  device, layer_node1,\n",
    "                                                      layer_node2, lr, weight_decay, num_epoch, embed_attention = embed_attention, \n",
    "                                                      weight_use = weight_use, weight_range = weight_range, weight_rate = weight_rate,\n",
    "                                                      target_chr_l = [])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 97,
   "id": "40e5284a",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Call TADs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 88,
   "id": "75730f7c",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Paramaters\n",
    "bd_weight_list = [1.5, 1.5, 1, 1]\n",
    "cluster_method = 'Mclust'\n",
    "window_range = 4000000\n",
    "wd_ci = 5\n",
    "wd_p = 5\n",
    "dist = 3\n",
    "pvalue_cut = 0.03\n",
    "exp_length = 400000\n",
    "length_cut = 3"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 89,
   "id": "77da9a53",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "For chr1\n",
      "For sub-matrix 0...\n",
      "20% bins done!\n",
      "20% bins done!\n",
      "20% bins done!\n",
      "20% bins done!\n",
      "Running time 21.269355058670044s\n"
     ]
    }
   ],
   "source": [
    "TADGATE_tads_psoas = CT.TADGATE_call_TADs(TADGATE_res_psoas, chr_size, resolution, bd_weight_list, \n",
    "                                         cluster_method, window_range, wd_ci, wd_p, dist, pvalue_cut, \n",
    "                                         exp_length, length_cut = 3, contact_fold_cut = 2, zero_ratio_cut = 0.3, \n",
    "                                         target_chr_l = [])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 100,
   "id": "cb3ee87d",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Compare original and imputed maps"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 90,
   "id": "fd663813",
   "metadata": {},
   "outputs": [],
   "source": [
    "mat_hic = copy.deepcopy(TADGATE_res_psoas[Chr]['mat_split'][0].X)\n",
    "mat_imputed = copy.deepcopy(TADGATE_res_psoas[Chr]['result'][0]['mat_imputed_sym'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 91,
   "id": "d0b008c2",
   "metadata": {},
   "outputs": [],
   "source": [
    "st = 4550\n",
    "ed = 4620\n",
    "mat_hic_whole, mat_imputed_whole, mat_combine_whole = PF.get_hic_map_original_and_imputed_compare(st, ed, mat_hic, mat_imputed, \n",
    "                                                                                                  QN = False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 92,
   "id": "3b9f5c8a",
   "metadata": {},
   "outputs": [],
   "source": [
    "bin_name_l = list(TADGATE_res_psoas[Chr]['mat_split'][0].obs_names)\n",
    "mat_list = [mat_hic_whole, mat_imputed_whole, mat_combine_whole]\n",
    "mat_para_list = []\n",
    "for i in range(3):\n",
    "    mat_para_list.append({'color': 'Reds', 'range':[0, 0.45], 'diag': False, 'net': False, 'value_type':'real', \n",
    "                          'tad_color':'#317FBA', 'tad_upper':True, 'tad_lower':False, 'norm_mat':False})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 93,
   "id": "6b75f0e2",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_tad_res = TADGATE_tads_psoas[Chr]['TADs'][0]\n",
    "df_tad_res_only = df_tad_res[df_tad_res['type'] == 'domain']\n",
    "df_tad_res_only = df_tad_res_only.reset_index(drop = True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 94,
   "id": "4ab4bdeb",
   "metadata": {},
   "outputs": [],
   "source": [
    "start_bin = 0\n",
    "tad_list_all = [[], []]\n",
    "TAD_l = TL.get_tad_list_in_target_ranges(st, ed, df_tad_res_only, resolution, start_bin, pos_type='bin')\n",
    "tad_list_all.append(TAD_l)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 95,
   "id": "f6922526",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1500x400 with 6 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fgsize = (15, 4)\n",
    "col_num = 3\n",
    "title_l = ['', 'Imputed', 'Comparison']\n",
    "tad_list_l = tad_list_all\n",
    "bar_label = True\n",
    "save_name = ''\n",
    "PF.draw_multi_mat_compare_multi_row_with_TADs(st, ed, mat_list, mat_para_list, tad_list_l, bin_name_l, Chr, resolution, col_num,\n",
    "                                             title_name_l=title_l, fgsize=fgsize, bin_size=20, save_name=save_name, ori='h', \n",
    "                                             bar_label = bar_label)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "3f050a58",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "114cc85b",
   "metadata": {},
   "source": [
    "# Apply TADGATE to single cell Hi-C contact map"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9291f808",
   "metadata": {},
   "source": [
    "## For GSM7682228 K562 cell 062"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 106,
   "id": "af2f0bf8",
   "metadata": {},
   "outputs": [],
   "source": [
    "resolution = 50000"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 107,
   "id": "389ef139",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Paramaters\n",
    "graph_radius = 2\n",
    "split_size = 'all'\n",
    "device = device_gpu0 \n",
    "diag_cut = 0\n",
    "\n",
    "layer_node1 = 500\n",
    "layer_node2 = 100\n",
    "lr = 0.001\n",
    "weight_decay = 0.0001\n",
    "num_epoch = 500\n",
    "embed_attention = False\n",
    "\n",
    "weight_use = 'Fix'\n",
    "weight_rate = 1.5\n",
    "weight_range = int(10000000 / resolution)\n",
    "\n",
    "impute_func = True\n",
    "impute_range = 5\n",
    "CNN_impute = False\n",
    "RWR_impute = False"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 108,
   "id": "3fd51ae7",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Paramaters for TADs\n",
    "#cluster_method = 'Mclust'\n",
    "cluster_method = 'K-means'\n",
    "window_range = 5000000\n",
    "wd_ci = 5\n",
    "wd_p = 3\n",
    "dist = 5\n",
    "pvalue_cut = 0.2\n",
    "filter_method = 'relax2'\n",
    "\n",
    "exp_length = 500000\n",
    "length_cut = 3\n",
    "bd_weight_list = [1.5, 1.5, 1, 1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 109,
   "id": "cca6f9ae",
   "metadata": {},
   "outputs": [],
   "source": [
    "target_chr_l_use = ['chr3']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 110,
   "id": "19f0ded9",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "For chr3\n",
      "Hi-C map is splited into 1 sub-map\n",
      "Build spatial network...\n",
      "Get mask-matrix or weight-matrix...\n",
      "For No.0 sub-map\n",
      "Train TADGATE....\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████| 500/500 [00:20<00:00, 24.86it/s]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Total time 21.810965538024902s\n"
     ]
    }
   ],
   "source": [
    "TADGATE_res_single_cell = TADGATE_main.TADGATE_for_embedding(hic_mat_K562_cell_062, chr_size_hg38, \n",
    "                                                             resolution, graph_radius, split_size,  \n",
    "                                                             device, layer_node1,layer_node2, lr, \n",
    "                                                             weight_decay, num_epoch, \n",
    "                                                             embed_attention = embed_attention, \n",
    "                                                             weight_use = weight_use, \n",
    "                                                             weight_range = weight_range, \n",
    "                                                             weight_rate = weight_rate,\n",
    "                                                             impute_func=impute_func, \n",
    "                                                             impute_range=impute_range, \n",
    "                                                             CNN_impute=CNN_impute, \n",
    "                                                             RWR_impute=RWR_impute, \n",
    "                                                             target_chr_l = target_chr_l_use)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 111,
   "id": "7f111442",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "For chr3\n",
      "For sub-matrix 0...\n",
      "20% bins done!\n",
      "20% bins done!\n",
      "20% bins done!\n",
      "20% bins done!\n",
      "Running time 33.841689586639404s\n"
     ]
    }
   ],
   "source": [
    "TADGATE_tads_all = CT.TADGATE_call_TADs(TADGATE_res_single_cell, chr_size, resolution, bd_weight_list, \n",
    "                                        cluster_method, window_range, wd_ci, wd_p, dist, pvalue_cut, \n",
    "                                        exp_length, length_cut = length_cut, contact_fold_cut = 2, \n",
    "                                        zero_ratio_cut = 0.3, expand_check = 2, filter_method = filter_method,\n",
    "                                        target_chr_l = target_chr_l_use)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 112,
   "id": "8f79649c",
   "metadata": {},
   "outputs": [],
   "source": [
    "Chr = 'chr3'\n",
    "st = 1390\n",
    "ed = 1448"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 113,
   "id": "09826a87",
   "metadata": {},
   "outputs": [],
   "source": [
    "mat_ori = hic_mat_K562_cell_062[Chr]\n",
    "mat_imputed = TADGATE_res_single_cell[Chr]['result'][0]['mat_imputed_sym']\n",
    "mat_hic_whole, mat_imputed_whole, mat_combine_whole = PF.get_hic_map_original_and_imputed_compare(st, ed, \n",
    "                                                                                                  mat_ori, \n",
    "                                                                                                  mat_imputed, \n",
    "                                                                                                  QN = False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 114,
   "id": "01060ca8",
   "metadata": {},
   "outputs": [],
   "source": [
    "bin_name_l = list(TADGATE_res_single_cell[Chr]['mat_split'][0].obs_names)\n",
    "mat_list = [mat_hic_whole, mat_imputed_whole, mat_combine_whole]\n",
    "mat_para_list = []\n",
    "for i in range(3):\n",
    "    mat_para_list.append({'color': 'Reds', 'range':[0, 0.2], 'diag': False, 'net': False, 'value_type':'real', \n",
    "                          'tad_color':'#317FBA', 'tad_upper':True, 'tad_lower':False, 'norm_mat':False})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 115,
   "id": "a616edf3",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_tad_res = TADGATE_tads_all[Chr]['TADs'][0]\n",
    "df_tad_res_only = df_tad_res[df_tad_res['type'] == 'domain']\n",
    "df_tad_res_only = df_tad_res_only.reset_index(drop = True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 116,
   "id": "3ef7a4e7",
   "metadata": {},
   "outputs": [],
   "source": [
    "start_bin = 0\n",
    "tad_list_all = [[], []]\n",
    "TAD_l = TL.get_tad_list_in_target_ranges(st, ed, df_tad_res_only, resolution, start_bin, pos_type='bin')\n",
    "tad_list_all.append(TAD_l)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 121,
   "id": "99ffa8c6",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x250 with 6 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fgsize = (10, 2.5)\n",
    "col_num = 3\n",
    "title_l = ['', 'Imputed', 'Comparison']\n",
    "tad_list_l = tad_list_all\n",
    "bar_label = True\n",
    "save_name = ''\n",
    "PF.draw_multi_mat_compare_multi_row_with_TADs(st, ed, mat_list, mat_para_list, tad_list_l, bin_name_l, \n",
    "                                              Chr, resolution, col_num,\n",
    "                                              title_name_l = title_l, fgsize = fgsize, bin_size = 19, \n",
    "                                              save_name = save_name, ori='h', \n",
    "                                              bar_label = bar_label, ticks_draw = True, frame_w = 4)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b15a6b01",
   "metadata": {},
   "source": [
    "## For GSM7682483 GM12878 cell 213"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 122,
   "id": "07f1755a",
   "metadata": {},
   "outputs": [],
   "source": [
    "target_chr_l_use = ['chr5']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 123,
   "id": "1078134f",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "For chr5\n",
      "Hi-C map is splited into 1 sub-map\n",
      "Build spatial network...\n",
      "Get mask-matrix or weight-matrix...\n",
      "For No.0 sub-map\n",
      "Train TADGATE....\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████| 500/500 [00:16<00:00, 29.66it/s]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Total time 18.313791036605835s\n"
     ]
    }
   ],
   "source": [
    "TADGATE_res_single_cell2 = TADGATE_main.TADGATE_for_embedding(hic_mat_GM12878_cell_213, chr_size_hg38, \n",
    "                                                             resolution, graph_radius, split_size,  \n",
    "                                                             device, layer_node1,layer_node2, lr, \n",
    "                                                             weight_decay, num_epoch, \n",
    "                                                             embed_attention = embed_attention, \n",
    "                                                             weight_use = weight_use, \n",
    "                                                             weight_range = weight_range, \n",
    "                                                             weight_rate = weight_rate,\n",
    "                                                             impute_func=impute_func, \n",
    "                                                             impute_range=impute_range, \n",
    "                                                             CNN_impute=CNN_impute, \n",
    "                                                             RWR_impute=RWR_impute, \n",
    "                                                             target_chr_l = target_chr_l_use)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 124,
   "id": "6c377147",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "For chr5\n",
      "For sub-matrix 0...\n",
      "20% bins done!\n",
      "20% bins done!\n",
      "20% bins done!\n",
      "20% bins done!\n",
      "Running time 31.00904893875122s\n"
     ]
    }
   ],
   "source": [
    "TADGATE_tads_all2 = CT.TADGATE_call_TADs(TADGATE_res_single_cell2, chr_size, resolution, bd_weight_list, \n",
    "                                        cluster_method, window_range, wd_ci, wd_p, dist, pvalue_cut, \n",
    "                                        exp_length, length_cut = length_cut, contact_fold_cut = 2, \n",
    "                                        zero_ratio_cut = 0.3, expand_check = 2, filter_method = filter_method,\n",
    "                                        target_chr_l = target_chr_l_use)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 125,
   "id": "d1bb046d",
   "metadata": {},
   "outputs": [],
   "source": [
    "Chr = 'chr5'\n",
    "st = 2410\n",
    "ed = 2468"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 126,
   "id": "4fd36646",
   "metadata": {},
   "outputs": [],
   "source": [
    "mat_ori = hic_mat_GM12878_cell_213[Chr]\n",
    "mat_imputed = TADGATE_res_single_cell2[Chr]['result'][0]['mat_imputed_sym']\n",
    "mat_hic_whole, mat_imputed_whole, mat_combine_whole = PF.get_hic_map_original_and_imputed_compare(st, ed, \n",
    "                                                                                                  mat_ori, \n",
    "                                                                                                  mat_imputed, \n",
    "                                                                                                  QN = False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 127,
   "id": "93872df6",
   "metadata": {},
   "outputs": [],
   "source": [
    "bin_name_l = list(TADGATE_res_single_cell2[Chr]['mat_split'][0].obs_names)\n",
    "mat_list = [mat_hic_whole, mat_imputed_whole, mat_combine_whole]\n",
    "mat_para_list = []\n",
    "for i in range(3):\n",
    "    mat_para_list.append({'color': 'Reds', 'range':[0, 0.2], 'diag': False, 'net': False, 'value_type':'real', \n",
    "                          'tad_color':'#317FBA', 'tad_upper':True, 'tad_lower':False, 'norm_mat':False})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 128,
   "id": "01e816d3",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_tad_res = TADGATE_tads_all2[Chr]['TADs'][0]\n",
    "df_tad_res_only = df_tad_res[df_tad_res['type'] == 'domain']\n",
    "df_tad_res_only = df_tad_res_only.reset_index(drop = True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 129,
   "id": "4ae4fe84",
   "metadata": {},
   "outputs": [],
   "source": [
    "start_bin = 0\n",
    "tad_list_all = [[], []]\n",
    "TAD_l = TL.get_tad_list_in_target_ranges(st, ed, df_tad_res_only, resolution, start_bin, pos_type='bin')\n",
    "tad_list_all.append(TAD_l)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 130,
   "id": "c4c21329",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x250 with 6 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fgsize = (10, 2.5)\n",
    "col_num = 3\n",
    "title_l = ['', 'Imputed', 'Comparison']\n",
    "tad_list_l = tad_list_all\n",
    "bar_label = True\n",
    "save_name = ''\n",
    "PF.draw_multi_mat_compare_multi_row_with_TADs(st, ed, mat_list, mat_para_list, tad_list_l, bin_name_l, \n",
    "                                              Chr, resolution, col_num,\n",
    "                                              title_name_l = title_l, fgsize = fgsize, bin_size = 19, \n",
    "                                              save_name = save_name, ori='h', \n",
    "                                              bar_label = bar_label, ticks_draw = True, frame_w = 4)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "147551f7",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "f7105818",
   "metadata": {},
   "source": [
    "# Run TADGATE with Command Line Interface"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "b25fc231",
   "metadata": {},
   "outputs": [],
   "source": [
    "# TADGATE_test should be inplaced by your conda environment that you install TADGATE\n",
    "# The detialed information about the paramaters can be seen in parameters.txt as well as the annotion of help(TADGATE_main.TADGATE_for_embedding)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 137,
   "id": "97d2abb3",
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "For chr1\n",
      "Hi-C map is splited into 1 sub-map\n",
      "Build spatial network...\n",
      "Get mask-matrix or weight-matrix...\n",
      "For No.0 sub-map\n",
      "Train TADGATE....\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
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    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "For chr2\n",
      "Hi-C map is splited into 1 sub-map\n",
      "Build spatial network...\n",
      "Get mask-matrix or weight-matrix...\n",
      "For No.0 sub-map\n",
      "Train TADGATE....\n"
     ]
    },
    {
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     "output_type": "stream",
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     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Total time 65.75977611541748s\n",
      "For chr1\n",
      "For sub-matrix 0...\n",
      "20% bins done!\n",
      "20% bins done!\n",
      "20% bins done!\n",
      "20% bins done!\n",
      "Running time 28.73313045501709s\n",
      "For chr2\n",
      "For sub-matrix 0...\n",
      "20% bins done!\n",
      "20% bins done!\n",
      "20% bins done!\n",
      "20% bins done!\n",
      "Running time 25.318306922912598s\n"
     ]
    }
   ],
   "source": [
    "%%bash\n",
    "source activate TADGATE_test\n",
    "python -u /home/dcdang/pycharm_workspace/TADGATE/TADGATE_script_new/TADGATE_CLI.py /mnt/disk2/ddc/project/TADGATE/Data_for_packages/parameters.txt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
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   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "1e5ed368",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "762d774c",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "b1c5a401",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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