Transfer Entropy/Transfer Entropy.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "d5fbe28d-4457-4e27-a1f8-42054d3128ee",
   "metadata": {},
   "source": [
    "# Transfer Entropy"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "3a1f46cb-946c-4f22-9d07-c45b42d70a08",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "numpy: 1.24.3\n",
      "matplotlib: 3.7.0\n",
      "scipy: 1.10.1\n",
      "torch: 2.0.1+cu117\n",
      "torchdiffeq: 0.2.3\n",
      "torchsummary: Unknown version\n",
      "minepy: b'1.2.6'\n",
      "pyrqa: Unknown version\n",
      "pyts: 0.12.0\n",
      "MFDFA: 0.4.3\n",
      "pyinform: Unknown version\n",
      "graphviz: 0.20.1\n",
      "fa2 is not installed.\n",
      "networkx: 3.0\n"
     ]
    }
   ],
   "source": [
    "import importlib\n",
    "\n",
    "# List of libraries to check\n",
    "libraries = [\n",
    "    'numpy',\n",
    "    'matplotlib',\n",
    "    'scipy',\n",
    "    'torch',\n",
    "    'torchdiffeq',\n",
    "    'torchsummary',\n",
    "    'minepy',\n",
    "    'pyrqa',\n",
    "    'pyts',\n",
    "    'MFDFA',\n",
    "    'pyinform',\n",
    "    'graphviz',\n",
    "    'fa2',\n",
    "    'networkx'\n",
    "]\n",
    "\n",
    "for lib in libraries:\n",
    "    try:\n",
    "        module = importlib.import_module(lib)\n",
    "        version = getattr(module, '__version__', 'Unknown version')\n",
    "        print(f'{lib}: {version}')\n",
    "    except ImportError:\n",
    "        print(f'{lib} is not installed.')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0768493e-e6d9-4597-b1ee-7ed21ce6fed9",
   "metadata": {},
   "source": [
    "# Hemispheric "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "18423dfb-24e5-47da-abf2-3fbf0a2aba84",
   "metadata": {},
   "source": [
    "<div style=\"font-size: 13px; font-family: 'Times New Roman', Times, serif; background-color: #181818; color: #D0D0D0; padding: 20px; border-radius: 8px; margin: 10px; display: flex; flex-wrap: nowrap; justify-content: space-between;\">\n",
    "    <!-- Column 1 -->\n",
    "    <div style=\"flex: 1; margin-right: 10px;\">\n",
    "        <h2>Introduction</h2>\n",
    "        <p>\n",
    "            This script performs analysis on EEG data using the concept of Transfer Entropy (TE). Specifically, it investigates the directionality of information flow between different EEG channels based on their 2D embeddings.\n",
    "        </p>\n",
    "        <h2>Data Preparation</h2>\n",
    "        <p>\n",
    "            Initially, the code unzips a dataset of 2D embedded EEG data for multiple channels. The embedded data is then loaded into Python, trimmed to a desired length, and grouped by hemisphere (left and right).\n",
    "        </p>\n",
    "    </div>\n",
    "    <!-- Column 2 -->\n",
    "    <div style=\"flex: 1; margin-left: 10px;\">\n",
    "        <h2>Analysis</h2>\n",
    "        <p>\n",
    "            Transfer Entropy calculations are conducted to quantify the amount of information flowing from one EEG channel to another. This is done after binning the data and applying the PyInform library’s TE function.\n",
    "        </p>\n",
    "        <p>\n",
    "            The TE formula is represented as:\n",
    "            \\[\n",
    "            TE_{X \\rightarrow Y} = \\sum_{y_{t+1}, y_t, x_t} p(y_{t+1}, y_t, x_t) \\log \\frac{p(y_{t+1} | y_t, x_t)}{p(y_{t+1} | y_t)}\n",
    "            \\]\n",
    "            Here \\(X\\) and \\(Y\\) are random variables, \\(p(y_{t+1}, y_t, x_t)\\) is the joint probability distribution function, and \\(p(y_{t+1} | y_t, x_t)\\) and \\(p(y_{t+1} | y_t)\\) are conditional probability distribution functions.\n",
    "        </p>\n",
    "        </p>\n",
    "    </div>\n",
    "</div>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "9346d482-d77e-4dc2-ba87-2c4402c38eee",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Transfer Entropy from Left to Right (2D embeddings): 0.5814364131726154\n",
      "Transfer Entropy from Right to Left (2D embeddings): 0.5016624825390452\n"
     ]
    }
   ],
   "source": [
    "import zipfile\n",
    "import numpy as np\n",
    "import os\n",
    "import shutil\n",
    "from pyinform import transfer_entropy\n",
    "\n",
    "# Path to the zipped 2D embedded data\n",
    "zip_file_path = '/home/vincent/AAA_projects/MVCS/Neuroscience/Analysis/Phase Space/2dembedded_data.zip'\n",
    "extraction_dir = '/home/vincent/AAA_projects/MVCS/Neuroscience/Analysis/Phase Space/temp_extraction'\n",
    "\n",
    "embedding_data_list_2D = []\n",
    "\n",
    "# Extract zipped data to a temporary directory\n",
    "with zipfile.ZipFile(zip_file_path, 'r') as zipf:\n",
    "    zipf.extractall(extraction_dir)\n",
    "\n",
    "eeg_channels = ['Fp1', 'Fpz', 'Fp2', 'F7', 'F3', 'Fz', 'F4', 'F8', 'FC5', 'FC1', 'FC2', 'FC6',\n",
    "                'M1', 'T7', 'C3', 'Cz', 'C4', 'T8', 'M2', 'CP5', 'CP1', 'CP2', 'CP6',\n",
    "                'P7', 'P3', 'Pz', 'P4', 'P8', 'POz', 'O1', 'Oz', 'O2']\n",
    "\n",
    "for channel in eeg_channels:\n",
    "    file_path = os.path.join(extraction_dir, f'2dembedded_{channel}_data.npy')\n",
    "    embedding_data = np.load(file_path)\n",
    "    embedding_data_list_2D.append(embedding_data)\n",
    "\n",
    "\n",
    "# Set the desired length\n",
    "desired_length = 4227688\n",
    "\n",
    "# Trim each array in embedding_data_list_2D to desired_length\n",
    "embedding_data_list_2D_trimmed = [data[:desired_length] for data in embedding_data_list_2D]\n",
    "\n",
    "left_channels = ['Fp1', 'F7', 'F3', 'FC5', 'M1', 'T7', 'C3', 'CP5', 'P7', 'P3', 'O1']\n",
    "right_channels = ['Fp2', 'F8', 'F4', 'FC6', 'M2', 'T8', 'C4', 'CP6', 'P8', 'P4', 'O2']\n",
    "central_channels = ['Fpz', 'Fz', 'FC1', 'FC2', 'Cz', 'CP1', 'CP2', 'Pz', 'POz', 'Oz']\n",
    "\n",
    "# Cleanup: Optionally remove the extraction directory after loading the data\n",
    "# shutil.rmtree(extraction_dir) \n",
    "\n",
    "# Group channels by hemisphere\n",
    "left_indices = [eeg_channels.index(ch) for ch in left_channels]\n",
    "right_indices = [eeg_channels.index(ch) for ch in right_channels]\n",
    "\n",
    "# Compute average embeddings for left and right channels\n",
    "left_embedding_avg = np.mean(np.array([embedding_data_list_2D_trimmed[i] for i in left_indices]), axis=0)\n",
    "right_embedding_avg = np.mean(np.array([embedding_data_list_2D_trimmed[i] for i in right_indices]), axis=0)\n",
    "\n",
    "# Use one of the dimensions (e.g., x-coordinate) for Transfer Entropy calculation\n",
    "left_data = left_embedding_avg[:, 0]\n",
    "right_data = right_embedding_avg[:, 0]\n",
    "\n",
    "def bin_data(data, num_bins):\n",
    "    hist, bins = np.histogram(data, bins=num_bins)\n",
    "    binned_data = np.digitize(data, bins[:-1]) - 1  # subtract 1 to start binning from 0\n",
    "    return binned_data\n",
    "\n",
    "left_data_binned = bin_data(left_data, 1000)\n",
    "right_data_binned = bin_data(right_data, 1000)\n",
    "\n",
    "# Compute Transfer Entropy\n",
    "k, l = 1, 1\n",
    "try:\n",
    "    TE_left_to_right = transfer_entropy(left_data_binned, right_data_binned, k)\n",
    "    TE_right_to_left = transfer_entropy(right_data_binned, left_data_binned, k)\n",
    "\n",
    "    print(f\"Transfer Entropy from Left to Right (2D embeddings): {TE_left_to_right}\")\n",
    "    print(f\"Transfer Entropy from Right to Left (2D embeddings): {TE_right_to_left}\")\n",
    "except Exception as e:\n",
    "    print(f\"Error computing Transfer Entropy: {e}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "254b51ba-1bb5-4491-bdd5-e2afdc89af2a",
   "metadata": {},
   "source": [
    "# Feature extraction"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "fd3dae98-881c-45eb-9742-2936f9e8d980",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Shape for CNN input: (92, 92)\n",
      "Shape for RNN input: (8454,)\n"
     ]
    }
   ],
   "source": [
    "WINDOW_SIZE = 1000  # Size of each window\n",
    "STEP_SIZE = 500     # Size of each step between windows\n",
    "\n",
    "def compute_transfer_entropy_sequence(left_data, right_data, window_size=WINDOW_SIZE, step_size=STEP_SIZE):\n",
    "    \"\"\"\n",
    "    Compute Transfer Entropy for sliding windows of the data.\n",
    "    \n",
    "    :param left_data: Left hemisphere data\n",
    "    :param right_data: Right hemisphere data\n",
    "    :param window_size: Size of each window\n",
    "    :param step_size: Size of each step between windows\n",
    "    :return: Sequence of Transfer Entropy values\n",
    "    \"\"\"\n",
    "    te_sequence = []\n",
    "\n",
    "    for start in range(0, len(left_data) - window_size + 1, step_size):\n",
    "        window_left_data = left_data[start:start+window_size]\n",
    "        window_right_data = right_data[start:start+window_size]\n",
    "\n",
    "        window_left_binned = bin_data(window_left_data, 1000)\n",
    "        window_right_binned = bin_data(window_right_data, 1000)\n",
    "\n",
    "        te_left_to_right = transfer_entropy(window_left_binned, window_right_binned, 1)\n",
    "        te_sequence.append(te_left_to_right)\n",
    "\n",
    "    return np.array(te_sequence)\n",
    "\n",
    "# Compute the TE sequence for the averaged hemispheres\n",
    "te_sequence = compute_transfer_entropy_sequence(left_data_binned, right_data_binned)\n",
    "\n",
    "# For CNNs, you may reshape this sequence to suit the model's input shape.\n",
    "# Get the nearest square greater than or equal to len(te_sequence)\n",
    "next_square = int(np.ceil(np.sqrt(len(te_sequence)))) ** 2\n",
    "\n",
    "# Create a zero-filled square matrix of shape (sqrt(next_square), sqrt(next_square))\n",
    "cnn_input = np.zeros((int(np.sqrt(next_square)), int(np.sqrt(next_square))))\n",
    "\n",
    "# Fill in the matrix with the values from te_sequence\n",
    "cnn_input.flat[:len(te_sequence)] = te_sequence\n",
    "\n",
    "# For RNNs, you can directly use te_sequence as a feature.\n",
    "rnn_input = te_sequence\n",
    "\n",
    "print(f\"Shape for CNN input: {cnn_input.shape}\")\n",
    "print(f\"Shape for RNN input: {rnn_input.shape}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3d079894-8c92-4fd9-b806-3bdb6b353d27",
   "metadata": {},
   "source": [
    "# Save features"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "c47eb12a-864b-4a6c-8e2b-41172019aedd",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Data saved in /home/vincent/AAA_projects/MVCS/Neuroscience/Analysis/Transfer Entropy\n"
     ]
    }
   ],
   "source": [
    "import os\n",
    "import numpy as np\n",
    "\n",
    "# Define the directory where you want to save the results\n",
    "output_dir = \"/home/vincent/AAA_projects/MVCS/Neuroscience/Analysis/Transfer Entropy\"\n",
    "\n",
    "# Ensure the directory exists, if not, create it\n",
    "if not os.path.exists(output_dir):\n",
    "    os.makedirs(output_dir)\n",
    "\n",
    "# Save the computed TE sequence\n",
    "np.save(os.path.join(output_dir, 'transfer_entropy_hemispheric_avg.npy'), te_sequence)\n",
    "\n",
    "# Save the CNN input\n",
    "np.save(os.path.join(output_dir, 'cnn_transfer_entropy_hemispheric_avg_input.npy'), cnn_input)\n",
    "\n",
    "# Save the RNN input (which is the same as the TE sequence in this case)\n",
    "np.save(os.path.join(output_dir, 'rnn_transfer_entropy_hemispheric_avg_input.npy'), rnn_input)\n",
    "\n",
    "print(f\"Data saved in {output_dir}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "224c89a1-d32f-405c-a9f8-0c0030b0cee0",
   "metadata": {},
   "source": [
    "# Hemispherical Pairs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "29620c7e-7bcb-414d-8a27-85215f3837f0",
   "metadata": {},
   "outputs": [
    {
     "ename": "KeyboardInterrupt",
     "evalue": "",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mKeyboardInterrupt\u001b[0m                         Traceback (most recent call last)",
      "Cell \u001b[0;32mIn[24], line 32\u001b[0m\n\u001b[1;32m     29\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m np\u001b[38;5;241m.\u001b[39marray(te_matrix)\n\u001b[1;32m     31\u001b[0m \u001b[38;5;66;03m# Compute transfer entropy for each channel pair between left and right hemispheres\u001b[39;00m\n\u001b[0;32m---> 32\u001b[0m te_matrix \u001b[38;5;241m=\u001b[39m \u001b[43mcompute_transfer_entropy_for_hemispheres\u001b[49m\u001b[43m(\u001b[49m\u001b[43membedding_data_list_2D_trimmed\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mleft_channels\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mright_channels\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m     34\u001b[0m \u001b[38;5;66;03m# This te_matrix is suitable for CNN as it's 2D. \u001b[39;00m\n\u001b[1;32m     35\u001b[0m \u001b[38;5;66;03m# For RNN, you can consider each row of the te_matrix as a sequence of TE values for a particular channel pairing over time.\u001b[39;00m\n",
      "Cell \u001b[0;32mIn[24], line 24\u001b[0m, in \u001b[0;36mcompute_transfer_entropy_for_hemispheres\u001b[0;34m(data, left_channels, right_channels, window_size, step_size)\u001b[0m\n\u001b[1;32m     21\u001b[0m     ch1_data_binned \u001b[38;5;241m=\u001b[39m bin_data(ch1_data[:, \u001b[38;5;241m0\u001b[39m], \u001b[38;5;241m1000\u001b[39m)\n\u001b[1;32m     22\u001b[0m     ch2_data_binned \u001b[38;5;241m=\u001b[39m bin_data(ch2_data[:, \u001b[38;5;241m0\u001b[39m], \u001b[38;5;241m1000\u001b[39m)\n\u001b[0;32m---> 24\u001b[0m     te_ch1_to_ch2 \u001b[38;5;241m=\u001b[39m \u001b[43mtransfer_entropy\u001b[49m\u001b[43m(\u001b[49m\u001b[43mch1_data_binned\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mch2_data_binned\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m1\u001b[39;49m\u001b[43m)\u001b[49m\n\u001b[1;32m     25\u001b[0m     te_values\u001b[38;5;241m.\u001b[39mappend(te_ch1_to_ch2)\n\u001b[1;32m     27\u001b[0m te_matrix\u001b[38;5;241m.\u001b[39mappend(te_values)\n",
      "File \u001b[0;32m~/miniconda3/lib/python3.10/site-packages/pyinform/transferentropy.py:220\u001b[0m, in \u001b[0;36mtransfer_entropy\u001b[0;34m(source, target, k, condition, local)\u001b[0m\n\u001b[1;32m    218\u001b[0m     _local_transfer_entropy(ydata, xdata, cdata, c_ulong(z), c_ulong(n), c_ulong(m), c_int(b), c_ulong(k), out, byref(e))\n\u001b[1;32m    219\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[0;32m--> 220\u001b[0m     te \u001b[38;5;241m=\u001b[39m \u001b[43m_transfer_entropy\u001b[49m\u001b[43m(\u001b[49m\u001b[43mydata\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mxdata\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mcdata\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mc_ulong\u001b[49m\u001b[43m(\u001b[49m\u001b[43mz\u001b[49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mc_ulong\u001b[49m\u001b[43m(\u001b[49m\u001b[43mn\u001b[49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mc_ulong\u001b[49m\u001b[43m(\u001b[49m\u001b[43mm\u001b[49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mc_int\u001b[49m\u001b[43m(\u001b[49m\u001b[43mb\u001b[49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mc_ulong\u001b[49m\u001b[43m(\u001b[49m\u001b[43mk\u001b[49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mbyref\u001b[49m\u001b[43m(\u001b[49m\u001b[43me\u001b[49m\u001b[43m)\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    222\u001b[0m error_guard(e)\n\u001b[1;32m    224\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m te\n",
      "\u001b[0;31mKeyboardInterrupt\u001b[0m: "
     ]
    }
   ],
   "source": [
    "def compute_transfer_entropy_for_hemispheres(data, left_channels, right_channels, window_size=1000, step_size=500):\n",
    "    \"\"\"\n",
    "    Compute Transfer Entropy for pairs of channels between left and right hemispheres over sliding windows of the data.\n",
    "    \n",
    "    :param data: EEG data\n",
    "    :param left_channels: List of channels from the left hemisphere\n",
    "    :param right_channels: List of channels from the right hemisphere\n",
    "    :param window_size: Size of each window\n",
    "    :param step_size: Size of each step between windows\n",
    "    :return: Matrix of Transfer Entropy values; each row is a time window and each column a channel pair\n",
    "    \"\"\"\n",
    "    te_matrix = []\n",
    "\n",
    "    for ch1 in left_channels:\n",
    "        for ch2 in right_channels:\n",
    "            te_values = []\n",
    "            for start in range(0, len(data[0]) - window_size + 1, step_size):\n",
    "                ch1_data = data[eeg_channels.index(ch1)][start:start+window_size]\n",
    "                ch2_data = data[eeg_channels.index(ch2)][start:start+window_size]\n",
    "\n",
    "                ch1_data_binned = bin_data(ch1_data[:, 0], 1000)\n",
    "                ch2_data_binned = bin_data(ch2_data[:, 0], 1000)\n",
    "\n",
    "                te_ch1_to_ch2 = transfer_entropy(ch1_data_binned, ch2_data_binned, 1)\n",
    "                te_values.append(te_ch1_to_ch2)\n",
    "            \n",
    "            te_matrix.append(te_values)\n",
    "\n",
    "    return np.array(te_matrix)\n",
    "\n",
    "# Compute transfer entropy for each channel pair between left and right hemispheres\n",
    "te_matrix = compute_transfer_entropy_for_hemispheres(embedding_data_list_2D_trimmed, left_channels, right_channels)\n",
    "\n",
    "# This te_matrix is suitable for CNN as it's 2D. \n",
    "# For RNN, you can consider each row of the te_matrix as a sequence of TE values for a particular channel pairing over time."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5562f44a-2d28-48c3-8736-939618be582b",
   "metadata": {},
   "source": [
    "# Regional"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "32dcf261-708d-4f2e-a1a7-ce904a188f63",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Transfer Entropy from Frontal to Temporal (2D embeddings): 0.25110661733698914\n",
      "Transfer Entropy from Frontal to Parietal (2D embeddings): 0.5773050773854287\n",
      "Transfer Entropy from Frontal to Occipital (2D embeddings): 0.6741032253719645\n",
      "Transfer Entropy from Temporal to Frontal (2D embeddings): 0.33752969048400794\n",
      "Transfer Entropy from Temporal to Parietal (2D embeddings): 0.4711875861147353\n",
      "Transfer Entropy from Temporal to Occipital (2D embeddings): 0.6126095442734832\n",
      "Transfer Entropy from Parietal to Frontal (2D embeddings): 0.38813154044068165\n",
      "Transfer Entropy from Parietal to Temporal (2D embeddings): 0.22015981791417624\n",
      "Transfer Entropy from Parietal to Occipital (2D embeddings): 0.6353775260357438\n",
      "Transfer Entropy from Occipital to Frontal (2D embeddings): 0.42216948662291265\n",
      "Transfer Entropy from Occipital to Temporal (2D embeddings): 0.2811912780352561\n",
      "Transfer Entropy from Occipital to Parietal (2D embeddings): 0.5849692342942411\n",
      "Transfer entropy results saved to: /home/vincent/AAA_projects/MVCS/Neuroscience/Analysis/Transfer Entropy/regional_transfer_entropy_results.npy\n"
     ]
    }
   ],
   "source": [
    "import zipfile\n",
    "import numpy as np\n",
    "import os\n",
    "import shutil\n",
    "from pyinform import transfer_entropy\n",
    "\n",
    "# Path to the zipped 2D embedded data\n",
    "zip_file_path = '/home/vincent/AAA_projects/MVCS/Neuroscience/Analysis/Phase Space/2dembedded_data.zip'\n",
    "extraction_dir = '/home/vincent/AAA_projects/MVCS/Neuroscience/Analysis/Phase Space/temp_extraction'\n",
    "\n",
    "embedding_data_list_2D = []\n",
    "\n",
    "# Extract zipped data to a temporary directory\n",
    "with zipfile.ZipFile(zip_file_path, 'r') as zipf:\n",
    "    zipf.extractall(extraction_dir)\n",
    "\n",
    "eeg_channels = ['Fp1', 'Fpz', 'Fp2', 'F7', 'F3', 'Fz', 'F4', 'F8', 'FC5', 'FC1', 'FC2', 'FC6',\n",
    "                'M1', 'T7', 'C3', 'Cz', 'C4', 'T8', 'M2', 'CP5', 'CP1', 'CP2', 'CP6',\n",
    "                'P7', 'P3', 'Pz', 'P4', 'P8', 'POz', 'O1', 'Oz', 'O2']\n",
    "\n",
    "for channel in eeg_channels:\n",
    "    file_path = os.path.join(extraction_dir, f'2dembedded_{channel}_data.npy')\n",
    "    embedding_data = np.load(file_path)\n",
    "    embedding_data_list_2D.append(embedding_data)\n",
    "\n",
    "desired_length = 4227688\n",
    "embedding_data_list_2D_trimmed = [data[:desired_length] for data in embedding_data_list_2D]\n",
    "\n",
    "# Brain regions\n",
    "frontal_channels = ['Fp1', 'Fpz', 'Fp2', 'F7', 'F3', 'Fz', 'F4', 'F8']\n",
    "temporal_channels = ['T7', 'T8']\n",
    "parietal_channels = ['CP5', 'CP1', 'CP2', 'CP6', 'P7', 'P3', 'Pz', 'P4', 'P8']\n",
    "occipital_channels = ['O1', 'Oz', 'O2']\n",
    "\n",
    "frontal_indices = [eeg_channels.index(ch) for ch in frontal_channels]\n",
    "temporal_indices = [eeg_channels.index(ch) for ch in temporal_channels]\n",
    "parietal_indices = [eeg_channels.index(ch) for ch in parietal_channels]\n",
    "occipital_indices = [eeg_channels.index(ch) for ch in occipital_channels]\n",
    "\n",
    "# Getting average for each region\n",
    "frontal_data_avg = np.mean([embedding_data_list_2D_trimmed[i] for i in frontal_indices], axis=0)\n",
    "temporal_data_avg = np.mean([embedding_data_list_2D_trimmed[i] for i in temporal_indices], axis=0)\n",
    "parietal_data_avg = np.mean([embedding_data_list_2D_trimmed[i] for i in parietal_indices], axis=0)\n",
    "occipital_data_avg = np.mean([embedding_data_list_2D_trimmed[i] for i in occipital_indices], axis=0)\n",
    "\n",
    "# Use one of the dimensions for Transfer Entropy calculation\n",
    "frontal_data = frontal_data_avg[:, 0]\n",
    "temporal_data = temporal_data_avg[:, 0]\n",
    "parietal_data = parietal_data_avg[:, 0]\n",
    "occipital_data = occipital_data_avg[:, 0]\n",
    "\n",
    "def bin_data(data, num_bins):\n",
    "    hist, bins = np.histogram(data, bins=num_bins)\n",
    "    binned_data = np.digitize(data, bins[:-1]) - 1\n",
    "    return binned_data\n",
    "\n",
    "frontal_data_binned = bin_data(frontal_data, 1000)\n",
    "temporal_data_binned = bin_data(temporal_data, 1000)\n",
    "parietal_data_binned = bin_data(parietal_data, 1000)\n",
    "occipital_data_binned = bin_data(occipital_data, 1000)\n",
    "\n",
    "# Store the regional data in a dictionary for easier processing\n",
    "region_data_binned = {\n",
    "    \"Frontal\": frontal_data_binned,\n",
    "    \"Temporal\": temporal_data_binned,\n",
    "    \"Parietal\": parietal_data_binned,\n",
    "    \"Occipital\": occipital_data_binned\n",
    "}\n",
    "\n",
    "k = 1\n",
    "\n",
    "\n",
    "# Directory to save the transfer entropy results\n",
    "results_dir = '/home/vincent/AAA_projects/MVCS/Neuroscience/Analysis/Transfer Entropy'\n",
    "if not os.path.exists(results_dir):\n",
    "    os.makedirs(results_dir)  # Create the directory if it doesn't exist\n",
    "\n",
    "# Dictionary to store results\n",
    "TE_results = {}\n",
    "\n",
    "# Compute and print the transfer entropy from each region to every other region\n",
    "for source_region, source_data in region_data_binned.items():\n",
    "    for target_region, target_data in region_data_binned.items():\n",
    "        if source_region != target_region:\n",
    "            try:\n",
    "                TE_value = transfer_entropy(source_data, target_data, k)\n",
    "                key = f\"{source_region}_to_{target_region}\"\n",
    "                TE_results[key] = TE_value\n",
    "                print(f\"Transfer Entropy from {source_region} to {target_region} (2D embeddings): {TE_value}\")\n",
    "            except Exception as e:\n",
    "                print(f\"Error computing Transfer Entropy from {source_region} to {target_region}: {e}\")\n",
    "\n",
    "# Save the computed Transfer Entropy results\n",
    "results_file_path = os.path.join(results_dir, 'regional_transfer_entropy_results.npy')\n",
    "np.save(results_file_path, TE_results)\n",
    "\n",
    "print(f\"Transfer entropy results saved to: {results_file_path}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9c45709a-aa4c-4f1f-a5df-f0375c46c62e",
   "metadata": {},
   "source": [
    "# Full Granularity"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "3d601414-db65-4f2b-ae89-34c632322a07",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Transfer Entropy from Fp1 to Fpz: 0.40323706303475343\n",
      "Transfer Entropy from Fp1 to Fp2: 0.2818704697781004\n",
      "Transfer Entropy from Fp1 to F7: 0.25450640673035146\n",
      "Transfer Entropy from Fp1 to F3: 0.3920366504025133\n",
      "Transfer Entropy from Fp1 to Fz: 0.340570439690493\n",
      "Transfer Entropy from Fp1 to F4: 0.36684320006698923\n",
      "Transfer Entropy from Fp1 to F8: 0.3814174869152535\n",
      "Transfer Entropy from Fp1 to FC5: 0.4008950684194118\n",
      "Transfer Entropy from Fp1 to FC1: 0.4868985959943641\n",
      "Transfer Entropy from Fp1 to FC2: 0.5637154724066433\n",
      "Transfer Entropy from Fp1 to FC6: 0.49389085353899803\n",
      "Transfer Entropy from Fp1 to M1: 0.47221756489424793\n",
      "Transfer Entropy from Fp1 to T7: 0.32894960730094375\n",
      "Transfer Entropy from Fp1 to C3: 0.38167164803444587\n",
      "Transfer Entropy from Fp1 to Cz: 0.6011588901131365\n",
      "Transfer Entropy from Fp1 to C4: 0.4697287943283873\n",
      "Transfer Entropy from Fp1 to T8: 0.5130112097503553\n",
      "Transfer Entropy from Fp1 to M2: 0.5672168204033003\n",
      "Transfer Entropy from Fp1 to CP5: 0.23824754062478157\n",
      "Transfer Entropy from Fp1 to CP1: 0.5927575243094223\n",
      "Transfer Entropy from Fp1 to CP2: 0.7304516712278878\n",
      "Transfer Entropy from Fp1 to CP6: 0.5333527182744573\n",
      "Transfer Entropy from Fp1 to P7: 0.5848131842038433\n",
      "Transfer Entropy from Fp1 to P3: 0.6223911000280086\n",
      "Transfer Entropy from Fp1 to Pz: 0.8419868187140546\n",
      "Transfer Entropy from Fp1 to P4: 0.741978782470686\n",
      "Transfer Entropy from Fp1 to P8: 0.5263928153052267\n",
      "Transfer Entropy from Fp1 to POz: 0.7199603925232134\n",
      "Transfer Entropy from Fp1 to O1: 0.6084761791049695\n",
      "Transfer Entropy from Fp1 to Oz: 0.6292160960469199\n",
      "Transfer Entropy from Fp1 to O2: 0.6162789021465184\n",
      "Transfer Entropy from Fpz to Fp1: 0.22548421233814356\n",
      "Transfer Entropy from Fpz to Fp2: 0.29535056198551324\n",
      "Transfer Entropy from Fpz to F7: 0.2728162785141356\n",
      "Transfer Entropy from Fpz to F3: 0.45271738327135497\n",
      "Transfer Entropy from Fpz to Fz: 0.3705970672961796\n",
      "Transfer Entropy from Fpz to F4: 0.39432191077563183\n",
      "Transfer Entropy from Fpz to F8: 0.4504715834492651\n",
      "Transfer Entropy from Fpz to FC5: 0.44204977680335245\n",
      "Transfer Entropy from Fpz to FC1: 0.4992650572589718\n",
      "Transfer Entropy from Fpz to FC2: 0.5845975781662247\n",
      "Transfer Entropy from Fpz to FC6: 0.5319088200449946\n",
      "Transfer Entropy from Fpz to M1: 0.5159233442783275\n",
      "Transfer Entropy from Fpz to T7: 0.34237604979236935\n",
      "Transfer Entropy from Fpz to C3: 0.425376402632431\n",
      "Transfer Entropy from Fpz to Cz: 0.6280055415339607\n",
      "Transfer Entropy from Fpz to C4: 0.4962428042428292\n",
      "Transfer Entropy from Fpz to T8: 0.5601906232950797\n",
      "Transfer Entropy from Fpz to M2: 0.619271715497946\n",
      "Transfer Entropy from Fpz to CP5: 0.25440289170605873\n",
      "Transfer Entropy from Fpz to CP1: 0.6628801471616039\n",
      "Transfer Entropy from Fpz to CP2: 0.8008384697272103\n",
      "Transfer Entropy from Fpz to CP6: 0.5650311929970476\n",
      "Transfer Entropy from Fpz to P7: 0.6536962363897626\n",
      "Transfer Entropy from Fpz to P3: 0.6977601985654825\n",
      "Transfer Entropy from Fpz to Pz: 0.889685555984976\n",
      "Transfer Entropy from Fpz to P4: 0.7971261643508482\n",
      "Transfer Entropy from Fpz to P8: 0.5727492123229471\n",
      "Transfer Entropy from Fpz to POz: 0.7609620316667555\n",
      "Transfer Entropy from Fpz to O1: 0.6206092451968968\n",
      "Transfer Entropy from Fpz to Oz: 0.6929789947962747\n",
      "Transfer Entropy from Fpz to O2: 0.6671739801660761\n",
      "Transfer Entropy from Fp2 to Fp1: 0.22253144619849255\n",
      "Transfer Entropy from Fp2 to Fpz: 0.4151031562687186\n",
      "Transfer Entropy from Fp2 to F7: 0.2959589968258271\n",
      "Transfer Entropy from Fp2 to F3: 0.4708117467388301\n",
      "Transfer Entropy from Fp2 to Fz: 0.3988820131932256\n",
      "Transfer Entropy from Fp2 to F4: 0.44835964986756977\n",
      "Transfer Entropy from Fp2 to F8: 0.4599383774702956\n",
      "Transfer Entropy from Fp2 to FC5: 0.4721761008201325\n",
      "Transfer Entropy from Fp2 to FC1: 0.549185894698739\n",
      "Transfer Entropy from Fp2 to FC2: 0.6349349586694903\n",
      "Transfer Entropy from Fp2 to FC6: 0.5384525072092683\n",
      "Transfer Entropy from Fp2 to M1: 0.5263852605331477\n",
      "Transfer Entropy from Fp2 to T7: 0.3703422497183083\n",
      "Transfer Entropy from Fp2 to C3: 0.4440234007863593\n",
      "Transfer Entropy from Fp2 to Cz: 0.6793640737691301\n",
      "Transfer Entropy from Fp2 to C4: 0.494082674954434\n",
      "Transfer Entropy from Fp2 to T8: 0.5652986856228639\n",
      "Transfer Entropy from Fp2 to M2: 0.623616768434703\n",
      "Transfer Entropy from Fp2 to CP5: 0.2972795221100576\n",
      "Transfer Entropy from Fp2 to CP1: 0.6766718698004434\n",
      "Transfer Entropy from Fp2 to CP2: 0.8371871287177642\n",
      "Transfer Entropy from Fp2 to CP6: 0.562561096852585\n",
      "Transfer Entropy from Fp2 to P7: 0.6631875126940144\n",
      "Transfer Entropy from Fp2 to P3: 0.7026918646703283\n",
      "Transfer Entropy from Fp2 to Pz: 0.9608386698956521\n",
      "Transfer Entropy from Fp2 to P4: 0.8017619570836667\n",
      "Transfer Entropy from Fp2 to P8: 0.5746023873839303\n",
      "Transfer Entropy from Fp2 to POz: 0.752846871809526\n",
      "Transfer Entropy from Fp2 to O1: 0.6268262361141601\n",
      "Transfer Entropy from Fp2 to Oz: 0.7097136754151835\n",
      "Transfer Entropy from Fp2 to O2: 0.6845591879800277\n",
      "Transfer Entropy from F7 to Fp1: 0.209224736645039\n",
      "Transfer Entropy from F7 to Fpz: 0.427079720994545\n",
      "Transfer Entropy from F7 to Fp2: 0.3118092032414955\n",
      "Transfer Entropy from F7 to F3: 0.33288594898698215\n",
      "Transfer Entropy from F7 to Fz: 0.3000542930570356\n",
      "Transfer Entropy from F7 to F4: 0.34980948427680597\n",
      "Transfer Entropy from F7 to F8: 0.35892417857510517\n",
      "Transfer Entropy from F7 to FC5: 0.2899615436500479\n",
      "Transfer Entropy from F7 to FC1: 0.4174725539041163\n",
      "Transfer Entropy from F7 to FC2: 0.5107229461509603\n",
      "Transfer Entropy from F7 to FC6: 0.4911189664837978\n",
      "Transfer Entropy from F7 to M1: 0.4673645712077154\n",
      "Transfer Entropy from F7 to T7: 0.27471370091822567\n",
      "Transfer Entropy from F7 to C3: 0.29553752616052786\n",
      "Transfer Entropy from F7 to Cz: 0.5057262221139318\n",
      "Transfer Entropy from F7 to C4: 0.4899128913209771\n",
      "Transfer Entropy from F7 to T8: 0.48247863762864207\n",
      "Transfer Entropy from F7 to M2: 0.46220881046253354\n",
      "Transfer Entropy from F7 to CP5: 0.17243649607056385\n",
      "Transfer Entropy from F7 to CP1: 0.49161749487330897\n",
      "Transfer Entropy from F7 to CP2: 0.5457029981636722\n",
      "Transfer Entropy from F7 to CP6: 0.5310947742973297\n",
      "Transfer Entropy from F7 to P7: 0.5367681550726636\n",
      "Transfer Entropy from F7 to P3: 0.5201898680210068\n",
      "Transfer Entropy from F7 to Pz: 0.7026634818914608\n",
      "Transfer Entropy from F7 to P4: 0.5676616328450815\n",
      "Transfer Entropy from F7 to P8: 0.5021918223810214\n",
      "Transfer Entropy from F7 to POz: 0.5865800437226907\n",
      "Transfer Entropy from F7 to O1: 0.5083477071393259\n",
      "Transfer Entropy from F7 to Oz: 0.5238700528348819\n",
      "Transfer Entropy from F7 to O2: 0.5156330051788834\n",
      "Transfer Entropy from F3 to Fp1: 0.2651447541394184\n",
      "Transfer Entropy from F3 to Fpz: 0.5259369841598357\n",
      "Transfer Entropy from F3 to Fp2: 0.39939512893641066\n",
      "Transfer Entropy from F3 to F7: 0.23154387513362276\n",
      "Transfer Entropy from F3 to Fz: 0.3441846498135728\n",
      "Transfer Entropy from F3 to F4: 0.4141160298990385\n",
      "Transfer Entropy from F3 to F8: 0.4171993976843795\n",
      "Transfer Entropy from F3 to FC5: 0.3218769419099474\n",
      "Transfer Entropy from F3 to FC1: 0.4712629740370795\n",
      "Transfer Entropy from F3 to FC2: 0.5399011048476986\n",
      "Transfer Entropy from F3 to FC6: 0.5711178492240735\n",
      "Transfer Entropy from F3 to M1: 0.545520262200558\n",
      "Transfer Entropy from F3 to T7: 0.28283591535388636\n",
      "Transfer Entropy from F3 to C3: 0.3522619247972086\n",
      "Transfer Entropy from F3 to Cz: 0.5620882102184691\n",
      "Transfer Entropy from F3 to C4: 0.5755898623520428\n",
      "Transfer Entropy from F3 to T8: 0.5633592210358906\n",
      "Transfer Entropy from F3 to M2: 0.5405512905318697\n",
      "Transfer Entropy from F3 to CP5: 0.1876820610957885\n",
      "Transfer Entropy from F3 to CP1: 0.619760519107217\n",
      "Transfer Entropy from F3 to CP2: 0.7202108894519004\n",
      "Transfer Entropy from F3 to CP6: 0.6295818062477966\n",
      "Transfer Entropy from F3 to P7: 0.6091414061649228\n",
      "Transfer Entropy from F3 to P3: 0.554641906902627\n",
      "Transfer Entropy from F3 to Pz: 0.726373859113473\n",
      "Transfer Entropy from F3 to P4: 0.7049984174036981\n",
      "Transfer Entropy from F3 to P8: 0.5874718064291378\n",
      "Transfer Entropy from F3 to POz: 0.7445814986336887\n",
      "Transfer Entropy from F3 to O1: 0.6234449285247656\n",
      "Transfer Entropy from F3 to Oz: 0.5695312892033086\n",
      "Transfer Entropy from F3 to O2: 0.545099083772171\n",
      "Transfer Entropy from Fz to Fp1: 0.24221807468398338\n",
      "Transfer Entropy from Fz to Fpz: 0.45796095840297535\n",
      "Transfer Entropy from Fz to Fp2: 0.3491674607300556\n",
      "Transfer Entropy from Fz to F7: 0.24413404282676826\n",
      "Transfer Entropy from Fz to F3: 0.38998596556393417\n",
      "Transfer Entropy from Fz to F4: 0.36822219654546046\n",
      "Transfer Entropy from Fz to F8: 0.4181566754429746\n",
      "Transfer Entropy from Fz to FC5: 0.3703491567190001\n",
      "Transfer Entropy from Fz to FC1: 0.42485324784106754\n",
      "Transfer Entropy from Fz to FC2: 0.5350318296342667\n",
      "Transfer Entropy from Fz to FC6: 0.5443053672251921\n",
      "Transfer Entropy from Fz to M1: 0.5160736364728813\n",
      "Transfer Entropy from Fz to T7: 0.2833177855486371\n",
      "Transfer Entropy from Fz to C3: 0.35944006231316306\n",
      "Transfer Entropy from Fz to Cz: 0.4692669166953484\n",
      "Transfer Entropy from Fz to C4: 0.5460395670150509\n",
      "Transfer Entropy from Fz to T8: 0.5396732732487385\n",
      "Transfer Entropy from Fz to M2: 0.5360380747508289\n",
      "Transfer Entropy from Fz to CP5: 0.20463758349428982\n",
      "Transfer Entropy from Fz to CP1: 0.6233771166028202\n",
      "Transfer Entropy from Fz to CP2: 0.6843582561045939\n",
      "Transfer Entropy from Fz to CP6: 0.6001780862726105\n",
      "Transfer Entropy from Fz to P7: 0.5750892965159602\n",
      "Transfer Entropy from Fz to P3: 0.5938263122327581\n",
      "Transfer Entropy from Fz to Pz: 0.7586462746385891\n",
      "Transfer Entropy from Fz to P4: 0.7008879119460192\n",
      "Transfer Entropy from Fz to P8: 0.5632205190987256\n",
      "Transfer Entropy from Fz to POz: 0.6784001143749826\n",
      "Transfer Entropy from Fz to O1: 0.5967238422253116\n",
      "Transfer Entropy from Fz to Oz: 0.5954800395156108\n",
      "Transfer Entropy from Fz to O2: 0.5793375696001052\n",
      "Transfer Entropy from F4 to Fp1: 0.2192756988143739\n",
      "Transfer Entropy from F4 to Fpz: 0.4209312090152685\n",
      "Transfer Entropy from F4 to Fp2: 0.34292640494827303\n",
      "Transfer Entropy from F4 to F7: 0.2620720374093887\n",
      "Transfer Entropy from F4 to F3: 0.4099273245907356\n",
      "Transfer Entropy from F4 to Fz: 0.3268706759704917\n",
      "Transfer Entropy from F4 to F8: 0.3974203835713979\n",
      "Transfer Entropy from F4 to FC5: 0.4178700169859713\n",
      "Transfer Entropy from F4 to FC1: 0.49261977837303084\n",
      "Transfer Entropy from F4 to FC2: 0.5574090256285634\n",
      "Transfer Entropy from F4 to FC6: 0.5464305450548195\n",
      "Transfer Entropy from F4 to M1: 0.5119359419839761\n",
      "Transfer Entropy from F4 to T7: 0.304108794748545\n",
      "Transfer Entropy from F4 to C3: 0.39117567192768576\n",
      "Transfer Entropy from F4 to Cz: 0.5470985817570448\n",
      "Transfer Entropy from F4 to C4: 0.5415503069297042\n",
      "Transfer Entropy from F4 to T8: 0.5333846750024308\n",
      "Transfer Entropy from F4 to M2: 0.5830639341582593\n",
      "Transfer Entropy from F4 to CP5: 0.2133684270845234\n",
      "Transfer Entropy from F4 to CP1: 0.6431847991622369\n",
      "Transfer Entropy from F4 to CP2: 0.7704642801713107\n",
      "Transfer Entropy from F4 to CP6: 0.6012495368219137\n",
      "Transfer Entropy from F4 to P7: 0.6093803436505312\n",
      "Transfer Entropy from F4 to P3: 0.5963866941007402\n",
      "Transfer Entropy from F4 to Pz: 0.789305865221836\n",
      "Transfer Entropy from F4 to P4: 0.772906097520076\n",
      "Transfer Entropy from F4 to P8: 0.5559533564921287\n",
      "Transfer Entropy from F4 to POz: 0.768061333099793\n",
      "Transfer Entropy from F4 to O1: 0.6302728069486067\n",
      "Transfer Entropy from F4 to Oz: 0.629919967112253\n",
      "Transfer Entropy from F4 to O2: 0.5874266530822311\n",
      "Transfer Entropy from F8 to Fp1: 0.22607537767458188\n",
      "Transfer Entropy from F8 to Fpz: 0.4724746462576873\n",
      "Transfer Entropy from F8 to Fp2: 0.34817209626635187\n",
      "Transfer Entropy from F8 to F7: 0.2506342934769467\n",
      "Transfer Entropy from F8 to F3: 0.3941614672378394\n",
      "Transfer Entropy from F8 to Fz: 0.355483108910025\n",
      "Transfer Entropy from F8 to F4: 0.38873398698112566\n",
      "Transfer Entropy from F8 to FC5: 0.411445005410226\n",
      "Transfer Entropy from F8 to FC1: 0.49762255381462794\n",
      "Transfer Entropy from F8 to FC2: 0.6067761080867932\n",
      "Transfer Entropy from F8 to FC6: 0.43028824032416946\n",
      "Transfer Entropy from F8 to M1: 0.449084666553153\n",
      "Transfer Entropy from F8 to T7: 0.330972143584159\n",
      "Transfer Entropy from F8 to C3: 0.4008503861471955\n",
      "Transfer Entropy from F8 to Cz: 0.5964801538506499\n",
      "Transfer Entropy from F8 to C4: 0.49260626591346146\n",
      "Transfer Entropy from F8 to T8: 0.4400142448346192\n",
      "Transfer Entropy from F8 to M2: 0.5441394925933131\n",
      "Transfer Entropy from F8 to CP5: 0.2437786861228755\n",
      "Transfer Entropy from F8 to CP1: 0.60088116800224\n",
      "Transfer Entropy from F8 to CP2: 0.763606907917181\n",
      "Transfer Entropy from F8 to CP6: 0.5698072304881495\n",
      "Transfer Entropy from F8 to P7: 0.5728444933785435\n",
      "Transfer Entropy from F8 to P3: 0.6603182351271305\n",
      "Transfer Entropy from F8 to Pz: 0.8707034282684714\n",
      "Transfer Entropy from F8 to P4: 0.7527762501637311\n",
      "Transfer Entropy from F8 to P8: 0.49280671228224576\n",
      "Transfer Entropy from F8 to POz: 0.7562746722759742\n",
      "Transfer Entropy from F8 to O1: 0.6242284253413856\n",
      "Transfer Entropy from F8 to Oz: 0.6173839736505841\n",
      "Transfer Entropy from F8 to O2: 0.5751129716709564\n",
      "Transfer Entropy from FC5 to Fp1: 0.2744206689739513\n",
      "Transfer Entropy from FC5 to Fpz: 0.507377247240566\n",
      "Transfer Entropy from FC5 to Fp2: 0.3891431508384015\n",
      "Transfer Entropy from FC5 to F7: 0.20309841850488092\n",
      "Transfer Entropy from FC5 to F3: 0.3235433671666623\n",
      "Transfer Entropy from FC5 to Fz: 0.3354941809952175\n",
      "Transfer Entropy from FC5 to F4: 0.40721054447816757\n",
      "Transfer Entropy from FC5 to F8: 0.43516365610998575\n",
      "Transfer Entropy from FC5 to FC1: 0.4509404614195442\n",
      "Transfer Entropy from FC5 to FC2: 0.5417885848010565\n",
      "Transfer Entropy from FC5 to FC6: 0.5664585940534665\n",
      "Transfer Entropy from FC5 to M1: 0.5328288880358402\n",
      "Transfer Entropy from FC5 to T7: 0.2824350489402219\n",
      "Transfer Entropy from FC5 to C3: 0.3139761237203531\n",
      "Transfer Entropy from FC5 to Cz: 0.5505130485605755\n",
      "Transfer Entropy from FC5 to C4: 0.558403361979837\n",
      "Transfer Entropy from FC5 to T8: 0.5479714050108613\n",
      "Transfer Entropy from FC5 to M2: 0.5519878041012428\n",
      "Transfer Entropy from FC5 to CP5: 0.18411069289979728\n",
      "Transfer Entropy from FC5 to CP1: 0.6409745166981834\n",
      "Transfer Entropy from FC5 to CP2: 0.7222924979017571\n",
      "Transfer Entropy from FC5 to CP6: 0.6049106124336661\n",
      "Transfer Entropy from FC5 to P7: 0.6053678419999592\n",
      "Transfer Entropy from FC5 to P3: 0.5584981208094395\n",
      "Transfer Entropy from FC5 to Pz: 0.7194732906750475\n",
      "Transfer Entropy from FC5 to P4: 0.700297947104999\n",
      "Transfer Entropy from FC5 to P8: 0.5715212927638625\n",
      "Transfer Entropy from FC5 to POz: 0.7467573852213278\n",
      "Transfer Entropy from FC5 to O1: 0.6265307573415986\n",
      "Transfer Entropy from FC5 to Oz: 0.5431474149512052\n",
      "Transfer Entropy from FC5 to O2: 0.5482844878207151\n",
      "Transfer Entropy from FC1 to Fp1: 0.2808880493602157\n",
      "Transfer Entropy from FC1 to Fpz: 0.4858918042913545\n",
      "Transfer Entropy from FC1 to Fp2: 0.38369708964922816\n",
      "Transfer Entropy from FC1 to F7: 0.25986257554970843\n",
      "Transfer Entropy from FC1 to F3: 0.42525898411532703\n",
      "Transfer Entropy from FC1 to Fz: 0.31400960864444977\n",
      "Transfer Entropy from FC1 to F4: 0.43870320509696437\n",
      "Transfer Entropy from FC1 to F8: 0.4607621704658753\n",
      "Transfer Entropy from FC1 to FC5: 0.4242960078989762\n",
      "Transfer Entropy from FC1 to FC2: 0.5837206621022315\n",
      "Transfer Entropy from FC1 to FC6: 0.5488606438948963\n",
      "Transfer Entropy from FC1 to M1: 0.5437530094706433\n",
      "Transfer Entropy from FC1 to T7: 0.33163429107339604\n",
      "Transfer Entropy from FC1 to C3: 0.381342498278394\n",
      "Transfer Entropy from FC1 to Cz: 0.5778924105476672\n",
      "Transfer Entropy from FC1 to C4: 0.5505372796617737\n",
      "Transfer Entropy from FC1 to T8: 0.5566677146184026\n",
      "Transfer Entropy from FC1 to M2: 0.5807701125320506\n",
      "Transfer Entropy from FC1 to CP5: 0.23541848104565302\n",
      "Transfer Entropy from FC1 to CP1: 0.7087686882160183\n",
      "Transfer Entropy from FC1 to CP2: 0.7935257515650826\n",
      "Transfer Entropy from FC1 to CP6: 0.6065033484155081\n",
      "Transfer Entropy from FC1 to P7: 0.6101733579249651\n",
      "Transfer Entropy from FC1 to P3: 0.647368987552461\n",
      "Transfer Entropy from FC1 to Pz: 0.8329630289734958\n",
      "Transfer Entropy from FC1 to P4: 0.7653903840605324\n",
      "Transfer Entropy from FC1 to P8: 0.5794370610120535\n",
      "Transfer Entropy from FC1 to POz: 0.7718258087860932\n",
      "Transfer Entropy from FC1 to O1: 0.646324634845309\n",
      "Transfer Entropy from FC1 to Oz: 0.649722768281883\n",
      "Transfer Entropy from FC1 to O2: 0.6436136793265926\n",
      "Transfer Entropy from FC2 to Fp1: 0.2581282749611645\n",
      "Transfer Entropy from FC2 to Fpz: 0.4673143714611598\n",
      "Transfer Entropy from FC2 to Fp2: 0.3625051592895219\n",
      "Transfer Entropy from FC2 to F7: 0.2655752058203292\n",
      "Transfer Entropy from FC2 to F3: 0.4230332505453134\n",
      "Transfer Entropy from FC2 to Fz: 0.3526079092233726\n",
      "Transfer Entropy from FC2 to F4: 0.42442705275287973\n",
      "Transfer Entropy from FC2 to F8: 0.47524539833901486\n",
      "Transfer Entropy from FC2 to FC5: 0.4204362547625147\n",
      "Transfer Entropy from FC2 to FC1: 0.5108896027505884\n",
      "Transfer Entropy from FC2 to FC6: 0.5983969054688704\n",
      "Transfer Entropy from FC2 to M1: 0.5658290875490554\n",
      "Transfer Entropy from FC2 to T7: 0.3041310860045622\n",
      "Transfer Entropy from FC2 to C3: 0.4153756404837343\n",
      "Transfer Entropy from FC2 to Cz: 0.6048296472894954\n",
      "Transfer Entropy from FC2 to C4: 0.594206606352386\n",
      "Transfer Entropy from FC2 to T8: 0.6067456442666673\n",
      "Transfer Entropy from FC2 to M2: 0.6158604586160105\n",
      "Transfer Entropy from FC2 to CP5: 0.23235873355815445\n",
      "Transfer Entropy from FC2 to CP1: 0.6953476482405847\n",
      "Transfer Entropy from FC2 to CP2: 0.8187040476825275\n",
      "Transfer Entropy from FC2 to CP6: 0.650305089710449\n",
      "Transfer Entropy from FC2 to P7: 0.6645718106272651\n",
      "Transfer Entropy from FC2 to P3: 0.7039992526205677\n",
      "Transfer Entropy from FC2 to Pz: 0.8289935987858127\n",
      "Transfer Entropy from FC2 to P4: 0.8236403212256016\n",
      "Transfer Entropy from FC2 to P8: 0.6229087667747264\n",
      "Transfer Entropy from FC2 to POz: 0.8089796669984013\n",
      "Transfer Entropy from FC2 to O1: 0.6612533531438027\n",
      "Transfer Entropy from FC2 to Oz: 0.6372086425936588\n",
      "Transfer Entropy from FC2 to O2: 0.6147472573983395\n",
      "Transfer Entropy from FC6 to Fp1: 0.24001588645879307\n",
      "Transfer Entropy from FC6 to Fpz: 0.46586700310665996\n",
      "Transfer Entropy from FC6 to Fp2: 0.3321860185328585\n",
      "Transfer Entropy from FC6 to F7: 0.28252231313360143\n",
      "Transfer Entropy from FC6 to F3: 0.44764502373053294\n",
      "Transfer Entropy from FC6 to Fz: 0.3893231218508609\n",
      "Transfer Entropy from FC6 to F4: 0.4499423535729028\n",
      "Transfer Entropy from FC6 to F8: 0.3420531757869358\n",
      "Transfer Entropy from FC6 to FC5: 0.47152023756452505\n",
      "Transfer Entropy from FC6 to FC1: 0.5167628259182291\n",
      "Transfer Entropy from FC6 to FC2: 0.6444400780203419\n",
      "Transfer Entropy from FC6 to M1: 0.4285857089447552\n",
      "Transfer Entropy from FC6 to T7: 0.36026119848140564\n",
      "Transfer Entropy from FC6 to C3: 0.4402211299962277\n",
      "Transfer Entropy from FC6 to Cz: 0.654068412676228\n",
      "Transfer Entropy from FC6 to C4: 0.4462629134411483\n",
      "Transfer Entropy from FC6 to T8: 0.4442412420759182\n",
      "Transfer Entropy from FC6 to M2: 0.5868951280792212\n",
      "Transfer Entropy from FC6 to CP5: 0.2866576443176058\n",
      "Transfer Entropy from FC6 to CP1: 0.662040601301077\n",
      "Transfer Entropy from FC6 to CP2: 0.8392118334850389\n",
      "Transfer Entropy from FC6 to CP6: 0.5114632503423725\n",
      "Transfer Entropy from FC6 to P7: 0.5938451883044574\n",
      "Transfer Entropy from FC6 to P3: 0.7105037956598554\n",
      "Transfer Entropy from FC6 to Pz: 0.9151925560938446\n",
      "Transfer Entropy from FC6 to P4: 0.8000260441670335\n",
      "Transfer Entropy from FC6 to P8: 0.46372480884918943\n",
      "Transfer Entropy from FC6 to POz: 0.7999453687613175\n",
      "Transfer Entropy from FC6 to O1: 0.6555571387673637\n",
      "Transfer Entropy from FC6 to Oz: 0.6769463605789564\n",
      "Transfer Entropy from FC6 to O2: 0.6226202797377951\n",
      "Transfer Entropy from M1 to Fp1: 0.24224604348833373\n",
      "Transfer Entropy from M1 to Fpz: 0.4667125319018863\n",
      "Transfer Entropy from M1 to Fp2: 0.3403045599619948\n",
      "Transfer Entropy from M1 to F7: 0.286165304805969\n",
      "Transfer Entropy from M1 to F3: 0.43989471566785937\n",
      "Transfer Entropy from M1 to Fz: 0.38046254006051783\n",
      "Transfer Entropy from M1 to F4: 0.438379869746892\n",
      "Transfer Entropy from M1 to F8: 0.3840361509393835\n",
      "Transfer Entropy from M1 to FC5: 0.4376068372189374\n",
      "Transfer Entropy from M1 to FC1: 0.5151564922734129\n",
      "Transfer Entropy from M1 to FC2: 0.6339474793478506\n",
      "Transfer Entropy from M1 to FC6: 0.4446750821342816\n",
      "Transfer Entropy from M1 to T7: 0.3714765275064403\n",
      "Transfer Entropy from M1 to C3: 0.4260250946035193\n",
      "Transfer Entropy from M1 to Cz: 0.6519110103559751\n",
      "Transfer Entropy from M1 to C4: 0.45179213863778594\n",
      "Transfer Entropy from M1 to T8: 0.43323330276118277\n",
      "Transfer Entropy from M1 to M2: 0.5783357064805341\n",
      "Transfer Entropy from M1 to CP5: 0.27880461935593864\n",
      "Transfer Entropy from M1 to CP1: 0.6394202324423525\n",
      "Transfer Entropy from M1 to CP2: 0.8301337714823536\n",
      "Transfer Entropy from M1 to CP6: 0.5225083680229148\n",
      "Transfer Entropy from M1 to P7: 0.6180791486891902\n",
      "Transfer Entropy from M1 to P3: 0.7141066530638719\n",
      "Transfer Entropy from M1 to Pz: 0.909821512406858\n",
      "Transfer Entropy from M1 to P4: 0.8021909788631344\n",
      "Transfer Entropy from M1 to P8: 0.4252346696563039\n",
      "Transfer Entropy from M1 to POz: 0.7890174990898806\n",
      "Transfer Entropy from M1 to O1: 0.6604098464460043\n",
      "Transfer Entropy from M1 to Oz: 0.6822375190117876\n",
      "Transfer Entropy from M1 to O2: 0.6391347400673207\n",
      "Transfer Entropy from T7 to Fp1: 0.22761504089207293\n",
      "Transfer Entropy from T7 to Fpz: 0.4239460049755076\n",
      "Transfer Entropy from T7 to Fp2: 0.33814743630504857\n",
      "Transfer Entropy from T7 to F7: 0.1944597504923592\n",
      "Transfer Entropy from T7 to F3: 0.3029863691161947\n",
      "Transfer Entropy from T7 to Fz: 0.2525203355964807\n",
      "Transfer Entropy from T7 to F4: 0.332396543779861\n",
      "Transfer Entropy from T7 to F8: 0.376867563582715\n",
      "Transfer Entropy from T7 to FC5: 0.2933285144784581\n",
      "Transfer Entropy from T7 to FC1: 0.4092611806935111\n",
      "Transfer Entropy from T7 to FC2: 0.4249328244537932\n",
      "Transfer Entropy from T7 to FC6: 0.4969823896291912\n",
      "Transfer Entropy from T7 to M1: 0.49071973547447745\n",
      "Transfer Entropy from T7 to C3: 0.3143682061613503\n",
      "Transfer Entropy from T7 to Cz: 0.47534586101104254\n",
      "Transfer Entropy from T7 to C4: 0.5013964653762745\n",
      "Transfer Entropy from T7 to T8: 0.5038427748820057\n",
      "Transfer Entropy from T7 to M2: 0.4989677214183821\n",
      "Transfer Entropy from T7 to CP5: 0.16183906581020063\n",
      "Transfer Entropy from T7 to CP1: 0.55509837768748\n",
      "Transfer Entropy from T7 to CP2: 0.6180650371935951\n",
      "Transfer Entropy from T7 to CP6: 0.5532742739744586\n",
      "Transfer Entropy from T7 to P7: 0.524902325888267\n",
      "Transfer Entropy from T7 to P3: 0.488016750183168\n",
      "Transfer Entropy from T7 to Pz: 0.589082732651706\n",
      "Transfer Entropy from T7 to P4: 0.6357775037585331\n",
      "Transfer Entropy from T7 to P8: 0.521378108959349\n",
      "Transfer Entropy from T7 to POz: 0.6470938548125686\n",
      "Transfer Entropy from T7 to O1: 0.5654459309283346\n",
      "Transfer Entropy from T7 to Oz: 0.4816908775485304\n",
      "Transfer Entropy from T7 to O2: 0.4962223139530741\n",
      "Transfer Entropy from C3 to Fp1: 0.26599422030334374\n",
      "Transfer Entropy from C3 to Fpz: 0.5075861043761491\n",
      "Transfer Entropy from C3 to Fp2: 0.39021067272664656\n",
      "Transfer Entropy from C3 to F7: 0.21736618208897066\n",
      "Transfer Entropy from C3 to F3: 0.37269497146156705\n",
      "Transfer Entropy from C3 to Fz: 0.3293137441282195\n",
      "Transfer Entropy from C3 to F4: 0.4233258532616056\n",
      "Transfer Entropy from C3 to F8: 0.4448526163233863\n",
      "Transfer Entropy from C3 to FC5: 0.3275768729100352\n",
      "Transfer Entropy from C3 to FC1: 0.45662390264475117\n",
      "Transfer Entropy from C3 to FC2: 0.5853391658383275\n",
      "Transfer Entropy from C3 to FC6: 0.5826314024478404\n",
      "Transfer Entropy from C3 to M1: 0.5460034116483873\n",
      "Transfer Entropy from C3 to T7: 0.30525794505866244\n",
      "Transfer Entropy from C3 to Cz: 0.5719632729081359\n",
      "Transfer Entropy from C3 to C4: 0.5884527266755075\n",
      "Transfer Entropy from C3 to T8: 0.574715755189436\n",
      "Transfer Entropy from C3 to M2: 0.5706733166095102\n",
      "Transfer Entropy from C3 to CP5: 0.2063820812401189\n",
      "Transfer Entropy from C3 to CP1: 0.6174597784107029\n",
      "Transfer Entropy from C3 to CP2: 0.6730648642222391\n",
      "Transfer Entropy from C3 to CP6: 0.6286615396568008\n",
      "Transfer Entropy from C3 to P7: 0.6031867586756696\n",
      "Transfer Entropy from C3 to P3: 0.6222820805900595\n",
      "Transfer Entropy from C3 to Pz: 0.8029063632371876\n",
      "Transfer Entropy from C3 to P4: 0.6773142640121943\n",
      "Transfer Entropy from C3 to P8: 0.5960733699661078\n",
      "Transfer Entropy from C3 to POz: 0.7063683729220696\n",
      "Transfer Entropy from C3 to O1: 0.6109749947659162\n",
      "Transfer Entropy from C3 to Oz: 0.5900569885917403\n",
      "Transfer Entropy from C3 to O2: 0.6092954200234817\n",
      "Transfer Entropy from Cz to Fp1: 0.28480675910703523\n",
      "Transfer Entropy from Cz to Fpz: 0.5071831978079726\n",
      "Transfer Entropy from Cz to Fp2: 0.38647272497545315\n",
      "Transfer Entropy from Cz to F7: 0.2500469951653287\n",
      "Transfer Entropy from Cz to F3: 0.41482459542364397\n",
      "Transfer Entropy from Cz to Fz: 0.30539702255159423\n",
      "Transfer Entropy from Cz to F4: 0.42264600503894373\n",
      "Transfer Entropy from Cz to F8: 0.46955272876065457\n",
      "Transfer Entropy from Cz to FC5: 0.4124846419838271\n",
      "Transfer Entropy from Cz to FC1: 0.48128874888437345\n",
      "Transfer Entropy from Cz to FC2: 0.6044827204247961\n",
      "Transfer Entropy from Cz to FC6: 0.6018637538042874\n",
      "Transfer Entropy from Cz to M1: 0.5772639752124228\n",
      "Transfer Entropy from Cz to T7: 0.31885978893068434\n",
      "Transfer Entropy from Cz to C3: 0.3983733094020566\n",
      "Transfer Entropy from Cz to C4: 0.606091637796723\n",
      "Transfer Entropy from Cz to T8: 0.5989982568302028\n",
      "Transfer Entropy from Cz to M2: 0.6020879266861191\n",
      "Transfer Entropy from Cz to CP5: 0.22715511753514855\n",
      "Transfer Entropy from Cz to CP1: 0.7121875114604178\n",
      "Transfer Entropy from Cz to CP2: 0.8050172284026301\n",
      "Transfer Entropy from Cz to CP6: 0.6515702820310094\n",
      "Transfer Entropy from Cz to P7: 0.6315034163606156\n",
      "Transfer Entropy from Cz to P3: 0.6713260541069318\n",
      "Transfer Entropy from Cz to Pz: 0.8305610713509728\n",
      "Transfer Entropy from Cz to P4: 0.8031952400601028\n",
      "Transfer Entropy from Cz to P8: 0.6165286498197367\n",
      "Transfer Entropy from Cz to POz: 0.7780858889704905\n",
      "Transfer Entropy from Cz to O1: 0.627452817472712\n",
      "Transfer Entropy from Cz to Oz: 0.6598440347199691\n",
      "Transfer Entropy from Cz to O2: 0.6440152411518153\n",
      "Transfer Entropy from C4 to Fp1: 0.2275191774530697\n",
      "Transfer Entropy from C4 to Fpz: 0.4431219343979519\n",
      "Transfer Entropy from C4 to Fp2: 0.3037208314855347\n",
      "Transfer Entropy from C4 to F7: 0.2820416525303275\n",
      "Transfer Entropy from C4 to F3: 0.4532265199022479\n",
      "Transfer Entropy from C4 to Fz: 0.39723446494561176\n",
      "Transfer Entropy from C4 to F4: 0.45957377547439576\n",
      "Transfer Entropy from C4 to F8: 0.4103631097284736\n",
      "Transfer Entropy from C4 to FC5: 0.4672289780711388\n",
      "Transfer Entropy from C4 to FC1: 0.5275102141848488\n",
      "Transfer Entropy from C4 to FC2: 0.6561561573247182\n",
      "Transfer Entropy from C4 to FC6: 0.4581155555191046\n",
      "Transfer Entropy from C4 to M1: 0.44791833470872894\n",
      "Transfer Entropy from C4 to T7: 0.36449265438272377\n",
      "Transfer Entropy from C4 to C3: 0.44443186092731285\n",
      "Transfer Entropy from C4 to Cz: 0.6779679052624765\n",
      "Transfer Entropy from C4 to T8: 0.4959258602576995\n",
      "Transfer Entropy from C4 to M2: 0.6016009362276266\n",
      "Transfer Entropy from C4 to CP5: 0.29928942395079783\n",
      "Transfer Entropy from C4 to CP1: 0.688447336698057\n",
      "Transfer Entropy from C4 to CP2: 0.8462868393474471\n",
      "Transfer Entropy from C4 to CP6: 0.46341425984702805\n",
      "Transfer Entropy from C4 to P7: 0.6137324712653139\n",
      "Transfer Entropy from C4 to P3: 0.7249921612162684\n",
      "Transfer Entropy from C4 to Pz: 0.9399977256806578\n",
      "Transfer Entropy from C4 to P4: 0.8138322710724541\n",
      "Transfer Entropy from C4 to P8: 0.5003839377526326\n",
      "Transfer Entropy from C4 to POz: 0.8040994363792496\n",
      "Transfer Entropy from C4 to O1: 0.6679406462325422\n",
      "Transfer Entropy from C4 to Oz: 0.6875079624632604\n",
      "Transfer Entropy from C4 to O2: 0.6412873600007891\n",
      "Transfer Entropy from T8 to Fp1: 0.24964982460632099\n",
      "Transfer Entropy from T8 to Fpz: 0.4797653226930973\n",
      "Transfer Entropy from T8 to Fp2: 0.3395873911293969\n",
      "Transfer Entropy from T8 to F7: 0.2646837701840812\n",
      "Transfer Entropy from T8 to F3: 0.4333858901330164\n",
      "Transfer Entropy from T8 to Fz: 0.37874566418292643\n",
      "Transfer Entropy from T8 to F4: 0.42830455306832677\n",
      "Transfer Entropy from T8 to F8: 0.34845808086859764\n",
      "Transfer Entropy from T8 to FC5: 0.4387354914158649\n",
      "Transfer Entropy from T8 to FC1: 0.501159264435174\n",
      "Transfer Entropy from T8 to FC2: 0.6352359029593639\n",
      "Transfer Entropy from T8 to FC6: 0.42391791931223965\n",
      "Transfer Entropy from T8 to M1: 0.398864907633702\n",
      "Transfer Entropy from T8 to T7: 0.3583212314863955\n",
      "Transfer Entropy from T8 to C3: 0.4265676378963282\n",
      "Transfer Entropy from T8 to Cz: 0.6326928576466867\n",
      "Transfer Entropy from T8 to C4: 0.4643395519887053\n",
      "Transfer Entropy from T8 to M2: 0.5721742189669775\n",
      "Transfer Entropy from T8 to CP5: 0.27289662497741407\n",
      "Transfer Entropy from T8 to CP1: 0.6429466750665006\n",
      "Transfer Entropy from T8 to CP2: 0.8192865734814008\n",
      "Transfer Entropy from T8 to CP6: 0.5403926456217284\n",
      "Transfer Entropy from T8 to P7: 0.5886061053303752\n",
      "Transfer Entropy from T8 to P3: 0.6991534839179641\n",
      "Transfer Entropy from T8 to Pz: 0.8994952265377982\n",
      "Transfer Entropy from T8 to P4: 0.7819066174712515\n",
      "Transfer Entropy from T8 to P8: 0.45416272287548126\n",
      "Transfer Entropy from T8 to POz: 0.7861547877249202\n",
      "Transfer Entropy from T8 to O1: 0.6467492868565516\n",
      "Transfer Entropy from T8 to Oz: 0.6590203798493345\n",
      "Transfer Entropy from T8 to O2: 0.5964088154544178\n",
      "Transfer Entropy from M2 to Fp1: 0.2729832346653959\n",
      "Transfer Entropy from M2 to Fpz: 0.5094704346604599\n",
      "Transfer Entropy from M2 to Fp2: 0.37520690003344453\n",
      "Transfer Entropy from M2 to F7: 0.2555019245965073\n",
      "Transfer Entropy from M2 to F3: 0.38492955702625553\n",
      "Transfer Entropy from M2 to Fz: 0.3538606256699939\n",
      "Transfer Entropy from M2 to F4: 0.4540385109661914\n",
      "Transfer Entropy from M2 to F8: 0.42449246572650545\n",
      "Transfer Entropy from M2 to FC5: 0.38256722097920126\n",
      "Transfer Entropy from M2 to FC1: 0.48762928873033723\n",
      "Transfer Entropy from M2 to FC2: 0.6229090171362787\n",
      "Transfer Entropy from M2 to FC6: 0.5524168297441244\n",
      "Transfer Entropy from M2 to M1: 0.5198949360159302\n",
      "Transfer Entropy from M2 to T7: 0.329828916619646\n",
      "Transfer Entropy from M2 to C3: 0.4016949675770862\n",
      "Transfer Entropy from M2 to Cz: 0.6155832434842541\n",
      "Transfer Entropy from M2 to C4: 0.5590706314417696\n",
      "Transfer Entropy from M2 to T8: 0.5522477580895141\n",
      "Transfer Entropy from M2 to CP5: 0.23464230512466072\n",
      "Transfer Entropy from M2 to CP1: 0.6189841060124309\n",
      "Transfer Entropy from M2 to CP2: 0.7479228310415068\n",
      "Transfer Entropy from M2 to CP6: 0.619640816584136\n",
      "Transfer Entropy from M2 to P7: 0.6330427457217864\n",
      "Transfer Entropy from M2 to P3: 0.6506398339563948\n",
      "Transfer Entropy from M2 to Pz: 0.8150277015405445\n",
      "Transfer Entropy from M2 to P4: 0.7432592726656267\n",
      "Transfer Entropy from M2 to P8: 0.5912004387734271\n",
      "Transfer Entropy from M2 to POz: 0.7364247205878687\n",
      "Transfer Entropy from M2 to O1: 0.5990944908408338\n",
      "Transfer Entropy from M2 to Oz: 0.6129759834623539\n",
      "Transfer Entropy from M2 to O2: 0.5695889107487881\n",
      "Transfer Entropy from CP5 to Fp1: 0.20276766588279074\n",
      "Transfer Entropy from CP5 to Fpz: 0.3950494742723641\n",
      "Transfer Entropy from CP5 to Fp2: 0.31675680383413013\n",
      "Transfer Entropy from CP5 to F7: 0.18125419196131184\n",
      "Transfer Entropy from CP5 to F3: 0.30033438325435846\n",
      "Transfer Entropy from CP5 to Fz: 0.2595997420269019\n",
      "Transfer Entropy from CP5 to F4: 0.288273190389089\n",
      "Transfer Entropy from CP5 to F8: 0.3467223722672132\n",
      "Transfer Entropy from CP5 to FC5: 0.30435119789689213\n",
      "Transfer Entropy from CP5 to FC1: 0.374315445816313\n",
      "Transfer Entropy from CP5 to FC2: 0.4357363305945459\n",
      "Transfer Entropy from CP5 to FC6: 0.44153014082768777\n",
      "Transfer Entropy from CP5 to M1: 0.4432265679399791\n",
      "Transfer Entropy from CP5 to T7: 0.238148429520541\n",
      "Transfer Entropy from CP5 to C3: 0.2928430158398981\n",
      "Transfer Entropy from CP5 to Cz: 0.44856004239163566\n",
      "Transfer Entropy from CP5 to C4: 0.4543071879274041\n",
      "Transfer Entropy from CP5 to T8: 0.4516290057986561\n",
      "Transfer Entropy from CP5 to M2: 0.471179603354463\n",
      "Transfer Entropy from CP5 to CP1: 0.5499837565918735\n",
      "Transfer Entropy from CP5 to CP2: 0.5987868153301504\n",
      "Transfer Entropy from CP5 to CP6: 0.501745868302056\n",
      "Transfer Entropy from CP5 to P7: 0.5041637668744706\n",
      "Transfer Entropy from CP5 to P3: 0.453689229483312\n",
      "Transfer Entropy from CP5 to Pz: 0.6069875823953674\n",
      "Transfer Entropy from CP5 to P4: 0.60859394921269\n",
      "Transfer Entropy from CP5 to P8: 0.4737066160339837\n",
      "Transfer Entropy from CP5 to POz: 0.616158248955714\n",
      "Transfer Entropy from CP5 to O1: 0.5347324545223567\n",
      "Transfer Entropy from CP5 to Oz: 0.4989838148113529\n",
      "Transfer Entropy from CP5 to O2: 0.5007355176586465\n",
      "Transfer Entropy from CP1 to Fp1: 0.28085265404163934\n",
      "Transfer Entropy from CP1 to Fpz: 0.5513275944351442\n",
      "Transfer Entropy from CP1 to Fp2: 0.4123930425903522\n",
      "Transfer Entropy from CP1 to F7: 0.3120042086253545\n",
      "Transfer Entropy from CP1 to F3: 0.45123019953972016\n",
      "Transfer Entropy from CP1 to Fz: 0.4211768211961787\n",
      "Transfer Entropy from CP1 to F4: 0.5238125327518869\n",
      "Transfer Entropy from CP1 to F8: 0.4666262030194362\n",
      "Transfer Entropy from CP1 to FC5: 0.466388403689516\n",
      "Transfer Entropy from CP1 to FC1: 0.5844991287950965\n",
      "Transfer Entropy from CP1 to FC2: 0.7241289172717942\n",
      "Transfer Entropy from CP1 to FC6: 0.6218656436586346\n",
      "Transfer Entropy from CP1 to M1: 0.570665767090662\n",
      "Transfer Entropy from CP1 to T7: 0.3639420147576637\n",
      "Transfer Entropy from CP1 to C3: 0.4452804042215395\n",
      "Transfer Entropy from CP1 to Cz: 0.7415446385160949\n",
      "Transfer Entropy from CP1 to C4: 0.6406168219160892\n",
      "Transfer Entropy from CP1 to T8: 0.6113897442736007\n",
      "Transfer Entropy from CP1 to M2: 0.6162727077013641\n",
      "Transfer Entropy from CP1 to CP5: 0.27994393144847773\n",
      "Transfer Entropy from CP1 to CP2: 0.7681985098593306\n",
      "Transfer Entropy from CP1 to CP6: 0.6758437872381273\n",
      "Transfer Entropy from CP1 to P7: 0.697370575484575\n",
      "Transfer Entropy from CP1 to P3: 0.73420658784119\n",
      "Transfer Entropy from CP1 to Pz: 0.9919956638205839\n",
      "Transfer Entropy from CP1 to P4: 0.7735496026495331\n",
      "Transfer Entropy from CP1 to P8: 0.6138433575184544\n",
      "Transfer Entropy from CP1 to POz: 0.7394211992317483\n",
      "Transfer Entropy from CP1 to O1: 0.6560182533045447\n",
      "Transfer Entropy from CP1 to Oz: 0.7115763909329005\n",
      "Transfer Entropy from CP1 to O2: 0.6809660858900355\n",
      "Transfer Entropy from CP2 to Fp1: 0.30421781335650794\n",
      "Transfer Entropy from CP2 to Fpz: 0.5646288759772858\n",
      "Transfer Entropy from CP2 to Fp2: 0.4291230429293488\n",
      "Transfer Entropy from CP2 to F7: 0.28842373566430163\n",
      "Transfer Entropy from CP2 to F3: 0.46298405185763025\n",
      "Transfer Entropy from CP2 to Fz: 0.39380031283329625\n",
      "Transfer Entropy from CP2 to F4: 0.5396443739655108\n",
      "Transfer Entropy from CP2 to F8: 0.519020172997948\n",
      "Transfer Entropy from CP2 to FC5: 0.45873626265639583\n",
      "Transfer Entropy from CP2 to FC1: 0.5662926163521093\n",
      "Transfer Entropy from CP2 to FC2: 0.7319134378071182\n",
      "Transfer Entropy from CP2 to FC6: 0.6735540127553125\n",
      "Transfer Entropy from CP2 to M1: 0.6425461387006969\n",
      "Transfer Entropy from CP2 to T7: 0.34973186853930105\n",
      "Transfer Entropy from CP2 to C3: 0.4272977356808945\n",
      "Transfer Entropy from CP2 to Cz: 0.7166377731465874\n",
      "Transfer Entropy from CP2 to C4: 0.6700458419963367\n",
      "Transfer Entropy from CP2 to T8: 0.67028654163871\n",
      "Transfer Entropy from CP2 to M2: 0.6375280369295905\n",
      "Transfer Entropy from CP2 to CP5: 0.26974241780418323\n",
      "Transfer Entropy from CP2 to CP1: 0.6644306610759935\n",
      "Transfer Entropy from CP2 to CP6: 0.7236152380464264\n",
      "Transfer Entropy from CP2 to P7: 0.705102261658833\n",
      "Transfer Entropy from CP2 to P3: 0.7338189565156642\n",
      "Transfer Entropy from CP2 to Pz: 1.009245230553781\n",
      "Transfer Entropy from CP2 to P4: 0.7385680535688937\n",
      "Transfer Entropy from CP2 to P8: 0.6851745937716947\n",
      "Transfer Entropy from CP2 to POz: 0.7167524266958696\n",
      "Transfer Entropy from CP2 to O1: 0.6161716761825685\n",
      "Transfer Entropy from CP2 to Oz: 0.7198698617889328\n",
      "Transfer Entropy from CP2 to O2: 0.7308687917076059\n",
      "Transfer Entropy from CP6 to Fp1: 0.23712503359213838\n",
      "Transfer Entropy from CP6 to Fpz: 0.45560025014485045\n",
      "Transfer Entropy from CP6 to Fp2: 0.31190751480795037\n",
      "Transfer Entropy from CP6 to F7: 0.2752122988952096\n",
      "Transfer Entropy from CP6 to F3: 0.45701127072376785\n",
      "Transfer Entropy from CP6 to Fz: 0.40007241304909325\n",
      "Transfer Entropy from CP6 to F4: 0.47087543330620324\n",
      "Transfer Entropy from CP6 to F8: 0.4393704419564172\n",
      "Transfer Entropy from CP6 to FC5: 0.4563405619653145\n",
      "Transfer Entropy from CP6 to FC1: 0.5217609529753696\n",
      "Transfer Entropy from CP6 to FC2: 0.6614396073811792\n",
      "Transfer Entropy from CP6 to FC6: 0.4675166577801748\n",
      "Transfer Entropy from CP6 to M1: 0.46124207713040677\n",
      "Transfer Entropy from CP6 to T7: 0.36914362442736065\n",
      "Transfer Entropy from CP6 to C3: 0.4364730751454995\n",
      "Transfer Entropy from CP6 to Cz: 0.6740313565292575\n",
      "Transfer Entropy from CP6 to C4: 0.4079575264607737\n",
      "Transfer Entropy from CP6 to T8: 0.5169216441989501\n",
      "Transfer Entropy from CP6 to M2: 0.6117063910724522\n",
      "Transfer Entropy from CP6 to CP5: 0.3004210782934484\n",
      "Transfer Entropy from CP6 to CP1: 0.6856097618073231\n",
      "Transfer Entropy from CP6 to CP2: 0.8669077150109646\n",
      "Transfer Entropy from CP6 to P7: 0.6153711492488189\n",
      "Transfer Entropy from CP6 to P3: 0.7344500950373174\n",
      "Transfer Entropy from CP6 to Pz: 0.9450782689708108\n",
      "Transfer Entropy from CP6 to P4: 0.8153349840700354\n",
      "Transfer Entropy from CP6 to P8: 0.4929453408429554\n",
      "Transfer Entropy from CP6 to POz: 0.7958692753280208\n",
      "Transfer Entropy from CP6 to O1: 0.6575521358705486\n",
      "Transfer Entropy from CP6 to Oz: 0.6888025376108107\n",
      "Transfer Entropy from CP6 to O2: 0.6404597743222343\n",
      "Transfer Entropy from P7 to Fp1: 0.25119918165370947\n",
      "Transfer Entropy from P7 to Fpz: 0.49637217298958447\n",
      "Transfer Entropy from P7 to Fp2: 0.368857763155908\n",
      "Transfer Entropy from P7 to F7: 0.259174338237262\n",
      "Transfer Entropy from P7 to F3: 0.42015797018986556\n",
      "Transfer Entropy from P7 to Fz: 0.34259467995486975\n",
      "Transfer Entropy from P7 to F4: 0.42916081642256265\n",
      "Transfer Entropy from P7 to F8: 0.40550129806769014\n",
      "Transfer Entropy from P7 to FC5: 0.41377534441489117\n",
      "Transfer Entropy from P7 to FC1: 0.47506229940989103\n",
      "Transfer Entropy from P7 to FC2: 0.6212094437343963\n",
      "Transfer Entropy from P7 to FC6: 0.5097007478952168\n",
      "Transfer Entropy from P7 to M1: 0.516060964414289\n",
      "Transfer Entropy from P7 to T7: 0.31634397652769036\n",
      "Transfer Entropy from P7 to C3: 0.3877339723979816\n",
      "Transfer Entropy from P7 to Cz: 0.5848997256436373\n",
      "Transfer Entropy from P7 to C4: 0.5169786786107995\n",
      "Transfer Entropy from P7 to T8: 0.5209513395138157\n",
      "Transfer Entropy from P7 to M2: 0.5865202941979875\n",
      "Transfer Entropy from P7 to CP5: 0.2473366970773057\n",
      "Transfer Entropy from P7 to CP1: 0.6555025823465721\n",
      "Transfer Entropy from P7 to CP2: 0.7741693405813315\n",
      "Transfer Entropy from P7 to CP6: 0.5743459486735876\n",
      "Transfer Entropy from P7 to P3: 0.6618620342612336\n",
      "Transfer Entropy from P7 to Pz: 0.8580709032558461\n",
      "Transfer Entropy from P7 to P4: 0.768404418320693\n",
      "Transfer Entropy from P7 to P8: 0.5295737324510357\n",
      "Transfer Entropy from P7 to POz: 0.7599441026378368\n",
      "Transfer Entropy from P7 to O1: 0.6344779857514274\n",
      "Transfer Entropy from P7 to Oz: 0.6069663370639066\n",
      "Transfer Entropy from P7 to O2: 0.5812729857541896\n",
      "Transfer Entropy from P3 to Fp1: 0.28277505134572395\n",
      "Transfer Entropy from P3 to Fpz: 0.5468056980820039\n",
      "Transfer Entropy from P3 to Fp2: 0.40481585648822593\n",
      "Transfer Entropy from P3 to F7: 0.27275276262810133\n",
      "Transfer Entropy from P3 to F3: 0.39360880341621357\n",
      "Transfer Entropy from P3 to Fz: 0.3797184546363368\n",
      "Transfer Entropy from P3 to F4: 0.44324428605691263\n",
      "Transfer Entropy from P3 to F8: 0.4958044442460554\n",
      "Transfer Entropy from P3 to FC5: 0.39928962330612344\n",
      "Transfer Entropy from P3 to FC1: 0.5186131255242833\n",
      "Transfer Entropy from P3 to FC2: 0.6788775775045697\n",
      "Transfer Entropy from P3 to FC6: 0.632285503275481\n",
      "Transfer Entropy from P3 to M1: 0.6120931599791238\n",
      "Transfer Entropy from P3 to T7: 0.32878705199843633\n",
      "Transfer Entropy from P3 to C3: 0.42214121217628126\n",
      "Transfer Entropy from P3 to Cz: 0.6510652227808342\n",
      "Transfer Entropy from P3 to C4: 0.6336933596905726\n",
      "Transfer Entropy from P3 to T8: 0.6366797941091709\n",
      "Transfer Entropy from P3 to M2: 0.6182120038156498\n",
      "Transfer Entropy from P3 to CP5: 0.250619686117817\n",
      "Transfer Entropy from P3 to CP1: 0.6909293884206953\n",
      "Transfer Entropy from P3 to CP2: 0.7970164614954279\n",
      "Transfer Entropy from P3 to CP6: 0.6900603001271559\n",
      "Transfer Entropy from P3 to P7: 0.6729583642534109\n",
      "Transfer Entropy from P3 to Pz: 0.8573290952156406\n",
      "Transfer Entropy from P3 to P4: 0.8003444092054056\n",
      "Transfer Entropy from P3 to P8: 0.6562966457988416\n",
      "Transfer Entropy from P3 to POz: 0.7913375828186647\n",
      "Transfer Entropy from P3 to O1: 0.6729057694689432\n",
      "Transfer Entropy from P3 to Oz: 0.6714088271134114\n",
      "Transfer Entropy from P3 to O2: 0.6859573135512539\n",
      "Transfer Entropy from Pz to Fp1: 0.28611226103862686\n",
      "Transfer Entropy from Pz to Fpz: 0.5197412275855209\n",
      "Transfer Entropy from Pz to Fp2: 0.409060351153753\n",
      "Transfer Entropy from Pz to F7: 0.2639465087968371\n",
      "Transfer Entropy from Pz to F3: 0.4056213572197862\n",
      "Transfer Entropy from Pz to Fz: 0.3695983243439643\n",
      "Transfer Entropy from Pz to F4: 0.4438572612792324\n",
      "Transfer Entropy from Pz to F8: 0.5026368844368214\n",
      "Transfer Entropy from Pz to FC5: 0.4013818709186775\n",
      "Transfer Entropy from Pz to FC1: 0.5133665993942269\n",
      "Transfer Entropy from Pz to FC2: 0.6085302533436973\n",
      "Transfer Entropy from Pz to FC6: 0.6198221509954254\n",
      "Transfer Entropy from Pz to M1: 0.5929499161768697\n",
      "Transfer Entropy from Pz to T7: 0.3018269518329596\n",
      "Transfer Entropy from Pz to C3: 0.4283781835243477\n",
      "Transfer Entropy from Pz to Cz: 0.6070932522211424\n",
      "Transfer Entropy from Pz to C4: 0.6234678265284159\n",
      "Transfer Entropy from Pz to T8: 0.6276026058632869\n",
      "Transfer Entropy from Pz to M2: 0.6008866153268025\n",
      "Transfer Entropy from Pz to CP5: 0.22875700687687325\n",
      "Transfer Entropy from Pz to CP1: 0.7189017051277292\n",
      "Transfer Entropy from Pz to CP2: 0.8508620913248183\n",
      "Transfer Entropy from Pz to CP6: 0.6762782792070746\n",
      "Transfer Entropy from Pz to P7: 0.6648833073233149\n",
      "Transfer Entropy from Pz to P3: 0.6599618828306203\n",
      "Transfer Entropy from Pz to P4: 0.8355532916484941\n",
      "Transfer Entropy from Pz to P8: 0.6436348879513077\n",
      "Transfer Entropy from Pz to POz: 0.8346202051154836\n",
      "Transfer Entropy from Pz to O1: 0.6635358250622138\n",
      "Transfer Entropy from Pz to Oz: 0.6312024138992479\n",
      "Transfer Entropy from Pz to O2: 0.6205787123304894\n",
      "Transfer Entropy from P4 to Fp1: 0.3089480021931509\n",
      "Transfer Entropy from P4 to Fpz: 0.5592582419993397\n",
      "Transfer Entropy from P4 to Fp2: 0.41097035257941833\n",
      "Transfer Entropy from P4 to F7: 0.27244901412699835\n",
      "Transfer Entropy from P4 to F3: 0.43316991485828543\n",
      "Transfer Entropy from P4 to Fz: 0.39658439170282744\n",
      "Transfer Entropy from P4 to F4: 0.5292397852573394\n",
      "Transfer Entropy from P4 to F8: 0.499327177435332\n",
      "Transfer Entropy from P4 to FC5: 0.42067429148983576\n",
      "Transfer Entropy from P4 to FC1: 0.5342203466656243\n",
      "Transfer Entropy from P4 to FC2: 0.7217821126333386\n",
      "Transfer Entropy from P4 to FC6: 0.6359979014064775\n",
      "Transfer Entropy from P4 to M1: 0.6138674625879365\n",
      "Transfer Entropy from P4 to T7: 0.3423126676404655\n",
      "Transfer Entropy from P4 to C3: 0.39867722622352686\n",
      "Transfer Entropy from P4 to Cz: 0.7036578040056441\n",
      "Transfer Entropy from P4 to C4: 0.6417440480400238\n",
      "Transfer Entropy from P4 to T8: 0.633372759018917\n",
      "Transfer Entropy from P4 to M2: 0.6193631521241213\n",
      "Transfer Entropy from P4 to CP5: 0.26020121072894253\n",
      "Transfer Entropy from P4 to CP1: 0.6509452060772606\n",
      "Transfer Entropy from P4 to CP2: 0.7211052575621919\n",
      "Transfer Entropy from P4 to CP6: 0.6880168050335022\n",
      "Transfer Entropy from P4 to P7: 0.690167851933255\n",
      "Transfer Entropy from P4 to P3: 0.7203292134508612\n",
      "Transfer Entropy from P4 to Pz: 0.9758305381264579\n",
      "Transfer Entropy from P4 to P8: 0.6468967789760403\n",
      "Transfer Entropy from P4 to POz: 0.7225874460437725\n",
      "Transfer Entropy from P4 to O1: 0.5953697436524638\n",
      "Transfer Entropy from P4 to Oz: 0.6614312125686215\n",
      "Transfer Entropy from P4 to O2: 0.6753239086754647\n",
      "Transfer Entropy from P8 to Fp1: 0.24392259407346656\n",
      "Transfer Entropy from P8 to Fpz: 0.4731676160157628\n",
      "Transfer Entropy from P8 to Fp2: 0.3345029484405739\n",
      "Transfer Entropy from P8 to F7: 0.2618976474825331\n",
      "Transfer Entropy from P8 to F3: 0.43198080290834356\n",
      "Transfer Entropy from P8 to Fz: 0.37908782915650147\n",
      "Transfer Entropy from P8 to F4: 0.4342890385820715\n",
      "Transfer Entropy from P8 to F8: 0.37730105494787547\n",
      "Transfer Entropy from P8 to FC5: 0.4317311901181148\n",
      "Transfer Entropy from P8 to FC1: 0.5011716902398708\n",
      "Transfer Entropy from P8 to FC2: 0.6384685140523935\n",
      "Transfer Entropy from P8 to FC6: 0.42657333467501796\n",
      "Transfer Entropy from P8 to M1: 0.3730038077135971\n",
      "Transfer Entropy from P8 to T7: 0.354700397684711\n",
      "Transfer Entropy from P8 to C3: 0.42371387525390997\n",
      "Transfer Entropy from P8 to Cz: 0.633499996611392\n",
      "Transfer Entropy from P8 to C4: 0.45143627143975223\n",
      "Transfer Entropy from P8 to T8: 0.43964209881932526\n",
      "Transfer Entropy from P8 to M2: 0.596212379553361\n",
      "Transfer Entropy from P8 to CP5: 0.2708579860269619\n",
      "Transfer Entropy from P8 to CP1: 0.6282375645095174\n",
      "Transfer Entropy from P8 to CP2: 0.8227482704275855\n",
      "Transfer Entropy from P8 to CP6: 0.4999007868742137\n",
      "Transfer Entropy from P8 to P7: 0.5796121090329287\n",
      "Transfer Entropy from P8 to P3: 0.7052043815467225\n",
      "Transfer Entropy from P8 to Pz: 0.9018078768683981\n",
      "Transfer Entropy from P8 to P4: 0.7843588835460187\n",
      "Transfer Entropy from P8 to POz: 0.7799399217482365\n",
      "Transfer Entropy from P8 to O1: 0.6446870259333928\n",
      "Transfer Entropy from P8 to Oz: 0.6602865129903335\n",
      "Transfer Entropy from P8 to O2: 0.5901483811461566\n",
      "Transfer Entropy from POz to Fp1: 0.3058488325837628\n",
      "Transfer Entropy from POz to Fpz: 0.5438917286473721\n",
      "Transfer Entropy from POz to Fp2: 0.3974323709017269\n",
      "Transfer Entropy from POz to F7: 0.29261419265048794\n",
      "Transfer Entropy from POz to F3: 0.46006444790186235\n",
      "Transfer Entropy from POz to Fz: 0.38118453143887054\n",
      "Transfer Entropy from POz to F4: 0.5392110846544154\n",
      "Transfer Entropy from POz to F8: 0.517246041727831\n",
      "Transfer Entropy from POz to FC5: 0.45140823779034733\n",
      "Transfer Entropy from POz to FC1: 0.5452654216586684\n",
      "Transfer Entropy from POz to FC2: 0.7233900643450631\n",
      "Transfer Entropy from POz to FC6: 0.6504106888222768\n",
      "Transfer Entropy from POz to M1: 0.6188130446030056\n",
      "Transfer Entropy from POz to T7: 0.3463809327790957\n",
      "Transfer Entropy from POz to C3: 0.421442434052833\n",
      "Transfer Entropy from POz to Cz: 0.695085368850095\n",
      "Transfer Entropy from POz to C4: 0.6437068168960972\n",
      "Transfer Entropy from POz to T8: 0.6524473948146415\n",
      "Transfer Entropy from POz to M2: 0.6343606692360518\n",
      "Transfer Entropy from POz to CP5: 0.26792201204451355\n",
      "Transfer Entropy from POz to CP1: 0.6258598498988869\n",
      "Transfer Entropy from POz to CP2: 0.7079979881496614\n",
      "Transfer Entropy from POz to CP6: 0.6842725039586182\n",
      "Transfer Entropy from POz to P7: 0.6988512841269896\n",
      "Transfer Entropy from POz to P3: 0.7235996628810841\n",
      "Transfer Entropy from POz to Pz: 1.0033988374843419\n",
      "Transfer Entropy from POz to P4: 0.7315188567910448\n",
      "Transfer Entropy from POz to P8: 0.6621032447982088\n",
      "Transfer Entropy from POz to O1: 0.5040522550485206\n",
      "Transfer Entropy from POz to Oz: 0.7050951202710743\n",
      "Transfer Entropy from POz to O2: 0.7164956509334204\n",
      "Transfer Entropy from O1 to Fp1: 0.2879157257824763\n",
      "Transfer Entropy from O1 to Fpz: 0.5000748663326027\n",
      "Transfer Entropy from O1 to Fp2: 0.3780831236749345\n",
      "Transfer Entropy from O1 to F7: 0.2813700837033936\n",
      "Transfer Entropy from O1 to F3: 0.4327106868384678\n",
      "Transfer Entropy from O1 to Fz: 0.3816143580749602\n",
      "Transfer Entropy from O1 to F4: 0.497881365433139\n",
      "Transfer Entropy from O1 to F8: 0.47828007722228916\n",
      "Transfer Entropy from O1 to FC5: 0.4283644234505236\n",
      "Transfer Entropy from O1 to FC1: 0.5211604477493811\n",
      "Transfer Entropy from O1 to FC2: 0.6767893874608424\n",
      "Transfer Entropy from O1 to FC6: 0.607622135647792\n",
      "Transfer Entropy from O1 to M1: 0.583110582310506\n",
      "Transfer Entropy from O1 to T7: 0.3533451294030663\n",
      "Transfer Entropy from O1 to C3: 0.41189099924103\n",
      "Transfer Entropy from O1 to Cz: 0.6585049028156075\n",
      "Transfer Entropy from O1 to C4: 0.6175644498271423\n",
      "Transfer Entropy from O1 to T8: 0.6133454756795951\n",
      "Transfer Entropy from O1 to M2: 0.5823056835436806\n",
      "Transfer Entropy from O1 to CP5: 0.2700300914126598\n",
      "Transfer Entropy from O1 to CP1: 0.6512620700340936\n",
      "Transfer Entropy from O1 to CP2: 0.7312113750695021\n",
      "Transfer Entropy from O1 to CP6: 0.6498583240445425\n",
      "Transfer Entropy from O1 to P7: 0.6633442503574516\n",
      "Transfer Entropy from O1 to P3: 0.7051634770828585\n",
      "Transfer Entropy from O1 to Pz: 0.9278486806470021\n",
      "Transfer Entropy from O1 to P4: 0.7048952120425446\n",
      "Transfer Entropy from O1 to P8: 0.6226052335977479\n",
      "Transfer Entropy from O1 to POz: 0.5889830924424602\n",
      "Transfer Entropy from O1 to Oz: 0.6508313953265039\n",
      "Transfer Entropy from O1 to O2: 0.6706090000917205\n",
      "Transfer Entropy from Oz to Fp1: 0.27895411465641\n",
      "Transfer Entropy from Oz to Fpz: 0.5284562406015565\n",
      "Transfer Entropy from Oz to Fp2: 0.3942450961859365\n",
      "Transfer Entropy from Oz to F7: 0.2463407700134964\n",
      "Transfer Entropy from Oz to F3: 0.3929228169603419\n",
      "Transfer Entropy from Oz to Fz: 0.3612123355721033\n",
      "Transfer Entropy from Oz to F4: 0.44625056886118014\n",
      "Transfer Entropy from Oz to F8: 0.439282774939853\n",
      "Transfer Entropy from Oz to FC5: 0.3578672074697291\n",
      "Transfer Entropy from Oz to FC1: 0.4983413538762678\n",
      "Transfer Entropy from Oz to FC2: 0.5758763327463812\n",
      "Transfer Entropy from Oz to FC6: 0.5820479867705555\n",
      "Transfer Entropy from Oz to M1: 0.5671435707731142\n",
      "Transfer Entropy from Oz to T7: 0.30359123572497193\n",
      "Transfer Entropy from Oz to C3: 0.3760892011127713\n",
      "Transfer Entropy from Oz to Cz: 0.6024649545973955\n",
      "Transfer Entropy from Oz to C4: 0.5812707964908721\n",
      "Transfer Entropy from Oz to T8: 0.5796809363948214\n",
      "Transfer Entropy from Oz to M2: 0.5605332259628545\n",
      "Transfer Entropy from Oz to CP5: 0.2415387737510631\n",
      "Transfer Entropy from Oz to CP1: 0.6491334300118347\n",
      "Transfer Entropy from Oz to CP2: 0.7571980012909698\n",
      "Transfer Entropy from Oz to CP6: 0.6342426495795793\n",
      "Transfer Entropy from Oz to P7: 0.6001838356093723\n",
      "Transfer Entropy from Oz to P3: 0.6444603825421643\n",
      "Transfer Entropy from Oz to Pz: 0.7835963027587441\n",
      "Transfer Entropy from Oz to P4: 0.7205077166560746\n",
      "Transfer Entropy from Oz to P8: 0.5973476297530016\n",
      "Transfer Entropy from Oz to POz: 0.7555103256179122\n",
      "Transfer Entropy from Oz to O1: 0.618781422982721\n",
      "Transfer Entropy from Oz to O2: 0.5491675015094409\n",
      "Transfer Entropy from O2 to Fp1: 0.2680962760415231\n",
      "Transfer Entropy from O2 to Fpz: 0.5032716643608136\n",
      "Transfer Entropy from O2 to Fp2: 0.37258731619218394\n",
      "Transfer Entropy from O2 to F7: 0.2402288791445957\n",
      "Transfer Entropy from O2 to F3: 0.38220653960286394\n",
      "Transfer Entropy from O2 to Fz: 0.34699060053854974\n",
      "Transfer Entropy from O2 to F4: 0.39920834827980745\n",
      "Transfer Entropy from O2 to F8: 0.3984273366845345\n",
      "Transfer Entropy from O2 to FC5: 0.37571885790177195\n",
      "Transfer Entropy from O2 to FC1: 0.49889110740516707\n",
      "Transfer Entropy from O2 to FC2: 0.5424604971940453\n",
      "Transfer Entropy from O2 to FC6: 0.5282512540448491\n",
      "Transfer Entropy from O2 to M1: 0.5238390919159943\n",
      "Transfer Entropy from O2 to T7: 0.31403881978301934\n",
      "Transfer Entropy from O2 to C3: 0.39140910309991866\n",
      "Transfer Entropy from O2 to Cz: 0.5877067028384575\n",
      "Transfer Entropy from O2 to C4: 0.5352647446042443\n",
      "Transfer Entropy from O2 to T8: 0.5177069517265268\n",
      "Transfer Entropy from O2 to M2: 0.5120614298723932\n",
      "Transfer Entropy from O2 to CP5: 0.2362900554214557\n",
      "Transfer Entropy from O2 to CP1: 0.6251003317790271\n",
      "Transfer Entropy from O2 to CP2: 0.7816889949624142\n",
      "Transfer Entropy from O2 to CP6: 0.5882846398934183\n",
      "Transfer Entropy from O2 to P7: 0.570606202572885\n",
      "Transfer Entropy from O2 to P3: 0.6614497142756367\n",
      "Transfer Entropy from O2 to Pz: 0.7636914586781992\n",
      "Transfer Entropy from O2 to P4: 0.7378666245416413\n",
      "Transfer Entropy from O2 to P8: 0.5321677892014791\n",
      "Transfer Entropy from O2 to POz: 0.7681231418244422\n",
      "Transfer Entropy from O2 to O1: 0.6342821531304308\n",
      "Transfer Entropy from O2 to Oz: 0.5444472315129361\n",
      "Transfer entropy results saved to: /home/vincent/AAA_projects/MVCS/Neuroscience/Analysis/Transfer Entropy/full_granularity_transfer_entropy_results.npy\n"
     ]
    }
   ],
   "source": [
    "import zipfile\n",
    "import numpy as np\n",
    "import os\n",
    "from pyinform import transfer_entropy\n",
    "import shutil\n",
    "\n",
    "# Paths and constants\n",
    "zip_file_path = '/home/vincent/AAA_projects/MVCS/Neuroscience/Analysis/Phase Space/2dembedded_data.zip'\n",
    "extraction_dir = '/home/vincent/AAA_projects/MVCS/Neuroscience/Analysis/Phase Space/temp_extraction'\n",
    "results_dir = '/home/vincent/AAA_projects/MVCS/Neuroscience/Analysis/Transfer Entropy'\n",
    "results_file_name = 'full_granularity_transfer_entropy_results.npy'\n",
    "\n",
    "eeg_channels = ['Fp1', 'Fpz', 'Fp2', 'F7', 'F3', 'Fz', 'F4', 'F8', 'FC5', 'FC1', 'FC2', 'FC6',\n",
    "                'M1', 'T7', 'C3', 'Cz', 'C4', 'T8', 'M2', 'CP5', 'CP1', 'CP2', 'CP6',\n",
    "                'P7', 'P3', 'Pz', 'P4', 'P8', 'POz', 'O1', 'Oz', 'O2']\n",
    "\n",
    "desired_length = 4227688\n",
    "num_bins = 1000\n",
    "k = 1\n",
    "\n",
    "# Helper functions\n",
    "def extract_data(zip_path, extraction_path):\n",
    "    with zipfile.ZipFile(zip_path, 'r') as zipf:\n",
    "        zipf.extractall(extraction_path)\n",
    "    return extraction_path\n",
    "\n",
    "def load_embedded_data(channels, extraction_path):\n",
    "    data = []\n",
    "    for channel in channels:\n",
    "        file_path = os.path.join(extraction_path, f'2dembedded_{channel}_data.npy')\n",
    "        embedding_data = np.load(file_path)\n",
    "        data.append(embedding_data)\n",
    "    return data\n",
    "\n",
    "def bin_data(data, bins):\n",
    "    hist, bin_edges = np.histogram(data, bins=bins)\n",
    "    binned_data = np.digitize(data, bin_edges[:-1]) - 1  # subtract 1 to start binning from 0\n",
    "    return binned_data\n",
    "\n",
    "# Create results directory if it doesn't exist\n",
    "if not os.path.exists(results_dir):\n",
    "    os.makedirs(results_dir)\n",
    "\n",
    "# Main execution\n",
    "extract_data(zip_file_path, extraction_dir)\n",
    "embedding_data_list_2D = load_embedded_data(eeg_channels, extraction_dir)\n",
    "\n",
    "# Trimming and binning the data\n",
    "embedding_data_list_2D_trimmed = [data[:desired_length, 0] for data in embedding_data_list_2D] \n",
    "embedding_data_list_2D_binned = [bin_data(data, num_bins) for data in embedding_data_list_2D_trimmed]\n",
    "\n",
    "# Dictionary to store transfer entropy results\n",
    "TE_results = {}\n",
    "\n",
    "# Compute Transfer Entropy for all pairs\n",
    "for i, source_channel in enumerate(eeg_channels):\n",
    "    for j, target_channel in enumerate(eeg_channels):\n",
    "        if i != j:  # To avoid computing Transfer Entropy for the same channel\n",
    "            try:\n",
    "                TE = transfer_entropy(embedding_data_list_2D_binned[i], embedding_data_list_2D_binned[j], k)\n",
    "                key = f\"{source_channel}_to_{target_channel}\"\n",
    "                TE_results[key] = TE\n",
    "                print(f\"Transfer Entropy from {source_channel} to {target_channel}: {TE}\")\n",
    "            except Exception as e:\n",
    "                print(f\"Error computing Transfer Entropy from {source_channel} to {target_channel}: {e}\")\n",
    "\n",
    "# Save the computed Transfer Entropy results to the specified directory\n",
    "results_file_path = os.path.join(results_dir, results_file_name)\n",
    "np.save(results_file_path, TE_results)\n",
    "\n",
    "print(f\"Transfer entropy results saved to: {results_file_path}\")\n",
    "\n",
    "# Optionally remove the extraction directory after loading the data\n",
    "shutil.rmtree(extraction_dir)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "b8d45dd3-633f-495e-91ff-bd04aa9f3c85",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import networkx as nx\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "\n",
    "# Load Transfer Entropy results from the saved .npy file\n",
    "results_file_path = '/home/vincent/AAA_projects/MVCS/Neuroscience/Analysis/Transfer Entropy/regional_transfer_entropy_results.npy'\n",
    "TE_results = np.load(results_file_path, allow_pickle=True).item()\n",
    "\n",
    "G = nx.DiGraph()  # Create a directed graph\n",
    "\n",
    "# Add edges to the graph\n",
    "for key, value in TE_results.items():\n",
    "    source, target = key.split(\"_to_\")\n",
    "    G.add_edge(source, target, weight=value)\n",
    "\n",
    "# Draw the graph\n",
    "pos = nx.spring_layout(G)  # Positioning of nodes\n",
    "labels = nx.get_edge_attributes(G, 'weight')\n",
    "\n",
    "nx.draw(G, pos, with_labels=True, node_color='skyblue', font_size=16, font_color='black', node_size=2000, edge_color='grey')\n",
    "nx.draw_networkx_edge_labels(G, pos, edge_labels=labels, font_size=12)\n",
    "plt.title('Transfer Entropy Between Brain Regions')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "7c5570d8-94b5-4364-b1dc-ef267e2930ae",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
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