FYS-STK4155/doc/Programs/HeisenbergIsingModels/Heisenberg3D_Vector_Classification.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import os\n",
    "import numpy as np\n",
    "import tensorflow as tf\n",
    "from tensorflow import keras\n",
    "from sklearn.model_selection import train_test_split\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "from matplotlib.colors import ListedColormap\n",
    "from sklearn.metrics import classification_report"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Get the current working directory of the notebook\n",
    "notebook_dir = os.getcwd()\n",
    "\n",
    "# Define the directories for Ferromagnetic and Paramagnetic data\n",
    "ferromagnetic_dir = os.path.join(notebook_dir, \"Ferromagnetic\")\n",
    "paramagnetic_dir = os.path.join(notebook_dir, \"Paramagnetic\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "comp = ''\n",
    "dim = 10\n",
    "steps = 10**6\n",
    "train_per_label = 3000\n",
    "ind_test_per_temp = 500"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Load data\n",
    "ferromagnetic_data = [np.load(os.path.join(ferromagnetic_dir, file)) for file in os.listdir(ferromagnetic_dir) if file.endswith('.npy')]\n",
    "paramagnetic_data = [np.load(os.path.join(paramagnetic_dir, file)) for file in os.listdir(paramagnetic_dir) if file.endswith('.npy')]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Create labels\n",
    "ferromagnetic_labels = np.ones(len(ferromagnetic_data))\n",
    "paramagnetic_labels = np.zeros(len(paramagnetic_data))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Combine data and labels\n",
    "data = np.concatenate([ferromagnetic_data, paramagnetic_data], axis=0)\n",
    "labels = np.concatenate([ferromagnetic_labels, paramagnetic_labels], axis=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Get the dimensions of the data\n",
    "x_dim, y_dim, z_dim, _ = data.shape[1:]\n",
    "\n",
    "# Convert the data to a 4D array\n",
    "data = data.reshape(-1, x_dim, y_dim, z_dim, 3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Split the data into training, validation, and test sets.\n",
    "X_train, X_temp, y_train, y_temp = train_test_split(data, labels, test_size=0.3, random_state=42)\n",
    "X_val, X_test, y_val, y_test = train_test_split(X_temp, y_temp, test_size=0.5, random_state=42)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Model Architecture\n",
    "model = tf.keras.Sequential([\n",
    "    tf.keras.layers.Conv3D(32, kernel_size=(3, 3, 3), activation='relu', input_shape=(x_dim, y_dim, z_dim, 3)),\n",
    "    tf.keras.layers.MaxPooling3D(pool_size=(2, 2, 2)),\n",
    "    tf.keras.layers.Conv3D(64, kernel_size=(3, 3, 3), activation='relu'),\n",
    "    tf.keras.layers.MaxPooling3D(pool_size=(2, 2, 2)),\n",
    "    tf.keras.layers.Flatten(),\n",
    "    tf.keras.layers.Dense(128, activation='relu'),\n",
    "    tf.keras.layers.Dense(1, activation='linear')  # Use linear activation for regression\n",
    "])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Compile the model with Mean Squared Error (MSE) loss\n",
    "model.compile(optimizer='adam', loss='mean_squared_error', metrics=['accuracy'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1/10\n",
      "132/132 [==============================] - 4s 20ms/step - loss: 0.0175 - accuracy: 0.9819 - val_loss: 2.2447e-05 - val_accuracy: 1.0000\n",
      "Epoch 2/10\n",
      "132/132 [==============================] - 2s 18ms/step - loss: 1.5618e-05 - accuracy: 1.0000 - val_loss: 1.0525e-05 - val_accuracy: 1.0000\n",
      "Epoch 3/10\n",
      "132/132 [==============================] - 2s 18ms/step - loss: 1.0447e-05 - accuracy: 1.0000 - val_loss: 8.8909e-06 - val_accuracy: 1.0000\n",
      "Epoch 4/10\n",
      "132/132 [==============================] - 2s 18ms/step - loss: 7.8524e-06 - accuracy: 1.0000 - val_loss: 5.7154e-06 - val_accuracy: 1.0000\n",
      "Epoch 5/10\n",
      "132/132 [==============================] - 2s 19ms/step - loss: 1.1048e-05 - accuracy: 1.0000 - val_loss: 7.3484e-06 - val_accuracy: 1.0000\n",
      "Epoch 6/10\n",
      "132/132 [==============================] - 2s 18ms/step - loss: 6.1966e-06 - accuracy: 1.0000 - val_loss: 4.2561e-06 - val_accuracy: 1.0000\n",
      "Epoch 7/10\n",
      "132/132 [==============================] - 2s 19ms/step - loss: 7.4232e-06 - accuracy: 1.0000 - val_loss: 3.6668e-05 - val_accuracy: 1.0000\n",
      "Epoch 8/10\n",
      "132/132 [==============================] - 3s 19ms/step - loss: 7.0051e-06 - accuracy: 1.0000 - val_loss: 4.4029e-06 - val_accuracy: 1.0000\n",
      "Epoch 9/10\n",
      "132/132 [==============================] - 3s 19ms/step - loss: 6.9637e-06 - accuracy: 1.0000 - val_loss: 6.2811e-06 - val_accuracy: 1.0000\n",
      "Epoch 10/10\n",
      "132/132 [==============================] - 3s 19ms/step - loss: 9.4459e-06 - accuracy: 1.0000 - val_loss: 1.4238e-05 - val_accuracy: 1.0000\n"
     ]
    }
   ],
   "source": [
    "# Train the model\n",
    "history = model.fit(X_train, y_train, validation_data=(X_val, y_val), epochs=10, batch_size=32)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Visualize the performance of training and validation accuracy\n",
    "plt.plot(history.history['accuracy'])\n",
    "plt.plot(history.history['val_accuracy'])\n",
    "plt.title('3D Heisenberg - Model Accuracy')\n",
    "plt.xlabel('Epoch')\n",
    "plt.ylabel('Accuracy')\n",
    "\n",
    "pow = str(steps).count('0')\n",
    "labels = [f'Lattice size ${dim}^3$', f'Steps $10^{pow}$', f'Files per label {train_per_label}']\n",
    "\n",
    "plt.legend(['Train', 'Validation'], loc='upper right', bbox_to_anchor=(1, 0.95))\n",
    "\n",
    "# Adding a box inside the plot with additional information\n",
    "additional_info = '\\n'.join(labels)\n",
    "plt.text(0.7, 0.05, additional_info, transform=plt.gca().transAxes, bbox=dict(facecolor='white', alpha=0.5))\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Visualize the performance of training and validation loss\n",
    "plt.plot(history.history['loss'])\n",
    "plt.plot(history.history['val_loss'])\n",
    "plt.title('3D Heisenberg - Model Loss')\n",
    "plt.xlabel('Epoch')\n",
    "plt.ylabel('Loss')\n",
    "plt.legend(['Train', 'Validation'], loc='upper right', bbox_to_anchor=(1, 1))\n",
    "plt.text(0.7, 0.1, additional_info, transform=plt.gca().transAxes, bbox=dict(facecolor='white', alpha=0.5))\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "29/29 [==============================] - 0s 4ms/step - loss: 1.4064e-05 - accuracy: 1.0000\n",
      "Test Loss: 1.406379942636704e-05\n",
      "Test Accuracy: 1.0\n"
     ]
    }
   ],
   "source": [
    "# Evaluate the model\n",
    "loss, accuracy = model.evaluate(X_test, y_test)\n",
    "print(\"Test Loss:\", loss)\n",
    "print(\"Test Accuracy:\", accuracy)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "29/29 [==============================] - 0s 4ms/step\n",
      "Test Accuracy: 1.0\n",
      "              precision    recall  f1-score   support\n",
      "\n",
      "         0.0       1.00      1.00      1.00       440\n",
      "         1.0       1.00      1.00      1.00       460\n",
      "\n",
      "    accuracy                           1.00       900\n",
      "   macro avg       1.00      1.00      1.00       900\n",
      "weighted avg       1.00      1.00      1.00       900\n",
      "\n"
     ]
    }
   ],
   "source": [
    "from sklearn.metrics import accuracy_score, confusion_matrix\n",
    "# Make predictions on the test data\n",
    "predictions = model.predict(X_test)\n",
    "# Calculate accuracy and classification report\n",
    "threshold = 0.5  # Threshold for classification\n",
    "predicted_labels = (predictions > threshold).astype(int).flatten()\n",
    "test_accuracy = (predicted_labels == y_test).mean()\n",
    "print(\"Test Accuracy:\", test_accuracy)\n",
    "print(classification_report(y_test, predicted_labels))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Define label names\n",
    "label_names = ['Paramagnetic', 'Ferromagnetic']\n",
    "\n",
    "# Create confusion matrix\n",
    "confusion = confusion_matrix(y_test, predicted_labels)\n",
    "\n",
    "# Create a heatmap of the confusion matrix\n",
    "sns.heatmap(confusion, annot=True, fmt='d', cmap=ListedColormap(['orange', 'blue']),\n",
    "            xticklabels=label_names, yticklabels=label_names)\n",
    "plt.title('Confusion Matrix - 3D Heisenberg model classification')\n",
    "plt.xlabel('Predicted Labels')\n",
    "plt.ylabel('True Labels')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Clear variables that are no longer needed\n",
    "del X_train, y_train, X_test, y_test, data, labels, history, predictions, predicted_labels\n",
    "del ferromagnetic_data, paramagnetic_data, ferromagnetic_labels, paramagnetic_labels, X_temp, y_temp, y_val, X_val"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1/1 [==============================] - 0s 18ms/step\n",
      "1/1 [==============================] - 0s 19ms/step\n",
      "1/1 [==============================] - 0s 18ms/step\n",
      "1/1 [==============================] - 0s 17ms/step\n",
      "1/1 [==============================] - 0s 18ms/step\n",
      "1/1 [==============================] - 0s 16ms/step\n",
      "1/1 [==============================] - 0s 18ms/step\n",
      "1/1 [==============================] - 0s 19ms/step\n",
      "1/1 [==============================] - 0s 20ms/step\n",
      "1/1 [==============================] - 0s 21ms/step\n",
      "1/1 [==============================] - 0s 20ms/step\n",
      "1/1 [==============================] - 0s 20ms/step\n",
      "1/1 [==============================] - 0s 16ms/step\n",
      "1/1 [==============================] - 0s 18ms/step\n",
      "1/1 [==============================] - 0s 16ms/step\n",
      "1/1 [==============================] - 0s 29ms/step\n",
      "1/1 [==============================] - 0s 26ms/step\n",
      "1/1 [==============================] - 0s 22ms/step\n",
      "1/1 [==============================] - 0s 25ms/step\n",
      "1/1 [==============================] - 0s 19ms/step\n",
      "1/1 [==============================] - 0s 17ms/step\n",
      "1/1 [==============================] - 0s 21ms/step\n",
      "1/1 [==============================] - 0s 26ms/step\n",
      "1/1 [==============================] - 0s 15ms/step\n",
      "1/1 [==============================] - 0s 23ms/step\n",
      "1/1 [==============================] - 0s 26ms/step\n",
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     ]
    }
   ],
   "source": [
    "import pandas as pd\n",
    "# Get the current working directory of the notebook\n",
    "notebook_dir = os.getcwd()\n",
    "\n",
    "# Define the directories for Ferromagnetic and Paramagnetic data\n",
    "directory = os.path.join(notebook_dir, \"For Testing\")\n",
    "\n",
    "subdirectories = [subdir for subdir in os.listdir(directory) if os.path.isdir(os.path.join(directory, subdir))]\n",
    "\n",
    "table_data = []\n",
    "\n",
    "Avg_Predictions = []\n",
    "for subdir in subdirectories:\n",
    "    temp = float(subdir)\n",
    "    if temp == 1.44:\n",
    "        continue\n",
    "    if temp < 1.44:\n",
    "        label = 'Ferromagnetic'\n",
    "        accuracy_func = lambda acc: acc\n",
    "    else:\n",
    "        label = 'Paramagnetic'\n",
    "        accuracy_func = lambda acc: 100 - acc\n",
    "    subdir_path = os.path.join(directory, subdir)\n",
    "    file_names = [file_name for file_name in os.listdir(subdir_path) if file_name.endswith('.npy')]\n",
    "    num_of_correct_predictions = 0\n",
    "    num_of_files = 0\n",
    "\n",
    "    Predictions_at_T = []\n",
    "    for file_name in file_names:\n",
    "        file_path = os.path.join(subdir_path, file_name)\n",
    "        new_data = np.load(file_path)\n",
    "        new_data = new_data.reshape(1, x_dim, y_dim, z_dim, 3)  # Reshape for model input\n",
    "        predictions = model.predict(new_data)\n",
    "        predicted_label = 'Ferromagnetic' if predictions[0][0] > 0.5 else 'Paramagnetic'\n",
    "        Predictions_at_T.append(predictions[0][0])\n",
    "        if predicted_label == label:\n",
    "            num_of_correct_predictions += 1\n",
    "        num_of_files += 1\n",
    "        \n",
    "    Avg_Predictions.append((temp, np.mean(Predictions_at_T), np.std(Predictions_at_T)))\n",
    "\n",
    "\n",
    "    accuracy = (num_of_correct_predictions / num_of_files) * 100\n",
    "    orderliness = accuracy_func(accuracy)\n",
    "    table_data.append((temp, orderliness))\n",
    "\n",
    "# Create a Pandas DataFrame from the table data\n",
    "df = pd.DataFrame(table_data, columns=['Temperature', 'Orderliness'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 900x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Sort the DataFrame by Temperature df = df.sort_values(by='Temperature')\n",
    "# Plot the graph\n",
    "plt.figure(figsize=(9, 6))\n",
    "plt.plot(df['Temperature'], df['Orderliness'], marker='o')\n",
    "plt.xlabel('Temperature (K)')\n",
    "plt.ylabel('Orderliness')\n",
    "plt.title('3D Heisenberg Model - Orderliness vs Temperature')\n",
    "plt.grid(True)\n",
    "\n",
    "# Store the graph values in a text file\n",
    "graph_data = pd.concat([df['Temperature'], df['Orderliness']], axis=1)\n",
    "graph_data.to_csv('orderliness_vs_temperature.txt', sep='\\t', index=False, header=False)\n",
    "\n",
    "pow = str(steps).count('0')\n",
    "labels = [f'Lattice size ${dim}^3$', f'Steps $10^{pow}$', f'Files per label {train_per_label}',\n",
    "          f'Independent testing files per temperature {ind_test_per_temp}']\n",
    "\n",
    "\n",
    "plt.legend(['Orderliness'], loc='upper right', frameon=False, bbox_to_anchor=(1, 0.95))\n",
    "\n",
    "# Adding a box inside the plot with additional information\n",
    "additional_info = '\\n'.join(labels)\n",
    "plt.text(0.6, 0.1, additional_info, transform=plt.gca().transAxes, bbox=dict(facecolor='white', alpha=0.5), fontsize=8)\n",
    "\n",
    "\n",
    "# Save the graph as an image\n",
    "plt.savefig('orderliness_vs_temperature.png')\n",
    "\n",
    "# Display the table\n",
    "#print(df)\n",
    "#print(Avg_Predictions)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 900x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Create a Pandas DataFrame from the table data\n",
    "df2 = pd.DataFrame(Avg_Predictions, columns=['Temperature', 'Avg_Predictions', 'Std_Deviation'])\n",
    "\n",
    "# Sort the DataFrame by Temperature\n",
    "df2 = df2.sort_values(by='Temperature')\n",
    "\n",
    "plt.figure(figsize=(9, 6))\n",
    "# Set the color of vertical error bars to red\n",
    "plt.errorbar(df2['Temperature'], df2['Avg_Predictions'], yerr=df2['Std_Deviation'], marker='o', ecolor='red')\n",
    "plt.xlabel('Temperature (K)')\n",
    "plt.ylabel('Avg Prediction')\n",
    "plt.title('3D Heisenberg Model - Average Prediction vs Temperature')\n",
    "plt.grid(True)\n",
    "\n",
    "# Store the graph values in a text file\n",
    "graph_data = pd.concat([df2['Temperature'], df2['Avg_Predictions'], df2['Std_Deviation']], axis=1)\n",
    "graph_data.to_csv('Average_Prediction_vs_temperature.txt', sep='\\t', index=False, header=False)\n",
    "\n",
    "plt.legend(['Avg Prediction'], loc='upper right', frameon=False, bbox_to_anchor=(1, 0.95))\n",
    "\n",
    "plt.text(0.6, 0.1, additional_info, transform=plt.gca().transAxes, bbox=dict(facecolor='white', alpha=0.5), fontsize=8)\n",
    "\n",
    "# Display the table\n",
    "#print(df2)\n",
    "plt.savefig('Average_Prediction_vs_temperature.png')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 900x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Create a Pandas DataFrame from the table data\n",
    "df2 = pd.DataFrame(Avg_Predictions, columns=['Temperature', 'Avg_Predictions', 'Std_Deviation'])\n",
    "\n",
    "# Sort the DataFrame by Temperature\n",
    "df2 = df2.sort_values(by='Temperature')\n",
    "\n",
    "# Define how many data points to drop from each end\n",
    "num_points_to_drop = 8\n",
    "\n",
    "# Drop data points from both ends\n",
    "df2 = df2.iloc[num_points_to_drop:-num_points_to_drop]\n",
    "\n",
    "plt.figure(figsize=(9, 6))\n",
    "# Plot the graph\n",
    "plt.errorbar(df2['Temperature'], df2['Avg_Predictions'], yerr=df2['Std_Deviation'], marker='o', ecolor='red')\n",
    "plt.xlabel('Temperature (K)')\n",
    "plt.ylabel('Avg Prediction')\n",
    "plt.title('3D Heisenberg Model - Average Prediction vs Temperature')\n",
    "plt.grid(True)\n",
    "\n",
    "# Store the graph values in a text file\n",
    "graph_data = pd.concat([df2['Temperature'], df2['Avg_Predictions'], df2['Std_Deviation']], axis=1)\n",
    "graph_data.to_csv('Average_Prediction_vs_temperature_narrow_band.txt', sep='\\t', index=False, header=False)\n",
    "\n",
    "plt.legend(['Avg Prediction'], loc='upper right', frameon=False, bbox_to_anchor=(1, 0.95))\n",
    "\n",
    "plt.text(0.1, 0.1, additional_info, transform=plt.gca().transAxes, bbox=dict(facecolor='white', alpha=0.5), fontsize=8)\n",
    "\n",
    "# Display the table\n",
    "plt.savefig('Average_Prediction_vs_temperature_narrow_band.png')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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