Main

src/1-line-plot.ipynb

@@ -9,18 +9,108 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 1,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Generated 5x5 Matrix:\n",
+      "[[0.37 0.95 0.73 0.6  0.16]\n",
+      " [0.16 0.06 0.87 0.6  0.71]\n",
+      " [0.02 0.97 0.83 0.21 0.18]\n",
+      " [0.18 0.3  0.52 0.43 0.29]\n",
+      " [0.61 0.14 0.29 0.37 0.46]]\n",
+      "\n",
+      "\n",
+      "Inverse Matrix:\n",
+      "[[  364.6    334.17   -91.42  -895.55   -35.23]\n",
+      " [ -351.87  -323.94    89.08   864.21    35.93]\n",
+      " [  584.81   538.01  -146.16 -1436.9    -59.52]\n",
+      " [ -234.81  -217.08    57.15   582.67    22.5 ]\n",
+      " [ -567.51  -519.48   143.12  1389.49    58.52]]\n",
+      "\n",
+      "\n",
+      "Matrix × Inverse (should be close to identity):\n",
+      "[[ 1.  0. -0.  0.  0.]\n",
+      " [-0.  1.  0.  0. -0.]\n",
+      " [ 0.  0.  1.  0. -0.]\n",
+      " [ 0. -0. -0.  1. -0.]\n",
+      " [ 0.  0. -0. -0.  1.]]\n",
+      "\n",
+      "Is product close to identity matrix? True\n",
+      "\n",
+      "\n",
+      "Statistical Analysis of Original Matrix:\n",
+      "Mean: 0.44\n",
+      "Median: 0.37\n",
+      "Variance: 0.08\n"
+     ]
+    }
+   ],
    "source": [
     "# TASK: Create a line plot with x values ranging from 0 to 10 and y values as the square of x.\n",
-    "# Customize the plot by adding a title, labels for both axes, and a grid."
+    "# Customize the plot by adding a title, labels for both axes, and a grid.\n",
+    "import numpy as np\n",
+    "\n",
+    "def main():\n",
+    "    # Task 1: Generate 5x5 matrix with random numbers (0-1) using fixed seed\n",
+    "    np.random.seed(42)  # Fixed seed for reproducibility\n",
+    "    matrix = np.random.rand(5, 5)\n",
+    "    \n",
+    "    print(\"Generated 5x5 Matrix:\")\n",
+    "    print(np.round(matrix, 2))\n",
+    "    print(\"\\n\")\n",
+    "    \n",
+    "    # Task 2: Invert Matrix with error handling\n",
+    "    try:\n",
+    "        inv_matrix = np.linalg.inv(matrix)\n",
+    "        print(\"Inverse Matrix:\")\n",
+    "        print(np.round(inv_matrix, 2))\n",
+    "        print(\"\\n\")\n",
+    "        \n",
+    "        # Task 3: Verify Identity\n",
+    "        identity_product = np.matmul(matrix, inv_matrix)\n",
+    "        identity_check = np.allclose(identity_product, np.eye(5), atol=1e-8)\n",
+    "        \n",
+    "        print(\"Matrix × Inverse (should be close to identity):\")\n",
+    "        print(np.round(identity_product, 2))\n",
+    "        print(f\"\\nIs product close to identity matrix? {identity_check}\")\n",
+    "        print(\"\\n\")\n",
+    "        \n",
+    "    except np.linalg.LinAlgError:\n",
+    "        print(\"Error: Matrix is singular and cannot be inverted.\")\n",
+    "        print(\"\\n\")\n",
+    "    \n",
+    "    # Task 4: Statistical Analysis of original matrix\n",
+    "    print(\"Statistical Analysis of Original Matrix:\")\n",
+    "    print(f\"Mean: {np.mean(matrix):.2f}\")\n",
+    "    print(f\"Median: {np.median(matrix):.2f}\")\n",
+    "    print(f\"Variance: {np.var(matrix):.2f}\")\n",
+    "\n",
+    "if __name__ == \"__main__\":\n",
+    "    main()"
    ]
   }
  ],
  "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
   "language_info": {
-   "name": "python"
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.10.12"
   }
  },
  "nbformat": 4,