Refactor code for improved readability and consistency across multiple Jupyter notebooks

- Added missing commas in various print statements and function calls for better syntax.
- Reformatted code to enhance clarity, including breaking long lines and aligning parameters.
- Updated function signatures to use float type for sigma parameters instead of int for better precision.
- Cleaned up comments and documentation strings for clarity and consistency.
- Ensured consistent formatting in plotting functions and data handling.

M1/Numerical Methods/TP_DANJOU_Arthur.ipynb

@@ -51,7 +51,7 @@
     "    for h in h_list:\n",
     "        t = np.arange(a, b, h)\n",
     "        y = np.array(\n",
-    "            [3 / 4 * h * f(t[i] + h / 3) + h / 4 * f(t[i] + h) for i in range(len(t))]\n",
+    "            [3 / 4 * h * f(t[i] + h / 3) + h / 4 * f(t[i] + h) for i in range(len(t))],\n",
     "        )\n",
     "        I_approx = np.sum(y)\n",
     "        I.append(I_approx)\n",
@@ -326,7 +326,7 @@
     "            1 + np.power(x, 2) * y - (z + 1) * x,\n",
     "            x * z - np.power(x, 2) * y,\n",
     "            -x * z + 1.45,\n",
-    "        ]\n",
+    "        ],\n",
     "    )\n",
     "\n",
     "\n",