DeepSeek-Coder/Flagellar_Motor__new.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "provenance": [],
      "authorship_tag": "ABX9TyMzf8pKQLwtDM0mYMXCz0mG",
      "include_colab_link": true
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/Orrm23/DeepSeek-Coder/blob/main/Flagellar_Motor__new.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "pip install numpy scipy matplotlib mrcfile scikit-image\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "VtHNWFURhnKX",
        "outputId": "3c55cad3-2f4a-4aec-81c9-06365d58c9a7"
      },
      "execution_count": 20,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Requirement already satisfied: numpy in /usr/local/lib/python3.11/dist-packages (1.26.4)\n",
            "Requirement already satisfied: scipy in /usr/local/lib/python3.11/dist-packages (1.13.1)\n",
            "Requirement already satisfied: matplotlib in /usr/local/lib/python3.11/dist-packages (3.10.0)\n",
            "Requirement already satisfied: mrcfile in /usr/local/lib/python3.11/dist-packages (1.5.4)\n",
            "Requirement already satisfied: scikit-image in /usr/local/lib/python3.11/dist-packages (0.25.2)\n",
            "Requirement already satisfied: contourpy>=1.0.1 in /usr/local/lib/python3.11/dist-packages (from matplotlib) (1.3.1)\n",
            "Requirement already satisfied: cycler>=0.10 in /usr/local/lib/python3.11/dist-packages (from matplotlib) (0.12.1)\n",
            "Requirement already satisfied: fonttools>=4.22.0 in /usr/local/lib/python3.11/dist-packages (from matplotlib) (4.56.0)\n",
            "Requirement already satisfied: kiwisolver>=1.3.1 in /usr/local/lib/python3.11/dist-packages (from matplotlib) (1.4.8)\n",
            "Requirement already satisfied: packaging>=20.0 in /usr/local/lib/python3.11/dist-packages (from matplotlib) (24.2)\n",
            "Requirement already satisfied: pillow>=8 in /usr/local/lib/python3.11/dist-packages (from matplotlib) (11.1.0)\n",
            "Requirement already satisfied: pyparsing>=2.3.1 in /usr/local/lib/python3.11/dist-packages (from matplotlib) (3.2.1)\n",
            "Requirement already satisfied: python-dateutil>=2.7 in /usr/local/lib/python3.11/dist-packages (from matplotlib) (2.8.2)\n",
            "Requirement already satisfied: networkx>=3.0 in /usr/local/lib/python3.11/dist-packages (from scikit-image) (3.4.2)\n",
            "Requirement already satisfied: imageio!=2.35.0,>=2.33 in /usr/local/lib/python3.11/dist-packages (from scikit-image) (2.37.0)\n",
            "Requirement already satisfied: tifffile>=2022.8.12 in /usr/local/lib/python3.11/dist-packages (from scikit-image) (2025.2.18)\n",
            "Requirement already satisfied: lazy-loader>=0.4 in /usr/local/lib/python3.11/dist-packages (from scikit-image) (0.4)\n",
            "Requirement already satisfied: six>=1.5 in /usr/local/lib/python3.11/dist-packages (from python-dateutil>=2.7->matplotlib) (1.17.0)\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import requests\n",
        "import gzip\n",
        "import shutil\n",
        "import mrcfile\n",
        "import matplotlib.pyplot as plt\n",
        "\n",
        "# Step 1: Download the dataset\n",
        "url = 'https://ftp.ebi.ac.uk/pub/databases/emdb/structures/EMD-0465/map/emd_0465.map.gz'\n",
        "response = requests.get(url)\n",
        "if response.status_code == 200:\n",
        "    with open('emd_0465.map.gz', 'wb') as file:\n",
        "        file.write(response.content)\n",
        "else:\n",
        "    print(f\"Failed to download the file. Status code: {response.status_code}\")\n",
        "\n",
        "# Step 2: Extract the .gz file\n",
        "with gzip.open('emd_0465.map.gz', 'rb') as f_in:\n",
        "    with open('emd_0465.map', 'wb') as f_out:\n",
        "        shutil.copyfileobj(f_in, f_out)\n",
        "\n",
        "# Step 3: Load the map file\n",
        "with mrcfile.open('emd_0465.map', permissive=True) as mrc:\n",
        "    volume = mrc.data\n",
        "    if volume is None:\n",
        "        raise ValueError(\"Failed to load volume data from the map file.\")\n",
        "\n",
        "# Step 4: Visualize the middle slice\n",
        "if volume is not None:\n",
        "    plt.imshow(volume[volume.shape[0] // 2], cmap='gray')\n",
        "    plt.title('Middle Slice of EMD-0465')\n",
        "    plt.show()\n",
        "else:\n",
        "    print(\"Volume data is None. Cannot visualize.\")\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 452
        },
        "id": "44dkua4UjdeG",
        "outputId": "d215ed13-f34d-4247-b3df-92425f02eab7"
      },
      "execution_count": 21,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from scipy.ndimage import gaussian_filter\n",
        "\n",
        "smoothed_volume = gaussian_filter(volume, sigma=1)\n"
      ],
      "metadata": {
        "id": "XqXR-v5Mh28a"
      },
      "execution_count": 22,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "from skimage import filters\n",
        "\n",
        "threshold = filters.threshold_otsu(smoothed_volume)\n",
        "binary_volume = smoothed_volume > threshold\n"
      ],
      "metadata": {
        "id": "i2ohs_TXh-b6"
      },
      "execution_count": 23,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "from scipy.ndimage import label\n",
        "\n",
        "labeled_volume, num_features = label(binary_volume)\n",
        "print(f'Number of features detected: {num_features}')\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "OUyZbEJriDB2",
        "outputId": "dbd65db4-12ef-4d2e-9cff-6fa4bcd79272"
      },
      "execution_count": 24,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Number of features detected: 4\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from skimage.measure import regionprops\n",
        "\n",
        "regions = regionprops(labeled_volume)\n",
        "\n",
        "for region in regions:\n",
        "    if region.area > 100:  # Filter small regions\n",
        "        z, y, x = region.centroid\n",
        "        print(f'Region at z={z}, y={y}, x={x} with area={region.area}')\n",
        "        # Visualize the region\n",
        "        plt.imshow(volume[int(z)], cmap='gray')\n",
        "        plt.scatter(x, y, c='red', s=50)\n",
        "        plt.title(f'Region at slice {int(z)}')\n",
        "        plt.show()\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 470
        },
        "id": "_LYE4usKiJe4",
        "outputId": "48211822-6c2f-413d-b71a-227b14785195"
      },
      "execution_count": 25,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Region at z=34.488482611453946, y=36.455689486129536, x=34.7159841974739 with area=346780.0\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    }
  ]
}