.. DO NOT EDIT.
.. THIS FILE WAS AUTOMATICALLY GENERATED BY SPHINX-GALLERY.
.. TO MAKE CHANGES, EDIT THE SOURCE PYTHON FILE:
.. "auto_examples/plot_basic_usage.py"
.. LINE NUMBERS ARE GIVEN BELOW.

.. only:: html

    .. note::
        :class: sphx-glr-download-link-note

        :ref:`Go to the end <sphx_glr_download_auto_examples_plot_basic_usage.py>`
        to download the full example code.

.. rst-class:: sphx-glr-example-title

.. _sphx_glr_auto_examples_plot_basic_usage.py:


Basic Tracking Example
======================

This example demonstrates how to use the `soft` package to detect and track features in synthetic data.

.. GENERATED FROM PYTHON SOURCE LINES 7-92



.. rst-class:: sphx-glr-horizontal


    *

      .. image-sg:: /auto_examples/images/sphx_glr_plot_basic_usage_001.png
         :alt: Frame 0
         :srcset: /auto_examples/images/sphx_glr_plot_basic_usage_001.png
         :class: sphx-glr-multi-img

    *

      .. image-sg:: /auto_examples/images/sphx_glr_plot_basic_usage_002.png
         :alt: Frame 4
         :srcset: /auto_examples/images/sphx_glr_plot_basic_usage_002.png
         :class: sphx-glr-multi-img


.. rst-class:: sphx-glr-script-out

 .. code-block:: none

    Running tracking...
    Number of cores used: 1
    Cleaning up
    Detecting features...
    Assigning unique IDs...

    0it [00:00, ?it/s]
    0it [00:00, ?it/s]
    Total number of unique IDs: 1
    Feature detection step ended
    Associating features...
    Starting the first round of association
    No associated files found.
    Cleaning up
    Starting tabulation
    No association or source files found for tabulation.
    No dataframe found.






|

.. code-block:: Python


    import numpy as np
    import matplotlib.pyplot as plt
    import soft.soft
    import os
    import shutil
    import astropy.io.fits

    # Create a temporary directory for data
    data_dir = "temp_data"
    os.makedirs(data_dir, exist_ok=True)
    os.makedirs(os.path.join(data_dir, "00-data"), exist_ok=True)
    os.makedirs(os.path.join(data_dir, "01-mask"), exist_ok=True)
    os.makedirs(os.path.join(data_dir, "02-id"), exist_ok=True)
    os.makedirs(os.path.join(data_dir, "03-assoc"), exist_ok=True)


    # Generate synthetic frames
    # We'll create a moving Gaussian blob
    nx, ny = 100, 100
    n_frames = 5
    x, y = np.meshgrid(np.arange(nx), np.arange(ny))

    for t in range(n_frames):
        # Blob moves along x=y
        cx, cy = 20 + t * 5, 20 + t * 5
        sigma = 5
        blob = 100 * np.exp(-((x - cx)**2 + (y - cy)**2) / (2 * sigma**2))

        # Add some noise
        noise = np.random.normal(0, 5, (ny, nx))
        frame = blob + noise

        filename = os.path.join(data_dir, "00-data", f"{t:04d}.fits")
        astropy.io.fits.writeto(filename, frame, overwrite=True)

        # Plot the first and last frame for visualization
        if t == 0 or t == n_frames - 1:
            plt.figure()
            plt.title(f"Frame {t}")
            plt.imshow(frame, origin='lower', cmap='gray')
            plt.colorbar()
            plt.show()

    # Set tracking parameters
    l_thr = 20  # Low threshold
    h_thr = 50  # High threshold
    min_size = 10
    min_distance = 5
    dx = 1.0
    dt = 1.0
    sign = "both"
    separation = True
    verbose = True
    cores = 1

    # Run tracking
    print("Running tracking...")
    soft.soft.track_all(data_dir, cores, min_distance, l_thr, h_thr, min_size, dx, dt, sign, separation, verbose)

    # Check results
    # Read the resulting dataframe
    import pandas as pd
    df_path = os.path.join(data_dir, "dataframe.json")
    if os.path.exists(df_path):
        df = pd.read_json(df_path)
        print("Tracking results:")
        print(df.head())

        # Plot trajectory
        plt.figure()
        plt.title("Tracked Trajectory")
        for label in df['label'].unique():
            subset = df[df['label'] == label]
            plt.plot(subset['X'], subset['Y'], 'o-', label=f'Label {label}')
        plt.legend()
        plt.xlabel("X pixel")
        plt.ylabel("Y pixel")
        plt.show()

    else:
        print("No dataframe found.")

    # Cleanup
    # shutil.rmtree(data_dir)


.. rst-class:: sphx-glr-timing

   **Total running time of the script:** (0 minutes 0.611 seconds)


.. _sphx_glr_download_auto_examples_plot_basic_usage.py:

.. only:: html

  .. container:: sphx-glr-footer sphx-glr-footer-example

    .. container:: sphx-glr-download sphx-glr-download-jupyter

      :download:`Download Jupyter notebook: plot_basic_usage.ipynb <plot_basic_usage.ipynb>`

    .. container:: sphx-glr-download sphx-glr-download-python

      :download:`Download Python source code: plot_basic_usage.py <plot_basic_usage.py>`

    .. container:: sphx-glr-download sphx-glr-download-zip

      :download:`Download zipped: plot_basic_usage.zip <plot_basic_usage.zip>`


.. only:: html

 .. rst-class:: sphx-glr-signature

    `Gallery generated by Sphinx-Gallery <https://sphinx-gallery.github.io>`_