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

    Click :ref:`here <sphx_glr_download_auto_examples_rgb_iris.py>` to download the full example code
.. rst-class:: sphx-glr-example-title

.. _sphx_glr_auto_examples_rgb_iris.py:


Convert to RGB format (vector data)
===========================
This example demonstrates convertion from wind data to uv rgb format (with HKO earth format).


Definitions
--------------------------------------------------------



Import all required modules and methods:



.. code-block:: python


    # Python package to allow system command line functions
    import os
    # Python package to manage warning message
    import warnings
    # Python package for time calculations
    import pandas as pd
    # Python package for numerical calculations
    import numpy as np
    # Python package for image generation
    from PIL import Image
    # Python package for image preview
    import matplotlib.pyplot as plt

    # swirlspy iris parser function
    from swirlspy.rad.iris import read_iris_grid
    # swirlspy regrid function
    from swirlspy.preprocess import grid_align
    # swirlspy rgb convertion function
    from swirlspy.utils.conversion import to_rgb_data, to_hko_earth_format
    # directory constants
    from swirlspy.tests.samples import DATA_DIR
    from swirlspy.tests.outputs import OUTPUT_DIR

    warnings.filterwarnings("ignore")

    # Logging
    start_time = pd.Timestamp.now()







Loading radar data
-----------------------------------------------------------------------




.. code-block:: python


    # Specify the basetime
    basetime = pd.Timestamp('201902190800')

    # Reading the wind data
    reflec = read_iris_grid(
        os.path.join(
            DATA_DIR,
            basetime.strftime("iris/ppi/TMS%y%m%d%H%M02.PPIMK3B")
        )
    )

    initialising_time = pd.Timestamp.now()








Reproject to WGS 84, required for HKO earth format
-----------------------------------------------------------------------




.. code-block:: python


    # calculate x, y step size
    y_step = -0.025
    x_step = 0.025
    y = np.arange(24.5, 20.5, y_step)
    x = np.arange(112, 116, x_step)

    reflec_wgs84 = grid_align(
        reflec, reflec.attrs['area_def'].proj_str,
        x, y, '+proj=longlat +datum=WGS84 +no_defs'
    )

    preparation_time = pd.Timestamp.now()







Convert image data into rgb format
-----------------------------------------------------------------------




.. code-block:: python


    # only shape with (y, x) is allowed
    data = reflec_wgs84.sel(time=basetime)

    # only allow positive values
    data = data.where(data >= 0)

    # this step is not necessary, depends on any meta data and preprocess is required by your platform
    earth_data = to_hko_earth_format(data, coords_dp=3, y_step=y_step, x_step=x_step)
    rgb = to_rgb_data(earth_data)

    convertion_time = pd.Timestamp.now()







Visualisation
-----------------------------------------------------------------------




.. code-block:: python


    path = os.path.join(OUTPUT_DIR, "rgb_wind.png")
    with Image.fromarray(rgb, 'RGBA') as img:
        img.save(path, 'png')

    # preview
    with Image.open(path) as image:
        plt.axis('off')
        plt.imshow(image)
        plt.plot()
        plt.show()

    visualise_time = pd.Timestamp.now()




.. image:: /auto_examples/images/sphx_glr_rgb_iris_001.png
    :class: sphx-glr-single-img




Checking run time of each component
-----------------------------------------------------------------------




.. code-block:: python


    print(f"Start time: {start_time}")
    print(f"Initialising time: {initialising_time}")
    print(f"Preparation time: {preparation_time}")
    print(f"Convertion time: {convertion_time}")
    print(f"Visualise time: {visualise_time}")

    print(f"Time to initialise: {initialising_time - start_time}")
    print(f"Time to prepare information: {preparation_time - initialising_time}")
    print(f"Time to convertion: {convertion_time - preparation_time}")
    print(f"Time to visualise: {visualise_time - convertion_time}")

    print(f"Total: {visualise_time - start_time}")




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

 Out:

 .. code-block:: none

    Start time: 2025-07-24 14:54:54.745834
    Initialising time: 2025-07-24 14:54:54.765841
    Preparation time: 2025-07-24 14:54:54.897652
    Convertion time: 2025-07-24 14:54:54.905468
    Visualise time: 2025-07-24 14:54:54.933522
    Time to initialise: 0 days 00:00:00.020007
    Time to prepare information: 0 days 00:00:00.131811
    Time to convertion: 0 days 00:00:00.007816
    Time to visualise: 0 days 00:00:00.028054
    Total: 0 days 00:00:00.187688


**Total running time of the script:** ( 0 minutes  0.190 seconds)


.. _sphx_glr_download_auto_examples_rgb_iris.py:


.. only :: html

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



  .. container:: sphx-glr-download

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



  .. container:: sphx-glr-download

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


.. only:: html

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

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