.. DO NOT EDIT.
.. THIS FILE WAS AUTOMATICALLY GENERATED BY SPHINX-GALLERY.
.. TO MAKE CHANGES, EDIT THE SOURCE PYTHON FILE:
.. "examples/suvi/plot_suvi_l2_flloc.py"
.. LINE NUMBERS ARE GIVEN BELOW.

.. only:: html

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

        :ref:`Go to the end <sphx_glr_download_examples_suvi_plot_suvi_l2_flloc.py>`
        to download the full example code.

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

.. _sphx_glr_examples_suvi_plot_suvi_l2_flloc.py:


Plot SUVI L2 Flare Locations
============================
Purpose:
  Use Python to plot the SUVI L2 flare location (flloc) product in various coordinate systems.

.. GENERATED FROM PYTHON SOURCE LINES 10-12

Overview
------------

.. GENERATED FROM PYTHON SOURCE LINES 14-26

In this example, we will be plotting both the flare location (flloc) and peak location (peak_loc) variables from
the flare location product. Flare location is determined by center-of-mass calculations, whereas peak location is
determined by the region with the highest irradiance.

We will plot both flloc and peak_loc for each of the following coordinate systems:
 * Heliographic Stonyhurst `(longitude, latitude)`
 * Heliographic Carrington `(longitude, latitude)`
 * Pixel `(x pixels, y pixels)`
 * R-Theta `(solar radii, degrees)`
 * Helioprojective Cartesian `(x arcsec, y arcsec)`
 * Heliocentric Cartesian `(x AU, y AU, z AU)`
 * Heliocentric Radial `(solar radii, degrees, z solar radii)`

.. GENERATED FROM PYTHON SOURCE LINES 28-30

Imports
-----------

.. GENERATED FROM PYTHON SOURCE LINES 32-33

First, we will import the necessary libraries:

.. GENERATED FROM PYTHON SOURCE LINES 33-50

.. code-block:: Python

    __authors__ = "elucas, ajarvis"

    import matplotlib.pyplot as plt
    import matplotlib.cm as cm
    import numpy as np
    from datetime import datetime, timedelta
    import netCDF4 as nc
    import astropy
    from astropy.coordinates import SkyCoord
    import sunpy
    import sunpy.map
    import astropy.units as u
    from sunpy.coordinates import frames
    from sunpy.net import Fido, attrs as a
    from astropy.io import fits









.. GENERATED FROM PYTHON SOURCE LINES 51-54

Helper Functions
-----------------------------------------
We need to define a few helper functions for use throughout plotting:

.. GENERATED FROM PYTHON SOURCE LINES 54-70

.. code-block:: Python


    # Fetch the SUVI SunPy map to use as a base for plotting.
    def create_suvi_sunpymap(date, goes=16, wavelength=131, rng=2):
        ds0 = (date - timedelta(minutes=rng)).strftime("%Y/%m/%d %H:%M:%S")
        ds1 = (date + timedelta(minutes=rng)).strftime("%Y/%m/%d %H:%M:%S")
        q = Fido.search(a.Time(ds0, ds1), a.Instrument.suvi, a.Wavelength(wavelength*u.angstrom))
        tmp_files = Fido.fetch(q)
        # Select only files for level 2 composites from G16
        for tmp_file in tmp_files:
            if (f'g{goes}' in tmp_file) and ('l2' in tmp_file):
                data, header = fits.getdata(tmp_file, ext=1), fits.getheader(tmp_file, ext=1)
                suvi_map = sunpy.map.Map(data, header)
                return suvi_map, data, header
        print('No SUVI map available')
        return None








.. GENERATED FROM PYTHON SOURCE LINES 71-79

.. code-block:: Python



    # Convert time given in the .nc file to datetime.
    def convert_time(time_nc):
        date_2000 = datetime(2000, 1, 1, 12, 0)
        date = date_2000 + timedelta(seconds=time_nc)
        return date








.. GENERATED FROM PYTHON SOURCE LINES 80-92

.. code-block:: Python



    # Define legend for this product.
    def legend_handles():
        markers = ['o', '*']
        fillstyle = ['none', 'full']
        labels = ['flloc', 'peak_loc']
        f = lambda m, fill: plt.plot([], [], marker=m, color='k', ls='none', fillstyle=fill)[0]
        handles = [f(markers[i], fillstyle[i]) for i in range(len(markers))]
        return handles, labels









.. GENERATED FROM PYTHON SOURCE LINES 93-95

Retrieving the SUVI SunPy Map
-------------------------------

.. GENERATED FROM PYTHON SOURCE LINES 97-100

| Let's use some of the helper functions above to retrieve a SUVI image.
| We'll grab an image of the sun in the 131Å wavelength for datetime 2024-01-23 03:44.
| Example data file: `dr_suvi-l2-flloc_g16_s20240123T034400Z_e20240123T034800Z_v1-0-6.nc <../../_static/suvi/dr_suvi-l2-flloc_g16_s20240123T034400Z_e20240123T034800Z_v1-0-6.nc>`__

.. GENERATED FROM PYTHON SOURCE LINES 100-107

.. code-block:: Python


    date = datetime(2024, 1, 23, 3, 44)
    goes = 16
    wavelength = 131
    suvi_flloc_path = f'../../data/suvi/dr_suvi-l2-flloc_g16_s20240123T034400Z_e20240123T034800Z_v1-0-6.nc'
    flloc_nc = nc.Dataset(suvi_flloc_path)








.. GENERATED FROM PYTHON SOURCE LINES 108-109

Let's look at the variables contained in the flare location files.

.. GENERATED FROM PYTHON SOURCE LINES 109-112

.. code-block:: Python

    for k in flloc_nc.variables.keys():
        print(k)





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

 .. code-block:: none

    time
    wavelength
    degraded_status
    num_flloc
    brght_area
    srs_status
    xrs_status
    euv_status
    flloc_pix
    flloc_hg
    flloc_car
    flloc_rtheta
    flloc_hpc
    flloc_hcc
    flloc_hcr
    tot_flux
    peak_flux
    peak_loc_pix
    peak_loc_hg
    peak_loc_car
    peak_loc_rtheta
    peak_loc_hpc
    peak_loc_hcc
    peak_loc_hcr




.. GENERATED FROM PYTHON SOURCE LINES 113-116

For our examples, we will be looking at the flloc and peak_loc variables.
We can see the general structure by inspecting the variables in any coordinate system, for example,
in Heliographic Stonyhurst.

.. GENERATED FROM PYTHON SOURCE LINES 116-121

.. code-block:: Python


    print(flloc_nc['flloc_hg'])
    print('')
    print(flloc_nc['peak_loc_hg'])





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

 .. code-block:: none

    <class 'netCDF4.Variable'>
    float32 flloc_hg(time, feature_number, wavelength, location)
        long_name: Flare location in Stonyhurst/heliographic coordinates (lon, lat)
        comments: Values provided for on-disk flares only.
        units: degrees, degrees
        _FillValue: -9999.0
    unlimited dimensions: time, feature_number, wavelength
    current shape = (1, 2, 6, 2)
    filling on

    <class 'netCDF4.Variable'>
    float32 peak_loc_hg(time, feature_number, wavelength, location)
        long_name: Peak bright region flux location in Stonyhurst/heliographic coordinates (lon, lat)
        comments: Values provided for on-disk flares only.
        units: degrees, degrees
        _FillValue: -9999.0
    unlimited dimensions: time, feature_number, wavelength
    current shape = (1, 2, 6, 2)
    filling on




.. GENERATED FROM PYTHON SOURCE LINES 122-127

| The structure for both in this example is `(1, 2, 6, 2)`:
|  `1`: The first dimension of the structure is the time dimension, which will always have 1 value for this product.
|  `2`: The second dimension is the number of separate flares within this image.
|  `6`: The third dimension is each wavelength, in the order [094, 131, 171, 195, 284, 304].
|  `2`: The fourth dimension is the coordinate pair (3 for HCC and HCR), with units as described above.

.. GENERATED FROM PYTHON SOURCE LINES 129-131

We need to extract the time (found in the 'time' variable), and convert to python datetime in order to fetch a
corresponding SUVI SunPy map at the closest time possible.

.. GENERATED FROM PYTHON SOURCE LINES 131-137

.. code-block:: Python


    # Get file time
    flloc_time = convert_time(flloc_nc['time'][:][0])
    # Access SUVI SunPy map for that time and defined wavelength
    suvi_map, suvi_data, suvi_header = create_suvi_sunpymap(flloc_time, goes=goes, wavelength=wavelength)





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

 .. code-block:: none

    /home/runner/micromamba/envs/goesr-spwx-examples/lib/python3.12/site-packages/sunpy/net/vso/vso.py:222: SunpyUserWarning: VSO-D400 Bad Request - Invalid wavelength, wavetype of filter specification
      warn_user(resp["error"])

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.. GENERATED FROM PYTHON SOURCE LINES 138-144

Plotting the Flare Locations
----------------------------
Now that the SUVI SunPy map has been retrieved, we can overplot the coordinates from the .nc file onto that image.

`Note: Heliographic Stonyhurst and Heliographic Carrington are only defined on-disk, so any features
(or pieces of features) that extend off-disk will not be plotted.`

.. GENERATED FROM PYTHON SOURCE LINES 146-148

Heliographic Stonyhurst Coordinates
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^

.. GENERATED FROM PYTHON SOURCE LINES 148-219

.. code-block:: Python


    # Plot the SUVI SunPy composite image
    fig_hg = plt.figure(figsize=(10, 10))
    fig_hg.tight_layout(h_pad=-50)
    fig_hg.suptitle(f'Heliographic Stonyhurst Coordinates, GOES-{goes}')
    ax_hg = fig_hg.add_subplot(projection=suvi_map)
    suvi_map.plot(axes=ax_hg, clip_interval=(0.1, 99.9) * u.percent)
    num_points = 100

    # Ignore INFO message about 'Missing metadata for solar radius: assuming the standard radius of the photosphere.'
    # RSUN_REF will be included in future data products.

    # Extract flare location from netCDF
    flloc_hg = flloc_nc['flloc_hg'][:][0]
    peak_hg = flloc_nc['peak_loc_hg'][:][0]

    wavelength_i = list(flloc_nc['wavelength'][:]).index(wavelength)
    colors = cm.Reds_r(np.linspace(0.2, 0.6, len(flloc_hg)))

    # Flare loc
    for flare, c in zip(flloc_hg, colors):
        flare[flare == -9999.] = np.nan
        flare = flare.filled(fill_value=np.nan)

        x = flare[wavelength_i][0]
        y = flare[wavelength_i][1]

        # Convert flare location into SkyCoord object in coordinate frame
        flloc_hgs_sc = SkyCoord(x * u.degree, y * u.degree, obstime=flloc_time, observer=suvi_map.observer_coordinate,
                                frame=frames.HeliographicStonyhurst)

        # Plot contours
        stonyhurst_frame = frames.HeliographicStonyhurst(obstime=suvi_map.date)
        constant_lon = SkyCoord(flloc_hgs_sc.lon, np.linspace(-90, 90, num_points) * u.deg,
                                frame=stonyhurst_frame)
        constant_lat = SkyCoord(np.linspace(-90, 90, num_points) * u.deg, flloc_hgs_sc.lat,
                                frame=stonyhurst_frame)

        ax_hg.plot_coord(constant_lon, color=c, alpha=0.7)
        ax_hg.plot_coord(constant_lat, color=c, alpha=0.7)

        # Transform SkyCoord object to the SUVI SunPy map's coordinate frame
        flloc_hgs_sc = flloc_hgs_sc.transform_to(suvi_map.coordinate_frame)

        # Plot flare
        ax_hg.plot_coord(flloc_hgs_sc, color=c, marker='o', fillstyle='none', markersize=8, alpha=0.7)

    # Peak loc
    for flare, c in zip(peak_hg, colors):
        flare[flare == -9999.] = np.nan
        flare = flare.filled(fill_value=np.nan)

        x = flare[wavelength_i][0]
        y = flare[wavelength_i][1]

        # Convert peak location into SkyCoord object in coordinate frame
        flloc_hgs_sc = SkyCoord(x * u.degree, y * u.degree, obstime=flloc_time, observer=suvi_map.observer_coordinate,
                                frame=frames.HeliographicStonyhurst)

        # Transform SkyCoord object to the SUVI SunPy map's coordinate frame
        flloc_hgs_sc = flloc_hgs_sc.transform_to(suvi_map.coordinate_frame)

        # Plot flare
        ax_hg.plot_coord(flloc_hgs_sc, color=c, marker='*', markersize=4, alpha=0.85)

    # Add legend for features
    handles, labels = legend_handles()
    plt.legend(handles, labels, loc=1, framealpha=1)

    plt.show()




.. image-sg:: /examples/suvi/images/sphx_glr_plot_suvi_l2_flloc_001.png
   :alt: Heliographic Stonyhurst Coordinates, GOES-16, SUVI $131 \; \mathrm{\mathring{A}}$ 2024-01-23 03:45:11
   :srcset: /examples/suvi/images/sphx_glr_plot_suvi_l2_flloc_001.png
   :class: sphx-glr-single-img


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

 .. code-block:: none

    INFO: Missing metadata for solar radius: assuming the standard radius of the photosphere. [sunpy.map.mapbase]
    INFO: Missing metadata for solar radius: assuming the standard radius of the photosphere. [sunpy.map.mapbase]




.. GENERATED FROM PYTHON SOURCE LINES 220-222

Heliographic Carrington Coordinates
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^

.. GENERATED FROM PYTHON SOURCE LINES 222-294

.. code-block:: Python


    # Plot the SUVI SunPy composite image
    fig_car = plt.figure(figsize=(10, 10))
    fig_car.tight_layout(h_pad=-50)
    fig_car.suptitle(f'Heliographic Carrington Coordinates, GOES-{goes}')
    ax_car = fig_car.add_subplot(projection=suvi_map)
    suvi_map.plot(axes=ax_car, clip_interval=(0.1, 99.9) * u.percent)
    num_points = 100

    # Extract flare location from netCDF
    flloc_car = flloc_nc['flloc_car'][:][0]
    peak_car = flloc_nc['peak_loc_car'][:][0]
    wavelength_i = list(flloc_nc['wavelength'][:]).index(wavelength)
    colors = cm.YlOrBr_r(np.linspace(0.5, 0.7, len(flloc_car)))

    # Flare loc
    for flare, c in zip(flloc_car, colors):
        flare[flare == -9999.] = np.nan
        flare = flare.filled(fill_value=np.nan)

        x = flare[wavelength_i][0]
        y = flare[wavelength_i][1]

        # Convert flare location into SkyCoord object in coordinate frame
        flloc_car_sc = SkyCoord(x * u.degree, y * u.degree, obstime=flloc_time, observer=suvi_map.observer_coordinate,
                                frame=frames.HeliographicCarrington)

        # Find Carrington rotation for cycle in degrees
        rot_car = sunpy.coordinates.sun.carrington_rotation_number(t=flloc_time)
        rot_mod = rot_car % 1
        rot_deg = rot_mod * 360.

        # Plot contours, offset by Carrington rotation
        carrington_frame = frames.HeliographicCarrington(obstime=suvi_map.date, observer=suvi_map.observer_coordinate)
        constant_lon = SkyCoord(flloc_car_sc.lon, np.linspace(-90, 90, num_points) * u.deg,
                                frame=carrington_frame)
        constant_lat = SkyCoord(np.linspace(-90. - rot_deg, 90. - rot_deg, num_points) * u.deg, flloc_car_sc.lat,
                                frame=carrington_frame)

        ax_car.plot_coord(constant_lon, color=c, alpha=0.7)
        ax_car.plot_coord(constant_lat, color=c, alpha=0.7)

        # Transform SkyCoord object to the SUVI SunPy map's coordinate frame
        flloc_car_sc = flloc_car_sc.transform_to(suvi_map.coordinate_frame)

        # Plot flare
        ax_car.plot_coord(flloc_car_sc, color=c, marker='o', fillstyle='none', markersize=8, alpha=0.7)

    # Peak loc
    for flare, c in zip(peak_car, colors):
        flare[flare == -9999.] = np.nan
        flare = flare.filled(fill_value=np.nan)

        x = flare[wavelength_i][0]
        y = flare[wavelength_i][1]

        # Convert peak location into SkyCoord object in coordinate frame
        flloc_car_sc = SkyCoord(x * u.degree, y * u.degree, obstime=flloc_time, observer=suvi_map.observer_coordinate,
                                frame=frames.HeliographicCarrington)

        # Transform SkyCoord object to the SUVI SunPy map's coordinate frame
        flloc_car_sc = flloc_car_sc.transform_to(suvi_map.coordinate_frame)

        # Plot flare
        ax_car.plot_coord(flloc_car_sc, color=c, marker='*', markersize=4, alpha=0.85)

    # Add legend for features
    handles, labels = legend_handles()
    plt.legend(handles, labels, loc=1, framealpha=1)

    plt.show()




.. image-sg:: /examples/suvi/images/sphx_glr_plot_suvi_l2_flloc_002.png
   :alt: Heliographic Carrington Coordinates, GOES-16, SUVI $131 \; \mathrm{\mathring{A}}$ 2024-01-23 03:45:11
   :srcset: /examples/suvi/images/sphx_glr_plot_suvi_l2_flloc_002.png
   :class: sphx-glr-single-img





.. GENERATED FROM PYTHON SOURCE LINES 295-297

Pixel Coordinates
^^^^^^^^^^^^^^^^^

.. GENERATED FROM PYTHON SOURCE LINES 297-344

.. code-block:: Python


    # Plot the SUVI SunPy composite image
    fig_px = plt.figure(figsize=(10, 10))
    fig_px.tight_layout()
    ax_px = fig_px.add_subplot(projection=suvi_map)
    suvi_map.plot(axes=ax_px, clip_interval=(0.1, 99.9) * u.percent)
    fig_px.suptitle(f'Pixel Coordinates, GOES-{goes}')
    num_points = 100

    # Extract flare location from netCDF
    flloc_pix = flloc_nc['flloc_pix'][:][0]
    peak_pix = flloc_nc['peak_loc_pix'][:][0]
    wavelength_i = list(flloc_nc['wavelength'][:]).index(wavelength)
    colors = cm.Greens_r(np.linspace(0.3, 0.6, len(flloc_pix)))

    # Flare loc
    for flare, c in zip(flloc_pix, colors):
        flare[flare == -9999.] = np.nan
        flare = flare.filled(fill_value=np.nan)

        x = flare[wavelength_i][0]
        y = flare[wavelength_i][1]

        # Plot crosshairs
        ax_px.axvline(x=x, color=c, alpha=0.7)
        ax_px.axhline(y=y, color=c, alpha=0.7)

        # Plot flare
        ax_px.plot_coord(x, y, color=c, marker='o', fillstyle='none', markersize=8, alpha=0.7)

    # Peak loc
    for flare, c in zip(peak_pix, colors):
        flare[flare == -9999.] = np.nan
        flare = flare.filled(fill_value=np.nan)

        x = flare[wavelength_i][0]
        y = flare[wavelength_i][1]

        # Plot flare
        ax_px.plot_coord(x, y, color=c, marker='*', markersize=4, alpha=0.85)

    # Add legend for features
    handles, labels = legend_handles()
    plt.legend(handles, labels, loc=1, framealpha=1)

    plt.show()




.. image-sg:: /examples/suvi/images/sphx_glr_plot_suvi_l2_flloc_003.png
   :alt: Pixel Coordinates, GOES-16, SUVI $131 \; \mathrm{\mathring{A}}$ 2024-01-23 03:45:11
   :srcset: /examples/suvi/images/sphx_glr_plot_suvi_l2_flloc_003.png
   :class: sphx-glr-single-img





.. GENERATED FROM PYTHON SOURCE LINES 345-347

R-Theta Coordinates
^^^^^^^^^^^^^^^^^^^

.. GENERATED FROM PYTHON SOURCE LINES 347-428

.. code-block:: Python


    # Plot the SUVI SunPy map
    fig_rt = plt.figure(figsize=(10, 10))
    fig_rt.suptitle(f'R-Theta Coordinates, GOES-{goes}')
    fig_rt.tight_layout(h_pad=-50)
    ax_rt = fig_rt.add_subplot(projection=suvi_map)
    suvi_map.plot(axes=ax_rt, clip_interval=(0.1, 99.9) * u.percent)
    num_points = 100

    # Extract flare location from netCDF
    flloc_rt = flloc_nc['flloc_rtheta'][:][0]
    peak_rt = flloc_nc['peak_loc_rtheta'][:][0]
    wavelength_i = list(flloc_nc['wavelength'][:]).index(wavelength)
    colors = cm.Purples_r(np.linspace(0.3, 0.6, len(flloc_rt)))

    # Flare loc
    for flare, c in zip(flloc_rt, colors):
        flare[flare == -9999.] = np.nan
        flare = flare.filled(fill_value=np.nan)
        # Need to rotate psi by 90 degrees, according to SkyCoord cylindrical specifications
        rho = flare[wavelength_i][0]
        psi = flare[wavelength_i][1] + 90.

        # R-Theta trigonometry to find correct z for initializing SkyCoord object
        # z is assumed to be 0 if feature is off-disk
        solar_radius = 1.
        if -1. <= rho <= 1.:
            angle = np.arcsin(rho / solar_radius)
            z = solar_radius * np.cos(angle)
        else:
            z = 0.

        # Create SkyCoord object in heliocentric frame
        flloc_rt_sc = SkyCoord(rho=rho * u.solRad, psi=psi * u.deg, z=z * u.solRad, representation_type='cylindrical',
                               obstime=flloc_time, observer=suvi_map.observer_coordinate, frame=frames.Heliocentric)

        # Plot r/psi 'crosshairs'
        heliocentric_frame = frames.Heliocentric(obstime=suvi_map.date, observer=suvi_map.observer_coordinate)
        r_vector = SkyCoord(rho=flloc_rt_sc.rho, psi=np.linspace(-360, 0, num_points) * u.deg, z=z * u.solRad,
                            frame=heliocentric_frame, representation_type='cylindrical')
        constant_psi = SkyCoord(rho=np.linspace(0, rho, num_points) * u.solRad, psi=flloc_rt_sc.psi, z=z * u.solRad,
                                frame=heliocentric_frame, representation_type='cylindrical')

        ax_rt.plot_coord(r_vector, color=c, alpha=0.7)
        ax_rt.plot_coord(constant_psi, color=c, alpha=0.7)

        # Plot flare
        flloc_rt_sc = flloc_rt_sc.transform_to(suvi_map.coordinate_frame)
        ax_rt.plot_coord(flloc_rt_sc, color=c, marker='o', fillstyle='none', markersize=8, alpha=0.7)

    # Peak loc
    for flare, c in zip(peak_rt, colors):
        flare[flare == -9999.] = np.nan
        flare = flare.filled(fill_value=np.nan)
        # Need to rotate psi by 90 degrees, according to SkyCoord cylindrical specifications
        rho = flare[wavelength_i][0]
        psi = flare[wavelength_i][1] + 90.

        # R-Theta trigonometry to find correct z for initializing SkyCoord object
        # z is assumed to be 0 if feature is off-disk
        solar_radius = 1.
        if -1. <= rho <= 1.:
            angle = np.arcsin(rho / solar_radius)
            z = solar_radius * np.cos(angle)
        else:
            z = 0.

        # Create SkyCoord object in heliocentric frame
        flloc_rt_sc = SkyCoord(rho=rho * u.solRad, psi=psi * u.deg, z=z * u.solRad, representation_type='cylindrical',
                               obstime=flloc_time, observer=suvi_map.observer_coordinate, frame=frames.Heliocentric)

        # Plot flare
        flloc_rt_sc = flloc_rt_sc.transform_to(suvi_map.coordinate_frame)
        ax_rt.plot_coord(flloc_rt_sc, color=c, marker='*', markersize=4, alpha=0.85)

    # Add legend for features
    handles, labels = legend_handles()
    plt.legend(handles, labels, loc=1, framealpha=1)

    plt.show()




.. image-sg:: /examples/suvi/images/sphx_glr_plot_suvi_l2_flloc_004.png
   :alt: R-Theta Coordinates, GOES-16, SUVI $131 \; \mathrm{\mathring{A}}$ 2024-01-23 03:45:11
   :srcset: /examples/suvi/images/sphx_glr_plot_suvi_l2_flloc_004.png
   :class: sphx-glr-single-img





.. GENERATED FROM PYTHON SOURCE LINES 429-431

Helioprojective Cartesian Coordinates
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^

.. GENERATED FROM PYTHON SOURCE LINES 431-508

.. code-block:: Python


    # Plot the composite image
    fig_hpc = plt.figure(figsize=(10, 10))
    fig_hpc.tight_layout(h_pad=-50)
    fig_hpc.suptitle(f'Helioprojective Cartesian Coordinates, GOES-{goes}')
    ax_hpc = fig_hpc.add_subplot(projection=suvi_map)
    suvi_map.plot(axes=ax_hpc, clip_interval=(0.1, 99.9) * u.percent)
    num_points = 100

    x_limits = ax_hpc.get_xlim()
    y_limits = ax_hpc.get_ylim()

    # Extract flare location from netCDF
    flloc_hpc = flloc_nc['flloc_hpc'][:][0]
    wavelength_i = list(flloc_nc['wavelength'][:]).index(wavelength)

    peak_hpc = flloc_nc['peak_loc_hpc'][:][0]

    colors = cm.Blues_r(np.linspace(0., 0.3, len(flloc_hpc)))

    for flare, c in zip(flloc_hpc, colors):
        flare[flare == -9999.] = np.nan
        flare = flare.filled(fill_value=np.nan)
        wavelength_i = list(flloc_nc['wavelength'][:]).index(wavelength)

        x = float(flare[wavelength_i][0])
        y = float(flare[wavelength_i][1])

        # Convert flare location into skycoord object in heliographic stonyhurst frame
        flloc_hpc_sc = SkyCoord(x * u.arcsec, y * u.arcsec, obstime=flloc_time, observer=suvi_map.observer_coordinate,
                                frame=frames.Helioprojective)

        # Set params
        line_resolution = 100

        # Draw x dimension of crosshairs
        x_location = np.repeat(x, line_resolution) * u.arcsec
        y_line = np.linspace(-1600, 1600, line_resolution) * u.arcsec
        # Draw y dimension of crosshairs
        y_location = np.repeat(y, line_resolution) * u.arcsec
        x_line = np.linspace(-1600, 1600, line_resolution) * u.arcsec

        # Transform skycoord object to the suvi sunpy map's coordinate frame
        flloc_hpc_sc = flloc_hpc_sc.transform_to(suvi_map.coordinate_frame)

        ax_hpc.plot(x_line.to(u.deg), y_location.to(u.deg), color=c, transform=ax_hpc.get_transform("world"))
        ax_hpc.plot(x_location.to(u.deg), y_line.to(u.deg), color=c, transform=ax_hpc.get_transform("world"))

        # Plot flare
        ax_hpc.plot_coord(flloc_hpc_sc, color=c, marker='o', fillstyle='none', markersize=8, alpha=0.7)

    for flare, c in zip(peak_hpc, colors):
        flare[flare == -9999.] = np.nan
        flare = flare.filled(fill_value=np.nan)
        wavelength_i = list(flloc_nc['wavelength'][:]).index(wavelength)

        x = float(flare[wavelength_i][0])
        y = float(flare[wavelength_i][1])

        # Convert flare location into skycoord object in heliographic stonyhurst frame
        flloc_hpc_sc = SkyCoord(x * u.arcsec, y * u.arcsec, obstime=flloc_time, observer=suvi_map.observer_coordinate,
                                frame=frames.Helioprojective)

        # Transform skycoord object to the suvi sunpy map's coordinate frame
        flloc_hpc_sc = flloc_hpc_sc.transform_to(suvi_map.coordinate_frame)

        # Plot flare
        ax_hpc.plot_coord(flloc_hpc_sc, color=c, marker='*', markersize=4, alpha=0.85)

    # add legend for features
    handles, labels = legend_handles()
    plt.legend(handles, labels, loc=1, framealpha=1)
    ax_hpc.set_xlim(x_limits)
    ax_hpc.set_ylim(y_limits)

    plt.show()




.. image-sg:: /examples/suvi/images/sphx_glr_plot_suvi_l2_flloc_005.png
   :alt: Helioprojective Cartesian Coordinates, GOES-16, SUVI $131 \; \mathrm{\mathring{A}}$ 2024-01-23 03:45:11
   :srcset: /examples/suvi/images/sphx_glr_plot_suvi_l2_flloc_005.png
   :class: sphx-glr-single-img





.. GENERATED FROM PYTHON SOURCE LINES 509-511

Heliocentric Cartesian Coordinates
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^

.. GENERATED FROM PYTHON SOURCE LINES 511-602

.. code-block:: Python


    # Plot the composite image
    fig_hcc = plt.figure(figsize=(10, 10))
    fig_hcc.tight_layout(h_pad=-50)
    fig_hcc.suptitle(f'Heliocentric Cartesian Coordinates, GOES-{goes}')
    ax_hcc = fig_hcc.add_subplot(projection=suvi_map)
    suvi_map.plot(axes=ax_hcc, clip_interval=(0.1, 99.9) * u.percent)
    num_points = 100

    x_limits = ax_hcc.get_xlim()
    y_limits = ax_hcc.get_ylim()

    # Extract flare location from netCDF
    flloc_hcc = flloc_nc['flloc_hcc'][:][0]
    wavelength_i = list(flloc_nc['wavelength'][:]).index(wavelength)

    peak_hcc = flloc_nc['peak_loc_hcc'][:][0]

    colors = cm.PiYG(np.linspace(0., 0.3, len(flloc_hcc)))

    for flare, c in zip(flloc_hcc, colors):
        flare[flare == -9999.] = np.nan
        flare = flare.filled(fill_value=np.nan)
        wavelength_i = list(flloc_nc['wavelength'][:]).index(wavelength)

        x = float(flare[wavelength_i][0])
        y = float(flare[wavelength_i][1])
        z = float(flare[wavelength_i][2])

        # Convert flare location into skycoord object in heliographic stonyhurst frame
        flloc_hcc_sc = SkyCoord(x * u.AU, y * u.AU, z * u.AU, obstime=flloc_time, observer=suvi_map.observer_coordinate,
                                frame=frames.Heliocentric)

        # Plot flare
        ax_hcc.plot_coord(flloc_hcc_sc, color=c, marker='o', fillstyle='none', markersize=8, alpha=0.7)

        # Set params
        line_resolution = 100

        # sunpy.sun.constants.AU.value*1E-3
        # Draw x dimension of crosshairs
        x_location = (np.repeat(x, line_resolution))
        y_line = (np.linspace(-0.00764747, 0.00765689, line_resolution))
        # Draw y dimension of crosshairs
        y_location = (np.repeat(y, line_resolution))
        x_line = (np.linspace(-0.00764747, 0.00765689, line_resolution))

        # Set up the coord instance for the X-position of a feature (flare/peak/centroid, etc)
        coord_x = SkyCoord(astropy.coordinates.representation.CartesianRepresentation(x_location * u.AU, y_line * u.AU,
                                                                                      np.repeat(0,
                                                                                                line_resolution) * u.AU),
                           obstime=flloc_time, observer=suvi_map.observer_coordinate, frame=frames.Heliocentric)

        # Set up the coord instance for the Y-position of a feature (flare/peak/centroid, etc)
        coord_y = SkyCoord(astropy.coordinates.representation.CartesianRepresentation(x_line * u.AU, y_location * u.AU,
                                                                                      np.repeat(0,
                                                                                                line_resolution) * u.AU),
                           obstime=flloc_time, observer=suvi_map.observer_coordinate, frame=frames.Heliocentric)
        ax_hcc.plot_coord(coord_x, color=c)
        ax_hcc.plot_coord(coord_y, color=c)
        # Transform skycoord object to the suvi sunpy map's coordinate frame
        # flloc_hcc_sc = flloc_hcc_sc.transform_to(suvi_map.coordinate_frame)

    for flare, c in zip(peak_hcc, colors):
        flare[flare == -9999.] = np.nan
        flare = flare.filled(fill_value=np.nan)
        wavelength_i = list(flloc_nc['wavelength'][:]).index(wavelength)

        x = float(flare[wavelength_i][0])
        y = float(flare[wavelength_i][1])
        z = float(flare[wavelength_i][2])

        # Convert flare location into skycoord object in heliographic stonyhurst frame
        flloc_hcc_sc = SkyCoord(x * u.AU, y * u.AU, z * u.AU, obstime=flloc_time, observer=suvi_map.observer_coordinate,
                                frame=frames.Heliocentric)

        # Transform skycoord object to the suvi sunpy map's coordinate frame
        flloc_hcc_sc = flloc_hcc_sc.transform_to(suvi_map.coordinate_frame)

        # Plot flare
        ax_hcc.plot_coord(flloc_hcc_sc, color=c, marker='*', markersize=4, alpha=0.85)

    # add legend for features
    handles, labels = legend_handles()
    plt.legend(handles, labels, loc=1, framealpha=1)

    ax_hcc.set_xlim(x_limits)
    ax_hcc.set_ylim(y_limits)

    plt.show()




.. image-sg:: /examples/suvi/images/sphx_glr_plot_suvi_l2_flloc_006.png
   :alt: Heliocentric Cartesian Coordinates, GOES-16, SUVI $131 \; \mathrm{\mathring{A}}$ 2024-01-23 03:45:11
   :srcset: /examples/suvi/images/sphx_glr_plot_suvi_l2_flloc_006.png
   :class: sphx-glr-single-img





.. GENERATED FROM PYTHON SOURCE LINES 603-605

Heliocentric Radial Coordinates
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^

.. GENERATED FROM PYTHON SOURCE LINES 605-668

.. code-block:: Python



    # Plot the SUVI SunPy map
    fig_hcr = plt.figure(figsize=(10, 10))
    fig_hcr.suptitle(f'Heliocentric Radial Coordinates, GOES-{goes}')
    fig_hcr.tight_layout(h_pad=-50)
    ax_hcr = fig_hcr.add_subplot(projection=suvi_map)
    suvi_map.plot(axes=ax_hcr, clip_interval=(0.1, 99.9) * u.percent)

    # Extract flare location from netCDF
    flloc_hcr = flloc_nc['flloc_hcr'][:][0]
    wavelength_i = list(flloc_nc['wavelength'][:]).index(wavelength)

    peak_rt = flloc_nc['peak_loc_hcr'][:][0]

    colors = cm.BuPu(np.linspace(0.85, 1., len(flloc_hcr)))

    for flare, c in zip(flloc_hcr, colors):
        flare[flare == -9999.] = np.nan
        flare = flare.filled(fill_value=np.nan)
        # Need to rotate theta by 90 to get psi, according to SkyCoord cylindrical specifications
        rho = flare[wavelength_i][0]
        psi = flare[wavelength_i][1] + 90.
        z = flare[wavelength_i][2]

        # Create SkyCoord object in heliocentric frame
        flloc_hcr_sc = SkyCoord(rho=rho * u.solRad, psi=psi * u.deg, z=z * u.solRad, representation_type='cylindrical',
                                obstime=flloc_time, observer=suvi_map.observer_coordinate, frame=frames.Heliocentric)

        # Plot r/psi 'crosshairs'
        heliocentric_frame = frames.Heliocentric(obstime=suvi_map.date, observer=suvi_map.observer_coordinate)
        r_vector = SkyCoord(rho=flloc_hcr_sc.rho, psi=np.linspace(-360, 0, num_points) * u.deg, z=z * u.solRad,
                            frame=heliocentric_frame, representation_type='cylindrical')
        constant_psi = SkyCoord(rho=np.linspace(0, rho, num_points) * u.solRad, psi=flloc_hcr_sc.psi, z=z * u.solRad,
                                frame=heliocentric_frame, representation_type='cylindrical')

        ax_hcr.plot_coord(r_vector, color=c, alpha=0.7)
        ax_hcr.plot_coord(constant_psi, color=c, alpha=0.7)

        # Plot flare
        flloc_hcr_sc = flloc_hcr_sc.transform_to(suvi_map.coordinate_frame)
        ax_hcr.plot_coord(flloc_hcr_sc, color=c, marker='o', fillstyle='none', markersize=8, alpha=0.7)

    for flare, c in zip(peak_rt, colors):
        flare[flare == -9999.] = np.nan
        flare = flare.filled(fill_value=np.nan)
        # Need to rotate theta by 90 to get psi, according to SkyCoord cylindrical specifications
        rho = flare[wavelength_i][0]
        psi = flare[wavelength_i][1] + 90.
        z = flare[wavelength_i][2]

        # Create SkyCoord object in heliocentric frame
        flloc_hcr_sc = SkyCoord(rho=rho * u.solRad, psi=psi * u.deg, z=z * u.solRad, representation_type='cylindrical',
                                obstime=flloc_time, observer=suvi_map.observer_coordinate, frame=frames.Heliocentric)
        # Plot flare
        flloc_hcr_sc = flloc_hcr_sc.transform_to(suvi_map.coordinate_frame)
        ax_hcr.plot_coord(flloc_hcr_sc, color=c, marker='*', markersize=4, alpha=0.85)

    # add legend for features
    handles, labels = legend_handles()
    plt.legend(handles, labels, loc=1, framealpha=1)

    plt.show()



.. image-sg:: /examples/suvi/images/sphx_glr_plot_suvi_l2_flloc_007.png
   :alt: Heliocentric Radial Coordinates, GOES-16, SUVI $131 \; \mathrm{\mathring{A}}$ 2024-01-23 03:45:11
   :srcset: /examples/suvi/images/sphx_glr_plot_suvi_l2_flloc_007.png
   :class: sphx-glr-single-img






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

   **Total running time of the script:** (0 minutes 18.649 seconds)


.. _sphx_glr_download_examples_suvi_plot_suvi_l2_flloc.py:

.. only:: html

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

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

      :download:`Download Jupyter notebook: plot_suvi_l2_flloc.ipynb <plot_suvi_l2_flloc.ipynb>`

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

      :download:`Download Python source code: plot_suvi_l2_flloc.py <plot_suvi_l2_flloc.py>`

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

      :download:`Download zipped: plot_suvi_l2_flloc.zip <plot_suvi_l2_flloc.zip>`


.. only:: html

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

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