Examples
========

Example #1: Equatorial Slice
----------------------------

.. image:: _static/sr_ex_eq_plot.png

.. code-block:: python

    import os
    import sys
    import pysunrunner
    import pysunrunner.pload as pp
    import pysunrunner.io as io
    import pysunrunner.pviz as pviz
    import numpy as np
    import matplotlib.pyplot as plt
    from pathlib import Path
    import requests

    def download_files(base_url, local_dir):
        if not os.path.exists(local_dir):
            os.makedirs(local_dir)

        # Assuming you have a list of filenames
        filenames = ['dbl.out','Bx1.0000.dbl','prs.0000.dbl','rho.0000.dbl','vx1.0000.dbl','grid.out']
        for filename in filenames:
            url = os.path.join(base_url, filename)
            local_path = os.path.join(local_dir, filename)
            response = requests.get(url)
            with open(local_path, 'wb') as f:
                f.write(response.content)
            print(f"Downloaded {filename}")

    base_url = 'http://www.predsci.com/~pete/research/sunrunner/test/output/'
    local_dir = './local_files/'

    download_files(base_url, local_dir)

    time_idx = 0

    # Load PLUTO results for this time point
    D = pp.pload(time_idx, w_dir=local_dir, datatype='dbl')

    # Variable to be plotted
    var_name = 'vx1'

    # Set polar projection for the plot
    subplot_kw = {'projection': "polar"}

    # Set color map for the plot (default is 'rainbow')
    cmap = 'rainbow'

    # Set title for the plot
    title = 'Radial Velocity'

    # Set log_scale to True for a log10 plot of the data (useful for variables like pressure)
    log_scale = False

    # Set r_scale to True to apply r^2 scaling (useful for variables like scaled radial magnetic field or density)
    r_scale = False

    # Create a figure with a single subplot using polar projection
    fig, ax = plt.subplots(subplot_kw=subplot_kw, figsize=(5, 5))

    # Plot the equatorial cut of the data on the polar projection
    axs = pviz.plot_equatorial_cut(D=D, var_name=var_name, ax=ax, cmap=cmap, title=title,
                               r_scale=r_scale, log_scale=log_scale)

    plt.show()

Example #2: Meridonial Slice
----------------------------

.. image:: _static/sr_ex_phi_plot.png

.. code-block:: python

    import os
    import sys
    import pysunrunner
    import pysunrunner.pload as pp
    import pysunrunner.io as io
    import pysunrunner.pviz as pviz
    import numpy as np
    import matplotlib.pyplot as plt
    from pathlib import Path
    import requests

    def download_files(base_url, local_dir):
        if not os.path.exists(local_dir):
            os.makedirs(local_dir)

        # Assuming you have a list of filenames
        filenames = ['dbl.out','Bx1.0000.dbl','prs.0000.dbl','rho.0000.dbl','vx1.0000.dbl','grid.out']
        for filename in filenames:
            url = os.path.join(base_url, filename)
            local_path = os.path.join(local_dir, filename)
            response = requests.get(url)
            with open(local_path, 'wb') as f:
                f.write(response.content)
            print(f"Downloaded {filename}")

    base_url = 'http://www.predsci.com/~pete/research/sunrunner/test/output/'
    local_dir = './local_files/'

    download_files(base_url, local_dir)

    time_idx = 0

    # Load PLUTO results for this time point
    D = pp.pload(time_idx, w_dir=local_dir, datatype='dbl')

    # Variable to be plotted
    var_name = 'Bx1'

    # set phi cut value in degrees.  Here it is set to 295 degrees.
    phi_cut = np.deg2rad(295.0)

    # Set polar projection for the plot
    subplot_kw = {'projection': "polar"}

    # Set color map for the plot (default is 'rainbow')
    cmap = 'coolwarm'

    # Set title for the plot
    title = 'Scaled Radial Magnetic Field, phi = '+str(np.rad2deg(phi_cut))

    # Set log_scale to True for a log10 plot of the data (useful for variables like pressure)
    log_scale = False

    # Set r_scale to True to apply r^2 scaling (useful for variables like scaled radial magnetic field or density)
    r_scale = True

    # convert from code units to nT
    b_fac_pluto = 0.0458505
    
    # Create a figure with a single subplot using polar projection
    fig, ax = plt.subplots(subplot_kw=subplot_kw, figsize=(5, 5))

    # Plot the phi cut of the data on the polar projection
    ax = pviz.plot_phi_cut(D=D, var_name = var_name,
        phi_cut = phi_cut, ax = ax,cmap = cmap, title = title,
        r_scale = r_scale, log_scale=log_scale, conversion_units = b_fac_pluto)

    plt.show()