PFSS and Outflow Field Line Comparison
======================================

This script calculates PFSS and Outflow fields, traces field lines and plots them to show the difference in field line/streamer shapes.

.. code-block:: python

    import outflowpy

    import numpy as np
    import random
    import matplotlib.pyplot as plt
    import astropy.constants as const
    import matplotlib.patches as patches

    #Specify model resolutions
    ns = 90
    nphi = 180
    nrho = 60
    rss = 4.0

    #Download data for a specific date and time
    obs_time = "2017-08-21T00:00:00"
    hmi_map = outflowpy.obtain_data.prepare_hmi_mdi_time(obs_time, ns, nphi, smooth = 1.0*5e-2/nphi, use_cached = True)

    #Set up Input files for PFSS and default outflow profile
    pfss_in = outflowpy.Input(hmi_map, nrho, rss, mf_constant = 0.0)
    outflow_in = outflowpy.Input(hmi_map, nrho, rss)

    #Calculate the magnetic fields
    pfss_out = outflowpy.outflow(pfss_in)
    outflow_out = outflowpy.outflow(outflow_in)

    #Calculate field line seeds
    #Alternatives are commented out -- either constrained to one plane, distributed based on Thomson Scattering, or completely random

    seeds = outflowpy.utils.equal_seed_sampler(outflow_out, 100, 1.5) #Constrained to one plane
    #seeds = outflowpy.utils.plane_seed_sampler(outflow_out, 250, 1.5, rss = 2.5) #Seeds distributed according to Thomson Scattering
    #seeds = outflowpy.utils.random_seed_sampler(outflow_out, 250, 1.5, rss = 2.5) #Seeds distributed randomly in all three dimensions

    #Set up FastTracer -- the Fortran tracer in the correct geometry
    tracer = outflowpy.tracing.FastTracer()

    field_lines_pfss = tracer.trace(seeds, pfss_out, save_flag = True)
    field_lines_outflow = tracer.trace(seeds, outflow_out, save_flag = True)

    #Define field line plotter function
    def plot_fieldlines(ax, field_lines, title):
        transformed_lines = []

        for fi, fline in enumerate(field_lines):
            coords = fline.coords
            coords.representation_type = 'cartesian'
            line = np.zeros((2, len(coords)))
            line[0,:] = coords.y/const.R_sun; line[1,:] = coords.z/const.R_sun
            transformed_lines.append([line[0,:], line[1,:]])

            ax.plot(line[0,:], line[1,:], c = 'blue', linewidth = 0.5, zorder = 0)

        circle = patches.Circle(
            (0.0, 0.0),
            1.0,
            facecolor="#fc9e23",
            edgecolor="black",
            linewidth=1
        )

        ax.add_patch(circle)
        ax.axis('equal')
        ax.set_xticks([])
        ax.set_yticks([])
        ax.set_axis_off()

        ax.set_title(title)

        return

    fig, axs = plt.subplots(2,1, figsize = (6.9, 10.0))

    ax = axs[0]
    plot_fieldlines(ax, field_lines_pfss, 'PFSS')
    ax = axs[1]
    plot_fieldlines(ax, field_lines_outflow, 'Outflow')

    plt.tight_layout()
    plt.show()

Expected output:

.. image:: images/3_plot_comparison.png