Using TracerMP Defaults

Perform simple tracing using the TracerMP class.

This example demonstrates how to use the TracerMP class to perform forward tracing of magnetic field lines from a set of default starting points.

import matplotlib.pyplot as plt

from mapflpy.tracer import TracerMP
from mapflpy.utils import plot_traces
from mapflpy.data import fetch_cor_magfiles

Load in the magnetic field files

The fetch_cor_magfiles() function returns a tuple of file paths corresponding to the radial, theta, and phi components of the magnetic field data.

magnetic_field_files = fetch_cor_magfiles()

The TracerMP class can be instantiated directly with the magnetic field file paths (along with any additional “mapfl params” as keyword arguments).

For now, the default mapfl configuration is used i.e. DEFAULT_PARAMS.

with TracerMP(*magnetic_field_files, context=CONTEXT) as tracer:
    traces = tracer.trace_fwd()

Note

The TracerMP class utilizes multiprocessing to instantiate a new mapflpy_fortran object in a worker process, and communicates with it via inter-process communication. The Pipe() protocol requires that the multiprocessing.connection.Connection is properly opened and closed to avoid resource leaks. Therefore, it is recommended to use the TracerMP class within a context manager (the with statement) to ensure that resources are properly managed.

Alternatively, the connect() and disconnect() methods can be used to manually manage the connection lifecycle.

The shape of the resulting traces geometry is an M x 3 x N array, where M is the field line length (i.e. the buffer_size), N is the number of launch points (here 128), and the second dimension corresponds to the radial-theta-phi coordinates.

The utility functions provided in utils are designed to work with this contiguous memory layout for efficient processing and visualization.

Traces can be plotted using the plot_traces() utility function

ax = plt.figure().add_subplot(projection='3d')
plot_traces(traces, ax=ax)

FOV = 4.0  # Rsun
for dim in 'xyz':
    getattr(ax, f'set_{dim}lim3d')((-FOV, FOV))
ax.set_box_aspect([1, 1, 1])

plt.show()