Logger reader
Before thinking about the reader implementation, lets start by imagining the kind of API we would like to provide to users.
with logger.Reader(basename) as f:
# Create a logger.ParticleSet of the particles we want to track.
# This function loops over all the index files and get all the particles
# contain cache for the particle set (for later)
particle_set = f.get_particles(type="Gas", cache=True)
particle_set -= f.get_particles(ids=[...])
# remove the use of the cache
particle_set.cache_enabled(False)
# Read some fields for some particles. This generates a new ParticleSet that
# contains the particles from `particle_set` that exist at time `time`, and
# populates their position and velocities.
particles_at_time_t = f.get_particle_data(
particles=particle_set,
fields=["Coordinates", "Velocities"],
time=time,
interpolation="linear")
# Extract the particle positions as an Nx3 matrix.
positions = particles_at_time_t["Coordinates"]
# Move a set of particles forward in time.
# here we should be fast thanks to the cache.
particles_at_time_t_plus_one = f.get_particle_data(
particles=particles_at_time_t,
fields=["Coordinates"],
time=time + 1)
# here we close the logfile and cleanup everythingThe main class here is logger.Reader, which manages the log and index files in the directory basename.
The logger.ParticleSet is an abstraction for a set of particles from a Reader. Like regular sets, we can add, subtract, and intersect ParticleSets.
The function Reader.get_particle_data extracts data for a set of particles at a given time.