Data filtering

In PyMSES, a Filter is a data source that :

• filter the data coming from an origin data source.
• provides a new data source out of this filtering process.

Region filter

For a lot of analysis, you are often interested in a particular region of your simulation domain, for example :

• spherical region centered on a dark matter halo in a cosmological simulation.
• cylindrical region containing a galactik disk or a cosmological filament.
• ...

# Region of interest
from pymses.utils.regions import Sphere
center = [0.5, 0.5, 0.5]
radius = 0.1
region = Sphere(center, radius)

To filter data source with a region, use the RegionFilter:

from pymses.filters import RegionFilter
from pymses import RamsesOutput
ro = RamsesOutput("/data/Aquarius/output/", 193)
parts = ro.particle_source(["mass"])
amr = ro.amr_source(["rho"])

# Particle filtering
filt_parts = RegionFilter(region, parts)

# AMR data filtering
filt_amr = RegionFilter(region, amr)

Note

The region filters can greatly improve the I/O performance of your analysis process since it doesn’t require to read all the cpu files (of your entire simulation domain) but only those whose domain intersects your region of interest.

The filtering process occurs not only at the cpu level (as any other Filter) but also in the choice of required cpu files.

The CellsToPoints filter

see AMR grid to cell list conversion.

Function filters

You can also define your own function filter. Here an example where only the particles of mass equal to 3\times10^{3} M_{\odot} are gathered :

from pymses.filters import PointFunctionFilter
from pymses.utils import constants as C

part_source = ro.particle_source(["mass"])

# Stellar disc particles filter : only keep particles of mass = 3000.0 Msun
part_mass_Msun = 3.0E3 * C.Msun
part_mass_code = part_mass_Msun.express(ro.info["unit_mass"])
st_disc_func = lambda dset: (dset["mass"]==part_mass_code)

# Stellar disc particle data source
st_disc_parts = PointFunctionFilter(st_disc_func, part_source)

Randomly decimated data

You can use the PointRandomDecimatedFilter filter to pick up only a given fraction of points (randomly chosen) from your point-based data:

from pymses.filters import PointRandomDecimatedFilter
part_source = ro.particle_source(["mass"])

# Pick up 10 % of the particles
fraction = 0.1
dec_parts = PointRandomDecimatedFilter(fraction, part_source)

Combining filters

You can pile up as many filters as you want to get the particular data you’re interested in:

# Region filter
reg_parts = RegionFilter(region, parts)

# Stellar disc filter
st_disc_parts = PointFunctionFilter(st_disc_func, reg_parts)

# 10 % randomly decimated filter
dec_parts = PointRandomDecimatedFilter(fraction, st_disc_parts)

In this example, the dec_parts data source will provide you 10% of the stellar particles contained within a given region