Reading data¶
The module offers one main function, read_array:
import eagle_IO.eagle_IO as E
M_200 = E.read_array(fileType, directory, tag, array)
read_array accepts 4 arguments; the first is a string describing the type of file and data read. The allowed values are:
| Value | Description | Example of data that can be read |
|---|---|---|
| FOF | FoF group informations | Group centre of mass, group length, group star formation rate |
| FOF_PARTICLES | IDs of the particles in a FOF group | Particle IDs |
| SNIP_FOF | FoF group informations (snipshot) | Group centre of mass, group length, group star formation rate |
| SNIP_FOF_PARTICLES | IDs of the particles in a FOF group (snipshot) | Particle IDs |
| PARTDATA | Particles that are in a FOF group | Particle Mass, velocity, entropy, stellar age |
| SNIP_PARTDATA | Particles that are in a FOF group (snipshot) | Particle Mass, velocity, entropy, stellar age |
| SNAP | Full information about all particles | Particle Mass, velocity, entropy, stellar age |
| SNIP | Reduced information about all particles | Mass, velocity |
| SUBFIND | Subhalo information | Subhalo mass, subhalo centre of potential |
| SUBFIND_GROUP | Subfind halo information | Group centre of potential, M_200, R_500 |
| SUBFIND_PARTICLES | IDs of the particles in a subhalo | Particle IDs |
| SNIP_SUBFIND | Subhalo information (snipshot) | Subhalo mass, subhalo centre of potential |
| SNIP_SUBFIND_GROUP | Subfind halo information (snipshot) | Group centre of potential, M_200, R_500 |
| SNIP_SUBFIND_PARTICLES | IDs of the particles in a subhalo (snipshot) | Particle IDs |
The second argument is the location of the directory containing the data. For instance:
"/cosma5/data/Eagle/ScienceRuns/Planck1/L0100N1504/PE/EagleReference/data/"
The third argument is the “tag” of the output. This is the part of the filename that contains the snapshot number and the redshift. For the 29 main output times in the fiducial periodic volumes, the values are:
“000_z020p000” “001_z015p132” “002_z009p993” “003_z008p988” “004_z008p075” “005_z007p050” “006_z005p971” “007_z005p487” “008_z005p037” “009_z004p485” “010_z003p984” “011_z003p528” “012_z003p017” “013_z002p478” “014_z002p237” “015_z002p012” “017_z001p487” “018_z001p259” “019_z001p004” “020_z000p865” “021_z000p736” “022_z000p615” “023_z000p503” “024_z000p366” “025_z000p271” “026_z000p183” “027_z000p101” “028_z000p000”
The last argument is the name of the array or attribute to be read. For instance:
"/PartType4/Metallicity"
or:
"/PartType5/BH_TimeLastmerger"
The routine returns a numpy array containing the values extracted from the files. The order of the elements is preserved and the type of the values is the same as that stored in the HDF5 files.
To read the value of \(M_200\) for all halos at \(z=1.5\) in the reference volume, one would use:
import eagle_IO.eagle_IO as E
sim = "/cosma5/data/Eagle/ScienceRuns/Planck1/L0100N1504/PE/EagleReference/data/"
tag = "017_z001p487"
M_200 = E.read_array("SUBFIND_GROUP", sim, tag, "FOF/Group_M_Crit200")