Here you’ll find all sorts of information about analysing the Caterpillar halos. If you still aren’t sure what to do after reading the documentation please send an email to Brendan Griffen. Make sure you have setup your work environment correctly and obtained the necessary libraries.
Loading Halo Catalogues¶
One example combining these two modules with some general inspection would look something like as follows:
import brendanlib.grifflib as glib import haloutils as htils # load the first 24 halos # (just change 14 to 11 for the lower resolution halos) hpaths = htils.get_paper_paths_lx(14) # loop through all high-resolution halos for hpath in hpaths: # strip down the path to just the halo id parentid = htils.get_parent_hid(hpath) # get the central host id of the zoom-in halo # parentid is named from the parent simulation # the zooms have different ids zoomid = htils.load_zoomid(hpath) # Return the pandas data frame with all the halos, # return mvir for example lastsnap = htils.get_lastsnap(hpath) halos = htils.load_rscat(hpath,lastsnap,verbose=True) mvir_host = halos.ix[zoomid]['mvir'] # units of Msol/h # get one specific parameter of the host at # z = 0 (quick version of above) mvir_host = htils.get_quant_zoom(hpath,'mvir') # units of Msol/h # return all halo virial masses all_mvir = halos['mvir'] # units of Msol/h # get the merger tree of the host and all its subs cat = htils.load_mtc(hpath,haloids=[zoomid]) # read in every halo's merger tree all_trees = htils.load_mtc(hpath,indexbyrsid=True) tree = all_trees[zoomid] # if you feed more than one id to the above # it would be cat,cat etc. # you can now access the main branch > try tree. then tab complete to see other functions mainbranch = tree.getMainBranch() # we also have a short hand version: # mainbranch = htils.get_mainbranch(hpath) # which is very fast and skips the reading of the entire progenitor tree if you don't need dit # see further down this page for more options # output the main branch virial mass print mainbranch['mvir']
As stated above, you can load a Rockstar catalogue for a given snapshot simply as:
rscat = htils.load_rscat(hpath,snapshot,verbose=True)
Once you do this however, you will have access to the following methods:
def __init__(self, dir, snap_num, version=2, sort_by='mvir', base='halos_', digits=2, AllParticles=False): def get_particles_from_halo(self, haloID): # @param haloID: id number of halo. Not its row position in matrix # @return: a list of particle IDs in the Halo def get_subhalos_from_halo(self,haloID): #Retrieve subhalos only one level deep. #Does not get sub-sub halos, etc. def get_subhalos_from_halos(self,haloIDs): #Returns an array of pandas data frames of subhalos. one data frame #for each host halo. returns only first level of subhalos. def get_subhalos_from_halos_flat(self,haloIDs): #Returns a flattened pandas data frame of all subhalos within #the hosts given by haloIDs. Returns only first level of subhalos. def get_hosts(self): # Get host halo frame only def get_subs(self): # Get subhalo frame only def get_all_subs_recurse(self,haloID): # Retrieve all subhalos: sub and sub-sub, etc. # just need mask of all subhalos, then return data frame subset def get_all_subhalos_from_halo(self,haloID): # Retrieve all subhalos: sub and sub-sub, etc. # return pandas data frame of subhalos def get_all_sub_particles_from_halo(self,haloID): #returns int array of particle IDs belonging to all substructure #within host of haloID def get_all_particles_from_halo(self,haloID): #returns int array of all particles belonging to haloID def get_all_num_particles_from_halo(self,haloID): # Get the actual number of particles 'total_npart' from halo as opposed to 'npart'. # mainly for versions less than 7 def get_block_from_halo(self, snapshot_dir, haloID, blockname, allparticles=True): # quick load a block (hdf5 block) of particles belong to halo. # e.g. you want particle positions for haloid = 10 (use blockname="pos") # this works fastest on snapshots ordered by id and requires import readsnapHDF5_greg def H(self): #returns hubble parameter for rockstar run def get_most_gravbound_particles_from_halo(self,snapshot_dir, haloID): # Gets most bound particles just based on potential energy for specific halo ID def get_most_bound_particles_from_halo(self, snapshot_dir, haloID): # Gets most bound particles for halo based on pot. energy and kin. energy # if potential block does not exist, it is calculate assuming a spherical halo def getversion(self): # returns the version of rockstar the run was done within # this will include versions made by Alex Ji, Greg Dooley & Brendan Griffen
Here is an example of some of these in action:
# load required modules import haloutils as htils import numpy as np # select Cat-1 halo hpaths = htils.get_paper_paths_lx(14) # select the last snapshot (z = 0) snapshot = htils.get_lastsnap(hpath) # load rockstar id of the host halo zoomid = htils.load_zoomid(hpath) #Load Halo Catalogue halos = htils.load_rscat(hpath,snapshot) #Select host halos hosts = halos.get_hosts() #Select subhalos subs = halos.get_subs() # Get positions of subs and hosts print hosts[['posX','posY','posZ']] print subs[['posX','posY','posZ']] #Get particle ids from halo of interest (here it is the host) print halos.get_particles_from_halo(zoomid) #Get virial radius of a specific halo id (in this case the host) print halos.ix[zoomid]['rvir'] # units of kpc/h
Loading Merger Trees¶
Similarly the merger tree catalogues (once loaded) have a number of its own functions.
def getMainBranch(self, row=0): """ @param row: row of the halo you want the main branch for. Defaults to row 0 Uses getSubTree, then finds the smallest dfid that has no progenitors @return: all halos that are in the main branch of the halo specified by row (in a np structured array) """ def getMMP(self, row): """ @param row: row number (int) of halo considered @return: row number of the most massive parent, or None if no parent """ def getNonMMPprogenitors(self,row): """ return row index of all progenitors that are not the most massive These are all the subhalos that were destroyed in the interval """
These can be used in the following example:
# load required modules import haloutils as htils import numpy as np # select the caterpillar halo of interest # based on halo id and resolution level hid = 1387186 lx = 14 hpath = htils.hid_hpath_lx(hid,lx) # select the last snapshot (z = 0) snapshot = htils.get_lastsnap(hpath) # load rockstar id of the host halo zoomid = htils.load_zoomid(hpath) # Load every tree (VERY slow) trees = htils.load_mtc(hpath) # Just look at the first tree # tree = cat # You can access all trees via: cat, cat etc. # If you want to load the tree for a particular ID from the rockstar catalogue trees = htils.load_mtc(haloids=[zoomid]) # in this case the host (quite slow) tree = cat # tree will contain all progenitors, including subhalos # Just say you want to index the merger tree by the z = 0 root rockstar id # (i.e. the base of the tree). This is quite powerful because you might select # halos of interest in the rockstar catalogue then want to know, just for those # what their merger tree is (e.g. say you just want dwarf systems of a particular size) trees = htils.load_mtc(haloids=[zoomid],indexbyrsid=True) tree = trees[zoomid] # You can just loop through rockstar ids (if you gave it more than one id above) # and get out the accretion histories for a small sample of trees quite quickly # to get the main branch main_branch = tree.getMainBranch() # print mass evolution for mass,scale in zip(main_branch['mvir'],main_branch['scale']): print "%3.2f: %3.2e" % (scale,mass) # output 1.00: 2.86e+14 0.99: 2.89e+14 0.98: 2.90e+14 0.97: 2.90e+14 0.95: 2.88e+14 0.94: 2.86e+14 0.93: 2.83e+14 0.92: 2.80e+14 0.91: 2.76e+14 0.90: 2.73e+14 0.89: 2.64e+14 0.88: 2.47e+14 ...
A function to find the descendent branch of any halo in merger tree catalogue. You should use it as follows:
# get a tree of interest mtc = haloutils.load_zoom_mtc(hpath) host = mtc.Trees # make a dictionary that maps ids to rows desc_map = host.get_desc_map() # get the descendent branch. desc_branch = host.getDescBranch(row, desc_map) # similarly for main branches, you can use a dictionary that speeds up the # getMainBranch call substantially. mmp_map = host.get_mmp_map() main_branch = host.getMainBranch(row, mmp_map) # you can get the branches without making the map as below, but they will be much slower. # only faster if you use ~ < 10 calls to the function. desc_branch = host.getDescBranch(row) main_branch = host.getMainBranch(row)
Loading Particle Data¶
If you want the Gadget header:
# get the first halo in the catalogue hpaths = htils.get_paper_paths_lx(14) # read its Gadget header header = htils.get_halo_header(hpath) # header contains the typical Gadget info header.boxsize header.massarr header.omegaL header.cooling header.metals header.redshift header.double header.nall header.sfr header.feedback header.nall_highword header.stellar_age header.filenum header.npart header.time header.hubble header.omega0
Be sure to divide the relevant quantities (pos, rvir etc.) by
header.hubble. See the Gadget section in the sidebar for more
information on the header and block types available.
If you wanted to get the postions of all the particles for a specific halo (or any block).
pos = htils.load_partblock(hpath,zoomid,"POS ") # units Mpc/h # "VEL ", "ID ", "MASS" etc. also work (notice the space) # check readsnapshots/readsnapHDF5.py for the other block names # you can call in the caterpillar modules print pos*1000. # kpc/h # output [ 32085.45117188 57312.79296875 44314.35546875] [ 27002.18554688 10062.73242188 9899.70019531] [ 26711.08789062 9560.22460938 10165.18847656] [ 49757.3515625 21470.00195312 6461.90917969] ...
If you want to read in the entire block, use the following:
import haloutils as htils hid = 1387186 lx = 14 hpath = htils.hid_hpath_lx(hid,lx) pos = htils.load_partblock(hpath,319,"POS ") mass = htils.load_partblock(hpath,319,"MASS")
Note that the mass block will have different values depending on how many layers of refinement there are for that zoom in simulation. If you use this code on a parent simulation it will be an array of length N all of the same value because there is only one particle type.
If you wanted just the ids for a selection of particle ids:
pos = htils.load_partblock(hpath,zoomid,"POS ",partids=[listofids]) # units Mpc/h