def get_offsets(cat, part_types=[0, 1, 4, 5], snap=None, run=None):
if snap and run:
group_file = "/n/ghernquist/Illustris/Runs/%s/postprocessing/offsets/snap_offsets_group_%s.hdf5" % (
run, snap)
halo_file = "/n/ghernquist/Illustris/Runs/%s/postprocessing/offsets/snap_offsets_subhalo_%s.hdf5" % (
run, snap)
if os.path.isfile(group_file) and os.path.isfile(halo_file):
print("READSUBF: found pretabulated offsets to read")
f = hdf5lib.OpenFile(group_file)
group_offsets = hdf5lib.GetData(f, "Offsets")[:]
f.close()
f = hdf5lib.OpenFile(halo_file)
halo_offsets = hdf5lib.GetData(f, "Offsets")[:]
f.close()
return np.array(group_offsets), np.array(halo_offsets)
else:
# /n/hernquistfs3/IllustrisTNG/Runs/L75n910TNG/postprocessing/offsets/
group_file = "/n/hernquistfs3/IllustrisTNG/Runs/%s/postprocessing/offsets/offsets_%s.hdf5" % (
run, str(snap).zfill(3))
# sys.exit()
if os.path.isfile(group_file):
f = hdf5lib.OpenFile(group_file)
group_offsets = np.copy(hdf5lib.GetData(f, "Group/SnapByType"))
halo_offsets = np.copy(hdf5lib.GetData(f,
"Subhalo/SnapByType"))
return group_offsets, halo_offsets
GroupOffset = np.zeros((cat.ngroups, 6), dtype="int64")
HaloOffset = np.zeros((cat.nsubs, 6), dtype="int64")
for parttype in part_types:
print("Calculating offsets for PartType: %d" % parttype)
k = 0
for i in range(0, cat.ngroups):
if i > 0:
GroupOffset[i, parttype] = GroupOffset[
i - 1, parttype] + cat.GroupLenType[i - 1, parttype]
if cat.GroupNsubs[i] > 0:
HaloOffset[k, parttype] = GroupOffset[i, parttype]
k += 1
for j in range(1, cat.GroupNsubs[i]):
HaloOffset[k, parttype] = HaloOffset[
k - 1, parttype] + cat.SubhaloLenType[k - 1, parttype]
k += 1
if k != cat.nsubs:
print("READHALO: problem with offset table", k, cat.nsubs)
sys.exit()
return np.array(GroupOffset), np.array(HaloOffset)
def return_tags(filename, parttype=-1, verbose=False):
if os.path.exists(filename):
curfilename=filename
elif os.path.exists(filename+".hdf5"):
curfilename = filename+".hdf5"
elif os.path.exists(filename+".0.hdf5"):
curfilename = filename+".0.hdf5"
else:
print("[error] file not found : {:s} in return_tags".format( filename ))
sys.stdout.flush()
sys.exit()
all_blocks = []
f=hdf5lib.OpenFile(filename)
for parttype in range(0,6):
this_block=[]
part_name='PartType'+str(parttype)
if (hdf5lib.Contains(f,"",part_name)):
iter = it=datablocks.__iter__()
next = iter.next()
while (1):
if (hdf5lib.Contains(f,part_name,datablocks[next][0])):
sys.stdout.flush()
this_block.append(next)
try:
next=iter.next()
except StopIteration:
break
all_blocks.append(this_block)
f.close()
gc.collect()
return all_blocks
def contains_block(filename, tag, parttype=-1, verbose=False):
if os.path.exists(filename):
curfilename=filename
elif os.path.exists(filename+".hdf5"):
curfilename = filename+".hdf5"
elif os.path.exists(filename+".0.hdf5"):
curfilename = filename+".0.hdf5"
else:
print("[error] file not found : {:s} in contains_block ".format( filename ))
sys.stdout.flush()
sys.exit()
contains_flag=False
f=hdf5lib.OpenFile(filename)
for parttype in range(0,6):
part_name='PartType'+str(parttype)
if (hdf5lib.Contains(f,"",part_name)):
iter = it=datablocks.__iter__()
next = iter.next()
while (1):
if (verbose):
print("check ", next, datablocks[next][0])
sys.stdout.flush()
if (hdf5lib.Contains(f,part_name,datablocks[next][0])):
if (next.find(tag)>-1):
contains_flag=True
try:
next=iter.next()
except StopIteration:
break
f.close()
gc.collect()
return contains_flag
def subhalo_gas_kinematics(base, snap=135, which="v_5"):
snaptag = str(snap)
file = base + '/postprocessing/gas_kinematics/gas_kinematic_info_' + snaptag + '.hdf5'
print(file)
f = hdf5lib.OpenFile(file, mode='r')
data = hdf5lib.GetData(f, "Subhalo/" + which)[:]
f.close()
return np.array(data)
def subhalo_gas_z_grad(base, snap=135, which="GradMetallicity_5"):
snaptag = str(snap)
file = base + '/postprocessing/gas_metallicity/gas_metallicity_info_' + snaptag + '.hdf5'
print(file)
f = hdf5lib.OpenFile(file, mode='r')
data = hdf5lib.GetData(f, "Subhalo/" + which)[:]
f.close()
return np.array(data)
def mass_from_mergers(base, snap=135):
snaptag = '000' + str(snap)
snaptag = snaptag[-3:]
f = hdf5lib.OpenFile(base + '/postprocessing/StellarAssembly/galaxies_' +
snaptag + '.hdf5',
mode='r')
delta = hdf5lib.GetData(f, "StellarMassFromMergers")[:]
f.close()
return np.array(delta)
def subhalo_overdensity(base, snap=135):
snaptag = '000' + str(snap)
snaptag = snaptag[-3:]
f = hdf5lib.OpenFile(base + '/postprocessing/environment/environment_' +
snaptag + '.hdf5',
mode='r')
delta = hdf5lib.GetData(f, "delta")[:]
f.close()
return np.array(delta)
def subhalo_offsets(snap=135, run='Illustris-1'):
snaptag = str(snap)
f = hdf5lib.OpenFile('/n/ghernquist/Illustris/Runs/' + run +
'/postprocessing/offsets/snap_offsets_subhalo_' +
snaptag + '.hdf5',
mode='r')
data = hdf5lib.GetData(f, "Offsets")[:]
f.close()
return np.array(data)
def number_of_minor_mergers(base, snap=135):
snaptag = '000' + str(snap)
snaptag = snaptag[-3:]
f = hdf5lib.OpenFile(
base + '/postprocessing/MergerHistory/merger_history_' + snaptag +
'.hdf5',
mode='r')
data = hdf5lib.GetData(f, "NumMinorMergersTotal")[:]
f.close()
return np.array(data)
def mass_from_minor_mergers(base, snap=135):
snaptag = '000' + str(snap)
snaptag = snaptag[-3:]
f = hdf5lib.OpenFile(
base + '/postprocessing/MergerHistory/merger_history_' + snaptag +
'.hdf5',
mode='r')
data = hdf5lib.GetData(f, "StellarMassFromMinorMergers")[:]
f.close()
return np.array(data)
def subhalo_insitu_fraction(snap=135):
snaptag = '000' + str(snap)
snaptag = snaptag[-3:]
f = hdf5lib.OpenFile(
'/n/ghernquist/Illustris/Runs/Illustris-1/postprocessing/InSituFraction/insitu_stellar_fraction_'
+ snaptag + '.hdf5',
mode='r')
data = hdf5lib.GetData(f, "InSitu")[:]
f.close()
return np.array(data)
def subhalo_circularities(base, snap=135):
snaptag = '000' + str(snap)
snaptag = snaptag[-3:]
print(base + '/postprocessing/circularities/circularities_' + snaptag +
'.hdf5')
f = hdf5lib.OpenFile(
base + '/postprocessing/circularities/circularities_' + snaptag +
'.hdf5',
mode='r')
data = np.array(hdf5lib.GetData(f, "CircAbove05Frac")[:])
data = np.reshape(data, -1)
f.close()
return data
def subhalo_stellar_age(snap=135):
snaptag = '000' + str(snap)
snaptag = snaptag[-3:]
file = '/n/ghernquist/Illustris/Runs/Illustris-1/postprocessing/galprop/galprop_' + snaptag + '.hdf5'
if os.path.exists(file):
f = hdf5lib.OpenFile(
'/n/ghernquist/Illustris/Runs/Illustris-1/postprocessing/galprop/galprop_'
+ snaptag + '.hdf5',
mode='r')
data = np.array(hdf5lib.GetData(f, "stellar_age_inrad")[:])
f.close()
else:
data = None
return data
def subhalo_stellar_vel_disp(base,
snap=135,
which="StellarVelDisp_HalfMassRad"):
#snaptag='000'+str(snap)
#snaptag=snaptag[-3:]
snaptag = str(snap)
print(base + '/postprocessing/stellar_vel_disp/stellar_vel_disp_' +
snaptag + '.hdf5')
f = hdf5lib.OpenFile(
base + '/postprocessing/stellar_vel_disp/stellar_vel_disp_' + snaptag +
'.hdf5',
mode='r')
delta = hdf5lib.GetData(f, "Subhalo/" + which)[:]
f.close()
return np.array(delta)
def subhalo_petrosian_radius(snap=135):
file = '/n/ghernquist/Illustris/Runs/Illustris-1/postprocessing/PhotometricMorphologies/nonparmorphs_iSDSS_135.hdf5'
if os.path.exists(file):
f = hdf5lib.OpenFile(file, mode='r')
data0 = np.array(hdf5lib.GetData(f, "RP_cam0")[:])
data = np.zeros((4, data0.shape[0]))
data[1, :] = np.array(hdf5lib.GetData(f, "RP_cam1")[:])
data[2, :] = np.array(hdf5lib.GetData(f, "RP_cam2")[:])
data[3, :] = np.array(hdf5lib.GetData(f, "RP_cam3")[:])
data = np.median(data, axis=0)
f.close()
else:
data = None
return data
def __init__(self,
basedir,
skipfac,
snapnum,
filenum=0,
tree_start=-1,
tree_num=-1,
keysel=None):
self.filebase = basedir + "trees_sf" + str(skipfac) + "_" + str(
snapnum).zfill(3)
self.basedir = basedir
self.filenum = filenum
filename = self.filebase + "." + str(filenum) + ".hdf5"
f = hdf5lib.OpenFile(filename)
self.NtreesPerFile = hdf5lib.GetAttr(f, "Header", "NtreesPerFile")
self.NumberOfOutputFiles = hdf5lib.GetAttr(f, "Header",
"NumberOfOutputFiles")
self.ParticleMass = hdf5lib.GetAttr(f, "Header", "ParticleMass")
if (self.ParticleMass == 0):
print(
"WARNING: ParticleMass = 0, needed for merger rate calculation"
)
self.TreeNHalos = hdf5lib.GetData(f, "Header/TreeNHalos")[:]
self.TotNsubhalos = hdf5lib.GetData(f, "Header/TotNsubhalos")[:]
self.Redshifts = hdf5lib.GetData(f, "Header/Redshifts")[:]
if (tree_start == -1) | (tree_num == -1):
tree_start = 0
tree_num = self.NtreesPerFile
self.trees = np.empty(tree_num - tree_start, dtype='object')
self.tree_start = tree_start
self.tree_num = tree_num
for ntree in range(tree_start, tree_start + tree_num):
list = []
if (keysel == None):
for datablock in list(mergertree_datablocks.keys()):
data = hdf5lib.GetData(
f, "Tree" + str(ntree) + "/" + datablock)[:]
list.append((datablock, data))
else:
for datablock in keysel:
if hdf5lib.Contains(f, "Tree" + str(ntree), datablock):
data = hdf5lib.GetData(
f, "Tree" + str(ntree) + "/" + datablock)[:]
list.append((datablock, data))
self.trees[ntree - tree_start] = dict(list)
f.close()
def list_blocks(self, parttype=-1, verbose=False):
curfile = self.firstfile
if not os.path.exists(curfile):
print("file not found:", curfile)
sys.exit()
f = hdf5lib.OpenFile(curfile)
iter = it = sub_datablocks.__iter__()
next = iter.next()
while (1):
print(next)
if (hdf5lib.Contains(f, "Subhalo", next)):
print("Subhalo: " + next)
sys.stdout.flush()
try:
next = iter.next()
except StopIteration:
break
f.close()
def __init__(self, basedir, snapnum, keysel=None, long_ids=False):
if long_ids: id_type = np.uint64
else: id_type = np.uint32
vardict = {}
if keysel is None:
keysel = galprop_datablocks.items()
file = naming.return_galprop_file(basedir, snapnum)
if os.path.exists(file):
f = hdf5lib.OpenFile(file, mode='r')
for key in keysel:
if hdf5lib.Contains(f, "", key):
val = galprop_datablocks[key]
type = val[0]
dim = val[1]
vars(self)[key] = np.array(hdf5lib.GetData(f, key)[:])
f.close()
else:
print("Galprop File Not Found...")
def contains_block(filename, tag, parttype=-1, verbose=False):
contains_flag=False
f=hdf5lib.OpenFile(filename)
for parttype in range(0,6):
part_name='PartType'+str(parttype)
if (hdf5lib.Contains(f,"",part_name)):
iter = it=datablocks.__iter__()
next = iter.next()
while (1):
if (verbose):
print("check ", next, datablocks[next][0])
sys.stdout.flush()
if (hdf5lib.Contains(f,part_name,datablocks[next][0])):
if (next.find(tag)>-1):
contains_flag=True
try:
next=iter.next()
except StopIteration:
break
f.close()
return contains_flag
def list_blocks(filename, parttype=-1, verbose=False):
f=hdf5lib.OpenFile(filename)
for parttype in range(0,6):
part_name='PartType'+str(parttype)
if (hdf5lib.Contains(f,"",part_name_)):
print("Parttype contains : ", parttype)
print("-------------------")
sys.stdout.flush()
iter = it=datablocks.__iter__()
next = iter.next()
while (1):
if (verbose):
print("check ", next, datablocks[next][0])
sys.stdout.flush()
if (hdf5lib.Contains(f,part_name,datablocks[next][0])):
print(next, datablocks[next][0])
sys.stdout.flush()
try:
next=iter.next()
except StopIteration:
break
f.close()
def __init__(self,
basedir,
snapnum,
long_ids=False,
double_output=False,
grpcat=True,
subcat=True,
name="fof_subhalo_tab",
keysel=None):
self.filebase = basedir + "/groups_" + str(snapnum).zfill(
3) + "/" + name + "_" + str(snapnum).zfill(3) + "."
if long_ids: self.id_type = np.uint64
else: self.id_type = np.uint32
if double_output: self.double_type = np.float32
else: self.double_type = np.float64
filenum = 0
doneflag = False
skip_gr = 0
skip_sub = 0
vardict = {}
while not doneflag:
curfile = self.filebase + str(filenum) + ".hdf5"
if (not os.path.exists(curfile)):
self.filebase = basedir + "/" + name + "_" + str(
snapnum).zfill(3)
curfile = self.filebase + ".hdf5"
if (not os.path.exists(curfile)):
print "file not found:", curfile
sys.exit()
f = hdf5lib.OpenFile(curfile)
ngroups = hdf5lib.GetAttr(f, "Header", "Ngroups_ThisFile")
nsubs = hdf5lib.GetAttr(f, "Header", "Nsubgroups_ThisFile")
nfiles = hdf5lib.GetAttr(f, "Header", "NumFiles")
if filenum == 0:
self.ngroups = hdf5lib.GetAttr(f, "Header", "Ngroups_Total")
self.nids = hdf5lib.GetAttr(f, "Header", "Nids_Total")
self.nsubs = hdf5lib.GetAttr(f, "Header", "Nsubgroups_Total")
#GROUPS
if (grpcat == True):
if (keysel == None):
for key, val in grp_datablocks.items():
if hdf5lib.Contains(f, "Group", key):
type = val[0]
dim = val[1]
if (type == 'FLOAT'):
vars(self)[key] = np.empty(
self.ngroups,
dtype=np.dtype(
(self.double_type, dim)))
if (type == 'INT'):
vars(self)[key] = np.empty(self.ngroups,
dtype=np.dtype(
(np.int32,
dim)))
if (type == 'INT64'):
vars(self)[key] = np.empty(self.ngroups,
dtype=np.dtype(
(np.int64,
dim)))
if (type == 'ID'):
vars(self)[key] = np.empty(
self.ngroups,
dtype=np.dtype((self.id_type, dim)))
vardict[key] = vars(self)[key]
else:
for key in keysel:
if hdf5lib.Contains(f, "Group", key):
val = grp_datablocks[key]
type = val[0]
dim = val[1]
if (type == 'FLOAT'):
vars(self)[key] = np.empty(
self.ngroups,
dtype=np.dtype(
(self.double_type, dim)))
if (type == 'INT'):
vars(self)[key] = np.empty(self.ngroups,
dtype=np.dtype(
(np.int32,
dim)))
if (type == 'INT64'):
vars(self)[key] = np.empty(self.ngroups,
dtype=np.dtype(
(np.int64,
dim)))
if (type == 'ID'):
vars(self)[key] = np.empty(
self.ngroups,
dtype=np.dtype((self.id_type, dim)))
vardict[key] = vars(self)[key]
#SUBHALOS
if (subcat == True):
if (keysel == None):
for key, val in sub_datablocks.items():
if hdf5lib.Contains(f, "Subhalo", key):
type = val[0]
dim = val[1]
if (type == 'FLOAT'):
vars(self)[key] = np.empty(
self.nsubs,
dtype=np.dtype((self.double_type, dim)))
if (type == 'INT'):
vars(self)[key] = np.empty(self.nsubs,
dtype=np.dtype(
(np.int32,
dim)))
if (type == 'INT64'):
vars(self)[key] = np.empty(self.nsubs,
dtype=np.dtype(
(np.int32,
dim)))
if (type == 'ID'):
vars(self)[key] = np.empty(self.nsubs,
dtype=np.dtype(
(self.id_type,
dim)))
vardict[key] = vars(self)[key]
else:
for key in keysel:
if hdf5lib.Contains(f, "Subhalo", key):
val = sub_datablocks[key]
type = val[0]
dim = val[1]
if (type == 'FLOAT'):
vars(self)[key] = np.empty(
self.nsubs,
dtype=np.dtype(
(self.double_type, dim)))
if (type == 'INT'):
vars(self)[key] = np.empty(self.nsubs,
dtype=np.dtype(
(np.int32,
dim)))
if (type == 'INT64'):
vars(self)[key] = np.empty(self.nsubs,
dtype=np.dtype(
(np.int64,
dim)))
if (type == 'ID'):
vars(self)[key] = np.empty(
self.nsubs,
dtype=np.dtype((self.id_type, dim)))
vardict[key] = vars(self)[key]
#GROUPS
if (grpcat == True):
if ngroups > 0:
if (keysel == None):
for key, val in grp_datablocks.items():
if hdf5lib.Contains(f, "Group", key):
type = val[0]
dim = val[1]
a = hdf5lib.GetData(f, "Group/" + key)
if dim == 1:
vardict[key][skip_gr:skip_gr +
ngroups] = a[:]
else:
for d in range(0, dim):
vardict[key][skip_gr:skip_gr + ngroups,
d] = a[:, d]
else:
for key in keysel:
if hdf5lib.Contains(f, "Group", key):
val = grp_datablocks[key]
type = val[0]
dim = val[1]
a = hdf5lib.GetData(f, "Group/" + key)
if dim == 1:
vardict[key][skip_gr:skip_gr +
ngroups] = a[:]
else:
for d in range(0, dim):
vardict[key][skip_gr:skip_gr + ngroups,
d] = a[:, d]
skip_gr += ngroups
#SUBHALOS
if (subcat == True):
if nsubs > 0:
if (keysel == None):
for key, val in sub_datablocks.items():
if hdf5lib.Contains(f, "Subhalo", key):
type = val[0]
dim = val[1]
a = hdf5lib.GetData(f, "Subhalo/" + key)
if dim == 1:
vardict[key][skip_sub:skip_sub +
nsubs] = a[:]
else:
for d in range(0, dim):
vardict[key][skip_sub:skip_sub + nsubs,
d] = a[:, d]
else:
for key in keysel:
if hdf5lib.Contains(f, "Subhalo", key):
val = sub_datablocks[key]
type = val[0]
dim = val[1]
a = hdf5lib.GetData(f, "Subhalo/" + key)
if dim == 1:
vardict[key][skip_sub:skip_sub +
nsubs] = a[:]
else:
for d in range(0, dim):
vardict[key][skip_sub:skip_sub + nsubs,
d] = a[:, d]
skip_sub += nsubs
f.close()
filenum += 1
if filenum == nfiles: doneflag = True
def openfile(filename, mode="w"): f=hdf5lib.OpenFile(filename, mode = mode) return f
def check_file(filename): f=hdf5lib.OpenFile(filename) f.close()
def read_block_single_file(filename, block_name, dim2, parttype=-1, no_mass_replicate=False, fill_block_name="", slab_start=-1, slab_len=-1, verbose=False):
if (verbose):
print("[single] reading file : ", filename )
print("[single] reading : ", block_name)
sys.stdout.flush()
head = snapshot_header(filename)
npart = head.npart
massarr = head.massarr
nall = head.nall
filenum = head.filenum
doubleflag = head.double #GADGET-2 change
#doubleflag = 0 #GADGET-2 change
if (parttype!=-1):
if (head.npart[parttype]==0):
return [0, False]
else:
if (head.npart.sum()==0):
return [0, False]
del head
#construct indices for partial access
if (slab_start!=-1) & (slab_len!=-1):
data_slice = slice(slab_start, (slab_start+slab_len))
else:
data_slice = slice(None, None, 1)
if (verbose):
print("[single] data slice: ", data_slice)
sys.stdout.flush()
f=hdf5lib.OpenFile(filename)
#read specific particle type (parttype>=0, non-default)
if parttype>=0:
if (verbose):
print("[single] parttype : ", parttype )
sys.stdout.flush()
if ((block_name=="Masses") & (npart[parttype]>0) & (massarr[parttype]>0)):
if (verbose):
print("[single] replicate mass block")
sys.stdout.flush()
ret_val=np.repeat(massarr[parttype], npart[parttype])[data_slice]
else:
part_name='PartType'+str(parttype)
ret_val = hdf5lib.GetData(f, part_name+"/"+block_name)[data_slice]
if (verbose):
print("[single] read particles (total) : ", ret_val.shape[0]/dim2)
sys.stdout.flush()
#read all particle types (parttype=-1, default)
if parttype==-1:
first=True
dim1=long(0)
for parttype in range(0,6):
part_name='PartType'+str(parttype)
if (hdf5lib.Contains(f,"",part_name)):
if (verbose):
print("[single] parttype : ", parttype)
print("[single] massarr : ", massarr)
print("[single] npart : ", npart)
sys.stdout.flush()
#replicate mass block per default (unless no_mass_replicate is set)
if ((block_name=="Masses") & (npart[parttype]>0) & (massarr[parttype]>0) & (no_mass_replicate==False)):
if (verbose):
print("[single] replicate mass block")
sys.stdout.flush()
if (first):
data=np.repeat(massarr[parttype], npart[parttype])
dim1+=long(data.shape[0])
ret_val=data
first=False
else:
data=np.repeat(massarr[parttype], npart[parttype])
dim1+=long(data.shape[0])
ret_val=np.append(ret_val, data)
if (verbose):
print("[single] read particles (total) : ", ret_val.shape[0]/dim2)
sys.stdout.flush()
if (doubleflag==0):
ret_val=ret_val.astype("float32")
#fill fill_block_name with zeros if fill_block_name is set and particle type is present and fill_block_name not already stored in file for that particle type
if ((block_name==fill_block_name) & (block_name!="Masses") & (npart[parttype]>0) & (hdf5lib.Contains(f,part_name, block_name)==False)):
if (verbose):
print("[single] replicate block name", fill_block_name)
sys.stdout.flush()
if (first):
data=np.repeat(0.0, npart[parttype]*dim2)
dim1+=long(data.shape[0])
ret_val=data
first=False
else:
data=np.repeat(0.0, npart[parttype]*dim2)
dim1+=long(data.shape[0])
ret_val=np.append(ret_val, data)
if (verbose):
print("[single] read particles (total) : ", ret_val.shape[0]/dim2)
sys.stdout.flush()
if (doubleflag==0):
ret_val=ret_val.astype("float32")
#default: just read the block
if (hdf5lib.Contains(f,part_name,block_name)):
if (first):
data=hdf5lib.GetData(f, part_name+"/"+block_name)[:]
dim1+=long(data.shape[0])
ret_val=data
first=False
else:
data=hdf5lib.GetData(f, part_name+"/"+block_name)[:]
dim1+=long(data.shape[0])
ret_val=np.append(ret_val, data)
if (verbose):
print("[single] read particles (total) : ", ret_val.shape[0]/dim2)
sys.stdout.flush()
if ((dim1>0) & (dim2>1)):
ret_val=ret_val.reshape(dim1,dim2)
if (verbose):
print("[single] reshape done: ", ret_val.shape)
sys.stdout.flush()
f.close()
return [ret_val, True]
def __init__(self, *args, **kwargs):
if (len(args) == 1):
filename = args[0]
if os.path.exists(filename):
curfilename=filename
elif os.path.exists(filename+".hdf5"):
curfilename = filename+".hdf5"
elif os.path.exists(filename+".0.hdf5"):
curfilename = filename+".0.hdf5"
else:
print("[error] file not found : ", filename)
sys.stdout.flush()
sys.exit()
f=hdf5lib.OpenFile(curfilename)
self.npart = hdf5lib.GetAttr(f, "Header", "NumPart_ThisFile")
self.nall = hdf5lib.GetAttr(f, "Header", "NumPart_Total")
self.nall_highword = hdf5lib.GetAttr(f, "Header", "NumPart_Total_HighWord")
self.massarr = hdf5lib.GetAttr(f, "Header", "MassTable")
self.time = hdf5lib.GetAttr(f, "Header", "Time")
self.redshift = hdf5lib.GetAttr(f, "Header", "Redshift")
self.boxsize = hdf5lib.GetAttr(f, "Header", "BoxSize")
self.filenum = hdf5lib.GetAttr(f, "Header", "NumFilesPerSnapshot")
self.omega0 = hdf5lib.GetAttr(f, "Header", "Omega0")
self.omegaL = hdf5lib.GetAttr(f, "Header", "OmegaLambda")
self.hubble = hdf5lib.GetAttr(f, "Header", "HubbleParam")
self.sfr = hdf5lib.GetAttr(f, "Header", "Flag_Sfr")
self.cooling = hdf5lib.GetAttr(f, "Header", "Flag_Cooling")
self.stellar_age = hdf5lib.GetAttr(f, "Header", "Flag_StellarAge")
self.metals = hdf5lib.GetAttr(f, "Header", "Flag_Metals")
self.feedback = hdf5lib.GetAttr(f, "Header", "Flag_Feedback")
self.double = hdf5lib.GetAttr(f, "Header", "Flag_DoublePrecision") #GADGET-2 change
f.close()
else:
#read arguments
self.npart = kwargs.get("npart")
self.nall = kwargs.get("nall")
self.nall_highword = kwargs.get("nall_highword")
self.massarr = kwargs.get("massarr")
self.time = kwargs.get("time")
self.redshift = kwargs.get("redshift")
self.boxsize = kwargs.get("boxsize")
self.filenum = kwargs.get("filenum")
self.omega0 = kwargs.get("omega0")
self.omegaL = kwargs.get("omegaL")
self.hubble = kwargs.get("hubble")
self.sfr = kwargs.get("sfr")
self.cooling = kwargs.get("cooling")
self.stellar_age = kwargs.get("stellar_age")
self.metals = kwargs.get("metals")
self.feedback = kwargs.get("feedback")
self.double = kwargs.get("double")
#set default values
if (self.npart == None):
self.npart = np.array([0,0,0,0,0,0], dtype="int32")
if (self.nall == None):
self.nall = np.array([0,0,0,0,0,0], dtype="uint32")
if (self.nall_highword == None):
self.nall_highword = np.array([0,0,0,0,0,0], dtype="uint32")
if (self.massarr == None):
self.massarr = np.array([0,0,0,0,0,0], dtype="float64")
if (self.time == None):
self.time = np.array([0], dtype="float64")
if (self.redshift == None):
self.redshift = np.array([0], dtype="float64")
if (self.boxsize == None):
self.boxsize = np.array([0], dtype="float64")
if (self.filenum == None):
self.filenum = np.array([1], dtype="int32")
if (self.omega0 == None):
self.omega0 = np.array([0], dtype="float64")
if (self.omegaL == None):
self.omegaL = np.array([0], dtype="float64")
if (self.hubble == None):
self.hubble = np.array([0], dtype="float64")
if (self.sfr == None):
self.sfr = np.array([0], dtype="int32")
if (self.cooling == None):
self.cooling = np.array([0], dtype="int32")
if (self.stellar_age == None):
self.stellar_age = np.array([0], dtype="int32")
if (self.metals == None):
self.metals = np.array([0], dtype="int32")
if (self.feedback == None):
self.feedback = np.array([0], dtype="int32")
if (self.double == None):
self.double = np.array([0], dtype="int32")
def read_insitu():
file="/n/ghernquist/vrodrigu/StellarAssembly/output/Illustris/L75n1820FP/stars_135.hdf5"
f=hdf5lib.OpenFile(file, mode ='r' )
data=hdf5lib.GetData(f, "InSitu")[:]
f.close()
return np.array(data)
def read_block(filename, block, parttype=-1, no_mass_replicate=False, fill_block="", slab_start=-1, slab_len=-1, ids=-1, verbose=False, multiple_files=False):
if os.path.exists(filename):
curfilename=filename
elif os.path.exists(filename+".hdf5"):
curfilename = filename+".hdf5"
elif os.path.exists(filename+".0.hdf5"):
curfilename = filename+".0.hdf5"
multiple_files=True
else:
print("[error] file not found : {:s} in 'read_block' ".format( filename ))
sys.stdout.flush()
sys.exit()
if (verbose):
print("reading block : ", block)
sys.stdout.flush()
if parttype not in [-1,0,1,2,3,4,5]:
print("[error] wrong parttype given")
sys.stdout.flush()
sys.exit()
slabflag=False
if ((slab_start!=-1) | (slab_len!=-1)):
slabflag=True
if (parttype==-1):
print("[error] slabs only supported for specific parttype")
sys.stdout.flush()
sys.exit()
idsflag=False
if type(ids) != int:
idsflag=True
ids = np.array(ids)
if parttype==-1:
print("[error] id list only supported for specific parttype")
sys.stdout.flush()
sys.exit()
if np.sum(ids==np.sort(ids)) < len(ids):
print("[error] input ids not sorted. must be in order!")
return
if (verbose):
print(curfilename)
head = snapshot_header(curfilename)
filenum = head.filenum
npart_all = np.array(head.nall)
highword = head.nall_highword
npart_all.astype(long)
# Need to determine size of array and data type to pre-allocate data.
if idsflag==True:
length = len(ids)
if slabflag==True:
length = slab_len
if idsflag==False and slabflag==False:
if parttype!=-1:
length=head.nall[parttype]
if highword[parttype]==1:
length += 2**32
else:
length=head.nall.sum()
if (verbose):
print("Length of data allocation:", length) #GREG
if (datablocks.has_key(block)):
block_name=datablocks[block][0]
dim2=datablocks[block][1]
first=True
if (verbose):
print("Reading HDF5 : ", block_name)
print("Data dimension : ", dim2)
print("Multiple file : ", multiple_files)
print("Slab data : ", slabflag)
sys.stdout.flush()
else:
print("[error] Block type ", block, "not known!")
sys.stdout.flush()
sys.exit()
fill_block_name=""
if (fill_block!=""):
if (datablocks.has_key(fill_block)):
fill_block_name=datablocks[fill_block][0]
dim2=datablocks[fill_block][1]
if (verbose):
print("Block filling active : ", fill_block_name)
sys.stdout.flush()
# set alloc_type here. read in example item to determine data type.
alloc_type=None
# need to loop over all files until block is found, or no more files left.
if not multiple_files:
filepaths= [curfilename]
else:
filepaths = [filename+"."+str(subfile)+".hdf5" for subfile in np.arange(filenum)]
for filepath in filepaths:
g=hdf5lib.OpenFile(filepath)
if parttype==-1:
for ptype in range(0,6):
try: contains=hdf5lib.Contains(g,'PartType'+str(ptype),block_name)
except: contains=False
if contains:
alloc_type = str(hdf5lib.GetData(g,'PartType'+str(ptype)+'/'+block_name)[0:1].dtype)
break
else:
try: contains=hdf5lib.Contains(g,'PartType'+str(parttype),block_name)
except: contains=False
if contains:
alloc_type = str(hdf5lib.GetData(g,'PartType'+str(parttype)+'/'+block_name)[0:1].dtype)
g.close()
gc.collect()
if contains==True:
break
# if block does not exist
if alloc_type==None:
if block=="ID ":
alloc_type=np.uint32
#else:
# alloc_type=np.float32
elif block=="MASS":
alloc_type=np.float32 #default to float32 for MASS
else:
print("[error] block : ", block, "of parttype : ", parttype, "not found")
sys.stdout.flush()
sys.exit()
if dim2 > 1:
ret_val = np.ndarray((length,dim2),alloc_type)
else:
ret_val = np.ndarray((length,),alloc_type)
if (verbose):
print("Allocated array")
if (multiple_files):
if slabflag==False and idsflag==False:
first=True
dim1=long(0)
for num in range(0,filenum):
curfilename=filename+"."+str(num)+".hdf5"
if (verbose):
print("Reading file : ", num, curfilename)
sys.stdout.flush()
data, succ = read_block_single_file(curfilename, block_name, dim2, parttype, no_mass_replicate, fill_block_name, slab_start, slab_len, verbose=False)
if succ == True:
if dim2 > 1:
ret_val[dim1:dim1+len(data),:] = data
else:
ret_val[dim1:dim1+len(data)] = data
dim1 += long(data.shape[0])
if (verbose):
if (succ):
print("Read particles (total) : ", ret_val.shape[0])
sys.stdout.flush()
else:
print("Read particles (total) : none")
sys.stdout.flush()
# Implementation of reading specified particle positions.
if (idsflag==True):
dim1=long(0)
for num in range(0,filenum):
curfilename=filename+"."+str(num)+".hdf5"
head = snapshot_header(curfilename)
nloc=head.npart[parttype]
low=ids[0] # First particle to read
high=ids[-1] # Last particle to read
if (nloc > low): # Something to read in this file
toread = ids[ids<nloc] # Need to get subset of ids still in this file
if (verbose):
print("Reading file : ", num, curfilename)
sys.stdout.flush()
data, succ = read_block_single_file(curfilename, block_name, dim2, parttype, no_mass_replicate, fill_block_name, ids=toread, verbose=verbose)
if (succ == True):
if dim2 > 1:
ret_val[dim1:dim1+len(data),:] = data
else:
ret_val[dim1:dim1+len(data)] = data
dim1+=data.shape[0]
if (verbose):
if (succ):
# No longer need to divide by dim2. append would flatten array, not now.
print("Read particles (total) : ", ret_val.shape[0])
sys.stdout.flush()
else:
print("Read particles (total) : none")
sys.stdout.flush()
ids -= nloc
ids = ids[ids>=0] # Only keep particles not yet read
if (len(ids)==0 or high<0):
break
if (slabflag==True):
off=slab_start
left=slab_len
first=True
dim1=long(0)
for num in range(0,filenum):
curfilename=filename+"."+str(num)+".hdf5"
head = snapshot_header(curfilename)
nloc=head.npart[parttype]
if (nloc > off):
start = off
if (nloc - off > left):
count = left
else:
count = nloc - off
if (verbose):
print("Reading file : ", num, curfilename, start, count)
sys.stdout.flush()
data, succ = read_block_single_file(curfilename, block_name, dim2, parttype, no_mass_replicate, fill_block_name, slab_start=start, slab_len=count, verbose=verbose)
if (succ == True):
if dim2 > 1:
ret_val[dim1:dim1+len(data),:] = data
else:
ret_val[dim1:dim1+len(data)] = data
dim1 += data.shape[0]
if (verbose):
if (succ):
# No longer need to divide by dim2, append would flatten array, not now.
print("Read particles (total) : ", ret_val.shape[0])
sys.stdout.flush()
else:
print("Read particles (total) : none")
sys.stdout.flush()
left -= count
off += count
if (left==0):
break
off -= nloc
if (verbose):
print("all partial files read in")
sys.stdout.flush()
else:
ret_val, succ = read_block_single_file(curfilename, block_name, dim2, parttype, no_mass_replicate, fill_block_name, slab_start, slab_len, verbose)
return ret_val
def __init__(self, res, vel, snapnum):
#self.res = res
#self.vel = vel
#self.snapnum = snapnum
if res == "1.12Mpc":
s_res = '112Mpc'
elif res == "1.4Mpc":
s_res = '14Mpc'
if vel == "Sig0":
s_vel = "Sig0"
elif vel == "11.8kms":
s_vel = '118kms'
snapnum = int(snapnum)
filename = "/n/hernquistfs3/mvogelsberger/GlobularClusters/InterfaceWArepo_All_" + res + '_' + vel + "/output/"
filename2 = filename + "GasOnly_FOF" #Used for readsubfHDF5
########## CHANGED FILENAME3 TO GROUPORDERED IN GAS ONLY
filename3 = filename2 + "/snap-groupordered_" + str(snapnum).zfill(
3) #Used for hdf5lib, snapHDF5
#### Not sure if this works with change but don't care about 2.8
if res == '2.8Mpc':
filename3 = filename + "snapdir_" + str(snapnum).zfill(
3) + "/snap_" + str(snapnum).zfill(3)
#Units
GRAVITY_cgs = 6.672e-8
UnitLength_in_cm = 3.085678e21 # code length unit in cm/h
UnitMass_in_g = 1.989e43 # code length unit in g/h
UnitVelocity_in_cm_per_s = 1.0e5
UnitTime_in_s = UnitLength_in_cm / UnitVelocity_in_cm_per_s
UnitDensity_in_cgs = UnitMass_in_g / np.power(UnitLength_in_cm, 3)
UnitPressure_in_cgs = UnitMass_in_g / UnitLength_in_cm / np.power(
UnitTime_in_s, 2)
UnitEnergy_in_cgs = UnitMass_in_g * np.power(
UnitLength_in_cm, 2) / np.power(UnitTime_in_s, 2)
GCONST = GRAVITY_cgs / np.power(
UnitLength_in_cm, 3) * UnitMass_in_g * np.power(UnitTime_in_s, 2)
critical_density = 3.0 * .1 * .1 / 8.0 / np.pi / GCONST #.1 is for 1/Mpc to 1/kpc, also in units of h^2
header = snap.snapshot_header(filename3)
if res == "2.8Mpc":
fs = hdf5lib.OpenFile(filename3 + ".0.hdf5")
else:
fs = hdf5lib.OpenFile(filename3 + ".hdf5")
red = hdf5lib.GetAttr(fs, "Header", "Redshift")
atime = hdf5lib.GetAttr(fs, "Header", "Time")
boxSize = hdf5lib.GetAttr(fs, "Header", "BoxSize")
boxSize *= atime #convert from ckpc/h to kpc/h
Omega0 = hdf5lib.GetAttr(fs, "Header", "Omega0")
OmegaLambda = hdf5lib.GetAttr(fs, "Header", "OmegaLambda")
fs.close()
cat = readsubfHDF5.subfind_catalog(filename2, snapnum)
Omega_a = Omega0 / (Omega0 + OmegaLambda * atime * atime * atime)
critical_density *= (Omega0 / Omega_a)
r200 = cat.Group_R_Crit200
r200 *= atime #convert from ckpc/h to kpc/h
m200 = cat.Group_M_Crit200
haloCMvel = cat.GroupVel
haloCMvel *= 1. / atime #convert from km/s/a to km/s
haloPos = cat.GroupPos
haloPos *= atime #convert from ckpc/h to kpc/h
#Read in particles
#read in all simulation masses to calculate cosmic baryon fraction
massgassim = snap.read_block(filename + "snap_" +
str(snapnum).zfill(3),
"MASS",
parttype=0)
massdmsim = snap.read_block(filename + "snap_" + str(snapnum).zfill(3),
"MASS",
parttype=1)
massgas = snap.read_block(filename3, "MASS", parttype=0)
massdm = snap.read_block(filename3, "MASS", parttype=1)
posgas = snap.read_block(filename3, "POS ", parttype=0)
posdm = snap.read_block(filename3, "POS ", parttype=1)
velgas = snap.read_block(filename3, "VEL ", parttype=0)
veldm = snap.read_block(filename3, "VEL ", parttype=1)
#redefine position units from ckpc/h to kpc/h
posgas *= atime
posdm *= atime
#redefine velocity units from kmsqrt(a)/s to km/s
velgas *= np.sqrt(atime)
veldm *= np.sqrt(atime)
fb = massgassim.sum(dtype="float64") / (
massgassim.sum(dtype="float64") + massdmsim.sum(dtype="float64"))
gaslimit = .4 # Set the limit for gas fraction in plots
#boxSize hubble flow correction for halo CM velocity subtraction
boxSizeVel = boxSize * .1 * UnitLength_in_cm / UnitVelocity_in_cm_per_s * np.sqrt(
Omega0 / atime / atime / atime + OmegaLambda)
#load particle indices
pGas = snap.read_block(filename3, "POS ", parttype=0)
mGas = snap.read_block(filename3, "MASS", parttype=0)
pDM = snap.read_block(filename3, "POS ", parttype=1)
halo100_indices = np.where(cat.GroupLenType[:, 0] > 100)[0]
startAllGas = []
endAllGas = []
for i in halo100_indices:
startAllGas += [np.sum(cat.GroupLenType[:i, 0])]
endAllGas += [startAllGas[-1] + cat.GroupLenType[i, 0]]
#Initialize arrays
spinparam = np.zeros(np.size(halo100_indices))
jsptotspinparam = np.zeros(np.size(halo100_indices))
jspgasspinparam = np.zeros(np.size(halo100_indices))
jspdmspinparam = np.zeros(np.size(halo100_indices))
gasfrac = np.zeros(np.size(halo100_indices))
costheta = np.zeros(np.size(halo100_indices)) #misalignment angle
v200 = np.zeros(np.size(halo100_indices))
velgasall = np.zeros(np.size(halo100_indices))
veldmall = np.zeros(np.size(halo100_indices))
virialratio = np.zeros(np.size(halo100_indices))
numGas = np.zeros(np.size(halo100_indices))
numDM = np.zeros(np.size(halo100_indices))
j200gas = np.zeros(np.size(halo100_indices))
j200dm = np.zeros(np.size(halo100_indices))
j200 = np.zeros(np.size(halo100_indices))
totmass = np.zeros(np.size(halo100_indices))
gasmass = np.zeros(np.size(halo100_indices))
DMmass = np.zeros(np.size(halo100_indices))
rmax = np.zeros(np.size(halo100_indices))
rmin = np.zeros(np.size(halo100_indices))
j200gasNoNorm = np.zeros(np.size(halo100_indices))
closestm200 = np.zeros(np.size(halo100_indices))
#some radii are errors and negative, will have a value of 1 to be excluded
negradii = np.zeros(np.size(halo100_indices))
#Indexing for global variable works because halos are ordered from largest to smallest so <100 particles are at the end and not counted.
for i in halo100_indices:
exec("cm = cm_%s_%s_%d[0][i]" % (s_res, s_vel, snapnum))
exec("rotation = rotation_%s_%s_%d[0][i]" %
(s_res, s_vel, snapnum))
exec("radii = radii_%s_%s_%d[0][i]" % (s_res, s_vel, snapnum))
#some radii are errors and negative, will have a value of 1 to be excluded
if radii[0] < 0.:
negradii[i] = 1.
else:
maxrad = radii[2]
maxrad *= atime #convert from ckpc to kpc
exec("mDM=mDM_%s_%s_%d[0][i]" % (s_res, s_vel, snapnum))
exec("DMinEll=DMindices_%s_%s_%d[0][i]" %
(s_res, s_vel, snapnum))
exec("m200dm = M200dm_%s_%s[snapnum-10][i]" % (s_res, s_vel))
#Check if CM is buggy
if np.sum(cm == np.array([0., 0., 0.])) == 3:
# it's probbaly an error; recompute com
totalGas = np.sum(mGas[startAllGas[i]:endAllGas[i]])
cm = np.array([
np.sum(pGas[startAllGas[i]:endAllGas[i], j] *
mGas[startAllGas[i]:endAllGas[i]]) / totalGas
for j in range(3)
])
# Get positions of gas particles
P = pGas[startAllGas[i]:endAllGas[i]]
# Shift coordinate system to center on the center of the ellipsoid
Precentered = dx_wrap(P - cm, boxSize / atime)
# Rotate coordinated to the the axes point along x,y,z directions:
Precentered = np.array(
[np.dot(pp, rotation.T) for pp in Precentered])
# Figure out which particles are inside the ellipsoid
inEll = (Precentered[:, 0]**2. / radii[0]**2. +
Precentered[:, 1]**2. / radii[1]**2 +
Precentered[:, 2]**2. / radii[2]**2) <= 1.
#remove halo CM velocity
tempvelgas = dx_wrap(
velgas[startAllGas[i]:endAllGas[i]][inEll] - haloCMvel[i],
boxSizeVel)
tempveldm = dx_wrap(veldm[DMinEll] - haloCMvel[i], boxSizeVel)
#redefine positions wrt COM
tempposgas = dx_wrap(
posgas[startAllGas[i]:endAllGas[i]][inEll] - haloPos[i],
boxSize)
tempposdm = dx_wrap(posdm[DMinEll] - haloPos[i], boxSize)
numDM[i] = np.size(tempposdm)
numGas[i] = np.size(tempposgas)
#Calculating j200
#j200 of all particles
j200vecgas = np.sum(
np.cross(tempposgas, tempvelgas) *
massgas[startAllGas[i]:endAllGas[i]][inEll][:, np.newaxis],
axis=0)
j200vecdm = np.sum(np.cross(tempposdm, tempveldm) *
massdm[DMinEll][:, np.newaxis],
axis=0)
#if np.size(tempveldm)!=0: #can be no dm particles!
# costheta[i] = np.dot(j200vecgas,j200vecdm)/np.linalg.norm(j200vecgas)/np.linalg.norm(j200vecdm)
j200vec = j200vecgas + j200vecdm
j200[i] = np.linalg.norm(j200vec)
j200dm[i] = np.linalg.norm(j200vecdm)
j200gas[i] = np.linalg.norm(j200vecgas)
j200gasNoNorm[i] = np.linalg.norm(j200vecgas)
gasmass[i] = np.sum(
massgas[startAllGas[i]:endAllGas[i]][inEll])
totmass[i] = gasmass[i] + mDM
DMmass[i] = mDM
rmax[i] = radii[2]
rmin[i] = radii[0]
closestm200[i] = m200dm
#using fudicial m200~6mgas
#get r200 from analytic formula in Barkana,Loeb 01 review
if gasmass[i] != 0.: #Some ellpsoids fit nothing
m200fid = 6. * gasmass[i]
omgz = .27 * atime**(-3.) / (.27 * atime**(-3.) + .73)
dfact = omgz - 1.
delc = 18. * np.pi**2. + 82 * dfact - 39. * dfact**2.
r200fid = .784 * (m200fid * 100.)**(1. / 3.) * (
.27 / omgz * delc / 18. / np.pi**2)**(-1. /
3.) * 10 * atime
v200fid = np.sqrt(GCONST * (m200fid) / r200fid)
j200gas[i] *= 1. / np.sqrt(2) / (
gasmass[i]) / v200fid / r200fid
j200[i] *= 1. / np.sqrt(2) / (
totmass[i]) / v200fid / r200fid
if mDM != 0.:
j200dm[i] *= 1. / np.sqrt(2) / mDM / v200fid / r200fid
gasfrac[i] = gasmass[i] / totmass[i]
#Reindex to account for shrunken ellipsoids with gas particles >100
goodidx, = np.where(np.logical_and(numGas > 100, negradii == 0.))
self.j200gas = j200gas[goodidx]
self.j200dm = j200dm[goodidx]
self.j200 = j200[goodidx]
self.j200gasNoNorm = j200gasNoNorm[goodidx]
self.gasfrac = gasfrac[goodidx]
self.totmass = totmass[goodidx]
self.totmass *= 10**10
#costheta = costheta[goodidx]
self.rmax = rmax[goodidx]
self.rmin = rmin[goodidx]
#thetadeg = np.arccos(costheta)*180./np.pi
self.gasmass = gasmass[goodidx]
self.closestm200 = closestm200[goodidx]
#Reindex the Rmin, R200_DM params
exec("self.rclosest = Rmin_%s_%s[snapnum-10][goodidx]" %
(s_res, s_vel))
exec("self.R200dm = R200dm_%s_%s[snapnum-10][goodidx]" %
(s_res, s_vel))
'SubhaloMassType', 'SubhaloSFR',
'SubhaloGasMetallicity',
'SubhaloGasMetallicitySfr'
])
stellar_masses = cat.SubhaloMassType[:,
4] * 1e10 / little_h # units of M_solar
sfr = cat.SubhaloSFR # units of M_solar / yr
gas_z = cat.SubhaloGasMetallicity # unitless metallicity
gas_sfr_z = cat.SubhaloGasMetallicitySfr # unitless metallicity
star_z = readsubfHDF5.subhalo_stellar_metallicities(snap=snap[0])
# read this guy in manually...
file = '/n/home01/ptorrey/ReviewPlots/cold_gas_masses_z' + str(
redshift) + '.hdf5'
f = hdf5lib.OpenFile(file, mode='r')
cold_gas_mass = np.array(
hdf5lib.GetData(f, "ColdGasMass")
[:]) # should already be in units of M_solar (per cold_gas_catalog.py)
f.close()
output_cgm = open(
'./data/cold_gas_mass_vs_stellar_mass_z' + str(redshift) + '.txt', 'w')
output_cgm.write(
'# Dense gas mass vs stellar mass (note, I used "cold" to describe this data throughout,\n'
)
output_cgm.write(
'# but its really only a density cut!!! per Romeels email) \n')
output_cgm.write('# col1 = stellar mass (in solar masses) \n')
output_cgm.write('# col2 = dense gas mass (in solar masses)\n')
output_cgm.write('# col3 = dense gas mass / stellar mass (unitless) \n')
def __init__(self,
basedir,
snapnum,
long_ids=False,
double_output=False,
grpcat=True,
subcat=True,
name="fof_subhalo_tab",
keysel=[]):
if long_ids: self.id_type = np.uint64
else: self.id_type = np.uint32
if double_output: self.double_type = np.float32
else: self.double_type = np.float64
filenum = 0
doneflag = False
skip_gr = 0
skip_sub = 0
vardict = {}
if keysel is None:
keysel = grp_datablocks.items()
while not doneflag:
self.filebase, curfile = naming.return_subfind_filebase(
basedir, snapnum, name, filenum)
self.firstfile = curfile
f = hdf5lib.OpenFile(curfile)
ngroups = hdf5lib.GetAttr(f, "Header", "Ngroups_ThisFile")
nsubs = hdf5lib.GetAttr(f, "Header", "Nsubgroups_ThisFile")
nfiles = hdf5lib.GetAttr(f, "Header", "NumFiles")
if filenum == 0:
self.ngroups = hdf5lib.GetAttr(f, "Header", "Ngroups_Total")
self.nids = hdf5lib.GetAttr(f, "Header", "Nids_Total")
self.nsubs = hdf5lib.GetAttr(f, "Header", "Nsubgroups_Total")
#GROUPS
if grpcat:
for key in keysel:
if hdf5lib.Contains(f, "Group", key):
val = grp_datablocks[key]
type = val[0]
dim = val[1]
if (type == 'FLOAT'):
vars(self)[key] = np.empty(
self.ngroups,
dtype=np.dtype((self.double_type, dim)))
if (type == 'INT'):
vars(self)[key] = np.empty(self.ngroups,
dtype=np.dtype(
(np.int32,
dim)))
if (type == 'INT64'):
vars(self)[key] = np.empty(self.ngroups,
dtype=np.dtype(
(np.int64,
dim)))
if (type == 'ID'):
vars(self)[key] = np.empty(self.ngroups,
dtype=np.dtype(
(self.id_type,
dim)))
vardict[key] = vars(self)[key]
#SUBHALOS
if subcat:
for key in keysel:
if hdf5lib.Contains(f, "Subhalo", key):
val = sub_datablocks[key]
type = val[0]
dim = val[1]
if (type == 'FLOAT'):
vars(self)[key] = np.empty(
self.nsubs,
dtype=np.dtype((self.double_type, dim)))
if (type == 'INT'):
vars(self)[key] = np.empty(self.nsubs,
dtype=np.dtype(
(np.int32,
dim)))
if (type == 'INT64'):
vars(self)[key] = np.empty(self.nsubs,
dtype=np.dtype(
(np.int64,
dim)))
if (type == 'ID'):
vars(self)[key] = np.empty(self.nsubs,
dtype=np.dtype(
(self.id_type,
dim)))
vardict[key] = vars(self)[key]
#GROUPS
if grpcat:
if ngroups > 0:
for key in keysel:
if hdf5lib.Contains(f, "Group", key):
val = grp_datablocks[key]
type = val[0]
dim = val[1]
a = hdf5lib.GetData(f, "Group/" + key)
if dim == 1:
vardict[key][skip_gr:skip_gr + ngroups] = a[:]
else:
for d in range(0, dim):
vardict[key][skip_gr:skip_gr + ngroups,
d] = a[:, d]
skip_gr += ngroups
#SUBHALOS
if subcat:
if nsubs > 0:
for key in keysel:
if hdf5lib.Contains(f, "Subhalo", key):
val = sub_datablocks[key]
type = val[0]
dim = val[1]
a = hdf5lib.GetData(f, "Subhalo/" + key)
if dim == 1:
vardict[key][skip_sub:skip_sub + nsubs] = a[:]
else:
for d in range(0, dim):
vardict[key][skip_sub:skip_sub + nsubs,
d] = a[:, d]
skip_sub += nsubs
f.close()
filenum += 1
if filenum == nfiles: doneflag = True
