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 __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 __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 __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))
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
def __init__(self, res, vel, snapnum):
self.vel = vel
self.res = res
self.snapnum = int(snapnum)
self.s_vel = vel.replace(".","")
self.s_res = res.replace(".","")
#File paths
filename = "/n/hernquistfs3/mvogelsberger/GlobularClusters/InterfaceWArepo_All_" + self.res + '_' + self.vel + "/output/"
filename2 = filename + "DM_FOF" #Used for readsubfHDF5
filename3 = filename + "snap_" + str(self.snapnum).zfill(3) #Used for hdf5lib, snapHDF5
#Read header information
header = snapHDF5.snapshot_header(filename3)
with hdf5lib.OpenFile(filename3 + ".hdf5") as fs:
red = hdf5lib.GetAttr(fs, "Header", "Redshift")
atime = hdf5lib.GetAttr(fs, "Header", "Time")
boxSize = hdf5lib.GetAttr(fs, "Header", "BoxSize")
boxSize *= atime / hubbleparam #convert from ckpc/h to kpc
Omega0 = hdf5lib.GetAttr(fs, "Header", "Omega0")
OmegaLambda = hdf5lib.GetAttr(fs, "Header", "OmegaLambda")
#Read halo catalog
cat = readsubfHDF5.subfind_catalog(filename2, self.snapnum)
#critical_density *= 1. / (Omega0 + OmegaLambda * atime * atime * atime) #redshift correction
r200 = cat.Group_R_Crit200
r200 *= atime / hubbleparam #convert from ckpc/h to kpc
m200 = cat.Group_M_Crit200
m200 *= 1. / hubbleparam #convert to 10^10 M_sun
haloCMvel = cat.GroupVel
haloCMvel *= 1. / atime #convert from km/s/a to km/s
haloPos = cat.GroupPos
haloPos *= atime / hubbleparam #convert from ckpc/h to kpc
#Initialize arrays
spinparamTotal = np.zeros(np.size(r200))
spinparamGas = np.zeros(np.size(r200))
spinparamDM = np.zeros(np.size(r200))
gasfrac = np.zeros(np.size(r200))
costheta = np.zeros(np.size(r200)) #misalignment angle
v200 = np.zeros(np.size(r200))
numGas = np.zeros(np.size(r200))
numDM = np.zeros(np.size(r200))
#Read in particles
massgas = snapHDF5.read_block(filename3, "MASS", parttype=0)
massdm = snapHDF5.read_block(filename3, "MASS", parttype=1)
posgas = snapHDF5.read_block(filename3, "POS ", parttype=0)
posdm = snapHDF5.read_block(filename3, "POS ", parttype=1)
velgas = snapHDF5.read_block(filename3, "VEL ", parttype=0)
veldm = snapHDF5.read_block(filename3, "VEL ", parttype=1)
#redefine position units from ckpc/h to kpc
posgas *= atime / hubbleparam
posdm *= atime / hubbleparam
#redefine velocity units from kmsqrt(a)/s to km/s
velgas *= np.sqrt(atime)
veldm *= np.sqrt(atime)
#boxSize hubble flow correction for halo CM velocity subtraction
boxSizeVel = boxSize * hubbleparam * .1 * np.sqrt(Omega0/atime/atime/atime + OmegaLambda)
#load particle indices
over300idx, indgas, inddm = np.load('particleindex_' + self.res + '_' + self.vel + '_' + str(self.snapnum) + '.npy')
over300idx = over300idx.astype(int)
over1 = []
for i,j in enumerate(over300idx):
#remove halo CM velocity
tempvelgas = dx_wrap(velgas[indgas[i]] - haloCMvel[j],boxSizeVel)
tempveldm = dx_wrap(veldm[inddm[i]] - haloCMvel[j],boxSizeVel)
#redefine positions wrt COM
tempposgas = dx_wrap(posgas[indgas[i]] - haloPos[j],boxSize)
tempposdm = dx_wrap(posdm[inddm[i]] - haloPos[j],boxSize)
numDM[j] = np.size(tempposdm)
numGas[j] = np.size(tempposgas)
#Calculating j200
#j200 of all particles
j200vecgas = np.sum(np.cross(tempposgas,tempvelgas)*massgas[indgas[i]][:, np.newaxis],axis=0)
j200vecdm = np.sum(np.cross(tempposdm,tempveldm)*massdm[inddm[i]][:, np.newaxis],axis=0)
if np.size(tempvelgas)!=0: #can be no gas particles!
costheta[j] = np.dot(j200vecgas,j200vecdm)/np.linalg.norm(j200vecgas)/np.linalg.norm(j200vecdm)
j200vec = j200vecgas + j200vecdm
j200 = np.linalg.norm(j200vec)
j200gas = np.linalg.norm(j200vecgas)
j200dm = np.linalg.norm(j200vecdm)
v200[j] = np.sqrt(GCONST*m200[j]/r200[j])
#Bullock spin parameter
totalmass = massgas[indgas[i]].sum(dtype='float64') + massdm[inddm[i]].sum(dtype='float64')
spinparamTotal[j] = j200/np.sqrt(2)/v200[j]/r200[j]/totalmass
if np.size(tempveldm)!=0: #tempveldm can be empty no dm particles!
spinparamDM[j] = j200dm/np.sqrt(2)/v200[j]/r200[j]/massdm[inddm[i]].sum(dtype='float64')
if np.size(tempvelgas)!=0: #tempvelgas can be empty no gas particles!
spinparamGas[j] = j200gas/np.sqrt(2)/v200[j]/r200[j]/massgas[indgas[i]].sum(dtype='float64')
gasfrac[j] = massgas[indgas[i]].sum(dtype='float64') / (massgas[indgas[i]].sum(dtype='float64') + massdm[inddm[i]].sum(dtype='float64'))
#Reindex over300idx to account for SO halos with DM particles >300
over300idx2 = over300idx[numDM[over300idx] > 300]
#Plotting
#Redfine in terms of over300idx2
self.spinparamTotal = spinparamTotal[over300idx2]
self.spinparamGas = spinparamGas[over300idx2]
self.spinparamDM = spinparamDM[over300idx2]
self.gasfrac = gasfrac[over300idx2]
self.m200 = m200[over300idx2]
self.m200 *= 10**10 #Convert to solar mass.
self.costheta = costheta[over300idx2]
self.gasfracCosTheta = self.gasfrac[self.costheta!=0.]
self.m2002 = self.m200[self.costheta!=0.]
self.costheta = self.costheta[self.costheta!=0.] #take out the 0 gas components
self.thetadeg = np.arccos(self.costheta)*180./np.pi
