def simple_previous_snap_read(Nsnap, use_multi='n'): if (int(Nsnap) < 10): Nsnapstring = '00'+str(Nsnap) elif (int(Nsnap) < 100): Nsnapstring = '0'+str(Nsnap) else: Nsnapstring = str(Nsnap) the_snapdir = './hdf5/' the_prefix ='snapshot' if (use_multi == 'y'): the_snapdir = './snapdir_'+Nsnapstring+'/' the_suffix = '.hdf5' print 'reading particle type 0 (gas?)' G = readsnap(the_snapdir, Nsnapstring, 0, snapshot_name=the_prefix, extension=the_suffix) if (len(G['p'][:,0]) < 1 ): print 'no previous snapshot detected! ',Nsnap sys.exit() x = G['p'][:,0] y = G['p'][:,1] z = G['p'][:,2] ID = G['id'] a = G['header'][2] Ttbl = (np.array([ID, x, y, z])).T return Ttbl, a
def importParticleData(self, ptype):
"""
Reads data in from whatever format you'd like.
Input:
ptype - The numerical index of the particle type you want
Output:
res - A dictionary that contains information for a *single* pointcloud!
"""
#we have a function of exactly this format, how convenient (/sarcasm)!
return readsnap(self.snapdir, self.snapnum, ptype)
def importParticleData(self,ptype): """ Reads data in from whatever format you'd like. Input: ptype - The numerical index of the particle type you want Output: res - A dictionary that contains information for a *single* pointcloud! """ #we have a function of exactly this format, how convenient (/sarcasm)! return readsnap(self.snapdir,self.snapnum,ptype)
def loop_rdf_wr(sdir, snum, num_bins, box_size=[1, 1, 1]):
"""This computes the radial distribution function(g(r)) and radial velocities
between grains of size bin i and those of size bin j, at separations given by
vector 'radii'. The results are stored as 3 dimensional matrices;
the first two axes are just spanning the possible i-j pairs, so it will be
lower triangular; the third direction runs over the separations at which g
and wr are computed"""
Pd = readsnap(sdir, snum, 3)
xd = Pd['p'][:, 0]
yd = Pd['p'][:, 1]
zd = Pd['p'][:, 2]
vxd = Pd['v'][:, 0]
vyd = Pd['v'][:, 1]
vzd = Pd['v'][:, 2]
# Shells
# to be modified such that these numbers are not hard coded, but passed on
# as a variable or something..
radii = np.array([0.0025, 0.005, 0.01, 0.025, 0.05])
dr = np.array([0.0025, 0.0025, 0.0075, 0.0225, 0.0275])
num_radii = radii.size
# Construct the dust size bins and the vectors with their indices, ok_ds
# The size bins are equally spaced in log-space
# ok_ds is a list of vectors, each vector containing the indices of dust
# particles in a certain size bin
e_min = np.amin(Pd['R_d'])
e_max = np.amax(Pd['R_d'])
size_bins = np.linspace(np.log10(e_min * 0.99),
np.log10(e_max * 1.01),
num=num_bins + 1,
endpoint=True)
ok_ds = []
for i in np.arange(num_bins):
dummy, = np.where((np.log10(Pd['R_d']) >= size_bins[i])
& (np.log10(Pd['R_d']) < size_bins[i + 1]))
ok_ds.append(dummy)
g_list = np.zeros((num_bins, num_bins, num_radii))
wr_list = np.zeros((num_bins, num_bins, num_radii))
for i in np.arange(num_bins):
for j in np.arange(i + 1):
print('Computing bins', i, j)
# This is the call to the main routine to compute g(r) and wr(r)
# between dust species i and dust species j
g,wr = compute_rdf_wr(xd[ok_ds[i]],yd[ok_ds[i]],zd[ok_ds[i]],\
xd[ok_ds[j]],yd[ok_ds[j]],zd[ok_ds[j]],\
vxd[ok_ds[i]],vyd[ok_ds[i]],vzd[ok_ds[i]],\
vxd[ok_ds[j]],vyd[ok_ds[j]],vzd[ok_ds[j]],\
box_size, radii, dr, 0.1, Nt=10)
g_list[i, j, :] = g
wr_list[i, j, :] = wr
return (g_list, wr_list, radii)
def readsnapToDF(snapdir, snapnum, parttype):
res = readsnap(snapdir, snapnum, parttype, cosmological='m12i' in snapdir)
ids = res.pop('id')
vels = res.pop('v')
coords = res.pop('p')
res['xs'], res['vxs'] = coords[:, 0], vels[:, 0]
res['ys'], res['vys'] = coords[:, 1], vels[:, 1]
res['zs'], res['vzs'] = coords[:, 2], vels[:, 2]
metallicity = res.pop('z')
for i, zarray in enumerate(metallicity.T):
res['met%d' % i] = zarray
snap_df = pd.DataFrame(res, index=ids)
return snap_df
def match_particles(PID_list, Nsnap, use_multi='n'): if (int(Nsnap) < 10): Nsnapstring = '00'+str(Nsnap) elif (int(Nsnap) < 100): Nsnapstring = '0'+str(Nsnap) else: Nsnapstring = str(Nsnap) the_snapdir = './hdf5/' the_prefix ='snapshot' if (use_multi == 'y'): the_snapdir = './snapdir_'+Nsnapstring+'/' the_suffix = '.hdf5' print 'reading particle type 0 (gas?)' G = readsnap(the_snapdir, Nsnapstring, 0, snapshot_name=the_prefix, extension=the_suffix) here = np.in1d(G['id'], PID_list) PID = G['id'][here] x = G['p'][:,0][here] y = G['p'][:,1][here] z = G['p'][:,2][here] vx = G['v'][:,0][here] vy = G['v'][:,1][here] vz = G['v'][:,2][here] h = G['header'][12] PhysTemp, PhysRho = convertTemp(G['u'][here], G['ne'][here], G['rho'][here], h) Metallicity = G['z'][:,0][here] a = G['header'][2] boxsize = G['header'][9] tbl = [] base = [PID, x,y,z, vx,vy,vz, PhysTemp, PhysRho, Metallicity] for part in base: tbl.append(part) tbl = np.array(tbl) Ttbl = tbl.T return (Ttbl, a, boxsize)
print "<nameout> == snapshot_184.hdf5"
print "<nchunks> == 8"
sys.exit(1337)
namein0 = sys.argv[1]
nameout = sys.argv[2]
nchunks = sys.argv[3]
fname_in = "%s/%s" % (dirpath, namein0)
fname_out = "%s/%s" % (dirpath, nameout)
print "Reading from input file"
import readsnap as reads
# For reading the properties
# Gas
print "Reading gas data"
P0 = reads.readsnap(dirpath, nchunks, 0, cosmological=1, loud=1)
# dark matter particles(high res.)
print "Reading Dark Matter data: (only high res. particles)"
P1 = reads.readsnap(dirpath, nchunks, 1, cosmological=1, loud=1)
print "Reading Dark Matter data: (low res. particles: PartType2)"
P2 = reads.readsnap(dirpath, nchunks, 2, cosmological=1, loud=1)
print "Reading Dark Matter data: (low res. particles: PartType3)"
P3 = reads.readsnap(dirpath, nchunks, 3, cosmological=1, loud=1)
# Stellar particles
print "Reading data for Stellar Particles"
P4 = reads.readsnap(dirpath, nchunks, 4, cosmological=1, loud=1)
# This is just for making a copy of the header
file = h5py.File(fname_in, 'r')
#fnew = h5py.File(fname_base+'.'+fname_ext, "w")
import h5py
import numpy as np
import readsnap as reads
halo_list = ['/gdata/rouge/agraus/Alternative_physics_runs/SIDM_runs/h11707/','/gdata/rouge/agraus/Alternative_physics_runs/WDM_runs/h11707/']
for halo_number in halo_list:
dirname = halo_number
snap_start = 'snapshot_184'
#For reading the properties
P0=reads.readsnap(dirname,7,0,cosmological=1,loud=1,snapshot_name=snap_start,h0=1.0)
P1=reads.readsnap(dirname,7,1,cosmological=1,loud=1,snapshot_name=snap_start,h0=1.0)
P2=reads.readsnap(dirname,7,2,cosmological=1,loud=1,snapshot_name=snap_start,h0=1.0)
P3=reads.readsnap(dirname,7,3,cosmological=1,loud=1,snapshot_name=snap_start,h0=1.0)
P5=reads.readsnap(dirname,7,5,cosmological=1,loud=1,snapshot_name=snap_start,h0=1.0)
P4=reads.readsnap(dirname,7,4,cosmological=1,loud=1,snapshot_name=snap_start,h0=1.0)
#This is just for making a copy of the header
print dirname+snap_start+'.0.hdf5'
print 'whatever'
file = h5py.File(dirname+snap_start+'.0.hdf5', 'r')
stars=file['PartType4']
coord = stars['Coordinates']
Masses = stars['Masses']
Metallicity = stars['Metallicity']
ParticleIDs = stars['ParticleIDs']
SFT = stars['StellarFormationTime']
Vel = stars['Velocities']
fnew = h5py.File(dirname+snap_start+'_for_rock.'+'hdf5', "w")
#Creating the header
import os, sys
from readsnap import readsnap
import np_tools
import numpy as np
global colormapMin,colormapMax
########################################################################
# Load the Data from the Data Files
########################################################################
# Load the snapshot data. datasetBase and snapshotNumber are defined in the config file!
res = readsnap(datasetBase, snapshotNumber, 0)
# Calculate what the radius and weight should be when shown, as an approximation to what it really is.
radius = np.power(((res['m'] / res['rho'])/(2 * np.pi) ),(1.0/3.0))
weight = 2 * radius * res['rho']
########################################################################
# Orient the Camera
########################################################################
if orientOnCoM:
cameraPosition, pivotPoint, cameraOrientation = np_tools.setCenterOfMassView( res['p'], res['m'], 4. )
########################################################################
# Put the Data in a Firefly-Recognizable Format
########################################################################
# Make a loader to keep the dataset around
numpy_loader = NumpyLoader()
#dirname = './halo796_Y13/snapdir_184/' #dirname = './halo897_Y13/snapdir_184/' #dirname = './halo897_Y13_stampede/' #dirname = './halo848_Y13/snapdir_184/' #dirname = './halo11707_Y13/snapdir_184/' #dirname = './halo1016_Y13/snapdir_184/' #dirname = './halo12596_Y13/snapdir_184/' #dirname = './halo20910_Y13/snapdir_184/' #dirname = './halo32503_Y13/snapdir_184/' #dirname = './halo20192_Y13/snapdir_184/' #dirname = './halo897_Y13/snapdir_184/' dirname = './snapdir_184/' import readsnap as reads # For reading the properties # Gas P0=reads.readsnap(dirname,7,0,cosmological=1,loud=1) # dark matter particles(high res.) P1=reads.readsnap(dirname,7,1,cosmological=1,loud=1) # dark matter particles(low res.) P2=reads.readsnap(dirname,7,2,cosmological=1,loud=1) P3=reads.readsnap(dirname,7,3,cosmological=1,loud=1) P5=reads.readsnap(dirname,7,5,cosmological=1,loud=1) # Stellar particles P4=reads.readsnap(dirname,7,4,cosmological=1,loud=1) # This is just for making a copy of the header file = h5py.File(dirname+'snapshot_184.0.hdf5', 'r') #stars=file['PartType4'] #coord = stars['Coordinates'] #Masses = stars['Masses'] #Metallicity = stars['Metallicity']
theN = Ns[count]
print 'reading particle type 4 for ', theN
if (theN < 10):
Nsnapstring = '00' + str(theN)
elif (theN < 100):
Nsnapstring = '0' + str(theN)
else:
Nsnapstring = str(theN)
the_snapdir = './hdf5/'
if (multifile):
the_snapdir = './snapdir_' + Nsnapstring + '/'
the_prefix = 'snapshot'
the_suffix = '.hdf5'
S = readsnap(the_snapdir,
Nsnapstring,
4,
snapshot_name=the_prefix,
extension=the_suffix)
thetime = S['header'][2]
redshift = S['header'][3]
boxsize = S['header'][9]
omega_matter = S['header'][10]
omega_L = S['header'][11]
h = S['header'][12]
AHF_haloX = x[count]
AHF_haloY = y[count]
AHF_haloZ = z[count]
AHF_Rvir = Rvir[count]
AHF_a = 1.0 / (1.0 + Zs[count])
if (adaptive_Rstar):
while (count < TheLen and not fake): theN = Ns[count] print 'reading particle type 4 for ',theN if (theN < 10): Nsnapstring = '00'+str(theN) elif (theN < 100): Nsnapstring = '0'+str(theN) else: Nsnapstring = str(theN) the_snapdir = './hdf5/' if (multifile): the_snapdir = './snapdir_'+Nsnapstring+'/' the_prefix ='snapshot' the_suffix = '.hdf5' S = readsnap(the_snapdir, Nsnapstring, 4, snapshot_name=the_prefix, extension=the_suffix) thetime = S['header'][2] redshift = S['header'][3] boxsize = S['header'][9] omega_matter = S['header'][10] omega_L = S['header'][11] h = S['header'][12] AHF_haloX = x[count] AHF_haloY = y[count] AHF_haloZ = z[count] AHF_Rvir = Rvir[count] AHF_a = 1.0 / (1.0 + Zs[count]) if (adaptive_Rstar): Rstars = Inner_SF_thresh*Rvir[count]
Nsnapstring = str(Nsnap)
the_snapdir = './hdf5/'
the_prefix = 'snapshot'
if (multifile == 'y'):
the_snapdir = './snapdir_' + Nsnapstring + '/'
the_suffix = '.hdf5'
#get the first 20 DM particles and see where they came from
the_ptype = 1
gthe_ptype = 0
sthe_ptype = 4
S = readsnap(the_snapdir,
Nsnapstring,
the_ptype,
snapshot_name=the_prefix,
extension=the_suffix)
gS = readsnap(the_snapdir,
Nsnapstring,
gthe_ptype,
snapshot_name=the_prefix,
extension=the_suffix)
sS = readsnap(the_snapdir,
Nsnapstring,
sthe_ptype,
snapshot_name=the_prefix,
extension=the_suffix)
PID_list = S['id'][:]
DMpos = S['p'][:, :]
print "<nchunks> == 8"
sys.exit(1337)
dirpath=sys.argv[1]
namein0=sys.argv[2]
nameout=sys.argv[3]
nchunks=sys.argv[4]
fname_in = "%s/%s"%(dirpath,namein0)
fname_out = "%s/%s"%(dirpath,nameout)
print "Reading from input file"
import readsnap as reads
# For reading the properties
# Gas
print "Reading gas data"
P0=reads.readsnap(dirpath,nchunks,0,cosmological=0,loud=1,snapshot_name='snapshot_184')
# dark matter particles(high res.)
print "Reading Dark Matter data: (only high res. particles)"
P1=reads.readsnap(dirpath,nchunks,1,cosmological=0,loud=1,snapshot_name='snapshot_184')
print "Reading Dark Matter data: (low res. particles: PartType2)"
P2=reads.readsnap(dirpath,nchunks,2,cosmological=0,loud=1,snapshot_name='snapshot_184')
print "Reading Dark Matter data: (low res. particles: PartType3)"
P3=reads.readsnap(dirpath,nchunks,3,cosmological=0,loud=1,snapshot_name='snapshot_184')
# Stellar particles
print "Reading data for Stellar Particles"
P4=reads.readsnap(dirpath,nchunks,4,cosmological=0,loud=1,snapshot_name='snapshot_184')
# This is just for making a copy of the header
print 'copying header from: '+str(fname_in)
file_copy = h5py.File(fname_in+'0.hdf5', 'r')
Nsnapstring = '00'+str(sys.argv[1]) elif (int(sys.argv[1]) < 100): Nsnapstring = '0'+str(sys.argv[1]) else: Nsnapstring = str(sys.argv[1]) Nsnap = int(sys.argv[1]) the_snapdir = './hdf5/' if (multifile): the_snapdir = './snapdir_'+Nsnapstring+'/' the_prefix ='snapshot' the_suffix = '.hdf5' #read the snapshot print 'reading particle type 0 (gas?)' G = readsnap(the_snapdir, Nsnapstring, 0, snapshot_name=the_prefix, extension=the_suffix) print 'reading particle type 4' S = readsnap(the_snapdir, Nsnapstring, 4, snapshot_name=the_prefix, extension=the_suffix) if (readDM): print 'reading particle type 5 (black holes? I hope not)' P5 = readsnap(the_snapdir, Nsnapstring, 5, snapshot_name=the_prefix, extension=the_suffix,skip_bh=1) print 'reading particle type 1 (fine DM?)' DM = readsnap(the_snapdir, Nsnapstring, 1, snapshot_name=the_prefix, extension=the_suffix) print 'reading particle type 2' P2 = readsnap(the_snapdir, Nsnapstring, 2, snapshot_name=the_prefix, extension=the_suffix) print 'reading particle type 3'
Nsnapstring = '0' + str(sys.argv[1])
else:
Nsnapstring = str(sys.argv[1])
Nsnap = int(sys.argv[1])
the_snapdir = './hdf5/'
if (multifile):
the_snapdir = './snapdir_' + Nsnapstring + '/'
the_prefix = 'snapshot'
the_suffix = '.hdf5'
#read the snapshot
print 'reading particle type 0 (gas?)'
G = readsnap(the_snapdir,
Nsnapstring,
0,
snapshot_name=the_prefix,
extension=the_suffix)
a = G['header'][2]
z = 1.0 / a - 1.0
redshift = G['header'][3]
boxsize = G['header'][9]
omega_matter = G['header'][10]
omega_L = G['header'][11]
h = G['header'][12]
redshiftstring = "{0:.3f}".format(redshift)
Hubble = hubble_param(a, omega_matter, h)
PhysTemp, PhysRho = SF.convertTemp(G['u'], G['ne'], G['rho'], h)
halostats = SF.find_halo_now(halo_to_do, a, therod=use_fixed_halos)
snum_max = snum_min
zmin = 0.510
zmax = 0.525
dt = 0.025
# don't forget to adjust colorbar min/max scale below
vmin = -0.5
vmax = 0.5
x_subtract = 0
y_subtract = 0
z_subtract = 0
xg, yg = np.mgrid[0:1:512j, 0:1:512j]
for snum in np.arange(snum_min, snum_max + 1):
print(snum)
H = readsnap(sdir, snum, 0, header_only=1)
time = H['time']
print('time', time)
P = readsnap(sdir, snum, 0)
Pd = readsnap(sdir, snum, 3)
x = P['p'][:, 0]
y = P['p'][:, 1]
z = P['p'][:, 2]
vx = P['v'][:, 0]
vy = P['v'][:, 1]
vz = P['v'][:, 2]
rho = P['rho']
xd = Pd['p'][:, 0]
yd = Pd['p'][:, 1]
zd = Pd['p'][:, 2]
def snapdata(path, snap):
data = rs.readsnap(path, snap, 0)
dataBH = rs.readsnap(path, snap, 5, skip_bh=1)
dataSTAR = rs.readsnap(path, snap, 4)
return data, dataBH, dataSTAR
