def test_pySpec(pt, space):
# read test data
fbox = h5py.File(os.path.join(dat_dir(), 'test_box.hdf5'), 'r')
xyz = fbox['xyz'][...]
vxyz = fbox['vxyz'][...]
Lbox = 2600. # box size
Ngrid = 360 # fft grid size
if space == 'rsd':
xyz_s = pySpec.applyRSD(xyz.T, vxyz.T, 0.5, h=0.7, omega0_m=0.3, LOS='z', Lbox=Lbox)
if pt == 2: # 2pt (power spectrum)
if space == 'real':
spec = pySpec.Pk_periodic(xyz.T, Lbox=Lbox, Ngrid=Ngrid, silent=False)
elif space == 'rsd':
spec = pySpec.Pk_periodic(xyz_s, Lbox=Lbox, Ngrid=Ngrid, silent=False)
assert spec['p0k'].mean() > 0.
elif pt == 3: # 3pt (bispectrum)
if space == 'real':
spec = pySpec.Bk_periodic(xyz.T, Lbox=Lbox, Ngrid=Ngrid, silent=False)
elif space == 'rsd':
spec = pySpec.Bk_periodic(xyz_s, Lbox=Lbox, Ngrid=Ngrid, silent=False)
print(spec['p0k1'])
print(spec['counts'])
print(spec['b123'])
assert spec['b123'].mean() > 0.
def QPMspectra(rsd=False):
''' calculate the powerspectrum and bispectrum of the QPM
catalog.
:param rsd: (default: False)
if True calculate in redshift space. Otherwise, real-space
'''
str_rsd = ''
if rsd: str_rsd = '.rsd'
f_halo = ''.join([dir_dat, 'halo_ascii.dat'])
f_hdf5 = ''.join([dir_dat, 'halo.mlim1e13.Lbox1050.hdf5'])
f_pell = ''.join([
dir_dat, 'pySpec.Plk.halo.mlim1e13.Lbox1050', '.Ngrid360', str_rsd,
'.dat'
])
f_pnkt = ''.join([
dir_dat, 'pySpec.Plk.halo.mlim1e13.Lbox1050', '.Ngrid360', '.nbodykit',
str_rsd, '.dat'
])
f_b123 = ''.join([
dir_dat, 'pySpec.B123.halo.mlim1e13.Lbox1050', '.Ngrid360', '.Nmax40',
'.Ncut3', '.step3', '.pyfftw', str_rsd, '.dat'
])
Lbox = 1050.
kf = 2. * np.pi / Lbox
# 1. read in ascii file
# 2. impose 10^13 halo mass limit
# 3. calculate RSD positions
# 4. write to hdf5 file
if not os.path.isfile(f_hdf5):
mh, x, y, z, vx, vy, vz = np.loadtxt(f_halo,
unpack=True,
skiprows=1,
usecols=[0, 1, 2, 3, 4, 5, 6])
xyz = np.zeros((len(x), 3))
xyz[:, 0] = x
xyz[:, 1] = y
xyz[:, 2] = z
vxyz = np.zeros((len(x), 3))
vxyz[:, 0] = vx
vxyz[:, 1] = vy
vxyz[:, 2] = vz
# RSD along the z axis
xyz_s = pySpec.applyRSD(xyz.T,
vxyz.T,
0.55,
h=0.7,
omega0_m=0.340563,
LOS='z',
Lbox=Lbox)
mlim = (mh > 1e13)
mh = mh[mlim]
xyz = xyz[mlim, :]
vxyz = vxyz[mlim, :]
xyz_s = xyz_s.T[mlim, :]
f = h5py.File(f_hdf5, 'w')
f.create_dataset('xyz', data=xyz)
f.create_dataset('vxyz', data=vxyz)
f.create_dataset('xyz_s', data=xyz_s)
f.create_dataset('mhalo', data=mh)
f.close()
else:
f = h5py.File(f_hdf5, 'r')
xyz = f['xyz'].value
xyz_s = f['xyz_s'].value
vxyz = f['vxyz'].value
mh = f['mhalo'].value
Nhalo = xyz.shape[0]
print('# halos = %i in %.1f box' % (Nhalo, Lbox))
nhalo = float(Nhalo) / Lbox**3
print('number density = %f' % nhalo)
print('1/nbar = %f' % (1. / nhalo))
# calculate powerspectrum
if not os.path.isfile(f_pell):
# calculate powerspectrum monopole
if not rsd:
spec = pySpec.Pk_periodic(xyz.T,
Lbox=Lbox,
Ngrid=360,
silent=False)
else:
spec = pySpec.Pk_periodic(xyz_s.T,
Lbox=Lbox,
Ngrid=360,
silent=False)
k = spec['k']
p0k = spec['p0k']
cnts = spec['counts']
# save to file
hdr = (
'pyspectrum P_l=0(k) calculation. Lbox=%.1f, k_f=%.5e, SN=%.5e' %
(Lbox, kf, 1. / nhalo))
np.savetxt(f_pell,
np.array([k, p0k, cnts]).T,
fmt='%.5e %.5e %.5e',
delimiter='\t',
header=hdr)
else:
k, p0k, cnts = np.loadtxt(f_pell,
skiprows=1,
unpack=True,
usecols=[0, 1, 2])
# calculate P(k) using nbodykit for santiy check
if not os.path.isfile(f_pnkt):
# get cosmology from header
Omega_m = 0.3175
Omega_b = 0.049 # fixed baryon
h = 0.6711
cosmo = NBlab.cosmology.Planck15.clone(Omega_cdm=Omega_m - Omega_b,
h=h,
Omega_b=Omega_b)
halo_data = {}
if not rsd: halo_data['Position'] = xyz
else: halo_data['Position'] = xyz_s
halo_data['Velocity'] = vxyz
halo_data['Mass'] = mh
print("putting it into array catalog")
halos = NBlab.ArrayCatalog(halo_data,
BoxSize=np.array([Lbox, Lbox, Lbox]))
print("putting it into halo catalog")
halos = NBlab.HaloCatalog(halos, cosmo=cosmo, redshift=0., mdef='vir')
print("putting it into mesh")
mesh = halos.to_mesh(window='tsc',
Nmesh=360,
compensated=True,
position='Position')
print("calculating powerspectrum")
r = NBlab.FFTPower(mesh, mode='1d', dk=kf, kmin=kf, poles=[0, 2, 4])
poles = r.poles
plk = {'k': poles['k']}
for ell in [0, 2, 4]:
P = (poles['power_%d' % ell].real)
if ell == 0:
P = P - poles.attrs[
'shotnoise'] # subtract shotnoise from monopole
plk['p%dk' % ell] = P
plk['shotnoise'] = poles.attrs['shotnoise'] # save shot noise term
# header
hdr = 'pyspectrum P_l(k) calculation. k_f = 2pi/%.1f; P_shotnoise %f' % (
Lbox, plk['shotnoise'])
# write to file
np.savetxt(f_pnkt,
np.array([plk['k'], plk['p0k'], plk['p2k'], plk['p4k']]).T,
header=hdr)
else:
_k, _p0k, _p2k, _p4k = np.loadtxt(f_pnkt,
skiprows=1,
unpack=True,
usecols=[0, 1, 2, 3])
plk = {}
plk['k'] = _k
plk['p0k'] = _p0k
plk['p2k'] = _p2k
plk['p4k'] = _p4k
# calculate bispectrum
if not os.path.isfile(f_b123):
# calculate bispectrum
if not rsd:
bispec = pySpec.Bk_periodic(xyz.T,
Lbox=Lbox,
Ngrid=360,
Nmax=40,
Ncut=3,
step=3,
fft='pyfftw',
nthreads=1,
silent=False)
else:
bispec = pySpec.Bk_periodic(xyz_s.T,
Lbox=Lbox,
Ngrid=360,
Nmax=40,
Ncut=3,
step=3,
fft='pyfftw',
nthreads=1,
silent=False)
i_k = bispec['i_k1']
j_k = bispec['i_k2']
l_k = bispec['i_k3']
p0k1 = bispec['p0k1']
p0k2 = bispec['p0k2']
p0k3 = bispec['p0k3']
b123 = bispec['b123']
b123_sn = bispec['b123_sn']
q123 = bispec['q123']
counts = bispec['counts']
# save to file
hdr = 'pyspectrum bispectrum calculation test. k_f = 2pi/%.1f' % Lbox
np.savetxt(f_b123,
np.array([
i_k, j_k, l_k, p0k1, p0k2, p0k3, b123, q123, counts,
b123_sn
]).T,
fmt='%i %i %i %.5e %.5e %.5e %.5e %.5e %.5e %.5e',
delimiter='\t',
header=hdr)
else:
i_k, j_k, l_k, p0k1, p0k2, p0k3, b123, q123, counts, b123_sn = np.loadtxt(
f_b123, skiprows=1, unpack=True, usecols=range(10))
# plot powerspecrtrum shape triangle plot
fig = plt.figure(figsize=(5, 5))
sub = fig.add_subplot(111)
sub.plot(k, p0k, c='k', lw=1, label='pySpectrum')
sub.plot(plk['k'], plk['p0k'], c='C1', lw=1, label='nbodykit')
sub.plot(i_k * kf, p0k1, c='k', lw=1, ls='--', label='bispectrum code')
sub.legend(loc='lower left', fontsize=20)
sub.set_ylabel('$P_0(k)$', fontsize=25)
#sub.set_ylim([1e2, 3e4])
sub.set_yscale('log')
sub.set_xlabel('$k$', fontsize=25)
sub.set_xlim([3e-3, 1.])
sub.set_xscale('log')
fig.savefig(''.join([dir_dat, 'qpm_p0k', str_rsd, '.png']),
bbox_inches='tight')
# plot bispectrum shape triangle plot
nbin = 31
x_bins = np.linspace(0., 1., nbin + 1)
y_bins = np.linspace(0.5, 1., (nbin // 2) + 1)
fig = plt.figure(figsize=(10, 5))
sub = fig.add_subplot(111)
Bgrid = Plots._BorQgrid(
l_k.astype(float) / i_k.astype(float),
j_k.astype(float) / i_k.astype(float), q123, counts, x_bins, y_bins)
bplot = plt.pcolormesh(x_bins,
y_bins,
Bgrid.T,
vmin=0,
vmax=1,
cmap='RdBu')
cbar = plt.colorbar(bplot, orientation='vertical')
sub.set_title(r'$Q(k_1, k_2, k_3)$ QPM halo catalog', fontsize=25)
sub.set_xlabel('$k_3/k_1$', fontsize=25)
sub.set_ylabel('$k_2/k_1$', fontsize=25)
fig.savefig(''.join([dir_dat, 'qpm_Q123_shape', str_rsd, '.png']),
bbox_inches='tight')
fig = plt.figure(figsize=(10, 5))
sub = fig.add_subplot(111)
Bgrid = Plots._BorQgrid(
l_k.astype(float) / i_k.astype(float),
j_k.astype(float) / i_k.astype(float), b123, counts, x_bins, y_bins)
bplot = plt.pcolormesh(x_bins,
y_bins,
Bgrid.T,
norm=LogNorm(vmin=1e6, vmax=1e8),
cmap='RdBu')
cbar = plt.colorbar(bplot, orientation='vertical')
sub.set_title(r'$B(k_1, k_2, k_3)$ QPM halo catalog', fontsize=25)
sub.set_xlabel('$k_3/k_1$', fontsize=25)
sub.set_ylabel('$k_2/k_1$', fontsize=25)
fig.savefig(''.join([dir_dat, 'qpm_B123_shape', str_rsd, '.png']),
bbox_inches='tight')
# plot bispectrum amplitude
fig = plt.figure(figsize=(10, 5))
sub = fig.add_subplot(111)
sub.scatter(range(len(b123)), q123, c='k', s=1)
sub.set_xlabel(r'$k_1 > k_2 > k_3$ triangle index', fontsize=25)
sub.set_xlim([0, len(b123)])
sub.set_ylabel(r'$Q(k_1, k_2, k_3)$', fontsize=25)
sub.set_ylim([0., 1.])
fig.savefig(''.join([dir_dat, 'qpm_Q123', str_rsd, '.png']),
bbox_inches='tight')
# plot bispectrum amplitude
fig = plt.figure(figsize=(10, 5))
sub = fig.add_subplot(111)
sub.scatter(range(len(b123)), b123, c='k', s=1)
sub.set_xlabel(r'$k_1 > k_2 > k_3$ triangle index', fontsize=25)
sub.set_xlim([0, len(b123)])
sub.set_ylabel(r'$B(k_1, k_2, k_3)$', fontsize=25)
sub.set_yscale('log')
fig.savefig(''.join([dir_dat, 'qpm_B123', str_rsd, '.png']),
bbox_inches='tight')
return None
def AEMspectra(rsd=False):
''' calculate the powerspectrum and bispectrum of the Aemulus simulation box
'''
str_rsd = ''
if rsd: str_rsd = '.rsd'
f_halo = ''.join(
[UT.dat_dir(), 'aemulus/aemulus_test002_halos.mlim1e13.hdf5'])
f_hdf5 = ''.join(
[UT.dat_dir(), 'aemulus/aemulus_test002_halos.mlim1e13.hdf5'])
f_pell = ''.join([
UT.dat_dir(), 'aemulus/pySpec.Plk.halo.mlim1e13.Ngrid360', str_rsd,
'.dat'
])
f_pnkt = ''.join([
UT.dat_dir(), 'aemulus/pySpec.Plk.halo.mlim1e13.Ngrid360.nbodykit',
str_rsd, '.dat'
])
f_b123 = ''.join([
UT.dat_dir(),
'aemulus/pySpec.B123.halo.mlim1e13.Ngrid360.Nmax40.Ncut3.step3.pyfftw',
str_rsd, '.dat'
])
Lbox = 1050.
kf = 2. * np.pi / Lbox
if not os.path.isfile(f_hdf5):
f = h5py.File(f_halo, 'r')
xyz = f['xyz'].value
vxyz = f['vxyz'].value
mh = f['mhalo'].value
xyz_s = pySpec.applyRSD(xyz.T,
vxyz.T,
0.55,
h=0.7,
omega0_m=0.340563,
LOS='z',
Lbox=Lbox)
xyz_s = xyz_s.T
f = h5py.File(f_hdf5, 'w')
f.create_dataset('xyz', data=xyz)
f.create_dataset('vxyz', data=vxyz)
f.create_dataset('xyz_s', data=xyz_s)
f.create_dataset('mhalo', data=mh)
f.close()
else:
f = h5py.File(f_hdf5, 'r')
xyz = f['xyz'].value
vxyz = f['vxyz'].value
xyz_s = f['xyz_s'].value
mh = f['mhalo'].value
f.close()
Nhalo = xyz.shape[0]
print('# halos = %i' % Nhalo)
nhalo = float(Nhalo) / Lbox**3
print('number density = %f' % nhalo)
print('1/nbar = %f' % (1. / nhalo))
# calculate powerspectrum
if not os.path.isfile(f_pell):
# calculate FFTs
if not rsd:
delta = pySpec.FFTperiodic(xyz.T,
fft='fortran',
Lbox=Lbox,
Ngrid=360,
silent=False)
else:
delta = pySpec.FFTperiodic(xyz_s.T,
fft='fortran',
Lbox=Lbox,
Ngrid=360,
silent=False)
delta_fft = pySpec.reflect_delta(delta, Ngrid=360)
# calculate powerspectrum monopole
k, p0k, cnts = pySpec.Pk_periodic(delta_fft)
k = k * kf
p0k = p0k / kf**3 - 1. / nhalo
# save to file
hdr = 'pyspectrum P_l=0(k) calculation. k_f = 2pi/1050.'
np.savetxt(f_pell,
np.array([k, p0k, cnts]).T,
fmt='%.5e %.5e %.5e',
delimiter='\t',
header=hdr)
else:
k, p0k, cnts = np.loadtxt(f_pell,
skiprows=1,
unpack=True,
usecols=[0, 1, 2])
# calculate P(k) using nbodykit for santiy check
if not os.path.isfile(f_pnkt):
# get cosmology from header
Omega_m = 0.3175
Omega_b = 0.049 # fixed baryon
h = 0.6711
cosmo = NBlab.cosmology.Planck15.clone(Omega_cdm=Omega_m - Omega_b,
h=h,
Omega_b=Omega_b)
halo_data = {}
if not rsd: halo_data['Position'] = xyz
else: halo_data['Position'] = xyz_s
halo_data['Velocity'] = vxyz
halo_data['Mass'] = mh
print("putting it into array catalog")
halos = NBlab.ArrayCatalog(halo_data,
BoxSize=np.array([Lbox, Lbox, Lbox]))
print("putting it into halo catalog")
halos = NBlab.HaloCatalog(halos, cosmo=cosmo, redshift=0., mdef='vir')
print("putting it into mesh")
mesh = halos.to_mesh(window='tsc',
Nmesh=360,
compensated=True,
position='Position')
print("calculating powerspectrum")
r = NBlab.FFTPower(mesh, mode='1d', dk=kf, kmin=kf, poles=[0, 2, 4])
poles = r.poles
plk = {'k': poles['k']}
for ell in [0, 2, 4]:
P = (poles['power_%d' % ell].real)
if ell == 0:
P = P - poles.attrs[
'shotnoise'] # subtract shotnoise from monopole
plk['p%dk' % ell] = P
plk['shotnoise'] = poles.attrs['shotnoise'] # save shot noise term
# header
hdr = 'pyspectrum P_l(k) calculation. k_f = 2pi/1050; P_shotnoise ' + str(
plk['shotnoise'])
# write to file
np.savetxt(f_pnkt,
np.array([plk['k'], plk['p0k'], plk['p2k'], plk['p4k']]).T,
header=hdr)
else:
_k, _p0k, _p2k, _p4k = np.loadtxt(f_pnkt,
skiprows=1,
unpack=True,
usecols=[0, 1, 2, 3])
plk = {}
plk['k'] = _k
plk['p0k'] = _p0k
plk['p2k'] = _p2k
plk['p4k'] = _p4k
# calculate bispectrum
if not os.path.isfile(f_b123):
if not rsd:
bispec = pySpec.Bk_periodic(xyz.T,
Lbox=Lbox,
Ngrid=360,
Nmax=40,
Ncut=3,
step=3,
fft='pyfftw',
nthreads=1,
silent=False)
else:
bispec = pySpec.Bk_periodic(xyz_s.T,
Lbox=Lbox,
Ngrid=360,
Nmax=40,
Ncut=3,
step=3,
fft='pyfftw',
nthreads=1,
silent=False)
i_k = bispec['i_k1']
j_k = bispec['i_k2']
l_k = bispec['i_k3']
p0k1 = bispec['p0k1']
p0k2 = bispec['p0k2']
p0k3 = bispec['p0k3']
b123 = bispec['b123']
b123_sn = bispec['b123_sn']
q123 = bispec['q123']
counts = bispec['counts']
# save to file
hdr = 'pyspectrum bispectrum calculation test. k_f = 2pi/%.1f' % Lbox
np.savetxt(f_b123,
np.array([
i_k, j_k, l_k, p0k1, p0k2, p0k3, b123, q123, counts,
b123_sn
]).T,
fmt='%i %i %i %.5e %.5e %.5e %.5e %.5e %.5e %.5e',
delimiter='\t',
header=hdr)
else:
i_k, j_k, l_k, p0k1, p0k2, p0k3, b123, q123, counts, b123_sn = np.loadtxt(
f_b123, skiprows=1, unpack=True, usecols=range(10))
# plot powerspecrtrum shape triangle plot
fig = plt.figure(figsize=(5, 5))
sub = fig.add_subplot(111)
sub.plot(k, p0k, c='k', lw=1, label='pySpectrum')
sub.plot(plk['k'], plk['p0k'], c='C1', lw=1, label='nbodykit')
iksort = np.argsort(i_k)
sub.plot(i_k[iksort] * kf,
p0k1[iksort],
c='k',
lw=1,
ls='--',
label='bispectrum code')
sub.legend(loc='lower left', fontsize=20)
sub.set_ylabel('$P_0(k)$', fontsize=25)
#sub.set_ylim([1e2, 3e4])
sub.set_yscale('log')
sub.set_xlabel('$k$', fontsize=25)
sub.set_xlim([3e-3, 1.])
sub.set_xscale('log')
fig.savefig(''.join([UT.dat_dir(), 'aemulus/aemulus_p0k', str_rsd,
'.png']),
bbox_inches='tight')
# plot bispectrum shape triangle plot
nbin = 31
x_bins = np.linspace(0., 1., nbin + 1)
y_bins = np.linspace(0.5, 1., (nbin // 2) + 1)
fig = plt.figure(figsize=(10, 5))
sub = fig.add_subplot(111)
Bgrid = Plots._BorQgrid(
l_k.astype(float) / i_k.astype(float),
j_k.astype(float) / i_k.astype(float), q123, counts, x_bins, y_bins)
bplot = plt.pcolormesh(x_bins,
y_bins,
Bgrid.T,
vmin=0,
vmax=1,
cmap='RdBu')
cbar = plt.colorbar(bplot, orientation='vertical')
sub.set_title(r'$Q(k_1, k_2, k_3)$ QPM halo catalog', fontsize=25)
sub.set_xlabel('$k_3/k_1$', fontsize=25)
sub.set_ylabel('$k_2/k_1$', fontsize=25)
fig.savefig(''.join(
[UT.dat_dir(), 'aemulus/aemulus_Q123_shape', str_rsd, '.png']),
bbox_inches='tight')
fig = plt.figure(figsize=(10, 5))
sub = fig.add_subplot(111)
Bgrid = Plots._BorQgrid(
l_k.astype(float) / i_k.astype(float),
j_k.astype(float) / i_k.astype(float), b123, counts, x_bins, y_bins)
bplot = plt.pcolormesh(x_bins,
y_bins,
Bgrid.T,
norm=LogNorm(vmin=1e6, vmax=1e8),
cmap='RdBu')
cbar = plt.colorbar(bplot, orientation='vertical')
sub.set_title(r'$B(k_1, k_2, k_3)$ QPM halo catalog', fontsize=25)
sub.set_xlabel('$k_3/k_1$', fontsize=25)
sub.set_ylabel('$k_2/k_1$', fontsize=25)
fig.savefig(''.join(
[UT.dat_dir(), 'aemulus/aemulus_B123_shape', str_rsd, '.png']),
bbox_inches='tight')
# plot bispectrum amplitude
fig = plt.figure(figsize=(10, 5))
sub = fig.add_subplot(111)
sub.scatter(range(len(b123)), q123, c='k', s=1)
sub.set_xlabel(r'$k_1 > k_2 > k_3$ triangle index', fontsize=25)
sub.set_xlim([0, len(b123)])
sub.set_ylabel(r'$Q(k_1, k_2, k_3)$', fontsize=25)
sub.set_ylim([0., 1.])
fig.savefig(''.join(
[UT.dat_dir(), 'aemulus/aemulus_Q123', str_rsd, '.png']),
bbox_inches='tight')
# plot bispectrum amplitude
fig = plt.figure(figsize=(10, 5))
sub = fig.add_subplot(111)
sub.scatter(range(len(b123)), b123, c='k', s=1)
sub.set_xlabel(r'$k_1 > k_2 > k_3$ triangle index', fontsize=25)
sub.set_xlim([0, len(b123)])
sub.set_ylabel(r'$B(k_1, k_2, k_3)$', fontsize=25)
sub.set_yscale('log')
fig.savefig(''.join(
[UT.dat_dir(), 'aemulus/aemulus_B123', str_rsd, '.png']),
bbox_inches='tight')
return None
mpl.rcParams['legend.frameon'] = False
Lbox = 2600. # box size
Ngrid = 360 # fft grid size
kf = 2 * np.pi / Lbox # fundament mode
# read in Nseries box data
fnbox = h5py.File(os.path.join(UT.dat_dir(), 'BoxN1.hdf5'), 'r')
xyz = fnbox['xyz'].value
vxyz = fnbox['vxyz'].value
nhalo = xyz.shape[0]
nbar = float(nhalo) / Lbox**3
# real-space power/bispectrum with pySpectrum
t0 = time.time()
pspec = pySpec.Pk_periodic(xyz.T, Lbox=Lbox, Ngrid=Ngrid, silent=False)
print('--pySpec.Pk_periodic: %f sec' % ((time.time() - t0) / 60.))
t0 = time.time()
bispec = pySpec.Bk_periodic(xyz.T, Lbox=Lbox, Ngrid=Ngrid, silent=False)
print('--pySpec.Bk_periodic: %f sec' % ((time.time() - t0) / 60.))
# compare real-space bispectrum with Roman's output
f_bk_rs = os.path.join(UT.dat_dir(), 'bk.BoxN1.mock')
_i, _j, _l, _pi, _pj, _pl, _b123, _q123 = np.loadtxt(
f_bk_rs, unpack=True, usecols=[0, 1, 2, 3, 4, 5, 6, 7])
# compare output powerspectrum
fig = plt.figure(figsize=(5, 5))
sub = fig.add_subplot(111)
isort = np.argsort(bispec['i_k1'])
sub.plot(pspec['k'], pspec['p0k'], c='C1', label='pySpec Pk code')
# read in Nseries box data
fnbox = h5py.File(os.path.join(UT.dat_dir(), 'BoxN1.hdf5'), 'r')
xyz = fnbox['xyz'][...]
vxyz = fnbox['vxyz'][...]
nhalo = xyz.shape[0]
nbar = float(nhalo) / Lbox**3
N = xyz.shape[1] # number of positions
kf = 2 * np.pi / Lbox
# Pk from real-space powerspectrum function
t0 = time.time()
pkout = pySpec.Pk_periodic(xyz.T,
Lbox=Lbox,
Ngrid=Ngrid,
fft='pyfftw',
silent=False)
print('--pySpec.Pk_periodic: %f sec' % ((time.time() - t0) / 60.))
t0 = time.time()
# Pk from redshift-space powerspectrum function
_pkout = pySpec.Pk_periodic_rsd(xyz.T,
Lbox=Lbox,
Ngrid=Ngrid,
rsd=2,
fft='pyfftw',
code='fortran',
silent=False)
print('--pySpec.Pk_periodic_rsd: %f sec' % ((time.time() - t0) / 60.))
def stage1(name):
''' stage 1 of mock challenge. run power spectrum for periodic box
'''
# read in mock
if name == 'unit':
_fname = 'UNIT_DESI_Shadab_HOD_snap97_ELG_v0.txt'
Lbox = 1000.
elif name == 'pmill':
_fname = 'DESI_ELG_z0.76_catalogue.dat'
Lbox = 542.16
x, y, z, z_rsd = np.loadtxt(os.path.join(dir_mc, _fname),
unpack=True,
usecols=[0, 1, 2, 3])
print('--- %s mock ---' % name)
print('%.1f < x < %.1f' % (x.min(), x.max()))
print('%.1f < y < %.1f' % (y.min(), y.max()))
print('%.1f < z < %.1f' % (z.min(), z.max()))
print('%.1f < z_rsd < %.1f' % (z_rsd.min(), z_rsd.max()))
# real power spectrum
xyz = np.array([x, y, z])
p0k_real = pySpec.Pk_periodic(xyz,
Lbox=Lbox,
Ngrid=512,
fft='pyfftw',
silent=False)
# redshift-space power spectrum
xyz_s = np.array([x, y, z_rsd])
pk_rsd = pySpec.Pk_periodic_rsd(xyz_s,
Lbox=Lbox,
Ngrid=512,
rsd=2,
Nmubin=120,
fft='pyfftw',
code='fortran',
silent=False)
# write out Pl(k)
fout = os.path.join(dir_mc, 'Pkl_lin_HAHN_%s_1.txt' % name.upper())
np.savetxt(fout,
np.array([
pk_rsd['k'], pk_rsd['p0k'], pk_rsd['p2k'], pk_rsd['p4k'],
pk_rsd['counts']
]).T,
header='k, p0k, p2k, p4k, n_modes',
fmt='%.5e %.5e %.5e %.5e %i')
fig = plt.figure(figsize=(5, 5))
sub = fig.add_subplot(111)
sub.plot(p0k_real['k'], p0k_real['p0k'], c='k', ls=':', label='real-space')
sub.plot(pk_rsd['k'], pk_rsd['p0k'], c='k', label='$\ell=0$')
sub.plot(pk_rsd['k'], pk_rsd['p2k'], c='C0', label='$\ell=2$')
sub.plot(pk_rsd['k'], pk_rsd['p4k'], c='C1', label='$\ell=4$')
sub.legend(loc='upper right', fontsize=15)
sub.set_xlabel('$k$ (Mpc/$h$)', fontsize=25)
sub.set_xlim(1e-2, 2)
sub.set_xscale("log")
sub.set_ylabel('$P_\ell(k)$', fontsize=25)
sub.set_yscale("log")
sub.set_ylim(3., 5e4)
fig.savefig(os.path.join(dir_mc,
'plk.%s.png' % _fname.replace('.txt', '')),
bbox_inches='tight')
# write out 2D P(k,mu)
fout = os.path.join(dir_mc, 'pk2D_lin_HAHN_%s_1.txt' % name.upper())
np.savetxt(fout,
np.array([
pk_rsd['k_kmu'].flatten(), pk_rsd['mu_kmu'].flatten(),
pk_rsd['p_kmu'].flatten(), pk_rsd['counts_kmu'].flatten()
]).T,
header='k, mu, p(k,mu), n_modes',
fmt='%.5e %.5e %.5e %i')
fig = plt.figure(figsize=(6, 5))
sub = fig.add_subplot(111)
cm = sub.pcolormesh(pk_rsd['mu_kmu'],
pk_rsd['k_kmu'],
pk_rsd['p_kmu'],
norm=LogNorm(vmin=1e3, vmax=1e5))
sub.set_yscale('log')
sub.set_ylim(1e-2, 2)
fig.savefig(os.path.join(dir_mc,
'pk2d.%s.png' % _fname.replace('.txt', '')),
bbox_inches='tight')
return None
'''
calculate powerspectrum
'''
import time
import numpy as np
import matplotlib.pyplot as plt
from pyspectrum import util as UT
from pyspectrum import pyspectrum as pySpec
if __name__ == "__main__":
# read in FFTed density grid
f_fft = ''.join([UT.dat_dir(), 'FFT.BoxN1.mock.Ngrid360'])
delta = pySpec.read_fortFFT(file=f_fft)
# calculate powerspectrum monopole
k, p0k = pySpec.Pk_periodic(delta)
kf = 2. * np.pi / 2600.
_k, _p0k = np.loadtxt(''.join([UT.dat_dir(), 'PK.BoxN1.mock.Ngrid360']),
unpack=True,
usecols=[0, 1])
plt.plot(kf * k, p0k / (2. * np.pi)**3 / kf**3)
plt.plot(_k, _p0k, ls='--')
plt.xscale("log")
plt.yscale("log")
plt.show()
def fastPM(z, str_flag='', mh_lim=15., Lbox=205., Nmax=40, Ncut=3, step=3):
''' calculate the powerspectrum and bispectrum of the fastPM catalog.
'''
dir_fpm = os.path.join(UT.dat_dir(), 'fastpm')
f_halo = ('halocat_FastPM_40step_N250_IC500_B2_z%.2f%s.txt' %
(z, str_flag))
f_mlim = ('halocat_FastPM_40step_N250_IC500_B2_z%.2f%s.mlim%.fe10' %
(z, str_flag, mh_lim))
f_hdf5 = ('%s/%s.hdf5' % (dir_fpm, f_mlim))
f_pell = ('%s/pySpec.Plk.%s.Lbox%.f.Ngrid360.dat' %
(dir_fpm, f_mlim, Lbox))
f_pnkt = ('%s/pySpec.Plk.%s.Lbox%.f.Ngrid360.nbodykit.dat' %
(dir_fpm, f_mlim, Lbox))
f_b123 = ('%s/pySpec.Bk.%s.Lbox%.f.Ngrid360.step%i.Ncut%i.Nmax%i.dat' %
(dir_fpm, f_mlim, Lbox, step, Ncut, Nmax))
kf = 2. * np.pi / Lbox
if not os.path.isfile(f_hdf5):
# read in halo catalog
dat_halo = np.loadtxt(os.path.join(dir_fpm, f_halo),
unpack=True,
usecols=[0, 1, 2, 3, 7, 8, 9])
mh = dat_halo[0]
Nhalo = len(mh)
print('%i halos in %.f Mpc/h box' % (len(mh), Lbox))
print('%f < M_h/10^10Msun < %f' % (mh.min(), mh.max()))
xyz = np.zeros((Nhalo, 3))
xyz[:, 0] = dat_halo[1]
xyz[:, 1] = dat_halo[2]
xyz[:, 2] = dat_halo[3]
print('%f < x < %f' % (xyz[:, 0].min(), xyz[:, 0].max()))
print('%f < y < %f' % (xyz[:, 1].min(), xyz[:, 1].max()))
print('%f < z < %f' % (xyz[:, 2].min(), xyz[:, 2].max()))
vxyz = np.zeros((Nhalo, 3))
vxyz[:, 0] = dat_halo[4]
vxyz[:, 1] = dat_halo[5]
vxyz[:, 2] = dat_halo[6]
mlim = (mh > 15.)
Nhalo = np.sum(mlim)
print('%i halos in %.f Mpc/h box with Mh > %f' % (Nhalo, Lbox, mh_lim))
mh = mh[mlim]
xyz = xyz[mlim, :]
vxyz = vxyz[mlim, :]
f = h5py.File(f_hdf5, 'w')
f.create_dataset('xyz', data=xyz)
f.create_dataset('vxyz', data=vxyz)
f.create_dataset('mhalo', data=mh)
f.close()
else:
f = h5py.File(f_hdf5, 'r')
xyz = f['xyz'].value
vxyz = f['vxyz'].value
mh = f['mhalo'].value
Nhalo = xyz.shape[0]
print('%i halos in %.f Mpc/h box with Mh > %f' %
(len(mh), Lbox, mh_lim))
nhalo = float(Nhalo) / Lbox**3
print('number density = %f' % nhalo)
print('1/nbar = %f' % (1. / nhalo))
# calculate powerspectrum
if not os.path.isfile(f_pell):
delta = pySpec.FFTperiodic(xyz.T,
fft='fortran',
Lbox=Lbox,
Ngrid=360,
silent=False)
delta_fft = pySpec.reflect_delta(delta, Ngrid=360)
# calculate powerspectrum monopole
k, p0k, cnts = pySpec.Pk_periodic(delta_fft)
k *= kf
p0k = p0k / (kf**3) - 1. / nhalo
# save to file
hdr = ('pySpectrum P_l=0(k). Nhalo=%i, Lbox=%.f, k_f=%.5e, SN=%.5e' %
(Nhalo, Lbox, kf, 1. / nhalo))
hdr += '\n k, p0k, counts'
np.savetxt(f_pell,
np.array([k, p0k, cnts]).T,
fmt='%.5e %.5e %.5e',
delimiter='\t',
header=hdr)
else:
k, p0k, cnts = np.loadtxt(f_pell,
skiprows=1,
unpack=True,
usecols=[0, 1, 2])
# calculate P(k) using nbodykit for santiy check
if not os.path.isfile(f_pnkt):
cosmo = NBlab.cosmology.Planck15
halo_data = {}
halo_data['Position'] = xyz
halo_data['Velocity'] = vxyz
halo_data['Mass'] = mh
print("putting it into array catalog")
halos = NBlab.ArrayCatalog(halo_data,
BoxSize=np.array([Lbox, Lbox, Lbox]))
print("putting it into halo catalog")
halos = NBlab.HaloCatalog(halos, cosmo=cosmo, redshift=z, mdef='vir')
print("putting it into mesh")
mesh = halos.to_mesh(window='tsc',
Nmesh=360,
compensated=True,
position='Position')
print("calculating powerspectrum")
r = NBlab.FFTPower(mesh, mode='1d', dk=kf, kmin=kf, poles=[0, 2, 4])
poles = r.poles
plk = {'k': poles['k']}
for ell in [0, 2, 4]:
P = (poles['power_%d' % ell].real)
if ell == 0:
P = P - poles.attrs[
'shotnoise'] # subtract shotnoise from monopole
plk['p%dk' % ell] = P
plk['shotnoise'] = poles.attrs['shotnoise'] # save shot noise term
# header
hdr = ('pySpectrum P_l(k). Nhalo=%i, Lbox=%.f, k_f=%.5e, SN=%.5e' %
(Nhalo, Lbox, kf, plk['shotnoise']))
hdr += '\n k, p0k, p2k, p4k'
# save to file
np.savetxt(f_pnkt,
np.array([plk['k'], plk['p0k'], plk['p2k'], plk['p4k']]).T,
header=hdr)
else:
_k, _p0k, _p2k, _p4k = np.loadtxt(f_pnkt,
skiprows=1,
unpack=True,
usecols=[0, 1, 2, 3])
plk = {}
plk['k'] = _k
plk['p0k'] = _p0k
plk['p2k'] = _p2k
plk['p4k'] = _p4k
# calculate bispectrum
if not os.path.isfile(f_b123):
# calculate bispectrum
bispec = pySpec.Bk_periodic(xyz.T,
Lbox=Lbox,
Ngrid=360,
Nmax=40,
Ncut=3,
step=3,
fft='pyfftw',
nthreads=1,
silent=False)
i_k = bispec['i_k1']
j_k = bispec['i_k2']
l_k = bispec['i_k3']
p0k1 = bispec['p0k1']
p0k2 = bispec['p0k2']
p0k3 = bispec['p0k3']
b123 = bispec['b123']
b123_sn = bispec['b123_sn']
q123 = bispec['q123']
counts = bispec['counts']
# save to file
hdr = 'pyspectrum bispectrum calculation test. k_f = 2pi/%.1f' % Lbox
hdr += '\n i_k1, i_k2, i_k3, p0k1, p0k2, p0k3, bk, qk, counts, bk_shotnoise'
np.savetxt(f_b123,
np.array([
i_k, j_k, l_k, p0k1, p0k2, p0k3, b123, q123, counts,
b123_sn
]).T,
fmt='%i %i %i %.5e %.5e %.5e %.5e %.5e %.5e %.5e',
delimiter='\t',
header=hdr)
else:
i_k, j_k, l_k, p0k1, p0k2, p0k3, b123, q123, counts, b123_sn = np.loadtxt(
f_b123, skiprows=1, unpack=True, usecols=range(10))
# plot powerspecrtrum shape triangle plot
fig = plt.figure(figsize=(5, 5))
sub = fig.add_subplot(111)
sub.plot(k, p0k, c='k', lw=1, label='pySpectrum')
sub.plot(plk['k'], plk['p0k'], c='C1', lw=1, label='nbodykit')
iksort = np.argsort(i_k)
sub.plot(i_k[iksort] * kf,
p0k1[iksort],
c='k',
lw=1,
ls='--',
label='bispectrum code')
sub.legend(loc='lower left', fontsize=20)
sub.set_ylabel('$P_0(k)$', fontsize=25)
sub.set_ylim([1e0, 1e4])
sub.set_yscale('log')
sub.set_xlabel('$k$', fontsize=25)
sub.set_xlim([1e-2, 10.])
sub.set_xscale('log')
fig.savefig(f_pell.replace('.dat', '.png'), bbox_inches='tight')
# plot bispectrum shape triangle plot
nbin = 31
x_bins = np.linspace(0., 1., nbin + 1)
y_bins = np.linspace(0.5, 1., (nbin // 2) + 1)
fig = plt.figure(figsize=(10, 5))
sub = fig.add_subplot(111)
Bgrid = Plots._BorQgrid(
l_k.astype(float) / i_k.astype(float),
j_k.astype(float) / i_k.astype(float), q123, counts, x_bins, y_bins)
bplot = plt.pcolormesh(x_bins,
y_bins,
Bgrid.T,
vmin=0,
vmax=1,
cmap='RdBu')
cbar = plt.colorbar(bplot, orientation='vertical')
sub.set_title(r'$Q(k_1, k_2, k_3)$ FastPM halo catalog', fontsize=25)
sub.set_xlabel('$k_3/k_1$', fontsize=25)
sub.set_ylabel('$k_2/k_1$', fontsize=25)
fig.savefig(f_b123.replace('.dat', '.Qk_shape.png'), bbox_inches='tight')
fig = plt.figure(figsize=(10, 5))
sub = fig.add_subplot(111)
Bgrid = Plots._BorQgrid(
l_k.astype(float) / i_k.astype(float),
j_k.astype(float) / i_k.astype(float), b123, counts, x_bins, y_bins)
bplot = plt.pcolormesh(x_bins,
y_bins,
Bgrid.T,
norm=LogNorm(vmin=1e6, vmax=1e8),
cmap='RdBu')
cbar = plt.colorbar(bplot, orientation='vertical')
sub.set_title(r'$B(k_1, k_2, k_3)$ FastPM halo catalog', fontsize=25)
sub.set_xlabel('$k_3/k_1$', fontsize=25)
sub.set_ylabel('$k_2/k_1$', fontsize=25)
fig.savefig(f_b123.replace('.dat', '.Bk_shape.png'), bbox_inches='tight')
# plot bispectrum amplitude
fig = plt.figure(figsize=(10, 5))
sub = fig.add_subplot(111)
sub.scatter(range(len(b123)), q123, c='k', s=1)
sub.set_xlabel(r'$k_1 > k_2 > k_3$ triangle index', fontsize=25)
sub.set_xlim([0, len(b123)])
sub.set_ylabel(r'$Q(k_1, k_2, k_3)$', fontsize=25)
sub.set_ylim([0., 1.])
fig.savefig(f_b123.replace('.dat', '.Qk.png'), bbox_inches='tight')
fig = plt.figure(figsize=(10, 5))
sub = fig.add_subplot(111)
sub.scatter(range(len(b123)), b123, c='k', s=1)
sub.set_xlabel(r'$k_1 > k_2 > k_3$ triangle index', fontsize=25)
sub.set_xlim([0, len(b123)])
sub.set_ylabel(r'$B(k_1, k_2, k_3)$', fontsize=25)
sub.set_yscale('log')
fig.savefig(f_b123.replace('.dat', '.Bk.png'), bbox_inches='tight')
return None
print(ax)
print(s_xyz[i, :10])
print(xyz_f[i, :10])
_delta = pySpec.FFTperiodic(s_xyz, Lbox=2600, Ngrid=360, silent=False)
delta = pySpec.reflect_delta(_delta, Ngrid=360, silent=False)
delt = pySpec.read_fortFFT(
file=os.path.join(UT.dat_dir(), 'FFT.BoxN1.mock.rsd_z.Ngrid360'))
print(delta - delt)[:10, 0, 0]
print delta.ravel()[np.argmax(np.abs(delta - delt))]
print delt.ravel()[np.argmax(np.abs(delta - delt))]
# calculate powerspectrum monopole
k, p0k, cnts = pySpec.Pk_periodic(delta)
f_pk = os.path.join(UT.dat_dir(), 'p0k.rsd_test.dat')
f_b123 = os.path.join(UT.dat_dir(), 'B123.rsd_test.dat')
# save to file
hdr = 'pyspectrum P_l=0(k) calculation'
np.savetxt(f_pk,
np.array([k * kf, p0k / (kf**3), cnts]).T,
fmt='%.5e %.5e %.5e',
delimiter='\t',
header=hdr)
# calculate bispectrum
bisp = pySpec.Bk123_periodic(delta,
Nmax=40,
Ncut=3,
step=3,
xyz = f['xyz'].value
xyz_s = f['xyz_s'].value
vxyz = f['vxyz'].value
mh = f['mhalo'].value
Nhalo = xyz.shape[0]
print('# halos = %i in %.1f box' % (Nhalo, Lbox))
nhalo = float(Nhalo) / Lbox**3
print('number density = %f' % nhalo)
print('1/nbar = %f' % (1. / nhalo))
# calculate powerspectrum
if not os.path.isfile(f_pell):
# calculate powerspectrum monopole
if not rsd:
spec = pySpec.Pk_periodic(xyz.T, Lbox=Lbox, Ngrid=360, silent=False)
else:
spec = pySpec.Pk_periodic(xyz_s.T, Lbox=Lbox, Ngrid=360, silent=False)
k = spec['k']
p0k = spec['p0k']
cnts = spec['counts']
# save to file
hdr = ('pyspectrum P_l=0(k) calculation. Lbox=%.1f, k_f=%.5e, SN=%.5e' %
(Lbox, kf, 1. / nhalo))
np.savetxt(f_pell,
np.array([k, p0k, cnts]).T,
fmt='%.5e %.5e %.5e',
delimiter='\t',
header=hdr)
else:
k, p0k, cnts = np.loadtxt(f_pell,