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 B0k(galaxies, Lbox=1000., Ngrid=360, step=3, Ncut=3, Nmax=40, fft='pyfftw'): ''' Measure the bispectrum monopole using the `pySpectrum` package Parameters ---------- galaxies : GalaxyCatalog object Return ------ bisp : dictionary ''' bisp = pySpec.Bk_periodic(galaxies, Lbox=Lbox, Ngrid=Ngrid, step=step, Ncut=Ncut, Nmax=Nmax, fft='pyfftw') return bisp
def egBk(): ''' calculate example Bk ''' Lbox = 2600. # box size Ngrid = 360 # fft grid size fnbox = h5py.File(os.path.join(UT.dat_dir(), 'BoxN1.hdf5'), 'r') xyz = fnbox['xyz'].value vxyz = fnbox['vxyz'].value xyz_s = pySpec.applyRSD(xyz.T, vxyz.T, 0.5, h=0.7, omega0_m=0.3, LOS='z', Lbox=2600.) bisp = pySpec.Bk_periodic(xyz_s, Lbox=Lbox, Ngrid=Ngrid, step=3, Ncut=3, Nmax=40, fft='pyfftw') pickle.dump(bisp, open(os.path.join(UT.dat_dir(), 'egBk.p'), 'wb')) return None
def find_Bk(snapshot, snapnum, Ngrid, Nmax, Ncut, step, do_RSD, axis, ptype, fbk): # read header head = readgadget.header(snapshot) BoxSize = head.boxsize / 1e3 #Mpc/h Omega_m = head.omega_m Omega_l = head.omega_l redshift = head.redshift Hubble = 100.0 * np.sqrt(Omega_m * (1.0 + redshift)**3 + Omega_l) #km/s/(Mpc/h) h = head.hubble # read the snapshot pos = readgadget.read_block(snapshot, "POS ", ptype) / 1e3 #Mpc/h # move positions to redshift-space if do_RSD: vel = readgadget.read_block(snapshot, "VEL ", ptype) #km/s RSL.pos_redshift_space(pos, vel, BoxSize, Hubble, redshift, axis) # calculate bispectrum b123out = pySpec.Bk_periodic(pos.T, Lbox=BoxSize, Ngrid=Ngrid, step=step, Ncut=Ncut, Nmax=Nmax, fft='pyfftw', nthreads=1, silent=False) i_k = b123out['i_k1'] j_k = b123out['i_k2'] l_k = b123out['i_k3'] p0k1 = b123out['p0k1'] p0k2 = b123out['p0k2'] p0k3 = b123out['p0k3'] b123 = b123out['b123'] b_sn = b123out['b123_sn'] q123 = b123out['q123'] cnts = b123out['counts'] hdr = ('matter bispectrum; k_f = 2pi/%.1f, Nhalo=%i' % (BoxSize, pos.shape[0])) np.savetxt( fbk, np.array([i_k, j_k, l_k, p0k1, p0k2, p0k3, b123, q123, b_sn, cnts]).T, fmt='%i %i %i %.5e %.5e %.5e %.5e %.5e %.5e %.5e', delimiter='\t', header=hdr)
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
def find_Bk(folder, snapdir, snapnum, axis, Ngrid, step, Ncut, Nmax, do_RSD, fixed_Mmin, Mmin, Nhalos): # read header head = readgadget.header(snapdir) BoxSize = head.boxsize / 1e3 #Mpc/h Omega_m = head.omega_m Omega_l = head.omega_l redshift = head.redshift Hubble = 100.0 * np.sqrt(Omega_m * (1.0 + redshift)**3 + Omega_l) #km/s/(Mpc/h) h = head.hubble # read halo catalogue FoF = readfof.FoF_catalog(folder, snapnum, long_ids=False, swap=False, SFR=False, read_IDs=False) pos_h = FoF.GroupPos / 1e3 #Mpc/h mass = FoF.GroupMass * 1e10 #Msun/h vel_h = FoF.GroupVel * (1.0 + redshift) #km/s if fixed_Mmin: indexes = np.where(mass > Mmin)[0] pos_h = pos_h[indexes] vel_h = vel_h[indexes] del indexes else: indexes = np.argsort(mass)[ -Nhalos:] #take the Nhalos most massive halos pos_h = pos_h[indexes] vel_h = vel_h[indexes] del indexes # move halos to redshift-space if do_RSD: RSL.pos_redshift_space(pos_h, vel_h, BoxSize, Hubble, redshift, axis) # calculate bispectrum b123out = pySpec.Bk_periodic(pos_h.T, Lbox=BoxSize, Ngrid=Ngrid, step=step, Ncut=Ncut, Nmax=Nmax, fft='pyfftw', nthreads=1, silent=False) i_k = b123out['i_k1'] j_k = b123out['i_k2'] l_k = b123out['i_k3'] p0k1 = b123out['p0k1'] p0k2 = b123out['p0k2'] p0k3 = b123out['p0k3'] b123 = b123out['b123'] b_sn = b123out['b123_sn'] q123 = b123out['q123'] cnts = b123out['counts'] hdr = ('halo bispectrum; k_f = 2pi/%.1f, Nhalo=%i' % (BoxSize, pos_h.shape[0])) np.savetxt( fbk, np.array([i_k, j_k, l_k, p0k1, p0k2, p0k3, b123, q123, b_sn, cnts]).T, fmt='%i %i %i %.5e %.5e %.5e %.5e %.5e %.5e %.5e', delimiter='\t', header=hdr)
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') sub.plot(kf * bispec['i_k1'][isort], bispec['p0k1'][isort], c='C0',
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
header=hdr) else: k, p0k, cnts = np.loadtxt(f_pell, skiprows=1, unpack=True, usecols=[0, 1, 2]) # calculate bispectrum if not os.path.isfile(f_b123): # calculate bispectrum if rsd: bispec = pySpec.Bk_periodic(xyz_s.T, Lbox=Lbox, Ngrid=360, Nmax=40, Ncut=3, step=3, fft='pyfftw', nthreads=1, silent=False) else: bispec = pySpec.Bk_periodic(xyz.T, Lbox=Lbox, Ngrid=360, Nmax=40, Ncut=3, step=3, fft='pyfftw', nthreads=1, silent=False)