Generate mock data from borg, create MB data and prepare likelihood
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Deaglan Bartlett
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15 changed files with 1192 additions and 11 deletions
5
tests/allocation_stats_0.txt
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tests/allocation_stats_0.txt
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Memory still allocated at the end: 0 MB
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Statistics per context (name, allocated, freed, peak)
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======================
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28
tests/fft_wisdom
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tests/fft_wisdom
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(fftw-3.3.10 fftw_wisdom #x3c273403 #x192df114 #x4d08727c #xe98e9b9d
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(fftw_dft_thr_vrank_geq1_register 0 #x10bdd #x10bdd #x0 #xe7f77f6a #xaf2de8b8 #xad19bc70 #x80305f29)
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(fftw_codelet_n1bv_32_avx 0 #x10bdd #x10bdd #x0 #x6d197f20 #xfc9cbd23 #x91ddb367 #x208619cb)
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(fftw_dft_thr_vrank_geq1_register 0 #x10bdd #x10bdd #x0 #x1f2e97fe #x61895cd8 #x6073a2f5 #x6ada2663)
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(fftw_dft_thr_vrank_geq1_register 0 #x10bdd #x10bdd #x0 #x84033142 #x81339a41 #xb78a491e #x66362e05)
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(fftw_codelet_n1bv_32_avx 0 #x10bdd #x10bdd #x0 #x35d0d312 #x6b498ae1 #x1ddcffdc #x4a1a1998)
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(fftw_dft_thr_vrank_geq1_register 0 #x10bdd #x10bdd #x0 #xbffceb36 #x5b340e87 #xc2433c88 #x10e155b2)
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(fftw_rdft2_thr_vrank_geq1_register 0 #x10bdd #x10bdd #x0 #x7ec9785e #x02957b55 #xab1017dc #xdcd04ed7)
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(fftw_codelet_r2cf_32 2 #x10bdd #x10bdd #x0 #x68269cfc #xb89b69b3 #x4eaad8fa #x9807c679)
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(fftw_rdft2_rank_geq2_register 0 #x10bdd #x10bdd #x0 #x7446ec55 #x3f800a5f #xba25afcf #xc0e9d5c1)
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(fftw_dft_thr_vrank_geq1_register 0 #x10bdd #x10bdd #x0 #x0ac209ed #x737616a2 #xc31f0ad8 #x13c3716f)
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(fftw_dft_vrank_geq1_register 0 #x10bdd #x10bdd #x0 #x4b54e3ca #x4f94ebf3 #x244f4da3 #x2412ca79)
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(fftw_rdft2_rank_geq2_register 0 #x10bdd #x10bdd #x0 #x68900aea #xb640ce9e #xcd3b0e06 #x8170fa63)
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(fftw_dft_vrank_geq1_register 0 #x10bdd #x10bdd #x0 #x404fdd72 #x2323d034 #xc860c577 #x4779492a)
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(fftw_rdft2_rank_geq2_register 0 #x10bdd #x10bdd #x0 #x3c2e2a1a #x07c08954 #x35c337d9 #x80864862)
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(fftw_codelet_n1fv_32_sse2 0 #x10bdd #x10bdd #x0 #xe61c7c8d #x2cea019e #x8489a633 #x8d6543c6)
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(fftw_rdft2_rank_geq2_register 0 #x10bdd #x10bdd #x0 #x962543ac #xb000f636 #xb27fc586 #xd4a83bb7)
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(fftw_codelet_n1fv_32_avx 0 #x10bdd #x10bdd #x0 #x94cb38f8 #xed5987e0 #xa3d4151a #xeb412d04)
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(fftw_codelet_r2cb_32 2 #x10bdd #x10bdd #x0 #x92bf92d5 #xdc456f1e #x5a32a424 #xe1f76e14)
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(fftw_codelet_n1fv_32_avx 0 #x10bdd #x10bdd #x0 #xb5d7d23e #x26089494 #x55133ef3 #x8ac38174)
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(fftw_dft_thr_vrank_geq1_register 0 #x10bdd #x10bdd #x0 #xe0a3b250 #xab7e7c07 #xf0935dde #x1568a95f)
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(fftw_codelet_r2cb_32 2 #x10bdd #x10bdd #x0 #x4e6e3714 #xebce55aa #x0ede5253 #x4faf4524)
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(fftw_codelet_n1bv_32_sse2 0 #x10bdd #x10bdd #x0 #x902cd310 #xa659999d #x6fde2637 #xb23e4fd2)
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(fftw_dft_thr_vrank_geq1_register 0 #x10bdd #x10bdd #x0 #x21347a5d #x286e0d10 #xabf9ff02 #xccdf80a5)
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)
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84
tests/test_forward.py
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tests/test_forward.py
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import numpy as np
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import aquila_borg as borg
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import configparser
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import matplotlib.pyplot as plt
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import borg_velocity.likelihood as likelihood
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import borg_velocity.utils as utils
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import borg_velocity.forwards as forwards
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ini_file = '../conf/basic_ini.ini'
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# Setup config
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config = configparser.ConfigParser()
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config.read(ini_file)
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# Cosmology
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cosmo = utils.get_cosmopar(ini_file)
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# Input box
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box_in = borg.forward.BoxModel()
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box_in.L = (float(config['system']['L0']), float(config['system']['L1']), float(config['system']['L2']))
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box_in.N = (int(config['system']['N0']), int(config['system']['N1']), int(config['system']['N2']))
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box_in.xmin = (float(config['system']['corner0']), float(config['system']['corner1']), float(config['system']['corner2']))
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# Load forward model
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fwd_model = likelihood.build_gravity_model(None, box_in, ini_file=ini_file)
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fwd_model.setCosmoParams(cosmo)
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# Make some initial conditions
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s_hat = np.fft.rfftn(np.random.randn(*box_in.N)) / box_in.Ntot ** (0.5)
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# Get the real version of this
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s_real = np.fft.irfftn(s_hat, norm="ortho")
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# Run BORG density field
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output_density = np.zeros(box_in.N)
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fwd_model.forwardModel_v2(s_hat)
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fwd_model.getDensityFinal(output_density)
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# Get growth rate
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cosmology = borg.cosmo.Cosmology(cosmo)
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af = float(config['model']['af'])
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f = cosmology.gplus(af) # dD / da
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f *= af / cosmology.d_plus(af) # f = dlnD / dlna
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# Get velocity
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smooth_R = float(config['model']['smooth_R'])
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output_vel = forwards.dens2vel_linear(output_density, f, box_in.L[0], smooth_R)
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print(output_vel.shape)
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# Plot the IC and dens fields
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fig, axs = plt.subplots(2, 3, figsize=(15,10))
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for i, field in enumerate([s_real, np.log10(2 + output_density)]):
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vmin, vmax = field.min(), field.max()
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pc = axs[i,0].pcolor(field[box_in.N[0]//2], vmin=vmin, vmax=vmax)
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fig.colorbar(pc, ax=axs[i,0])
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pc = axs[i,1].pcolor(field[:,box_in.N[1]//2,:], vmin=vmin, vmax=vmax)
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fig.colorbar(pc, ax=axs[i,1])
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pc = axs[i,2].pcolor(field[:,:,box_in.N[2]//2], vmin=vmin, vmax=vmax)
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fig.colorbar(pc, ax=axs[i,2])
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axs[0,1].set_title('Initial Conditions')
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axs[1,1].set_title(r'$\log_{10} (2 + \delta)$')
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for ax in axs.flatten():
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ax.set_aspect('equal')
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fig.savefig('../figs/test_dens_ic.png')
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# Plot the velocity fields
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fig, axs = plt.subplots(3, 3, figsize=(15,15))
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vmin, vmax = output_vel.min(), output_vel.max()
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for i in range(3):
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pc = axs[i,0].pcolor(output_vel[i,box_in.N[0]//2], vmin=vmin, vmax=vmax)
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fig.colorbar(pc, ax=axs[i,0])
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pc = axs[i,1].pcolor(output_vel[i,:,box_in.N[1]//2,:], vmin=vmin, vmax=vmax)
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fig.colorbar(pc, ax=axs[i,1])
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pc = axs[i,2].pcolor(output_vel[i,:,:,box_in.N[2]//2], vmin=vmin, vmax=vmax)
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fig.colorbar(pc, ax=axs[i,2])
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axs[0,1].set_title(r'$v_x$')
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axs[1,1].set_title(r'$v_y$')
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axs[2,1].set_title(r'$v_z$')
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for ax in axs.flatten():
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ax.set_aspect('equal')
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fig.savefig('../figs/test_vel.png')
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7
tests/timing_stats_0.txt
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tests/timing_stats_0.txt
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ARES version c6de4f62faad20ede0bb40aa3678551dceee637b modules
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Cumulative timing spent in different context
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--------------------------------------------
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Context, Total time (seconds)
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[/build/jenkins/miniconda3/envs/builder/conda-bld/aquila_borg_1686906696789/work/libLSS/physics/forwards/adapt_generic_bias.cpp]void {anonymous}::bias_registrator() 1 0.000723925
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