Add some likelihood tests

borg_velocity/likelihood.py

@@ -50,6 +50,9 @@ class VelocityBORGLikelihood(borg.likelihood.BaseLikelihood):
         # What type of run we're doing
         self.run_type = config['run']['run_type']
         
+        # Seed if creating mocks
+        self.mock_seed = int(config['mock']['seed'])
+        
         # Model parameters
         self.ai = float(config['model']['ai'])
         self.af = float(config['model']['af'])
@@ -198,7 +201,7 @@ class VelocityBORGLikelihood(borg.likelihood.BaseLikelihood):
             self.MB_pos[i] = jnp.transpose(self.MB_pos[i], (2, 1, 0))
         
         
-    def generateMockData(self, s_hat: np.ndarray, state: borg.likelihood.MarkovState, make_plot: bool=True) -> None:
+    def generateMockData(self, s_hat: np.ndarray, state: borg.likelihood.MarkovState,) -> None:
         """
         Generates mock data by simulating the forward model with the given white noise,
         drawing distance tracers from the density field, computing their distance
@@ -215,6 +218,7 @@ class VelocityBORGLikelihood(borg.likelihood.BaseLikelihood):
         elif self.run_type == 'velmass':
             raise NotImplementedError
         elif self.run_type == 'mock':
+            np.random.seed(self.mock_seed)
             self.coord_true, self.coord_meas, self.sig_mu, self.vr_true, self.cz_obs = \
                 mock_maker.borg_mock(s_hat, state, self.fwd, self.ini_file)
         else:

conf/basic_ini.ini

@@ -74,19 +74,20 @@ NCAT = 0
 NSAMP = 2
 
 [mock]
+seed = 5
 R_max = 100
 
 [python]
 likelihood_path = /home/bartlett/fsigma8/borg_velocity/borg_velocity/likelihood.py
 
 [sample_0]
-Nt = 345
+Nt = 160
 muA = 1.0
 alpha = 1.4
 frac_sig_rhMpc = 0.07
 
 [sample_1]
-Nt = 1682
+Nt = 230
 muA = 1.0
 alpha = 1.4
 frac_sig_rhMpc = 0.07

tests/allocation_stats_0.txt

@@ -1,5 +1,19 @@
-Memory still allocated at the end: 0 MB
+Memory still allocated at the end: 14.4902 MB
 
 Statistics per context (name, allocated, freed, peak)
 ======================
 
+*none*                                   80.4688 0.250069 14.9746
+BORG LPT MODEL                           533.774 532.007 14.9902
+BORGForwardModel::setup                  0.000160217 0 2.23588
+BorgLptModel::BorgLptModel               1.54688 0 2.23581
+[/build/jenkins/miniconda3/envs/builder/conda-bld/aquila_borg_1686906696789/work/libLSS/physics/chain_forward_model.cpp]virtual void LibLSS::ChainForwardModel::forwardModel_v2(LibLSS::detail_input::ModelInput<3>) 240.656 80.2188 15.2402
+[/build/jenkins/miniconda3/envs/builder/conda-bld/aquila_borg_1686906696789/work/libLSS/physics/forward_model.cpp]void LibLSS::BORGForwardModel::setupDefault() 0.53125 0 0.688934
+[/build/jenkins/miniconda3/envs/builder/conda-bld/aquila_borg_1686906696789/work/libLSS/physics/forwards/borg_lpt.cpp]std::shared_ptr<LibLSS::BORGForwardModel> build_borg_lpt(std::shared_ptr<LibLSS::MPI_Communication>, const LibLSS::BoxModel&, const LibLSS::PropertyProxy&) [with Grid = LibLSS::ClassicCloudInCell<double>; LibLSS::BoxModel = LibLSS::NBoxModel<3>] 0 0 0.157661
+[/build/jenkins/miniconda3/envs/builder/conda-bld/aquila_borg_1686906696789/work/libLSS/physics/forwards/particle_balancer/balanceinfo.hpp]void LibLSS::BalanceInfo::allocate(LibLSS::MPI_Communication*, size_t) 76.2534 76.0009 14.9902
+[/build/jenkins/miniconda3/envs/builder/conda-bld/aquila_borg_1686906696789/work/libLSS/physics/forwards/primordial_as.cpp]std::shared_ptr<LibLSS::BORGForwardModel> build_primordial_as(std::shared_ptr<LibLSS::MPI_Communication>, const LibLSS::BoxModel&, const LibLSS::PropertyProxy&) 0.078804 7.62939e-06 0.0788498
+[/build/jenkins/miniconda3/envs/builder/conda-bld/aquila_borg_1686906696789/work/libLSS/physics/forwards/transfer_class.cpp]std::shared_ptr<LibLSS::BORGForwardModel> build_class(std::shared_ptr<LibLSS::MPI_Communication>, const LibLSS::BoxModel&, const LibLSS::PropertyProxy&) 0.078804 7.62939e-06 0.157669
+[/build/jenkins/miniconda3/envs/builder/conda-bld/aquila_borg_1686906696789/work/libLSS/physics/model_io/base.hpp]void LibLSS::detail_model::ModelIO<Nd>::transfer(LibLSS::detail_model::ModelIO<Nd>&&) [with long unsigned int Nd = 3] 0 235.156 0
+[/build/jenkins/miniconda3/envs/builder/conda-bld/aquila_borg_1686906696789/work/libLSS/samplers/core/gridLikelihoodBase.cpp]LibLSS::GridDensityLikelihoodBase<Dims>::GridDensityLikelihoodBase(LibLSS::MPI_Communication*, const GridSizes&, const GridLengths&) [with int Dims = 3; GridSizes = std::array<long unsigned int, 3>; GridLengths = std::array<double, 3>] 0.53125 0.515625 2.76713
+[/build/jenkins/miniconda3/envs/builder/conda-bld/aquila_borg_1686906696789/work/python/pyforward.cpp]void do_get_density_final(LibLSS::BORGForwardModel*, pybind11::array) 80.2188 75.5 14.9902
+lpt_ic                                   80.2188 80.2188 15.2558

tests/fft_wisdom

@@ -1,18 +1,18 @@
 (fftw-3.3.10 fftw_wisdom #x3c273403 #x192df114 #x4d08727c #xe98e9b9d
+  (fftw_dft_thr_vrank_geq1_register 0 #x10bdd #x10bdd #x0 #x21347a5d #x286e0d10 #xabf9ff02 #xccdf80a5)
   (fftw_dft_thr_vrank_geq1_register 0 #x10bdd #x10bdd #x0 #xe7f77f6a #xaf2de8b8 #xad19bc70 #x80305f29)
   (fftw_codelet_n1bv_32_avx 0 #x10bdd #x10bdd #x0 #x6d197f20 #xfc9cbd23 #x91ddb367 #x208619cb)
   (fftw_dft_thr_vrank_geq1_register 0 #x10bdd #x10bdd #x0 #x1f2e97fe #x61895cd8 #x6073a2f5 #x6ada2663)
   (fftw_dft_thr_vrank_geq1_register 0 #x10bdd #x10bdd #x0 #x84033142 #x81339a41 #xb78a491e #x66362e05)
+  (fftw_dft_thr_vrank_geq1_register 0 #x10bdd #x10bdd #x0 #x0ac209ed #x737616a2 #xc31f0ad8 #x13c3716f)
   (fftw_rdft2_thr_vrank_geq1_register 0 #x10bdd #x10bdd #x0 #x40ffeb6f #x4d232a35 #x49c61e65 #x4d75fa83)
   (fftw_codelet_n1bv_32_avx 0 #x10bdd #x10bdd #x0 #x35d0d312 #x6b498ae1 #x1ddcffdc #x4a1a1998)
   (fftw_dft_thr_vrank_geq1_register 0 #x10bdd #x10bdd #x0 #xbffceb36 #x5b340e87 #xc2433c88 #x10e155b2)
-  (fftw_rdft2_thr_vrank_geq1_register 0 #x10bdd #x10bdd #x0 #x7ec9785e #x02957b55 #xab1017dc #xdcd04ed7)
   (fftw_codelet_r2cf_32 2 #x10bdd #x10bdd #x0 #xe5219ff5 #x7cc0cc2f #x9ce07377 #x12d27b02)
   (fftw_dft_thr_vrank_geq1_register 0 #x10bdd #x10bdd #x0 #xd78cc60c #x6e1210c6 #x5868829d #x70ada990)
   (fftw_codelet_r2cf_32 2 #x10bdd #x10bdd #x0 #x68269cfc #xb89b69b3 #x4eaad8fa #x9807c679)
   (fftw_rdft2_rank_geq2_register 0 #x10bdd #x10bdd #x0 #x7446ec55 #x3f800a5f #xba25afcf #xc0e9d5c1)
-  (fftw_dft_thr_vrank_geq1_register 0 #x10bdd #x10bdd #x0 #x0ac209ed #x737616a2 #xc31f0ad8 #x13c3716f)
+  (fftw_rdft2_thr_vrank_geq1_register 0 #x10bdd #x10bdd #x0 #x7ec9785e #x02957b55 #xab1017dc #xdcd04ed7)
-  (fftw_dft_vrank_geq1_register 0 #x10bdd #x10bdd #x0 #x4b54e3ca #x4f94ebf3 #x244f4da3 #x2412ca79)
   (fftw_rdft2_rank_geq2_register 0 #x10bdd #x10bdd #x0 #x68900aea #xb640ce9e #xcd3b0e06 #x8170fa63)
   (fftw_dft_vrank_geq1_register 0 #x10bdd #x10bdd #x0 #x404fdd72 #x2323d034 #xc860c577 #x4779492a)
   (fftw_rdft2_rank_geq2_register 0 #x10bdd #x10bdd #x0 #x3c2e2a1a #x07c08954 #x35c337d9 #x80864862)
@@ -24,5 +24,5 @@
   (fftw_dft_thr_vrank_geq1_register 0 #x10bdd #x10bdd #x0 #xe0a3b250 #xab7e7c07 #xf0935dde #x1568a95f)
   (fftw_codelet_r2cb_32 2 #x10bdd #x10bdd #x0 #x4e6e3714 #xebce55aa #x0ede5253 #x4faf4524)
   (fftw_codelet_n1bv_32_sse2 0 #x10bdd #x10bdd #x0 #x902cd310 #xa659999d #x6fde2637 #xb23e4fd2)
-  (fftw_dft_thr_vrank_geq1_register 0 #x10bdd #x10bdd #x0 #x21347a5d #x286e0d10 #xabf9ff02 #xccdf80a5)
+  (fftw_dft_vrank_geq1_register 0 #x10bdd #x10bdd #x0 #x4b54e3ca #x4f94ebf3 #x244f4da3 #x2412ca79)
 )

tests/test_likelihood.py

@@ -0,0 +1,157 @@
+import aquila_borg as borg
+import configparser
+import numpy as np
+import matplotlib.pyplot as plt
+
+import borg_velocity.likelihood as likelihood
+import borg_velocity.forwards as forwards
+import borg_velocity.utils as utils
+
+ini_file = '../conf/basic_ini.ini'
+test_scaling = False
+test_sigma8 = False
+test_omegam = False
+test_alpha = False
+test_muA = True
+
+# Input box
+box_in = borg.forward.BoxModel()
+config = configparser.ConfigParser()
+config.read(ini_file)
+box_in.L = (float(config['system']['L0']), float(config['system']['L1']), float(config['system']['L2']))
+box_in.N = (int(config['system']['N0']), int(config['system']['N1']), int(config['system']['N2']))
+box_in.xmin = (float(config['system']['corner0']), float(config['system']['corner1']), float(config['system']['corner2']))
+
+# Setup BORG forward model and likelihood
+model = likelihood.build_gravity_model(None, box_in, ini_file=ini_file)
+cosmo = utils.get_cosmopar(ini_file)
+model.setCosmoParams(cosmo)
+fwd_param = forwards.NullForward(box_in)
+mylike = likelihood.VelocityBORGLikelihood(model, fwd_param, ini_file)
+
+# Create mock data
+state = borg.likelihood.MarkovState()
+mylike.initializeLikelihood(state)
+mylike.updateCosmology(cosmo)
+s_hat = np.fft.rfftn(np.random.randn(*box_in.N)) / box_in.Ntot ** (0.5)
+mylike.generateMockData(s_hat, state)
+
+if test_scaling:
+    all_scale = np.linspace(0.5, 1.5, 100)
+    all_lkl = np.empty(all_scale.shape)
+    for i, scale in enumerate(all_scale):
+        all_lkl[i] = mylike.logLikelihoodComplex(scale * s_hat, None)
+    fid_lkl = mylike.logLikelihoodComplex(s_hat, None)
+    all_lkl -= fid_lkl
+    all_lkl = np.exp(-all_lkl)
+
+    fig, ax = plt.subplots(1, 1, figsize=(5,5))
+    ax.plot(all_scale, all_lkl)
+    ax.axhline(y=0, color='k')
+    ax.axvline(x=1, color='k')
+    ax.set_xlabel(r'$\hat{s}$ scaling')
+    ax.set_ylabel(r'$\mathcal{L}$')
+    fig.tight_layout()
+    fig.savefig('../figs/scaling_test.png')
+    fig.clf()
+    plt.close(fig)
+    
+# Test sigma8
+if test_sigma8:
+    all_sigma8 = np.linspace(0.5, 1.2, 40)
+    all_lkl = np.empty(all_sigma8.shape)
+    cosmo_true = mylike.fwd.getCosmoParams()
+    cosmo = mylike.fwd.getCosmoParams()
+    for i, sigma8 in enumerate(all_sigma8):
+        cosmo.sigma8 = sigma8
+        mylike.updateCosmology(cosmo)
+        all_lkl[i] = mylike.logLikelihoodComplex(s_hat, None)
+    mylike.updateCosmology(cosmo_true)
+    fid_lkl = mylike.logLikelihoodComplex(s_hat, None)
+    all_lkl -= fid_lkl
+    all_lkl = np.exp(-all_lkl)
+    
+    fig, ax = plt.subplots(1, 1, figsize=(5,5))
+    ax.plot(all_sigma8, all_lkl)
+    ax.axhline(y=0, color='k')
+    ax.axvline(x=cosmo_true.sigma8, color='k')
+    ax.set_xlabel(r'$\sigma_8$')
+    ax.set_ylabel(r'$\mathcal{L}$')
+    fig.tight_layout()
+    fig.savefig('../figs/sigma8_test.png')
+    fig.clf()
+    plt.close(fig)
+    
+    
+# Test sigma8
+if test_omegam:
+    all_omegam = np.linspace(0.1, 0.6, 40)
+    all_lkl = np.empty(all_omegam.shape)
+    cosmo_true = mylike.fwd.getCosmoParams()
+    cosmo = mylike.fwd.getCosmoParams()
+    for i, omegam in enumerate(all_omegam):
+        cosmo.omega_m = omegam
+        mylike.updateCosmology(cosmo)
+        all_lkl[i] = mylike.logLikelihoodComplex(s_hat, None)
+    mylike.updateCosmology(cosmo_true)
+    fid_lkl = mylike.logLikelihoodComplex(s_hat, None)
+    all_lkl -= fid_lkl
+    all_lkl = np.exp(-all_lkl)
+    
+    fig, ax = plt.subplots(1, 1, figsize=(5,5))
+    ax.plot(all_omegam, all_lkl)
+    ax.axhline(y=0, color='k')
+    ax.axvline(x=cosmo_true.omega_m, color='k')
+    ax.set_xlabel(r'$\Omega_{\rm m}$')
+    ax.set_ylabel(r'$\mathcal{L}$')
+    fig.tight_layout()
+    fig.savefig('../figs/omegam_test.png')
+    fig.clf()
+    plt.close(fig)
+    
+# Test bias model 
+if test_alpha:
+    all_alpha = np.linspace(-1.0, 5.0, 50)
+    all_lkl = np.empty(all_alpha.shape)
+    for i, alpha in enumerate(all_alpha):
+        mylike.fwd_param.setModelParams({'alpha0':alpha})
+        all_lkl[i] = mylike.logLikelihoodComplex(s_hat, None)
+    mylike.fwd_param.setModelParams({'alpha0':mylike.alpha[0]})
+    fid_lkl = mylike.logLikelihoodComplex(s_hat, None)
+    all_lkl -= fid_lkl
+    all_lkl = np.exp(-all_lkl)
+
+    fig, ax = plt.subplots(1, 1, figsize=(5,5))
+    ax.plot(all_alpha, all_lkl)
+    ax.axhline(y=0, color='k')
+    ax.axvline(x=mylike.alpha[0], color='k')
+    ax.set_xlabel(r'$\alpha_0$')
+    ax.set_ylabel(r'$\mathcal{L}$')
+    fig.tight_layout()
+    fig.savefig('../figs/alpha_test.png')
+    fig.clf()
+    plt.close(fig)
+    
+    
+# Test bias model 
+if test_muA:
+    all_muA = np.linspace(0.5, 1.5, 50)
+    all_lkl = np.empty(all_muA.shape)
+    for i, muA in enumerate(all_muA):
+        mylike.fwd_param.setModelParams({'muA0':muA})
+        all_lkl[i] = mylike.logLikelihoodComplex(s_hat, None)
+    mylike.fwd_param.setModelParams({'muA0':mylike.muA[0]})
+    fid_lkl = mylike.logLikelihoodComplex(s_hat, None)
+    all_lkl -= fid_lkl
+    all_lkl = np.exp(-all_lkl)
+
+    fig, ax = plt.subplots(1, 1, figsize=(5,5))
+    ax.plot(all_muA, all_lkl)
+    ax.axhline(y=0, color='k')
+    ax.axvline(x=mylike.muA[0], color='k')
+    ax.set_xlabel(r'$\mu_0$')
+    ax.set_ylabel(r'$\mathcal{L}$')
+    fig.tight_layout()
+    fig.savefig('../figs/muA_test.png')
+    fig.clf()
+    plt.close(fig)

tests/timing_stats_0.txt

@@ -4,4 +4,48 @@ Cumulative timing spent in different context
 --------------------------------------------
 Context,   Total time (seconds)
 
- [/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
+ [/build/jenkins/miniconda3/envs/builder/conda-bld/aquila_borg_1686906696789/work/libLSS/physics/chain_forward_model.cpp]virtual void LibLSS::ChainForwardModel::forwardModel_v2(LibLSS::detail_input::ModelInput<3>)	302	6.31245
+                          BORG LPT MODEL	302	5.82636
+                      BORG forward model	302	5.80025
+ [/build/jenkins/miniconda3/envs/builder/conda-bld/aquila_borg_1686906696789/work/libLSS/physics/forward_model.cpp]void LibLSS::ForwardModel::setCosmoParams(const LibLSS::CosmologicalParameters&)	29	1.56883
+ [/build/jenkins/miniconda3/envs/builder/conda-bld/aquila_borg_1686906696789/work/libLSS/physics/forwards/borg_lpt.cpp]void LibLSS::BorgLptModel<CIC>::updateCosmo() [with CIC = LibLSS::ClassicCloudInCell<double>]	5	0.710055
+                   lightcone computation	1	0.69232
+ [/build/jenkins/miniconda3/envs/builder/conda-bld/aquila_borg_1686906696789/work/libLSS/physics/cosmo.cpp]void LibLSS::Cosmology::precompute_d_plus()	1	0.603931
+                                  lpt_ic	302	0.392354
+ [/build/jenkins/miniconda3/envs/builder/conda-bld/aquila_borg_1686906696789/work/libLSS/physics/forwards/lpt/borg_fwd_lpt.cpp]void LibLSS::BorgLptModel<CIC>::getDensityFinal(LibLSS::detail_output::ModelOutput<3>) [with CIC = LibLSS::ClassicCloudInCell<double>]	302	0.321819
+                  Classic CIC projection	302	0.256846
+               FFTW_Manager::execute_c2r	906	0.122506
+ [/build/jenkins/miniconda3/envs/builder/conda-bld/aquila_borg_1686906696789/work/libLSS/physics/forwards/transfer_class.cpp]virtual void LibLSS::ForwardClass::updateCosmo()	5	0.0733008
+ [/build/jenkins/miniconda3/envs/builder/conda-bld/aquila_borg_1686906696789/work/libLSS/physics/class_cosmo.cpp]LibLSS::ClassCosmo::ClassCosmo(const LibLSS::CosmologicalParameters&, unsigned int, double, std::string, unsigned int, const std::map<std::__cxx11::basic_string<char>, std::__cxx11::basic_string<char> >&)	1	0.0726085
+ [/build/jenkins/miniconda3/envs/builder/conda-bld/aquila_borg_1686906696789/work/libLSS/physics/cosmo.cpp]void LibLSS::Cosmology::precompute_com2a()	1	0.0703289
+ [/build/jenkins/miniconda3/envs/builder/conda-bld/aquila_borg_1686906696789/work/python/pyforward.cpp]void do_get_density_final(LibLSS::BORGForwardModel*, pybind11::array)	302	0.0631881
+ [/build/jenkins/miniconda3/envs/builder/conda-bld/aquila_borg_1686906696789/work/python/pyforward.cpp]void transfer_in(std::shared_ptr<LibLSS::FFTW_Manager<double, 3> >&, T&, U&, bool) [with T = boost::multi_array_ref<std::complex<double>, 3>; U = pybind11::detail::unchecked_reference<std::complex<double>, 3>]	302	0.0370347
+ [/build/jenkins/miniconda3/envs/builder/conda-bld/aquila_borg_1686906696789/work/libLSS/physics/model_io.cpp]LibLSS::detail_output::ModelOutputBase<Nd, Super>::~ModelOutputBase() [with long unsigned int Nd = 3; Super = LibLSS::detail_model::ModelIO<3>]	3322	0.0272583
+ [/build/jenkins/miniconda3/envs/builder/conda-bld/aquila_borg_1686906696789/work/libLSS/physics/chain_forward_model.cpp]virtual void LibLSS::ChainForwardModel::getDensityFinal(LibLSS::detail_output::ModelOutput<3>)	302	0.0215866
+ [/build/jenkins/miniconda3/envs/builder/conda-bld/aquila_borg_1686906696789/work/libLSS/physics/model_io.cpp]void LibLSS::detail_output::ModelOutputBase<Nd, Super>::transfer(LibLSS::detail_output::ModelOutputBase<Nd, Super>&&) [with long unsigned int Nd = 3; Super = LibLSS::detail_model::ModelIO<3>]	2718	0.0201743
+ [/build/jenkins/miniconda3/envs/builder/conda-bld/aquila_borg_1686906696789/work/libLSS/physics/forwards/particle_balancer/balanceinfo.hpp]void LibLSS::BalanceInfo::allocate(LibLSS::MPI_Communication*, size_t)	302	0.0151142
+ [/build/jenkins/miniconda3/envs/builder/conda-bld/aquila_borg_1686906696789/work/libLSS/physics/model_io/base.hpp]void LibLSS::detail_model::ModelIO<Nd>::transfer(LibLSS::detail_model::ModelIO<Nd>&&) [with long unsigned int Nd = 3]	6946	0.00685386
+ [/build/jenkins/miniconda3/envs/builder/conda-bld/aquila_borg_1686906696789/work/libLSS/physics/forwards/primordial_as.cpp]virtual void LibLSS::ForwardPrimordial_As::forwardModel_v2(LibLSS::detail_input::ModelInput<3>)	302	0.00566568
+ [/build/jenkins/miniconda3/envs/builder/conda-bld/aquila_borg_1686906696789/work/libLSS/physics/forwards/borg_lpt.cpp]std::shared_ptr<LibLSS::BORGForwardModel> build_borg_lpt(std::shared_ptr<LibLSS::MPI_Communication>, const LibLSS::BoxModel&, const LibLSS::PropertyProxy&) [with Grid = LibLSS::ClassicCloudInCell<double>; LibLSS::BoxModel = LibLSS::NBoxModel<3>]	1	0.00491132
+              BorgLptModel::BorgLptModel	1	0.00483932
+           FFTW_Manager::create_r2c_plan	3	0.00401923
+ [/build/jenkins/miniconda3/envs/builder/conda-bld/aquila_borg_1686906696789/work/libLSS/physics/forwards/transfer_class.cpp]virtual void LibLSS::ForwardClass::forwardModel_v2(LibLSS::detail_input::ModelInput<3>)	302	0.00395206
+ [/build/jenkins/miniconda3/envs/builder/conda-bld/aquila_borg_1686906696789/work/libLSS/physics/forwards/adapt_generic_bias.cpp]void {anonymous}::bias_registrator()	1	0.00265152
+ [/build/jenkins/miniconda3/envs/builder/conda-bld/aquila_borg_1686906696789/work/libLSS/physics/model_io.cpp]void LibLSS::detail_output::ModelOutputBase<Nd, Super>::close() [with long unsigned int Nd = 3; Super = LibLSS::detail_model::ModelIO<3>]	3322	0.00252739
+ [/build/jenkins/miniconda3/envs/builder/conda-bld/aquila_borg_1686906696789/work/libLSS/physics/forward_model.cpp]void LibLSS::BORGForwardModel::setupDefault()	1	0.00234709
+           FFTW_Manager::create_c2r_plan	2	0.00231646
+ [/build/jenkins/miniconda3/envs/builder/conda-bld/aquila_borg_1686906696789/work/libLSS/physics/forwards/transfer_class.cpp]std::shared_ptr<LibLSS::BORGForwardModel> build_class(std::shared_ptr<LibLSS::MPI_Communication>, const LibLSS::BoxModel&, const LibLSS::PropertyProxy&)	1	0.00229587
+ [/build/jenkins/miniconda3/envs/builder/conda-bld/aquila_borg_1686906696789/work/libLSS/physics/forwards/primordial_as.cpp]std::shared_ptr<LibLSS::BORGForwardModel> build_primordial_as(std::shared_ptr<LibLSS::MPI_Communication>, const LibLSS::BoxModel&, const LibLSS::PropertyProxy&)	1	0.00227005
+ [/build/jenkins/miniconda3/envs/builder/conda-bld/aquila_borg_1686906696789/work/libLSS/samplers/core/gridLikelihoodBase.cpp]LibLSS::GridDensityLikelihoodBase<Dims>::GridDensityLikelihoodBase(LibLSS::MPI_Communication*, const GridSizes&, const GridLengths&) [with int Dims = 3; GridSizes = std::array<long unsigned int, 3>; GridLengths = std::array<double, 3>]	1	0.00177235
+ [/build/jenkins/miniconda3/envs/builder/conda-bld/aquila_borg_1686906696789/work/libLSS/physics/class_cosmo.cpp]void LibLSS::ClassCosmo::retrieve_Tk(double)	2	0.00115242
+ [/build/jenkins/miniconda3/envs/builder/conda-bld/aquila_borg_1686906696789/work/libLSS/physics/model_io.cpp]void LibLSS::detail_output::ModelOutputBase<Nd, Super>::setRequestedIO(LibLSS::PreferredIO) [with long unsigned int Nd = 3; Super = LibLSS::detail_model::ModelIO<3>]	1208	0.00107811
+ [/build/jenkins/miniconda3/envs/builder/conda-bld/aquila_borg_1686906696789/work/libLSS/physics/class_cosmo.cpp]void LibLSS::ClassCosmo::reinterpolate(const array_ref_1d&, const array_ref_1d&, LibLSS::internal_auto_interp::auto_interpolator<double>&)	6	0.00102937
+ [/build/jenkins/miniconda3/envs/builder/conda-bld/aquila_borg_1686906696789/work/libLSS/physics/forwards/primordial_as.cpp]virtual void LibLSS::ForwardPrimordial_As::updateCosmo()	10	0.0010009
+ [/build/jenkins/miniconda3/envs/builder/conda-bld/aquila_borg_1686906696789/work/libLSS/physics/model_io.cpp]void LibLSS::detail_input::ModelInputBase<Nd, Super>::setRequestedIO(LibLSS::PreferredIO) [with long unsigned int Nd = 3; Super = LibLSS::detail_model::ModelIO<3>]	906	0.000742612
+ [/build/jenkins/miniconda3/envs/builder/conda-bld/aquila_borg_1686906696789/work/libLSS/physics/forwards/primordial_as.cpp]void LibLSS::ForwardPrimordial_As::updatePower()	5	0.000559304
+ [/build/jenkins/miniconda3/envs/builder/conda-bld/aquila_borg_1686906696789/work/libLSS/physics/model_io.cpp]void LibLSS::detail_input::ModelInputBase<Nd, Super>::needDestroyInput() [with long unsigned int Nd = 3; Super = LibLSS::detail_model::ModelIO<3>]	302	0.000316937
+                   particle distribution	302	0.000287307
+                 BORGForwardModel::setup	7	0.000122816
+                Initializing peer system	12	4.3684e-05
+ [/build/jenkins/miniconda3/envs/builder/conda-bld/aquila_borg_1686906696789/work/libLSS/physics/forwards/transfer_class.cpp]virtual void LibLSS::ForwardClass::setModelParams(const LibLSS::ModelDictionnary&)	1	1.2359e-05
+ [/build/jenkins/miniconda3/envs/builder/conda-bld/aquila_borg_1686906696789/work/libLSS/physics/forward_model.cpp]virtual void LibLSS::ForwardModel::setModelParams(const LibLSS::ModelDictionnary&)	1	2.473e-06