Index

A

add_title() (nnero.analysis.AxesGrid method)

AxesGrid (class in nnero.analysis)

B

bestfit (nnero.analysis.ProcessedData attribute)

C

centers (nnero.analysis.ProcessedData attribute) check_ik_R() (in module nnero.cosmology) check_values() (in module nnero.predictor) Classifier (class in nnero.classifier) compatible_with() (nnero.analysis.GaussianInfo method) compute_parameter() (in module nnero.analysis) compute_quantiles() (in module nnero.analysis)

compute_stats() (nnero.analysis.MPChain method) compute_tau() (in module nnero.analysis) convergence() (nnero.analysis.EMCEESamples method) (nnero.analysis.MPSamples method) convert_array() (in module nnero.cosmology) cov (nnero.analysis.GaussianInfo attribute) covmat() (nnero.analysis.MPSamples method)

D

DataPartition (class in nnero.data) DataSet (class in nnero.data) dmhalo_dmuv() (in module nnero.astrophysics)

dn_dm() (in module nnero.cosmology) dsigma_m_dm() (in module nnero.cosmology) dsigma_r_dr() (in module nnero.cosmology)

E

edges (nnero.analysis.ProcessedData attribute)

EMCEESamples (class in nnero.analysis)

F

f_duty() (in module nnero.astrophysics) flat() (nnero.analysis.EMCEESamples method) (nnero.analysis.GaussianSamples method) (nnero.analysis.MPSamples method) (nnero.analysis.Samples method)

forward() (nnero.classifier.Classifier method) (nnero.regressor.Regressor method)

G

GaussianInfo (class in nnero.analysis) GaussianSamples (class in nnero.analysis) generate_contours() (in module nnero.analysis) get() (nnero.analysis.AxesGrid method) get_k_max() (nnero.mcmc.UVLFLikelihood method)

get_x() (nnero.mcmc.Likelihood method) get_x_dict() (nnero.mcmc.Likelihood method) get_x_dicts() (nnero.mcmc.Likelihood method) get_Xe_stats() (in module nnero.analysis) get_Xe_tanh_stats() (in module nnero.analysis) growth_function() (in module nnero.cosmology)

H

h_factor_no_rad() (in module nnero.cosmology) h_factor_numpy() (in module nnero.cosmology)

hists_1D (nnero.analysis.ProcessedData attribute) hists_2D (nnero.analysis.ProcessedData attribute)

I

index_1D() (nnero.analysis.AxesGrid method) index_from_name() (nnero.analysis.AxesGrid method) indices_2D() (nnero.analysis.AxesGrid method)

info() (nnero.network.NeuralNetwork method) init_principal_components() (nnero.data.DataSet method) initialise_walkers() (in module nnero.mcmc) input_values() (in module nnero.predictor)

L

latex_labels() (in module nnero.data) levels (nnero.analysis.ProcessedData attribute) Likelihood (class in nnero.mcmc) load() (nnero.analysis.MPChain method) (nnero.classifier.Classifier class method) (nnero.data.DataPartition class method) (nnero.data.MetaData class method) (nnero.regressor.Regressor class method) load_chains() (nnero.analysis.EMCEESamples method) (nnero.analysis.MPSamples method)

load_data() (nnero.analysis.GaussianSamples method) load_paramnames() (nnero.analysis.MPSamples method) load_scaling_factor() (nnero.analysis.MPSamples method) load_weights_and_extras() (nnero.network.NeuralNetwork method) log_likelihood() (in module nnero.mcmc) log_prior() (in module nnero.mcmc) log_probability() (in module nnero.mcmc) loglkl() (nnero.mcmc.Likelihood method) loss_tau() (nnero.regressor.Regressor method) loss_xHII() (nnero.regressor.Regressor method)

M

m_halo() (in module nnero.astrophysics) mean (nnero.analysis.GaussianInfo attribute) (nnero.analysis.ProcessedData attribute) median (nnero.analysis.ProcessedData attribute) message (nnero.cosmology.ShortPowerSpectrumRange attribute) MetaData (class in nnero.data) metadata (nnero.network.NeuralNetwork attribute) module nnero.analysis nnero.astrophysics nnero.classifier nnero.constants nnero.cosmology nnero.data nnero.mcmc nnero.network nnero.predictor nnero.regressor

MPChain (class in nnero.analysis) MPSamples (class in nnero.analysis)

N

n_baryons() (in module nnero.cosmology) n_hydrogen() (in module nnero.cosmology) n_ur() (in module nnero.cosmology) name (nnero.network.NeuralNetwork attribute) NeuralNetwork (class in nnero.network) neutrino_masses() (in module nnero.analysis) nnero.analysis module nnero.astrophysics module nnero.classifier module nnero.constants module

nnero.cosmology module nnero.data module nnero.mcmc module nnero.network module nnero.predictor module nnero.regressor module

O

omega_nu() (in module nnero.cosmology) omega_r() (in module nnero.cosmology)

optical_depth_no_rad() (in module nnero.cosmology) OpticalDepthLikelihood (class in nnero.mcmc)

P

param_names (nnero.analysis.GaussianInfo attribute) partition (nnero.network.NeuralNetwork attribute) phi_uv() (in module nnero.astrophysics) plot_2D_marginal() (in module nnero.analysis) plot_data() (in module nnero.analysis) predict_classifier() (in module nnero.predictor) predict_classifier_numpy() (in module nnero.predictor) predict_interpolator() (in module nnero.predictor) predict_interpolator_numpy() (in module nnero.predictor) predict_parameter() (in module nnero.predictor) predict_parameter_numpy() (in module nnero.predictor) predict_regressor() (in module nnero.predictor) predict_regressor_numpy() (in module nnero.predictor) predict_tau() (in module nnero.predictor)

predict_tau_from_Xe() (in module nnero.predictor) predict_tau_from_Xe_numpy() (in module nnero.predictor) predict_tau_from_xHII() (in module nnero.predictor) predict_tau_from_xHII_numpy() (in module nnero.predictor) predict_tau_numpy() (in module nnero.predictor) predict_Xe() (in module nnero.predictor) predict_Xe_numpy() (in module nnero.predictor) predict_xHII() (in module nnero.predictor) predict_xHII_numpy() (in module nnero.predictor) prepare_data_plot() (in module nnero.analysis) prepare_data_Xe() (in module nnero.analysis) preprocess_raw_data() (in module nnero.data) print_best_fit() (nnero.analysis.MPSamples method) print_structure() (nnero.network.NeuralNetwork method) ProcessedData (class in nnero.analysis)

Q

q (nnero.analysis.ProcessedData attribute)

quantiles (nnero.analysis.ProcessedData attribute)

R

Regressor (class in nnero.regressor) ReionizationLikelihood (class in nnero.mcmc)

remove_burnin() (nnero.analysis.MPChain method) rho_baryons() (in module nnero.cosmology)

S

Samples (class in nnero.analysis) samples (nnero.analysis.ProcessedData attribute) save() (nnero.data.DataPartition method) (nnero.data.MetaData method) (nnero.network.NeuralNetwork method) save_sampling_parameters() (in module nnero.analysis)

set_check_metadata_and_partition() (nnero.network.NeuralNetwork method) set_label() (nnero.analysis.AxesGrid method) ShortPowerSpectrumRange show() (nnero.analysis.AxesGrid method) sigma_m() (in module nnero.cosmology) sigma_r() (in module nnero.cosmology) size (nnero.analysis.ProcessedData attribute)

T

tau_ion() (nnero.regressor.Regressor method) test() (nnero.classifier.Classifier method) test_tau() (nnero.regressor.Regressor method) test_xHII() (nnero.regressor.Regressor method) to_21cmFAST_names() (in module nnero.analysis) to_CLASS_names() (in module nnero.analysis)

TorchDataset (class in nnero.data) train_accuracy (nnero.network.NeuralNetwork attribute) train_classifier() (in module nnero.classifier) train_loss (nnero.network.NeuralNetwork attribute) train_regressor() (in module nnero.regressor) true_to_uniform() (in module nnero.data)

U

uniform_input_array() (in module nnero.predictor) uniform_input_values() (in module nnero.predictor) uniform_to_true() (in module nnero.data)

update_edges() (nnero.analysis.AxesGrid method) update_labels() (nnero.analysis.AxesGrid method) update_titles() (nnero.analysis.AxesGrid method) UVLFLikelihood (class in nnero.mcmc)

V

valid_accuracy (nnero.network.NeuralNetwork attribute) valid_loss (nnero.network.NeuralNetwork attribute)

validate() (nnero.classifier.Classifier method) values() (nnero.analysis.MPChain method)