Index

_

__call__() (EarlyStopping method) __getitem__() (PhotometryDataset method) (RandomDataset method), [1] __len__() (PhotometryDataset method) (RandomDataset method), [1]

_flatten() (in module calpit.nn.umnn.MonotonicNN) (in module calpit.nn.umnn.NeuralIntegral) (in module calpit.nn.umnn.ParallelNeuralIntegral) _normalize() (in module calpit.utils)

A

all_layers (IsplineNN attribute), [1] (MLP attribute)

anderson_darling_statistic() (in module calpit.metrics)

B

backward() (NeuralIntegral static method), [1] (ParallelNeuralIntegral static method), [1]

basis_vectors (ISplineLayer attribute) best_score (EarlyStopping attribute)

C

calpit module CalPit (class in calpit) (class in calpit.diagnostics_and_calibration) calpit.datasets module calpit.diagnostics_and_calibration module calpit.example_benchmarks module calpit.metrics module calpit.nn module calpit.nn.ispline_nn module calpit.nn.models module calpit.nn.umnn module

calpit.nn.umnn.MonotonicNN module calpit.nn.umnn.NeuralIntegral module calpit.nn.umnn.ParallelNeuralIntegral module calpit.nn.utils module calpit.utils module cde_loss() (in module calpit.metrics) (in module calpit.nn.utils) clipped_relu() (in module calpit.nn.umnn.MonotonicNN) coefs (ISplineLayer attribute) compute_cc_weights() (in module calpit.nn.umnn.NeuralIntegral) (in module calpit.nn.umnn.ParallelNeuralIntegral) computeIntegrand() (in module calpit.nn.umnn.NeuralIntegral) (in module calpit.nn.umnn.ParallelNeuralIntegral) count_parameters() (in module calpit.nn.utils) counter (EarlyStopping attribute) cramer_von_mises_statistic() (in module calpit.metrics)

D

delta (EarlyStopping attribute) device (CalPit attribute), [1]

dims (TuningFork attribute) dropout_p (IsplineNN attribute), [1]

E

early_stop (EarlyStopping attribute)

EarlyStopping (class in calpit.nn.utils)

F

fit() (CalPit method), [1] fit_transform() (CalPit method), [1] forward() (IntegrandNN method), [1] (ISplineLayer method) (IsplineNN method), [1] (MLP method), [1] (MonotonicNN method), [1] (NeuralIntegral static method), [1] (ParallelNeuralIntegral static method), [1]

G

generate_data() (TuningFork method)

grid (ISplineLayer attribute)

H

hidden_layers (IsplineNN attribute), [1]

I

in_features (ISplineLayer attribute) integrand (MonotonicNN attribute), [1] IntegrandNN (class in calpit.nn.umnn) (class in calpit.nn.umnn.MonotonicNN) integrate() (in module calpit.nn.umnn.NeuralIntegral) (in module calpit.nn.umnn.ParallelNeuralIntegral)

interp1d() (ISplineLayer method) ISplineLayer (class in calpit.nn.ispline_nn) IsplineNN (class in calpit.nn) (class in calpit.nn.ispline_nn)

K

kolmogorov_smirnov_statistic() (in module calpit.metrics)

L

lam (TuningFork attribute) layer_list (MLP attribute)

layers (MLP attribute) len_x (RandomDataset attribute), [1]

M

memory_computation() (in module calpit.example_benchmarks) MLP (class in calpit.nn.models) mlp_layer_list (IsplineNN attribute), [1] mlp_layers (IsplineNN attribute), [1] model (CalPit attribute), [1] module calpit calpit.datasets calpit.diagnostics_and_calibration calpit.example_benchmarks calpit.metrics calpit.nn calpit.nn.ispline_nn calpit.nn.models calpit.nn.umnn calpit.nn.umnn.MonotonicNN calpit.nn.umnn.NeuralIntegral calpit.nn.umnn.ParallelNeuralIntegral calpit.nn.utils calpit.utils

MonotonicNN (class in calpit.nn.umnn) (class in calpit.nn.umnn.MonotonicNN)

N

nb_steps (MonotonicNN attribute), [1] net (IntegrandNN attribute), [1] (MonotonicNN attribute), [1] NeuralIntegral (class in calpit.nn.umnn) (class in calpit.nn.umnn.NeuralIntegral)

normalize() (in module calpit.utils) num_basis (ISplineLayer attribute) (IsplineNN attribute), [1]

O

oversample (RandomDataset attribute), [1]

P

ParallelNeuralIntegral (class in calpit.nn.umnn) (class in calpit.nn.umnn.ParallelNeuralIntegral) path (EarlyStopping attribute) patience (EarlyStopping attribute)

PhotometryDataset (class in calpit.datasets) pit (PhotometryDataset attribute) plot_pit() (in module calpit.utils) predict() (CalPit method), [1] probability_integral_transform() (in module calpit.metrics)

R

RandomDataset (class in calpit.datasets) (class in calpit.nn.utils)

runtime_computation() (in module calpit.example_benchmarks)

S

save_checkpoint() (EarlyStopping method) scaler (PhotometryDataset attribute)

seed (TuningFork attribute) sigmoid (MonotonicNN attribute), [1] spline_layer (IsplineNN attribute), [1]

T

trace_func (EarlyStopping attribute) training_loss (CalPit attribute), [1] transform() (CalPit method), [1]

trapz_grid() (in module calpit.utils) trapz_grid_torch() (in module calpit.utils) TuningFork (class in calpit.datasets)

V

val_loss_min (CalPit attribute), [1] (EarlyStopping attribute)

validation_bce (CalPit attribute), [1] verbose (EarlyStopping attribute)

X

x_data (RandomDataset attribute), [1]

Y

y_data (RandomDataset attribute), [1]