latest
Datasets
Galaxy10 DECals Dataset
Galaxy10 SDSS Dataset
Basics of astroNN
Getting Started
Contributor and Issue Reporting guide
History
Publications using astroNN
Loss Functions and Metrics
Layers
Callbacks and Utilities
NeuralODE
Neural Nets Classes and Basic Usage
NN Introduction and Demo
Bayesian Neural Net with Dropout Variational Inference
Gaia DR2 with astroNN result
APOGEE/Gaia/LAMOST Tools and models
Mini Tools for APOGEE data
Mini Tools for LAMOST data
Mini Tools for Gaia data
APOGEE Spectra with Convolutional Neural Net -
ApogeeCNN
APOGEE Spectra with Bayesian Neural Net -
ApogeeBCNN
APOGEE Spectra with Censored Bayesian NN -
ApogeeBCNNCensored
APOGEE Spectra with Bayesian NN and Gaia offset calibration -
ApogeeDR14GaiaDR2BCNN
Convolutional Variational Autoencoder -
ApogeeCVAE
Encoder-decoder for APOGEE and Kepler -
ApokascEncoderDecoder
StarNet (arXiv:1709.09182)
Cifar10 with astroNN
astroNN
Index
Edit on GitHub
Index
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A
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B
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C
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E
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F
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G
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H
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I
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J
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K
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L
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M
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N
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O
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P
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R
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S
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T
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U
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V
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W
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X
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Z
_
__call__() (astroNN.nn.layers.FastMCInference method)
A
absmag_to_fakemag() (in module astroNN.gaia)
absmag_to_logsol() (in module astroNN.gaia)
absmag_to_pc() (in module astroNN.gaia)
allstar() (in module astroNN.apogee)
allstar_cannon() (in module astroNN.apogee)
allvisit() (in module astroNN.apogee)
apogee_astronn() (in module astroNN.apogee.downloader)
apogee_continuum() (in module astroNN.apogee)
apogee_distances() (in module astroNN.apogee)
ApogeeBCNN (class in astroNN.models.apogee_models)
ApogeeBCNNCensored (class in astroNN.models.apogee_models)
ApogeeCNN (class in astroNN.models.apogee_models)
ApogeeCVAE (class in astroNN.models.apogee_models)
ApogeeDR14GaiaDR2BCNN (class in astroNN.models.apogee_models)
ApokascEncoderDecoder (class in astroNN.models.apogee_models)
aspcap_mask() (in module astroNN.apogee)
astroNN.apogee
module
astroNN.apogee.chips
module
astroNN.apogee.downloader
module
astroNN.config
module
astroNN.datasets.galaxy10
module
astroNN.datasets.galaxy10sdss
module
astroNN.gaia
module
astroNN.gaia.downloader
module
astroNN.lamost
module
astroNN.models
module
astroNN.models.apogee_models
module
,
[1]
,
[2]
,
[3]
,
[4]
,
[5]
,
[6]
astroNN.neuralode
module
astroNN.neuralode.odeint
module
astroNN.nn
module
,
[1]
astroNN.nn.callbacks
module
astroNN.nn.layers
module
astroNN.nn.losses
module
astroNN.nn.metrics
module
astroNN.nn.numpy
module
astroNN.nn.utilities
module
astroNN.nn.utilities.normalizer
module
B
bayesian_binary_crossentropy_var_wrapper() (in module astroNN.nn.losses)
bayesian_binary_crossentropy_wrapper() (in module astroNN.nn.losses)
bayesian_categorical_crossentropy_var_wrapper() (in module astroNN.nn.losses)
bayesian_categorical_crossentropy_wrapper() (in module astroNN.nn.losses)
BayesianCNNBase (class in astroNN.models.base_bayesian_cnn)
binary_accuracy() (in module astroNN.nn.losses)
binary_crossentropy() (in module astroNN.nn.losses)
bitmask_boolean() (in module astroNN.apogee)
bitmask_decompositor() (in module astroNN.apogee)
BoolMask (class in astroNN.nn.layers)
C
call() (astroNN.nn.layers.BoolMask method)
(astroNN.nn.layers.ErrorProp method)
(astroNN.nn.layers.FastMCInferenceMeanVar method)
(astroNN.nn.layers.FastMCRepeat method)
(astroNN.nn.layers.KLDivergenceLayer method)
(astroNN.nn.layers.MCBatchNorm method)
(astroNN.nn.layers.MCConcreteDropout method)
(astroNN.nn.layers.MCDropout method)
(astroNN.nn.layers.MCGaussianDropout method)
(astroNN.nn.layers.MCSpatialDropout1D method)
(astroNN.nn.layers.MCSpatialDropout2D method)
(astroNN.nn.layers.PolyFit method)
(astroNN.nn.layers.StopGrad method)
(astroNN.nn.layers.TensorInput method)
categorical_accuracy() (in module astroNN.nn.losses)
categorical_crossentropy() (in module astroNN.nn.losses)
chips_pix_info() (in module astroNN.apogee)
chips_split() (in module astroNN.apogee)
CNNBase (class in astroNN.models.base_cnn)
combined_spectra() (in module astroNN.apogee)
ConvVAEBase (class in astroNN.models.base_vae)
custom_train_step() (astroNN.models.base_bayesian_cnn.BayesianCNNBase method)
(astroNN.models.base_vae.ConvVAEBase method)
E
ErrorOnNaN (class in astroNN.nn.callbacks)
ErrorProp (class in astroNN.nn.layers)
evaluate() (astroNN.models.base_bayesian_cnn.BayesianCNNBase method)
(astroNN.models.base_cnn.CNNBase method)
(astroNN.models.base_vae.ConvVAEBase method)
extinction_correction() (in module astroNN.gaia)
F
fakemag_to_absmag() (in module astroNN.gaia)
fakemag_to_logsol() (in module astroNN.gaia)
fakemag_to_mag() (in module astroNN.gaia)
fakemag_to_parallax() (in module astroNN.gaia)
fakemag_to_pc() (in module astroNN.gaia)
FastMCInference (class in astroNN.nn.layers)
FastMCInferenceMeanVar (class in astroNN.nn.layers)
FastMCRepeat (class in astroNN.nn.layers)
fit() (astroNN.models.base_bayesian_cnn.BayesianCNNBase method)
(astroNN.models.base_cnn.CNNBase method)
(astroNN.models.base_vae.ConvVAEBase method)
fit_on_batch() (astroNN.models.base_bayesian_cnn.BayesianCNNBase method)
(astroNN.models.base_cnn.CNNBase method)
(astroNN.models.base_vae.ConvVAEBase method)
flush() (astroNN.models.base_master_nn.NeuralNetMaster method)
G
gaiadr2_parallax() (in module astroNN.gaia)
gap_delete() (in module astroNN.apogee)
get_config() (astroNN.models.base_master_nn.NeuralNetMaster method)
(astroNN.nn.layers.BoolMask method)
(astroNN.nn.layers.ErrorProp method)
(astroNN.nn.layers.FastMCInference method)
(astroNN.nn.layers.FastMCInferenceMeanVar method)
(astroNN.nn.layers.FastMCRepeat method)
(astroNN.nn.layers.KLDivergenceLayer method)
(astroNN.nn.layers.MCBatchNorm method)
(astroNN.nn.layers.MCConcreteDropout method)
(astroNN.nn.layers.MCDropout method)
(astroNN.nn.layers.MCGaussianDropout method)
(astroNN.nn.layers.MCSpatialDropout1D method)
(astroNN.nn.layers.MCSpatialDropout2D method)
(astroNN.nn.layers.PolyFit method)
(astroNN.nn.layers.StopGrad method)
(astroNN.nn.layers.TensorInput method)
get_layer() (astroNN.models.base_master_nn.NeuralNetMaster method)
get_weights() (astroNN.models.base_master_nn.NeuralNetMaster method)
H
has_model (astroNN.models.base_master_nn.NeuralNetMaster property)
hessian() (astroNN.models.base_master_nn.NeuralNetMaster method)
I
input_shape (astroNN.models.base_master_nn.NeuralNetMaster property)
intpow_avx2() (in module astroNN.nn)
J
jacobian() (astroNN.models.base_master_nn.NeuralNetMaster method)
jacobian_latent() (astroNN.models.base_vae.ConvVAEBase method)
K
kl_divergence() (in module astroNN.nn.numpy)
KLDivergenceLayer (class in astroNN.nn.layers)
L
l1() (in module astroNN.nn.numpy)
l2() (in module astroNN.nn.numpy)
load_allstar_dr5() (in module astroNN.lamost)
load_apogee_distances() (in module astroNN.datasets)
load_apogee_rc() (in module astroNN.datasets.apogee)
load_folder() (in module astroNN.models)
logsol_to_absmag() (in module astroNN.gaia)
logsol_to_fakemag() (in module astroNN.gaia)
M
mag_to_absmag() (in module astroNN.gaia)
mag_to_fakemag() (in module astroNN.gaia)
magic_correction_term() (in module astroNN.nn.losses)
MCBatchNorm (class in astroNN.nn.layers)
MCConcreteDropout (class in astroNN.nn.layers)
MCDropout (class in astroNN.nn.layers)
MCGaussianDropout (class in astroNN.nn.layers)
MCSpatialDropout1D (class in astroNN.nn.layers)
MCSpatialDropout2D (class in astroNN.nn.layers)
mean_absolute_error() (in module astroNN.nn.losses)
(in module astroNN.nn.numpy)
mean_absolute_percentage_error() (in module astroNN.nn.losses)
(in module astroNN.nn.numpy)
mean_error() (in module astroNN.nn.losses)
mean_percentage_error() (in module astroNN.nn.losses)
mean_squared_error() (in module astroNN.nn.losses)
mean_squared_logarithmic_error() (in module astroNN.nn.losses)
median_absolute_error() (in module astroNN.nn.numpy)
median_absolute_percentage_error() (in module astroNN.nn.numpy)
module
astroNN.apogee
astroNN.apogee.chips
astroNN.apogee.downloader
astroNN.config
astroNN.datasets.galaxy10
astroNN.datasets.galaxy10sdss
astroNN.gaia
astroNN.gaia.downloader
astroNN.lamost
astroNN.models
astroNN.models.apogee_models
,
[1]
,
[2]
,
[3]
,
[4]
,
[5]
,
[6]
astroNN.neuralode
astroNN.neuralode.odeint
astroNN.nn
,
[1]
astroNN.nn.callbacks
astroNN.nn.layers
astroNN.nn.losses
astroNN.nn.metrics
astroNN.nn.numpy
astroNN.nn.utilities
astroNN.nn.utilities.normalizer
mse_lin_wrapper() (in module astroNN.nn.losses)
mse_var_wrapper() (in module astroNN.nn.losses)
N
NeuralNetMaster (class in astroNN.models.base_master_nn)
O
odeint() (in module astroNN.neuralode.odeint)
output_shape (astroNN.models.base_master_nn.NeuralNetMaster property)
P
plot_dense_stats() (astroNN.models.base_master_nn.NeuralNetMaster method)
plot_model() (astroNN.models.base_master_nn.NeuralNetMaster method)
PolyFit (class in astroNN.nn.layers)
predict() (astroNN.models.base_bayesian_cnn.BayesianCNNBase method)
(astroNN.models.base_cnn.CNNBase method)
(astroNN.models.base_vae.ConvVAEBase method)
predict_decoder() (astroNN.models.base_vae.ConvVAEBase method)
predict_encoder() (astroNN.models.base_vae.ConvVAEBase method)
pseudo_continuum() (in module astroNN.lamost)
pylab_style() (in module astroNN.shared.matplotlib)
R
recompile() (astroNN.models.base_bayesian_cnn.BayesianCNNBase method)
(astroNN.models.base_cnn.CNNBase method)
(astroNN.models.base_vae.ConvVAEBase method)
reduce_var() (in module astroNN.nn)
relu() (in module astroNN.nn.numpy)
robust_binary_crossentropy() (in module astroNN.nn.losses)
robust_categorical_crossentropy() (in module astroNN.nn.losses)
robust_mse() (in module astroNN.nn.losses)
S
save() (astroNN.models.base_master_nn.NeuralNetMaster method)
save_weights() (astroNN.models.base_master_nn.NeuralNetMaster method)
savefile() (astroNN.nn.callbacks.VirutalCSVLogger method)
sigmoid() (in module astroNN.nn.numpy)
sigmoid_inv() (in module astroNN.nn.numpy)
StarNet2017 (class in astroNN.models.apogee_models)
StopGrad (class in astroNN.nn.layers)
summary() (astroNN.models.base_master_nn.NeuralNetMaster method)
T
TensorInput (class in astroNN.nn.layers)
tgas() (in module astroNN.gaia)
tgas_load() (in module astroNN.gaia)
transfer_weights() (astroNN.models.base_master_nn.NeuralNetMaster method)
U
uses_learning_phase (astroNN.models.base_master_nn.NeuralNetMaster property)
V
VirutalCSVLogger (class in astroNN.nn.callbacks)
visit_spectra() (in module astroNN.apogee)
W
wavelength_solution() (in module astroNN.apogee)
(in module astroNN.lamost)
X
xmatch() (in module astroNN.datasets.xmatch)
Z
zeros_loss() (in module astroNN.nn.losses)
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