AstroVAE

Data reduction, emulation and inference using a combination of GP processes and Variational autoencoder. Currently applied for CMB angular power spectra C_l and matter power spectra P(k). In principle, this can be extended to image emulations as well.

Parameter inference is done using MCMC for cosmological parameters, with public PLANCK/WMAP/SPT data.

Sync commands

From phoenix -> laptop (AstroVAE/Cl_data/Data)

scp phoenix:/homes/nramachandra/AstroVAE/Cl_data/Model/7500 mcs:/homes/nramachandra/DataP5/Model/ scp phoenix:/homes/nramachandra/AstroVAE/Cl_data/Data/norm7500 mcs:/homes/nramachandra/DataP5/ scp phoenix:/homes/nramachandra/AstroVAE/Cl_data/Data/mean7500 mcs:/homes/nramachandra/DataP5/ scp phoenix:/homes/nramachandra/AstroVAE/Cl_data/Data/encoded7500 mcs:/homes/nramachandra/DataP5/

From laptop -> phoenix

scp P25. mcs:/homes/nramachandra/DataP5/raw/

Future implementations

Error propoagation using Bayesian neural networks
t-SNE for reduction and visualization
RNN for time analysis
Adversarial AEs

Name		Name	Last commit message	Last commit date
Latest commit History 786 Commits
.ipynb_checkpoints		.ipynb_checkpoints
ComparisonTests		ComparisonTests
MNIST_data		MNIST_data
OldSlurms		OldSlurms
OldSubmissionScripts		OldSubmissionScripts
P10		P10
otherCodes		otherCodes
scikit-optimize		scikit-optimize
.DS_Store		.DS_Store
.gitignore		.gitignore
.gpfit_cvae.zip		.gpfit_cvae.zip
.params_debug.py.swp		.params_debug.py.swp
CLID_train_7500.txt		CLID_train_7500.txt
ClTrainTestP4.py		ClTrainTestP4.py
Cl_CVAE.py		Cl_CVAE.py
Cl_GPfitforWP4.py		Cl_GPfitforWP4.py
Cl_SVDP4.py		Cl_SVDP4.py
Cl_VAEpredictGPy.py		Cl_VAEpredictGPy.py
Cl_VAEpredictGPyPol.py		Cl_VAEpredictGPyPol.py
Cl_VAEpredictP4.py		Cl_VAEpredictP4.py
Cl_VAEpredictP4_apr18.py		Cl_VAEpredictP4_apr18.py
Cl_VAEpredictP4_debug.py		Cl_VAEpredictP4_debug.py
Cl_VAEpredictP4_mar18.py		Cl_VAEpredictP4_mar18.py
Cl_VAEpredictP4_may18.py		Cl_VAEpredictP4_may18.py
Cl_denoiseP4.py		Cl_denoiseP4.py
Cl_denoiseP4_apr18.py		Cl_denoiseP4_apr18.py
Cl_denoiseP4_debug.py		Cl_denoiseP4_debug.py
Cl_denoiseP4_mar18.py		Cl_denoiseP4_mar18.py
Cl_denoiseP4_may18.py		Cl_denoiseP4_may18.py
Cl_linear.py		Cl_linear.py
Cl_load.py		Cl_load.py
Cl_predict.py		Cl_predict.py
Cl_predict_var.py		Cl_predict_var.py
Cl_predict_varPol.py		Cl_predict_varPol.py
LINEAR_test_7500.txt		LINEAR_test_7500.txt
LINEAR_train_7500.txt		LINEAR_train_7500.txt
LatinCAMBPk.py		LatinCAMBPk.py
LatinSq128.txt		LatinSq128.txt
New_CAMBGen2.py		New_CAMBGen2.py
New_CAMBGen2.py~		New_CAMBGen2.py~
New_CAMBGenChecks.py		New_CAMBGenChecks.py
New_CCLGen2.py		New_CCLGen2.py
Pemu_rank16.png		Pemu_rank16.png
Pk_VAEpredictGPy.py		Pk_VAEpredictGPy.py
Pk_VAEpredictP5.py		Pk_VAEpredictP5.py
Pk_denoiseP5.py		Pk_denoiseP5.py
Pk_denoiseP5_05.py		Pk_denoiseP5_05.py
README.md		README.md
README_phoenix_submissio.txt		README_phoenix_submissio.txt
SetPub.py		SetPub.py
TestArr_1.txt		TestArr_1.txt
alsa-info.sh		alsa-info.sh
cambVclass.py		cambVclass.py
conv1d.py		conv1d.py
conv1dvae_cnn_galsim_cosmos.h5		conv1dvae_cnn_galsim_cosmos.h5
cvae_2.py		cvae_2.py
cvae_Scatter_z.png		cvae_Scatter_z.png
cvae_conv1d.py		cvae_conv1d.py
debug_100.txt		debug_100.txt
debug_100_new_gp.txt		debug_100_new_gp.txt
debug_200_new_gp.txt		debug_200_new_gp.txt
debug_2500.txt		debug_2500.txt
debug_25000_new_gp.txt		debug_25000_new_gp.txt
debug_3000_new_gp.txt		debug_3000_new_gp.txt
debug_300_new_gp.txt		debug_300_new_gp.txt
debug_7500_new.txt		debug_7500_new.txt
debug_7500_new_gp.txt		debug_7500_new_gp.txt
encoded_test_originalP5.txt		encoded_test_originalP5.txt
encoded_trainP5.txt		encoded_trainP5.txt
gaussian_mcmc.py		gaussian_mcmc.py
gpflow_pca.ipynb		gpflow_pca.ipynb
gpflow_rank16.png		gpflow_rank16.png
gpflow_rank32.png		gpflow_rank32.png
gpflow_rank8.png		gpflow_rank8.png
gpflow_vae-1.ipynb		gpflow_vae-1.ipynb
gpflow_vae-2.ipynb		gpflow_vae-2.ipynb
gpflow_vae.ipynb		gpflow_vae.ipynb
gpflow_vae.py		gpflow_vae.py
latin.py		latin.py
latinCAMBGenP4.py		latinCAMBGenP4.py
latinP4.py		latinP4.py
lhc_128.txt		lhc_128.txt
mcmcP5.py		mcmcP5.py
mcmc_5para.py		mcmc_5para.py
mcmc_GP.py		mcmc_GP.py
mcmc_GPburn.py		mcmc_GPburn.py
mcmc_P.py		mcmc_P.py
mcmc_R.py		mcmc_R.py
mcmc_R_py.py		mcmc_R_py.py
mcmc_combine.py		mcmc_combine.py
mcmc_spt.py		mcmc_spt.py
model.png		model.png
nramachandra@roomba@hep.anl.gov		nramachandra@roomba@hep.anl.gov
para4_new.txt		para4_new.txt
para4_train.txt		para4_train.txt
params.py		params.py
paramsPk.py		paramsPk.py
paramsPk_05.py		paramsPk_05.py
params_apr18.py		params_apr18.py
params_debug.py		params_debug.py

nesar/AstroVAE

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