A Matlab toolbox for sampling inverse problems with complex priors
Switch branches/tags
Nothing to show
Clone or download
Type Name Latest commit message Commit time
Failed to load latest commit information.
data/crosshole removing TI (moving to mGstat) Feb 23, 2016
doc ..,,.. Feb 9, 2017
examples . Oct 30, 2018
misc curvuature Jan 8, 2018
obsolete sippi_prior_init: do not compute mean/std of Gaussian type prior if t… Sep 20, 2018
plotting .. Nov 7, 2018
toolboxes . May 31, 2018
.gitmodules New submodules, MPSLIB and mGstat Mar 20, 2018
LICENSE Initial upload of SIPPI, accompanying two papers in Computers and Geo… Oct 5, 2012
README.md Update README.md Mar 20, 2018
sippi_adjust_step_size.m documentation ... Oct 10, 2012
sippi_anneal_temperature.m Getting ready to merge back Jun 2, 2015
sippi_compute_acceptance_rate.m Updated verbose output of sippi_metropolis Feb 23, 2017
sippi_compute_modelization_forward_error.m ..,,.. Dec 20, 2016
sippi_forward.m Example of infering std of noise as part of inversion Nov 14, 2016
sippi_forward_jacobian.m ..,,.. Feb 23, 2017
sippi_forward_linear.m Linear forward operator for SIPPI Aug 15, 2016
sippi_get_resim_data.m Adding a unified approach for sequentiual Gibbs resimulation - sippi_… Feb 10, 2017
sippi_get_sample.m . Oct 30, 2018
sippi_least_squares.m Updating sippi_least_squares.m Jan 13, 2017
sippi_likelihood.m 2D linear straight ray kernel added, written by Bo Holm Jacobsen. Oct 4, 2016
sippi_mcmc_init.m Optional 1D or 2D gibbs sampling at each step of the extende Metropol… Nov 15, 2017
sippi_metropolis.m .. Nov 7, 2018
sippi_metropolis_gibbs.m sippi_metropolis_gibbs: Now works with annealing and temperature... Sep 20, 2018
sippi_metropolis_gibbs_random_iteration.m sippi_prior_init: do not compute mean/std of Gaussian type prior if t… Sep 20, 2018
sippi_metropolis_gibbs_random_iteration_2d.m sippi_metropolis_gibbs: 2D gibbs Now works with annealing and tempera… Sep 20, 2018
sippi_metropolis_iteration.m sippi_metropolis_gibbs: Now works with annealing and temperature... Sep 20, 2018
sippi_metropolis_mulrun.m Upudated sippi_metropolis_mulruns... Nov 17, 2016
sippi_prior.m Allow CONVERTED type of prior.. COmbines other priors into a not prio… Dec 1, 2017
sippi_prior_cholesky.m general prior type with m-file Mar 20, 2018
sippi_prior_dsim.m small bug related to setting m0 using a linear forward kernel Feb 11, 2015
sippi_prior_init.m sippi_prior_init: do not compute mean/std of Gaussian type prior if t… Sep 20, 2018
sippi_prior_mixsim.m Initial support for 2D mixed point simulation (mixsim_2D) May 16, 2017
sippi_prior_mps.m MPS prior updates May 31, 2018
sippi_prior_plurigaussian.m Examples of using plurigaussian priors Feb 3, 2016
sippi_prior_set_steplength.m Cleaning up Jun 24, 2015
sippi_prior_sisim.m Added seperate files for SISIM, VISIM, SNESIM prior, and added some c… Nov 19, 2014
sippi_prior_snesim.m updating issstr to ischar Nov 30, 2015
sippi_prior_snesim_std.m Allow hard_data setting for sippi_prior_snesim_std. Allows setting op… Apr 8, 2016
sippi_prior_uniform.m better support for chains Apr 29, 2015
sippi_prior_visim.m More tekst and additional input option Mar 28, 2017
sippi_prior_voronoi.m Updated help on use of VORONOIS type prior Aug 10, 2017
sippi_rejection.m sippi_rejection: added possibility to continue sampling if sampling w… Feb 24, 2017
sippi_sequential_gibbs_resim.m Adding a unified approach for sequentiual Gibbs resimulation - sippi_… Feb 10, 2017
sippi_set_path.m Cleaning up for new release Aug 18, 2016
sippi_tikhonov.m general prior type with m-file Mar 20, 2018







Latest stable release

The simplest approach to start using SIPPI is to download the latest SIPPI package from http://sippi.sourceforge.net/

Simply download SIPPI.zip, and unzip SIPPI.zip to a folder such as $SIPPI.

Then start Matlab and add the appropriate paths using

 >> addpath $SIPPI
 >> sippi_set_path

Please go to (http://sippi.sourceforge.net) for examples and details on how to use SIPPI.

Installation from github

The latest version of SIPPI can be downloaded from github. This is the version the developers use. The documentation is usually slightly outdated compared to the github version. The latest copy of SIPPI, including mGstat and MPSLIB, can be downloaded using (most users of SIPPI would need this):

 git clone --recursive https://github.com/cultpenguin/sippi.git SIPPI

Then add a path to SIPPI

 >> sippi_set_path

To update SIPPI, including submodules (mGstat and MPSLIB) use

 git pull --recurse-submodules

SIPPI, mGstat and MPSLIB can also be downloaded seperately (a develope weould probably prefer this) from github using

  git clone --depth 1 https://github.com/cultpenguin/sippi.git SIPPI
  git clone --depth 1 https://github.com/cultpenguin/mgstat.git SIPPI/toolboxes/mGstat
  git clone --depth 1 https://github.com/ergosimulation/mpslib.git SIPPI/toolboxes/MPSLIB

Then add a path to both SIPPI, mGstat in Matlab using:

 >> addpath INSTALL_DIR/mGstat
 >> addpath INSTALL_DIR/MPSLIB/matlab
 >> sippi_set_path

See also https://www.gitbook.com/book/cultpenguin/sippi for more details on manual installation.


$SIPPI/ SIPPI core m-files

$SIPPI/plotting Directory containing m-files for plotting

$SIPPI/data Currently only contains the data from ARRENAES described in the paper


+'fast_marching_kron' -> Fast marching toolbox by Dirk-Jan Kroon. http://www.mathworks.com/matlabcentral/fileexchange/24531-accurate-fast-marching

+'mGstat' -> geostatistical toolbox for Matlab, by Thomas M Hansen and Knud S Cordua http://github.com/cultpenguin/mgstat

+'MPSLIB' --> Multiple Point Statistics C++ library, https://github.com/ergosimulation/mpslib

+'tomography' -> A few m-files realated to the cross hole tomographic examples

$SIPPI/examples/ contains a number of example for using/running SIPPI

$SIPPI/examples/prior_tests contains m-files used to generate samples from the prior pdf of a number of different prior type models

$SIPPI/examples/case_line_fit sippi_line_fit.m demonstrates fitting a straight lin, CASE 1 in the SIPPI manuscript

$SIPPI/examples/tomography contains a number of examples of sampling the a posteriori pdf for tomographic inverse problems, CASE 2 in the SIPPI manuscript

  • using data AM13 (2D)

sippi_AM13_metropolis_gaussian.m: Metropolis sampling using Gaussian prior

sippi_AM13_metropolis_bimodal.m: Metropolis sampling using Gaussian prior / bimodal distribution

sippi_AM13_metropolis_uniform.m: Metropolis sampling using Gaussian prior / uniform distribution

sippi_AM13_rejection_gaussian.m: Rejection sampling using Gaussian prior

sippi_AM13_least_squares.m: Least squares inversion using Gaussian prior

  • using data AM24 (2D)

sippi_AM24_gaussian.m: as sippi_AM13_metropolis_gaussian.m but for data set AM24

  • using data AM1234 (3D)

sippi_AM1234_metropolis_gaussian.m : sippi_AM13_metropolis_gaussian.m but for data set AM1234


  • jura_covariance_inference: Example of probabilistic covariance model parameter inference following Hansen et al., 2015 - A general probabilistic approach for inference of Gaussian model parameters from noisy data of point and volume support. doi:10.1007/s11004-014-9567-5

Releases history

#v1.5 2016-08-18 Notice that V1.3 was packed without mGstat :/ MPSLIB (https://github.com/ergosimulation/mpslib) added for the first time (MPS based prior sampling, SNESIM and ENESIM type algorithms)

#v1.4 2016-02-01 Notice that V1.3 was packed without mGstat :/ So v1.4 is like V1.4 but repackaged properly with mGstat.

  • sippi_prior_plurigaussian added for the first time.

#v1.3 Added parallel tempering to sippi_metropolis Many small bugfixes. Testet with Matlab R2015b

#v1.2 Moving from SVN to GIT (on github)

#1.1.1 (01-12-2014) [rev 272] Fixed bugh in sippi_get_sample that prevented most sippi_plot_posterior_* algorithms to wokr properly

#1.1 (20-11-2014) [rev 265] Added consistency checks to sippi_prior_init Seperated visim, sisim prior types into seperate m-files, sippi_prior_visim, sippi_prior_sisim

#1.03 (22-10-2014) [rev 240] Removed the use of xcorr from signal processing toolbox Update sippi_get_sample, and most sippi_plot_posterior_* routines

#1.02 (07-10-2014) [rev 235] Bug fix (sippi_plot_posterior, prior{ip}.cax need not be set)

#1.01 (09-07-2014) LUSIM type a priori model UNIFORM type a priori model bug fixes

#1.00 (09-07-2014) Multiple updates,

  • new figures
  • Annealing type schedule for monte Carlo Sampling
  • more example
  • many bugfixes
  • quantifying and accounting for modeling errors

#0.96 (12-03-2014) Many updates for sippi_metropolis sippi_plot_prior sippi_plot_posterior


#0.94 Updates for handling prior types VISIM/SNESIM/FFTMA/SISIM

#0.93 Updates for plotting prior and posterior statistics (sippi_plot_prior, sippi_plot_posterior) Updates for fft_ma for better 1D simulation


Fixed plotting of prior and posterior statistic for a scalar, 1D, 2D, and 3D a priori model types


Initial release