From 97feeb32b6c069d7bb44cd995531c2b820d59771 Mon Sep 17 00:00:00 2001 From: tgnassou <66993815+tgnassou@users.noreply.github.com> Date: Mon, 16 Jan 2023 18:09:44 +0100 Subject: [MRG] OT for Gaussian distributions (#428) MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit * add gaussian modules * add gaussian modules * add PR to release.md * Apply suggestions from code review Co-authored-by: Alexandre Gramfort * Apply suggestions from code review Co-authored-by: Alexandre Gramfort * Update ot/gaussian.py * Update ot/gaussian.py * add empirical bures wassertsein distance, fix docstring and test * update to fit with new networkx API * add test for jax et tf" * fix test * fix test? * add empirical_bures_wasserstein_mapping * fix docs * fix doc * fix docstring * add tgnassou to contributors * add more coverage for gaussian.py * add deprecated function * fix doc math" " * fix doc math" " * add remi flamary to authors of gaussiansmodule * fix equation Co-authored-by: Rémi Flamary Co-authored-by: Alexandre Gramfort --- examples/domain-adaptation/plot_otda_linear_mapping.py | 2 +- examples/gromov/plot_barycenter_fgw.py | 2 +- 2 files changed, 2 insertions(+), 2 deletions(-) (limited to 'examples') diff --git a/examples/domain-adaptation/plot_otda_linear_mapping.py b/examples/domain-adaptation/plot_otda_linear_mapping.py index a44096a..8284a2a 100644 --- a/examples/domain-adaptation/plot_otda_linear_mapping.py +++ b/examples/domain-adaptation/plot_otda_linear_mapping.py @@ -61,7 +61,7 @@ plt.plot(xt[:, 0], xt[:, 1], 'o') # Estimate linear mapping and transport # ------------------------------------- -Ae, be = ot.da.OT_mapping_linear(xs, xt) +Ae, be = ot.gaussian.empirical_bures_wasserstein_mapping(xs, xt) xst = xs.dot(Ae) + be diff --git a/examples/gromov/plot_barycenter_fgw.py b/examples/gromov/plot_barycenter_fgw.py index 556e08f..dc3c6aa 100644 --- a/examples/gromov/plot_barycenter_fgw.py +++ b/examples/gromov/plot_barycenter_fgw.py @@ -174,7 +174,7 @@ A, C, log = fgw_barycenters(sizebary, Ys, Cs, ps, lambdas, alpha=0.95, log=True) # ------------------------- #%% Create the barycenter -bary = nx.from_numpy_matrix(sp_to_adjency(C, threshinf=0, threshsup=find_thresh(C, sup=100, step=100)[0])) +bary = nx.from_numpy_array(sp_to_adjency(C, threshinf=0, threshsup=find_thresh(C, sup=100, step=100)[0])) for i, v in enumerate(A.ravel()): bary.add_node(i, attr_name=v) -- cgit v1.2.3