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author | Gard Spreemann <gspr@nonempty.org> | 2020-07-09 08:50:11 +0200 |
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committer | Gard Spreemann <gspr@nonempty.org> | 2020-07-09 08:50:11 +0200 |
commit | 616c6039614e96b6cfd88eb7db25ce11c7302c30 (patch) | |
tree | a745ec24604f660b256dbaee214affa497c9c21e /ot/optim.py | |
parent | d62f05daf348b4e554056f298c66cbd64f5e3c6e (diff) | |
parent | a16b9471d7114ec08977479b7249efe747702b97 (diff) |
Merge branch 'dfsg/latest' into debian/sid
Diffstat (limited to 'ot/optim.py')
-rw-r--r-- | ot/optim.py | 8 |
1 files changed, 5 insertions, 3 deletions
diff --git a/ot/optim.py b/ot/optim.py index 0abd9e9..b9ca891 100644 --- a/ot/optim.py +++ b/ot/optim.py @@ -1,6 +1,6 @@ # -*- coding: utf-8 -*- """ -Optimization algorithms for OT +Generic solvers for regularized OT """ # Author: Remi Flamary <remi.flamary@unice.fr> @@ -134,7 +134,7 @@ def solve_linesearch(cost, G, deltaG, Mi, f_val, return alpha, fc, f_val -def cg(a, b, M, reg, f, df, G0=None, numItermax=200, +def cg(a, b, M, reg, f, df, G0=None, numItermax=200, numItermaxEmd=100000, stopThr=1e-9, stopThr2=1e-9, verbose=False, log=False, **kwargs): """ Solve the general regularized OT problem with conditional gradient @@ -172,6 +172,8 @@ def cg(a, b, M, reg, f, df, G0=None, numItermax=200, initial guess (default is indep joint density) numItermax : int, optional Max number of iterations + numItermaxEmd : int, optional + Max number of iterations for emd stopThr : float, optional Stop threshol on the relative variation (>0) stopThr2 : float, optional @@ -238,7 +240,7 @@ def cg(a, b, M, reg, f, df, G0=None, numItermax=200, Mi += Mi.min() # solve linear program - Gc = emd(a, b, Mi) + Gc = emd(a, b, Mi, numItermax=numItermaxEmd) deltaG = Gc - G |