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| author | vivienseguy <vivienseguy@gmail.com> | 2018-07-05 18:26:55 +0900 |
|---|---|---|
| committer | vivienseguy <vivienseguy@gmail.com> | 2018-07-05 18:26:55 +0900 |
| commit | 98ce4ccd3536d95c609ee1c5b737ced85d68f786 (patch) | |
| tree | d5716a2854e15c9acbb1aa40d09549fa87f7a51e /examples | |
| parent | 3f23fa1a950ffde4a4224a6343a504a0c5b7851b (diff) | |
free support barycenter
Diffstat (limited to 'examples')
| -rw-r--r-- | examples/plot_free_support_barycenter.py | 9 |
1 files changed, 4 insertions, 5 deletions
diff --git a/examples/plot_free_support_barycenter.py b/examples/plot_free_support_barycenter.py index a733745..274cf76 100644 --- a/examples/plot_free_support_barycenter.py +++ b/examples/plot_free_support_barycenter.py @@ -17,7 +17,6 @@ import numpy as np import matplotlib.pylab as pl import ot.plot - ############################################################################## # Generate data # ------------- @@ -29,10 +28,10 @@ measures_weights = [] for i in range(N): - n = np.rand.int(low=1, high=20) # nb samples + n = np.random.randint(low=1, high=20) # nb samples mu = np.random.normal(0., 1., (d,)) - cov = np.random.normal(0., 1., (d,d)) + cov = np.random.uniform(0., 1., (d,d)) xs = ot.datasets.make_2D_samples_gauss(n, mu, cov) b = np.random.uniform(0., 1., n) @@ -49,7 +48,7 @@ b_init = np.ones((k,)) / k ############################################################################## # Compute free support barycenter # ------------- -X = ot.lp.barycenter(measures_locations, measures_weights, X_init, b_init) +X = ot.lp.cvx.free_support_barycenter(measures_locations, measures_weights, X_init, b_init) ############################################################################## @@ -60,7 +59,7 @@ X = ot.lp.barycenter(measures_locations, measures_weights, X_init, b_init) pl.figure(1) for (xs, b) in zip(measures_locations, measures_weights): - pl.scatter(xs[:, 0], xs[:, 1], s=b, c=np.tile(np.rand(0. ,255., size=(3,)), (1,b.size(0))) , label='Data measures') + pl.scatter(xs[:, 0], xs[:, 1], s=b, c=np.tile(np.random.uniform(0. ,255., size=(3,)), (1,b.size(0))) , label='Data measures') pl.scatter(xs[:, 0], xs[:, 1], s=b, c='black' , label='2-Wasserstein barycenter') pl.legend(loc=0) pl.title('Data measures and their barycenter') |