diff options
| author | Nicolas Courty <Nico@MacBook-Pro-de-Nicolas.local> | 2017-09-01 15:37:09 +0200 |
|---|---|---|
| committer | Nicolas Courty <Nico@MacBook-Pro-de-Nicolas.local> | 2017-09-01 15:37:09 +0200 |
| commit | 53e1115349ddbdff83b74c5dd15fc4b258c46cd4 (patch) | |
| tree | ac4619872b341ef0471cc70d671d566526113c0b /examples/plot_gromov_barycenter.py | |
| parent | f12322c1a288baedffd5b6aedcff15747aadac8e (diff) | |
docstrings + naming
Diffstat (limited to 'examples/plot_gromov_barycenter.py')
| -rwxr-xr-x | examples/plot_gromov_barycenter.py | 34 |
1 files changed, 21 insertions, 13 deletions
diff --git a/examples/plot_gromov_barycenter.py b/examples/plot_gromov_barycenter.py index f0657e1..4f17117 100755 --- a/examples/plot_gromov_barycenter.py +++ b/examples/plot_gromov_barycenter.py @@ -45,19 +45,19 @@ def smacof_mds(C, dim, max_iter=3000, eps=1e-9): dimension of the targeted space
max_iter : int
Maximum number of iterations of the SMACOF algorithm for a single run
-
- eps : relative tolerance w.r.t stress to declare converge
+ eps : float
+ relative tolerance w.r.t stress to declare converge
Returns
-------
- npos : R**dim ndarray
+ npos : ndarray, shape (R, dim)
Embedded coordinates of the interpolated point cloud (defined with one isometry)
"""
- seed = np.random.RandomState(seed=3)
+ rng = np.random.RandomState(seed=3)
mds = manifold.MDS(
dim,
@@ -72,7 +72,7 @@ def smacof_mds(C, dim, max_iter=3000, eps=1e-9): max_iter=max_iter,
eps=1e-9,
dissimilarity="precomputed",
- random_state=seed,
+ random_state=rng,
n_init=1)
npos = nmds.fit_transform(C, init=pos)
@@ -132,23 +132,31 @@ lambdast = [[float(i) / 3, float(3 - i) / 3] for i in [1, 2]] Ct01 = [0 for i in range(2)]
for i in range(2):
- Ct01[i] = ot.gromov.gromov_barycenters(n_samples, [Cs[0], Cs[1]], [
- ps[0], ps[1]], p, lambdast[i], 'square_loss', 5e-4, numItermax=100, stopThr=1e-3)
+ Ct01[i] = ot.gromov.gromov_barycenters(n_samples, [Cs[0], Cs[1]],
+ [ps[0], ps[1]
+ ], p, lambdast[i], 'square_loss', 5e-4,
+ max_iter=100, stopThr=1e-3)
Ct02 = [0 for i in range(2)]
for i in range(2):
- Ct02[i] = ot.gromov.gromov_barycenters(n_samples, [Cs[0], Cs[2]], [
- ps[0], ps[2]], p, lambdast[i], 'square_loss', 5e-4, numItermax=100, stopThr=1e-3)
+ Ct02[i] = ot.gromov.gromov_barycenters(n_samples, [Cs[0], Cs[2]],
+ [ps[0], ps[2]
+ ], p, lambdast[i], 'square_loss', 5e-4,
+ max_iter=100, stopThr=1e-3)
Ct13 = [0 for i in range(2)]
for i in range(2):
- Ct13[i] = ot.gromov.gromov_barycenters(n_samples, [Cs[1], Cs[3]], [
- ps[1], ps[3]], p, lambdast[i], 'square_loss', 5e-4, numItermax=100, stopThr=1e-3)
+ Ct13[i] = ot.gromov.gromov_barycenters(n_samples, [Cs[1], Cs[3]],
+ [ps[1], ps[3]
+ ], p, lambdast[i], 'square_loss', 5e-4,
+ max_iter=100, stopThr=1e-3)
Ct23 = [0 for i in range(2)]
for i in range(2):
- Ct23[i] = ot.gromov.gromov_barycenters(n_samples, [Cs[2], Cs[3]], [
- ps[2], ps[3]], p, lambdast[i], 'square_loss', 5e-4, numItermax=100, stopThr=1e-3)
+ Ct23[i] = ot.gromov.gromov_barycenters(n_samples, [Cs[2], Cs[3]],
+ [ps[2], ps[3]
+ ], p, lambdast[i], 'square_loss', 5e-4,
+ max_iter=100, stopThr=1e-3)
"""
Visualization
|