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| author | Slasnista <stan.chambon@gmail.com> | 2017-08-29 09:05:01 +0200 |
|---|---|---|
| committer | Slasnista <stan.chambon@gmail.com> | 2017-08-29 09:05:01 +0200 |
| commit | a29e22db4772ebc4a8266c917e2e662f624c6baa (patch) | |
| tree | 352a04e3e01ffbb0696403f9af4857758ed86342 /examples/da/plot_otda_d2.py | |
| parent | 7d3fc95abe059cc7404f3c213dfd5019cf110737 (diff) | |
addressed AG comments + adding random seed
Diffstat (limited to 'examples/da/plot_otda_d2.py')
| -rw-r--r-- | examples/da/plot_otda_d2.py | 14 |
1 files changed, 8 insertions, 6 deletions
diff --git a/examples/da/plot_otda_d2.py b/examples/da/plot_otda_d2.py index 1d2192f..8833eb2 100644 --- a/examples/da/plot_otda_d2.py +++ b/examples/da/plot_otda_d2.py @@ -19,17 +19,19 @@ of what the transport methods are doing. # License: MIT License import matplotlib.pylab as pl +import numpy as np import ot -# number of source and target points to generate -ns = 150 -nt = 150 +np.random.seed(42) -Xs, ys = ot.datasets.get_data_classif('3gauss', ns) -Xt, yt = ot.datasets.get_data_classif('3gauss2', nt) +n_samples_source = 150 +n_samples_target = 150 + +Xs, ys = ot.datasets.get_data_classif('3gauss', n_samples_source) +Xt, yt = ot.datasets.get_data_classif('3gauss2', n_samples_target) # Cost matrix -M = ot.dist(Xs, Xt) +M = ot.dist(Xs, Xt, metric='sqeuclidean') # Instantiate the different transport algorithms and fit them |