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import ot
import numpy as np
import pytest
try: # test if cudamat installed
import ot.dr
nogo = False
except ImportError:
nogo = True
@pytest.mark.skipif(nogo, reason="Missing modules (autograd or pymanopt)")
def test_fda():
n = 100 # nb samples in source and target datasets
nz = 0.2
np.random.seed(0)
# generate circle dataset
t = np.random.rand(n) * 2 * np.pi
ys = np.floor((np.arange(n) * 1.0 / n * 3)) + 1
xs = np.concatenate(
(np.cos(t).reshape((-1, 1)), np.sin(t).reshape((-1, 1))), 1)
xs = xs * ys.reshape(-1, 1) + nz * np.random.randn(n, 2)
nbnoise = 8
xs = np.hstack((xs, np.random.randn(n, nbnoise)))
p = 2
Pfda, projfda = ot.dr.fda(xs, ys, p)
projfda(xs)
assert np.allclose(np.sum(Pfda**2, 0), np.ones(p))
@pytest.mark.skipif(nogo, reason="Missing modules (autograd or pymanopt)")
def test_wda():
n = 100 # nb samples in source and target datasets
nz = 0.2
np.random.seed(0)
# generate circle dataset
t = np.random.rand(n) * 2 * np.pi
ys = np.floor((np.arange(n) * 1.0 / n * 3)) + 1
xs = np.concatenate(
(np.cos(t).reshape((-1, 1)), np.sin(t).reshape((-1, 1))), 1)
xs = xs * ys.reshape(-1, 1) + nz * np.random.randn(n, 2)
nbnoise = 8
xs = np.hstack((xs, np.random.randn(n, nbnoise)))
p = 2
Pwda, projwda = ot.dr.wda(xs, ys, p, maxiter=10)
projwda(xs)
assert np.allclose(np.sum(Pwda**2, 0), np.ones(p))
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