144 lines
3.8 KiB
Python
144 lines
3.8 KiB
Python
"""Testing routines for the lpls engine.
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"""
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from math import sqrt as msqrt
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from numpy.testing import *
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set_package_path()
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from pyblm import lpls
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from numpy import dot, eye, random,asarray,empty
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from numpy.random import rand, randn
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from numpy.linalg import svd,norm
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restore_path()
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def blm_array(shape=(5,10), comp=3, noise=0,seed=1,dtype='d'):
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assert(min(*shape)>=comp)
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random.seed(seed)
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t = rand(shape[0], comp)
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p = rand(shape[1], comp)
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x = dot(t, p.T)
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if noise>0:
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noise = noise*randn(*shape)
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return x + noise
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class LplsTestCase(NumpyTestCase):
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def setUp(self):
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self.a = blm_array(shape=(5,10),noise=.1)
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self.b = blm_array(shape=(5,3), noise=.1)
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self.c = blm_array(shape=(10,10), noise=.1)
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self.nc = 2
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def check_single(self):
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self.a = asarray(self.a, dtype='f')
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self.b = asarray(self.b, dtype='f')
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self.c = asarray(self.c, dtype='f')
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self.do()
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def check_double(self):
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a = asarray(self.a, dtype='d')
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b = asarray(self.b, dtype='d')
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c = asarray(self.c, dtype='d')
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self.do()
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def do(self,*args):
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pass
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#raise NotImplementedError
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class testAlphaZero(LplsTestCase):
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def do(self):
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#dat = lpls(self.a, self.b, self.c, self.nc, alpha=0.0)
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#assert_almost_equal(t1, t2)
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pass
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class testAlphaOne(LplsTestCase):
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pass
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class testZidentity(LplsTestCase):
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def do(self):
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I = eye(self.a.shape[1])
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dat = lpls(self.a, self.b, I, 2, alpha=1.0)
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dat2 = lpls(self.a, self.b, self.c, self.nc, alpha=0.0)
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assert_almost_equal(dat['T'], dat2['T'])
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class testYidentity(LplsTestCase):
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def do(self):
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I = eye(self.b.shape[0], dtype=self.a.dtype)
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T0 = lpls(self.a, I, self.c, self.nc, alpha=0.0, mean_ctr=[-1,-1,-1])['T']
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u, s, vt = svd(self.a, 0)
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T = u*s
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assert_almost_equal(abs(T0), abs(T[:,:self.nc]),5)
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class testWideX(LplsTestCase):
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pass
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class testTallX(LplsTestCase):
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pass
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class testWideY(LplsTestCase):
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pass
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class testTallY(LplsTestCase):
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pass
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class testWideZ(LplsTestCase):
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pass
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class testTallZ(LplsTestCase):
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pass
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class testRankDeficientX(LplsTestCase):
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pass
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class testRankDeficientY(LplsTestCase):
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pass
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class testRankDeficientZ(LplsTestCase):
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pass
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class testCenterX(LplsTestCase):
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def do(self):
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T = lpls(self.a, self.b, self.c, self.nc, mean_ctr=[0,-1,-1])['T']
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assert_almost_equal(T.mean(0), 0)
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W = lpls(self.a, self.b, self.c, self.nc, alpha=0,mean_ctr=[1,-1,-1])['W']
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assert_almost_equal(W.mean(0), 0)
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class testResiduals(NumpyTestCase):
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def setUp(self):
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self.a = blm_array(shape=(5,5),noise=0, comp=3)
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self.b = self.a.copy()
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self.c = self.a.copy().T
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self.nc = 3
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def check_single(self):
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self.a = asarray(self.a, dtype='f')
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self.b = asarray(self.b, dtype='f')
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self.c = asarray(self.c, dtype='f')
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self.do()
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def check_double(self):
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a = asarray(self.a, dtype='d')
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b = asarray(self.b, dtype='d')
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c = asarray(self.c, dtype='d')
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self.do()
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def do(self):
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dat = lpls(self.a, self.b, self.c, self.nc, mean_ctr=[-1,-1,-1])
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class testOrthogonality(LplsTestCase):
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def do(self):
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dat = lpls(self.a, self.b, self.c, self.nc, mean_ctr=[0,0,0],scale='loads')
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T, W, L, E, F = dat['T'],dat['W'],dat['L'],dat['E'],dat['F']
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assert_almost_equal(dot(T.T,T), eye(T.shape[1]))
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for i,w in enumerate(W.T):
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W[:,i] = w/norm(w)
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assert_almost_equal(dot(W.T, W), eye(W.shape[1]), 3)
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assert_almost_equal(dot(T.T,E), 0, 3)
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assert_almost_equal(dot(T.T,F), 0, 3)
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if __name__ == '__main__':
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NumpyTest().run()
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