def test_indexing(self):
big = ch.Ch(np.arange(60).reshape((10, 6)))
little = big[1:3, 3:6]
self.assertTrue(
np.max(np.abs(little.r -
np.array([[9, 10, 11], [15, 16, 17]]))) == 0)
little = big[5]
self.assertTrue(np.max(np.abs(little.r - np.arange(30, 36))) == 0)
self.assertTrue(
np.max(
np.abs(
sp.coo_matrix(little.dr_wrt(big)).col -
np.arange(30, 36))) == 0)
little = big[2, 3]
self.assertTrue(little.r[0] == 15.0)
little = big[2, 3:5]
self.assertTrue(np.max(np.abs(little.r - np.array([15, 16]))) == 0.)
_ = little.dr_wrt(big)
# Tests assignment through reorderings
aa = ch.arange(4 * 4 * 4).reshape((4, 4, 4))[:3, :3, :3]
aa[0, 1, 2] = 100
self.assertTrue(aa[0, 1, 2].r[0] == 100)
# Tests assignment through reorderings (NaN's are a special case)
aa = ch.arange(9).reshape((3, 3))
aa[1, 1] = np.nan
self.assertTrue(np.isnan(aa.r[1, 1]))
self.assertFalse(np.isnan(aa.r[0, 0]))
def test_indexing(self):
big = ch.Ch(np.arange(60).reshape((10,6)))
little = big[1:3, 3:6]
self.assertTrue(np.max(np.abs(little.r - np.array([[9,10,11],[15,16,17]]))) == 0)
little = big[5]
self.assertTrue(np.max(np.abs(little.r - np.arange(30, 36))) == 0)
self.assertTrue(np.max(np.abs(sp.coo_matrix(little.dr_wrt(big)).col - np.arange(30,36))) == 0)
little = big[2, 3]
self.assertTrue(little.r[0] == 15.0)
little = big[2, 3:5]
self.assertTrue(np.max(np.abs(little.r - np.array([15, 16]))) == 0.)
_ = little.dr_wrt(big)
# Tests assignment through reorderings
aa = ch.arange(4*4*4).reshape((4,4,4))[:3,:3,:3]
aa[0,1,2] = 100
self.assertTrue(aa[0,1,2].r[0] == 100)
# Tests assignment through reorderings (NaN's are a special case)
aa = ch.arange(9).reshape((3,3))
aa[1,1] = np.nan
self.assertTrue(np.isnan(aa.r[1,1]))
self.assertFalse(np.isnan(aa.r[0,0]))
def test_tensordot(self):
an = np.arange(60.).reshape(3,4,5)
bn = np.arange(24.).reshape(4,3,2)
cn = np.tensordot(an,bn, axes=([1,0],[0,1]))
ac = ch.arange(60.).reshape(3,4,5)
bc = ch.arange(24.).reshape(4,3,2)
cc = ch.tensordot(ac,bc, axes=([1,0],[0,1]))
cc.r
cc.dr_wrt(ac)
cc.dr_wrt(bc)
def test_dr_wrt_selection(self):
aa = ch.arange(10,20)
bb = ch.arange(1,11)
cc = aa * bb + aa + bb +2
dr0 = cc.dr_wrt(aa[4:6])
dr1 = cc.dr_wrt(aa)[:,4:6]
self.assertTrue((dr0 - dr1).nnz == 0)
dr0 = cc.dr_wrt(bb[5:8])
dr1 = cc.dr_wrt(bb)[:,5:8]
self.assertTrue((dr0 - dr1).nnz == 0)
def test_tensordot(self):
an = np.arange(60.).reshape(3, 4, 5)
bn = np.arange(24.).reshape(4, 3, 2)
cn = np.tensordot(an, bn, axes=([1, 0], [0, 1]))
ac = ch.arange(60.).reshape(3, 4, 5)
bc = ch.arange(24.).reshape(4, 3, 2)
cc = ch.tensordot(ac, bc, axes=([1, 0], [0, 1]))
cc.r
cc.dr_wrt(ac)
cc.dr_wrt(bc)
def test_dr_wrt_selection(self):
aa = ch.arange(10, 20)
bb = ch.arange(1, 11)
cc = aa * bb + aa + bb + 2
dr0 = cc.dr_wrt(aa[4:6])
dr1 = cc.dr_wrt(aa)[:, 4:6]
self.assertTrue((dr0 - dr1).nnz == 0)
dr0 = cc.dr_wrt(bb[5:8])
dr1 = cc.dr_wrt(bb)[:, 5:8]
self.assertTrue((dr0 - dr1).nnz == 0)
def test_nested_concatenate(self):
aa = ch.arange(3)
bb = ch.arange(4)
cc = ch.arange(5)
result = ch.concatenate((ch.concatenate((aa,bb)),cc))
self.assertTrue(result.m0 is aa)
self.assertTrue(result.m1 is bb)
self.assertTrue(result.m2 is cc)
self.assertTrue(result.dr_wrt(aa).nnz > 0)
self.assertTrue(result.dr_wrt(bb).nnz > 0)
self.assertTrue(result.dr_wrt(cc).nnz > 0)
def test_nested_concatenate(self):
aa = ch.arange(3)
bb = ch.arange(4)
cc = ch.arange(5)
result = ch.concatenate((ch.concatenate((aa, bb)), cc))
self.assertTrue(result.m0 is aa)
self.assertTrue(result.m1 is bb)
self.assertTrue(result.m2 is cc)
self.assertTrue(result.dr_wrt(aa).nnz > 0)
self.assertTrue(result.dr_wrt(bb).nnz > 0)
self.assertTrue(result.dr_wrt(cc).nnz > 0)