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import itertools
import numpy as np
from six.moves import xrange
from dtcwt.utils import *
def test_complex_type_for_complex():
assert np.issubsctype(appropriate_complex_type_for(np.zeros((2,3), np.complex64)), np.complex64)
assert np.issubsctype(appropriate_complex_type_for(np.zeros((2,3), np.complex128)), np.complex128)
def test_complex_type_for_float():
assert np.issubsctype(appropriate_complex_type_for(np.zeros((2,3), np.float32)), np.complex64)
assert np.issubsctype(appropriate_complex_type_for(np.zeros((2,3), np.float64)), np.complex128)
def test_draw_circ():
c = drawcirc(20, 4, -4, -5, 50)
assert c.shape == (50, 50)
assert c[45,45] == 0
assert c[25,25] == 1
def test_draw_edge():
e = drawedge(20, (20,20), 4, 50)
assert e.shape == (50, 50)
def test_stacked_2d_matrix_vector_product():
nr, nc = (30, 20)
mr, mc = (3, 4)
# Generate a random stack of 2d matrices and 2d vectors
matrices = np.random.rand(nr, nc, mr, mc)
vectors = np.random.rand(nr, nc, mc)
# Compute product to test
out = stacked_2d_matrix_vector_prod(matrices, vectors)
# Check output shape is what we expect
assert out.shape == (nr, nc, mr)
# Check each product
for r, c in itertools.product(xrange(nr), xrange(nc)):
m = matrices[r, c, :, :]
v = vectors[r, c, :]
o = out[r, c, :]
assert m.shape == (mr, mc)
assert v.shape == (mc,)
assert o.shape == (mr,)
gold = m.dot(v)
max_delta = np.abs(gold - o).max()
assert max_delta < 1e-8
def test_stacked_2d_vector_matrix_product():
nr, nc = (30, 20)
mr, mc = (3, 4)
# Generate a random stack of 2d matrices and 2d vectors
matrices = np.random.rand(nr, nc, mr, mc)
vectors = np.random.rand(nr, nc, mr)
# Compute product to test
out = stacked_2d_vector_matrix_prod(vectors, matrices)
# Check output shape is what we expect
assert out.shape == (nr, nc, mc)
# Check each product
for r, c in itertools.product(xrange(nr), xrange(nc)):
m = matrices[r, c, :, :]
v = vectors[r, c, :]
o = out[r, c, :]
assert m.shape == (mr, mc)
assert v.shape == (mr,)
assert o.shape == (mc,)
gold = v.dot(m)
max_delta = np.abs(gold - o).max()
assert max_delta < 1e-8
def test_stacked_2d_matrix_matrix_product():
nr, nc = (30, 20)
mr1, k, mc2 = (3, 4, 5)
# Generate a random stack of 2d matrices and 2d vectors
matrices1 = np.random.rand(nr, nc, mr1, k)
matrices2 = np.random.rand(nr, nc, k, mc2)
# Compute product to test
out = stacked_2d_matrix_matrix_prod(matrices1, matrices2)
# Check output shape is what we expect
assert out.shape == (nr, nc, mr1, mc2)
# Check each product
for r, c in itertools.product(xrange(nr), xrange(nc)):
m1 = matrices1[r, c, :, :]
m2 = matrices2[r, c, :, :]
o = out[r, c, :, :]
assert m1.shape == (mr1, k)
assert m2.shape == (k, mc2)
assert o.shape == (mr1, mc2)
gold = m1.dot(m2)
max_delta = np.abs(gold - o).max()
assert max_delta < 1e-8
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