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"""Test functions for matrix module
"""
from __future__ import division, absolute_import, print_function
from numpy.testing import *
from numpy import ( arange, rot90, add, fliplr, flipud, zeros, ones, eye,
array, diag, histogram2d, tri, mask_indices, triu_indices,
triu_indices_from, tril_indices, tril_indices_from )
import numpy as np
from numpy.compat import asbytes, asbytes_nested
def get_mat(n):
data = arange(n)
data = add.outer(data,data)
return data
class TestEye(TestCase):
def test_basic(self):
assert_equal(eye(4),array([[1,0,0,0],
[0,1,0,0],
[0,0,1,0],
[0,0,0,1]]))
assert_equal(eye(4,dtype='f'),array([[1,0,0,0],
[0,1,0,0],
[0,0,1,0],
[0,0,0,1]],'f'))
assert_equal(eye(3) == 1, eye(3,dtype=bool))
def test_diag(self):
assert_equal(eye(4,k=1),array([[0,1,0,0],
[0,0,1,0],
[0,0,0,1],
[0,0,0,0]]))
assert_equal(eye(4,k=-1),array([[0,0,0,0],
[1,0,0,0],
[0,1,0,0],
[0,0,1,0]]))
def test_2d(self):
assert_equal(eye(4,3),array([[1,0,0],
[0,1,0],
[0,0,1],
[0,0,0]]))
assert_equal(eye(3,4),array([[1,0,0,0],
[0,1,0,0],
[0,0,1,0]]))
def test_diag2d(self):
assert_equal(eye(3,4,k=2),array([[0,0,1,0],
[0,0,0,1],
[0,0,0,0]]))
assert_equal(eye(4,3,k=-2),array([[0,0,0],
[0,0,0],
[1,0,0],
[0,1,0]]))
def test_eye_bounds(self):
assert_equal(eye(2, 2, 1), [[0, 1], [0, 0]])
assert_equal(eye(2, 2, -1), [[0, 0], [1, 0]])
assert_equal(eye(2, 2, 2), [[0, 0], [0, 0]])
assert_equal(eye(2, 2, -2), [[0, 0], [0, 0]])
assert_equal(eye(3, 2, 2), [[0, 0], [0, 0], [0, 0]])
assert_equal(eye(3, 2, 1), [[0, 1], [0, 0], [0, 0]])
assert_equal(eye(3, 2, -1), [[0, 0], [1, 0], [0, 1]])
assert_equal(eye(3, 2, -2), [[0, 0], [0, 0], [1, 0]])
assert_equal(eye(3, 2, -3), [[0, 0], [0, 0], [0, 0]])
def test_strings(self):
assert_equal(eye(2, 2, dtype='S3'),
asbytes_nested([['1', ''], ['', '1']]))
def test_bool(self):
assert_equal(eye(2, 2, dtype=bool), [[True, False], [False, True]])
class TestDiag(TestCase):
def test_vector(self):
vals = (100 * arange(5)).astype('l')
b = zeros((5, 5))
for k in range(5):
b[k, k] = vals[k]
assert_equal(diag(vals), b)
b = zeros((7, 7))
c = b.copy()
for k in range(5):
b[k, k + 2] = vals[k]
c[k + 2, k] = vals[k]
assert_equal(diag(vals, k=2), b)
assert_equal(diag(vals, k=-2), c)
def test_matrix(self, vals=None):
if vals is None:
vals = (100 * get_mat(5) + 1).astype('l')
b = zeros((5,))
for k in range(5):
b[k] = vals[k,k]
assert_equal(diag(vals), b)
b = b * 0
for k in range(3):
b[k] = vals[k, k + 2]
assert_equal(diag(vals, 2), b[:3])
for k in range(3):
b[k] = vals[k + 2, k]
assert_equal(diag(vals, -2), b[:3])
def test_fortran_order(self):
vals = array((100 * get_mat(5) + 1), order='F', dtype='l')
self.test_matrix(vals)
def test_diag_bounds(self):
A = [[1, 2], [3, 4], [5, 6]]
assert_equal(diag(A, k=2), [])
assert_equal(diag(A, k=1), [2])
assert_equal(diag(A, k=0), [1, 4])
assert_equal(diag(A, k=-1), [3, 6])
assert_equal(diag(A, k=-2), [5])
assert_equal(diag(A, k=-3), [])
def test_failure(self):
self.assertRaises(ValueError, diag, [[[1]]])
class TestFliplr(TestCase):
def test_basic(self):
self.assertRaises(ValueError, fliplr, ones(4))
a = get_mat(4)
b = a[:,::-1]
assert_equal(fliplr(a),b)
a = [[0,1,2],
[3,4,5]]
b = [[2,1,0],
[5,4,3]]
assert_equal(fliplr(a),b)
class TestFlipud(TestCase):
def test_basic(self):
a = get_mat(4)
b = a[::-1,:]
assert_equal(flipud(a),b)
a = [[0,1,2],
[3,4,5]]
b = [[3,4,5],
[0,1,2]]
assert_equal(flipud(a),b)
class TestRot90(TestCase):
def test_basic(self):
self.assertRaises(ValueError, rot90, ones(4))
a = [[0,1,2],
[3,4,5]]
b1 = [[2,5],
[1,4],
[0,3]]
b2 = [[5,4,3],
[2,1,0]]
b3 = [[3,0],
[4,1],
[5,2]]
b4 = [[0,1,2],
[3,4,5]]
for k in range(-3,13,4):
assert_equal(rot90(a,k=k),b1)
for k in range(-2,13,4):
assert_equal(rot90(a,k=k),b2)
for k in range(-1,13,4):
assert_equal(rot90(a,k=k),b3)
for k in range(0,13,4):
assert_equal(rot90(a,k=k),b4)
def test_axes(self):
a = ones((50,40,3))
assert_equal(rot90(a).shape,(40,50,3))
class TestHistogram2d(TestCase):
def test_simple(self):
x = array([ 0.41702200, 0.72032449, 0.00011437481, 0.302332573, 0.146755891])
y = array([ 0.09233859, 0.18626021, 0.34556073, 0.39676747, 0.53881673])
xedges = np.linspace(0,1,10)
yedges = np.linspace(0,1,10)
H = histogram2d(x, y, (xedges, yedges))[0]
answer = array([[0, 0, 0, 1, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 1, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0],
[1, 0, 1, 0, 0, 0, 0, 0, 0],
[0, 1, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0]])
assert_array_equal(H.T, answer)
H = histogram2d(x, y, xedges)[0]
assert_array_equal(H.T, answer)
H,xedges,yedges = histogram2d(list(range(10)),list(range(10)))
assert_array_equal(H, eye(10,10))
assert_array_equal(xedges, np.linspace(0,9,11))
assert_array_equal(yedges, np.linspace(0,9,11))
def test_asym(self):
x = array([1, 1, 2, 3, 4, 4, 4, 5])
y = array([1, 3, 2, 0, 1, 2, 3, 4])
H, xed, yed = histogram2d(x,y, (6, 5), range = [[0,6],[0,5]], normed=True)
answer = array([[0.,0,0,0,0],
[0,1,0,1,0],
[0,0,1,0,0],
[1,0,0,0,0],
[0,1,1,1,0],
[0,0,0,0,1]])
assert_array_almost_equal(H, answer/8., 3)
assert_array_equal(xed, np.linspace(0,6,7))
assert_array_equal(yed, np.linspace(0,5,6))
def test_norm(self):
x = array([1,2,3,1,2,3,1,2,3])
y = array([1,1,1,2,2,2,3,3,3])
H, xed, yed = histogram2d(x,y,[[1,2,3,5], [1,2,3,5]], normed=True)
answer=array([[1,1,.5],
[1,1,.5],
[.5,.5,.25]])/9.
assert_array_almost_equal(H, answer, 3)
def test_all_outliers(self):
r = rand(100)+1.
H, xed, yed = histogram2d(r, r, (4, 5), range=([0,1], [0,1]))
assert_array_equal(H, 0)
def test_empty(self):
a, edge1, edge2 = histogram2d([],[], bins=([0,1],[0,1]))
assert_array_max_ulp(a, array([[ 0.]]))
a, edge1, edge2 = histogram2d([], [], bins=4)
assert_array_max_ulp(a, np.zeros((4, 4)))
class TestTri(TestCase):
def test_dtype(self):
out = array([[1,0,0],
[1,1,0],
[1,1,1]])
assert_array_equal(tri(3),out)
assert_array_equal(tri(3,dtype=bool),out.astype(bool))
def test_tril_triu():
for dtype in np.typecodes['AllFloat'] + np.typecodes['AllInteger']:
a = np.ones((2, 2), dtype=dtype)
b = np.tril(a)
c = np.triu(a)
assert_array_equal(b, [[1, 0], [1, 1]])
assert_array_equal(c, b.T)
# should return the same dtype as the original array
assert_equal(b.dtype, a.dtype)
assert_equal(c.dtype, a.dtype)
def test_mask_indices():
# simple test without offset
iu = mask_indices(3, np.triu)
a = np.arange(9).reshape(3, 3)
yield (assert_array_equal, a[iu], array([0, 1, 2, 4, 5, 8]))
# Now with an offset
iu1 = mask_indices(3, np.triu, 1)
yield (assert_array_equal, a[iu1], array([1, 2, 5]))
def test_tril_indices():
# indices without and with offset
il1 = tril_indices(4)
il2 = tril_indices(4, 2)
a = np.array([[1, 2, 3, 4],
[5, 6, 7, 8],
[9, 10, 11, 12],
[13, 14, 15, 16]])
# indexing:
yield (assert_array_equal, a[il1],
array([ 1, 5, 6, 9, 10, 11, 13, 14, 15, 16]) )
# And for assigning values:
a[il1] = -1
yield (assert_array_equal, a,
array([[-1, 2, 3, 4],
[-1, -1, 7, 8],
[-1, -1, -1, 12],
[-1, -1, -1, -1]]) )
# These cover almost the whole array (two diagonals right of the main one):
a[il2] = -10
yield (assert_array_equal, a,
array([[-10, -10, -10, 4],
[-10, -10, -10, -10],
[-10, -10, -10, -10],
[-10, -10, -10, -10]]) )
class TestTriuIndices(object):
def test_triu_indices(self):
iu1 = triu_indices(4)
iu2 = triu_indices(4, 2)
a = np.array([[1, 2, 3, 4],
[5, 6, 7, 8],
[9, 10, 11, 12],
[13, 14, 15, 16]])
# Both for indexing:
yield (assert_array_equal, a[iu1],
array([1, 2, 3, 4, 6, 7, 8, 11, 12, 16]))
# And for assigning values:
a[iu1] = -1
yield (assert_array_equal, a,
array([[-1, -1, -1, -1],
[ 5, -1, -1, -1],
[ 9, 10, -1, -1],
[13, 14, 15, -1]]) )
# These cover almost the whole array (two diagonals right of the main one):
a[iu2] = -10
yield ( assert_array_equal, a,
array([[ -1, -1, -10, -10],
[ 5, -1, -1, -10],
[ 9, 10, -1, -1],
[ 13, 14, 15, -1]]) )
class TestTrilIndicesFrom(object):
def test_exceptions(self):
assert_raises(ValueError, tril_indices_from, np.ones((2,)))
assert_raises(ValueError, tril_indices_from, np.ones((2,2,2)))
assert_raises(ValueError, tril_indices_from, np.ones((2,3)))
class TestTriuIndicesFrom(object):
def test_exceptions(self):
assert_raises(ValueError, triu_indices_from, np.ones((2,)))
assert_raises(ValueError, triu_indices_from, np.ones((2,2,2)))
assert_raises(ValueError, triu_indices_from, np.ones((2,3)))
if __name__ == "__main__":
run_module_suite()
|
