JayKimDevolved/deepseek

c011401 verified 11 months ago

33.3 kB

	from __future__ import division, absolute_import, print_function

	import sys
	from functools import reduce

	import numpy as np
	from numpy.ma import *
	from numpy.core.numerictypes import float32
	from numpy.ma.core import umath
	from numpy.testing import *

	pi = np.pi


	def eq(v, w, msg=''):
	result = allclose(v, w)
	if not result:
	print("""Not eq:%s
	%s
	----
	%s""" % (msg, str(v), str(w)))
	return result


	class TestMa(TestCase):

	def setUp(self):
	x = np.array([1., 1., 1., -2., pi/2.0, 4., 5., -10., 10., 1., 2., 3.])
	y = np.array([5., 0., 3., 2., -1., -4., 0., -10., 10., 1., 0., 3.])
	a10 = 10.
	m1 = [1, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0]
	m2 = [0, 0, 1, 0, 0, 1, 1, 0, 0, 0, 0, 1]
	xm = array(x, mask=m1)
	ym = array(y, mask=m2)
	z = np.array([-.5, 0., .5, .8])
	zm = array(z, mask=[0, 1, 0, 0])
	xf = np.where(m1, 1e+20, x)
	s = x.shape
	xm.set_fill_value(1e+20)
	self.d = (x, y, a10, m1, m2, xm, ym, z, zm, xf, s)

	def test_testBasic1d(self):
	# Test of basic array creation and properties in 1 dimension.
	(x, y, a10, m1, m2, xm, ym, z, zm, xf, s) = self.d
	self.assertFalse(isMaskedArray(x))
	self.assertTrue(isMaskedArray(xm))
	self.assertEqual(shape(xm), s)
	self.assertEqual(xm.shape, s)
	self.assertEqual(xm.dtype, x.dtype)
	self.assertEqual(xm.size, reduce(lambda x, y:x * y, s))
	self.assertEqual(count(xm), len(m1) - reduce(lambda x, y:x + y, m1))
	self.assertTrue(eq(xm, xf))
	self.assertTrue(eq(filled(xm, 1.e20), xf))
	self.assertTrue(eq(x, xm))

	def test_testBasic2d(self):
	# Test of basic array creation and properties in 2 dimensions.
	for s in [(4, 3), (6, 2)]:
	(x, y, a10, m1, m2, xm, ym, z, zm, xf, s) = self.d
	x.shape = s
	y.shape = s
	xm.shape = s
	ym.shape = s
	xf.shape = s

	self.assertFalse(isMaskedArray(x))
	self.assertTrue(isMaskedArray(xm))
	self.assertEqual(shape(xm), s)
	self.assertEqual(xm.shape, s)
	self.assertEqual(xm.size, reduce(lambda x, y:x * y, s))
	self.assertEqual(count(xm),
	len(m1) - reduce(lambda x, y:x + y, m1))
	self.assertTrue(eq(xm, xf))
	self.assertTrue(eq(filled(xm, 1.e20), xf))
	self.assertTrue(eq(x, xm))
	self.setUp()

	def test_testArithmetic(self):
	# Test of basic arithmetic.
	(x, y, a10, m1, m2, xm, ym, z, zm, xf, s) = self.d
	a2d = array([[1, 2], [0, 4]])
	a2dm = masked_array(a2d, [[0, 0], [1, 0]])
	self.assertTrue(eq(a2d * a2d, a2d * a2dm))
	self.assertTrue(eq(a2d + a2d, a2d + a2dm))
	self.assertTrue(eq(a2d - a2d, a2d - a2dm))
	for s in [(12,), (4, 3), (2, 6)]:
	x = x.reshape(s)
	y = y.reshape(s)
	xm = xm.reshape(s)
	ym = ym.reshape(s)
	xf = xf.reshape(s)
	self.assertTrue(eq(-x, -xm))
	self.assertTrue(eq(x + y, xm + ym))
	self.assertTrue(eq(x - y, xm - ym))
	self.assertTrue(eq(x * y, xm * ym))
	with np.errstate(divide='ignore', invalid='ignore'):
	self.assertTrue(eq(x / y, xm / ym))
	self.assertTrue(eq(a10 + y, a10 + ym))
	self.assertTrue(eq(a10 - y, a10 - ym))
	self.assertTrue(eq(a10 * y, a10 * ym))
	with np.errstate(divide='ignore', invalid='ignore'):
	self.assertTrue(eq(a10 / y, a10 / ym))
	self.assertTrue(eq(x + a10, xm + a10))
	self.assertTrue(eq(x - a10, xm - a10))
	self.assertTrue(eq(x * a10, xm * a10))
	self.assertTrue(eq(x / a10, xm / a10))
	self.assertTrue(eq(x 2, xm 2))
	self.assertTrue(eq(abs(x) 2.5, abs(xm) 2.5))
	self.assertTrue(eq(x y, xm ym))
	self.assertTrue(eq(np.add(x, y), add(xm, ym)))
	self.assertTrue(eq(np.subtract(x, y), subtract(xm, ym)))
	self.assertTrue(eq(np.multiply(x, y), multiply(xm, ym)))
	with np.errstate(divide='ignore', invalid='ignore'):
	self.assertTrue(eq(np.divide(x, y), divide(xm, ym)))

	def test_testMixedArithmetic(self):
	na = np.array([1])
	ma = array([1])
	self.assertTrue(isinstance(na + ma, MaskedArray))
	self.assertTrue(isinstance(ma + na, MaskedArray))

	def test_testUfuncs1(self):
	# Test various functions such as sin, cos.
	(x, y, a10, m1, m2, xm, ym, z, zm, xf, s) = self.d
	self.assertTrue(eq(np.cos(x), cos(xm)))
	self.assertTrue(eq(np.cosh(x), cosh(xm)))
	self.assertTrue(eq(np.sin(x), sin(xm)))
	self.assertTrue(eq(np.sinh(x), sinh(xm)))
	self.assertTrue(eq(np.tan(x), tan(xm)))
	self.assertTrue(eq(np.tanh(x), tanh(xm)))
	with np.errstate(divide='ignore', invalid='ignore'):
	self.assertTrue(eq(np.sqrt(abs(x)), sqrt(xm)))
	self.assertTrue(eq(np.log(abs(x)), log(xm)))
	self.assertTrue(eq(np.log10(abs(x)), log10(xm)))
	self.assertTrue(eq(np.exp(x), exp(xm)))
	self.assertTrue(eq(np.arcsin(z), arcsin(zm)))
	self.assertTrue(eq(np.arccos(z), arccos(zm)))
	self.assertTrue(eq(np.arctan(z), arctan(zm)))
	self.assertTrue(eq(np.arctan2(x, y), arctan2(xm, ym)))
	self.assertTrue(eq(np.absolute(x), absolute(xm)))
	self.assertTrue(eq(np.equal(x, y), equal(xm, ym)))
	self.assertTrue(eq(np.not_equal(x, y), not_equal(xm, ym)))
	self.assertTrue(eq(np.less(x, y), less(xm, ym)))
	self.assertTrue(eq(np.greater(x, y), greater(xm, ym)))
	self.assertTrue(eq(np.less_equal(x, y), less_equal(xm, ym)))
	self.assertTrue(eq(np.greater_equal(x, y), greater_equal(xm, ym)))
	self.assertTrue(eq(np.conjugate(x), conjugate(xm)))
	self.assertTrue(eq(np.concatenate((x, y)), concatenate((xm, ym))))
	self.assertTrue(eq(np.concatenate((x, y)), concatenate((x, y))))
	self.assertTrue(eq(np.concatenate((x, y)), concatenate((xm, y))))
	self.assertTrue(eq(np.concatenate((x, y, x)), concatenate((x, ym, x))))

	def test_xtestCount(self):
	# Test count
	ott = array([0., 1., 2., 3.], mask=[1, 0, 0, 0])
	self.assertTrue(count(ott).dtype.type is np.intp)
	self.assertEqual(3, count(ott))
	self.assertEqual(1, count(1))
	self.assertTrue(eq(0, array(1, mask=[1])))
	ott = ott.reshape((2, 2))
	self.assertTrue(count(ott).dtype.type is np.intp)
	assert_(isinstance(count(ott, 0), np.ndarray))
	self.assertTrue(count(ott).dtype.type is np.intp)
	self.assertTrue(eq(3, count(ott)))
	assert_(getmask(count(ott, 0)) is nomask)
	self.assertTrue(eq([1, 2], count(ott, 0)))

	def test_testMinMax(self):
	# Test minimum and maximum.
	(x, y, a10, m1, m2, xm, ym, z, zm, xf, s) = self.d
	xr = np.ravel(x) # max doesn't work if shaped
	xmr = ravel(xm)

	# true because of careful selection of data
	self.assertTrue(eq(max(xr), maximum(xmr)))
	self.assertTrue(eq(min(xr), minimum(xmr)))

	def test_testAddSumProd(self):
	# Test add, sum, product.
	(x, y, a10, m1, m2, xm, ym, z, zm, xf, s) = self.d
	self.assertTrue(eq(np.add.reduce(x), add.reduce(x)))
	self.assertTrue(eq(np.add.accumulate(x), add.accumulate(x)))
	self.assertTrue(eq(4, sum(array(4), axis=0)))
	self.assertTrue(eq(4, sum(array(4), axis=0)))
	self.assertTrue(eq(np.sum(x, axis=0), sum(x, axis=0)))
	self.assertTrue(eq(np.sum(filled(xm, 0), axis=0), sum(xm, axis=0)))
	self.assertTrue(eq(np.sum(x, 0), sum(x, 0)))
	self.assertTrue(eq(np.product(x, axis=0), product(x, axis=0)))
	self.assertTrue(eq(np.product(x, 0), product(x, 0)))
	self.assertTrue(eq(np.product(filled(xm, 1), axis=0),
	product(xm, axis=0)))
	if len(s) > 1:
	self.assertTrue(eq(np.concatenate((x, y), 1),
	concatenate((xm, ym), 1)))
	self.assertTrue(eq(np.add.reduce(x, 1), add.reduce(x, 1)))
	self.assertTrue(eq(np.sum(x, 1), sum(x, 1)))
	self.assertTrue(eq(np.product(x, 1), product(x, 1)))

	def test_testCI(self):
	# Test of conversions and indexing
	x1 = np.array([1, 2, 4, 3])
	x2 = array(x1, mask=[1, 0, 0, 0])
	x3 = array(x1, mask=[0, 1, 0, 1])
	x4 = array(x1)
	# test conversion to strings
	junk, garbage = str(x2), repr(x2)
	assert_(eq(np.sort(x1), sort(x2, fill_value=0)))
	# tests of indexing
	assert_(type(x2[1]) is type(x1[1]))
	assert_(x1[1] == x2[1])
	assert_(x2[0] is masked)
	assert_(eq(x1[2], x2[2]))
	assert_(eq(x1[2:5], x2[2:5]))
	assert_(eq(x1[:], x2[:]))
	assert_(eq(x1[1:], x3[1:]))
	x1[2] = 9
	x2[2] = 9
	assert_(eq(x1, x2))
	x1[1:3] = 99
	x2[1:3] = 99
	assert_(eq(x1, x2))
	x2[1] = masked
	assert_(eq(x1, x2))
	x2[1:3] = masked
	assert_(eq(x1, x2))
	x2[:] = x1
	x2[1] = masked
	assert_(allequal(getmask(x2), array([0, 1, 0, 0])))
	x3[:] = masked_array([1, 2, 3, 4], [0, 1, 1, 0])
	assert_(allequal(getmask(x3), array([0, 1, 1, 0])))
	x4[:] = masked_array([1, 2, 3, 4], [0, 1, 1, 0])
	assert_(allequal(getmask(x4), array([0, 1, 1, 0])))
	assert_(allequal(x4, array([1, 2, 3, 4])))
	x1 = np.arange(5) * 1.0
	x2 = masked_values(x1, 3.0)
	assert_(eq(x1, x2))
	assert_(allequal(array([0, 0, 0, 1, 0], MaskType), x2.mask))
	assert_(eq(3.0, x2.fill_value))
	x1 = array([1, 'hello', 2, 3], object)
	x2 = np.array([1, 'hello', 2, 3], object)
	s1 = x1[1]
	s2 = x2[1]
	self.assertEqual(type(s2), str)
	self.assertEqual(type(s1), str)
	self.assertEqual(s1, s2)
	assert_(x1[1:1].shape == (0,))

	def test_testCopySize(self):
	# Tests of some subtle points of copying and sizing.
	n = [0, 0, 1, 0, 0]
	m = make_mask(n)
	m2 = make_mask(m)
	self.assertTrue(m is m2)
	m3 = make_mask(m, copy=1)
	self.assertTrue(m is not m3)

	x1 = np.arange(5)
	y1 = array(x1, mask=m)
	self.assertTrue(y1._data is not x1)
	self.assertTrue(allequal(x1, y1._data))
	self.assertTrue(y1.mask is m)

	y1a = array(y1, copy=0)
	self.assertTrue(y1a.mask is y1.mask)

	y2 = array(x1, mask=m, copy=0)
	self.assertTrue(y2.mask is m)
	self.assertTrue(y2[2] is masked)
	y2[2] = 9
	self.assertTrue(y2[2] is not masked)
	self.assertTrue(y2.mask is not m)
	self.assertTrue(allequal(y2.mask, 0))

	y3 = array(x1 * 1.0, mask=m)
	self.assertTrue(filled(y3).dtype is (x1 * 1.0).dtype)

	x4 = arange(4)
	x4[2] = masked
	y4 = resize(x4, (8,))
	self.assertTrue(eq(concatenate([x4, x4]), y4))
	self.assertTrue(eq(getmask(y4), [0, 0, 1, 0, 0, 0, 1, 0]))
	y5 = repeat(x4, (2, 2, 2, 2), axis=0)
	self.assertTrue(eq(y5, [0, 0, 1, 1, 2, 2, 3, 3]))
	y6 = repeat(x4, 2, axis=0)
	self.assertTrue(eq(y5, y6))

	def test_testPut(self):
	# Test of put
	d = arange(5)
	n = [0, 0, 0, 1, 1]
	m = make_mask(n)
	x = array(d, mask=m)
	self.assertTrue(x[3] is masked)
	self.assertTrue(x[4] is masked)
	x[[1, 4]] = [10, 40]
	self.assertTrue(x.mask is not m)
	self.assertTrue(x[3] is masked)
	self.assertTrue(x[4] is not masked)
	self.assertTrue(eq(x, [0, 10, 2, -1, 40]))

	x = array(d, mask=m)
	x.put([0, 1, 2], [-1, 100, 200])
	self.assertTrue(eq(x, [-1, 100, 200, 0, 0]))
	self.assertTrue(x[3] is masked)
	self.assertTrue(x[4] is masked)

	def test_testMaPut(self):
	(x, y, a10, m1, m2, xm, ym, z, zm, xf, s) = self.d
	m = [1, 0, 0, 0, 0, 0, 1, 0, 0, 1, 0, 1]
	i = np.nonzero(m)[0]
	put(ym, i, zm)
	assert_(all(take(ym, i, axis=0) == zm))

	def test_testOddFeatures(self):
	# Test of other odd features
	x = arange(20)
	x = x.reshape(4, 5)
	x.flat[5] = 12
	assert_(x[1, 0] == 12)
	z = x + 10j * x
	assert_(eq(z.real, x))
	assert_(eq(z.imag, 10 * x))
	assert_(eq((z * conjugate(z)).real, 101 * x * x))
	z.imag[...] = 0.0

	x = arange(10)
	x[3] = masked
	assert_(str(x[3]) == str(masked))
	c = x >= 8
	assert_(count(where(c, masked, masked)) == 0)
	assert_(shape(where(c, masked, masked)) == c.shape)
	z = where(c, x, masked)
	assert_(z.dtype is x.dtype)
	assert_(z[3] is masked)
	assert_(z[4] is masked)
	assert_(z[7] is masked)
	assert_(z[8] is not masked)
	assert_(z[9] is not masked)
	assert_(eq(x, z))
	z = where(c, masked, x)
	assert_(z.dtype is x.dtype)
	assert_(z[3] is masked)
	assert_(z[4] is not masked)
	assert_(z[7] is not masked)
	assert_(z[8] is masked)
	assert_(z[9] is masked)
	z = masked_where(c, x)
	assert_(z.dtype is x.dtype)
	assert_(z[3] is masked)
	assert_(z[4] is not masked)
	assert_(z[7] is not masked)
	assert_(z[8] is masked)
	assert_(z[9] is masked)
	assert_(eq(x, z))
	x = array([1., 2., 3., 4., 5.])
	c = array([1, 1, 1, 0, 0])
	x[2] = masked
	z = where(c, x, -x)
	assert_(eq(z, [1., 2., 0., -4., -5]))
	c[0] = masked
	z = where(c, x, -x)
	assert_(eq(z, [1., 2., 0., -4., -5]))
	assert_(z[0] is masked)
	assert_(z[1] is not masked)
	assert_(z[2] is masked)
	assert_(eq(masked_where(greater(x, 2), x), masked_greater(x, 2)))
	assert_(eq(masked_where(greater_equal(x, 2), x),
	masked_greater_equal(x, 2)))
	assert_(eq(masked_where(less(x, 2), x), masked_less(x, 2)))
	assert_(eq(masked_where(less_equal(x, 2), x), masked_less_equal(x, 2)))
	assert_(eq(masked_where(not_equal(x, 2), x), masked_not_equal(x, 2)))
	assert_(eq(masked_where(equal(x, 2), x), masked_equal(x, 2)))
	assert_(eq(masked_where(not_equal(x, 2), x), masked_not_equal(x, 2)))
	assert_(eq(masked_inside(list(range(5)), 1, 3), [0, 199, 199, 199, 4]))
	assert_(eq(masked_outside(list(range(5)), 1, 3), [199, 1, 2, 3, 199]))
	assert_(eq(masked_inside(array(list(range(5)),
	mask=[1, 0, 0, 0, 0]), 1, 3).mask,
	[1, 1, 1, 1, 0]))
	assert_(eq(masked_outside(array(list(range(5)),
	mask=[0, 1, 0, 0, 0]), 1, 3).mask,
	[1, 1, 0, 0, 1]))
	assert_(eq(masked_equal(array(list(range(5)),
	mask=[1, 0, 0, 0, 0]), 2).mask,
	[1, 0, 1, 0, 0]))
	assert_(eq(masked_not_equal(array([2, 2, 1, 2, 1],
	mask=[1, 0, 0, 0, 0]), 2).mask,
	[1, 0, 1, 0, 1]))
	assert_(eq(masked_where([1, 1, 0, 0, 0], [1, 2, 3, 4, 5]),
	[99, 99, 3, 4, 5]))
	atest = ones((10, 10, 10), dtype=float32)
	btest = zeros(atest.shape, MaskType)
	ctest = masked_where(btest, atest)
	assert_(eq(atest, ctest))
	z = choose(c, (-x, x))
	assert_(eq(z, [1., 2., 0., -4., -5]))
	assert_(z[0] is masked)
	assert_(z[1] is not masked)
	assert_(z[2] is masked)
	x = arange(6)
	x[5] = masked
	y = arange(6) * 10
	y[2] = masked
	c = array([1, 1, 1, 0, 0, 0], mask=[1, 0, 0, 0, 0, 0])
	cm = c.filled(1)
	z = where(c, x, y)
	zm = where(cm, x, y)
	assert_(eq(z, zm))
	assert_(getmask(zm) is nomask)
	assert_(eq(zm, [0, 1, 2, 30, 40, 50]))
	z = where(c, masked, 1)
	assert_(eq(z, [99, 99, 99, 1, 1, 1]))
	z = where(c, 1, masked)
	assert_(eq(z, [99, 1, 1, 99, 99, 99]))

	def test_testMinMax2(self):
	# Test of minumum, maximum.
	assert_(eq(minimum([1, 2, 3], [4, 0, 9]), [1, 0, 3]))
	assert_(eq(maximum([1, 2, 3], [4, 0, 9]), [4, 2, 9]))
	x = arange(5)
	y = arange(5) - 2
	x[3] = masked
	y[0] = masked
	assert_(eq(minimum(x, y), where(less(x, y), x, y)))
	assert_(eq(maximum(x, y), where(greater(x, y), x, y)))
	assert_(minimum(x) == 0)
	assert_(maximum(x) == 4)

	def test_testTakeTransposeInnerOuter(self):
	# Test of take, transpose, inner, outer products
	x = arange(24)
	y = np.arange(24)
	x[5:6] = masked
	x = x.reshape(2, 3, 4)
	y = y.reshape(2, 3, 4)
	assert_(eq(np.transpose(y, (2, 0, 1)), transpose(x, (2, 0, 1))))
	assert_(eq(np.take(y, (2, 0, 1), 1), take(x, (2, 0, 1), 1)))
	assert_(eq(np.inner(filled(x, 0), filled(y, 0)),
	inner(x, y)))
	assert_(eq(np.outer(filled(x, 0), filled(y, 0)),
	outer(x, y)))
	y = array(['abc', 1, 'def', 2, 3], object)
	y[2] = masked
	t = take(y, [0, 3, 4])
	assert_(t[0] == 'abc')
	assert_(t[1] == 2)
	assert_(t[2] == 3)

	def test_testInplace(self):
	# Test of inplace operations and rich comparisons
	y = arange(10)

	x = arange(10)
	xm = arange(10)
	xm[2] = masked
	x += 1
	assert_(eq(x, y + 1))
	xm += 1
	assert_(eq(x, y + 1))

	x = arange(10)
	xm = arange(10)
	xm[2] = masked
	x -= 1
	assert_(eq(x, y - 1))
	xm -= 1
	assert_(eq(xm, y - 1))

	x = arange(10) * 1.0
	xm = arange(10) * 1.0
	xm[2] = masked
	x *= 2.0
	assert_(eq(x, y * 2))
	xm *= 2.0
	assert_(eq(xm, y * 2))

	x = arange(10) * 2
	xm = arange(10)
	xm[2] = masked
	x //= 2
	assert_(eq(x, y))
	xm //= 2
	assert_(eq(x, y))

	x = arange(10) * 1.0
	xm = arange(10) * 1.0
	xm[2] = masked
	x /= 2.0
	assert_(eq(x, y / 2.0))
	xm /= arange(10)
	assert_(eq(xm, ones((10,))))

	x = arange(10).astype(float32)
	xm = arange(10)
	xm[2] = masked
	x += 1.
	assert_(eq(x, y + 1.))

	def test_testPickle(self):
	# Test of pickling
	import pickle
	x = arange(12)
	x[4:10:2] = masked
	x = x.reshape(4, 3)
	s = pickle.dumps(x)
	y = pickle.loads(s)
	assert_(eq(x, y))

	def test_testMasked(self):
	# Test of masked element
	xx = arange(6)
	xx[1] = masked
	self.assertTrue(str(masked) == '--')
	self.assertTrue(xx[1] is masked)
	self.assertEqual(filled(xx[1], 0), 0)
	# don't know why these should raise an exception...
	#self.assertRaises(Exception, lambda x,y: x+y, masked, masked)
	#self.assertRaises(Exception, lambda x,y: x+y, masked, 2)
	#self.assertRaises(Exception, lambda x,y: x+y, masked, xx)
	#self.assertRaises(Exception, lambda x,y: x+y, xx, masked)

	def test_testAverage1(self):
	# Test of average.
	ott = array([0., 1., 2., 3.], mask=[1, 0, 0, 0])
	self.assertTrue(eq(2.0, average(ott, axis=0)))
	self.assertTrue(eq(2.0, average(ott, weights=[1., 1., 2., 1.])))
	result, wts = average(ott, weights=[1., 1., 2., 1.], returned=1)
	self.assertTrue(eq(2.0, result))
	self.assertTrue(wts == 4.0)
	ott[:] = masked
	self.assertTrue(average(ott, axis=0) is masked)
	ott = array([0., 1., 2., 3.], mask=[1, 0, 0, 0])
	ott = ott.reshape(2, 2)
	ott[:, 1] = masked
	self.assertTrue(eq(average(ott, axis=0), [2.0, 0.0]))
	self.assertTrue(average(ott, axis=1)[0] is masked)
	self.assertTrue(eq([2., 0.], average(ott, axis=0)))
	result, wts = average(ott, axis=0, returned=1)
	self.assertTrue(eq(wts, [1., 0.]))

	def test_testAverage2(self):
	# More tests of average.
	w1 = [0, 1, 1, 1, 1, 0]
	w2 = [[0, 1, 1, 1, 1, 0], [1, 0, 0, 0, 0, 1]]
	x = arange(6)
	self.assertTrue(allclose(average(x, axis=0), 2.5))
	self.assertTrue(allclose(average(x, axis=0, weights=w1), 2.5))
	y = array([arange(6), 2.0 * arange(6)])
	self.assertTrue(allclose(average(y, None),
	np.add.reduce(np.arange(6)) * 3. / 12.))
	self.assertTrue(allclose(average(y, axis=0), np.arange(6) * 3. / 2.))
	self.assertTrue(allclose(average(y, axis=1),
	[average(x, axis=0), average(x, axis=0)*2.0]))
	self.assertTrue(allclose(average(y, None, weights=w2), 20. / 6.))
	self.assertTrue(allclose(average(y, axis=0, weights=w2),
	[0., 1., 2., 3., 4., 10.]))
	self.assertTrue(allclose(average(y, axis=1),
	[average(x, axis=0), average(x, axis=0)*2.0]))
	m1 = zeros(6)
	m2 = [0, 0, 1, 1, 0, 0]
	m3 = [[0, 0, 1, 1, 0, 0], [0, 1, 1, 1, 1, 0]]
	m4 = ones(6)
	m5 = [0, 1, 1, 1, 1, 1]
	self.assertTrue(allclose(average(masked_array(x, m1), axis=0), 2.5))
	self.assertTrue(allclose(average(masked_array(x, m2), axis=0), 2.5))
	self.assertTrue(average(masked_array(x, m4), axis=0) is masked)
	self.assertEqual(average(masked_array(x, m5), axis=0), 0.0)
	self.assertEqual(count(average(masked_array(x, m4), axis=0)), 0)
	z = masked_array(y, m3)
	self.assertTrue(allclose(average(z, None), 20. / 6.))
	self.assertTrue(allclose(average(z, axis=0),
	[0., 1., 99., 99., 4.0, 7.5]))
	self.assertTrue(allclose(average(z, axis=1), [2.5, 5.0]))
	self.assertTrue(allclose(average(z, axis=0, weights=w2),
	[0., 1., 99., 99., 4.0, 10.0]))

	a = arange(6)
	b = arange(6) * 3
	r1, w1 = average([[a, b], [b, a]], axis=1, returned=1)
	self.assertEqual(shape(r1), shape(w1))
	self.assertEqual(r1.shape, w1.shape)
	r2, w2 = average(ones((2, 2, 3)), axis=0, weights=[3, 1], returned=1)
	self.assertEqual(shape(w2), shape(r2))
	r2, w2 = average(ones((2, 2, 3)), returned=1)
	self.assertEqual(shape(w2), shape(r2))
	r2, w2 = average(ones((2, 2, 3)), weights=ones((2, 2, 3)), returned=1)
	self.assertTrue(shape(w2) == shape(r2))
	a2d = array([[1, 2], [0, 4]], float)
	a2dm = masked_array(a2d, [[0, 0], [1, 0]])
	a2da = average(a2d, axis=0)
	self.assertTrue(eq(a2da, [0.5, 3.0]))
	a2dma = average(a2dm, axis=0)
	self.assertTrue(eq(a2dma, [1.0, 3.0]))
	a2dma = average(a2dm, axis=None)
	self.assertTrue(eq(a2dma, 7. / 3.))
	a2dma = average(a2dm, axis=1)
	self.assertTrue(eq(a2dma, [1.5, 4.0]))

	def test_testToPython(self):
	self.assertEqual(1, int(array(1)))
	self.assertEqual(1.0, float(array(1)))
	self.assertEqual(1, int(array([[[1]]])))
	self.assertEqual(1.0, float(array([[1]])))
	self.assertRaises(TypeError, float, array([1, 1]))
	self.assertRaises(ValueError, bool, array([0, 1]))
	self.assertRaises(ValueError, bool, array([0, 0], mask=[0, 1]))

	def test_testScalarArithmetic(self):
	xm = array(0, mask=1)
	#TODO FIXME: Find out what the following raises a warning in r8247
	with np.errstate(divide='ignore'):
	self.assertTrue((1 / array(0)).mask)
	self.assertTrue((1 + xm).mask)
	self.assertTrue((-xm).mask)
	self.assertTrue((-xm).mask)
	self.assertTrue(maximum(xm, xm).mask)
	self.assertTrue(minimum(xm, xm).mask)
	self.assertTrue(xm.filled().dtype is xm._data.dtype)
	x = array(0, mask=0)
	self.assertTrue(x.filled() == x._data)
	self.assertEqual(str(xm), str(masked_print_option))

	def test_testArrayMethods(self):
	a = array([1, 3, 2])
	self.assertTrue(eq(a.any(), a._data.any()))
	self.assertTrue(eq(a.all(), a._data.all()))
	self.assertTrue(eq(a.argmax(), a._data.argmax()))
	self.assertTrue(eq(a.argmin(), a._data.argmin()))
	self.assertTrue(eq(a.choose(0, 1, 2, 3, 4),
	a._data.choose(0, 1, 2, 3, 4)))
	self.assertTrue(eq(a.compress([1, 0, 1]), a._data.compress([1, 0, 1])))
	self.assertTrue(eq(a.conj(), a._data.conj()))
	self.assertTrue(eq(a.conjugate(), a._data.conjugate()))
	m = array([[1, 2], [3, 4]])
	self.assertTrue(eq(m.diagonal(), m._data.diagonal()))
	self.assertTrue(eq(a.sum(), a._data.sum()))
	self.assertTrue(eq(a.take([1, 2]), a._data.take([1, 2])))
	self.assertTrue(eq(m.transpose(), m._data.transpose()))

	def test_testArrayAttributes(self):
	a = array([1, 3, 2])
	self.assertEqual(a.ndim, 1)

	def test_testAPI(self):
	self.assertFalse([m for m in dir(np.ndarray)
	if m not in dir(MaskedArray) and
	not m.startswith('_')])

	def test_testSingleElementSubscript(self):
	a = array([1, 3, 2])
	b = array([1, 3, 2], mask=[1, 0, 1])
	self.assertEqual(a[0].shape, ())
	self.assertEqual(b[0].shape, ())
	self.assertEqual(b[1].shape, ())


	class TestUfuncs(TestCase):
	def setUp(self):
	self.d = (array([1.0, 0, -1, pi / 2] * 2, mask=[0, 1] + [0] * 6),
	array([1.0, 0, -1, pi / 2] * 2, mask=[1, 0] + [0] * 6),)

	def test_testUfuncRegression(self):
	f_invalid_ignore = [
	'sqrt', 'arctanh', 'arcsin', 'arccos',
	'arccosh', 'arctanh', 'log', 'log10', 'divide',
	'true_divide', 'floor_divide', 'remainder', 'fmod']
	for f in ['sqrt', 'log', 'log10', 'exp', 'conjugate',
	'sin', 'cos', 'tan',
	'arcsin', 'arccos', 'arctan',
	'sinh', 'cosh', 'tanh',
	'arcsinh',
	'arccosh',
	'arctanh',
	'absolute', 'fabs', 'negative',
	# 'nonzero', 'around',
	'floor', 'ceil',
	# 'sometrue', 'alltrue',
	'logical_not',
	'add', 'subtract', 'multiply',
	'divide', 'true_divide', 'floor_divide',
	'remainder', 'fmod', 'hypot', 'arctan2',
	'equal', 'not_equal', 'less_equal', 'greater_equal',
	'less', 'greater',
	'logical_and', 'logical_or', 'logical_xor']:
	try:
	uf = getattr(umath, f)
	except AttributeError:
	uf = getattr(fromnumeric, f)
	mf = getattr(np.ma, f)
	args = self.d[:uf.nin]
	with np.errstate():
	if f in f_invalid_ignore:
	np.seterr(invalid='ignore')
	if f in ['arctanh', 'log', 'log10']:
	np.seterr(divide='ignore')
	ur = uf(*args)
	mr = mf(*args)
	self.assertTrue(eq(ur.filled(0), mr.filled(0), f))
	self.assertTrue(eqmask(ur.mask, mr.mask))

	def test_reduce(self):
	a = self.d[0]
	self.assertFalse(alltrue(a, axis=0))
	self.assertTrue(sometrue(a, axis=0))
	self.assertEqual(sum(a[:3], axis=0), 0)
	self.assertEqual(product(a, axis=0), 0)

	def test_minmax(self):
	a = arange(1, 13).reshape(3, 4)
	amask = masked_where(a < 5, a)
	self.assertEqual(amask.max(), a.max())
	self.assertEqual(amask.min(), 5)
	self.assertTrue((amask.max(0) == a.max(0)).all())
	self.assertTrue((amask.min(0) == [5, 6, 7, 8]).all())
	self.assertTrue(amask.max(1)[0].mask)
	self.assertTrue(amask.min(1)[0].mask)

	def test_nonzero(self):
	for t in "?bhilqpBHILQPfdgFDGO":
	x = array([1, 0, 2, 0], mask=[0, 0, 1, 1])
	self.assertTrue(eq(nonzero(x), [0]))


	class TestArrayMethods(TestCase):

	def setUp(self):
	x = np.array([8.375, 7.545, 8.828, 8.5, 1.757, 5.928,
	8.43, 7.78, 9.865, 5.878, 8.979, 4.732,
	3.012, 6.022, 5.095, 3.116, 5.238, 3.957,
	6.04, 9.63, 7.712, 3.382, 4.489, 6.479,
	7.189, 9.645, 5.395, 4.961, 9.894, 2.893,
	7.357, 9.828, 6.272, 3.758, 6.693, 0.993])
	X = x.reshape(6, 6)
	XX = x.reshape(3, 2, 2, 3)

	m = np.array([0, 1, 0, 1, 0, 0,
	1, 0, 1, 1, 0, 1,
	0, 0, 0, 1, 0, 1,
	0, 0, 0, 1, 1, 1,
	1, 0, 0, 1, 0, 0,
	0, 0, 1, 0, 1, 0])
	mx = array(data=x, mask=m)
	mX = array(data=X, mask=m.reshape(X.shape))
	mXX = array(data=XX, mask=m.reshape(XX.shape))

	self.d = (x, X, XX, m, mx, mX, mXX)

	#------------------------------------------------------
	def test_trace(self):
	(x, X, XX, m, mx, mX, mXX,) = self.d
	mXdiag = mX.diagonal()
	self.assertEqual(mX.trace(), mX.diagonal().compressed().sum())
	self.assertTrue(eq(mX.trace(),
	X.trace() - sum(mXdiag.mask * X.diagonal(),
	axis=0)))

	def test_clip(self):
	(x, X, XX, m, mx, mX, mXX,) = self.d
	clipped = mx.clip(2, 8)
	self.assertTrue(eq(clipped.mask, mx.mask))
	self.assertTrue(eq(clipped._data, x.clip(2, 8)))
	self.assertTrue(eq(clipped._data, mx._data.clip(2, 8)))

	def test_ptp(self):
	(x, X, XX, m, mx, mX, mXX,) = self.d
	(n, m) = X.shape
	self.assertEqual(mx.ptp(), mx.compressed().ptp())
	rows = np.zeros(n, np.float_)
	cols = np.zeros(m, np.float_)
	for k in range(m):
	cols[k] = mX[:, k].compressed().ptp()
	for k in range(n):
	rows[k] = mX[k].compressed().ptp()
	self.assertTrue(eq(mX.ptp(0), cols))
	self.assertTrue(eq(mX.ptp(1), rows))

	def test_swapaxes(self):
	(x, X, XX, m, mx, mX, mXX,) = self.d
	mXswapped = mX.swapaxes(0, 1)
	self.assertTrue(eq(mXswapped[-1], mX[:, -1]))
	mXXswapped = mXX.swapaxes(0, 2)
	self.assertEqual(mXXswapped.shape, (2, 2, 3, 3))

	def test_cumprod(self):
	(x, X, XX, m, mx, mX, mXX,) = self.d
	mXcp = mX.cumprod(0)
	self.assertTrue(eq(mXcp._data, mX.filled(1).cumprod(0)))
	mXcp = mX.cumprod(1)
	self.assertTrue(eq(mXcp._data, mX.filled(1).cumprod(1)))

	def test_cumsum(self):
	(x, X, XX, m, mx, mX, mXX,) = self.d
	mXcp = mX.cumsum(0)
	self.assertTrue(eq(mXcp._data, mX.filled(0).cumsum(0)))
	mXcp = mX.cumsum(1)
	self.assertTrue(eq(mXcp._data, mX.filled(0).cumsum(1)))

	def test_varstd(self):
	(x, X, XX, m, mx, mX, mXX,) = self.d
	self.assertTrue(eq(mX.var(axis=None), mX.compressed().var()))
	self.assertTrue(eq(mX.std(axis=None), mX.compressed().std()))
	self.assertTrue(eq(mXX.var(axis=3).shape, XX.var(axis=3).shape))
	self.assertTrue(eq(mX.var().shape, X.var().shape))
	(mXvar0, mXvar1) = (mX.var(axis=0), mX.var(axis=1))
	for k in range(6):
	self.assertTrue(eq(mXvar1[k], mX[k].compressed().var()))
	self.assertTrue(eq(mXvar0[k], mX[:, k].compressed().var()))
	self.assertTrue(eq(np.sqrt(mXvar0[k]),
	mX[:, k].compressed().std()))


	def eqmask(m1, m2):
	if m1 is nomask:
	return m2 is nomask
	if m2 is nomask:
	return m1 is nomask
	return (m1 == m2).all()

	#def timingTest():
	# for f in [testf, testinplace]:
	# for n in [1000,10000,50000]:
	# t = testta(n, f)
	# t1 = testtb(n, f)
	# t2 = testtc(n, f)
	# print f.test_name
	# print """\
	#n = %7d
	#numpy time (ms) %6.1f
	#MA maskless ratio %6.1f
	#MA masked ratio %6.1f
	#""" % (n, t*1000.0, t1/t, t2/t)

	#def testta(n, f):
	# x=np.arange(n) + 1.0
	# tn0 = time.time()
	# z = f(x)
	# return time.time() - tn0

	#def testtb(n, f):
	# x=arange(n) + 1.0
	# tn0 = time.time()
	# z = f(x)
	# return time.time() - tn0

	#def testtc(n, f):
	# x=arange(n) + 1.0
	# x[0] = masked
	# tn0 = time.time()
	# z = f(x)
	# return time.time() - tn0

	#def testf(x):
	# for i in range(25):
	# y = x *2 + 2.0 x - 1.0
	# w = x **2 + 1.0
	# z = (y / w) ** 2
	# return z
	#testf.test_name = 'Simple arithmetic'

	#def testinplace(x):
	# for i in range(25):
	# y = x**2
	# y += 2.0*x
	# y -= 1.0
	# y /= x
	# return y
	#testinplace.test_name = 'Inplace operations'

	if __name__ == "__main__":
	run_module_suite()