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| from functools import reduce | |
| import numpy as np | |
| import numpy.core.umath as umath | |
| import numpy.core.fromnumeric as fromnumeric | |
| from numpy.testing import ( | |
| assert_, assert_raises, assert_equal, | |
| ) | |
| from numpy.ma import ( | |
| MaskType, MaskedArray, absolute, add, all, allclose, allequal, alltrue, | |
| arange, arccos, arcsin, arctan, arctan2, array, average, choose, | |
| concatenate, conjugate, cos, cosh, count, divide, equal, exp, filled, | |
| getmask, greater, greater_equal, inner, isMaskedArray, less, | |
| less_equal, log, log10, make_mask, masked, masked_array, masked_equal, | |
| masked_greater, masked_greater_equal, masked_inside, masked_less, | |
| masked_less_equal, masked_not_equal, masked_outside, | |
| masked_print_option, masked_values, masked_where, maximum, minimum, | |
| multiply, nomask, nonzero, not_equal, ones, outer, product, put, ravel, | |
| repeat, resize, shape, sin, sinh, sometrue, sort, sqrt, subtract, sum, | |
| take, tan, tanh, transpose, where, zeros, | |
| ) | |
| from numpy.compat import pickle | |
| pi = np.pi | |
| def eq(v, w, msg=''): | |
| result = allclose(v, w) | |
| if not result: | |
| print(f'Not eq:{msg}\n{v}\n----{w}') | |
| return result | |
| class TestMa: | |
| 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 | |
| assert_(not isMaskedArray(x)) | |
| assert_(isMaskedArray(xm)) | |
| assert_equal(shape(xm), s) | |
| assert_equal(xm.shape, s) | |
| assert_equal(xm.dtype, x.dtype) | |
| assert_equal(xm.size, reduce(lambda x, y:x * y, s)) | |
| assert_equal(count(xm), len(m1) - reduce(lambda x, y:x + y, m1)) | |
| assert_(eq(xm, xf)) | |
| assert_(eq(filled(xm, 1.e20), xf)) | |
| assert_(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 | |
| assert_(not isMaskedArray(x)) | |
| assert_(isMaskedArray(xm)) | |
| assert_equal(shape(xm), s) | |
| assert_equal(xm.shape, s) | |
| assert_equal(xm.size, reduce(lambda x, y:x * y, s)) | |
| assert_equal(count(xm), | |
| len(m1) - reduce(lambda x, y:x + y, m1)) | |
| assert_(eq(xm, xf)) | |
| assert_(eq(filled(xm, 1.e20), xf)) | |
| assert_(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]]) | |
| assert_(eq(a2d * a2d, a2d * a2dm)) | |
| assert_(eq(a2d + a2d, a2d + a2dm)) | |
| assert_(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) | |
| assert_(eq(-x, -xm)) | |
| assert_(eq(x + y, xm + ym)) | |
| assert_(eq(x - y, xm - ym)) | |
| assert_(eq(x * y, xm * ym)) | |
| with np.errstate(divide='ignore', invalid='ignore'): | |
| assert_(eq(x / y, xm / ym)) | |
| assert_(eq(a10 + y, a10 + ym)) | |
| assert_(eq(a10 - y, a10 - ym)) | |
| assert_(eq(a10 * y, a10 * ym)) | |
| with np.errstate(divide='ignore', invalid='ignore'): | |
| assert_(eq(a10 / y, a10 / ym)) | |
| assert_(eq(x + a10, xm + a10)) | |
| assert_(eq(x - a10, xm - a10)) | |
| assert_(eq(x * a10, xm * a10)) | |
| assert_(eq(x / a10, xm / a10)) | |
| assert_(eq(x ** 2, xm ** 2)) | |
| assert_(eq(abs(x) ** 2.5, abs(xm) ** 2.5)) | |
| assert_(eq(x ** y, xm ** ym)) | |
| assert_(eq(np.add(x, y), add(xm, ym))) | |
| assert_(eq(np.subtract(x, y), subtract(xm, ym))) | |
| assert_(eq(np.multiply(x, y), multiply(xm, ym))) | |
| with np.errstate(divide='ignore', invalid='ignore'): | |
| assert_(eq(np.divide(x, y), divide(xm, ym))) | |
| def test_testMixedArithmetic(self): | |
| na = np.array([1]) | |
| ma = array([1]) | |
| assert_(isinstance(na + ma, MaskedArray)) | |
| assert_(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 | |
| assert_(eq(np.cos(x), cos(xm))) | |
| assert_(eq(np.cosh(x), cosh(xm))) | |
| assert_(eq(np.sin(x), sin(xm))) | |
| assert_(eq(np.sinh(x), sinh(xm))) | |
| assert_(eq(np.tan(x), tan(xm))) | |
| assert_(eq(np.tanh(x), tanh(xm))) | |
| with np.errstate(divide='ignore', invalid='ignore'): | |
| assert_(eq(np.sqrt(abs(x)), sqrt(xm))) | |
| assert_(eq(np.log(abs(x)), log(xm))) | |
| assert_(eq(np.log10(abs(x)), log10(xm))) | |
| assert_(eq(np.exp(x), exp(xm))) | |
| assert_(eq(np.arcsin(z), arcsin(zm))) | |
| assert_(eq(np.arccos(z), arccos(zm))) | |
| assert_(eq(np.arctan(z), arctan(zm))) | |
| assert_(eq(np.arctan2(x, y), arctan2(xm, ym))) | |
| assert_(eq(np.absolute(x), absolute(xm))) | |
| assert_(eq(np.equal(x, y), equal(xm, ym))) | |
| assert_(eq(np.not_equal(x, y), not_equal(xm, ym))) | |
| assert_(eq(np.less(x, y), less(xm, ym))) | |
| assert_(eq(np.greater(x, y), greater(xm, ym))) | |
| assert_(eq(np.less_equal(x, y), less_equal(xm, ym))) | |
| assert_(eq(np.greater_equal(x, y), greater_equal(xm, ym))) | |
| assert_(eq(np.conjugate(x), conjugate(xm))) | |
| assert_(eq(np.concatenate((x, y)), concatenate((xm, ym)))) | |
| assert_(eq(np.concatenate((x, y)), concatenate((x, y)))) | |
| assert_(eq(np.concatenate((x, y)), concatenate((xm, y)))) | |
| assert_(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]) | |
| assert_(count(ott).dtype.type is np.intp) | |
| assert_equal(3, count(ott)) | |
| assert_equal(1, count(1)) | |
| assert_(eq(0, array(1, mask=[1]))) | |
| ott = ott.reshape((2, 2)) | |
| assert_(count(ott).dtype.type is np.intp) | |
| assert_(isinstance(count(ott, 0), np.ndarray)) | |
| assert_(count(ott).dtype.type is np.intp) | |
| assert_(eq(3, count(ott))) | |
| assert_(getmask(count(ott, 0)) is nomask) | |
| assert_(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 | |
| assert_(eq(max(xr), maximum.reduce(xmr))) | |
| assert_(eq(min(xr), minimum.reduce(xmr))) | |
| def test_testAddSumProd(self): | |
| # Test add, sum, product. | |
| (x, y, a10, m1, m2, xm, ym, z, zm, xf, s) = self.d | |
| assert_(eq(np.add.reduce(x), add.reduce(x))) | |
| assert_(eq(np.add.accumulate(x), add.accumulate(x))) | |
| assert_(eq(4, sum(array(4), axis=0))) | |
| assert_(eq(4, sum(array(4), axis=0))) | |
| assert_(eq(np.sum(x, axis=0), sum(x, axis=0))) | |
| assert_(eq(np.sum(filled(xm, 0), axis=0), sum(xm, axis=0))) | |
| assert_(eq(np.sum(x, 0), sum(x, 0))) | |
| assert_(eq(np.product(x, axis=0), product(x, axis=0))) | |
| assert_(eq(np.product(x, 0), product(x, 0))) | |
| assert_(eq(np.product(filled(xm, 1), axis=0), | |
| product(xm, axis=0))) | |
| if len(s) > 1: | |
| assert_(eq(np.concatenate((x, y), 1), | |
| concatenate((xm, ym), 1))) | |
| assert_(eq(np.add.reduce(x, 1), add.reduce(x, 1))) | |
| assert_(eq(np.sum(x, 1), sum(x, 1))) | |
| assert_(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 | |
| str(x2) # raises? | |
| repr(x2) # raises? | |
| 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] | |
| assert_equal(type(s2), str) | |
| assert_equal(type(s1), str) | |
| assert_equal(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) | |
| assert_(m is m2) | |
| m3 = make_mask(m, copy=True) | |
| assert_(m is not m3) | |
| x1 = np.arange(5) | |
| y1 = array(x1, mask=m) | |
| assert_(y1._data is not x1) | |
| assert_(allequal(x1, y1._data)) | |
| assert_(y1._mask is m) | |
| y1a = array(y1, copy=0) | |
| # For copy=False, one might expect that the array would just | |
| # passed on, i.e., that it would be "is" instead of "==". | |
| # See gh-4043 for discussion. | |
| assert_(y1a._mask.__array_interface__ == | |
| y1._mask.__array_interface__) | |
| y2 = array(x1, mask=m3, copy=0) | |
| assert_(y2._mask is m3) | |
| assert_(y2[2] is masked) | |
| y2[2] = 9 | |
| assert_(y2[2] is not masked) | |
| assert_(y2._mask is m3) | |
| assert_(allequal(y2.mask, 0)) | |
| y2a = array(x1, mask=m, copy=1) | |
| assert_(y2a._mask is not m) | |
| assert_(y2a[2] is masked) | |
| y2a[2] = 9 | |
| assert_(y2a[2] is not masked) | |
| assert_(y2a._mask is not m) | |
| assert_(allequal(y2a.mask, 0)) | |
| y3 = array(x1 * 1.0, mask=m) | |
| assert_(filled(y3).dtype is (x1 * 1.0).dtype) | |
| x4 = arange(4) | |
| x4[2] = masked | |
| y4 = resize(x4, (8,)) | |
| assert_(eq(concatenate([x4, x4]), y4)) | |
| assert_(eq(getmask(y4), [0, 0, 1, 0, 0, 0, 1, 0])) | |
| y5 = repeat(x4, (2, 2, 2, 2), axis=0) | |
| assert_(eq(y5, [0, 0, 1, 1, 2, 2, 3, 3])) | |
| y6 = repeat(x4, 2, axis=0) | |
| assert_(eq(y5, y6)) | |
| def test_testPut(self): | |
| # Test of put | |
| d = arange(5) | |
| n = [0, 0, 0, 1, 1] | |
| m = make_mask(n) | |
| m2 = m.copy() | |
| x = array(d, mask=m) | |
| assert_(x[3] is masked) | |
| assert_(x[4] is masked) | |
| x[[1, 4]] = [10, 40] | |
| assert_(x._mask is m) | |
| assert_(x[3] is masked) | |
| assert_(x[4] is not masked) | |
| assert_(eq(x, [0, 10, 2, -1, 40])) | |
| x = array(d, mask=m2, copy=True) | |
| x.put([0, 1, 2], [-1, 100, 200]) | |
| assert_(x._mask is not m2) | |
| assert_(x[3] is masked) | |
| assert_(x[4] is masked) | |
| assert_(eq(x, [-1, 100, 200, 0, 0])) | |
| def test_testPut2(self): | |
| # Test of put | |
| d = arange(5) | |
| x = array(d, mask=[0, 0, 0, 0, 0]) | |
| z = array([10, 40], mask=[1, 0]) | |
| assert_(x[2] is not masked) | |
| assert_(x[3] is not masked) | |
| x[2:4] = z | |
| assert_(x[2] is masked) | |
| assert_(x[3] is not masked) | |
| assert_(eq(x, [0, 1, 10, 40, 4])) | |
| d = arange(5) | |
| x = array(d, mask=[0, 0, 0, 0, 0]) | |
| y = x[2:4] | |
| z = array([10, 40], mask=[1, 0]) | |
| assert_(x[2] is not masked) | |
| assert_(x[3] is not masked) | |
| y[:] = z | |
| assert_(y[0] is masked) | |
| assert_(y[1] is not masked) | |
| assert_(eq(y, [10, 40])) | |
| assert_(x[2] is masked) | |
| assert_(x[3] is not masked) | |
| assert_(eq(x, [0, 1, 10, 40, 4])) | |
| 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=np.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 minimum, 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.reduce(x) == 0) | |
| assert_(maximum.reduce(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(np.float32) | |
| xm = arange(10) | |
| xm[2] = masked | |
| x += 1. | |
| assert_(eq(x, y + 1.)) | |
| def test_testPickle(self): | |
| # Test of pickling | |
| x = arange(12) | |
| x[4:10:2] = masked | |
| x = x.reshape(4, 3) | |
| for proto in range(2, pickle.HIGHEST_PROTOCOL + 1): | |
| s = pickle.dumps(x, protocol=proto) | |
| y = pickle.loads(s) | |
| assert_(eq(x, y)) | |
| def test_testMasked(self): | |
| # Test of masked element | |
| xx = arange(6) | |
| xx[1] = masked | |
| assert_(str(masked) == '--') | |
| assert_(xx[1] is masked) | |
| assert_equal(filled(xx[1], 0), 0) | |
| def test_testAverage1(self): | |
| # Test of average. | |
| ott = array([0., 1., 2., 3.], mask=[1, 0, 0, 0]) | |
| assert_(eq(2.0, average(ott, axis=0))) | |
| assert_(eq(2.0, average(ott, weights=[1., 1., 2., 1.]))) | |
| result, wts = average(ott, weights=[1., 1., 2., 1.], returned=True) | |
| assert_(eq(2.0, result)) | |
| assert_(wts == 4.0) | |
| ott[:] = masked | |
| assert_(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 | |
| assert_(eq(average(ott, axis=0), [2.0, 0.0])) | |
| assert_(average(ott, axis=1)[0] is masked) | |
| assert_(eq([2., 0.], average(ott, axis=0))) | |
| result, wts = average(ott, axis=0, returned=True) | |
| assert_(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) | |
| assert_(allclose(average(x, axis=0), 2.5)) | |
| assert_(allclose(average(x, axis=0, weights=w1), 2.5)) | |
| y = array([arange(6), 2.0 * arange(6)]) | |
| assert_(allclose(average(y, None), | |
| np.add.reduce(np.arange(6)) * 3. / 12.)) | |
| assert_(allclose(average(y, axis=0), np.arange(6) * 3. / 2.)) | |
| assert_(allclose(average(y, axis=1), | |
| [average(x, axis=0), average(x, axis=0)*2.0])) | |
| assert_(allclose(average(y, None, weights=w2), 20. / 6.)) | |
| assert_(allclose(average(y, axis=0, weights=w2), | |
| [0., 1., 2., 3., 4., 10.])) | |
| assert_(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] | |
| assert_(allclose(average(masked_array(x, m1), axis=0), 2.5)) | |
| assert_(allclose(average(masked_array(x, m2), axis=0), 2.5)) | |
| assert_(average(masked_array(x, m4), axis=0) is masked) | |
| assert_equal(average(masked_array(x, m5), axis=0), 0.0) | |
| assert_equal(count(average(masked_array(x, m4), axis=0)), 0) | |
| z = masked_array(y, m3) | |
| assert_(allclose(average(z, None), 20. / 6.)) | |
| assert_(allclose(average(z, axis=0), | |
| [0., 1., 99., 99., 4.0, 7.5])) | |
| assert_(allclose(average(z, axis=1), [2.5, 5.0])) | |
| assert_(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=True) | |
| assert_equal(shape(r1), shape(w1)) | |
| assert_equal(r1.shape, w1.shape) | |
| r2, w2 = average(ones((2, 2, 3)), axis=0, weights=[3, 1], returned=True) | |
| assert_equal(shape(w2), shape(r2)) | |
| r2, w2 = average(ones((2, 2, 3)), returned=True) | |
| assert_equal(shape(w2), shape(r2)) | |
| r2, w2 = average(ones((2, 2, 3)), weights=ones((2, 2, 3)), returned=True) | |
| assert_(shape(w2) == shape(r2)) | |
| a2d = array([[1, 2], [0, 4]], float) | |
| a2dm = masked_array(a2d, [[0, 0], [1, 0]]) | |
| a2da = average(a2d, axis=0) | |
| assert_(eq(a2da, [0.5, 3.0])) | |
| a2dma = average(a2dm, axis=0) | |
| assert_(eq(a2dma, [1.0, 3.0])) | |
| a2dma = average(a2dm, axis=None) | |
| assert_(eq(a2dma, 7. / 3.)) | |
| a2dma = average(a2dm, axis=1) | |
| assert_(eq(a2dma, [1.5, 4.0])) | |
| def test_testToPython(self): | |
| assert_equal(1, int(array(1))) | |
| assert_equal(1.0, float(array(1))) | |
| assert_equal(1, int(array([[[1]]]))) | |
| assert_equal(1.0, float(array([[1]]))) | |
| assert_raises(TypeError, float, array([1, 1])) | |
| assert_raises(ValueError, bool, array([0, 1])) | |
| assert_raises(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'): | |
| assert_((1 / array(0)).mask) | |
| assert_((1 + xm).mask) | |
| assert_((-xm).mask) | |
| assert_((-xm).mask) | |
| assert_(maximum(xm, xm).mask) | |
| assert_(minimum(xm, xm).mask) | |
| assert_(xm.filled().dtype is xm._data.dtype) | |
| x = array(0, mask=0) | |
| assert_(x.filled() == x._data) | |
| assert_equal(str(xm), str(masked_print_option)) | |
| def test_testArrayMethods(self): | |
| a = array([1, 3, 2]) | |
| assert_(eq(a.any(), a._data.any())) | |
| assert_(eq(a.all(), a._data.all())) | |
| assert_(eq(a.argmax(), a._data.argmax())) | |
| assert_(eq(a.argmin(), a._data.argmin())) | |
| assert_(eq(a.choose(0, 1, 2, 3, 4), | |
| a._data.choose(0, 1, 2, 3, 4))) | |
| assert_(eq(a.compress([1, 0, 1]), a._data.compress([1, 0, 1]))) | |
| assert_(eq(a.conj(), a._data.conj())) | |
| assert_(eq(a.conjugate(), a._data.conjugate())) | |
| m = array([[1, 2], [3, 4]]) | |
| assert_(eq(m.diagonal(), m._data.diagonal())) | |
| assert_(eq(a.sum(), a._data.sum())) | |
| assert_(eq(a.take([1, 2]), a._data.take([1, 2]))) | |
| assert_(eq(m.transpose(), m._data.transpose())) | |
| def test_testArrayAttributes(self): | |
| a = array([1, 3, 2]) | |
| assert_equal(a.ndim, 1) | |
| def test_testAPI(self): | |
| assert_(not [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]) | |
| assert_equal(a[0].shape, ()) | |
| assert_equal(b[0].shape, ()) | |
| assert_equal(b[1].shape, ()) | |
| class TestUfuncs: | |
| 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', | |
| 'floor', 'ceil', | |
| '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) | |
| assert_(eq(ur.filled(0), mr.filled(0), f)) | |
| assert_(eqmask(ur.mask, mr.mask)) | |
| def test_reduce(self): | |
| a = self.d[0] | |
| assert_(not alltrue(a, axis=0)) | |
| assert_(sometrue(a, axis=0)) | |
| assert_equal(sum(a[:3], axis=0), 0) | |
| assert_equal(product(a, axis=0), 0) | |
| def test_minmax(self): | |
| a = arange(1, 13).reshape(3, 4) | |
| amask = masked_where(a < 5, a) | |
| assert_equal(amask.max(), a.max()) | |
| assert_equal(amask.min(), 5) | |
| assert_((amask.max(0) == a.max(0)).all()) | |
| assert_((amask.min(0) == [5, 6, 7, 8]).all()) | |
| assert_(amask.max(1)[0].mask) | |
| assert_(amask.min(1)[0].mask) | |
| def test_nonzero(self): | |
| for t in "?bhilqpBHILQPfdgFDGO": | |
| x = array([1, 0, 2, 0], mask=[0, 0, 1, 1]) | |
| assert_(eq(nonzero(x), [0])) | |
| class TestArrayMethods: | |
| 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() | |
| assert_equal(mX.trace(), mX.diagonal().compressed().sum()) | |
| assert_(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) | |
| assert_(eq(clipped.mask, mx.mask)) | |
| assert_(eq(clipped._data, x.clip(2, 8))) | |
| assert_(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 | |
| assert_equal(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() | |
| assert_(eq(mX.ptp(0), cols)) | |
| assert_(eq(mX.ptp(1), rows)) | |
| def test_swapaxes(self): | |
| (x, X, XX, m, mx, mX, mXX,) = self.d | |
| mXswapped = mX.swapaxes(0, 1) | |
| assert_(eq(mXswapped[-1], mX[:, -1])) | |
| mXXswapped = mXX.swapaxes(0, 2) | |
| assert_equal(mXXswapped.shape, (2, 2, 3, 3)) | |
| def test_cumprod(self): | |
| (x, X, XX, m, mx, mX, mXX,) = self.d | |
| mXcp = mX.cumprod(0) | |
| assert_(eq(mXcp._data, mX.filled(1).cumprod(0))) | |
| mXcp = mX.cumprod(1) | |
| assert_(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) | |
| assert_(eq(mXcp._data, mX.filled(0).cumsum(0))) | |
| mXcp = mX.cumsum(1) | |
| assert_(eq(mXcp._data, mX.filled(0).cumsum(1))) | |
| def test_varstd(self): | |
| (x, X, XX, m, mx, mX, mXX,) = self.d | |
| assert_(eq(mX.var(axis=None), mX.compressed().var())) | |
| assert_(eq(mX.std(axis=None), mX.compressed().std())) | |
| assert_(eq(mXX.var(axis=3).shape, XX.var(axis=3).shape)) | |
| assert_(eq(mX.var().shape, X.var().shape)) | |
| (mXvar0, mXvar1) = (mX.var(axis=0), mX.var(axis=1)) | |
| for k in range(6): | |
| assert_(eq(mXvar1[k], mX[k].compressed().var())) | |
| assert_(eq(mXvar0[k], mX[:, k].compressed().var())) | |
| assert_(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() | |