diff options
Diffstat (limited to 'numpy')
| -rw-r--r-- | numpy/core/tests/test_maskna.py | 333 | ||||
| -rw-r--r-- | numpy/core/tests/test_na.py | 326 |
2 files changed, 333 insertions, 326 deletions
diff --git a/numpy/core/tests/test_maskna.py b/numpy/core/tests/test_maskna.py new file mode 100644 index 000000000..3dca0ce7e --- /dev/null +++ b/numpy/core/tests/test_maskna.py @@ -0,0 +1,333 @@ +import numpy as np +from numpy.compat import asbytes +from numpy.testing import * +import sys, warnings + +def test_array_maskna_flags(): + a = np.arange(3) + assert_(not a.flags.maskna) + assert_(not a.flags.ownmaskna) + assert_(not a.flags['MASKNA']) + assert_(not a.flags['OWNMASKNA']) + # Add a mask by setting the flag + a.flags.maskna = True + assert_(a.flags.maskna) + assert_(a.flags.ownmaskna) + assert_(a.flags['MASKNA']) + assert_(a.flags['OWNMASKNA']) + # Can't remove the mask once it's created + def setmaskna(x, v): + x.maskna = v + assert_raises(ValueError, setmaskna, a.flags, False) + def setownmaskna(x, v): + x.ownmaskna = v + assert_raises(ValueError, setownmaskna, a.flags, False) + +def test_array_maskna_construction(): + # Construction with NA inputs + a = np.array([1.0, 2.0, np.NA, 7.0], maskna=True) + assert_equal(a.dtype, np.dtype('f8')) + assert_(a.flags.maskna) + assert_equal(type(a[2]), np.NAType) + # Without the 'maskna=True', produces an object array + a = np.array([1.0, 2.0, np.NA, 7.0]) + assert_equal(a.dtype, np.dtype('O')) + assert_equal(type(a[2]), np.NAType) + + # From np.NA as a straight scalar + a = np.array(np.NA, maskna=True) + assert_equal(type(a), np.ndarray) + assert_(np.isna(a)) + + # As a special case, converting np.NA to an array produces + # a zero-dimensional masked array + a = np.array(np.NA) + assert_equal(type(a), np.ndarray) + assert_(np.isna(a)) + +def test_isna(): + # Objects which are not np.NA or ndarray all return False + assert_equal(np.isna(True), False) + assert_equal(np.isna("abc"), False) + assert_equal(np.isna([1,2,3]), False) + assert_equal(np.isna({3:5}), False) + # Various NA values return True + assert_equal(np.isna(np.NA), True) + assert_equal(np.isna(np.NA()), True) + assert_equal(np.isna(np.NA(5)), True) + assert_equal(np.isna(np.NA(dtype='f4')), True) + assert_equal(np.isna(np.NA(12,dtype='f4')), True) + +def test_array_maskna_isna_1D(): + a = np.arange(10) + + # With no mask, it returns all False + assert_equal(np.isna(a), False) + assert_equal(np.isna(a).shape, (10,)) + + # With a mask but no NAs, it still returns all False + a.flags.maskna = True + assert_equal(np.isna(a), False) + assert_equal(np.isna(a).shape, (10,)) + + # Checking isna of a single value + assert_equal(np.isna(a[4]), False) + # Assigning NA to a single value + a[3] = np.NA + assert_equal(np.isna(a), [0,0,0,1,0,0,0,0,0,0]) + # Checking isna of a single value + assert_equal(np.isna(a[3]), True) + + # Checking isna of a slice + assert_equal(np.isna(a[1:6]), [0,0,1,0,0]) + # Assigning NA to a slice + a[5:7] = np.NA + assert_equal(np.isna(a), [0,0,0,1,0,1,1,0,0,0]) + + # Checking isna of a strided slice + assert_equal(np.isna(a[1:8:2]), [0,1,1,0]) + # Assigning NA to a strided slice + a[2:10:3] = np.NA + assert_equal(np.isna(a), [0,0,1,1,0,1,1,0,1,0]) + + # Checking isna of a boolean mask index + mask = np.array([1,1,0,0,0,1,0,1,1,0], dtype='?') + assert_equal(np.isna(a[mask]), [0,0,1,0,1]) + # Assigning NA to a boolean masked index + a[mask] = np.NA + assert_equal(np.isna(a), [1,1,1,1,0,1,1,1,1,0]) + + # TODO: fancy indexing is next... + +def test_array_maskna_view_function(): + a = np.arange(10) + + # Taking a view of a non-masked array, making sure there's a mask + b = a.view(maskna=True) + assert_(not a.flags.maskna) + assert_(b.flags.maskna) + assert_(b.flags.ownmaskna) + + # Taking a view of a non-masked array, making sure there's an owned mask + b = a.view(ownmaskna=True) + assert_(not a.flags.maskna) + assert_(b.flags.maskna) + assert_(b.flags.ownmaskna) + + # Taking a view of a masked array + c = b.view() + assert_(b.flags.maskna) + assert_(b.flags.ownmaskna) + assert_(c.flags.maskna) + assert_(not c.flags.ownmaskna) + + # Taking a view of a masked array, making sure there's a mask + c = b.view(maskna = True) + assert_(b.flags.maskna) + assert_(b.flags.ownmaskna) + assert_(c.flags.maskna) + assert_(not c.flags.ownmaskna) + + # Taking a view of a masked array, making sure there's an owned mask + c = b.view(ownmaskna = True) + assert_(b.flags.maskna) + assert_(b.flags.ownmaskna) + assert_(c.flags.maskna) + assert_(c.flags.ownmaskna) + +def test_array_maskna_array_function_1D(): + a = np.arange(10) + a_ref = a.copy() + b = a.view(maskna=True) + b[3:10:2] = np.NA + b_view = b.view() + + # Ensure the setup is correct + assert_(not a.flags.maskna) + assert_(b.flags.maskna) + assert_(b.flags.ownmaskna) + assert_(b_view.flags.maskna) + assert_(not b_view.flags.ownmaskna) + + # Should be able to add a mask with 'maskna=' + c = np.array(a, maskna=True) + assert_(c.flags.maskna) + assert_(c.flags.ownmaskna) + assert_(not (c is b)) + + # Should be able to add a mask with 'ownmaskna=' + c = np.array(a, ownmaskna=True) + assert_(c.flags.maskna) + assert_(c.flags.ownmaskna) + assert_(not (c is b)) + + # Should propagate mask + c = np.array(b) + assert_(c.flags.maskna) + assert_(c.flags.ownmaskna) + assert_equal(np.isna(b), np.isna(c)) + assert_(not (c is b)) + + # Should propagate mask with 'maskna=True' + c = np.array(b, maskna=True) + assert_(c.flags.maskna) + assert_(c.flags.ownmaskna) + assert_equal(np.isna(b), np.isna(c)) + assert_(not (c is b)) + + # Should propagate mask with 'ownmaskna=True' + c = np.array(b, ownmaskna=True) + assert_(c.flags.maskna) + assert_(c.flags.ownmaskna) + assert_equal(np.isna(b), np.isna(c)) + assert_(not (c is b)) + + # Should be able to pass it through + c = np.array(b, copy=False) + assert_(c is b) + + # Should be able to pass it through with 'maskna=True' + c = np.array(b, copy=False, maskna=True) + assert_(c is b) + + # Should be able to pass it through with 'maskna=True' + c = np.array(b_view, copy=False, maskna=True) + assert_(c is b_view) + + # Should be able to pass an owned mask through with 'ownmaskna=True' + c = np.array(b, copy=False, ownmaskna=True) + assert_(c is b) + + # Should produce a view with an owned mask with 'ownmaskna=True' + c = np.array(b_view, copy=False, ownmaskna=True) + assert_(c.base is a) + assert_(c.flags.ownmaskna) + assert_(not (c is b_view)) + +def test_array_maskna_view_NA_assignment_1D(): + a = np.arange(10) + a_ref = a.copy() + + # Make sure that assigning NA doesn't affect the original data + b = a.view(maskna=True) + b[...] = np.NA + assert_equal(np.isna(b), True) + assert_equal(a, a_ref) + + b = a.view(maskna=True) + b[:] = np.NA + assert_equal(np.isna(b), True) + assert_equal(a, a_ref) + + b = a.view(maskna=True) + b[3:5] = np.NA + assert_equal(np.isna(b), [0,0,0,1,1,0,0,0,0,0]) + assert_equal(a, a_ref) + + b = a.view(maskna=True) + b[3:10:3] = np.NA + assert_equal(np.isna(b), [0,0,0,1,0,0,1,0,0,1]) + assert_equal(a, a_ref) + + b = a.view(maskna=True) + b[3] = np.NA + assert_equal(np.isna(b), [0,0,0,1,0,0,0,0,0,0]) + assert_equal(a, a_ref) + + b = a.view(maskna=True) + mask = np.array([0,1,0,1,1,0,0,0,1,1], dtype='?') + b[mask] = np.NA + assert_equal(np.isna(b), mask) + assert_equal(a, a_ref) + + # TODO: fancy indexing is next... + +def test_array_maskna_view_array_assignment_1D(): + a = np.arange(5) + b = a.view(maskna=True) + + # Assigning a constant scalar should unmask the values + b[...] = np.NA + b[...] = 3 + assert_equal(a, 3) + assert_equal(np.isna(b), False) + + # Assigning from a list should unmask the values + b[...] = np.NA + b[...] = [2] + assert_equal(a, [2,2,2,2,2]) + assert_equal(np.isna(b), False) + + # Assigning from a list should unmask the values + b[...] = np.NA + b[...] = [2,3,4,5,6] + assert_equal(a, [2,3,4,5,6]) + assert_equal(np.isna(b), False) + + # Assigning from an unmasked array should unmask the values + b[...] = np.NA + b[...] = np.arange(5) + assert_equal(a, np.arange(5)) + assert_equal(np.isna(b), False) + + # Assigning from a masked array with no NAs should unmask the values + b[...] = np.NA + tmp = np.arange(5) + 1 + tmp.flags.maskna = True + b[...] = tmp + assert_equal(a, np.arange(5) + 1) + assert_equal(np.isna(b), False) + + # Assigning from a masked array with some NAs should unmask most + # of the values, and leave the value behind the NAs untouched + b[...] = np.NA + tmp = np.arange(5) + 5 + tmp.flags.maskna = True + tmp[2] = np.NA + b[...] = tmp + assert_equal(a, [5,6,3,8,9]) + assert_equal(np.isna(b), [0,0,1,0,0]) + + # Assigning to a single element should unmask the value + b[...] = np.NA + b[2] = 10 + assert_equal(a, [5,6,10,8,9]) + assert_equal(np.isna(b), [1,1,0,1,1]) + + # Assigning to a simple slice should unmask the values + b[...] = np.NA + b[2:] = 4 + assert_equal(a, [5,6,4,4,4]) + assert_equal(np.isna(b), [1,1,0,0,0]) + + # Assigning to a strided slice should unmask the values + b[...] = np.NA + b[3::-2] = 12 + assert_equal(a, [5,12,4,12,4]) + assert_equal(np.isna(b), [1,0,1,0,1]) + + # Assigning to a boolean index should unmask the values + b[...] = np.NA + mask = np.array([0,1,1,0,1], dtype='?') + b[mask] = 7 + assert_equal(a, [5,7,7,12,7]) + assert_equal(np.isna(b), [1,0,0,1,0]) + + # Assigning a list to a boolean index should unmask the values + b[...] = np.NA + mask = np.array([1,0,0,0,1], dtype='?') + b[mask] = [8,1] + assert_equal(a, [8,7,7,12,1]) + assert_equal(np.isna(b), [0,1,1,1,0]) + + # Assigning a list with NA to a boolean index should unmask non-NA values + b[...] = np.NA + mask = np.array([0,1,1,0,0], dtype='?') + b[mask] = [8,np.NA] + assert_equal(a, [8,8,7,12,1]) + assert_equal(np.isna(b), [1,0,1,1,1]) + + # TODO: fancy indexing is next... + +if __name__ == "__main__": + run_module_suite() diff --git a/numpy/core/tests/test_na.py b/numpy/core/tests/test_na.py index dec5379b4..676377ca1 100644 --- a/numpy/core/tests/test_na.py +++ b/numpy/core/tests/test_na.py @@ -149,331 +149,5 @@ def test_na_other_operations(): assert_equal((np.NA | False).dtype, np.array(False).dtype) assert_equal((np.NA & True).dtype, np.array(True).dtype) -def test_array_maskna_flags(): - a = np.arange(3) - assert_(not a.flags.maskna) - assert_(not a.flags.ownmaskna) - assert_(not a.flags['MASKNA']) - assert_(not a.flags['OWNMASKNA']) - # Add a mask by setting the flag - a.flags.maskna = True - assert_(a.flags.maskna) - assert_(a.flags.ownmaskna) - assert_(a.flags['MASKNA']) - assert_(a.flags['OWNMASKNA']) - # Can't remove the mask once it's created - def setmaskna(x, v): - x.maskna = v - assert_raises(ValueError, setmaskna, a.flags, False) - def setownmaskna(x, v): - x.ownmaskna = v - assert_raises(ValueError, setownmaskna, a.flags, False) - -def test_array_maskna_construction(): - # Construction with NA inputs - a = np.array([1.0, 2.0, np.NA, 7.0], maskna=True) - assert_equal(a.dtype, np.dtype('f8')) - assert_(a.flags.maskna) - assert_equal(type(a[2]), np.NAType) - # Without the 'maskna=True', produces an object array - a = np.array([1.0, 2.0, np.NA, 7.0]) - assert_equal(a.dtype, np.dtype('O')) - assert_equal(type(a[2]), np.NAType) - - # From np.NA as a straight scalar - a = np.array(np.NA, maskna=True) - assert_equal(type(a), np.ndarray) - assert_(np.isna(a)) - - # As a special case, converting np.NA to an array produces - # a zero-dimensional masked array - a = np.array(np.NA) - assert_equal(type(a), np.ndarray) - assert_(np.isna(a)) - -def test_isna(): - # Objects which are not np.NA or ndarray all return False - assert_equal(np.isna(True), False) - assert_equal(np.isna("abc"), False) - assert_equal(np.isna([1,2,3]), False) - assert_equal(np.isna({3:5}), False) - # Various NA values return True - assert_equal(np.isna(np.NA), True) - assert_equal(np.isna(np.NA()), True) - assert_equal(np.isna(np.NA(5)), True) - assert_equal(np.isna(np.NA(dtype='f4')), True) - assert_equal(np.isna(np.NA(12,dtype='f4')), True) - -def test_array_maskna_isna_1D(): - a = np.arange(10) - - # With no mask, it returns all False - assert_equal(np.isna(a), False) - assert_equal(np.isna(a).shape, (10,)) - - # With a mask but no NAs, it still returns all False - a.flags.maskna = True - assert_equal(np.isna(a), False) - assert_equal(np.isna(a).shape, (10,)) - - # Checking isna of a single value - assert_equal(np.isna(a[4]), False) - # Assigning NA to a single value - a[3] = np.NA - assert_equal(np.isna(a), [0,0,0,1,0,0,0,0,0,0]) - # Checking isna of a single value - assert_equal(np.isna(a[3]), True) - - # Checking isna of a slice - assert_equal(np.isna(a[1:6]), [0,0,1,0,0]) - # Assigning NA to a slice - a[5:7] = np.NA - assert_equal(np.isna(a), [0,0,0,1,0,1,1,0,0,0]) - - # Checking isna of a strided slice - assert_equal(np.isna(a[1:8:2]), [0,1,1,0]) - # Assigning NA to a strided slice - a[2:10:3] = np.NA - assert_equal(np.isna(a), [0,0,1,1,0,1,1,0,1,0]) - - # Checking isna of a boolean mask index - mask = np.array([1,1,0,0,0,1,0,1,1,0], dtype='?') - assert_equal(np.isna(a[mask]), [0,0,1,0,1]) - # Assigning NA to a boolean masked index - a[mask] = np.NA - assert_equal(np.isna(a), [1,1,1,1,0,1,1,1,1,0]) - - # TODO: fancy indexing is next... - -def test_array_maskna_view_function(): - a = np.arange(10) - - # Taking a view of a non-masked array, making sure there's a mask - b = a.view(maskna=True) - assert_(not a.flags.maskna) - assert_(b.flags.maskna) - assert_(b.flags.ownmaskna) - - # Taking a view of a non-masked array, making sure there's an owned mask - b = a.view(ownmaskna=True) - assert_(not a.flags.maskna) - assert_(b.flags.maskna) - assert_(b.flags.ownmaskna) - - # Taking a view of a masked array - c = b.view() - assert_(b.flags.maskna) - assert_(b.flags.ownmaskna) - assert_(c.flags.maskna) - assert_(not c.flags.ownmaskna) - - # Taking a view of a masked array, making sure there's a mask - c = b.view(maskna = True) - assert_(b.flags.maskna) - assert_(b.flags.ownmaskna) - assert_(c.flags.maskna) - assert_(not c.flags.ownmaskna) - - # Taking a view of a masked array, making sure there's an owned mask - c = b.view(ownmaskna = True) - assert_(b.flags.maskna) - assert_(b.flags.ownmaskna) - assert_(c.flags.maskna) - assert_(c.flags.ownmaskna) - -def test_array_maskna_array_function_1D(): - a = np.arange(10) - a_ref = a.copy() - b = a.view(maskna=True) - b[3:10:2] = np.NA - b_view = b.view() - - # Ensure the setup is correct - assert_(not a.flags.maskna) - assert_(b.flags.maskna) - assert_(b.flags.ownmaskna) - assert_(b_view.flags.maskna) - assert_(not b_view.flags.ownmaskna) - - # Should be able to add a mask with 'maskna=' - c = np.array(a, maskna=True) - assert_(c.flags.maskna) - assert_(c.flags.ownmaskna) - assert_(not (c is b)) - - # Should be able to add a mask with 'ownmaskna=' - c = np.array(a, ownmaskna=True) - assert_(c.flags.maskna) - assert_(c.flags.ownmaskna) - assert_(not (c is b)) - - # Should propagate mask - c = np.array(b) - assert_(c.flags.maskna) - assert_(c.flags.ownmaskna) - assert_equal(np.isna(b), np.isna(c)) - assert_(not (c is b)) - - # Should propagate mask with 'maskna=True' - c = np.array(b, maskna=True) - assert_(c.flags.maskna) - assert_(c.flags.ownmaskna) - assert_equal(np.isna(b), np.isna(c)) - assert_(not (c is b)) - - # Should propagate mask with 'ownmaskna=True' - c = np.array(b, ownmaskna=True) - assert_(c.flags.maskna) - assert_(c.flags.ownmaskna) - assert_equal(np.isna(b), np.isna(c)) - assert_(not (c is b)) - - # Should be able to pass it through - c = np.array(b, copy=False) - assert_(c is b) - - # Should be able to pass it through with 'maskna=True' - c = np.array(b, copy=False, maskna=True) - assert_(c is b) - - # Should be able to pass it through with 'maskna=True' - c = np.array(b_view, copy=False, maskna=True) - assert_(c is b_view) - - # Should be able to pass an owned mask through with 'ownmaskna=True' - c = np.array(b, copy=False, ownmaskna=True) - assert_(c is b) - - # Should produce a view with an owned mask with 'ownmaskna=True' - c = np.array(b_view, copy=False, ownmaskna=True) - assert_(c.base is a) - assert_(c.flags.ownmaskna) - assert_(not (c is b_view)) - -def test_array_maskna_view_NA_assignment_1D(): - a = np.arange(10) - a_ref = a.copy() - - # Make sure that assigning NA doesn't affect the original data - b = a.view(maskna=True) - b[...] = np.NA - assert_equal(np.isna(b), True) - assert_equal(a, a_ref) - - b = a.view(maskna=True) - b[:] = np.NA - assert_equal(np.isna(b), True) - assert_equal(a, a_ref) - - b = a.view(maskna=True) - b[3:5] = np.NA - assert_equal(np.isna(b), [0,0,0,1,1,0,0,0,0,0]) - assert_equal(a, a_ref) - - b = a.view(maskna=True) - b[3:10:3] = np.NA - assert_equal(np.isna(b), [0,0,0,1,0,0,1,0,0,1]) - assert_equal(a, a_ref) - - b = a.view(maskna=True) - b[3] = np.NA - assert_equal(np.isna(b), [0,0,0,1,0,0,0,0,0,0]) - assert_equal(a, a_ref) - - b = a.view(maskna=True) - mask = np.array([0,1,0,1,1,0,0,0,1,1], dtype='?') - b[mask] = np.NA - assert_equal(np.isna(b), mask) - assert_equal(a, a_ref) - - # TODO: fancy indexing is next... - -def test_array_maskna_view_array_assignment_1D(): - a = np.arange(5) - b = a.view(maskna=True) - - # Assigning a constant scalar should unmask the values - b[...] = np.NA - b[...] = 3 - assert_equal(a, 3) - assert_equal(np.isna(b), False) - - # Assigning from a list should unmask the values - b[...] = np.NA - b[...] = [2] - assert_equal(a, [2,2,2,2,2]) - assert_equal(np.isna(b), False) - - # Assigning from a list should unmask the values - b[...] = np.NA - b[...] = [2,3,4,5,6] - assert_equal(a, [2,3,4,5,6]) - assert_equal(np.isna(b), False) - - # Assigning from an unmasked array should unmask the values - b[...] = np.NA - b[...] = np.arange(5) - assert_equal(a, np.arange(5)) - assert_equal(np.isna(b), False) - - # Assigning from a masked array with no NAs should unmask the values - b[...] = np.NA - tmp = np.arange(5) + 1 - tmp.flags.maskna = True - b[...] = tmp - assert_equal(a, np.arange(5) + 1) - assert_equal(np.isna(b), False) - - # Assigning from a masked array with some NAs should unmask most - # of the values, and leave the value behind the NAs untouched - b[...] = np.NA - tmp = np.arange(5) + 5 - tmp.flags.maskna = True - tmp[2] = np.NA - b[...] = tmp - assert_equal(a, [5,6,3,8,9]) - assert_equal(np.isna(b), [0,0,1,0,0]) - - # Assigning to a single element should unmask the value - b[...] = np.NA - b[2] = 10 - assert_equal(a, [5,6,10,8,9]) - assert_equal(np.isna(b), [1,1,0,1,1]) - - # Assigning to a simple slice should unmask the values - b[...] = np.NA - b[2:] = 4 - assert_equal(a, [5,6,4,4,4]) - assert_equal(np.isna(b), [1,1,0,0,0]) - - # Assigning to a strided slice should unmask the values - b[...] = np.NA - b[3::-2] = 12 - assert_equal(a, [5,12,4,12,4]) - assert_equal(np.isna(b), [1,0,1,0,1]) - - # Assigning to a boolean index should unmask the values - b[...] = np.NA - mask = np.array([0,1,1,0,1], dtype='?') - b[mask] = 7 - assert_equal(a, [5,7,7,12,7]) - assert_equal(np.isna(b), [1,0,0,1,0]) - - # Assigning a list to a boolean index should unmask the values - b[...] = np.NA - mask = np.array([1,0,0,0,1], dtype='?') - b[mask] = [8,1] - assert_equal(a, [8,7,7,12,1]) - assert_equal(np.isna(b), [0,1,1,1,0]) - - # Assigning a list with NA to a boolean index should unmask non-NA values - b[...] = np.NA - mask = np.array([0,1,1,0,0], dtype='?') - b[mask] = [8,np.NA] - assert_equal(a, [8,8,7,12,1]) - assert_equal(np.isna(b), [1,0,1,1,1]) - - # TODO: fancy indexing is next... - if __name__ == "__main__": run_module_suite() |