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Editing: test_recfunctions.py
import pytest import numpy as np import numpy.ma as ma from numpy.ma.mrecords import MaskedRecords from numpy.ma.testutils import assert_equal from numpy.testing import assert_, assert_raises from numpy.lib.recfunctions import ( drop_fields, rename_fields, get_fieldstructure, recursive_fill_fields, find_duplicates, merge_arrays, append_fields, stack_arrays, join_by, repack_fields, unstructured_to_structured, structured_to_unstructured, apply_along_fields, require_fields, assign_fields_by_name) get_fieldspec = np.lib.recfunctions._get_fieldspec get_names = np.lib.recfunctions.get_names get_names_flat = np.lib.recfunctions.get_names_flat zip_descr = np.lib.recfunctions._zip_descr zip_dtype = np.lib.recfunctions._zip_dtype class TestRecFunctions: # Misc tests def setup_method(self): x = np.array([1, 2, ]) y = np.array([10, 20, 30]) z = np.array([('A', 1.), ('B', 2.)], dtype=[('A', '|S3'), ('B', float)]) w = np.array([(1, (2, 3.0)), (4, (5, 6.0))], dtype=[('a', int), ('b', [('ba', float), ('bb', int)])]) self.data = (w, x, y, z) def test_zip_descr(self): # Test zip_descr (w, x, y, z) = self.data # Std array test = zip_descr((x, x), flatten=True) assert_equal(test, np.dtype([('', int), ('', int)])) test = zip_descr((x, x), flatten=False) assert_equal(test, np.dtype([('', int), ('', int)])) # Std & flexible-dtype test = zip_descr((x, z), flatten=True) assert_equal(test, np.dtype([('', int), ('A', '|S3'), ('B', float)])) test = zip_descr((x, z), flatten=False) assert_equal(test, np.dtype([('', int), ('', [('A', '|S3'), ('B', float)])])) # Standard & nested dtype test = zip_descr((x, w), flatten=True) assert_equal(test, np.dtype([('', int), ('a', int), ('ba', float), ('bb', int)])) test = zip_descr((x, w), flatten=False) assert_equal(test, np.dtype([('', int), ('', [('a', int), ('b', [('ba', float), ('bb', int)])])])) def test_drop_fields(self): # Test drop_fields a = np.array([(1, (2, 3.0)), (4, (5, 6.0))], dtype=[('a', int), ('b', [('ba', float), ('bb', int)])]) # A basic field test = drop_fields(a, 'a') control = np.array([((2, 3.0),), ((5, 6.0),)], dtype=[('b', [('ba', float), ('bb', int)])]) assert_equal(test, control) # Another basic field (but nesting two fields) test = drop_fields(a, 'b') control = np.array([(1,), (4,)], dtype=[('a', int)]) assert_equal(test, control) # A nested sub-field test = drop_fields(a, ['ba', ]) control = np.array([(1, (3.0,)), (4, (6.0,))], dtype=[('a', int), ('b', [('bb', int)])]) assert_equal(test, control) # All the nested sub-field from a field: zap that field test = drop_fields(a, ['ba', 'bb']) control = np.array([(1,), (4,)], dtype=[('a', int)]) assert_equal(test, control) # dropping all fields results in an array with no fields test = drop_fields(a, ['a', 'b']) control = np.array([(), ()], dtype=[]) assert_equal(test, control) def test_rename_fields(self): # Test rename fields a = np.array([(1, (2, [3.0, 30.])), (4, (5, [6.0, 60.]))], dtype=[('a', int), ('b', [('ba', float), ('bb', (float, 2))])]) test = rename_fields(a, {'a': 'A', 'bb': 'BB'}) newdtype = [('A', int), ('b', [('ba', float), ('BB', (float, 2))])] control = a.view(newdtype) assert_equal(test.dtype, newdtype) assert_equal(test, control) def test_get_names(self): # Test get_names ndtype = np.dtype([('A', '|S3'), ('B', float)]) test = get_names(ndtype) assert_equal(test, ('A', 'B')) ndtype = np.dtype([('a', int), ('b', [('ba', float), ('bb', int)])]) test = get_names(ndtype) assert_equal(test, ('a', ('b', ('ba', 'bb')))) ndtype = np.dtype([('a', int), ('b', [])]) test = get_names(ndtype) assert_equal(test, ('a', ('b', ()))) ndtype = np.dtype([]) test = get_names(ndtype) assert_equal(test, ()) def test_get_names_flat(self): # Test get_names_flat ndtype = np.dtype([('A', '|S3'), ('B', float)]) test = get_names_flat(ndtype) assert_equal(test, ('A', 'B')) ndtype = np.dtype([('a', int), ('b', [('ba', float), ('bb', int)])]) test = get_names_flat(ndtype) assert_equal(test, ('a', 'b', 'ba', 'bb')) ndtype = np.dtype([('a', int), ('b', [])]) test = get_names_flat(ndtype) assert_equal(test, ('a', 'b')) ndtype = np.dtype([]) test = get_names_flat(ndtype) assert_equal(test, ()) def test_get_fieldstructure(self): # Test get_fieldstructure # No nested fields ndtype = np.dtype([('A', '|S3'), ('B', float)]) test = get_fieldstructure(ndtype) assert_equal(test, {'A': [], 'B': []}) # One 1-nested field ndtype = np.dtype([('A', int), ('B', [('BA', float), ('BB', '|S1')])]) test = get_fieldstructure(ndtype) assert_equal(test, {'A': [], 'B': [], 'BA': ['B', ], 'BB': ['B']}) # One 2-nested fields ndtype = np.dtype([('A', int), ('B', [('BA', int), ('BB', [('BBA', int), ('BBB', int)])])]) test = get_fieldstructure(ndtype) control = {'A': [], 'B': [], 'BA': ['B'], 'BB': ['B'], 'BBA': ['B', 'BB'], 'BBB': ['B', 'BB']} assert_equal(test, control) # 0 fields ndtype = np.dtype([]) test = get_fieldstructure(ndtype) assert_equal(test, {}) def test_find_duplicates(self): # Test find_duplicates a = ma.array([(2, (2., 'B')), (1, (2., 'B')), (2, (2., 'B')), (1, (1., 'B')), (2, (2., 'B')), (2, (2., 'C'))], mask=[(0, (0, 0)), (0, (0, 0)), (0, (0, 0)), (0, (0, 0)), (1, (0, 0)), (0, (1, 0))], dtype=[('A', int), ('B', [('BA', float), ('BB', '|S1')])]) test = find_duplicates(a, ignoremask=False, return_index=True) control = [0, 2] assert_equal(sorted(test[-1]), control) assert_equal(test[0], a[test[-1]]) test = find_duplicates(a, key='A', return_index=True) control = [0, 1, 2, 3, 5] assert_equal(sorted(test[-1]), control) assert_equal(test[0], a[test[-1]]) test = find_duplicates(a, key='B', return_index=True) control = [0, 1, 2, 4] assert_equal(sorted(test[-1]), control) assert_equal(test[0], a[test[-1]]) test = find_duplicates(a, key='BA', return_index=True) control = [0, 1, 2, 4] assert_equal(sorted(test[-1]), control) assert_equal(test[0], a[test[-1]]) test = find_duplicates(a, key='BB', return_index=True) control = [0, 1, 2, 3, 4] assert_equal(sorted(test[-1]), control) assert_equal(test[0], a[test[-1]]) def test_find_duplicates_ignoremask(self): # Test the ignoremask option of find_duplicates ndtype = [('a', int)] a = ma.array([1, 1, 1, 2, 2, 3, 3], mask=[0, 0, 1, 0, 0, 0, 1]).view(ndtype) test = find_duplicates(a, ignoremask=True, return_index=True) control = [0, 1, 3, 4] assert_equal(sorted(test[-1]), control) assert_equal(test[0], a[test[-1]]) test = find_duplicates(a, ignoremask=False, return_index=True) control = [0, 1, 2, 3, 4, 6] assert_equal(sorted(test[-1]), control) assert_equal(test[0], a[test[-1]]) def test_repack_fields(self): dt = np.dtype('u1,f4,i8', align=True) a = np.zeros(2, dtype=dt) assert_equal(repack_fields(dt), np.dtype('u1,f4,i8')) assert_equal(repack_fields(a).itemsize, 13) assert_equal(repack_fields(repack_fields(dt), align=True), dt) # make sure type is preserved dt = np.dtype((np.record, dt)) assert_(repack_fields(dt).type is np.record) def test_structured_to_unstructured(self, tmp_path): a = np.zeros(4, dtype=[('a', 'i4'), ('b', 'f4,u2'), ('c', 'f4', 2)]) out = structured_to_unstructured(a) assert_equal(out, np.zeros((4,5), dtype='f8')) b = np.array([(1, 2, 5), (4, 5, 7), (7, 8 ,11), (10, 11, 12)], dtype=[('x', 'i4'), ('y', 'f4'), ('z', 'f8')]) out = np.mean(structured_to_unstructured(b[['x', 'z']]), axis=-1) assert_equal(out, np.array([ 3. , 5.5, 9. , 11. ])) out = np.mean(structured_to_unstructured(b[['x']]), axis=-1) assert_equal(out, np.array([ 1. , 4. , 7. , 10. ])) c = np.arange(20).reshape((4,5)) out = unstructured_to_structured(c, a.dtype) want = np.array([( 0, ( 1., 2), [ 3., 4.]), ( 5, ( 6., 7), [ 8., 9.]), (10, (11., 12), [13., 14.]), (15, (16., 17), [18., 19.])], dtype=[('a', 'i4'), ('b', [('f0', 'f4'), ('f1', 'u2')]), ('c', 'f4', (2,))]) assert_equal(out, want) d = np.array([(1, 2, 5), (4, 5, 7), (7, 8 ,11), (10, 11, 12)], dtype=[('x', 'i4'), ('y', 'f4'), ('z', 'f8')]) assert_equal(apply_along_fields(np.mean, d), np.array([ 8.0/3, 16.0/3, 26.0/3, 11. ])) assert_equal(apply_along_fields(np.mean, d[['x', 'z']]), np.array([ 3. , 5.5, 9. , 11. ])) # check that for uniform field dtypes we get a view, not a copy: d = np.array([(1, 2, 5), (4, 5, 7), (7, 8 ,11), (10, 11, 12)], dtype=[('x', 'i4'), ('y', 'i4'), ('z', 'i4')]) dd = structured_to_unstructured(d) ddd = unstructured_to_structured(dd, d.dtype) assert_(np.shares_memory(dd, d)) assert_(np.shares_memory(ddd, d)) # check that reversing the order of attributes works dd_attrib_rev = structured_to_unstructured(d[['z', 'x']]) assert_equal(dd_attrib_rev, [[5, 1], [7, 4], [11, 7], [12, 10]]) assert_(np.shares_memory(dd_attrib_rev, d)) # including uniform fields with subarrays unpacked d = np.array([(1, [2, 3], [[ 4, 5], [ 6, 7]]), (8, [9, 10], [[11, 12], [13, 14]])], dtype=[('x0', 'i4'), ('x1', ('i4', 2)), ('x2', ('i4', (2, 2)))]) dd = structured_to_unstructured(d) ddd = unstructured_to_structured(dd, d.dtype) assert_(np.shares_memory(dd, d)) assert_(np.shares_memory(ddd, d)) # check that reversing with sub-arrays works as expected d_rev = d[::-1] dd_rev = structured_to_unstructured(d_rev) assert_equal(dd_rev, [[8, 9, 10, 11, 12, 13, 14], [1, 2, 3, 4, 5, 6, 7]]) # check that sub-arrays keep the order of their values d_attrib_rev = d[['x2', 'x1', 'x0']] dd_attrib_rev = structured_to_unstructured(d_attrib_rev) assert_equal(dd_attrib_rev, [[4, 5, 6, 7, 2, 3, 1], [11, 12, 13, 14, 9, 10, 8]]) # with ignored field at the end d = np.array([(1, [2, 3], [[4, 5], [6, 7]], 32), (8, [9, 10], [[11, 12], [13, 14]], 64)], dtype=[('x0', 'i4'), ('x1', ('i4', 2)), ('x2', ('i4', (2, 2))), ('ignored', 'u1')]) dd = structured_to_unstructured(d[['x0', 'x1', 'x2']]) assert_(np.shares_memory(dd, d)) assert_equal(dd, [[1, 2, 3, 4, 5, 6, 7], [8, 9, 10, 11, 12, 13, 14]]) # test that nested fields with identical names don't break anything point = np.dtype([('x', int), ('y', int)]) triangle = np.dtype([('a', point), ('b', point), ('c', point)]) arr = np.zeros(10, triangle) res = structured_to_unstructured(arr, dtype=int) assert_equal(res, np.zeros((10, 6), dtype=int)) # test nested combinations of subarrays and structured arrays, gh-13333 def subarray(dt, shape): return np.dtype((dt, shape)) def structured(*dts): return np.dtype([('x{}'.format(i), dt) for i, dt in enumerate(dts)]) def inspect(dt, dtype=None): arr = np.zeros((), dt) ret = structured_to_unstructured(arr, dtype=dtype) backarr = unstructured_to_structured(ret, dt) return ret.shape, ret.dtype, backarr.dtype dt = structured(subarray(structured(np.int32, np.int32), 3)) assert_equal(inspect(dt), ((6,), np.int32, dt)) dt = structured(subarray(subarray(np.int32, 2), 2)) assert_equal(inspect(dt), ((4,), np.int32, dt)) dt = structured(np.int32) assert_equal(inspect(dt), ((1,), np.int32, dt)) dt = structured(np.int32, subarray(subarray(np.int32, 2), 2)) assert_equal(inspect(dt), ((5,), np.int32, dt)) dt = structured() assert_raises(ValueError, structured_to_unstructured, np.zeros(3, dt)) # these currently don't work, but we may make it work in the future assert_raises(NotImplementedError, structured_to_unstructured, np.zeros(3, dt), dtype=np.int32) assert_raises(NotImplementedError, unstructured_to_structured, np.zeros((3,0), dtype=np.int32)) # test supported ndarray subclasses d_plain = np.array([(1, 2), (3, 4)], dtype=[('a', 'i4'), ('b', 'i4')]) dd_expected = structured_to_unstructured(d_plain, copy=True) # recarray d = d_plain.view(np.recarray) dd = structured_to_unstructured(d, copy=False) ddd = structured_to_unstructured(d, copy=True) assert_(np.shares_memory(d, dd)) assert_(type(dd) is np.recarray) assert_(type(ddd) is np.recarray) assert_equal(dd, dd_expected) assert_equal(ddd, dd_expected) # memmap d = np.memmap(tmp_path / 'memmap', mode='w+', dtype=d_plain.dtype, shape=d_plain.shape) d[:] = d_plain dd = structured_to_unstructured(d, copy=False) ddd = structured_to_unstructured(d, copy=True) assert_(np.shares_memory(d, dd)) assert_(type(dd) is np.memmap) assert_(type(ddd) is np.memmap) assert_equal(dd, dd_expected) assert_equal(ddd, dd_expected) def test_unstructured_to_structured(self): # test if dtype is the args of np.dtype a = np.zeros((20, 2)) test_dtype_args = [('x', float), ('y', float)] test_dtype = np.dtype(test_dtype_args) field1 = unstructured_to_structured(a, dtype=test_dtype_args) # now field2 = unstructured_to_structured(a, dtype=test_dtype) # before assert_equal(field1, field2) def test_field_assignment_by_name(self): a = np.ones(2, dtype=[('a', 'i4'), ('b', 'f8'), ('c', 'u1')]) newdt = [('b', 'f4'), ('c', 'u1')] assert_equal(require_fields(a, newdt), np.ones(2, newdt)) b = np.array([(1,2), (3,4)], dtype=newdt) assign_fields_by_name(a, b, zero_unassigned=False) assert_equal(a, np.array([(1,1,2),(1,3,4)], dtype=a.dtype)) assign_fields_by_name(a, b) assert_equal(a, np.array([(0,1,2),(0,3,4)], dtype=a.dtype)) # test nested fields a = np.ones(2, dtype=[('a', [('b', 'f8'), ('c', 'u1')])]) newdt = [('a', [('c', 'u1')])] assert_equal(require_fields(a, newdt), np.ones(2, newdt)) b = np.array([((2,),), ((3,),)], dtype=newdt) assign_fields_by_name(a, b, zero_unassigned=False) assert_equal(a, np.array([((1,2),), ((1,3),)], dtype=a.dtype)) assign_fields_by_name(a, b) assert_equal(a, np.array([((0,2),), ((0,3),)], dtype=a.dtype)) # test unstructured code path for 0d arrays a, b = np.array(3), np.array(0) assign_fields_by_name(b, a) assert_equal(b[()], 3) class TestRecursiveFillFields: # Test recursive_fill_fields. def test_simple_flexible(self): # Test recursive_fill_fields on flexible-array a = np.array([(1, 10.), (2, 20.)], dtype=[('A', int), ('B', float)]) b = np.zeros((3,), dtype=a.dtype) test = recursive_fill_fields(a, b) control = np.array([(1, 10.), (2, 20.), (0, 0.)], dtype=[('A', int), ('B', float)]) assert_equal(test, control) def test_masked_flexible(self): # Test recursive_fill_fields on masked flexible-array a = ma.array([(1, 10.), (2, 20.)], mask=[(0, 1), (1, 0)], dtype=[('A', int), ('B', float)]) b = ma.zeros((3,), dtype=a.dtype) test = recursive_fill_fields(a, b) control = ma.array([(1, 10.), (2, 20.), (0, 0.)], mask=[(0, 1), (1, 0), (0, 0)], dtype=[('A', int), ('B', float)]) assert_equal(test, control) class TestMergeArrays: # Test merge_arrays def setup_method(self): x = np.array([1, 2, ]) y = np.array([10, 20, 30]) z = np.array( [('A', 1.), ('B', 2.)], dtype=[('A', '|S3'), ('B', float)]) w = np.array( [(1, (2, 3.0, ())), (4, (5, 6.0, ()))], dtype=[('a', int), ('b', [('ba', float), ('bb', int), ('bc', [])])]) self.data = (w, x, y, z) def test_solo(self): # Test merge_arrays on a single array. (_, x, _, z) = self.data test = merge_arrays(x) control = np.array([(1,), (2,)], dtype=[('f0', int)]) assert_equal(test, control) test = merge_arrays((x,)) assert_equal(test, control) test = merge_arrays(z, flatten=False) assert_equal(test, z) test = merge_arrays(z, flatten=True) assert_equal(test, z) def test_solo_w_flatten(self): # Test merge_arrays on a single array w & w/o flattening w = self.data[0] test = merge_arrays(w, flatten=False) assert_equal(test, w) test = merge_arrays(w, flatten=True) control = np.array([(1, 2, 3.0), (4, 5, 6.0)], dtype=[('a', int), ('ba', float), ('bb', int)]) assert_equal(test, control) def test_standard(self): # Test standard & standard # Test merge arrays (_, x, y, _) = self.data test = merge_arrays((x, y), usemask=False) control = np.array([(1, 10), (2, 20), (-1, 30)], dtype=[('f0', int), ('f1', int)]) assert_equal(test, control) test = merge_arrays((x, y), usemask=True) control = ma.array([(1, 10), (2, 20), (-1, 30)], mask=[(0, 0), (0, 0), (1, 0)], dtype=[('f0', int), ('f1', int)]) assert_equal(test, control) assert_equal(test.mask, control.mask) def test_flatten(self): # Test standard & flexible (_, x, _, z) = self.data test = merge_arrays((x, z), flatten=True) control = np.array([(1, 'A', 1.), (2, 'B', 2.)], dtype=[('f0', int), ('A', '|S3'), ('B', float)]) assert_equal(test, control) test = merge_arrays((x, z), flatten=False) control = np.array([(1, ('A', 1.)), (2, ('B', 2.))], dtype=[('f0', int), ('f1', [('A', '|S3'), ('B', float)])]) assert_equal(test, control) def test_flatten_wflexible(self): # Test flatten standard & nested (w, x, _, _) = self.data test = merge_arrays((x, w), flatten=True) control = np.array([(1, 1, 2, 3.0), (2, 4, 5, 6.0)], dtype=[('f0', int), ('a', int), ('ba', float), ('bb', int)]) assert_equal(test, control) test = merge_arrays((x, w), flatten=False) controldtype = [('f0', int), ('f1', [('a', int), ('b', [('ba', float), ('bb', int), ('bc', [])])])] control = np.array([(1., (1, (2, 3.0, ()))), (2, (4, (5, 6.0, ())))], dtype=controldtype) assert_equal(test, control) def test_wmasked_arrays(self): # Test merge_arrays masked arrays (_, x, _, _) = self.data mx = ma.array([1, 2, 3], mask=[1, 0, 0]) test = merge_arrays((x, mx), usemask=True) control = ma.array([(1, 1), (2, 2), (-1, 3)], mask=[(0, 1), (0, 0), (1, 0)], dtype=[('f0', int), ('f1', int)]) assert_equal(test, control) test = merge_arrays((x, mx), usemask=True, asrecarray=True) assert_equal(test, control) assert_(isinstance(test, MaskedRecords)) def test_w_singlefield(self): # Test single field test = merge_arrays((np.array([1, 2]).view([('a', int)]), np.array([10., 20., 30.])),) control = ma.array([(1, 10.), (2, 20.), (-1, 30.)], mask=[(0, 0), (0, 0), (1, 0)], dtype=[('a', int), ('f1', float)]) assert_equal(test, control) def test_w_shorter_flex(self): # Test merge_arrays w/ a shorter flexndarray. z = self.data[-1] # Fixme, this test looks incomplete and broken #test = merge_arrays((z, np.array([10, 20, 30]).view([('C', int)]))) #control = np.array([('A', 1., 10), ('B', 2., 20), ('-1', -1, 20)], # dtype=[('A', '|S3'), ('B', float), ('C', int)]) #assert_equal(test, control) # Hack to avoid pyflakes warnings about unused variables merge_arrays((z, np.array([10, 20, 30]).view([('C', int)]))) np.array([('A', 1., 10), ('B', 2., 20), ('-1', -1, 20)], dtype=[('A', '|S3'), ('B', float), ('C', int)]) def test_singlerecord(self): (_, x, y, z) = self.data test = merge_arrays((x[0], y[0], z[0]), usemask=False) control = np.array([(1, 10, ('A', 1))], dtype=[('f0', int), ('f1', int), ('f2', [('A', '|S3'), ('B', float)])]) assert_equal(test, control) class TestAppendFields: # Test append_fields def setup_method(self): x = np.array([1, 2, ]) y = np.array([10, 20, 30]) z = np.array( [('A', 1.), ('B', 2.)], dtype=[('A', '|S3'), ('B', float)]) w = np.array([(1, (2, 3.0)), (4, (5, 6.0))], dtype=[('a', int), ('b', [('ba', float), ('bb', int)])]) self.data = (w, x, y, z) def test_append_single(self): # Test simple case (_, x, _, _) = self.data test = append_fields(x, 'A', data=[10, 20, 30]) control = ma.array([(1, 10), (2, 20), (-1, 30)], mask=[(0, 0), (0, 0), (1, 0)], dtype=[('f0', int), ('A', int)],) assert_equal(test, control) def test_append_double(self): # Test simple case (_, x, _, _) = self.data test = append_fields(x, ('A', 'B'), data=[[10, 20, 30], [100, 200]]) control = ma.array([(1, 10, 100), (2, 20, 200), (-1, 30, -1)], mask=[(0, 0, 0), (0, 0, 0), (1, 0, 1)], dtype=[('f0', int), ('A', int), ('B', int)],) assert_equal(test, control) def test_append_on_flex(self): # Test append_fields on flexible type arrays z = self.data[-1] test = append_fields(z, 'C', data=[10, 20, 30]) control = ma.array([('A', 1., 10), ('B', 2., 20), (-1, -1., 30)], mask=[(0, 0, 0), (0, 0, 0), (1, 1, 0)], dtype=[('A', '|S3'), ('B', float), ('C', int)],) assert_equal(test, control) def test_append_on_nested(self): # Test append_fields on nested fields w = self.data[0] test = append_fields(w, 'C', data=[10, 20, 30]) control = ma.array([(1, (2, 3.0), 10), (4, (5, 6.0), 20), (-1, (-1, -1.), 30)], mask=[( 0, (0, 0), 0), (0, (0, 0), 0), (1, (1, 1), 0)], dtype=[('a', int), ('b', [('ba', float), ('bb', int)]), ('C', int)],) assert_equal(test, control) class TestStackArrays: # Test stack_arrays def setup_method(self): x = np.array([1, 2, ]) y = np.array([10, 20, 30]) z = np.array( [('A', 1.), ('B', 2.)], dtype=[('A', '|S3'), ('B', float)]) w = np.array([(1, (2, 3.0)), (4, (5, 6.0))], dtype=[('a', int), ('b', [('ba', float), ('bb', int)])]) self.data = (w, x, y, z) def test_solo(self): # Test stack_arrays on single arrays (_, x, _, _) = self.data test = stack_arrays((x,)) assert_equal(test, x) assert_(test is x) test = stack_arrays(x) assert_equal(test, x) assert_(test is x) def test_unnamed_fields(self): # Tests combinations of arrays w/o named fields (_, x, y, _) = self.data test = stack_arrays((x, x), usemask=False) control = np.array([1, 2, 1, 2]) assert_equal(test, control) test = stack_arrays((x, y), usemask=False) control = np.array([1, 2, 10, 20, 30]) assert_equal(test, control) test = stack_arrays((y, x), usemask=False) control = np.array([10, 20, 30, 1, 2]) assert_equal(test, control) def test_unnamed_and_named_fields(self): # Test combination of arrays w/ & w/o named fields (_, x, _, z) = self.data test = stack_arrays((x, z)) control = ma.array([(1, -1, -1), (2, -1, -1), (-1, 'A', 1), (-1, 'B', 2)], mask=[(0, 1, 1), (0, 1, 1), (1, 0, 0), (1, 0, 0)], dtype=[('f0', int), ('A', '|S3'), ('B', float)]) assert_equal(test, control) assert_equal(test.mask, control.mask) test = stack_arrays((z, x)) control = ma.array([('A', 1, -1), ('B', 2, -1), (-1, -1, 1), (-1, -1, 2), ], mask=[(0, 0, 1), (0, 0, 1), (1, 1, 0), (1, 1, 0)], dtype=[('A', '|S3'), ('B', float), ('f2', int)]) assert_equal(test, control) assert_equal(test.mask, control.mask) test = stack_arrays((z, z, x)) control = ma.array([('A', 1, -1), ('B', 2, -1), ('A', 1, -1), ('B', 2, -1), (-1, -1, 1), (-1, -1, 2), ], mask=[(0, 0, 1), (0, 0, 1), (0, 0, 1), (0, 0, 1), (1, 1, 0), (1, 1, 0)], dtype=[('A', '|S3'), ('B', float), ('f2', int)]) assert_equal(test, control) def test_matching_named_fields(self): # Test combination of arrays w/ matching field names (_, x, _, z) = self.data zz = np.array([('a', 10., 100.), ('b', 20., 200.), ('c', 30., 300.)], dtype=[('A', '|S3'), ('B', float), ('C', float)]) test = stack_arrays((z, zz)) control = ma.array([('A', 1, -1), ('B', 2, -1), ( 'a', 10., 100.), ('b', 20., 200.), ('c', 30., 300.)], dtype=[('A', '|S3'), ('B', float), ('C', float)], mask=[(0, 0, 1), (0, 0, 1), (0, 0, 0), (0, 0, 0), (0, 0, 0)]) assert_equal(test, control) assert_equal(test.mask, control.mask) test = stack_arrays((z, zz, x)) ndtype = [('A', '|S3'), ('B', float), ('C', float), ('f3', int)] control = ma.array([('A', 1, -1, -1), ('B', 2, -1, -1), ('a', 10., 100., -1), ('b', 20., 200., -1), ('c', 30., 300., -1), (-1, -1, -1, 1), (-1, -1, -1, 2)], dtype=ndtype, mask=[(0, 0, 1, 1), (0, 0, 1, 1), (0, 0, 0, 1), (0, 0, 0, 1), (0, 0, 0, 1), (1, 1, 1, 0), (1, 1, 1, 0)]) assert_equal(test, control) assert_equal(test.mask, control.mask) def test_defaults(self): # Test defaults: no exception raised if keys of defaults are not fields. (_, _, _, z) = self.data zz = np.array([('a', 10., 100.), ('b', 20., 200.), ('c', 30., 300.)], dtype=[('A', '|S3'), ('B', float), ('C', float)]) defaults = {'A': '???', 'B': -999., 'C': -9999., 'D': -99999.} test = stack_arrays((z, zz), defaults=defaults) control = ma.array([('A', 1, -9999.), ('B', 2, -9999.), ( 'a', 10., 100.), ('b', 20., 200.), ('c', 30., 300.)], dtype=[('A', '|S3'), ('B', float), ('C', float)], mask=[(0, 0, 1), (0, 0, 1), (0, 0, 0), (0, 0, 0), (0, 0, 0)]) assert_equal(test, control) assert_equal(test.data, control.data) assert_equal(test.mask, control.mask) def test_autoconversion(self): # Tests autoconversion adtype = [('A', int), ('B', bool), ('C', float)] a = ma.array([(1, 2, 3)], mask=[(0, 1, 0)], dtype=adtype) bdtype = [('A', int), ('B', float), ('C', float)] b = ma.array([(4, 5, 6)], dtype=bdtype) control = ma.array([(1, 2, 3), (4, 5, 6)], mask=[(0, 1, 0), (0, 0, 0)], dtype=bdtype) test = stack_arrays((a, b), autoconvert=True) assert_equal(test, control) assert_equal(test.mask, control.mask) with assert_raises(TypeError): stack_arrays((a, b), autoconvert=False) def test_checktitles(self): # Test using titles in the field names adtype = [(('a', 'A'), int), (('b', 'B'), bool), (('c', 'C'), float)] a = ma.array([(1, 2, 3)], mask=[(0, 1, 0)], dtype=adtype) bdtype = [(('a', 'A'), int), (('b', 'B'), bool), (('c', 'C'), float)] b = ma.array([(4, 5, 6)], dtype=bdtype) test = stack_arrays((a, b)) control = ma.array([(1, 2, 3), (4, 5, 6)], mask=[(0, 1, 0), (0, 0, 0)], dtype=bdtype) assert_equal(test, control) assert_equal(test.mask, control.mask) def test_subdtype(self): z = np.array([ ('A', 1), ('B', 2) ], dtype=[('A', '|S3'), ('B', float, (1,))]) zz = np.array([ ('a', [10.], 100.), ('b', [20.], 200.), ('c', [30.], 300.) ], dtype=[('A', '|S3'), ('B', float, (1,)), ('C', float)]) res = stack_arrays((z, zz)) expected = ma.array( data=[ (b'A', [1.0], 0), (b'B', [2.0], 0), (b'a', [10.0], 100.0), (b'b', [20.0], 200.0), (b'c', [30.0], 300.0)], mask=[ (False, [False], True), (False, [False], True), (False, [False], False), (False, [False], False), (False, [False], False) ], dtype=zz.dtype ) assert_equal(res.dtype, expected.dtype) assert_equal(res, expected) assert_equal(res.mask, expected.mask) class TestJoinBy: def setup_method(self): self.a = np.array(list(zip(np.arange(10), np.arange(50, 60), np.arange(100, 110))), dtype=[('a', int), ('b', int), ('c', int)]) self.b = np.array(list(zip(np.arange(5, 15), np.arange(65, 75), np.arange(100, 110))), dtype=[('a', int), ('b', int), ('d', int)]) def test_inner_join(self): # Basic test of join_by a, b = self.a, self.b test = join_by('a', a, b, jointype='inner') control = np.array([(5, 55, 65, 105, 100), (6, 56, 66, 106, 101), (7, 57, 67, 107, 102), (8, 58, 68, 108, 103), (9, 59, 69, 109, 104)], dtype=[('a', int), ('b1', int), ('b2', int), ('c', int), ('d', int)]) assert_equal(test, control) def test_join(self): a, b = self.a, self.b # Fixme, this test is broken #test = join_by(('a', 'b'), a, b) #control = np.array([(5, 55, 105, 100), (6, 56, 106, 101), # (7, 57, 107, 102), (8, 58, 108, 103), # (9, 59, 109, 104)], # dtype=[('a', int), ('b', int), # ('c', int), ('d', int)]) #assert_equal(test, control) # Hack to avoid pyflakes unused variable warnings join_by(('a', 'b'), a, b) np.array([(5, 55, 105, 100), (6, 56, 106, 101), (7, 57, 107, 102), (8, 58, 108, 103), (9, 59, 109, 104)], dtype=[('a', int), ('b', int), ('c', int), ('d', int)]) def test_join_subdtype(self): # tests the bug in https://stackoverflow.com/q/44769632/102441 foo = np.array([(1,)], dtype=[('key', int)]) bar = np.array([(1, np.array([1,2,3]))], dtype=[('key', int), ('value', 'uint16', 3)]) res = join_by('key', foo, bar) assert_equal(res, bar.view(ma.MaskedArray)) def test_outer_join(self): a, b = self.a, self.b test = join_by(('a', 'b'), a, b, 'outer') control = ma.array([(0, 50, 100, -1), (1, 51, 101, -1), (2, 52, 102, -1), (3, 53, 103, -1), (4, 54, 104, -1), (5, 55, 105, -1), (5, 65, -1, 100), (6, 56, 106, -1), (6, 66, -1, 101), (7, 57, 107, -1), (7, 67, -1, 102), (8, 58, 108, -1), (8, 68, -1, 103), (9, 59, 109, -1), (9, 69, -1, 104), (10, 70, -1, 105), (11, 71, -1, 106), (12, 72, -1, 107), (13, 73, -1, 108), (14, 74, -1, 109)], mask=[(0, 0, 0, 1), (0, 0, 0, 1), (0, 0, 0, 1), (0, 0, 0, 1), (0, 0, 0, 1), (0, 0, 0, 1), (0, 0, 1, 0), (0, 0, 0, 1), (0, 0, 1, 0), (0, 0, 0, 1), (0, 0, 1, 0), (0, 0, 0, 1), (0, 0, 1, 0), (0, 0, 0, 1), (0, 0, 1, 0), (0, 0, 1, 0), (0, 0, 1, 0), (0, 0, 1, 0), (0, 0, 1, 0), (0, 0, 1, 0)], dtype=[('a', int), ('b', int), ('c', int), ('d', int)]) assert_equal(test, control) def test_leftouter_join(self): a, b = self.a, self.b test = join_by(('a', 'b'), a, b, 'leftouter') control = ma.array([(0, 50, 100, -1), (1, 51, 101, -1), (2, 52, 102, -1), (3, 53, 103, -1), (4, 54, 104, -1), (5, 55, 105, -1), (6, 56, 106, -1), (7, 57, 107, -1), (8, 58, 108, -1), (9, 59, 109, -1)], mask=[(0, 0, 0, 1), (0, 0, 0, 1), (0, 0, 0, 1), (0, 0, 0, 1), (0, 0, 0, 1), (0, 0, 0, 1), (0, 0, 0, 1), (0, 0, 0, 1), (0, 0, 0, 1), (0, 0, 0, 1)], dtype=[('a', int), ('b', int), ('c', int), ('d', int)]) assert_equal(test, control) def test_different_field_order(self): # gh-8940 a = np.zeros(3, dtype=[('a', 'i4'), ('b', 'f4'), ('c', 'u1')]) b = np.ones(3, dtype=[('c', 'u1'), ('b', 'f4'), ('a', 'i4')]) # this should not give a FutureWarning: j = join_by(['c', 'b'], a, b, jointype='inner', usemask=False) assert_equal(j.dtype.names, ['b', 'c', 'a1', 'a2']) def test_duplicate_keys(self): a = np.zeros(3, dtype=[('a', 'i4'), ('b', 'f4'), ('c', 'u1')]) b = np.ones(3, dtype=[('c', 'u1'), ('b', 'f4'), ('a', 'i4')]) assert_raises(ValueError, join_by, ['a', 'b', 'b'], a, b) def test_same_name_different_dtypes_key(self): a_dtype = np.dtype([('key', 'S5'), ('value', '<f4')]) b_dtype = np.dtype([('key', 'S10'), ('value', '<f4')]) expected_dtype = np.dtype([ ('key', 'S10'), ('value1', '<f4'), ('value2', '<f4')]) a = np.array([('Sarah', 8.0), ('John', 6.0)], dtype=a_dtype) b = np.array([('Sarah', 10.0), ('John', 7.0)], dtype=b_dtype) res = join_by('key', a, b) assert_equal(res.dtype, expected_dtype) def test_same_name_different_dtypes(self): # gh-9338 a_dtype = np.dtype([('key', 'S10'), ('value', '<f4')]) b_dtype = np.dtype([('key', 'S10'), ('value', '<f8')]) expected_dtype = np.dtype([ ('key', '|S10'), ('value1', '<f4'), ('value2', '<f8')]) a = np.array([('Sarah', 8.0), ('John', 6.0)], dtype=a_dtype) b = np.array([('Sarah', 10.0), ('John', 7.0)], dtype=b_dtype) res = join_by('key', a, b) assert_equal(res.dtype, expected_dtype) def test_subarray_key(self): a_dtype = np.dtype([('pos', int, 3), ('f', '<f4')]) a = np.array([([1, 1, 1], np.pi), ([1, 2, 3], 0.0)], dtype=a_dtype) b_dtype = np.dtype([('pos', int, 3), ('g', '<f4')]) b = np.array([([1, 1, 1], 3), ([3, 2, 1], 0.0)], dtype=b_dtype) expected_dtype = np.dtype([('pos', int, 3), ('f', '<f4'), ('g', '<f4')]) expected = np.array([([1, 1, 1], np.pi, 3)], dtype=expected_dtype) res = join_by('pos', a, b) assert_equal(res.dtype, expected_dtype) assert_equal(res, expected) def test_padded_dtype(self): dt = np.dtype('i1,f4', align=True) dt.names = ('k', 'v') assert_(len(dt.descr), 3) # padding field is inserted a = np.array([(1, 3), (3, 2)], dt) b = np.array([(1, 1), (2, 2)], dt) res = join_by('k', a, b) # no padding fields remain expected_dtype = np.dtype([ ('k', 'i1'), ('v1', 'f4'), ('v2', 'f4') ]) assert_equal(res.dtype, expected_dtype) class TestJoinBy2: @classmethod def setup_method(cls): cls.a = np.array(list(zip(np.arange(10), np.arange(50, 60), np.arange(100, 110))), dtype=[('a', int), ('b', int), ('c', int)]) cls.b = np.array(list(zip(np.arange(10), np.arange(65, 75), np.arange(100, 110))), dtype=[('a', int), ('b', int), ('d', int)]) def test_no_r1postfix(self): # Basic test of join_by no_r1postfix a, b = self.a, self.b test = join_by( 'a', a, b, r1postfix='', r2postfix='2', jointype='inner') control = np.array([(0, 50, 65, 100, 100), (1, 51, 66, 101, 101), (2, 52, 67, 102, 102), (3, 53, 68, 103, 103), (4, 54, 69, 104, 104), (5, 55, 70, 105, 105), (6, 56, 71, 106, 106), (7, 57, 72, 107, 107), (8, 58, 73, 108, 108), (9, 59, 74, 109, 109)], dtype=[('a', int), ('b', int), ('b2', int), ('c', int), ('d', int)]) assert_equal(test, control) def test_no_postfix(self): assert_raises(ValueError, join_by, 'a', self.a, self.b, r1postfix='', r2postfix='') def test_no_r2postfix(self): # Basic test of join_by no_r2postfix a, b = self.a, self.b test = join_by( 'a', a, b, r1postfix='1', r2postfix='', jointype='inner') control = np.array([(0, 50, 65, 100, 100), (1, 51, 66, 101, 101), (2, 52, 67, 102, 102), (3, 53, 68, 103, 103), (4, 54, 69, 104, 104), (5, 55, 70, 105, 105), (6, 56, 71, 106, 106), (7, 57, 72, 107, 107), (8, 58, 73, 108, 108), (9, 59, 74, 109, 109)], dtype=[('a', int), ('b1', int), ('b', int), ('c', int), ('d', int)]) assert_equal(test, control) def test_two_keys_two_vars(self): a = np.array(list(zip(np.tile([10, 11], 5), np.repeat(np.arange(5), 2), np.arange(50, 60), np.arange(10, 20))), dtype=[('k', int), ('a', int), ('b', int), ('c', int)]) b = np.array(list(zip(np.tile([10, 11], 5), np.repeat(np.arange(5), 2), np.arange(65, 75), np.arange(0, 10))), dtype=[('k', int), ('a', int), ('b', int), ('c', int)]) control = np.array([(10, 0, 50, 65, 10, 0), (11, 0, 51, 66, 11, 1), (10, 1, 52, 67, 12, 2), (11, 1, 53, 68, 13, 3), (10, 2, 54, 69, 14, 4), (11, 2, 55, 70, 15, 5), (10, 3, 56, 71, 16, 6), (11, 3, 57, 72, 17, 7), (10, 4, 58, 73, 18, 8), (11, 4, 59, 74, 19, 9)], dtype=[('k', int), ('a', int), ('b1', int), ('b2', int), ('c1', int), ('c2', int)]) test = join_by( ['a', 'k'], a, b, r1postfix='1', r2postfix='2', jointype='inner') assert_equal(test.dtype, control.dtype) assert_equal(test, control) class TestAppendFieldsObj: """ Test append_fields with arrays containing objects """ # https://github.com/numpy/numpy/issues/2346 def setup_method(self): from datetime import date self.data = dict(obj=date(2000, 1, 1)) def test_append_to_objects(self): "Test append_fields when the base array contains objects" obj = self.data['obj'] x = np.array([(obj, 1.), (obj, 2.)], dtype=[('A', object), ('B', float)]) y = np.array([10, 20], dtype=int) test = append_fields(x, 'C', data=y, usemask=False) control = np.array([(obj, 1.0, 10), (obj, 2.0, 20)], dtype=[('A', object), ('B', float), ('C', int)]) assert_equal(test, control)
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