AlkantarClanX12
Your IP : 3.144.31.17
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)