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test_dtype.py
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test_dtype.py
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import sys
import operator
import pytest
import ctypes
import gc
import warnings
import numpy as np
from numpy.core._rational_tests import rational
from numpy.core._multiarray_tests import create_custom_field_dtype
from numpy.testing import (
assert_, assert_equal, assert_array_equal, assert_raises, HAS_REFCOUNT,
IS_PYSTON)
from numpy.compat import pickle
from itertools import permutations
def assert_dtype_equal(a, b):
assert_equal(a, b)
assert_equal(hash(a), hash(b),
"two equivalent types do not hash to the same value !")
def assert_dtype_not_equal(a, b):
assert_(a != b)
assert_(hash(a) != hash(b),
"two different types hash to the same value !")
class TestBuiltin:
@pytest.mark.parametrize('t', [int, float, complex, np.int32, str, object,
np.compat.unicode])
def test_run(self, t):
"""Only test hash runs at all."""
dt = np.dtype(t)
hash(dt)
@pytest.mark.parametrize('t', [int, float])
def test_dtype(self, t):
# Make sure equivalent byte order char hash the same (e.g. < and = on
# little endian)
dt = np.dtype(t)
dt2 = dt.newbyteorder("<")
dt3 = dt.newbyteorder(">")
if dt == dt2:
assert_(dt.byteorder != dt2.byteorder, "bogus test")
assert_dtype_equal(dt, dt2)
else:
assert_(dt.byteorder != dt3.byteorder, "bogus test")
assert_dtype_equal(dt, dt3)
def test_equivalent_dtype_hashing(self):
# Make sure equivalent dtypes with different type num hash equal
uintp = np.dtype(np.uintp)
if uintp.itemsize == 4:
left = uintp
right = np.dtype(np.uint32)
else:
left = uintp
right = np.dtype(np.ulonglong)
assert_(left == right)
assert_(hash(left) == hash(right))
def test_invalid_types(self):
# Make sure invalid type strings raise an error
assert_raises(TypeError, np.dtype, 'O3')
assert_raises(TypeError, np.dtype, 'O5')
assert_raises(TypeError, np.dtype, 'O7')
assert_raises(TypeError, np.dtype, 'b3')
assert_raises(TypeError, np.dtype, 'h4')
assert_raises(TypeError, np.dtype, 'I5')
assert_raises(TypeError, np.dtype, 'e3')
assert_raises(TypeError, np.dtype, 'f5')
if np.dtype('g').itemsize == 8 or np.dtype('g').itemsize == 16:
assert_raises(TypeError, np.dtype, 'g12')
elif np.dtype('g').itemsize == 12:
assert_raises(TypeError, np.dtype, 'g16')
if np.dtype('l').itemsize == 8:
assert_raises(TypeError, np.dtype, 'l4')
assert_raises(TypeError, np.dtype, 'L4')
else:
assert_raises(TypeError, np.dtype, 'l8')
assert_raises(TypeError, np.dtype, 'L8')
if np.dtype('q').itemsize == 8:
assert_raises(TypeError, np.dtype, 'q4')
assert_raises(TypeError, np.dtype, 'Q4')
else:
assert_raises(TypeError, np.dtype, 'q8')
assert_raises(TypeError, np.dtype, 'Q8')
def test_richcompare_invalid_dtype_equality(self):
# Make sure objects that cannot be converted to valid
# dtypes results in False/True when compared to valid dtypes.
# Here 7 cannot be converted to dtype. No exceptions should be raised
assert not np.dtype(np.int32) == 7, "dtype richcompare failed for =="
assert np.dtype(np.int32) != 7, "dtype richcompare failed for !="
@pytest.mark.parametrize(
'operation',
[operator.le, operator.lt, operator.ge, operator.gt])
def test_richcompare_invalid_dtype_comparison(self, operation):
# Make sure TypeError is raised for comparison operators
# for invalid dtypes. Here 7 is an invalid dtype.
with pytest.raises(TypeError):
operation(np.dtype(np.int32), 7)
@pytest.mark.parametrize("dtype",
['Bool', 'Bytes0', 'Complex32', 'Complex64', 'Datetime64', 'Float16', 'Float32', 'Float64',
'Int8', 'Int16', 'Int32', 'Int64', 'Object0', 'Str0', 'Timedelta64',
'UInt8', 'UInt16', 'Uint32', 'UInt32', 'Uint64', 'UInt64', 'Void0',
"Float128", "Complex128"])
def test_numeric_style_types_are_invalid(self, dtype):
with assert_raises(TypeError):
np.dtype(dtype)
@pytest.mark.parametrize(
'value',
['m8', 'M8', 'datetime64', 'timedelta64',
'i4, (2,3)f8, f4', 'a3, 3u8, (3,4)a10',
'>f', '<f', '=f', '|f',
])
def test_dtype_bytes_str_equivalence(self, value):
bytes_value = value.encode('ascii')
from_bytes = np.dtype(bytes_value)
from_str = np.dtype(value)
assert_dtype_equal(from_bytes, from_str)
def test_dtype_from_bytes(self):
# Empty bytes object
assert_raises(TypeError, np.dtype, b'')
# Byte order indicator, but no type
assert_raises(TypeError, np.dtype, b'|')
# Single character with ordinal < NPY_NTYPES returns
# type by index into _builtin_descrs
assert_dtype_equal(np.dtype(bytes([0])), np.dtype('bool'))
assert_dtype_equal(np.dtype(bytes([17])), np.dtype(object))
# Single character where value is a valid type code
assert_dtype_equal(np.dtype(b'f'), np.dtype('float32'))
# Bytes with non-ascii values raise errors
assert_raises(TypeError, np.dtype, b'\xff')
assert_raises(TypeError, np.dtype, b's\xff')
def test_bad_param(self):
# Can't give a size that's too small
assert_raises(ValueError, np.dtype,
{'names':['f0', 'f1'],
'formats':['i4', 'i1'],
'offsets':[0, 4],
'itemsize':4})
# If alignment is enabled, the alignment (4) must divide the itemsize
assert_raises(ValueError, np.dtype,
{'names':['f0', 'f1'],
'formats':['i4', 'i1'],
'offsets':[0, 4],
'itemsize':9}, align=True)
# If alignment is enabled, the individual fields must be aligned
assert_raises(ValueError, np.dtype,
{'names':['f0', 'f1'],
'formats':['i1', 'f4'],
'offsets':[0, 2]}, align=True)
def test_field_order_equality(self):
x = np.dtype({'names': ['A', 'B'],
'formats': ['i4', 'f4'],
'offsets': [0, 4]})
y = np.dtype({'names': ['B', 'A'],
'formats': ['f4', 'i4'],
'offsets': [4, 0]})
assert_equal(x == y, False)
# But it is currently an equivalent cast:
assert np.can_cast(x, y, casting="equiv")
class TestRecord:
def test_equivalent_record(self):
"""Test whether equivalent record dtypes hash the same."""
a = np.dtype([('yo', int)])
b = np.dtype([('yo', int)])
assert_dtype_equal(a, b)
def test_different_names(self):
# In theory, they may hash the same (collision) ?
a = np.dtype([('yo', int)])
b = np.dtype([('ye', int)])
assert_dtype_not_equal(a, b)
def test_different_titles(self):
# In theory, they may hash the same (collision) ?
a = np.dtype({'names': ['r', 'b'],
'formats': ['u1', 'u1'],
'titles': ['Red pixel', 'Blue pixel']})
b = np.dtype({'names': ['r', 'b'],
'formats': ['u1', 'u1'],
'titles': ['RRed pixel', 'Blue pixel']})
assert_dtype_not_equal(a, b)
@pytest.mark.skipif(not HAS_REFCOUNT, reason="Python lacks refcounts")
def test_refcount_dictionary_setting(self):
names = ["name1"]
formats = ["f8"]
titles = ["t1"]
offsets = [0]
d = dict(names=names, formats=formats, titles=titles, offsets=offsets)
refcounts = {k: sys.getrefcount(i) for k, i in d.items()}
np.dtype(d)
refcounts_new = {k: sys.getrefcount(i) for k, i in d.items()}
assert refcounts == refcounts_new
def test_mutate(self):
# Mutating a dtype should reset the cached hash value
a = np.dtype([('yo', int)])
b = np.dtype([('yo', int)])
c = np.dtype([('ye', int)])
assert_dtype_equal(a, b)
assert_dtype_not_equal(a, c)
a.names = ['ye']
assert_dtype_equal(a, c)
assert_dtype_not_equal(a, b)
state = b.__reduce__()[2]
a.__setstate__(state)
assert_dtype_equal(a, b)
assert_dtype_not_equal(a, c)
def test_not_lists(self):
"""Test if an appropriate exception is raised when passing bad values to
the dtype constructor.
"""
assert_raises(TypeError, np.dtype,
dict(names={'A', 'B'}, formats=['f8', 'i4']))
assert_raises(TypeError, np.dtype,
dict(names=['A', 'B'], formats={'f8', 'i4'}))
def test_aligned_size(self):
# Check that structured dtypes get padded to an aligned size
dt = np.dtype('i4, i1', align=True)
assert_equal(dt.itemsize, 8)
dt = np.dtype([('f0', 'i4'), ('f1', 'i1')], align=True)
assert_equal(dt.itemsize, 8)
dt = np.dtype({'names':['f0', 'f1'],
'formats':['i4', 'u1'],
'offsets':[0, 4]}, align=True)
assert_equal(dt.itemsize, 8)
dt = np.dtype({'f0': ('i4', 0), 'f1':('u1', 4)}, align=True)
assert_equal(dt.itemsize, 8)
# Nesting should preserve that alignment
dt1 = np.dtype([('f0', 'i4'),
('f1', [('f1', 'i1'), ('f2', 'i4'), ('f3', 'i1')]),
('f2', 'i1')], align=True)
assert_equal(dt1.itemsize, 20)
dt2 = np.dtype({'names':['f0', 'f1', 'f2'],
'formats':['i4',
[('f1', 'i1'), ('f2', 'i4'), ('f3', 'i1')],
'i1'],
'offsets':[0, 4, 16]}, align=True)
assert_equal(dt2.itemsize, 20)
dt3 = np.dtype({'f0': ('i4', 0),
'f1': ([('f1', 'i1'), ('f2', 'i4'), ('f3', 'i1')], 4),
'f2': ('i1', 16)}, align=True)
assert_equal(dt3.itemsize, 20)
assert_equal(dt1, dt2)
assert_equal(dt2, dt3)
# Nesting should preserve packing
dt1 = np.dtype([('f0', 'i4'),
('f1', [('f1', 'i1'), ('f2', 'i4'), ('f3', 'i1')]),
('f2', 'i1')], align=False)
assert_equal(dt1.itemsize, 11)
dt2 = np.dtype({'names':['f0', 'f1', 'f2'],
'formats':['i4',
[('f1', 'i1'), ('f2', 'i4'), ('f3', 'i1')],
'i1'],
'offsets':[0, 4, 10]}, align=False)
assert_equal(dt2.itemsize, 11)
dt3 = np.dtype({'f0': ('i4', 0),
'f1': ([('f1', 'i1'), ('f2', 'i4'), ('f3', 'i1')], 4),
'f2': ('i1', 10)}, align=False)
assert_equal(dt3.itemsize, 11)
assert_equal(dt1, dt2)
assert_equal(dt2, dt3)
# Array of subtype should preserve alignment
dt1 = np.dtype([('a', '|i1'),
('b', [('f0', '<i2'),
('f1', '<f4')], 2)], align=True)
assert_equal(dt1.descr, [('a', '|i1'), ('', '|V3'),
('b', [('f0', '<i2'), ('', '|V2'),
('f1', '<f4')], (2,))])
def test_union_struct(self):
# Should be able to create union dtypes
dt = np.dtype({'names':['f0', 'f1', 'f2'], 'formats':['<u4', '<u2', '<u2'],
'offsets':[0, 0, 2]}, align=True)
assert_equal(dt.itemsize, 4)
a = np.array([3], dtype='<u4').view(dt)
a['f1'] = 10
a['f2'] = 36
assert_equal(a['f0'], 10 + 36*256*256)
# Should be able to specify fields out of order
dt = np.dtype({'names':['f0', 'f1', 'f2'], 'formats':['<u4', '<u2', '<u2'],
'offsets':[4, 0, 2]}, align=True)
assert_equal(dt.itemsize, 8)
# field name should not matter: assignment is by position
dt2 = np.dtype({'names':['f2', 'f0', 'f1'],
'formats':['<u4', '<u2', '<u2'],
'offsets':[4, 0, 2]}, align=True)
vals = [(0, 1, 2), (3, -1, 4)]
vals2 = [(0, 1, 2), (3, -1, 4)]
a = np.array(vals, dt)
b = np.array(vals2, dt2)
assert_equal(a.astype(dt2), b)
assert_equal(b.astype(dt), a)
assert_equal(a.view(dt2), b)
assert_equal(b.view(dt), a)
# Should not be able to overlap objects with other types
assert_raises(TypeError, np.dtype,
{'names':['f0', 'f1'],
'formats':['O', 'i1'],
'offsets':[0, 2]})
assert_raises(TypeError, np.dtype,
{'names':['f0', 'f1'],
'formats':['i4', 'O'],
'offsets':[0, 3]})
assert_raises(TypeError, np.dtype,
{'names':['f0', 'f1'],
'formats':[[('a', 'O')], 'i1'],
'offsets':[0, 2]})
assert_raises(TypeError, np.dtype,
{'names':['f0', 'f1'],
'formats':['i4', [('a', 'O')]],
'offsets':[0, 3]})
# Out of order should still be ok, however
dt = np.dtype({'names':['f0', 'f1'],
'formats':['i1', 'O'],
'offsets':[np.dtype('intp').itemsize, 0]})
@pytest.mark.parametrize(["obj", "dtype", "expected"],
[([], ("(2)f4,"), np.empty((0, 2), dtype="f4")),
(3, "(3)f4,", [3, 3, 3]),
(np.float64(2), "(2)f4,", [2, 2]),
([((0, 1), (1, 2)), ((2,),)], '(2,2)f4', None),
(["1", "2"], "(2)i,", None)])
def test_subarray_list(self, obj, dtype, expected):
dtype = np.dtype(dtype)
res = np.array(obj, dtype=dtype)
if expected is None:
# iterate the 1-d list to fill the array
expected = np.empty(len(obj), dtype=dtype)
for i in range(len(expected)):
expected[i] = obj[i]
assert_array_equal(res, expected)
def test_comma_datetime(self):
dt = np.dtype('M8[D],datetime64[Y],i8')
assert_equal(dt, np.dtype([('f0', 'M8[D]'),
('f1', 'datetime64[Y]'),
('f2', 'i8')]))
def test_from_dictproxy(self):
# Tests for PR #5920
dt = np.dtype({'names': ['a', 'b'], 'formats': ['i4', 'f4']})
assert_dtype_equal(dt, np.dtype(dt.fields))
dt2 = np.dtype((np.void, dt.fields))
assert_equal(dt2.fields, dt.fields)
def test_from_dict_with_zero_width_field(self):
# Regression test for #6430 / #2196
dt = np.dtype([('val1', np.float32, (0,)), ('val2', int)])
dt2 = np.dtype({'names': ['val1', 'val2'],
'formats': [(np.float32, (0,)), int]})
assert_dtype_equal(dt, dt2)
assert_equal(dt.fields['val1'][0].itemsize, 0)
assert_equal(dt.itemsize, dt.fields['val2'][0].itemsize)
def test_bool_commastring(self):
d = np.dtype('?,?,?') # raises?
assert_equal(len(d.names), 3)
for n in d.names:
assert_equal(d.fields[n][0], np.dtype('?'))
def test_nonint_offsets(self):
# gh-8059
def make_dtype(off):
return np.dtype({'names': ['A'], 'formats': ['i4'],
'offsets': [off]})
assert_raises(TypeError, make_dtype, 'ASD')
assert_raises(OverflowError, make_dtype, 2**70)
assert_raises(TypeError, make_dtype, 2.3)
assert_raises(ValueError, make_dtype, -10)
# no errors here:
dt = make_dtype(np.uint32(0))
np.zeros(1, dtype=dt)[0].item()
def test_fields_by_index(self):
dt = np.dtype([('a', np.int8), ('b', np.float32, 3)])
assert_dtype_equal(dt[0], np.dtype(np.int8))
assert_dtype_equal(dt[1], np.dtype((np.float32, 3)))
assert_dtype_equal(dt[-1], dt[1])
assert_dtype_equal(dt[-2], dt[0])
assert_raises(IndexError, lambda: dt[-3])
assert_raises(TypeError, operator.getitem, dt, 3.0)
assert_equal(dt[1], dt[np.int8(1)])
@pytest.mark.parametrize('align_flag',[False, True])
def test_multifield_index(self, align_flag):
# indexing with a list produces subfields
# the align flag should be preserved
dt = np.dtype([
(('title', 'col1'), '<U20'), ('A', '<f8'), ('B', '<f8')
], align=align_flag)
dt_sub = dt[['B', 'col1']]
assert_equal(
dt_sub,
np.dtype({
'names': ['B', 'col1'],
'formats': ['<f8', '<U20'],
'offsets': [88, 0],
'titles': [None, 'title'],
'itemsize': 96
})
)
assert_equal(dt_sub.isalignedstruct, align_flag)
dt_sub = dt[['B']]
assert_equal(
dt_sub,
np.dtype({
'names': ['B'],
'formats': ['<f8'],
'offsets': [88],
'itemsize': 96
})
)
assert_equal(dt_sub.isalignedstruct, align_flag)
dt_sub = dt[[]]
assert_equal(
dt_sub,
np.dtype({
'names': [],
'formats': [],
'offsets': [],
'itemsize': 96
})
)
assert_equal(dt_sub.isalignedstruct, align_flag)
assert_raises(TypeError, operator.getitem, dt, ())
assert_raises(TypeError, operator.getitem, dt, [1, 2, 3])
assert_raises(TypeError, operator.getitem, dt, ['col1', 2])
assert_raises(KeyError, operator.getitem, dt, ['fake'])
assert_raises(KeyError, operator.getitem, dt, ['title'])
assert_raises(ValueError, operator.getitem, dt, ['col1', 'col1'])
def test_partial_dict(self):
# 'names' is missing
assert_raises(ValueError, np.dtype,
{'formats': ['i4', 'i4'], 'f0': ('i4', 0), 'f1':('i4', 4)})
def test_fieldless_views(self):
a = np.zeros(2, dtype={'names':[], 'formats':[], 'offsets':[],
'itemsize':8})
assert_raises(ValueError, a.view, np.dtype([]))
d = np.dtype((np.dtype([]), 10))
assert_equal(d.shape, (10,))
assert_equal(d.itemsize, 0)
assert_equal(d.base, np.dtype([]))
arr = np.fromiter((() for i in range(10)), [])
assert_equal(arr.dtype, np.dtype([]))
assert_raises(ValueError, np.frombuffer, b'', dtype=[])
assert_equal(np.frombuffer(b'', dtype=[], count=2),
np.empty(2, dtype=[]))
assert_raises(ValueError, np.dtype, ([], 'f8'))
assert_raises(ValueError, np.zeros(1, dtype='i4').view, [])
assert_equal(np.zeros(2, dtype=[]) == np.zeros(2, dtype=[]),
np.ones(2, dtype=bool))
assert_equal(np.zeros((1, 2), dtype=[]) == a,
np.ones((1, 2), dtype=bool))
class TestSubarray:
def test_single_subarray(self):
a = np.dtype((int, (2)))
b = np.dtype((int, (2,)))
assert_dtype_equal(a, b)
assert_equal(type(a.subdtype[1]), tuple)
assert_equal(type(b.subdtype[1]), tuple)
def test_equivalent_record(self):
"""Test whether equivalent subarray dtypes hash the same."""
a = np.dtype((int, (2, 3)))
b = np.dtype((int, (2, 3)))
assert_dtype_equal(a, b)
def test_nonequivalent_record(self):
"""Test whether different subarray dtypes hash differently."""
a = np.dtype((int, (2, 3)))
b = np.dtype((int, (3, 2)))
assert_dtype_not_equal(a, b)
a = np.dtype((int, (2, 3)))
b = np.dtype((int, (2, 2)))
assert_dtype_not_equal(a, b)
a = np.dtype((int, (1, 2, 3)))
b = np.dtype((int, (1, 2)))
assert_dtype_not_equal(a, b)
def test_shape_equal(self):
"""Test some data types that are equal"""
assert_dtype_equal(np.dtype('f8'), np.dtype(('f8', tuple())))
# FutureWarning during deprecation period; after it is passed this
# should instead check that "(1)f8" == "1f8" == ("f8", 1).
with pytest.warns(FutureWarning):
assert_dtype_equal(np.dtype('f8'), np.dtype(('f8', 1)))
assert_dtype_equal(np.dtype((int, 2)), np.dtype((int, (2,))))
assert_dtype_equal(np.dtype(('<f4', (3, 2))), np.dtype(('<f4', (3, 2))))
d = ([('a', 'f4', (1, 2)), ('b', 'f8', (3, 1))], (3, 2))
assert_dtype_equal(np.dtype(d), np.dtype(d))
def test_shape_simple(self):
"""Test some simple cases that shouldn't be equal"""
assert_dtype_not_equal(np.dtype('f8'), np.dtype(('f8', (1,))))
assert_dtype_not_equal(np.dtype(('f8', (1,))), np.dtype(('f8', (1, 1))))
assert_dtype_not_equal(np.dtype(('f4', (3, 2))), np.dtype(('f4', (2, 3))))
def test_shape_monster(self):
"""Test some more complicated cases that shouldn't be equal"""
assert_dtype_not_equal(
np.dtype(([('a', 'f4', (2, 1)), ('b', 'f8', (1, 3))], (2, 2))),
np.dtype(([('a', 'f4', (1, 2)), ('b', 'f8', (1, 3))], (2, 2))))
assert_dtype_not_equal(
np.dtype(([('a', 'f4', (2, 1)), ('b', 'f8', (1, 3))], (2, 2))),
np.dtype(([('a', 'f4', (2, 1)), ('b', 'i8', (1, 3))], (2, 2))))
assert_dtype_not_equal(
np.dtype(([('a', 'f4', (2, 1)), ('b', 'f8', (1, 3))], (2, 2))),
np.dtype(([('e', 'f8', (1, 3)), ('d', 'f4', (2, 1))], (2, 2))))
assert_dtype_not_equal(
np.dtype(([('a', [('a', 'i4', 6)], (2, 1)), ('b', 'f8', (1, 3))], (2, 2))),
np.dtype(([('a', [('a', 'u4', 6)], (2, 1)), ('b', 'f8', (1, 3))], (2, 2))))
def test_shape_sequence(self):
# Any sequence of integers should work as shape, but the result
# should be a tuple (immutable) of base type integers.
a = np.array([1, 2, 3], dtype=np.int16)
l = [1, 2, 3]
# Array gets converted
dt = np.dtype([('a', 'f4', a)])
assert_(isinstance(dt['a'].shape, tuple))
assert_(isinstance(dt['a'].shape[0], int))
# List gets converted
dt = np.dtype([('a', 'f4', l)])
assert_(isinstance(dt['a'].shape, tuple))
#
class IntLike:
def __index__(self):
return 3
def __int__(self):
# (a PyNumber_Check fails without __int__)
return 3
dt = np.dtype([('a', 'f4', IntLike())])
assert_(isinstance(dt['a'].shape, tuple))
assert_(isinstance(dt['a'].shape[0], int))
dt = np.dtype([('a', 'f4', (IntLike(),))])
assert_(isinstance(dt['a'].shape, tuple))
assert_(isinstance(dt['a'].shape[0], int))
def test_shape_matches_ndim(self):
dt = np.dtype([('a', 'f4', ())])
assert_equal(dt['a'].shape, ())
assert_equal(dt['a'].ndim, 0)
dt = np.dtype([('a', 'f4')])
assert_equal(dt['a'].shape, ())
assert_equal(dt['a'].ndim, 0)
dt = np.dtype([('a', 'f4', 4)])
assert_equal(dt['a'].shape, (4,))
assert_equal(dt['a'].ndim, 1)
dt = np.dtype([('a', 'f4', (1, 2, 3))])
assert_equal(dt['a'].shape, (1, 2, 3))
assert_equal(dt['a'].ndim, 3)
def test_shape_invalid(self):
# Check that the shape is valid.
max_int = np.iinfo(np.intc).max
max_intp = np.iinfo(np.intp).max
# Too large values (the datatype is part of this)
assert_raises(ValueError, np.dtype, [('a', 'f4', max_int // 4 + 1)])
assert_raises(ValueError, np.dtype, [('a', 'f4', max_int + 1)])
assert_raises(ValueError, np.dtype, [('a', 'f4', (max_int, 2))])
# Takes a different code path (fails earlier:
assert_raises(ValueError, np.dtype, [('a', 'f4', max_intp + 1)])
# Negative values
assert_raises(ValueError, np.dtype, [('a', 'f4', -1)])
assert_raises(ValueError, np.dtype, [('a', 'f4', (-1, -1))])
def test_alignment(self):
#Check that subarrays are aligned
t1 = np.dtype('(1,)i4', align=True)
t2 = np.dtype('2i4', align=True)
assert_equal(t1.alignment, t2.alignment)
def iter_struct_object_dtypes():
"""
Iterates over a few complex dtypes and object pattern which
fill the array with a given object (defaults to a singleton).
Yields
------
dtype : dtype
pattern : tuple
Structured tuple for use with `np.array`.
count : int
Number of objects stored in the dtype.
singleton : object
A singleton object. The returned pattern is constructed so that
all objects inside the datatype are set to the singleton.
"""
obj = object()
dt = np.dtype([('b', 'O', (2, 3))])
p = ([[obj] * 3] * 2,)
yield pytest.param(dt, p, 6, obj, id="<subarray>")
dt = np.dtype([('a', 'i4'), ('b', 'O', (2, 3))])
p = (0, [[obj] * 3] * 2)
yield pytest.param(dt, p, 6, obj, id="<subarray in field>")
dt = np.dtype([('a', 'i4'),
('b', [('ba', 'O'), ('bb', 'i1')], (2, 3))])
p = (0, [[(obj, 0)] * 3] * 2)
yield pytest.param(dt, p, 6, obj, id="<structured subarray 1>")
dt = np.dtype([('a', 'i4'),
('b', [('ba', 'O'), ('bb', 'O')], (2, 3))])
p = (0, [[(obj, obj)] * 3] * 2)
yield pytest.param(dt, p, 12, obj, id="<structured subarray 2>")
@pytest.mark.skipif(not HAS_REFCOUNT, reason="Python lacks refcounts")
class TestStructuredObjectRefcounting:
"""These tests cover various uses of complicated structured types which
include objects and thus require reference counting.
"""
@pytest.mark.parametrize(['dt', 'pat', 'count', 'singleton'],
iter_struct_object_dtypes())
@pytest.mark.parametrize(["creation_func", "creation_obj"], [
pytest.param(np.empty, None,
# None is probably used for too many things
marks=pytest.mark.skip("unreliable due to python's behaviour")),
(np.ones, 1),
(np.zeros, 0)])
def test_structured_object_create_delete(self, dt, pat, count, singleton,
creation_func, creation_obj):
"""Structured object reference counting in creation and deletion"""
# The test assumes that 0, 1, and None are singletons.
gc.collect()
before = sys.getrefcount(creation_obj)
arr = creation_func(3, dt)
now = sys.getrefcount(creation_obj)
assert now - before == count * 3
del arr
now = sys.getrefcount(creation_obj)
assert now == before
@pytest.mark.parametrize(['dt', 'pat', 'count', 'singleton'],
iter_struct_object_dtypes())
def test_structured_object_item_setting(self, dt, pat, count, singleton):
"""Structured object reference counting for simple item setting"""
one = 1
gc.collect()
before = sys.getrefcount(singleton)
arr = np.array([pat] * 3, dt)
assert sys.getrefcount(singleton) - before == count * 3
# Fill with `1` and check that it was replaced correctly:
before2 = sys.getrefcount(one)
arr[...] = one
after2 = sys.getrefcount(one)
assert after2 - before2 == count * 3
del arr
gc.collect()
assert sys.getrefcount(one) == before2
assert sys.getrefcount(singleton) == before
@pytest.mark.parametrize(['dt', 'pat', 'count', 'singleton'],
iter_struct_object_dtypes())
@pytest.mark.parametrize(
['shape', 'index', 'items_changed'],
[((3,), ([0, 2],), 2),
((3, 2), ([0, 2], slice(None)), 4),
((3, 2), ([0, 2], [1]), 2),
((3,), ([True, False, True]), 2)])
def test_structured_object_indexing(self, shape, index, items_changed,
dt, pat, count, singleton):
"""Structured object reference counting for advanced indexing."""
zero = 0
one = 1
arr = np.zeros(shape, dt)
gc.collect()
before_zero = sys.getrefcount(zero)
before_one = sys.getrefcount(one)
# Test item getting:
part = arr[index]
after_zero = sys.getrefcount(zero)
assert after_zero - before_zero == count * items_changed
del part
# Test item setting:
arr[index] = one
gc.collect()
after_zero = sys.getrefcount(zero)
after_one = sys.getrefcount(one)
assert before_zero - after_zero == count * items_changed
assert after_one - before_one == count * items_changed
@pytest.mark.parametrize(['dt', 'pat', 'count', 'singleton'],
iter_struct_object_dtypes())
def test_structured_object_take_and_repeat(self, dt, pat, count, singleton):
"""Structured object reference counting for specialized functions.
The older functions such as take and repeat use different code paths
then item setting (when writing this).
"""
indices = [0, 1]
arr = np.array([pat] * 3, dt)
gc.collect()
before = sys.getrefcount(singleton)
res = arr.take(indices)
after = sys.getrefcount(singleton)
assert after - before == count * 2
new = res.repeat(10)
gc.collect()
after_repeat = sys.getrefcount(singleton)
assert after_repeat - after == count * 2 * 10
class TestStructuredDtypeSparseFields:
"""Tests subarray fields which contain sparse dtypes so that
not all memory is used by the dtype work. Such dtype's should
leave the underlying memory unchanged.
"""
dtype = np.dtype([('a', {'names':['aa', 'ab'], 'formats':['f', 'f'],
'offsets':[0, 4]}, (2, 3))])
sparse_dtype = np.dtype([('a', {'names':['ab'], 'formats':['f'],
'offsets':[4]}, (2, 3))])
def test_sparse_field_assignment(self):
arr = np.zeros(3, self.dtype)
sparse_arr = arr.view(self.sparse_dtype)
sparse_arr[...] = np.finfo(np.float32).max
# dtype is reduced when accessing the field, so shape is (3, 2, 3):
assert_array_equal(arr["a"]["aa"], np.zeros((3, 2, 3)))
def test_sparse_field_assignment_fancy(self):
# Fancy assignment goes to the copyswap function for complex types:
arr = np.zeros(3, self.dtype)
sparse_arr = arr.view(self.sparse_dtype)
sparse_arr[[0, 1, 2]] = np.finfo(np.float32).max
# dtype is reduced when accessing the field, so shape is (3, 2, 3):
assert_array_equal(arr["a"]["aa"], np.zeros((3, 2, 3)))
class TestMonsterType:
"""Test deeply nested subtypes."""
def test1(self):
simple1 = np.dtype({'names': ['r', 'b'], 'formats': ['u1', 'u1'],
'titles': ['Red pixel', 'Blue pixel']})
a = np.dtype([('yo', int), ('ye', simple1),
('yi', np.dtype((int, (3, 2))))])
b = np.dtype([('yo', int), ('ye', simple1),
('yi', np.dtype((int, (3, 2))))])
assert_dtype_equal(a, b)
c = np.dtype([('yo', int), ('ye', simple1),
('yi', np.dtype((a, (3, 2))))])
d = np.dtype([('yo', int), ('ye', simple1),
('yi', np.dtype((a, (3, 2))))])
assert_dtype_equal(c, d)
@pytest.mark.skipif(IS_PYSTON, reason="Pyston disables recursion checking")
def test_list_recursion(self):
l = list()
l.append(('f', l))
with pytest.raises(RecursionError):
np.dtype(l)
@pytest.mark.skipif(IS_PYSTON, reason="Pyston disables recursion checking")
def test_tuple_recursion(self):
d = np.int32
for i in range(100000):
d = (d, (1,))
with pytest.raises(RecursionError):
np.dtype(d)
@pytest.mark.skipif(IS_PYSTON, reason="Pyston disables recursion checking")
def test_dict_recursion(self):
d = dict(names=['self'], formats=[None], offsets=[0])
d['formats'][0] = d
with pytest.raises(RecursionError):
np.dtype(d)
class TestMetadata:
def test_no_metadata(self):
d = np.dtype(int)
assert_(d.metadata is None)
def test_metadata_takes_dict(self):
d = np.dtype(int, metadata={'datum': 1})
assert_(d.metadata == {'datum': 1})
def test_metadata_rejects_nondict(self):
assert_raises(TypeError, np.dtype, int, metadata='datum')
assert_raises(TypeError, np.dtype, int, metadata=1)
assert_raises(TypeError, np.dtype, int, metadata=None)
def test_nested_metadata(self):
d = np.dtype([('a', np.dtype(int, metadata={'datum': 1}))])
assert_(d['a'].metadata == {'datum': 1})
def test_base_metadata_copied(self):
d = np.dtype((np.void, np.dtype('i4,i4', metadata={'datum': 1})))
assert_(d.metadata == {'datum': 1})
class TestString:
def test_complex_dtype_str(self):
dt = np.dtype([('top', [('tiles', ('>f4', (64, 64)), (1,)),
('rtile', '>f4', (64, 36))], (3,)),
('bottom', [('bleft', ('>f4', (8, 64)), (1,)),
('bright', '>f4', (8, 36))])])
assert_equal(str(dt),
"[('top', [('tiles', ('>f4', (64, 64)), (1,)), "
"('rtile', '>f4', (64, 36))], (3,)), "
"('bottom', [('bleft', ('>f4', (8, 64)), (1,)), "
"('bright', '>f4', (8, 36))])]")
# If the sticky aligned flag is set to True, it makes the
# str() function use a dict representation with an 'aligned' flag
dt = np.dtype([('top', [('tiles', ('>f4', (64, 64)), (1,)),
('rtile', '>f4', (64, 36))],
(3,)),
('bottom', [('bleft', ('>f4', (8, 64)), (1,)),
('bright', '>f4', (8, 36))])],
align=True)
assert_equal(str(dt),
"{'names':['top','bottom'], "
"'formats':[([('tiles', ('>f4', (64, 64)), (1,)), "
"('rtile', '>f4', (64, 36))], (3,)),"
"[('bleft', ('>f4', (8, 64)), (1,)), "
"('bright', '>f4', (8, 36))]], "
"'offsets':[0,76800], "
"'itemsize':80000, "
"'aligned':True}")
assert_equal(np.dtype(eval(str(dt))), dt)
dt = np.dtype({'names': ['r', 'g', 'b'], 'formats': ['u1', 'u1', 'u1'],
'offsets': [0, 1, 2],
'titles': ['Red pixel', 'Green pixel', 'Blue pixel']})
assert_equal(str(dt),
"[(('Red pixel', 'r'), 'u1'), "
"(('Green pixel', 'g'), 'u1'), "
"(('Blue pixel', 'b'), 'u1')]")
dt = np.dtype({'names': ['rgba', 'r', 'g', 'b'],
'formats': ['<u4', 'u1', 'u1', 'u1'],
'offsets': [0, 0, 1, 2],
'titles': ['Color', 'Red pixel',
'Green pixel', 'Blue pixel']})
assert_equal(str(dt),
"{'names':['rgba','r','g','b'],"
" 'formats':['<u4','u1','u1','u1'],"
" 'offsets':[0,0,1,2],"
" 'titles':['Color','Red pixel',"
"'Green pixel','Blue pixel'],"
" 'itemsize':4}")
dt = np.dtype({'names': ['r', 'b'], 'formats': ['u1', 'u1'],
'offsets': [0, 2],
'titles': ['Red pixel', 'Blue pixel']})
assert_equal(str(dt),
"{'names':['r','b'],"
" 'formats':['u1','u1'],"
" 'offsets':[0,2],"
" 'titles':['Red pixel','Blue pixel'],"
" 'itemsize':3}")
dt = np.dtype([('a', '<m8[D]'), ('b', '<M8[us]')])
assert_equal(str(dt),
"[('a', '<m8[D]'), ('b', '<M8[us]')]")
def test_repr_structured(self):
dt = np.dtype([('top', [('tiles', ('>f4', (64, 64)), (1,)),
('rtile', '>f4', (64, 36))], (3,)),
('bottom', [('bleft', ('>f4', (8, 64)), (1,)),
('bright', '>f4', (8, 36))])])
assert_equal(repr(dt),
"dtype([('top', [('tiles', ('>f4', (64, 64)), (1,)), "
"('rtile', '>f4', (64, 36))], (3,)), "
"('bottom', [('bleft', ('>f4', (8, 64)), (1,)), "
"('bright', '>f4', (8, 36))])])")
dt = np.dtype({'names': ['r', 'g', 'b'], 'formats': ['u1', 'u1', 'u1'],
'offsets': [0, 1, 2],
'titles': ['Red pixel', 'Green pixel', 'Blue pixel']},
align=True)
assert_equal(repr(dt),
"dtype([(('Red pixel', 'r'), 'u1'), "
"(('Green pixel', 'g'), 'u1'), "
"(('Blue pixel', 'b'), 'u1')], align=True)")
def test_repr_structured_not_packed(self):
dt = np.dtype({'names': ['rgba', 'r', 'g', 'b'],
'formats': ['<u4', 'u1', 'u1', 'u1'],
'offsets': [0, 0, 1, 2],
'titles': ['Color', 'Red pixel',
'Green pixel', 'Blue pixel']}, align=True)
assert_equal(repr(dt),
"dtype({'names':['rgba','r','g','b'],"
" 'formats':['<u4','u1','u1','u1'],"
" 'offsets':[0,0,1,2],"
" 'titles':['Color','Red pixel',"
"'Green pixel','Blue pixel'],"
" 'itemsize':4}, align=True)")
dt = np.dtype({'names': ['r', 'b'], 'formats': ['u1', 'u1'],
'offsets': [0, 2],
'titles': ['Red pixel', 'Blue pixel'],
'itemsize': 4})
assert_equal(repr(dt),
"dtype({'names':['r','b'], "
"'formats':['u1','u1'], "
"'offsets':[0,2], "
"'titles':['Red pixel','Blue pixel'], "
"'itemsize':4})")
def test_repr_structured_datetime(self):
dt = np.dtype([('a', '<M8[D]'), ('b', '<m8[us]')])
assert_equal(repr(dt),
"dtype([('a', '<M8[D]'), ('b', '<m8[us]')])")
def test_repr_str_subarray(self):
dt = np.dtype(('<i2', (1,)))
assert_equal(repr(dt), "dtype(('<i2', (1,)))")
assert_equal(str(dt), "('<i2', (1,))")
def test_base_dtype_with_object_type(self):
# Issue gh-2798, should not error.
np.array(['a'], dtype="O").astype(("O", [("name", "O")]))
def test_empty_string_to_object(self):
# Pull request #4722
np.array(["", ""]).astype(object)
def test_void_subclass_unsized(self):
dt = np.dtype(np.record)
assert_equal(repr(dt), "dtype('V')")
assert_equal(str(dt), '|V0')
assert_equal(dt.name, 'record')
def test_void_subclass_sized(self):
dt = np.dtype((np.record, 2))
assert_equal(repr(dt), "dtype('V2')")
assert_equal(str(dt), '|V2')
assert_equal(dt.name, 'record16')
def test_void_subclass_fields(self):
dt = np.dtype((np.record, [('a', '<u2')]))
assert_equal(repr(dt), "dtype((numpy.record, [('a', '<u2')]))")
assert_equal(str(dt), "(numpy.record, [('a', '<u2')])")
assert_equal(dt.name, 'record16')