pybind11/example/example-numpy-dtypes.py

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#!/usr/bin/env python
from __future__ import print_function
import unittest
import numpy as np
from example import (
create_rec_simple, create_rec_packed, create_rec_nested, print_format_descriptors,
print_rec_simple, print_rec_packed, print_rec_nested, print_dtypes, get_format_unbound,
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create_rec_partial, create_rec_partial_nested, create_string_array, print_string_array,
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test_array_ctors, test_dtype_ctors, test_dtype_methods
)
def check_eq(arr, data, dtype):
np.testing.assert_equal(arr, np.array(data, dtype=dtype))
unittest.TestCase().assertRaisesRegex(
RuntimeError, 'unsupported buffer format', get_format_unbound)
print_format_descriptors()
print_dtypes()
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simple_dtype = np.dtype({'names': ['x', 'y', 'z'],
'formats': ['?', 'u4', 'f4'],
'offsets': [0, 4, 8]})
packed_dtype = np.dtype([('x', '?'), ('y', 'u4'), ('z', 'f4')])
elements = [(False, 0, 0.0), (True, 1, 1.5), (False, 2, 3.0)]
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for func, dtype in [(create_rec_simple, simple_dtype), (create_rec_packed, packed_dtype)]:
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arr = func(0)
assert arr.dtype == dtype
check_eq(arr, [], simple_dtype)
check_eq(arr, [], packed_dtype)
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arr = func(3)
assert arr.dtype == dtype
check_eq(arr, elements, simple_dtype)
check_eq(arr, elements, packed_dtype)
if dtype == simple_dtype:
print_rec_simple(arr)
else:
print_rec_packed(arr)
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arr = create_rec_partial(3)
print(arr.dtype)
partial_dtype = arr.dtype
assert '' not in arr.dtype.fields
assert partial_dtype.itemsize > simple_dtype.itemsize
check_eq(arr, elements, simple_dtype)
check_eq(arr, elements, packed_dtype)
arr = create_rec_partial_nested(3)
print(arr.dtype)
assert '' not in arr.dtype.fields
assert '' not in arr.dtype.fields['a'][0].fields
assert arr.dtype.itemsize > partial_dtype.itemsize
np.testing.assert_equal(arr['a'], create_rec_partial(3))
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nested_dtype = np.dtype([('a', simple_dtype), ('b', packed_dtype)])
arr = create_rec_nested(0)
assert arr.dtype == nested_dtype
check_eq(arr, [], nested_dtype)
arr = create_rec_nested(3)
assert arr.dtype == nested_dtype
check_eq(arr, [((False, 0, 0.0), (True, 1, 1.5)),
((True, 1, 1.5), (False, 2, 3.0)),
((False, 2, 3.0), (True, 3, 4.5))], nested_dtype)
print_rec_nested(arr)
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assert create_rec_nested.__doc__.strip().endswith('numpy.ndarray[dtype=NestedStruct]')
arr = create_string_array(True)
print(arr.dtype)
print_string_array(arr)
dtype = arr.dtype
assert arr['a'].tolist() == [b'', b'a', b'ab', b'abc']
assert arr['b'].tolist() == [b'', b'a', b'ab', b'abc']
arr = create_string_array(False)
assert dtype == arr.dtype
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data = np.arange(1, 7, dtype='int32')
for i in range(8):
np.testing.assert_array_equal(test_array_ctors(10 + i), data.reshape((3, 2)))
np.testing.assert_array_equal(test_array_ctors(20 + i), data.reshape((3, 2)))
for i in range(5):
np.testing.assert_array_equal(test_array_ctors(30 + i), data)
np.testing.assert_array_equal(test_array_ctors(40 + i), data)
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d1 = np.dtype({'names': ['a', 'b'], 'formats': ['int32', 'float64'],
'offsets': [1, 10], 'itemsize': 20})
d2 = np.dtype([('a', 'i4'), ('b', 'f4')])
assert test_dtype_ctors() == [np.dtype('int32'), np.dtype('float64'),
np.dtype('bool'), d1, d1, np.dtype('uint32'), d2]
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assert test_dtype_methods() == [np.dtype('int32'), simple_dtype, False, True,
np.dtype('int32').itemsize, simple_dtype.itemsize]