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