7 examples of 'initialize array in python' in Python

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13def __init__(self, arr):
14 assert arr is not None
15 self.shape = arr.shape
16 self.array = arr
17 self.size = self.array.size
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53def __init__(self, size):
54 assert size > 0, "Array size must be > 0"
55 self._size = size
56 PyArrayType = ctypes.py_object * size
57 self._elements = PyArrayType()
58 self.clear(None)
97def __init__(self, elemtype, *ignored):
98 '''Note: elemcount is ignored when using in the Python scope.
99 '''
100 self.elemtype = elemtype
490def __init__(self, array, on_shape_change='raise'):
491 """
492 array is a numpy array of data.
493 on_shape_change is one of ('raise', 'pass', 'recompile'), and
494 determines the behaviour when the data is set to a new value with a
495 different shape
496 """
497 super(DataHolder, self).__init__()
498 dtype = normalize_dtype(array)
499 self._array = np.asarray(array, dtype=dtype)
500 assert on_shape_change in ['raise', 'pass', 'recompile']
501 self.on_shape_change = on_shape_change
301def __init__(self, db, ARRAY, varlength=1):
302 self.db = db
303 self.ARRAY = ARRAY
304 self.LLTYPE = ARRAY
305 self.varlength = varlength
306 self.dependencies = {}
307 self.itemtypename = db.gettype(ARRAY.OF, who_asks=self)
17def __init__(self,
18 *array: Union[np.ndarray, pd.DataFrame, pd.Series,
19 torch.Tensor],
20 dtypes: Union[None, Sequence[torch.dtype]] = None):
21 if dtypes is None:
22 dtypes = [torch.get_default_dtype()] * len(array)
23 if len(dtypes) != len(array):
24 raise ValueError('length of dtypes not equal to length of array')
25
26 array = [
27 self._convert(data, dtype) for data, dtype in zip(array, dtypes)
28 ]
29 super().__init__(*array)
40def init_array(C, A, B, alpha, beta):
41 n = N.get()
42 m = M.get()
43
44 alpha[0] = datatype(1.5)
45 beta[0] = datatype(1.2)
46
47 for i in range(m):
48 for j in range(n):
49 C[i, j] = datatype((i + j) % 100) / m
50 B[i, j] = datatype((n + i - j) % 100) / m
51 for i in range(m):
52 for j in range(i + 1):
53 A[i, j] = datatype((i + j) % 100) / m
54 for j in range(i + 1, m):
55 A[i, j] = -999
56 # regions of arrays that should not be used
57
58 print('aval', beta[0] * C[0, 0] + alpha[0] * B[0, 0] * A[0, 0])

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