7 examples of 'sum of all elements in array python' in Python

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7def test_sum(self):
8 self.create_node('Sum', {'input[0]': 5.0, 'input[1]': -3.0, 'input[2]': 2.0}, 4.0)
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431def _prod(array):
432 prod = 1
433 for value in array:
434 prod *= value
435 return prod
284def prod(array):
285 """Element-wise product of a numpy array across all the slave processes.
286 The result is only available in the main_slave (rank 1)."""
287 _reduce(array, "PROD")
41def countArrayElements(array):
42 '''
43 Simple method to count the repetitions of elements in an array
44
45 @param array: An array of elements
46 @return: A tuple (elements,counters), where elements is a list with the distinct elements and counters is the list with the number of times they appear in the array
47 '''
48 elements = []
49 counters = []
50 for element in array:
51 if element in elements:
52 indx = elements.index(element)
53 counters[indx] += 1
54 else:
55 elements.append(element)
56 counters.append(1)
57 return elements,counters
402def sum(self, axis=None, dtype=None, out=None):
403 """
404 Returns the sum of the matrix elements, along the given axis.
405
406 Refer to `numpy.sum` for full documentation.
407
408 See Also
409 --------
410 numpy.sum
411
412 Notes
413 -----
414 This is the same as `ndarray.sum`, except that where an `ndarray` would
415 be returned, a `matrix` object is returned instead.
416
417 Examples
418 --------
419 >>> x = np.matrix([[1, 2], [4, 3]])
420 >>> x.sum()
421 10
422 >>> x.sum(axis=1)
423 matrix([[3],
424 [7]])
425 >>> x.sum(axis=1, dtype='float')
426 matrix([[ 3.],
427 [ 7.]])
428 >>> out = np.zeros((1, 2), dtype='float')
429 >>> x.sum(axis=1, dtype='float', out=out)
430 matrix([[ 3.],
431 [ 7.]])
432
433 """
434 return N.ndarray.sum(self, axis, dtype, out)._align(axis)
433def sum_sum(values: TypeValList) -> float:
434 """Calculate the sum of ``values``."""
435 if len(values) == 0:
436 return np.nan
437
438 return sum(values)
6@jit(native=True, xsimd=True)
7def row_sum(arr, columns):
8 return arr.T[columns].sum(0)

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