parameters: (a, axis=None, dtype=None, out=None, keepdims=np._NoValue, initial=np._NoValue)
return_statement: return _wrapreduction(a, np.add, 'sum', axis, dtype, out, keepdims=keepdims,
                            initial=initial)
docstring: Sum of array elements over a given axis.
  
      Parameters
      ----------
      a : array_like
          Elements to sum.
      axis : None or int or tuple of ints, optional
          Axis or axes along which a sum is performed.  The default,
          axis=None, will sum all of the elements of the input array.  If
          axis is negative it counts from the last to the first axis.
  
          .. versionadded:: 1.7.0
  
          If axis is a tuple of ints, a sum is performed on all of the axes
          specified in the tuple instead of a single axis or all the axes as
          before.
      dtype : dtype, optional
          The type of the returned array and of the accumulator in which the
          elements are summed.  The dtype of `a` is used by default unless `a`
          has an integer dtype of less precision than the default platform
          integer.  In that case, if `a` is signed then the platform integer
          is used while if `a` is unsigned then an unsigned integer of the
          same precision as the platform integer is used.
      out : ndarray, optional
          Alternative output array in which to place the result. It must have
          the same shape as the expected output, but the type of the output
          values will be cast if necessary.
      keepdims : bool, optional
          If this is set to True, the axes which are reduced are left
          in the result as dimensions with size one. With this option,
          the result will broadcast correctly against the input array.
  
          If the default value is passed, then `keepdims` will not be
          passed through to the `sum` method of sub-classes of
          `ndarray`, however any non-default value will be.  If the
          sub-class' method does not implement `keepdims` any
          exceptions will be raised.
      initial : scalar, optional
          Starting value for the sum. See `~numpy.ufunc.reduce` for details.
  
          .. versionadded:: 1.15.0
  
      Returns
      -------
      sum_along_axis : ndarray
          An array with the same shape as `a`, with the specified
          axis removed.   If `a` is a 0-d array, or if `axis` is None, a scalar
          is returned.  If an output array is specified, a reference to
          `out` is returned.
  
      See Also
      --------
      ndarray.sum : Equivalent method.
  
      cumsum : Cumulative sum of array elements.
  
      trapz : Integration of array values using the composite trapezoidal rule.
  
      mean, average
  
      Notes
      -----
      Arithmetic is modular when using integer types, and no error is
      raised on overflow.
  
      The sum of an empty array is the neutral element 0:
  
      >>> np.sum([])
      0.0
  
      Examples
      --------
      >>> np.sum([0.5, 1.5])
      2.0
      >>> np.sum([0.5, 0.7, 0.2, 1.5], dtype=np.int32)
      1
      >>> np.sum([[0, 1], [0, 5]])
      6
      >>> np.sum([[0, 1], [0, 5]], axis=0)
      array([0, 6])
      >>> np.sum([[0, 1], [0, 5]], axis=1)
      array([1, 5])
  
      If the accumulator is too small, overflow occurs:
  
      >>> np.ones(128, dtype=np.int8).sum(dtype=np.int8)
      -128
  
      You can also start the sum with a value other than zero:
  
      >>> np.sum([10], initial=5)
      15
docstring_summary: Sum of array elements over a given axis.
docstring_tokens: Sum of array elements over a given axis .
function: def sum(a, axis=None, dtype=None, out=None, keepdims=np._NoValue, initial=np._NoValue):
      """
      Sum of array elements over a given axis.
  
      Parameters
      ----------
      a : array_like
          Elements to sum.
      axis : None or int or tuple of ints, optional
          Axis or axes along which a sum is performed.  The default,
          axis=None, will sum all of the elements of the input array.  If
          axis is negative it counts from the last to the first axis.
  
          .. versionadded:: 1.7.0
  
          If axis is a tuple of ints, a sum is performed on all of the axes
          specified in the tuple instead of a single axis or all the axes as
          before.
      dtype : dtype, optional
          The type of the returned array and of the accumulator in which the
          elements are summed.  The dtype of `a` is used by default unless `a`
          has an integer dtype of less precision than the default platform
          integer.  In that case, if `a` is signed then the platform integer
          is used while if `a` is unsigned then an unsigned integer of the
          same precision as the platform integer is used.
      out : ndarray, optional
          Alternative output array in which to place the result. It must have
          the same shape as the expected output, but the type of the output
          values will be cast if necessary.
      keepdims : bool, optional
          If this is set to True, the axes which are reduced are left
          in the result as dimensions with size one. With this option,
          the result will broadcast correctly against the input array.
  
          If the default value is passed, then `keepdims` will not be
          passed through to the `sum` method of sub-classes of
          `ndarray`, however any non-default value will be.  If the
          sub-class' method does not implement `keepdims` any
          exceptions will be raised.
      initial : scalar, optional
          Starting value for the sum. See `~numpy.ufunc.reduce` for details.
  
          .. versionadded:: 1.15.0
  
      Returns
      -------
      sum_along_axis : ndarray
          An array with the same shape as `a`, with the specified
          axis removed.   If `a` is a 0-d array, or if `axis` is None, a scalar
          is returned.  If an output array is specified, a reference to
          `out` is returned.
  
      See Also
      --------
      ndarray.sum : Equivalent method.
  
      cumsum : Cumulative sum of array elements.
  
      trapz : Integration of array values using the composite trapezoidal rule.
  
      mean, average
  
      Notes
      -----
      Arithmetic is modular when using integer types, and no error is
      raised on overflow.
  
      The sum of an empty array is the neutral element 0:
  
      >>> np.sum([])
      0.0
  
      Examples
      --------
      >>> np.sum([0.5, 1.5])
      2.0
      >>> np.sum([0.5, 0.7, 0.2, 1.5], dtype=np.int32)
      1
      >>> np.sum([[0, 1], [0, 5]])
      6
      >>> np.sum([[0, 1], [0, 5]], axis=0)
      array([0, 6])
      >>> np.sum([[0, 1], [0, 5]], axis=1)
      array([1, 5])
  
      If the accumulator is too small, overflow occurs:
  
      >>> np.ones(128, dtype=np.int8).sum(dtype=np.int8)
      -128
  
      You can also start the sum with a value other than zero:
  
      >>> np.sum([10], initial=5)
      15
      """
      if isinstance(a, _gentype):
          # 2018-02-25, 1.15.0
          warnings.warn(
              "Calling np.sum(generator) is deprecated, and in the future will give a different result. "
              "Use np.sum(np.fromiter(generator)) or the python sum builtin instead.",
              DeprecationWarning, stacklevel=2)
  
          res = _sum_(a)
          if out is not None:
              out[...] = res
              return out
          return res
  
      return _wrapreduction(a, np.add, 'sum', axis, dtype, out, keepdims=keepdims,
                            initial=initial)
function_tokens: def sum ( a , axis = None , dtype = None , out = None , keepdims = np . _NoValue , initial = np . _NoValue ) : if isinstance ( a , _gentype ) : # 2018-02-25, 1.15.0 warnings . warn ( "Calling np.sum(generator) is deprecated, and in the future will give a different result. " "Use np.sum(np.fromiter(generator)) or the python sum builtin instead." , DeprecationWarning , stacklevel = 2 ) res = _sum_ ( a ) if out is not None : out [ ... ] = res return out return res return _wrapreduction ( a , np . add , 'sum' , axis , dtype , out , keepdims = keepdims , initial = initial )