parameters: (arr, mask, vals)
return_statement: return _insert(arr, mask, vals)
docstring: Change elements of an array based on conditional and input values.
  
      Similar to ``np.putmask(arr, mask, vals)``, the difference is that `place`
      uses the first N elements of `vals`, where N is the number of True values
      in `mask`, while `putmask` uses the elements where `mask` is True.
  
      Note that `extract` does the exact opposite of `place`.
  
      Parameters
      ----------
      arr : array_like
          Array to put data into.
      mask : array_like
          Boolean mask array. Must have the same size as `a`.
      vals : 1-D sequence
          Values to put into `a`. Only the first N elements are used, where
          N is the number of True values in `mask`. If `vals` is smaller
          than N it will be repeated.
  
      See Also
      --------
      putmask, put, take, extract
  
      Examples
      --------
      >>> arr = np.arange(6).reshape(2, 3)
      >>> np.place(arr, arr>2, [44, 55])
      >>> arr
      array([[ 0,  1,  2],
             [44, 55, 44]])
docstring_summary: Change elements of an array based on conditional and input values.
docstring_tokens: Change elements of an array based on conditional and input values .
function: def place(arr, mask, vals):
      """
      Change elements of an array based on conditional and input values.
  
      Similar to ``np.putmask(arr, mask, vals)``, the difference is that `place`
      uses the first N elements of `vals`, where N is the number of True values
      in `mask`, while `putmask` uses the elements where `mask` is True.
  
      Note that `extract` does the exact opposite of `place`.
  
      Parameters
      ----------
      arr : array_like
          Array to put data into.
      mask : array_like
          Boolean mask array. Must have the same size as `a`.
      vals : 1-D sequence
          Values to put into `a`. Only the first N elements are used, where
          N is the number of True values in `mask`. If `vals` is smaller
          than N it will be repeated.
  
      See Also
      --------
      putmask, put, take, extract
  
      Examples
      --------
      >>> arr = np.arange(6).reshape(2, 3)
      >>> np.place(arr, arr>2, [44, 55])
      >>> arr
      array([[ 0,  1,  2],
             [44, 55, 44]])
  
      """
      return _insert(arr, mask, vals)
function_tokens: def place ( arr , mask , vals ) : return _insert ( arr , mask , vals )