human
Here's a good function header given the following:
I wrote the below code

    if is_scalar(result):
        return result
    def trans(x):
        return x
    if isinstance(dtype, string_types):
        if (dtype == 'infer'):
            inferred_type = lib.infer_dtype(_ensure_object(result.ravel()))
            if (inferred_type == 'boolean'):
                dtype = 'bool'
            elif (inferred_type == 'integer'):
                dtype = 'int64'
            elif (inferred_type == 'datetime64'):
                dtype = 'datetime64[ns]'
            elif (inferred_type == 'timedelta64'):
                dtype = 'timedelta64[ns]'
            elif (inferred_type == 'floating'):
                dtype = 'int64'
                if issubclass(result.dtype.type, np.number):
                    def trans(x):
                        return x.round()
            else:
                dtype = 'object'
    if isinstance(dtype, string_types):
        dtype = np.dtype(dtype)
    try:
        if (dtype.kind == result.dtype.kind):
            if ((result.dtype.itemsize <= dtype.itemsize) and np.prod(result.shape)):
                return result
        if (is_bool_dtype(dtype) or is_integer_dtype(dtype)):
            if (not np.prod(result.shape)):
                return trans(result).astype(dtype)
            r = result.ravel()
            arr = np.array([r[0]])
            if (isna(arr).any() or (not np.allclose(arr, trans(arr).astype(dtype), rtol=0))):
                return result
            elif (not isinstance(r[0], (np.integer, np.floating, np.bool, int, float, bool))):
                return result
            if (issubclass(result.dtype.type, (np.object_, np.number)) and notna(result).all()):
                new_result = trans(result).astype(dtype)
                try:
                    if np.allclose(new_result, result, rtol=0):
                        return new_result
                except:
                    if (new_result == result).all():
                        return new_result
        elif (issubclass(dtype.type, np.floating) and (not is_bool_dtype(result.dtype))):
   ...

What's a good function header?
assistant
#Here's a good function header.

def maybe_downcast_to_dtype(result, dtype):