def linear(x, y, new_x):
    """
    Linearly interpolates values in new_x based on the values in x and y

    Parameters
    ----------
    x : array_like
        Independent values
    y : array_like
        Dependent values
    new_x : array_like
        The x values to return the interpolated y values.

    """
    x = atleast_1d_and_contiguous(x, np.float64)
    y = atleast_1d_and_contiguous(y, np.float64)
    new_x = atleast_1d_and_contiguous(new_x, np.float64)

    if 2 > y.ndim:
        raise ValueError("`linear` only works with 1-D or 2-D arrays.")
    if len(y.shape) == 2:
        new_y = np.zeros((y.shape[0], len(new_x)), np.float64)
        for i in range(len(new_y)):  # for each row
            _interpolate.linear_dddd(x, y[i], new_x, new_y[i])
    else:
        new_y = np.zeros(len(new_x), np.float64)
        _interpolate.linear_dddd(x, y, new_x, new_y)

    return new_y
dataset/ETHPy150Open scipy/scipy/scipy/interpolate/interpolate_wrapper.py/linear/swapped operands of `>`