def show_2D_dataset(dataset_observations, scale, margin = 0, cutoff = 0, cutoffed_nodes = []):
    """
    Draws the dataset into a PIL image and returns it.
    The scale parameter is a pixel multiplication factor for the image size, the margin
    is a quantity in pixels that will be added to each of the sides of the bounding
    box (previous to the scale multiplication). The cutoff is the radius used to do the gromos
    clusterization, and the cutoffed_nodes list stores the nodes we want to draw their cutoffs.
    """
    scaled_radi = cutoff*scale

    (image,draw,boundaries) = create_canvas(dataset_observations, scale, margin)

    for i in range(len(dataset_observations)):
        position = draw_point_into_canvas(dataset_observations,i,draw,scale,margin,"#ff0000",boundaries)
        if i in cutoffed_nodes:
            draw.ellipse((scaled_radi-position[0],position[1]-scaled_radi,\
                          position[0]+scaled_radi,position[1]+scaled_radi))
    return image
dataset/ETHPy150Open victor-gil-sepulveda/pyProCT/validation/bidimensional/validationTools.py/show_2D_dataset/swapped operands of `-`