import yt

import numpy as np    

from IPython.display import display

def create_fake_dataset(px=0.2):

    grid_data = [
        dict(left_edge=[0.0, 0.0, 0.0],
             right_edge=[1.0,1.0,1.0],
             level=0,
             dimensions = [8, 8, 8],
             number_of_particles=0),
        dict(left_edge=[0.25, 0.25, 0.25],
             right_edge=[0.75,0.75,0.75],
             level=1,
             dimensions = [8, 8, 8],
             number_of_particles=0),
    ]

    particle_position = [px, 0.5, 0.5]

    if particle_position[0] < 0.25 or particle_position[0] > 0.75:
        update_grid = 0
    else:
        update_grid = 1

    field_data = {
        'particle_position_x': np.array([particle_position[0]]),
        'particle_position_y': np.array([particle_position[1]]),
        'particle_position_z': np.array([particle_position[2]]),
        'particle_mass': np.array([1.0,]),
        'number_of_particles': 1
    }

    grid_data[update_grid].update(field_data)

    bbox = np.array([[0,1],[0,1],[0,1]])

    ds = yt.load_amr_grids(grid_data, [8,8,8], bbox=bbox)
    
    return yt.SlicePlot(ds, 2, ('deposit', 'io_cic')).annotate_grids()

for px in [0.24, 0.26]:
    display(create_fake_dataset(px))