# Best used in ipython notebook
import yt
import numpy as np
import matplotlib.pyplot as plt
%matplotlib inline


npart = 1024
data = dict(particle_mass = np.random.random(size=npart),
            particle_position_x = np.random.random(size=npart),
            particle_position_y = np.random.random(size=npart),
            particle_position_z = np.random.random(size=npart)
           )
# Move one particle to other corner
data['particle_position_x'][-1] = 1.5
data['particle_position_y'][-1] = 1.5

ds = yt.load_particles(data, bbox = np.array([[0.0, 2.0], [0.0, 2.0], [0.0, 2.0]]))

## This is what we want to obtain as uniformly gridded data
yt.ProjectionPlot(ds, 'z', ('deposit', 'all_cic'))

## Create two grids with different refinements
level = ds.index.max_level
dims = ds.domain_dimensions * ds.refine_by**level
cg0 = ds.covering_grid(0, left_edge=ds.domain_left_edge, dims = ds.domain_dimensions)
cg1 = ds.covering_grid(level, left_edge=ds.domain_left_edge, dims = dims)

# Here the data from the one moved particle seems to be missing
plt.imshow(np.sum(np.array(cg1['all_cic'])[:,:,:],axis=2),interpolation='none')
# ...although it is here
plt.imshow(np.sum(np.array(cg0['all_cic'])[:,:,:],axis=2),interpolation='none')