BUG: missing values for minimum value of the data

[chrishavlin]

Elements where the data value is equal to the minimum are not being rendered. Here's an example that builds some refined grids:

import yt
import numpy as np
import yt
import yt_idv

bbox = np.array([
    [0., 1.],
    [0., 1.],
    [0., 1.]
])
bbox_wid = bbox[:,1] - bbox[:,0]
bbox_c = np.mean(bbox,axis=1)
sz_0 = np.array((64, 64, 64))
refine_factor = 2
max_lev = 5

# divide grid by 2 every time


dd0 = bbox_wid / sz_0
sz_i = sz_0.copy()
grids = []
for lev in range(max_lev):

    box_wid_factor = 2. * int(lev > 0) + int(lev==0) * 1.
    bbox_wid = bbox_wid / box_wid_factor
    le_i = bbox_c - bbox_wid/2.
    re_i = bbox_c + bbox_wid/2.

    # find closest start/end index in lev 0 grid
    start_i = np.round(le_i / dd0).astype(int)
    end_i = np.round(re_i / dd0).astype(int)
    #print(start_i, end_i)
    sz_0 = end_i - start_i

    # recompute for rounding errors
    le_i = start_i * dd0
    re_i = le_i + sz_0 * dd0

    sz_i = sz_0 * 2 ** lev

    levp1 = np.full(sz_i, lev+1.0)
    if lev==0:
        levp1[32:,32:,32:] = 1.5
    grid = {'left_edge': le_i,
            'right_edge': re_i,
            'dimensions': sz_i,
            'level': lev,
            ('gas', 'density'): np.random.random(sz_i) * (lev+1),
            ('stream', 'lev_p1'): levp1,
           }
    grids.append(grid)


ds = yt.load_amr_grids(
        grids,
        sz_0,
        bbox=bbox,    
        length_unit=1,
    ) 

fld = ('stream', 'lev_p1')
slc = yt.SlicePlot(ds, 'x', fld)
slc.set_log(fld, False)
slc.annotate_grids()
slc.save()

rc = yt_idv.render_context(height=800, width=800, gui=True)
sg = rc.add_scene(ds, fld, no_ghost=True)
rc.scene.components[0].sample_factor = 50.0
rc.scene.components[0].cmap_log = False
rc.scene.components[0]._reset_cmap_bounds()

rc.run()

Results in the following yt slice plot

and the following in yt_idv

The outermost level 0 grid is missing.