def test_stream_hexahedral():
np.random.seed(0x4D3D3D3)
Nx, Ny, Nz = 32, 18, 24
# Note what we're doing here -- we are creating a randomly spaced mesh, but
# because of how the accumulate operation works, we also reset the leftmost
# cell boundary to 0.0.
cell_x = np.random.random(Nx + 1)
cell_x /= cell_x.sum()
cell_x = np.add.accumulate(cell_x)
cell_x[0] = 0.0
cell_y = np.random.random(Ny + 1)
cell_y /= cell_y.sum()
cell_y = np.add.accumulate(cell_y)
cell_y[0] = 0.0
cell_z = np.random.random(Nz + 1)
cell_z /= cell_z.sum()
cell_z = np.add.accumulate(cell_z)
cell_z[0] = 0.0
coords, conn = hexahedral_connectivity(cell_x, cell_y, cell_z)
data = {"random_field": np.random.random((Nx, Ny, Nz))}
bbox = np.array([[0.0, 1.0], [0.0, 1.0], [0.0, 1.0]])
ds = load_hexahedral_mesh(data, conn, coords, bbox=bbox)
dd = ds.all_data()
# raise RuntimeError
assert_almost_equal(float(dd[("gas", "cell_volume")].sum(dtype="float64")),
1.0)
assert_equal(dd[("index", "ones")].size, Nx * Ny * Nz)
# Now we try it with a standard mesh
cell_x = np.linspace(0.0, 1.0, Nx + 1)
cell_y = np.linspace(0.0, 1.0, Ny + 1)
cell_z = np.linspace(0.0, 1.0, Nz + 1)
coords, conn = hexahedral_connectivity(cell_x, cell_y, cell_z)
data = {"random_field": np.random.random((Nx, Ny, Nz))}
bbox = np.array([[0.0, 1.0], [0.0, 1.0], [0.0, 1.0]])
ds = load_hexahedral_mesh(data, conn, coords, bbox=bbox)
dd = ds.all_data()
assert_almost_equal(float(dd[("gas", "cell_volume")].sum(dtype="float64")),
1.0)
assert_equal(dd[("index", "ones")].size, Nx * Ny * Nz)
assert_almost_equal(dd[("index", "dx")].to_ndarray(), 1.0 / Nx)
assert_almost_equal(dd[("index", "dy")].to_ndarray(), 1.0 / Ny)
assert_almost_equal(dd[("index", "dz")].to_ndarray(), 1.0 / Nz)
s = SlicePlot(ds, "x", "random_field")
s._setup_plots()
s.frb[("stream", "random_field")]
def __init__(self,
ds,
image_name="ytSliceImage",
axis='z',
variable='density',
center=[0.0, 0.0, 0.0],
width=10.0,
units='kpc',
color_map='hot',
show_annotations=True):
from yt import SlicePlot
p = SlicePlot(ds, axis, variable, center=center, width=(width, units))
p.hide_axes()
p.hide_colorbar()
p.set_cmap(variable, color_map)
p._setup_plots()
plot = p.plots[variable]
plot.canvas.draw()
buff = plot.canvas.tostring_argb()
ncols, nrows = plot.canvas.get_width_height()
vv = np.fromstring(buff, dtype=np.uint8).reshape((nrows, ncols, 4),
order="C")
if show_annotations:
p = SlicePlot(ds,
axis,
variable,
center=center,
width=(width, units))
p.set_cmap(variable, color_map)
p._setup_plots()
plot = p.plots[variable]
plot.canvas.draw()
buff2 = plot.canvas.tostring_argb()
ncols2, nrows2 = plot.canvas.get_width_height()
vv2 = np.fromstring(buff2, dtype=np.uint8).reshape(
(nrows2, ncols2, 4), order="C")
ncols = vv.shape[1]
nrows = vv.shape[0]
# delete if already there
for im in bpy.data.images:
if im.name == image_name:
delete_unused_images(image_name)
delete_unused_textures(image_name)
delete_unused_materials(image_name)
# for annotations
for im in bpy.data.images:
if im.name == image_name + '_ann':
delete_unused_images(image_name + '_ann')
delete_unused_textures(image_name + '_ann')
delete_unused_materials(image_name + '_ann')
# switching a from back to front, and flipping image
# if also with annotation do a nice one in the domain
pixels_tmp = np.array(vv)
for i in range(0, nrows):
#pixels_tmp[i,:,0] = vv[i,:,0]
#pixels_tmp[i,:,1] = vv[i,:,1]
#pixels_tmp[i,:,2] = vv[i,:,2]
#pixels_tmp[i,:,3] = vv[i,:,3]
pixels_tmp[i, :, 3] = vv[nrows - 1 - i, :, 0]
pixels_tmp[i, :, 0] = vv[nrows - 1 - i, :, 1]
pixels_tmp[i, :, 1] = vv[nrows - 1 - i, :, 2]
pixels_tmp[i, :, 2] = vv[nrows - 1 - i, :, 3]
if show_annotations:
pixels_tmp2 = np.array(vv2)
if show_annotations:
for i in range(0, nrows2):
pixels_tmp2[i, :, 3] = vv2[nrows2 - 1 - i, :, 0]
pixels_tmp2[i, :, 0] = vv2[nrows2 - 1 - i, :, 1]
pixels_tmp2[i, :, 1] = vv2[nrows2 - 1 - i, :, 2]
pixels_tmp2[i, :, 2] = vv2[nrows2 - 1 - i, :, 3]
# blank image
image = bpy.data.images.new(image_name, width=ncols, height=nrows)
if show_annotations:
image2 = bpy.data.images.new(image_name + '_ann',
width=ncols2,
height=nrows2)
pixels = pixels_tmp.ravel() / 255.
#pixels = vv.ravel()/255.
if show_annotations:
pixels2 = pixels_tmp2.ravel() / 255.
image.pixels = pixels
if show_annotations:
image2.pixels = pixels2
# activate the image in the uv editor
for area in bpy.context.screen.areas:
if area.type == 'IMAGE_EDITOR':
if show_annotations:
area.spaces.active.image = image2
else:
area.spaces.active.image = image
elif area.type == 'VIEW_3D': # make sure material/render view is on
for space in area.spaces:
if space.type == 'VIEW_3D':
if (space.viewport_shade != 'RENDERED') and (
space.viewport_shade != 'MATERIAL'):
space.viewport_shade = 'RENDERED' # material is too slow
# also, attach to the projection in the blender 3d window
# now, set color
figmat = makeMaterial(image_name, (0, 0, 0), (1, 1, 1), 1.0,
0.0) # no emissivity or transperency for now
setMaterial(bpy.data.objects[image_name], figmat)
# also, make shadeless
bpy.data.materials[image_name].use_shadeless = True
# Create image texture from image
cTex = bpy.data.textures.new(image_name, type='IMAGE')
cTex.image = image
# Add texture slot for color texture
mat = bpy.data.materials[image_name]
mtex = mat.texture_slots.add()
mtex.texture = cTex
#mtex.texture_coords = 'UV'
mtex.texture_coords = 'OBJECT' # this seems to work better for figures, but certainly needs to be tested
mtex.use_map_color_diffuse = True
mtex.use_map_color_emission = True
mtex.emission_color_factor = 0.5
mtex.use_map_density = True
mtex.mapping = 'FLAT'
# map to object
mtex.object = bpy.data.objects[image_name]