Once the bug you mention gets fixed (seems like an straightforward patch for write_png?), we could probably add this as an answer test. We do some image comparison tests already in the tests for PlotWindow plots. On Thu, Jul 31, 2014 at 10:57 AM, Michael Zingale < michael.zingale@stonybrook.edu> wrote:
To help with understanding the volume rendering orientation issues, here's a self-contained test that I've been using.
This puts a single cube on +x, two cubes on +y, and three cubes on +z. North is set to +z.
The save_annotated image has the right orientation and handedness.
The write_png image is upside down.
I found this data very helpful in understanding and testing orientations.
Mike
------
import pylab import yt import numpy as np
N = 128
xmin = ymin = zmin = -1.0 xmax = ymax = zmax = 1.0
arr = np.zeros((N,N,N), dtype=np.float64) arr[:,:,:] = 1.e-4
bbox = np.array([ [xmin, xmax], [ymin, ymax], [zmin, zmax] ])
# coordinates -- in the notation data[i, j, k] x = (np.arange(N) + 0.5)*(xmax - xmin)/N + xmin y = (np.arange(N) + 0.5)*(ymax - ymin)/N + ymin z = (np.arange(N) + 0.5)*(zmax - zmin)/N + zmin
x3d, y3d, z3d = np.meshgrid(x, y, z, indexing="ij")
# single cube on +x xc = 0.75 dx = 0.05 idx = np.logical_and(np.logical_and(x3d > xc-dx, x3d < xc+dx), np.logical_and(np.logical_and(y3d > -dx, y3d < dx), np.logical_and(z3d > -dx, z3d < dx)) )
arr[idx] = 1.0
# two cubes on +y dy = 0.05 for yc in [0.65, 0.85]:
idx = np.logical_and(np.logical_and(y3d > yc-dy, y3d < yc+dy), np.logical_and(np.logical_and(x3d > -dy, x3d < dy), np.logical_and(z3d > -dy, z3d < dy)) )
arr[idx] = 0.8
# three cubes on +z dz = 0.05 for zc in [0.5, 0.7, 0.9]:
idx = np.logical_and(np.logical_and(z3d > zc-dz, z3d < zc+dz), np.logical_and(np.logical_and(x3d > -dz, x3d < dz), np.logical_and(y3d > -dz, y3d < dz)) )
arr[idx] = 0.6
data = dict(Density = arr) ds = yt.load_uniform_grid(data, arr.shape, bbox=bbox)
import yt.visualization.volume_rendering.api as vr
c = np.array([0, 0, 0]) L = np.array([1.0, 1.0, 1.0]) W = 2.0*ds.domain_width N = 720
north = np.array([0, 0, 1])
tf = vr.ColorTransferFunction((0.1,1.0)) tf.sample_colormap(1.0, 0.05, colormap="coolwarm") tf.sample_colormap(0.8, 0.05, colormap="coolwarm") tf.sample_colormap(0.6, 0.05, colormap="coolwarm")
cam = vr.Camera(c, L, W, N, transfer_function=tf, north_vector = north, ds=ds, fields=[('gas', 'Density')], log_fields=[False])
im = cam.snapshot() nim = cam.draw_domain(im)
nim.write_png("test.png")
cam.save_annotated("test_annotated.png", nim)
------
-- Michael Zingale Associate Professor
Dept. of Physics & Astronomy • Stony Brook University • Stony Brook, NY 11794-3800 *phone*: 631-632-8225 *e-mail*: Michael.Zingale@stonybrook.edu *web*: http://www.astro.sunysb.edu/mzingale
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