def create_image(filename_prefix):
fields = ['noise%d' % i for i in range(4)]
p = SlicePlot(ds, 'z', fields)
p.save('%s_log' % filename_prefix)
p.set_log('all', False)
p.save('%s_lin' % filename_prefix)
def create_image(filename_prefix):
fields = ["noise%d" % i for i in range(4)]
p = SlicePlot(ds, "z", fields)
p.save(f"{filename_prefix}_log")
p.set_log("all", False)
p.save(f"{filename_prefix}_lin")
def create_image(filename_prefix):
fields = ["noise%d" % i for i in range(4)]
for normal in ("phi", "theta"):
p = SlicePlot(ds, normal, fields)
p.save(f"{filename_prefix}_{normal}")
units = 'kpc'
color_map = 'algae'
show_annotations = True
image_name = 'testslice44'
#my_sphere = ds.sphere(center, (width, units))
from yt import SlicePlot
#p = SlicePlot(my_sphere, axis, variable, center = center, width = (width, units))
p = SlicePlot(ds, axis, variable, center=center, width=(width, units))
p.hide_axes()
p.hide_colorbar()
plot = p.plots[variable]
p.set_cmap(variable, "hot")
p.save('~/Desktop/testslc.png')
#fig = plot.figure
#f = BytesIO()
#vv = yt.write_image(np.log10(p.frb[variable][:,:-1].d),f, cmap_name = color_map)
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))
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),
