def build_transfer_function(self):
"""
Builds the transfer function according to the current state of the
TransferFunctionHelper.
Parameters
----------
None
Returns
-------
A ColorTransferFunction object.
"""
if self.bounds is None:
mylog.info(
'Calculating data bounds. This may take a while.' +
' Set the TransferFunctionHelper.bounds to avoid this.')
self.set_bounds()
if self.log:
mi, ma = np.log10(self.bounds[0]), np.log10(self.bounds[1])
else:
mi, ma = self.bounds
self.tf = ColorTransferFunction((mi, ma),
grey_opacity=self.grey_opacity,
nbins=512)
return self.tf
def make_yt_transfer(bounds=(0.0, 1.0), colormap="algae", bins=1000, scale=1.0, scale_func=None):
"""Defines a transfer function offset given a transfer function.
"""
mi, ma = bounds
transfer = ColorTransferFunction((mi, ma), bins)
if scale_func == None:
transfer.map_to_colormap(mi, ma, colormap=colormap, scale=1.0)
else:
transfer.map_to_colormap(mi, ma, colormap=colormap, scale_func=scale_func)
return transfer
def main():
global window, ts, width, height
(width, height) = (1024, 1024)
glutInit(sys.argv)
glutInitDisplayMode(GLUT_RGBA | GLUT_DOUBLE | GLUT_ALPHA | GLUT_DEPTH)
glutInitWindowSize(width, height)
glutInitWindowPosition(0, 0)
window = glutCreateWindow("Stereo Volume Rendering")
glutDisplayFunc(display)
glutIdleFunc(idle)
glutReshapeFunc(resize)
glutMouseFunc(mouseButton)
glutMotionFunc(mouseMotion)
glutKeyboardFunc(keyPressed)
init_gl(width, height)
# create texture for blitting to screen
create_texture(width, height)
import pycuda.gl.autoinit
import pycuda.gl
cuda_gl = pycuda.gl
create_PBO(width, height)
# ----- Load and Set Volume Data -----
density_grid = np.load("/home/bogert/dd150_log_densities.npy")
mi, ma = 21.5, 24.5
bins = 5000
tf = ColorTransferFunction((mi, ma), bins)
tf.map_to_colormap(mi, ma, colormap="algae", scale_func=scale_func)
ts = TheiaScene(volume=density_grid,
raycaster=FrontToBackRaycaster(size=(width, height),
tf=tf))
ts.get_raycaster().set_sample_size(0.01)
ts.get_raycaster().set_max_samples(5000)
ts.update()
glutMainLoop()
def main():
global window, ts, width, height
(width, height) = (1024, 1024)
glutInit(sys.argv)
glutInitDisplayMode(GLUT_RGBA | GLUT_DOUBLE | GLUT_ALPHA | GLUT_DEPTH )
glutInitWindowSize(width, height)
glutInitWindowPosition(0, 0)
window = glutCreateWindow("Stereo Volume Rendering")
glutDisplayFunc(display)
glutIdleFunc(idle)
glutReshapeFunc(resize)
glutMouseFunc( mouseButton )
glutMotionFunc( mouseMotion )
glutKeyboardFunc(keyPressed)
init_gl(width, height)
# create texture for blitting to screen
create_texture(width, height)
import pycuda.gl.autoinit
import pycuda.gl
cuda_gl = pycuda.gl
create_PBO(width, height)
# ----- Load and Set Volume Data -----
density_grid = np.load("/home/bogert/dd150_log_densities.npy")
mi, ma= 21.5, 24.5
bins = 5000
tf = ColorTransferFunction( (mi, ma), bins)
tf.map_to_colormap(mi, ma, colormap="algae", scale_func = scale_func)
ts = TheiaScene(volume = density_grid, raycaster = FrontToBackRaycaster(size = (width, height), tf = tf))
ts.get_raycaster().set_sample_size(0.01)
ts.get_raycaster().set_max_samples(5000)
ts.update()
glutMainLoop()
def make_yt_transfer(
bounds=(0.0, 1.0), colormap="algae", bins=1000, scale=1.0,
scale_func=None):
"""Defines a transfer function offset given a transfer function.
"""
mi, ma = bounds
transfer = ColorTransferFunction((mi, ma), bins)
if scale_func == None:
transfer.map_to_colormap(mi, ma, colormap=colormap, scale=1.0)
else:
transfer.map_to_colormap(mi,
ma,
colormap=colormap,
scale_func=scale_func)
return transfer
class TransferFunctionHelper(object):
r"""A transfer function helper.
This attempts to help set up a good transfer function by finding
bounds, handling linear/log options, and displaying the transfer
function combined with 1D profiles of rendering quantity.
Parameters
----------
ds: A Dataset instance
A static output that is currently being rendered. This is used to
help set up data bounds.
Notes
-----
"""
profiles = None
def __init__(self, ds):
self.ds = ds
self.field = None
self.log = False
self.tf = None
self.bounds = None
self.grey_opacity = False
self.profiles = {}
def set_bounds(self, bounds=None):
"""
Set the bounds of the transfer function.
Parameters
----------
bounds: array-like, length 2, optional
A length 2 list/array in the form [min, max]. These should be the
raw values and not the logarithm of the min and max. If bounds is
None, the bounds of the data are calculated from all of the data
in the dataset. This can be slow for very large datasets.
"""
if bounds is None:
bounds = self.ds.h.all_data().quantities['Extrema'](self.field,
non_zero=True)
bounds = [b.ndarray_view() for b in bounds]
self.bounds = bounds
# Do some error checking.
assert (len(self.bounds) == 2)
if self.log:
assert (self.bounds[0] > 0.0)
assert (self.bounds[1] > 0.0)
return
def set_field(self, field):
"""
Set the field to be rendered
Parameters
----------
field: string
The field to be rendered.
"""
if field != self.field:
self.log = self.ds._get_field_info(field).take_log
self.field = field
def set_log(self, log):
"""
Set whether or not the transfer function should be in log or linear
space. Also modifies the ds.field_info[field].take_log attribute to
stay in sync with this setting.
Parameters
----------
log: boolean
Sets whether the transfer function should use log or linear space.
"""
self.log = log
def build_transfer_function(self):
"""
Builds the transfer function according to the current state of the
TransferFunctionHelper.
Parameters
----------
None
Returns
-------
A ColorTransferFunction object.
"""
if self.bounds is None:
mylog.info(
'Calculating data bounds. This may take a while.' +
' Set the TransferFunctionHelper.bounds to avoid this.')
self.set_bounds()
if self.log:
mi, ma = np.log10(self.bounds[0]), np.log10(self.bounds[1])
else:
mi, ma = self.bounds
self.tf = ColorTransferFunction((mi, ma),
grey_opacity=self.grey_opacity,
nbins=512)
return self.tf
def setup_default(self):
"""Setup a default colormap
Creates a ColorTransferFunction including 10 gaussian layers whose
colors sample the 'spectral' colormap. Also attempts to scale the
transfer function to produce a natural contrast ratio.
"""
if LooseVersion(matplotlib.__version__) < LooseVersion('2.0.0'):
colormap_name = 'spectral'
else:
colormap_name = 'nipy_spectral'
self.tf.add_layers(10, colormap=colormap_name)
factor = self.tf.funcs[-1].y.size / self.tf.funcs[-1].y.sum()
self.tf.funcs[-1].y *= 2 * factor
def plot(self, fn=None, profile_field=None, profile_weight=None):
"""
Save the current transfer function to a bitmap, or display
it inline.
Parameters
----------
fn: string, optional
Filename to save the image to. If None, the returns an image
to an IPython session.
Returns
-------
If fn is None, will return an image to an IPython notebook.
"""
from yt.visualization._mpl_imports import FigureCanvasAgg
from matplotlib.figure import Figure
if self.tf is None:
self.build_transfer_function()
self.setup_default()
tf = self.tf
if self.log:
xfunc = np.logspace
xmi, xma = np.log10(self.bounds[0]), np.log10(self.bounds[1])
else:
xfunc = np.linspace
# Need to strip units off of the bounds to avoid a recursion error
# in matplotlib 1.3.1
xmi, xma = [np.float64(b) for b in self.bounds]
x = xfunc(xmi, xma, tf.nbins)
y = tf.funcs[3].y
w = np.append(x[1:] - x[:-1], x[-1] - x[-2])
colors = np.array(
[tf.funcs[0].y, tf.funcs[1].y, tf.funcs[2].y,
np.ones_like(x)]).T
fig = Figure(figsize=[6, 3])
canvas = FigureCanvasAgg(fig)
ax = fig.add_axes([0.2, 0.2, 0.75, 0.75])
ax.bar(x,
tf.funcs[3].y,
w,
edgecolor=[0.0, 0.0, 0.0, 0.0],
log=self.log,
color=colors,
bottom=[0])
if profile_field is not None:
try:
prof = self.profiles[self.field]
except KeyError:
self.setup_profile(profile_field, profile_weight)
prof = self.profiles[self.field]
try:
prof[profile_field]
except KeyError:
prof.add_fields([profile_field])
# Strip units, if any, for matplotlib 1.3.1
xplot = np.array(prof.x)
yplot = np.array(prof[profile_field] * tf.funcs[3].y.max() /
prof[profile_field].max())
ax.plot(xplot, yplot, color='w', linewidth=3)
ax.plot(xplot, yplot, color='k')
ax.set_xscale({True: 'log', False: 'linear'}[self.log])
ax.set_xlim(x.min(), x.max())
ax.set_xlabel(self.ds._get_field_info(self.field).get_label())
ax.set_ylabel(r'$\mathrm{alpha}$')
ax.set_ylim(y.max() * 1.0e-3, y.max() * 2)
if fn is None:
from IPython.core.display import Image
f = BytesIO()
canvas.print_figure(f)
f.seek(0)
img = f.read()
return Image(img)
else:
fig.savefig(fn)
def setup_profile(self, profile_field=None, profile_weight=None):
if profile_field is None:
profile_field = 'cell_volume'
prof = create_profile(self.ds.all_data(),
self.field,
profile_field,
n_bins=128,
extrema={self.field: self.bounds},
weight_field=profile_weight,
logs={self.field: self.log})
self.profiles[self.field] = prof
return
#load the uniform grid from a numpy array file
bolshoi = "/home/bogert/log_densities_1024.npy"
density_grid = np.load(bolshoi)
#Set the TheiaScene to use the density_grid and
#setup the raycaster for a resulting 1080p image
ts = TheiaScene(volume=density_grid,
raycaster=FrontToBackRaycaster(size=(1920, 1080)))
#the min and max values in the data to color
mi, ma = 0.0, 3.6
#setup colortransferfunction
bins = 5000
tf = ColorTransferFunction((mi, ma), bins)
tf.map_to_colormap(0.5, ma, colormap="spring", scale_func=scale_func)
#pass the transfer function to the ray caster
ts.source.raycaster.set_transfer(tf)
#Initial configuration for start of video
#set initial opacity and brightness values
#then zoom into the center of the data 30%
ts.source.raycaster.set_opacity(0.03)
ts.source.raycaster.set_brightness(2.3)
ts.camera.zoom(30.0)
#path to ffmpeg executable
FFMPEG_BIN = "/usr/local/bin/ffmpeg"
return np.minimum(1.0, (v-mi)/(ma-mi) + 0.0) #load the uniform grid from a numpy array file bolshoi = "/home/bogert/log_densities_1024.npy" density_grid = np.load(bolshoi) #Set the TheiaScene to use the density_grid and #setup the raycaster for a resulting 1080p image ts = TheiaScene(volume = density_grid, raycaster = FrontToBackRaycaster(size = (1920,1080) )) #the min and max values in the data to color mi, ma = 0.0, 3.6 #setup colortransferfunction bins = 5000 tf = ColorTransferFunction( (mi, ma), bins) tf.map_to_colormap(0.5, ma, colormap="spring", scale_func = scale_func) #pass the transfer function to the ray caster ts.source.raycaster.set_transfer(tf) #Initial configuration for start of video #set initial opacity and brightness values #then zoom into the center of the data 30% ts.source.raycaster.set_opacity(0.03) ts.source.raycaster.set_brightness(2.3) ts.camera.zoom(30.0) #path to ffmpeg executable FFMPEG_BIN = "/usr/local/bin/ffmpeg"
