def __init__(self, scene=None, source=None, throws=1, steps=50, seed=None, use_visualiser=True, show_log=True, background=(0.957, 0.957, 1), ambient=0.5):
super(Tracer, self).__init__()
self.scene = scene
from LightSources import SimpleSource, PlanarSource, CylindricalSource, PointSource, RadialSource
self.source = source
self.throws = throws
self.steps = steps
self.totalsteps = 0
self.seed = seed
self.killed = 0
self.database = PhotonDatabase.PhotonDatabase()
self.stats = dict()
self.show_log = show_log
np.random.seed(self.seed)
if not use_visualiser:
Visualiser.VISUALISER_ON = False
else:
Visualiser.VISUALISER_ON = True
self.visualiser = Visualiser(background=background, ambient=ambient)
for obj in scene.objects:
if obj != scene.bounds:
if not isinstance(obj.shape, CSGadd) and not isinstance(obj.shape, CSGint) and not isinstance(obj.shape, CSGsub):
if isinstance(obj.material, SimpleMaterial):
wavelength = obj.material.bandgap
else:
if not hasattr(obj.material, 'all_absorption_coefficients'):
maxindex = obj.material.emission_data.y.argmax()
wavelength = obj.material.emission_data.x[maxindex]
colour = wav2RGB(wavelength)
else:
# It is possible to processes the most likley colour of a spectrum in a better way than this!
colour = [0.1,0.1,0.1]
if colour[0] == np.nan or colour[1] == np.nan or colour[2] == np.nan:
colour = [0.1,0.1,0.1]
self.visualiser.addObject(obj.shape, colour=colour)
self.show_lines = True#False
self.show_exit = True
self.show_path = True#False
self.show_start = True
def __init__(self,
scene=None,
source=None,
throws=1,
steps=50,
seed=None,
use_visualiser=True,
show_log=False,
background=(0.957, 0.957, 1),
ambient=0.5,
database_file="pvtracedb.sql"):
super(Tracer, self).__init__()
self.scene = scene
from LightSources import SimpleSource, PlanarSource, CylindricalSource, PointSource, RadialSource
self.source = source
self.throws = throws
self.steps = steps
self.totalsteps = 0
self.seed = seed
self.killed = 0
self.database = PhotonDatabase.PhotonDatabase(database_file)
self.stats = dict()
self.show_log = show_log
np.random.seed(self.seed)
if not use_visualiser:
Visualiser.VISUALISER_ON = False
else:
Visualiser.VISUALISER_ON = True
self.visualiser = Visualiser(background=background, ambient=ambient)
# This should not happen here in the tracer... refactor this non-sense
if VISUAL_INSTALLED:
for obj in scene.objects:
if obj != scene.bounds:
if not isinstance(obj.shape, CSGadd) and not isinstance(
obj.shape, CSGint) and not isinstance(
obj.shape, CSGsub):
#import pdb; pdb.set_trace()
if isinstance(obj, RayBin):
#checkerboard = ( (0,0.01,0,0.01), (0.01,0,0.01,0), (0,0.01,0,1), (0.01,0,0.01,0) )
#checkerboard = ( (0,1,0,1), (1,0,1,0), (0,1,0,1), (1,0,1,0) )
#material = visual.materials.texture(data=checkerboard, mapping="rectangular", interpolate=False)
material = visual.materials.wood
colour = visual.color.blue
opacity = 1.
elif isinstance(obj, Coating):
colour = visual.color.white
opacity = 0.5
material = visual.materials.plastic
if hasattr(obj.reflectivity, 'lambertian'):
if obj.reflectivity.lambertian is True:
# The material is a diffuse reflector
colour = visual.color.white
opacity = 1.
material = visual.materials.plastic
elif isinstance(obj.material, SimpleMaterial):
#import pdb; pdb.set_trace()
wavelength = obj.material.bandgap
colour = norm(wav2RGB(wavelength))
opacity = 0.5
material = visual.materials.plastic
else:
if not hasattr(obj.material,
'all_absorption_coefficients'):
try:
maxindex = obj.material.emission_data.y.argmax(
)
wavelength = obj.material.emission_data.x[
maxindex]
colour = norm(wav2RGB(wavelength))
except:
colour = (0.2, 0.2, 0.2)
opacity = 0.5
material = visual.materials.plastic
else:
# It is possible to processes the most likley colour of a spectrum in a better way than this!
colour = (0.2, 0.2, 0.2)
opacity = 0.5
material = visual.materials.plastic
if colour[0] == np.nan or colour[
1] == np.nan or colour[2] == np.nan:
colour = (0.2, 0.2, 0.2)
self.visualiser.addObject(obj.shape,
colour=colour,
opacity=opacity,
material=material)
self.show_lines = True #False
self.show_exit = True
self.show_path = True #False
self.show_start = True
self.show_normals = False
