######################################
# Options
# Sphere origin
orig = [0, 0, 0]
# Gridding, number of pixels in slice
nPhi = 50
# Detector filename
fname = "AllDetector_1_LED.bin"
# Axis of the slice
sliceAx = 'y'
# Detector width, anlge that the detector sees. [deg]
detAng = 5.0
######################################
df = ft.loadDetectorData(fname)
gp = dt.convertToSlice(df, nPhi=nPhi, detAng=detAng)
fig = plt.figure()
ax = fig.add_subplot(111)
# Sum pixels
gg = gp['radPower']
gg.plot()
plt.xlabel('Angle on slice, deg. (Axis %s)' % sliceAx)
plt.ylabel('W/sr')
plt.legend()
plt.show(block=True)
def _tracerProcessEnded(self, lines):
# Check if process ended correctly
# TODO! raise APIError (temporarily commented out for testing)
if "########## Tracing done ################" in lines:
logger.info("Tracing successful!")
else:
for line in lines:
logger.debug(line)
print(lines)
logger.info("Tracing was not successful!")
raise APIError.APIError("Tracing was not successful!")
# Read absorption data
(points, absorb) = vtkS.readAbsorptionData(self._absorptionFilePath)
# print(points)
# print(absorb)
# Get field
key = (FieldID.FID_Thermal_absorption_volume, self._curTStep)
print(self.fields)
f = self.fields[key]
# Convert point data to field mesh
if self._convertPointData:
if meshS.FASTisAvailable():
meshS.convertPointDataToMeshFAST(
pointdataVTKfile=self._absorptionFilePath,
field=f, inplace=True)
else:
meshS.convertPointDataToMesh(points, absorb, f, inplace=True)
# Read line data (if needed): (TODO: not tested)
# (pts, wv, offs) = vtkS.readLineData("ray_paths.vtp")
# Read photometric data from overall detector
df = ft.loadDetectorData('AllDetector_1_LED.bin')
data = dt.convertToSphere(df)
# Set data to properties
# Spectrum
key = (PropertyID.PID_LEDSpectrum, objID.OBJ_LED,
self._curTStep)
p = self.properties[key]
p.value['wavelengths'] = data['wavelengths']
p.value['intensities'] = data['intensities']
# Color x
key = (PropertyID.PID_LEDColor_x, objID.OBJ_LED,
self._curTStep)
p = self.properties[key]
p.value = data['color_x']
# Color y
key = (PropertyID.PID_LEDColor_y, objID.OBJ_LED,
self._curTStep)
p = self.properties[key]
p.value = data['color_y']
# CCT
key = (PropertyID.PID_LEDCCT, objID.OBJ_LED,
self._curTStep)
p = self.properties[key]
p.value = data['CCT']
# RadPower
key = (PropertyID.PID_LEDRadiantPower, objID.OBJ_LED,
self._curTStep)
p = self.properties[key]
p.value = data['radPower']
import numpy as np
from mpl_toolkits.mplot3d import Axes3D
import os
import io
import pyraytracer.fileTools as ft
# Set axes equal
axesEqual = False
# Create figure
fig = plt.figure()
ax = fig.add_subplot(111, projection='3d')
fpath = "AllDetector_1_LED.bin"
df = ft.loadDetectorData(fpath)
# plot
plt.plot(df['x'], df['y'], df['z'], 'x')
# Equalize axes (approximately, maybe)
if axesEqual:
axLim = ax.get_w_lims()
MAX = np.max(axLim)
for direction in (-1, 1):
for point in np.diag(direction * MAX * np.array([1, 1, 1])):
ax.plot([point[0]], [point[1]], [np.abs(point[2])], 'w')
plt.show()
def _tracerProcessEnded(self, lines):
# Check if process ended correctly
# TODO! raise APIError (temporarily commented out for testing)
if "########## Tracing done ################" in lines:
logger.info("Tracing successful!")
else:
for line in lines:
logger.debug(line)
print(lines)
logger.info("Tracing was not successful!")
raise APIError.APIError("Tracing was not successful!")
# Read absorption data
(points, absorb) = vtkS.readAbsorptionData(self._absorptionFilePath)
# print(points)
# print(absorb)
# Get field
key = (FieldID.FID_Thermal_absorption_volume, self._curTStep)
print(self.fields)
f = self.fields[key]
# Convert point data to field mesh
if self._convertPointData:
if meshS.FASTisAvailable():
meshS.convertPointDataToMeshFAST(
pointdataVTKfile=self._absorptionFilePath,
field=f,
inplace=True)
else:
meshS.convertPointDataToMesh(points, absorb, f, inplace=True)
# Read line data (if needed): (TODO: not tested)
# (pts, wv, offs) = vtkS.readLineData("ray_paths.vtp")
# Read photometric data from overall detector
df = ft.loadDetectorData('AllDetector_1_LED.bin')
data = dt.convertToSphere(df)
# Set data to properties
# Spectrum
key = (PropertyID.PID_LEDSpectrum, objID.OBJ_LED, self._curTStep)
p = self.properties[key]
p.value['wavelengths'] = data['wavelengths']
p.value['intensities'] = data['intensities']
# Color x
key = (PropertyID.PID_LEDColor_x, objID.OBJ_LED, self._curTStep)
p = self.properties[key]
p.value = data['color_x']
# Color y
key = (PropertyID.PID_LEDColor_y, objID.OBJ_LED, self._curTStep)
p = self.properties[key]
p.value = data['color_y']
# CCT
key = (PropertyID.PID_LEDCCT, objID.OBJ_LED, self._curTStep)
p = self.properties[key]
p.value = data['CCT']
# RadPower
key = (PropertyID.PID_LEDRadiantPower, objID.OBJ_LED, self._curTStep)
p = self.properties[key]
p.value = data['radPower']
