galaxy = Galaxy(10000)
galaxy.reset(13000, 4000, 0.0004, 0.90, 0.90, 0.5, 200, 300)
# coldest and hottest temperatures of out galaxy
t0, t1 = 200.0, 10000.0
# total number of discrete colors between t0 and t1
n = 1000
dt = (t1 - t0) / n
# maps [0, n) -> colors
# generate a linear interpolation of temperatures
# then map the temperatures to colors using black body
# color predictions
colors = np.zeros(n, dtype=(np.float32, 3))
for i in range(n):
temperature = t0 + i * dt
x, y, z = galaxy_specrend.spectrum_to_xyz(galaxy_specrend.bb_spectrum,
temperature)
r, g, b = galaxy_specrend.xyz_to_rgb(galaxy_specrend.SMPTEsystem, x, y, z)
r = min((max(r, 0), 1))
g = min((max(g, 0), 1))
b = min((max(b, 0), 1))
colors[i] = galaxy_specrend.norm_rgb(r, g, b)
# load the PNG that we use to blend the star with
# to provide a circular look to each star.
def load_galaxy_star_image():
fname = io.load_data_file('galaxy/star-particle.png')
raw_image = io.read_png(fname)
return raw_image
galaxy = Galaxy(10000)
galaxy.reset(13000, 4000, 0.0004, 0.90, 0.90, 0.5, 200, 300)
# coldest and hottest temperatures of out galaxy
t0, t1 = 200.0, 10000.0
# total number of discrete colors between t0 and t1
n = 1000
dt = (t1 - t0) / n
# maps [0, n) -> colors
# generate a linear interpolation of temperatures
# then map the temperatures to colors using black body
# color predictions
colors = np.zeros(n, dtype=(np.float32, 3))
for i in range(n):
temperature = t0 + i * dt
x, y, z = galaxy_specrend.spectrum_to_xyz(galaxy_specrend.bb_spectrum,
temperature)
r, g, b = galaxy_specrend.xyz_to_rgb(galaxy_specrend.SMPTEsystem, x, y, z)
r = min((max(r, 0), 1))
g = min((max(g, 0), 1))
b = min((max(b, 0), 1))
colors[i] = galaxy_specrend.norm_rgb(r, g, b)
# load the PNG that we use to blend the star with
# to provide a circular look to each star.
def load_galaxy_star_image():
fname = io.load_data_file('galaxy/star-particle.png')
raw_image = io.read_png(fname)
return raw_image