def test_judd_wyszecki(self, verbose=False):
''' Test computed chromaticities vs table in Judd and Wyszecki. '''
if verbose:
print('Test vs. Judd and Wyszecki:')
table = Judd_Wyszeki_blackbody_chromaticity_table
num_rows = table.shape[0]
for i in range(0, num_rows):
# Read temperature and expected chromaticity.
T = table[i][0]
x_expect = table[i][1]
y_expect = table[i][2]
# Calculate chromaticity for the temperature.
xyz = blackbody.blackbody_color(T)
colormodels.xyz_normalize(xyz)
x_actual = xyz[0]
y_actual = xyz[1]
# Check against the tabulated result.
x_error = math.fabs(x_actual - x_expect)
y_error = math.fabs(y_actual - y_expect)
# The tolerance used is larger than desired.
# A tolerance of 5.0e-5 would match the precision in the book.
tolerance = 15.0e-5
self.assertAlmostEqual(x_actual, x_expect, delta=tolerance)
self.assertAlmostEqual(y_actual, y_expect, delta=tolerance)
# Print results.
msg = 'T: %8.1f K Calculated x,y: %.5f, %.5f Expected x,y: %.5f, %.5f Error: %.5e, %.5e' % (
T, x_actual, y_actual, x_expect, y_expect, x_error, y_error)
if verbose:
print(msg)
def test_judd_wyszecki(self, verbose=False):
''' Test computed chromaticities vs table in Judd and Wyszecki. '''
if verbose:
print ('Test vs. Judd and Wyszecki:')
table = Judd_Wyszeki_blackbody_chromaticity_table
num_rows = table.shape[0]
for i in range (0, num_rows):
# Read temperature and expected chromaticity.
T = table [i][0]
x_expect = table [i][1]
y_expect = table [i][2]
# Calculate chromaticity for the temperature.
xyz = blackbody.blackbody_color (T)
colormodels.xyz_normalize (xyz)
x_actual = xyz[0]
y_actual = xyz[1]
# Check against the tabulated result.
x_error = math.fabs(x_actual - x_expect)
y_error = math.fabs(y_actual - y_expect)
# The tolerance used is larger than desired.
# A tolerance of 5.0e-5 would match the precision in the book.
tolerance = 15.0e-5
self.assertAlmostEqual(x_actual, x_expect, delta=tolerance)
self.assertAlmostEqual(y_actual, y_expect, delta=tolerance)
# Print results.
msg = 'T: %8.1f K Calculated x,y: %.5f, %.5f Expected x,y: %.5f, %.5f Error: %.5e, %.5e' % (
T, x_actual, y_actual, x_expect, y_expect, x_error, y_error)
if verbose:
print (msg)
def get_normalized_spectral_line_colors_annotated (
brightness = 1.0,
num_purples = 0,
dwl_angstroms = 10):
'''Get an array of xyz colors covering the visible spectrum.
Optionally add a number of 'purples', which are colors interpolated between the color
of the lowest wavelength (violet) and the highest (red).
A text string describing the color is supplied for each color.
brightness - Desired maximum rgb component of each color. Default 1.0. (Maxiumum displayable brightness)
num_purples - Number of colors to interpolate in the 'purple' range. Default 0. (No purples)
dwl_angstroms - Wavelength separation, in angstroms (0.1 nm). Default 10 A. (1 nm spacing)
'''
# get range of wavelengths, in angstroms, so that we can have finer resolution than 1 nm
wl_angstrom_range = range (10*start_wl_nm, 10*(end_wl_nm + 1), dwl_angstroms)
# get total point count
num_spectral = len (wl_angstrom_range)
num_points = num_spectral + num_purples
xyzs = numpy.empty ((num_points, 3))
names = []
# build list of normalized color x,y values proceeding along each wavelength
i = 0
for wl_A in wl_angstrom_range:
wl_nm = wl_A * 0.1
xyz = xyz_from_wavelength (wl_nm)
colormodels.xyz_normalize (xyz)
xyzs [i] = xyz
name = '%.1f nm' % wl_nm
names.append (name)
i += 1
# interpolate from end point to start point (filling in the purples)
first_xyz = xyzs [0]
last_xyz = xyzs [num_spectral - 1]
for ipurple in range (0, num_purples):
t = float (ipurple) / float (num_purples - 1)
omt = 1.0 - t
xyz = t * first_xyz + omt * last_xyz
colormodels.xyz_normalize (xyz)
xyzs [i] = xyz
name = '%03d purple' % math.floor (1000.0 * t + 0.5)
names.append (name)
i += 1
# scale each color to have the max rgb component equal to the desired brightness
for i in range (0, num_points):
rgb = colormodels.brightest_rgb_from_xyz (xyzs [i], brightness)
xyzs [i] = colormodels.xyz_from_rgb (rgb)
# done
return (xyzs, names)
def xyzFromRGB(red, green=None, blue=None): """ RGB转成xyz """ if isinstance(red, basestring): # assume a hex string is passed if red[0] == "#": colorString = red[1:] else: colorString = red red = int(colorString[0:2], 16) green = int(colorString[2:4], 16) blue = int(colorString[4:], 16) # We need to convert the RGB value to Yxy. redScale = float(red) / 255.0 greenScale = float(green) / 255.0 blueScale = float(blue) / 255.0 colormodels.init( phosphor_red=colormodels.xyz_color(0.64843, 0.33086), phosphor_green=colormodels.xyz_color(0.4091, 0.518), phosphor_blue=colormodels.xyz_color(0.167, 0.04)) xyz = colormodels.irgb_color(red, green, blue) xyz = colormodels.xyz_from_rgb(xyz) xyz = colormodels.xyz_normalize(xyz) return xyz
def get_normalized_spectral_line_colors(brightness=1.0,
num_purples=0,
dwl_angstroms=10):
'''Get an array of xyz colors covering the visible spectrum.
Optionally add a number of 'purples', which are colors interpolated between the color
of the lowest wavelength (violet) and the highest (red).
brightness - Desired maximum rgb component of each color. Default 1.0. (Maxiumum displayable brightness)
num_purples - Number of colors to interpolate in the 'purple' range. Default 0. (No purples)
dwl_angstroms - Wavelength separation, in angstroms (0.1 nm). Default 10 A. (1 nm spacing)
'''
# get range of wavelengths, in angstroms, so that we can have finer resolution than 1 nm
wl_angstrom_range = xrange(10 * start_wl_nm, 10 * (end_wl_nm + 1),
dwl_angstroms)
# get total point count
num_spectral = len(wl_angstrom_range)
num_points = num_spectral + num_purples
xyzs = numpy.empty((num_points, 3))
# build list of normalized color x,y values proceeding along each wavelength
i = 0
for wl_A in wl_angstrom_range:
wl_nm = wl_A * 0.1
xyz = xyz_from_wavelength(wl_nm)
colormodels.xyz_normalize(xyz)
xyzs[i] = xyz
i += 1
# interpolate from end point to start point (filling in the purples)
first_xyz = xyzs[0]
last_xyz = xyzs[num_spectral - 1]
for ipurple in xrange(0, num_purples):
t = float(ipurple) / float(num_purples - 1)
omt = 1.0 - t
xyz = t * first_xyz + omt * last_xyz
colormodels.xyz_normalize(xyz)
xyzs[i] = xyz
i += 1
# scale each color to have the max rgb component equal to the desired brightness
for i in xrange(0, num_points):
rgb = colormodels.rgb_from_xyz(xyzs[i])
max_rgb = max(rgb)
if max_rgb != 0.0:
scale = brightness / max_rgb
rgb *= scale
xyzs[i] = colormodels.xyz_from_rgb(rgb)
# done
return xyzs
def test_gold_point(self, verbose=False):
''' Test the chromaticity at the 'gold point'. '''
# From Wyszecki & Stiles, p. 28.
T = 1336.0 # 'Gold' point
x_expect = 0.607
y_expect = 0.381
xyz = blackbody.blackbody_color(T)
colormodels.xyz_normalize(xyz)
x_actual = xyz[0]
y_actual = xyz[1]
# Check result. The tolerance is high, there is a discrepancy
# in the last printed digit in the table in the book.
# A tolerance of 5.0e-4 would match the precision in the book.
tolerance = 6.0e-4
self.assertAlmostEqual(x_actual, x_expect, delta=tolerance)
self.assertAlmostEqual(y_actual, y_expect, delta=tolerance)
# This source is supposed to be 0.11 cd/cm^2 = 1100 cd/m^2,
# whereas monitors are c. 80 cd/m^2 to 300 cd/m^2.
msg = 'Blackbody color at gold point: %s' % (str(xyz))
if verbose:
print(msg)
def test_gold_point(self, verbose=False):
''' Test the chromaticity at the 'gold point'. '''
# From Wyszecki & Stiles, p. 28.
T = 1336.0 # 'Gold' point
x_expect = 0.607
y_expect = 0.381
xyz = blackbody.blackbody_color (T)
colormodels.xyz_normalize (xyz)
x_actual = xyz[0]
y_actual = xyz[1]
# Check result. The tolerance is high, there is a discrepancy
# in the last printed digit in the table in the book.
# A tolerance of 5.0e-4 would match the precision in the book.
tolerance = 6.0e-4
self.assertAlmostEqual(x_actual, x_expect, delta=tolerance)
self.assertAlmostEqual(y_actual, y_expect, delta=tolerance)
# This source is supposed to be 0.11 cd/cm^2 = 1100 cd/m^2,
# whereas monitors are c. 80 cd/m^2 to 300 cd/m^2.
msg = 'Blackbody color at gold point: %s' % (str (xyz))
if verbose:
print (msg)
def test_book (verbose=1):
'''Test that the computed chromaticities match an existing table, from Judd and Wyszecki.'''
num_passed = 0
num_failed = 0
(num_rows, num_cols) = book_chrom_table.shape
for i in xrange (0, num_rows):
T = book_chrom_table [i][0]
book_x = book_chrom_table [i][1]
book_y = book_chrom_table [i][2]
# calculate color for T
xyz = blackbody.blackbody_color (T)
colormodels.xyz_normalize (xyz)
dx = xyz [0] - book_x
dy = xyz [1] - book_y
# did we match the tablulated result?
tolerance = 2.0e-4
passed = (math.fabs (dx) <= tolerance) and (math.fabs (dy) <= tolerance)
if passed:
status = 'pass'
else:
status = 'FAILED'
msg = 'test_book() : T = %g : calculated x,y = %g,%g : book values x,y = %g,%g : errors = %g,%g' % (
T, xyz [0], xyz [1], book_x, book_y, dx, dy)
if verbose >= 1:
print msg
if not passed:
pass
raise ValueError, msg
if passed:
num_passed += 1
else:
num_failed += 1
msg = 'test_book() : %d tests passed, %d tests failed' % (
num_passed, num_failed)
print msg
def test_book (verbose=1):
'''Test that the computed chromaticities match an existing table, from Judd and Wyszecki.'''
num_passed = 0
num_failed = 0
(num_rows, num_cols) = book_chrom_table.shape
for i in xrange (0, num_rows):
T = book_chrom_table [i][0]
book_x = book_chrom_table [i][1]
book_y = book_chrom_table [i][2]
# calculate color for T
xyz = blackbody.blackbody_color (T)
colormodels.xyz_normalize (xyz)
dx = xyz [0] - book_x
dy = xyz [1] - book_y
# did we match the tablulated result?
tolerance = 2.0e-4
passed = (math.fabs (dx) <= tolerance) and (math.fabs (dy) <= tolerance)
if passed:
status = 'pass'
else:
status = 'FAILED'
msg = 'test_book() : T = %g : calculated x,y = %g,%g : book values x,y = %g,%g : errors = %g,%g' % (
T, xyz [0], xyz [1], book_x, book_y, dx, dy)
if verbose >= 1:
print msg
if not passed:
pass
raise ValueError, msg
if passed:
num_passed += 1
else:
num_failed += 1
msg = 'test_book() : %d tests passed, %d tests failed' % (
num_passed, num_failed)
print msg
def shark_fin_plot ():
'''Draw the 'shark fin' CIE chromaticity diagram of the pure spectral lines (plus purples) in xy space.'''
# get array of (approximate) colors for the boundary of the fin
xyz_list = ciexyz.get_normalized_spectral_line_colors (brightness=1.0, num_purples=200, dwl_angstroms=2)
# get normalized colors
xy_list = xyz_list.copy()
(num_colors, num_cols) = xy_list.shape
for i in xrange (0, num_colors):
colormodels.xyz_normalize (xy_list [i])
# get phosphor colors and normalize
red = colormodels.PhosphorRed
green = colormodels.PhosphorGreen
blue = colormodels.PhosphorBlue
white = colormodels.PhosphorWhite
colormodels.xyz_normalize (red)
colormodels.xyz_normalize (green)
colormodels.xyz_normalize (blue)
colormodels.xyz_normalize (white)
def get_direc_to_white (xyz):
'''Get unit vector (xy plane) in direction of the white point.'''
direc = white - xyz
mag = math.hypot (direc [0], direc [1])
if mag != 0.0:
direc /= mag
return (direc[0], direc[1])
# plot
pylab.clf ()
# draw color patches for point in xy_list
s = 0.025 # distance in xy plane towards white point
for i in xrange (0, len (xy_list)-1):
x0 = xy_list [i][0]
y0 = xy_list [i][1]
x1 = xy_list [i+1][0]
y1 = xy_list [i+1][1]
# get unit vectors in direction of white point
(dir_x0, dir_y0) = get_direc_to_white (xy_list [i])
(dir_x1, dir_y1) = get_direc_to_white (xy_list [i+1])
# polygon vertices
poly_x = [x0, x1, x1 + s*dir_x1, x0 + s*dir_x0]
poly_y = [y0, y1, y1 + s*dir_y1, y0 + s*dir_y0]
# draw (using full color, not normalized value)
color_string = colormodels.irgb_string_from_rgb (
colormodels.rgb_from_xyz (xyz_list [i]))
pylab.fill (poly_x, poly_y, color_string, edgecolor=color_string)
# draw the curve of the xy values of the spectral lines and purples
pylab.plot (xy_list [:,0], xy_list [:,1], color='#808080', linewidth=3.0)
# draw monitor gamut and white point
pylab.plot ([red [0], green[0]], [red [1], green[1]], 'o-', color='k')
pylab.plot ([green[0], blue [0]], [green[1], blue [1]], 'o-', color='k')
pylab.plot ([blue [0], red [0]], [blue [1], red [1]], 'o-', color='k')
pylab.plot ([white[0], white[0]], [white[1], white[1]], 'o-', color='k')
# label phosphors
dx = 0.01
dy = 0.01
pylab.text (red [0] + dx, red [1], 'Red', ha='left', va='center')
pylab.text (green [0], green [1] + dy, 'Green', ha='center', va='bottom')
pylab.text (blue [0] - dx, blue [1], 'Blue', ha='right', va='center')
pylab.text (white [0], white [1] + dy, 'White', ha='center', va='bottom')
# titles etc
pylab.axis ([0.0, 0.85, 0.0, 0.85])
pylab.xlabel (r'CIE $x$')
pylab.ylabel (r'CIE $y$')
pylab.title (r'CIE Chromaticity Diagram')
filename = 'ChromaticityDiagram'
print 'Saving plot %s' % (str (filename))
pylab.savefig (filename)
def shark_fin_plot():
'''Draw the 'shark fin' CIE chromaticity diagram of the pure spectral lines (plus purples) in xy space.'''
# get array of (approximate) colors for the boundary of the fin
xyz_list = ciexyz.get_normalized_spectral_line_colors(brightness=1.0,
num_purples=200,
dwl_angstroms=2)
# get normalized colors
xy_list = xyz_list.copy()
(num_colors, num_cols) = xy_list.shape
for i in xrange(0, num_colors):
colormodels.xyz_normalize(xy_list[i])
# get phosphor colors and normalize
red = colormodels.PhosphorRed
green = colormodels.PhosphorGreen
blue = colormodels.PhosphorBlue
white = colormodels.PhosphorWhite
colormodels.xyz_normalize(red)
colormodels.xyz_normalize(green)
colormodels.xyz_normalize(blue)
colormodels.xyz_normalize(white)
def get_direc_to_white(xyz):
'''Get unit vector (xy plane) in direction of the white point.'''
direc = white - xyz
mag = math.hypot(direc[0], direc[1])
if mag != 0.0:
direc /= mag
return (direc[0], direc[1])
# plot
pylab.clf()
# draw color patches for point in xy_list
s = 0.025 # distance in xy plane towards white point
for i in xrange(0, len(xy_list) - 1):
x0 = xy_list[i][0]
y0 = xy_list[i][1]
x1 = xy_list[i + 1][0]
y1 = xy_list[i + 1][1]
# get unit vectors in direction of white point
(dir_x0, dir_y0) = get_direc_to_white(xy_list[i])
(dir_x1, dir_y1) = get_direc_to_white(xy_list[i + 1])
# polygon vertices
poly_x = [x0, x1, x1 + s * dir_x1, x0 + s * dir_x0]
poly_y = [y0, y1, y1 + s * dir_y1, y0 + s * dir_y0]
# draw (using full color, not normalized value)
color_string = colormodels.irgb_string_from_rgb(
colormodels.rgb_from_xyz(xyz_list[i]))
pylab.fill(poly_x, poly_y, color_string, edgecolor=color_string)
# draw the curve of the xy values of the spectral lines and purples
pylab.plot(xy_list[:, 0], xy_list[:, 1], color='#808080', linewidth=3.0)
# draw monitor gamut and white point
pylab.plot([red[0], green[0]], [red[1], green[1]], 'o-', color='k')
pylab.plot([green[0], blue[0]], [green[1], blue[1]], 'o-', color='k')
pylab.plot([blue[0], red[0]], [blue[1], red[1]], 'o-', color='k')
pylab.plot([white[0], white[0]], [white[1], white[1]], 'o-', color='k')
# label phosphors
dx = 0.01
dy = 0.01
pylab.text(red[0] + dx, red[1], 'Red', ha='left', va='center')
pylab.text(green[0], green[1] + dy, 'Green', ha='center', va='bottom')
pylab.text(blue[0] - dx, blue[1], 'Blue', ha='right', va='center')
pylab.text(white[0], white[1] + dy, 'White', ha='center', va='bottom')
# titles etc
pylab.axis([0.0, 0.85, 0.0, 0.85])
pylab.xlabel(r'CIE $x$')
pylab.ylabel(r'CIE $y$')
pylab.title(r'CIE Chromaticity Diagram')
filename = 'ChromaticityDiagram'
print 'Saving plot %s' % (str(filename))
pylab.savefig(filename)
def shark_fin_plot():
'''Draw the 'shark fin' CIE chromaticity diagram of the pure spectral lines (plus purples) in xy space.'''
# get array of (approximate) colors for the boundary of the fin
xyz_list = ciexyz.get_normalized_spectral_line_colors(brightness=1.0,
num_purples=200,
dwl_angstroms=2)
# get normalized colors
xy_list = xyz_list.copy()
(num_colors, num_cols) = xy_list.shape
for i in range(0, num_colors):
colormodels.xyz_normalize(xy_list[i])
# get phosphor colors and normalize
red = colormodels.PhosphorRed
green = colormodels.PhosphorGreen
blue = colormodels.PhosphorBlue
white = colormodels.PhosphorWhite
colormodels.xyz_normalize(red)
colormodels.xyz_normalize(green)
colormodels.xyz_normalize(blue)
colormodels.xyz_normalize(white)
def get_direc_to_white(xyz):
'''Get unit vector (xy plane) in direction of the white point.'''
direc = white - xyz
mag = math.hypot(direc[0], direc[1])
if mag != 0.0:
direc /= mag
return (direc[0], direc[1])
# plot
pylab.clf()
# draw best attempt at pure spectral colors on inner edge of shark fin
s = 0.025 # distance in xy plane towards white point
for i in range(0, len(xy_list) - 1):
x0 = xy_list[i][0]
y0 = xy_list[i][1]
x1 = xy_list[i + 1][0]
y1 = xy_list[i + 1][1]
# get unit vectors in direction of white point
(dir_x0, dir_y0) = get_direc_to_white(xy_list[i])
(dir_x1, dir_y1) = get_direc_to_white(xy_list[i + 1])
# polygon vertices
poly_x = [x0, x1, x1 + s * dir_x1, x0 + s * dir_x0]
poly_y = [y0, y1, y1 + s * dir_y1, y0 + s * dir_y0]
# draw (using full color, not normalized value)
color_string = colormodels.irgb_string_from_rgb(
colormodels.rgb_from_xyz(xyz_list[i]))
pylab.fill(poly_x, poly_y, color_string, edgecolor=color_string)
# fill in the monitor gamut with true colors
def get_brightest_irgb_string(xyz):
'''Convert the xyz color to rgb, scale to maximum displayable brightness, and convert to a string.'''
rgb = colormodels.brightest_rgb_from_xyz(xyz)
color_string = colormodels.irgb_string_from_rgb(rgb)
return color_string
def fill_gamut_slice(v0, v1, v2):
'''Fill in a slice of the monitor gamut with the correct colors.'''
#num_s, num_t = 10, 10
#num_s, num_t = 25, 25
num_s, num_t = 50, 50
dv10 = v1 - v0
dv21 = v2 - v1
for i_s in range(num_s):
s_a = float(i_s) / float(num_s)
s_b = float(i_s + 1) / float(num_s)
for i_t in range(num_t):
t_a = float(i_t) / float(num_t)
t_b = float(i_t + 1) / float(num_t)
# vertex coords
v_aa = v0 + t_a * (dv10 + s_a * dv21)
v_ab = v0 + t_b * (dv10 + s_a * dv21)
v_ba = v0 + t_a * (dv10 + s_b * dv21)
v_bb = v0 + t_b * (dv10 + s_b * dv21)
# poly coords
poly_x = [v_aa[0], v_ba[0], v_bb[0], v_ab[0]]
poly_y = [v_aa[1], v_ba[1], v_bb[1], v_ab[1]]
# average color
avg = 0.25 * (v_aa + v_ab + v_ba + v_bb)
# convert to rgb and scale to maximum displayable brightness
color_string = get_brightest_irgb_string(avg)
pylab.fill(poly_x,
poly_y,
color_string,
edgecolor=color_string)
fill_gamut_slice(white, blue, green)
fill_gamut_slice(white, green, red)
fill_gamut_slice(white, red, blue)
# draw the curve of the xy values of the spectral lines and purples
pylab.plot(xy_list[:, 0], xy_list[:, 1], color='#808080', linewidth=3.0)
# draw monitor gamut and white point
pylab.plot([red[0], green[0]], [red[1], green[1]], 'o-', color='k')
pylab.plot([green[0], blue[0]], [green[1], blue[1]], 'o-', color='k')
pylab.plot([blue[0], red[0]], [blue[1], red[1]], 'o-', color='k')
pylab.plot([white[0], white[0]], [white[1], white[1]], 'o-', color='k')
# label phosphors
dx = 0.01
dy = 0.01
pylab.text(red[0] + dx, red[1], 'Red', ha='left', va='center')
pylab.text(green[0], green[1] + dy, 'Green', ha='center', va='bottom')
pylab.text(blue[0] - dx, blue[1], 'Blue', ha='right', va='center')
pylab.text(white[0], white[1] + dy, 'White', ha='center', va='bottom')
# titles etc
pylab.axis([0.0, 0.85, 0.0, 0.85])
pylab.xlabel(r'CIE $x$')
pylab.ylabel(r'CIE $y$')
pylab.title(r'CIE Chromaticity Diagram')
filename = 'ChromaticityDiagram'
print('Saving plot %s' % (str(filename)))
pylab.savefig(filename)
def shark_fin_plot ():
'''Draw the 'shark fin' CIE chromaticity diagram of the pure spectral lines (plus purples) in xy space.'''
# get array of (approximate) colors for the boundary of the fin
xyz_list = ciexyz.get_normalized_spectral_line_colors (brightness=1.0, num_purples=200, dwl_angstroms=2)
# get normalized colors
xy_list = xyz_list.copy()
(num_colors, num_cols) = xy_list.shape
for i in range (0, num_colors):
colormodels.xyz_normalize (xy_list [i])
# get phosphor colors and normalize
red = colormodels.PhosphorRed
green = colormodels.PhosphorGreen
blue = colormodels.PhosphorBlue
white = colormodels.PhosphorWhite
colormodels.xyz_normalize (red)
colormodels.xyz_normalize (green)
colormodels.xyz_normalize (blue)
colormodels.xyz_normalize (white)
def get_direc_to_white (xyz):
'''Get unit vector (xy plane) in direction of the white point.'''
direc = white - xyz
mag = math.hypot (direc [0], direc [1])
if mag != 0.0:
direc /= mag
return (direc[0], direc[1])
# plot
pylab.clf ()
# draw best attempt at pure spectral colors on inner edge of shark fin
s = 0.025 # distance in xy plane towards white point
for i in range (0, len (xy_list)-1):
x0 = xy_list [i][0]
y0 = xy_list [i][1]
x1 = xy_list [i+1][0]
y1 = xy_list [i+1][1]
# get unit vectors in direction of white point
(dir_x0, dir_y0) = get_direc_to_white (xy_list [i])
(dir_x1, dir_y1) = get_direc_to_white (xy_list [i+1])
# polygon vertices
poly_x = [x0, x1, x1 + s*dir_x1, x0 + s*dir_x0]
poly_y = [y0, y1, y1 + s*dir_y1, y0 + s*dir_y0]
# draw (using full color, not normalized value)
color_string = colormodels.irgb_string_from_rgb (
colormodels.rgb_from_xyz (xyz_list [i]))
pylab.fill (poly_x, poly_y, color_string, edgecolor=color_string)
# fill in the monitor gamut with true colors
def get_brightest_irgb_string (xyz):
'''Convert the xyz color to rgb, scale to maximum displayable brightness, and convert to a string.'''
rgb = colormodels.brightest_rgb_from_xyz (xyz)
color_string = colormodels.irgb_string_from_rgb (rgb)
return color_string
def fill_gamut_slice (v0, v1, v2):
'''Fill in a slice of the monitor gamut with the correct colors.'''
#num_s, num_t = 10, 10
#num_s, num_t = 25, 25
num_s, num_t = 50, 50
dv10 = v1 - v0
dv21 = v2 - v1
for i_s in range (num_s):
s_a = float (i_s) / float (num_s)
s_b = float (i_s+1) / float (num_s)
for i_t in range (num_t):
t_a = float (i_t) / float (num_t)
t_b = float (i_t+1) / float (num_t)
# vertex coords
v_aa = v0 + t_a * (dv10 + s_a * dv21)
v_ab = v0 + t_b * (dv10 + s_a * dv21)
v_ba = v0 + t_a * (dv10 + s_b * dv21)
v_bb = v0 + t_b * (dv10 + s_b * dv21)
# poly coords
poly_x = [v_aa [0], v_ba [0], v_bb [0], v_ab [0]]
poly_y = [v_aa [1], v_ba [1], v_bb [1], v_ab [1]]
# average color
avg = 0.25 * (v_aa + v_ab + v_ba + v_bb)
# convert to rgb and scale to maximum displayable brightness
color_string = get_brightest_irgb_string (avg)
pylab.fill (poly_x, poly_y, color_string, edgecolor=color_string)
fill_gamut_slice (white, blue, green)
fill_gamut_slice (white, green, red)
fill_gamut_slice (white, red, blue)
# draw the curve of the xy values of the spectral lines and purples
pylab.plot (xy_list [:,0], xy_list [:,1], color='#808080', linewidth=3.0)
# draw monitor gamut and white point
pylab.plot ([red [0], green[0]], [red [1], green[1]], 'o-', color='k')
pylab.plot ([green[0], blue [0]], [green[1], blue [1]], 'o-', color='k')
pylab.plot ([blue [0], red [0]], [blue [1], red [1]], 'o-', color='k')
pylab.plot ([white[0], white[0]], [white[1], white[1]], 'o-', color='k')
# label phosphors
dx = 0.01
dy = 0.01
pylab.text (red [0] + dx, red [1], 'Red', ha='left', va='center')
pylab.text (green [0], green [1] + dy, 'Green', ha='center', va='bottom')
pylab.text (blue [0] - dx, blue [1], 'Blue', ha='right', va='center')
pylab.text (white [0], white [1] + dy, 'White', ha='center', va='bottom')
# titles etc
pylab.axis ([0.0, 0.85, 0.0, 0.85])
pylab.xlabel (r'CIE $x$')
pylab.ylabel (r'CIE $y$')
pylab.title (r'CIE Chromaticity Diagram')
filename = 'ChromaticityDiagram'
print ('Saving plot %s' % (str (filename)))
pylab.savefig (filename)
import colormodels
# This script prints CIE xy coordinates for the monochromatic "rainbow" colors as a C++ array.
# Wavelenghts: begin, end and increment.
begin_wl = 360 # hardcoded in get_normalized_spectral_line_colors
end_wl = 830
delta_wl = 20
xyz_list = ciexyz.get_normalized_spectral_line_colors(brightness=1.0,
dwl_angstroms=delta_wl *
10)
xy_list = xyz_list.copy()
(num_colors, num_cols) = xy_list.shape
for i in xrange(0, num_colors):
colormodels.xyz_normalize(xy_list[i])
entries = len(xy_list)
# print array
print "int begin_wl = {begin_wl};".format(begin_wl=begin_wl)
print "int end_wl = {end_wl};".format(end_wl=end_wl)
print "int delta_wl = {delta_wl};".format(delta_wl=delta_wl)
print "int entries = {entries};".format(entries=entries)
print "qreal monochromatic_xy[{entries}][2] = {{".format(entries=entries)
for xyz in xy_list:
x = xyz[0]
y = xyz[1]
print(" {{ {x:.10f}, {y:.10f} }},").format(x=x, y=y)
print "};"
