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_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 check_xyz_rgb(self, xyz0, verbose):
''' Check that the xyz color, converted to rgb then back, remains the same. '''
rgb0 = colormodels.rgb_from_xyz (xyz0)
xyz1 = colormodels.xyz_from_rgb (rgb0)
rgb1 = colormodels.rgb_from_xyz (xyz1)
# Check errors.
err_rgb = rgb1 - rgb0
error_rgb = math.sqrt (numpy.dot (err_rgb, err_rgb))
err_xyz = xyz1 - xyz0
error_xyz = math.sqrt (numpy.dot (err_xyz, err_xyz))
tolerance = 1.0e-10
self.assertLess(error_xyz, tolerance)
self.assertLess(error_rgb, tolerance)
msg = 'xyz: %s rgb: %s xyz2: %s rgb2: %s' % (
str(xyz0), str(rgb0), str(xyz1), str(rgb1))
if verbose:
print (msg)
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 check_xyz_rgb(self, xyz0, verbose):
''' Check that the xyz color, converted to rgb then back, remains the same. '''
rgb0 = colormodels.rgb_from_xyz(xyz0)
xyz1 = colormodels.xyz_from_rgb(rgb0)
rgb1 = colormodels.rgb_from_xyz(xyz1)
# Check errors.
err_rgb = rgb1 - rgb0
error_rgb = math.sqrt(numpy.dot(err_rgb, err_rgb))
err_xyz = xyz1 - xyz0
error_xyz = math.sqrt(numpy.dot(err_xyz, err_xyz))
tolerance = 1.0e-10
self.assertLess(error_xyz, tolerance)
self.assertLess(error_rgb, tolerance)
msg = 'xyz: %s rgb: %s xyz2: %s rgb2: %s' % (
str(xyz0), str(rgb0), str(xyz1), str(rgb1))
if verbose:
print(msg)
def test_A (xyz0, tolerance=1.0e-10, verbose=1):
rgb0 = colormodels.rgb_from_xyz (xyz0)
xyz1 = colormodels.xyz_from_rgb (rgb0)
rgb1 = colormodels.rgb_from_xyz (xyz1)
# check errors
err_rgb = rgb1 - rgb0
error_rgb = math.sqrt (numpy.dot (err_rgb, err_rgb))
err_xyz = xyz1 - xyz0
error_xyz = math.sqrt (numpy.dot (err_xyz, err_xyz))
passed = (error_rgb <= tolerance) and (error_xyz <= tolerance)
if passed:
status = 'pass'
else:
status = 'FAILED'
msg = 'test_xyz_rgb.test_A() : xyz0 = %s, rgb(xyz0) = %s, xyz(rgb(xyz0)) = %s, rgb(xyz(rgb(xyz0))) = %s, errors = (%g, %g), %s' % (
str (xyz0), str (rgb0), str (xyz1), str (rgb1), error_rgb, error_xyz, status)
if verbose >= 1:
print msg
if not passed:
pass
raise ValueError, msg
return passed
def test_A(xyz0, tolerance=1.0e-10, verbose=1):
rgb0 = colormodels.rgb_from_xyz(xyz0)
xyz1 = colormodels.xyz_from_rgb(rgb0)
rgb1 = colormodels.rgb_from_xyz(xyz1)
# check errors
err_rgb = rgb1 - rgb0
error_rgb = math.sqrt(numpy.dot(err_rgb, err_rgb))
err_xyz = xyz1 - xyz0
error_xyz = math.sqrt(numpy.dot(err_xyz, err_xyz))
passed = (error_rgb <= tolerance) and (error_xyz <= tolerance)
if passed:
status = 'pass'
else:
status = 'FAILED'
msg = 'test_xyz_rgb.test_A() : xyz0 = %s, rgb(xyz0) = %s, xyz(rgb(xyz0)) = %s, rgb(xyz(rgb(xyz0))) = %s, errors = (%g, %g), %s' % (
str(xyz0), str(rgb0), str(xyz1), str(rgb1), error_rgb, error_xyz,
status)
if verbose >= 1:
print(msg)
if not passed:
pass
raise ValueError(msg)
return passed
