def calc_xy_from_white_to_primary_n_step(name=cs.BT709, step=5, color='green'):
"""
Examples
--------
>>> calc_xy_from_white_to_primary_n_step(name=cs.BT709,
step=5, color='green')
[[0.31269999999999998, 0.329000000000000],
[0.30952499999999999, 0.396750000000000],
[0.30635000000000001, 0.464499999999999],
[0.30317499999999997, 0.532250000000000],
[0.29999999999999999, 0.600000000000000]]
"""
pos1_temp = D65_WHITE
if color == 'red':
pos2_temp = tpg.get_primaries(name)[0][0]
elif color == 'green':
pos2_temp = tpg.get_primaries(name)[0][1]
else:
pos2_temp = tpg.get_primaries(name)[0][2]
if pos1_temp[1] < pos2_temp[1]:
pos1 = pos1_temp
pos2 = pos2_temp
else:
pos1 = pos2_temp
pos2 = pos1_temp
x, y = def_line(pos1, pos2)
z = np.linspace(pos1[0], pos2[0], step)
val = [[w, y.subs({x: w}).evalf()] for w in z]
return np.array(val)
def _get_primary_secondary_large_y(name):
"""
Primary, Secondary の Y値を求める。
色度パターン作成時に、パッチごとにYの値が変わらないように
後で xy --> xyY 変換時に使用する。
Parameters
----------
name : string
target color space name.
Returns
-------
array_like
large Y value for primary and secondary.
"""
# RGBMYC の Y値リストを得る
_, primary = tpg.get_primaries(name)
_, secondary = tpg.get_secondaries(name)
data = np.vstack((primary, secondary))
rgb_to_xyz_mtx = colour.RGB_COLOURSPACES[name].RGB_to_XYZ_matrix
data = tpg.do_matrix(img=data, mtx=rgb_to_xyz_mtx)
return data[..., 1]
def get_intersection_primary(out_side_name, in_side_name):
"""
BT.2020 の Primary と D65 を結ぶ直線と
BT.709 の Gamut が交差する点を求める
"""
bt2020_p, _ = tpg.get_primaries(name=out_side_name)
primary, _ = tpg.get_primaries(name=in_side_name)
white_point = sympy.Point(tpg.D65_WHITE[0], tpg.D65_WHITE[1])
bt2020_p_points = [
sympy.Point(bt2020_p[x][0], bt2020_p[x][1]) for x in range(3)
]
primary_points = [
sympy.Point(primary[x][0], primary[x][1]) for x in range(4)
]
bt2020_p_lines = [
sympy.Line(bt2020_p_points[x], white_point) for x in range(3)
]
# よく考えたら、どの線と交差するかは gamut の形で決まるんだった…マニュアルで。
# ----------------------------------------------------------------------
primary_lines = [
sympy.Line(primary_points[2], primary_points[3]),
sympy.Line(primary_points[1], primary_points[2]),
sympy.Line(primary_points[1], primary_points[2])
]
# 交点求める。evalf() して式の評価も済ませておく
# -------------------------------------------
intersections = [
sympy.intersection(bt2020_p_lines[x], primary_lines[x])[0].evalf()
for x in range(3)
]
# 後で扱いやすいように xy の配列に変換しておく
# -----------------------------------------
intersections = [[intersections[x].x, intersections[x].y]
for x in range(3)]
return np.array(intersections)
def plot_chromaticity_diagram(gamut, data, title=None):
xyY = ryr.rgb_to_xyY(data, gamut)
gamut_xy, _ = tpg.get_primaries(gamut)
cmf_xy = tpg._get_cmfs_xy()
rate = 1.0
ax1 = pu.plot_1_graph(fontsize=20 * rate,
figsize=(8 * rate, 9 * rate),
graph_title=title,
graph_title_size=16,
xlabel=None,
ylabel=None,
axis_label_size=None,
legend_size=18 * rate,
xlim=(0, 0.8),
ylim=(0, 0.9),
xtick=[x * 0.1 for x in range(9)],
ytick=[x * 0.1 for x in range(10)],
xtick_size=17 * rate,
ytick_size=17 * rate,
linewidth=4 * rate,
minor_xtick_num=2,
minor_ytick_num=2)
color = data.reshape((data.shape[0] * data.shape[1], data.shape[2]))
ax1.plot(cmf_xy[..., 0], cmf_xy[..., 1], '-k', lw=3.5 * rate, label=None)
ax1.plot((cmf_xy[-1, 0], cmf_xy[0, 0]), (cmf_xy[-1, 1], cmf_xy[0, 1]),
'-k',
lw=2.5 * rate,
label=None)
ax1.patch.set_facecolor("#F2F2F2")
ax1.plot(gamut_xy[..., 0],
gamut_xy[..., 1],
c=K_BAR_COLOR,
label="BT.709",
lw=3 * rate)
ax1.scatter(xyY[..., 0],
xyY[..., 1],
s=2 * rate,
marker='o',
c=color,
edgecolors=None,
linewidth=1 * rate,
zorder=100)
ax1.scatter(np.array([0.3127]),
np.array([0.3290]),
s=150 * rate,
marker='x',
c="#000000",
edgecolors=None,
linewidth=2.5 * rate,
zorder=101,
label="D65")
plt.legend(loc='upper right')
file_name = './figures/xy_chromaticity_{}.png'.format(title)
plt.savefig(file_name, bbox_inches='tight')
def plot_ap0_ap1():
ap0, _ = tpg.get_primaries(cs.ACES_AP0)
ap1, _ = tpg.get_primaries(cs.ACES_AP1)
ax1 = pu.plot_1_graph(fontsize=20,
figsize=(9, 11),
graph_title="CIE1931 Chromaticity Diagram",
graph_title_size=None,
xlabel=None, ylabel=None,
axis_label_size=None,
legend_size=18,
xlim=(-0.1, 0.8),
ylim=(-0.1, 1.1),
xtick=[x * 0.1 - 0.1 for x in range(10)],
ytick=[x * 0.1 - 0.1 for x in range(12)],
xtick_size=17,
ytick_size=17,
linewidth=2,
minor_xtick_num=2,
minor_ytick_num=2)
ax1.plot(ap0[..., 0], ap0[..., 1], label="AP0")
ax1.plot(ap1[..., 0], ap1[..., 1], label="AP1")
plt.legend(loc='upper right')
plt.show()
def get_intersection_secondary(out_side_name, in_side_name):
"""
BT.2020 の Secondary と D65 を結ぶ直線と
BT.709 の Gamut が交差する点を求める
"""
secondary, _ = tpg.get_secondaries(name=out_side_name)
primary, _ = tpg.get_primaries(name=in_side_name)
white_point = sympy.Point(tpg.D65_WHITE[0], tpg.D65_WHITE[1])
secondary_points = [
sympy.Point(secondary[x][0], secondary[x][1]) for x in range(3)
]
primary_points = [
sympy.Point(primary[x][0], primary[x][1]) for x in range(4)
]
secondary_lines = [
sympy.Line(secondary_points[x], white_point) for x in range(3)
]
primary_lines = [
sympy.Line(primary_points[(x + 2) % 3], primary_points[(x + 3) % 3])
for x in range(3)
]
# 交点求める。evalf() して式の評価も済ませておく
# -------------------------------------------
intersections = [
sympy.intersection(secondary_lines[x], primary_lines[x])[0].evalf()
for x in range(3)
]
# 後で扱いやすいように xy の配列に変換しておく
# -----------------------------------------
intersections = [[intersections[x].x, intersections[x].y]
for x in range(3)]
return np.array(intersections)
def _get_test_scatter_data(sample_num=6):
color_space_name = TARGET_COLORSPACE
inter_section_space_name = COMPARATIVE_COLORSPACE
primaries, primary_rgb = tpg.get_primaries(color_space_name)
secondaries, secondary_rgb = tpg.get_secondaries(color_space_name)
primary_intersections\
= get_intersection_primary(out_side_name=color_space_name,
in_side_name=inter_section_space_name)
secondary_intersections\
= get_intersection_secondary(out_side_name=color_space_name,
in_side_name=inter_section_space_name)
ed_xy = np.vstack((primaries[:3, :], secondaries))
st_xy = np.vstack((primary_intersections, secondary_intersections))
patch_xy = [
_get_interpolated_xy(st_xy[idx], ed_xy[idx], sample_num)
for idx in range(st_xy.shape[0])
]
patch_xy = np.array(patch_xy)
specific = _get_primary_secondary_large_y(name=color_space_name)
specific = specific[:, np.newaxis]
specific = np.tile(specific, sample_num)
rgb = tpg.xy_to_rgb(patch_xy,
color_space_name,
normalize='specific',
specific=specific)
# rgb = tpg.xy_to_rgb(patch_xy, color_space_name,
# normalize='maximum', specific=specific)
rgb = rgb**(1 / 2.2)
rgb = rgb.reshape((rgb.shape[0] * rgb.shape[1], rgb.shape[2]))
# return xy, rgb.reshape((rgb.shape[0] * rgb.shape[1], 3))
return patch_xy, rgb
def plot_chromaticity_diagram(
rate=480/755.0*2, xmin=0.0, xmax=0.8, ymin=0.0, ymax=0.9, **kwargs):
"""
>>> xy = calc_xy_from_white_to_primary_n_step(name=name, step=step,
>>> color=primary_color)
>>> linear_rgb = get_normalize_rgb_value_from_small_xy(xy, cs.ACES_AP1)
>>> rgb = tf.oetf(linear_rgb, oetf_name)
>>> plot_chromaticity_diagram(rate=480/755.0*2,
>>> xmin=-0.1, xmax=0.8, ymin=-0.1, ymax=1.05,
>>> test_scatter=(xy, rgb),
>>> white_point=D65_WHITE)
"""
# キーワード引数の初期値設定
# ------------------------------------
test_scatter = kwargs.get('test_scatter', None)
white_point = kwargs.get('white_point', None)
# プロット用データ準備
# ---------------------------------
xy_image = tpg.get_chromaticity_image(
xmin=xmin, xmax=xmax, ymin=ymin, ymax=ymax)
cmf_xy = tpg._get_cmfs_xy()
bt709_gamut, _ = tpg.get_primaries(name=cs.BT709)
bt2020_gamut, _ = tpg.get_primaries(name=cs.BT2020)
dci_p3_gamut, _ = tpg.get_primaries(name=cs.P3_D65)
ap0_gamut, _ = tpg.get_primaries(name=cs.ACES_AP0)
ap1_gamut, _ = tpg.get_primaries(name=cs.ACES_AP1)
xlim = (min(0, xmin), max(0.8, xmax))
ylim = (min(0, ymin), max(0.9, ymax))
ax1 = pu.plot_1_graph(fontsize=20 * rate,
figsize=((xmax - xmin) * 10 * rate,
(ymax - ymin) * 10 * rate),
graph_title="CIE1931 Chromaticity Diagram",
graph_title_size=None,
xlabel=None, ylabel=None,
axis_label_size=None,
legend_size=18 * rate,
xlim=xlim, ylim=ylim,
xtick=[x * 0.1 + xmin for x in
range(int((xlim[1] - xlim[0])/0.1) + 1)],
ytick=[x * 0.1 + ymin for x in
range(int((ylim[1] - ylim[0])/0.1) + 1)],
xtick_size=17 * rate,
ytick_size=17 * rate,
linewidth=4 * rate,
minor_xtick_num=2,
minor_ytick_num=2)
ax1.plot(cmf_xy[..., 0], cmf_xy[..., 1], '-k', lw=3.5*rate, label=None)
ax1.plot((cmf_xy[-1, 0], cmf_xy[0, 0]), (cmf_xy[-1, 1], cmf_xy[0, 1]),
'-k', lw=3.5*rate, label=None)
ax1.plot(bt709_gamut[:, 0], bt709_gamut[:, 1],
c=tpg.UNIVERSAL_COLOR_LIST[0], label="BT.709", lw=2.75*rate)
ax1.plot(bt2020_gamut[:, 0], bt2020_gamut[:, 1],
c=tpg.UNIVERSAL_COLOR_LIST[1], label="BT.2020", lw=2.75*rate)
ax1.plot(dci_p3_gamut[:, 0], dci_p3_gamut[:, 1],
c=tpg.UNIVERSAL_COLOR_LIST[2], label="DCI-P3", lw=2.75*rate)
ax1.plot(ap1_gamut[:, 0], ap1_gamut[:, 1],
c=tpg.UNIVERSAL_COLOR_LIST[3], label="ACES AP1", lw=2.75*rate)
ax1.plot(ap0_gamut[:, 0], ap0_gamut[:, 1],
c=tpg.UNIVERSAL_COLOR_LIST[4], label="ACES AP0", lw=2.75*rate)
if test_scatter is not None:
xy, rgb = test_scatter
ax1.scatter(xy[..., 0], xy[..., 1], s=300*rate, marker='s', c=rgb,
edgecolors='#404040', linewidth=2*rate)
if white_point is not None:
ax1.plot(white_point[0], white_point[1], 'kx', label="D65",
markersize=10*rate, markeredgewidth=2.0*rate)
for idx in range(test_scatter[0].shape[0]):
text = "No.{}".format(idx)
xy = (test_scatter[0][idx][0]+0.01, test_scatter[0][idx][1])
xy_text = (xy[0] + 0.35, xy[1] + 0.1)
ax1.annotate(text, xy=xy, xycoords='data',
xytext=xy_text, textcoords='data',
ha='left', va='bottom',
arrowprops=dict(facecolor='#333333', shrink=0.0))
ax1.imshow(xy_image, extent=(xmin, xmax, ymin, ymax))
plt.legend(loc='upper right')
plt.savefig('temp_fig.png', bbox_inches='tight')
plt.show()