def choose_light_palette_husl(h=(0, 359),
s=(0, 99),
l=(0, 99),
n=(3, 17)):
color = h, s, l
pal[:] = light_palette(color, n, input="husl")
palplot(pal)
if as_cmap:
colors = light_palette(color, 256, input="husl")
_update_lut(cmap, colors)
def choose_light_palette_hls(h=(0., 1.),
l=(0., 1.),
s=(0., 1.),
n=(3, 17)):
color = h, l, s
pal[:] = light_palette(color, n, input="hls")
palplot(pal)
if as_cmap:
colors = light_palette(color, 256, input="husl")
_update_lut(cmap, colors)
def choose_light_palette_rgb(r=(0., 1.),
g=(0., 1.),
b=(0., 1.),
n=(3, 17)):
color = r, g, b
pal[:] = light_palette(color, n, input="rgb")
palplot(pal)
if as_cmap:
colors = light_palette(color, 256, input="husl")
_update_lut(cmap, colors)
def choose_diverging(name=opts,
n=(2, 16),
desat=FloatSliderWidget(min=0, max=1, value=1),
variant=variants):
if variant == "reverse":
name += "_r"
pal[:] = color_palette(name, n, desat)
palplot(pal)
if as_cmap:
colors = color_palette(name, 256, desat)
_update_lut(cmap, np.c_[colors, np.ones(256)])
def choose_cubehelix(n_colors=IntSliderWidget(min=2, max=16, value=9),
start=FloatSliderWidget(min=0, max=3, value=0),
rot=FloatSliderWidget(min=-1, max=1, value=.4),
gamma=FloatSliderWidget(min=0, max=5, value=1),
hue=FloatSliderWidget(min=0, max=1, value=.8),
light=FloatSliderWidget(min=0, max=1, value=.85),
dark=FloatSliderWidget(min=0, max=1, value=.15),
reverse=False):
pal[:] = cubehelix_palette(n_colors, start, rot, gamma, hue, light,
dark, reverse)
palplot(pal)
if as_cmap:
colors = cubehelix_palette(256, start, rot, gamma, hue, light,
dark, reverse)
_update_lut(cmap, np.c_[colors, np.ones(256)])
def choose_diverging_palette(h_neg=IntSliderWidget(min=0,
max=359,
value=220),
h_pos=IntSliderWidget(min=0,
max=359,
value=10),
s=IntSliderWidget(min=0, max=99, value=74),
l=IntSliderWidget(min=0, max=99, value=50),
sep=IntSliderWidget(min=1, max=50, value=10),
n=(2, 16),
center=["light", "dark"]):
pal[:] = diverging_palette(h_neg, h_pos, s, l, sep, n, center)
palplot(pal)
if as_cmap:
colors = diverging_palette(h_neg, h_pos, s, l, sep, 256, center)
_update_lut(cmap, colors)
def test_palplot_size(self):
"""
The plot that is made must have the right dimensions.
"""
pal4 = color_palette("husl", 4)
misc.palplot(pal4)
size4 = plt.gcf().get_size_inches()
self.assertEqual(tuple(size4), (4, 1))
pal5 = color_palette("husl", 5)
misc.palplot(pal5)
size5 = plt.gcf().get_size_inches()
self.assertEqual(tuple(size5), (5, 1))
palbig = color_palette("husl", 3)
misc.palplot(palbig, 2)
sizebig = plt.gcf().get_size_inches()
self.assertEqual(tuple(sizebig), (6, 2))
plt.close("all")
def choose_qualitative(name=opts,
n=(2, 16),
desat=FloatSliderWidget(min=0, max=1, value=1)):
pal[:] = color_palette(name, n, desat)
palplot(pal)