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)