import numpy as np import matplotlib.pyplot as plt from matplotlib.colors import LinearSegmentedColormap # Lots of different places that widgets could come from... try: from ipywidgets import interact, FloatSlider, IntSlider except ImportError: import warnings # ignore ShimWarning raised by IPython, see GH #892 with warnings.catch_warnings(): warnings.simplefilter("ignore") try: from IPython.html.widgets import interact, FloatSlider, IntSlider except ImportError: try: from IPython.html.widgets import (interact, FloatSliderWidget, IntSliderWidget) FloatSlider = FloatSliderWidget IntSlider = IntSliderWidget except ImportError: pass from .miscplot import palplot from .palettes import (color_palette, dark_palette, light_palette, diverging_palette, cubehelix_palette) __all__ = ["choose_colorbrewer_palette", "choose_cubehelix_palette", "choose_dark_palette", "choose_light_palette", "choose_diverging_palette"] def _init_mutable_colormap(): """Create a matplotlib colormap that will be updated by the widgets.""" greys = color_palette("Greys", 256) cmap = LinearSegmentedColormap.from_list("interactive", greys) cmap._init() cmap._set_extremes() return cmap def _update_lut(cmap, colors): """Change the LUT values in a matplotlib colormap in-place.""" cmap._lut[:256] = colors cmap._set_extremes() def _show_cmap(cmap): """Show a continuous matplotlib colormap.""" from .rcmod import axes_style # Avoid circular import with axes_style("white"): f, ax = plt.subplots(figsize=(8.25, .75)) ax.set(xticks=[], yticks=[]) x = np.linspace(0, 1, 256)[np.newaxis, :] ax.pcolormesh(x, cmap=cmap) def choose_colorbrewer_palette(data_type, as_cmap=False): """Select a palette from the ColorBrewer set. These palettes are built into matplotlib and can be used by name in many seaborn functions, or by passing the object returned by this function. Parameters ---------- data_type : {'sequential', 'diverging', 'qualitative'} This describes the kind of data you want to visualize. See the seaborn color palette docs for more information about how to choose this value. Note that you can pass substrings (e.g. 'q' for 'qualitative. as_cmap : bool If True, the return value is a matplotlib colormap rather than a list of discrete colors. Returns ------- pal or cmap : list of colors or matplotlib colormap Object that can be passed to plotting functions. See Also -------- dark_palette : Create a sequential palette with dark low values. light_palette : Create a sequential palette with bright low values. diverging_palette : Create a diverging palette from selected colors. cubehelix_palette : Create a sequential palette or colormap using the cubehelix system. """ if data_type.startswith("q") and as_cmap: raise ValueError("Qualitative palettes cannot be colormaps.") pal = [] if as_cmap: cmap = _init_mutable_colormap() if data_type.startswith("s"): opts = ["Greys", "Reds", "Greens", "Blues", "Oranges", "Purples", "BuGn", "BuPu", "GnBu", "OrRd", "PuBu", "PuRd", "RdPu", "YlGn", "PuBuGn", "YlGnBu", "YlOrBr", "YlOrRd"] variants = ["regular", "reverse", "dark"] @interact def choose_sequential(name=opts, n=(2, 18), desat=FloatSlider(min=0, max=1, value=1), variant=variants): if variant == "reverse": name += "_r" elif variant == "dark": name += "_d" if as_cmap: colors = color_palette(name, 256, desat) _update_lut(cmap, np.c_[colors, np.ones(256)]) _show_cmap(cmap) else: pal[:] = color_palette(name, n, desat) palplot(pal) elif data_type.startswith("d"): opts = ["RdBu", "RdGy", "PRGn", "PiYG", "BrBG", "RdYlBu", "RdYlGn", "Spectral"] variants = ["regular", "reverse"] @interact def choose_diverging(name=opts, n=(2, 16), desat=FloatSlider(min=0, max=1, value=1), variant=variants): if variant == "reverse": name += "_r" if as_cmap: colors = color_palette(name, 256, desat) _update_lut(cmap, np.c_[colors, np.ones(256)]) _show_cmap(cmap) else: pal[:] = color_palette(name, n, desat) palplot(pal) elif data_type.startswith("q"): opts = ["Set1", "Set2", "Set3", "Paired", "Accent", "Pastel1", "Pastel2", "Dark2"] @interact def choose_qualitative(name=opts, n=(2, 16), desat=FloatSlider(min=0, max=1, value=1)): pal[:] = color_palette(name, n, desat) palplot(pal) if as_cmap: return cmap return pal def choose_dark_palette(input="husl", as_cmap=False): """Launch an interactive widget to create a dark sequential palette. This corresponds with the :func:`dark_palette` function. This kind of palette is good for data that range between relatively uninteresting low values and interesting high values. Requires IPython 2+ and must be used in the notebook. Parameters ---------- input : {'husl', 'hls', 'rgb'} Color space for defining the seed value. Note that the default is different than the default input for :func:`dark_palette`. as_cmap : bool If True, the return value is a matplotlib colormap rather than a list of discrete colors. Returns ------- pal or cmap : list of colors or matplotlib colormap Object that can be passed to plotting functions. See Also -------- dark_palette : Create a sequential palette with dark low values. light_palette : Create a sequential palette with bright low values. cubehelix_palette : Create a sequential palette or colormap using the cubehelix system. """ pal = [] if as_cmap: cmap = _init_mutable_colormap() if input == "rgb": @interact def choose_dark_palette_rgb(r=(0., 1.), g=(0., 1.), b=(0., 1.), n=(3, 17)): color = r, g, b if as_cmap: colors = dark_palette(color, 256, input="rgb") _update_lut(cmap, colors) _show_cmap(cmap) else: pal[:] = dark_palette(color, n, input="rgb") palplot(pal) elif input == "hls": @interact def choose_dark_palette_hls(h=(0., 1.), l=(0., 1.), # noqa: E741 s=(0., 1.), n=(3, 17)): color = h, l, s if as_cmap: colors = dark_palette(color, 256, input="hls") _update_lut(cmap, colors) _show_cmap(cmap) else: pal[:] = dark_palette(color, n, input="hls") palplot(pal) elif input == "husl": @interact def choose_dark_palette_husl(h=(0, 359), s=(0, 99), l=(0, 99), # noqa: E741 n=(3, 17)): color = h, s, l if as_cmap: colors = dark_palette(color, 256, input="husl") _update_lut(cmap, colors) _show_cmap(cmap) else: pal[:] = dark_palette(color, n, input="husl") palplot(pal) if as_cmap: return cmap return pal def choose_light_palette(input="husl", as_cmap=False): """Launch an interactive widget to create a light sequential palette. This corresponds with the :func:`light_palette` function. This kind of palette is good for data that range between relatively uninteresting low values and interesting high values. Requires IPython 2+ and must be used in the notebook. Parameters ---------- input : {'husl', 'hls', 'rgb'} Color space for defining the seed value. Note that the default is different than the default input for :func:`light_palette`. as_cmap : bool If True, the return value is a matplotlib colormap rather than a list of discrete colors. Returns ------- pal or cmap : list of colors or matplotlib colormap Object that can be passed to plotting functions. See Also -------- light_palette : Create a sequential palette with bright low values. dark_palette : Create a sequential palette with dark low values. cubehelix_palette : Create a sequential palette or colormap using the cubehelix system. """ pal = [] if as_cmap: cmap = _init_mutable_colormap() if input == "rgb": @interact def choose_light_palette_rgb(r=(0., 1.), g=(0., 1.), b=(0., 1.), n=(3, 17)): color = r, g, b if as_cmap: colors = light_palette(color, 256, input="rgb") _update_lut(cmap, colors) _show_cmap(cmap) else: pal[:] = light_palette(color, n, input="rgb") palplot(pal) elif input == "hls": @interact def choose_light_palette_hls(h=(0., 1.), l=(0., 1.), # noqa: E741 s=(0., 1.), n=(3, 17)): color = h, l, s if as_cmap: colors = light_palette(color, 256, input="hls") _update_lut(cmap, colors) _show_cmap(cmap) else: pal[:] = light_palette(color, n, input="hls") palplot(pal) elif input == "husl": @interact def choose_light_palette_husl(h=(0, 359), s=(0, 99), l=(0, 99), # noqa: E741 n=(3, 17)): color = h, s, l if as_cmap: colors = light_palette(color, 256, input="husl") _update_lut(cmap, colors) _show_cmap(cmap) else: pal[:] = light_palette(color, n, input="husl") palplot(pal) if as_cmap: return cmap return pal def choose_diverging_palette(as_cmap=False): """Launch an interactive widget to choose a diverging color palette. This corresponds with the :func:`diverging_palette` function. This kind of palette is good for data that range between interesting low values and interesting high values with a meaningful midpoint. (For example, change scores relative to some baseline value). Requires IPython 2+ and must be used in the notebook. Parameters ---------- as_cmap : bool If True, the return value is a matplotlib colormap rather than a list of discrete colors. Returns ------- pal or cmap : list of colors or matplotlib colormap Object that can be passed to plotting functions. See Also -------- diverging_palette : Create a diverging color palette or colormap. choose_colorbrewer_palette : Interactively choose palettes from the colorbrewer set, including diverging palettes. """ pal = [] if as_cmap: cmap = _init_mutable_colormap() @interact def choose_diverging_palette( h_neg=IntSlider(min=0, max=359, value=220), h_pos=IntSlider(min=0, max=359, value=10), s=IntSlider(min=0, max=99, value=74), l=IntSlider(min=0, max=99, value=50), # noqa: E741 sep=IntSlider(min=1, max=50, value=10), n=(2, 16), center=["light", "dark"] ): if as_cmap: colors = diverging_palette(h_neg, h_pos, s, l, sep, 256, center) _update_lut(cmap, colors) _show_cmap(cmap) else: pal[:] = diverging_palette(h_neg, h_pos, s, l, sep, n, center) palplot(pal) if as_cmap: return cmap return pal def choose_cubehelix_palette(as_cmap=False): """Launch an interactive widget to create a sequential cubehelix palette. This corresponds with the :func:`cubehelix_palette` function. This kind of palette is good for data that range between relatively uninteresting low values and interesting high values. The cubehelix system allows the palette to have more hue variance across the range, which can be helpful for distinguishing a wider range of values. Requires IPython 2+ and must be used in the notebook. Parameters ---------- as_cmap : bool If True, the return value is a matplotlib colormap rather than a list of discrete colors. Returns ------- pal or cmap : list of colors or matplotlib colormap Object that can be passed to plotting functions. See Also -------- cubehelix_palette : Create a sequential palette or colormap using the cubehelix system. """ pal = [] if as_cmap: cmap = _init_mutable_colormap() @interact def choose_cubehelix(n_colors=IntSlider(min=2, max=16, value=9), start=FloatSlider(min=0, max=3, value=0), rot=FloatSlider(min=-1, max=1, value=.4), gamma=FloatSlider(min=0, max=5, value=1), hue=FloatSlider(min=0, max=1, value=.8), light=FloatSlider(min=0, max=1, value=.85), dark=FloatSlider(min=0, max=1, value=.15), reverse=False): if as_cmap: colors = cubehelix_palette(256, start, rot, gamma, hue, light, dark, reverse) _update_lut(cmap, np.c_[colors, np.ones(256)]) _show_cmap(cmap) else: pal[:] = cubehelix_palette(n_colors, start, rot, gamma, hue, light, dark, reverse) palplot(pal) if as_cmap: return cmap return pal