from __future__ import absolute_import, division, print_function # Declare Python2/3 unicode-safe string type try: basestring except NameError: basestring = str # Lookup of web color names to their hex codes. color_lookup = {'aliceblue': '#F0F8FF', 'antiquewhite': '#FAEBD7', 'aqua': '#00FFFF', 'aquamarine': '#7FFFD4', 'azure': '#F0FFFF', 'beige': '#F5F5DC', 'bisque': '#FFE4C4', 'black': '#000000', 'blanchedalmond': '#FFEBCD', 'blue': '#0000FF', 'blueviolet': '#8A2BE2', 'brown': '#A52A2A', 'burlywood': '#DEB887', 'cadetblue': '#5F9EA0', 'chartreuse': '#7FFF00', 'chocolate': '#D2691E', 'coral': '#FF7F50', 'cornflowerblue': '#6495ED', 'cornsilk': '#FFF8DC', 'crimson': '#DC143C', 'cyan': '#00FFFF', 'darkblue': '#00008B', 'darkcyan': '#008B8B', 'darkgoldenrod': '#B8860B', 'darkgray': '#A9A9A9', 'darkgreen': '#006400', 'darkgrey': '#A9A9A9', 'darkkhaki': '#BDB76B', 'darkmagenta': '#8B008B', 'darkolivegreen': '#556B2F', 'darkorange': '#FF8C00', 'darkorchid': '#9932CC', 'darkred': '#8B0000', 'darksage': '#598556', 'darksalmon': '#E9967A', 'darkseagreen': '#8FBC8F', 'darkslateblue': '#483D8B', 'darkslategray': '#2F4F4F', 'darkslategrey': '#2F4F4F', 'darkturquoise': '#00CED1', 'darkviolet': '#9400D3', 'deeppink': '#FF1493', 'deepskyblue': '#00BFFF', 'dimgray': '#696969', 'dimgrey': '#696969', 'dodgerblue': '#1E90FF', 'firebrick': '#B22222', 'floralwhite': '#FFFAF0', 'forestgreen': '#228B22', 'fuchsia': '#FF00FF', 'gainsboro': '#DCDCDC', 'ghostwhite': '#F8F8FF', 'gold': '#FFD700', 'goldenrod': '#DAA520', 'gray': '#808080', 'green': '#008000', 'greenyellow': '#ADFF2F', 'grey': '#808080', 'honeydew': '#F0FFF0', 'hotpink': '#FF69B4', 'indianred': '#CD5C5C', 'indigo': '#4B0082', 'ivory': '#FFFFF0', 'khaki': '#F0E68C', 'lavender': '#E6E6FA', 'lavenderblush': '#FFF0F5', 'lawngreen': '#7CFC00', 'lemonchiffon': '#FFFACD', 'lightblue': '#ADD8E6', 'lightcoral': '#F08080', 'lightcyan': '#E0FFFF', 'lightgoldenrodyellow': '#FAFAD2', 'lightgray': '#D3D3D3', 'lightgreen': '#90EE90', 'lightgrey': '#D3D3D3', 'lightpink': '#FFB6C1', 'lightsage': '#BCECAC', 'lightsalmon': '#FFA07A', 'lightseagreen': '#20B2AA', 'lightskyblue': '#87CEFA', 'lightslategray': '#778899', 'lightslategrey': '#778899', 'lightsteelblue': '#B0C4DE', 'lightyellow': '#FFFFE0', 'lime': '#00FF00', 'limegreen': '#32CD32', 'linen': '#FAF0E6', 'magenta': '#FF00FF', 'maroon': '#800000', 'mediumaquamarine': '#66CDAA', 'mediumblue': '#0000CD', 'mediumorchid': '#BA55D3', 'mediumpurple': '#9370DB', 'mediumseagreen': '#3CB371', 'mediumslateblue': '#7B68EE', 'mediumspringgreen': '#00FA9A', 'mediumturquoise': '#48D1CC', 'mediumvioletred': '#C71585', 'midnightblue': '#191970', 'mintcream': '#F5FFFA', 'mistyrose': '#FFE4E1', 'moccasin': '#FFE4B5', 'navajowhite': '#FFDEAD', 'navy': '#000080', 'oldlace': '#FDF5E6', 'olive': '#808000', 'olivedrab': '#6B8E23', 'orange': '#FFA500', 'orangered': '#FF4500', 'orchid': '#DA70D6', 'palegoldenrod': '#EEE8AA', 'palegreen': '#98FB98', 'paleturquoise': '#AFEEEE', 'palevioletred': '#DB7093', 'papayawhip': '#FFEFD5', 'peachpuff': '#FFDAB9', 'peru': '#CD853F', 'pink': '#FFC0CB', 'plum': '#DDA0DD', 'powderblue': '#B0E0E6', 'purple': '#800080', 'red': '#FF0000', 'rosybrown': '#BC8F8F', 'royalblue': '#4169E1', 'saddlebrown': '#8B4513', 'sage': '#87AE73', 'salmon': '#FA8072', 'sandybrown': '#FAA460', 'seagreen': '#2E8B57', 'seashell': '#FFF5EE', 'sienna': '#A0522D', 'silver': '#C0C0C0', 'skyblue': '#87CEEB', 'slateblue': '#6A5ACD', 'slategray': '#708090', 'slategrey': '#708090', 'snow': '#FFFAFA', 'springgreen': '#00FF7F', 'steelblue': '#4682B4', 'tan': '#D2B48C', 'teal': '#008080', 'thistle': '#D8BFD8', 'tomato': '#FF6347', 'turquoise': '#40E0D0', 'violet': '#EE82EE', 'wheat': '#F5DEB3', 'white': '#FFFFFF', 'whitesmoke': '#F5F5F5', 'yellow': '#FFFF00', 'yellowgreen': '#9ACD32'} def hex_to_rgb(x): """Convert a color hexcode to an rgb tuple. Example ------- >>> rgb('#FFFFFF') (255, 255, 255) """ if not (x.startswith('#') and len(x) == 7): raise ValueError("Invalid hex color") x = x.strip('#') try: return (int(x[:2], 16), int(x[2:4], 16), int(x[4:], 16)) except ValueError: raise ValueError("Invalid hex color") def rgb(x): """Return a triple representing rgb color. Can convert colors by name or hexcode. Passing in a valid rgb tuple is idempotent. Example ------- >>> rgb('plum') (221, 160, 221) >>> rgb('#FFFFFF') (255, 255, 255) >>> rgb((255, 255, 255)) (255, 255, 255) """ if isinstance(x, basestring): if x.startswith('#'): return hex_to_rgb(x) elif x in color_lookup: return hex_to_rgb(color_lookup[x]) else: raise ValueError("Unknown color: '{0}'".format(x)) elif isinstance(x, tuple) and len(x) == 3: if min(x) < 0 or max(x) > 255: raise ValueError("Invalid RGB tuple") else: raise TypeError("Don't know how to convert {0} to RGB".format(x)) return x # Example palettes # Copied from from bokeh.palettes.Greys9 Greys9 = ["#000000", "#252525", "#525252", "#737373", "#969696", "#bdbdbd", "#d9d9d9", "#f0f0f0", "#ffffff"] # Adapted from matplotlib.cm.hot to be more uniform at the high end Hot = ["black", "maroon", "darkred", "red", "orangered", "darkorange", "orange", "gold", "yellow", "white"] # pseudo terrestial elevation ramp Elevation = ["aqua", "sandybrown", "limegreen", "green", "green", "darkgreen", "saddlebrown", "gray", "white"] # Qualitative color maps, for use in colorizing categories # Originally from Cynthia Brewer (http://colorbrewer2.org), via Bokeh Set1 = ['#e41a1c', '#377eb8', '#4daf4a', '#984ea3', '#ff7f00', '#ffff33', '#a65628', '#f781bf', '#999999'] Set2 = ['#66c2a5', '#fc8d62', '#8da0cb', '#e78ac3', '#a6d854', '#ffd92f', '#e5c494', '#b3b3b3'] Set3 = ['#8dd3c7', '#ffffb3', '#bebada', '#fb8072', '#80b1d3', '#fdb462', '#b3de69', '#fccde5', '#d9d9d9', '#bc80bd', '#ccebc5', '#ffed6f'] # Sets 1, 2, and 3 combined, minus indistinguishable colors Sets1to3 = Set1+Set2[0:3]+Set2[4:7]+Set3[1:2]+Set3[3:4]+Set3[5:6]+Set3[7:9]+Set3[10:] def _mpl_cmdata_to_bokeh_palette(cm_data): """Given the data from a Matplotlib colormap as a list of three-item lists in the range 0,1.0, convert colors into the range 0,256 and return as a list of tuples""" return [(int(r*256),int(g*256),int(b*256)) for r,g,b in cm_data] # Copied from matplotlib/_cm_listed.py _inferno_data = [[0.001462, 0.000466, 0.013866], [0.002267, 0.001270, 0.018570], [0.003299, 0.002249, 0.024239], [0.004547, 0.003392, 0.030909], [0.006006, 0.004692, 0.038558], [0.007676, 0.006136, 0.046836], [0.009561, 0.007713, 0.055143], [0.011663, 0.009417, 0.063460], [0.013995, 0.011225, 0.071862], [0.016561, 0.013136, 0.080282], [0.019373, 0.015133, 0.088767], [0.022447, 0.017199, 0.097327], [0.025793, 0.019331, 0.105930], [0.029432, 0.021503, 0.114621], [0.033385, 0.023702, 0.123397], [0.037668, 0.025921, 0.132232], [0.042253, 0.028139, 0.141141], [0.046915, 0.030324, 0.150164], [0.051644, 0.032474, 0.159254], [0.056449, 0.034569, 0.168414], [0.061340, 0.036590, 0.177642], [0.066331, 0.038504, 0.186962], [0.071429, 0.040294, 0.196354], [0.076637, 0.041905, 0.205799], [0.081962, 0.043328, 0.215289], [0.087411, 0.044556, 0.224813], [0.092990, 0.045583, 0.234358], [0.098702, 0.046402, 0.243904], [0.104551, 0.047008, 0.253430], [0.110536, 0.047399, 0.262912], [0.116656, 0.047574, 0.272321], [0.122908, 0.047536, 0.281624], [0.129285, 0.047293, 0.290788], [0.135778, 0.046856, 0.299776], [0.142378, 0.046242, 0.308553], [0.149073, 0.045468, 0.317085], [0.155850, 0.044559, 0.325338], [0.162689, 0.043554, 0.333277], [0.169575, 0.042489, 0.340874], [0.176493, 0.041402, 0.348111], [0.183429, 0.040329, 0.354971], [0.190367, 0.039309, 0.361447], [0.197297, 0.038400, 0.367535], [0.204209, 0.037632, 0.373238], [0.211095, 0.037030, 0.378563], [0.217949, 0.036615, 0.383522], [0.224763, 0.036405, 0.388129], [0.231538, 0.036405, 0.392400], [0.238273, 0.036621, 0.396353], [0.244967, 0.037055, 0.400007], [0.251620, 0.037705, 0.403378], [0.258234, 0.038571, 0.406485], [0.264810, 0.039647, 0.409345], [0.271347, 0.040922, 0.411976], [0.277850, 0.042353, 0.414392], [0.284321, 0.043933, 0.416608], [0.290763, 0.045644, 0.418637], [0.297178, 0.047470, 0.420491], [0.303568, 0.049396, 0.422182], [0.309935, 0.051407, 0.423721], [0.316282, 0.053490, 0.425116], [0.322610, 0.055634, 0.426377], [0.328921, 0.057827, 0.427511], [0.335217, 0.060060, 0.428524], [0.341500, 0.062325, 0.429425], [0.347771, 0.064616, 0.430217], [0.354032, 0.066925, 0.430906], [0.360284, 0.069247, 0.431497], [0.366529, 0.071579, 0.431994], [0.372768, 0.073915, 0.432400], [0.379001, 0.076253, 0.432719], [0.385228, 0.078591, 0.432955], [0.391453, 0.080927, 0.433109], [0.397674, 0.083257, 0.433183], [0.403894, 0.085580, 0.433179], [0.410113, 0.087896, 0.433098], [0.416331, 0.090203, 0.432943], [0.422549, 0.092501, 0.432714], [0.428768, 0.094790, 0.432412], [0.434987, 0.097069, 0.432039], [0.441207, 0.099338, 0.431594], [0.447428, 0.101597, 0.431080], [0.453651, 0.103848, 0.430498], [0.459875, 0.106089, 0.429846], [0.466100, 0.108322, 0.429125], [0.472328, 0.110547, 0.428334], [0.478558, 0.112764, 0.427475], [0.484789, 0.114974, 0.426548], [0.491022, 0.117179, 0.425552], [0.497257, 0.119379, 0.424488], [0.503493, 0.121575, 0.423356], [0.509730, 0.123769, 0.422156], [0.515967, 0.125960, 0.420887], [0.522206, 0.128150, 0.419549], [0.528444, 0.130341, 0.418142], [0.534683, 0.132534, 0.416667], [0.540920, 0.134729, 0.415123], [0.547157, 0.136929, 0.413511], [0.553392, 0.139134, 0.411829], [0.559624, 0.141346, 0.410078], [0.565854, 0.143567, 0.408258], [0.572081, 0.145797, 0.406369], [0.578304, 0.148039, 0.404411], [0.584521, 0.150294, 0.402385], [0.590734, 0.152563, 0.400290], [0.596940, 0.154848, 0.398125], [0.603139, 0.157151, 0.395891], [0.609330, 0.159474, 0.393589], [0.615513, 0.161817, 0.391219], [0.621685, 0.164184, 0.388781], [0.627847, 0.166575, 0.386276], [0.633998, 0.168992, 0.383704], [0.640135, 0.171438, 0.381065], [0.646260, 0.173914, 0.378359], [0.652369, 0.176421, 0.375586], [0.658463, 0.178962, 0.372748], [0.664540, 0.181539, 0.369846], [0.670599, 0.184153, 0.366879], [0.676638, 0.186807, 0.363849], [0.682656, 0.189501, 0.360757], [0.688653, 0.192239, 0.357603], [0.694627, 0.195021, 0.354388], [0.700576, 0.197851, 0.351113], [0.706500, 0.200728, 0.347777], [0.712396, 0.203656, 0.344383], [0.718264, 0.206636, 0.340931], [0.724103, 0.209670, 0.337424], [0.729909, 0.212759, 0.333861], [0.735683, 0.215906, 0.330245], [0.741423, 0.219112, 0.326576], [0.747127, 0.222378, 0.322856], [0.752794, 0.225706, 0.319085], [0.758422, 0.229097, 0.315266], [0.764010, 0.232554, 0.311399], [0.769556, 0.236077, 0.307485], [0.775059, 0.239667, 0.303526], [0.780517, 0.243327, 0.299523], [0.785929, 0.247056, 0.295477], [0.791293, 0.250856, 0.291390], [0.796607, 0.254728, 0.287264], [0.801871, 0.258674, 0.283099], [0.807082, 0.262692, 0.278898], [0.812239, 0.266786, 0.274661], [0.817341, 0.270954, 0.270390], [0.822386, 0.275197, 0.266085], [0.827372, 0.279517, 0.261750], [0.832299, 0.283913, 0.257383], [0.837165, 0.288385, 0.252988], [0.841969, 0.292933, 0.248564], [0.846709, 0.297559, 0.244113], [0.851384, 0.302260, 0.239636], [0.855992, 0.307038, 0.235133], [0.860533, 0.311892, 0.230606], [0.865006, 0.316822, 0.226055], [0.869409, 0.321827, 0.221482], [0.873741, 0.326906, 0.216886], [0.878001, 0.332060, 0.212268], [0.882188, 0.337287, 0.207628], [0.886302, 0.342586, 0.202968], [0.890341, 0.347957, 0.198286], [0.894305, 0.353399, 0.193584], [0.898192, 0.358911, 0.188860], [0.902003, 0.364492, 0.184116], [0.905735, 0.370140, 0.179350], [0.909390, 0.375856, 0.174563], [0.912966, 0.381636, 0.169755], [0.916462, 0.387481, 0.164924], [0.919879, 0.393389, 0.160070], [0.923215, 0.399359, 0.155193], [0.926470, 0.405389, 0.150292], [0.929644, 0.411479, 0.145367], [0.932737, 0.417627, 0.140417], [0.935747, 0.423831, 0.135440], [0.938675, 0.430091, 0.130438], [0.941521, 0.436405, 0.125409], [0.944285, 0.442772, 0.120354], [0.946965, 0.449191, 0.115272], [0.949562, 0.455660, 0.110164], [0.952075, 0.462178, 0.105031], [0.954506, 0.468744, 0.099874], [0.956852, 0.475356, 0.094695], [0.959114, 0.482014, 0.089499], [0.961293, 0.488716, 0.084289], [0.963387, 0.495462, 0.079073], [0.965397, 0.502249, 0.073859], [0.967322, 0.509078, 0.068659], [0.969163, 0.515946, 0.063488], [0.970919, 0.522853, 0.058367], [0.972590, 0.529798, 0.053324], [0.974176, 0.536780, 0.048392], [0.975677, 0.543798, 0.043618], [0.977092, 0.550850, 0.039050], [0.978422, 0.557937, 0.034931], [0.979666, 0.565057, 0.031409], [0.980824, 0.572209, 0.028508], [0.981895, 0.579392, 0.026250], [0.982881, 0.586606, 0.024661], [0.983779, 0.593849, 0.023770], [0.984591, 0.601122, 0.023606], [0.985315, 0.608422, 0.024202], [0.985952, 0.615750, 0.025592], [0.986502, 0.623105, 0.027814], [0.986964, 0.630485, 0.030908], [0.987337, 0.637890, 0.034916], [0.987622, 0.645320, 0.039886], [0.987819, 0.652773, 0.045581], [0.987926, 0.660250, 0.051750], [0.987945, 0.667748, 0.058329], [0.987874, 0.675267, 0.065257], [0.987714, 0.682807, 0.072489], [0.987464, 0.690366, 0.079990], [0.987124, 0.697944, 0.087731], [0.986694, 0.705540, 0.095694], [0.986175, 0.713153, 0.103863], [0.985566, 0.720782, 0.112229], [0.984865, 0.728427, 0.120785], [0.984075, 0.736087, 0.129527], [0.983196, 0.743758, 0.138453], [0.982228, 0.751442, 0.147565], [0.981173, 0.759135, 0.156863], [0.980032, 0.766837, 0.166353], [0.978806, 0.774545, 0.176037], [0.977497, 0.782258, 0.185923], [0.976108, 0.789974, 0.196018], [0.974638, 0.797692, 0.206332], [0.973088, 0.805409, 0.216877], [0.971468, 0.813122, 0.227658], [0.969783, 0.820825, 0.238686], [0.968041, 0.828515, 0.249972], [0.966243, 0.836191, 0.261534], [0.964394, 0.843848, 0.273391], [0.962517, 0.851476, 0.285546], [0.960626, 0.859069, 0.298010], [0.958720, 0.866624, 0.310820], [0.956834, 0.874129, 0.323974], [0.954997, 0.881569, 0.337475], [0.953215, 0.888942, 0.351369], [0.951546, 0.896226, 0.365627], [0.950018, 0.903409, 0.380271], [0.948683, 0.910473, 0.395289], [0.947594, 0.917399, 0.410665], [0.946809, 0.924168, 0.426373], [0.946392, 0.930761, 0.442367], [0.946403, 0.937159, 0.458592], [0.946903, 0.943348, 0.474970], [0.947937, 0.949318, 0.491426], [0.949545, 0.955063, 0.507860], [0.951740, 0.960587, 0.524203], [0.954529, 0.965896, 0.540361], [0.957896, 0.971003, 0.556275], [0.961812, 0.975924, 0.571925], [0.966249, 0.980678, 0.587206], [0.971162, 0.985282, 0.602154], [0.976511, 0.989753, 0.616760], [0.982257, 0.994109, 0.631017], [0.988362, 0.998364, 0.644924]] inferno = _mpl_cmdata_to_bokeh_palette(_inferno_data) # Copied from matplotlib/_cm_listed.py _viridis_data = [[0.267004, 0.004874, 0.329415], [0.268510, 0.009605, 0.335427], [0.269944, 0.014625, 0.341379], [0.271305, 0.019942, 0.347269], [0.272594, 0.025563, 0.353093], [0.273809, 0.031497, 0.358853], [0.274952, 0.037752, 0.364543], [0.276022, 0.044167, 0.370164], [0.277018, 0.050344, 0.375715], [0.277941, 0.056324, 0.381191], [0.278791, 0.062145, 0.386592], [0.279566, 0.067836, 0.391917], [0.280267, 0.073417, 0.397163], [0.280894, 0.078907, 0.402329], [0.281446, 0.084320, 0.407414], [0.281924, 0.089666, 0.412415], [0.282327, 0.094955, 0.417331], [0.282656, 0.100196, 0.422160], [0.282910, 0.105393, 0.426902], [0.283091, 0.110553, 0.431554], [0.283197, 0.115680, 0.436115], [0.283229, 0.120777, 0.440584], [0.283187, 0.125848, 0.444960], [0.283072, 0.130895, 0.449241], [0.282884, 0.135920, 0.453427], [0.282623, 0.140926, 0.457517], [0.282290, 0.145912, 0.461510], [0.281887, 0.150881, 0.465405], [0.281412, 0.155834, 0.469201], [0.280868, 0.160771, 0.472899], [0.280255, 0.165693, 0.476498], [0.279574, 0.170599, 0.479997], [0.278826, 0.175490, 0.483397], [0.278012, 0.180367, 0.486697], [0.277134, 0.185228, 0.489898], [0.276194, 0.190074, 0.493001], [0.275191, 0.194905, 0.496005], [0.274128, 0.199721, 0.498911], [0.273006, 0.204520, 0.501721], [0.271828, 0.209303, 0.504434], [0.270595, 0.214069, 0.507052], [0.269308, 0.218818, 0.509577], [0.267968, 0.223549, 0.512008], [0.266580, 0.228262, 0.514349], [0.265145, 0.232956, 0.516599], [0.263663, 0.237631, 0.518762], [0.262138, 0.242286, 0.520837], [0.260571, 0.246922, 0.522828], [0.258965, 0.251537, 0.524736], [0.257322, 0.256130, 0.526563], [0.255645, 0.260703, 0.528312], [0.253935, 0.265254, 0.529983], [0.252194, 0.269783, 0.531579], [0.250425, 0.274290, 0.533103], [0.248629, 0.278775, 0.534556], [0.246811, 0.283237, 0.535941], [0.244972, 0.287675, 0.537260], [0.243113, 0.292092, 0.538516], [0.241237, 0.296485, 0.539709], [0.239346, 0.300855, 0.540844], [0.237441, 0.305202, 0.541921], [0.235526, 0.309527, 0.542944], [0.233603, 0.313828, 0.543914], [0.231674, 0.318106, 0.544834], [0.229739, 0.322361, 0.545706], [0.227802, 0.326594, 0.546532], [0.225863, 0.330805, 0.547314], [0.223925, 0.334994, 0.548053], [0.221989, 0.339161, 0.548752], [0.220057, 0.343307, 0.549413], [0.218130, 0.347432, 0.550038], [0.216210, 0.351535, 0.550627], [0.214298, 0.355619, 0.551184], [0.212395, 0.359683, 0.551710], [0.210503, 0.363727, 0.552206], [0.208623, 0.367752, 0.552675], [0.206756, 0.371758, 0.553117], [0.204903, 0.375746, 0.553533], [0.203063, 0.379716, 0.553925], [0.201239, 0.383670, 0.554294], [0.199430, 0.387607, 0.554642], [0.197636, 0.391528, 0.554969], [0.195860, 0.395433, 0.555276], [0.194100, 0.399323, 0.555565], [0.192357, 0.403199, 0.555836], [0.190631, 0.407061, 0.556089], [0.188923, 0.410910, 0.556326], [0.187231, 0.414746, 0.556547], [0.185556, 0.418570, 0.556753], [0.183898, 0.422383, 0.556944], [0.182256, 0.426184, 0.557120], [0.180629, 0.429975, 0.557282], [0.179019, 0.433756, 0.557430], [0.177423, 0.437527, 0.557565], [0.175841, 0.441290, 0.557685], [0.174274, 0.445044, 0.557792], [0.172719, 0.448791, 0.557885], [0.171176, 0.452530, 0.557965], [0.169646, 0.456262, 0.558030], [0.168126, 0.459988, 0.558082], [0.166617, 0.463708, 0.558119], [0.165117, 0.467423, 0.558141], [0.163625, 0.471133, 0.558148], [0.162142, 0.474838, 0.558140], [0.160665, 0.478540, 0.558115], [0.159194, 0.482237, 0.558073], [0.157729, 0.485932, 0.558013], [0.156270, 0.489624, 0.557936], [0.154815, 0.493313, 0.557840], [0.153364, 0.497000, 0.557724], [0.151918, 0.500685, 0.557587], [0.150476, 0.504369, 0.557430], [0.149039, 0.508051, 0.557250], [0.147607, 0.511733, 0.557049], [0.146180, 0.515413, 0.556823], [0.144759, 0.519093, 0.556572], [0.143343, 0.522773, 0.556295], [0.141935, 0.526453, 0.555991], [0.140536, 0.530132, 0.555659], [0.139147, 0.533812, 0.555298], [0.137770, 0.537492, 0.554906], [0.136408, 0.541173, 0.554483], [0.135066, 0.544853, 0.554029], [0.133743, 0.548535, 0.553541], [0.132444, 0.552216, 0.553018], [0.131172, 0.555899, 0.552459], [0.129933, 0.559582, 0.551864], [0.128729, 0.563265, 0.551229], [0.127568, 0.566949, 0.550556], [0.126453, 0.570633, 0.549841], [0.125394, 0.574318, 0.549086], [0.124395, 0.578002, 0.548287], [0.123463, 0.581687, 0.547445], [0.122606, 0.585371, 0.546557], [0.121831, 0.589055, 0.545623], [0.121148, 0.592739, 0.544641], [0.120565, 0.596422, 0.543611], [0.120092, 0.600104, 0.542530], [0.119738, 0.603785, 0.541400], [0.119512, 0.607464, 0.540218], [0.119423, 0.611141, 0.538982], [0.119483, 0.614817, 0.537692], [0.119699, 0.618490, 0.536347], [0.120081, 0.622161, 0.534946], [0.120638, 0.625828, 0.533488], [0.121380, 0.629492, 0.531973], [0.122312, 0.633153, 0.530398], [0.123444, 0.636809, 0.528763], [0.124780, 0.640461, 0.527068], [0.126326, 0.644107, 0.525311], [0.128087, 0.647749, 0.523491], [0.130067, 0.651384, 0.521608], [0.132268, 0.655014, 0.519661], [0.134692, 0.658636, 0.517649], [0.137339, 0.662252, 0.515571], [0.140210, 0.665859, 0.513427], [0.143303, 0.669459, 0.511215], [0.146616, 0.673050, 0.508936], [0.150148, 0.676631, 0.506589], [0.153894, 0.680203, 0.504172], [0.157851, 0.683765, 0.501686], [0.162016, 0.687316, 0.499129], [0.166383, 0.690856, 0.496502], [0.170948, 0.694384, 0.493803], [0.175707, 0.697900, 0.491033], [0.180653, 0.701402, 0.488189], [0.185783, 0.704891, 0.485273], [0.191090, 0.708366, 0.482284], [0.196571, 0.711827, 0.479221], [0.202219, 0.715272, 0.476084], [0.208030, 0.718701, 0.472873], [0.214000, 0.722114, 0.469588], [0.220124, 0.725509, 0.466226], [0.226397, 0.728888, 0.462789], [0.232815, 0.732247, 0.459277], [0.239374, 0.735588, 0.455688], [0.246070, 0.738910, 0.452024], [0.252899, 0.742211, 0.448284], [0.259857, 0.745492, 0.444467], [0.266941, 0.748751, 0.440573], [0.274149, 0.751988, 0.436601], [0.281477, 0.755203, 0.432552], [0.288921, 0.758394, 0.428426], [0.296479, 0.761561, 0.424223], [0.304148, 0.764704, 0.419943], [0.311925, 0.767822, 0.415586], [0.319809, 0.770914, 0.411152], [0.327796, 0.773980, 0.406640], [0.335885, 0.777018, 0.402049], [0.344074, 0.780029, 0.397381], [0.352360, 0.783011, 0.392636], [0.360741, 0.785964, 0.387814], [0.369214, 0.788888, 0.382914], [0.377779, 0.791781, 0.377939], [0.386433, 0.794644, 0.372886], [0.395174, 0.797475, 0.367757], [0.404001, 0.800275, 0.362552], [0.412913, 0.803041, 0.357269], [0.421908, 0.805774, 0.351910], [0.430983, 0.808473, 0.346476], [0.440137, 0.811138, 0.340967], [0.449368, 0.813768, 0.335384], [0.458674, 0.816363, 0.329727], [0.468053, 0.818921, 0.323998], [0.477504, 0.821444, 0.318195], [0.487026, 0.823929, 0.312321], [0.496615, 0.826376, 0.306377], [0.506271, 0.828786, 0.300362], [0.515992, 0.831158, 0.294279], [0.525776, 0.833491, 0.288127], [0.535621, 0.835785, 0.281908], [0.545524, 0.838039, 0.275626], [0.555484, 0.840254, 0.269281], [0.565498, 0.842430, 0.262877], [0.575563, 0.844566, 0.256415], [0.585678, 0.846661, 0.249897], [0.595839, 0.848717, 0.243329], [0.606045, 0.850733, 0.236712], [0.616293, 0.852709, 0.230052], [0.626579, 0.854645, 0.223353], [0.636902, 0.856542, 0.216620], [0.647257, 0.858400, 0.209861], [0.657642, 0.860219, 0.203082], [0.668054, 0.861999, 0.196293], [0.678489, 0.863742, 0.189503], [0.688944, 0.865448, 0.182725], [0.699415, 0.867117, 0.175971], [0.709898, 0.868751, 0.169257], [0.720391, 0.870350, 0.162603], [0.730889, 0.871916, 0.156029], [0.741388, 0.873449, 0.149561], [0.751884, 0.874951, 0.143228], [0.762373, 0.876424, 0.137064], [0.772852, 0.877868, 0.131109], [0.783315, 0.879285, 0.125405], [0.793760, 0.880678, 0.120005], [0.804182, 0.882046, 0.114965], [0.814576, 0.883393, 0.110347], [0.824940, 0.884720, 0.106217], [0.835270, 0.886029, 0.102646], [0.845561, 0.887322, 0.099702], [0.855810, 0.888601, 0.097452], [0.866013, 0.889868, 0.095953], [0.876168, 0.891125, 0.095250], [0.886271, 0.892374, 0.095374], [0.896320, 0.893616, 0.096335], [0.906311, 0.894855, 0.098125], [0.916242, 0.896091, 0.100717], [0.926106, 0.897330, 0.104071], [0.935904, 0.898570, 0.108131], [0.945636, 0.899815, 0.112838], [0.955300, 0.901065, 0.118128], [0.964894, 0.902323, 0.123941], [0.974417, 0.903590, 0.130215], [0.983868, 0.904867, 0.136897], [0.993248, 0.906157, 0.143936]] viridis = _mpl_cmdata_to_bokeh_palette(_viridis_data) def colormap_select(base_colormap, start=0, end=1.0, reverse=False): """ Given a colormap in the form of a list, such as a Bokeh palette, return a version of the colormap reversed if requested, and selecting a subset (on a scale 0,1.0) of the elements in the colormap list. For instance: >>> cmap = ["#000000", "#969696", "#d9d9d9", "#ffffff"] >>> colormap_select(cmap,reverse=True) ['#ffffff', '#d9d9d9', '#969696', '#000000'] >>> colormap_select(cmap,0.3,reverse=True) ['#d9d9d9', '#969696', '#000000'] """ full = list(reversed(base_colormap) if reverse else base_colormap) num = len(full) return full[int(start*num):int(end*num)]