# -*- coding: utf-8 -*- """ Utilities for generating static image and line plots of near-publishable quality Created on Thu May 05 13:29:12 2016 @author: Suhas Somnath, Chris R. Smith """ from __future__ import division, print_function, absolute_import, unicode_literals from numbers import Number import sys import matplotlib as mpl import numpy as np from dask import array as da from matplotlib import pyplot as plt from matplotlib.colors import LinearSegmentedColormap if sys.version_info.major == 3: unicode = str default_cmap = plt.cm.viridis def get_cmap_object(cmap): """ Get the matplotlib.colors.LinearSegmentedColormap object regardless of the input Parameters ---------- cmap : String, or matplotlib.colors.LinearSegmentedColormap object (Optional) Requested color map Returns ------- cmap : matplotlib.colors.LinearSegmentedColormap object Requested / Default colormap object """ if cmap is None: return default_cmap elif type(cmap) in [str, unicode]: return plt.get_cmap(cmap) elif not isinstance(cmap, mpl.colors.Colormap): raise TypeError('cmap should either be a matplotlib.colors.Colormap object or a string') return cmap def cmap_jet_white_center(): """ Generates the jet colormap with a white center Returns ------- white_jet : matplotlib.colors.LinearSegmentedColormap object color map object that can be used in place of the default colormap """ # For red - central column is like brightness # For blue - last column is like brightness cdict = {'red': ((0.00, 0.0, 0.0), (0.30, 0.0, 0.0), (0.50, 1.0, 1.0), (0.90, 1.0, 1.0), (1.00, 0.5, 1.0)), 'green': ((0.00, 0.0, 0.0), (0.10, 0.0, 0.0), (0.42, 1.0, 1.0), (0.58, 1.0, 1.0), (0.90, 0.0, 0.0), (1.00, 0.0, 0.0)), 'blue': ((0.00, 0.0, 0.5), (0.10, 1.0, 1.0), (0.50, 1.0, 1.0), (0.70, 0.0, 0.0), (1.00, 0.0, 0.0)) } return LinearSegmentedColormap('white_jet', cdict) def cmap_from_rgba(name, interp_vals, normalization_val): """ Generates a colormap given a matlab-style interpolation table Parameters ---------- name : String / Unicode Name of the desired colormap interp_vals : List of tuples Interpolation table that describes the desired color map. Each entry in the table should be described as: (position in the colorbar, (red, green, blue, alpha)) The position in the color bar, red, green, blue, and alpha vary from 0 to the normalization value normalization_val : number The common maximum value for the position in the color bar, red, green, blue, and alpha Returns ------- new_cmap : matplotlib.colors.LinearSegmentedColormap object desired color map """ if not isinstance(name, (str, unicode)): raise TypeError('name should be a string') if not isinstance(interp_vals, (list, tuple, np.array)): raise TypeError('interp_vals must be a list of tuples') if not isinstance(normalization_val, Number): raise TypeError('normalization_val must be a number') normalization_val = np.round(1.0 * normalization_val) cdict = {'red': tuple([(dist / normalization_val, colors[0] / normalization_val, colors[0] / normalization_val) for (dist, colors) in interp_vals][::-1]), 'green': tuple([(dist / normalization_val, colors[1] / normalization_val, colors[1] / normalization_val) for (dist, colors) in interp_vals][::-1]), 'blue': tuple([(dist / normalization_val, colors[2] / normalization_val, colors[2] / normalization_val) for (dist, colors) in interp_vals][::-1]), 'alpha': tuple([(dist / normalization_val, colors[3] / normalization_val, colors[3] / normalization_val) for (dist, colors) in interp_vals][::-1])} return LinearSegmentedColormap(name, cdict) def make_linear_alpha_cmap(name, solid_color, normalization_val, min_alpha=0, max_alpha=1): """ Generates a transparent to opaque color map based on a single solid color Parameters ---------- name : String / Unicode Name of the desired colormap solid_color : List of numbers red, green, blue, and alpha values for a specific color normalization_val : number The common maximum value for the red, green, blue, and alpha values. This is 1 in matplotlib min_alpha : float (optional. Default = 0 : ie- transparent) Lowest alpha value for the bottom of the color bar max_alpha : float (optional. Default = 1 : ie- opaque) Highest alpha value for the top of the color bar Returns ------- new_cmap : matplotlib.colors.LinearSegmentedColormap object transparent to opaque color map based on the provided color """ if not isinstance(name, (str, unicode)): raise TypeError('name should be a string') if not isinstance(solid_color, (list, tuple, np.ndarray, da.core.Array)): raise TypeError('solid_color must be a list of numbers') if not len(solid_color) == 4: raise ValueError('solid-color should have fourth values') if not np.all([isinstance(x, Number) for x in solid_color]): raise TypeError('solid_color should have three numbers for red, green, blue') if not isinstance(normalization_val, Number): raise TypeError('normalization_val must be a number') if not isinstance(min_alpha, Number): raise TypeError('min_alpha should be a Number') if not isinstance(max_alpha, Number): raise TypeError('max_alpha should be a Number') if min_alpha >= max_alpha: raise ValueError('min_alpha must be less than max_alpha') solid_color = np.array(solid_color) / normalization_val * 1.0 interp_table = [(1.0, (solid_color[0], solid_color[1], solid_color[2], max_alpha)), (0, (solid_color[0], solid_color[1], solid_color[2], min_alpha))] return cmap_from_rgba(name, interp_table, 1) def cmap_hot_desaturated(): """ Returns a desaturated color map based on the hot colormap Returns ------- new_cmap : matplotlib.colors.LinearSegmentedColormap object Desaturated version of the hot color map """ hot_desaturated = [(255.0, (255, 76, 76, 255)), (218.5, (107, 0, 0, 255)), (182.1, (255, 96, 0, 255)), (145.6, (255, 255, 0, 255)), (109.4, (0, 127, 0, 255)), (72.675, (0, 255, 255, 255)), (36.5, (0, 0, 91, 255)), (0, (71, 71, 219, 255))] return cmap_from_rgba('hot_desaturated', hot_desaturated, 255) def discrete_cmap(num_bins, cmap=None): """ Create an N-bin discrete colormap from the specified input map specified Parameters ---------- num_bins : unsigned int Number of discrete bins cmap : matplotlib.colors.Colormap object Base color map to discretize Returns ------- new_cmap : matplotlib.colors.LinearSegmentedColormap object Discretized color map Notes ----- Jake VanderPlas License: BSD-style https://gist.github.com/jakevdp/91077b0cae40f8f8244a """ if cmap is None: cmap = default_cmap.name elif isinstance(cmap, mpl.colors.Colormap): cmap = cmap.name elif not isinstance(cmap, (str, unicode)): raise TypeError('cmap should be a string or a matplotlib.colors.Colormap object') if not isinstance(num_bins, int): raise TypeError('num_bins must be an unsigned integer') return plt.get_cmap(cmap, num_bins)