#=============================================================================== # Copyright (c) 2015, Max Zwiessele # All rights reserved. # # Redistribution and use in source and binary forms, with or without # modification, are permitted provided that the following conditions are met: # # * Redistributions of source code must retain the above copyright notice, this # list of conditions and the following disclaimer. # # * Redistributions in binary form must reproduce the above copyright notice, # this list of conditions and the following disclaimer in the documentation # and/or other materials provided with the distribution. # # * Neither the name of GPy.plotting.matplot_dep.plot_definitions nor the names of its # contributors may be used to endorse or promote products derived from # this software without specific prior written permission. # # THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" # AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE # IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE # DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE # FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL # DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR # SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER # CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, # OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE # OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. #=============================================================================== import numpy as np from matplotlib import pyplot as plt from ..abstract_plotting_library import AbstractPlottingLibrary from .. import Tango from . import defaults from matplotlib.colors import LinearSegmentedColormap from .controllers import ImshowController class MatplotlibPlots(AbstractPlottingLibrary): def __init__(self): super(MatplotlibPlots, self).__init__() self._defaults = defaults.__dict__ def get_new_canvas(self, xlabel=None, ylabel=None, zlabel=None, title=None, projection='2d', **kwargs): if projection == '3d': from mpl_toolkits.mplot3d import Axes3D elif projection == '2d': projection = None if 'ax' in kwargs: ax = kwargs.pop('ax') elif 'num' in kwargs and 'figsize' in kwargs: ax = plt.figure(num=kwargs.pop('num'), figsize=kwargs.pop('figsize')).add_subplot(111, projection=projection) elif 'num' in kwargs: ax = plt.figure(num=kwargs.pop('num')).add_subplot(111, projection=projection) elif 'figsize' in kwargs: ax = plt.figure(figsize=kwargs.pop('figsize')).add_subplot(111, projection=projection) else: ax = plt.figure().add_subplot(111, projection=projection) if xlabel is not None: ax.set_xlabel(xlabel) if ylabel is not None: ax.set_ylabel(ylabel) if zlabel is not None: ax.set_zlabel(zlabel) if title is not None: ax.set_title(title) return ax, kwargs def show_canvas(self, ax, plots, xlim=None, ylim=None, zlim=None, legend=False, **kwargs): try: ax.autoscale_view() ax.set_xlim(xlim) ax.set_ylim(ylim) if legend: ax.legend() if zlim is not None: ax.set_zlim(zlim) ax.figure.canvas.draw() except: pass return plots def scatter(self, ax, X, Y, Z=None, color=Tango.colorsHex['mediumBlue'], label=None, marker='o', **kwargs): if Z is not None: return ax.scatter(X, Y, c=color, zs=Z, label=label, marker=marker, **kwargs) return ax.scatter(X, Y, c=color, label=label, marker=marker, **kwargs) def plot(self, ax, X, Y, color=None, label=None, **kwargs): return ax.plot(X, Y, color=color, label=label, **kwargs) def plot_axis_lines(self, ax, X, color=Tango.colorsHex['mediumBlue'], label=None, **kwargs): from matplotlib import transforms from matplotlib.path import Path if 'marker' not in kwargs: kwargs['marker'] = Path([[-.2,0.], [-.2,.5], [0.,1.], [.2,.5], [.2,0.], [-.2,0.]], [Path.MOVETO, Path.LINETO, Path.LINETO, Path.LINETO, Path.LINETO, Path.CLOSEPOLY]) if 'transform' not in kwargs: if X.shape[1] == 1: kwargs['transform'] = transforms.blended_transform_factory(ax.transData, ax.transAxes) if X.shape[1] == 2: return ax.scatter(X[:,0], X[:,1], ax.get_zlim()[0], c=color, label=label, **kwargs) return ax.scatter(X, np.zeros_like(X), c=color, label=label, **kwargs) def barplot(self, ax, x, height, width=0.8, bottom=0, color=Tango.colorsHex['mediumBlue'], label=None, **kwargs): if 'align' not in kwargs: kwargs['align'] = 'center' return ax.bar(left=x, height=height, width=width, bottom=bottom, label=label, color=color, **kwargs) def xerrorbar(self, ax, X, Y, error, Z=None, color=Tango.colorsHex['mediumBlue'], label=None, **kwargs): if not('linestyle' in kwargs or 'ls' in kwargs): kwargs['ls'] = 'none' if Z is not None: return ax.errorbar(X, Y, Z, xerr=error, ecolor=color, label=label, **kwargs) return ax.errorbar(X, Y, xerr=error, ecolor=color, label=label, **kwargs) def yerrorbar(self, ax, X, Y, error, Z=None, color=Tango.colorsHex['mediumBlue'], label=None, **kwargs): if not('linestyle' in kwargs or 'ls' in kwargs): kwargs['ls'] = 'none' if Z is not None: return ax.errorbar(X, Y, Z, yerr=error, ecolor=color, label=label, **kwargs) return ax.errorbar(X, Y, yerr=error, ecolor=color, label=label, **kwargs) def imshow(self, ax, X, extent=None, label=None, plot_function=None, resolution=None, vmin=None, vmax=None, **kwargs): if plot_function is not None: self.controller = ImshowController(ax, plot_function, extent, resolution=resolution, vmin=vmin, vmax=vmax, **kwargs) return self.controller return ax.imshow(X, label=label, extent=extent, vmin=vmin, vmax=vmax, **kwargs) def contour(self, ax, X, Y, C, levels=20, label=None, **kwargs): return ax.contour(X, Y, C, levels=np.linspace(C.min(), C.max(), levels), label=label, **kwargs) def surface(self, ax, X, Y, Z, color=None, label=None, **kwargs): return ax.plot_surface(X, Y, Z, label=label, **kwargs) def fill_between(self, ax, X, lower, upper, color=Tango.colorsHex['mediumBlue'], label=None, **kwargs): return ax.fill_between(X, lower, upper, facecolor=color, label=label, **kwargs) def fill_gradient(self, canvas, X, percentiles, color=Tango.colorsHex['mediumBlue'], label=None, **kwargs): ax = canvas plots = [] if 'edgecolors' not in kwargs: kwargs['edgecolors'] = 'none' if 'facecolors' in kwargs: color = kwargs.pop('facecolors') if 'array' in kwargs: array = kwargs.pop('array') else: array = 1.-np.abs(np.linspace(-.97, .97, len(percentiles)-1)) if 'alpha' in kwargs: alpha = kwargs.pop('alpha') else: alpha = .8 if 'cmap' in kwargs: cmap = kwargs.pop('cmap') else: cmap = LinearSegmentedColormap.from_list('WhToColor', (color, color), N=array.size) cmap._init() cmap._lut[:-3, -1] = alpha*array kwargs['facecolors'] = [cmap(i) for i in np.linspace(0,1,cmap.N)] # pop where from kwargs where = kwargs.pop('where') if 'where' in kwargs else None # pop interpolate, which we actually do not do here! if 'interpolate' in kwargs: kwargs.pop('interpolate') def pairwise(iterable): "s -> (s0,s1), (s1,s2), (s2, s3), ..." from itertools import tee #try: # from itertools import izip as zip #except ImportError: # pass a, b = tee(iterable) next(b, None) return zip(a, b) polycol = [] for y1, y2 in pairwise(percentiles): import matplotlib.mlab as mlab # Handle united data, such as dates ax._process_unit_info(xdata=X, ydata=y1) ax._process_unit_info(ydata=y2) # Convert the arrays so we can work with them from numpy import ma x = ma.masked_invalid(ax.convert_xunits(X)) y1 = ma.masked_invalid(ax.convert_yunits(y1)) y2 = ma.masked_invalid(ax.convert_yunits(y2)) if y1.ndim == 0: y1 = np.ones_like(x) * y1 if y2.ndim == 0: y2 = np.ones_like(x) * y2 if where is None: where = np.ones(len(x), np.bool) else: where = np.asarray(where, np.bool) if not (x.shape == y1.shape == y2.shape == where.shape): raise ValueError("Argument dimensions are incompatible") from functools import reduce mask = reduce(ma.mask_or, [ma.getmask(a) for a in (x, y1, y2)]) if mask is not ma.nomask: where &= ~mask polys = [] for ind0, ind1 in mlab.contiguous_regions(where): xslice = x[ind0:ind1] y1slice = y1[ind0:ind1] y2slice = y2[ind0:ind1] if not len(xslice): continue N = len(xslice) p = np.zeros((2 * N + 2, 2), np.float) # the purpose of the next two lines is for when y2 is a # scalar like 0 and we want the fill to go all the way # down to 0 even if none of the y1 sample points do start = xslice[0], y2slice[0] end = xslice[-1], y2slice[-1] p[0] = start p[N + 1] = end p[1:N + 1, 0] = xslice p[1:N + 1, 1] = y1slice p[N + 2:, 0] = xslice[::-1] p[N + 2:, 1] = y2slice[::-1] polys.append(p) polycol.extend(polys) from matplotlib.collections import PolyCollection if 'zorder' not in kwargs: kwargs['zorder'] = 0 plots.append(PolyCollection(polycol, **kwargs)) ax.add_collection(plots[-1], autolim=True) ax.autoscale_view() return plots