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[plotting] library is unfolding and should be working tonight
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mzwiessele
parent
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commit
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13 changed files with 648 additions and 263 deletions
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@ -1,54 +1,6 @@
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# Copyright (c) 2014, GPy authors (see AUTHORS.txt).
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# Licensed under the BSD 3-clause license (see LICENSE.txt)
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from matplotlib import pyplot as plt
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from . import defaults
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def get_new_canvas(kwargs):
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"""
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Return a canvas, kwargupdate for matplotlib. This just a
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dictionary for the collection and we add the an axis to kwarg.
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This method does two things, it creates an empty canvas
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and updates the kwargs (deletes the unnecessary kwargs)
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for further usage in normal plotting.
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in matplotlib this means it deletes references to ax, as
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plotting is done on the axis itself and is not a kwarg.
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"""
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if 'ax' in kwargs:
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ax = kwargs.pop('ax')
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elif 'num' in kwargs and 'figsize' in kwargs:
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ax = plt.figure(num=kwargs.pop('num'), figsize=kwargs.pop('figsize')).add_subplot(111)
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elif 'num' in kwargs:
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ax = plt.figure(num=kwargs.pop('num')).add_subplot(111)
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elif 'figsize' in kwargs:
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ax = plt.figure(figsize=kwargs.pop('figsize')).add_subplot(111)
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else:
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ax = plt.figure().add_subplot(111)
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# Add ax to kwargs to add all subsequent plots to this axis:
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#kwargs['ax'] = ax
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return ax, kwargs
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def show_canvas(canvas):
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try:
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canvas.figure.canvas.draw()
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canvas.figure.tight_layout()
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except:
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pass
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return canvas
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def scatter(ax, *args, **kwargs):
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ax.scatter(*args, **kwargs)
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def plot(ax, *args, **kwargs):
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ax.plot(*args, **kwargs)
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def imshow(ax, *args, **kwargs):
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ax.imshow(*args, **kwargs)
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from . import base_plots
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from . import models_plots
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from . import priors_plots
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@ -39,12 +39,15 @@ it gives back an empty default, when defaults are not defined.
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'''
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from matplotlib import cm
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from . import Tango
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# Data:
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data_1d = dict(lw=1.5, marker='x', edgecolor='k')
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data_2d = dict(s=35, edgecolors='none', linewidth=0., cmap=cm.get_cmap('hot'))
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xerrorbar = dict(ecolor='k', fmt='none', elinewidth=.5, alpha=.5)
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yerrorbar = dict(ecolor='darkred', fmt='none', elinewidth=.5, alpha=.5)
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yerrorbar = dict(ecolor=Tango.colorsHex['darkBlue'], fmt='none', elinewidth=.5, alpha=.5)
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# GP plots
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meanplot = dict(color='#3300FF', linewidth=2)
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meanplot_1d = dict(color=Tango.colorsHex['mediumBlue'], linewidth=2)
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meanplot_2d = dict(cmap='hot', linewidth=.5)
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confidence_interval = dict(linecolor=Tango.colorsHex['darkBlue'],fillcolor=Tango.colorsHex['lightBlue'])
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@ -259,12 +259,12 @@ def plot_fit(self, plot_limits=None, which_data_rows='all',
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#define the frame for plotting on
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resolution = resolution or 50
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Xnew, _, _, xmin, xmax = x_frame2D(X[:,free_dims], plot_limits, resolution)
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Xnew, x, y, xmin, xmax = x_frame2D(X[:,free_dims], plot_limits, resolution)
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Xgrid = np.empty((Xnew.shape[0],self.input_dim))
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Xgrid[:,free_dims] = Xnew
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for i,v in fixed_inputs:
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Xgrid[:,i] = v
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x, y = np.linspace(xmin[0], xmax[0], resolution), np.linspace(xmin[1], xmax[1], resolution)
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#x, y = np.linspace(xmin[0], xmax[0], resolution), np.linspace(xmin[1], xmax[1], resolution)
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#predict on the frame and plot
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if plot_raw:
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166
GPy/plotting/matplot_dep/plot_definitions.py
Normal file
166
GPy/plotting/matplot_dep/plot_definitions.py
Normal file
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@ -0,0 +1,166 @@
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#===============================================================================
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# Copyright (c) 2015, Max Zwiessele
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# All rights reserved.
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#
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# Redistribution and use in source and binary forms, with or without
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# modification, are permitted provided that the following conditions are met:
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#
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# * Redistributions of source code must retain the above copyright notice, this
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# list of conditions and the following disclaimer.
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#
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# * Redistributions in binary form must reproduce the above copyright notice,
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# this list of conditions and the following disclaimer in the documentation
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# and/or other materials provided with the distribution.
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#
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# * Neither the name of GPy.plotting.matplot_dep.plot_definitions nor the names of its
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# contributors may be used to endorse or promote products derived from
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# this software without specific prior written permission.
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#
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# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
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# AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
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# IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
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# DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE
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# FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL
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# DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR
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# SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER
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# CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY,
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# OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
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# OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
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#===============================================================================
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import numpy as np
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from matplotlib import pyplot as plt
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from ..abstract_plotting_library import AbstractPlottingLibrary
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from . import defaults
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class MatplotlibPlots(AbstractPlottingLibrary):
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def __init__(self):
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super(MatplotlibPlots, self).__init__()
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self._defaults = defaults.__dict__
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def get_new_canvas(self, kwargs):
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if 'ax' in kwargs:
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ax = kwargs.pop('ax')
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elif 'num' in kwargs and 'figsize' in kwargs:
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ax = plt.figure(num=kwargs.pop('num'), figsize=kwargs.pop('figsize')).add_subplot(111)
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elif 'num' in kwargs:
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ax = plt.figure(num=kwargs.pop('num')).add_subplot(111)
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elif 'figsize' in kwargs:
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ax = plt.figure(figsize=kwargs.pop('figsize')).add_subplot(111)
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else:
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ax = plt.figure().add_subplot(111)
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# Add ax to kwargs to add all subsequent plots to this axis:
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#kwargs['ax'] = ax
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return ax, kwargs
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def show_canvas(self, ax, plots):
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try:
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ax.autoscale_view()
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ax.figure.canvas.draw()
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ax.figure.tight_layout()
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except:
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pass
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return ax
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def scatter(self, ax, X, Y, **kwargs):
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return ax.scatter(X, Y, **kwargs)
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def plot(self, ax, X, Y, **kwargs):
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return ax.plot(X, Y, **kwargs)
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def xerrorbar(self, ax, X, Y, error, **kwargs):
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if not('linestyle' in kwargs or 'ls' in kwargs):
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kwargs['ls'] = 'none'
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return ax.errorbar(X, Y, xerr=error, **kwargs)
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def yerrorbar(self, ax, X, Y, error, **kwargs):
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if not('linestyle' in kwargs or 'ls' in kwargs):
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kwargs['ls'] = 'none'
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return ax.errorbar(X, Y, yerr=error, **kwargs)
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def imshow(self, ax, X, **kwargs):
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return ax.imshow(**kwargs)
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def contour(self, ax, X, Y, C, levels=20, **kwargs):
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return ax.contour(X, Y, C, levels=np.linspace(C.min(), C.max(), levels), **kwargs)
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def fill_between(self, ax, X, lower, upper, **kwargs):
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return ax.fill_between(X.flatten(), lower.flatten(), upper.flatten(), **kwargs)
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def fill_gradient(self, canvas, X, percentiles, **kwargs):
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ax = canvas
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plots = []
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if not 'alpha' in kwargs.keys():
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kwargs['alpha'] = 1./(len(percentiles))
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# pop where from kwargs
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where = kwargs.pop('where') if 'where' in kwargs else None
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# pop interpolate, which we actually do not do here!
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if 'interpolate' in kwargs: kwargs.pop('interpolate')
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def pairwise(inlist):
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l = len(inlist)
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for i in range(int(np.ceil(l/2.))):
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yield inlist[:][i], inlist[:][(l-1)-i]
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polycol = []
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for y1, y2 in pairwise(percentiles):
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import matplotlib.mlab as mlab
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# Handle united data, such as dates
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ax._process_unit_info(xdata=X, ydata=y1)
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ax._process_unit_info(ydata=y2)
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# Convert the arrays so we can work with them
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from numpy import ma
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x = ma.masked_invalid(ax.convert_xunits(X))
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y1 = ma.masked_invalid(ax.convert_yunits(y1))
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y2 = ma.masked_invalid(ax.convert_yunits(y2))
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if y1.ndim == 0:
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y1 = np.ones_like(x) * y1
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if y2.ndim == 0:
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y2 = np.ones_like(x) * y2
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if where is None:
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where = np.ones(len(x), np.bool)
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else:
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where = np.asarray(where, np.bool)
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if not (x.shape == y1.shape == y2.shape == where.shape):
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raise ValueError("Argument dimensions are incompatible")
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mask = reduce(ma.mask_or, [ma.getmask(a) for a in (x, y1, y2)])
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if mask is not ma.nomask:
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where &= ~mask
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polys = []
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for ind0, ind1 in mlab.contiguous_regions(where):
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xslice = x[ind0:ind1]
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y1slice = y1[ind0:ind1]
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y2slice = y2[ind0:ind1]
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if not len(xslice):
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continue
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N = len(xslice)
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X = np.zeros((2 * N + 2, 2), np.float)
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# the purpose of the next two lines is for when y2 is a
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# scalar like 0 and we want the fill to go all the way
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# down to 0 even if none of the y1 sample points do
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start = xslice[0], y2slice[0]
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end = xslice[-1], y2slice[-1]
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X[0] = start
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X[N + 1] = end
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X[1:N + 1, 0] = xslice
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X[1:N + 1, 1] = y1slice
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X[N + 2:, 0] = xslice[::-1]
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X[N + 2:, 1] = y2slice[::-1]
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polys.append(X)
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polycol.extend(polys)
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from matplotlib.collections import PolyCollection
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plots.append(PolyCollection(polycol, **kwargs))
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ax.add_collection(plots[-1], autolim=True)
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ax.autoscale_view()
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return plots
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