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GPy/GPy/plotting/matplot_dep/plot_definitions.py
Max Zwiessele 885d3722cc [mrd] plot_scales and plot_latent added
2016-03-01 10:02:02 +00:00

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#===============================================================================
# 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, ImAnnotateController
import itertools
from .util import legend_ontop
class MatplotlibPlots(AbstractPlottingLibrary):
def __init__(self):
super(MatplotlibPlots, self).__init__()
self._defaults = defaults.__dict__
def figure(self, rows=1, cols=1, gridspec_kwargs={}, tight_layout=True, **kwargs):
fig = plt.figure(tight_layout=tight_layout, **kwargs)
fig.rows = rows
fig.cols = cols
fig.gridspec = plt.GridSpec(rows, cols, **gridspec_kwargs)
return fig
def new_canvas(self, figure=None, row=1, col=1, projection='2d', xlabel=None, ylabel=None, zlabel=None, title=None, xlim=None, ylim=None, zlim=None, **kwargs):
if projection == '3d':
from mpl_toolkits.mplot3d import Axes3D
elif projection == '2d':
projection = None
if 'ax' in kwargs:
ax = kwargs.pop('ax')
else:
if figure is not None:
fig = figure
elif 'num' in kwargs and 'figsize' in kwargs:
fig = self.figure(num=kwargs.pop('num'), figsize=kwargs.pop('figsize'))
elif 'num' in kwargs:
fig = self.figure(num=kwargs.pop('num'))
elif 'figsize' in kwargs:
fig = self.figure(figsize=kwargs.pop('figsize'))
else:
fig = self.figure()
#if hasattr(fig, 'rows') and hasattr(fig, 'cols'):
ax = fig.add_subplot(fig.gridspec[row-1, col-1], projection=projection)
if xlim is not None: ax.set_xlim(xlim)
if ylim is not None: ax.set_ylim(ylim)
if xlabel is not None: ax.set_xlabel(xlabel)
if ylabel is not None: ax.set_ylabel(ylabel)
if title is not None: ax.set_title(title)
if projection == '3d':
if zlim is not None: ax.set_zlim(zlim)
if zlabel is not None: ax.set_zlabel(zlabel)
return ax, kwargs
def add_to_canvas(self, ax, plots, legend=False, title=None, **kwargs):
#ax.autoscale_view()
fontdict=dict(family='sans-serif', weight='light', size=9)
if legend is True:
ax.legend(*ax.get_legend_handles_labels())
elif legend >= 1:
#ax.legend(prop=fontdict)
legend_ontop(ax, ncol=legend, fontdict=fontdict)
if title is not None: ax.figure.suptitle(title)
return ax
def show_canvas(self, ax):
ax.figure.canvas.draw()
return ax.figure
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, Z=None, color=None, label=None, **kwargs):
if Z is not None:
return ax.plot(X, Y, color=color, zs=Z, label=label, **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, 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, 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, vmin=None, vmax=None, **imshow_kwargs):
if 'origin' not in imshow_kwargs:
imshow_kwargs['origin'] = 'lower'
#xmin, xmax, ymin, ymax = extent
#xoffset, yoffset = (xmax - xmin) / (2. * X.shape[0]), (ymax - ymin) / (2. * X.shape[1])
#xmin, xmax, ymin, ymax = extent = xmin-xoffset, xmax+xoffset, ymin-yoffset, ymax+yoffset
return ax.imshow(X, label=label, extent=extent, vmin=vmin, vmax=vmax, **imshow_kwargs)
def imshow_interact(self, ax, plot_function, extent, label=None, resolution=None, vmin=None, vmax=None, **imshow_kwargs):
if imshow_kwargs is None: imshow_kwargs = {}
if 'origin' not in imshow_kwargs:
imshow_kwargs['origin'] = 'lower'
return ImshowController(ax, plot_function, extent, resolution=resolution, vmin=vmin, vmax=vmax, **imshow_kwargs)
def annotation_heatmap(self, ax, X, annotation, extent=None, label=None, imshow_kwargs=None, **annotation_kwargs):
if imshow_kwargs is None: imshow_kwargs = {}
if 'origin' not in imshow_kwargs:
imshow_kwargs['origin'] = 'lower'
if ('ha' not in annotation_kwargs) and ('horizontalalignment' not in annotation_kwargs):
annotation_kwargs['ha'] = 'center'
if ('va' not in annotation_kwargs) and ('verticalalignment' not in annotation_kwargs):
annotation_kwargs['va'] = 'center'
imshow = self.imshow(ax, X, extent, label, **imshow_kwargs)
if extent is None:
extent = (0, X.shape[0], 0, X.shape[1])
xmin, xmax, ymin, ymax = extent
xoffset, yoffset = (xmax - xmin) / (2. * X.shape[0]), (ymax - ymin) / (2. * X.shape[1])
xlin = np.linspace(xmin, xmax, X.shape[0], endpoint=False)
ylin = np.linspace(ymin, ymax, X.shape[1], endpoint=False)
annotations = []
for [i, x], [j, y] in itertools.product(enumerate(xlin), enumerate(ylin)):
annotations.append(ax.text(x+xoffset, y+yoffset, "{}".format(annotation[j, i]), **annotation_kwargs))
return imshow, annotations
def annotation_heatmap_interact(self, ax, plot_function, extent, label=None, resolution=15, imshow_kwargs=None, **annotation_kwargs):
if imshow_kwargs is None: imshow_kwargs = {}
if 'origin' not in imshow_kwargs:
imshow_kwargs['origin'] = 'lower'
return ImAnnotateController(ax, plot_function, extent, resolution=resolution, imshow_kwargs=imshow_kwargs or {}, **annotation_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
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