import math, copy
import param
import numpy as np
import matplotlib as mpl
import matplotlib.pyplot as plt
import matplotlib.colors as mpl_colors
from matplotlib import ticker
from matplotlib.dates import date2num
from ...core import util
from ...core import (OrderedDict, NdOverlay, DynamicMap,
CompositeOverlay, Element3D, Element)
from ...core.options import abbreviated_exception
from ..plot import GenericElementPlot, GenericOverlayPlot
from ..util import dynamic_update
from .plot import MPLPlot, mpl_rc_context
from .util import wrap_formatter
from distutils.version import LooseVersion
class ElementPlot(GenericElementPlot, MPLPlot):
apply_ticks = param.Boolean(default=True, doc="""
Whether to apply custom ticks.""")
aspect = param.Parameter(default='square', doc="""
The aspect ratio mode of the plot. By default, a plot may
select its own appropriate aspect ratio but sometimes it may
be necessary to force a square aspect ratio (e.g. to display
the plot as an element of a grid). The modes 'auto' and
'equal' correspond to the axis modes of the same name in
matplotlib, a numeric value may also be passed.""")
bgcolor = param.ClassSelector(class_=(str, tuple), default=None, doc="""
If set bgcolor overrides the background color of the axis.""")
invert_axes = param.ObjectSelector(default=False, doc="""
Inverts the axes of the plot. Note that this parameter may not
always be respected by all plots but should be respected by
adjoined plots when appropriate.""")
invert_xaxis = param.Boolean(default=False, doc="""
Whether to invert the plot x-axis.""")
invert_yaxis = param.Boolean(default=False, doc="""
Whether to invert the plot y-axis.""")
invert_zaxis = param.Boolean(default=False, doc="""
Whether to invert the plot z-axis.""")
labelled = param.List(default=['x', 'y'], doc="""
Whether to plot the 'x' and 'y' labels.""")
logx = param.Boolean(default=False, doc="""
Whether to apply log scaling to the x-axis of the Chart.""")
logy = param.Boolean(default=False, doc="""
Whether to apply log scaling to the y-axis of the Chart.""")
logz = param.Boolean(default=False, doc="""
Whether to apply log scaling to the y-axis of the Chart.""")
show_legend = param.Boolean(default=False, doc="""
Whether to show legend for the plot.""")
show_grid = param.Boolean(default=False, doc="""
Whether to show a Cartesian grid on the plot.""")
xaxis = param.ObjectSelector(default='bottom',
objects=['top', 'bottom', 'bare', 'top-bare',
'bottom-bare', None], doc="""
Whether and where to display the xaxis, bare options allow suppressing
all axis labels including ticks and xlabel. Valid options are 'top',
'bottom', 'bare', 'top-bare' and 'bottom-bare'.""")
yaxis = param.ObjectSelector(default='left',
objects=['left', 'right', 'bare', 'left-bare',
'right-bare', None], doc="""
Whether and where to display the yaxis, bare options allow suppressing
all axis labels including ticks and ylabel. Valid options are 'left',
'right', 'bare' 'left-bare' and 'right-bare'.""")
zaxis = param.Boolean(default=True, doc="""
Whether to display the z-axis.""")
xticks = param.Parameter(default=None, doc="""
Ticks along x-axis specified as an integer, explicit list of
tick locations, list of tuples containing the locations and
labels or a matplotlib tick locator object. If set to None
default matplotlib ticking behavior is applied.""")
xrotation = param.Integer(default=0, bounds=(0, 360), doc="""
Rotation angle of the xticks.""")
yticks = param.Parameter(default=None, doc="""
Ticks along y-axis specified as an integer, explicit list of
tick locations, list of tuples containing the locations and
labels or a matplotlib tick locator object. If set to None
default matplotlib ticking behavior is applied.""")
yrotation = param.Integer(default=0, bounds=(0, 360), doc="""
Rotation angle of the yticks.""")
zrotation = param.Integer(default=0, bounds=(0, 360), doc="""
Rotation angle of the zticks.""")
zticks = param.Parameter(default=None, doc="""
Ticks along z-axis specified as an integer, explicit list of
tick locations, list of tuples containing the locations and
labels or a matplotlib tick locator object. If set to None
default matplotlib ticking behavior is applied.""")
# Element Plots should declare the valid style options for matplotlib call
style_opts = []
# Whether plot has axes, disables setting axis limits, labels and ticks
_has_axes = True
def __init__(self, element, **params):
super(ElementPlot, self).__init__(element, **params)
check = self.hmap.last
if isinstance(check, CompositeOverlay):
check = check.values()[0] # Should check if any are 3D plots
if isinstance(check, Element3D):
self.projection = '3d'
for hook in self.initial_hooks:
try:
hook(self, element)
except Exception as e:
self.warning("Plotting hook %r could not be applied:\n\n %s" % (hook, e))
def _finalize_axis(self, key, element=None, title=None, dimensions=None, ranges=None, xticks=None,
yticks=None, zticks=None, xlabel=None, ylabel=None, zlabel=None):
"""
Applies all the axis settings before the axis or figure is returned.
Only plots with zorder 0 get to apply their settings.
When the number of the frame is supplied as n, this method looks
up and computes the appropriate title, axis labels and axis bounds.
"""
if element is None:
element = self._get_frame(key)
self.current_frame = element
if not dimensions and element and not self.subplots:
el = element.traverse(lambda x: x, [Element])
if el: dimensions = el[0].dimensions()
axis = self.handles['axis']
subplots = list(self.subplots.values()) if self.subplots else []
if self.zorder == 0 and key is not None:
if self.bgcolor:
if LooseVersion(mpl.__version__) <= '1.5.9':
axis.set_axis_bgcolor(self.bgcolor)
else:
axis.set_facecolor(self.bgcolor)
# Apply title
title = self._format_title(key)
if self.show_title and title is not None:
fontsize = self._fontsize('title')
if 'title' in self.handles:
self.handles['title'].set_text(title)
else:
self.handles['title'] = axis.set_title(title, **fontsize)
# Apply subplot label
self._subplot_label(axis)
# Apply axis options if axes are enabled
if element and not any(not sp._has_axes for sp in [self] + subplots):
# Set axis labels
if dimensions:
self._set_labels(axis, dimensions, xlabel, ylabel, zlabel)
if not subplots:
legend = axis.get_legend()
if legend:
legend.set_visible(self.show_legend)
self.handles["bbox_extra_artists"] += [legend]
axis.xaxis.grid(self.show_grid)
axis.yaxis.grid(self.show_grid)
# Apply log axes
if self.logx:
axis.set_xscale('log')
if self.logy:
axis.set_yscale('log')
if not self.projection == '3d':
self._set_axis_position(axis, 'x', self.xaxis)
self._set_axis_position(axis, 'y', self.yaxis)
# Apply ticks
if self.apply_ticks:
self._finalize_ticks(axis, dimensions, xticks, yticks, zticks)
# Set axes limits
self._set_axis_limits(axis, element, subplots, ranges)
# Apply aspects
if self.aspect is not None and self.projection != 'polar' and not self.adjoined:
self._set_aspect(axis, self.aspect)
if not subplots and not self.drawn:
self._finalize_artist(element)
for hook in self.finalize_hooks:
try:
hook(self, element)
except Exception as e:
self.warning("Plotting hook %r could not be applied:\n\n %s" % (hook, e))
return super(ElementPlot, self)._finalize_axis(key)
def _finalize_ticks(self, axis, dimensions, xticks, yticks, zticks):
"""
Finalizes the ticks on the axes based on the supplied ticks
and Elements. Sets the axes position as well as tick positions,
labels and fontsize.
"""
ndims = len(dimensions) if dimensions else 0
xdim = dimensions[0] if ndims else None
ydim = dimensions[1] if ndims > 1 else None
# Tick formatting
if xdim:
self._set_axis_formatter(axis.xaxis, xdim)
if ydim:
self._set_axis_formatter(axis.yaxis, ydim)
if self.projection == '3d':
zdim = dimensions[2] if ndims > 2 else None
if zdim:
self._set_axis_formatter(axis.zaxis, zdim)
xticks = xticks if xticks else self.xticks
self._set_axis_ticks(axis.xaxis, xticks, log=self.logx,
rotation=self.xrotation)
yticks = yticks if yticks else self.yticks
self._set_axis_ticks(axis.yaxis, yticks, log=self.logy,
rotation=self.yrotation)
if self.projection == '3d':
zticks = zticks if zticks else self.zticks
self._set_axis_ticks(axis.zaxis, zticks, log=self.logz,
rotation=self.zrotation)
for ax, ax_obj in zip('xy', [axis.xaxis, axis.yaxis]):
tick_fontsize = self._fontsize('%sticks' % ax,'labelsize',common=False)
if tick_fontsize: ax_obj.set_tick_params(**tick_fontsize)
def _finalize_artist(self, element):
"""
Allows extending the _finalize_axis method with Element
specific options.
"""
pass
def _set_labels(self, axes, dimensions, xlabel=None, ylabel=None, zlabel=None):
"""
Sets the labels of the axes using the supplied list of dimensions.
Optionally explicit labels may be supplied to override the dimension
label.
"""
xlabel, ylabel, zlabel = self._get_axis_labels(dimensions, xlabel, ylabel, zlabel)
if self.invert_axes:
xlabel, ylabel = ylabel, xlabel
if xlabel and self.xaxis and 'x' in self.labelled:
axes.set_xlabel(xlabel, **self._fontsize('xlabel'))
if ylabel and self.yaxis and 'y' in self.labelled:
axes.set_ylabel(ylabel, **self._fontsize('ylabel'))
if zlabel and self.zaxis and 'z' in self.labelled:
axes.set_zlabel(zlabel, **self._fontsize('zlabel'))
def _set_axis_formatter(self, axis, dim):
"""
Set axis formatter based on dimension formatter.
"""
if isinstance(dim, list): dim = dim[0]
formatter = None
if dim.value_format:
formatter = dim.value_format
elif dim.type in dim.type_formatters:
formatter = dim.type_formatters[dim.type]
if formatter:
axis.set_major_formatter(wrap_formatter(formatter))
def _set_aspect(self, axes, aspect):
"""
Set the aspect on the axes based on the aspect setting.
"""
if isinstance(aspect, util.basestring) and aspect != 'square':
axes.set_aspect(aspect)
return
(x0, x1), (y0, y1) = axes.get_xlim(), axes.get_ylim()
xsize = np.log(x1) - np.log(x0) if self.logx else x1-x0
ysize = np.log(y1) - np.log(y0) if self.logy else y1-y0
xsize = max(abs(xsize), 1e-30)
ysize = max(abs(ysize), 1e-30)
data_ratio = 1./(ysize/xsize)
if aspect != 'square':
data_ratio = data_ratio/aspect
axes.set_aspect(float(data_ratio))
def _set_axis_limits(self, axis, view, subplots, ranges):
"""
Compute extents for current view and apply as axis limits
"""
# Extents
scalex, scaley = True, True
extents = self.get_extents(view, ranges)
if extents and not self.overlaid:
coords = [coord if np.isreal(coord) or isinstance(coord, np.datetime64) else np.NaN for coord in extents]
coords = [date2num(util.dt64_to_dt(c)) if isinstance(c, np.datetime64) else c
for c in coords]
valid_lim = lambda c: util.isnumeric(c) and not np.isnan(c)
if self.projection == '3d' or len(extents) == 6:
l, b, zmin, r, t, zmax = coords
if self.invert_zaxis or any(p.invert_zaxis for p in subplots):
zmin, zmax = zmax, zmin
if zmin != zmax:
if valid_lim(zmin):
axis.set_zlim(bottom=zmin)
if valid_lim(zmax):
axis.set_zlim(top=zmax)
else:
l, b, r, t = coords
if self.invert_axes:
l, b, r, t = b, l, t, r
if self.invert_xaxis or any(p.invert_xaxis for p in subplots):
r, l = l, r
if l != r:
lims = {}
if valid_lim(l):
lims['left'] = l
scalex = False
if valid_lim(r):
lims['right'] = r
scalex = False
if lims:
axis.set_xlim(**lims)
if self.invert_yaxis or any(p.invert_yaxis for p in subplots):
t, b = b, t
if b != t:
lims = {}
if valid_lim(b):
lims['bottom'] = b
scaley = False
if valid_lim(t):
lims['top'] = t
scaley = False
if lims:
axis.set_ylim(**lims)
axis.autoscale_view(scalex=scalex, scaley=scaley)
def _set_axis_position(self, axes, axis, option):
"""
Set the position and visibility of the xaxis or yaxis by
supplying the axes object, the axis to set, i.e. 'x' or 'y'
and an option to specify the position and visibility of the axis.
The option may be None, 'bare' or positional, i.e. 'left' and
'right' for the yaxis and 'top' and 'bottom' for the xaxis.
May also combine positional and 'bare' into for example 'left-bare'.
"""
positions = {'x': ['bottom', 'top'], 'y': ['left', 'right']}[axis]
axis = axes.xaxis if axis == 'x' else axes.yaxis
if option is None:
axis.set_visible(False)
for pos in positions:
axes.spines[pos].set_visible(False)
else:
if 'bare' in option:
axis.set_ticklabels([])
axis.set_label_text('')
if option != 'bare':
option = option.split('-')[0]
axis.set_ticks_position(option)
axis.set_label_position(option)
if not self.overlaid and not self.show_frame and self.projection != 'polar':
pos = (positions[1] if (option and (option == 'bare' or positions[0] in option))
else positions[0])
axes.spines[pos].set_visible(False)
def _set_axis_ticks(self, axis, ticks, log=False, rotation=0):
"""
Allows setting the ticks for a particular axis either with
a tuple of ticks, a tick locator object, an integer number
of ticks, a list of tuples containing positions and labels
or a list of positions. Also supports enabling log ticking
if an integer number of ticks is supplied and setting a
rotation for the ticks.
"""
if isinstance(ticks, (list, tuple)) and all(isinstance(l, list) for l in ticks):
axis.set_ticks(ticks[0])
axis.set_ticklabels(ticks[1])
elif isinstance(ticks, ticker.Locator):
axis.set_major_locator(ticks)
elif not ticks and ticks is not None:
axis.set_ticks([])
elif isinstance(ticks, int):
if log:
locator = ticker.LogLocator(numticks=ticks,
subs=range(1,10))
else:
locator = ticker.MaxNLocator(ticks)
axis.set_major_locator(locator)
elif isinstance(ticks, (list, tuple)):
labels = None
if all(isinstance(t, tuple) for t in ticks):
ticks, labels = zip(*ticks)
axis.set_ticks(ticks)
if labels:
axis.set_ticklabels(labels)
for tick in axis.get_ticklabels():
tick.set_rotation(rotation)
@mpl_rc_context
def update_frame(self, key, ranges=None, element=None):
"""
Set the plot(s) to the given frame number. Operates by
manipulating the matplotlib objects held in the self._handles
dictionary.
If n is greater than the number of available frames, update
using the last available frame.
"""
reused = isinstance(self.hmap, DynamicMap) and self.overlaid
if not reused and element is None:
element = self._get_frame(key)
elif element is not None:
self.current_key = key
self.current_frame = element
if element is not None:
self.set_param(**self.lookup_options(element, 'plot').options)
axis = self.handles['axis']
axes_visible = element is not None or self.overlaid
axis.xaxis.set_visible(axes_visible and self.xaxis)
axis.yaxis.set_visible(axes_visible and self.yaxis)
axis.patch.set_alpha(np.min([int(axes_visible), 1]))
for hname, handle in self.handles.items():
hideable = hasattr(handle, 'set_visible')
if hname not in ['axis', 'fig'] and hideable:
handle.set_visible(element is not None)
if element is None:
return
ranges = self.compute_ranges(self.hmap, key, ranges)
ranges = util.match_spec(element, ranges)
label = element.label if self.show_legend else ''
style = dict(label=label, zorder=self.zorder, **self.style[self.cyclic_index])
axis_kwargs = self.update_handles(key, axis, element, ranges, style)
self._finalize_axis(key, element=element, ranges=ranges,
**(axis_kwargs if axis_kwargs else {}))
@mpl_rc_context
def initialize_plot(self, ranges=None):
element = self.hmap.last
ax = self.handles['axis']
key = list(self.hmap.data.keys())[-1]
dim_map = dict(zip((d.name for d in self.hmap.kdims), key))
key = tuple(dim_map.get(d.name, None) for d in self.dimensions)
ranges = self.compute_ranges(self.hmap, key, ranges)
ranges = util.match_spec(element, ranges)
style = dict(zorder=self.zorder, **self.style[self.cyclic_index])
if self.show_legend:
style['label'] = element.label
plot_data, plot_kwargs, axis_kwargs = self.get_data(element, ranges, style)
with abbreviated_exception():
handles = self.init_artists(ax, plot_data, plot_kwargs)
self.handles.update(handles)
return self._finalize_axis(self.keys[-1], element=element, ranges=ranges,
**axis_kwargs)
def init_artists(self, ax, plot_args, plot_kwargs):
"""
Initializes the artist based on the plot method declared on
the plot.
"""
plot_method = self._plot_methods.get('batched' if self.batched else 'single')
plot_fn = getattr(ax, plot_method)
artist = plot_fn(*plot_args, **plot_kwargs)
return {'artist': artist[0] if isinstance(artist, list) and
len(artist) == 1 else artist}
def update_handles(self, key, axis, element, ranges, style):
"""
Update the elements of the plot.
"""
self.teardown_handles()
plot_data, plot_kwargs, axis_kwargs = self.get_data(element, ranges, style)
with abbreviated_exception():
handles = self.init_artists(axis, plot_data, plot_kwargs)
self.handles.update(handles)
return axis_kwargs
def teardown_handles(self):
"""
If no custom update_handles method is supplied this method
is called to tear down any previous handles before replacing
them.
"""
if 'artist' in self.handles:
self.handles['artist'].remove()
class ColorbarPlot(ElementPlot):
colorbar = param.Boolean(default=False, doc="""
Whether to draw a colorbar.""")
clipping_colors = param.Dict(default={}, doc="""
Dictionary to specify colors for clipped values, allows
setting color for NaN values and for values above and below
the min and max value. The min, max or NaN color may specify
an RGB(A) color as a color hex string of the form #FFFFFF or
#FFFFFFFF or a length 3 or length 4 tuple specifying values in
the range 0-1 or a named HTML color.""")
cbar_padding = param.Number(default=0.01, doc="""
Padding between colorbar and other plots.""")
cbar_ticks = param.Parameter(default=None, doc="""
Ticks along colorbar-axis specified as an integer, explicit
list of tick locations, list of tuples containing the
locations and labels or a matplotlib tick locator object. If
set to None default matplotlib ticking behavior is
applied.""")
cbar_width = param.Number(default=0.05, doc="""
Width of the colorbar as a fraction of the main plot""")
symmetric = param.Boolean(default=False, doc="""
Whether to make the colormap symmetric around zero.""")
_colorbars = {}
def __init__(self, *args, **kwargs):
super(ColorbarPlot, self).__init__(*args, **kwargs)
self._cbar_extend = 'neither'
def _adjust_cbar(self, cbar, label, dim):
noalpha = math.floor(self.style[self.cyclic_index].get('alpha', 1)) == 1
if (cbar.solids and noalpha):
cbar.solids.set_edgecolor("face")
cbar.set_label(label)
if isinstance(self.cbar_ticks, ticker.Locator):
cbar.ax.yaxis.set_major_locator(self.cbar_ticks)
elif self.cbar_ticks == 0:
cbar.set_ticks([])
elif isinstance(self.cbar_ticks, int):
locator = ticker.MaxNLocator(self.cbar_ticks)
cbar.ax.yaxis.set_major_locator(locator)
elif isinstance(self.cbar_ticks, list):
if all(isinstance(t, tuple) for t in self.cbar_ticks):
ticks, labels = zip(*self.cbar_ticks)
else:
ticks, labels = zip(*[(t, dim.pprint_value(t))
for t in self.cbar_ticks])
cbar.set_ticks(ticks)
cbar.set_ticklabels(labels)
def _finalize_artist(self, element):
artist = self.handles.get('artist', None)
if artist and self.colorbar:
self._draw_colorbar()
def _draw_colorbar(self, dim=None, redraw=True):
element = self.hmap.last
artist = self.handles.get('artist', None)
fig = self.handles['fig']
axis = self.handles['axis']
ax_colorbars, position = ColorbarPlot._colorbars.get(id(axis), ([], None))
specs = [spec[:2] for _, _, spec, _ in ax_colorbars]
spec = util.get_spec(element)
if position is None or not redraw:
if redraw:
fig.canvas.draw()
bbox = axis.get_position()
l, b, w, h = bbox.x0, bbox.y0, bbox.width, bbox.height
else:
l, b, w, h = position
# Get colorbar label
dim = element.get_dimension(dim)
if dim:
label = dim.pprint_label
elif element.vdims:
label = element.vdims[0].pprint_label
elif dim is None:
label = ''
padding = self.cbar_padding
width = self.cbar_width
if spec[:2] not in specs:
offset = len(ax_colorbars)
scaled_w = w*width
cax = fig.add_axes([l+w+padding+(scaled_w+padding+w*0.15)*offset,
b, scaled_w, h])
cbar = fig.colorbar(artist, cax=cax, ax=axis, extend=self._cbar_extend)
self._adjust_cbar(cbar, label, dim)
self.handles['cax'] = cax
self.handles['cbar'] = cbar
ylabel = cax.yaxis.get_label()
self.handles['bbox_extra_artists'] += [cax, ylabel]
ax_colorbars.append((artist, cax, spec, label))
for i, (artist, cax, spec, label) in enumerate(ax_colorbars):
scaled_w = w*width
cax.set_position([l+w+padding+(scaled_w+padding+w*0.15)*i,
b, scaled_w, h])
ColorbarPlot._colorbars[id(axis)] = (ax_colorbars, (l, b, w, h))
def _norm_kwargs(self, element, ranges, opts, vdim):
"""
Returns valid color normalization kwargs
to be passed to matplotlib plot function.
"""
clim = opts.pop('clims', None)
if clim is None:
cs = element.dimension_values(vdim)
if not isinstance(cs, np.ndarray):
cs = np.array(cs)
if len(cs) and cs.dtype.kind in 'if':
clim = ranges[vdim.name] if vdim.name in ranges else element.range(vdim)
if self.logz:
# Lower clim must be >0 when logz=True
# Choose the maximum between the lowest non-zero value
# and the overall range
if clim[0] == 0:
vals = element.dimension_values(vdim)
clim = (vals[vals!=0].min(), clim[1])
if self.symmetric:
clim = -np.abs(clim).max(), np.abs(clim).max()
else:
clim = (0, len(np.unique(cs)))
if self.logz:
if self.symmetric:
norm = mpl_colors.SymLogNorm(vmin=clim[0], vmax=clim[1],
linthresh=clim[1]/np.e)
else:
norm = mpl_colors.LogNorm(vmin=clim[0], vmax=clim[1])
opts['norm'] = norm
opts['vmin'] = clim[0]
opts['vmax'] = clim[1]
# Check whether the colorbar should indicate clipping
values = np.asarray(element.dimension_values(vdim))
if values.dtype.kind not in 'OSUM':
try:
el_min, el_max = np.nanmin(values), np.nanmax(values)
except ValueError:
el_min, el_max = -np.inf, np.inf
else:
el_min, el_max = -np.inf, np.inf
vmin = -np.inf if opts['vmin'] is None else opts['vmin']
vmax = np.inf if opts['vmax'] is None else opts['vmax']
if el_min < vmin and el_max > vmax:
self._cbar_extend = 'both'
elif el_min < vmin:
self._cbar_extend = 'min'
elif el_max > vmax:
self._cbar_extend = 'max'
# Define special out-of-range colors on colormap
cmap = opts.get('cmap')
if isinstance(cmap, list):
cmap = mpl_colors.ListedColormap(cmap)
elif isinstance(cmap, util.basestring):
cmap = copy.copy(plt.cm.get_cmap(cmap))
else:
cmap = copy.copy(cmap)
colors = {}
for k, val in self.clipping_colors.items():
if isinstance(val, tuple):
colors[k] = {'color': val[:3],
'alpha': val[3] if len(val) > 3 else 1}
elif isinstance(val, util.basestring):
color = val
alpha = 1
if color.startswith('#') and len(color) == 9:
alpha = int(color[-2:], 16)/255.
color = color[:-2]
colors[k] = {'color': color, 'alpha': alpha}
if 'max' in colors: cmap.set_over(**colors['max'])
if 'min' in colors: cmap.set_under(**colors['min'])
if 'NaN' in colors: cmap.set_bad(**colors['NaN'])
opts['cmap'] = cmap
class LegendPlot(ElementPlot):
show_legend = param.Boolean(default=True, doc="""
Whether to show legend for the plot.""")
legend_cols = param.Integer(default=None, doc="""
Number of legend columns in the legend.""")
legend_position = param.ObjectSelector(objects=['inner', 'right',
'bottom', 'top',
'left', 'best',
'top_right',
'top_left',
'bottom_left',
'bottom_right'],
default='inner', doc="""
Allows selecting between a number of predefined legend position
options. The predefined options may be customized in the
legend_specs class attribute. By default, 'inner', 'right',
'bottom', 'top', 'left', 'best', 'top_right', 'top_left',
'bottom_right' and 'bottom_left' are supported.""")
legend_specs = {'inner': {},
'best': {},
'left': dict(bbox_to_anchor=(-.15, 1), loc=1),
'right': dict(bbox_to_anchor=(1.05, 1), loc=2),
'top': dict(bbox_to_anchor=(0., 1.02, 1., .102),
ncol=3, loc=3, mode="expand", borderaxespad=0.),
'bottom': dict(ncol=3, mode="expand", loc=2,
bbox_to_anchor=(0., -0.25, 1., .102),
borderaxespad=0.1),
'top_right': dict(loc=1),
'top_left': dict(loc=2),
'bottom_left': dict(loc=3),
'bottom_right': dict(loc=4)}
[docs]class OverlayPlot(LegendPlot, GenericOverlayPlot):
"""
OverlayPlot supports compositors processing of Overlays across maps.
"""
_passed_handles = ['fig', 'axis']
_propagate_options = ['aspect', 'fig_size', 'xaxis', 'yaxis', 'zaxis',
'labelled', 'bgcolor', 'fontsize', 'invert_axes',
'show_frame', 'show_grid', 'logx', 'logy', 'logz',
'xticks', 'yticks', 'zticks', 'xrotation', 'yrotation'
'zrotation', 'invert_xaxis', 'invert_yaxis',
'invert_zaxis', 'title_format']
def __init__(self, overlay, ranges=None, **params):
if 'projection' not in params:
params['projection'] = self._get_projection(overlay)
super(OverlayPlot, self).__init__(overlay, ranges=ranges, **params)
def _finalize_artist(self, element):
for subplot in self.subplots.values():
subplot._finalize_artist(element)
def _adjust_legend(self, overlay, axis):
"""
Accumulate the legend handles and labels for all subplots
and set up the legend
"""
legend_data = []
dimensions = overlay.kdims
title = ', '.join([d.name for d in dimensions])
for key, subplot in self.subplots.items():
element = overlay.data.get(key, False)
if not subplot.show_legend or not element: continue
title = ', '.join([d.name for d in dimensions])
handle = subplot.handles.get('artist', False)
if isinstance(overlay, NdOverlay):
key = (dim.pprint_value(k) for k, dim in zip(key, dimensions))
label = ','.join([str(k) + dim.unit if dim.unit else str(k) for dim, k in
zip(dimensions, key)])
if handle:
legend_data.append((handle, label))
else:
if isinstance(subplot, OverlayPlot):
legend_data += subplot.handles.get('legend_data', {}).items()
if element.label and handle:
legend_data.append((handle, element.label))
all_handles, all_labels = list(zip(*legend_data)) if legend_data else ([], [])
data = OrderedDict()
used_labels = []
for handle, label in zip(all_handles, all_labels):
if handle and (handle not in data) and label and label not in used_labels:
data[handle] = label
used_labels.append(label)
if (not len(set(data.values())) > 0) or not self.show_legend:
legend = axis.get_legend()
if legend:
legend.set_visible(False)
else:
leg_spec = self.legend_specs[self.legend_position]
if self.legend_cols: leg_spec['ncol'] = self.legend_cols
leg = axis.legend(data.keys(), data.values(),
title=title, scatterpoints=1,
**dict(leg_spec, **self._fontsize('legend')))
title_fontsize = self._fontsize('legend_title')
if title_fontsize:
leg.get_title().set_fontsize(title_fontsize['fontsize'])
frame = leg.get_frame()
frame.set_facecolor('1.0')
frame.set_edgecolor('0.0')
frame.set_linewidth('1.0')
leg.set_zorder(10e6)
self.handles['legend'] = leg
self.handles['bbox_extra_artists'].append(leg)
self.handles['legend_data'] = data
@mpl_rc_context
def initialize_plot(self, ranges=None):
axis = self.handles['axis']
key = self.keys[-1]
element = self._get_frame(key)
ranges = self.compute_ranges(self.hmap, key, ranges)
for k, subplot in self.subplots.items():
subplot.initialize_plot(ranges=ranges)
if isinstance(element, CompositeOverlay):
frame = element.get(k, None)
subplot.current_frame = frame
if self.show_legend and element is not None:
self._adjust_legend(element, axis)
return self._finalize_axis(key, element=element, ranges=ranges,
title=self._format_title(key))
@mpl_rc_context
def update_frame(self, key, ranges=None, element=None):
axis = self.handles['axis']
reused = isinstance(self.hmap, DynamicMap) and self.overlaid
if element is None and not reused:
element = self._get_frame(key)
elif element is not None:
self.current_frame = element
self.current_key = key
empty = element is None
if isinstance(self.hmap, DynamicMap):
range_obj = element
else:
range_obj = self.hmap
items = [] if element is None else element.items()
if not empty:
ranges = self.compute_ranges(range_obj, key, ranges)
for k, subplot in self.subplots.items():
el = None if empty else element.get(k, None)
if isinstance(self.hmap, DynamicMap) and not empty:
idx = dynamic_update(self, subplot, k, element, items)
if idx is not None:
_, el = items.pop(idx)
subplot.update_frame(key, ranges, el)
if isinstance(self.hmap, DynamicMap) and items:
raise Exception("Some Elements returned by the dynamic callback "
"were not initialized correctly and could not be "
"rendered.")
if self.show_legend and not empty:
self._adjust_legend(element, axis)
self._finalize_axis(key, element=element, ranges=ranges)
