浅谈matplotlib中FigureCanvasXAgg的用法

背景知识：

FigureCanvasXAgg就是一个渲染器，渲染器的工作就是drawing，执行绘图的这个动作。渲染器是使物体显示在屏幕上

主要内容：

将一个figure渲染的canvas变为一个Qt widgets，figure显示的过程是需要管理器（manager），需要FigureCanvasBase来管理。报错信息’FigureCanvasQTAgg’ object has no attribute ‘manager’

将一个navigation toolbar渲染成Qt widgets

使用用户事件来实时更新matplotlib plot

matplotlib针对GUI设计了两层结构概念：canvas，renderer。

下面我将以默认自带的后端 tkAgg：from matplotlib.backends.backend_tkagg import FigureCanvasTkAgg as FigureCanvas为例，为大家讲解画布与渲染器的知识。

一. canvas（画布）

对应抽象的类：FigureCanvasBase and FigureManagerBase

作用：

保存对图像的引用

更新图像通过对画布的引用

定义运行注册的事件方法

将本地工具箱事件转为matplotlib事件抽象框架

定义绘制渲染图片的方法

停止和开始nono-GUI事件循环

1. 追寻matplotlib.figure.Figure.show( )

以下引自matplotlib.figure.Figure.show( ) 源码和注释：

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#matplotlib.figure.Figure.show( )
def show(self, warn=True):
 """
 If using a GUI backend with pyplot, display the figure window.

 If the figure was not created using
 :func:`~matplotlib.pyplot.figure`, it will lack a
 :class:`~matplotlib.backend_bases.FigureManagerBase`, and
 will raise an AttributeError.

 Parameters
 ----------
 warm : bool
  If ``True``, issue warning when called on a non-GUI backend

 Notes
 -----
 For non-GUI backends, this does nothing, in which case a warning will
 be issued if *warn* is ``True`` (default).
 """
 try:
  manager = getattr(self.canvas, 'manager')
 except AttributeError as err:
  raise AttributeError("%sn"
        "Figure.show works only "
        "for figures managed by pyplot, normally "
        "created by pyplot.figure()." % err)

 if manager is not None:
  try:
   manager.show()
   return
  except NonGuiException:
   pass

它是通过manager.show()来实现画图的动作的。

2. 追寻plt.show（）

而在==plt.show( )==的源码中我们可以查到：

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#plt.show（）
from matplotlib.backends import pylab_setup
_show = pylab_setup()
def show(*args, **kw):

 global _show
 return _show(*args, **kw)

而我们继续查找就得到了,这是在backends包的__init__.py模块里的代码，代码说了一大堆，无非就是说它返回了四个对象：backend_mod, new_figure_manager, draw_if_interactive, show。而show就是show = getattr(backend_mod, ‘show’, do_nothing_show)得到的其中backend_mod就是要导入模块的绝对路径，之后验证的show就是matplotlib.backends.backend_tkagg._BackendTkAgg，继续追寻之后我们得到class _BackendTkAgg(_BackendTk): FigureCanvas = FigureCanvasTkAgg,之后我们用help函数得到

代码语言：javascript复制

show(block=None) method of builtins.type instance
 Show all figures.
 
 `show` blocks by calling `mainloop` if *block* is ``True``, or if it
 is ``None`` and we are neither in IPython's ``%pylab`` mode, nor in
 `interactive` mode.

我们继续刨根，寻找从FigureCanvas开始的类的关系和其方法，类的继承结构关系如下图

然后终于在FigureCnavasTk类的声明中找到了这样的一句声明：

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show = cbook.deprecated("2.2", name="FigureCanvasTk.show",
       alternative="FigureCanvasTk.draw")(
        lambda self: self.draw())

也就是说show归根结底是backend里的一个FigureCanvasTk.draw（）的一个变形 ！

pylab_setup代码如下：

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def pylab_setup(name=None):
 '''return new_figure_manager, draw_if_interactive and show for pyplot

 This provides the backend-specific functions that are used by
 pyplot to abstract away the difference between interactive backends.

 Parameters
 ----------
 name : str, optional
  The name of the backend to use. If `None`, falls back to
  ``matplotlib.get_backend()`` (which return :rc:`backend`).

 '''
 # Import the requested backend into a generic module object
 if name is None:
  # validates, to match all_backends
  name = matplotlib.get_backend()
 if name.startswith('module://'):
  backend_name = name[9:]
 else:
  backend_name = 'backend_'   name
  backend_name = backend_name.lower() # until we banish mixed case
  backend_name = 'matplotlib.backends.%s' % backend_name.lower()

 # the last argument is specifies whether to use absolute or relative
 # imports. 0 means only perform absolute imports.
 #得到模块的绝对路径backend_mod，然后通过绝对路径加.就可以调用各个抽象类
 #<module 'matplotlib.backends.backend_tkagg' from 'D:Python36libsite-packagesmatplotlibbackendsbackend_tkagg.py' 默认实验的！
 backend_mod = __import__(backend_name, globals(), locals(),
        [backend_name], 0)

 # Things we pull in from all backends
 new_figure_manager = backend_mod.new_figure_manager

 # image backends like pdf, agg or svg do not need to do anything
 # for "show" or "draw_if_interactive", so if they are not defined
 # by the backend, just do nothing
 def do_nothing_show(*args, **kwargs):
  frame = inspect.currentframe()
  fname = frame.f_back.f_code.co_filename
  if fname in ('<stdin ', '<ipython console '):
   warnings.warn("""
Your currently selected backend, '%s' does not support show().
Please select a GUI backend in your matplotlibrc file ('%s')
or with matplotlib.use()""" %
       (name, matplotlib.matplotlib_fname()))

 def do_nothing(*args, **kwargs):
  pass

 backend_version = getattr(backend_mod, 'backend_version', 'unknown')

 show = getattr(backend_mod, 'show', do_nothing_show)

 draw_if_interactive = getattr(backend_mod, 'draw_if_interactive',
         do_nothing)

 _log.debug('backend %s version %s', name, backend_version)

 # need to keep a global reference to the backend for compatibility
 # reasons. See https://github.com/matplotlib/matplotlib/issues/6092
 global backend
 backend = name
 return backend_mod, new_figure_manager, draw_if_interactive, show

3. 追寻plt.figure()

我们创建的这个figure必须有manager，否则则会报错，如果是plt.figure初始化的,plt.figure( )源码如下：

plt.figure（）示例

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def figure():

 figManager = _pylab_helpers.Gcf.get_fig_manager(num)

 figManager = new_figure_manager(num,figsize=figsize,dpi=dpi,facecolor=facecolor,edgecolor=edgecolor,frameon=frameon,FigureClass=FigureClass,**kwargs)
 ......
 ......
 return figManager.canvas.figure

4. 追寻matplotlib.figure.Figure()

而在matplotlib.figure.Figure() 中，其初始化函数__init__（）,并没有默认生成manager这个属性，所以在调用show的时候，就会报错！如上其show函数定义的那样

代码语言：javascript复制

def __init__(self,
figsize=None, # defaults to rc figure.figsize
dpi=None, # defaults to rc figure.dpi
facecolor=None, # defaults to rc figure.facecolor
edgecolor=None, # defaults to rc figure.edgecolor
linewidth=0.0, # the default linewidth of the frame
frameon=None, # whether or not to draw the figure frame
subplotpars=None, # default to rc
tight_layout=None, # default to rc figure.autolayout
constrained_layout=None, # default to rc
#figure.constrained_layout.use
):
"""
Parameters
----------
figsize : 2-tuple of floats
``(width, height)`` tuple in inches
dpi : float
Dots per inch
facecolor
The figure patch facecolor; defaults to rc ``figure.facecolor``
edgecolor
The figure patch edge color; defaults to rc ``figure.edgecolor``
linewidth : float
The figure patch edge linewidth; the default linewidth of the frame
frameon : bool
If ``False``, suppress drawing the figure frame
subplotpars : :class:`SubplotParams`
Subplot parameters, defaults to rc
tight_layout : bool
If ``False`` use *subplotpars*; if ``True`` adjust subplot
parameters using `.tight_layout` with default padding.
When providing a dict containing the keys
``pad``, ``w_pad``, ``h_pad``, and ``rect``, the default
`.tight_layout` paddings will be overridden.
Defaults to rc ``figure.autolayout``.
constrained_layout : bool
If ``True`` use constrained layout to adjust positioning of plot
elements. Like ``tight_layout``, but designed to be more
flexible. See
:doc:`/tutorials/intermediate/constrainedlayout_guide`
for examples. (Note: does not work with :meth:`.subplot` or
:meth:`.subplot2grid`.)
Defaults to rc ``figure.constrained_layout.use``.
"""
Artist.__init__(self)
# remove the non-figure artist _axes property
# as it makes no sense for a figure to be _in_ an axes
# this is used by the property methods in the artist base class
# which are over-ridden in this class
del self._axes
self.callbacks = cbook.CallbackRegistry()
if figsize is None:
figsize = rcParams['figure.figsize']
if dpi is None:
dpi = rcParams['figure.dpi']
if facecolor is None:
facecolor = rcParams['figure.facecolor']
if edgecolor is None:
edgecolor = rcParams['figure.edgecolor']
if frameon is None:
frameon = rcParams['figure.frameon']
if not np.isfinite(figsize).all():
raise ValueError('figure size must be finite not '
'{}'.format(figsize))
self.bbox_inches = Bbox.from_bounds(0, 0, *figsize)
self.dpi_scale_trans = Affine2D().scale(dpi, dpi)
# do not use property as it will trigger
self._dpi = dpi
self.bbox = TransformedBbox(self.bbox_inches, self.dpi_scale_trans)
self.frameon = frameon
self.transFigure = BboxTransformTo(self.bbox)
self.patch = Rectangle(
xy=(0, 0), width=1, height=1,
facecolor=facecolor, edgecolor=edgecolor, linewidth=linewidth)
self._set_artist_props(self.patch)
self.patch.set_aa(False)
self._hold = rcParams['axes.hold']
if self._hold is None:
self._hold = True
self.canvas = None
self._suptitle = None
if subplotpars is None:
subplotpars = SubplotParams()
self.subplotpars = subplotpars
# constrained_layout:
self._layoutbox = None
# set in set_constrained_layout_pads()
self.set_constrained_layout(constrained_layout)
self.set_tight_layout(tight_layout)
self._axstack = AxesStack() # track all figure axes and current axes
self.clf()
self._cachedRenderer = None
# groupers to keep track of x and y labels we want to align.
# see self.align_xlabels and self.align_ylabels and
# axis._get_tick_boxes_siblings
self._align_xlabel_grp = cbook.Grouper()
self._align_ylabel_grp = cbook.Grouper()

综上所述，我们通过matplotlib.figure.Figure()来创建得到的fig，并不具备manager的属性，而通过plt.figure（）创建的fig，就默认创建了manager。

二 . renderer（渲染器），默认是tkagg

对应抽象的类：RendererBase and GraphicsContextBase

作用：

– 很多渲染操作都传递给一个额外的抽象：GraphicsContextBase，它为处理颜色、线条样式、起始样式、混合属性和反混叠选项等的代码提供了一个干净的分离。

Qt & matplotlib示例代码

代码语言：javascript复制

#import modules from Matplotlib
from matplotlib.backends.backend_qt4agg import FigureCanvasQTAgg as FigureCanvas
from matplotlib.backends.backend_qt4agg import NavigationToolbar2QTAgg as NavigationToolbar
import matplotlib.pyplot as plt
#import random module to generate set
import random
class Window(QtGui.QDialog):
def __init__(self, parent=None):
super(Window, self).__init__(parent)
#init figure and canvas
self.figure = plt.figure()
self.canvas = FigureCanvas(self.figure)
#init nav toolbar
self.toolbar = NavigationToolbar(self.canvas, self)
# Add plot button
self.button = QtGui.QPushButton('Plot')
# connect button to custom slot (see later)
self.button.clicked.connect(self.plot)
# set the layout
layout = QtGui.QVBoxLayout()
layout.addWidget(self.toolbar)
layout.addWidget(self.canvas)
layout.addWidget(self.button)
self.setLayout(layout)
### our custom slot
def plot(self):
# random data
data = [random.random() for i in range(25)]
# create an axis
ax = self.figure.add_subplot(1,1,1)
# discards the old graph
ax.hold(False)
# plot data
ax.plot(data, '*­')
# refresh canvas
self.canvas.draw()

三. Problems（GUI画3D不能旋转）

一个Axes3D创建callback函数给画布上的图形实现旋转特性。如果说先给图形（figure）增加axes或者其他配件的时候，在之后将图形附加到画布的时候，之前添加的axes的callback函数可能不能够接收消息事件，也就没办法在绘出的GUI实现旋转的性能。

所以应该先将图形附加到画布上，然后再对图形增加axes和其他的配件。

FigureCanvas（figure，canvas）

figure：需要附加的图形（添加者），canvas提供渲染功能的对象（承载者）

每一次你调用FigureCanvas（）的时候，你都是将图形附加到新画布上（这不是你所看到的的那个canvas），于是 the call-backs函数将不会被射击（接收事件信号），因为他们正在监听一个你看不到的canvas。

四 . 附录

以上这篇浅谈matplotlib中FigureCanvasXAgg的用法就是小编分享给大家的全部内容了，希望能给大家一个参考。

python matlab numpy canvas

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