python画图程序库_python绘图matplotlib绘图库入门

简介：matplotlib 是Python最著名的绘图库，它提供了一整套和matlab相似的命令API，十分适合交互式地行制图。而且也可以方便地将它作为绘

图控件，嵌入GUI应用程序中。

在Python中使用matplotlib.pyplot快速绘图

下面是matplotlib库所给的介绍

"""

This is an object-oriented plotting library.

这是面向对象的绘图库

A procedural interface is provided by the companion pyplot module,（程序接口直接import matplotlib.pyplot as plt 就可以了，或者使用ipython）

which may be imported directly, e.g.::

import matplotlib.pyplot as plt

or using ipython::

ipython

at your terminal, followed by::

In [1]: %matplotlib

In [2]: import matplotlib.pyplot as plt

at the ipython shell prompt.

For the most part, direct use of the object-oriented library is

encouraged when programming; pyplot is primarily for working

interactively. The

exceptions are the pyplot commands :func:`~matplotlib.pyplot.figure`,

:func:`~matplotlib.pyplot.subplot`,

:func:`~matplotlib.pyplot.subplots`, and

:func:`~pyplot.savefig`, which can greatly simplify scripting.

Modules include: (matplotlib模块里面有axes,figure,artist,lines,........)

:mod:`matplotlib.axes`

defines the :class:`~matplotlib.axes.Axes` class. Most pylab

commands are wrappers for :class:`~matplotlib.axes.Axes`

methods. The axes module is the highest level of OO access to

the library.

:mod:`matplotlib.figure`

defines the :class:`~matplotlib.figure.Figure` class.

:mod:`matplotlib.artist`

defines the :class:`~matplotlib.artist.Artist` base class for

all classes that draw things.

:mod:`matplotlib.lines`

defines the :class:`~matplotlib.lines.Line2D` class for

drawing lines and markers

:mod:`matplotlib.patches`

defines classes for drawing polygons

:mod:`matplotlib.text`

defines the :class:`~matplotlib.text.Text`,

:class:`~matplotlib.text.TextWithDash`, and

:class:`~matplotlib.text.Annotate` classes

:mod:`matplotlib.image`

defines the :class:`~matplotlib.image.AxesImage` and

:class:`~matplotlib.image.FigureImage` classes

:mod:`matplotlib.collections`

classes for efficient drawing of groups of lines or polygons

:mod:`matplotlib.colors`

classes for interpreting color specifications and for making

colormaps

:mod:`matplotlib.cm`

colormaps and the :class:`~matplotlib.image.ScalarMappable`

mixin class for providing color mapping functionality to other

classes

:mod:`matplotlib.ticker`

classes for calculating tick mark locations and for formatting

tick labels

:mod:`matplotlib.backends`

a subpackage with modules for various gui libraries and output

formats

The base matplotlib namespace includes:

:data:`~matplotlib.rcParams`

a global dictionary of default configuration settings. It is

initialized by code which may be overridded by a matplotlibrc

file.

:func:`~matplotlib.rc`

a function for setting groups of rcParams values

:func:`~matplotlib.use`

a function for setting the matplotlib backend. If used, this

function must be called immediately after importing matplotlib

for the first time. In particular, it must be called

**before** importing pylab (if pylab is imported).

matplotlib was initially written by John D. Hunter (1968-2012) and is now

developed and maintained by a host of others.

Occasionally the internal documentation (python docstrings) will refer

to MATLAB®, a registered trademark of The MathWorks, Inc.

"""阅读后，我们明白matplotlib实际上是一套面向对象的绘图库，它所绘制的图表中的每个绘图元素，例如线条Line2D、文字Text、刻度等在内存中都有一个对象与之对应。

我们只需要调用pyplot模块所提供的函数就可以实现快速绘图以及设置图表的各种细节。

def sca(ax):

"""

Set the current Axes instance to *ax*.

The current Figure is updated to the parent of *ax*.

"""

managers = _pylab_helpers.Gcf.get_all_fig_managers()

for m in managers:

if ax in m.canvas.figure.axes:

_pylab_helpers.Gcf.set_active(m)

m.canvas.figure.sca(ax)

return

raise ValueError("Axes instance argument was not found in a figure.")

def gcf():

"Get a reference to the current figure."

figManager = _pylab_helpers.Gcf.get_active()

if figManager is not None:

return figManager.canvas.figure

else:

return figure()为了将面向对象的绘图库包装成只使用函数的调用接口，pyplot模块的内部保存了当前图表以及当前子图等信息。当前的图表和子图可以使用plt.gcf()和plt.gca()获得，分别表示"Get Current Figure"和"Get Current Axes"。在pyplot模块中，许多函数都是对当前的Figure或Axes对象进行处理，比如说：

plt.plot()实际上会通过plt.gca()获得当前的Axes对象ax，然后再调用ax.plot()方法实现真正的绘图。

绘制多子图（快速绘图）

Matplotlib 里的常用类的包含关系为 Figure -> Axes -> (Line2D, Text, etc.)一个Figure对象可以包含多个子图(Axes)，在matplotlib中用Axes对象表示一个绘图区域，可以理解为子图。

可以使用subplot()快速绘制包含多个子图的图表，它的调用形式如下：

subplot(numRows, numCols, plotNum)

subplot将整个绘图区域等分为numRows行* numCols列个子区域，然后plotNum(1<=plotNum<=4且plotNum必须为正整数)按照从左到右，从上到下的顺序对每个子区域进行编号，左上的子区域的编号为1。如果numRows，numCols和plotNum这三个数都小于10的话，可以把它们缩写为一个整数，例如subplot(323)和subplot(3,2,3)是相同的，其中最后一位的3表示在第三象限画图的。subplot在plotNum指定的区域中创建一个轴对象。如果新创建的轴和之前创建的轴重叠的话，之前的轴将被删除。

''' 为了方便快速绘图matplotlib通过pyplot模块提供了一套和MATLAB类似的绘图API，

将众多绘图对象所构成的复杂结构隐藏在这套API内部。

我们只需要调用pyplot模块所提供的函数就可以实现快速绘图以及设置图表的各种细节 '''

''' plt.plot()实际上会通过plt.gca()获得当前的Axes对象ax，然后再调用ax.plot()方法实现真正的绘图。 '''

def learn2():

plt.figure(1) # 创建图表1

plt.figure(2) # 创建图表2

ax1 = plt.subplot(211) # 在图表2中创建子图1

ax2 = plt.subplot(212) # 在图表2中创建子图2

x = np.linspace(0, 3, 100)

for i in xrange(5):

plt.figure(1) # 选择图表1

# plt.plot(x, np.exp(i * x / 3), 'o')

plt.sca(ax1) # 将子图1放进for厘面的plt中

plt.plot(x, np.sin(i * x))

plt.sca(ax2)

plt.plot(x, np.cos(i * x))

plt.show()参考来自：

http://www.voidcn.com/article/p-kdngefxg-bp.html