簡介：matplotlib 是Python最著名的繪相簿，它提供了一整套和matlab相似的命令API，十分適合互動式地行製圖。而且也可以方便地將它作為繪

圖控制元件，嵌入GUI應用程式中。

在Python中使用matplotlib.pyplot快速繪圖

下面是matplotlib庫所給的介紹

"""
This is an object-oriented plotting library.
 這是面向物件的繪相簿
A procedural interface is provided by the companion pyplot module,（程式介面直接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模組裡面有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.

"""
 

閱讀後，我們明白matplotlib實際上是一套面向物件的繪相簿，它所繪製的圖表中的每個繪圖元素，例如線條Line2D、文字Text、刻度等在記憶體中都有一個物件與之對應。

我們只需要呼叫pyplot模組所提供的函式就可以實現快速繪圖以及設定圖表的各種細節。

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()

為了將面向物件的繪相簿包裝成只使用函式的呼叫介面，pyplot模組的內部儲存了當前圖表以及當前子圖等資訊。當前的圖表和子圖可以使用plt.gcf()和plt.gca()獲得，分別表示"Get Current Figure"和"Get Current Axes"。在pyplot模組中，許多函式都是對當前的Figure或Axes物件進行處理，比如說：

plt.plot()實際上會通過plt.gca()獲得當前的Axes物件ax，然後再呼叫ax.plot()方法實現真正的繪圖。

繪製多子圖（快速繪圖）

Matplotlib 裡的常用類的包含關係為 Figure -> Axes -> (Line2D, Text, etc.)一個Figure物件可以包含多個子圖(Axes)，在matplotlib中用Axes物件表示一個繪圖區域，可以理解為子圖。
可以使用subplot()快速繪製包含多個子圖的圖表，它的呼叫形式如下：
subplot(numRows, numCols, plotNum)
subplot將整個繪圖區域等分為numRows行* numCols列個子區域，然後plotNum(1<=plotNum<=4且plotNum必須為正整數)按照從左到右，從上到下的順序對每個子區域進行編號，左上的子區域的編號為1。如果numRows，numCols和plotNum這三個數都小於10的話，可以把它們縮寫為一個整數，例如subplot(323)和subplot(3,2,3)是相同的，其中最後一位的3表示在第三象限畫圖的。subplot在plotNum指定的區域中建立一個軸物件。如果新建立的軸和之前建立的軸重疊的話，之前的軸將被刪除。

'''  為了方便快速繪圖matplotlib通過pyplot模組提供了一套和MATLAB類似的繪圖API，
將眾多繪圖物件所構成的複雜結構隱藏在這套API內部。
我們只需要呼叫pyplot模組所提供的函式就可以實現快速繪圖以及設定圖表的各種細節  '''
''' plt.plot()實際上會通過plt.gca()獲得當前的Axes物件ax，然後再呼叫ax.plot()方法實現真正的繪圖。 '''
def learn2():
    plt.figure(1)  # 建立圖表1
    plt.figure(2)  # 建立圖表2
    ax1 = plt.subplot(211)  # 在圖表2中建立子圖1
    ax2 = plt.subplot(212)  # 在圖表2中建立子圖2
    x = np.linspace(0, 3, 100)
    for i in xrange(5):
        plt.figure(1)  # 選擇圖表1
        # plt.plot(x, np.exp(i * x / 3), 'o')
        plt.sca(ax1) # 將子圖1放進for釐面的plt中
        plt.plot(x, np.sin(i * x))
        plt.sca(ax2)
        plt.plot(x, np.cos(i * x))
    plt.show()

參考來自：http://blog.csdn.net/ywjun0919/article/details/8692018