python Plot 画图用法

以下内容全部转载 粘贴复制于：CS青雀，重附连接：https://blog.csdn.net/ztf312/article/details/49933497

仅作自行查阅方便只用！！

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图的存在，让数据变得形象化。无论多么复杂的东西，都是简单的组合。

plot画图时可以设定线条参数。包括：颜色、线型、标记风格。
1）控制颜色
颜色之间的对应关系为
b---blue   c---cyan  g---green    k----black
m---magenta r---red  w---white    y----yellow
有三种表示颜色的方式:
a:用全名  b:16进制如：#FF00FF  c：RGB或RGBA元组（1,0,1,1） d：灰度强度如：‘0.7’
2)控制线型
符号和线型之间的对应关系
-      实线
--     短线
-.     短点相间线
：     虚点线

>>>import matplotlib
 
>>>from pylab import *
>>>help(plot)
Help on function plot in module matplotlib.pyplot:
 
plot(*args, **kwargs)
    Plot lines and/or markers to the
    :class:`~matplotlib.axes.Axes`.  *args* is a variable length
    argument, allowing for multiple *x*, *y* pairs with an
    optional format string.  For example, each of the following is
    legal::
    
        plot(x, y)         # plot x and y using default line style and color
        plot(x, y, 'bo')   # plot x and y using blue circle markers
        plot(y)            # plot y using x as index array 0..N-1
        plot(y, 'r+')      # ditto, but with red plusses
    
    If *x* and/or *y* is 2-dimensional, then the corresponding columns
    will be plotted.
    
    An arbitrary number of *x*, *y*, *fmt* groups can be
    specified, as in::
    
        a.plot(x1, y1, 'g^', x2, y2, 'g-')
    
    Return value is a list of lines that were added.
    
    The following format string characters are accepted to control
    the line style or marker:
    
    ================    ===============================
    character           description
    ================    ===============================
    ``'-'``             solid line style
    ``'--'``            dashed line style
    ``'-.'``            dash-dot line style
    ``':'``             dotted line style
    ``'.'``             point marker
    ``','``             pixel marker
    ``'o'``             circle marker
    ``'v'``             triangle_down marker
    ``'^'``             triangle_up marker
    ``'<'``             triangle_left marker
    ``'>'``             triangle_right marker
    ``'1'``             tri_down marker
    ``'2'``             tri_up marker
    ``'3'``             tri_left marker
    ``'4'``             tri_right marker
    ``'s'``             square marker
    ``'p'``             pentagon marker
    ``'*'``             star marker
    ``'h'``             hexagon1 marker
    ``'H'``             hexagon2 marker
    ``'+'``             plus marker
    ``'x'``             x marker
    ``'D'``             diamond marker
    ``'d'``             thin_diamond marker
    ``'|'``             vline marker
    ``'_'``             hline marker
    ================    ===============================
    
    The following color abbreviations are supported:
    
    ==========  ========
    character   color
    ==========  ========
    'b'         blue
    'g'         green
    'r'         red
    'c'         cyan
    'm'         magenta
    'y'         yellow
    'k'         black
    'w'         white
    ==========  ========
    
    In addition, you can specify colors in many weird and
    wonderful ways, including full names (``'green'``), hex
    strings (``'#008000'``), RGB or RGBA tuples (``(0,1,0,1)``) or
    grayscale intensities as a string (``'0.8'``).  Of these, the
    string specifications can be used in place of a ``fmt`` group,
    but the tuple forms can be used only as ``kwargs``.
    
    Line styles and colors are combined in a single format string, as in
    ``'bo'`` for blue circles.
    
    The *kwargs* can be used to set line properties (any property that has
    a ``set_*`` method).  You can use this to set a line label (for auto
    legends), linewidth, anitialising, marker face color, etc.  Here is an
    example::
    
        plot([1,2,3], [1,2,3], 'go-', label='line 1', linewidth=2)
        plot([1,2,3], [1,4,9], 'rs',  label='line 2')
        axis([0, 4, 0, 10])
        legend()
    
    If you make multiple lines with one plot command, the kwargs
    apply to all those lines, e.g.::
    
        plot(x1, y1, x2, y2, antialised=False)
    
    Neither line will be antialiased.
    
    You do not need to use format strings, which are just
    abbreviations.  All of the line properties can be controlled
    by keyword arguments.  For example, you can set the color,
    marker, linestyle, and markercolor with::
    
        plot(x, y, color='green', linestyle='dashed', marker='o',
             markerfacecolor='blue', markersize=12).  See
             :class:`~matplotlib.lines.Line2D` for details.
    
    The kwargs are :class:`~matplotlib.lines.Line2D` properties:
    
      agg_filter: unknown
      alpha: float (0.0 transparent through 1.0 opaque)         
      animated: [True | False]         
      antialiased or aa: [True | False]         
      axes: an :class:`~matplotlib.axes.Axes` instance         
      clip_box: a :class:`matplotlib.transforms.Bbox` instance         
      clip_on: [True | False]         
      clip_path: [ (:class:`~matplotlib.path.Path`,         :class:`~matplotlib.transforms.Transform`) |         :class:`~matplotlib.patches.Patch` | None ]         
      color or c: any matplotlib color         
      contains: a callable function         
      dash_capstyle: ['butt' | 'round' | 'projecting']         
      dash_joinstyle: ['miter' | 'round' | 'bevel']         
      dashes: sequence of on/off ink in points         
      data: 2D array (rows are x, y) or two 1D arrays         
      drawstyle: [ 'default' | 'steps' | 'steps-pre' | 'steps-mid' | 'steps-post' ]         
      figure: a :class:`matplotlib.figure.Figure` instance         
      fillstyle: ['full' | 'left' | 'right' | 'bottom' | 'top']         
      gid: an id string         
      label: any string         
      linestyle or ls: [ ``'-'`` | ``'--'`` | ``'-.'`` | ``':'`` | ``'None'`` | ``' '`` | ``''`` ]         and any drawstyle in combination with a linestyle, e.g. ``'steps--'``.         
      linewidth or lw: float value in points         
      lod: [True | False]         
      marker: [ ``7`` | ``4`` | ``5`` | ``6`` | ``'o'`` | ``'D'`` | ``'h'`` | ``'H'`` | ``'_'`` | ``''`` | ``None`` | ``'None'`` | ``' '`` | ``'8'`` | ``'p'`` | ``','`` | ``'+'`` | ``'.'`` | ``'s'`` | ``'*'`` | ``'d'`` | ``3`` | ``0`` | ``1`` | ``2`` | ``'1'`` | ``'3'`` | ``'4'`` | ``'2'`` | ``'v'`` | ``'<'`` | ``'>'`` | ``'^'`` | ``'|'`` | ``'x'`` | ``'$...$'`` | *tuple* | *Nx2 array* ]
      markeredgecolor or mec: any matplotlib color         
      markeredgewidth or mew: float value in points         
      markerfacecolor or mfc: any matplotlib color         
      markerfacecoloralt or mfcalt: any matplotlib color         
      markersize or ms: float         
      markevery: None | integer | (startind, stride)
      picker: float distance in points or callable pick function         ``fn(artist, event)``         
      pickradius: float distance in points         
      rasterized: [True | False | None]         
      snap: unknown
      solid_capstyle: ['butt' | 'round' |  'projecting']         
      solid_joinstyle: ['miter' | 'round' | 'bevel']         
      transform: a :class:`matplotlib.transforms.Transform` instance         
      url: a url string         
      visible: [True | False]         
      xdata: 1D array         
      ydata: 1D array         
      zorder: any number         
    
    kwargs *scalex* and *scaley*, if defined, are passed on to
    :meth:`~matplotlib.axes.Axes.autoscale_view` to determine
    whether the *x* and *y* axes are autoscaled; the default is
    *True*.
    
    Additional kwargs: hold = [True|False] overrides default hold state

自用小代码：

from matplotlib import pyplot as plt

filename = './loss.txt'
step, v_loss, gan = [], [], []
j = 0
i = 1
# 相比open(),with open()不用手动调用close()方法
with open(filename, 'r') as f:
    # 将txt中的数据逐行存到列表lines里 lines的每一个元素对应于txt中的一行。然后将每个元素中的不同信息提取出来
    lines = f.readlines()
    # i变量，由于这个txt存储时有空行，所以增只读偶数行，主要看txt文件的格式，一般不需要
    # j用于判断读了多少条，step为画图的X轴
    for line in lines:
        if i > 1600:
            step.append(30 * i)
            v_loss.append(float(line))
            gan.append(float(0.2))
            i = i + 1
        else:
            i = i + 1

        # temp = line.split('loss ')
        # t = temp[1].split(',')
        # step.append(30*j)
        # j = j + 1
        # v_loss.append(float(line))
        # i = i + 1

fig = plt.figure(figsize=(10, 5))  # 创建绘图窗口，并设置窗口大小
# 画第一张图
ax1 = fig.add_subplot(111)  # 将画面分割为2行1列选第一个
ax1.plot(step, v_loss, 'blue', label='Loss', linewidth=1)  # 画dis-loss的值，颜色红
ax1.legend(loc='upper right')  # 绘制图例，plot()中的label值
ax1.set_xlabel('step')  # 设置X轴名称
ax1.set_ylabel('Training loss')  # 设置Y轴名称
# ax1.set_title('Training Loss for U-Net')
# plt.show()

# 画第二张图
# ax2 = fig.add_subplot(212)  # 将画面分割为2行1列选第二个
# ax2.plot(step, gan, 'blue', label='gan')  # 画gan-loss的值，颜色蓝
# ax2.legend(loc='upper right')  # loc为图例位置，设置在右上方，（右下方为lower right）
# ax2.set_xlabel('step')
# ax2.set_ylabel('Generator-loss')
# plt.show()  # 显示绘制的图

# plt.figure()
# plt.plot(step, dis, 'red', label='dis')
plt.plot(step, gan, 'red', label='y=0.2', linewidth=3, linestyle="--")
plt.legend()
plt.show()