matplotlib笔记

1.imshow()

matplotlib.pyplot.imshow(Xcmap=Nonenorm=Noneaspect=Noneinterpolation=Nonealpha=Nonevmin=Nonevmax=Noneorigin=Noneextent=Noneshape=filternorm=1filterrad=4.0imlim=resample=Noneurl=None*data=None**kwargs)

(1)cmap

Accent, Accent_r, Blues, Blues_r, BrBG, BrBG_r, BuGn, BuGn_r, BuPu, BuPu_r, CMRmap, CMRmap_r, Dark2, Dark2_r, GnBu, GnBu_r, Greens, Greens_r, Greys, Greys_r, OrRd, OrRd_r, Oranges, Oranges_r, PRGn, PRGn_r, Paired, Paired_r, Pastel1, Pastel1_r, Pastel2, Pastel2_r, PiYG, PiYG_r, PuBu, PuBuGn, PuBuGn_r, PuBu_r, PuOr, PuOr_r, PuRd, PuRd_r, Purples, Purples_r, RdBu, RdBu_r, RdGy, RdGy_r, RdPu, RdPu_r, RdYlBu, RdYlBu_r, RdYlGn, RdYlGn_r, Reds, Reds_r, Set1, Set1_r, Set2, Set2_r, Set3, Set3_r, Spectral, Spectral_r, Wistia, Wistia_r, YlGn, YlGnBu, YlGnBu_r, YlGn_r, YlOrBr, YlOrBr_r, YlOrRd, YlOrRd_r, afmhot, afmhot_r, autumn, autumn_r, binary, binary_r, bone, bone_r, brg, brg_r, bwr, bwr_r, cividis, cividis_r, cool, cool_r, coolwarm, coolwarm_r, copper, copper_r, cubehelix, cubehelix_r, flag, flag_r, gist_earth, gist_earth_r, gist_gray, gist_gray_r, gist_heat, gist_heat_r, gist_ncar, gist_ncar_r, gist_rainbow, gist_rainbow_r, gist_stern, gist_stern_r, gist_yarg, gist_yarg_r, gnuplot, gnuplot2, gnuplot2_r, gnuplot_r, gray, gray_r, hot, hot_r, hsv, hsv_r, inferno, inferno_r, jet, jet_r, magma, magma_r, nipy_spectral, nipy_spectral_r, ocean, ocean_r, pink, pink_r, plasma, plasma_r, prism, prism_r, rainbow, rainbow_r, seismic, seismic_r, spring, spring_r, summer, summer_r, tab10, tab10_r, tab20, tab20_r, tab20b, tab20b_r, tab20c, tab20c_r, terrain, terrain_r, twilight, twilight_r, twilight_shifted, twilight_shifted_r, viridis, viridis_r, winter, winter_r

2.Axis()

xmin,xmax,ymin,ymax=axis()

xmin,xmax,ymin,ymax=axis([xmin,xmax,ymin,ymax])

xmin,xmax,ymin,ymax=axis(option)

xmin,xmax,ymin,ymax=axis(**kwargs)

(1)option : bool or str

ValueDescription

'on'    Turn on axis lines and labels. Same as True.

'off'    Turn off axis lines and labels. Same as False.

'equal' Set equal scaling (i.e., make circles circular) by changing axis limits.

'scaled'    Set equal scaling (i.e., make circles circular) by changing dimensions of the plot box.

'tight'    Set limits just large enough to show all data.

'auto'    Automatic scaling (fill plot box with data).

'normal'    Same as 'auto'; deprecated.

'image'    'scaled' with axis limits equal to data limits.

'square'    Square plot; similar to 'scaled', but initially forcing xmax-xmin = ymax-ymin.

3.cubplot()

subplot(nrows,ncols,index,**kwargs)

subplot(pos,**kwargs)

subplot(ax)

4.plt.rcParams[] 

原文链接:https://www.cnblogs.com/pacino12134/p/9776882.html

5.plot()

color:颜色,linewidth:线宽,linestyle:线条类型,label:图例,marker:数据点的类型,alpha:透明度

原文链接:https://blog.csdn.net/weixin_40683253/article/details/87376085

原文链接:https://blog.csdn.net/sinat_36219858/article/details/79800460

十六进制颜色代码表(文字型):https://blog.csdn.net/sutiesenn/article/details/84962522

6.legend()

原文链接:https://blog.csdn.net/qq_33221533/article/details/81431264

7.time、xlabel、ylabel、xticks、yticks函数:设置坐标轴

        可以调用 xlable() 和 ylabel() 函数分别设置 X 轴、Y 轴的名称,也可以通过 title() 函数设置整个数据图的标题,还可以调用 xticks()、yticks() 函数分别改变 X 轴、Y 轴的刻度值(允许使用文本作为刻度值)。

原文链接:http://c.biancheng.net/view/2705.html

xticks()、yticks() 函数:https://matplotlib.org/api/_as_gen/matplotlib.pyplot.xticks.html?highlight=xticks#matplotlib.pyplot.xticks

(1)matplotlib.pyplot.xticks(ticks = None,labels = None,** kwargs )

(2)matplotlib.pyplot.yticks(ticks=None, labels=None, **kwargs)

8.ion()和ioff()的使用

原文链接:https://blog.csdn.net/zbrwhut/article/details/80625702

9.cla() clf() close()用途

(1).cla() # Clear axis即清除当前图形中的当前活动轴。其他轴不受影响。

(2).clf()  # Clear figure清除所有轴,但是窗口打开,这样它可以被重复使用。

(3).close() # Close a figure window

10.xlim()、ylim()、axis()

原文链接:https://blog.csdn.net/The_Time_Runner/article/details/89928057

11.ax.spines——坐标轴设置

原文链接:https://blog.csdn.net/qq_41011336/article/details/83015986

12.linspace()

原文链接:https://blog.csdn.net/weixin_41042404/article/details/81913901

13.gca()

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。 

原文链接:https://www.cnblogs.com/ymjyqsx/p/7390288.html

14.scatter()散点图

原文链接:https://blog.csdn.net/qq_38486203/article/details/80578260

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