【Python】【matplotlib】面向对象方式绘图

不用面向对象方式画图，优点在于代码简单，缺点在于画多图和多子图附带各种标注时，代码很乱。
当然，更复杂和标注清晰的图，大部分需求场景是成熟的可视化展示，这种情况下用echart更好。

各个对象

plt.figure()

先生成一个figure，在figure上生成一个Axes，在Axes上面生成line（plot）,或者生成patch(bar&hist)

它们之间的关系参照这段代码:

f.axes[0].lines[0]

获取的方法1

f=plt.gcf()#get current figurea=plt.gca()#get current axes

获取的方法2

f=plt.gcf()a=plt.getp(f,'axes')[0]l=plt.getp(f,'lines')[0]

共有属性

这些对象共有的一些属性：

关键字 解释 alpha 透明度，0~1 animated 布尔值，用于绘制动画效果 axes 所在的axes clip_box 对象的裁剪框 clip_on 是否裁剪 clip_path 裁剪的路径 contains 判断指定点是否在对象上的函数 figure 对象所在的figure label 文本标签 picker 用来控制对象的选取 transform 控制偏移、旋转、缩放等 visible 是否可见 zorder 控制绘图顺序,any number

figure

f=plt.gcf()f=plt.figure(1)

figure的类型是：

<class 'matplotlib.figure.Figure'>

figure下的属性（用plt.getp(f)获取）

agg_filter = Nonealpha = Noneanimated = Falseaxes = [<matplotlib.axes._subplots.AxesSubplot>]children = [<matplotlib.patches.Rectangle>]clip_box = Noneclip_on = Trueclip_path = Nonecontains = Nonedefault_bbox_extra_artists = [<matplotlib.axes._subplots.AxesSubplot>]dpi = 72.0edgecolor = (1.0, 1.0, 1.0, 0.0)facecolor = (1.0, 1.0, 1.0, 0.0)figheight = 4.0figure = Nonefigwidth = 6.0frameon = Truegid = Nonelabel =path_effects = []picker = Nonerasterized = Nonesize_inches = [ 6.  4.]sketch_params = Nonesnap = Nonetight_layout = Falsetransform = IdentityTransform()transformed_clip_path_and_affine = (None, None)url = Nonevisible = Truewindow_extent = TransformedBbox(Bbox([[0.0, 0.0], [6.0, 4.0]]))zorder = 0

一些解释：

属性 意义 axes Axes对象列表 patch 作为背景的Rectangle对象 images FigureImage对象列表，用于显示图像 lines Line2D对象列表 patches Patch对象列表 text Text对象列表，用于显示文字

Axes

对象信息：

<matplotlib.axes._subplots.AxesSubplot at 0x263c9ba9320>

可以有两种方法获取

a1=plt.getp(f,'axes')#生成的是一个lista2=plt.gca()#当前激活的axes

axes对象的属性：(用plt.getp(a2)获取)

adjustable = boxagg_filter = Nonealpha = Noneanchor = Canimated = Falseaspect = autoautoscale_on = Falseautoscalex_on = Trueautoscaley_on = Falseaxes = Axes(0.125,0.125;0.775x0.755)axes_locator = Noneaxis_bgcolor = (1.0, 1.0, 1.0, 1)axisbelow = linechildren = [<matplotlib.lines.Line2D>]clip_box = Noneclip_on = Trueclip_path = Nonecontains = Nonecursor_props = (1, (0.0, 0.0, 0.0, 1))data_ratio = 0.36363636363636365default_bbox_extra_artists = [<matplotlib.lines.Line2D>]facecolor = (1.0, 1.0, 1.0, 1)fc = (1.0, 1.0, 1.0, 1)figure = Figure(432x288)frame_on = Truegeometry = (1, 1, 1)gid = Noneimages = <a list of 0 AxesImage objects>label =legend = Nonelegend_handles_labels = ([], [])lines = <a list of 34 Line2D objects>navigate = Truenavigate_mode = Nonepath_effects = []picker = Noneposition = Bbox(x0=0.125, y0=0.125, x1=0.9, y1=0.88)rasterization_zorder = Nonerasterized = Nonerenderer_cache = Noneshared_x_axes = <matplotlib.cbook.Groupershared_y_axes = <matplotlib.cbook.Groupersketch_params = Nonesnap = Nonesubplotspec = <matplotlib.gridspec.SubplotSpectitle = Pyplottransform = IdentityTransform()transformed_clip_path_and_affine = (None, None)url = Nonevisible = Truewindow_extent = Bbox(x0=50.5, y0=32.5, x1=392.3, y1=256.94)xaxis = XAxis(54.000000,36.000000)xaxis_transform = BlendedGenericTransform(CompositeGenericTransform(...))xbound = (-0.30000000000000004, 6.2999999999999998)xgridlines = <a list of 9 Line2D xgridline objects>xlabel = Time(s)xlim = (-0.30000000000000004, 6.2999999999999998)xmajorticklabels = <a list of 9 Text xticklabel objects>xminorticklabels = <a list of 0 Text xticklabel objects>xscale = linearxticklabels = <a list of 9 Text xticklabel objects>xticklines = <a list of 18 Text xtickline objects>xticks = [-1.  0.  1.  2.  3.  4.]...yaxis = YAxis(54.000000,36.000000)yaxis_transform = BlendedGenericTransform(BboxTransformTo(Transforme...))ybound = (-1.2, 1.2)ygridlines = <a list of 7 Line2D ygridline objects>ylabel = Voltylim = (-1.2, 1.2)ymajorticklabels = <a list of 7 Text yticklabel objects>yminorticklabels = <a list of 0 Text yticklabel objects>yscale = linearyticklabels = <a list of 7 Text yticklabel objects>yticklines = <a list of 14 Line2D ytickline objects>yticks = [-1.5 -1.  -0.5  0.   0.5  1. ]...zorder = 0

参数 意义 xlabel, ylabel X, Y轴的标题文字 title 标题 xlim, ylim X, Y轴的范围 legend 显示图示

Axes的方法

显示legend：ax1.legend()
自动调整横纵坐标：ax.autoscale_view()
不显示坐标轴：ax.set_axis_off()

axes对象可以包含的对象

Axes方法 所创建的对象 添加进的列表 annotate Annotate texts bars Rectangle patches errorbar Line2D,Rectangle lines,patches fill Polygon patches hist Rectangle patches imshow AxesImage images legend Legend legends plot Line2D lines scatter PolygonCollection Collections text Text texts

line

对象信息：

<matplotlib.lines.Line2D at 0x263c9fc0a20>

获取方法类似

l=plt.getp(a,'lines')#是一个listl=plt.plot(...)#这个可以注意一下l=plt.plot(x,y,label="$sin(x)$",color='red',linewidth=2)#可以直接在plot中配置参数

获取line属性的方法

line=plt.plot(x,y)plt.getp(line[0],'color')plt.setp(line[0],'color','r')plt.setp(line,'color','r')#setp可以对一组对象进行操作，getp只能操作一个

line有这些属性：

agg_filter = Nonealpha = Noneanimated = Falseantialiased or aa = Trueaxes = Axes(0.125,0.125;0.775x0.755)children = []clip_box = TransformedBbox(Bbox([[0.0, 0.0], [1.0, 1.0]]), Co...)clip_on = Trueclip_path = Nonecolor or c = #1f77b4contains = Nonedash_capstyle = buttdash_joinstyle = rounddata = (array([ 0.        ,  0.66666667,  1.33333333,  2....]))drawstyle = defaultfigure = Figure(432x288)fillstyle = fullgid = Nonelabel = $cos(x^2)$linestyle or ls = -linewidth or lw = 1.5marker = +markeredgecolor or mec = #1f77b4markeredgewidth or mew = 1.0markerfacecolor or mfc = #1f77b4markerfacecoloralt or mfcalt = nonemarkersize or ms = 6.0markevery = Nonepath = Path(array([[ 0., -0.],[ 0...]]))path_effects = []picker = Nonepickradius = 5rasterized = Nonesketch_params = Nonesnap = Nonesolid_capstyle = projectingsolid_joinstyle = roundtransform = CompositeGenericTransform(TransformWrapper(Blended...))transformed_clip_path_and_affine = (None, None)url = Nonevisible = Truexdata = [ 0.          0.66666667  1.33333333  2.          ]xydata = [[ 0.         -0.        ]  [ 0.66666667 -0.618369.]]ydata = [-0.         -0.6183698  -0.9719379  -0.90929743 -...]zorder = 2

属性 解释 label 给plot的曲线一个标签名字，可以使用LaTeX color 给曲线指定颜色，可以是英文单词’red’等，也可以是16进制数’##ff0000’,也可以用0~1tuple(1.0,0,0) linewidth 曲线宽度，可以不是整数

linestyle

character description '-' solid line style '--' dashed line style '-.' dash-dot line style ':' dotted line style

marker

character description '.' point marker点 ',' pixel marker一个像素点 'o' circle marker实心圆 '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方块 'p' pentagon marker五边形 '*' star marker五角星 'h' hexagon1 marker六边形 'H' hexagon2 marker横六边形 '+' plus marker 'x' x marker 'D' diamond marker菱形 'd' thin_diamond marker瘦菱形 “’ ‘“ '_' hline marker横线

color

character color ‘b’ blue ‘g’ green ‘r’ red ‘c’ cyan ‘m’ magenta ‘y’ yellow ‘k’ black ‘w’ white

line的其他参数

antialiased or aa: [True | False]axes: an :class:`~matplotlib.axes.Axes` instanceclip_box: a :class:`matplotlib.transforms.Bbox` instanceclip_on: [True | False]clip_path: [ (:class:`~matplotlib.path.Path`, :class:`~matplotlib.transforms.Transform`) | :class:`~matplotlib.patches.Patch` | None ]contains: a callable functiondash_capstyle: ['butt' | 'round' | 'projecting']dash_joinstyle: ['miter' | 'round' | 'bevel']dashes: sequence of on/off ink in pointsdrawstyle: ['default' | 'steps' | 'steps-pre' | 'steps-mid' | 'steps-post']figure: a :class:`matplotlib.figure.Figure` instancefillstyle: ['full' | 'left' | 'right' | 'bottom' | 'top' | 'none']gid: an id stringlabel: string or anything printable with '%s' conversion.linestylemarkeredgecolor or mec: any matplotlib colormarkeredgewidth or mew: float value in pointsmarkerfacecolor or mfc: any matplotlib colormarkerfacecoloralt or mfcalt: any matplotlib colormarkersize or ms: floatmarkevery: [None | int | length-2 tuple of int | slice | list/array of int | float | length-2 tuple of float]path_effects: unknownpicker: float distance in points or callable pick function ``fn(artist, event)``pickradius: float distance in pointsrasterized: [True | False | None]sketch_params: unknownsnap: unknownsolid_capstyle: ['butt' | 'round' |  'projecting']solid_joinstyle: ['miter' | 'round' | 'bevel']transform: a :class:`matplotlib.transforms.Transform` instanceurl: a url stringxdata: 1D arrayydata: 1D array

patch

bar()和hist()都是创建Patch对象列表
每个Patch列表中

n,bins,rects=ax.hist(...)

• 这里的rects是
• rects[0]是

import matplotlib.pyplot as pltfrom scipy.stats import normf1 = plt.figure(1)ax = plt.subplot(111)n, bins, rects = ax.hist(norm.rvs(loc=0, scale=1, size=100))rects

Axis

fig = plt.figure(1)ax = fig.add_subplot(111)line=ax.plot([1,2,3,4,5])xaxis=ax.xaxisplt.getp(xaxis)

可以获得它们的属性：

agg_filter = Nonealpha = Noneanimated = Falseaxes = Axes(0.125,0.11;0.775x0.77)children = [<matplotlib.text.Text object at 0x0000020033F2F78...>]clip_box = TransformedBbox(Bbox([[0.0, 0.0], [1.0, 1.0]]), Co...)clip_on = Trueclip_path = Nonecontains = Nonedata_interval = [ 0.  4.]figure = Figure(640x480)gid = Nonegridlines = <a list of 11 Line2D gridline objects>label = Text(0.5,0,'')label_position = bottomlabel_text =major_formatter = <matplotlib.ticker.ScalarFormatter>major_locator = <matplotlib.ticker.AutoLocator>major_ticks = [<matplotlib.axis.XTick>]majorticklabels = <a list of 11 Text major ticklabel objects>majorticklines = <a list of 22 Line2D ticklines objects>majorticklocs = [-0.5  0.   0.5  1.   1.5  2. ]...minor_formatter = <matplotlib.ticker.NullFormatter>minor_locator = <matplotlib.ticker.NullLocator>minor_ticks = []minorticklabels = <a list of 0 Text minor ticklabel objects>minorticklines = <a list of 0 Line2D ticklines objects>minorticklocs = []minpos = 1.0offset_text = Text(1,0,'')path_effects = []picker = Nonepickradius = 15rasterized = Nonescale = linearsketch_params = Nonesmart_bounds = Falsesnap = Nonetick_padding = 3.5tick_space = 11ticklabels = <a list of 11 Text major ticklabel objects>ticklines = <a list of 22 Line2D ticklines objects>ticklocs = [-0.5  0.   0.5  1.   1.5  2. ]...ticks_position = bottomtransform = IdentityTransform()transformed_clip_path_and_affine = (None, None)units = Noneurl = Noneview_interval = [-0.2  4.2]visible = Truezorder = 0

属性 意义 ticklocs 刻度位置 ticklabels 刻度对应的文字

annotate

用来绘制带箭头的注释文字

annotate(s,xy,xytext,xycoords='data',textcoords='data',arrowprops=None)

• s:注释文本
• xy:箭头处的坐标
• xytext:注释文本的坐标
• xycoords&textcoords都是字符串, 解释在下表

属性值 解释 figure points 以点为单位的坐标，图表左下角的坐标(0,0) figure pixels 以像素为单位的坐标，图表左下角为(0,0) figure fraction 图表坐标系中的坐标，左下角是(0,0)，右上角是(1,1) axes points 以点为单位的坐标，子图左下角的坐标(0,0) axes pixels 以像素为单位的坐标，子图左下角的坐标(0,0) axes fraction 子图坐标系中的坐标,左下角是(0,0),右上角是(1,1) data 数据坐标系中的坐标 offset points 以点为单位，相对于点xy的坐标 polar 数据坐标系中的极坐标

test

用来绘制文字

ax.text(x,y,string,fontname='STKaiti',fontsize=20,color='r',transform=ax.transData)#数据坐标ax.text(x,y,string,fontname='STKaiti',fontsize=20,color='r',transform=ax.transAxes)#Axes内坐标，左下是(0,0)，右上是(1,1)fig.text(x,y,string,fontname='STKaiti',fontsize=20,color='r',transform=ax.transData)#数据坐标fig.text(x,y,string,fontname='STKaiti',fontsize=20,color='r',transform=ax.transAxes)#Figure内坐标，左下是(0,0)，右上是(1,1)

• fontname：字体，参见这里