1. Pyplot Simple

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import matplotlib.pyplot as plt plt.plot([1,2,3,4]) plt.ylabel('some numbers') plt.show()

2. Pyplot Formatstr

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import matplotlib.pyplot as plt plt.plot([1,2,3,4], [1,4,9,16], 'ro') plt.axis([0, 6, 0, 20]) plt.show()

3. Pyplot Three

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import numpy as np import matplotlib.pyplot as plt# evenly sampled time at 200ms intervals t = np.arange(0., 5., 0.2)# red dashes, blue squares and green triangles plt.plot(t, t, 'r--', t, t**2, 'bs', t, t**3, 'g^') plt.show()

4. Fig X

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import numpy as np import matplotlib.pyplot as plt import matplotlib.lines as linesfig = plt.figure()l1 = lines.Line2D([0, 1], [0, 1], transform=fig.transFigure, figure=fig)l2 = lines.Line2D([0, 1], [1, 0], transform=fig.transFigure, figure=fig)fig.lines.extend([l1, l2])plt.show()

5. Whats New 0.98.4 Legend

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import matplotlib.pyplot as plt import numpy as npax = plt.subplot(111) t1 = np.arange(0.0, 1.0, 0.01) for n in [1, 2, 3, 4]: plt.plot(t1, t1**n, label="n=%d"%(n,))leg = plt.legend(loc='best', ncol=2, mode="expand", shadow=True, fancybox=True) leg.get_frame().set_alpha(0.5)plt.show()

6. Pyplot Two Subplots

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import numpy as np import matplotlib.pyplot as pltdef f(t): return np.exp(-t) * np.cos(2*np.pi*t)t1 = np.arange(0.0, 5.0, 0.1) t2 = np.arange(0.0, 5.0, 0.02)plt.figure(1) plt.subplot(211) plt.plot(t1, f(t1), 'bo', t2, f(t2), 'k')plt.subplot(212) plt.plot(t2, np.cos(2*np.pi*t2), 'r--') plt.show()

7. Annotating a plot
【Pyplot】此示例演示如何用指向提供的坐标的箭头对绘图进行批注。我们修改箭头的默认值，以 "缩小" 它。


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import numpy as np import matplotlib.pyplot as pltfig, ax = plt.subplots()t = np.arange(0.0, 5.0, 0.01) s = np.cos(2*np.pi*t) line, = ax.plot(t, s, lw=2)ax.annotate('local max', xy=(2, 1), xytext=(3, 1.5), arrowprops=dict(facecolor='black', shrink=0.05), ) ax.set_ylim(-2, 2) plt.show()

8. Whats New 0.99 Mplot3d

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import numpy as np import matplotlib.pyplot as plt from matplotlib import cm from mpl_toolkits.mplot3d import Axes3DX = np.arange(-5, 5, 0.25) Y = np.arange(-5, 5, 0.25) X, Y = np.meshgrid(X, Y) R = np.sqrt(X**2 + Y**2) Z = np.sin(R)fig = plt.figure() ax = Axes3D(fig) ax.plot_surface(X, Y, Z, rstride=1, cstride=1, cmap=cm.viridis)plt.show()

9. Whats New 0.98.4 Fill Between

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import matplotlib.pyplot as plt import numpy as npx = np.arange(0.0, 2, 0.01) y1 = np.sin(2*np.pi*x) y2 = 1.2*np.sin(4*np.pi*x)fig, ax = plt.subplots() ax.plot(x, y1, x, y2, color='black') ax.fill_between(x, y1, y2, where=y2>y1, facecolor='green') ax.fill_between(x, y1, y2, where=y2<=y1, facecolor='red') ax.set_title('fill between where')plt.show()

10. Pyplot Mathtext

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import numpy as np import matplotlib.pyplot as plt t = np.arange(0.0, 2.0, 0.01) s = np.sin(2*np.pi*t)plt.plot(t,s) plt.title(r'$\alpha_i > \beta_i$', fontsize=20) plt.text(1, -0.6, r'$\sum_{i=0}^\infty x_i$', fontsize=20) plt.text(0.6, 0.6, r'$\mathcal{A}\mathrm{sin}(2 \omega t)$', fontsize=20) plt.xlabel('time (s)') plt.ylabel('volts (mV)') plt.show()

11. Dollar Ticks

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import numpy as np import matplotlib.pyplot as plt import matplotlib.ticker as ticker# Fixing random state for reproducibility np.random.seed(19680801)fig, ax = plt.subplots() ax.plot(100*np.random.rand(20))formatter = ticker.FormatStrFormatter('$%1.2f') ax.yaxis.set_major_formatter(formatter)for tick in ax.yaxis.get_major_ticks(): tick.label1On = False tick.label2On = True tick.label2.set_color('green')plt.show()

12. Pyplot Text

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import numpy as np import matplotlib.pyplot as plt# Fixing random state for reproducibility np.random.seed(19680801)mu, sigma = 100, 15 x = mu + sigma * np.random.randn(10000)# the histogram of the data n, bins, patches = plt.hist(x, 50, density=True, facecolor='g', alpha=0.75)plt.xlabel('Smarts') plt.ylabel('Probability') plt.title('Histogram of IQ') plt.text(60, .025, r'$\mu=100,\ \sigma=15$') plt.axis([40, 160, 0, 0.03]) plt.grid(True) plt.show()

13. Fig Axes Labels Simple

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import numpy as np import matplotlib.pyplot as pltfig = plt.figure() fig.subplots_adjust(top=0.8) ax1 = fig.add_subplot(211) ax1.set_ylabel('volts') ax1.set_title('a sine wave')t = np.arange(0.0, 1.0, 0.01) s = np.sin(2*np.pi*t) line, = ax1.plot(t, s, color='blue', lw=2)# Fixing random state for reproducibility np.random.seed(19680801)ax2 = fig.add_axes([0.15, 0.1, 0.7, 0.3]) n, bins, patches = ax2.hist(np.random.randn(1000), 50, facecolor='yellow', edgecolor='yellow') ax2.set_xlabel('time (s)')plt.show()

14. Fig Axes Customize Simple

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import numpy as np import matplotlib.pyplot as plt

plt.figure 创建一个 matplotlib.figure.Figure 实例

fig = plt.figure() rect = fig.patch # a rectangle instance rect.set_facecolor('lightgoldenrodyellow')ax1 = fig.add_axes([0.1, 0.3, 0.4, 0.4]) rect = ax1.patch rect.set_facecolor('lightslategray')for label in ax1.xaxis.get_ticklabels(): # label is a Text instance label.set_color('red') label.set_rotation(45) label.set_fontsize(16)for line in ax1.yaxis.get_ticklines(): # line is a Line2D instance line.set_color('green') line.set_markersize(25) line.set_markeredgewidth(3)plt.show()

15. Annotation Polar

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import numpy as np import matplotlib.pyplot as pltfig = plt.figure() ax = fig.add_subplot(111, polar=True) r = np.arange(0,1,0.001) theta = 2 * 2*np.pi * r line, = ax.plot(theta, r, color='#ee8d18', lw=3)ind = 800 thisr, thistheta = r[ind], theta[ind] ax.plot([thistheta], [thisr], 'o') ax.annotate('a polar annotation', xy=(thistheta, thisr),# theta, radius xytext=(0.05, 0.05),# fraction, fraction textcoords='figure fraction', arrowprops=dict(facecolor='black', shrink=0.05), horizontalalignment='left', verticalalignment='bottom', ) plt.show()

16. Align Ylabels

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import numpy as np import matplotlib.pyplot as pltbox = dict(facecolor='yellow', pad=5, alpha=0.2)fig, ((ax1, ax2), (ax3, ax4)) = plt.subplots(2, 2) fig.subplots_adjust(left=0.2, wspace=0.6)# Fixing random state for reproducibility np.random.seed(19680801)ax1.plot(2000*np.random.rand(10)) ax1.set_title('ylabels not aligned') ax1.set_ylabel('misaligned 1', bbox=box) ax1.set_ylim(0, 2000)ax3.set_ylabel('misaligned 2',bbox=box) ax3.plot(np.random.rand(10))labelx = -0.3# axes coordsax2.set_title('ylabels aligned') ax2.plot(2000*np.random.rand(10)) ax2.set_ylabel('aligned 1', bbox=box) ax2.yaxis.set_label_coords(labelx, 0.5) ax2.set_ylim(0, 2000)ax4.plot(np.random.rand(10)) ax4.set_ylabel('aligned 2', bbox=box) ax4.yaxis.set_label_coords(labelx, 0.5)plt.show()

17. Whats New 0.99 Axes Grid

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import numpy as np import matplotlib.pyplot as plt from mpl_toolkits.axes_grid1.axes_rgb import RGBAxesdef get_demo_image(): # prepare image delta = 0.5extent = (-3, 4, -4, 3) x = np.arange(-3.0, 4.001, delta) y = np.arange(-4.0, 3.001, delta) X, Y = np.meshgrid(x, y) Z1 = np.exp(-X**2 - Y**2) Z2 = np.exp(-(X - 1)**2 - (Y - 1)**2) Z = (Z1 - Z2) * 2return Z, extentdef get_rgb(): Z, extent = get_demo_image()Z[Z < 0] = 0. Z = Z / Z.max()R = Z[:13, :13] G = Z[2:, 2:] B = Z[:13, 2:]return R, G, Bfig = plt.figure(1) ax = RGBAxes(fig, [0.1, 0.1, 0.8, 0.8])r, g, b = get_rgb() kwargs = dict(origin="lower", interpolation="nearest") ax.imshow_rgb(r, g, b, **kwargs)ax.RGB.set_xlim(0., 9.5) ax.RGB.set_ylim(0.9, 10.6)plt.draw() plt.show()

18. Text Commands

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import matplotlib.pyplot as pltfig = plt.figure() fig.suptitle('bold figure suptitle', fontsize=14, fontweight='bold')ax = fig.add_subplot(111) fig.subplots_adjust(top=0.85) ax.set_title('axes title')ax.set_xlabel('xlabel') ax.set_ylabel('ylabel')ax.text(3, 8, 'boxed italics text in data coords', style='italic', bbox={'facecolor':'red', 'alpha':0.5, 'pad':10})ax.text(2, 6, r'an equation: $E=mc^2$', fontsize=15)ax.text(3, 2, u'unicode: Institut f\374r Festk\366rperphysik')ax.text(0.95, 0.01, 'colored text in axes coords', verticalalignment='bottom', horizontalalignment='right', transform=ax.transAxes, color='green', fontsize=15)ax.plot([2], [1], 'o') ax.annotate('annotate', xy=(2, 1), xytext=(3, 4), arrowprops=dict(facecolor='black', shrink=0.05))ax.axis([0, 10, 0, 10])plt.show()

19. Whats New 1 Subplot3d

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from mpl_toolkits.mplot3d.axes3d import Axes3D from matplotlib import cm #from matplotlib.ticker import LinearLocator, FixedLocator, FormatStrFormatter import matplotlib.pyplot as plt import numpy as npfig = plt.figure()ax = fig.add_subplot(1, 2, 1, projection='3d') X = np.arange(-5, 5, 0.25) Y = np.arange(-5, 5, 0.25) X, Y = np.meshgrid(X, Y) R = np.sqrt(X**2 + Y**2) Z = np.sin(R) surf = ax.plot_surface(X, Y, Z, rstride=1, cstride=1, cmap=cm.jet, linewidth=0, antialiased=False) ax.set_zlim3d(-1.01, 1.01)#ax.w_zaxis.set_major_locator(LinearLocator(10)) #ax.w_zaxis.set_major_formatter(FormatStrFormatter('%.03f'))fig.colorbar(surf, shrink=0.5, aspect=5)from mpl_toolkits.mplot3d.axes3d import get_test_data ax = fig.add_subplot(1, 2, 2, projection='3d') X, Y, Z = get_test_data(0.05) ax.plot_wireframe(X, Y, Z, rstride=10, cstride=10)plt.show()

20. Auto Subplots Adjust

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import matplotlib.pyplot as plt import matplotlib.transforms as mtransforms fig = plt.figure() ax = fig.add_subplot(111) ax.plot(range(10)) ax.set_yticks((2,5,7)) labels = ax.set_yticklabels(('really, really, really', 'long', 'labels'))def on_draw(event): bboxes = [] for label in labels: bbox = label.get_window_extent() # the figure transform goes from relative coords->pixels and we # want the inverse of that bboxi = bbox.inverse_transformed(fig.transFigure) bboxes.append(bboxi)# this is the bbox that bounds all the bboxes, again in relative # figure coords bbox = mtransforms.Bbox.union(bboxes) if fig.subplotpars.left < bbox.width: # we need to move it over fig.subplots_adjust(left=1.1*bbox.width) # pad a little fig.canvas.draw() return Falsefig.canvas.mpl_connect('draw_event', on_draw)plt.show()

21. Annotate Transform

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import numpy as np import matplotlib.pyplot as pltx = np.arange(0, 10, 0.005) y = np.exp(-x/2.) * np.sin(2*np.pi*x)fig = plt.figure() ax = fig.add_subplot(111) ax.plot(x, y) ax.set_xlim(0, 10) ax.set_ylim(-1, 1)xdata, ydata = https://www.it610.com/article/5, 0 xdisplay, ydisplay = ax.transData.transform_point((xdata, ydata))bbox = dict(boxstyle="round", fc="0.8") arrowprops = dict( arrowstyle = "->", connectionstyle = "angle,angleA=0,angleB=90,rad=10")offset = 72 ax.annotate('data = https://www.it610.com/article/(%.1f, %.1f)'%(xdata, ydata), (xdata, ydata), xytext=(-2*offset, offset), textcoords='offset points', bbox=bbox, arrowprops=arrowprops)disp = ax.annotate('display = (%.1f, %.1f)'%(xdisplay, ydisplay), (xdisplay, ydisplay), xytext=(0.5*offset, -offset), xycoords='figure pixels', textcoords='offset points', bbox=bbox, arrowprops=arrowprops)plt.show()

22. Whats New 0.99 Spines

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import matplotlib.pyplot as plt import numpy as npdef adjust_spines(ax,spines): for loc, spine in ax.spines.items(): if loc in spines: spine.set_position(('outward',10)) # outward by 10 points else: spine.set_color('none') # don't draw spine# turn off ticks where there is no spine if 'left' in spines: ax.yaxis.set_ticks_position('left') else: # no yaxis ticks ax.yaxis.set_ticks([])if 'bottom' in spines: ax.xaxis.set_ticks_position('bottom') else: # no xaxis ticks ax.xaxis.set_ticks([])fig = plt.figure()x = np.linspace(0,2*np.pi,100) y = 2*np.sin(x)ax = fig.add_subplot(2,2,1) ax.plot(x,y) adjust_spines(ax,['left'])ax = fig.add_subplot(2,2,2) ax.plot(x,y) adjust_spines(ax,[])ax = fig.add_subplot(2,2,3) ax.plot(x,y) adjust_spines(ax,['left','bottom'])ax = fig.add_subplot(2,2,4) ax.plot(x,y) adjust_spines(ax,['bottom'])plt.show()

23. Compound Path Demo

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import numpy as npimport matplotlib.pyplot as plt import matplotlib.patches as patches import matplotlib.path as pathfig = plt.figure() ax = fig.add_subplot(111)# Fixing random state for reproducibility np.random.seed(19680801)# histogram our data with numpy data = https://www.it610.com/article/np.random.randn(1000) n, bins = np.histogram(data, 100)# get the corners of the rectangles for the histogram left = np.array(bins[:-1]) right = np.array(bins[1:]) bottom = np.zeros(len(left)) top = bottom + n nrects = len(left)nverts = nrects*(1+3+1) verts = np.zeros((nverts, 2)) codes = np.ones(nverts, int) * path.Path.LINETO codes[0::5] = path.Path.MOVETO codes[4::5] = path.Path.CLOSEPOLY verts[0::5,0] = left verts[0::5,1] = bottom verts[1::5,0] = left verts[1::5,1] = top verts[2::5,0] = right verts[2::5,1] = top verts[3::5,0] = right verts[3::5,1] = bottombarpath = path.Path(verts, codes) patch = patches.PathPatch(barpath, facecolor='green', edgecolor='yellow', alpha=0.5) ax.add_patch(patch)ax.set_xlim(left[0], right[-1]) ax.set_ylim(bottom.min(), top.max())plt.show()

24. Pyplot Scales

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import numpy as np import matplotlib.pyplot as pltfrom matplotlib.ticker import NullFormatter# useful for `logit` scale# Fixing random state for reproducibility np.random.seed(19680801)# make up some data in the interval ]0, 1[ y = np.random.normal(loc=0.5, scale=0.4, size=1000) y = y[(y > 0) & (y < 1)] y.sort() x = np.arange(len(y))# plot with various axes scales plt.figure(1)# linear plt.subplot(221) plt.plot(x, y) plt.yscale('linear') plt.title('linear') plt.grid(True)# log plt.subplot(222) plt.plot(x, y) plt.yscale('log') plt.title('log') plt.grid(True)# symmetric log plt.subplot(223) plt.plot(x, y - y.mean()) plt.yscale('symlog', linthreshy=0.01) plt.title('symlog') plt.grid(True)# logit plt.subplot(224) plt.plot(x, y) plt.yscale('logit') plt.title('logit') plt.grid(True) # Format the minor tick labels of the y-axis into empty strings with # `NullFormatter`, to avoid cumbering the axis with too many labels. plt.gca().yaxis.set_minor_formatter(NullFormatter()) # Adjust the subplot layout, because the logit one may take more space # than usual, due to y-tick labels like "1 - 10^{-3}" plt.subplots_adjust(top=0.92, bottom=0.08, left=0.10, right=0.95, hspace=0.25, wspace=0.35)plt.show()

25. Boxplot Demo
示例箱线图代码

import numpy as np import matplotlib.pyplot as plt# Fixing random state for reproducibility np.random.seed(19680801)# fake up some data spread = np.random.rand(50) * 100 center = np.ones(25) * 50 flier_high = np.random.rand(10) * 100 + 100 flier_low = np.random.rand(10) * -100 data = https://www.it610.com/article/np.concatenate((spread, center, flier_high, flier_low), 0)

![sphx_glr_boxplot_demo_pyplot_003.png](https://upload-images.jianshu.io/upload_images/7740545-e30b926509860a80.png?imageMogr2/auto-orient/strip%7CimageView2/2/w/1240) fig1, ax1 = plt.subplots() ax1.set_title('Basic Plot') ax1.boxplot(data)

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fig2, ax2 = plt.subplots() ax2.set_title('Notched boxes') ax2.boxplot(data, notch=True)

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green_diamond = dict(markerfacecolor='g', marker='D') fig3, ax3 = plt.subplots() ax3.set_title('Changed Outlier Symbols') ax3.boxplot(data, flierprops=green_diamond)

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fig4, ax4 = plt.subplots() ax4.set_title('Hide Outlier Points') ax4.boxplot(data, showfliers=False)

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red_square = dict(markerfacecolor='r', marker='s') fig5, ax5 = plt.subplots() ax5.set_title('Horizontal Boxes') ax5.boxplot(data, vert=False, flierprops=red_square)

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fig6, ax6 = plt.subplots() ax6.set_title('Shorter Whisker Length') ax6.boxplot(data, flierprops=red_square, vert=False, whis=0.75)

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伪造更多的数据

spread = np.random.rand(50) * 100 center = np.ones(25) * 40 flier_high = np.random.rand(10) * 100 + 100 flier_low = np.random.rand(10) * -100 d2 = np.concatenate((spread, center, flier_high, flier_low), 0) data.shape = (-1, 1) d2.shape = (-1, 1)

如果所有列的长度相同，则使2维数组有效。如果不是，则使用列表代替。这实际上更有效，因为箱线图无论如何将2维数组转换为向量列表。

data = https://www.it610.com/article/[data, d2, d2[::2,0]] fig7, ax7 = plt.subplots() ax7.set_title('Multiple Samples with Different sizes') ax7.boxplot(data)plt.show()

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26. Whats New 0.98.4 Fancy

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import matplotlib.patches as mpatch import matplotlib.pyplot as pltfigheight = 8 fig = plt.figure(1, figsize=(9, figheight), dpi=80) fontsize = 0.4 * fig.dpidef make_boxstyles(ax): styles = mpatch.BoxStyle.get_styles()for i, (stylename, styleclass) in enumerate(sorted(styles.items())): ax.text(0.5, (float(len(styles)) - 0.5 - i)/len(styles), stylename, ha="center", size=fontsize, transform=ax.transAxes, bbox=dict(boxstyle=stylename, fc="w", ec="k"))def make_arrowstyles(ax): styles = mpatch.ArrowStyle.get_styles()ax.set_xlim(0, 4) ax.set_ylim(0, figheight)for i, (stylename, styleclass) in enumerate(sorted(styles.items())): y = (float(len(styles)) -0.25 - i) # /figheight p = mpatch.Circle((3.2, y), 0.2, fc="w") ax.add_patch(p)ax.annotate(stylename, (3.2, y), (2., y), #xycoords="figure fraction", textcoords="figure fraction", ha="right", va="center", size=fontsize, arrowprops=dict(arrowstyle=stylename, patchB=p, shrinkA=5, shrinkB=5, fc="w", ec="k", connectionstyle="arc3,rad=-0.05", ), bbox=dict(boxstyle="square", fc="w"))ax.xaxis.set_visible(False) ax.yaxis.set_visible(False)ax1 = fig.add_subplot(121, frameon=False, xticks=[], yticks=[]) make_boxstyles(ax1)ax2 = fig.add_subplot(122, frameon=False, xticks=[], yticks=[]) make_arrowstyles(ax2)plt.show()

27. Text Layout

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import matplotlib.pyplot as plt import matplotlib.patches as patches# build a rectangle in axes coords left, width = .25, .5 bottom, height = .25, .5 right = left + width top = bottom + heightfig = plt.figure() ax = fig.add_axes([0,0,1,1])# axes coordinates are 0,0 is bottom left and 1,1 is upper right p = patches.Rectangle( (left, bottom), width, height, fill=False, transform=ax.transAxes, clip_on=False )ax.add_patch(p)ax.text(left, bottom, 'left top', horizontalalignment='left', verticalalignment='top', transform=ax.transAxes)ax.text(left, bottom, 'left bottom', horizontalalignment='left', verticalalignment='bottom', transform=ax.transAxes)ax.text(right, top, 'right bottom', horizontalalignment='right', verticalalignment='bottom', transform=ax.transAxes)ax.text(right, top, 'right top', horizontalalignment='right', verticalalignment='top', transform=ax.transAxes)ax.text(right, bottom, 'center top', horizontalalignment='center', verticalalignment='top', transform=ax.transAxes)ax.text(left, 0.5*(bottom+top), 'right center', horizontalalignment='right', verticalalignment='center', rotation='vertical', transform=ax.transAxes)ax.text(left, 0.5*(bottom+top), 'left center', horizontalalignment='left', verticalalignment='center', rotation='vertical', transform=ax.transAxes)ax.text(0.5*(left+right), 0.5*(bottom+top), 'middle', horizontalalignment='center', verticalalignment='center', fontsize=20, color='red', transform=ax.transAxes)ax.text(right, 0.5*(bottom+top), 'centered', horizontalalignment='center', verticalalignment='center', rotation='vertical', transform=ax.transAxes)ax.text(left, top, 'rotated\nwith newlines', horizontalalignment='center', verticalalignment='center', rotation=45, transform=ax.transAxes)ax.set_axis_off() plt.show()

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