Matplotlib 可能是 Python 2D-绘图领域使用最广泛的套件。它能让使用者很轻松地将数据图形化,并且提供多样化的输出格式。
from pylab import * size = 128,16 dpi = 72.0 figsize= size[0]/float(dpi),size[1]/float(dpi) fig = figure(figsize=figsize, dpi=dpi) fig.patch.set_alpha(0) axes([0,0,1,1], frameon=False) rcParams['text.antialiased'] = False text(0.5,0.5,"Aliased",ha='center',va='center') plt.xlim(0,1),plt.ylim(0,1), plt.xticks([]),plt.yticks([])
from pylab import * size = 256,16 dpi = 72.0 figsize= size[0]/float(dpi),size[1]/float(dpi) fig = figure(figsize=figsize, dpi=dpi) fig.patch.set_alpha(0) axes([0,0.1,1,.8], frameon=False) for i in range(1,11): plt.axvline(i, linewidth=1, color='blue',alpha=.25+.75*i/10.) xlim(0,11) xticks([]),yticks([])
from pylab import * size = 128,16 dpi = 72.0 figsize= size[0]/float(dpi),size[1]/float(dpi) fig = figure(figsize=figsize, dpi=dpi) fig.patch.set_alpha(0) axes([0,0,1,1], frameon=False) rcParams['text.antialiased'] = True text(0.5,0.5,"Anti-aliased",ha='center',va='center') plt.xlim(0,1),plt.ylim(0,1), plt.xticks([]),plt.yticks([])
from pylab import * axes([0.1,0.1,.8,.8]) xticks([]), yticks([]) text(0.6,0.6, 'axes([0.1,0.1,.8,.8])',ha='center',va='center',size=20,alpha=.5) axes([0.2,0.2,.3,.3]) xticks([]), yticks([]) text(0.5,0.5, 'axes([0.2,0.2,.3,.3])',ha='center',va='center',size=16,alpha=.5)
from pylab import * axes([0.1,0.1,.5,.5]) xticks([]), yticks([]) text(0.1,0.1, 'axes([0.1,0.1,.5,.5])',ha='left',va='center',size=16,alpha=.5) axes([0.2,0.2,.5,.5]) xticks([]), yticks([]) text(0.1,0.1, 'axes([0.2,0.2,.5,.5])',ha='left',va='center',size=16,alpha=.5) axes([0.3,0.3,.5,.5]) xticks([]), yticks([]) text(0.1,0.1, 'axes([0.3,0.3,.5,.5])',ha='left',va='center',size=16,alpha=.5) axes([0.4,0.4,.5,.5]) xticks([]), yticks([]) text(0.1,0.1, 'axes([0.4,0.4,.5,.5])',ha='left',va='center',size=16,alpha=.5) # plt.savefig("../figures/axes-2.png",dpi=64) show()
import numpy as np import matplotlib matplotlib.use('Agg') import matplotlib.pyplot as plt fig = plt.figure(figsize=(5,4),dpi=72) axes = fig.add_axes([0.01, 0.01, .98, 0.98]) X = np.linspace(0,2,200,endpoint=True) Y = np.sin(2*np.pi*X) plt.plot (X, Y, lw=.25, c='k') plt.xticks(np.arange(0.0, 2.0, 0.1)) plt.yticks(np.arange(-1.0,1.0, 0.1)) plt.grid()
import numpy as np import matplotlib.pyplot as plt n = 12 X = np.arange(n) Y1 = (1-X/float(n)) * np.random.uniform(0.5,1.0,n) Y2 = (1-X/float(n)) * np.random.uniform(0.5,1.0,n) plt.axes([0.025,0.025,0.95,0.95]) plt.bar(X, +Y1, facecolor='#9999ff', edgecolor='white') plt.bar(X, -Y2, facecolor='#ff9999', edgecolor='white') for x,y in zip(X,Y1): plt.text(x+0.4, y+0.05, '%.2f' % y, ha='center', va= 'bottom') for x,y in zip(X,Y2): plt.text(x+0.4, -y-0.05, '%.2f' % y, ha='center', va= 'top') plt.xlim(-.5,n), plt.xticks([]) plt.ylim(-1.25,+1.25), plt.yticks([]) # savefig('../figures/bar_ex.png', dpi=48) plt.show()
import numpy as np import matplotlib matplotlib.use('Agg') import matplotlib.pyplot as plt fig = plt.figure(figsize=(8,5),dpi=72) fig.patch.set_alpha(0.0) axes = plt.subplot(111) n = 5 Z = np.zeros((n,4)) X = np.linspace(0,2,n,endpoint=True) Y = np.random.random((n,4)) plt.boxplot(Y) #plt.xlim(-0.2,4.2) #plt.ylim(-1.2,1.2) plt.xticks([]), plt.yticks([]) plt.text(-0.05, 1.05, " Box Plot \n\n", horizontalalignment='left', verticalalignment='top', family='Lint McCree Intl BB', size='x-large', bbox=dict(alpha=1.0, width=350,height=60), transform = axes.transAxes) plt.text(-0.05, .95, " Make a box and whisker plot ", horizontalalignment='left', verticalalignment='top', family='Lint McCree Intl BB', size='medium', transform = axes.transAxes) plt.show()
from pylab import * size = 256,16 dpi = 72.0 figsize= size[0]/float(dpi),size[1]/float(dpi) fig = figure(figsize=figsize, dpi=dpi) fig.patch.set_alpha(0) axes([0,0.1,1,.8], frameon=False) for i in range(1,11): plot( [i,i], [0,1], lw=1.5 ) xlim(0,11) xticks([]),yticks([])
from pylab import * def colormap(cmap,filename): n = 512 Z = np.linspace(0,1,n,endpoint=True).reshape((1,n)) size = 512,16 dpi = 72.0 figsize= size[0]/float(dpi),size[1]/float(dpi) fig = plt.figure(figsize=figsize, dpi=dpi) fig.patch.set_alpha(0) axes([0.,0.,1.,1.], frameon=False) xticks([]), yticks([]) imshow(Z,aspect='auto',cmap=cmap,origin="lower") cmaps = [m for m in cm.datad if not m.endswith("_r")] cmaps.sort() for i in range(len(cmaps)): name = cmaps[i] filename = name if name == 'Spectral': filename = 'spectral-2' colormap(name,filename)
from pylab import * def f(x,y): return (1-x/2+x**5+y**3)*np.exp(-x**2-y**2) n = 256 x = np.linspace(-3,3,n) y = np.linspace(-3,3,n) X,Y = np.meshgrid(x,y) contourf(X, Y, f(X,Y), 8, alpha=.75, cmap=cm.hot) C = contour(X, Y, f(X,Y), 8, colors='black', linewidth=.5) clabel(C, inline=1, fontsize=10) xticks([]), yticks([]) text(-0.05, 1.05, " Contour Plot \n\n", horizontalalignment='left', verticalalignment='top', family='Lint McCree Intl BB', size='x-large', bbox=dict(facecolor='white', alpha=1.0, width=350,height=60), transform = gca().transAxes) text(-0.05, .975, " Draw contour lines and filled contours ", horizontalalignment='left', verticalalignment='top', family='Lint McCree Intl BB', size='medium', transform = gca().transAxes)
import numpy as np import matplotlib.pyplot as plt def f(x,y): return (1-x/2+x**5+y**3)*np.exp(-x**2-y**2) n = 256 x = np.linspace(-3,3,n) y = np.linspace(-3,3,n) X,Y = np.meshgrid(x,y) plt.axes([0.025,0.025,0.95,0.95]) plt.contourf(X, Y, f(X,Y), 8, alpha=.75, cmap=plt.cm.hot) C = plt.contour(X, Y, f(X,Y), 8, colors='black', linewidth=.5) plt.clabel(C, inline=1, fontsize=10) plt.xticks([]), plt.yticks([]) # savefig('../figures/contour_ex.png',dpi=48) plt.show()
from pylab import * size = 256,16 dpi = 72.0 figsize= size[0]/float(dpi),size[1]/float(dpi) fig = figure(figsize=figsize, dpi=dpi) fig.patch.set_alpha(0) axes([0,0,1,1], frameon=False) plot(np.arange(4), np.ones(4), color="blue", dashes=[15,15], linewidth=8, dash_capstyle = 'butt') plot(5+np.arange(4), np.ones(4), color="blue", dashes=[15,15], linewidth=8, dash_capstyle = 'round') plot(10+np.arange(4), np.ones(4), color="blue", dashes=[15,15], linewidth=8, dash_capstyle = 'projecting') xlim(0,14) xticks([]),yticks([]) show()
from pylab import * size = 256,16 dpi = 72.0 figsize= size[0]/float(dpi),size[1]/float(dpi) fig = figure(figsize=figsize, dpi=dpi) fig.patch.set_alpha(0) axes([0,0,1,1], frameon=False) plot(np.arange(3), [0,1,0], color="blue", dashes=[12,5], linewidth=8, dash_joinstyle = 'miter') plot(4+np.arange(3), [0,1,0], color="blue", dashes=[12,5], linewidth=8, dash_joinstyle = 'bevel') plot(8+np.arange(3), [0,1,0], color="blue", dashes=[12,5], linewidth=8, dash_joinstyle = 'round') xlim(0,12), ylim(-1,2) xticks([]),yticks([]) show()
import numpy as np import matplotlib.pyplot as plt X = np.linspace(-np.pi, np.pi, 256, endpoint=True) C,S = np.cos(X), np.sin(X) plt.plot(X,C) plt.plot(X,S) plt.show()
# Imports import numpy as np import matplotlib.pyplot as plt # Create a new figure of size 8x6 points, using 100 dots per inch plt.figure(figsize=(8,6), dpi=100) # Create a new subplot from a grid of 1x1 plt.subplot(111) X = np.linspace(-np.pi, np.pi, 256,endpoint=True) C,S = np.cos(X), np.sin(X) # Plot cosine using blue color with a continuous line of width 1 (pixels) plt.plot(X, C, color="blue", linewidth=1.0, linestyle="-") # Plot sine using green color with a continuous line of width 1 (pixels) plt.plot(X, S, color="green", linewidth=1.0, linestyle="-") # Set x limits plt.xlim(-4.0,4.0) # Set x ticks plt.xticks(np.linspace(-4,4,9,endpoint=True)) # Set y limits plt.ylim(-1.0,1.0) # Set y ticks plt.yticks(np.linspace(-1,1,5,endpoint=True)) # Save figure using 72 dots per inch # savefig("../figures/exercice_2.png",dpi=72) # Show result on screen plt.show()
import numpy as np import matplotlib.pyplot as plt plt.figure(figsize=(8,5), dpi=80) plt.subplot(111) X = np.linspace(-np.pi, np.pi, 256,endpoint=True) C,S = np.cos(X), np.sin(X) plt.plot(X, C, color="blue", linewidth=2.5, linestyle="-") plt.plot(X, S, color="red", linewidth=2.5, linestyle="-") plt.xlim(-4.0,4.0) plt.xticks(np.linspace(-4,4,9,endpoint=True)) plt.ylim(-1.0,1.0) plt.yticks(np.linspace(-1,1,5,endpoint=True)) plt.show()
import numpy as np import matplotlib.pyplot as plt plt.figure(figsize=(8,5), dpi=80) plt.subplot(111) X = np.linspace(-np.pi, np.pi, 256,endpoint=True) C,S = np.cos(X), np.sin(X) plt.plot(X, C, color="blue", linewidth=2.5, linestyle="-") plt.plot(X, S, color="red", linewidth=2.5, linestyle="-") plt.xlim(X.min()*1.1, X.max()*1.1) plt.ylim(C.min()*1.1,C.max()*1.1) plt.show()
from pylab import * figure(figsize=(8,5), dpi=80) subplot(111) X = np.linspace(-np.pi, np.pi, 256,endpoint=True) C,S = np.cos(X), np.sin(X) plot(X, C, color="blue", linewidth=2.5, linestyle="-") plot(X+.1, C, color="blue", linewidth=2.5, linestyle="-",alpha=.15) plot(X, S, color="red", linewidth=2.5, linestyle="-") xlim(X.min()*1.1, X.max()*1.1) ylim(C.min()*1.1,C.max()*1.1) # savefig("../figures/exercice_4.png",dpi=72) show()
import numpy as np import matplotlib.pyplot as plt plt.figure(figsize=(8,5), dpi=80) plt.subplot(111) X = np.linspace(-np.pi, np.pi, 256,endpoint=True) C,S = np.cos(X), np.sin(X) plt.plot(X, C, color="blue", linewidth=2.5, linestyle="-") plt.plot(X, S, color="red", linewidth=2.5, linestyle="-") plt.xlim(X.min()*1.1, X.max()*1.1) plt.xticks([-np.pi, -np.pi/2, 0, np.pi/2, np.pi]) plt.ylim(C.min()*1.1,C.max()*1.1) plt.yticks([-1, 0, +1]) plt.show()
import numpy as np import matplotlib.pyplot as plt plt.figure(figsize=(8,5), dpi=80) plt.subplot(111) X = np.linspace(-np.pi, np.pi, 256,endpoint=True) C,S = np.cos(X), np.sin(X) plt.plot(X, C, color="blue", linewidth=2.5, linestyle="-") plt.plot(X, S, color="red", linewidth=2.5, linestyle="-") plt.xlim(X.min()*1.1, X.max()*1.1) plt.xticks([-np.pi, -np.pi/2, 0, np.pi/2, np.pi], [r'$-\pi$', r'$-\pi/2$', r'$0$', r'$+\pi/2$', r'$+\pi$']) plt.ylim(C.min()*1.1,C.max()*1.1) plt.yticks([-1, 0, +1], [r'$-1$', r'$0$', r'$+1$']) plt.show()
import numpy as np import matplotlib.pyplot as plt plt.figure(figsize=(8,5), dpi=80) ax = plt.subplot(111) ax.spines['right'].set_color('none') ax.spines['top'].set_color('none') ax.xaxis.set_ticks_position('bottom') ax.spines['bottom'].set_position(('data',0)) ax.yaxis.set_ticks_position('left') ax.spines['left'].set_position(('data',0)) X = np.linspace(-np.pi, np.pi, 256,endpoint=True) C,S = np.cos(X), np.sin(X) plt.plot(X, C, color="blue", linewidth=2.5, linestyle="-") plt.plot(X, S, color="red", linewidth=2.5, linestyle="-") plt.xlim(X.min()*1.1, X.max()*1.1) plt.xticks([-np.pi, -np.pi/2, 0, np.pi/2, np.pi], [r'$-\pi$', r'$-\pi/2$', r'$0$', r'$+\pi/2$', r'$+\pi$']) plt.ylim(C.min()*1.1,C.max()*1.1) plt.yticks([-1, 0, +1], [r'$-1$', r'$0$', r'$+1$']) plt.show()
import numpy as np import matplotlib.pyplot as plt plt.figure(figsize=(8,5), dpi=80) ax = plt.subplot(111) ax.spines['right'].set_color('none') ax.spines['top'].set_color('none') ax.xaxis.set_ticks_position('bottom') ax.spines['bottom'].set_position(('data',0)) ax.yaxis.set_ticks_position('left') ax.spines['left'].set_position(('data',0)) X = np.linspace(-np.pi, np.pi, 256,endpoint=True) C,S = np.cos(X), np.sin(X) plt.plot(X, C, color="blue", linewidth=2.5, linestyle="-", label="cosine") plt.plot(X, S, color="red", linewidth=2.5, linestyle="-", label="sine") plt.xlim(X.min()*1.1, X.max()*1.1) plt.xticks([-np.pi, -np.pi/2, 0, np.pi/2, np.pi], [r'$-\pi$', r'$-\pi/2$', r'$0$', r'$+\pi/2$', r'$+\pi$']) plt.ylim(C.min()*1.1,C.max()*1.1) plt.yticks([-1, +1], [r'$-1$', r'$+1$']) plt.legend(loc='upper left', frameon=False) # plt.savefig("../figures/exercice_8.png",dpi=72) plt.show()
import numpy as np import matplotlib.pyplot as plt plt.figure(figsize=(8,5), dpi=80) ax = plt.subplot(111) ax.spines['right'].set_color('none') ax.spines['top'].set_color('none') ax.xaxis.set_ticks_position('bottom') ax.spines['bottom'].set_position(('data',0)) ax.yaxis.set_ticks_position('left') ax.spines['left'].set_position(('data',0)) X = np.linspace(-np.pi, np.pi, 256,endpoint=True) C,S = np.cos(X), np.sin(X) plt.plot(X, C, color="blue", linewidth=2.5, linestyle="-", label="cosine") plt.plot(X, S, color="red", linewidth=2.5, linestyle="-", label="sine") plt.xlim(X.min()*1.1, X.max()*1.1) plt.xticks([-np.pi, -np.pi/2, 0, np.pi/2, np.pi], [r'$-\pi$', r'$-\pi/2$', r'$0$', r'$+\pi/2$', r'$+\pi$']) plt.ylim(C.min()*1.1,C.max()*1.1) plt.yticks([-1, +1], [r'$-1$', r'$+1$']) t = 2*np.pi/3 plt.plot([t,t],[0,np.cos(t)], color ='blue', linewidth=1.5, linestyle="--") plt.scatter([t,],[np.cos(t),], 50, color ='blue') plt.annotate(r'$\cos(\frac{2\pi}{3})=-\frac{1}{2}$', xy=(t, np.cos(t)), xycoords='data', xytext=(-90, -50), textcoords='offset points', fontsize=16, arrowprops=dict(arrowstyle="->", connectionstyle="arc3,rad=.2")) plt.plot([t,t],[0,np.sin(t)], color ='red', linewidth=1.5, linestyle="--") plt.scatter([t,],[np.sin(t),], 50, color ='red') plt.annotate(r'$\sin(\frac{2\pi}{3})=\frac{\sqrt{3}}{2}$', xy=(t, np.sin(t)), xycoords='data', xytext=(+10, +30), textcoords='offset points', fontsize=16, arrowprops=dict(arrowstyle="->", connectionstyle="arc3,rad=.2")) plt.legend(loc='upper left', frameon=False) #plt.savefig("../figures/exercice_9.png",dpi=72) plt.show()
import numpy as np import matplotlib.pyplot as plt plt.figure(figsize=(8,5), dpi=80) ax = plt.subplot(111) ax.spines['right'].set_color('none') ax.spines['top'].set_color('none') ax.xaxis.set_ticks_position('bottom') ax.spines['bottom'].set_position(('data',0)) ax.yaxis.set_ticks_position('left') ax.spines['left'].set_position(('data',0)) X = np.linspace(-np.pi, np.pi, 256,endpoint=True) C,S = np.cos(X), np.sin(X) plt.plot(X, C, color="blue", linewidth=2.5, linestyle="-", label="cosine", zorder=-1) plt.plot(X, S, color="red", linewidth=2.5, linestyle="-", label="sine", zorder=-2) plt.xlim(X.min()*1.1, X.max()*1.1) plt.xticks([-np.pi, -np.pi/2, 0, np.pi/2, np.pi], [r'$-\pi$', r'$-\pi/2$', r'$0$', r'$+\pi/2$', r'$+\pi$']) plt.ylim(C.min()*1.1,C.max()*1.1) plt.yticks([-1, +1], [r'$-1$', r'$+1$']) plt.legend(loc='upper left', frameon=False) t = 2*np.pi/3 plt.plot([t,t],[0,np.cos(t)], color ='blue', linewidth=1.5, linestyle="--") plt.scatter([t,],[np.cos(t),], 50, color ='blue') plt.annotate(r'$\sin(\frac{2\pi}{3})=\frac{\sqrt{3}}{2}$', xy=(t, np.sin(t)), xycoords='data', xytext=(+10, +30), textcoords='offset points', fontsize=16, arrowprops=dict(arrowstyle="->", connectionstyle="arc3,rad=.2")) plt.plot([t,t],[0,np.sin(t)], color ='red', linewidth=1.5, linestyle="--") plt.scatter([t,],[np.sin(t),], 50, color ='red') plt.annotate(r'$\cos(\frac{2\pi}{3})=-\frac{1}{2}$', xy=(t, np.cos(t)), xycoords='data', xytext=(-90, -50), textcoords='offset points', fontsize=16, arrowprops=dict(arrowstyle="->", connectionstyle="arc3,rad=.2")) for label in ax.get_xticklabels() + ax.get_yticklabels(): label.set_fontsize(16) label.set_bbox(dict(facecolor='white', edgecolor='None', alpha=0.65 )) #plt.savefig("../figures/exercice_10.png",dpi=72) plt.show()
import numpy as np import matplotlib matplotlib.use('Agg') import matplotlib.pyplot as plt fig = plt.figure(figsize=(5,4),dpi=72) axes = fig.add_axes([0.01, 0.01, .98, 0.98]) #, frameon=False) X = np.linspace(0,2,200,endpoint=True) Y = np.sin(2*np.pi*X) plt.plot (X, Y, lw=2) plt.ylim(-1.1,1.1) plt.grid()
import numpy as np import matplotlib.pyplot as plt ax = plt.axes([0.025,0.025,0.95,0.95]) ax.set_xlim(0,4) ax.set_ylim(0,3) ax.xaxis.set_major_locator(plt.MultipleLocator(1.0)) ax.xaxis.set_minor_locator(plt.MultipleLocator(0.1)) ax.yaxis.set_major_locator(plt.MultipleLocator(1.0)) ax.yaxis.set_minor_locator(plt.MultipleLocator(0.1)) ax.grid(which='major', axis='x', linewidth=0.75, linestyle='-', color='0.75') ax.grid(which='minor', axis='x', linewidth=0.25, linestyle='-', color='0.75') ax.grid(which='major', axis='y', linewidth=0.75, linestyle='-', color='0.75') ax.grid(which='minor', axis='y', linewidth=0.25, linestyle='-', color='0.75') ax.set_xticklabels([]) ax.set_yticklabels([]) # savefig('../figures/grid_ex.png',dpi=48) plt.show()
from pylab import * import matplotlib.gridspec as gridspec G = gridspec.GridSpec(3, 3) axes_1 = subplot(G[0, :]) xticks([]), yticks([]) text(0.5,0.5, 'Axes 1',ha='center',va='center',size=24,alpha=.5) axes_2 = subplot(G[1,:-1]) xticks([]), yticks([]) text(0.5,0.5, 'Axes 2',ha='center',va='center',size=24,alpha=.5) axes_3 = subplot(G[1:, -1]) xticks([]), yticks([]) text(0.5,0.5, 'Axes 3',ha='center',va='center',size=24,alpha=.5) axes_4 = subplot(G[-1,0]) xticks([]), yticks([]) text(0.5,0.5, 'Axes 4',ha='center',va='center',size=24,alpha=.5) axes_5 = subplot(G[-1,-2]) xticks([]), yticks([]) text(0.5,0.5, 'Axes 5',ha='center',va='center',size=24,alpha=.5) #plt.savefig('../figures/gridspec.png', dpi=64) show()
import numpy as np import matplotlib.pyplot as plt def f(x,y): return (1-x/2+x**5+y**3)*np.exp(-x**2-y**2) n = 10 x = np.linspace(-3,3,3.5*n) y = np.linspace(-3,3,3.0*n) X,Y = np.meshgrid(x,y) Z = f(X,Y) plt.axes([0.025,0.025,0.95,0.95]) plt.imshow(Z,interpolation='bicubic', cmap='bone', origin='lower') plt.colorbar(shrink=.92) plt.xticks([]), plt.yticks([]) # savefig('../figures/imshow_ex.png', dpi=48) plt.show()
from pylab import * def linestyle(ls,name): size = 256,16 dpi = 72.0 figsize= size[0]/float(dpi),size[1]/float(dpi) fig = figure(figsize=figsize, dpi=dpi) fig.patch.set_alpha(0) axes([0,0,1,1],frameon=False) X = np.arange(11) Y = np.ones(11) plot(X,Y,ls,color=(.0,.0,1,1), lw=3, ms=10, mfc=(.75,.75,1,1), mec=(0,0,1,1)) xlim(0,10) xticks([]), yticks([]) for ls in ['-','--',':',',','o','^','v','<','>','s', '+','x','d','1','2','3','4','h','p','|','_']: linestyle(ls,ls) linestyle('D', 'dd') linestyle('H', 'hh') linestyle('.', 'dot') linestyle('-.', '-dot')
from pylab import * size = 256,16 dpi = 72.0 figsize= size[0]/float(dpi),size[1]/float(dpi) fig = figure(figsize=figsize, dpi=dpi) fig.patch.set_alpha(0) axes([0,.1,1,.8], frameon=False) for i in range(1,11): plot( [i,i], [0,1], color='b', lw=i/2. ) xlim(0,11),ylim(0,1) xticks([]),yticks([])
from pylab import * def marker(m,name): size = 256,16 dpi = 72.0 figsize= size[0]/float(dpi),size[1]/float(dpi) fig = figure(figsize=figsize, dpi=dpi) fig.patch.set_alpha(0) axes([0,0,1,1],frameon=False) X = np.arange(11) Y = np.ones(11) plot(X,Y,color='w', lw=1, marker=m, ms=10, mfc=(.75,.75,1,1), mec=(0,0,1,1)) xlim(0,10) xticks([]), yticks([]) for m in [0,1,2,3,4,5,6,7,'o','h','_','1','2','3','4','8','p', '^','v','<','>','|','d',',','+','s','*','|','x']: if type(m) is int: marker(m, 'i%d' % m) else: marker(m,m) marker('D', 'dd') marker('H', 'hh') marker('.', 'dot') marker(r"$\sqrt{2}$", "latex")
from pylab import * size = 256,16 dpi = 72.0 figsize= size[0]/float(dpi),size[1]/float(dpi) fig = figure(figsize=figsize, dpi=dpi) fig.patch.set_alpha(0) axes([0,0,1,1], frameon=False) for i in range(1,11): r,g,b = np.random.uniform(0,1,3) plot([i,],[1,],'s', markersize=5, markerfacecolor='w', markeredgewidth=1.5, markeredgecolor=(r,g,b,1)) xlim(0,11) xticks([]),yticks([])
from pylab import * size = 256,16 dpi = 72.0 figsize= size[0]/float(dpi),size[1]/float(dpi) fig = figure(figsize=figsize, dpi=dpi) fig.patch.set_alpha(0) axes([0,0,1,1], frameon=False) for i in range(1,11): plot([i,],[1,],'s', markersize=5, markeredgewidth=1+i/10., markeredgecolor='k', markerfacecolor='w') xlim(0,11) xticks([]),yticks([])
from pylab import * size = 256,16 dpi = 72.0 figsize= size[0]/float(dpi),size[1]/float(dpi) fig = figure(figsize=figsize, dpi=dpi) fig.patch.set_alpha(0) axes([0,0,1,1], frameon=False) for i in range(1,11): r,g,b = np.random.uniform(0,1,3) plot([i,],[1,],'s', markersize=8, markerfacecolor=(r,g,b,1), markeredgewidth=.1, markeredgecolor=(0,0,0,.5)) xlim(0,11) xticks([]),yticks([])
from pylab import * size = 256,16 dpi = 72.0 figsize= size[0]/float(dpi),size[1]/float(dpi) fig = figure(figsize=figsize, dpi=dpi) fig.patch.set_alpha(0) axes([0,0,1,1], frameon=False) for i in range(1,11): plot([i,],[1,],'s', markersize=i, markerfacecolor='w', markeredgewidth=.5, markeredgecolor='k') xlim(0,11) xticks([]),yticks([])