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','','','','','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','_','','','','','','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([])

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