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吴裕雄--天生自然Python Matplotlib库学习笔记：matplotlib绘图

2020-01-23 14:51:14  阅读：417  来源： 互联网

标签：plt Python axes Matplotlib figsize np 吴裕雄 dpi size 


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()

 

 正在更新中...

标签：plt,Python,axes,Matplotlib,figsize,np,吴裕雄,dpi,size
来源： https://www.cnblogs.com/tszr/p/12230618.html

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