I have to check whether my parameters setting is right, so I need to draw many plots, and for drawing these plots, I choose to use matplotlib. After each checking, I need to click the close button on the top left conner. It's trivial. So is there any method that can make the plot show in about 3 or 5 seconds and automatically close without clicking? I know about the plt.close()
, but it doesn't work. Here is my code.
from math import *
import sys
import numpy as np
from scipy import special
import matplotlib.pyplot as plt
x1=[]
y1=[]
x2=[]
y2=[]
x3=[]
y3=[]
with open('fort.222','r') as f:
for line in f:
a,b=line.split()
x1.append(float(a))
y1.append(float(b))
n=int(sys.argv[1])
i=0
with open('fort.777','r') as f:
for line in f:
if i==0:
k1=float(line)
i=i+1
x1,y1=np.array(x1),np.array(y1)
z1=special.eval_hermite(n,x1*k1)*sqrt(1/(sqrt(pi)*pow(2,n)*factorial(n)))*sqrt(k1)*np.exp(-np.power(k1*x1,2)/2.)
plt.figure()
plt.plot(x1,z1)
plt.plot(x1,y1)
plt.plot(x1,np.zeros(len(x1)))
plt.title('single center & double center')
plt.xlim(x1.min(),x1.max())
plt.ylim(-max(abs(y1.min()-0.1),y1.max()+0.1),max(abs(y1.min()-0.2),y1.max()+0.2))
plt.xlabel('$\zeta$'+'/fm')
plt.legend(('single, n='+sys.argv[1],'double, n='+sys.argv[1]),loc=2,frameon=True)
plt.show()
plt.close()
Plotting from an IPython shell Using plt. show() in Matplotlib mode is not required.
In the current versions of the IPython notebook and jupyter notebook, it is not necessary to use the %matplotlib inline function. As, whether you call matplotlib. pyplot. show() function or not, the graph output will be displayed in any case.
Documentation on pyplot.show()
reads:
matplotlib.pyplot.show(*args, **kw)
Display a figure. When running in ipython with its pylab mode, display all figures and return to the ipython prompt.
In non-interactive mode, display all figures and block until the figures have been closed; in interactive mode it has no effect unless figures were created prior to a change from non-interactive to interactive mode (not recommended). In that case it displays the figures but does not block.
A single experimental keyword argument,
block
, may be set toTrue
orFalse
to override the blocking behavior described above.
So the solution is this:
plt.show(block=False) plt.pause(3) plt.close()
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