如何绘制这些数据？

Question

I am trying to plot this data:

h = 1
m = 1

E1 = (((h**2)/(2*m)) * ((((1*np.pi)/2)+((1*np.pi)/2))**2))
E2 = (((h**2)/(2*m)) * ((((2*np.pi)/2)+((2*np.pi)/2))**2))
E3 = (((h**2)/(2*m)) * ((((3*np.pi)/2)+((3*np.pi)/2))**2))
E4 = (((h**2)/(2*m)) * ((((4*np.pi)/2)+((4*np.pi)/2))**2))

k1 = ((((1*np.pi)/2)+((1*np.pi)/2))**2)
k2 = ((((2*np.pi)/2)+((2*np.pi)/2))**2)
k3 = ((((3*np.pi)/2)+((3*np.pi)/2))**2)
k4 = ((((4*np.pi)/2)+((4*np.pi)/2))**2)


E = list[E1, E2, E3, E4]
k = list[k1, k2, k3, k4]

plt.scatter(k,E)
plt.show()

The list function doesn't seem to work for this. I don't think it can get the pre-defined values. Using np.array also doesn't seem to work.

Answer 1

The way you define your lists is the issue.

Try:

E = [E1, E2, E3, E4]
k = [k1, k2, k3, k4]

Or if you want to use numpy:

E = np.array([E1, E2, E3, E4])
k = np.array([k1, k2, k3, k4])

Answer 2

Not an answer, just a suggestion but I wanted to write out enough code that wouldn't fit in a comment.

Instead of writing out four nearly identical lines, you can define a function:

def E(n, h=1.0, m=1.0):
    return (((h**2)/(2*m)) * ((((n*np.pi)/2)+((n*np.pi)/2))**2))

Note that it accepts values for h and m as arguments, but if none are provided, it will use 1.0 as default for both. This can even be simplified further, just by cleaning up the notation a bit (eg, you have something/2 + something/2 , which is equivalent to something , see my comment on your question)

def E(n, h=1.0, m=1.0):
    return (.5*h**2/m) * (n*np.pi)**2

And similarly for k :

def k(n):
    return (n*np.pi)**2

The best thing about this, is that you can now do this all at once without manually building that list:

>>> ns = np.arange(1,5)  # this is np.array([1,2,3,4])
>>> E(ns)
array([  4.9348022 ,  19.7392088 ,  44.4132198 ,  78.95683521])
>>> k(ns)
array([   9.8696044 ,   39.4784176 ,   88.82643961,  157.91367042])

Obviously this precise code won't work for you given the parenthesis typo, but I hope it helps with using numpy! This is the entire code at once:

import numpy as np
import matplotlib.pyplot as plt

def E(n, h=1.0, m=1.0):
    return (.5*h**2/m) * (n*np.pi)**2

def k(n):
    return (n*np.pi)**2

ns = np.arange(1, 5)
plt.scatter(k(ns), E(ns))
plt.show()