大学物理实验 载流圆线圈轴线上的磁场分布

首先说好，本宝宝不定期更新
另外，代码写的比较冗杂，需要拿走，不喜勿喷。

考虑到有可能会有不太精通Python的朋友，首先是说好，本代码仅支持Jupyter Notebook，因为用到了魔法函数。

额。。。

反正就是只能用jupyter，具体操作见最后。

实验数据处理

import matplotlib.pyplot as plt
import numpy as np
%matplotlib inline

# 前提准备
x = np.arange(-7,8)*0.01

u=4*3.14*(10**-7)
N = 500
R = 0.11
I = 0.3
#开始计算
Bl = (u*N*I*R*R)/(2*(R*R+x*x)**(3/2))*1000
print("理论数值为：",np.round(Bl,3))

# 实际测量值为：
Ba =[0.509,0.576,0.643,0.711,0.772,0.823,0.855,0.865,0.855,0.821,0.770,0.709,0.640,0.572,0.504]
# 求相对误差
dif = (Ba-Bl)/Bl*100
print("相对误差为：",np.round(dif,3))

b1 = [0.159,0.182,0.209,0.242,0.275,0.321,0.369,0.422,0.479,0.545,0.616,0.685,0.752,0.807,0.848,0.867,0.864,0.838,0.793,0.736,0.667]
b2 = [0.650,0.719,0.782,0.828,0.860,0.873,0.859,0.824,0.773,0.703,0.640,0.568,0.504,0.443,0.387,0.336,0.293,0.258,0.225,0.199,0.175]

b1 = np.array(b1)
b2 = np.array(b2)

print(b1+b2)

画图

%matplotlib inline
import matplotlib.pyplot as plt
import numpy as np
# let's draw a picture
plt.rcParams['font.sans-serif'] = ['SimHei']  # 用来正常显示中文标签
plt.rcParams['axes.unicode_minus'] = False  # 用来正常显示负号

#数据准备
Bl = np.array([0.514, 0.58, 0.646, 0.711, 0.769, 0.816, 0.846, 0.857, 0.846, 0.816, 0.769, 0.711, 0.646, 0.58, 0.514])
Ba = np.array([0.509,0.576,0.643,0.711,0.772,0.823,0.855,0.865,0.855,0.821,0.770,0.709,0.640,0.572,0.504])
x = np.arange(-7,8)

plt.figure()
plt.ylim((0,1))

#画图
plt.plot(x,Bl,'-or',label='理论曲线')
plt.plot(x,Ba,'ok',label='实验曲线')
plt.legend(loc='lower right')

#调整
plt.xlabel('x/cm')
plt.ylabel('B/mT')

new_ticks = np.array([-8,-6,-4,-2,0,2,4,6,8])
plt.xticks(new_ticks)

plt.grid(True)#网格线
plt.title('图1：载流圆线圈轴线上的磁场分布图')

#gca = get current axis
ax = plt.gca()
ax.spines['right'].set_color('none')
ax.spines['top'].set_color('none')

ax.xaxis.set_ticks_position('bottom')
ax.yaxis.set_ticks_position('left')
ax.spines['bottom'].set_position(('data', 0))
ax.spines['left'].set_position(('data', 0))

plt.savefig('./图1：载流圆线圈轴线上的磁场分布图.jpg',dpi=400) #保存图片，清晰度400
plt.show()

同理，改改就是另外几个图了，还不快copy paste modify一下！

---

仅供参考哦

%matplotlib inline
import matplotlib.pyplot as plt
import numpy as np
# let's draw a picture
plt.rcParams['font.sans-serif'] = ['SimHei']  # 用来正常显示中文标签
plt.rcParams['axes.unicode_minus'] = False  # 用来正常显示负号

b1 = np.array([0.159,0.182,0.209,0.242,0.275,0.321,0.369,0.422,0.479,0.545,0.616,0.685,0.752,0.807,0.848,0.867,0.864,0.838,0.793,0.736,0.667])
b2 = np.array([0.650,0.719,0.782,0.828,0.860,0.873,0.859,0.824,0.773,0.703,0.640,0.568,0.504,0.443,0.387,0.336,0.293,0.258,0.225,0.199,0.175])
b12 = np.array([0.806,0.898,0.988,1.070,1.134,1.187,1.222,1.240,1.247,1.249,1.249,1.248,1.246,1.241,1.224,1.195,1.147,1.087,1.008,0.924,0.833])
x = np.arange(-10,11)

plt.figure()
plt.ylim((0,1.5))

plt.plot(x,b1+b2,'-or',label=r'$B_1+B_2$')
plt.plot(x,b12,'ok',label=r'$B_{1+2}$')
plt.legend(loc='lower right')

plt.xlabel('x/cm')
plt.ylabel('B/mT')
plt.grid(True)#网格线
plt.title('图2：亥姆霍兹线圈轴线上的磁场分布图')

new_ticks = np.array([-10,-8,-6,-4,-2,0,2,4,6,8,10])
plt.xticks(new_ticks)

#gca = get current axis
ax = plt.gca()
ax.spines['right'].set_color('none')
ax.spines['top'].set_color('none')

ax.xaxis.set_ticks_position('bottom')
ax.yaxis.set_ticks_position('left')
ax.spines['bottom'].set_position(('data', 0))
ax.spines['left'].set_position(('data', 0))

plt.savefig('./图2：亥姆霍兹线圈轴线上的磁场分布图.jpg',dpi=400) #保存图片，清晰度400
plt.show()

---

%matplotlib inline
import matplotlib.pyplot as plt
import numpy as np
# let's draw a picture
plt.rcParams['font.sans-serif'] = ['SimHei']  # 用来正常显示中文标签
plt.rcParams['axes.unicode_minus'] = False  # 用来正常显示负号
b1 = np.array([0.159,0.182,0.209,0.242,0.275,0.321,0.369,0.422,0.479,0.545,0.616,0.685,0.752,0.807,0.848,0.867,0.864,0.838,0.793,0.736,0.667])
b2 = np.array([0.650,0.719,0.782,0.828,0.860,0.873,0.859,0.824,0.773,0.703,0.640,0.568,0.504,0.443,0.387,0.336,0.293,0.258,0.225,0.199,0.175])
x = np.arange(-10,11)

plt.figure()

plt.plot(x,b1,'k')
plt.plot(x,b2,'k')
plt.plot(x,b1+b2,'r')
plt.text(-5.0,0.9,r"$B_2$",fontdict={
    'size':16})
plt.text(5.0,0.9,r"$B_1$",fontdict={
    'size':16})
plt.text(5.2,1.3,r"$B=B_1+B_2$",fontdict={
    'size':16})

plt.ylim((0,1.5))
plt.xlabel('x')
plt.ylabel('B')
plt.grid(True)#网格线
plt.title('图3：亥姆霍兹线圈轴线上的磁场')

#gca = get current axis
ax = plt.gca()
ax.spines['right'].set_color('none')
ax.spines['top'].set_color('none')

ax.xaxis.set_ticks_position('bottom')
ax.yaxis.set_ticks_position('left')
ax.spines['bottom'].set_position(('data', 0))
ax.spines['left'].set_position(('data', 0))


plt.savefig('./图3：亥姆霍兹线圈轴线上的磁场.jpg',dpi=400) #保存图片，清晰度400
plt.show()

萌新教程

• 代码分为数据处理和画图两个部分，你需要的是拿你的实验数据来替换我的，注意对应好，别理论值实验值傻傻分不清cu。
• 数据处理部分：进行相应的计算，这样比计算器还快，其他的实验也可以批量计算，改改公式即可
• 画图部分的数据，相应的数据由数据处理部分复制而来（也有一点点是自己手输），所以记得分成几个ceil运行代码，我已经给分好了
• 画图坐标：调一下x,y即可，分别是x = np.arange(-7,8)和plt.ylim((0,1))，其中x的原则是你有多少个数据就设置多少，例如15个数据就设置x为（-7,8）因为8-（-7）=15，而y的原则是你的数据显示，比方说这15个数都分布在0到10之间，那我设置y轴为（0,10）就很好，如果分布在0到1呢，可能变换就不明显了，此时应当限制y为（0,1）才能看到明显的曲线变换。
• 画图坐标轴：plt.xlabel(‘x’)，这是控制显示在xy轴上的数据的，可以随便改，也可以删掉。
• 画图文本：plt.text(-5.0,0.9,r"$B_2$",fontdict={‘size’:16})，同上，可改引号内内容，也可删
• 画图标题：写着汉字，自己改。总之一句话，“调整”部分的代码，自己看着办，不动也行。
• 图片保存：返回jupyter的主页，就能看到，勾选，点Download即可，实在不行截屏也可。

这要是再有人不会，我可就不服了哦！！！
有问题欢迎联系本人或在下方评论区评论。