In [1]:
import numpy as np
import scipy as ps
import pandas as pd
import matplotlib.pyplot as plt
%matplotlib inline
In [80]:
table_1 = pd.read_excel('lab-2-2.xlsx', '1')
table_1.iloc[:, :8]
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In [81]:
table_1.iloc[:, 8:]
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table_2 = pd.read_excel('lab-2-2.xlsx', '2')
table_2.iloc[:, :8]
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table_2.iloc[:, 8:]
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table_3 = pd.read_excel('lab-2-2.xlsx', '3')
table_3
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table_4 = pd.read_excel('lab-2-2.xlsx', '4')
table_4
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In [86]:
onet = table_3.values[:, 3]
lneta = table_3.values[:, 4]
donet = table_4.values[:, 3]
dlneta =table_4.values[:, 4]
In [152]:
k, b = np.polyfit(onet, lneta, deg=1)
k1, b1 = np.polyfit(onet, lneta + dlneta * np.linspace(-0.3, -0.4, len(dlneta)), deg=1)
k2, b2 = np.polyfit(onet, lneta - dlneta * np.linspace(-1.1, 0.7, len(dlneta)), deg=1)
In [186]:
plt.figure(figsize=(15,6))
plt.grid(linestyle='-.', lw=0.5, color='#cccccc')
plt.title('', fontweight='bold')
plt.ylabel('')
plt.xlabel('')
plt.scatter(onet, lneta)
x = np.linspace(0.00316, 0.00342)
plt.plot(x, k * x + b, color='black')
plt.plot(x, k1 * x + b1, '--', lw=0.5, color='black')
plt.plot(x, k2 * x + b2, '--', lw=0.5, color='black')
plt.errorbar(onet, lneta, xerr=donet, yerr=dlneta, fmt='o', color='black', lw=1.5)
plt.xlim((0.00316, 0.00342))
plt.ylim((-2.1, -0.58))
plt.show()
In [195]:
bolts = 1.38 * 10 ** (-23)
W = k * bolts
dW = np.abs(k2 - k1) * bolts / 2
print(W, dW, 100*dW/W)
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