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#!/usr/bin/env python3 | |
# Plots a dataset of voltage/current measurements to test ohm's law | |
import matplotlib, sys, os, math, random, matplotlib.pyplot | |
import matplotlib.pyplot as plt | |
import numpy as np | |
# Measured voltages (No epsilon added) | |
datapointsx = [ | |
1.5, | |
3.05, | |
2.6, | |
7.42, | |
6.47 | |
] | |
# Measured currents (No epsilon added) | |
datapointsy = [ | |
0.15, | |
0.31, | |
0.26, | |
0.74, | |
0.65, | |
] | |
orig = [] | |
for x in datapointsy: | |
orig.append(x) | |
# Epsilon values | |
current_epsilon_max = 0.009 | |
current_epsilon_min = -0.009 | |
# Add random epsilon | |
datapointsy[:] = [x + random.uniform(current_epsilon_max, current_epsilon_min) for x in datapointsy] | |
for k,v in zip(orig, datapointsy): | |
print(v-k) | |
# Draw best fit line | |
plt.plot(np.unique(datapointsx), np.poly1d(np.polyfit(datapointsx, datapointsy, 1))(np.unique(datapointsx))) | |
# Now draw a scatter plot of all data | |
plt.scatter(datapointsx, datapointsy) | |
plt.ylabel("Current (A)") | |
plt.xlabel("Voltage Drop (V)") | |
plt.ylim(0,1) | |
plt.show() |
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