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Spectrophotometry Lab
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import matplotlib.pyplot as plt | |
import numpy | |
from numpy.linalg import lstsq | |
concentrations = numpy.asarray((.25, .20, .15, .1, .05)) | |
absorbtivities = numpy.asarray((.131, .129, .126, .119, .109)) | |
# Prepare data for fitting | |
conc_vstack = numpy.vstack([concentrations, numpy.ones(len(concentrations))]).T | |
# Calculate least squares linear fit | |
slope, intercept = lstsq(conc_vstack, absorbtivities)[0] | |
# Plot data as points | |
plt.scatter(concentrations, absorbtivities) | |
# Plot best fit line | |
plt.plot(concentrations, slope * concentrations + intercept, label='fit') | |
# Labels | |
plt.title('Concentration vs Absorbtivity') | |
plt.xlabel('Concentration (M)') | |
plt.ylabel('Absorbtivity') | |
plt.show() | |
# Additional metrics | |
print('Dilutions (ML): ' + str(concentrations / .25 * 10)) | |
print('Variance: ' + str(numpy.var(absorbtivities))) | |
print('Standard deviation: ' + str(absorbtivities.std())) | |
print('Slope: ' + str(slope)) | |
print('Y-int: ' + str(intercept)) | |
print('Mean Concentration, Absorption: (' + str(numpy.mean(concentrations)) + ', ' + str(numpy.mean(absorbtivities)) + ')') | |
print('Unknown substitution: ' + str(slope * .142 + intercept)) |
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