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August 29, 2015 14:05
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scidavis linear fit, leasts squares model
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| import numpy as np | |
| import pylab as pl | |
| x1 = np.arange(15) | |
| y1 = 0.5*x1 + 0.6 | |
| x2=[0,2,4,6,8,10,12,14] | |
| y2=[0,2,4,4,5,5,7,8] | |
| plot1=pl.plot(x1,y1,'r') | |
| plot2=pl.plot(x2,y2,'go') | |
| pl.title('Plotando y vs. x') | |
| pl.xlabel('eixo x') | |
| pl.ylabel('eixo y') | |
| pl.xlim(0,15) | |
| pl.ylim(0,15) | |
| pl.show() |
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