CODEWITHSUNDEEP
pythonscipyregression
Paolo Amboni
Paolo Amboni

Reputation: 3

scipy.odr output intercept and slope

I'm trying to plot ad odr regression. I used the code from this post as an example: sample code this is my code:

# regressione ODR  
import scipy.odr as odr
def funzione(B,x):
    return B[0]*x+B[1]
linear= odr.Model(funzione)
variabili=odr.Data(database.valore_rut,database.valore_cap)
regressione_ortogonale=odr.ODR(variabili,linear,beta0=[1., 2.])
output=regressione_ortogonale.run()    
output.pprint()

this is the output

Beta: [ 1.00088365  1.78267543]
Beta Std Error: [ 0.04851125  0.41899546]
Beta Covariance: [[ 0.00043625 -0.00154797]
[-0.00154797  0.03254372]]
Residual Variance: 5.39450361153
Inverse Condition #: 0.109803542662
Reason(s) for Halting:
Sum of squares convergence

where can i find the intercept and the slope to draw the line?

Thanks

Upvotes: 0

Views: 1394

Answers (1)

Warren Weckesser
Warren Weckesser

Reputation: 114921

The attribute output.beta holds the coefficients, which you called B in your code. So the slope is output.beta[0] and the intercept is output.beta[1].

To draw a line, you could do something like:

# xx holds the x limits of the line to draw.  The graph is a straight line,
# so we only need the endpoints to draw it.
xx = np.array([start, stop])  
yy = funzione(output.beta, xx)
plot(xx, yy)

Upvotes: 1

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