Hi there!
I am trying to find some parameters with the least squares algorithm
within Sage (v 4.0.2) . Unfortunately, when I try to use the
scipy.optimize.leastsq() method within Sage I get the following error:
>>> array cannot be safely cast to required type.
Strange enough, if I do the same directly with iPython I can perform
the computation properly. Do I have to cast my original data to some
special type in Sage (i.e RealNumbers)???. If yes, how? I tried lists,
tuples and NumPy arrays but It did not work.
here the simplified code:
# some dummy x,y data for testing
x = np.arange(0,3.0,0.25)
y =
np.array([0.0,0.3066,1.2263,2.7591,4.9050,7.6641,11.0363,15.0216,19.6200,24.8316,30.6562,37.0941],dtype=float)
# define a residuals function
def residuals(p,x,y):
k,degree = p
err = y -(k*(x**degree))
return err
# initial guess, k = 4.0, exp = 3?
pinit = [4.0,3]
#compute the leastsq algorithm
leastsq(residuals,pinit,args=(x,y))
Thank you very much in advance!
Jose.
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