arbitrary numerical precision and giacpy

[jocaps]

I encountered a problem with giacpy. I have a minimal code that shows it (sorry for the long code)

Code : Tout sélectionner

from giacpy import matrix, giac, svd

#giac("Digits:=20") #if I uncomment this then svd cannot output properly

mat = 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A = matrix(mat)

(U,d,V) = svd(A)

print(d)

In the line that is commented if I set the precision to higher (more precision than a typical floating point) then I would get undef outputs. So clearly python cannot show the values in this precision. Perhaps python tries to convert something of larger precision to float or something? I could execute this without problem in XCas. Any help here?

[frederic han]

I think there is several problems.
1) What ever you put the Digits value, it is only for giacpy (giac/xcas) objects so if you enter 0.0 in python such as is:
mat = [[2.0,1.0],[11.0,9.0]]
then you just have a python float and you can't send it to giacpy and expect a better precision. So you need to use quotes

Ex here the inverse of A is only done in float but for B we have the 30 Digits

Code : Tout sélectionner

>>> from giacpy import giacsettings,giac
>>> giacsettings.digits=30
>>> A=giac( [[2.0,1.0],[11.0,9.0]])
>>> B=giac('[[2.0,1.0],[11.0,9.0]]')
>>> A.inverse()
[[1.2857142857143,-0.14285714285714],[-1.5714285714286,0.28571428571428]]
>>> (B).inverse()
[[1.28571428571428571428571428571,-0.142857142857142857142857142857],[-1.57142857142857142857142857143,0.285714285714285714285714285714]]

2) Not all giac functions are able to use the high precision. I don't think that in xcas you will have the 30 digits for svd. (That' why I gave you an example with the inverse)
3) In giacpy 1/B seems to use the classic precision of floats while in xcas it gives the 30 digits. So in giacpy: giacpy.inv(B) is better or
this one also works

Code : Tout sélectionner

>>> giacpy.evalf(1)/B
[[1.28571428571428571428571428571,-0.142857142857142857142857142857],[-1.57142857142857142857142857143,0.285714285714285714285714285714]]