[Numpy-discussion] using numpy functions on an array of objects

[Sebastian Walter]

Hey,

What is  the best solution to get this code working?
Anyone a good idea?

------------------ test.py -----------------------------------------------
import numpy
import numpy.linalg

class afloat:
	def __init__(self,x):
		self.x = x

	def __add__(self,rhs):
		return self.x + rhs.x

	def sin(self):
		return numpy.sin(self.x)

	def inv(self):
		return numpy.linalg.inv(self.x)

	def trace(self):
		return 0

y = afloat(numpy.eye(3))
z = afloat(numpy.ones(3))
print y + z # works
print numpy.sin(y) # works
print numpy.trace(y) # doesn't work...???
print numpy.linalg.inv(y)  # doesn't work ...???

-------------------- end test.py --------------------------------


=== Explanation why I need that ===

I have the following problem. I need to do numerical calculations on
generalized versions of real numbers.
In particular with  truncated Taylor polynomials. I've implemented
that as a class that I called TC.
To define what the multiplication of two Taylor polynomials is I use
operator overloading.
Additionally, I need to compute sine, cosine, exp, etc. of Taylor polynomials.

For that, I can use the numpy functions. Numpy is apparently smart
enough to call the member function sin(self) of my class afloat
when it realizes that the argument of numpy.sin is not a known type.

This is really great. However, some functions are not as smart: Among them
trace
inv
dot


As a workaround, i could this:

def inv(X):
	if X.__class__ == afloat:
		return X.inv()
	else:
		return numpy.linalg.inv(X)

This is somewhat OK, but I'd like to use already existing Python code
that uses Numpy internally.
So I have to rely that numpy.inv(X) calls X.inv() when X is object of my class.


best regards,
Sebastian