Co-Processor

Are there any plans for a new release?

Thank you for showing this possibility: using conc and {} is also a useful "trick". B.t.w. in the documentation for each is documented with join, but join seems to be just a REDUCE synonym for conc. Is that the Lisp "conc"?

thank you, that works. I have checked the documentation (http://www.reduce-algebra.com/manual/manual.pdf) again, but I do not feel that I have overlooked something ... Using t instead of 1 also works and looks more consistent to me (sorry, if I seem picky, but I want to understand ...). Is there a way in REDUCE to compose functions in a way similiar to this: procedure divable(p,d); if remainder(p,d) = 0 then t else nil; extractlist({x,y}, divable(~p,x)); with expected output {x}? (The above code...

I am still fighting with the basics of REDUCE. From a list of polynomials I want to extract those that are divisible by a given polynomial. I have tried the following: procedure ismultx(p); if remainder(p,x) = 0 then 1 else 0; load_package assist; extractlist({x,y}, ismultx); But this returns the whole list {x,y}, although ismultx(y) gives 0. Is there a simpler way than writing my own procedure extractmultiples(polylist,poly)?

Basically that would do it. For plotting one would have to generate points and pass them to the plot command, if I got that correctly. But I was looking for a way of (programmatically) generating a function/procedure mapping the x-value to the y-value. In python one could do something like this (using strings here for simplicity instead of symbolic expressions like provided by sympy): def genPieceFunc(pdf:list): def pieceFunc(x): for upper,expr in pdf: if x < upper: return eval(expr, {'x':x}) return...

Ok, I managed to implement a first version of a convolution procedure pw_conv for piecewise functions represented as list as proposed above. The standard uniform distribution is represented as {{0,0},{1,1},{INFINITY,0}} (a trailing {INFINITY,0} could be omitted). The successive convolutions with itself give the expected results {{0,0},{1,x},{2,2-x}}, ... (see attached code + screenshot). Now I am stuck on how to convert this representation to a procedure for numerical evaluation and plotting. Is...

Here is the screenshot:

Ok, I managed to implement a first version of a convolution procedure pw_conv for piecewise functions represented as proposed above. The standard uniform distribution is represented as {{0,0},{1,1},{INFINITY,0}} (a trailing {INFINITY,0} could be omitted). The successive convolutions with itself give the expected results {{0,0},{1,x},{2,2-x}}, ... (see attached code + screenshot). Now I am stuck on how to convert this representation to a procedure for numerical evaluation and plotting. Is it possible...