I started recently some work on a symbolic expression for variance and covariance in *sympy.stats* module:
https://github.com/sympy/sympy/pull/10247 The current *stats* module defines functions such as *P (probability), E (expectation), variance, covariance, moment, *and so on, to perform the integral given random variables or conditions on random variables. I think it's convenient to also have the possibility to operate at a higher level of abstraction, by keeping unevaluated symbolic expressions and operating with their properties on them. The idea is to define a class with the same name of the function, with capital first letter: - Expectation( ) vs expectation( ) - Probability( ) vs probability( ) - Variance( ) vs variance( ) - ... and so on ... The latter ones are the existing functions, whereas the first ones are classes that create the unevaluated expression. The method *.doit()* calls the corresponding function to perform the integral. A similar relationship already exists in SymPy: - Integral( ) vs integrate( ) - Derivative( ) vs diff( ) - Sum( ) vs sum( ) *.doit()* calls the function. I'd like to have some feedback before going on. Do you think this is a good idea? Would you merge this once it's finished? -- You received this message because you are subscribed to the Google Groups "sympy" group. To unsubscribe from this group and stop receiving emails from it, send an email to sympy+unsubscr...@googlegroups.com. To post to this group, send email to sympy@googlegroups.com. Visit this group at https://groups.google.com/group/sympy. To view this discussion on the web visit https://groups.google.com/d/msgid/sympy/d0dff984-3457-4e53-89ea-bb2b120beb1c%40googlegroups.com. For more options, visit https://groups.google.com/d/optout.
