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Doing Symbolic Math with SymPy

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Re: Doing Symbolic Math with SymPy

#11

Post by ByteJockey »

abdullahkhalids wrote: post #8

SymPy's problem is that it is based on an object-oriented language. This results in SymPy (and friends) demanding that users abandon hundreds of years of math notation, to conform to the whims of a programming language. In SymPy you do M.diagonalize(), which makes no sense. The matrix M does not have a property diagonalize. Rather, you should apply a choosen diagonalization algorithm like Diagonalize(M) to produce a…

There's no reason you can't do this. Python has free functions. It was an intentional style choice to do it this way.

You can also make a diagonalize function that just calls the method if you like that style better, half of python's generic functions (e.g. len) just call methods anyways.

Re: Doing Symbolic Math with SymPy

#12

Post by stochastician »

I want to encourage people to think of sympy not just as a competitor to Mathematica but additionally as an incredibly valuable library that can be used _inside_ of other projects. Sometimes, you just want to compute an antiderivative, or you want user-supplied functions that you can manipulate easily, or you want to do some actual algebra.

Think of it less as a Mathematica replacement (like "Linux on the Desktop") and more as a crucial library enabling a lot of fun new creative things (like "embedded linux running on your toaster").

For example, in some of my computational chemistry work we use it to allow users to specify certain functionals, which we can then manipulate symbolically, do expression reduction and elimination on, and prove certain properties about. It's great!

Re: Doing Symbolic Math with SymPy

#13

Post by [deleted] »

ByteJockey wrote: post #11
abdullahkhalids wrote: post #8

SymPy's problem is that it is based on an object-oriented language. This results in SymPy (and friends) demanding that users abandon hundreds of years of math notation, to conform to the whims of a programming language. In SymPy you do M.diagonalize(), which makes no sense. The matrix M does not have a property diagonalize. Rather, you should apply a choosen diagonalization algorithm like Diagonalize(M) to produce a…

There's no reason you can't do this. Python has free functions. It was an intentional style choice to do it this way. You can also make a diagonalize function that just calls the method if you like that style better, half of python's generic functions (e.g. len) just call methods anyways.

[deleted]

Re: Doing Symbolic Math with SymPy

#14

Post by prionassembly »

prof-dr-ir wrote: post #2

SymPy is fantastic and impressive and I am a fan. It however does few things better than the program it is directly trying to compete with, namely Mathematica. This gives me scary flashbacks to the early 'Linux on the desktop' advocates, whose main argument was that it was all 'free' in every sense of the word. As we know now, that simply was not enough to switch the majority of users. Do people see a space where Sym…

It runs on a google colab tab that you can spin up pressing "ctrl-T" in any available computer.

Re: Doing Symbolic Math with SymPy

#15

Post by joshuaissac »

vanderZwan wrote: post #9
abdullahkhalids wrote: post #8

SymPy's problem is that it is based on an object-oriented language. This results in SymPy (and friends) demanding that users abandon hundreds of years of math notation, to conform to the whims of a programming language. In SymPy you do M.diagonalize(), which makes no sense. The matrix M does not have a property diagonalize. Rather, you should apply a choosen diagonalization algorithm like Diagonalize(M) to produce a…

> Mathematica wins, and will continue to win, because the language is functional and conforms to how Mathematicians think, rather than how programmers like to code. Or maybe Python "will win" because it conforms to how programmers think, rather than forcing them to think like mathematicians (also, why capitalize "mathematicians" in your sentence?), letting them get their shit done. More importantly, "win" what exactl…

It depends on who the intended users of SymPy are. If they are programmers, then conforming to how programmers would think would be useful. If it is targeted at mathematicians, then confirming to how programmers think would just be another unnecessary hurdle to using the library, and would hurt adoption (which is what "win" means here).

Re: Doing Symbolic Math with SymPy

#16

Post by mehrdadn »

The trouble with SymPy is it's, well, buggy. I tried it a few years ago, and as soon as I got serious, I quite quickly ran into problems that I reported, some of which I now see they apparently still haven't gotten around to addressing. [1] [2]

Symbolic math is hard; they have my sympathies. I don't think I could do better. But as long as bugs like these exist, it's going to be hard to convince people to switch away from better tools like Mathematica.

[1] https://github.com/sympy/sympy/issues/12561

[2] https://github.com/sympy/sympy/issues/12562

Re: Doing Symbolic Math with SymPy

#17

Post by ChrisRackauckas »

fdej wrote: post #7
xvilka wrote: post #5

Earlier quoted context omitted.

Maxima plus Sage Math wrappers works more appropriately, I think. Though I would prefer a faster language than Python for such systems. Something like Sage but with Julia.

Nemo ( http://nemocas.org/ ) and Oscar ( https://oscar.computeralgebra.de/ ) are such projects. However, they are focused on algebra and have no support for expression manipulation, symbolic integration and the like.

For symbolic manipulation and all of that, ModelingToolkit.jl (https://mtk.sciml.ai/dev/) is the project, and it's getting SymEngine-like speeds in about a day or so. There's still more to do, but where this shines is the connection to numerical computing, i.e. partially solving models and then spitting out optimized parallelized code for the ODE solver for the other half of the model.

Re: Doing Symbolic Math with SymPy

#18

Post by leephillips »

abdullahkhalids wrote: post #8

SymPy's problem is that it is based on an object-oriented language. This results in SymPy (and friends) demanding that users abandon hundreds of years of math notation, to conform to the whims of a programming language. In SymPy you do M.diagonalize(), which makes no sense. The matrix M does not have a property diagonalize. Rather, you should apply a choosen diagonalization algorithm like Diagonalize(M) to produce a…

This is problem I have with Python in general; that even if you prefer to use it in a functional style, most libraries are written by real Python programmers, and using them will force you to grapple with the object-oriented inversion of common sense (https://lee-phillips.org/pythonhate/).

My favorite example is: ','.join(['a', 'b'])

Re: Doing Symbolic Math with SymPy

#19

Post by enriquto »

billfruit wrote: post #10
abdullahkhalids wrote: post #8

SymPy's problem is that it is based on an object-oriented language. This results in SymPy (and friends) demanding that users abandon hundreds of years of math notation, to conform to the whims of a programming language. In SymPy you do M.diagonalize(), which makes no sense. The matrix M does not have a property diagonalize. Rather, you should apply a choosen diagonalization algorithm like Diagonalize(M) to produce a…

May be the way mathematicians notate is frankly ambiguous and confusing, and recent decades of programming experience have given good insight into more expressive methods of notation.

> recent decades of programming experience

as opposed to recent millennia of mathematical experience?

Re: Doing Symbolic Math with SymPy

#20

Post by [deleted] »

abdullahkhalids wrote: post #8

SymPy's problem is that it is based on an object-oriented language. This results in SymPy (and friends) demanding that users abandon hundreds of years of math notation, to conform to the whims of a programming language. In SymPy you do M.diagonalize(), which makes no sense. The matrix M does not have a property diagonalize. Rather, you should apply a choosen diagonalization algorithm like Diagonalize(M) to produce a…

[deleted]
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