(ps I'm aware that the examples (sum, Max) I gave up there use iterables )
Here's an excerpt from the model training dataset
what be the maximum of D, m => Max ( D , m )
what be the max of D, m => Max ( D , m )
what be the biggest of D, m => Max ( D , m )
find the sum of D, m => sum ( D , m )
find the total of D, m => sum ( D , m )
find the minimum of D, m => Min ( D , m )
find the min of D, m => Min ( D , m )
find the smallest of D, m => Min ( D , m )
find the maximum of D, m => Max ( D , m )
find the max of D, m => Max ( D , m )
The above dataset is from a lemmatized version of natural language queries
(is -> be)
and this is how the output looks like when passed to sympify
>>> sympify('Max(1, 2, 3)')
3
>>> sympify('Max(1, 2, x)')
Max(2, x)
On Thursday, May 14, 2020 at 12:23:45 AM UTC+5:30, Moses Paul wrote:
>
>
>
> On Wednesday, May 13, 2020 at 11:47:22 PM UTC+5:30, Aaron Meurer wrote:
>>
>> What sorts of things is it able to parse?
>>
>
> As of now, it can do stuff like
>
> - "What is the maximum of x,3,4,5,y" which returns Max(3,4,5,x,y)
> (passed to sympify)
> - "Find the sum of x, x+y, x^3" -> sum(x, x+y, x**3)
> - "Calculate the integral of x^2 + 3x" -> Integral(x**2+3*x)
> - "Sum of x from 0 to 100" -> Sum(x, (x, 0, 100))
>
> Kinda like that.
> ( I'm structuring work I've done so far, I'll post a link to my repo here,
> once I finish that )
>
>>
>> I don't know if there is a well structured glossary of SymPy
>> functions. The default namespace (what gets imported with "from sympy
>> import *") is the best place to start.
>>
>> Gotcha!
>
> Aaron Meurer
>>
>> On Wed, May 13, 2020 at 11:19 AM Moses Paul <[email protected]> wrote:
>> >
>> > So I've been working on an NLP parser for sympy.
>> > This is how it works,
>> >
>> > The Input is first "cleaned up" and rewritten into a structure that is
>> comprehended by a NMT model (seq2seq)
>> > The processed input is passed on to the model which then gives a
>> specific type of output, which is then "processed".
>> > The final result is one that works when used inside
>> > sympify('Expression')
>> >
>> > So Far I've been able to train using data generated from Functions
>> similar to Sum, Max, Min i.e functions with a list of inputs and also with
>> functions such as Summations and Integrals.
>> > Since I haven't gone through SymPy's entire codebase, it would be
>> really useful if I had sort of a Glossary or an equivalent structure from
>> which I can glean information about the various functions SymPy has, like a
>> list of single parameter functions, two parameters, multiple parameters and
>> so on.
>> >
>> > I haven't been able to find anything so far, help would be much
>> appreciated
>> >
>> > Cheers
>> > Moses Paul
>> >
>> > --
>> > 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 [email protected].
>> > To view this discussion on the web visit
>> https://groups.google.com/d/msgid/sympy/9fef4da7-aa4f-4c47-ac44-932efacb1dcd%40googlegroups.com.
>>
>>
>>
>
--
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 [email protected].
To view this discussion on the web visit
https://groups.google.com/d/msgid/sympy/e88b5533-19d6-4b0f-9ce7-222735b1adfc%40googlegroups.com.
