Thanks Aaron,

I read the discussion <https://github.com/sympy/sympy/issues/7748> to 
improve pattern matching algorithm. Can you give some information about 
which algorithm is currently being used for pattern matching? 

I have been testing `match()` to check if it works properly for complex 
expressions. It gives correct answer if we `exclude` the integration 
variable. However, there can be issues in matching expression when brackets 
are automatically evaluated by SymPy:

>>> x, y, z, F, fx = symbols('x, y, z, F, fx')

>>> a = Wild('a', exclude=[x])

>>> b = Wild('b', exclude=[x])

>>> c = Wild('c', exclude=[x])

>>> d = Wild('d', exclude=[x])

>>> e = Wild('e', exclude=[x])

>>> f = Wild('f', exclude=[x])

>>> g = Wild('g', exclude=[x])

>>> p = Wild('p', exclude=[x])

>>> n = Wild('n', exclude=[x])

>>> m = Wild('m', exclude=[x])

>>> expr = ((1 + 2*x)**3) * ((F**(4*(5 + fx)))**6) * (6 + 7*(F**(4*(5 + 
fx))))**8

>>> pattern = ((c + d*x)**m) * ((F**(g*(e + fx)))**n) * (a + b*(F**(g*(e + 
fx))))**p

>>> pprint(pattern)

                   p                         n

⎛ g⋅(fx + e)      ⎞           m ⎛ g⋅(fx + e)⎞ 

⎝F          ⋅b + a⎠ ⋅(x⋅d + c) ⋅⎝F          ⎠ 

>>> pprint(expr)

                               8           

 24⋅fx + 120 ⎛   4⋅fx + 20    ⎞           3

F           ⋅⎝7⋅F          + 6⎠ ⋅(2⋅x + 1) 

>>> expr.match(pattern)

{p_: 1, g_: 1, m_: 3, d_: 2, n_: 0, e_: 23*fx + 120, c_: 1, a_: 0, b_: 
(7*F**(4*fx + 20) + 6)**8}


We need to find a way to convert the expresison into known standard form so 
pattern matching can be done peoperly or implement such functionality in 
`.match()` itself.


Thanks



On Thursday, March 9, 2017 at 12:16:41 AM UTC+5:30, Aaron Meurer wrote:
>
> That's sounds fine, though it should also include a docstring that lists 
> the rule so we don't have to depend on the Rubi site. This will also let us 
> generate some documentation on what rules are supported. 
>
> We will likely want to extend the rules beyond what Rubi has eventually, 
> so we should also consider that. 
>
> Aaron Meurer 
>
> On Wed, Mar 8, 2017 at 12:07 PM Arihant Parsoya <[email protected] 
> <javascript:>> wrote:
>
>> Hi, 
>>
>> I observed that rules in manualintegrate() are countable in number. While 
>> implementing ~7000 rules, naming each rule is also going to be a big issue. 
>> I was thinking, names should be given based on the serial number of the 
>> rule in Rubi 
>> <http://www.apmaths.uwo.ca/%7Earich/IntegrationRules/PortableDocumentFiles/PortableDocumentFiles.html>
>>  
>> website. For example algebric rules for linear products 
>> <http://www.apmaths.uwo.ca/%7Earich/IntegrationRules/PortableDocumentFiles/1%20Algebraic%20functions/1%20Linear%20products/1.1%20(a+b%20x)%5Em.pdf>
>>  
>> should be named as:
>>
>> >>> def rule_algebric_integrand_1_1_1_1(expr, symbol):
>>
>> ...     return log(expr)
>>
>> Using the above syntax for names of rules, we will be able to uniquely 
>> identify each rule. Is this desirable?
>>
>> Thanks,
>> Arihant Parsoya
>>
>> On Monday, March 6, 2017 at 10:44:41 PM UTC+5:30, Abdullah Javed Nesar 
>> wrote:
>>>
>>> Hi,
>>>
>>> I was looking into sympy.integrals.manualintegrate.py it seems that the 
>>> pattern matching (in manualintegrate) is quite different from what is 
>>> expected in Rubi. As PR #7748 
>>> <https://github.com/sympy/sympy/issues/7748> mentions we'll be using a 
>>> better approach using decision tree, can you elaborate on what is expected? 
>>> How decision tree concludes to a rule of integration then falls into 
>>> function integrate() which contains rules like 1.1.1 (a + b*x)**m 
>>> <http://www.apmaths.uwo.ca/~arich/IntegrationRules/PortableDocumentFiles/1%20Algebraic%20functions/1%20Linear%20products/1.1%20(a+b%20x)%5Em.pdf>
>>> ?
>>>
>>> Abdullah Javed Nesar 
>>>
>>> On Monday, March 6, 2017 at 2:59:38 AM UTC+5:30, Aaron Meurer wrote:
>>>>
>>>> integrate() uses several algorithms, and one or more algorithms may 
>>>> apply to any specific integral. Some algorithms, if you know how they 
>>>> work, you can easily see if they won't apply to a specific integrand. 
>>>> The best way to tell how it works for a specific integral is to check 
>>>> the various algorithms. Another thing that I highly suggest is to run 
>>>> the integrate() function through a debugger, so you can see how it 
>>>> works (I like PuDB, but any debugger that you are comfortable with 
>>>> will work). 
>>>>
>>>> Here are the algorithms used by integrate() (I hope I didn't forget 
>>>> any).  You can import each algorithm from the specified module to try 
>>>> it 
>>>>
>>>> sympy.integrals.risch.risch_integrate() - Risch algorithm. Currently 
>>>> only works for transcendental equations with exp() and log(). 
>>>>
>>>> sympy.integrals.manualintegrate.manualintegrate() - Manual 
>>>> integration. That means, integration akin to how you would do things 
>>>> by hand. This is very similar to Rubi in that it does pattern matching 
>>>> against some rules. Ideally any implementation of Rubi would merge 
>>>> with manualintegrate() so we don't have two pattern matching 
>>>> integrators. 
>>>>
>>>> sympy.integrals.trigonometry.trigintegrate() - Integrate trig 
>>>> functions. Also uses pattern matching. 
>>>>
>>>> sympy.integrals.rationaltools.ratint() - Integrate rational functions. 
>>>>
>>>> sympy.integrals.meijerint.meijerg_definite() and 
>>>> sympy.integrals.meijerint.meijerg_indefinite() - Integration using the 
>>>> Meijer G algorithm (roughly, by translating the integral to a Meijer 
>>>> G-function, integrating, then translating back). 
>>>>
>>>> sympy.integrals.heurisch.heurisch() - The heuristic Risch algorithm. 
>>>> This is tried last, because it can be very slow (sometimes hanging the 
>>>> integrator), but there are cases where only it can produce an answer. 
>>>>
>>>> You should be able to apply any of these functions directly on an 
>>>> integrand to see if they can produce an answer. 
>>>>
>>>> The algorithms are tried in order until one gives an answer. I don't 
>>>> remember exactly what order, but I think it's similar to the above. I 
>>>> do know that heurisch() is last, because it's the worst. 
>>>>
>>>> Aaron Meurer 
>>>>
>>>>
>>>> On Sun, Mar 5, 2017 at 12:00 PM, Abdullah Javed Nesar 
>>>> <[email protected]> wrote: 
>>>> > Hi Aaron, 
>>>> > 
>>>> > Thanks for your explanation. 
>>>> > 
>>>> > How does SymPy evaluates integrals like, 
>>>> > 
>>>> >>>integrate((a + b*u)**m, x) when u = c + dx  (i.e. Integration by 
>>>> >>> substitution) 
>>>> > 
>>>> > I couldn't find such an example can give one? 
>>>> > 
>>>> > Abdullah Javed Nesar 
>>>> > 
>>>> > On Sunday, March 5, 2017 at 11:58:20 AM UTC+5:30, Aaron Meurer wrote: 
>>>> >> 
>>>> >> The SymPy assumptions system lets you define x = Symbol('x', 
>>>> >> positive=True) (and query like x.is_positive). The pattern matcher 
>>>> >> will need to be able to set and define restrictions like this. Also 
>>>> >> note that expand_log() and logcombine() already expand and combine 
>>>> >> logarithms and check the domain restrictions. 
>>>> >> 
>>>> >> Another thing is that the integrator should return a Piecewise 
>>>> >> whenever possible. For example, the current integrator: 
>>>> >> 
>>>> >> In [6]: integrate(x**n, x) 
>>>> >> Out[6]: 
>>>> >> ⎧log(x)  for n = -1 
>>>> >> ⎪ 
>>>> >> ⎪ n + 1 
>>>> >> ⎨x 
>>>> >> ⎪──────  otherwise 
>>>> >> ⎪n + 1 
>>>> >> ⎩ 
>>>> >> 
>>>> >> This way we get results that are mathematically correct, even when 
>>>> >> assumptions aren't set. 
>>>> >> 
>>>> >> Aaron Meurer 
>>>> >> 
>>>> >> On Thu, Mar 2, 2017 at 8:56 AM, Abdullah Javed Nesar 
>>>> >> <[email protected]> wrote: 
>>>> >> > Hi Ondřej, 
>>>> >> > 
>>>> >> > I am willing to work on Rubi Integrator this summer. I went 
>>>> through the 
>>>> >> > issues you raised for this project and this idea really sounds 
>>>> cool. It 
>>>> >> > would be great to segregate the different methods of integration 
>>>> into a 
>>>> >> > decision tree which would hence improve its performance. 
>>>> >> > 
>>>> >> > Before implementing Rule-based integrator we need to implement 
>>>> fast 
>>>> >> > pattern 
>>>> >> > matching/replacement for the set of 10,000 rules so we need to 
>>>> plan out 
>>>> >> > an 
>>>> >> > efficient decision tree for it. 
>>>> >> > 
>>>> >> > log(x*y) -> log(x) + log(y);   x > 0, y > 0 
>>>> >> > 
>>>> >> > 
>>>> >> > In the above example how do we exactly move on with domain 
>>>> restrictions 
>>>> >> > (i.e. x, y). 
>>>> >> > 
>>>> >> > On Wednesday, March 1, 2017 at 8:39:41 PM UTC+5:30, Ondřej Čertík 
>>>> wrote: 
>>>> >> >> 
>>>> >> >> Hi, 
>>>> >> >> 
>>>> >> >> Here is a project that I would love to see happen: 
>>>> >> >> 
>>>> >> >> https://github.com/sympy/sympy/issues/12233 
>>>> >> >> 
>>>> >> >> I am available to mentor it, and I think quite a few people are 
>>>> >> >> excited about it and such a system/framework (i.e. set of rules 
>>>> for 
>>>> >> >> patter matching + compiler to generate a fast if/then/else 
>>>> decision 
>>>> >> >> tree) would have applications beyond just integration, but 
>>>> integration 
>>>> >> >> would already be super useful. As you can browse on Rubi web 
>>>> page, the 
>>>> >> >> integrator's capabilities are very impressive, i.e. the rule 
>>>> based 
>>>> >> >> system Rubi 4.9 can do more integrals than Mathematica, and is 
>>>> about 
>>>> >> >> as fast, due to the large number of rules, and the if/then/else 
>>>> >> >> decision tree Rubi 5 promises an order of magnitude (or more) 
>>>> speedup, 
>>>> >> >> but it's still in development. 
>>>> >> >> 
>>>> >> >> The project is big in scope, so there could even be multiple 
>>>> projects. 
>>>> >> >> If anybody is interested in this, please get in touch, and try to 
>>>> >> >> propose a good plan. 
>>>> >> >> 
>>>> >> >> Ondrej 
>>>> >> > 
>>>> >> > -- 
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>>>> >> > 
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>>>>  
>>>>
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