Thank you for your feedback. I have added another paragraph in the Motivation section where the I have added how these new solvers are advantageous to the end users.
On Monday, March 23, 2020 at 1:25:31 AM UTC+5:30, Oscar wrote: > > I took a quick look. It's long so I didn't read it fully but it looks > good. There is a lot of detail about what you would do but perhaps the > motivation section can be strengthened. What does all of this mean for > end users etc? If you completed the work described then sympy's > capabilities for systems of ODEs would be expanded enormously. > > On Sun, 22 Mar 2020 at 19:26, Milan Jolly <milan....@gmail.com > <javascript:>> wrote: > > > > Here is the link to my proposal: > https://docs.google.com/document/d/12QN19LSjwEvYoSukyq-BWd76ZrI24FQuU0CGIOIx6Ww/edit?usp=sharing > > > > > On Saturday, March 21, 2020 at 3:22:00 AM UTC+5:30, Oscar wrote: > >> > >> Stating clearly what the different parts do in high-level terms should > >> be sufficient. > >> > >> On Fri, 20 Mar 2020 at 16:57, Milan Jolly <milan....@gmail.com> wrote: > >> > > >> > Thanks for clearing my doubt. > >> > > >> > Now, I have started preparing my GSOC proposal and it will be ready > soon. But, I wanted to know that will it be ok that I don't give details > about the implementations of the helper functions and solvers and simply > state what they do, which parameters they take, what they return and how > they fit in the solving process while I give more details about how they > fit together more generally. I would like to elucidate more on how the main > function ode_sol handles the system of equations using the helper functions > and various solvers as it is the only thing that is not clearly mentioned > in the roadmap. > >> > > >> > On Friday, March 20, 2020 at 7:33:17 PM UTC+5:30, Oscar wrote: > >> >> > >> >> It's not always the case that symmetric matrices commute so actually > >> >> checking if it is symmetric is not sufficient e.g.: > >> >> > >> >> In [83]: M = Matrix([[2*x**2, x], [x, x**2]]) > >> >> > >> >> In [84]: M.is_symmetric() > >> >> Out[84]: True > >> >> > >> >> In [85]: M*M.diff(x) == M.diff(x)*M > >> >> Out[85]: False > >> >> > >> >> Maybe there is something that can be said more generally about > >> >> `exp(M(t)).diff(t)` when `M` is symmetric but does not necessarily > >> >> commute with `M.diff(t)`... > >> >> > >> >> > >> >> On Thu, 19 Mar 2020 at 18:34, Milan Jolly <milan....@gmail.com> > wrote: > >> >> > > >> >> > In ODE systems roadmap, you have mentioned that for system of ODEs > where the coefficient matrix is non-constant, if the coefficient matrix > A(t) is symmetric, then A(t) and its anti derivative B(t) commute and thus > we get the solution based on this fact. But it is also mentioned that if A > and B commuting is more general than when A is symmetric, that is, it is > possible that A is not symmetric but A and B commute. So, for that solver, > should we first compute its anti derivative and test it that commutes with > A or just check if A is symmetric and use the solution? > >> >> > > >> >> > On Wednesday, March 18, 2020 at 3:18:31 AM UTC+5:30, Oscar wrote: > >> >> >> > >> >> >> That sounds reasonable. > >> >> >> > >> >> >> Note that we can't start raising NotImplementedError yet. You > will > >> >> >> need to think about how to introduce the new code gradually while > >> >> >> still ensuring that dsolve falls back on the old code for cases > not > >> >> >> yet handled by the new code. > >> >> >> > >> >> >> On Tue, 17 Mar 2020 at 17:51, Milan Jolly <milan....@gmail.com> > wrote: > >> >> >> > > >> >> >> > So, I have made a rough layout of the main function that will > be used to solve ODEs with the methods like > neq_nth_order_linear_constant_coeff_homogeneous/nonhomogeneous, > neq_nth_linear_symmetric_coeff_homogeneous/nonhomogeneous, special case > non-linear solvers, etc. > >> >> >> > > >> >> >> > Some notations used: > >> >> >> > eqs: Equations, funcs: dependent variables, t: independent > variable, wcc: weakly connected component, scc: strongly connected > component > >> >> >> > > >> >> >> > Introduction to helper functions that will be used(these are > temporary names, parameters and return elements and may be changed if > required): > >> >> >> > > >> >> >> > 1. match_ode:- > >> >> >> > Parameters: eqs, funcs, t > >> >> >> > Returns: dictionary which has important keys like: > order(a dict that has func as a key and maximum order found as value), > is_linear, is_constant, is_homogeneous, eqs, funcs. > >> >> >> > > >> >> >> > 2. component_division:- > >> >> >> > Paramters: eqs, funcs > >> >> >> > Returns: A 3D list where the eqs are first divided into > its wccs and then into its sccs. > >> >> >> > This function is suggested to be implemented later. So, > until all the other solvers are not ready(tested and working), this > function will just take eqs and return [[eqs]]. > >> >> >> > > >> >> >> > 3. get_coeff_matrix:- > >> >> >> > Parameters: eqs, funcs > >> >> >> > Returns: coefficient matrix A(t) and f(t) > >> >> >> > This function takes in a first order linear ODE and > returns matrix A(t) and f(t) from X' = A(t) * X + f(t). > >> >> >> > > >> >> >> > 4. nth_order_to_first_order:- > >> >> >> > Parameters: eqs, order > >> >> >> > Returns: first order ODE with new introduced dependent > variables. > >> >> >> > > >> >> >> > And all the first order linear solvers mentioned above. > >> >> >> > > >> >> >> > Now, besides the main function, there are two separate > functions depending on whether the system of ODEs is linear or not, namely > _linear_ode_sol and _non_linear_ode_sol. > >> >> >> > > >> >> >> > 1. _first_order_linear_ode_sol:- > >> >> >> > Parameters: match dict(obtained earlier and maybe > modified in ode_sol) > >> >> >> > Returns: Dict with keys as func and value as its > solution that solves the ODE. > >> >> >> > Working: First, extracts A(t) and f(t) using > get_coeff_matrix, then using match dict, identify which solver is required > and solve the ODE if it is possible to do so. For example: Case where A(t) > is not symmetric isn't solved. > >> >> >> > > >> >> >> > 2. _non_linear_ode_sol has similar Parameters and Returns but > the function operates differently that's why it is essential to use a > different function. But I don't have a clear understanding > >> >> >> > of how to design _non_linear_ode_sol yet but here is what I > have came up with: First match the condition where it is possible seperate > out the independent variable to get a relationship > >> >> >> > between the dependent variables and then finally, just use > the special solver to solve the ODE. > >> >> >> > > >> >> >> > Now, coming to the main function ode_sol(for now, I haven't > considered initial values):- > >> >> >> > Parameters: eqs, funcs, t > >> >> >> > Returns: Solution in a dict form where func is the key and > value is the solution for that corresponding func. > >> >> >> > > >> >> >> > Working: > >> >> >> > The steps of its working- > >> >> >> > 1. Preprocess the equations. > >> >> >> > 2. Get the match dict using match_ode function. > >> >> >> > 3. Convert nth order equations to first order equations > using nth_order_to_first_order while storing the funcs seperately so that > we can later filter out the dependent variables that were introduced in > this step. > >> >> >> > 4. Get the 3D list of equations using component_division > function. > >> >> >> > 5. Iterate through the wccs and solve and store solutions > seperately but for sccs, first solve the first set of equations in a scc, > then substitute the solutions found in the first set of the current scc to > the second > >> >> >> > set of current scc. Keep doing this until the all the > sets for a particular scc is solved. > >> >> >> > 6. For solving a component, choose either _linear_ode_sol > or _non_linear_ode_sol depending upon the set of equations to be solved. > >> >> >> > 7. Return a dict by taking out values from the solution > obtained using all the dependent variables in funcs as there may be more > variables introduced when we made the system into first order. > >> >> >> > > >> >> >> > For now, this is what I have came up with. Obviously the order > in which we will proceed is, build the basic layout of the main function > and component_division will just increase the number of dimensions to 3 > rudimentarily as we > >> >> >> > will have to first ensure that the general solvers work well > since working on both of them simultaneously will make it tough to pinpoint > the errors. Along with that, non-linear solvers can be implemented later, > we can just raise a > >> >> >> > NotImplementedError for now till we have completed both the > general linear solvers and the component_division and then add the special > case solvers. > >> >> >> > > >> >> >> > On Tuesday, March 17, 2020 at 3:02:29 AM UTC+5:30, Oscar wrote: > >> >> >> >> > >> >> >> >> There are possibilities to go from nonlinear to linear e.g.: > >> >> >> >> > >> >> >> >> In [6]: x, y = symbols('x, y', cls=Function) > >> >> >> >> > >> >> >> >> In [7]: eqs = [x(t).diff(t)**2 - y(t)**2, y(t).diff(t)**2 - > x(t)**2] > >> >> >> >> > >> >> >> >> In [8]: eqs > >> >> >> >> Out[8]: > >> >> >> >> ⎡ 2 2⎤ > >> >> >> >> ⎢ 2 ⎛d ⎞ 2 ⎛d ⎞ ⎥ > >> >> >> >> ⎢- y (t) + ⎜──(x(t))⎟ , - x (t) + ⎜──(y(t))⎟ ⎥ > >> >> >> >> ⎣ ⎝dt ⎠ ⎝dt ⎠ ⎦ > >> >> >> >> > >> >> >> >> In [9]: solve(eqs, [x(t).diff(t), y(t).diff(t)], dict=True) > >> >> >> >> Out[9]: > >> >> >> >> ⎡⎧d d ⎫ ⎧d d > ⎫ > >> >> >> >> ⎧d d ⎫ ⎧d d > ⎫⎤ > >> >> >> >> ⎢⎨──(x(t)): -y(t), ──(y(t)): -x(t)⎬, ⎨──(x(t)): -y(t), > ──(y(t)): > >> >> >> >> x(t)⎬, ⎨──(x(t)): y(t), ──(y(t)): -x(t)⎬, ⎨──(x(t)): y(t), > ──(y(t)): > >> >> >> >> x(t)⎬⎥ > >> >> >> >> ⎣⎩dt dt ⎭ ⎩dt dt > ⎭ > >> >> >> >> ⎩dt dt ⎭ ⎩dt dt > ⎭⎦ > >> >> >> >> > >> >> >> >> On Mon, 16 Mar 2020 at 15:48, Milan Jolly <milan....@gmail.com> > wrote: > >> >> >> >> > > >> >> >> >> > Thanks for the suggestion, I have started with the design > for these solvers. But I have one doubt, namely since now we are using > linear_eq_to_matrix function to check if the system of ODEs is linear or > not, would we require the canonical rearrangements part? Or rather are > there other cases when we can reduce non-linear ODEs into linear ODEs. > >> >> >> >> > > >> >> >> >> > On Monday, March 16, 2020 at 2:53:57 AM UTC+5:30, Oscar > wrote: > >> >> >> >> >> > >> >> >> >> >> That seems reasonable to me. Since the plan is a total > rewrite I think > >> >> >> >> >> that it would be good to put some time in at the beginning > for > >> >> >> >> >> designing how all of these pieces would fit together. For > example even > >> >> >> >> >> if the connected components part comes at the end it would > be good to > >> >> >> >> >> think about how that code would fit in from the beginning > and to > >> >> >> >> >> clearly document it both in issues and in the code. > >> >> >> >> >> > >> >> >> >> >> Getting a good design is actually more important than > implementing all > >> >> >> >> >> of the pieces. If the groundwork is done then other > contributors in > >> >> >> >> >> future can easily implement the remaining features one by > one. Right > >> >> >> >> >> now it is not easy to improve the code for systems because > of the way > >> >> >> >> >> that it is structured. > >> >> >> >> >> > >> >> >> >> >> On Sun, 15 Mar 2020 at 19:27, Milan Jolly < > milan....@gmail.com> wrote: > >> >> >> >> >> > > >> >> >> >> >> > Thanks for your reply. I have planned a rough layout for > the phases. I took a lot of time this past month to understand all the > mathematics that will be involved and have grasped some part of it. > >> >> >> >> >> > > >> >> >> >> >> > If I am lucky and get selected for GSOC'20 for this > organisation, then the below is the rough plan. Please comment on > suggestions if necessary. > >> >> >> >> >> > > >> >> >> >> >> > Community Bonding phase: > >> >> >> >> >> > 1. Using matrix exponential to solve first order linear > constant coefficient homogeneous systems(n equations). > >> >> >> >> >> > 2. Adding new test cases and/or updating old ones. > >> >> >> >> >> > 3. Removing and closing related issues if they are solved > by the addition of this general solver. Identifying and removing the > special cases solvers which are covered by this general solver. > >> >> >> >> >> > > >> >> >> >> >> > Phase I: > >> >> >> >> >> > 1. Adding technique to solve first order constant > coefficient non-homogeneous systems(n equations). > >> >> >> >> >> > 2. Adding the functionality that reduces higher order > linear ODEs to first order linear ODEs(if not done already, and if done, > then incorporating it to solve higher order ODEs). > >> >> >> >> >> > 3. Adding a special case solver when non-constant linear > first order ODE has symmetric coefficient matrix. > >> >> >> >> >> > > >> >> >> >> >> > Phase II: > >> >> >> >> >> > 1. Adding technique to solve non-constant non-homogeneous > linear ODE based off the solver added by the end of Phase I. > >> >> >> >> >> > 2. Evaluating and eliminating unnecessary solvers. > >> >> >> >> >> > 3. Closing related issues solved by the general solvers > and identifying and removing unwanted solvers. > >> >> >> >> >> > 4. Adding basic rearrangements to simplify the system of > ODEs. > >> >> >> >> >> > > >> >> >> >> >> > Phase III: > >> >> >> >> >> > 1. Dividing the ODEs by evaluating which sub-systems are > weakly and strongly connected and handling both of these cases accordingly. > >> >> >> >> >> > 2. Adding a special case solver where the independent > variable can be eliminated and thus solving the system becomes easier. > >> >> >> >> >> > 3. Wrapping things up: adding test cases, eliminating > unwanted solvers and updating documentation. > >> >> >> >> >> > > >> >> >> >> >> > This is the rough layout and my plan for summer if I get > selected. If this plan seems ok then I would include this plan in my > proposal. > >> >> >> >> >> > > >> >> >> >> >> > On Saturday, March 14, 2020 at 9:37:31 PM UTC+5:30, Oscar > wrote: > >> >> >> >> >> >> > >> >> >> >> >> >> It's hard to say how much time each of these would take. > The roadmap > >> >> >> >> >> >> aims to completely replace all of the existing code for > systems of > >> >> >> >> >> >> ODEs. How much of that you think you would be able to do > is up to you > >> >> >> >> >> >> if making a proposal. > >> >> >> >> >> >> > >> >> >> >> >> >> None of the other things described in the roadmap is > implemented > >> >> >> >> >> >> anywhere as far as I know. Following the roadmap it > should be possible > >> >> >> >> >> >> to close all of these issues I think: > >> >> >> >> >> >> > https://github.com/sympy/sympy/issues?q=is%3Aopen+is%3Aissue+label%3Asolvers.dsolve.system > > >> >> >> >> >> >> > >> >> >> >> >> >> On Fri, 13 Mar 2020 at 22:30, Milan Jolly < > milan....@gmail.com> wrote: > >> >> >> >> >> >> > > >> >> >> >> >> >> > I have mostly read and understood matrix exponentials > and Jordan forms along with the ODE systems roadmap. But I am unclear as to > what has already been done when it comes to implementing the general > solvers. For example: The matrix exponentials part has already been > implemented and now I have a PR that has revived the matrix exponential > code. > >> >> >> >> >> >> > > >> >> >> >> >> >> > I want to make a proposal and contribute to make these > general solvers during this summer if my proposal gets accepted. But I am > unclear what should be the parts I need to work during community bonding > period, phase 1, phase 2 and phase 3 as I am unaware how much time each > part of the general solvers would take. > >> >> >> >> >> >> > > >> >> >> >> >> >> > If someone can help me in this regard(helping me with > these 2 questions) then it would be great. > >> >> >> >> >> >> > > >> >> >> >> >> >> > > >> >> >> >> >> >> > On Tue, Feb 25, 2020, 5:09 AM Milan Jolly < > milan....@gmail.com> wrote: > >> >> >> >> >> >> >> > >> >> >> >> >> >> >> I will go through the roadmap. Also, I will work on > reviving and finishing the stalled PRs namely the matrix exponential one > for now as I am interested in working towards this. Thanks. > >> >> >> >> >> >> >> > >> >> >> >> >> >> >> On Mon, Feb 24, 2020, 9:56 PM Oscar Benjamin < > oscar.j...@gmail.com> wrote: > >> >> >> >> >> >> >>> > >> >> >> >> >> >> >>> This section in the roadmap refers to existing > stalled PRs trying to > >> >> >> >> >> >> >>> fix the n-equations solver for constant coefficient > homogeneous ODEs > >> >> >> >> >> >> >>> which is the first step: > >> >> >> >> >> >> >>> > https://github.com/sympy/sympy/wiki/ODE-Systems-roadmap#constant-coefficients---current-status > > >> >> >> >> >> >> >>> > >> >> >> >> >> >> >>> A first step would be to attempt to revive one or > both of those PRs > >> >> >> >> >> >> >>> and finish them off. > >> >> >> >> >> >> >>> > >> >> >> >> >> >> >>> On Mon, 24 Feb 2020 at 05:59, Milan Jolly < > milan....@gmail.com> wrote: > >> >> >> >> >> >> >>> > > >> >> >> >> >> >> >>> > So, I am interested in rewriting parts of the > current ODE as discussed in the roadmap. Is there any work started in that > direction and if not then can I create a PR for the same? > >> >> >> >> >> >> >>> > > >> >> >> >> >> >> >>> > On Mon, Feb 24, 2020, 2:52 AM Oscar Benjamin < > oscar.j...@gmail.com> wrote: > >> >> >> >> >> >> >>> >> > >> >> >> >> >> >> >>> >> The current refactoring effort applies only to > the case of solving > >> >> >> >> >> >> >>> >> *single* ODEs. The ODE systems code also needs to > be refactored but > >> >> >> >> >> >> >>> >> (in my opinion) needs a complete rewrite. That is > what the roadmap is > >> >> >> >> >> >> >>> >> about (it describes how to rewrite everything). > The code for systems > >> >> >> >> >> >> >>> >> of ODEs should also get refactored in the process > but there is no need > >> >> >> >> >> >> >>> >> to "refactor" it in its current form if it is in > fact being > >> >> >> >> >> >> >>> >> *completely* rewritten: we can just make sure > that the new code is > >> >> >> >> >> >> >>> >> written the way we want it to be. > >> >> >> >> >> >> >>> >> > >> >> >> >> >> >> >>> >> On Sun, 23 Feb 2020 at 19:52, Milan Jolly < > milan....@gmail.com> wrote: > >> >> >> >> >> >> >>> >> > > >> >> >> >> >> >> >>> >> > Ok so I have gone through the links suggested > and I have realised that as far as ODE module is concerned, refactoring is > the most important task. But, as far as that is concerned, I think Mohit > Balwani is working on this for a while and I want to limit any collisions > with my co-contributors. So, I have couple of ideas to work on: > >> >> >> >> >> >> >>> >> > 1. Helping to extend the solvers, > i.e.implementing a fully working n-equations solver for constant > coefficient homogeneous systems. This is from the ODE systems map. I am > interested in working on this but I understand that it might be hard to > work upon it while refactoring takes place. Still, if its possible to work > on this and if no one else has started to work in this direction yet then I > am willing to work for this. > >> >> >> >> >> >> >>> >> > 2. Using connected components function > implemented by Oscar Benjamin in https://github.com/sympy/sympy/pull/16225 > to enhance ODE solvers and computing eigen values faster as mentioned here > https://github.com/sympy/sympy/issues/16207 . > >> >> >> >> >> >> >>> >> > 3. This idea is not mentioned in the ideas page > and is something of my own. If there is anything possible, then I can also > work on extending functions like maximum, minimum, argmax, argmin, etc in > calculus module. I have been working on the issue > https://github.com/sympy/sympy/pull/18550 and I think there is some scope > to extend these functionalities. > >> >> >> >> >> >> >>> >> > > >> >> >> >> >> >> >>> >> > On Sunday, February 23, 2020 at 1:32:20 AM > UTC+5:30, Milan Jolly wrote: > >> >> >> >> >> >> >>> >> >> > >> >> >> >> >> >> >>> >> >> Hello everyone, > >> >> >> >> >> >> >>> >> >> > >> >> >> >> >> >> >>> >> >> My name is Milan Jolly and I am an > undergraduate student at Indian Institute of Technology, Patna. For the > past 2 month, I have been learning and exploring sympy through either > contributions, reading documentation or trying examples out. This last > month I have learned a lot of new things thanks to the well designed > code-base, the structured way this community works and most importantly the > maintainers who make it work. It has been a pleasure to be a part of the > community. > >> >> >> >> >> >> >>> >> >> > >> >> >> >> >> >> >>> >> >> I am interested in participating for GSoC this > year and I would like to work for this org during the summers if I am > lucky. I particularly want to work on improving the current ODE module as > it is given in the idea list. There is a lot of work that needs to be taken > care of like: > >> >> >> >> >> >> >>> >> >> 1. Implementing solvers for solving constant > coefficient non-homogeneous systems > >> >> >> >> >> >> >>> >> >> 2. Solving mixed order ODEs > >> >> >> >> >> >> >>> >> >> 3. Adding rearrangements to solve the system > >> >> >> >> >> >> >>> >> >> > >> >> >> >> >> >> >>> >> >> These are not my ideas but I have taken > inspiration from the ideas page but I am up for working on these. If > someone can guide me regarding this then it would be really helpful. > >> >> >> >> >> >> >>> >> > > >> >> >> >> >> >> >>> >> > -- > >> >> >> >> >> >> >>> >> > 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 sy...@googlegroups.com. > >> >> >> >> >> >> >>> >> > To view this discussion on the web visit > https://groups.google.com/d/msgid/sympy/1033f581-abbb-4be5-a5b2-1988f4261535%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 sy...@googlegroups.com. > >> >> >> >> >> >> >>> >> To view this discussion on the web visit > 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