Francesco is the most knowledgeable about this subject. Jason moorepants.info +01 530-601-9791
On Thu, Mar 28, 2019 at 9:24 AM <zhiqik...@gmail.com> wrote: > Hello Jason, > > Thank you! It seems that you are quite busy now greeting to the newbies. > :-) > I am waiting for someone to review my proposal. Could you please tell me > to whom I should reach out? > > Regards, > Zhiqi > > 在 2019年3月28日星期四 UTC+1下午5:14:46，Jason Moore写道： >> >> Zhiqi, >> >> This looks well thought out a first glance. Check out >> https://github.com/sympy/sympy/wiki/GSoC-2019-Student-Instructions if >> you haven't yet. >> >> Jason >> moorepants.info >> +01 530-601-9791 >> >> >> On Wed, Mar 27, 2019 at 12:13 AM <zhiq...@gmail.com> wrote: >> >>> Hello, >>> >>> >>> My name is Zhiqi KANG, I am a 4th year undergraduate of a 5-year >>> engineering institution: Université de Technologie de Compiègne, France. I >>> am interested in the project Linear algebra: Tensor core.Here is the link >>> for the description of project idea. >>> https://github.com/sympy/sympy/wiki/GSoC-2019-Ideas#linear-algebra-tensor-core >>> Even >>> though I am not very familiar with the tensor in the physical field, its >>> principal in the mathematical field is quite interesting. I have >>> precisely looked at the requirement of this project and make sure that I am >>> capable to accomplish most of its task. However, there are still many >>> questions that I would like to discuss with all contributors of SymPy and >>> expecially with the mentor. One urgent problem is that I don't find the >>> name of mentor for this project, so I don't really know who I should CC. >>> Could you please help me to find the mentor for this project? >>> >>> >>> Please review this draft proposal and tell me what to be ameliorated. >>> Thank you! >>> >>> >>> >>> Ø Better Algorithms for sparse array: >>> >>> The idea is to manipulate directly les arrays in the sparse array level. >>> Casting sparse arrays to a dense array and then operating is kind of a >>> redundancy. I have found an example in tomatrix() function of >>> sympy\sympy\tensor\array\sparse_ndim_array.py where we convert the >>> sparse_array to a new dictionay and then cast it to matrix.(Code bellow) >>> >>> But I cannot find more cases in the array/tensor module, it would be >>> great if some one can help me find out where other cases are. >>> >>> >>> from sympy.matrices import SparseMatrix >>> >>> if self.rank() != 2: >>> >>> raise ValueError('Dimensions must be of size of 2') >>> >>> mat_sparse = {} >>> >>> for key, value in self._sparse_array.items(): >>> >>> mat_sparse[self._get_tuple_index(key)] = value >>> >>> return SparseMatrix(self.shape[0], self.shape[1], mat_sparse) >>> >>> >>> >>> Ø NumPy-like operations >>> >>> We have now some operations for arrays in SymPy: >>> >>> ² arrayfy >>> >>> ² tensor product >>> >>> ² derivatives by array >>> >>> ² permute dimension >>> >>> ² contraction >>> >>> For this part of project, I am planning to implement some operations >>> such as: >>> >>> ² sum >>> >>> ² divide/multiply(element wise) >>> >>> ² any >>> >>> ² comparators(greater/less/equal) >>> >>> ² logical operator(and/or/not/xor) >>> >>> ² random >>> >>> >>> >>> Ø lazy operators on arrays >>> >>> lazy evaluation can improve the performance while iterating the array >>> since it creates value only if it is called. To implement lazy operators, I >>> am thinking about two plans: >>> >>> 1. Create a new sub-module named lazy-array (larray) of which most >>> of the operations are lazy evaluated. A standard Array can be cast to a >>> lazy-array by simply calling the constructor of larray and passing it as >>> parameter. By doing so, users can choose whatever they want in the module >>> level, which means that to manipulate a simple array or a lazy array. >>> >>> >>> >>> 1. Create a lazy version for les operators mentioned above. The >>> lazy operators are accessible for a specific purpose. This implementation >>> focusses on a function level for calling lazy evaluated operations, which >>> means to call a simple inverse_matrix function or a lazy one. >>> >>> >>> >>> Besides, I have found in sympy\sympy\tensor\tensor.py a class >>> _TensorDataLazyEvaluator which can be an example for me to implement these >>> functionalities. It has methods like delete item, inverse matrix, etc. >>> >>> >>> >>> Ø code generation for arrays and array operators >>> >>> This part of project should be involved with another GSoC project purely >>> for code generation. I would like to discuss with the mentor of the codegen >>> project to have a better point of view for it. >>> >>> I have had an internship for 6 months in BNP Paribas Securities Services >>> in Paris as developer. During this period, I have similarly worked on code >>> generation task, except that the programming language is C#.( I was using >>> EntityFramework and T4 by Microsoft) I believe that this experience can >>> help me to get familiar with the code generation process in this project. >>> >>> >>> >>> Ø Integration over indexed symbols and arrays >>> >>> Firstly, I would like to talk about integration over arrays: >>> >>> Can we imagine the array as a set of coordinates? Suppose that we have a >>> array A, say 2-dimension as (p, q). We can image two axis x and y so that >>> index i and j are coordinates for the point Pij in axis x and axis y. The >>> value A[pi,qj] should be the coordinate of axis z. By assuming this, we can >>> use a Riemann integral or Lebesgue integral to calculate its integration >>> like summing the column in the 3D space. >>> >>> I don’t know if this idea is correct, I would love to discuss it with >>> you! >>> >>> >>> >>> Secondly, for integration over indexed symbols, I don’t really know what >>> it means. Should the output be an expression rather than a value? It would >>> be great if someone can show me with an example, thanks! >>> >>> >>> >>> Ø Equation solving with indexed symbols. >>> >>> I am not very familiar with this topic either. Should the result be an >>> expression as well? It would be great if someone can show me with an >>> example, thanks! >>> >>> >>> Ø Implement some well-known tensor math >>> >>> If the time permits, I would be glad to do the extra part of this >>> project. But I don’t know very well relativity, electromagnetism, etc. >>> It would take me some time to better understand the principles and start to >>> work on it. However, I do find some math formula that associated with this >>> topic. https://en.wikipedia.org/wiki/Integral >>> >>> >>> Ø Unify the various SymPy module >>> >>> To be done. >>> >>> >>> -- >>> 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 post to this group, send email to sy...@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/a5ff49d3-63e4-45e5-b87f-4b9d6be30085%40googlegroups.com >>> <https://groups.google.com/d/msgid/sympy/a5ff49d3-63e4-45e5-b87f-4b9d6be30085%40googlegroups.com?utm_medium=email&utm_source=footer> >>> . >>> For more options, visit https://groups.google.com/d/optout. >>> >> -- > 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/91ab9eee-afef-41fa-8b60-ea2b47fb074c%40googlegroups.com > <https://groups.google.com/d/msgid/sympy/91ab9eee-afef-41fa-8b60-ea2b47fb074c%40googlegroups.com?utm_medium=email&utm_source=footer> > . > For more options, visit https://groups.google.com/d/optout. > -- 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/CAP7f1Ah8btwxHXNL3Lqmx5prp18y7LEC8%3DpCdkb7KZ7zGZ%2BnzA%40mail.gmail.com. For more options, visit https://groups.google.com/d/optout.
