I have just rewritten and add a few functions for row operations in my
current PR. The diff looks quite messy just have a look at [1]. This is
rewritten although it is largely the same.
Here is the summary of profile results. I am now using gmpy ground types.
>>> for i in range(1000, 3000):
... n.append(i)
...
>>> for i in range(1000, 3000):
... m.append(n)
...
>>> a = Matrix(m)
>>> cProfile.run("a + a")
40012072 function calls in 23.230 seconds
ncalls tottime percall cumtime percall filename:lineno(function)
4000000 1.624 0.000 2.809 0.000 matrices.py:152(<lambda>)
4000000 2.575 0.000 13.641 0.000 matrices.py:519(<lambda>)
4000000 3.077 0.000 4.052 0.000 numbers.py:1522(__new__)
4000000 4.845 0.000 11.066 0.000 numbers.py:1588(__add__)
8000000 2.486 0.000 2.486 0.000 sympify.py:50(sympify)
12002006 3.145 0.000 3.145 0.000 {isinstance}
4002000 0.297 0.000 0.297 0.000 {method 'append' of 'list'
objects}
>>> cProfile.run("add(m, m, ZZ)")
28008005 function calls in 12.874 seconds
ncalls tottime percall cumtime percall filename:lineno(function)
2000 5.772 0.003 12.492 0.006 densetools.py:11(addrow)
8000000 2.280 0.000 3.151 0.000 domain.py:64(new)
8000000 3.230 0.000 6.381 0.000 domain.py:67(__call__)
8000000 0.871 0.000 0.871 0.000 {gmpy.mpz}
Of course the part that is pulling current matrices backwards are the
sympify calls and calls from numbers.py. I am not sure if sympify will be
added in the WIP matrix design. Also interesting are the lambda calls of
Matrix class.
I have not found any difference if I make the list of lists as this. They
take exactly the same number of function calls. Maybe I am doing something
wrong here.
m, n = [], []
>>> for i in range(1000, 3000):
... n.append(ZZ(i))
...
>>> for m in range(1000, 3000):
... m.append(n)
Also, can anyone please see if the current thing is in right direction as
level 0 of dense? I am now working assuming that dense matrices will be
represented internally just as lists of lists. I would especially
appreciate feedback from Mateusez since the design is similar to Polys'
design he implemented[2]
Also, can anyone please suggest me some references for algorithms of rref?
I know it's currently in sympy but I want to explore if I can make the
current thing faster.
-Saurabh
[1]
https://github.com/SaurabhJha/sympy/blob/d62233663e5d234090124aacce71fe37106e5a32/sympy/matrices/densetools.py
[2] http://mattpap.github.io/masters-thesis/html/index.html
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