In the thread ; https://groups.google.com/forum/#!topic/sympy/eUfW6C_nHdI
I was seeking feedback and help with the problem of type ;
( 1.414213562^6000) % 400)
After reviewing all the excellent collaboration at the above link, Im
feeling
a little lost and overwhelmed. So many good suggestions were made and
also a lot of bugs, and bottlenecks discovered - Im not sure which approach
is best for what I am hoping to solve?
Ive been reviewing the problems with the different approaches, including
precision loss
with use of floats, some of the suggested functions, etc.
Oscar mentioned the solution of using a string value and storing it as a
possibility?
My hope is to arrive at a method that returns lossless precision, if I dont
have to sacrifice speed then
thats great but if preserving accuracy comes at a cost of speed thats ok
with me.
I'd like also to get the highest precision available, if possible past the
15 digit limit, the larger the better.
What do you guys think is the best code solution for ;
given any rational between 1.0x and 2, for example "1.414213562"
being raised to a power as high as 6000
with modulus returned of 400
( 1.414213562^6000) % 400) ?
So that the greatest and most accurate precision is kept?
I have been testing out some of the code ideas such as ;
from sympy import mpmath
mpmath.mp.dps = 821
x = mpmath.mpf('1.414213562') ** 6000
Thanks Oscar, Aaron and everyone! I have a few questions to ask, but first
wanted to say this entire thread has been so meaningful as a learning
process for me!
I am an intermediate VB programmer and newbie to python and this single
thread you have all been so gracefully collaborating together on has taught
me more and helped me to understand the issues surrounding this than any
other source online I have researched and I am saving this entire thread
for future use and review!
I have been trying to keep pace with all the excellent insights and
suggestions as well as potential bottlenecks.
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