This would be a lot more readable, to me, if you supplied a J
implementation that matched the informal math notation (which is easy
to read for people that mostly already know what you were going to
say).

Thanks,

-- 
Raul

On Thu, Oct 3, 2013 at 10:11 AM, km <[email protected]> wrote:
> Cool examples given in Gilbert Strang's Introduction to Linear Algebra are
>
>
> From Section 6.2 -- The solution to u(k+1) = A uk starting from u0 is
>
> uk = A^k  u0 = S Lambda^k  S^-1 u0 , so that
>
> uk = c1 lambda1^k x1 + ... + cn lambdan^k xn  provided
>
> u0 = c1 x1 + ... + cn xn   (xk is eigenvector corrresponding to eigenvalue 
> lamdak)
>
> Lambda is a diagonal matrix with the eigenvalues of A on the diagonal, and S 
> is a
> square matrix whose columns are the eigenvectors.  Strang illustrates with the
> Fibonnaci sequence F0 F1 F2 ... , setting  uk = ( F(k+1) , Fk )  and u0 = (1 
> , 0) .
>
>
> From Section 6.3 -- The solution to u' = A u starting from u(0) is
>
> u(t) = c1 e^(lambda1 t) x1 + ... + cn e^(lambdan t) xn  provided
>
> u(0) = c1 x1 + ... + cn xn .  The solution can be expressed as
>
> u(t) = e^(A t) u(0)  with the matrix exponential e^(A t) .
>
> Equations involving y'' reduce to u' = A u by combining y' and y into
>
> u = (y' , y)
>
>
> --Kip Murray
>
> Sent from my iPad
>
>> On Oct 3, 2013, at 6:10 AM, Raul Miller <[email protected]> wrote:
>>
>> I was looking at those the other day and ran into a variety of difficulties.
>>
>> I'll not bore you with the details, but I'll admit that I would love
>> to see some pages devoted to example usages.
>>
>> I'm not really looking for comprehensive, in-depth documentation -
>> that's already available through web searching ... if I can understand
>> what terms I need to use to search on. What I'm looking for are cool
>> examples - things that probe the possibilities, bits of prose perhaps
>> which hint at relevant search terms. Failed attempts might also be
>> useful, as stepping stones for finding or writing more better or
>> slightly beautiful expositions.
>>
>> Thanks,
>>
>> --
>> Raul
>>
>>> On Wed, Oct 2, 2013 at 12:27 PM, km <[email protected]> wrote:
>>> Here is a resource that should be better known.  To use it you load
>>> ~addons/math/mt/mt.ijs    --Kip Murray
>>>
>>>
>>>>>> On Mon, Apr 8, 2013 at 3:17 AM, Kip Murray <[email protected]> wrote:
>>>>>
>>>>> Igor Zhuravlof provides j routines that model LAPACK routines for
>>>>> eigenvalues and eigenvectors.  See "matrix toolbox"
>>>>>
>>>>> ~addons/math/mt
>>>>>
>>>>> with contents summarized in
>>>>>
>>>>> ~addons/math/mt/mt.ijs
>>>>>
>>>>> I have not tried them but would expect them to run in j701JHS.
>>>
>>> Sent from my iPad
>>>
>>>> On Oct 2, 2013, at 9:21 AM, Raul Miller <[email protected]> wrote:
>>>>
>>>> J's support for mechanisms to compute eigenvalues has been rather
>>>> messy. And, by messy I mean that it looks like we rarely exercise
>>>> these mechanisms - we don't have unit tests on the entry points to be
>>>> run before uploading library updates, we don't have particularly good
>>>> documentation on the code we have and there are other problems.
>>>>
>>>> Here's an example I stumbled over today:
>>>>
>>>>  docs_jlapack_''
>>>> |value error: dirs
>>>> |       dirs jpathsep path,'doc/*.lap'
>>>>  require'dirs'
>>>> not found: /Users/rdmiller/Applications/j64-801/bin/dirs
>>>> |file name error: script
>>>> |       0!:0 y[4!:55<'y'
>>>>  require 'dir'
>>>>  docs_jlapack_''
>>>> |value error: dirs
>>>> |       dirs jpathsep path,'doc/*.lap'
>>>>  getscripts_j_ 'dir'
>>>>
>>>>
>>>> So here's a question: does anyone have the time and energy to put into
>>>> this mess?
>>>>
>>>> Thanks,
>>>>
>>>> --
>>>> Raul
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