[SciPyuser] (no subject)
James Bednar
jbednar@inf.ed.ac...
Wed Oct 3 09:13:52 CDT 2007
Subject: Re: [SciPyuser] plotting a surface
InReplyTo: <mailman.96104.1191343217.30507.scipyuser@scipy.org>
References: <mailman.96104.1191343217.30507.scipyuser@scipy.org>
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From: "James A. Bednar" <jbednar@inf.ed.ac.uk>
 Date: Tue, 02 Oct 2007 04:56:56 0400
 From: Joe Harrington <jh@physics.ucf.edu>
 Subject: Re: [SciPyuser] plotting a surface
 Cc:
 MessageID: <1191315416.6370.780.camel@glup.physics.ucf.edu>
 ContentType: text/plain

 Or, you could just do it with matplotlib...

 http://physicsmajor.wordpress.com/2007/04/22/3dsurfacewithmatplotlib/

 This was the first hit on a google search for "matplotlib surface". I
 tested it and it works in 0.90.1.

 jh




 

 Message: 2
 Date: Tue, 2 Oct 2007 07:42:38 0400
 From: Tommy Grav <tgrav@mac.com>
 Subject: [SciPyuser] Scipy Superpack for OS X
 To: scipyuser@scipy.org
 MessageID: <F1E9D29DD8F04B19B3472B5E8D7C8DC4@mac.com>
 ContentType: text/plain; charset=USASCII; delsp=yes; format=flowed

 I downloaded the Scipy Superpack for OS X at trichech.us, and noticed
 that there
 are inconsistencies in the different webpages:

 scipy.org claims that the binary installation version give you
 version 0.6.0
 trichech.us says that the metapackage contains recent SVN builds of
 version 0.7
 The downloaded scipy superpack for PPC Macintosh however lists the
 version as 0.5.3
 (which is what is installed).

 Some reconciliation of the three webpages pointing to the same
 resource might be
 in order.

 Cheers
 Tommy




 

 Message: 3
 Date: Tue, 02 Oct 2007 20:52:38 +0900
 From: David Cournapeau <david@ar.media.kyotou.ac.jp>
 Subject: Re: [SciPyuser] Scipy Superpack for OS X
 To: SciPy Users List <scipyuser@scipy.org>
 MessageID: <47023106.1010901@ar.media.kyotou.ac.jp>
 ContentType: text/plain; charset=ISO88591; format=flowed

 Tommy Grav wrote:
 > I downloaded the Scipy Superpack for OS X at trichech.us, and noticed
 > that there
 > are inconsistencies in the different webpages:
 >
 > scipy.org claims that the binary installation version give you
 > version 0.6.0
 > trichech.us says that the metapackage contains recent SVN builds of
 > version 0.7
 0.6.0 is released, but 0.7.0 is not yet (SVN build of 0.7 means that it
 is between 0.6 and 0.7, if this is what bothers you here)
 > The downloaded scipy superpack for PPC Macintosh however lists the
 > version as 0.5.3
 > (which is what is installed).
 This looks more like a problem at trichech.us, no ?

 cheers,

 David


 

 Message: 4
 Date: Tue, 2 Oct 2007 08:21:08 0400
 From: Tommy Grav <tgrav@mac.com>
 Subject: Re: [SciPyuser] Scipy Superpack for OS X
 To: SciPy Users List <scipyuser@scipy.org>
 MessageID: <566BB51AB43D4E76ACA9FD87DFD03F3B@mac.com>
 ContentType: text/plain; charset=USASCII; format=flowed

 > This looks more like a problem at trichech.us, no ?

 I guess the correct person to correct all this would be
 trichech.us, which is the maintainer of this great resource.
 I just wanted to point out the inconsistencies in the hope
 that someone would be able to reconcile it :)

 Cheers
 Tommy


 

 Message: 5
 Date: Tue, 2 Oct 2007 09:37:41 0400
 From: Alan G Isaac <aisaac@american.edu>
 Subject: Re: [SciPyuser] HodrickPrescott filter
 To: SciPy Users List <scipyuser@scipy.org>
 MessageID: <Mahogany0.67.0157620071002093741.00@american.edu>
 ContentType: TEXT/PLAIN; CHARSET=UTF8

 On Mon, 1 Oct 2007, Alan G Isaac apparently wrote:
 > I'm looking for a HodrickPrescott filter.
 > http://en.wikipedia.org/wiki/HodrickPrescott_filter#External_links
 > Is there one in SciPy, or can someone post one?


 Well, nobody replied to this yet, so here is a really basic
 implementation: ``hpfilter`` in
 http://econpy.googlecode.com/svn/trunk/pytrix/tseries.py
 Suggestions welcome.

 Cheers,
 Alan Isaac





 

 Message: 6
 Date: Tue, 2 Oct 2007 08:40:45 0700
 From: "Christopher Burns" <cburns@berkeley.edu>
 Subject: Re: [SciPyuser] OS X users  Please try multiple
 scipy.test() runs
 To: "SciPy Users List" <scipyuser@scipy.org>
 MessageID:
 <764e38540710020840j64f0ed1fs5caea77ea0f8a282@mail.gmail.com>
 ContentType: text/plain; charset="iso88591"

 All tests pass on my OSX machine. Thanks Pearu.

 On 10/2/07, Pearu Peterson <pearu@cens.ioc.ee> wrote:
 >
 >
 > I have ported the veclib support from scipy.linalg to
 > scipy.lib.blas. I cannot test it myself. So, anyone
 > on OSX who had problems with scipy.lib, could you
 > execute the following commands:
 >
 > cd svn/scipy/scipy/lib/blas
 > python setup.py build
 > python tests/test_fblas.py
 >
 > to see if tests pass or if there are any compiler errors?
 >
 > Pearu
 >

 
 Christopher Burns, Software Engineer
 Computational Infrastructure for Research Labs
 10 Giannini Hall, UC Berkeley
 phone: 510.643.4014
 http://cirl.berkeley.edu/
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 Message: 7
 Date: Tue, 2 Oct 2007 09:18:42 0700
 From: "Dinesh B Vadhia" <dineshbvadhia@hotmail.com>
 Subject: [SciPyuser] NumPy matrixvector calculation
 To: <scipyuser@scipy.org>
 MessageID: <BAY109DAV1B0A9363EF6EB5D46D49DA3AE0@phx.gbl>
 ContentType: text/plain; charset="iso88591"

 Hello! I am an experienced software engineer but relatively new to Python, NumPy and SciPy. I'll say up front that I've have scanned all the pertinent documentation including the paidfor NumPy book but not found an answer to our problem(s):

 We have an MxN (M not equal to N) integer matrix A. The data for A is readin from a file on persistant storage and the data is immutable (ie. does not change and cannot be changed).

 The vector x is a vector of size Nx1. The data elements of x are calculated during the program execution.

 We then perform a matrixvector calculation ie. y = Ax, where the resulting y is a Mx1 vector.

 Both x and y are then discarded and a new x and y are calculated and this continues until program execution stops but at all times the matrix A remains the same until ...

 Under certain circumstances, we may have to increase the size of M to M+R leaving N alone ie. append R rows to the end of matrix A. We would want to do this while the program is executing.

 Here are the questions:

  What NumPy array structure do we use for A  an array or matrix (and why)?
  If A is a matrix data structure then do the x and y vectors have to be matrix structures too or can you mix the data structures?
  If A is a matrix or an array structure, can we append rows during program execution and if so, how do we do this?

 Any help towards these questions will be gratefully appreciated. Thankyou

 Dinesh
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 Message: 8
 Date: Tue, 2 Oct 2007 12:39:46 0400
 From: "Anne Archibald" <peridot.faceted@gmail.com>
 Subject: Re: [SciPyuser] NumPy matrixvector calculation
 To: "SciPy Users List" <scipyuser@scipy.org>
 MessageID:
 <ce557a360710020939m7193d209u47202dffd1cdf857@mail.gmail.com>
 ContentType: text/plain; charset=UTF8

 On 02/10/2007, Dinesh B Vadhia <dineshbvadhia@hotmail.com> wrote:

 > We have an MxN (M not equal to N) integer matrix A. The data for A is
 > readin from a file on persistant storage and the data is immutable (ie.
 > does not change and cannot be changed).
 >
 > The vector x is a vector of size Nx1. The data elements of x are calculated
 > during the program execution.
 >
 > We then perform a matrixvector calculation ie. y = Ax, where the resulting
 > y is a Mx1 vector.
 >
 > Both x and y are then discarded and a new x and y are calculated and this
 > continues until program execution stops but at all times the matrix A
 > remains the same until ...
 >
 > Under certain circumstances, we may have to increase the size of M to M+R
 > leaving N alone ie. append R rows to the end of matrix A. We would want to
 > do this while the program is executing.
 >
 > Here are the questions:
 >
 >  What NumPy array structure do we use for A  an array or matrix (and why)?
 >  If A is a matrix data structure then do the x and y vectors have to be
 > matrix structures too or can you mix the data structures?
 >  If A is a matrix or an array structure, can we append rows during program
 > execution and if so, how do we do this?

 The only difference between numpy arrays and matrices is the way
 functions act on them  in particular, the * operator behaves
 differently (for arrays it operates elementwise and for matrices it
 applies the matrix product, specifically the function dot()). As data
 structures they are identical.

 When you talk about increasing M, that presumably means enlarging A.
 Is your idea that A has changed on disk? (You did say it was
 immutable.) The short answer is that you basically can't enlarge an
 array in place, as it is (under the hood) a single large block of
 memory. Copying is not all that expensive, for a onceinawhile
 operation, so you can just use hstack() or vstack() or concatenate()
 to enlarge A, allocating a new array in the process. If A is on disk,
 and you want to reflect changes on disk, you can try using numpy's
 memory mapped arrays: these take advantage of your operating system's
 ability to make a disk file look like a piece of memory. Each
 matrixvector product does require traversing all of A, though, so the
 matrix will need to be loaded into memory regardless. (Incidentally,
 if you combine several vectors into a matrix and multiply them by A
 all at once it will probably be faster, since numpy/scipy uses
 optimized matrixmultiplication routines that are reasonably smart
 about cache.)

 Anne


 

 Message: 9
 Date: Tue, 2 Oct 2007 18:40:13 +0200
 From: "Matthieu Brucher" <matthieu.brucher@gmail.com>
 Subject: Re: [SciPyuser] NumPy matrixvector calculation
 To: "SciPy Users List" <scipyuser@scipy.org>
 MessageID:
 <e76aa17f0710020940y1e752f8cy8d34de10aecdb54a@mail.gmail.com>
 ContentType: text/plain; charset="iso88591"

 Hi,

 Matrix and array are basically the same, you can do what you want with both,
 the only difference you will notice is that the multplication is the matrix
 multiplication in one case and the elementwise multiplication in the other
 case. Just try to be consistent and use only matrix or only arrays.
 Then, if you have to add rows or columns, see hstack() and vstack()

 Matthieu

 2007/10/2, Dinesh B Vadhia <dineshbvadhia@hotmail.com>:
 >
 > Hello! I am an experienced software engineer but relatively new to
 > Python, NumPy and SciPy. I'll say up front that I've have scanned all the
 > pertinent documentation including the paidfor NumPy book but not found an
 > answer to our problem(s):
 >
 > We have an MxN (M not equal to N) integer matrix A. The data for A is
 > readin from a file on persistant storage and the data is immutable (ie.
 > does not change and cannot be changed).
 >
 > The vector x is a vector of size Nx1. The data elements of x are
 > calculated during the program execution.
 >
 > We then perform a matrixvector calculation ie. y = Ax, where the
 > resulting y is a Mx1 vector.
 >
 > Both x and y are then discarded and a new x and y are calculated and this
 > continues until program execution stops but at all times the matrix A
 > remains the same until ...
 >
 > Under certain circumstances, we may have to increase the size of M to M+R
 > leaving N alone ie. append R rows to the end of matrix A. We would want to
 > do this while the program is executing.
 >
 > Here are the questions:
 >
 >  What NumPy array structure do we use for A  an array or matrix (and
 > why)?
 >  If A is a matrix data structure then do the x and y vectors have to be
 > matrix structures too or can you mix the data structures?
 >  If A is a matrix or an array structure, can we append rows during
 > program execution and if so, how do we do this?
 >
 > Any help towards these questions will be gratefully appreciated.
 > Thankyou
 >
 > Dinesh
 >
 >
 > _______________________________________________
 > SciPyuser mailing list
 > SciPyuser@scipy.org
 > http://projects.scipy.org/mailman/listinfo/scipyuser
 >
 >
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