[SciPy-user] (no subject)

James Bednar jbednar at inf.ed.ac.uk
Wed Oct 3 10:13:52 EDT 2007


Subject: Re: [SciPy-user] plotting a surface
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From: "James A. Bednar" <jbednar at inf.ed.ac.uk>

|  Date: Tue, 02 Oct 2007 04:56:56 -0400
|  From: Joe Harrington <jh at physics.ucf.edu>
|  Subject: Re: [SciPy-user] plotting a surface
|  Cc: 
|  Message-ID: <1191315416.6370.780.camel at glup.physics.ucf.edu>
|  Content-Type: text/plain
|  
|  Or, you could just do it with matplotlib...
|  
|  http://physicsmajor.wordpress.com/2007/04/22/3d-surface-with-matplotlib/
|  
|  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 at mac.com>
|  Subject: [SciPy-user] Scipy Superpack for OS X
|  To: scipy-user at scipy.org
|  Message-ID: <F1E9D29D-D8F0-4B19-B347-2B5E8D7C8DC4 at mac.com>
|  Content-Type: text/plain; charset=US-ASCII; delsp=yes; format=flowed
|  
|  I downloaded the Scipy Superpack for OS X at trichech.us, and noticed  
|  that there
|  are in-consistencies in the different webpages:
|  
|  scipy.org claims that the binary installation version give you  
|  version 0.6.0
|  trichech.us says that the meta-package 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 at ar.media.kyoto-u.ac.jp>
|  Subject: Re: [SciPy-user] Scipy Superpack for OS X
|  To: SciPy Users List <scipy-user at scipy.org>
|  Message-ID: <47023106.1010901 at ar.media.kyoto-u.ac.jp>
|  Content-Type: text/plain; charset=ISO-8859-1; format=flowed
|  
|  Tommy Grav wrote:
|  > I downloaded the Scipy Superpack for OS X at trichech.us, and noticed  
|  > that there
|  > are in-consistencies in the different webpages:
|  >
|  > scipy.org claims that the binary installation version give you  
|  > version 0.6.0
|  > trichech.us says that the meta-package 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 at mac.com>
|  Subject: Re: [SciPy-user] Scipy Superpack for OS X
|  To: SciPy Users List <scipy-user at scipy.org>
|  Message-ID: <566BB51A-B43D-4E76-ACA9-FD87DFD03F3B at mac.com>
|  Content-Type: text/plain; charset=US-ASCII; 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 at american.edu>
|  Subject: Re: [SciPy-user] Hodrick-Prescott filter
|  To: SciPy Users List <scipy-user at scipy.org>
|  Message-ID: <Mahogany-0.67.0-1576-20071002-093741.00 at american.edu>
|  Content-Type: TEXT/PLAIN; CHARSET=UTF-8
|  
|  On Mon, 1 Oct 2007, Alan G Isaac apparently wrote:
|  > I'm looking for a Hodrick-Prescott filter. 
|  > http://en.wikipedia.org/wiki/Hodrick-Prescott_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 at berkeley.edu>
|  Subject: Re: [SciPy-user] OS X users - Please try multiple
|  	scipy.test() runs
|  To: "SciPy Users List" <scipy-user at scipy.org>
|  Message-ID:
|  	<764e38540710020840j64f0ed1fs5caea77ea0f8a282 at mail.gmail.com>
|  Content-Type: text/plain; charset="iso-8859-1"
|  
|  All tests pass on my OSX machine.  Thanks Pearu.
|  
|  On 10/2/07, Pearu Peterson <pearu at 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 at hotmail.com>
|  Subject: [SciPy-user] NumPy matrix-vector calculation
|  To: <scipy-user at scipy.org>
|  Message-ID: <BAY109-DAV1B0A9363EF6EB5D46D49DA3AE0 at phx.gbl>
|  Content-Type: text/plain; charset="iso-8859-1"
|  
|  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 paid-for 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 read-in 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 matrix-vector 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.  Thank-you 
|  
|  Dinesh
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|  
|  ------------------------------
|  
|  Message: 8
|  Date: Tue, 2 Oct 2007 12:39:46 -0400
|  From: "Anne Archibald" <peridot.faceted at gmail.com>
|  Subject: Re: [SciPy-user] NumPy matrix-vector calculation
|  To: "SciPy Users List" <scipy-user at scipy.org>
|  Message-ID:
|  	<ce557a360710020939m7193d209u47202dffd1cdf857 at mail.gmail.com>
|  Content-Type: text/plain; charset=UTF-8
|  
|  On 02/10/2007, Dinesh B Vadhia <dineshbvadhia at hotmail.com> wrote:
|  
|  > We have an MxN (M not equal to N) integer matrix A.  The data for A is
|  > read-in 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 matrix-vector 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 once-in-a-while
|  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
|  matrix-vector 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 matrix-multiplication routines that are reasonably smart
|  about cache.)
|  
|  Anne
|  
|  
|  ------------------------------
|  
|  Message: 9
|  Date: Tue, 2 Oct 2007 18:40:13 +0200
|  From: "Matthieu Brucher" <matthieu.brucher at gmail.com>
|  Subject: Re: [SciPy-user] NumPy matrix-vector calculation
|  To: "SciPy Users List" <scipy-user at scipy.org>
|  Message-ID:
|  	<e76aa17f0710020940y1e752f8cy8d34de10aecdb54a at mail.gmail.com>
|  Content-Type: text/plain; charset="iso-8859-1"
|  
|  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 at 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 paid-for 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
|  > read-in 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 matrix-vector 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.
|  > Thank-you
|  >
|  > Dinesh
|  >
|  >
|  > _______________________________________________
|  > SciPy-user mailing list
|  > SciPy-user at scipy.org
|  > http://projects.scipy.org/mailman/listinfo/scipy-user
|  >
|  >
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