Mailman 3 September 2001 - NumPy-Discussion

ANN: gracePlot.py
by Nathaniel Gray 30 Sep '01

30 Sep '01

__________________________________________________________________ Announcing: gracePlot.py v0.5 An interactive, user-friendly python interface to the Grace plotting package. __________________________________________________________________ * WHAT IS IT? gracePlot.py is a high-level interface to the Grace plotting package available at: http://plasma-gate.weizmann.ac.il/Grace/ The goal of gracePlot is to offer the user an interactive plotting capability similar to that found in commercial packages such as Matlab and Mathematica, including GUI support for modifying plots and a user-friendly, pythonic interactive command-line interface. * WHAT FEATURES DOES IT OFFER? Since this package is in the early stages of development it does not yet provide high-level command-line access to all of Grace's plotting functionality. It does, however, offer: * Line Plots (with or without errorbars) * Histograms (with or without errorbars) * Multiple graphs (sets of axes) per plot * Multiple simultaneous plots (grace sessions) * Overlaid graphs, using a 'hold' command similar to Matlab's * Legends, titles, axis labels, and axis limits * Integration with Numerical Python and Scientific Python's Histogram object Note that all advanced features and customizations are available through the Grace UI, so you can compose rough plots in Python and then polish them up in Grace. * HOW DO I USE IT? Here is an example session that creates a plot with two sets of axes, putting a line plot in one and a histogram in the other: Python 2.1.1 (#2, Jul 31 2001, 14:10:42) [GCC 2.96 20000731 (Linux-Mandrake 8.0 2.96-0.48mdk)] on linux2 Type "copyright", "credits" or "license" for more information. >>> from gracePlot import gracePlot >>> p = gracePlot() # A grace session opens >>> p.plot( [1,2,3,4,5], [10, 4, 2, 4, 10], [1, 0.7, 0.5, 1, 2], ... symbols=1 ) # A plot with errorbars & symbols >>> p.title('Funding: Ministry of Silly Walks') >>> p.ylabel('Funding (Pounds\S10\N)') >>> p.multi(2,1) # Multiple plots: 2 rows, 1 column >>> p.xlimit(0, 6) # Set limits of x-axis >>> p.focus(1,0) # Set current graph to row 1, column 0 >>> p.histoPlot( [7, 15, 18, 20, 21], x_min=1, ... dy=[2, 3.5, 4.6, 7.2, 8.8]) # A histogram w/errorbars >>> p.xlabel('Silliness Index') >>> p.ylabel('Applications/yr') >>> p.xlimit(0, 6) # Set limits of x-axis The result of this session can be found at: http://www.idyll.org/~n8gray/code/index.html * WHERE DO I GET IT? gracePlot is available here: http://www.idyll.org/~n8gray/code/index.html ___________________________________________________________ Cheers, -n8 -- Nathaniel Gray California Institute of Technology Computation and Neural Systems --

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Re: [Numpy-discussion] searching for a better 3d field file format
by Rob 28 Sep '01

28 Sep '01

Hi Janko, yes I would love to have it. Thank you! I once installed Viz5D, but didn't quite know what to do with it. One thing though, the Windows version requires an X11 server, but thats better than no program at all :) I also installed OpenDX, the FreeBSD port version, but everytime I try to do anything it core dumps. I also want to look into VRML. Rob. Janko Hauser wrote: > > I would try vis5d, which is a very nice out of the box viewer of > 5D-Data. I have a module which can write vis5d-files directly from > numpy-data. The module is not polished, so if there is interest I > would send it privatly to you. > > http://vis5d.sourceforge.net/ > > http://www.ssec.wisc.edu/~billh/vis5d.html > > HTH, > > __Janko > > Rob writes: > > I've been using the "brick of bytes" format for my FDTD outputs, but > > unfortunately I can' find any type of 3d viewer for Windows. I am now > > using the X11/OpenGL based Animabob, which creates a movie of the series > > of dumped files. > > > > I am thinking of trying some other type of file format and viewer. I am > > wondering what others use to view 3d fields or data? Of course if it > > used Numpy and Python all the better. > > > > Thanks, Rob. > > > > > > -- > > The Numeric Python EM Project > > > > www.members.home.net/europax > > > > _______________________________________________ > > Numpy-discussion mailing list > > Numpy-discussion(a)lists.sourceforge.net > > https://lists.sourceforge.net/lists/listinfo/numpy-discussion -- The Numeric Python EM Project www.members.home.net/europax

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searching for a better 3d field file format
by Rob 27 Sep '01

27 Sep '01

I've been using the "brick of bytes" format for my FDTD outputs, but unfortunately I can' find any type of 3d viewer for Windows. I am now using the X11/OpenGL based Animabob, which creates a movie of the series of dumped files. I am thinking of trying some other type of file format and viewer. I am wondering what others use to view 3d fields or data? Of course if it used Numpy and Python all the better. Thanks, Rob. -- The Numeric Python EM Project www.members.home.net/europax

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Can I further Numpy-ize this code?
by Rob 27 Sep '01

27 Sep '01

I've been working on this for so long I may be missing the obvious. Here is a snippet of code that I would like to at least get rid of one more indexing operation. The problem is the presence of the one dimensional array constants which are functions of x,y, or z depending on their location: (you may recognize this as some FDTD code) Any ideas? Thanks, Rob. ####################################/ # Update the interior of the mesh: # all vector H vector components # ## for az in range(0,nz): for ay in range(0,ny): for ax in range(0,nx): dstore[ax,ay,0:nz]=Bx[ax,ay,0:nz] Bx[ax,ay,0:nz] = Bx[ax,ay,0:nz] * C1[0:nz] + ( ( (Ey[ax,ay,1:(nz+1)]-Ey[ax,ay,0:nz] ) / dz - (Ez[ax,ay+1,0:nz]-Ez[ax,ay,0:nz]) / dy ) * C2[0:nz] ) Hx[ax,ay,0:nz]= Hx[ax,ay,0:nz] * C3[ay] + ( ( Bx[ax,ay,0:nz] * C5[ax] - dstore[ax,ay,0:nz] * C6[ax] ) * C4h[ay] ) dstore[ax,ay,0:nz]=By[ax,ay,0:nz] By[ax,ay,0:nz] = By[ax,ay,0:nz] * C1[ax] + ( ( (Ez[ax+1,ay,0:nz]-Ez[ax,ay,0:nz]) / dx - (Ex[ax,ay,1:(nz+1)]-Ex[ax,ay,0:nz]) / dz ) * C2[ax] ) Hy[ax,ay,0:nz]= Hy[ax,ay,0:nz] * C3[0:nz] + ( ( By[ax,ay,0:nz] * C5[ay] - dstore[ax,ay,0:nz] * C6[ay] ) * C4h[0:nz] ) dstore[ax,ay,0:nz]=Bz[ax,ay,0:nz] Bz[ax,ay,0:nz] = Bz[ax,ay,0:nz] * C1[ay] + ( ( (Ex[ax,ay+1,0:nz]-Ex[ax,ay,0:nz] ) / dy - (Ey[ax+1,ay,0:nz]-Ey[ax,ay,0:nz] ) / dx ) * C2[ay] ) Hz[ax,ay,0:nz]= Hz[ax,ay,0:nz] * C3[ax] + ( ( Bz[ax,ay,0:nz] * C5[0:nz] - dstore[ax,ay,0:nz] * C6[0:nz] ) * C4h[ax] ) -- The Numeric Python EM Project www.members.home.net/europax

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FAST and EASY data plotting for Python, NumPy and Qt
by Gerard Vermeulen 26 Sep '01

26 Sep '01

Announcing PyQwt-0.29.91 FAST and EASY data plotting for Python, NumPy and Qt PyQwt is a set of Python bindings for the Qwt C++ class library. The Qwt library extend the Qt framework with widgets for Scientific and Engineering applications. It contains QwtPlot, a 2d plotting widget, and widgets for data input/output such as and QwtCounter, QwtKnob, QwtThermo and QwtWheel. PyQwt requires and extends PyQt, a set of Python bindings for Qt. PyQwt requires NumPy. NumPy extends the Python language with new data types that make Python an ideal language for numerical computing and experimentation (like MatLab, but better). The home page of PyQwt is http://gerard.vermeulen.free.fr NEW in PyQwt-0.29.91: 1. compatible with PyQt-2.5/sip-2.5 and PyQt-2.4/sip-2.4. 2. compatible with NumPy-20.2.0, and lower. 3. *.exe installer for Windows (requires Qt-2.3.0-NC). 4. build instructions for Windows and other versions of Qt. 5. HTML documentation with installation instructions and a reference listing the Python calls to PyQwt that are different from the corresponding C++ calls to Qwt. 6. fixed reference counting bug in the methods with NumPy arrays as arguments. 7. new methods: QwtPlot.axisMargins() QwtPlot.closestCurve() QwtPlot.curveKeys() QwtPlot.markerKeys() QwtPlot.title() QwtPlot.titleFont() QwtScale.labelFormat() QwtScale.map() 8. changed methods: QwtCurve.verifyRange() -- cleaned up interface QwtPlot.adjust() -- is now fully implemented QwtPlot.enableLegend() -- (de)selects all items or a single item 9. removed methods (incompatible with Python, because unsafe, even in C++): QwtCurve.setRawData() QwtPlot.setCurveRawData() QwtSpline.copyValues() Gerard Vermeulen

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append number to vector
by Henry Harpending 25 Sep '01

25 Sep '01

I often find myself wanting to append a number to a vector. After fumbling experimentation I use def comma(ar,inint): "comma(array,integer) returns array with integer appended" t=array([inint,]) return(concatenate((ar,t),1)) which is used like the comma in apl, i.e. ar <- ar, inint. This seems klutzy to me. Is there a simpler way to do it? If ar were a list, ar.append(inint) works, but no such luck after ar has become an array. Thanks, Henry Harpending, University of Utah

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expect a new wave of Numpy'ers
by Rob 20 Sep '01

20 Sep '01

I just announced a ham radio type FDTD simulation to the ham newsgroups. I couldn't resist trying out a ham type antenna, instead of all the waveguide stuff I've been doing. Rob. -- The Numeric Python EM Project www.members.home.net/europax

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Offset 2D arrays
by Mike Romberg 19 Sep '01

19 Sep '01

I am attempting to create 2D arrays which are offset copies of a given starting array. For example if I have a 2D array like this: array([[1, 2, 3], [4, 5, 6], [7, 8, 9]]) I would like to offset it by some amount in either or both the x and y dimension. Lets say that both the x and y offset would be 1. Then I would like to have an array like this: array([[5, 6, 0], [8, 9, 0], [0, 0, 0]]) Here I don't really care about the values which are now zero. The main point is that now I can compare the data values at any given (x,y) point with the values at the adjacent point (over one on each axis). This would be useful for the kinds of calculations we need to do. I just can't come up with a numeric way to do this. Does anyone have any ideas? Thanks alot, Mike Romberg (romberg(a)fsl.noaa.gov)

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simple array help?
by Pete Shinners 17 Sep '01

17 Sep '01

i have a simple array with floating values >>> print a array([ 0. , 0.2, 0.4, 0.6, 0.8]) what i need to do is change each index into another dimension with 3 indices. hmm, kind of confusing, an example will explain better >>> b = array(zip(a,a,a)) >>> print b array([[ 0. , 0. , 0. ], [ 0.2, 0.2, 0.2], [ 0.4, 0.4, 0.4], [ 0.6, 0.6, 0.6], [ 0.8, 0.8, 0.8]]) ok, this does the job, but once i start using large arrays, the back-n-forth conversion between arrays and python lists is costing me quite a bit. is there a way i can reshape the array this way without the call to python's 'zip'? (no, 'map' doesn't count either) i've tried much fooling with NewAxis, resize, and friends. but either i haven't stumbled upon the correct combination or i'm not trying the correct tools. i'd like to keep this as quick as possible, so hopefully it can be done without anything too elaborate. thanks (doh, sorry for the previous distutils related post... hit the wrong mailing list)

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RE: Segfault with latest lapack_litemodule using complex matrices.
by Paul F. Dubois 17 Sep '01

17 Sep '01

A. Mirone rode to the rescue and the fix is available as Numeric-20.2.1.tar.gz or in CVS. -----Original Message----- From: Travis Oliphant [mailto:oliphant.travis@ieee.org] Sent: Saturday, September 15, 2001 6:58 PM To: Paul F. Dubois Subject: Segfault with latest lapack_litemodule using complex matrices. Hi Paul, With the latest changes to the lapack_lite module, I now get segfaults when I'm trying to load call LinearAlgebra.eigenvectors using a complex-valued matrix. Could you check this on your system? Thanks, -Travis

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