[ANN] PyDSTool 0.88 -- dynamical systems modeling tools
A new release of the dynamical systems modeling toolbox PyDSTool is available from Sourceforge: http://www.sourceforge.net/projects/pydstool/ Highlights from the release notes: * Cleanup of global imports, especially: entire numpy.random and linalg namespaces no longer imported by default * Added support for 'min' and 'max' keywords in functional specifications (for ODE right-hand sides, for instance) * Optimization tools from third-party genericOpt (included with permission) and improved parameter estimation examples making use of this code * Numerical phase-response calculations now possible in PRC toolbox * Fully-fledged DSSRT toolbox for neural modeling (see wiki page) * New tests/demonstrations in PyDSTool/tests * Major improvements to intelligent expr2func (symbolic - python function conversion) * Improved compatibility with cross-platform use and with recent python versions and associated libraries * Added many minor features (see timeline on Trac http://jay.cam.cornell.edu/pydstool/timeline) * Fixed many bugs and quirks (see timeline on Trac http://jay.cam.cornell.edu/pydstool/timeline) This is mainly a bugfix release in preparation for a substantial upgrade at version 0.90, which will have a proper installer, unit testing, symbolic expression support via SymPy, and greatly improved interfacing to legacy ODE integrators. These features are being actively developed in 2009/2010. For installation and setting up, please carefully read the GettingStarted page at our wiki for platform-specific details: http://pydstool.sourceforge.net Please use the bug tracker and user discussion list at Sourceforge to report bugs or provide feedback. Code and documentation contributions are always welcome. Regards, Rob Clewley -- http://mail.python.org/mailman/listinfo/python-announce-list Support the Python Software Foundation: http://www.python.org/psf/donations/
Re: Mathematical Python Library
The closest thing so far is probably going to be a combination of the numpy, scipy, and sympy libraries. The latter is the one with the most functionality for solving equations algebraically, but is also the least mature package at the moment. The first two also provide the basic tools for calculating the nulls of a function (for instance) as numerical approximations, provided you are able to write small scripts to use those tools. -Rob On Mon, Apr 7, 2008 at 12:05 PM, mc [EMAIL PROTECTED] wrote: I'm looking for a library which can do mathematical stuff like solving equations. Or calculation the nulls of a function and so on. Does anyone know one? Thanks in advance! -- http://mail.python.org/mailman/listinfo/python-list -- Robert H. Clewley, Ph. D. Assistant Professor Department of Mathematics and Statistics Georgia State University 720 COE, 30 Pryor St Atlanta, GA 30303, USA tel: 404-413-6420 fax: 404-651-2246 http://www.mathstat.gsu.edu/~matrhc http://brainsbehavior.gsu.edu/ -- http://mail.python.org/mailman/listinfo/python-list
Re: Can someone tell me why i get None at the end please this has me stuck for ages
You get None b/c that's what's being returned from your join strings function. Your function already prints out the result and doesn't return the joined strings a your usage case expects. So either return the joined strings from your function and don't print them inside the function, or vice versa. Besides, can't you just use print .join(list_of_strings) ? On Mon, Feb 23, 2009 at 2:22 PM, Gary Wood woody...@sky.com wrote: '''exercise to complete and test this function''' import string def joinStrings(items): '''Join all the strings in stringList into one string, and return the result. For example: print joinStrings(['very', 'hot', 'day']) 'veryhotday' ''' word = [items] for item in items: print (item, end='') def main(): print(joinStrings(['very', 'hot','day'])) print(joinStrings(['this', 'is','it'])) print(joinStrings(['1', '2', '3', '4', '5'])) main() -- http://mail.python.org/mailman/listinfo/python-list
[JOB] Short-term python programming consultant - funds expire soon!
Dear Pythonistas, Our open-source software project (PyDSTool) has money to hire an experienced Python programmer on a short-term, per-task basis as a technical consultant (i.e., no fringe benefits offered). The work can be done remotely and will be paid after the satisfactory completion of the objectives. The work must be completed by the end of April, when the current funds expire. The basic work plan and design documents are already laid out from previous work on these tasks, but the finer details will be negotiable. We plan to pay approximately $2-3k per task, depending on the exact code design and amount of time required. Prospective consultants could be professionals or students but must have proven experience with SWIG and both python and numpy distutils, and be willing to write a short document about the completed work for future maintenance purposes. We have a template for a simple contract and invoices can be relatively coarse-grained. As an open-source project, all contributed code will be BSD licensed as part of our project, although it will retain attribution of your authorship. We have two objectives for this work, which could be satisfied by two individual consultants but more likely by one: (1) This objective involves completing the implementation of automated compilation of C code into DLLs. These DLLs are dynamically created from a user's specification in python. The DLLs can be updated and reloaded if the user changes specifications at the python level. This functionality is crucial to providing fast solving of differential equations using legacy solvers written in C and Fortran. This functionality is relatively independent from the inner workings of our project so there should be minimal overhead to completing this task. We need to complete the integration of an existing code idea for this objective with the main trunk of our project. The existing code works as a stand-alone test for our C legacy solver but is not completed for our Fortran legacy solver (so that numpy's distutils needs to be used instead of python distutils) and needs to be integrated into the current SVN trunk. The design document and implementation for the C solver should be a helpful template for the Fortran solver. (2) We need a setup.py package installer for our project that automatically compiles the static parts of the legacy differential equation solvers during installation according to the directory structure and SWIG/distutils implementation to be completed in objective (1). If the consultant is experienced with writing python package installers, he/she may wish to negotiate working on a more advanced system such as an egg installer. PyDSTool (pydstool.sourceforge.net) is a multi-platform, open-source environment offering a range of library tools and utilities for research in dynamical systems modeling for scientists and engineers. Please contact Dr. Rob Clewley (rclewley) at (@) the Department of Mathematics, Georgia State University (gsu.edu) for more information. -- Robert H. Clewley, Ph.D. Assistant Professor Department of Mathematics and Statistics and Neuroscience Institute Georgia State University 720 COE, 30 Pryor St Atlanta, GA 30303, USA tel: 404-413-6420 fax: 404-413-6403 http://www2.gsu.edu/~matrhc http://brainsbehavior.gsu.edu/ -- http://mail.python.org/mailman/listinfo/python-list
Re: [JOB] Short-term python programming consultant - funds expire soon!
Please see http://www.python.org/community/jobs/ for where to post this most effectively. OK, sorry, I hadn't seen that site before. Our open-source software project (PyDSTool) has money to hire an experienced Python programmer on a short-term, per-task basis as a technical consultant (i.e., no fringe benefits offered) FYI I also discovered that the funds will in fact be available until **early June** which I will correct in the posting to that jobs site. Thanks, Rob -- http://mail.python.org/mailman/listinfo/python-list
pyconfig on 64-bit machines with distutils vs 32-bit legacy code
Hi, I have a problem compiling legacy C code using distutils on a colleague's 64 bit intel machine running linux. The legacy code is linked to user-generated code from python and distutils is a convenient platform independent way to call whatever compiler is available to create a DLL as a python module via SWIG. My code works fine on 32 bit machines, but on a 64 bit machine the error /data/home/nwagner/local/lib/python2.5/pyport.h:734:2: #error LONG_BIT definition appears wrong for platform (bad gcc/glibc config?). was generated. I looked this error up and found it referred to a bug in python about pyconfig.h not being automatically adaptive when mixing 32-bit code and 64-bit libraries. There were various vague references to solutions and a supposed fix in python, but the posts were at least a couple of years old and didn't make a lot of sense to me. I tried adding the '-m32' option to the gcc call using extra_compile_args but that was not enough. According to a different suggestion on a different mailing list, I tried replacing pyconfig.h with a version that used 32-bit settings for the size of LONG and the other 64-bit specific sizes. That did not help at all. The gcc call created from my PyDSTool package's code via distutils is (slightly reformatted for easy reading): gcc -pthread -fno-strict-aliasing -DNDEBUG -g -O3 -Wall -Wstrict-prototypes -fPIC -I/data/home/nwagner/local/lib/python2.5/site-packages/numpy/core/include -I/data/home/nwagner/local/lib/python2.5/site-packages/numpy/numarray -I/data/home/nwagner/svn/PyDSTool/PyDSTool/tests -I/data/home/nwagner/svn/PyDSTool/PyDSTool/integrator -I/data/home/nwagner/svn/PyDSTool/PyDSTool/tests/dopri853_temp -I/data/home/nwagner/local/include/python2.5 -c /data/home/nwagner/svn/PyDSTool/PyDSTool/tests/dopri853_temp/dop853_HHnet_vf_wrap.c -o /data/home/nwagner/svn/PyDSTool/PyDSTool/tests/dopri853_temp/data/home/nwagner/svn/PyDSTool/PyDSTool/tests/dopri853_temp/dop853_HHnet_vf_wrap.o -w -m32 -D__DOPRI__ Can anyone offer any advice as to what I might be missing or misunderstanding? I assumed it would be possible to do this compilation even if a 64 bit version of python has been installed on this linux box. I'm somewhat out of my depth talking about these internal gubbins so please go easy on me. Thanks in advance, Rob -- http://mail.python.org/mailman/listinfo/python-list
Re: pyconfig on 64-bit machines with distutils vs 32-bit legacy code
Thanks for replying, Martin. I got my colleague (Nils) to run exactly the gcc call you described in your post (see below for what he ran) but it only returns the following: /home/nwagner/svn/PyDSTool/PyDSTool/tests/dopri853_temp/dop853_HHnet_vf_wrap.c:124:20: error: Python.h: Datei oder Verzeichnis nicht gefunden /home/nwagner/svn/PyDSTool/PyDSTool/tests/dopri853_temp/dop853_HHnet_vf_wrap.c:2495:4: error: #error This python version requires swigto be run with the '-classic' option In file included from /home/nwagner/local/lib64/python2.6/site-packages/numpy/core/include/numpy/ndarrayobject.h:61, from /home/nwagner/local/lib64/python2.6/site-packages/numpy/core/include/numpy/arrayobject.h:14, from /home/nwagner/local/lib64/python2.6/site-packages/numpy/numarray/numpy/libnumarray.h:7, from /home/nwagner/svn/PyDSTool/PyDSTool/tests/dopri853_temp/dop853_HHnet_vf_wrap.c:2758: /home/nwagner/local/lib64/python2.6/site-packages/numpy/core/include/numpy/npy_common.h:71:2: error: #error Must use Python with unicode enabled. The command was gcc -pthread -fno-strict-aliasing -DNDEBUG -g -O3 -Wall -Wstrict-prototypes -fPIC -I/data/home/nwagner/local/lib/python2.5/site-packages/numpy/core/include -I/data/home/nwagner/local/lib/python2.5/site-packages/numpy/numarray -I/data/home/nwagner/svn/PyDSTool/PyDSTool/tests -I/data/home/nwagner/svn/PyDSTool/PyDSTool/integrator -I/data/home/nwagner/svn/PyDSTool/PyDSTool/tests/dopri853_temp -I/data/home/nwagner/local/include/python2.5 -E -dD /data/home/nwagner/svn/PyDSTool/PyDSTool/tests/dopri853_temp/dop853_HHnet_vf_wrap.c -w -m32 -D__DOPRI__ Maybe Nils can pick up the thread from here. Thanks, Rob On Sun, Mar 22, 2009 at 2:36 AM, Martin v. Löwis mar...@v.loewis.de wrote: /data/home/nwagner/local/lib/python2.5/pyport.h:734:2: #error LONG_BIT definition appears wrong for platform (bad gcc/glibc config?). Can anyone offer any advice as to what I might be missing or misunderstanding? You need to understand where the error comes from: 1. what is the *actual* value of SIZEOF_LONG (it should be 4)? 2. what is the actual value of LONG_BIT, and where does it come from? (it should be 32) To understand that better, I recommend to edit the command line of gcc in the following way (assuming you use gcc 4.x): 1. replace -c with -E -dD 2. remove the -o file option This will generate preprocessor output to stdout, which you then need to search for SIZEOF_LONG and LONG_BIT. Searching back for # number lines will tell you where the definition was made. If that doesn't make it clear what the problem is, post your findings here. Regards, Martin -- http://mail.python.org/mailman/listinfo/python-list
ANN: PyDSTool 0.85 released
We have released an update to the PyDSTool dynamical systems and modeling package at http://sourceforge.net/projects/pydstool. There are lots of minor improvements and fixes in this version, but a powerful new feature is the support for user-defined functions for continuation using PyCont. We have also added some tools for basic phase-plane analysis, calculation of phase response curves for oscillators, and support for some special math functions. Please see the release notes for more details, and the documentation at http://pydstool.sourceforge.net. We plan to continue to add features and improve our code over the coming months, and we look forward to hearing feedback on our progress. In particular, contributions are very welcome. Thanks again to the Scipy, Numpy, Matplotlib, and SWIG developers for facilitating our work! -- The PyDSTool developers -- http://mail.python.org/mailman/listinfo/python-list
New python module to simulate arbitrary fixed and infinite precision binary floating point
Dear Pythonistas,
How many times have we seen posts recently along the lines of why is
it that 0.1 appears as 0.10001 in python? that lead to
posters being sent to the definition of the IEEE 754 standard and the
decimal.py module? I am teaching an introductory numerical analysis
class this fall, and I realized that the best way to teach this stuff
is to be able to play with the representations directly, in particular
to be able to see it in action on a simpler system than full 64-bit
precision, especially when str(f) or repr(f) won't show *all* of the
significant digits stored in a float. The decimal class deliberately
avoids binary representation issues, and I can't find what I want
online.
Consequently, I have written a module to simulate the machine
representation of binary floating point numbers and their arithmetic.
Values can be of arbitrary fixed precision or infinite precision,
along the same lines as python's in-built decimal class. The code is
here: http://www2.gsu.edu/~matrhc/binary.html
The design is loosely based on that decimal module, although it
doesn't get in to threads, for instance. You can play with different
IEEE 754 representations with different precisions and rounding modes,
and compare with infinite precision Binary numbers. For instance, it
is easy to learn about machine epsilon, representation/rounding error
using a much simpler format such as a 4-bit exponent and 6-bit
mantissa. Such a format is easily defined in the new module and can be
manipulated easily:
context = define_context(4, 6, ROUND_DOWN)
zero = context(0)
Binary(0, (4, 6, ROUND_DOWN))
print zero # sign, characteristic, significand bits
0 00
zero.next()
Binary(0.001E-9, (4, 6, ROUND_DOWN))
print zero.next()
0 01
largest_denormalized = context('0 11') # direct spec of the sign,
characteristic, and significand bits
largest_denormalized
Binary(0.11E-6, (4, 6, ROUND_DOWN))
largest_denormalized.as_decimal()
Decimal(0.015380859375)
n01 = context(0.1) # nearest representable is actually stored
print n01, rounded to , n01.as_decimal()
0 0011 100110 rounded to 0.099609375
Binary('-10111.001').as_decimal()
Decimal(-23.0078125)
Binary('-10111.001', context).as_decimal() # not enough precision
in this context
Decimal(-23.)
diff = abs(Binary('-10111.001') - Binary('-10111.001', context))
diff
Binary(0.1E-6, (4, 6, ROUND_DOWN))
The usual arithmetic operations are permitted on these objects, as
well as representations of their values in decimal or binary form.
Default contexts for half, single, double, and quadruple IEEE 754
precision floats are provided. Binary integer classes are also
provided, and some other utility functions for converting between
decimal and binary string representations. The module is compatible
with the numpy float classes and requires numpy to be installed.
The source code is released under the BSD license, but I am amenable
to other licensing ideas if there is interest in adapting the code for
some other purpose. Full details of the functionality and known issues
are in the module's docstring, and many examples of usage are in the
accompanying file binary_tests.py (which also acts to validate the
common representations against the built-in floating point types). I
look forward to hearing feedback, especially in case of bugs or
suggestions for improvements.
-Rob
--
Robert H. Clewley, Ph. D.
Assistant Professor
Department of Mathematics and Statistics
Georgia State University
720 COE, 30 Pryor St
Atlanta, GA 30303, USA
tel: 404-413-6420 fax: 404-413-6403
http://www2.gsu.edu/~matrhc
http://brainsbehavior.gsu.edu/
--
http://mail.python.org/mailman/listinfo/python-list
Re: New python module to simulate arbitrary fixed and infinite precision binary floating point
Is this related to minifloats? http://en.wikipedia.org/wiki/Minifloat Strictly speaking, yes, although after a brief introduction to the general idea, the entry on that page focuses entirely on the interpretation of the values as integers. My code *only* represents the values in the same way as the regular-sized IEEE 754 formats, i.e. the smallest representable number is a fraction 1, not the integer 1. I haven't supplied a way to use my classes to encode integers in this way, but it wouldn't be hard for someone to add that functionality in a sub-class of my ContextClass. Thanks for pointing out that page, anyway. I didn't know the smaller formats had been given their own name. -Rob -- http://mail.python.org/mailman/listinfo/python-list
Re: floating point arithmetic
I understand that due to different arithmetic used in floating points they are just approximations. Hence, 180/100=1 in my python interpreter. No, that's not the reason you get 1, it's because the current version of python does integer division by default. Try doing 180.0/100 or including from __future__ import division at the top of your scripts before dividing your numbers. How can I tackle this problem of inaccurate floating point numbers? There are few occasions for regular users to worry about the inaccuracy of floating point, unless you are doing very technical calculations at high precision. If you need decimals to be represented perfectly in python (e.g. you are writing scripts for financial applications), try importing the decimal package (look it up in the python docs). -Rob -- http://mail.python.org/mailman/listinfo/python-list
ANN: updated release of PyDSTool dynamical systems package (version 0.83.2 patch #1)
Version 0.83.2 of PyDSTool has been released, and now includes a patchfor compilation of AUTO on Linux (as of 15th June).PyDSTool is an open-source project providing a range of dynamical systems simulation and analysis tools. It supports both continuous-and discrete-time systems including ordinary differential equations,differential-algebraic equations, maps, and hybrid event-driven systems. It also provides model building classes and templates forspecification of complex networks, including the manipulation ofsymbolic math expressions. Other features include enhancements ofSciPy and Numarray classes. The sub-package PyCont provides native continuation and bifurcationanalysis tools (now including a low-level interface to AUTO).Included toolbox utilities provide template classes and functions for scientific applications, including to systems biology and computationalneuroscience.Documentation and tutorial information can be found on the wiki: http://pydstool.sourceforge.net or download the package directly fromhttp://sourceforge.net/projects/pydstool Your continuing feedback and code contributions are greatly appreciated. Please help us improve this project!Thanks for your attention,Rob Clewley, Erik Sherwood, Drew LaMar,Dept. of Mathematics and Center for Applied Mathematics, Cornell University. -- http://mail.python.org/mailman/listinfo/python-list
Re: urgent - Matplolib with IDLE!
Dear Ana, I have the same problem with a similar setup (except Python 2.4.3) and have tried the same solutions (BTW those steps really did used to work on my machine using Python 2.3.5). In the short term you could either try IPython (a proper solution to this problem, which returns me to the prompt just fine after closing the figure) or try the following quick and dirty fix with IDLE: 1) If your script does stuff other than define classes and functions, put in a command that prevents it getting to the calculations (e.g. insert a 1/0 line) or, for instance, turn all your calculations into function calls that you can easily comment out (temporarily). Run your script using F5 so that you just get the prompt. 3) Create an empty figure using pylab.figure() or whatever. 2) Close the figure and the IDLE console (command prompt window) that opened when you ran the script (you have to say Yes when it asks about killing a python process). 3) This leaves an orphaned python process which you have to clean up later using your Task Manager, but ... 4) you can now continue to interact with any new IDLE console created in the current session when you bring up new figures. i.e. uncomment the parts of your script that actually do stuff and run it again. At least that's a quick fix that's working for me while I await a better answer too... Perhaps this hack will outrage someone's sensibilities sufficiently that we'll hear of a better IDLE solution. HTH, Rob -- http://mail.python.org/mailman/listinfo/python-list
Re: matplotlib basic question
On 19 Apr 2007 16:13:43 -0700, [EMAIL PROTECTED] [EMAIL PROTECTED] wrote: So, first off, what's up with the [matplotlib.lines.Line2D instance at 0x017C38C8] line that shows up after my plot command? And second, when I call show(), a new figure pops up with my sin wave -- seems all right, yes? But I'm not given another prompt in IDLE until or unless I close the figure that popped up with the show() call. This may not be strictly correct but thats a reference to the plot instance which is subsequently passed to show(). If you don't want to see it put a semicolon at the end of your command eg. plot(range(5)); My understanding is that the semicolon trick is specific to IPython, and does not work in IDLE. I don't know about in other environments. You can just assign the list of returned plot objects to a variable to make it invisible at the command line although these return values (like all return values) are not shown in the command window (i.e. passed to stdout) if they are returned from calls made in a script. The issue with IDLE is to due with lack of connection between the python interpreter event loop and the event loop of matplotlib (I think). For me the solution was to install the ipython shell (http:// ipython.scipy.org/moin/). If you run ipython with the -pylab flag then you can matplotlib interactively. For example plot(range(5),'bo') show() clf() plot([1,2,3,4,5],range(0,10,2),'r-') (no need for another show() command since the graphics display is already visible ... unless of course I deleted it in between plot commands) The OP appears to be using IDLE, for which the things to try are: In site-packages/matplotlib/backends/backend_tkagg.py uncomment the line #os.environ['PYTHONINSPECT'] = '1' Set interactive=True in share/matplotlib/.matplotlibrc Start IDLE with the -n flag In site-packages/matplotlib/backends/backend_tkagg.py comment out the line Tk.mainloop() in the function show -Rob -- http://mail.python.org/mailman/listinfo/python-list
ANN: PyDSTool v0.83.3 released
We are pleased to announce version 0.83.3 of our open-source simulation, modeling, and analysis package PyDSTool. New features include improved graphical capabilities in the PyCont bifurcation and continuation sub-package and its interface with AUTO, and better support for domain bound enforcement on state variables and parameters. There are several bug fixes and general improvements to the API in this release too. Please see http://pydstool.sourceforge.net for details and documentation. Regards, Rob, Drew, and Erik. Center for Applied Mathematics, Cornell University. ** PyDSTool is an integrated simulation, modeling and analysis package for dynamical systems, written in Python (and partly in C). It is being developed at Cornell University, and the source code is available under the terms of the BSD license. PyDSTool runs on Linux, Windows, and Macs, and aims to have a minimal number of package dependencies. Currently, it requires (old) SciPy, Numarray, and Matplotlib. -- http://mail.python.org/mailman/listinfo/python-list
ANN: PyDSTool now compatible with numpy 1.0.1, scipy 0.5.2 and 64-bit CPUs.
We are pleased to announce version 0.84 of PyDSTool, an open-source dynamical systems simulation, modeling, and analysis package. This long-overdue release is primarily intended to bring existing PyDSTool functionality up to date with the latest numpy and scipy releases (previous versions required scipy 0.3.2, numarray, numeric, etc). Also, PyDSTool is now compatible with 64-bit CPUs. While we have added a few new features and made several fixes, major improvements to functionality are in the pipeline for version 0.90. Please see http://pydstool.sourceforge.net for release notes and documentation, and http://sourceforge.net/projects/pydstool for downloading. As ever, please send us feedback if you have any problems with this new release or ideas and code contributions for future releases. Regards, Rob, Erik, and Drew. Center for Applied Mathematics, Cornell University. ** PyDSTool is an integrated simulation, modeling and analysis package for dynamical systems, written in Python (and partly in C). It is being developed at Cornell University, and the source code is available under the terms of the BSD license. PyDSTool runs on Linux, Windows, and Macs, and aims to have a minimal number of package dependencies. -- http://mail.python.org/mailman/listinfo/python-list
Re: ANN: PyDSTool now compatible with numpy 1.0.1, scipy 0.5.2 and 64-bit CPUs.
Mike, Yes, that is a pretty fair description of our support for symbolics using Python's own inheritance. Our ModelSpec classes provide only an elementary form of inheritance, polymorphism and type checking. We hope to expand our existing support for hybrid/DAE systems at the level of our ModelSpec model-building tools. All ideas and code contributions are welcome! Cheers, Rob -- http://mail.python.org/mailman/listinfo/python-list
Re: ANN: PyDSTool now compatible with numpy 1.0.1, scipy 0.5.2 and 64-bit CPUs.
This kind of comment comes up often, so I think it's worth spelling out a response that will persist on the web and can appear in our FAQ. I have a different and admittedly limited view of hybrid systems as part of dynamical systems theory. In principle, I would love to have time to write an interface to something like Modelica, but PyDSTool isn't intended as an industrial-scale simulation package: it is intended for applied dynamical systems research involving small systems that people want to analyze with tools like bifurcation theory and parameter estimation. I also want to switch components in and out of a model with minimum overhead as part of model estimation and parameter estimation routines that remain an open research area. Partly for this reason I don't want to start depending on large external packages, most features of which people may never be needed. Given my present purposes the overhead of writing an interface is a demanding sink of my time when basic (essentially prototype) tools suffice in the short term. That is also why I am not planning a graphical UI at this time. (The related DsTool and XPP packages already have GUIs.) I appreciate the idea of outsourcing to take advantage of good work in areas such as yours. I hope to step up to that bar later on as part of an ongoing research project connected to me, which involves studying the mechanisms of locomotion in insects. There are other mechanical simulation packages that I would like to interface to (most are commercial), but on close inspection it turns out there's a lot of very technical issues involved -- although at least modelica is open source! Sorry to be taking a short-term view here (I try to avoid that), but we're just a couple of guys trying to concentrate on our day jobs... Rob -- http://mail.python.org/mailman/listinfo/python-list
Re: Box plot in Python
Matplotlib supports boxplots in a very straightforward fashion and is reasonably documented (just google it!) I actually just submitted a patch for extra boxplot features in matplotlib, which you can find on the sourceforge patch tracker. -Rob -- http://mail.python.org/mailman/listinfo/python-list
Unexpected behavior with dictionary keys containment and a user-defined class
Hi, the short version of my question is: when is a dictionary's __contains__ method behavior different to using the 'in' idiom? (because I have an example of a difference in my code). Longer version: I have a user-defined class with a few overrides of special methods, particularly __eq__ and __ne__. I also have a dictionary keyed by instances of these classes, and I'm confused about the unexpected behavior trying to test whether an instance is in the dictionary's keys. The instance is i and the dictionary is d. I have been using the idiom i in d which I understood to be the pythonic way to test the keys, but it doesn't work. However, when I debug my code I see the instance in the list of keys, and in fact i in d.keys() and d.keys()[10] == i both return True. But d.__contains__(i) d.has_key(i) d.keys()[10] is i return False. I put a print statement in my class's __eq__ method and it is being called. It tests equality of some of my class instance's attributes. I didn't realize there was any situation where you could expect different results from i in d versus i in d.keys() -- am I misunderstanding something? I'm not sure what other details to provide! Thanks a lot, Rob -- http://mail.python.org/mailman/listinfo/python-list
Re: Unexpected behavior with dictionary keys containment and a user-defined class
Hi, the short version of my question is: when is a dictionary's __contains__ method behavior different to using the 'in' idiom? (because I have an example of a difference in my code). Never. Yes, sorry, I managed to summarize the long version incorrectly :) Well, the only conclusion is that dict uses the hash of an object to test containment while lists use id. Great, thanks. I think a copy of my object has been made so that it doesn't hash to the same thing. I'll write a __hash__ as suggested in the other post. I forgot all about dictionary hashing for some reason... -Rob -- http://mail.python.org/mailman/listinfo/python-list
Re: 4 hundred quadrillonth?
On Thu, May 21, 2009 at 8:19 PM, Gary Herron gher...@islandtraining.com wrote: MRAB wrote: Grant Edwards wrote: On 2009-05-21, Christian Heimes li...@cheimes.de wrote: seanm...@gmail.com schrieb: The explaination in my introductory Python book is not very satisfying, and I am hoping someone can explain the following to me: 4 / 5.0 0.80004 4 / 5.0 is 0.8. No more, no less. So what's up with that 4 at the end. It bothers me. Welcome to IEEE 754 floating point land! :) FYI you can explore the various possible IEEE-style implementations with my python simulator of arbitrary floating or fixed precision numbers: http://www2.gsu.edu/~matrhc/binary.html -- http://mail.python.org/mailman/listinfo/python-list
Re: ODE, GUI, plotter in Python
There was just an announcement on this list and the scipy list for PyLab_Works, which sounds exactly like what you're looking for. I would not recommend starting over with a new simulator at this point. -Rob On Tue, Jun 16, 2009 at 12:00 PM, Alashaib...@ymail.com wrote: Hello everyone. I am starting on implementing a simulator using python, and since it's the first time I code in python would appreciate a few pointers: The simulator will use a coupled ODE for the most part of the simulation, I plan to use scipy. (Anything considered faster/better than scipy for solving coupled ODEs? ) I plan for a GUI program with network graph plotting. I am leaning towards using Qt for the GUI (internet forums seem to recommend it, anyone got other preferences? ) Since the GUI application will contain few buttons and a plot, I am planning to implement matplotlib into the GUI. But does anyone know if matplotlib allows for interaction with the graph plot? (say for a network simulation, allowing to right click on nodes and disable them for instance, or alter some other properties of nodes and/or links across them). I am just starting out, hence I'd rather get some advice and experiment a bit for my self as I go along. Thank you. -- http://mail.python.org/mailman/listinfo/python-list
Re: OT: looking for best solutions for tracking projects and skills
I don't know about civic hacking, but Trello is a free online tool to track high level aspects of collaborative projects. It is somewhat focused on a to do planning perspective. But with the customizable columns, labels, and checklists associated with items in the view I think you might be able to track static info like skills. -Rob On Fri, Oct 11, 2013 at 11:09 PM, Jason Hsu jhsu802...@gmail.com wrote: I realize this is off-topic, but I'm not sure what forum is best for asking about this. I figure that at least a few of you are involved in civic hacking groups. I recently joined a group that does civic hacking. (Adopt-A-Hydrant is an example of civic hacking.) We need a solution for tracking projects and the skills needed for the projects (such as Ruby on Rails, Python, Drupal, Javascript, etc.). I'd like to hear from those of you in similar groups that have a great system for tracking projects. Is there an in-house solution you use, or is there something else available? -- https://mail.python.org/mailman/listinfo/python-list -- Robert Clewley, Ph.D. Assistant Professor Neuroscience Institute and Department of Mathematics and Statistics Georgia State University PO Box 5030 Atlanta, GA 30302, USA tel: 404-413-6420 fax: 404-413-5446 http://neuroscience.gsu.edu/rclewley.html -- https://mail.python.org/mailman/listinfo/python-list
Is there existing code to log-with-bells-on for runtime algorithm diagnostics?
Hi, I'm in need of a system for logging the step-wise results and diagnostic metadata about a python function implementation of an algorithm that I'm developing. The specific algorithm is not of great consequence except that it's for scientific computing and may produce large (e.g., '00s or maybe '000s, but not big data scale) amounts of intermediate numerical data that can be complex to understand when debugging its progress. In fact, I'm trying to build a general purpose tool for exploring the inner workings of numerical algorithms for teaching and learning purposes, e.g. for graduate student training or for figuring out parameter choices in difficult applications. I want to be able to insert commands inside of the loops that log certain variable states, completed stages of the algorithm (assume it's hierarchical), text warnings, and possibly even 'pointers' to graphical output objects of some of the intermediate data (e.g. matplotlib object handles for lines, points). Then I can trace the work done afterwards or step through the process in an IDE debugger and make interactive calls to access recent steps, plot certain relationships in the current state, etc. The basic logger's levels of output don't really apply here. I at least want categories, if not hierarchical sub-categories. I don't think the built-in logger is sophisticated enough for this, being a flat record of freeform text AFAIU, but the API looks appealing. I'm considering an in-memory sqlite DB to store structured records at any logged step, and an accompanying dictionary to store references to any python object metadata, keyed by a unique ID in the DB log. Then I'd write an API for it that resembles the logger's. It's not super hard for me to write my own thing here, but I'm wondering if anyone has come across any existing solutions in this vein, or has any advice before I go further in designing a solution? I can't really believe that no-one has attempted this before, but it's been really hard to find any existing work through online search. Thanks, Rob -- https://mail.python.org/mailman/listinfo/python-list
Re: [SciPy-User] Is there existing code to log-with-bells-on for runtime algorithm diagnostics?
All of these ideas and links are very helpful, thank you! -Rob -- https://mail.python.org/mailman/listinfo/python-list
Re: [SciPy-User] Is there existing code to log-with-bells-on for runtime algorithm diagnostics?
Just to follow up on this thread, for interested readers' future reference... On Tue, Apr 21, 2015 at 4:22 PM, Robert Kern robert.k...@gmail.com wrote: On Tue, Apr 21, 2015 at 8:02 PM, Rob Clewley rob.clew...@gmail.com wrote: In fact, I'm trying to build a general purpose tool for exploring the inner workings of numerical algorithms for teaching and learning purposes, e.g. for graduate student training or for figuring out parameter choices in difficult applications. The term you want to search for is structured logging. http://www.structlog.org/en/stable/ http://eliot.readthedocs.org/en/stable/ https://twiggy.readthedocs.org/en/latest/logging.html#structured-logging http://netlogger.lbl.gov/ I posted a new blog entry about my prototypical diagnosis and visualization tools for python numerical algorithms, built over matplotlib: http://robclewley.github.io/logging-and-diagnostic-tools-for-numeric-python-algorithms/ They utilize structlog, and I hooked up a noSQL DB (tinydb) to the logging to enable search capabilities of the log post-mortem. Comments and PRs most welcome. Thanks to everyone for the pointers. -Rob -- https://mail.python.org/mailman/listinfo/python-list
