Numpy wraps the FORTRAN libs. I'm certain this is what she should try: http://numpy.scipy.org/
Bet your friend would find it groovy too. Let Python rise to the occasion, like a Loch Ness from the sea (lake, whatever). Kirby On Thu, Oct 20, 2011 at 1:55 PM, Chris McDonald <[email protected]> wrote: > I have a friend that would very likely be interested in this as well. > He does a heavy amount of scientific computing but most of it is in > Fortran, he is looking to move to Python eventually though and I think > this would be ideal for him. I on the other hand have lots of python > experience but non in the big dataset/scientific world but I can help > in the same way offered by Andrew, a web developer who knows how to > distribute tasks using queues and databases. > > I'll ping him with regards to this and see what he thinks. > > -Wraithan > > On Thu, Oct 20, 2011 at 1:46 PM, Andrew Brookins <[email protected]> > wrote: >> Heather (and everyone), >> >> On Oct 14, 2011, at 8:22 PM, Heather Lintz wrote: >> >>> Hi Pythonistas, >>> >>> I am a Corvallis ghost member of your group. My name is Heather. I am also >>> an ecologist working on climate change topics. I program all the time in >>> MATLAB, and less often in R and Python. So far, I have only used Python to >>> do some ArcGIS tasks using the ArcGIS library in Python (and some other >>> basic libraries too). However, I now have a couple somewhat hefty new >>> projects I would like to accomplish in Python. I was wondering if there is a >>> good time/place to catch some of you and talk about some potential >>> Python tutoring with these tasks in mind. I already have some experience >>> with the language (for example, I posted some of my code below that I wrote >>> awhile and forgot about). Is the monthly meet-up a good place for this? >>> You seem to have agendas for those meetings perhaps? >>> >>> Here are the projects I have in mind that I would like to work on: >>> >>> 1. Code a statistical algorithm and divide and delegate computation tasks to >>> multiple processors on a Linux system. The processors would each generate >>> results and the results would be pooled for an optimization. >>> >>> 2. Import RNA Seq data generated from the Illumina High Seq 2000 and learn >>> how to manipulate INSANELY large bioinformatics/genomics data sets. I >>> especially like >>> to do statistics on such data (things that I normally do in MATLAB). >>> But this time it would be treating the INSANELY LARGE AMOUNT of data as a >>> matrix to manipulate it, etc. in Python. >>> >>> I'd like to come up twice a month for Python 'tutoring' to get these >>> projects accomplished and learn Python better. There's nothing like wisdom >>> from other programmers to help. Would this interest any of you? Can you >>> recommend someone in your group that is great at >>> scientific-python-programming-teaching challenges? >>> >>> Many thanks, >>> Heather >>> >>> >>> P.s. Here's my previous dinky Python code that I already forgot about. It's >>> the max of my ability. >>> >>> ######################## >>> # Import system modules >>> ######################## >>> >>> import sys, string, os, arcgisscripting, copy, glob, linecache, csv from >>> quantile import quantile >>> >>> # Create the Geoprocessor >>> gp = arcgisscripting.create() >>> gp.overwriteoutput = 1 >>> >>> #################################################################### >>> #READ DATA FROM EACH ASC FILE AND CALCULATE QUANTILES FROM EACH FILE >>> #################################################################### >>> >>> q1=[] >>> q2=[] >>> q3=[] >>> >>> os.chdir(ascDIR) >>> runlist=os.listdir(ascDIR) >>> print repr(runlist) >>> print len(runlist) >>> for file in runlist: >>> print repr(file) >>> gq=[] >>> x=open(file,'r') >>> for i in xrange(6): >>> x.readline() >>> z= x.readline() >>> while z != '': >>> z=z.strip().split() >>> for num in z: >>> num=float(num) >>> if num > -1: >>> gq.append(num) >>> z= x.readline() >>> a=quantile(gq, .25, qtype = 7, issorted = False) >>> #print a >>> b=quantile(gq, .5, qtype = 7, issorted = False) >>> c=quantile(gq, .75, qtype = 7, issorted = False) >>> q1.append(a) >>> q2.append(b) >>> q3.append(c) >>> print len(q1), len(q2), len(q3) >>> >>> outfile = open("outfile.txt", "w") >>> for i in xrange(len(q1)): >>> outfile.write("%12.3e%12.3e%12.3e\n" % (q1[i], q2[i], q3[i])) >>> outfile.close() >>> >>> outfile = open("outfilezones.txt", "w") >>> for i in xrange(len(q1)): >>> outfile.write(runlist) >>> outfile.close() >>> >>> >>> >>> _______________________________________________ >>> Portland mailing list >>> [email protected] >>> http://mail.python.org/mailman/listinfo/portland >> >> This is a really awesome question. >> >> There are a few hack-nights around town that aren't oriented around a >> specific language that you could attend. Check: http://calagator.org/ >> >> I'm not aware of a regular Python tutoring/workshop style meeting (maybe >> someone else is). However, I would be very interested in participating in >> and helping to organize such a meeting. >> >> As for your particular problem, I haven't done any scientific computing, but >> I can share my experience using Python for web development. Maybe there is >> some technology crossover (message queues, or even just your database layer? >> Oops, I dunno, I'm not a scientist!). >> >> Anyway, "large bioinformatics/genomics data"? Sounds awesome! >> >> Best, >> Andrew >> _______________________________________________ >> Portland mailing list >> [email protected] >> http://mail.python.org/mailman/listinfo/portland >> > _______________________________________________ > Portland mailing list > [email protected] > http://mail.python.org/mailman/listinfo/portland > _______________________________________________ Portland mailing list [email protected] http://mail.python.org/mailman/listinfo/portland
