Mailman 3 June 2011 - SciPy-User

scipy.io.numpyio.fwrite replacement??
by Andres Luhamaa Oct. 12, 2011

Oct. 12, 2011

Hi all, I try to upgrade code from scipy 0.7.2 to 0.9.0 and see that there is no more scipy.io.numpyio. I found two similar questions in the archive of this list without a reasonable answer (new in the list, so cannot replay to these). In particular I need scipy.io.numpyio.fwrite and I do not know how to replace it with something else. np.save seems to save in double, np.lib.format has some options, but nothing seems what I want. As I am not using python to read the data file, using some other file format like ".npy" or ".npz" is not an option. To illustrate what I want to get, to those familiar with fortran, the write sequence in fortran looks like this: open (filenum, file=filename,form='unformatted', & & access='DIRECT', status='unknown', RECL=lon) write (filenum,REC=IREC) data Any guidance really appreciated, Andres

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inverse function of a spline
by josef.pktd＠gmail.com Oct. 2, 2011

Oct. 2, 2011

I have a function y = f(x) which is monotonically increasing (a cumulative distribution function) f is defined by piecewise polynomial interpolation, an interpolating spline on some points I would like to get the inverse function (ppf) x = f^{-1} (y) if the spline is of higher order than linear In the linear case it's trivial, because the inverse function is also just a piecewise linear interpolation. If I have a cubic spline, or any other smooth interpolator in scipy, is there a way to get the inverse function directly? I don't know much about general properties of splines, and would appreciate any hints, so I can avoid numerical inversion (fsolve or similar) Thanks, Josef

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Separate scales for left and right axis broken
by Christopher Peters Sept. 29, 2011

Sept. 29, 2011

All, I am trying to run the code at http://pytseries.sourceforge.net/lib.plotting.examples.html#separate-scales… to generate separate scales for left and right axes for tsplot in scikits.timeseries.lib.plotlib, but I am getting an error. Package versions: Numpy: 1.5.1 Matplotlib: 1.0.1 Scikits Timeseries: 0.91.3 Code to test: import numpy as np print np.__version__ import numpy.ma as ma import matplotlib.pyplot as plt print matplotlib.__version__ import scikits.timeseries as ts print ts.__version__ import scikits.timeseries.lib.plotlib as tpl # generate some random data data1 = np.cumprod(1 + np.random.normal(0, 1, 300)/100) data2 = np.cumprod(1 + np.random.normal(0, 1, 300)/100)*100 start_date = ts.Date(freq='M', year=1982, month=1) series1 = ts.time_series(data1, start_date=start_date-50) series2 = ts.time_series(data2, start_date=start_date) fig = tpl.tsfigure() fsp = fig.add_tsplot(111) # plot series on left axis fsp.tsplot(series1, 'b-', label='<- left series') fsp.set_ylim(ma.min(series1.series), ma.max(series1.series)) # create right axis fsp_right = fsp.add_yaxis(position='right', yscale='log') # plot series on right axis fsp_right.tsplot(series2, 'r-', label='-> right series') fsp_right.set_ylim(ma.min(series2.series), ma.max(series2.series)) # setup legend fsp.legend( (fsp.lines[-1], fsp_right.lines[-1]), (fsp.lines[-1].get_label(), fsp_right.lines[-1].get_label()), ) plt.show() Traceback (most recent call last): File "<pyshell#75>", line 23, in <module> fsp_right = fsp.add_yaxis(position='right', yscale='log') File "C:\Python27\lib\site-packages\scikits\timeseries\lib\plotlib.py", line 1196, in add_yaxis fsp_alt_args = (fsp._rows, fsp._cols, fsp._num + 1) AttributeError: 'TimeSeriesPlot' object has no attribute '_rows' My guess is that the newest version of matplotlib (1.0.1) removed the _rows (_cols, and _num as well) attribute for the Subplot base class, but this was not propagated to plotlib.py. Looking at the revision log at http://projects.scipy.org/scikits/log/trunk/timeseries/scikits/timeseries/l… , it appears that 20 months ago there were some fixes for matplotlib version 0.99.0. It seems that this question was already posed by Dave Hirschfeld on 2010 Nov 8 (a post entitled "TimeSeries Plotting Broken?" at http://permalink.gmane.org/gmane.comp.python.scientific.devel/14645), but there were no replies. Any help on this would be greatly appreciated!

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scikits timeseries tofile
by Gar Brown Sept. 28, 2011

Sept. 28, 2011

Hi All, While trying to write a timeseries object to file I the following error: File "C:\Python27\lib\site-packages\scikits\timeseries\tseries.py", line 1527, in tofile return scipy.io.write_array(fileobject, tmpfiller, **optpars) AttributeError: 'module' object has no attribute 'write_array' I noticed that the scipy.io.write_array function has been deprecated for some time, is there a fix or workaround for avoiding this error. I really like the time series functionality of scikits.timeseries timeseries version: __author__ = "Pierre GF Gerard-Marchant & Matt Knox ($Author: mattknox_ca $)" __revision__ = "$Revision: 2213 $" __date__ = '$Date: 2009-08-23 12:43:40 -0400 (Sun, 23 Aug 2009) $'

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computing local extrema
by fred Sept. 16, 2011

Sept. 16, 2011

Hi, I would like to compute local extrema of an array (2D/3D), ie get a list of points (coords + value). How could I do this? Any hint? TIA. Cheers, -- Fred

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scipy.optimize named argument inconsistency
by Joon Ro Sept. 14, 2011

Sept. 14, 2011

Hi, I just found that for some functions such as fmin_bfgs, the argument name for the objective function to be minimized is f, and for others such as fmin, it is func. I was wondering if this was intended, because I think it would be better to have consistent argument names across those functions. http://docs.scipy.org/doc/scipy/reference/optimize.html -Joon --

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[ANN] Bottleneck 0.5.0 released
by Keith Goodman Aug. 14, 2011

Aug. 14, 2011

Bottleneck is a collection of fast NumPy array functions written in Cython. It contains functions like median, nanmedian, nanargmax, move_max, rankdata. The fifth release of bottleneck adds four new functions, comes in a single source distribution instead of separate 32 and 64 bit versions, and contains bug fixes. J. David Lee wrote the C-code implementation of the double heap moving window median. New functions: - move_median(), moving window median - partsort(), partial sort - argpartsort() - ss(), sum of squares, faster version of scipy.stats.ss Changes: - Single source distribution instead of separate 32 and 64 bit versions - nanmax and nanmin now follow Numpy 1.6 (not 1.5.1) when input is all NaN Bug fixes: - #14 Support python 2.5 by importing `with` statement - #22 nanmedian wrong for particular ordering of NaN and non-NaN elements - #26 argpartsort, nanargmin, nanargmax returned wrong dtype on 64-bit Windows - #29 rankdata and nanrankdata crashed on 64-bit Windows download http://pypi.python.org/pypi/Bottleneck docs http://berkeleyanalytics.com/bottleneck code http://github.com/kwgoodman/bottleneck mailing list http://groups.google.com/group/bottle-neck mailing list 2 http://mail.scipy.org/mailman/listinfo/scipy-user

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What happened with chisquare_contingency?
by Yang Zhang July 29, 2011

July 29, 2011

Looked like a useful addition: http://mail.scipy.org/pipermail/scipy-dev/2010-June/014538.html I originally was rolling my own and found the chisquare ddof parameter to be confusing - Googling turned this up. Just wondering if this is still on its way into the codebase. Thanks!

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random variable for truncated multivariate normal and t distributions
by josef.pktd＠gmail.com July 5, 2011

July 5, 2011

(another random question) I would like to generate random variables for multivariate normal and t distributions that are truncated on a rectangular area (element wise upper and lower bounds). Is there anything better available than sampling from the un-truncated distributions and throwing away the out of bounds samples ? Josef

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Time Series using 15 minute intervals using scikits.timeseries
by David Montgomery July 4, 2011

July 4, 2011

Hi, Using scikits timeseries I can create daily and hourly time series....no prob But.... I have time series at 15 minutes intervals...this I dont know how to do... Can a timeseries array handle 15 min intervals? Do I use a minute intervals and use mask arrays for the missing minutes? Also..I can figure out how to create a array at minute intervals. So..what is best practice? Any examples? Thanks st = ts.Date('H', year=ts_start_date.year,month=ts_start_date.month,day=ts_start_date.day,hour=ts_start_hour) ed = ts.Date('H', year=ts_end_date.year,month=ts_end_date.month,day=ts_end_date.day,hour=ts_end_hour) st_beg = st.asfreq('H', relation='START') ed_end = ed.asfreq('H', relation='END')

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