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From: Edoardo Pasca <e.pasca@nk...>  20090331 10:58:24

Dear users, I'd like to use gnuplotpy on windowsxp. I have python 2.6. Apparently I managed to take the setup.py install to the end. As a matter of facts import Gnuplot doesn't return errors. Anyway when I try the demo.py I get this: gnuplot> set terminal windows gnuplot> set title "A simple example" gnuplot> set data style linespoints gnuplot> plot "c:\\docume~1\\ef634~1.pas\\locals~1\\temp\\tmpm5ee2g.gnuplot" notitle Please press return to continue... Traceback (most recent call last): File "C:\Program Files\Paive1.0\Lib\sitepackages\Gnuplot\demo.py", line 110, in <module> demo() File "C:\Program Files\Paive1.0\Lib\sitepackages\Gnuplot\demo.py", line 36, in demo g.reset() File "C:\Program Files\Paive1.0\lib\sitepackages\Gnuplot\_Gnuplot.py", line 366, in reset self('reset') File "C:\Program Files\Paive1.0\lib\sitepackages\Gnuplot\_Gnuplot.py", line 210, in __call__ self.gnuplot(s) File "C:\Program Files\Paive1.0\lib\sitepackages\Gnuplot\gp_win32.py", line 130, in __call__ self.write(s + '\n') IOError: [Errno 22] Invalid argument I have tried to check the proper file names in the gp_win32.py and updated to the location of pgnuplot.exe but there was no apparent difference: it always failed. I presume that the error is indicating something different but I cannot figure out what. I gave a look at the mailing list archives before writing this email. Thanks Edoardo  Edoardo Pasca, Ph.D Nederlands Kanker Instituut  Antoni van Leeuwenhoek Ziekenhuis Radiotherapy Department Plesmanlaan 121 1066 CX Amsterdam tel: 0031 (0)20 512 1759 
From: Xaver Wurzenberger <xaver.xn@we...>  20090304 15:46:37

Hi, basically, I agree, we probably don't need to raise an exception. However, isinstance(m, numpy.ndarray) returns 'True' for any valid numpy array, which includes e. g. string arrays, and for a nongnuplot compatible array the error message with your code is gnuplot> plot "/tmp/tmpndt27x.gnuplot/fifo" notitle ^ line 0: Bad data on line 1 ..not very helpful. I'd propose to rather have explicitly permitted array types, like if m.dtype.name in ('float64','float32','int32',int64'): return m else: return numpy.array(m,dtype=numpy.float32) whereas the 'else' clause serves mainly for having a defined error message, maybe intercepted by a 'try...except'. This might also eliminate the redundant conversion from float32 to float32 (if python/numpy is not intelligent enough to not do that). What about int32 / int64 arrays? It would be just fine to not convert them as well, right? Saves memory, I guess... Xaver P.S.: Is diff context oldfile.py oldfile_new.py >> mypatch.py.patch the right way to make a patch file for the tracker? I've never done that before... Am Dienstag, 3. März 2009 14:40:51 schrieb Alan G Isaac: > You are correct: the try clause now succeeds > > because downcasting is allowed: > >>> x = np.random.random((5,)) > >>> x.dtype > > dtype('float64') > > >>> x32 = x.astype(np.float32) > >>> x32.dtype > > dtype('float32') > > How about returning any ndarray untouched? > > if isinstance(m, numpy.ndarray): > return m > else: > return numpy.array(m,dtype=numpy.float32) > > I see no need to print an error message: > NumPy will report appropriately. > > Alan Isaac > > > >  > Open Source Business Conference (OSBC), March 2425, 2009, San > Francisco, CA OSBC tackles the biggest issue in open source: Open Sourcing > the Enterprise Strategies to boost innovation and cut costs with open > source participation Receive a $600 discount off the registration fee with > the source code: SFAD http://p.sf.net/sfu/XcvMzF8H > _______________________________________________ > Gnuplotpyusers mailing list > Gnuplotpyusers@... > https://lists.sourceforge.net/lists/listinfo/gnuplotpyusers 
From: Alan G Isaac <aisaac@am...>  20090303 13:41:10

You are correct: the try clause now succeeds because downcasting is allowed: >>> x = np.random.random((5,)) >>> x.dtype dtype('float64') >>> x32 = x.astype(np.float32) >>> x32.dtype dtype('float32') How about returning any ndarray untouched? if isinstance(m, numpy.ndarray): return m else: return numpy.array(m,dtype=numpy.float32) I see no need to print an error message: NumPy will report appropriately. Alan Isaac 
From: Lois <lois.shekinah@gm...>  20090303 09:39:16

I've been trying to make Gnuplotpy to work with MacPython 2.5 (I have VPython installed) and haven't had much success.I'm a new PC convert, I've learnt a few basics things in Terminal, like changing directories. I'll be very grateful if someone guides me through this. These are the files I downloaded (from Sourceforge.net) gnuplot4.3.020081121.tar gnuplotpy1.8.tar numpy1.2.1py2.5macosx10.5.dmg AquaTerm1.0.1.dmg Thanks, Lois 
From: Benny Malengier <benny.malengier@gm...>  20090303 08:12:53

I suggest you look up things in numpy doc. If nothing there, use the python way of determining things: if m: if isinstance(m[0], numpy.float64): raise TypeError Provide a patch to gnuplot when you make it work. Benny 2009/3/3 Michael Haggerty <mhagger@...> > Xaver Wurzenberger wrote: > > Hi guys, > > > > I'm sorry to bring this up again, but I'm about to publish my code and > I'd > > really love to get this straight/fixed. In case you don't remember, I'm > > trying to plot high precision numbers (float64, that is), but gnuplot.py > > converts them to float32 arrays. > > Michael Haggerty told me to 'workaround' by using numpy double arrays, > but it > > seems that's not working here. I think the problem might be here: > > (/usr/share/pyshared/Gnuplot/utils.py, line 20ff) > > > >> def float_array(m): > >> """Return the argument as a numpy array of type at least 'Float32'. > >> > >> Leave 'Float64' unchanged, but upcast all other types to > >> 'Float32'. Allow also for the possibility that the argument is a > >> python native type that can be converted to a numpy array using > >> 'numpy.asarray()', but in that case don't worry about > >> downcasting to singleprecision float. > >> > >> """ > >> > >> try: > >> # Try Float32 (this will refuse to downcast) > >> return numpy.asarray(m, numpy.float32) > >> except TypeError: > >> # That failure might have been because the input array was > >> # of a wider data type than float32; try to convert to the > >> # largest floatingpoint type available: > >> # NOTE TBD: I'm not sure float_ is the best datatype for this... > >> try: > >> return numpy.asarray(m, numpy.float_) > >> except TypeError: > >> # TBD: Need better handling of this error! > >> print "Fatal: array dimensions not equal!" > >> return None > > > > If I understand this correctly, the line > >> return numpy.asarray(m, numpy.float32) > > is supposed to raise a TypeError if you give a numpy.float64 array. > > However, my python shell doesn't: > > > >> (00:13:52)xaver@...:~$python > >> Python 2.5.4 (r254:67916, Feb 18 2009, 03:00:47) > >> [GCC 4.3.3] on linux2 > >> Type "help", "copyright", "credits" or "license" for more information. > >>>>> import numpy > >>>>> a = numpy.array( [2.000000001,3.0,4.0] ) > >>>>> a.dtype > >> dtype('float64') > >>>>> numpy.asarray(a, numpy.float32) > >> array([ 2., 3., 4.], dtype=float32) > > > > Am I doing sth wrong? Can anyone confirm that? > > I don't see that you are doing anything wrong. That arrayconversion > code was written long ago, originally for Numeric (not numpy). > Apparently numpy behaves differently than Numeric in this situation, > resulting in a Gnuplot.py bug. > > I suggest that you try to find the right incantation for Gnuplot.py to > do this conversion without losing precision, and submit a patch to > Gnuplot.py. > > Michael > > >  > Open Source Business Conference (OSBC), March 2425, 2009, San Francisco, > CA > OSBC tackles the biggest issue in open source: Open Sourcing the > Enterprise > Strategies to boost innovation and cut costs with open source > participation > Receive a $600 discount off the registration fee with the source code: > SFAD > http://p.sf.net/sfu/XcvMzF8H > _______________________________________________ > Gnuplotpyusers mailing list > Gnuplotpyusers@... > https://lists.sourceforge.net/lists/listinfo/gnuplotpyusers > 
From: Michael Haggerty <mhagger@al...>  20090303 05:34:19

Xaver Wurzenberger wrote: > Hi guys, > > I'm sorry to bring this up again, but I'm about to publish my code and I'd > really love to get this straight/fixed. In case you don't remember, I'm > trying to plot high precision numbers (float64, that is), but gnuplot.py > converts them to float32 arrays. > Michael Haggerty told me to 'workaround' by using numpy double arrays, but it > seems that's not working here. I think the problem might be here: > (/usr/share/pyshared/Gnuplot/utils.py, line 20ff) > >> def float_array(m): >> """Return the argument as a numpy array of type at least 'Float32'. >> >> Leave 'Float64' unchanged, but upcast all other types to >> 'Float32'. Allow also for the possibility that the argument is a >> python native type that can be converted to a numpy array using >> 'numpy.asarray()', but in that case don't worry about >> downcasting to singleprecision float. >> >> """ >> >> try: >> # Try Float32 (this will refuse to downcast) >> return numpy.asarray(m, numpy.float32) >> except TypeError: >> # That failure might have been because the input array was >> # of a wider data type than float32; try to convert to the >> # largest floatingpoint type available: >> # NOTE TBD: I'm not sure float_ is the best datatype for this... >> try: >> return numpy.asarray(m, numpy.float_) >> except TypeError: >> # TBD: Need better handling of this error! >> print "Fatal: array dimensions not equal!" >> return None > > If I understand this correctly, the line >> return numpy.asarray(m, numpy.float32) > is supposed to raise a TypeError if you give a numpy.float64 array. > However, my python shell doesn't: > >> (00:13:52)xaver@...:~$python >> Python 2.5.4 (r254:67916, Feb 18 2009, 03:00:47) >> [GCC 4.3.3] on linux2 >> Type "help", "copyright", "credits" or "license" for more information. >>>>> import numpy >>>>> a = numpy.array( [2.000000001,3.0,4.0] ) >>>>> a.dtype >> dtype('float64') >>>>> numpy.asarray(a, numpy.float32) >> array([ 2., 3., 4.], dtype=float32) > > Am I doing sth wrong? Can anyone confirm that? I don't see that you are doing anything wrong. That arrayconversion code was written long ago, originally for Numeric (not numpy). Apparently numpy behaves differently than Numeric in this situation, resulting in a Gnuplot.py bug. I suggest that you try to find the right incantation for Gnuplot.py to do this conversion without losing precision, and submit a patch to Gnuplot.py. Michael 
From: Xaver Wurzenberger <xaver.xn@we...>  20090302 23:20:24

Hi guys, I'm sorry to bring this up again, but I'm about to publish my code and I'd really love to get this straight/fixed. In case you don't remember, I'm trying to plot high precision numbers (float64, that is), but gnuplot.py converts them to float32 arrays. Michael Haggerty told me to 'workaround' by using numpy double arrays, but it seems that's not working here. I think the problem might be here: (/usr/share/pyshared/Gnuplot/utils.py, line 20ff) >def float_array(m): > """Return the argument as a numpy array of type at least 'Float32'. > > Leave 'Float64' unchanged, but upcast all other types to > 'Float32'. Allow also for the possibility that the argument is a > python native type that can be converted to a numpy array using > 'numpy.asarray()', but in that case don't worry about > downcasting to singleprecision float. > > """ > > try: > # Try Float32 (this will refuse to downcast) > return numpy.asarray(m, numpy.float32) > except TypeError: > # That failure might have been because the input array was > # of a wider data type than float32; try to convert to the > # largest floatingpoint type available: > # NOTE TBD: I'm not sure float_ is the best datatype for this... > try: > return numpy.asarray(m, numpy.float_) > except TypeError: > # TBD: Need better handling of this error! > print "Fatal: array dimensions not equal!" > return None If I understand this correctly, the line > return numpy.asarray(m, numpy.float32) is supposed to raise a TypeError if you give a numpy.float64 array. However, my python shell doesn't: >(00:13:52)xaver@...:~$python >Python 2.5.4 (r254:67916, Feb 18 2009, 03:00:47) >[GCC 4.3.3] on linux2 >Type "help", "copyright", "credits" or "license" for more information. >>>> import numpy >>>> a = numpy.array( [2.000000001,3.0,4.0] ) >>>> a.dtype >dtype('float64') >>>> numpy.asarray(a, numpy.float32) >array([ 2., 3., 4.], dtype=float32) Am I doing sth wrong? Can anyone confirm that? Thanks in advance, Xaver 
From: Michael Haggerty <mhagger@al...>  20090301 08:33:51

Matt Ball wrote: > What is the easiest way to create a scatterplot using gnuplot.py? I > simply need to plot sets of data points as (x,y) pairs, but can't find > any reasonable documentation on this. I know I can plot a 1D Python > array by passing that array to a plot() command (in Python, of > course), but I can't do the same if I pass in a 2D array, e.g. where > array[*][0] is the xcoordinate and array[*][1] is the ycoordinate. > Surely there must be a deadsimple way to do this that I'm missing! demo.py has some examples. Michael 
From: Matt Ball <ball@br...>  20090301 08:21:00

What is the easiest way to create a scatterplot using gnuplot.py? I simply need to plot sets of data points as (x,y) pairs, but can't find any reasonable documentation on this. I know I can plot a 1D Python array by passing that array to a plot() command (in Python, of course), but I can't do the same if I pass in a 2D array, e.g. where array[*][0] is the xcoordinate and array[*][1] is the ycoordinate. Surely there must be a deadsimple way to do this that I'm missing! Thanks, Matt 