numpy.mean slicing in a netCDF file
Hi all, I wrote a script and plot monthly mean zonal wind (from a netcdf file names uwnd.mon.mean.nc) and I'm not sure if I'm doing it correctly. What I have: ******************************************************************************** *#this part calculates mean values for january only, from 1980-2010; thus the index looks like this 396:757:12* def ujan(): f = nc.Dataset('~/data/ncep/uwnd.mon.mean.nc') u10_1 = f.variables['uwnd'] u10_2 = np.mean(u10_1[396:757:12,:,38,39:43],axis=0) return u10_2 uJan = ujan()* #calling function* *#this part is only to define lon, lat and level * q = nc.Dataset('~/data/ncep/uwnd.mon.mean.nc') lon=q.variables['lon'] lat=q.variables['lat'] lev=q.variables['level'] *#for some reason I need to define this unless it gave error "length of x must be number of column in z"* lon=lon[39:43] *#begin plotting* clevs=np.arange(-10.,10.,0.5) fig = plt.figure(figsize=(11, 8)) fig.clf() ax = fig.add_subplot(111) ax.axis([97.5, 105., 1000., 10.]) ax.tick_params(direction='out', which='both') ax.set_xlabel('Lon (degrees)') ax.set_ylabel('Pressure (mb)') ax.set_xticks(np.arange(97.5, 105., .5)) ax.set_yticks([1000, 700, 500, 300, 100, 10]) cs=ax.contourf(lon, lev, uJan, clevs, extend='both',cmap='seismic') plt.title('Zonal winds average (Jan, 1981-2010)') cax = fig.add_axes([0.99, 0.1, 0.03, 0.8]) aa=fig.colorbar(cs,cax=cax,orientation='vertical') aa.set_label('m/s') plt.savefig('~/uwind-crossection-test.png', bbox_inches='tight') ******************************************************************************* the result is attached. I have no idea how to confirm the result (at least until this email is written) , but I believe the lower altitude values should be mostly negative, because over this region, the zonal wind are usually easterly (thus,negative values), but I got positive values. Put the information above aside, *I just want to know if my slicing in the ujan() function is correct*. If it is, then, there must be nothing wrong(except my above mentioned assumption). The data file dimension is: *[time,level,latitude,longitude]* This part: *u10_2 = np.mean(u10_1[396:757:12,:,38,39:43],axis=0)* The line above will calculate the mean of zonal wind (uwnd) in a range of time index 396 to 757 for each year (january only), for all vertical level, at latitude index 38 (5 N) and in between longitude index 39 to 43 (97.5E-105E). I assume it will calculate a 30-year average of zonal wind for january only. Is this correct? Thank you. Fadzil
Hi Fadzil, My strong recommendation is that you don't just use numpy/netCDF4 to process your data, but rather use one of a multitude of packages that have been developed specifically to facilitate working with labeled data from netCDF files: - Iris: http://scitools.org.uk/iris/ - CDAT: http://uvcdat.llnl.gov/ - xray (my project): http://xray.readthedocs.org I can't answer your specific question without taking a careful look at your data, but in very general terms, your code will have fewer bugs if you can use meaningful labels to refer to your data rather than numeric ranges like 396:757:12. Best, Stephan On Tue, Oct 14, 2014 at 3:50 AM, Fadzil Mnor <fadzilmnor84@gmail.com> wrote:
Hi all, I wrote a script and plot monthly mean zonal wind (from a netcdf file names uwnd.mon.mean.nc) and I'm not sure if I'm doing it correctly. What I have:
******************************************************************************** *#this part calculates mean values for january only, from 1980-2010; thus the index looks like this 396:757:12*
def ujan(): f = nc.Dataset('~/data/ncep/uwnd.mon.mean.nc') u10_1 = f.variables['uwnd'] u10_2 = np.mean(u10_1[396:757:12,:,38,39:43],axis=0) return u10_2
uJan = ujan()* #calling function*
*#this part is only to define lon, lat and level * q = nc.Dataset('~/data/ncep/uwnd.mon.mean.nc') lon=q.variables['lon'] lat=q.variables['lat'] lev=q.variables['level']
*#for some reason I need to define this unless it gave error "length of x must be number of column in z"*
lon=lon[39:43]
*#begin plotting*
clevs=np.arange(-10.,10.,0.5) fig = plt.figure(figsize=(11, 8)) fig.clf() ax = fig.add_subplot(111) ax.axis([97.5, 105., 1000., 10.]) ax.tick_params(direction='out', which='both') ax.set_xlabel('Lon (degrees)') ax.set_ylabel('Pressure (mb)') ax.set_xticks(np.arange(97.5, 105., .5)) ax.set_yticks([1000, 700, 500, 300, 100, 10]) cs=ax.contourf(lon, lev, uJan, clevs, extend='both',cmap='seismic') plt.title('Zonal winds average (Jan, 1981-2010)') cax = fig.add_axes([0.99, 0.1, 0.03, 0.8]) aa=fig.colorbar(cs,cax=cax,orientation='vertical') aa.set_label('m/s') plt.savefig('~/uwind-crossection-test.png', bbox_inches='tight')
*******************************************************************************
the result is attached. I have no idea how to confirm the result (at least until this email is written) , but I believe the lower altitude values should be mostly negative, because over this region, the zonal wind are usually easterly (thus,negative values), but I got positive values.
Put the information above aside, *I just want to know if my slicing in the ujan() function is correct*. If it is, then, there must be nothing wrong(except my above mentioned assumption). The data file dimension is: *[time,level,latitude,longitude]*
This part: *u10_2 = np.mean(u10_1[396:757:12,:,38,39:43],axis=0)* The line above will calculate the mean of zonal wind (uwnd) in a range of time index 396 to 757 for each year (january only), for all vertical level, at latitude index 38 (5 N) and in between longitude index 39 to 43 (97.5E-105E). I assume it will calculate a 30-year average of zonal wind for january only. Is this correct?
Thank you.
Fadzil
_______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
Thank you Stephan, I've been trying to install IRIS on my laptop (OS X) for months. Errors everywhere. I'll look at that IRIS again, and other links. Cheers, Fadzil On Tue, Oct 14, 2014 at 7:09 PM, Stephan Hoyer <shoyer@gmail.com> wrote:
Hi Fadzil,
My strong recommendation is that you don't just use numpy/netCDF4 to process your data, but rather use one of a multitude of packages that have been developed specifically to facilitate working with labeled data from netCDF files: - Iris: http://scitools.org.uk/iris/ - CDAT: http://uvcdat.llnl.gov/ - xray (my project): http://xray.readthedocs.org
I can't answer your specific question without taking a careful look at your data, but in very general terms, your code will have fewer bugs if you can use meaningful labels to refer to your data rather than numeric ranges like 396:757:12.
Best, Stephan
On Tue, Oct 14, 2014 at 3:50 AM, Fadzil Mnor <fadzilmnor84@gmail.com> wrote:
Hi all, I wrote a script and plot monthly mean zonal wind (from a netcdf file names uwnd.mon.mean.nc) and I'm not sure if I'm doing it correctly. What I have:
******************************************************************************** *#this part calculates mean values for january only, from 1980-2010; thus the index looks like this 396:757:12*
def ujan(): f = nc.Dataset('~/data/ncep/uwnd.mon.mean.nc') u10_1 = f.variables['uwnd'] u10_2 = np.mean(u10_1[396:757:12,:,38,39:43],axis=0) return u10_2
uJan = ujan()* #calling function*
*#this part is only to define lon, lat and level * q = nc.Dataset('~/data/ncep/uwnd.mon.mean.nc') lon=q.variables['lon'] lat=q.variables['lat'] lev=q.variables['level']
*#for some reason I need to define this unless it gave error "length of x must be number of column in z"*
lon=lon[39:43]
*#begin plotting*
clevs=np.arange(-10.,10.,0.5) fig = plt.figure(figsize=(11, 8)) fig.clf() ax = fig.add_subplot(111) ax.axis([97.5, 105., 1000., 10.]) ax.tick_params(direction='out', which='both') ax.set_xlabel('Lon (degrees)') ax.set_ylabel('Pressure (mb)') ax.set_xticks(np.arange(97.5, 105., .5)) ax.set_yticks([1000, 700, 500, 300, 100, 10]) cs=ax.contourf(lon, lev, uJan, clevs, extend='both',cmap='seismic') plt.title('Zonal winds average (Jan, 1981-2010)') cax = fig.add_axes([0.99, 0.1, 0.03, 0.8]) aa=fig.colorbar(cs,cax=cax,orientation='vertical') aa.set_label('m/s') plt.savefig('~/uwind-crossection-test.png', bbox_inches='tight')
*******************************************************************************
the result is attached. I have no idea how to confirm the result (at least until this email is written) , but I believe the lower altitude values should be mostly negative, because over this region, the zonal wind are usually easterly (thus,negative values), but I got positive values.
Put the information above aside, *I just want to know if my slicing in the ujan() function is correct*. If it is, then, there must be nothing wrong(except my above mentioned assumption). The data file dimension is: *[time,level,latitude,longitude]*
This part: *u10_2 = np.mean(u10_1[396:757:12,:,38,39:43],axis=0)* The line above will calculate the mean of zonal wind (uwnd) in a range of time index 396 to 757 for each year (january only), for all vertical level, at latitude index 38 (5 N) and in between longitude index 39 to 43 (97.5E-105E). I assume it will calculate a 30-year average of zonal wind for january only. Is this correct?
Thank you.
Fadzil
_______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
_______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
On Tue, Oct 14, 2014 at 11:30 AM, Fadzil Mnor <fadzilmnor84@gmail.com> wrote:
I've been trying to install IRIS on my laptop (OS X) for months. Errors everywhere. I'll look at that IRIS again, and other links.
IRIS has been an install challeng,e but gotten better. And you ay even find a conda package for it if you use Anaconda -- I put one up during Scipy -- they may be a newer build, though. -Chris
Cheers,
Fadzil
On Tue, Oct 14, 2014 at 7:09 PM, Stephan Hoyer <shoyer@gmail.com> wrote:
Hi Fadzil,
My strong recommendation is that you don't just use numpy/netCDF4 to process your data, but rather use one of a multitude of packages that have been developed specifically to facilitate working with labeled data from netCDF files: - Iris: http://scitools.org.uk/iris/ - CDAT: http://uvcdat.llnl.gov/ - xray (my project): http://xray.readthedocs.org
I can't answer your specific question without taking a careful look at your data, but in very general terms, your code will have fewer bugs if you can use meaningful labels to refer to your data rather than numeric ranges like 396:757:12.
Best, Stephan
On Tue, Oct 14, 2014 at 3:50 AM, Fadzil Mnor <fadzilmnor84@gmail.com> wrote:
Hi all, I wrote a script and plot monthly mean zonal wind (from a netcdf file names uwnd.mon.mean.nc) and I'm not sure if I'm doing it correctly. What I have:
******************************************************************************** *#this part calculates mean values for january only, from 1980-2010; thus the index looks like this 396:757:12*
def ujan(): f = nc.Dataset('~/data/ncep/uwnd.mon.mean.nc') u10_1 = f.variables['uwnd'] u10_2 = np.mean(u10_1[396:757:12,:,38,39:43],axis=0) return u10_2
uJan = ujan()* #calling function*
*#this part is only to define lon, lat and level * q = nc.Dataset('~/data/ncep/uwnd.mon.mean.nc') lon=q.variables['lon'] lat=q.variables['lat'] lev=q.variables['level']
*#for some reason I need to define this unless it gave error "length of x must be number of column in z"*
lon=lon[39:43]
*#begin plotting*
clevs=np.arange(-10.,10.,0.5) fig = plt.figure(figsize=(11, 8)) fig.clf() ax = fig.add_subplot(111) ax.axis([97.5, 105., 1000., 10.]) ax.tick_params(direction='out', which='both') ax.set_xlabel('Lon (degrees)') ax.set_ylabel('Pressure (mb)') ax.set_xticks(np.arange(97.5, 105., .5)) ax.set_yticks([1000, 700, 500, 300, 100, 10]) cs=ax.contourf(lon, lev, uJan, clevs, extend='both',cmap='seismic') plt.title('Zonal winds average (Jan, 1981-2010)') cax = fig.add_axes([0.99, 0.1, 0.03, 0.8]) aa=fig.colorbar(cs,cax=cax,orientation='vertical') aa.set_label('m/s') plt.savefig('~/uwind-crossection-test.png', bbox_inches='tight')
*******************************************************************************
the result is attached. I have no idea how to confirm the result (at least until this email is written) , but I believe the lower altitude values should be mostly negative, because over this region, the zonal wind are usually easterly (thus,negative values), but I got positive values.
Put the information above aside, *I just want to know if my slicing in the ujan() function is correct*. If it is, then, there must be nothing wrong(except my above mentioned assumption). The data file dimension is: *[time,level,latitude,longitude]*
This part: *u10_2 = np.mean(u10_1[396:757:12,:,38,39:43],axis=0)* The line above will calculate the mean of zonal wind (uwnd) in a range of time index 396 to 757 for each year (january only), for all vertical level, at latitude index 38 (5 N) and in between longitude index 39 to 43 (97.5E-105E). I assume it will calculate a 30-year average of zonal wind for january only. Is this correct?
Thank you.
Fadzil
_______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
_______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
_______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
-- Christopher Barker, Ph.D. Oceanographer Emergency Response Division NOAA/NOS/OR&R (206) 526-6959 voice 7600 Sand Point Way NE (206) 526-6329 fax Seattle, WA 98115 (206) 526-6317 main reception Chris.Barker@noaa.gov
Stephen is being a bit modest by putting xray last in the list. I recommend it, and it is very painless to install. I could only get iris installed via a SciTools repo on binstar and even then, I had to tinker with a few things to get it working (and it was only the linux binaries, too). Ben Root On Wed, Oct 15, 2014 at 3:44 PM, Chris Barker <chris.barker@noaa.gov> wrote:
On Tue, Oct 14, 2014 at 11:30 AM, Fadzil Mnor <fadzilmnor84@gmail.com> wrote:
I've been trying to install IRIS on my laptop (OS X) for months. Errors everywhere. I'll look at that IRIS again, and other links.
IRIS has been an install challeng,e but gotten better.
And you ay even find a conda package for it if you use Anaconda -- I put one up during Scipy -- they may be a newer build, though.
-Chris
Cheers,
Fadzil
On Tue, Oct 14, 2014 at 7:09 PM, Stephan Hoyer <shoyer@gmail.com> wrote:
Hi Fadzil,
My strong recommendation is that you don't just use numpy/netCDF4 to process your data, but rather use one of a multitude of packages that have been developed specifically to facilitate working with labeled data from netCDF files: - Iris: http://scitools.org.uk/iris/ - CDAT: http://uvcdat.llnl.gov/ - xray (my project): http://xray.readthedocs.org
I can't answer your specific question without taking a careful look at your data, but in very general terms, your code will have fewer bugs if you can use meaningful labels to refer to your data rather than numeric ranges like 396:757:12.
Best, Stephan
On Tue, Oct 14, 2014 at 3:50 AM, Fadzil Mnor <fadzilmnor84@gmail.com> wrote:
Hi all, I wrote a script and plot monthly mean zonal wind (from a netcdf file names uwnd.mon.mean.nc) and I'm not sure if I'm doing it correctly. What I have:
******************************************************************************** *#this part calculates mean values for january only, from 1980-2010; thus the index looks like this 396:757:12*
def ujan(): f = nc.Dataset('~/data/ncep/uwnd.mon.mean.nc') u10_1 = f.variables['uwnd'] u10_2 = np.mean(u10_1[396:757:12,:,38,39:43],axis=0) return u10_2
uJan = ujan()* #calling function*
*#this part is only to define lon, lat and level * q = nc.Dataset('~/data/ncep/uwnd.mon.mean.nc') lon=q.variables['lon'] lat=q.variables['lat'] lev=q.variables['level']
*#for some reason I need to define this unless it gave error "length of x must be number of column in z"*
lon=lon[39:43]
*#begin plotting*
clevs=np.arange(-10.,10.,0.5) fig = plt.figure(figsize=(11, 8)) fig.clf() ax = fig.add_subplot(111) ax.axis([97.5, 105., 1000., 10.]) ax.tick_params(direction='out', which='both') ax.set_xlabel('Lon (degrees)') ax.set_ylabel('Pressure (mb)') ax.set_xticks(np.arange(97.5, 105., .5)) ax.set_yticks([1000, 700, 500, 300, 100, 10]) cs=ax.contourf(lon, lev, uJan, clevs, extend='both',cmap='seismic') plt.title('Zonal winds average (Jan, 1981-2010)') cax = fig.add_axes([0.99, 0.1, 0.03, 0.8]) aa=fig.colorbar(cs,cax=cax,orientation='vertical') aa.set_label('m/s') plt.savefig('~/uwind-crossection-test.png', bbox_inches='tight')
*******************************************************************************
the result is attached. I have no idea how to confirm the result (at least until this email is written) , but I believe the lower altitude values should be mostly negative, because over this region, the zonal wind are usually easterly (thus,negative values), but I got positive values.
Put the information above aside, *I just want to know if my slicing in the ujan() function is correct*. If it is, then, there must be nothing wrong(except my above mentioned assumption). The data file dimension is: *[time,level,latitude,longitude]*
This part: *u10_2 = np.mean(u10_1[396:757:12,:,38,39:43],axis=0)* The line above will calculate the mean of zonal wind (uwnd) in a range of time index 396 to 757 for each year (january only), for all vertical level, at latitude index 38 (5 N) and in between longitude index 39 to 43 (97.5E-105E). I assume it will calculate a 30-year average of zonal wind for january only. Is this correct?
Thank you.
Fadzil
_______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
_______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
_______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
--
Christopher Barker, Ph.D. Oceanographer
Emergency Response Division NOAA/NOS/OR&R (206) 526-6959 voice 7600 Sand Point Way NE (206) 526-6329 fax Seattle, WA 98115 (206) 526-6317 main reception
Chris.Barker@noaa.gov
_______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
Thanks for confirming that I'm not the only one having trouble with IRIS installation. Such a pain! Back to the first question, I figured that the NCEP Reanalysis data has the y axis "from 90N to 90S", means the indexing started from north (90), not south (-90), which means that my calculation was on 5 S instead of 5 N. Fadzil Postgraduate Student Room 1U09 - Dept of Meteorology University of Reading, Earley Gate Reading RG6 6BB, UK On Wed, Oct 15, 2014 at 10:04 PM, Benjamin Root <ben.root@ou.edu> wrote:
Stephen is being a bit modest by putting xray last in the list. I recommend it, and it is very painless to install. I could only get iris installed via a SciTools repo on binstar and even then, I had to tinker with a few things to get it working (and it was only the linux binaries, too).
Ben Root
On Wed, Oct 15, 2014 at 3:44 PM, Chris Barker <chris.barker@noaa.gov> wrote:
On Tue, Oct 14, 2014 at 11:30 AM, Fadzil Mnor <fadzilmnor84@gmail.com> wrote:
I've been trying to install IRIS on my laptop (OS X) for months. Errors everywhere. I'll look at that IRIS again, and other links.
IRIS has been an install challeng,e but gotten better.
And you ay even find a conda package for it if you use Anaconda -- I put one up during Scipy -- they may be a newer build, though.
-Chris
Cheers,
Fadzil
On Tue, Oct 14, 2014 at 7:09 PM, Stephan Hoyer <shoyer@gmail.com> wrote:
Hi Fadzil,
My strong recommendation is that you don't just use numpy/netCDF4 to process your data, but rather use one of a multitude of packages that have been developed specifically to facilitate working with labeled data from netCDF files: - Iris: http://scitools.org.uk/iris/ - CDAT: http://uvcdat.llnl.gov/ - xray (my project): http://xray.readthedocs.org
I can't answer your specific question without taking a careful look at your data, but in very general terms, your code will have fewer bugs if you can use meaningful labels to refer to your data rather than numeric ranges like 396:757:12.
Best, Stephan
On Tue, Oct 14, 2014 at 3:50 AM, Fadzil Mnor <fadzilmnor84@gmail.com> wrote:
Hi all, I wrote a script and plot monthly mean zonal wind (from a netcdf file names uwnd.mon.mean.nc) and I'm not sure if I'm doing it correctly. What I have:
******************************************************************************** *#this part calculates mean values for january only, from 1980-2010; thus the index looks like this 396:757:12*
def ujan(): f = nc.Dataset('~/data/ncep/uwnd.mon.mean.nc') u10_1 = f.variables['uwnd'] u10_2 = np.mean(u10_1[396:757:12,:,38,39:43],axis=0) return u10_2
uJan = ujan()* #calling function*
*#this part is only to define lon, lat and level * q = nc.Dataset('~/data/ncep/uwnd.mon.mean.nc') lon=q.variables['lon'] lat=q.variables['lat'] lev=q.variables['level']
*#for some reason I need to define this unless it gave error "length of x must be number of column in z"*
lon=lon[39:43]
*#begin plotting*
clevs=np.arange(-10.,10.,0.5) fig = plt.figure(figsize=(11, 8)) fig.clf() ax = fig.add_subplot(111) ax.axis([97.5, 105., 1000., 10.]) ax.tick_params(direction='out', which='both') ax.set_xlabel('Lon (degrees)') ax.set_ylabel('Pressure (mb)') ax.set_xticks(np.arange(97.5, 105., .5)) ax.set_yticks([1000, 700, 500, 300, 100, 10]) cs=ax.contourf(lon, lev, uJan, clevs, extend='both',cmap='seismic') plt.title('Zonal winds average (Jan, 1981-2010)') cax = fig.add_axes([0.99, 0.1, 0.03, 0.8]) aa=fig.colorbar(cs,cax=cax,orientation='vertical') aa.set_label('m/s') plt.savefig('~/uwind-crossection-test.png', bbox_inches='tight')
*******************************************************************************
the result is attached. I have no idea how to confirm the result (at least until this email is written) , but I believe the lower altitude values should be mostly negative, because over this region, the zonal wind are usually easterly (thus,negative values), but I got positive values.
Put the information above aside, *I just want to know if my slicing in the ujan() function is correct*. If it is, then, there must be nothing wrong(except my above mentioned assumption). The data file dimension is: *[time,level,latitude,longitude]*
This part: *u10_2 = np.mean(u10_1[396:757:12,:,38,39:43],axis=0)* The line above will calculate the mean of zonal wind (uwnd) in a range of time index 396 to 757 for each year (january only), for all vertical level, at latitude index 38 (5 N) and in between longitude index 39 to 43 (97.5E-105E). I assume it will calculate a 30-year average of zonal wind for january only. Is this correct?
Thank you.
Fadzil
_______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
_______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
_______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
--
Christopher Barker, Ph.D. Oceanographer
Emergency Response Division NOAA/NOS/OR&R (206) 526-6959 voice 7600 Sand Point Way NE (206) 526-6329 fax Seattle, WA 98115 (206) 526-6317 main reception
Chris.Barker@noaa.gov
_______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
_______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
participants (4)
-
Benjamin Root -
Chris Barker -
Fadzil Mnor -
Stephan Hoyer