Re: [Numpy-discussion] numpy.mean slicing in a netCDF file
On Tue, Oct 14, 2014 at 11:30 AM, Fadzil Mnor fadzilmno...@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 sho...@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 fadzilmno...@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
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--
Christopher Barker, Ph.D.
Oceanographer
Emergency Response Division
NOAA/NOS/ORR(206) 526-6959 voice
7600 Sand Point Way NE (206) 526-6329 fax
Seattle, WA 98115 (206) 526-6317 main reception
chris.bar...@noaa.gov
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Re: [Numpy-discussion] numpy.mean slicing in a netCDF file
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.bar...@noaa.gov wrote:
On Tue, Oct 14, 2014 at 11:30 AM, Fadzil Mnor fadzilmno...@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 sho...@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 fadzilmno...@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
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___
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--
Christopher Barker, Ph.D.
Oceanographer
Emergency Response Division
NOAA/NOS/ORR(206) 526-6959 voice
7600 Sand Point Way NE (206) 526-6329 fax
Seattle, WA 98115 (206) 526-6317 main reception
chris.bar...@noaa.gov
___
Re: [Numpy-discussion] numpy.mean slicing in a netCDF file
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.r...@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.bar...@noaa.gov
wrote:
On Tue, Oct 14, 2014 at 11:30 AM, Fadzil Mnor fadzilmno...@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 sho...@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 fadzilmno...@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
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[Numpy-discussion] 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
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Re: [Numpy-discussion] numpy.mean slicing in a netCDF file
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 fadzilmno...@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
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Re: [Numpy-discussion] numpy.mean slicing in a netCDF file
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 sho...@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 fadzilmno...@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
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