Difference between revisions of "Python/PlotMetData"
From mn/geo/geoit
(Created page with "<rst> ========================================== Plotting Meteorological Data with Python ========================================== This is a very brief introduction to using p...") |
|||
| (5 intermediate revisions by one other user not shown) | |||
| Line 1: | Line 1: | ||
| − | + | = Plotting Meteorological Data with Python = | |
| − | = | ||
| − | Plotting Meteorological Data with Python | ||
| − | |||
| − | This is a very brief introduction to using pygrib and NetCDFFile in order to plot met data in Python. Note that you should read the | + | This is a very brief introduction to using pygrib and NetCDFFile in order to plot met data in Python. Note that you should read the [[Python/SettingPaths]] section in order to be sure that you'll be able to import the appropriate modules. |
Let's get started with some test data:: | Let's get started with some test data:: | ||
mkdir test | mkdir test | ||
| − | + | cd test | |
| − | + | cp ~sec/kleinproject/FUKU/geop_april* . | |
| − | + | ||
| + | |||
Now, start ipython in your shell, or create a python file in the test directory:: | Now, start ipython in your shell, or create a python file in the test directory:: | ||
ipython | ipython | ||
| − | + | ||
| − | |||
| − | |||
| − | |||
| − | |||
| − | |||
| − | |||
| − | |||
| − | |||
| − | |||
| − | |||
| − | |||
| − | |||
| − | |||
| − | |||
| − | |||
| − | |||
| − | |||
| − | |||
| − | |||
| − | |||
| − | |||
| − | |||
| − | |||
| − | |||
| − | |||
| − | |||
| − | |||
| − | + | Next, let's take care of some basic imports:: <source lang="python"> | |
| − | + | import matplotlib.pyplot as plt | |
| − | + | import pygrib | |
| − | + | from netCDF4 import Dataset as NetCDFFile | |
| − | + | </source> | |
| − | |||
| − | |||
| − | |||
| − | |||
| − | |||
| − | |||
| − | + | <br/>Now, we'll write some python code to plot the netcdf variables:: <source lang="python"> | |
| + | nci = NetCDFFile('geopot_april_01.nc') | ||
| + | nci.variables #will print a listing of the variables (note: nci.variables is a dictionary) | ||
| + | z = nci.variables['z'] | ||
| + | z.shape #what shape is the 'z' array? | ||
| + | for i in range(3): | ||
| + | plt.figure() | ||
| + | plt.imshow(z[0,i,:,:]) #we take the i'th slab | ||
| + | plt.title('netcdf geopot {0}'.format(i)) | ||
| + | plt.colorbar() | ||
| + | plt.savefig('nc_geopot_{}'.format(i)) | ||
| + | |||
| + | </source> Now, let's take a look at the grib data:: <source lang="python"> | ||
| + | grbs = pygrib.open('geop_april_01_2011.grib') | ||
| + | for grb in grbs: | ||
| + | grb | ||
| + | </source> This will print a listing of all the gribs in the grib file. Make sure we reset the grbs back to the beginning:: <source lang="python"> | ||
| + | grbs.seek(0) | ||
| + | ghs = grbs.select(name='Geopotential') | ||
| − | </ | + | for i,grb in enumerate(ghs): |
| + | plt.figure() | ||
| + | g = grb | ||
| + | plt.imshow(g.values) | ||
| + | title = g.name + ' at level ' + str(g.level) + ' [' + g.units + ']' | ||
| + | plt.title(title) | ||
| + | plt.colorbar() | ||
| + | plt.savefig(g.name + str(i) + '.png') | ||
| + | </source> That's it! In your folder you should have some test plots. | ||
Latest revision as of 10:29, 11 February 2015
Plotting Meteorological Data with Python
This is a very brief introduction to using pygrib and NetCDFFile in order to plot met data in Python. Note that you should read the Python/SettingPaths section in order to be sure that you'll be able to import the appropriate modules.
Let's get started with some test data::
mkdir test cd test cp ~sec/kleinproject/FUKU/geop_april* .
Now, start ipython in your shell, or create a python file in the test directory::
ipythonNext, let's take care of some basic imports::
import matplotlib.pyplot as plt
import pygrib
from netCDF4 import Dataset as NetCDFFile
Now, we'll write some python code to plot the netcdf variables::
nci = NetCDFFile('geopot_april_01.nc')
nci.variables #will print a listing of the variables (note: nci.variables is a dictionary)
z = nci.variables['z']
z.shape #what shape is the 'z' array?
for i in range(3):
plt.figure()
plt.imshow(z[0,i,:,:]) #we take the i'th slab
plt.title('netcdf geopot {0}'.format(i))
plt.colorbar()
plt.savefig('nc_geopot_{}'.format(i))
grbs = pygrib.open('geop_april_01_2011.grib')
for grb in grbs:
grb
grbs.seek(0)
ghs = grbs.select(name='Geopotential')
for i,grb in enumerate(ghs):
plt.figure()
g = grb
plt.imshow(g.values)
title = g.name + ' at level ' + str(g.level) + ' [' + g.units + ']'
plt.title(title)
plt.colorbar()
plt.savefig(g.name + str(i) + '.png')
