Getting the data

Please look at the information in the `get_data.ipynb` notebook. You have to end up with `swift.dkrz.de` folder located somwere in your system. All data used in this examples are located in this folder.



In [1]:

    
import sys
sys.path.append("../")

import pyfesom as pf
import matplotlib.pyplot as plt
from mpl_toolkits.basemap import Basemap
from matplotlib.colors import LinearSegmentedColormap
import numpy as np
#%matplotlib notebook
%matplotlib inline
from matplotlib import cm
from netCDF4 import Dataset, MFDataset

First, as usuall load the mesh:



In [2]:

    
meshpath  ='../../swift.dkrz.de/COREII'
mesh = pf.load_mesh(meshpath, usepickle=True)









    



/scratch/users/nkolduno/swift.dkrz.de/COREII/pickle_mesh
2
The usepickle == True)
The pickle file for python 2 exists.
The mesh will be loaded from /scratch/users/nkolduno/swift.dkrz.de/COREII/pickle_mesh

Load data for one year:



In [4]:

    
fl = Dataset('../../swift.dkrz.de/COREII_data/fesom.1951.oce.mean.nc')



In [5]:

    
fl.variables['temp'].shape









    Out[5]:





(12, 3668773)

Make a mean over all timesteps:



In [6]:

    
%%time
temp_mean = fl.variables['temp'][:,:].mean(axis=0)









    



CPU times: user 440 ms, sys: 124 ms, total: 564 ms
Wall time: 1.08 s

And plot the data



In [7]:

    
m = Basemap(projection='robin',lon_0=0, resolution='c')
x, y = m(mesh.x2, mesh.y2)



In [8]:

    
%%time
level_data, elem_no_nan = pf.get_data(temp_mean,mesh,100)

plt.figure(figsize=(10,7))
m.drawmapboundary(fill_color='0.9')
m.drawcoastlines()

levels = np.arange(-3., 30., 1)
plt.tricontourf(x, y, elem_no_nan[::], level_data, levels = levels, \
                cmap=cm.Spectral_r, extend='both')
cbar = plt.colorbar(orientation='horizontal', pad=0.03);
cbar.set_label("Temperature, $^{\circ}$C")
plt.title('Temperature at 100m depth')
plt.tight_layout()









    



For depth 100 model level 100.0 will be used
CPU times: user 712 ms, sys: 232 ms, total: 944 ms
Wall time: 679 ms

Do STD instead of mean



In [9]:

    
%%time
temp_std = fl.variables['temp'][:,:].std(axis=0)









    



CPU times: user 224 ms, sys: 392 ms, total: 616 ms
Wall time: 626 ms



In [11]:

    
%%time
level_data, elem_no_nan = pf.get_data(temp_std,mesh,100)

plt.figure(figsize=(10,7))
m.drawmapboundary(fill_color='0.9')
m.drawcoastlines()

levels = np.arange(0, 3., 0.2)
eps=(levels.max()-levels.min())/50.
level_data[level_data<=levels.min()]=levels.min()+eps
level_data[level_data>=levels.max()]=levels.max()-eps
plt.tricontourf(x, y, elem_no_nan[::], level_data, levels = levels, \
                cmap=cm.magma_r, extend='both')
cbar = plt.colorbar(orientation='horizontal', pad=0.03);
cbar.set_label("Temperature, $^{\circ}$C")
plt.title('Temperature at 100m depth')
plt.tight_layout()









    



For depth 100 model level 100.0 will be used






    



/scratch/users/nkolduno/miniconda2/lib/python2.7/site-packages/ipykernel/__main__.py:9: RuntimeWarning: invalid value encountered in less_equal
/scratch/users/nkolduno/miniconda2/lib/python2.7/site-packages/ipykernel/__main__.py:10: RuntimeWarning: invalid value encountered in greater_equal






    



CPU times: user 464 ms, sys: 192 ms, total: 656 ms
Wall time: 445 ms

Or make an interactive plotting interface:



In [12]:

    
from ipywidgets import interact, interactive, fixed
import ipywidgets as widgets



In [15]:

    
def sp(mon=0, depth = 100):
    level_data, elem_no_nan = pf.get_data(fl.variables['temp'][mon-1,:]-temp_mean,\
                                          mesh, depth)

    plt.figure(figsize=(10,7))
    m.drawmapboundary(fill_color='0.9')
    m.drawcoastlines()

    levels = np.arange(-2, 2., 0.2)
    eps=(levels.max()-levels.min())/50.
    level_data[level_data<=levels.min()]=levels.min()+eps
    level_data[level_data>=levels.max()]=levels.max()-eps
    plt.tricontourf(x, y, elem_no_nan[::], level_data, levels = levels, \
                    cmap=cm.coolwarm, extend='both')
    cbar = plt.colorbar(orientation='horizontal', pad=0.03);
    cbar.set_label("Temperature, $^{\circ}$C")
    plt.title('Temperature at {}m depth, month {}'.format(str(depth),str(mon)))
    plt.tight_layout()



In [16]:

    
interact(sp, mon =(1,24), depth = (0,5000,100));









    



For depth 100 model level 100.0 will be used






    



/scratch/users/nkolduno/miniconda2/lib/python2.7/site-packages/ipykernel/__main__.py:10: RuntimeWarning: invalid value encountered in less_equal
/scratch/users/nkolduno/miniconda2/lib/python2.7/site-packages/ipykernel/__main__.py:11: RuntimeWarning: invalid value encountered in greater_equal



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Getting the data

Please look at the information in the get_data.ipynb notebook. You have to end up with swift.dkrz.de folder located somwere in your system. All data used in this examples are located in this folder.

Please look at the information in the `get_data.ipynb` notebook. You have to end up with `swift.dkrz.de` folder located somwere in your system. All data used in this examples are located in this folder.