README

How do I get set up?

To avoid problems with installation, use of the virtualenv Python virtual environment is recommended.

Then use pip to install all dependencies (numpy, scipy, matplotlib, netCDF4, cython, pyproj, Shapely, ...), e.g.:

pip install cython numpy matplotlib scipy netCDF4 shapely pyproj

Then run the following to install the eddy tracker:

python setup.py install

Two executables are now available in your PATH: EddyIdentification and EddyTracking

Edit the corresponding yaml files and then run the code, e.g.:

EddyIdentification eddy_identification.yaml

for identification, followed by:

EddyTracking tracking.yaml

for tracking.

Py Eddy Tracker module

Grid manipulation

Loading grid

from py_eddy_tracker.dataset.grid import RegularGridDataset
h = RegularGridDataset('share/nrt_global_allsat_phy_l4_20190223_20190226.nc', 'longitude', 'latitude')

Plotting grid

from matplotlib import pyplot as plt
fig = plt.figure(figsize=(14, 12))
ax = fig.add_axes([.02, .51, .9, .45])
ax.set_title('ADT (m)')
ax.set_ylim(-75, 75)
ax.set_aspect('equal')
m=ax.pcolormesh(h.x_bounds, h.y_bounds, h.grid('adt').T.copy(), vmin=-1, vmax=1, cmap='coolwarm')
ax.grid(True)
plt.colorbar(m, cax=fig.add_axes([.94, .51, .01, .45]))

Filtering

h.bessel_high_filter('adt', 500, order=3)

Add second plot

ax = fig.add_axes([.03, .02, .9, .45])
ax.set_title('ADT Filtered (m)')
ax.set_aspect('equal')
ax.set_ylim(-75, 75)
m=ax.pcolormesh(h.x_bounds, h.y_bounds, h.grid('adt').T, vmin=-.1, vmax=.1, cmap='coolwarm')
ax.grid(True)
plt.colorbar(m, cax=fig.add_axes([.94, .02, .01, .45]))
fig.savefig('share/png/filter.png')

Compute spectrum and spectrum ratio on some area

Load data

grid_name, lon_name, lat_name = 'share/nrt_global_allsat_phy_l4_20190223_20190226.nc', 'longitude', 'latitude'
raw = RegularGridDataset(grid_name, lon_name, lat_name)
filtered = RegularGridDataset(grid_name, lon_name, lat_name)
filtered.bessel_low_filter('adt', 150, order=3)

areas = dict(
    sud_pacific=dict(llcrnrlon=188, urcrnrlon=280, llcrnrlat=-64, urcrnrlat=-7),
    atlantic_nord=dict(llcrnrlon=290, urcrnrlon=340, llcrnrlat=19.5, urcrnrlat=43),
    indien_sud=dict(llcrnrlon=35, urcrnrlon=110, llcrnrlat=-49, urcrnrlat=-26),
    )

Compute and display spectrum

fig = plt.figure(figsize=(10,6))
ax = fig.add_subplot(111)
ax.set_title('Spectrum')
ax.set_xlabel('km')
for name_area, area in areas.items():

    lon_spec, lat_spec = raw.spectrum_lonlat('adt', area=area)
    mappable = ax.loglog(*lat_spec, label='lat %s raw' % name_area)[0]
    ax.loglog(*lon_spec, label='lon %s raw' % name_area, color=mappable.get_color(), linestyle='--')

    lon_spec, lat_spec = filtered.spectrum_lonlat('adt', area=area)
    mappable = plt.loglog(*lat_spec, label='lat %s high' % name_area)[0]
    plt.loglog(*lon_spec, label='lon %s high' % name_area, color=mappable.get_color(), linestyle='--')

ax.set_xscale('log')
ax.legend()
ax.grid()
fig.savefig('share/png/spectrum.png')

Compute and display spectrum ratio

fig = plt.figure(figsize=(10,6))
ax = fig.add_subplot(111)
ax.set_title('Spectrum ratio')
ax.set_xlabel('km')
for name_area, area in areas.items():
    lon_spec, lat_spec = filtered.spectrum_lonlat('adt', area=area, ref=raw)
    mappable = ax.plot(*lat_spec, label='lat %s high' % name_area)[0]
    ax.plot(*lon_spec, label='lon %s high' % name_area, color=mappable.get_color(), linestyle='--')

ax.set_xscale('log')
ax.legend()
ax.grid()
fig.savefig('share/png/spectrum_ratio.png')