Geographical statistics

from matplotlib import pyplot as plt
import py_eddy_tracker_sample

from py_eddy_tracker.observations.tracking import TrackEddiesObservations


def start_axes(title):
    fig = plt.figure(figsize=(13.5, 5))
    ax = fig.add_axes([0.03, 0.03, 0.90, 0.94])
    ax.set_xlim(-6, 36.5), ax.set_ylim(30, 46)
    ax.set_aspect("equal")
    ax.set_title(title)
    return ax

Load an experimental med atlas over a period of 26 years (1993-2019), we merge the 2 datasets

a = TrackEddiesObservations.load_file(
    py_eddy_tracker_sample.get_demo_path(
        "eddies_med_adt_allsat_dt2018/Anticyclonic.zarr"
    )
)
c = TrackEddiesObservations.load_file(
    py_eddy_tracker_sample.get_demo_path("eddies_med_adt_allsat_dt2018/Cyclonic.zarr")
)
a = a.merge(c)

step = 0.1

Mean of amplitude in each box

ax = start_axes("Amplitude mean by box of %s°" % step)
g = a.grid_stat(((-7, 37, step), (30, 46, step)), "amplitude")
m = g.display(ax, name="amplitude", vmin=0, vmax=10, factor=100)
ax.grid()
cb = plt.colorbar(m, cax=ax.figure.add_axes([0.94, 0.05, 0.01, 0.9]))
cb.set_label("Amplitude (cm)")

Mean of speed radius in each box

ax = start_axes("Speed radius mean by box of %s°" % step)
g = a.grid_stat(((-7, 37, step), (30, 46, step)), "radius_s")
m = g.display(ax, name="radius_s", vmin=10, vmax=50, factor=0.001)
ax.grid()
cb = plt.colorbar(m, cax=ax.figure.add_axes([0.94, 0.05, 0.01, 0.9]))
cb.set_label("Speed radius (km)")

Percent of virtual on the whole obs in each box

ax = start_axes("Percent of virtual by box of %s°" % step)
g = a.grid_stat(((-7, 37, step), (30, 46, step)), "virtual")
g.vars["virtual"] *= 100
m = g.display(ax, name="virtual", vmin=0, vmax=15)
ax.grid()
cb = plt.colorbar(m, cax=ax.figure.add_axes([0.94, 0.05, 0.01, 0.9]))
cb.set_label("Percent of virtual (%)")