Birth and death

Following figures are based on https://doi.org/10.1016/j.pocean.2011.01.002

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))
    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


def update_axes(ax, mappable=None):
    ax.grid()
    if mappable:
        plt.colorbar(mappable, cax=ax.figure.add_axes([0.95, 0.05, 0.01, 0.9]))

Load an experimental med atlas over a period of 26 years (1993-2019)

kwargs_load = dict(
    include_vars=(
        "longitude",
        "latitude",
        "observation_number",
        "track",
        "time",
        "speed_contour_longitude",
        "speed_contour_latitude",
    )
)
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")
)

t0, t1 = a.period
step = 0.125
bins = ((-10, 37, step), (30, 46, step))
kwargs = dict(cmap="terrain_r", factor=100 / (t1 - t0), name="count", vmin=0, vmax=1)

Cyclonic

ax = start_axes("Birth cyclonic frenquency (%)")
g_c_first = c.first_obs().grid_count(bins, intern=True)
m = g_c_first.display(ax, **kwargs)
update_axes(ax, m)

ax = start_axes("Death cyclonic frenquency (%)")
g_c_last = c.last_obs().grid_count(bins, intern=True)
m = g_c_last.display(ax, **kwargs)
update_axes(ax, m)

Anticyclonic

ax = start_axes("Birth anticyclonic frequency (%)")
g_a_first = a.first_obs().grid_count(bins, intern=True)
m = g_a_first.display(ax, **kwargs)
update_axes(ax, m)

ax = start_axes("Death anticyclonic frequency (%)")
g_a_last = a.last_obs().grid_count(bins, intern=True)
m = g_a_last.display(ax, **kwargs)
update_axes(ax, m)