The boundary cannot be closed normally, and the longitude and latitude of some points are wrong。

[thomaseocean]

Hello, I am using your code. There is a problem with the longitude and latitude data calculated. According to the sample code you gave, the result of my running is as shown in the figure. Is it the wrong version of some Python libraries?，The boundary cannot be closed normally, and the longitude and latitude of some points are wrong。

[AntSimi]

To provide help, we need reproducible problem. Like snippet code, data and explanation how it's run (platform, version, expected result).

[thomaseocean]

pyeddytracker-3.6.1，python3.9，windows，data：dt_med_allsat_phy_l4_20160515_20190101.nc，use your excemple：pet_sla_and_adt.py，code： from datetime import datetime from matplotlib import pyplot as plt from py_eddy_tracker import data from py_eddy_tracker.dataset.grid import RegularGridDataset

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 Input grid, ADT will be used to detect eddies

g = RegularGridDataset( data.get_demo_path("dt_med_allsat_phy_l4_20160515_20190101.nc"), "longitude", "latitude", ) g.add_uv("adt", "ugos", "vgos") g.add_uv("sla", "ugosa", "vgosa") wavelength = 400 g.copy("adt", "adt_raw") g.copy("sla", "sla_raw") g.bessel_high_filter("adt", wavelength) g.bessel_high_filter("sla", wavelength) date = datetime(2016, 5, 15)

kwargs_a_adt = dict( lw=0.5, label="Anticyclonic ADT ({nb_obs} eddies)", ref=-10, color="k" ) kwargs_c_adt = dict(lw=0.5, label="Cyclonic ADT ({nb_obs} eddies)", ref=-10, color="r")

kwargs_a_sla = dict( lw=0.5, label="Anticyclonic SLA ({nb_obs} eddies)", ref=-10, color="g" ) kwargs_c_sla = dict(lw=0.5, label="Cyclonic SLA ({nb_obs} eddies)", ref=-10, color="b")

Run algorithm of detection

a_adt, c_adt = g.eddy_identification("adt", "ugos", "vgos", date, 0.002) a_sla, c_sla = g.eddy_identification("sla", "ugosa", "vgosa", date, 0.002)

over filtered

ax = start_axes(f"ADT (m) filtered ({wavelength}km)")

m = g.display(ax, "adt", vmin=-0.15, vmax=0.15)

a_adt.display(ax, kwargs_a_adt)
c_adt.display(ax, kwargs_c_adt)

ax.legend(), update_axes(ax, m) plt.show()

ax = start_axes(f"SLA (m) filtered ({wavelength}km)") m = g.display(ax, "sla", vmin=-0.15, vmax=0.15) a_sla.display(ax, kwargs_a_sla), c_sla.display(ax, kwargs_c_sla) ax.legend(), update_axes(ax, m)

over raw

ax = start_axes("ADT (m)") m = g.display(ax, "adt_raw", vmin=-0.15, vmax=0.15) a_adt.display(ax, kwargs_a_adt), c_adt.display(ax, kwargs_c_adt) ax.legend(), update_axes(ax, m)

ax = start_axes("SLA (m)") m = g.display(ax, "sla_raw", vmin=-0.15, vmax=0.15) a_sla.display(ax, kwargs_a_sla), c_sla.display(ax, kwargs_c_sla) ax.legend(), update_axes(ax, m)

Display detection

ax = start_axes("Eddies detected") a_adt.display(ax, kwargs_a_adt) a_sla.display(ax, kwargs_a_sla) c_adt.display(ax, kwargs_c_adt) c_sla.display(ax, kwargs_c_sla) ax.legend() update_axes(ax)

Match

-----------------------

Where cyclone meet anticyclone

i_c_adt, i_a_sla, c = c_adt.match(a_sla, cmin=0.01) i_a_adt, i_c_sla, c = a_adt.match(c_sla, cmin=0.01)

ax = start_axes("Cyclone share area with anticyclone") a_adt.index(i_a_adt).display(ax, kwargs_a_adt) c_adt.index(i_c_adt).display(ax, kwargs_c_adt) a_sla.index(i_a_sla).display(ax, kwargs_a_sla) c_sla.index(i_c_sla).display(ax, kwargs_c_sla) ax.legend() update_axes(ax)

Scatter plot

------------

i_a_adt, i_a_sla, c = a_adt.match(a_sla, cmin=0.1) i_c_adt, i_c_sla, c = c_adt.match(c_sla, cmin=0.1)

where is lonely eddies

ax = start_axes("Eddies with no match") a_adt.index(i_a_adt, reverse=True).display(ax, kwargs_a_adt) c_adt.index(i_c_adt, reverse=True).display(ax, kwargs_c_adt) a_sla.index(i_a_sla, reverse=True).display(ax, kwargs_a_sla) c_sla.index(i_c_sla, reverse=True).display(ax, kwargs_c_sla) ax.legend() update_axes(ax)

fig = plt.figure(figsize=(12, 12)) fig.suptitle(f"Scatter plot (A : {i_a_adt.shape[0]}, C : {i_c_adt.shape[0]} matches)")

for i, (label, field, factor, stop) in enumerate( ( ("speed radius (km)", "radius_s", 0.001, 80), ("outter radius (km)", "radius_e", 0.001, 120), ("amplitude (cm)", "amplitude", 100, 25), ("speed max (cm/s)", "speed_average", 100, 25), ) ): ax = fig.add_subplot(2, 2, i + 1, title=label) ax.set_xlabel("Absolute Dynamic Topography") ax.set_ylabel("Sea Level Anomaly")

ax.plot(
    a_adt[field][i_a_adt] * factor,
    a_sla[field][i_a_sla] * factor,
    "r.",
    label="Anticyclonic",
)
ax.plot(
    c_adt[field][i_c_adt] * factor,
    c_sla[field][i_c_sla] * factor,
    "b.",
    label="Cyclonic",
)
ax.set_aspect("equal"), ax.grid()
ax.plot((0, 1000), (0, 1000), "g")
ax.set_xlim(0, stop), ax.set_ylim(0, stop)
ax.legend()

plt.show()

[thomaseocean]

[thomaseocean]

just get the result，the result is different with you，l can not find the wrong

[AntSimi]

it looks like #130

[thomaseocean]

l try https://github.com/AntSimi/py-eddy-tracker/issues/130, i can get right result,thanks.