def test_get_variables(benchmark):
r = reader_netCDF_CF_unstructured.Reader(akvaplan, proj4=proj)
x = np.array([5.6e5, 5.6e5])
y = np.array([7.76e6, 7.76e6])
z = np.array([0, 30])
u = benchmark(r.get_variables, ['x_sea_water_velocity'], r.start_time, x,
y, z)['x_sea_water_velocity']
print(u)
print(u.shape)
assert u.shape == (len(x),)
assert len(u) == len(x)
# test get_variables against manually retrieved value
tidx = [3,4]
idx = [150, 170, 171, 2000]
zidx = [0, 3, 4, 7]
times = r.times[tidx]
xc = r.xc[idx]
yc = r.yc[idx]
z = (r.dataset['siglay_center'][zidx, idx] * r.dataset['h_center'][idx]).diagonal()
assert z.shape == xc.shape
# u is a face / siglay variable
uu = r.dataset['u'][tidx[0], zidx, idx].diagonal()
u = r.get_variables(['x_sea_water_velocity'], times[0], xc, yc, z)['x_sea_water_velocity']
np.testing.assert_array_equal(uu, u)
uu = r.dataset['u'][tidx[1], zidx, idx].diagonal()
u = r.get_variables(['x_sea_water_velocity'], times[1], xc, yc, z)['x_sea_water_velocity']
np.testing.assert_array_equal(uu, u)
def test_get_variables_many(benchmark):
r = reader_netCDF_CF_unstructured.Reader(akvaplan, proj4=proj)
x = np.linspace(5.6e5, 6.0e5, 1000)
y = np.linspace(7.76e6, 7.8e6, 1000)
z = np.array([0, 30]).repeat(500)
u = benchmark(r.get_variables, ['x_sea_water_velocity'], r.start_time, x, y, z)['x_sea_water_velocity']
assert len(u) == len(x)
def test_nearest_node(benchmark):
r = reader_netCDF_CF_unstructured.Reader(akvaplan, proj4=proj)
x = np.linspace(5.6e5, 6.0e5, 100)
y = np.linspace(7.4e6, 7.6e6, 100)
x, y = np.meshgrid(x, y)
x = x.ravel()
y = y.ravel()
print("getting nearest for %d points" % len(x))
benchmark(r._nearest_node_, x, y)
def tets_not_contains(benchmark):
r = reader_netCDF_CF_unstructured.Reader(akvaplan, proj4=proj)
x = np.linspace(5.6e5, 6.0e5, 100)
y = np.linspace(7.4e6, 7.6e6, 100)
x, y = np.meshgrid(x, y)
x = x.ravel()
y = y.ravel()
# r.plot_mesh()
# plt.scatter(x, y, marker = 'x', color = 'b')
# plt.show()
covers = benchmark(r.covers_positions, x, y)
assert not np.all(covers)
def test_profile():
o = OceanDrift()
r = reader_netCDF_CF_unstructured.Reader(akvaplan, proj4=proj)
o.add_reader(r)
o.seed_elements(lon=17, lat=70, z=np.atleast_1d([0, -10, -50]),
number=3, time=r.start_time)
print(o)
o.run(steps=3)
#o.plot(linecolor='z')
# Elements at 0 and 10m depth should not have same trajectory
# This is ok
assert o.elements.lon[0] != o.elements.lon[1]
# Elements at 10 and 50m depth should not have same trajectory
# This is presently failing
assert o.elements.lon[1] != o.elements.lon[2]
FVCOM: Using model input from unstructured grid
===============================================
"""
from datetime import timedelta
import urllib.request as urllib_request
import numpy as np
from opendrift.readers import reader_netCDF_CF_unstructured
from opendrift.readers import reader_global_landmask
from opendrift.models.oceandrift import OceanDrift
o = OceanDrift(loglevel=20) # Set loglevel to 0 for debug information
proj = "+proj=utm +zone=33W, +north +ellps=WGS84 +datum=WGS84 +units=m +no_defs"
fvcom = reader_netCDF_CF_unstructured.Reader(
filename=
'https://thredds.met.no/thredds/dodsC/metusers/knutfd/thredds/netcdf_unstructured_samples/AkvaplanNiva_sample_lonlat_fixed.nc',
proj4=proj)
o.add_reader(fvcom)
print(fvcom)
# Seed elements at defined positions, depth and time
N = 1000
z = -10 * np.random.uniform(0, 1, N)
o.seed_elements(lon=18.0,
lat=69.8,
radius=2000,
number=N,
z=z,
time=fvcom.start_time)
#%%
def test_open():
r = reader_netCDF_CF_unstructured.Reader(akvaplan, proj4=proj)
print(r)
