def test_eraint(self):
f = get_demo_file('era_interim_tibet.nc')
d = GeoNetcdf(f)
assert d.grid.origin == 'upper-left'
stat_lon = 91.1
stat_lat = 31.1
with netCDF4.Dataset(f) as nc:
nc.set_auto_mask(False)
flon = nc.variables['longitude'][:]
flat = nc.variables['latitude'][:]
alon = np.argmin(np.abs(flon - stat_lon))
alat = np.argmin(np.abs(flat - stat_lat))
d.set_subset(corners=((stat_lon, stat_lat), (stat_lon, stat_lat)))
slon, slat = d.grid.ll_coordinates
assert_array_equal(flon[alon], slon)
assert_allclose(flat[alat], slat)
# Exotic subset
assert_array_equal(flon[alon], d.get_vardata('longitude'))
assert_allclose(flat[alat], d.get_vardata('latitude'))
assert_allclose(nc.variables['t2m'][:, alat, alon],
np.squeeze(d.get_vardata('t2m')))
d.set_period(t0='2012-06-01 06:00:00', t1='2012-06-01 12:00:00')
assert_allclose(nc.variables['t2m'][1:3, alat, alon],
np.squeeze(d.get_vardata('t2m')))
def test_har(self):
# HAR
hf = get_demo_file('har_d30km_y_2d_t2_2000.nc')
d = GeoNetcdf(hf)
reflon = np.squeeze(d.get_vardata('lon'))
reflat = np.squeeze(d.get_vardata('lat'))
mylon, mylat = d.grid.ll_coordinates
np.testing.assert_allclose(reflon, mylon, atol=1e-5)
np.testing.assert_allclose(reflat, mylat, atol=1e-5)
def test_har(self):
# HAR
hf = get_demo_file("har_d30km_y_2d_t2_2000.nc")
d = GeoNetcdf(hf)
reflon = np.squeeze(d.get_vardata("lon"))
reflat = np.squeeze(d.get_vardata("lat"))
mylon, mylat = d.grid.ll_coordinates
np.testing.assert_allclose(reflon, mylon, atol=1e-5)
np.testing.assert_allclose(reflat, mylat, atol=1e-5)
def test_eraint(self):
f = get_demo_file("era_interim_tibet.nc")
d = GeoNetcdf(f)
assert d.grid.order == "ul"
stat_lon = 91.1
stat_lat = 31.1
nc = netCDF4.Dataset(f)
flon = nc.variables["longitude"][:]
flat = nc.variables["latitude"][:]
alon = np.argmin(np.abs(flon - stat_lon))
alat = np.argmin(np.abs(flat - stat_lat))
d.set_subset(corners=((stat_lon, stat_lat), (stat_lon, stat_lat)))
slon, slat = d.grid.ll_coordinates
assert_array_equal(flon[alon], slon)
assert_allclose(flat[alat], slat)
# Exotic subset
assert_array_equal(flon[alon], d.get_vardata("longitude"))
assert_allclose(flat[alat], d.get_vardata("latitude"))
assert_allclose(nc.variables["t2m"][:, alat, alon], np.squeeze(d.get_vardata("t2m")))
d.set_period(t0="2012-06-01 06:00:00", t1="2012-06-01 12:00:00")
assert_allclose(nc.variables["t2m"][1:3, alat, alon], np.squeeze(d.get_vardata("t2m")))
def test_diagnostic_vars(self):
d = WRF(get_demo_file('wrf_tip_d1.nc'))
d2 = GeoNetcdf(get_demo_file('wrf_tip_d2.nc'))
self.assertTrue('T2C' in d.variables)
ref = d.get_vardata('T2')
tot = d.get_vardata('T2C') + 273.15
np.testing.assert_allclose(ref, tot)
d.set_roi(grid=d2.grid)
d.set_subset(toroi=True)
ref = d.get_vardata('T2')
tot = d.get_vardata('T2C') + 273.15
self.assertEqual(tot.shape[-1] * 3, d2.grid.nx)
self.assertEqual(tot.shape[-2] * 3, d2.grid.ny)
np.testing.assert_allclose(ref, tot)
d = WRF(get_demo_file('wrf_tip_d1.nc'))
ref = d.variables['T2'][:]
d.set_subset(margin=-5)
tot = d.get_vardata('T2')
assert_array_equal(ref.shape[1] - 10, tot.shape[1])
assert_array_equal(ref.shape[2] - 10, tot.shape[2])
assert_array_equal(ref[:, 5:-5, 5:-5], tot)
def test_visible(self):
import matplotlib as mpl
x = [91.176036, 92.05, 88.880927]
y = [29.649702, 31.483333, 29.264956]
g = GoogleVisibleMap(x=x,
y=y,
size_x=400,
size_y=400,
maptype='terrain')
img = g.get_vardata()[..., :3]
i, j = g.grid.transform(x, y, nearest=True)
for _i, _j in zip(i, j):
img[_j - 3:_j + 4, _i - 3:_i + 4, 0] = 1
img[_j - 3:_j + 4, _i - 3:_i + 4, 1:] = 0
# from PIL import Image
# Image.fromarray((img * 255).astype(np.uint8)).save(
# get_demo_file('hef_google_visible.png'))
ref = mpl.image.imread(get_demo_file('hef_google_visible.png'))
rmsd = np.sqrt(np.mean((ref - img)**2))
self.assertTrue(rmsd < 1e-1)
self.assertRaises(ValueError, GoogleVisibleMap, x=x, y=y, zoom=12)
fw = get_demo_file('wrf_tip_d1.nc')
d = GeoNetcdf(fw)
i, j = d.grid.ij_coordinates
g = GoogleVisibleMap(x=i, y=j, crs=d.grid, size_x=500, size_y=500)
img = g.get_vardata()[..., :3]
mask = g.grid.map_gridded_data(i * 0 + 1, d.grid)
img[np.nonzero(mask)] = np.clip(img[np.nonzero(mask)] + 0.3, 0, 1)
# from PIL import Image
# Image.fromarray((img * 255).astype(np.uint8)).save(
# get_demo_file('hef_google_visible_grid.png'))
ref = mpl.image.imread(get_demo_file('hef_google_visible_grid.png'))
rmsd = np.sqrt(np.mean((ref - img)**2))
self.assertTrue(rmsd < 5e-1)
gm = GoogleVisibleMap(x=i, y=j, crs=d.grid, size_x=500, size_y=500)
gm2 = GoogleVisibleMap(x=i,
y=j,
crs=d.grid,
scale=2,
size_x=500,
size_y=500)
assert (gm.grid.nx * 2) == gm2.grid.nx
assert gm.grid.extent == gm2.grid.extent
# Test regression for non array inputs
grid = mercator_grid(center_ll=(72.5, 30.), extent=(2.0e6, 2.0e6))
GoogleVisibleMap(x=[0, grid.nx - 1], y=[0, grid.ny - 1], crs=grid)
def test_longtime(self):
"""There was a bug with time"""
fs = get_demo_file('test_longtime.nc')
c = GeoNetcdf(fs)
self.assertEqual(len(c.time), 2424)
assert_array_equal(c.time[0:2], pd.to_datetime([datetime(1801, 10, 1),
datetime(1801, 11,
1)]))
def test_as_xarray(self):
f = get_demo_file("era_interim_tibet.nc")
d = GeoNetcdf(f)
t2 = d.get_vardata("t2m", as_xarray=True)
stat_lon = 91.1
stat_lat = 31.1
d.set_subset(corners=((stat_lon, stat_lat), (stat_lon, stat_lat)))
t2_sub = d.get_vardata("t2m", as_xarray=True)
np.testing.assert_allclose(t2_sub - t2, np.zeros(4).reshape((4, 1, 1)))
d.set_period(t0="2012-06-01 06:00:00", t1="2012-06-01 12:00:00")
t2_sub = d.get_vardata("t2m", as_xarray=True)
np.testing.assert_allclose(t2_sub - t2, np.zeros(2).reshape((2, 1, 1)))
wf = get_demo_file("wrf_cropped.nc")
d = WRF(wf)
tk = d.get_vardata("TK", as_xarray=True)
def test_staggeredcoords(self):
wf = get_demo_file('wrf_cropped.nc')
nc = GeoNetcdf(wf)
lon, lat = nc.grid.xstagg_ll_coordinates
assert_allclose(np.squeeze(nc.variables['XLONG_U'][0, ...]), lon,
atol=1e-4)
assert_allclose(np.squeeze(nc.variables['XLAT_U'][0, ...]), lat,
atol=1e-4)
lon, lat = nc.grid.ystagg_ll_coordinates
assert_allclose(np.squeeze(nc.variables['XLONG_V'][0, ...]), lon,
atol=1e-4)
assert_allclose(np.squeeze(nc.variables['XLAT_V'][0, ...]), lat,
atol=1e-4)
def test_wrf_polar(self):
d = GeoNetcdf(get_demo_file('geo_em_d01_polarstereo.nc'))
mylon, mylat = d.grid.ll_coordinates
reflon = np.squeeze(d.get_vardata('XLONG_M'))
reflat = np.squeeze(d.get_vardata('XLAT_M'))
np.testing.assert_allclose(reflon, mylon, atol=5e-3)
np.testing.assert_allclose(reflat, mylat, atol=5e-3)
d = GeoNetcdf(get_demo_file('geo_em_d02_polarstereo.nc'))
mylon, mylat = d.grid.ll_coordinates
reflon = np.squeeze(d.get_vardata('XLONG_M'))
reflat = np.squeeze(d.get_vardata('XLAT_M'))
np.testing.assert_allclose(reflon, mylon, atol=1e-4)
np.testing.assert_allclose(reflat, mylat, atol=1e-4)
def test_visible(self):
x = [91.176036, 92.05, 88.880927]
y = [29.649702, 31.483333, 29.264956]
g = GoogleVisibleMap(x=x,
y=y,
size_x=400,
size_y=400,
maptype='terrain')
img = g.get_vardata()
i, j = g.grid.transform(x, y, nearest=True)
for _i, _j in zip(i, j):
img[_j - 3:_j + 4, _i - 3:_i + 4, 0] = 1
img[_j - 3:_j + 4, _i - 3:_i + 4, 1:] = 0
# from scipy.misc import toimage
# toimage(img).save(get_demo_file('hef_google_visible.png'))
ref = mpl.image.imread(get_demo_file('hef_google_visible.png'))
rmsd = np.sqrt(np.mean((ref - img)**2))
self.assertTrue(rmsd < 1e-1)
self.assertRaises(ValueError, GoogleVisibleMap, x=x, y=y, zoom=12)
fw = get_demo_file('wrf_tip_d1.nc')
d = GeoNetcdf(fw)
i, j = d.grid.ij_coordinates
g = GoogleVisibleMap(x=i, y=j, crs=d.grid, size_x=500, size_y=500)
img = g.get_vardata()
mask = g.grid.map_gridded_data(i * 0 + 1, d.grid)
img[np.nonzero(mask)] = np.clip(img[np.nonzero(mask)] + 0.3, 0, 1)
# from scipy.misc import toimage
# toimage(img).save(get_demo_file('hef_google_visible_grid.png'))
ref = mpl.image.imread(get_demo_file('hef_google_visible_grid.png'))
rmsd = np.sqrt(np.mean((ref - img)**2))
self.assertTrue(rmsd < 5e-1)
def test_wrf(self):
"""Open WRF, do subsets and stuff"""
fs = get_demo_file('chinabang.shp')
for d in ['1', '2']:
fw = get_demo_file('wrf_tip_d{}.nc'.format(d))
d = GeoNetcdf(fw)
self.assertTrue(isinstance(d, GeoDataset))
mylon, mylat = d.grid.ll_coordinates
reflon = d.get_vardata('XLONG')
reflat = d.get_vardata('XLAT')
np.testing.assert_allclose(reflon, mylon, rtol=0.000001)
np.testing.assert_allclose(reflat, mylat, rtol=0.00001)
d.set_roi(shape=fs)
np.testing.assert_array_equal(d.get_vardata('roi'), d.roi)
d1 = GeoNetcdf(get_demo_file('wrf_tip_d1.nc'))
d2 = GeoNetcdf(get_demo_file('wrf_tip_d2.nc'))
# Auto dimensions
self.assertTrue(d1.t_dim == 'Time')
self.assertTrue(d1.x_dim == 'west_east')
self.assertTrue(d1.y_dim == 'south_north')
self.assertTrue(d1.z_dim is None)
#Time
assert_array_equal(
d1.time,
pd.to_datetime([datetime(2005, 9, 21),
datetime(2005, 9, 21, 3)]))
assert_array_equal(
d2.time,
pd.to_datetime([datetime(2005, 9, 21),
datetime(2005, 9, 21, 1)]))
bef = d2.get_vardata('T2')
d2.set_period(t0=datetime(2005, 9, 21, 1))
assert_array_equal(bef[[1], ...], d2.get_vardata('T2'))
d2.set_period()
assert_array_equal(bef, d2.get_vardata('T2'))
d2.set_period(t1=datetime(2005, 9, 21, 0))
assert_array_equal(bef[[0], ...], d2.get_vardata('T2'))
# ROIS
d1.set_roi(grid=d2.grid)
d1.set_subset(toroi=True)
self.assertEqual(d1.grid.nx * 3, d2.grid.nx)
self.assertEqual(d1.grid.ny * 3, d2.grid.ny)
self.assertTrue(np.min(d1.roi) == 1)
mylon, mylat = d1.grid.ll_coordinates
reflon = d1.get_vardata('XLONG')
reflat = d1.get_vardata('XLAT')
np.testing.assert_allclose(reflon, mylon, atol=1e-4)
np.testing.assert_allclose(reflat, mylat, atol=1e-4)
reflon = d2.get_vardata('XLONG')[1::3, 1::3]
reflat = d2.get_vardata('XLAT')[1::3, 1::3]
np.testing.assert_allclose(reflon, mylon, atol=1e-4)
np.testing.assert_allclose(reflat, mylat, atol=1e-4)
# Mercator
d = GeoNetcdf(get_demo_file('wrf_mercator.nc'))
mylon, mylat = d.grid.ll_coordinates
reflon = np.squeeze(d.get_vardata('XLONG'))
reflat = np.squeeze(d.get_vardata('XLAT'))
np.testing.assert_allclose(reflon, mylon, atol=1e-5)
np.testing.assert_allclose(reflat, mylat, atol=1e-5)
# Test xarray
ds = xr.open_dataset(get_demo_file('wrf_mercator.nc'))
mylon, mylat = ds.salem.grid.ll_coordinates
np.testing.assert_allclose(reflon, mylon, atol=1e-5)
np.testing.assert_allclose(reflat, mylat, atol=1e-5)
d = GeoNetcdf(get_demo_file('wrf_tip_d1.nc'))
reflon = np.squeeze(d.get_vardata('XLONG'))
reflat = np.squeeze(d.get_vardata('XLAT'))
ds = xr.open_dataset(get_demo_file('wrf_tip_d1.nc'))
mylon, mylat = ds.salem.grid.ll_coordinates
np.testing.assert_allclose(reflon, mylon, atol=1e-4)
np.testing.assert_allclose(reflat, mylat, atol=1e-4)
def test_as_xarray(self):
f = get_demo_file('era_interim_tibet.nc')
d = GeoNetcdf(f)
t2 = d.get_vardata('t2m', as_xarray=True)
stat_lon = 91.1
stat_lat = 31.1
d.set_subset(corners=((stat_lon, stat_lat), (stat_lon, stat_lat)))
t2_sub = d.get_vardata('t2m', as_xarray=True)
np.testing.assert_allclose(t2_sub - t2, np.zeros(4).reshape((4, 1, 1)))
d.set_period(t0='2012-06-01 06:00:00', t1='2012-06-01 12:00:00')
t2_sub = d.get_vardata('t2m', as_xarray=True)
np.testing.assert_allclose(t2_sub - t2, np.zeros(2).reshape((2, 1, 1)))
wf = get_demo_file('wrf_cropped.nc')
d = WRF(wf)
tk = d.get_vardata('TK', as_xarray=True)
def test_wrf(self):
"""Open WRF, do subsets and stuff"""
fs = get_demo_file("chinabang.shp")
for d in ["1", "2"]:
fw = get_demo_file("wrf_tip_d{}.nc".format(d))
d = GeoNetcdf(fw)
self.assertTrue(isinstance(d, GeoDataset))
mylon, mylat = d.grid.ll_coordinates
reflon = d.get_vardata("XLONG")
reflat = d.get_vardata("XLAT")
np.testing.assert_allclose(reflon, mylon, rtol=0.000001)
np.testing.assert_allclose(reflat, mylat, rtol=0.00001)
d.set_roi(shape=fs)
np.testing.assert_array_equal(d.get_vardata("roi"), d.roi)
d1 = GeoNetcdf(get_demo_file("wrf_tip_d1.nc"))
d2 = GeoNetcdf(get_demo_file("wrf_tip_d2.nc"))
# Auto dimensions
self.assertTrue(d1.t_dim == "Time")
self.assertTrue(d1.x_dim == "west_east")
self.assertTrue(d1.y_dim == "south_north")
self.assertTrue(d1.z_dim is None)
# Time
assert_array_equal(d1.time, pd.to_datetime([datetime(2005, 9, 21), datetime(2005, 9, 21, 3)]))
assert_array_equal(d2.time, pd.to_datetime([datetime(2005, 9, 21), datetime(2005, 9, 21, 1)]))
bef = d2.get_vardata("T2")
d2.set_period(t0=datetime(2005, 9, 21, 1))
assert_array_equal(bef[[1], ...], d2.get_vardata("T2"))
d2.set_period()
assert_array_equal(bef, d2.get_vardata("T2"))
d2.set_period(t1=datetime(2005, 9, 21, 0))
assert_array_equal(bef[[0], ...], d2.get_vardata("T2"))
# ROIS
d1.set_roi(grid=d2.grid)
d1.set_subset(toroi=True)
self.assertEqual(d1.grid.nx * 3, d2.grid.nx)
self.assertEqual(d1.grid.ny * 3, d2.grid.ny)
self.assertTrue(np.min(d1.roi) == 1)
mylon, mylat = d1.grid.ll_coordinates
reflon = d1.get_vardata("XLONG")
reflat = d1.get_vardata("XLAT")
np.testing.assert_allclose(reflon, mylon, atol=1e-4)
np.testing.assert_allclose(reflat, mylat, atol=1e-4)
reflon = d2.get_vardata("XLONG")[1::3, 1::3]
reflat = d2.get_vardata("XLAT")[1::3, 1::3]
np.testing.assert_allclose(reflon, mylon, atol=1e-4)
np.testing.assert_allclose(reflat, mylat, atol=1e-4)
# Mercator
d = GeoNetcdf(get_demo_file("wrf_mercator.nc"))
mylon, mylat = d.grid.ll_coordinates
reflon = np.squeeze(d.get_vardata("XLONG"))
reflat = np.squeeze(d.get_vardata("XLAT"))
np.testing.assert_allclose(reflon, mylon, atol=1e-5)
np.testing.assert_allclose(reflat, mylat, atol=1e-5)
# Test xarray
ds = xr.open_dataset(get_demo_file("wrf_mercator.nc"))
mylon, mylat = ds.salem.grid.ll_coordinates
np.testing.assert_allclose(reflon, mylon, atol=1e-5)
np.testing.assert_allclose(reflat, mylat, atol=1e-5)
d = GeoNetcdf(get_demo_file("wrf_tip_d1.nc"))
reflon = np.squeeze(d.get_vardata("XLONG"))
reflat = np.squeeze(d.get_vardata("XLAT"))
ds = xr.open_dataset(get_demo_file("wrf_tip_d1.nc"))
mylon, mylat = ds.salem.grid.ll_coordinates
np.testing.assert_allclose(reflon, mylon, atol=1e-4)
np.testing.assert_allclose(reflat, mylat, atol=1e-4)
