def from_netCDF(cls,
filename=None,
dataset=None,
grid_topology=None,
units=None,
time=None,
ice_concentration=None,
grid=None,
grid_file=None,
data_file=None,
**kwargs):
if filename is not None:
data_file = filename
grid_file = filename
if grid is None:
grid = PyGrid.from_netCDF(grid_file, grid_topology=grid_topology)
if ice_concentration is None:
ice_concentration = (IceConcentration.from_netCDF(
filename=filename,
dataset=dataset,
data_file=data_file,
grid_file=grid_file,
time=time,
grid=grid,
**kwargs))
return cls(ice_concentration=ice_concentration, **kwargs)
def test_construction(self, sg_data, sg_topology):
filename = sg_data[0]
dataset = sg_data[1]
grid_topology = sg_topology
sg = Grid_S.from_netCDF(filename, dataset,
grid_topology=grid_topology)
assert sg.filename == filename
sg2 = Grid_S.from_netCDF(filename)
assert sg2.filename == filename
sg3 = PyGrid.from_netCDF(filename, dataset,
grid_topology=grid_topology)
print sg3.shape
assert sg == sg3
sg4 = PyGrid.from_netCDF(filename)
print sg4.shape
assert sg2 == sg4
def test_construction(self, sg_data, sg_topology):
filename = sg_data[0]
dataset = sg_data[1]
grid_topology = sg_topology
sg = Grid_S.from_netCDF(filename, dataset, grid_topology=grid_topology)
assert sg.filename == filename
sg2 = Grid_S.from_netCDF(filename)
assert sg2.filename == filename
sg3 = PyGrid.from_netCDF(filename,
dataset,
grid_topology=grid_topology)
print sg3.shape
assert sg == sg3
sg4 = PyGrid.from_netCDF(filename)
print sg4.shape
assert sg2 == sg4
def test_construction(self, ug_data, ug_topology):
filename = ug_data[0]
dataset = ug_data[1]
grid_topology = ug_topology
ug = Grid_U.from_netCDF(filename, dataset, grid_topology=grid_topology)
# assert ug.filename == filename
# assert isinstance(ug.node_lon, nc.Variable)
# assert ug.node_lon.name == 'lonc'
ug2 = Grid_U.from_netCDF(filename)
assert ug2.filename == filename
# assert isinstance(ug2.node_lon, nc.Variable)
# assert ug2.node_lon.name == 'lon'
ug3 = PyGrid.from_netCDF(filename, dataset,
grid_topology=grid_topology)
ug4 = PyGrid.from_netCDF(filename)
print ug3.shape
print ug4.shape
assert ug == ug3
assert ug2 == ug4
def test_construction(self, ug_data, ug_topology):
filename = ug_data[0]
dataset = ug_data[1]
grid_topology = ug_topology
ug = Grid_U.from_netCDF(filename, dataset, grid_topology=grid_topology)
# assert ug.filename == filename
# assert isinstance(ug.node_lon, nc.Variable)
# assert ug.node_lon.name == 'lonc'
ug2 = Grid_U.from_netCDF(filename)
assert ug2.filename == filename
# assert isinstance(ug2.node_lon, nc.Variable)
# assert ug2.node_lon.name == 'lon'
ug3 = PyGrid.from_netCDF(filename,
dataset,
grid_topology=grid_topology)
ug4 = PyGrid.from_netCDF(filename)
print ug3.shape
print ug4.shape
assert ug == ug3
assert ug2 == ug4
def test_construction(self):
data = sinusoid['u'][:]
grid = PyGrid.from_netCDF(dataset=sinusoid)
time = None
u = Variable(name='u',
units='m/s',
data=data,
grid=grid,
time=time,
data_file='staggered_sine_channel.nc',
grid_file='staggered_sine_channel.nc')
curr_file = os.path.join(s_data, 'staggered_sine_channel.nc')
k = Variable.from_netCDF(filename=curr_file, varname='u', name='u')
assert k.name == u.name
assert k.units == 'm/s'
# fixme: this was failing
# assert k.time == u.time
assert k.data[0, 0] == u.data[0, 0]
def test_construction(self):
data = sinusoid['u'][:]
grid = PyGrid.from_netCDF(dataset=sinusoid)
time = None
u = Variable(name='u',
units='m/s',
data=data,
grid=grid,
time=time,
data_file='staggered_sine_channel.nc',
grid_file='staggered_sine_channel.nc')
curr_file = os.path.join(s_data, 'staggered_sine_channel.nc')
k = Variable.from_netCDF(filename=curr_file, varname='u', name='u')
assert k.name == u.name
assert k.units == 'm/s'
# fixme: this was failing
# assert k.time == u.time
assert k.data[0, 0] == u.data[0, 0]
def gen_vortex_3D(filename=None):
x, y = np.mgrid[-30:30:61j, -30:30:61j]
y = np.ascontiguousarray(y.T)
x = np.ascontiguousarray(x.T)
x_size = 61
y_size = 61
g = Grid_S(node_lon=x, node_lat=y)
g.build_celltree()
lin_nodes = g._cell_trees['node'][1]
lin_faces = np.array([
np.array([([lx, lx + x_size + 1, lx + 1
], [lx, lx + x_size, lx + x_size + 1])
for lx in range(0, x_size - 1, 1)]) + ly * x_size
for ly in range(0, y_size - 1)
])
lin_faces = lin_faces.reshape(-1, 3)
# y += np.sin(x) / 1
# x += np.sin(x) / 5
t0 = datetime(2001, 1, 1, 0, 0)
tarr = [t0 + timedelta(hours=i) for i in range(0, 11)]
angs = -np.arctan2(y, x)
mag = np.sqrt(x**2 + y**2)
vx = np.cos(angs) * mag
vy = np.sin(angs) * mag
vx = vx[np.newaxis, :] * 20
vy = vy[np.newaxis, :] * 20
vw = -0.001
d_scale = [1, 0.5, 0, -0.5, -1]
t_scale = np.linspace(0, 1, 11)
tvx = np.array([vx * t for t in t_scale]).squeeze()
tvy = np.array([vy * t for t in t_scale]).squeeze()
dvx = np.array([vx * s for s in d_scale]).squeeze()
dvy = np.array([vy * s for s in d_scale]).squeeze()
tdvx = np.array([dvx * t for t in t_scale]).squeeze()
tdvy = np.array([dvy * t for t in t_scale]).squeeze()
lin_vx = vx.reshape(-1)
lin_vy = vy.reshape(-1)
lin_tvx = np.array([lin_vx * t for t in t_scale])
lin_tvy = np.array([lin_vy * t for t in t_scale])
lin_dvx = np.array([lin_vx * s for s in d_scale])
lin_dvy = np.array([lin_vy * s for s in d_scale])
lin_tdvx = np.array([lin_dvx * t for t in t_scale])
lin_tdvy = np.array([lin_dvy * t for t in t_scale])
ds = None
if filename is not None:
ds = nc4.Dataset(filename, 'w', diskless=True, persist=True)
ds.createDimension('y', y.shape[0])
ds.createDimension('x', x.shape[1])
ds.createDimension('time', len(tarr))
ds.createDimension('depth', len(d_scale))
ds.createVariable('x', 'f8', dimensions=('x', 'y'))
ds['x'][:] = x
ds.createVariable('y', 'f8', dimensions=('x', 'y'))
ds['y'][:] = y
ds.createVariable('time', 'f8', dimensions=('time'))
ds['time'][:] = nc4.date2num(tarr, 'hours since {0}'.format(t0))
ds['time'].setncattr('units', 'hours since {0}'.format(t0))
ds.createVariable('vx', 'f8', dimensions=('x', 'y'))
ds.createVariable('vy', 'f8', dimensions=('x', 'y'))
ds['vx'][:] = vx
ds['vy'][:] = vy
ds.createVariable('tvx', 'f8', dimensions=('time', 'x', 'y'))
ds.createVariable('tvy', 'f8', dimensions=('time', 'x', 'y'))
ds['tvx'][:] = tvx
ds['tvy'][:] = tvy
ds.createVariable('dvx', 'f8', dimensions=('depth', 'x', 'y'))
ds.createVariable('dvy', 'f8', dimensions=('depth', 'x', 'y'))
ds['dvx'][:] = dvx
ds['dvy'][:] = dvy
ds.createVariable('tdvx', 'f8', dimensions=('time', 'depth', 'x', 'y'))
ds.createVariable('tdvy', 'f8', dimensions=('time', 'depth', 'x', 'y'))
ds['tdvx'][:] = tdvx
ds['tdvy'][:] = tdvy
for v in ds.variables:
if 'v' in v:
ds[v].units = 'm/s'
ds.createDimension('nv', lin_nodes.shape[0])
ds.createDimension('nele', lin_faces.shape[0])
ds.createDimension('two', 2)
ds.createDimension('three', 3)
ds.createVariable('nodes', 'f8', dimensions=('nv', 'two'))
ds.createVariable('faces', 'f8', dimensions=('nele', 'three'))
ds.createVariable('lin_vx', 'f8', dimensions=('nv'))
ds.createVariable('lin_vy', 'f8', dimensions=('nv'))
ds.createVariable('lin_tvx', 'f8', dimensions=('time', 'nv'))
ds.createVariable('lin_tvy', 'f8', dimensions=('time', 'nv'))
ds.createVariable('lin_dvx', 'f8', dimensions=('depth', 'nv'))
ds.createVariable('lin_dvy', 'f8', dimensions=('depth', 'nv'))
ds.createVariable('lin_tdvx', 'f8', dimensions=('time', 'depth', 'nv'))
ds.createVariable('lin_tdvy', 'f8', dimensions=('time', 'depth', 'nv'))
for k, v in {
'nodes': lin_nodes,
'faces': lin_faces,
'lin_vx': lin_vx,
'lin_vy': lin_vy,
'lin_tvx': lin_tvx,
'lin_tvy': lin_tvy,
'lin_dvx': lin_dvx,
'lin_dvy': lin_dvy,
'lin_tdvx': lin_tdvx,
'lin_tdvy': lin_tdvy
}.items():
ds[k][:] = v
if 'lin' in k:
ds[k].units = 'm/s'
PyGrid._get_grid_type(ds,
grid_topology={
'node_lon': 'x',
'node_lat': 'y'
})
PyGrid._get_grid_type(ds)
ds.setncattr('grid_type', 'sgrid')
if ds is not None:
# Need to test the dataset...
sgt = {'node_lon': 'x', 'node_lat': 'y'}
_sg = PyGrid.from_netCDF(dataset=ds,
grid_topology=sgt,
grid_type='sgrid')
_sgc1 = GridCurrent.from_netCDF(dataset=ds,
varnames=['vx', 'vy'],
grid_topology=sgt)
_sgc2 = GridCurrent.from_netCDF(dataset=ds,
varnames=['tvx', 'tvy'],
grid_topology=sgt)
_sgc3 = GridCurrent.from_netCDF(dataset=ds,
varnames=['dvx', 'dvy'],
grid_topology=sgt)
_sgc4 = GridCurrent.from_netCDF(dataset=ds,
varnames=['tdvx', 'tdvy'],
grid_topology=sgt)
ugt = {'nodes': 'nodes', 'faces': 'faces'}
# ug = PyGrid_U(nodes=ds['nodes'][:], faces=ds['faces'][:])
_ugc1 = GridCurrent.from_netCDF(dataset=ds,
varnames=['lin_vx', 'lin_vy'],
grid_topology=ugt)
_ugc2 = GridCurrent.from_netCDF(dataset=ds,
varnames=['lin_tvx', 'lin_tvy'],
grid_topology=ugt)
_ugc3 = GridCurrent.from_netCDF(dataset=ds,
varnames=['lin_dvx', 'lin_dvy'],
grid_topology=ugt)
_ugc4 = GridCurrent.from_netCDF(dataset=ds,
varnames=['lin_tdvx', 'lin_tdvy'],
grid_topology=ugt)
ds.close()
return {
'sgrid': (x, y),
'sgrid_vel': (dvx, dvy),
'sgrid_depth_vel': (tdvx, tdvy),
'ugrid': (lin_nodes, lin_faces),
'ugrid_depth_vel': (lin_tdvx, lin_tdvy)
}
def ug(ug_data, ug_topology):
return PyGrid.from_netCDF(ug_data[0], ug_data[1],
grid_topology=ug_topology)
def sg(sg_data, sg_topology):
return PyGrid.from_netCDF(sg_data[0], sg_data[1],
grid_topology=sg_topology)
def ug(ug_data, ug_topology):
return PyGrid.from_netCDF(ug_data[0],
ug_data[1],
grid_topology=ug_topology)
def sg(sg_data, sg_topology):
return PyGrid.from_netCDF(sg_data[0],
sg_data[1],
grid_topology=sg_topology)
def gen_vortex_3D(filename=None):
x, y = np.mgrid[-30:30:61j, -30:30:61j]
y = np.ascontiguousarray(y.T)
x = np.ascontiguousarray(x.T)
x_size = 61
y_size = 61
g = Grid_S(node_lon=x,
node_lat=y)
g.build_celltree()
lin_nodes = g._cell_trees['node'][1]
lin_faces = np.array([np.array([([lx, lx + x_size + 1, lx + 1],
[lx, lx + x_size, lx + x_size + 1])
for lx in range(0, x_size - 1, 1)]) + ly * x_size
for ly in range(0, y_size - 1)])
lin_faces = lin_faces.reshape(-1, 3)
# y += np.sin(x) / 1
# x += np.sin(x) / 5
t0 = datetime(2001, 1, 1, 0, 0)
tarr = [t0 + timedelta(hours=i) for i in range(0, 11)]
angs = -np.arctan2(y, x)
mag = np.sqrt(x ** 2 + y ** 2)
vx = np.cos(angs) * mag
vy = np.sin(angs) * mag
vx = vx[np.newaxis, :] * 20
vy = vy[np.newaxis, :] * 20
vw = -0.001
d_scale = [1, 0.5, 0, -0.5, -1]
t_scale = np.linspace(0, 1, 11)
tvx = np.array([vx * t for t in t_scale]).squeeze()
tvy = np.array([vy * t for t in t_scale]).squeeze()
dvx = np.array([vx * s for s in d_scale]).squeeze()
dvy = np.array([vy * s for s in d_scale]).squeeze()
tdvx = np.array([dvx * t for t in t_scale]).squeeze()
tdvy = np.array([dvy * t for t in t_scale]).squeeze()
lin_vx = vx.reshape(-1)
lin_vy = vy.reshape(-1)
lin_tvx = np.array([lin_vx * t for t in t_scale])
lin_tvy = np.array([lin_vy * t for t in t_scale])
lin_dvx = np.array([lin_vx * s for s in d_scale])
lin_dvy = np.array([lin_vy * s for s in d_scale])
lin_tdvx = np.array([lin_dvx * t for t in t_scale])
lin_tdvy = np.array([lin_dvy * t for t in t_scale])
ds = None
if filename is not None:
ds = nc4.Dataset(filename, 'w', diskless=True, persist=True)
ds.createDimension('y', y.shape[0])
ds.createDimension('x', x.shape[1])
ds.createDimension('time', len(tarr))
ds.createDimension('depth', len(d_scale))
ds.createVariable('x', 'f8', dimensions=('x', 'y'))
ds['x'][:] = x
ds.createVariable('y', 'f8', dimensions=('x', 'y'))
ds['y'][:] = y
ds.createVariable('time', 'f8', dimensions=('time'))
ds['time'][:] = nc4.date2num(tarr, 'hours since {0}'.format(t0))
ds['time'].setncattr('units', 'hours since {0}'.format(t0))
ds.createVariable('vx', 'f8', dimensions=('x', 'y'))
ds.createVariable('vy', 'f8', dimensions=('x', 'y'))
ds['vx'][:] = vx
ds['vy'][:] = vy
ds.createVariable('tvx', 'f8', dimensions=('time', 'x', 'y'))
ds.createVariable('tvy', 'f8', dimensions=('time', 'x', 'y'))
ds['tvx'][:] = tvx
ds['tvy'][:] = tvy
ds.createVariable('dvx', 'f8', dimensions=('depth', 'x', 'y'))
ds.createVariable('dvy', 'f8', dimensions=('depth', 'x', 'y'))
ds['dvx'][:] = dvx
ds['dvy'][:] = dvy
ds.createVariable('tdvx', 'f8', dimensions=('time', 'depth', 'x', 'y'))
ds.createVariable('tdvy', 'f8', dimensions=('time', 'depth', 'x', 'y'))
ds['tdvx'][:] = tdvx
ds['tdvy'][:] = tdvy
for v in ds.variables:
if 'v' in v:
ds[v].units = 'm/s'
ds.createDimension('nv', lin_nodes.shape[0])
ds.createDimension('nele', lin_faces.shape[0])
ds.createDimension('two', 2)
ds.createDimension('three', 3)
ds.createVariable('nodes', 'f8', dimensions=('nv', 'two'))
ds.createVariable('faces', 'f8', dimensions=('nele', 'three'))
ds.createVariable('lin_vx', 'f8', dimensions=('nv'))
ds.createVariable('lin_vy', 'f8', dimensions=('nv'))
ds.createVariable('lin_tvx', 'f8', dimensions=('time', 'nv'))
ds.createVariable('lin_tvy', 'f8', dimensions=('time', 'nv'))
ds.createVariable('lin_dvx', 'f8', dimensions=('depth', 'nv'))
ds.createVariable('lin_dvy', 'f8', dimensions=('depth', 'nv'))
ds.createVariable('lin_tdvx', 'f8', dimensions=('time', 'depth', 'nv'))
ds.createVariable('lin_tdvy', 'f8', dimensions=('time', 'depth', 'nv'))
for k, v in {'nodes': lin_nodes,
'faces': lin_faces,
'lin_vx': lin_vx,
'lin_vy': lin_vy,
'lin_tvx': lin_tvx,
'lin_tvy': lin_tvy,
'lin_dvx': lin_dvx,
'lin_dvy': lin_dvy,
'lin_tdvx': lin_tdvx,
'lin_tdvy': lin_tdvy
}.items():
ds[k][:] = v
if 'lin' in k:
ds[k].units = 'm/s'
PyGrid._get_grid_type(ds,
grid_topology={'node_lon': 'x', 'node_lat': 'y'})
PyGrid._get_grid_type(ds)
ds.setncattr('grid_type', 'sgrid')
if ds is not None:
# Need to test the dataset...
sgt = {'node_lon': 'x', 'node_lat': 'y'}
_sg = PyGrid.from_netCDF(dataset=ds, grid_topology=sgt,
grid_type='sgrid')
_sgc1 = GridCurrent.from_netCDF(dataset=ds, varnames=['vx', 'vy'],
grid_topology=sgt)
_sgc2 = GridCurrent.from_netCDF(dataset=ds, varnames=['tvx', 'tvy'],
grid_topology=sgt)
_sgc3 = GridCurrent.from_netCDF(dataset=ds, varnames=['dvx', 'dvy'],
grid_topology=sgt)
_sgc4 = GridCurrent.from_netCDF(dataset=ds, varnames=['tdvx', 'tdvy'],
grid_topology=sgt)
ugt = {'nodes': 'nodes', 'faces': 'faces'}
# ug = PyGrid_U(nodes=ds['nodes'][:], faces=ds['faces'][:])
_ugc1 = GridCurrent.from_netCDF(dataset=ds,
varnames=['lin_vx', 'lin_vy'],
grid_topology=ugt)
_ugc2 = GridCurrent.from_netCDF(dataset=ds,
varnames=['lin_tvx', 'lin_tvy'],
grid_topology=ugt)
_ugc3 = GridCurrent.from_netCDF(dataset=ds,
varnames=['lin_dvx', 'lin_dvy'],
grid_topology=ugt)
_ugc4 = GridCurrent.from_netCDF(dataset=ds,
varnames=['lin_tdvx', 'lin_tdvy'],
grid_topology=ugt)
ds.close()
return {'sgrid': (x, y),
'sgrid_vel': (dvx, dvy),
'sgrid_depth_vel': (tdvx, tdvy),
'ugrid': (lin_nodes, lin_faces),
'ugrid_depth_vel': (lin_tdvx, lin_tdvy)}