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 = PyGrid_S.from_netCDF(filename,
dataset,
grid_topology=grid_topology)
assert sg.filename == filename
sg2 = PyGrid_S.from_netCDF(filename)
assert sg2.filename == filename
sg3 = PyGrid.from_netCDF(filename,
dataset,
grid_topology=grid_topology)
sg4 = PyGrid.from_netCDF(filename)
print sg3.shape
print sg4.shape
assert sg == sg3
assert sg2 == sg4
def test_construction(self, ug_data, ug_topology):
filename = ug_data[0]
dataset = ug_data[1]
grid_topology = ug_topology
ug = PyGrid_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 = PyGrid_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 = GriddedProp(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 = GriddedProp.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 wrapper(*args, **kws):
def _mod(n):
k = kws
s = shared
return (n in s) and ((n not in k) or
(n in k and k[n] is None))
if 'filename' in kws and kws['filename'] is not None:
kws['data_file'] = kws['grid_file'] = kws['filename']
if _mod('dataset'):
if 'grid_file' in kws and 'data_file' in kws:
if kws['grid_file'] == kws['data_file']:
ds = dg = _get_dataset(kws['grid_file'])
else:
ds = _get_dataset(kws['data_file'])
dg = _get_dataset(kws['grid_file'])
kws['dataset'] = ds
else:
if 'grid_file' in kws and kws['grid_file'] is not None:
dg = _get_dataset(kws['grid_file'])
else:
dg = kws['dataset']
ds = kws['dataset']
if _mod('grid'):
gt = kws.get('grid_topology', None)
kws['grid'] = PyGrid.from_netCDF(kws['grid_file'],
dataset=dg,
grid_topology=gt)
# if kws.get('varnames', None) is None:
# varnames = cls._gen_varnames(kws['data_file'],
# dataset=ds)
# if _mod('time'):
# time = Time.from_netCDF(filename=kws['data_file'],
# dataset=ds,
# varname=data)
# kws['time'] = time
return func(*args, **kws)
def ug():
return PyGrid.from_netCDF(ug_data()[0],
ug_data()[1],
grid_topology=ug_topology())
def sg():
return PyGrid.from_netCDF(sg_data()[0],
sg_data()[1],
grid_topology=sg_topology())
def from_netCDF(cls,
filename=None,
varnames=None,
grid_topology=None,
name=None,
units=None,
time=None,
grid=None,
depth=None,
data_file=None,
grid_file=None,
dataset=None,
load_all=False,
**kwargs):
'''
Allows one-function creation of a GridVectorProp from a file.
:param filename: Default data source. Parameters below take precedence
:param varnames: Names of the variables in the data source file
:param grid_topology: Description of the relationship between grid attributes and variable names.
:param name: Name of property
:param units: Units
:param time: Time axis of the data
:param data: Underlying data source
:param grid: Grid that the data corresponds with
:param dataset: Instance of open Dataset
:param data_file: Name of data source file
:param grid_file: Name of grid source file
:type filename: string
:type varnames: [] of string
:type grid_topology: {string : string, ...}
:type name: string
:type units: string
:type time: [] of datetime.datetime, netCDF4 Variable, or Time object
:type data: netCDF4.Variable or numpy.array
:type grid: pysgrid or pyugrid
:type dataset: netCDF4.Dataset
:type data_file: string
:type grid_file: string
'''
if filename is not None:
data_file = filename
grid_file = filename
ds = None
dg = None
if dataset is None:
if grid_file == data_file:
ds = dg = _get_dataset(grid_file)
else:
ds = _get_dataset(data_file)
dg = _get_dataset(grid_file)
else:
if grid_file is not None:
dg = _get_dataset(grid_file)
else:
dg = dataset
ds = dataset
if grid is None:
grid = PyGrid.from_netCDF(grid_file,
dataset=dg,
grid_topology=grid_topology)
if varnames is None:
varnames = cls._gen_varnames(data_file, dataset=ds)
if name is None:
name = cls.__name__ + str(cls._def_count)
cls._def_count += 1
data = ds[varnames[0]]
if time is None:
time = Time.from_netCDF(filename=data_file,
dataset=ds,
datavar=data)
if depth is None:
if (isinstance(grid, PyGrid_S) and len(data.shape) == 4
or (len(data.shape) == 3 and time is None)
or (isinstance(grid, PyGrid_U) and len(data.shape) == 3 or
(len(data.shape) == 2 and time is None))):
from gnome.environment.environment_objects import Depth
depth = Depth(surface_index=-1)
# if len(data.shape) == 4 or (len(data.shape) == 3 and time is None):
# from gnome.environment.environment_objects import S_Depth
# depth = S_Depth.from_netCDF(grid=grid,
# depth=1,
# data_file=data_file,
# grid_file=grid_file,
# **kwargs)
variables = OrderedCollection(dtype=EnvProp)
for vn in varnames:
if vn is not None:
variables.append(
GriddedProp.from_netCDF(filename=filename,
varname=vn,
grid_topology=grid_topology,
units=units,
time=time,
grid=grid,
depth=depth,
data_file=data_file,
grid_file=grid_file,
dataset=ds,
load_all=load_all,
**kwargs))
if units is None:
units = [v.units for v in variables]
if all(u == units[0] for u in units):
units = units[0]
return cls(name=name,
filename=filename,
varnames=varnames,
grid_topology=grid_topology,
units=units,
time=time,
grid=grid,
depth=depth,
variables=variables,
data_file=data_file,
grid_file=grid_file,
dataset=ds,
load_all=load_all,
**kwargs)
def from_netCDF(cls,
filename=None,
varname=None,
grid_topology=None,
name=None,
units=None,
time=None,
grid=None,
depth=None,
dataset=None,
data_file=None,
grid_file=None,
load_all=False,
fill_value=0,
**kwargs):
'''
Allows one-function creation of a GriddedProp from a file.
:param filename: Default data source. Parameters below take precedence
:param varname: Name of the variable in the data source file
:param grid_topology: Description of the relationship between grid attributes and variable names.
:param name: Name of property
:param units: Units
:param time: Time axis of the data
:param data: Underlying data source
:param grid: Grid that the data corresponds with
:param depth: Depth axis object
:param dataset: Instance of open Dataset
:param data_file: Name of data source file
:param grid_file: Name of grid source file
:type filename: string
:type varname: string
:type grid_topology: {string : string, ...}
:type name: string
:type units: string
:type time: [] of datetime.datetime, netCDF4 Variable, or Time object
:type data: netCDF4.Variable or numpy.array
:type grid: pysgrid or pyugrid
:type depth: Depth, S_Depth or L_Depth
:type dataset: netCDF4.Dataset
:type data_file: string
:type grid_file: string
'''
if filename is not None:
data_file = filename
grid_file = filename
ds = None
dg = None
if dataset is None:
if grid_file == data_file:
ds = dg = _get_dataset(grid_file)
else:
ds = _get_dataset(data_file)
dg = _get_dataset(grid_file)
else:
if grid_file is not None:
dg = _get_dataset(grid_file)
else:
dg = dataset
ds = dataset
if grid is None:
grid = PyGrid.from_netCDF(grid_file,
dataset=dg,
grid_topology=grid_topology)
if varname is None:
varname = cls._gen_varname(data_file, dataset=ds)
if varname is None:
raise NameError(
'Default current names are not in the data file, must supply variable name'
)
data = ds[varname]
if name is None:
name = cls.__name__ + str(cls._def_count)
cls._def_count += 1
if units is None:
try:
units = data.units
except AttributeError:
units = None
if time is None:
time = Time.from_netCDF(filename=data_file,
dataset=ds,
datavar=data)
if depth is None:
if (isinstance(grid, PyGrid_S) and len(data.shape) == 4
or isinstance(grid, PyGrid_U) and len(data.shape) == 3):
from gnome.environment.environment_objects import Depth
depth = Depth(surface_index=-1)
# if len(data.shape) == 4 or (len(data.shape) == 3 and time is None):
# from gnome.environment.environment_objects import S_Depth
# depth = S_Depth.from_netCDF(grid=grid,
# depth=1,
# data_file=data_file,
# grid_file=grid_file,
# **kwargs)
if load_all:
data = data[:]
return cls(name=name,
units=units,
time=time,
data=data,
grid=grid,
depth=depth,
grid_file=grid_file,
data_file=data_file,
fill_value=fill_value,
varname=varname,
**kwargs)