def __init__(self,pattern,dimension,dim_func,variable=None,preload=False):
files = glob(pattern)
files.sort()
if len(files) == 0:
raise Exception("No files matching pattern", pattern)
layer_dim = [dim_func(f) for f in files]
self.variable = variable
#import h5py
#self.fh = h5py.File(filename,'r')
self.file_layers = [_spatial_file_loader(filename,variable) for filename in files]
self.ref_fh = self.file_layers[0]
#lats,lons = self.fh['dimensions/latitude'][...], self.fh['dimensions/longitude'][...]
self._flat_cs = self.ref_fh.get_coords()
self.cs = mt.CoordinateSet((mt.Coordinates(dimension,layer_dim),self._flat_cs['latitude'],self._flat_cs['longitude']))
if preload:
self.v =[fh.data[...] for fh in self.file_layers]
else:
self.v = [fh.data for fh in self.file_layers]
self.dtype = self.v[0].dtype
self._shaper = _3shaper
def __init__(self,path,pattern,nc_var,preload=False):
import netCDF4 as nc
self.fh = nc.Dataset(path+pattern,'r')
self.v = self.fh.variables[nc_var]
self.time_idx = self.fh.variables['time'][:]
lats,lons = self.fh.variables['latitude'][...], self.fh.variables['longitude'][...]
self.cs = mt.CoordinateSet(mt.latlon_to_coords(lats,lons))
def __init__(self, filename, variable, preload=False):
import netCDF4 as nc
self.fh = nc.Dataset(filename, 'r')
lats, lons = self.fh.variables['latitude'][
...], self.fh.variables['longitude'][...]
self.cs = mt.CoordinateSet(mt.latlon_to_coords(lats, lons))
if preload:
self.v = self.fh.variables[variable][...]
else:
self.v = self.fh.variables[variable]
def get_data(self,coords):
idx = self._flat_cs.get_index(mt.CoordinateSet([coords.latitude,coords.longitude]))
out_shape = tuple([len(self.cs[0])] + list(index_shape(idx)))
out_data = np.empty(out_shape,dtype=self.dtype)
for i,v in enumerate(self.v):
out_data[i] = v[idx]
return out_data.reshape(self._shaper(self.cs,coords))
def __setitem__(self, k, extent):
group = self.f.create_group(k)
g = DatasetManager(group)
lats = mt.Coordinates(mt.latitude, extent.latitudes.to_degrees())
lons = mt.Coordinates(mt.longitude, extent.longitudes.to_degrees())
cs = mt.CoordinateSet([lats, lons])
v = mt.Variable(
'area', 'm2',
dict(long_name='Metres squared covered by cell',
cell_size=extent.cell_size.to_degrees(),
lat_orient=extent.parent_ref.lat_orient))
mapped_var = mt.MappedVariable(v, cs, np.float64)
ncv = g.create_variable(mapped_var)
ncv[...] = extent.areas.data
def __init__(self,filename,variable,preload=False):
self.filename = filename
self.variable = variable
self.preload = preload
import h5py
self.fh = h5py.File(filename,'r')
lats,lons = self.fh['dimensions/latitude'][...], self.fh['dimensions/longitude'][...]
self.cs = mt.CoordinateSet(mt.latlon_to_coords(lats,lons))
if preload:
self.v = self.fh[variable][...]
else:
self.v = self.fh[variable]
self.dtype = self.v.dtype
def get_data(self, coords):
idx = self.cs.get_index(
mt.CoordinateSet([coords.latitude, coords.longitude]))
return self.v[idx].reshape(self._shaper(self.cs, coords))
def get_coords(self):
return mt.CoordinateSet([
mt.Coordinates(mt.get_dimension(k, '', self._dim_handles[k].dtype),
self._dim_handles[k][...]) for k in self.dims
])
def get_coords(self):
return mt.CoordinateSet([mt.Coordinates(mt.get_dimension(k),self.fh['dimensions'][k][...]) for k in self.dims])
