def __getitem__(self, slice_):
if not self._valid:
raise Exception('Invalid slicing of parameter "%s"' % self._pparam.name)
if not isinstance(slice_, tuple): slice_ = (slice_,)
print 'slice_: %s' % (slice_,)
# get the time verticies based on the first member of the slice
tverts=self._tverts[slice_[0]]
try:
ntverts=len(tverts)
except Exception:
ntverts=1
print 'num time_verts: %s' % ntverts
# slice_=slice_[1:]
# Get the entities pertaining to the requested slice
# print 'ent_handles_shp: %s' % (self._ent_hndls.shape,)
# sents=self._ent_hndls[slice_]
# print 'sents_shp: %s' % (sents.shape,)
# Return the data for the appropriate entities
nshp=(ntverts,)+self.shape[1:]
print nshp
return utils.get_packed_data(self._pparam._tag_hndl, tverts, self._pparam.data_type).reshape(nshp)[(slice(None),)+slice_[1:]]
## Method one extracts data one ts at a time and builds the complete timeseries for each variable piecemeal
# This method is slower but robust if data variables are added/removed during the timeseries
# NOTE: does not yet deal with gaps in the timeseries
for i in range(ntimes):
try:
tsvert = mesh.getEntAdj(tlines[i], iBase.Type.vertex)[0]
except IndexError:
tsvert = mesh.getEntAdj(tlines[i - 1], iBase.Type.vertex)[0]
topo_set = iMesh.EntitySet(t_topo_tag[tsvert], mesh)
verts = topo_set.getEntities(type=iBase.Type.vertex)
dtags = mesh.getAllTags(tsvert)
for dt in (dt for dt in dtags if dt.name.startswith("DATA")):
dtc, _ = utils.unpack_data_tag_name(dt.name)
data = utils.get_packed_data(dt, tsvert, dtc)
if not dt.name in data_map:
data_map[dt.name] = data
else:
data_map[dt.name] = numpy.vstack([data_map[dt.name], data])
else:
## Method two extracts the entire timeseries for each variable
# This method is faster but only works if data exists for all vertices
# Extract the temporal vertex array from the time_topology (tlines)
tsverts = [x[0] for x in mesh.getEntAdj(tlines, iBase.Type.vertex)]
tsverts.append(mesh.getEntAdj(tlines[len(tlines) - 1], iBase.Type.vertex)[1])
dtags = mesh.getAllTags(tsverts[0]) # This assumes that all data_tags are present on the first vertex
for dt in (dt for dt in dtags if dt.name.startswith("DATA")):
dtc, _ = utils.unpack_data_tag_name(dt.name)
ts_sets=t_set.getChildren()
for i in range(ntimes):
try:
stn_set = ts_sets[i]
except:
stn_set = None
if stn_set is None:
raise Exception("The EntitySet %s does not contain a point, cannot process" % ts_sets[i])
dtags=mesh.getAllTags(stn_set)
for dt in dtags:
dtc,_=utils.unpack_data_tag_name(dt.name)
data=utils.get_packed_data(dt, stn_set, dtc)
if not dt.name in data_map:
data_map[dt.name] = data
else:
data_map[dt.name] = numpy.vstack([data_map[dt.name],data])
nvars=len(data_map)
nrow=2
ncol=int(nvars/nrow)+1
# Apply units, _FillValue, scale_factor, add_offset and plot
fig = figure()
i=1
for var in data_map:
dtc, varname=utils.unpack_data_tag_name(var)
# Get the units, _FillValue, scale_factor, and add_offset
fill_val=numpy.nan
scale_factor=None
add_offset=None
units='Unknown'
if varname in var_atts:
if '_FillValue' in var_atts[varname]:
fill_val=var_atts[varname]['_FillValue']
if 'scale_factor' in var_atts[varname]:
scale_factor=var_atts[varname]['scale_factor']
if 'add_offset' in var_atts[varname]:
add_offset=var_atts[varname]['add_offset']
if 'units' in var_atts[varname]:
units=var_atts[varname]['units']
data=utils.get_packed_data(data_t, set, dtc)
# data=data_t[set]
data=numpy.ma.masked_equal(data,fill_val,copy=False)
# apply the scale_factor
if scale_factor is not None:
data=data.astype(scale_factor.dtype.char)*scale_factor
# apply the add_offset
if add_offset is not None:
data+=add_offset
qvert_list=mesh.getEntAdj(quads,iBase.Type.vertex)
poly_list=[]
for qv in qvert_list:
cds=mesh.getVtxCoords(qv)
poly_list.append(cds[:,[0,1]].tolist())
