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"""Plugin for HDF5 files created with using pytables (tables.netcdf3)"""
__author__ = "Jeffrey Whitaker <jeffrey.s.whitaker@noaa.gov>"
from __future__ import division
import os.path
import re
import types
# Requires tables.netcdf3
from tables.netcdf3 import NetCDFFile
from dap import dtypes
from dap.server import BaseHandler
from dap.exceptions import ConstraintExpressionError, OpenFileError
from dap.util.arrayterator import arrayterator
from dap.helper import getslice, typecode_to_dap
extensions = r"""^.*\.(h5|hdf5|H5|HDF5)$"""
BUFFER = 10000 # how many values to read at a time.
def get_attributes(var):
attributes = {}
attrs = [attr for attr in var.ncattrs()]
for attr in attrs:
value = getattr(var, attr)
if hasattr(value, 'tolist'): value = value.tolist()
attributes[attr] = value
return attributes
class Handler(BaseHandler):
def __init__(self, filepath):
dir, self.filename = os.path.split(filepath)
try:
self._file = NetCDFFile(filepath)
except:
raise OpenFileError, 'Unable to open file %s.' % filepath
def _parseconstraints(self, constraints=None):
# Build the dataset.
dataset = dtypes.DatasetType(name=self.filename)
# Add attributes.
dataset.attributes = get_attributes(self._file)
grids = [g for g in self._file.variables if g not in self._file.dimensions]
if not constraints:
# Build the grids.
for name in grids:
# Instantiate the grid.
grid = self._file.variables[name]
data = arrayterator(grid, nrecs=BUFFER)
g = dataset[name] = dtypes.GridType(data=data,
name=name,
dimensions=grid.dimensions,
shape=grid.shape,
type=typecode_to_dap[grid.typecode()],
attributes=get_attributes(grid))
# Build maps.
for mapname,shape in zip(g.dimensions, g.shape):
if mapname in self._file.variables:
map_ = self._file.variables[mapname]
data = arrayterator(map_, nrecs=BUFFER)
dataset[mapname] = g.maps[mapname] = dtypes.ArrayType(data=data,
name=mapname,
shape=map_.shape,
type=typecode_to_dap[map_.typecode()],
attributes=get_attributes(map_))
else:
# Some NetCDF files have dimensions without values?!
dataset[mapname] = g.maps[mapname] = dtypes.ArrayType(data=range(shape),
name=mapname,
shape=[shape],
type='Int32',
attributes={})
# Leftover arrays.
arrays = [a for a in self._file.variables if a not in dataset.keys()]
for name in arrays:
array_ = self._file.variables[name]
data = arrayterator(array_, nrecs=BUFFER)
dataset[name] = dtypes.ArrayType(data=data,
name=name,
shape=array_.shape,
type=typecode_to_dap[array_.typecode()],
attributes=get_attributes(array_))
else:
vars = constraints.split(',')
for var in vars:
p = re.compile(r'(?P<name>[^[]+)(?P<shape>(\[[^\]]+\])*)')
c = p.match(var).groupdict()
name = c['name']
#if name not in self._file.variables and name not in self._file.dimensions:
# raise ConstraintExpressionError, 'Variable %s not in dataset.' % name
# Check if var is grid or array.
if name not in self._file.dimensions and '.' not in name:
grid = self._file.variables[name]
slice_ = getslice(c['shape'], grid.shape)
start = [i.start for i in slice_]
stride = [i.step for i in slice_]
shape = [(i.stop - i.start) for i in slice_]
# Build grid.
data = arrayterator(grid, start=start, shape=shape, stride=stride, nrecs=BUFFER)
g = dataset[name] = dtypes.GridType(data=data,
name=name,
dimensions=grid.dimensions,
shape=shape,
type=typecode_to_dap[grid.typecode()],
attributes=get_attributes(grid))
# Build maps.
dimmap = zip(g.dimensions, start, shape, stride)
for mapname,start_,shape_,stride_ in dimmap:
if mapname in self._file.variables:
map_ = self._file.variables[mapname]
data = arrayterator(map_, start=[start_], shape=[shape_], stride=[stride_], nrecs=BUFFER)
g.maps[mapname] = dtypes.ArrayType(data=data,
name=mapname,
shape=[shape_],
type=typecode_to_dap[map_.typecode()],
attributes=get_attributes(map_))
else:
# Some NetCDF files have dimensions without values?!
g.maps[mapname] = dtypes.ArrayType(data=range(shape_),
name=mapname,
shape=[shape_],
type='Int32',
attributes={})
else:
# Build array.
if '.' in name:
try:
grid, name = name.split('.')
assert grid in grids
assert name in self._file.variables[grid].dimensions or name == grid
except:
raise ConstraintExpressionError, 'Invalid name in constraint expression: %s.' % c['name']
array_ = self._file.variables[name]
slice_ = getslice(c['shape'], array_.shape)
start = [i.start for i in slice_]
stride = [i.step for i in slice_]
shape = [(i.stop - i.start) for i in slice_]
data = arrayterator(array_, start=start, shape=shape, stride=stride, nrecs=BUFFER)
if not grid in dataset.keys():
structure = dataset[grid] = dtypes.StructureType(name=grid)
structure[name] = dtypes.ArrayType(data=data,
name=name,
shape=shape,
type=typecode_to_dap[array_.typecode()],
attributes=get_attributes(array_))
else:
if name in self._file.variables:
array_ = self._file.variables[name]
slice_ = getslice(c['shape'], array_.shape)
start = [i.start for i in slice_]
stride = [i.step for i in slice_]
shape = [(i.stop - i.start) for i in slice_]
data = arrayterator(array_, start=start, shape=shape, stride=stride, nrecs=BUFFER)
dataset[name] = dtypes.ArrayType(data=data,
name=name,
shape=shape,
type=typecode_to_dap[array_.typecode()],
attributes=get_attributes(array_))
elif name in self._file.dimensions:
# Some NetCDF files have dimensions without values.
shape = self._file.dimensions[name]
dataset[name] = dtypes.ArrayType(data=range(shape),
name=name,
shape=[shape],
type='Int32',
attributes={})
return dataset
def close(self):
self._file.close()
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