def __init__(self, filepath):
BaseHandler.__init__(self)
try:
self.fp = h5py.File(filepath, 'r')
except Exception, exc:
message = 'Unable to open file %s: %s' % (filepath, exc)
raise OpenFileError(message)
def __init__(self, filepath):
BaseHandler.__init__(self)
try:
self.fp = netcdf_file(filepath)
except Exception, exc:
message = "Unable to open file %s: %s" % (filepath, exc)
raise OpenFileError(message)
def __init__(self, filepath):
BaseHandler.__init__(self)
try:
self.fp = h5py.File(filepath, 'r')
except Exception, exc:
message = 'Unable to open file %s: %s' % (filepath, exc)
raise OpenFileError(message)
def __init__(self, filepath):
BaseHandler.__init__(self)
try:
with open(filepath, 'Ur') as fp:
reader = csv.reader(fp, quoting=csv.QUOTE_NONNUMERIC)
vars = reader.next()
except Exception, exc:
message = 'Unable to open file {filepath}: {exc}'.format(filepath=filepath, exc=exc)
raise OpenFileError(message)
def __init__(self, filepath):
BaseHandler.__init__(self)
try:
with open(filepath, 'Ur') as fp:
reader = csv.reader(fp, quoting=csv.QUOTE_NONNUMERIC)
vars = reader.next()
except Exception, exc:
message = 'Unable to open file {filepath}: {exc}'.format(
filepath=filepath, exc=exc)
raise OpenFileError(message)
def __init__(self, filepath):
"""Prepare dataset."""
BaseHandler.__init__(self)
# open the YAML file and parse configuration
try:
with open(filepath, 'Ur') as fp:
fp = open(filepath, 'Ur')
config = yaml.load(fp)
except Exception, exc:
message = 'Unable to open file {filepath}: {exc}'.format(
filepath=filepath, exc=exc)
raise OpenFileError(message)
def __init__(self, filepath):
BaseHandler.__init__(self)
if filepath is None:
self.config = {}
self.dataset = None
else:
try:
with open(filepath, 'r') as file:
config = yaml.load(file, Loader=yaml.FullLoader)
except Exception as exc:
raise OpenFileError(
'Unable to open file {filepath}: {exc}'.format(
filepath=filepath, exc=exc))
self.config = config
self.dataset = dataset_model(config)
def __init__(self, filepath):
BaseHandler.__init__(self)
self.filepath = filepath
try:
with netcdf_file(self.filepath, 'r') as source:
self.additional_headers.append(('Last-modified', (formatdate(
time.mktime(time.localtime(
os.stat(filepath)[ST_MTIME]))))))
# shortcuts
vars = source.variables
dims = source.dimensions
# build dataset
name = os.path.split(filepath)[1]
self.dataset = DatasetType(
name, attributes=dict(NC_GLOBAL=attrs(source)))
for dim in dims:
if dims[dim] is None:
self.dataset.attributes['DODS_EXTRA'] = {
'Unlimited_Dimension': dim,
}
break
# add grids
grids = [var for var in vars if var not in dims]
for grid in grids:
self.dataset[grid] = GridType(grid, attrs(vars[grid]))
# add array
self.dataset[grid][grid] = BaseType(
grid, LazyVariable(source, grid, grid, self.filepath),
vars[grid].dimensions, attrs(vars[grid]))
# add maps
for dim in vars[grid].dimensions:
self.dataset[grid][dim] = BaseType(
dim, vars[dim][:], None, attrs(vars[dim]))
# add dims
for dim in dims:
self.dataset[dim] = BaseType(dim, vars[dim][:], None,
attrs(vars[dim]))
except Exception as exc:
raise
message = 'Unable to open file %s: %s' % (filepath, exc)
raise OpenFileError(message)
def __init__(self, filepath):
"""
Prepare dataset.
The `__init__` method of handlers is responsible for preparing the dataset
for incoming requests.
"""
BaseHandler.__init__(self)
# open the YAML file and parse configuration
try:
with open(filepath, 'Ur') as fp:
fp = open(filepath, 'Ur')
config = yaml.load(fp)
except Exception, exc:
message = 'Unable to open file {filepath}: {exc}'.format(filepath=filepath, exc=exc)
raise OpenFileError(message)
def __init__(self, dataset=None):
BaseHandler.__init__(self, dataset)
self.additional_headers = [("X-debug", "True")]
def __getattr__(self, name):
if name != 'dataset': raise AttributeError
BaseHandler.__init__(self)
self.dataset = make_dataset(self.filepath)
return self.dataset
def __init__(self, dataset=None):
BaseHandler.__init__(self, dataset)
self.additional_headers = [
("X-debug", "True")
]
def __init__(self, filepath):
BaseHandler.__init__(self)
self.filepath = filepath
self.cache = FileAttributeCache()
def __init__(self, filepath):
BaseHandler.__init__(self)
self.filepath = filepath
self.filename = os.path.split(filepath)[1]
temporal_resolution = "Monthly"
if 'weeks' in filepath:
temporal_resolution = "Weekly"
elif self.daily.match(self.filename):
temporal_resolution = "Daily"
elif self.day_3.match(self.filename):
temporal_resolution = "3-Day"
self.dataset = DatasetType(name=self.filename, attributes={
"SSMI_GLOBAL" : {
"CONVENTIONS" : "COARDS",
"short_name" : "SSMIS",
"long_name" : "Special Sensor Microwave Image Sounder",
"producer_agency" : "Remote Sensing Systems",
"product_version" : "Version-7",
"spatial_resolution" : "0.25 degree",
"temporal_resolution" : temporal_resolution,
"instrument" : "SSMIS",
"original_filename" : self.filename,
}
})
time_variable = False
if self.daily.match(self.filename) and not 'weeks' in filepath:
time_variable = True
_dim = ('lon', 'lat', 'part_of_day')
_shape = (1440, 720, 2)
_type = UInt16
self.variables = []
if time_variable:
self.variables.append(
BaseType(
name='time',
data=None,
shape=_shape,
dimensions=_dim,
type=_type,
attributes={
'long_name' : 'Time',
'add_offset' : 0,
'scale_factor' : 6,
'_FillValue' : 254,
'units' : 'minutes',
'coordinates': 'lon lat'
}
))
self.variables.append(BaseType(
name='wspd',
data=None,
shape=_shape,
dimensions=_dim,
type=_type,
attributes={
'long_name' : '10 meter Surface Wind Speed',
'add_offset' : 0,
'scale_factor' : 0.2,
'_FillValue' : 254,
'units' : 'm/sec',
'coordinates': 'lon lat'
}
))
self.variables.append(BaseType(
name='vapor',
data=None,
shape=_shape,
dimensions=_dim,
type=_type,
attributes=({
'long_name' : 'Atmospheric Water Vapor',
'add_offset' : 0,
'scale_factor' : 0.3,
'_FillValue' : 254,
'units' : 'mm',
'coordinates': 'lon lat'
})
))
self.variables.append(BaseType(
name='cloud',
data=None,
shape=_shape,
dimensions=_dim,
type=_type,
attributes=({
'long_name' : 'Cloud liquid Water',
'add_offset' : -0.05,
'scale_factor' : 0.01,
'_FillValue' : 254,
'units' : 'mm',
'coordinates': 'lon lat'
})
))
self.variables.append(BaseType(
name='rain',
data=None,
shape=_shape,
dimensions=_dim,
type=_type,
attributes=({
'long_name' : 'Rain Rate',
'add_offset' : 0,
'scale_factor' : 0.1,
'_FillValue' : 254,
'units' : 'mm/hr',
'coordinates': 'lon lat'
})
))
lonVar = BaseType(
name='lon',
data=None,
shape=(1440,),
dimensions=('lon',),
type=Float32,
attributes=({
'long_name' : 'longitude',
# 'add_offset' : 0,
# 'scale_factor' : 1,
'valid_range' : '-180, 180',
'units' : 'degrees_east'
})
)
latVar = BaseType(
name='lat',
data=None,
shape=(720,),
dimensions=('lat',),
type=Float32,
attributes=({
'long_name' : 'latitude',
# 'add_offset' : 0,
# 'scale_factor' : 1,
'valid_range' : '-90, 90',
'units' : 'degrees_north'
})
)
partVar = BaseType(
name='part_of_day',
data=None,
shape=(2,),
dimensions=('part_of_day',),
type=UInt16,
attributes=({
'long_name' : 'part_of_day',
# 'add_offset' : 0,
# 'scale_factor' : 1,
'valid_range' : '0, 1',
'units' : 'part_of_day'
})
)
self.dataset['lon'] = lonVar
self.dataset['lat'] = latVar
self.dataset['part_of_day'] = partVar
for variable in self.variables:
# print variable.name
g = GridType(name=variable.name)
g[variable.name] = variable
g['lon'] = lonVar.__deepcopy__()
g['lat'] = latVar.__deepcopy__()
g['part_of_day'] = partVar.__deepcopy__()
g.attributes = variable.attributes
self.dataset[variable.name] = g
