def __init__(self, path_to_data, network=None):
"""
collects metadata from all files in path_to_data and saves metadata information
in numpy file in folder path_to_data/python_metadata/
First initialization can take a minute or so if all ISMN
data is present in path_to_data
"""
if not os.path.exists(os.path.join(path_to_data, 'python_metadata', 'metadata.npy')):
self.metadata = metadata_collector.collect_from_folder(
path_to_data)
os.mkdir(os.path.join(path_to_data, 'python_metadata'))
np.save(
os.path.join(path_to_data, 'python_metadata', 'metadata.npy'), self.metadata)
#np.savetxt(os.path.join(path_to_data,'python_metadata','metadata.npy'), self.metadata,delimiter=',')
else:
self.metadata = np.load(
os.path.join(path_to_data, 'python_metadata', 'metadata.npy'))
if network is not None:
if type(network) is not list:
network = [network]
# initialize binary mask the size of metadata
mask = np.zeros(self.metadata.shape[0], dtype=np.bool)
for net in network:
if net in self.metadata['network']:
mask = mask | (self.metadata['network'] == net)
else:
raise ISMNError("Network {} not found".format(net))
self.metadata = self.metadata[mask]
# initialize grid object for all stations
self.grid = grids.BasicGrid(self.metadata['longitude'],
self.metadata['latitude'],
setup_kdTree=False)
def _init_grid(self):
"""
initialize the grid of the dataset
"""
x = self.ds.variables[self.lat_var][:]
y = self.ds.variables[self.lon_var][:]
xs, ys = np.meshgrid(x, y)
self.grid = grids.BasicGrid(xs.flatten(),
ys.flatten(),
shape=(1200, 2400))
def __init__(self, path_to_data, network=None):
"""
collects metadata from all files in path_to_data and saves metadata information
in numpy file in folder path_to_data/python_metadata/
First initialization can take a minute or so if all ISMN
data is present in path_to_data
"""
if not os.path.exists(
os.path.join(path_to_data, 'python_metadata', 'metadata.npy')):
os.mkdir(os.path.join(path_to_data, 'python_metadata'))
self.metadata = metadata_collector.collect_from_folder(
path_to_data)
np.save(
os.path.join(path_to_data, 'python_metadata', 'metadata.npy'),
self.metadata)
#np.savetxt(os.path.join(path_to_data,'python_metadata','metadata.npy'), self.metadata,delimiter=',')
else:
self.metadata = np.load(
os.path.join(path_to_data, 'python_metadata', 'metadata.npy'))
if network is not None:
if type(network) is not list:
network = [network]
# initialize binary mask the size of metadata
mask = np.zeros(self.metadata.shape[0], dtype=np.bool)
for net in network:
if net in self.metadata['network']:
mask = mask | (self.metadata['network'] == net)
else:
raise ISMNError("Network {} not found".format(net))
self.metadata = self.metadata[mask]
# initialize grid object for all stations
self.grid = grids.BasicGrid(self.metadata['longitude'],
self.metadata['latitude'],
setup_kdTree=False)
# read cci landcover class names and their identifiers
config = configparser.ConfigParser()
config.optionxform = str
config.read_file(
open(
os.path.join(os.path.dirname(os.path.abspath(__file__)),
'classifications.ini')))
landcover = dict(config.items('LANDCOVER'))
self.landcover = dict([(int(v), k) for k, v in landcover.items()])
self.climate = dict(config.items('KOEPPENGEIGER'))
def activate_network(self, network):
"""
Load or update metadata for reading one or multiple networks.
Parameters
---------
network : list or str
Name of a network in the initialised path or multiple networks as
a list of strings that are loaded.
"""
if not os.path.exists(
os.path.join(self.path_to_data, 'python_metadata',
'metadata.npy')):
os.mkdir(os.path.join(self.path_to_data, 'python_metadata'))
self.metadata = metadata_collector.collect_from_folder(
self.path_to_data)
np.save(
os.path.join(self.path_to_data, 'python_metadata',
'metadata.npy'), self.metadata)
#np.savetxt(os.path.join(path_to_data,'python_metadata','metadata.npy'), self.metadata,delimiter=',')
else:
self.metadata = np.load(os.path.join(self.path_to_data,
'python_metadata',
'metadata.npy'),
allow_pickle=True)
if network is not None:
if type(network) is not list:
network = [network]
# initialize binary mask the size of metadata
mask = np.zeros(self.metadata.shape[0], dtype=np.bool)
for net in network:
if net in self.metadata['network']:
mask = mask | (self.metadata['network'] == net)
else:
raise ISMNError("Network {} not found".format(net))
self.metadata = self.metadata[mask]
# initialize grid object for all stations
self.grid = grids.BasicGrid(self.metadata['longitude'],
self.metadata['latitude'],
setup_kdTree=False)
def setUp(self):
"""
Define test file.
"""
self.testfilename = os.path.join(mkdtemp(), 'test.nc')
self.grid = grids.BasicGrid(np.arange(180), np.arange(180) - 90)
def _load_grid(self):
lons = self.dataset.variables[self.lon_var][:]
lats = self.dataset.variables[self.lat_var][:]
self.grid = grids.BasicGrid(lons, lats)