def read_dimensions(f, name=None, ix=slice(None), verbose=False):
""" return an Axes object
name, optional: variable name
return: Axes object
"""
f, close = check_file(f, mode='r', verbose=verbose)
# dimensions associated to the variable to load
if name is None:
dims = f.dimensions.keys()
else:
try:
dims = f.variables[name].dimensions
except KeyError:
print "Available variable names:", f.variables.keys()
raise
dims = [str(d) for d in dims] # conversion to string
# load axes
axes = Axes()
for k in dims:
try:
values = f.variables[k][ix]
except KeyError:
msg = "'{}' dimension not found, define integer range".format(k)
warnings.warn(msg)
values = np.arange(len(f.dimensions[k]))
# replace unicode by str as a temporary bug fix (any string seems otherwise to be treated as unicode in netCDF4)
if values.size > 0 and type(values[0]) is unicode:
for i, val in enumerate(values):
if type(val) is unicode:
values[i] = str(val)
axes.append(Axis(values, k))
if close: f.close()
return axes
def read_dimensions(f, name=None, ix=slice(None), verbose=False):
""" return an Axes object
name, optional: variable name
return: Axes object
"""
f, close = check_file(f, mode='r', verbose=verbose)
# dimensions associated to the variable to load
if name is None:
dims = f.dimensions.keys()
else:
try:
dims = f.variables[name].dimensions
except KeyError:
print "Available variable names:",f.variables.keys()
raise
dims = [str(d) for d in dims] # conversion to string
# load axes
axes = Axes()
for k in dims:
try:
values = f.variables[k][ix]
except KeyError:
msg = "'{}' dimension not found, define integer range".format(k)
warnings.warn(msg)
values = np.arange(len(f.dimensions[k]))
# replace unicode by str as a temporary bug fix (any string seems otherwise to be treated as unicode in netCDF4)
if values.size > 0 and type(values[0]) is unicode:
for i, val in enumerate(values):
if type(val) is unicode:
values[i] = str(val)
axes.append(Axis(values, k))
if close: f.close()
return axes
def read_dimensions(f, name=None, ix=slice(None), dimensions_mapping=None, verbose=False):
""" return an Axes object
Parameters
----------
name : str, optional
variable name
ix : integer (position) index
dimensions_mapping : dict, optional
mapping between dimension and variable names
Returns
-------
Axes object
"""
f, close = _check_file(f, mode='r', verbose=verbose)
# dimensions associated to the variable to load
if name is None:
dims = f.dimensions.keys()
else:
try:
dims = f.variables[name].dimensions
except KeyError:
print "Available variable names:",f.variables.keys()
raise
dims = [str(d) for d in dims] # conversion to string
# load axes
axes = Axes()
for dim in dims:
if dimensions_mapping is not None:
# user-provided mapping between dimensions and variable name
dim_name = dimensions_mapping[dim]
values = f.variables[dim_name][ix]
elif dim in f.variables.keys():
# assume that the variable and dimension have the same name
values = f.variables[dim][ix]
else:
# default, dummy dimension axis
msg = "'{}' dimension not found, define integer range".format(dim)
warnings.warn(msg)
values = np.arange(len(f.dimensions[dim]))
# replace unicode by str as a temporary bug fix (any string seems otherwise to be treated as unicode in netCDF4)
if values.size > 0 and type(values[0]) is unicode:
for i, val in enumerate(values):
if type(val) is unicode:
values[i] = str(val)
axis = Axis(values, dim)
# add metadata
if dim in f.variables.keys():
meta = _read_attributes(f, dim)
axis._metadata(meta)
axes.append(axis)
if close: f.close()
return axes
