Commit c3285a34 authored by Pierre Cazenave's avatar Pierre Cazenave

Complete the loading of QXF (netCDF) data. This includes making all arrays...

Complete the loading of QXF (netCDF) data. This includes making all arrays have the same number of values (i.e. 1D are tiled to match the 2D shapes).
parent 88c19df7
Pipeline #795 canceled with stage
......@@ -910,14 +910,22 @@ class CTD(object):
"""
with Dataset(header['file_name'], 'r') as ds:
# Grab each variable and dump it into self. Special care is taken to make depth arrays (
# ADEP-something) match the data.
# Grab each variable and dump it into self. If we have more than 1 dimension in the input file,
# repeat 1D arrays to match the 2D array shapes.
for variable in ds.variables:
if variable.startswith('ADEP') and ':' in variable:
# This is probably a depth array and we need to repeat it to match the raveled array lengths.
self.depth = 0
pass
setattr(self, variable, ds.variables[variable][:].ravel()) # make everything 1D
if len(ds.variables[variable].dimensions) == 1 and len(ds.dimensions) > 1:
# In order to make all arrays the same shape, we repeat each 1D one to match the 2D sizes.
# We also do this for the Cycle array.
num_time = ds.dimensions['primary'].size
num_depth = ds.dimensions['secondary'].size
# If the number of dimensions in the netCDF is more than 1, then we're assuming the data are
# 2D (time, depth) and we need a time-resolved depth array.
# Use the appropriate dimension when tiling.
if ds.variables[variable].dimensions[0] == 'primary':
setattr(self, variable, np.tile(ds.variables[variable][:], num_depth))
elif ds.variables[variable].dimensions[0] == 'secondary':
setattr(self, variable, np.tile(ds.variables[variable][:], num_time))
def _read_wco(self, header):
"""
......
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