def test_io_sections_property():
ds = DataStore({
'st': (['x', 'time'], np.ones((5, 5))),
'ast': (['x', 'time'], np.ones((5, 5))),
'probe1Temperature': (['time'], range(5)),
'probe2Temperature': (['time'], range(5))
},
coords={
'x': range(5),
'time': range(5)})
sections = {
'probe1Temperature': [slice(7.5, 17.), slice(70., 80.)], # cold bath
'probe2Temperature': [slice(24., 34.), slice(85., 95.)], # warm bath
}
ds.sections = sections
with tempfile.NamedTemporaryFile() as tmp:
ds.to_netcdf(path=tmp.name)
ds2 = open_datastore(tmp.name)
assert ds.sections == ds2.sections
pass
def test_sections_property():
ds = DataStore({
'st': (['x', 'time'], np.ones((5, 5))),
'ast': (['x', 'time'], np.ones((5, 5))),
'probe1Temperature': (['time'], range(5)),
'probe2Temperature': (['time'], range(5))
},
coords={
'x': range(5),
'time': range(5)})
sections1 = {
'probe1Temperature': [slice(7.5, 17.), slice(70., 80.)], # cold bath
'probe2Temperature': [slice(24., 34.), slice(85., 95.)], # warm bath
}
sections2 = {
'probe1Temperature': [slice(0., 17.), slice(70., 80.)], # cold bath
'probe2Temperature': [slice(24., 34.), slice(85., 95.)], # warm bath
}
ds.sections = sections1
assert isinstance(ds._sections, str)
assert ds.sections == sections1
assert ds.sections != sections2
# delete property
del ds.sections
assert ds.sections is None
pass
def test_io_sections_property():
ds = DataStore(
{
'st': (['x', 'time'], np.ones((100, 5))),
'ast': (['x', 'time'], np.ones((100, 5))),
'probe1Temperature': (['time'], range(5)),
'probe2Temperature': (['time'], range(5))
},
coords={
'x': ('x', range(100), {
'units': 'm'
}),
'time': range(5)
})
sections = {
'probe1Temperature': [slice(7.5, 17.),
slice(70., 80.)], # cold bath
'probe2Temperature': [slice(24., 34.),
slice(85., 95.)], # warm bath
}
ds['x'].attrs['units'] = 'm'
ds.sections = sections
# Create a temporary file to write data to.
# 'with' method is used so the file is closed by tempfile
# and free to be overwritten.
with tempfile.NamedTemporaryFile('w') as tmp:
temppath = tmp.name
# Write the datastore to the temp file
ds.to_netcdf(path=temppath)
try:
ds2 = open_datastore(temppath)
except ValueError as e:
if str(e) != 'cannot guess the engine, try passing one explicitly':
raise
else:
warnings.warn('Could not guess engine, defaulted to netcdf4')
ds2 = open_datastore(temppath, engine='netcdf4')
assert ds.sections == ds2.sections
# Close the datastore so the temp file can be removed
ds2.close()
ds2 = None
# Remove the temp file once the test is done
if os.path.exists(temppath):
os.remove(temppath)
pass
def test_io_sections_property():
ds = DataStore(
{
'st': (['x', 'time'], np.ones((100, 5))),
'ast': (['x', 'time'], np.ones((100, 5))),
'probe1Temperature': (['time'], range(5)),
'probe2Temperature': (['time'], range(5))
},
coords={
'x': ('x', range(100), {
'units': 'm'
}),
'time': range(5)
})
sections = {
'probe1Temperature': [slice(7.5, 17.),
slice(70., 80.)], # cold bath
'probe2Temperature': [slice(24., 34.),
slice(85., 95.)], # warm bath
}
ds['x'].attrs['units'] = 'm'
ds.sections = sections
# Create a temporary file to write data to.
# 'with' method is used so the file is closed by tempfile
# and free to be overwritten.
with tempfile.NamedTemporaryFile('w') as tmp:
temppath = tmp.name
# Write the datastore to the temp file
ds.to_netcdf(path=temppath)
ds2 = open_datastore(temppath)
assert ds.sections == ds2.sections
# Close the datastore so the temp file can be removed
ds2.close()
ds2 = None
# Remove the temp file once the test is done
if os.path.exists(temppath):
os.remove(temppath)
pass