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When using the PAR model's sample method and providing a context, there is an error if the context columns aren't in the same order as the original data.
Expected Behavior: I expect that it's ok if the columns are in a different order. They are named so it's possible to know which column is which.
Steps to reproduce
fromsdv.demoimportload_timeseries_demofromsdv.timeseriesimportPARimportpandasaspddata=load_timeseries_demo()
model=PAR(
entity_columns=['Symbol'],
context_columns=['MarketCap', 'Sector', 'Industry'],
sequence_index='Date',
epochs=1
)
model.fit(data)
# these are in the wrong order# original data has MarketCap, Sector then Industrycontext=pd.DataFrame(data={
'Symbol': ['Apple', 'Google'],
'Sector': ['Technology', 'Health Care'],
'MarketCap': [1.2345e+11, 4.5678e+10],
'Industry': ['Electronic Components', 'Medical/Nursing Services']
})
model.sample(context=context)
The above code will work if I just move the columns around
Environment Details
Error Description
When using the PAR model's
sample
method and providing a context, there is an error if the context columns aren't in the same order as the original data.Expected Behavior: I expect that it's ok if the columns are in a different order. They are named so it's possible to know which column is which.
Steps to reproduce
The above code will work if I just move the columns around
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