tab data format

[gpagliuca]

the tab.data dataframe is difficult to handle (properties as index), its structure should be changed

[kjeeetil]

xarray provides a very convenient format for this type of data. if you pass a pandas dataframe with an appropriate multiindexed dataframe as input everything works out nicely:

tab=pyfas.tab.Tab("PVTtable.tab") tab.export_all()

columns=tab.data["Property"].values data=tab.data["values"].values

series={} for i, array in enumerate(data): #cycles through each column in data, creating a pandas dataseries with properties as columns series[columns[i]]=array

new_p=[] new_t=[]

for p in tab.metadata['p_array'][0]: new_t=new_t+list(tab.metadata['t_array'][0]) new_p=new_p+[p/1e5 for x in tab.metadata['p_array'][0]]

index=zip(new_p, new_t) #creates a list of tuples which can be used in a multiindex index=pd.MultiIndex.from_tuples(index, names=["P", "T"]) #creates a multiindex with pressure and temperature

df=pd.DataFrame(series, index=index) #creates a dataframe from the tab data with pressure and temperature as index da=df.to_xarray() #passes the dataframe to an xarray dataarray

The dataarray will have pressure and temperature as dimensions, and each column in the dataframe as a variable. The datarray allows you to do things like fast linear interpolation (e.g. da.interp(T=50, P=[50, 60, 70])["LIQUID DENSITY"]) which is extremely useful especially when comparing tables with different spacing between input parameters.

[gpagliuca]

thanks for the suggestion, it looks very interesting. Also here if you have the possibility a PR would be quite useful since you know xarray better than me

[daniel-brett]

Has this issue been addressed with https://github.com/gpagliuca/pyfas/pull/23?

[gpagliuca]

Yes, it was

Cheers

Il giorno mer 26 apr 2023 alle ore 15:18 daniel-brett < @.***> ha scritto:

Has this issue been addressed with #23 https://github.com/gpagliuca/pyfas/pull/23?

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