HDDM "load" function equivalent in HSSM?

[nancyebner]

I would like to use my own dataset instead of simulating one, in the HDDM package the load function could be used to call a csv file containing my own dataset. I am struggling to find an equivalent in the HSSM framework. It is likely that I am misunderstanding something but I am unable to go on without this step so any help is much appreciated! (ps: I also tried to follow this example (in GoogleColab) using the package-supplied dataset:

"Load a package-supplied dataset"
cav_data = hssm.load_data('cavanagh_theta')

(https://lnccbrown.github.io/HSSM/#installation) but this is once again a package-supplied dataset, and I would like to use my own. Is this a possibility?

[digicosmos86]

Hi,

HSSM just accepts pandas DataFrames now, so you can just use pd.read_csv to get a DataFrame and pass it to HSSM. In a future version we might just do this in HSSM so people will just need to pass a string of the path to the csv.

[nancyebner]

Hi,

Thank you for your answer. I was able to get the dataframe but how do I pass it to HSSM now?
Thanks again.

[frankmj]

HI Paul, once it is a dataframe you can pass it to HSSM in the same way as in the tutorial using simulated data with whatever model specification you want. e.g. for the most basic model: simple_ddm_model = hssm.HSSM(data=dataset) replacing 'dataset' with the name of your dataframe, which has to have columns for response and rt in seconds. M

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