How to save results of single simulations and explorations? about neurolib HOT 7 CLOSED

Imagine:

model = Model()
model.run()
model.results # an xarray

circuit = Circuit(*models)
circuit.run()
circuit.results # an xarray

All the same syntax for different levels!

from neurolib.

Definitely tabulated values, for now, I'd use xarray as you suggest. the integration could look like

circuit = Circuit(...)
circuit.run(...)
print(circuit.results)
# will print results in a xarray.DataField
circuit.save_results("results.hdf")  # or .nc, or .pkl or .csv if only 2D

from neurolib.

actually, the model results are always 2D (number of state vector variables x time) so pandas is enough there, only exploration results would need multi-d representation, so xarray

from neurolib.

I was actually tryig to avoid using pandas because I'm not sure if it is fit for timeseries data (I might be wrong). I'm rather used to process results with it. xarr however seems to be perfect for this job, especially if you can extend it many more dimensions in (state variables x time x parameters) space. It seems kinda straightforward to save explorations in it or to dump data into an xarr from a pypet trajectory.

from neurolib.

yup, agreed, we need not use pandas and use xarray instead for greater compatibility of model results vs. exploration results

from neurolib.

in 6 months we are there :)

from neurolib.

Single simulations save their results into a .results object, can be accessed via keys a la model['x'] or attributes, a la model.x. now and also converted to an xr DataArray via model.xr().

Exploration results are all saved in hdf files and are also accessible via exploration.results and a summary accessible as a pandas DataFrame via exploration.dfResults.

from neurolib.