# shorthand for:
# ctx = {}
# for xfa in xfspec:
# ctx = xforms.evaluate_step(xfa, ctx)
if browse_results:
import nems.gui.editors as gui
ex = gui.browse_xform_fit(ctx, xfspec)
if save_results:
# ----------------------------------------------------------------------------
# SAVE YOUR RESULTS
# save results to file
destination = os.path.join(results_dir, str(batch), xforms.get_meta(ctx)['cellid'],
ms.get_modelspec_longname(ctx['modelspec']))
log.info('Saving modelspec(s) to {0} ...'.format(destination))
xforms.save_analysis(destination,
recording=ctx['rec'],
modelspec=ctx['modelspec'],
xfspec=xfspec,
figures=ctx['figures'],
log=log_xf)
# save summary of results to a database
log.info('Saving metadata to db ...')
modelspec = ctx['modelspec']
modelspec.meta['modelpath'] = destination
modelspec.meta['figurefile'] = destination + 'figure.0000.png'
nd.update_results_table(modelspec)
def test_get_meta(context):
m = xforms.get_meta(context)
def test_fit_performance(context):
# Note: will no longer pass if the modelspec setup in conftest changes.
m1 = np.round(xforms.get_meta(context)['r_test']*100)
m2 = np.array([47.0])
assert m1 == m2
def test_get_meta(context):
m = xf.get_meta(context)