def load_modelspecs(modelspecs, uris, IsReload=False, **context):
'''
i.e. Load a modelspec from a specific place. This is not
the same as reloading a model for later inspection; it would be more
appropriate when doing something complicated with several different
models.
'''
if not IsReload:
modelspecs = [load_resource(uri) for uri in uris]
return {'modelspecs': modelspecs}
def reload_model(model_uri):
'''
Reloads an xspec and modelspec that were saved in some directory somewhere.
This recreates the context that occurred during the fit.
Passes additional context {'IsReload': True}, which xforms should react to
if they are not intended to be run on a reload.
'''
xfspec_uri = model_uri + 'xfspec.json'
# TODO: instead of just reading the first modelspec, read ALL of the modelspecs
# I'm not sure how to know how many there are without a directory listing!
modelspec_uri = model_uri + 'modelspec.0000.json'
xfspec = load_resource(xfspec_uri)
modelspec = load_resource(modelspec_uri)
ctx, reloadlog = xforms.evaluate(xfspec, {
'IsReload': True,
'modelspecs': [modelspec]
})
return ctx
def _get_modelspecs(cellids, batch, modelname, multi='mean'):
filepaths = load_batch_modelpaths(batch,
modelname,
cellids,
eval_model=False)
speclists = []
for path in filepaths:
mspaths = []
path = path.replace('http://hyrax.ohsu.edu:3003/',
'/auto/data/nems_db/')
if get_setting('NEMS_RESULTS_DIR').startswith("/Volumes"):
path = path.replace('/auto/', '/Volumes/')
for file in os.listdir(path):
if file.startswith("modelspec"):
mspaths.append(os.path.join(path, file))
speclists.append([load_resource(p) for p in mspaths])
modelspecs = []
for m in speclists:
if len(m) > 1:
if multi == 'first':
this_mspec = m[0]
elif multi == 'all':
this_mspec = m
elif multi == 'mean':
stats = ms.summary_stats(m)
temp_spec = copy.deepcopy(m[0])
phis = [m['phi'] for m in temp_spec]
for p in phis:
for k in p:
for s in stats:
if s.endswith('--' + k):
p[k] = stats[s]['mean']
for m, p in zip(temp_spec, phis):
m['phi'] = p
this_mspec = temp_spec
else:
log.warning(
"Couldn't interpret <multi> parameter. Got: %s,\n"
"Expected one of: 'mean, first, random, all'.\n"
"Using first modelspec instead.", multi)
this_mspec = m[0]
else:
this_mspec = m[0]
modelspecs.append(ms.ModelSpec([this_mspec]))
return modelspecs
def get_preview():
"""Queries the database for the filepath to the preview image
for the selected cell, batch and model combination(s)
"""
session = Session()
Results = Tables()['Results']
# Only get the numerals for the selected batch, not the description.
bSelected = request.args.get('bSelected', type=str)[:3]
cSelected = request.args.getlist('cSelected[]')
mSelected = request.args.getlist('mSelected[]')
figurefile = None
path = (
session.query(Results)
.filter(Results.batch == bSelected)
.filter(Results.cellid.in_(cSelected))
.filter(Results.modelname.in_(mSelected))
.first()
)
if not path:
session.close()
return jsonify(image='missing preview')
else:
figurefile = str(path.figurefile)
session.close()
# Another temporary compatibility hack to convert
# s3://... to https://
if figurefile.startswith('s3'):
prefix = 'https://s3-us-west2.amazonaws.com'
parsed = urlparse(figurefile)
bucket = parsed.netloc
path = parsed.path
figurefile = prefix + '/' + bucket + '/' + path
# TODO: this should eventually be the only thing that gets
# called - above try/except ugliness is temporary for
# backwards compatibility
image_bytes = load_resource(figurefile)
b64img = str(b64encode(image_bytes))[2:-1]
return jsonify(image=b64img)
def load_xform(uri):
'''
Loads and returns xform saved as a JSON.
'''
xform = load_resource(uri)
return xform