ax = plt.subplot(3, 1, 3)
plt.imshow(raster[:, 0, :])
plt.tight_layout()
# see what a "traditional" NEMS model looks like
nems_modelname = "ozgf.fs100.ch18-ld-sev_dlog-wc.18x2.g-do.2x15-lvl.1-dexp.1_init-basic"
xfspec, ctx = load_model_xform(cellid, batch=batch, modelname=nems_modelname)
nplt.quickplot(ctx)
ex = gui.browse_xform_fit(ctx, xfspec)
##
batch, cellid = 308, 'AMT018a-09-1'
modelname = 'ozgf.fs100.ch18-ld-sev_dlog-wc.18x4.g-fir.2x15x2-relu.2-wc.2x1-lvl.1-dexp.1_init.tf.rb5-tf.n'
xfspec, ctx = fit_model_xform(cellid, batch=batch, modelname=modelname)
nplt.quickplot(ctx)
ex = gui.browse_xform_fit(ctx, xfspec)
###Plot complexity of model versus how effective it was
batch = 308
metric = 'r_test'
metric2 = 'n_parms'
metric3 = 'se_test'
query = "SELECT {0}, {1}, {2}, {3} FROM NarfResults WHERE batch = 308".format(
metric, metric2, metric3, 'modelname')
results = nd.pd_query(sql=query)
group = results.groupby('modelname')
mean_rtest = group.mean()
mean_rtest.plot(x='n_parms', y='r_test', kind='scatter', yerr='se_test')
log.info("Starting QUEUEID={}".format(queueid))
nd.update_job_start(queueid)
log.info("HOSTNAME={}".format(os.environ.get('HOSTNAME', 'unknown')))
if len(sys.argv) < 4:
print('syntax: fit_single cellid batch modelname')
exit(-1)
cellid = sys.argv[1]
batch = sys.argv[2]
modelname = sys.argv[3]
log.info("Running xform_helper.fit_model_xform({0},{1},{2})".format(
cellid, batch, modelname))
#savefile = nw.fit_model_xforms_baphy(cellid, batch, modelname, saveInDB=True)
savefile = xhelp.fit_model_xform(cellid, batch, modelname, saveInDB=True)
log.info("Done with fit.")
# Mark completed in the queue. Note that this should happen last thing!
# Otherwise the job might still crash after being marked as complete.
if db_exists & bool(queueid):
nd.update_job_complete(queueid)
if 'SLURM_JOB_ID' in os.environ:
# need to copy the job log over to the queue log dir
log_file_dir = Path.home() / 'job_history'
log_file = list(
log_file_dir.glob(
f'*jobid{os.environ["SLURM_JOB_ID"]}_log.out'))
if len(log_file) == 1:
batch = 320
# uncomment cell to analyze
#cellid = "NMK003c-02-1"
cellid = "NMK020c-29-1"
modelname = "psth.fs20.pup-ld-st.pup.fil-tar-psthfr.tar_stategain.S_jk.nf20.p-basic"
modelname2 = "psth.fs20.pup-ld-st.pup.fil0-tar-psthfr.tar_stategain.S_jk.nf20.p-basic"
browse_results = False
#save_file = xhelp.fit_model_xform(cellid, batch, modelname)
#xfspec, ctx = xhelp.load_model_xform(cellid, batch, modelname)
xfspec, ctx = xhelp.fit_model_xform(cellid,
batch,
modelname,
autoPlot=False,
returnModel=True)
xfspec2, ctx2 = xhelp.fit_model_xform(cellid,
batch,
modelname2,
autoPlot=False,
returnModel=True)
modelspec = ctx['modelspec']
modelspec2 = ctx2['modelspec']
val = ctx['val']
r = val['resp']
state_channels = val['state'].chans
file_epochs = r.epochs.loc[r.epochs.name.str.startswith("FILE")]
import nems import nems.xform_helper as xhelp modelname = 'ozgf.fs50.ch18.pop-loadpop.cc20-norm-pca.no-popev_wc.18x4R.g-fir.4x12xR-lvl.R-dexp.R_tfinit.n.lr1e3.et3-newtf.n.lr1e4' batch = 322 siteid = 'bbl086b' xf, ctx = xhelp.fit_model_xform(siteid, batch, modelname, returnModel=True)
# 100Hz, no pupil
recording_file = "TAR010c.NAT.fs100.ch18.tgz"
# MODEL SPEC
modelname = 'ld-sev_dlog-wc.18x1.g-fir.1x15-lvl.1-dexp.1_init-basic'
# 50Hz, pupil
#recording_file = "TAR010c.NAT.fs50.ch18.pup.tgz"
# MODEL SPEC
#modelname = 'ld-st.pup-tev_dlog-wc.18x1.g-fir.1x15-lvl.1-stategain.2-dexp.1_init.st-basic'
recording.get_demo_recordings(name=recording_file)
recording_uri = os.path.join(get_setting('NEMS_RECORDINGS_DIR'),
recording_file)
# run and return
xfspec, ctx = fit_model_xform(cellid,
batch,
modelname,
recording_uri=recording_uri,
returnModel=True)
ex = gui.browse_xform_fit(ctx, xfspec)
# run and save to database
#saveuri = fit_model_xform(cellid, batch, modelname, recording_uri=recording_uri, saveInDB=True)
# load previously saved
#xfspec, ctx = load_model_xform(cellid, batch, modelname)
#ex = gui.browse_xform_fit(ctx, xfspec)