def spike_clusters_into_kwik(scname, kwikname, clustering_name):
try:
print("Loading {0}".format(scname))
sc = np.loadtxt(scname, dtype=int) - 1
print("Loaded {0} spikes".format(len(sc)))
except(IOError, OSError) as e:
print("Error opening file: {1}".format(e))
return
model = KwikModel(kwikname)
print("Adding {0} into {1}, clustering {2}".format(sys.argv[1], sys.argv[2], sys.argv[3]))
try:
model.add_clustering(clustering_name, sc)
except ValueError:
print("Overwriting old clustering!")
time.sleep(5)
# Hack to switch then overwrite clustering...
model.add_clustering('123_interim_temp', sc)
model.clustering = '123_interim_temp'
model.delete_clustering(clustering_name)
model.copy_clustering('123_interim_temp', clustering_name)
def spike_clusters_into_kwik(scname, kwikname, clustering_name):
try:
print("Loading {0}".format(scname))
sc = np.loadtxt(scname, dtype=int) - 1
print("Loaded {0} spikes".format(len(sc)))
except (IOError, OSError) as e:
print("Error opening file: {1}".format(e))
return
model = KwikModel(kwikname)
print("Adding {0} into {1}, clustering {2}".format(sys.argv[1],
sys.argv[2],
sys.argv[3]))
try:
model.add_clustering(clustering_name, sc)
except ValueError:
print("Overwriting old clustering!")
time.sleep(5)
# Hack to switch then overwrite clustering...
model.add_clustering('123_interim_temp', sc)
model.clustering = '123_interim_temp'
model.delete_clustering(clustering_name)
model.copy_clustering('123_interim_temp', clustering_name)
