def driver(host,
token,
col,
exp,
z_range,
y_range,
x_range,
path="./results/"):
print("Generating PyMeda Plots...")
info = locals()
data_dict = get_data(host, token, col, exp, z_range, y_range, x_range)
results = run_nomads(data_dict)
results_key = "_".join(["nomads", col, exp, "z", str(z_range[0]), str(z_range[1]), "y", \
str(y_range[0]), str(y_range[1]), "x", str(x_range[0]), str(x_range[1])])
pickle.dump(results, open(path + results_key + ".pkl", "wb"))
print("Saved pickled results (np array) {} in {}".format(
results_key, path))
title = "PyMeda Plots on {}".format(exp)
pymeda_driver.pymeda_pipeline(results, data_dict, title=title, path=path)
upload_results(path, results_key)
return info, results
def driver(bucket, host, token, col, exp, z_range, y_range, x_range, path = "./results/"):
print("Starting Nomads Unsupervised...")
results_key = "_".join(["nomads-unsupervised", col, exp, "z", str(z_range[0]), str(z_range[1]), "y", \
str(y_range[0]), str(y_range[1]), "x", str(x_range[0]), str(x_range[1])])
info = locals()
try:
data_dict = get_data(host, token, col, exp, z_range, y_range, x_range)
except Exception as e:
logging.info("Failed to pull data from BOSS. Run with smaller cube of data or check if BOSS is online.")
logging.info(e)
logging.info("Exiting...")
upload_results(bucket, path, results_key)
print_exc()
return
try:
results = run_nomads(data_dict)
except Exception as e:
logging.info("Failed to run Nomads-Unsupervised detection algorithm on data.")
logging.info(e)
logging.info("Exiting...")
upload_results(bucket, path, results_key)
print_exc()
return
results = results.astype(np.uint8)
np.putmask(results, results, 255)
pickle.dump(results, open(path + "nomads-unsupervised-predictions" + ".pkl", "wb"))
print("Saved pickled results (np array) {} in {}".format("nomads-unsupervised-predictions.pkl", path))
norm_data = load_and_preproc(data_dict)
try:
pymeda_driver.pymeda_pipeline(results, norm_data, title = "PyMeda Plots on All Predicted Synapses", path = path)
except:
logging.info("Failed to generate plots for all predictions. No synapses detected.")
print("Uploading results...")
#results = pickle.load(open("./results/nomads-unsupervised-predictions.pkl", "rb"))
try:
boss_links = boss_push(token, "collman_nomads", "nomads_predictions", z_range, y_range, x_range, {results_key: results}, results_key)
with open('results/NDVIS_links.csv', 'w') as csv_file:
writer = csv.writer(csv_file)
for key, value in boss_links.items():
writer.writerow([key, value])
except Exception as e:
logging.info("Failed to push results to BOSS. Check permissions and Boss online status.")
logging.info(e)
logging.info("Finished job, uploading results. END")
upload_results(bucket, path, results_key)
return info, results, boss_links
def driver(host,
token,
col,
exp,
z_range,
y_range,
x_range,
path="./results/"):
print("Starting Nomads Unsupervised...")
info = locals()
data_dict, voxel_size = get_data(host, token, col, exp, z_range, y_range,
x_range)
results = run_nomads(data_dict)
results = results.astype(np.uint8)
np.putmask(results, results, 255)
results_key = "_".join(["nomads-unsupervised", col, exp, "z", str(z_range[0]), str(z_range[1]), "y", \
str(y_range[0]), str(y_range[1]), "x", str(x_range[0]), str(x_range[1])])
pickle.dump(results,
open(path + "nomads-unsupervised-predictions" + ".pkl", "wb"))
print("Saved pickled results (np array) {} in {}".format(
"nomads-unsupervised-predictions.pkl", path))
print("Generating PyMeda Plots...")
norm_data = load_and_preproc(data_dict)
try:
pymeda_driver.pymeda_pipeline(
results,
norm_data,
title="PyMeda Plots on All Predicted Synapses",
path=path)
except:
print(
"Not generating plots for all synapses, no predictions classified as Gaba"
)
print("Uploading results...")
#results = pickle.load(open("./results/nomads-unsupervised-predictions.pkl", "rb"))
boss_links = boss_push(token, "collman_nomads", "nomads_predictions",
z_range, y_range, x_range, {results_key: results},
results_key)
with open('results/NDVIS_links.csv', 'w') as csv_file:
writer = csv.writer(csv_file)
for key, value in boss_links.items():
writer.writerow([key, value])
upload_results(path, results_key)
return info, results, boss_links
def driver(bucket,
host,
token,
col,
exp,
z_range,
y_range,
x_range,
path="./results/"):
print("Starting Nomads Classifier...")
results_key = "_".join(["nomads-classifier", col, exp, "z", str(z_range[0]), str(z_range[1]), "y", \
str(y_range[0]), str(y_range[1]), "x", str(x_range[0]), str(x_range[1])])
info = locals()
try:
data_dict = get_data(host, token, col, exp, z_range, y_range, x_range)
except Exception as e:
logging.info(
"Failed to pull data from BOSS. Run with smaller cube of data or check if BOSS is online."
)
logging.info(e)
logging.info("Exiting...")
upload_results(bucket, path, results_key)
print_exc()
return
try:
results = run_nomads(data_dict)
except Exception as e:
logging.info(
"Failed to run Nomads-Unsupervised detection algorithm on data.")
logging.info(e)
logging.info("Exiting...")
upload_results(bucket, path, results_key)
print_exc()
return
results = results.astype(np.uint8)
np.putmask(results, results, 255)
pickle.dump(results,
open(path + "nomads-unsupervised-predictions" + ".pkl", "wb"))
print("Saved pickled predictions (np array) {} in {}".format(
"nomads-unsupervised-predictions.pkl", path))
norm_data = load_and_preproc(data_dict)
try:
#results = pickle.load(open("results/nomads-unsupervised-predictions.pkl", "rb"))
connected_components, label_vol = pymeda_driver.label_predictions(
results)
synapse_centroids = pymeda_driver.calculate_synapse_centroids(
connected_components)
class_list = gaba_classifier_pipeline(data_dict, synapse_centroids)
no_pred_vol, non_gaba_vol, gaba_vol = split_vol_by_id(
label_vol, class_list, 3)
except Exception as e:
logging.info("Failed to run Nomads-Classfier algorithm on data.")
logging.info(e)
logging.info("Exiting...")
upload_results(bucket, path, results_key)
print_exc()
return
gaba_vol = gaba_vol.astype(np.uint8)
np.putmask(gaba_vol, gaba_vol, 255)
non_gaba_vol = non_gaba_vol.astype(np.uint8)
np.putmask(non_gaba_vol, non_gaba_vol, 255)
pickle.dump(gaba_vol, open(path + "gaba" + ".pkl", "wb"))
print("Saved pickled gaba (np array) {} in {}".format("gaba.pkl", path))
pickle.dump(non_gaba_vol, open(path + "non_gaba" + ".pkl", "wb"))
print("Saved pickled gaba (np array) {} in {}".format(
"non_gaba.pkl", path))
try:
pymeda_driver.pymeda_pipeline(
results,
norm_data,
title="PyMeda Plots on All Predicted Synapses",
path=path)
except:
logging.info(
"Failed to generate plots for all predictions. No synapses detected."
)
try:
pymeda_driver.pymeda_pipeline(
non_gaba_vol,
norm_data,
title="PyMeda Plots on Predicted NonGaba Synapses",
path=path)
except:
logging.info(
"PyMeda failed to generate plots for NonGaba. No Non-Gaba synapses found."
)
try:
pymeda_driver.pymeda_pipeline(
gaba_vol,
norm_data,
title="PyMeda Plots on Predicted Gaba Synapses",
path=path)
except:
logging.info(
"PyMeda failed to generate plots for Gaba. No Gaba synapses found."
)
print("Uploading results...")
results_dict = {"All": results, "Gaba": gaba_vol, "NonGaba": non_gaba_vol}
try:
boss_links = boss_push(token, "collman_nomads", "nomads_predictions",
z_range, y_range, x_range, results_dict,
results_key)
with open('results/NDVIS_links.csv', 'w') as csv_file:
writer = csv.writer(csv_file)
for key, value in boss_links.items():
writer.writerow([key, value])
except Exception as e:
logging.info(
"Failed to push results to BOSS. Check permissions and Boss online status."
)
logging.info(e)
logging.info("Finished, uploading results. END")
upload_results(bucket, path, results_key)
return info, results, boss_links