Unseeded NTAC example

This example shows how to use NTAC in unseeded mode, with the Flywire dataset.

import ntac
from ntac import Ntac, FAFBData
import os
from os.path import join
import numpy as np



# first download the flywire data we'll need for this example. This will be cached in ~/.ntac/flywire_data
ntac.download_flywire_data(verbose=True)


# This is where the data lives:
base_path = join(os.path.expanduser("~"), ".ntac")


# now we decide which part of the flywire dataset we want to use:
side = "left"
gender = "female"
area = "ol_intrinsic" #we pick a small area to speed up the example

data_path = join(base_path,f"flywire_data/dynamic_data/{gender}_brain/{area}")
edges_file = f"{data_path}/{side}_edges.csv"
types_file = f"{data_path}/{side}_clusters.csv"

data = FAFBData(edges_file=edges_file, types_file=types_file)

#No need to pass in labels, as we will be using the unseeded method
nt = Ntac(data = data, labels = None, verbose=True)

#print num unique labels
print(f"Number of unique labels: {data.unique_labels.shape[0]}")
nt.solve_unseeded(
    max_k=230
)

nt.map_partition_to_gt_labels(data.labels)
partition = nt.get_partition()
metrics = data.get_metrics(partition, np.array(range(data.n)), data.labels)
print(f"Accuracy: {metrics['acc']:.3f} ARI: {metrics['ari']:.3f}", f"Weighted F1: {metrics['f1']:.3f}")