import numpy as np

META = {
    'name': 'laplacian_coherence_graph',
    'domain': 'graph-nn',
    'description': 'Synthetic weakly coupled two-community graph node classification.'
}

def get_dataset(seed, n_train, n_test):
    rng = np.random.default_rng(seed)
    n = n_train + n_test
    y = (np.arange(n) >= n // 2).astype(np.int64)
    x = rng.normal(0, .7, (n, 8)).astype(np.float32)
    s = 2*y - 1
    x[:, 0] = .18*s
    x[:, 1] = .12*s
    flip = rng.random(n) < .12
    y[flip] = 1 - y[flip]
    return {'xtr': x[:n_train], 'ytr': y[:n_train],
            'xte': x[n_train:], 'yte': y[n_train:],
            'task': 'classification', 'metric': 'err', 'out_dim': 2}