Allow absolute cosine similarity

[shntnu]

Sometimes both, strong positive and strong negative correlations are meaningful, so we should allow for that.

One way to do this is to add a boolean absolute_value argument to pairwise_cosine

copairs/src/copairs/compute.py

Lines 65 to 69 in c10c93e

	def pairwise_cosine(x_sample: np.ndarray, y_sample: np.ndarray) -> np.ndarray:
	x_norm = x_sample / np.linalg.norm(x_sample, axis=1)[:, np.newaxis]
	y_norm = y_sample / np.linalg.norm(y_sample, axis=1)[:, np.newaxis]
	c_sim = np.sum(x_norm * y_norm, axis=1)
	return c_sim

def pairwise_cosine(x_sample: np.ndarray, y_sample: np.ndarray, absolute_value: bool = False) -> np.ndarray:
    x_norm = x_sample / np.linalg.norm(x_sample, axis=1)[:, np.newaxis]
    y_norm = y_sample / np.linalg.norm(y_sample, axis=1)[:, np.newaxis]
    c_sim = np.sum(x_norm * y_norm, axis=1)
    if absolute_value:
        c_sim = np.abs(c_sim)
    return c_sim

[shntnu]

One way to do this is to add a boolean absolute_value argument to pairwise_cosine

Is that reasonable?