X = np.array(...) # Shape: (Anzahl Atome x Raumdimensionen)
max_coords = np.array(...) # Shape: (Raumdimensionen)

# Ohne ausmultiplizieren
deltas = np.abs(X[None, :] - X[:, None])
torus_deltas = np.minimum(deltas, max_coords - deltas)
squared_distances = np.square(torus_deltas).sum(axis=-1)
distances = np.sqrt(squared_distances)

np.fill_diagonal(distances, np.inf)
mean_shortest_distance = distances.min(axis=1).mean()

name,x,y,z
Klaus,1.5,2,3
Peter,2,7.3,12
Günter,4,2,0.7

import numpy as np
import pandas as pd

def nearest_neighbour_torus(X, max_coords):
    deltas = np.abs(X[None, :] - X[:, None])
    torus_deltas = np.minimum(deltas, max_coords - deltas)
    squared_distances = np.square(torus_deltas).sum(axis=-1)
    np.fill_diagonal(squared_distances, np.inf)
    return np.sqrt(squared_distances.min(-1))

atoms = pd.read_csv('atoms.csv', index_col='name')
max_coords = np.array([10, 12, 17])

atoms['distance'] = nearest_neighbour_torus(atoms.values, max_coords)

print(atoms)
print("mean distance:", atoms.distance.mean())

          x    y     z  distance
name                            
Klaus   1.5  2.0   3.0  3.397058
Peter   2.0  7.3  12.0  8.036168
Günter  4.0  2.0   0.7  3.397058

mean distance: 4.943427780576996

In [8]: np.newaxis is None
Out[8]: True

void communication_thread() {
    socket.connect(address);

    while(running) {
        // incoming messages
        poll(socket, wait=100ms);
        if (socket.has_message_waiting) {
            message = socket.receive();
            if (message.command == DO_STUFF) {
                for (listener in listeners) {
                    listener.notify(message.data);
                }
            }
        }

        // outgoing messages
        while (to_send = message_queue.pop()) {
            socket.send(to_send);
        }
    }

    socket.close();
}