private void createLinks()

in commons-math-neuralnet/src/main/java/org/apache/commons/math4/neuralnet/twod/NeuronSquareMesh2D.java [463:593]
114 lines of code
46 McCabe index (conditional complexity)

    private void createLinks() {
        // "linkEnd" will store the identifiers of the "neighbours".
        final List<Long> linkEnd = new ArrayList<>();
        final int iLast = numberOfRows - 1;
        final int jLast = numberOfColumns - 1;
        for (int i = 0; i < numberOfRows; i++) {
            for (int j = 0; j < numberOfColumns; j++) {
                linkEnd.clear();

                switch (neighbourhood) {

                case MOORE:
                    // Add links to "diagonal" neighbours.
                    if (i > 0) {
                        if (j > 0) {
                            linkEnd.add(identifiers[i - 1][j - 1]);
                        }
                        if (j < jLast) {
                            linkEnd.add(identifiers[i - 1][j + 1]);
                        }
                    }
                    if (i < iLast) {
                        if (j > 0) {
                            linkEnd.add(identifiers[i + 1][j - 1]);
                        }
                        if (j < jLast) {
                            linkEnd.add(identifiers[i + 1][j + 1]);
                        }
                    }
                    if (wrapRows) {
                        if (i == 0) {
                            if (j > 0) {
                                linkEnd.add(identifiers[iLast][j - 1]);
                            }
                            if (j < jLast) {
                                linkEnd.add(identifiers[iLast][j + 1]);
                            }
                        } else if (i == iLast) {
                            if (j > 0) {
                                linkEnd.add(identifiers[0][j - 1]);
                            }
                            if (j < jLast) {
                                linkEnd.add(identifiers[0][j + 1]);
                            }
                        }
                    }
                    if (wrapColumns) {
                        if (j == 0) {
                            if (i > 0) {
                                linkEnd.add(identifiers[i - 1][jLast]);
                            }
                            if (i < iLast) {
                                linkEnd.add(identifiers[i + 1][jLast]);
                            }
                        } else if (j == jLast) {
                            if (i > 0) {
                                linkEnd.add(identifiers[i - 1][0]);
                            }
                            if (i < iLast) {
                                linkEnd.add(identifiers[i + 1][0]);
                            }
                        }
                    }
                    if (wrapRows &&
                        wrapColumns) {
                        if (i == 0 &&
                            j == 0) {
                            linkEnd.add(identifiers[iLast][jLast]);
                        } else if (i == 0 &&
                                   j == jLast) {
                            linkEnd.add(identifiers[iLast][0]);
                        } else if (i == iLast &&
                                   j == 0) {
                            linkEnd.add(identifiers[0][jLast]);
                        } else if (i == iLast &&
                                   j == jLast) {
                            linkEnd.add(identifiers[0][0]);
                        }
                    }

                    // Case falls through since the "Moore" neighbourhood
                    // also contains the neurons that belong to the "Von
                    // Neumann" neighbourhood.

                    // fallthru (CheckStyle)
                case VON_NEUMANN:
                    // Links to preceding and following "row".
                    if (i > 0) {
                        linkEnd.add(identifiers[i - 1][j]);
                    }
                    if (i < iLast) {
                        linkEnd.add(identifiers[i + 1][j]);
                    }
                    if (wrapRows) {
                        if (i == 0) {
                            linkEnd.add(identifiers[iLast][j]);
                        } else if (i == iLast) {
                            linkEnd.add(identifiers[0][j]);
                        }
                    }

                    // Links to preceding and following "column".
                    if (j > 0) {
                        linkEnd.add(identifiers[i][j - 1]);
                    }
                    if (j < jLast) {
                        linkEnd.add(identifiers[i][j + 1]);
                    }
                    if (wrapColumns) {
                        if (j == 0) {
                            linkEnd.add(identifiers[i][jLast]);
                        } else if (j == jLast) {
                            linkEnd.add(identifiers[i][0]);
                        }
                    }
                    break;

                default:
                    throw new IllegalStateException(); // Cannot happen.
                }

                final Neuron aNeuron = network.getNeuron(identifiers[i][j]);
                for (final long b : linkEnd) {
                    final Neuron bNeuron = network.getNeuron(b);
                    // Link to all neighbours.
                    // The reverse links will be added as the loop proceeds.
                    network.addLink(aNeuron, bNeuron);
                }
            }
        }
    }