async def do_cluster():
app_state.generator = ClusterGenerator(dsm_mat=app_state.dsm)
c_orig = app_state.generator.cluster(app_state.dsm)
total_coord_cost = app_state.generator.total_coord_cost
cost_history = app_state.generator.cost_history
c = ClusterMatrix.reorder(c_orig)
new_dsm = DSMMatrix.reorder_by_cluster(app_state.dsm, c)
d_new_g = DSMMatrix.place_diag(new_dsm)
app_state.cluster_result = c
app_state.dsm_result = d_new_g
app_state.dsm_annotated = DSMMatrix.annotate_clusters(d_new_g, c)
return {
"dsm": app_state.dsm_result.tojson(),
"labels": app_state.dsm_result.labels,
"cluster": app_state.cluster_result.tojson(),
"dsm_a": app_state.dsm_annotated.tojson(),
}
def test_place_diag(self):
d_mat = np.array([[0, 0, 1, 0, 0, 1, 0, 1], [1, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 1, 0, 0, 0, 1], [0, 0, 1, 0, 0, 0, 0, 1],
[0, 0, 0, 0, 0, 1, 0, 0], [0, 1, 0, 0, 0, 0, 1, 0],
[1, 0, 0, 1, 0, 0, 0, 0], [0, 0, 1, 0, 0, 0, 0, 0]])
d_list = ["a", "b", "c", "d", "e", "f", "g", "h"]
d = DSMMatrix(d_mat, activity_labels=d_list)
d_diag = DSMMatrix.place_diag(d)
d_mat_result = np.array([[1, 0, 1, 0, 0, 1, 0, 1],
[1, 1, 0, 0, 0, 0, 0, 0],
[0, 0, 1, 1, 0, 0, 0, 1],
[0, 0, 1, 1, 0, 0, 0, 1],
[0, 0, 0, 0, 1, 1, 0, 0],
[0, 1, 0, 0, 0, 1, 1, 0],
[1, 0, 0, 1, 0, 0, 1, 0],
[0, 0, 1, 0, 0, 0, 0, 1]])
d_result = DSMMatrix(d_mat_result, activity_labels=d_list)
assert np.equal(d_diag.mat, d_result.mat).all()