def main2(): np.set_printoptions(suppress=True) data = tool.my_data("D:/pythonWorkspace/data/iris.csv")[50:150] dist = tool.cal_dist(np.array(data).reshape(100, 4)) #降维 V = np.real(mds.MDS(dist, 2)).tolist() new_dist = tool.cal_dist(np.array(V).reshape(100, 2)) E = tool.k_edge(0.5, new_dist) graph_data = (V, E) graph = FruchtermannReingold('', graph_data[0], graph_data[1], 30, 5, 0.5, 4, 0.02) #新的数据 value = graph.draw() print(value)
def main2(): np.set_printoptions(suppress=True) data = tool.my_data("D:/pythonWorkspace/data/iris.csv")[50:150] dist = tool.cal_dist(np.array(data).reshape(100, 4)) #降维 V = np.real(mds.MDS(dist, 2)).tolist() new_dist = tool.cal_dist(np.array(V).reshape(100, 2)) # print(new_dist[:9:, :9:]-dist[:9:, :9:]) E = tool.k_edge(0.5, new_dist) graph_data = (V, E) graph = FruchtermannReingold('', graph_data[0], graph_data[1], 30, 5, 0.5, 4, 0.02) #新的数据 value = graph.draw().tolist() # 计算各个特征的边界值 feature1 = [x[0] for x in value] feature2 = [x[1] for x in value] feature1_border = km.kmeans_border(km.kmeans_class(np.array(feature1).reshape(-1, 1), 2)) feature2_border = km.kmeans_border(km.kmeans_class(np.array(feature2).reshape(-1, 1), 2))
def read_graph_data(k, dir): V = tool.my_data(dir) E = tool.my_k_edge(k, dir) return (V, E)