import matplotlib.pyplot as plt
import numpy as np
from random import uniform, seed, shuffle ,sample
import math
import logging

from random import random

'''JY_Toolkit.py'''
class Jy_makeDataset(object):

def random_state(random_seed):    seed(int(random_seed))def draw_HalfMoon(n_sample: int = 1000,       # 样本点个数，两个分类一共 n_sample                  w: float = 1,              # 半月的线宽                  radius: float = 4,         # 半月的半径                  hor_distance: float = 4,   # Horizontal direction distance for two point                  ver_distance: float = 0,   # Vertical direction distance for two point                  slope: float = 0,          # 半月歪斜的角度  [0 ~ 180]                  positive_val: int = 1,                  negative_val: int = -1,                  ):    slope %= 180            # make the `slope`  between 0 and 180    # 将 n_sample 和样本分为两类每个样本 n_sample / 2 类    each_m = n_sample//2    # circle origin point of positive moon [x , y]    p_origin = [1 + w/2 + radius, 1 + w/2 + radius + ver_distance]    # circle origin point of negative moon [x , y]    n_origin = [p_origin[0] + hor_distance, p_origin[1] - ver_distance]    # product positive point    p_sample = []    n_sample = []    for i in range(each_m):        # Randomly generate l        temp_l = radius + uniform(-(w/2), w/2)        # Randomly generate angle i.e. theta        temp_angle = uniform(slope, slope + 180)        point_x = p_origin[0] + temp_l*math.cos(math.pi/180*temp_angle)        point_y = p_origin[1] + temp_l*math.sin(math.pi/180*temp_angle)        p_sample.append([point_x, point_y, positive_val])    for i in range(each_m):        # Randomly generate l        temp_l = radius + uniform(-(w/2), w/2)        # Randomly generate angle i.e. theta , but the angle of negative point should between `slope + 180` and `slope + 360`        temp_angle = uniform(slope + 180, slope + 360)        point_x = n_origin[0] + temp_l*math.cos(math.pi/180*temp_angle)        point_y = n_origin[1] + temp_l*math.sin(math.pi/180*temp_angle)        n_sample.append([point_x, point_y, negative_val])    sample_points = p_sample + n_sample    shuffle(sample_points)    sample_points = np.array(sample_points)    return sample_points[:, 0:2], sample_points[:, 2]pass

class Jy_dataSetProcess(object):

def Jy_train_test_split(X,                        y,                        test_size : 0.2,                        ):    data = np.column_stack((X,y))    if test_size >=[PerfectMoney下载](https://www.gendan5.com/wallet/PerfectMoney.html) 1 and test_size <= 0:        logging.exception('test_size must be greater than 0 less than 1, we will assign test_size value of 0.2')        test_size = 0.2    sample_count = int(len(data)*test_size)    '''    拆散思路：    先将输出的数据集打乱，而后取前 test_size 局部为测试集，后局部为训练集    '''    shuffle(data)    X_test = data[0:sample_count-1]    X_train = data[sample_count:]    return X_train[:,0:2],  X_test[:,0:2] ,X_train[:,2] , X_test[:,2]pass

if name == '__main__':

random_seed = 52Jy_makeDataset.random_state(random_seed)np_data, label = Jy_makeDataset.draw_HalfMoon(n_sample=2000)p_point_x1 = [np_data[i][0] for i in range(len(np_data)) if label[i] == 1]p_point_x2 = [np_data[i][1] for i in range(len(np_data)) if label[i] == 1]n_point_x1 = [np_data[i][0] for i in range(len(np_data)) if label[i] == -1]n_point_x2 = [np_data[i][1] for i in range(len(np_data)) if label[i] == -1]fig = plt.figure(num="HalfMoons", figsize=(8, 8))ax1 = fig.add_subplot(111)ax1.scatter(p_point_x1, p_point_x2, c='red')ax1.scatter(n_point_x1, n_point_x2, c='blue')plt.show()print(np_data)