根据轨迹离散分布生成的数学 生成 # 参考文档 https://www.jianshu.com/p/3f968958af5a 成功率很高 90% 往上 :param distance: 缺口位置 :param seconds: 时间 :param ease_func: 生成函数 :return: 轨迹数组
(distance)
| 1124 | |
| 1125 | |
| 1126 | def get_generate_tracks(distance): |
| 1127 | """ |
| 1128 | 根据轨迹离散分布生成的数学 生成 # 参考文档 https://www.jianshu.com/p/3f968958af5a |
| 1129 | 成功率很高 90% 往上 |
| 1130 | :param distance: 缺口位置 |
| 1131 | :param seconds: 时间 |
| 1132 | :param ease_func: 生成函数 |
| 1133 | :return: 轨迹数组 |
| 1134 | """ |
| 1135 | distance += 20 |
| 1136 | tracks = [0] |
| 1137 | offsets = [0] |
| 1138 | seconds = random.randint(2,4) |
| 1139 | for t in np.arange(0.0, seconds, 0.1): |
| 1140 | offset = round((1 - pow(1 - (t / seconds), 4)) * distance) |
| 1141 | tracks.append(offset - offsets[-1]) |
| 1142 | offsets.append(offset) |
| 1143 | tracks.extend([-3, -2, -3, -2, -2, -2, -2, -1, -0, -1, -1, -1]) |
| 1144 | return tracks |
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