0.1.179
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		| @@ -1,7 +1,7 @@ | ||||
| [metadata] | ||||
| # replace with your username: | ||||
| name = guan | ||||
| version = 0.1.178 | ||||
| version = 0.1.179 | ||||
| author = guanjihuan | ||||
| author_email = guanjihuan@163.com | ||||
| description = An open source python package | ||||
|   | ||||
| @@ -1,6 +1,6 @@ | ||||
| Metadata-Version: 2.4 | ||||
| Name: guan | ||||
| Version: 0.1.178 | ||||
| Version: 0.1.179 | ||||
| Summary: An open source python package | ||||
| Home-page: https://py.guanjihuan.com | ||||
| Author: guanjihuan | ||||
|   | ||||
| @@ -101,6 +101,20 @@ def generate_random_int_number_for_a_specific_seed(seed=0, x_min=0, x_max=10): | ||||
|     rand_num = np.random.randint(x_min, x_max) # 左闭右开[x_min, x_max) | ||||
|     return rand_num | ||||
|  | ||||
| # 使用Numpy库计算总体标准差 | ||||
| def standard_deviation(data_array): | ||||
|     import numpy as np | ||||
|     std_result = np.std(data_array) | ||||
|     return std_result | ||||
|  | ||||
| # 使用公式计算总体标准差 | ||||
| def standard_deviation_with_formula(data_array): | ||||
|     import numpy as np | ||||
|     averaged_data = sum(data_array)/len(data_array) | ||||
|     averaged_squared_data = sum(np.array(data_array)**2)/len(data_array) | ||||
|     std_result = np.sqrt(averaged_squared_data-averaged_data**2) | ||||
|     return std_result | ||||
|  | ||||
| # 获取两个模式之间的字符串 | ||||
| def get_string_between_two_patterns(original_string, start, end, include_start_and_end=0): | ||||
|     import re | ||||
|   | ||||
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