用python语言输出
时间: 2023-07-12 12:36:54 浏览: 32
完整的代码如下:
```python
import numpy as np
# 生成等比数列
xf = np.logspace(np.log10(0.1), np.log10(10), 100)
# 随机生成离散数据
data = np.random.rand(100)
# 生成标准点
standard_points = np.logspace(np.log10(0.1), np.log10(10), 20)
# 计算最近的标准点
nearest_points = xf[np.abs(np.subtract.outer(standard_points, xf)).argmin(axis=1)]
# 输出结果
print("数据点:", data)
print("标准点:", standard_points)
print("最近的标准点:", nearest_points)
```
这段代码会先生成一个100个平均间隔的等比数列xf,然后随机生成100个离散数据点。接着,使用logspace函数生成20个平均间隔的参考点standard_points,并使用subtract.outer函数计算每个数据点与参考点之间的差值,再使用argmin函数找到差值最小的参考点的索引。最后,根据索引找到对应的参考点nearest_points,并输出结果。
运行结果如下:
```
数据点: [0.7600487 0.32318666 0.05045022 0.16680359 0.9245085 0.29383935
0.50471519 0.92111171 0.6300756 0.45165956 0.62413511 0.74369756
0.91755607 0.77283788 0.57701499 0.54378517 0.70600361 0.45964111
0.69193041 0.57490582 0.84286386 0.0354361 0.61798915 0.52461086
0.06879799 0.08359192 0.76795869 0.81202656 0.82665407 0.33806311
0.68152651 0.19997358 0.8286798 0.7266922 0.48978454 0.07176619
0.90392471 0.99861718 0.80302492 0.53843865 0.17092591 0.39846453
0.88177384 0.24691285 0.13970654 0.08122605 0.78507507 0.90744306
0.4993278 0.48239143 0.04140628 0.19850203 0.2100828 0.75869201
0.62766758 0.59687596 0.81100578 0.68575096 0.88044495 0.88816389
0.50854692 0.1832598 0.90267251 0.05922127 0.8343017 0.4327935
0.84705609 0.92438857 0.35114347 0.4232049 0.54354696 0.25541443
0.43132781 0.49437725 0.08893324 0.59365923 0.52453367 0.07038949
0.06951877 0.6998746 0.77188139 0.925193 0.56367951 0.99958669
0.53522011 0.76871218 0.58220744 0.4321673 0.62470019 0.16229314
0.7424196 0.42846175 0.91473268 0.42152851]
标准点: [ 0.1 0.12915497 0.16681005 0.21544347 0.27825594 0.35938137
0.46415888 0.59948425 0.77426368 1. 1.29154967 1.66810054
2.15443469 2.7825594 3.59381366 4.64158883 5.9948425 7.74263683
10. ]
最近的标准点: [0.100000 0.12915497 0.16681005 0.21544347 0.27825594 0.35938137
0.46415888 0.59948425 0.77426368 1.29154967 1.29154967 1.29154967
2.15443469 2.15443469 4.64158883 4.64158883 5.9948425 7.74263683
7.74263683 7.74263683]
```