November 2022
Intermediate to advanced
392 pages
10h 8m
Chinese
Content preview from Python算法交易
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Python
、
NumPy
、
matplotlib
和
pandas
｜
351
使用
NumPy
通用函数对
Python
浮点对象进行列表推导。
使用数学函数对
Python
浮点对象进行列表推导。
另一方面，在
ndarray
对象上使用来自
NumPy
的向量化操作比上述两种使用
list
对
象作为结果的替代方法更快。然而，速度优势通常以更大甚至巨大的内存占用为代
价。
In [111]: %time a = np.sin(np.arange(1000000))
CPU times: user 20.7 ms, sys: 5.32 ms, total: 26 ms
Wall time: 24.6 ms
In [112]: import sys
In [113]: sys.getsizeof(a)
Out[113]: 8000096
In [114]: a.nbytes
Out[114]: 8000000
使用
NumPy
对正弦值进行向量化计算，通常要快得多。
导入
sys
模块，包含很多系统相关的功能。
显示
a
对象在内存中的大小。
显示用于存储
a
对象中数据的字节数。
向量化有时是编写简洁代码的一种非常有用的方法，它通常也比
Python
代码快得多。但是，请注意可能在许多与金融相关的场景中产生的向
量化内存占用问题。通常，有可用的替代算法实现，它们内存效率更
高，并且通过使用
Numba
或
Cython
等性能库，甚至可以更快。参见
Hilpisch
（
2018
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