Question

我尝试使用cython来提高循环的性能，但我正在运行在某些问题中声明了输入的类型。

如何在我的类型化结构中包含一个字段，该字符串可以是无论是“前线”还是“前线”。或者＆＃39;返回＆＃39;

我有np.recarray，如下所示（注意长度 recarray未知为编译时间）

import numpy as np
weights = np.recarray(4, dtype=[('a', np.int64),  ('b', np.str_, 5), ('c', np.float64)])
weights[0] = (0, "front", 0.5)
weights[1] = (0, "back", 0.5)
weights[2] = (1, "front", 1.0)
weights[3] = (1, "back", 0.0)

以及字符串列表和pandas.Timestamp

的输入

import pandas as pd
ts = pd.Timestamp("2015-01-01")
contracts = ["CLX16", "CLZ16"]

我正在尝试对以下循环进行cython化

def ploop(weights, contracts, timestamp):
    cwts = []
    for gen_num, position, weighting in weights:
        if weighting != 0:
            if position == "front":
                cntrct_idx = gen_num
            elif position == "back":
                cntrct_idx = gen_num + 1
            else:
                raise ValueError("transition.columns must contain "
                                 "'front' or 'back'")
            cwts.append((gen_num, contracts[cntrct_idx], weighting, timestamp))
    return cwts

我的尝试涉及在cython中输入weights输入作为结构，在文件struct_test.pyx中，如下所示

import numpy as np
cimport numpy as np


cdef packed struct tstruct:
    np.int64_t gen_num
    char[5] position
    np.float64_t weighting


def cloop(tstruct[:] weights_array, contracts, timestamp):
    cdef tstruct weights
    cdef int i
    cdef int cntrct_idx

    cwts = []
    for k in xrange(len(weights_array)):
        w = weights_array[k]
        if w.weighting != 0:
            if w.position == "front":
                cntrct_idx = w.gen_num
            elif w.position == "back":
                cntrct_idx = w.gen_num + 1
            else:
                raise ValueError("transition.columns must contain "
                                 "'front' or 'back'")
            cwts.append((w.gen_num, contracts[cntrct_idx], w.weighting,
                         timestamp))
    return cwts

但是我收到运行时错误，我认为这与错误相关 char[5] position。

import pyximport
pyximport.install()
import struct_test

struct_test.cloop(weights, contracts, ts)

ValueError: Does not understand character buffer dtype format string ('w')

另外，我有点不清楚如何输入contracts 为timestamp。

Answer 1

您的ploop（没有timestamp变量）会产生：

In [226]: ploop(weights, contracts)
Out[226]: [(0, 'CLX16', 0.5), (0, 'CLZ16', 0.5), (1, 'CLZ16', 1.0)]

没有循环的等效函数：

def ploopless(weights, contracts):
    arr_contracts = np.array(contracts) # to allow array indexing
    wgts1 = weights[weights['c']!=0]
    mask = wgts1['b']=='front'
    wgts1['b'][mask] = arr_contracts[wgts1['a'][mask]]
    mask = wgts1['b']=='back'
    wgts1['b'][mask] = arr_contracts[wgts1['a'][mask]+1]
    return wgts1.tolist()

In [250]: ploopless(weights, contracts)
Out[250]: [(0, 'CLX16', 0.5), (0, 'CLZ16', 0.5), (1, 'CLZ16', 1.0)]

我正在利用返回的元组列表与输入weight数组具有相同（int，str，int）布局的事实。所以我只是复制weights并替换b字段的选定值。

请注意，我在mask之前使用字段选择索引。布尔值mask生成一个副本，因此我们必须注意索引顺序。

我猜测无环阵列版本将与cloop（在真实数组上）及时竞争。 cloop中的字符串和列表操作可能会限制其加速。

Cython键入字符串列表

1 个答案: