有没有一种方法可以对代码进行矢量化或细胞化以填充熊猫数据帧中的numpy数组？

Question

我有熊猫数据框。

使用此数据帧的 start ， end 和 signal 列，我使用该信号从头到尾填充numpy数组值。

这是使用下面的apply和list理解的工作代码。

有没有一种方法可以对这一过程进行矢量化或细胞化？

import numpy as np
import pandas as pd
import time
import random


def f(start,end,signal,chrBasedSignalArray):
    chrBasedSignalArray[start:end]+=signal

def updateChrBasedSignalArray(data_row,chrBasedSignalArray):
    chrBasedSignalArray[data_row['start']:data_row['end']] += data_row['signal']

numberofRows=1000000
startList = random.sample(range(1, 240000000), numberofRows)
endList = [x+100 for x in startList]
signalList = [random.randrange(0,10) for i in range(numberofRows)]

df = pd.DataFrame({'chrom': ['chr1'] * numberofRows, 'start': startList, 'end':endList, 'signal':signalList})

print('##################################')
chrBasedSignalArray = np.zeros(240000000, dtype=np.float32)
print('Before np.sum(chrBasedSignalArray: %f' %np.sum(chrBasedSignalArray))
start_time = time.time()
[f(start,end,signal,chrBasedSignalArray) for start,end,signal in zip(df['start'],df['end'],df['signal'])]
print("--- %s seconds using list comprehension---" % ((time.time() - start_time)))
print('After np.sum(chrBasedSignalArray): %f' %np.sum(chrBasedSignalArray))
print('##################################')

print('##################################')
chrBasedSignalArray = np.zeros(240000000, dtype=np.float32)
print('Before np.sum(chrBasedSignalArray: %f' %np.sum(chrBasedSignalArray))
start_time = time.time()
df.apply(updateChrBasedSignalArray, chrBasedSignalArray=chrBasedSignalArray, axis=1)
print("--- %s seconds using apply---" % ((time.time() - start_time)))
print('After np.sum(chrBasedSignalArray): %f' %np.sum(chrBasedSignalArray))
print('##################################')