numpy.loadtxt跳过多行 [英] numpy.loadtxt Skipping multiple rows

问题描述

我相信该主题的标题可以解释我所寻找的内容.我很想知道跳过多行的语法是什么；我似乎在任何地方都找不到这样的信息.

I believe the title of this thread explains what I am looking for. I am curious to know what the syntax is for skipping multiple rows; I can't seem to find such information anywhere.

推荐答案

使用help(np.loadtxt).您会发现skiprows参数将允许您跳过前N行:

Use help(np.loadtxt). You'll find the skiprows parameter will allow you to skip the first N rows:

In [1]: import numpy as np

In [2]: help(np.loadtxt)
Help on function loadtxt in module numpy.lib.npyio:

loadtxt(fname, dtype=<type 'float'>, comments='#', delimiter=None, converters=None, skiprows=0, usecols=None, unpack=False, ndmin=0)
    ...
    skiprows : int, optional
        Skip the first `skiprows` lines; default: 0.

因此，您要跳过N行

np.loadtxt(fname, skiprows=N)

---

如果您需要过滤除 first N行之外的其他行，请使用np.genfromtxt，它可以使用一个生成字符串的迭代器作为其第一个参数:

---

If you need to filter rows other than the first N rows, use np.genfromtxt which can take an iterator which yields strings as its first argument:

with open(filename, 'r') as f:
    lines = (line for line in f if predicate(line))
    arr = np.genfromtxt(lines)

---

要跳过中间的一系列行，例如第47--50行，可以使用itertools这样:

---

To skip a sequence of rows in the middle, such as rows 47--50, you could use itertools like this:

import itertools as IT

with open(filename, 'r') as f:
    lines = IT.chain(IT.islice(f, 46), IT.islice(f, 4, None))
    arr = np.genfromtxt(lines)

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