Question

我正在将文件中的数据（数字）读入列表，如下所示：

    weight_file = open(model_name, 'r').readlines()
    weights = weight_file[6:]

似乎我无法将它们直接读入numpy.array，因为该文件的第一行包含单词。

现在，在weights我有一个列表如下：[['1 2 3'] ['4 5 6']]

现在我想将其转换为numpy.array。我试过这个：

    weights_np = np.array([])
    for weight in weights:
        weights_np = np.append(weights_np, weight.split())

这样做是创建一个向量：[1, 2, 3, 4, 5, 6]，但我需要将它表示为某种矩阵 - 就像列表一样。我怎么能这样做？

由于

Answer 1

如果weights_np是这样的话：

In [23]: weights_np = np.array([1, 2, 3, 4, 5, 6])

然后您可以使用reshape将其设为2维，包含3列：

In [24]: weights_np = weights_np.reshape((-1, 3))

In [25]: weights_np
Out[25]: 
array([[1, 2, 3],
       [4, 5, 6]])

但更令人满意的方法是使用np.loadtxt或np.genfromtxt正确解析文件。（这比使用Python循环和调用np.append要快得多。）请注意，这些函数有一个skiprows参数，可用于跳过前几行：

weights = np.loadtxt(model_name, skiprows=6)

Answer 2

要获得＆＃34;类型的矩阵＆＃34;，只需使用：

numpy.array([[int(val) for val in line.split()] for line in open(model_name)])

要获得简单的向量，请使用：

numpy.array([int(val) for line in open(model_name) for val in line.split()])

Answer 3

>>> import numpy as np
>>> weights = ['1 2 3', '4 5 6']
>>> weights_np = np.array(map(lambda x: map(int, x.split()), weights))
>>> weights_np
array([[1, 2, 3],
       [4, 5, 6]])

Answer 4

以这种方式尝试：

weights_np = np.empty((0,len(weights[0].split())),int)
for weight in weights:
    weights_np = np.append(weights_np, [map(int,weight.split())], axis=0)

演示：

>>> weights = ['1 2 3','4 5 6']
>>> weights_np = np.empty((0,len(weights[0].split())),int)
>>> for weight in weights:
...     weights_np = np.append(weights_np, [map(int,weight.split())], axis=0)
... 
>>> weights_np
array([[1, 2, 3],
       [4, 5, 6]])

将字符串列表转换为numpy列表列表

4 个答案: