使用 astype(int) 将 numpy 数组转换为整数在 Python 3.6 上不起作用

Question

I have a large text file with labels 0 or 1 in each line like this:

1
0
0
1
...

I load it, convert it into a numpy array, and then I want to convert the array into dtype=int64 (as I assume these are strings). I do it like this:

def load_data(infile):
    text_file = open(infile,'r')
    text = text_file.readlines()
    text = map(str.strip,text)
    return text
labels = load_data('labels.txt')
labels_encoded = np.array(labels)
labels_encoded = labels_encoded.astype(int)

It works fine in Python 2.7, and I can work on the array later with my code, but for now I'm stuck with Python 3.6 and when I ran my code, I get an error:

Traceback (most recent call last):
   File "dText.py", line 77, in <module>
   labels_encoded = labels_encoded.astype(int)
TypeError: int() argument must be a string, a bytes-like object or a number, not 'map'

Can anyone help me figure out what is going on here and how to get it to work on Python 3.6? I also tried:

labels_encoded = np.int_(labels_encoded)

but I got the same error. I'm using numpy version 1.13.3. Thanks.

Answer 1

You are passing a map object into the array and trying to convert it. Take a look at the array once it has been created. It looks like this:

array(<map object at 0x127680cf8>, dtype=object)

Try using list(map(...)) instead.

def load_data(infile):
    text_file = open(infile,'r')
    text = text_file.readlines()
    text = list(map(str.strip,text))
    return text
labels = load_data('labels.txt')
labels_encoded = np.array(labels)
labels_encoded = labels_encoded.astype(int)
labels_encoded
array([1, 0, 1, 0])

If you are just making the jump from 2.7 you should note that map no longer returns a list but an iterable.

Answer 2

I had same problem. My code did not work:

train_size = np.ceil(len(dataset) * 0.8).astype(int)
print(type(train_size))  # --> numpy.int32

But this works great:

train_size = int(np.ceil(len(dataset) * 0.8))
print(type(train_size))  # --> int