从文件中使用numpy.load负载COM pressed数据 [英] Load compressed data from file using numpy.load

问题描述

我有一个数组：

>>> data = np.ones((1,3,128))

我保存它使用到文件 savez_com pressed ：

>>> with open('afile','w') as f:
        np.savez_compressed(f,data=data)

当我尝试加载它，我似乎不能够访问数据：

When I try to load it I don't seem to be able to access the data:

>>> with open('afile','r') as f:
        b=np.load(f)
>>> b.files
['data']
>>> b['data']

Traceback (most recent call last):
  File "<pyshell#196>", line 1, in <module>
    b['data']
  File "C:\Python27\lib\site-packages\numpy\lib\npyio.py", line 238, in __getitem__
    bytes = self.zip.read(key)
  File "C:\Python27\lib\zipfile.py", line 828, in read
    return self.open(name, "r", pwd).read()
  File "C:\Python27\lib\zipfile.py", line 853, in open
    zef_file.seek(zinfo.header_offset, 0)
ValueError: I/O operation on closed file

我做得显然是错误的？

Am I doing something obviously wrong?

修改

继@Saullo卡斯特罗的回答我尝试这样做：

Following @Saullo Castro's answer I tried this:

>>> np.savez_compressed('afile.npz',data=data)
>>> b=np.load('afile.npz')
>>> b.files
['data']
>>> b['data']

和得到了以下错误：

Traceback (most recent call last):
  File "<pyshell#253>", line 1, in <module>
    b['data']
  File "C:\Python27\lib\site-packages\numpy\lib\npyio.py", line 241, in __getitem__
    return format.read_array(value)
  File "C:\Python27\lib\site-packages\numpy\lib\format.py", line 440, in read_array
    shape, fortran_order, dtype = read_array_header_1_0(fp)
  File "C:\Python27\lib\site-packages\numpy\lib\format.py", line 336, in read_array_header_1_0
    d = safe_eval(header)
  File "C:\Python27\lib\site-packages\numpy\lib\utils.py", line 1156, in safe_eval
    ast = compiler.parse(source, mode="eval")
  File "C:\Python27\lib\compiler\transformer.py", line 53, in parse
    return Transformer().parseexpr(buf)
  File "C:\Python27\lib\compiler\transformer.py", line 132, in parseexpr
    return self.transform(parser.expr(text))
  File "C:\Python27\lib\compiler\transformer.py", line 124, in transform
    return self.compile_node(tree)
  File "C:\Python27\lib\compiler\transformer.py", line 159, in compile_node
    return self.eval_input(node[1:])
  File "C:\Python27\lib\compiler\transformer.py", line 194, in eval_input
    return Expression(self.com_node(nodelist[0]))
  File "C:\Python27\lib\compiler\transformer.py", line 805, in com_node
    return self._dispatch[node[0]](node[1:])
  File "C:\Python27\lib\compiler\transformer.py", line 578, in testlist
    return self.com_binary(Tuple, nodelist)
  File "C:\Python27\lib\compiler\transformer.py", line 1082, in com_binary
    return self.lookup_node(n)(n[1:])
  File "C:\Python27\lib\compiler\transformer.py", line 596, in test
    then = self.com_node(nodelist[0])
  File "C:\Python27\lib\compiler\transformer.py", line 805, in com_node
    return self._dispatch[node[0]](node[1:])
  File "C:\Python27\lib\compiler\transformer.py", line 610, in or_test
    return self.com_binary(Or, nodelist)
  File "C:\Python27\lib\compiler\transformer.py", line 1082, in com_binary
    return self.lookup_node(n)(n[1:])
  File "C:\Python27\lib\compiler\transformer.py", line 615, in and_test
    return self.com_binary(And, nodelist)
  File "C:\Python27\lib\compiler\transformer.py", line 1082, in com_binary
    return self.lookup_node(n)(n[1:])
  File "C:\Python27\lib\compiler\transformer.py", line 619, in not_test
    result = self.com_node(nodelist[-1])
  File "C:\Python27\lib\compiler\transformer.py", line 805, in com_node
    return self._dispatch[node[0]](node[1:])
  File "C:\Python27\lib\compiler\transformer.py", line 626, in comparison
    node = self.com_node(nodelist[0])
  File "C:\Python27\lib\compiler\transformer.py", line 805, in com_node
    return self._dispatch[node[0]](node[1:])
  File "C:\Python27\lib\compiler\transformer.py", line 659, in expr
    return self.com_binary(Bitor, nodelist)
  File "C:\Python27\lib\compiler\transformer.py", line 1082, in com_binary
    return self.lookup_node(n)(n[1:])
  File "C:\Python27\lib\compiler\transformer.py", line 663, in xor_expr
    return self.com_binary(Bitxor, nodelist)
  File "C:\Python27\lib\compiler\transformer.py", line 1082, in com_binary
    return self.lookup_node(n)(n[1:])
  File "C:\Python27\lib\compiler\transformer.py", line 667, in and_expr
    return self.com_binary(Bitand, nodelist)
  File "C:\Python27\lib\compiler\transformer.py", line 1082, in com_binary
    return self.lookup_node(n)(n[1:])
  File "C:\Python27\lib\compiler\transformer.py", line 671, in shift_expr
    node = self.com_node(nodelist[0])
  File "C:\Python27\lib\compiler\transformer.py", line 805, in com_node
    return self._dispatch[node[0]](node[1:])
  File "C:\Python27\lib\compiler\transformer.py", line 683, in arith_expr
    node = self.com_node(nodelist[0])
  File "C:\Python27\lib\compiler\transformer.py", line 805, in com_node
    return self._dispatch[node[0]](node[1:])
  File "C:\Python27\lib\compiler\transformer.py", line 695, in term
    node = self.com_node(nodelist[0])
  File "C:\Python27\lib\compiler\transformer.py", line 805, in com_node
    return self._dispatch[node[0]](node[1:])
  File "C:\Python27\lib\compiler\transformer.py", line 715, in factor
    node = self.lookup_node(nodelist[-1])(nodelist[-1][1:])
  File "C:\Python27\lib\compiler\transformer.py", line 727, in power
    node = self.com_node(nodelist[0])
  File "C:\Python27\lib\compiler\transformer.py", line 805, in com_node
    return self._dispatch[node[0]](node[1:])
  File "C:\Python27\lib\compiler\transformer.py", line 739, in atom
    return self._atom_dispatch[nodelist[0][0]](nodelist)
  File "C:\Python27\lib\compiler\transformer.py", line 754, in atom_lbrace
    return self.com_dictorsetmaker(nodelist[1])
  File "C:\Python27\lib\compiler\transformer.py", line 1214, in com_dictorsetmaker
    assert nodelist[0] == symbol.dictorsetmaker
AssertionError

编辑2

在IDLE上述错误。它的工作使用IPython的。

The above error was in IDLE. It worked using Ipython.

推荐答案

在使用 numpy.load 你的可以通过文件名，如果​​扩展名是 .npz ，它会先descom preSS：

When using numpy.load you can pass the file name, and if the extension is .npz, it will first descompress:

np.savez_compressed('filename.npz', array1=array1, array2=array2)
b = np.load('filename.npz')

和做 B ['数组1'] 等来检索每个阵列...

and do b['array1'] and so forth to retrieve the data from each array...

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