从压缩字节加载 numpy 数组

Question

我试图将一堆 numpy 数组保存（使用 savez_compressed）到一个 BytesIO 对象中，然后将它们加载回一个变量。到目前为止，我可以使用以下代码保存数组

# Arrays
a = numpy.random.uniform(size=(10,10)) # dtype is float64
b = numpy.random.uniform(size=(10,10)) # dtype is float64

# Create bytes object
buf = io.BytesIO()

# Save the arrays into the buffer
numpy.savez_compressed(buf, a=a, b=b)

# Closed the buffer
buf.close()

我一直在尝试不同的方法来加载它们。例如

ab = numpy.frombuffer(buf.read(), dtype='float64')

加注 ValueError: buffer size must be a multiple of element size。并尝试像文件一样加载

ab = numpy.load(buf)

加注 ValueError: Cannot load file containing pickled data when allow_pickle=False 并且当 buf.read() 我得到 ValueError: embedded null byte.

Answer 1

以下对我有效 [Numpy version: numpy==1.16.1]:

import numpy
import io

# Arrays
a = numpy.random.uniform(size=(10,10)) # dtype is float64
b = numpy.random.uniform(size=(10,10)) # dtype is float64

# Create bytes object
buf = io.BytesIO()

# Save the arrays into the buffer
numpy.savez_compressed(buf, a=a, b=b)
buf.seek(0)

ab = numpy.load(buf)
print(ab['a'])
print(ab['b'])

# Closed the buffer
buf.close()

从压缩字节加载 numpy 数组

Load numpy arrays from compressed bytes

python

load

numpy

save

bytesio