Python 是否可以转换以字节为单位的要素映射？

Python 3.6

Unity 2019

我正试图找到将要素地图数据传输到unity的最佳解决方案

我想用字节发送数据。然而，我并没有找到如何将其编码为字节，然后在统一中对其进行解码

基本上是一个4d数组，需要根据我对它的理解转换成字节

蟒蛇片

for fmap in feature_maps:
            bytes = []
            bytes.append(fmap)
            arrays_of_features.append(bytes)

        data = np.array(arrays_of_features, dtype=float) # this is not working because of the fact is multidimensional array apparently. 
        print(fmap)
        c.sendall(data.tobytes())

统一件： 字节[]字节=新字节[4000]； int idxUsedBytes=client.Receive（字节）

灵感：

要素地图如下所示：

[[[[ 0.          0.          0.         ...  0.         12.569366
 0.        ]
[ 0.          0.          0.         ...  0.          4.421044
 0.        ]
[ 0.          0.          0.         ...  0.          0.19193476
 0.        ]
...
[ 0.          0.          0.         ...  0.          0.
 0.        ]
[ 0.          0.          0.         ...  0.          0.
 0.        ]
[ 0.          0.          0.         ...  0.          0.
 0.        ]]

[[ 0.          0.          0.         ...  0.         12.910363
 0.        ]
[ 0.          0.          0.         ...  0.          3.987629
 0.        ]
[ 0.          0.          0.         ...  0.          1.6041028
 0.        ]
...
[ 0.          0.          0.         ...  0.          0.
 0.        ]
[ 0.          0.          0.         ...  0.          0.
 0.        ]
[ 0.          0.          0.         ...  0.          0.
 0.        ]]

[[ 0.          0.          0.         ...  0.          0.
 0.        ]
[ 0.          0.          0.         ...  0.          0.
 0.        ]
[ 0.          0.          0.         ...  0.          0.
 0.        ]
 ...
[ 0.          0.          0.         ...  0.          0.
 0.        ]
[ 0.          0.          0.         ...  0.          0.
 0.        ]
[ 0.          0.          0.         ...  0.          0.
 0.        ]]

...

[[ 0.          0.          0.         ...  0.          0.
 0.        ]
[ 0.          0.          0.         ...  0.          0.
 0.        ]
[ 0.          0.          0.         ...  0.          0.
 0.        ]
...
[ 0.          0.          0.         ...  0.          0.
49.52598   ]
[ 0.          0.          0.         ...  0.          0.
10.050183  ]
[ 0.          0.          0.         ...  0.          9.6911745
 0.        ]]
[[ 0.          0.          0.         ...  0.          0.
 0.        ]
[ 0.          0.          0.         ...  0.          0.
 0.        ]
[ 0.          0.          0.         ...  0.          0.
 0.        ]
...
[ 0.          0.          0.         ...  0.          0.
29.483086  ]
[ 0.          0.          0.         ...  0.          0.
24.422682  ]
[ 0.          0.          2.253025   ...  0.          0.
15.935954  ]]

[[ 0.          0.          0.         ...  0.          0.
 0.        ]
[ 0.          0.          0.         ...  0.          0.
 0.        ]
[ 0.          0.         18.458588   ... 15.824303    0.
 0.        ]
 ...
[ 0.          0.          0.         ... 25.163502   56.87079
42.9939    ]
[ 0.          0.         11.397255   ... 36.644962   17.04247
44.108196  ]
[ 0.          0.         33.134758   ... 30.220499    8.817273
36.6427    ]]]]

---

你的问题很不清楚，我相信你对numpy的工作原理感到困惑。如果是这样，让我们解释一些事情。numpy中的数组只不过是内存中的一个字节字符串。特别是，当为您显示这些字节时，它们将由数据类型进行解释。数据类型不用于存储基础数据，而仅用于显示它。因此，更改数据类型只会更改数据的外观，而不会更改数据本身。维度也是一样。数据的维度只会更改数据的显示和访问方式，python实际上不会移动数据或更改数据本身。比如说,

import numpy as np

x = np.array([[1,2,3],[4,5,6]],dtype='int64') #48 bytes, each int takes up 8 bytes.
print(x)
x.dtype = 'int32'
print(x)
x.dtype = 'float'
print(x)
x.dtype = 'int16'
print(x)

请注意，我们可以更改数据类型，绝对零计算由数组完成（因为底层数据已经是字节数组）。同样地，我们可以改变形状，也可以进行绝对零计算

x.shape = (2,2,6)
print(x)

形状和数据类型与内存中存储的数据无关。希望这能清楚地说明我们现在如何使用字节数组

x = np.array([[1,2,3],[4,5,6]],dtype='int64')
print(x)
y = x.tobytes()

# Send y somewhere. Save to a file. Etc.

z = np.frombuffer(y)
z.dtype = 'int64'
z.shape = (2,3)
print(z)

x = np.array([[1,2,3],[4,5,6]],dtype='int64')
print(x)
y = x.tobytes()

# Send y somewhere. Save to a file. Etc.

z = np.frombuffer(y)
z.dtype = 'int64'
z.shape = (2,3)
print(z)