Python 如何压缩numpy阵列列表？

我有一个numpy阵列的目录：

{'data1': array([[0.16461831, 0.82400555],
        [0.02958593, 0.483629  ],
        [0.51268564, 0.07030046],
        [0.17027816, 0.35304705]]),
 'data2': array([[0.8292598 , 0.78136548],
        [0.30389913, 0.69250432],
        [0.66608852, 0.42237639],
        [0.72678807, 0.40486951]]),
 'data3': array([[0.45614633, 0.96677904],
        [0.87066105, 0.75826116],
        [0.39431988, 0.73041888],
        [0.65685809, 0.65498308]])}

预期产出：

[([0.16461831, 0.82400555], [0.8292598 , 0.78136548], [0.45614633, 0.96677904]), 
 ([0.02958593, 0.483629 ],  [0.66608852, 0.42237639], [0.87066105, 0.75826116]), 
 ([0.51268564, 0.07030046], [0.66608852, 0.42237639], [0.39431988, 0.73041888]), 
 ([0.17027816, 0.35304705], [0.72678807, 0.40486951], [0.65685809, 0.65498308])]

但当我尝试使用zip时：

list(zip(data.values()))

获取此输出：

[(array([[0.16461831, 0.82400555],
         [0.02958593, 0.483629  ],
         [0.51268564, 0.07030046],
         [0.17027816, 0.35304705]]),),
 (array([[0.8292598 , 0.78136548],
         [0.30389913, 0.69250432],
         [0.66608852, 0.42237639],
         [0.72678807, 0.40486951]]),),
 (array([[0.45614633, 0.96677904],
         [0.87066105, 0.75826116],
         [0.39431988, 0.73041888],
         [0.65685809, 0.65498308]]),)]

如何压缩numpy阵列列表？

使用

列表（zip（*data.values（））

输出：

[(array([0.16461831, 0.82400555]),
  array([0.8292598 , 0.78136548]),
  array([0.45614633, 0.96677904])),
 (array([0.02958593, 0.483629  ]),
  array([0.30389913, 0.69250432]),
  array([0.87066105, 0.75826116])),
 (array([0.51268564, 0.07030046]),
  array([0.66608852, 0.42237639]),
  array([0.39431988, 0.73041888])),
 (array([0.17027816, 0.35304705]),
  array([0.72678807, 0.40486951]),
  array([0.65685809, 0.65498308]))]

---

如果3D阵列适合您，您可以将其堆叠在第二个轴上（

轴=1

）：

---

以下代码将创建您的输出：

tmp = [data[d].tolist() for d in data]      
tmp = list(zip(*tmp))

输出：

[0.828292598，0.78136548；0.4561464633，0.9667677904；0.45614633，0.9667677904；以及[0.0.0.16461614140404040400.16461831.16461831，0.164610.164610.164610.1640.1646158585858585858585858585841410[[0.1640.164414141404040400.0.41414141414141415，0.0.0.0.0.414141404040404040406，0.4565656565656565656565656565656565656565656565332、0.6660852、0.6660858585852、0.6660858585852、0.6660858585852、0.660.6660858585852、0.代码>

链接将以另一种方式解释语法：

[tuple(x) for x in np.stack(data.values(),axis=1).tolist()]

[([0.16461831, 0.82400555], [0.8292598, 0.78136548], [0.45614633, 0.96677904]), 
 ([0.02958593, 0.483629], [0.30389913, 0.69250432], [0.87066105, 0.75826116]), 
 ([0.51268564, 0.07030046], [0.66608852, 0.42237639], [0.39431988, 0.73041888]), 
 ([0.17027816, 0.35304705], [0.72678807, 0.40486951], [0.65685809, 0.65498308])]

---

@任何东西都可以，一个numpy数组的元组或列表的元组。

[tuple(x) for x in np.stack(data.values(),axis=1).tolist()]

[([0.16461831, 0.82400555], [0.8292598, 0.78136548], [0.45614633, 0.96677904]), 
 ([0.02958593, 0.483629], [0.30389913, 0.69250432], [0.87066105, 0.75826116]), 
 ([0.51268564, 0.07030046], [0.66608852, 0.42237639], [0.39431988, 0.73041888]), 
 ([0.17027816, 0.35304705], [0.72678807, 0.40486951], [0.65685809, 0.65498308])]