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EX.Teleportation

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暮晨 2018-11-20 23:30:43 +08:00 committed by 暮晨
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@ -52,7 +52,7 @@ So, here we go...
- [> Let's see if you can guess this?/看看你能否猜到这一点?](#-lets-see-if-you-can-guess-this看看你能否猜到这一点) - [> Let's see if you can guess this?/看看你能否猜到这一点?](#-lets-see-if-you-can-guess-this看看你能否猜到这一点)
- [Section: Appearances are deceptive!](#section-appearances-are-deceptive) - [Section: Appearances are deceptive!](#section-appearances-are-deceptive)
- [> Skipping lines?/跳过一行?](#-skipping-lines跳过一行) - [> Skipping lines?/跳过一行?](#-skipping-lines跳过一行)
- [> Teleportation *](#-teleportation-) - [> Teleportation/空间移动 *](#-teleportation空间移动-)
- [> Well, something is fishy...](#-well-something-is-fishy) - [> Well, something is fishy...](#-well-something-is-fishy)
- [Section: Watch out for the landmines!](#section-watch-out-for-the-landmines) - [Section: Watch out for the landmines!](#section-watch-out-for-the-landmines)
- [> Modifying a dictionary while iterating over it](#-modifying-a-dictionary-while-iterating-over-it) - [> Modifying a dictionary while iterating over it](#-modifying-a-dictionary-while-iterating-over-it)
@ -1272,17 +1272,17 @@ False
--- ---
### > Teleportation * ### > Teleportation/空间移动 *
```py ```py
import numpy as np import numpy as np
def energy_send(x): def energy_send(x):
# Initializing a numpy array # 初始化一个 numpy 数组
np.array([float(x)]) np.array([float(x)])
def energy_receive(): def energy_receive():
# Return an empty numpy array # 返回一个空的 numpy 数组
return np.empty((), dtype=np.float).tolist() return np.empty((), dtype=np.float).tolist()
``` ```
@ -1293,12 +1293,12 @@ def energy_receive():
123.456 123.456
``` ```
Where's the Nobel Prize? 谁来给我发个诺贝尔奖?
#### 💡 Explanation: #### 💡 说明:
* Notice that the numpy array created in the `energy_send` function is not returned, so that memory space is free to reallocate. * 注意在 `energy_send` 函数中创建的 numpy 数组并没有返回, 因此内存空间被释放并可以被重新分配.
* `numpy.empty()` returns the next free memory slot without reinitializing it. This memory spot just happens to be the same one that was just freed (usually, but not always). * `numpy.empty()` 直接返回下一段空闲内存，而不重新初始化. 而这个内存点恰好就是刚刚释放的那个(通常情况下, 并不绝对).
--- ---