在numpy数组中使用等价运算符意味着什么

Question

我正在按照我在Python数据科学手册中找到的一个例子，这个例子的目的是创建两个数组掩码以最终输出夏天的雨天，作者认为夏天从6月21日开始，这是第172天它在3个月后结束。

在这里，我只对他在夏季间隔的代码段感兴趣：

# Construct a mask for all summer days (June 21st is the 172nd day)
summer = (np.arange((365) - 172 < 90 ) & np.arange((365) - 172 > 0)

在本书的另一个版本中，我发现了这段代码，我认为它会导致相同的结果：

# construct a mask of all summer days (June 21st is the 172nd day)
days = np.arange(365)
summer = (days > 172) & (days < 262)

这两个例子都不清楚，请帮忙。

Answer 1

也许一个简单的例子有助于更好地理解它。

# sample array
In [19]: week = np.arange(1, 8)

# find middle 3 days of the week
# to do so, we first find boolean masks by performing
# (week > 2) which performs element-wise comparison, so does (week < 6)
# then we simply do a `logical_and` on these two boolean masks
In [20]: middle = (week > 2) & (week < 6)

In [21]: middle
Out[21]: array([False, False,  True,  True,  True, False, False])

# index into the original array to get the days
In [22]: week[middle]
Out[22]: array([3, 4, 5])

---

&算子相当于numpy.logical_and()，而>和<算子分别相当于numpy.greater()和numpy.less。

# create a boolean mask (for days greater than 2)
In [23]: week > 2
Out[23]: array([False, False,  True,  True,  True,  True,  True])

# create a boolean mask (for days less than 6)
In [24]: week < 6
Out[24]: array([ True,  True,  True,  True,  True, False, False])

# perform a `logical_and`; note that this is exactly same as `middle`
In [25]: np.logical_and((week > 2), (week < 6))
Out[25]: array([False, False,  True,  True,  True, False, False])

In [26]: mid = np.logical_and((week > 2), (week < 6))

# sanity check again
In [27]: week[mid]
Out[27]: array([3, 4, 5])