python - 如何在 numpy 数组中找到连续的正数、负数和零？

Question

我使用以下函数来查找连续的负数和正数，现在我还想添加一个条件来获取连续的零。我该怎么做？

def consecutive_counts(arr):
    '''
    Returns number of consecutive negative and positive numbers
    arr = np.array
    negative = consecutive_counts()[0]
    positive = consecutive_counts()[1]
    '''
    pos = arr > 0
    # is used to Compute indices that are non-zero in the flattened version of arr
    idx = np.flatnonzero(pos[1:] != pos[:-1])
    count = np.concatenate(([idx[0]+1], idx[1:] - idx[:-1], [arr.size-1-idx[-1]]))
    negative = count[1::2], count[::2]
    positive = count[::2], count[1::2]
    if arr[0] < 0:
        return negative
    else:
        return positive

这是 Pandas 系列:

In [221]: n.temp.p['50000']
Out[221]: 
name
0         0.00
1       -92.87
2       -24.01
3       -92.87
4       -92.87
5       -92.87
...       ...

我是这样使用的:

arr = n.temp.p['50000'].values #Will be a numpy array as the input

预期输出:

In [225]: consecutive_counts(a)
Out[225]: (array([30, 29, 11, ...,  2,  1,  3]), array([19,  1,  1, ...,  1,  1,  2]))

谢谢:)

Answer 1

由于您标记了 pandas，所以这里有一种方法:

# random data
np.random.seed(1)
a = np.random.choice(range(-2,3), 1000)

# np.sign: + = 1, 0 = 0, - = -1
b = pd.Series(np.sign(a))

# b.head()
# 0    1
# 1    1
# 2   -1
# 3   -1
# 4    1
# dtype: int32

# sign blocks
blks = b.diff().ne(0).cumsum()

# blks.head()
# 0    1
# 1    1
# 2    2
# 3    2
# 4    3
# dtype: int32

# number of blocks:
blks.iloc[-1]
# 654

# block counts:
blks.value_counts()

# 1      2
# 2      2
# 3      1
# 4      3
# 5      2
# ...