如何用Python计算干湿法术？

Question

我有一个随机的时间序列数据,有四列,如:年,月,日,降水.我想计算不同法术长度的干/湿法术.我正在寻找一种更方便的方法来做到这一点,而目前正在做一些丑陋的代码,如下所示:

import numpy as np
data = np.loadtxt('Data Series.txt', usecols=(1,3))
dry = np.zeros(12)
wet = np.zeros(12)

rows,cols = data.shape #reading number of rows and columns into variables

for i in xrange (0,rows):
    for m in xrange(0,12):
        if data[i,1] == 0 and data[i-1,1] == 0 and data[i-2,1] == 0:
            if data[i,0] == m+1:
                dry[m] += 1.0
        if data[i,1] > 0 and data[i-1,1] > 0 and data[i-2,1] > 0:
            if data[i,0] == m+1:
                wet[m] += 1.0
print '3 Days Dry Spell\n', dry
print '3 Days Wet Spell\n', wet

现在,如果我想计算4,5,6天法术,那么"如果数据[i,1] == 0和数据[i-1,1] == 0 ......"变成一个巨大的法术.任何人都可以帮助我,以便我可以只给出法术长度,而不是这个长丑陋的线？

Answer 1

您可能想尝试这样的事情:

# first extract precipitation data for later use
precipitation = [data[i][1] for i in xrange(0, rows)]

# then test the range (i, i+m)
all_dry = all([(data==0) for data in precipitation[i:i+m]])
all_wet = not any([(data==0) for data in precipitation[i:i+m]])
# of course you can also use
all_wet = all([(data>0) for data in precipitation[i:i+m]])

但请注意,此方法在测试相邻日期时会引入冗余计算,因此可能不适合处理大量数据.

编辑:

好的,这一次让我们寻找一种更有效的方法.

# still extract precipitation data for later use first
precipitation = [data[i][1] for i in xrange(0, rows)]

# let's start our calculations by counting the longest consecutive dry days 
consecutive_dry = [1 if data == 0 else 0 for data in precipitation]
for i in xrange(1, len(consecutive_dry))
    if consecutive_dry[i] == 1:
        consecutive_dry[i] += consecutive_dry[i - 1]

# then you will see, if till day i there're m consecutive dry days, then:
consecutive_dry[i] >= m    # here is the test

# ...and it would be same for wet day testings.

这显然比上述方法更有效:为了测试具有M个连续范围的总共N天,前一个需要O(N*M)个操作来计算,并且这个操作需要O(N).

再次编辑:

这是原始代码的编辑版本.由于您的代码可以运行,这也应该在您的PC上运行或者运行.

import numpy as np
data = np.loadtxt('Data Series.txt', usecols=(1,3))
dry = np.zeros(12)
wet = np.zeros(12)

rows,cols = data.shape #reading number of rows and columns into variables

# prepare 
precipitation = [data[i][1] for i in xrange(0, rows)]

# collecting data for consecutive dry days
consecutive_dry = [1 if data == 0 else 1 for data in precipitation]
for i in xrange(1, len(consecutive_dry))
    if consecutive_dry[i] == 1:
        consecutive_dry[i] += consecutive_dry[i - 1]

# ...and for wet days
consecutive_wet = [1 if data > 0 else 0 for data in precipitation]
for i in xrange(1, len(consecutive_wet))
    if consecutive_wet[i] == 1:
        consecutive_wet[i] += consecutive_wet[i - 1]

# set your day range here. 
day_range = 3

for i in xrange (0,rows):
    if consecutive_dry[i] >= day_range:
        month_id = data[i,0]
        dry[month_id - 1] += 1
    if consecutive_wet[i] >= day_range:
        month_id = data[i,0]
        wet[month_id - 1] += 1

print '3 Days Dry Spell\n', dry
print '3 Days Wet Spell\n', wet

请尝试这个,如果有任何问题请告诉我.