如何在Python中聚合时间序列？
我有两个不同的时间序列，部分重叠的时间戳：
import scikits.timeseries as ts
from datetime import datetime
a = ts.time_series([1,2,3], dates=[datetime(2010,10,20), datetime(2010,10,21), datetime(2010,10,23)], freq='D')
b = ts.time_series([4,5,6], dates=[datetime(2010,10,20), datetime(2010,10,22), datetime(2010,10,23)], freq='D')
Day: 20. 21. 22. 23.
a: 1 2 - 3
b: 4 - 5 6
Day 20.: (0.3 * 1 + 0.7 * 4) / (0.3 + 0.7) = 3.1 / 1. = 3.1
Day 21.: (0.3 * 2 ) / (0.3 ) = 0.6 / 0.3 = 2
Day 22.: ( 0.7 * 5) / ( 0.7) = 3.5 / 0.7 = 5
Day 23.: (0.3 * 3 + 0.7 * 6) / (0.3 + 0.7) = 3.1 / 1. = 5.1
a1, b1 = ts.aligned(a, b)
timeseries([1 2 -- 3],
dates = [20-Oct-2010 ... 23-Oct-2010],
freq = D)
timeseries([4 -- 5 6],
dates = [20-Oct-2010 ... 23-Oct-2010],
freq = D)
a1 * 0.3 + b1 * 0.7
timeseries([3.1 -- -- 5.1],
dates = [20-Oct-2010 ... 23-Oct-2010],
freq = D)
timeseries([3.1 2. 5. 5.1],
dates = [20-Oct-2010 ... 23-Oct-2010],
freq = D)
| T1 | T2 | T3 | T4 |
weight | 0.1 | 0.2 | 0.3 | 0.4 |
-------------------------------------
all present | 10% | 20% | 30% | 40% |
T1 missing | | 22% | 33% | 45% |
T1,T2 miss. | | | 43% | 57% |
T4 missing | 17% | 33% | 50% | |
etc.
没有找到相关结果
已邀请:
1 个回复
甲车劲
aWgt = 0.3 bWgt = 0.7 print (np.where(a1.mask, 0., a1.data * aWgt) + np.where(b1.mask, 0., b1.data * bWgt)) / (np.where(a1.mask, 0., aWgt) + np.where(b1.mask, 0., bWgt)) # array([ 3.1, 2. , 5. , 5.1])def weightedAvg(weightedTimeseries): sumA = np.sum((np.where(ts.mask, 0., ts.data * weight) for ts, weight in weightedTimeseries), axis=0) sumB = np.sum((np.where(ts.mask, 0., weight) for ts, weight in weightedTimeseries), axis=0) return np.divide(sumA, sumB) weightedAvg(((a1, 0.3), (bb, 0.7))) # array([ 3.1, 2. , 5. , 5.1])