我想从 a 中读取两列 S1_max 和 S2_max dataframe
data
。无论 S1_max 列中的哪个值存在,我都想检查每个S1_max
值是否都有相应的S2_max
信号。如果是这样,我计算S1_max
和S2_max
信号之间的时间增量。然后,此结果datetime[64ns]
在单独的 S2_max 列的索引处被索引,dict
d
然后附加到list
delta_data
. 如何将此结果添加到data
相应datetime[64ns]
索引处已存在的数据框中?
这是我的创作delta_data
:
#time between each S2 global maxima: 86 ns/samp freq 200 = 0.43 ns
#Checking that each S1 is succeeded by a corresponging S2 signal and calculating the time delta:
delta_data = []
diff_S1 = 0
diff_S2 = 0
i = 0
while((i + diff_S1 + 1 < len(peak_indexes_S1)) and (i + diff_S2<len(peak_indexes_S2))):
# Find next ppg peak after S1 peak
while (df["S2"].index[peak_indexes_S2[i + diff_S2]] < df["S1"].index[peak_indexes_S1[i+diff_S1]]):
diff_S2=diff_S2+1
while (df["S1"].index[peak_indexes_S1[i+diff_S1+1]] < df["S2"].index[peak_indexes_S2[i + diff_S2]]):
diff_S1=diff_S1+1
i_peak_S2 = peak_indexes_S2[i + diff_S2]
i_peak_S1 = peak_indexes_S1[i + diff_S1]
d={}
d["td"] = (df["S2"].index[i_peak_S2]-df["S1"].index[i_peak_S1]).microseconds
d["time"] = df["S2"].index[i_peak_S2]
PATdata.append(d)
i = i + 1
time_delta=pd.DataFrame(delta_data)
delta_data
打印出来:
td time
0 355000 2019-08-07 13:06:31.010
1 355000 2019-08-07 13:06:31.850
2 355000 2019-08-07 13:06:32.695
这是我的data
数据框:
l1 l2 l3 l4 S1 S2 S2_max S1_max
2019-08-07 13:11:21.485 0.572720 0.353433 0.701320 1.418840 4.939690 2.858326 2.858326 NaN
2019-08-07 13:11:21.490 0.572807 0.353526 0.701593 1.419052 4.939804 2.854604 NaN 4.939804
此数据框由以下人员创建:
data = pd.read_csv('file.txt')
data.columns = ['l1','l2','l3','l4','S1','S2']
nbrMeasurments = sum(1 for line in open('file.txt'))
data.index = pd.date_range('2019-08-07 13:06:30'), periods=nbrMeasurments-1, freq="5L")
我试过DataFrame.combine_first
和append
.
此外,尝试将另一个数据帧添加到data
. 此数据帧在日期时间帧中没有 ms:
S3 S4
Date
2019-08-07 13:06:30 111 61