我有以下数据,但我可以控制它的格式。基本上,我想使用Python和Numpy或Pandas来对数据进行插值,以实现每秒钟的二次插值,并使其分辨率更高。
所以我希望在保留原始值的同时,在我当前拥有的每个真实值之间线性插值并产生新值。
如何使用Pandas或Numpy完成这个任务?
以这种类型的数据为例:
请给我一个实现这个功能的例子,谢谢!
我已经尝试过以下方法:
所以我希望在保留原始值的同时,在我当前拥有的每个真实值之间线性插值并产生新值。
如何使用Pandas或Numpy完成这个任务?
以这种类型的数据为例:
TIME ECI_X ECI_Y ECI_Z
2013-12-07 00:00:00, -7346664.77912, -13323447.6311, 21734849.5263,@
2013-12-07 00:01:00, -7245621.40363, -13377562.35, 21735850.3527,@
2013-12-07 00:01:30, -7142326.20854, -13432541.9267, 21736462.4521,@
2013-12-07 00:02:00, -7038893.48454, -13487262.8599, 21736650.3293,@
2013-12-07 00:02:30, -6935325.24526, -13541724.0946, 21736413.9937,@
2013-12-07 00:03:00, -6833738.23865, -13594806.9333, 21735778.2218,@
2013-12-07 00:03:30, -6729905.37597, -13648746.6281, 21734705.6406,@
2013-12-07 00:04:00, -6625943.01291, -13702423.5112, 21733208.9233,@
2013-12-07 00:04:30, -6521853.17291, -13755836.5481, 21731288.1125,@
2013-12-07 00:05:00, -6419753.85176, -13807871.3011, 21729016.1386,@
2013-12-07 00:05:30, -6315415.32918, -13860754.6497, 21726259.4135,@
2013-12-07 00:06:00, -6210955.33186, -13913371.1187, 21723078.7695,@
...
我希望你能将这个功能实现,即每秒更新一次。
2013-12-07 00:00:00, -7346664.77912, -13323447.6311, 21734849.5263,@
2013-12-07 00:00:01, -7346665.10000, -13323448.1000, 21734850.1000,@
...
2013-12-07 00:00:59, -7346611.10000, -13323461.1000, 21734850.1000,@
2013-12-07 00:01:00, -7245621.40363, -13377562.3500, 21735850.3527,@
请给我一个实现这个功能的例子,谢谢!
我已经尝试过以下方法:
#! /usr/bin/python
import datetime
from pandas import *
first = datetime(2013,12,8,0,0,0)
second = datetime(2013,12,8,0,2,0)
dates = [first,second]
x = np.array([617003.390723, 884235.38059])
newRange = date_range(first, second, freq='S')
ts = Series(x, index=dates)
ts.interpolate()
print ts.head()
#2013-12-08 00:00:00, 617003.390723, -26471116.2566, 3974868.93334,@
#2013-12-08 00:02:00, 884235.38059, -26519366.9219, 3601627.52947,@
我该如何使用"newRange"在"x"的真实值之间创建线性插值呢?