问题描述
我正在将from scipy.signal import gaussian应用于一组点，以滚动方式平滑曲线。
def smooth_gaussian(data,window,std):
g = gaussian(window,std,sym=True)
con = np.convolve(g/g.sum(),data,mode='valid')
con_shift = np.r_[np.full(int(window*0.5),np.nan),con,np.full(int(window*0.5),np.nan)]
return con_shift
但是，在执行此操作时，该函数将值从开头和结尾偏移std-1个位置，并用nans填充。
smooth_gaussian(x,5,3)
x = [0.0,0.0185444808621514,0.04353375061397004,0.0,0.037009453627706586,-0.002574811929754943,-0.008514606925496021,-0.004525364338418344,0.01603344879624361,-0.008176977610078684,-0.01013245952744958,0.03996290965967278,0.004585506533521074,0.01120825808877464,-0.014854987339931331,0.027839959669720065,-0.01363659727385685,-0.009635505397613021,0.015952626842982574,-0.05723201212379214,-0.007780069509540553,0.004382874236289852,0.038106785772339016,0.0020824367482471916,0.009206907087771247,-0.005312729628236836,0.0003880320778995375,0.00336355496824854,-0.010513187775929366,-0.004263141180765177,4.0797273904902634e-05,0.0026873894750915357,0.04737815797347586,0.03626967474190855,-0.001326958533547213,0.006573790793200369,-0.012210432139001255,-0.005373057181818514,0.016644712998042103,-0.012265613043462619,0.11261448009585626,-0.012185874851013743,0.0005792221659147861,0.08345293709945158,-0.005246029136623375,0.0015148005522818237,0.001830695038247017,0.003687504607556841,0.0065507216003178395,0.00117405250448804,0.014311546898334035,0.017903880444956242,-0.006553897125751214,-0.07215579508846881,0.014181691708626792,0.017493159929742756,0.009550277653690674,-0.003356974394831732,0.0327208871241706,0.002795052678830963,-0.0037707485693199783,0.06211202416416171,0.015181750267714622,0.00334460827605957,-0.00021393411588840287,0.02503678667112154,-0.00466151928887153,0.06231556188921662,-0.11946455099766087,0.004232213476864264,-0.015338758071829633,-0.018906328574624865]
结果是：
array([ nan,nan,2.10349055e-02,2.35864806e-03,1.73461936e-02,1.59561400e-02,-4.26660062e-03,-5.73985110e-03,4.92612899e-03,3.27209493e-03,-6.97831701e-03,1.39369457e-02,2.09944748e-02,8.16964809e-03,-7.64435525e-04,6.03942428e-03,5.97089401e-03,-9.67266366e-03,2.57063885e-03,5.54861712e-03,-2.66962686e-02,-3.04662584e-02,-3.26920778e-03,2.94363128e-03,1.80616142e-02,1.79964811e-02,2.36393111e-03,5.16194246e-03,1.90536838e-03,-1.94961572e-03,1.61117216e-03,1.59253745e-03,-2.09649704e-04,-5.07213168e-03,-6.95261269e-03,-2.21077837e-03,2.54849096e-03,2.46239791e-02,3.94073221e-02,1.80239542e-02,3.53458603e-03,2.70115693e-03,-5.70966673e-03,-7.78881961e-03,4.58850968e-03,1.91504673e-03,-1.99075206e-03,5.26407851e-02,5.26412919e-02,-2.42272310e-03,-5.44020155e-03,2.35800108e-03,3.92900195e-02,3.91217709e-02,1.76058419e-05,-1.69258247e-03,1.52960978e-03,2.83255426e-03,4.90808043e-03,4.16438980e-03,8.00317308e-03,1.50047039e-02,5.75233874e-03,-4.67031944e-03,-3.41464738e-02,-3.35421047e-02,5.07473061e-03,1.48998963e-02,8.92716005e-03,5.00770626e-03,4.39834755e-03,-1.29671612e-03,-6.21006659e-04,1.53823996e-02,1.66109984e-02,2.31579756e-03,2.75440728e-02,2.95660756e-02,9.05984198e-03,8.72256686e-03,2.65024164e-03,1.17818429e-02,1.17765298e-02,6.03242779e-04,-3.67528126e-04,2.71334365e-02,2.91908596e-02,1.80942572e-03,-3.48822318e-03,-5.61009027e-02,-5.46800643e-02,-8.72490815e-03,nan])
我不想将这些值替换为零，而是将其替换为高斯曲线的一部分-正态分布。可以这样做吗？
亲切的问候
解决方法
尝试将% PL-Unit: fifteen_with_foldl ... done
% All 3 tests passed
true.
与np.convolve
mode='same'制作测试数据（from scipy.signal import gaussian
def smooth_gaussian(data,window,std):
g = gaussian(window,std,sym=True)
con = np.convolve(g/g.sum(),data,mode='same')
return con
，蓝色），添加噪声（s0，橙色），然后对其进行平滑处理（s1，绿色）：
con没有nan：
s0 = np.zeros(1000)
s0[:500] = 1
s1 = s0 + np.random.randn(len(s0))*0.1
con = smooth_gaussian(s,5,3)
plt.plot(s0)
plt.plot(s1)
plt.plot(con)
