单变量样条插值全为NaN但没有不良参数迹象

Question

我写了一个函数，用来创建一个样条插值函数，这个函数会检查输入数据是否有错误。如果数据通过了检查，就会生成一个点的数量是原始数量倍数的样条。但是，尽管我的错误检查没有发现问题，这个函数似乎还是不工作。

我检查了以下几个方面：

x和y的数据大小必须相同
生成的点的倍数必须大于零，<1表示样条中的点更少，>1表示样条中的点更多，1表示点的数量不变
样条的阶数必须在1到5之间（包括1和5）
x的数据必须是严格递增的
x或y的数据中至少有一个包含NaN（不是一个数字）

我觉得这个检查列表很全面，应该能避免生成全是NaN的样条，但当我输入数据时，似乎没有任何错误被触发。

这是我的代码：

##
# Univariate Spline Interpolation
##

## This function interpolates the data by creating multiple times the amount of points in the data set and fitting a spline to it
## Input:
# dataX - X axis that you corresponds to dataset
# dataY - Y axis of data to fit spline on (must be same size as dataX)
# multiple - the multiplication factor, default is 2 ( <1 - Less points, 1 - same amount of points, >1 - more points)
# order - order of spline, default is 4 (3 - Cubic, 4 - Quartic)
## Output
# spline - interpolation spline object to be used for peak detection
# splinedDataX - splined X Axis
# splinedDataY - splined Y Axis

#import scipy modules for spling creation and class methods
from scipy.interpolate import UnivariateSpline, LSQUnivariateSpline

#import numpy module for linear spacing creation
from numpy import linspace, NaN

def univariate_spline_interpolation(dataX, dataY, multiple=2, order=4):

    #Libraries
    from scipy.interpolate import UnivariateSpline, LSQUnivariateSpline
    from myUnivariateSpline import MyUnivariateSpline

    #Find sizes of x and y axis for comparison and multiple
    sizeX = len(dataX)
    sizeY = len(dataY)

    #Error catching
    if(sizeX != sizeY):
        print "Data X axis and Y axis must have same size"
        return

    if(multiple <= 0):
        print "Multiple must be greater than 0"
        return

    if(order < 1 or order >5):
        print "Order must be 1 <= order <= 5"
        return

    #check for monotonic increasting function
    for indx, val in enumerate(dataX): #set first value as largest value, need to have all following increase
        if indx == 0:
            high = val
            highIndx = indx
            continue
        #if the curent value is lower than 
        if val <= high:
            print "timestamp out of order"
            print "value at ", highIndx, "is ", high
            print "value at ", indx, "is ", val
            break

    #check for NaN in x and y
    for indx, val in enumerate(dataY):
        if(val == NaN):
            print "Value in Data Y at indx", indx, "is NaN"
            return

    for indx, val in enumerate(dataX):
        if(val == NaN):
            print "Value in Data X at indx", indx, "is NaN"
            return

    #Create Spline
    spline = UnivariateSpline(dataX, dataY, k=order, s=0)   

    #Create new axis based on numPoints
    numPoints = sizeX * multiple   #Find number of points for spline
    startPt = dataX[0]   #find value of first point on x axis
    endPt = dataX[-1]   #find value of last point on x axis
    splinedDataX = linspace(startPt, endPt, numPoints)   #create evenly spaced points on axis based on start, end, and number of desired data points

    #Create Y axis of splined Data
    splinedDataY = spline(splinedDataX)   #Create new Y axis with numPoints etnries of data splined to fit the original data

    return spline, splinedDataX, splinedDataY

这是我尝试输入的三个数据集中的一个，但这三个数据集都导致返回的splinedDataY字段全是NaN。interpDataY的大小和对应的interpDataX是一样的。我不知道是什么原因导致它只返回NaN。

X数据 Y数据

这两组数据都是pandas的Series，但即使把它们转换成列表也没有解决问题。

我不知道这是否相关，但当我打印这个列表时，里面全是nan，而不是NaN。

数据检查 pandas 样条插值 NaN处理数据大小一致性严格递增阶数限制数据集验证

单变量样条插值全为NaN但没有不良参数迹象

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