moving average difference between numpy and mathdotnet.com - numpy

Question

First, a picture:
Column A is my source data, 50 points.
Column C and D are the SMA calculated with numpy and mathdotnet.com, respectively, with a window of 15.
Column F is the delta.
As we can see, about halfway, the data becomes identical, but the first half is not. I do not understand why, and, more importantly, do not know what to trust.
So I got from SO an optimized version of the SMA and ran the data through it.
The code is here:
private static NDArray SMA(this NDArray Data, int Period)
{
var Length = Data.len;
// calculate the moving average
var Buffer = new double[Period];
var Output = new double[Length];
var CurrentIndex = 0;
for (var i = 0; i < Length; i++)
{
Buffer[CurrentIndex] = Data.GetDouble(i) / Period;
var MA = 0.0;
for (var j = 0; j < Period; j++)
{
MA += Buffer[j];
}
Output[i] = MA;
CurrentIndex = (CurrentIndex + 1) % Period;
}
var R = new ArraySegment<double>(Output, Period - 1, Length - Period + 1);
return new NDArray(R.ToArray());
}
It is using NumSharp, the .net port of numpy, to hold the source array.
While it is all different code, the C# code and python numpy output the same results (differences happen after the 12th decimal point, so we can consider them identical).
This points out to mathdotnet.com being different; so I guess I can trust the numpy / C# versions more.
Are there different variations of the SMA that could cause this? or something obvious I don't see?
I have put all the data here: https://pastebin.com/WgYJUUJF
Edit:
Here is the numpy code:
import numpy as np
def calcSma(data, smaPeriod):
j = next(i for i, x in enumerate(data) if x is not None)
our_range = range(len(data))[j + smaPeriod - 1:]
empty_list = [None] * (j + smaPeriod - 1)
sub_result = [np.mean(data[i - smaPeriod + 1: i + 1]) for i in our_range]
return np.array(empty_list + sub_result)
def calcSma2(data_set, periods=3):
weights = np.ones(periods) / periods
return np.convolve(data_set, weights, mode='valid')
a = np.array([1.1282553063375, 1.13157696082132, 1.13275406120136, 1.1332879715733, 1.12761933580452, 1.12621836040801, 1.12282485875706, 1.12265572041877, 1.13094386506532, 1.12320520490577, 1.12427293064877, 1.1328332027022, 1.13099445663901, 1.12843355605048, 1.13002750724853, 1.12843355605048, 1.13099445663901, 1.12709476494142, 1.12684879712348, 1.12672349888807, 1.12600933402474, 1.13112070248549, 1.12985951088976, 1.12822416032659, 1.12471789559362, 1.12651004224413, 1.12442669033881, 1.12334638977164, 1.12714333124378, 1.1312233808195, 1.12713229372575, 1.128255040952, 1.12585669781931, 1.12763457442902, 1.12470631424376, 1.12223443223443, 1.12506842815956, 1.12691187181355, 1.12385654130971, 1.13026344596074, 1.12237927400894, 1.1245915922457, 1.13088395780284, 1.13211944646759, 1.12590649028825, 1.12829127560895, 1.11876736364966, 1.12222667492441, 1.12169543369019, 1.12199031071285])
b = calcSma(a, 15)
c = calcSma2(a, 15)
print b
print "----------------------------------"
print c
and here is the mathdotnet one:
var data = Vector<double>.Build.Dense(new[] { 1.1282553063375, 1.13157696082132, 1.13275406120136, 1.1332879715733, 1.12761933580452, 1.12621836040801, 1.12282485875706, 1.12265572041877, 1.13094386506532, 1.12320520490577, 1.12427293064877, 1.1328332027022, 1.13099445663901, 1.12843355605048, 1.13002750724853, 1.12843355605048, 1.13099445663901, 1.12709476494142, 1.12684879712348, 1.12672349888807, 1.12600933402474, 1.13112070248549, 1.12985951088976, 1.12822416032659, 1.12471789559362, 1.12651004224413, 1.12442669033881, 1.12334638977164, 1.12714333124378, 1.1312233808195, 1.12713229372575, 1.128255040952, 1.12585669781931, 1.12763457442902, 1.12470631424376, 1.12223443223443, 1.12506842815956, 1.12691187181355, 1.12385654130971, 1.13026344596074, 1.12237927400894, 1.1245915922457, 1.13088395780284, 1.13211944646759, 1.12590649028825, 1.12829127560895, 1.11876736364966, 1.12222667492441, 1.12169543369019, 1.12199031071285 });
var sma = Vector<double>.Build.Dense(data.MovingAverage(15).Skip(14).ToArray());
var s = sma.Aggregate(string.Empty, (Current, v) => Current + $"{v}, ");
Console.WriteLine(s);