find_reversal_racetrack_filtered returning the original datapoint and not the bin datapoint

I believe the find_reversal_racetrack_filtered is returning the wrong vector.
It should return rev[ix[ixr]], ix[ixr] and not y[ix[ixr]], ix[ixr]

Here is the piece of code I was playing with to understand the behaviour of racetrack_filter:
```
y = np.random.normal(size=50)*10
fig = go.Figure()
time = x=[i for i, val in enumerate(y)]
fig.add_trace(go.Scatter(x=time,y=y, mode='markers', marker_size=10, name='Raw Data'))
binsDataFiltering = 6
reversal, indInit = fatpack.find_reversals(y, k=binsDataFiltering)
fig.add_trace((go.Scatter(x=indInit, y=reversal, name='find_reversal')))
reversal, indInit = fatpack.find_reversals_racetrack_filtered(y, h=0, k=binsDataFiltering)
fig.add_trace((go.Scatter(x=indInit, y=reversal, name='find_reversals_racetrack_filtered h=0')))

bound = fatpack.rainflow.get_load_class_boundaries(y, k=binsDataFiltering)
boundCouple = zip(bound[:-1], bound[1:])

for boundaryCouple in boundCouple:
fig.add_hline(y=(boundaryCouple[1]+boundaryCouple[0])/2, line_dash='dash', line_color='green')
fig.update_layout(title=dict(text="Rainflow counting with FatPack test"),xaxis=dict(title=dict(text="Time")),yaxis=dict(title=dict(text="physical value")))
fig.show()
```

Thanks for this great package !


Start at the find_reversals_racetrack_filtered entry point and compare its returned vector with the issue's expected rev[ix[ixr]], ix[ixr] result. Reproduce the behavior using the provided NumPy example and verify that the function returns the bin datapoint rather than the original datapoint.

Written by the indexing model from the issue text.