The way the convolution of sample and model is done is too fragile. It works for the given examples, but it exhibits boundary effects at data extremes and if a user decides to change the input and give a range that is not symmetric or does not have a constant step in energy, the result will be wrong.
The way the convolution of sample and model is done is too fragile. It works for the given examples, but it exhibits boundary effects at data extremes and if a user decides to change the input and give a range that is not symmetric or does not have a constant step in energy, the result will be wrong.