Python中的多个高斯自动拟合

Question

问题是让我的所有波长峰值都适应高斯，以便尽可能精确地进行介质调整

我的问题是如何自动对所有峰进行高斯调整，而不必手动指定峰的坐标

为此，我实现了最亮峰的高斯调整，但我想将其推广到以下峰。随后，高斯调整将使我能够获得足够精细的多项式调整，以错开波长上的像素

import itertools

records = []

for key, group in itertools.groupby(filters, lambda x: x['dimensionName']):
    groups = list(group)
    rec = {'dimensionName':key}

    # assuming there are no duplicates of the operator
    rec['operator'] = min([x['operator'] for x in groups])    

    # the `sum` expression reduces the list of lists of expressions it is slow but readable. For production, revisit
    rec['expressions'] = sum([x['expressions'] for x in groups],[])

    records.append(rec)

print(records)

# [{'dimensionName': 'ga:pagePath',
#  'operator': 'PARTIAL',
#  'expressions': ['substring1', 'substring2']}]