[Python] Non-integral optimizer parameters in scipy.stats.fit

I am trying to fit a distribution to some data using scipy.stats.fit. I specifically need the stats.nbinom distribution to be fit using a non-integer value for parameter n.

I've made this minimal example of what I'd like to achieve. I can't see what I've done incorrectly.

This is a modified version of the example here

from scipy import stats
from scipy.optimize import differential_evolution
import numpy as np

rng = np.random.default_rng()

def optimizer(fun, bounds, *, integrality):
return differential_evolution(fun, bounds, strategy='best2bin',
rng=rng, integrality=[False, False, False])

data = [0,0,0,1,2,4,11]
bounds = [(1.5, 1.55), (0, 1)]
res4 = stats.fit(stats.nbinom, data, bounds, optimizer=optimizer)
print(res4.params)


Thanks

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