NaN's in model evaluation

[damskii9992]

easyreflectometry: 1.3.3
Lmfit: 1.3.3

When using LMFit_differential_evolution as the minimizer, model evaluation can return NaN's which breaks the fitting:

Full workflow to replicate error below:

%matplotlib inline

import numpy as np
from easyreflectometry.calculators import CalculatorFactory
from easyreflectometry.data import load
from easyreflectometry.fitting import MultiFitter
from easyreflectometry.model import Model, PercentageFwhm
from easyreflectometry.plot import plot
from easyreflectometry.sample import (
    Layer,
    Material,
    Multilayer,
    LayerAreaPerMolecule,
    SurfactantLayer,
    Sample,
)
from easyscience.fitting import AvailableMinimizers
from pooch import retrieve

file_path = "amor_reduced_iofq.ort"

data = load(file_path)

plot(data)

# Set total refelctivity to 1 and plot reduced data

reflectivity = data["data"]["R_0"].values

scale_factor = 1 / np.max(reflectivity)
data["data"]["R_0"].values *= scale_factor

# print(f"Scale factor applied: {scale_factor}")
# print(f"Maximum reflectivity after scaling: {np.max(data['data']['R_0'].values)}")
plot(data)

# Create a model for the sample

si = Material(sld=2.07, isld=0.0, name="Si")
sio2 = Material(sld=3.47, isld=0.0, name="SiO2")
d2o = Material(sld=6.33, isld=0.0, name="D2O")
dlipids = Material(sld=5.0, isld=0.0, name="DLipids")

superphase = Layer(material=si, thickness=0, roughness=0, name="Si superphase")
sio2_layer = Layer(material=sio2, thickness=20, roughness=4, name="SiO2 layer")
dlipids_layer = Layer(material=dlipids, thickness=40, roughness=4, name="DLipids layer")
subphase = Layer(material=d2o, thickness=0, roughness=5, name="D2O subphase")



multi_sample = Sample(
    Multilayer(superphase),
    Multilayer(sio2_layer,),
    Multilayer(dlipids_layer),
    Multilayer(subphase),
    name="Multilayer Structure",
)

multi_layer_model = Model(
    sample=multi_sample,
    scale=1,
    background=0.000001,
    resolution_function=PercentageFwhm(0),
    name="Multilayer Model",
)

# Set the fitting parameters

sio2_layer.roughness.bounds = (3, 12)
sio2_layer.material.sld.bounds = (3.47, 5)
sio2_layer.thickness.bounds = (10, 30)

subphase.material.sld.bounds = (6, 6.35)
dlipids_layer.thickness.bounds = (30, 60)
dlipids_layer.roughness.bounds = (3, 10)
dlipids_layer.material.sld.bounds = (4, 6)

multi_layer_model.scale.bounds = (0.8, 1.2)
multi_layer_model.background.bounds = (1e-6, 1e-3)

# Run the model and plot the results

multi_layer_model.interface = CalculatorFactory()

fitter1 = MultiFitter(multi_layer_model)
fitter1.switch_minimizer(AvailableMinimizers.LMFit_differential_evolution)

analysed = fitter1.fit(data)

plot(analysed)