smps.fit.LogNormal.fit#
- LogNormal.fit(X, Y, modes=1, xmin=None, xmax=None, weight='number', fit_kwargs=None, **kwargs)#
Fit a multi-mode lognormal aerosol distribution.
- Parameters
- Xarray-like
Training data
- Yarray-like
The target values.
- modesint, default=1
The number of models for the model to fit to.
- xminfloat, default=None
The minimum particle diameter (in nm) to consider.
- xmaxfloat, default=None
The maximum particle diameter (in nm) to consider.
- weightstr, default=’number’
The moment of the distribution to fit. Should be one of (“number”, “surface”, “volume”).
- fit_kwargsdict
Optional kwargs to be passed directly to
scipy.optimize.curve_fit. Read more here.- p0array-like
Array of initial guesses
- Returns
- smps.fit.LogNormalFitResults
Examples
Create a single-mode fit:
>>> from smps.fit import LogNormal >>> model = LogNormal() >>> results = model.fit(obj.midpoints, obj.dndlogdp.mean(), modes=1)