smps.fit.LogNormal#

class smps.fit.LogNormal#

A multi-mode LogNormal particle size distribution.

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

See also

Examples

Create a single-mode fit:

>>> from smps.fit import LogNormal
>>> model = LogNormal()
>>> results = model.fit(obj.midpoints, obj.dndlogdp.mean(), modes=1)