smps.fit.LogNormalFitResults.predict

LogNormalFitResults.predict(X, weight='number')

Predict new values using the fit model.

Parameters

Xarray-like

An array of particle diameters at which to predict the number concentration based on the fit model.

weight: str, default=’number’

The moment of the model to fit at. Should be one of (‘number’, ‘surface’, ‘volume’).

Returns

An array of number concentrations.

Examples

Predict the number concentration at 1 and 2.5 µm:

>>> from smps.fit import LogNormal
>>>
>>> model = LogNormal()
>>>
>>> results = model.fit(obj.midpoints, obj.dndlogdp.mean(), modes=1)
>>> 
>>> results.predict([1., 2.5])