Generate search space

This function is implemented in the gpModel class to generate a search space.

genSearchSpace(self, parameters)

Function to fit the data to Gaussian process regression model.

Parameters:

parameters – dict. A dictionary containing the parameters for finding the top signals.

It generates the following attributes in the gpModel object:

  • gridX: a numpy array containing the gradients for the search space.

  • gradientPct: a 1D numpy array containing the percentage of strong mobile phase used by each gradient in the search space.

  • scaler: a sklearn.preprocessing.StandardScaler object used to scale the data.

  • scaledX: a numpy array containing the scaled gradients for the search space.

To use this function:

# You need a gpModel object (d).

d.genSearchSpace(parameters)