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
: asklearn.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)