lightkurve.correctors.DesignMatrixCollection

class lightkurve.correctors.DesignMatrixCollection(matrices)

Object which stores multiple design matrices.

DesignMatrixCollection objects are useful when users want to regress against multiple different systematics, but still keep the different systematics distinct.

Examples

>>> from lightkurve.correctors.designmatrix import create_spline_matrix, DesignMatrix, DesignMatrixCollection
>>> dm1 = create_spline_matrix(np.arange(100), n_knots=5, name='spline')
>>> dm2 = DesignMatrix(np.arange(100), name='slope')
>>> dmc = DesignMatrixCollection([dm1, dm2])
>>> dmc
DesignMatrixCollection:
    spline DesignMatrix (100, 5)
    slope DesignMatrix (100, 1)
>>> dmc.matrices
[spline DesignMatrix (100, 5), slope DesignMatrix (100, 1)]

__init__(matrices)

Methods

__init__(matrices)
plot([ax])	Visualize the design matrix values as an image.
plot_priors([ax])	Visualize the prior_mu and prior_sigma attributes.
split(row_indices)	Returns a new DesignMatrixCollection with regressors split into multiple columns.
standardize()	Returns a new DesignMatrixCollection in which all the matrices have been standardized using the DesignMatrix.standardize method.
to_designmatrix([name])	Flatten a DesignMatrixCollection into a DesignMatrix.
validate()

Attributes

columns	List of column names.
prior_mu	Coefficient prior means.
prior_sigma	Coefficient prior standard deviations.
values	2D numpy array containing the matrix values.

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