Documentation for design_matrix

scatterbrain.designmatrix.design_matrix (ABC)

Base class to store design matrices. This is an abstract base class.

design_matrix objects have the following properties.

Attributes:

Name	Type	Description
name	str	Name of the design matrix
prior_mu	xp.ndarray, int or float	The prior mean of the design matrix components
prior_sigma	xp.ndarray, int or float	The prior standard deviation of the design matrix components
sigma_f	xp.ndarray	The weights for each pixel in the design matrix. Default is equal weights.
A	xp.ndarray	The design matrix array.
sigma_w_inv	xp.ndarray	Inverse covariance matrix of the design matrix
shape	tuple	Shape of the design matrix

copy(self)

Create a deep copy of self

dot(self, other)

Takes the dot product of self with a vector.

fit_batch(self, flux_cube)

Fit a given cube of data

Parameters:

Name	Type	Description	Default
flux	np.ndarray	3D array of values, must be shape (N, self.shape[1]**0.5, self.shape[1]**0.5)	required

Returns:

Type	Description
np.ndarray	2D array of weights, shape (N, self.shape[0])

fit_frame(self, flux)

Fit a given frame of data

Parameters:

Name	Type	Description	Default
flux	np.ndarray	2D array of values, must be shape (self.shape[1]**0.5, self.shape[1]**0.5)	required

Returns:

Type	Description
np.ndarray	1D array of weights, shape self.shape[0], i.e. number of components

join(self, other)

Join two design matrices together, by stacking them horizontally.

update_sigma_f(self, sigma_f)

Update the sigma_f values with new ones.

scatterbrain.designmatrix.TESS_design_matrix (design_matrix)

design_matrix Class specifically for working with TESS. Note you can not initialize this class, it has no _build method.

This object hard codes certain values, for example that TESS images are 2048x2048 pixels.

Attributes:

Name	Type	Description
ccd	int	CCD number
column	None or xp.ndarray	The column numbers to evaluate the design matrix at. If None, uses all pixels.
row	None or xp.ndarray	The column numbers to evaluate the design matrix at. If None, uses all pixels.
cutout_size	int	Size of a "cutout" of images to use. Default is 2048. Use a smaller cut out to test functionality
bore_pixel	tuple	Location of the pixel closest to the telescope boresight
name	str	Name of the design matrix
prior_mu	xp.ndarray, int or float	The prior mean of the design matrix components
prior_sigma	xp.ndarray, int or float	The prior standard deviation of the design matrix components
sigma_f	xp.ndarray	The weights for each pixel in the design matrix. Default is equal weights.
A	xp.ndarray	The design matrix array.
sigma_w_inv	xp.ndarray	Inverse covariance matrix of the design matrix
shape	tuple	Shape of the design matrix

__init__(self, sigma_f=None, prior_sigma=None, prior_mu=None, ccd=3, column=None, row=None, name='TESS', cutout_size=2048) special

Create a TESS_design_matrix object. Note, you can not initialize this object as it has no _build method.

Parameters:

Name	Type	Description	Default
sigma_f	xp.ndarray	The weights for each pixel in the design matrix. Default is equal weights.	None
prior_sigma	xp.ndarray, int or float	The prior standard deviation of the design matrix components	None
prior_mu	xp.ndarray, int or float	The prior mean of the design matrix components	None
ccd	int	CCD number	3
column	None or xp.ndarray	The column numbers to evaluate the design matrix at. If None, uses all pixels.	None
row	None or xp.ndarray	The column numbers to evaluate the design matrix at. If None, uses all pixels.	None
name	str	Name for design matrix	'TESS'
cutout_size	int	Size of a "cutout" of images to use. Default is 2048. Use a smaller cut out to test functionality	2048

scatterbrain.designmatrix.cartesian_design_matrix (TESS_design_matrix)

Design matrix for 2D Polynomial in cartesian space

__init__(self, sigma_f=None, prior_sigma=None, prior_mu=None, ccd=3, npoly=5, column=None, row=None, cutout_size=2048) special

Create a cartesian_design_matrix object.

Parameters:

Name	Type	Description	Default
sigma_f	xp.ndarray	The weights for each pixel in the design matrix. Default is equal weights.	None
prior_sigma	xp.ndarray, int or float	The prior standard deviation of the design matrix components	None
prior_mu	xp.ndarray, int or float	The prior mean of the design matrix components	None
ccd	int	CCD number	3
npoly	int	Order of polymomial to create.	5
column	None or xp.ndarray	The column numbers to evaluate the design matrix at. If None, uses all pixels.	None
row	None or xp.ndarray	The column numbers to evaluate the design matrix at. If None, uses all pixels.	None
name	str	Name for design matrix	required
cutout_size	int	Size of a "cutout" of images to use. Default is 2048. Use a smaller cut out to test functionality	2048

scatterbrain.designmatrix.radial_design_matrix (TESS_design_matrix)

Design matrix for creating a polynomial in radial dimension from boresight pixel

__init__(self, sigma_f=None, prior_sigma=None, prior_mu=None, ccd=3, npoly=10, column=None, row=None, cutout_size=2048) special

Create a radial_design_matrix object.

Parameters:

Name	Type	Description	Default
sigma_f	xp.ndarray	The weights for each pixel in the design matrix. Default is equal weights.	None
prior_sigma	xp.ndarray, int or float	The prior standard deviation of the design matrix components	None
prior_mu	xp.ndarray, int or float	The prior mean of the design matrix components	None
ccd	int	CCD number	3
npoly	int	Order of polymomial to create.	10
column	None or xp.ndarray	The column numbers to evaluate the design matrix at. If None, uses all pixels.	None
row	None or xp.ndarray	The column numbers to evaluate the design matrix at. If None, uses all pixels.	None
name	str	Name for design matrix	required
cutout_size	int	Size of a "cutout" of images to use. Default is 2048. Use a smaller cut out to test functionality	2048

scatterbrain.designmatrix.spline_design_matrix (TESS_design_matrix)

Design matrix for creating a 2D cartesian spline.

__init__(self, sigma_f=None, prior_sigma=None, prior_mu=None, ccd=3, nknots=40, degree=2, column=None, row=None, cutout_size=2048) special

Create a spline_design_matrix object.

Parameters:

Name	Type	Description	Default
sigma_f	xp.ndarray	The weights for each pixel in the design matrix. Default is equal weights.	None
prior_sigma	xp.ndarray, int or float	The prior standard deviation of the design matrix components	None
prior_mu	xp.ndarray, int or float	The prior mean of the design matrix components	None
ccd	int	CCD number	3
nknots	int	Number of knots to use	40
degree	int	Degree of basis spline	2
column	None or xp.ndarray	The column numbers to evaluate the design matrix at. If None, uses all pixels.	None
row	None or xp.ndarray	The column numbers to evaluate the design matrix at. If None, uses all pixels.	None
name	str	Name for design matrix	required
cutout_size	int	Size of a "cutout" of images to use. Default is 2048. Use a smaller cut out to test functionality	2048

scatterbrain.designmatrix.spline_design_matrix (TESS_design_matrix)

Design matrix for creating a 2D cartesian spline.

__init__(self, sigma_f=None, prior_sigma=None, prior_mu=None, ccd=3, nknots=40, degree=2, column=None, row=None, cutout_size=2048) special

Create a spline_design_matrix object.

Parameters:

Name	Type	Description	Default
sigma_f	xp.ndarray	The weights for each pixel in the design matrix. Default is equal weights.	None
prior_sigma	xp.ndarray, int or float	The prior standard deviation of the design matrix components	None
prior_mu	xp.ndarray, int or float	The prior mean of the design matrix components	None
ccd	int	CCD number	3
nknots	int	Number of knots to use	40
degree	int	Degree of basis spline	2
column	None or xp.ndarray	The column numbers to evaluate the design matrix at. If None, uses all pixels.	None
row	None or xp.ndarray	The column numbers to evaluate the design matrix at. If None, uses all pixels.	None
name	str	Name for design matrix	required
cutout_size	int	Size of a "cutout" of images to use. Default is 2048. Use a smaller cut out to test functionality	2048