tuskitoo.SpectralExtraction.function_maker module

create_multigaussian_model(num_image, ydata, initial_separation=None, initial_center=None)[source]

Creates a multi-Gaussian model for fitting purposes.

Parameters:

num_imageint: Number of images to be modeled.
ydataarray-like: The dependent data (observations or measurements) to be modeled.
initial_separationlist or None, optional, default=None: Initial guess for the separation between the Gaussian components. If provided, the parameters of the model will be named as center1, separation2, separation3, …, etc.
initial_centerfloat or None, optional, default=None: Initial estimates for the center (mean or peak position) of each Gaussian component. If initial_separation is not provided, the parameters of the model will be named as center1, center2, center3, …, etc.

modelModel object: The constructed multi-Gaussian model with the specified initial parameters.

If initial_separation is provided, the model parameters will be named as center1, separation2, separation3, …, etc.
If initial_separation is not provided, the model parameters will be named as center1, center2, center3, …, etc.

create_multimoffat_model(num_image, ydata, initial_separation=None, initial_center=None)[source]

Creates a multi-Moffat model for fitting purposes.

num_imageint: Number of images to be modeled.
ydataarray-like: The dependent data (observations or measurements) to be modeled.
initial_separationlist or None, optional, default=None: Initial guess for the separation between the Moffat components. If provided, the parameters of the model will be named as center1, separation2, separation3, …, etc.
initial_centerfloat or None, optional, default=None: Initial estimates for the center (mean or peak position) of each Moffat component. If initial_separation is not provided, the parameters of the model will be named as center1, center2, center3, …, etc.

modelModel object: The constructed multi-Moffat model with the specified initial parameters.

If initial_separation is provided, the model parameters will be named as center1, separation2, separation3, …, etc.
If initial_separation is not provided, the model parameters will be named as center1, center2, center3, …, etc.