scarlet.renderer¶

class scarlet.renderer.ConvolutionRenderer(data_frame, model_frame, *parameters, convolution_type='fft', padding=10, psf_shift=None)[source]¶

Bases: scarlet.renderer.Renderer

Attributes

children: List of child models
convolution_bounds: Build the slices needed for convolution in real space
parameters: List of parameters, including from the children

Methods

`__call__`(model, *parameters)	Call self as a function.
`check_parameters`()	Check that all parameters have finite elements
`convolve`(model[, convolution_type, psf_shift])	Convolve the model in a single band
`get_channel_map`(data_frame, model_frame)	Compute the mapping between channels in the model frame and this observation
`get_model`(*parameters)	Get the model realization
`get_models_of_children`(parameters, *kwargs)	Get realization of all child models
`get_parameter`(i, *parameters)	Access parameters by list index or by name
`map_channels`(model)	Map to model channels onto the observation channels
`update`()	Update internal state or configuration of the model

property convolution_bounds¶: Build the slices needed for convolution in real space

convolve(model, convolution_type=None, psf_shift=None)[source]¶: Convolve the model in a single band

get_model(*parameters)[source]¶

Get the model realization

Parameters

parameters: tuple of optimimzation parameters

Returns

model: array: Realization of the model

class scarlet.renderer.NullRenderer(data_frame, model_frame)[source]¶

Bases: scarlet.renderer.Renderer

Attributes

children: List of child models
parameters: List of parameters, including from the children

Methods

`__call__`(model, *parameters)	Call self as a function.
`check_parameters`()	Check that all parameters have finite elements
`get_channel_map`(data_frame, model_frame)	Compute the mapping between channels in the model frame and this observation
`get_model`()	Get the model realization
`get_models_of_children`(parameters, *kwargs)	Get realization of all child models
`get_parameter`(i, *parameters)	Access parameters by list index or by name
`map_channels`(model)	Map to model channels onto the observation channels
`update`()	Update internal state or configuration of the model

get_model()[source]¶

Get the model realization

Parameters

parameters: tuple of optimimzation parameters

Returns

model: array: Realization of the model

class scarlet.renderer.Renderer(data_frame, model_frame, *parameters)[source]¶

Bases: scarlet.model.Model

Attributes

children: List of child models
parameters: List of parameters, including from the children

Methods

`__call__`(model, *parameters)	Call self as a function.
`check_parameters`()	Check that all parameters have finite elements
`get_channel_map`(data_frame, model_frame)	Compute the mapping between channels in the model frame and this observation
`get_model`(parameters, *kwargs)	Get the model realization
`get_models_of_children`(parameters, *kwargs)	Get realization of all child models
`get_parameter`(i, *parameters)	Access parameters by list index or by name
`map_channels`(model)	Map to model channels onto the observation channels
`update`()	Update internal state or configuration of the model

get_channel_map(data_frame, model_frame)[source]¶

Compute the mapping between channels in the model frame and this observation

Parameters

model_frame: a `scarlet.Frame` instance: The frame to match

Returns

channel_map: None, slice, or array: None for identical channels in both frames; slice for concatenated channels; array for linear mapping of model channels onto observation channels

map_channels(model)[source]¶

Map to model channels onto the observation channels

Parameters

model: array: The hyperspectral model

Returns

obs_model: array: model mapped onto the observation channels

class scarlet.renderer.ResolutionRenderer(data_frame, model_frame, padding=10)[source]¶

Bases: scarlet.renderer.Renderer

Attributes

children: List of child models
parameters: List of parameters, including from the children

Methods

`__call__`(model, *parameters)	Call self as a function.
`build_diffkernel`(data_frame, model_frame)	Builds the differential convolution kernel between the observation and the model psf
`check_parameters`()	Check that all parameters have finite elements
`get_channel_map`(data_frame, model_frame)	Compute the mapping between channels in the model frame and this observation
`get_model`(*parameters)	Get the model realization
`get_models_of_children`(parameters, *kwargs)	Get realization of all child models
`get_parameter`(i, *parameters)	Access parameters by list index or by name
`map_channels`(model)	Map to model channels onto the observation channels
`sinc_shift`(imgs, shifts, axes)	Performs 2 1D sinc convolutions and shifting along one rotated axis in Fourier space.
`update`()	Update internal state or configuration of the model

build_diffkernel(data_frame, model_frame)[source]¶

Builds the differential convolution kernel between the observation and the model psf

Parameters

model_frame: Frame object: the frame of the model
Returns
——-
diff_psf: array: the differential psf between observation and frame psf.

get_model(*parameters)[source]¶

Get the model realization

Parameters

parameters: tuple of optimimzation parameters

Returns

model: array: Realization of the model

sinc_shift(imgs, shifts, axes)[source]¶

Performs 2 1D sinc convolutions and shifting along one rotated axis in Fourier space.

Parameters

imgs: Fourier: a Fourier object of 2D data to sinc convolve and shift to the adequate shape.
shifts: array: an array of the shift values for each line and columns of data in imgs
axes: array: Optional argument that specifies the axes along which to apply sinc convolution.

Returns

result: array: the shifted and sinc convolved array in configuration space