Forward Projector Gpu

Description

This plugin uses ToMoBAR software and GPU Astra projector to generate parallel-beam projection data. The plugin will project the given object using the available metadata OR user-provided geometry. In case when angles set to None, the metadata projection geometry will be used.

Parameters

in_datasets:
    visibility: datasets
    dtype: "[list[],list[str]]"
    description:
        summary: A list of the dataset(s) to process.
        verbose: A list of strings, where each string gives the name of a dataset that was either specified by a loader plugin or created as output to a previous plugin.  The length of the list is the number of input datasets requested by the plugin.  If there is only one dataset and the list is left empty it will default to that dataset.
    default: "[]"

out_datasets:
    visibility: datasets
    dtype: "[list[],list[str]]"
    description: The default names
    default: "['forw_proj']"

angles_deg:
    visibility: advanced
    dtype: "[None, list[float,float,int]]"
    description: "Projection angles in degrees in a format [start, stop, total number of angles]."
    default: None

det_horiz:
    visibility: advanced
    dtype: "[None,int]"
    description: The size of the horizontal detector.
    default: None

centre_of_rotation:
    visibility: advanced
    dtype: "[None,float]"
    description: The centre of rotation.
    default: None

Key

visibility: The visibility level of the parameter
dtype: The type of data
description: A short explanation of the parameter
default: The default value
options: A list of permitted values
dependency: The name of the parameter and value which this parameter depends upon
range: A guide for the range of the parameter

Citations

No citations

API

class ForwardProjectorGpu

get_max_frames()

nInput_datasets()

The number of datasets required as input to the plugin

Returns

Number of input datasets

nOutput_datasets()

The number of datasets created by the plugin

Returns

Number of output datasets

new_shape(full_shape, data)

post_process()

This method is called after the process function in the pipeline framework as a post-processing step. All processes will have finished performing the main processing at this stage.

Parameters

exp (experiment class instance) – An experiment object, holding input and output datasets

pre_process()

This method is called immediately after base_pre_process().

process_frames(data)

This method is called after the plugin has been created by the pipeline framework and forms the main processing step

Parameters

data (list(np.array)) – A list of numpy arrays for each input dataset.

set_filter_padding(**kwargs)

Should be overridden to define how wide the frame should be for each input data set

setup(**kwargs)

This method is first to be called after the plugin has been created. It determines input/output datasets and plugin specific dataset information such as the pattern (e.g. sinogram/projection).