savu.data.data_structures.data_notes module

axis_labels()

Note

axis_labels keyword argument

Options to pass are:

1. Data object: Copy all labels from the Data object.

   >>> out_dataset[0].create_dataset(axis_labels=in_dataset[0], shape=new_shape)
   

2. {Data_obj: list}: Copy labels from the Data object and then remove or insert.

• To remove dimensions: list_entry = ‘dim’. For example, to remove the first and last axis_labels from the copied list:

>>> out_dataset[0].create_dataset(axis_labels={in_dataset[0]: ['1', '-1']), shape=new_shape})

• To add/replace dimensions: list_entry = ‘dim.name.unit’.

>>> out_dataset[0].create_dataset(axis_labels={in_dataset[0]: ['2.det_x.pixel', '3.det_y.pixel']}, shape=new_shape)

• To insert dimensions: list_entry = ‘~dim.name.unit’.

>>> out_dataset[0].create_dataset(axis_labels={in_dataset[0]: ['~2.det_x.pixel', '~3.det_y.pixel']}, shape=new_shape)

(or a combination, where each successive step is applied after the previous changes have been made.)

3. list: Where each element is of the form ‘name.unit’.

   >>> out_dataset[0].create_dataset(axis_labels=['rotation.deg', 'det_x.pixel', 'det_y.pixel'], shape=new_shape)
   

image_key()

This is a helper function to be used after savu.data.data_structures.data_create.DataCreate.create_dataset(),

>>> out_dataset[0].create_dataset(in_dataset[0])
>>> out_dataset[0].trim_output_data(in_dataset[0], image_key=0)

if in_dataset[0] is a plugin input dataset with an image_key and 0 is the data index.

patterns()

Note

patterns keyword argument

Options to pass are:

1. Data object: Copy all patterns from the Data object.

   >>> out_dataset[0].create_dataset(axis_labels=labels, shape=new_shape, patterns=in_dataset[0])
   

2. {Data_obj: list}: Copy only the patterns given in the list from the Data object.

• Copy the patterns: list_entry = ‘name’

>>> out_dataset[0].create_dataset(axis_labels=labels, shape=new_shape, patterns={in_dataset[0]: ['SINOGRAM', 'PROJECTION']})

• Copy patterns but remove dimensions: list_entry = ‘name1.r1,r2…’:

>>> out_dataset[0].create_dataset(axis_labels=labels, shape=new_shape, patterns={in_dataset[0]: ['SINOGRAM.1', 'PROJECTION.1']})

• Copy ALL patterns but remove dimensions: list_entry = ‘*.r1,r2…’:

>>> out_dataset[0].create_dataset(axis_labels=labels, shape=new_shape, patterns={in_dataset[0]: '*.0'})