nabu.stitching.alignment module¶
- class nabu.stitching.alignment.AlignmentAxis2(value, names=None, *, module=None, qualname=None, type=None, start=1, boundary=None)[source]¶
Bases:
Enum
Specific alignment named to help users orienting themself with specific name
- CENTER = 'center'¶
- LEFT = 'left'¶
- RIGTH = 'right'¶
- class nabu.stitching.alignment.AlignmentAxis1(value, names=None, *, module=None, qualname=None, type=None, start=1, boundary=None)[source]¶
Bases:
Enum
Specific alignment named to help users orienting themself with specific name
- FRONT = 'front'¶
- CENTER = 'center'¶
- BACK = 'back'¶
- nabu.stitching.alignment.align_frame(data: ndarray, alignment: _Alignment, alignment_axis: int, new_aligned_axis_size: int, pad_mode='constant')[source]¶
Align 2D array to extend if size along alignment_axis to new_aligned_axis_size.
- Parameters:
data (numpy.ndarray) – data (frame) to align (2D numpy array)
alignment_axis – axis along which we want to align the frame. Must be in (0, 1)
alignment (HAlignment) – alignment strategy
new_width (int) – output data width
- nabu.stitching.alignment.align_horizontally(data: ndarray, alignment: AlignmentAxis2, new_width: int, pad_mode='constant')[source]¶
Align data horizontally to make sure new data width will ne new_width.
- Parameters:
data (numpy.ndarray) – data to align
alignment (HAlignment) – alignment strategy
new_width (int) – output data width
- class nabu.stitching.alignment.PaddedRawData(data: ndarray | Dataset, axis_1_pad_width: tuple)[source]¶
Bases:
object
Util class to extend a data when necessary Must to aplpy to a volume and to an hdf5dataset - array The idea behind is to avoid loading all the data in memory
- property empty_frame¶
- property shape¶
- property raw_data¶
- property raw_data_start¶
- property raw_data_end¶
- property dtype¶