mumott

mumott is a Python library for the analysis of multi-modal tensor tomography data.

Main

• Background
• Workflow
  • Pipelines
  • Object structure
  • Asynchronous reconstruction

Tutorials

• Loading and inspecting data
  • The DataContainer object
  • Inspecting individual projections
  • Geometry
  • Skipping data
• Phase matching alignment of data
  • Inspecting the original data
  • First run
  • Second run
  • Third run
  • Comparing projections
  • Saving
• Optical flow alignment
  • Loading data
  • Checking unaligned data
  • Step 1: Approximate alignment
  • Step 2: Refinement
  • Final comparison
• Reconstruction using pipelines
  • SIRT – simultaneous iterative reconstruction tomography
  • MITRA - modular iterative tomographic reconstruction algorithm
  • DD - discrete directions
• Regularization L-curves
  • SIGTT - Spherical Integral Geometric Tensor Tomgraphy
• Asynchronous reconstruction
  • Asynchronous Tensor SIRT
  • MOTR - Momentum-accelerated Total variation Reconstruction
  • RADTT - Huber-TV reconstruction
• Reconstruction and visualization
  • Loading data
  • Initializing the DataContainer
  • Visualizing the output
• Projection and adjoint
  • Loading data
  • Looking at the simulated data
  • The adjoint
• Line segment integration
  • SLERP
  • NearestNeighbor
  • GaussianKernels
  • SphericalHarmonics
  • Evaluation
  • Line segment length
  • Weak additivity
• Simulation of samples
  • Defining the volume
  • Defining the simulation and sources
  • Carrying out the simulation
  • Creating artificial data
  • Reconstructing the artifical data
• Zonal harmonics 2-step reconstruction workflow
  • Imports
  • Initialize objects for first optimization
  • First optimization
  • Find approximate symmetry axis
  • Choose a direction and calculate the best-fit symmetric coefficients
  • Fit the symmetric model
  • Generate output

Function reference

• Data handling
  • DataContainer
  • Utilities
• Methods
  • Basis sets
  • Projectors
  • Residual calculators
  • Utilities
• Optimization
  • Loss functions
  • Regularizers
  • Optimizers
• Output handling
  • OrientationImageMapper
  • ProjectionViewer
• Pipelines
  • Reconstruction
  • Alignment
  • Utilities
• Core
  • Geometry
  • GeometryTuple
  • ProjectionStack
  • Projection
  • SphericalHarmonicMapper
  • ProbedCoordinates
  • Simulator
  • list_to_hash()
  • john_transform()
  • john_transform_adjoint()
  • john_transform_adjoint_cuda()
  • john_transform_cuda()
  • john_transform_adjoint_sparse_cuda()
  • john_transform_sparse_cuda()
  • cuda_difference()
  • cuda_framewise_contraction()
  • cuda_framewise_contraction_adjoint()
  • cuda_l1_gradient()
  • cuda_lower_bound()
  • cuda_rescale()
  • cuda_rescale_array()
  • cuda_scaled_difference()
  • cuda_sum()
  • cuda_tv_gradient()
  • cuda_weighted_difference()
  • cuda_weighted_sign()
  • calculate_sph_coefficients_rotated_around_z()
  • calculate_sph_coefficients_rotated_around_z_derived_wrt_the_angle()
  • calculate_sph_coefficients_rotated_by_90_degrees_around_negative_x()
  • calculate_sph_coefficients_rotated_by_90_degrees_around_positive_x()
  • calculate_sph_coefficients_rotated_by_euler_angles()
  • load_d_matrices()

Backmatter

• Bibliography
• Glossary
• Index