Commit f7fec1df authored by Edward Andò's avatar Edward Andò
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[skip-ci] dots

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......@@ -195,9 +195,9 @@ Currently, the most-used scripts are related to image correlation:
- `spam-ddic` and `spam-discreteStrain`: A "discrete" image correlation script [@hall2010discrete; @ando2012experimental], working on greyscale 3D images plus a "labelled" image of the reference configuration. This script also has its own strain calculation based on a triangulation of grain centres.
`spam-ddic` is presented in the [scripts page](https://ttk.gricad-pages.univ-grenoble-alpes.fr/spam/scripts.html#discrete-local-dic-script-spam-ddic) and is the subject of the [discrete DIC tutorial](https://ttk.gricad-pages.univ-grenoble-alpes.fr/spam/tutorial-04-discreteDIC.html)
- `spam-gdic` (in beta test): A "global" image correlation script, where the displacement field between two 3D images is computed as a global problem expressed on a tetrahedral mesh.
- `spam-gdic` (in beta test): A "global" image correlation script, where the displacement field between two 3D images is computed as a global problem expressed on a tetrahedral mesh
- `spam-mmr` and `spam-mmr-graphical`: A pair of "multi-modal registration" scripts (command-line and graphical) allowing 3D images of different modalities (*e.g.*, a neutron tomography and an x-ray tomography of the same sample) to be registered (*i.e.*, aligned).
- `spam-mmr` and `spam-mmr-graphical`: A pair of "multi-modal registration" scripts (command-line and graphical) allowing 3D images of different modalities (*e.g.*, a neutron tomography and an x-ray tomography of the same sample) to be registered (*i.e.*, aligned)
# Technical details
......@@ -205,11 +205,11 @@ Currently, the most-used scripts are related to image correlation:
Spam is based on simple Python data types, avoiding complex data structures, and all functions have a reasonable and safe set of default parameters, with required parameters kept to a minimum.
Spam has a number of different use cases:
- Use in a highly interactive manner in iPython or Jupyter. Many outputs from 3D analysis in materials science are highly sensitive to the parameters used, encouraging a "live" exploration of optimal settings.
- Use in a highly interactive manner in iPython or Jupyter. Many outputs from 3D analysis in materials science are highly sensitive to the parameters used, encouraging a "live" exploration of optimal settings
- To be imported and used within user-written Python scripts.
- To be imported and used within user-written Python scripts
- Standalone use of more complex `spam-` scripts. These chain together a number of functions and are intended to be called from a command line, and produce output as live plots, or files saved to disk.
- Standalone use of more complex `spam-` scripts. These chain together a number of functions and are intended to be called from a command line, and produce output as live plots, or files saved to disk
Given the large data volumes often encountered in 3D analysis, critical parts of the code are written in C/C++ wrapped with appropriate Python calling functions which are responsible for checking input sanity.
The current wrapping method is with pybind11 [@pybind11].
......@@ -228,11 +228,11 @@ The documentation for this project is available online at this address:
There are three main components to the documentation:
- The module index is built automatically by `sphinx`, and function headers are written in such a way (following the NumPy norm) that a brief description appears in the module index.
- The module index is built automatically by `sphinx`, and function headers are written in such a way (following the NumPy norm) that a brief description appears in the module index
- A "Gallery of Examples" using `sphinx-gallery` where downloadable Python scripts or Jupyter notebooks are executed during the compilation of the documentation and whose results are visible.
- A "Gallery of Examples" using `sphinx-gallery` where downloadable Python scripts or Jupyter notebooks are executed during the compilation of the documentation and whose results are visible
- A series of "Tutorials" with longer and more detailed explanations are available, which cover the mathematical/mechanics background of the functions provided, and some longer examples of using the provided tools.
- A series of "Tutorials" with longer and more detailed explanations are available, which cover the mathematical/mechanics background of the functions provided, and some longer examples of using the provided tools
<!-- # Other software available -->
......@@ -247,7 +247,7 @@ The `spam.DIC.register` correlation engine uses a well-known mathematical framew
The discrete and multimodal image correlation are much more unique.
A number of other image correlation codes exist (this is by far not an exhaustive list):
- CMV and CMV\_3D: Developed at Laboratoire Navier [@bornert2004mesure], local and non-rigid code allowing discrete DVC used in @hall2010discrete.
- CMV and CMV\_3D: Developed at Laboratoire Navier [@bornert2004mesure], local and non-rigid code allowing discrete DVC used in @hall2010discrete
- Correlli: Developed by LMT Cachan, shared with colleagues but not open source [@hild2008correliq4]. Contains a cutting edge integrated DVC global approach
- FIDVC and qDIC: Open source code 2D running on Matlab [@bar2014fast, @Landauer2018] from The Franck Lab which is suitable for measuring large transformations
- TomoWarp2: Developed by some of the co-authors [@tudisco2017tomowarp2]. This software has a graphical interface for facilitating correlation but is technically limited to displacements/rotations, and has a slow line-search in rotation space
......@@ -269,16 +269,16 @@ Compilation for Windows has not been attempted given the large number of depende
Spam has already enabled research progress on a number of fronts, resulting in the following publications:
- @roubin2016perco: Use of `excursions` toolkit to predict percolation threshold in n-dimensional Euclidean spaces (Figures 1 and 2).
- @stamati2018phase: Use of `filters` toolkit to identify aggregates in concrete (Figure 5).
- @stamati2018tensile: Use of `spam-ldic` and `spam-ddic` scripts to measure deformation in a concrete sample subjected to a tension test (Figure 8) and `mesh` projection functions to conduct the FE analysis (Figure 2).
- @stavropoulou2019liquid: Use of `spam-ldic` script to measure deformation of a claystone (Figures 10 and 11).
- @wiebicke2019benchmark: Use of `kalisphera` (Figure 5) and `label` toolkits to benchmark sand-grain contact measurements (Figure 8 and others), provides an example script.
- @ando2019peek: Use of `spam-ddic` script and the `label` toolkit to measure small displacements in a creep test on sand, see Figure 4.
- @roubin2019colours: Application of Multi Modal Registration to concrete (Figure 4 onwards).
- @hurley2019situ: Use of `deformation` toolkit to measure deformation in concrete (strain in Figure 2b).
- @wiebicke2020measuring: Use of `label` toolkit for the analysis of inter-particle contacts (Figure 1) as well as the `plotting` toolkit to plot the distribution of orientations (Figures 7 and 8).
- @stavropoulou2020: Use of `spam-mmr` and `spam-gdic` scripts (respectively Figures 2, 3, 4; and 7), and the `mesh` toolkit to measure water absorption in claystone (Figures 8 and 9).
- @roubin2016perco: Use of `excursions` toolkit to predict percolation threshold in n-dimensional Euclidean spaces (Figures 1 and 2)
- @stamati2018phase: Use of `filters` toolkit to identify aggregates in concrete (Figure 5)
- @stamati2018tensile: Use of `spam-ldic` and `spam-ddic` scripts to measure deformation in a concrete sample subjected to a tension test (Figure 8) and `mesh` projection functions to conduct the FE analysis (Figure 2)
- @stavropoulou2019liquid: Use of `spam-ldic` script to measure deformation of a claystone (Figures 10 and 11)
- @wiebicke2019benchmark: Use of `kalisphera` (Figure 5) and `label` toolkits to benchmark sand-grain contact measurements (Figure 8 and others), provides an example script
- @ando2019peek: Use of `spam-ddic` script and the `label` toolkit to measure small displacements in a creep test on sand, see Figure 4
- @roubin2019colours: Application of Multi Modal Registration to concrete (Figure 4 onwards)
- @hurley2019situ: Use of `deformation` toolkit to measure deformation in concrete (strain in Figure 2b)
- @wiebicke2020measuring: Use of `label` toolkit for the analysis of inter-particle contacts (Figure 1) as well as the `plotting` toolkit to plot the distribution of orientations (Figures 7 and 8)
- @stavropoulou2020: Use of `spam-mmr` and `spam-gdic` scripts (respectively Figures 2, 3, 4; and 7), and the `mesh` toolkit to measure water absorption in claystone (Figures 8 and 9)
# Acknowledgements
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