@@ -214,7 +214,7 @@ Spam has a number of different use cases:

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].

Building on the large number of functions already available in NumPy [@numpy], SciPy [@SciPy2020], scikit-image [@scikitimage] and making use of tifffile [@tifffile] and meshio [@meshio], spam adds a large amount of functionality, which means that a number of advanced forms of data analysis can be chained together in ways that are otherwise complex, requiring the combination of many different tools.

Building on the large number of functions already available in NumPy [@numpy], SciPy [@SciPy2020], scikit-image [@scikitimage] and making use of tifffile [@tifffile] and meshio [@meshio], the spam project adds a large amount of functionality, which means that a number of advanced forms of data analysis can be chained together in ways that are otherwise complex, requiring the combination of many different tools.

Spam uses `unittest` to check each commit with a coverage of more than 90\% of lines of code covered as of June 2020.

[Details of the coverage](https://ttk.gricad-pages.univ-grenoble-alpes.fr/spam/coverage/) are available on the GitLab repository.

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@@ -243,9 +243,9 @@ Other open-source packages include ITK [@schroeder2003itk], which is a quite com

All of the above have some version of the `label` toolkit which allows discrete objects to be characterised as well as some parts of the `measurements` toolkit.

On the specific topic of Digital Image/Volume Correlation, many pieces of software are available for 2D, surface and 3D image correlation.

The `spam.DIC.register` correlation engine uses a well-known mathematical framework dating back to [@lucasKanade], but distinguishes itself by being non-rigid, 2/3D compatible, clearly documented and relatvely fast.

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):

The `spam.DIC.register` correlation engine uses a well-known mathematical framework dating back to [@lucasKanade], but distinguishes itself by being non-rigid, 2/3D compatible, clearly documented and relatively fast.

The discrete and multimodal image correlation are much less common.

A number of other image correlation codes exist (this is really not an exhaustive list):

- CMV and CMV\_3D: Developed at Laboratoire Navier [@bornert2004mesure], local and non-rigid code allowing discrete DVC used in @hall2010discrete

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@@ -294,7 +294,7 @@ Spam has already enabled research progress on a number of fronts, resulting in t

- @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)

- @stavropoulou2020: Use of `spam-mmr` and `spam-gdic` scripts (Figures 2, 3, 4 and Figure 7 respectively), and the `mesh` toolkit to measure water absorption in claystone (Figures 8 and 9)