samc 1.3.0

Fixed an issue with the check() function when data contains NA’s.
Fixed an issue with the raster returned from locate(samc) having 0 for NA cells.
Improved error checking and messaging for the check() and locate() functions.
Named rows and columns for the P matrix is now supported. Previously, naming the rows and columns would cause some checks fail. If names are not manually assigned, the names are simply the row/column numbers converted to character strings.
Analytical functions updated to support named inputs for the origin and dest location parameters
When both the origin and dest parameter is used in a function, the inputs can be paired vectors.
Added the pairwise() utility function
Created a new Locations tutorial vignette for new location input options.

samc 1.2.1

Fixed a regression in v1.2.0 where the samc() function would not work correctly unless matrix/raster layers contained at least one NA cell
Revamped the automated test suite with more test scenarios to better catch issues before release
Added checks during samc-class creation to prevent potential issues with discontinuous/clumped input data. Currently, this type of data will not work with the cond_passage() function, but will in a future release.
Reworked some of the vignettes to produce cleaner pages and remove suggested dependencies (e.g. gifski, gganimate, ggplot2) from the package so that users aren’t bugged about installing them if they don’t need them.

Added the ability to create samc-class objects from a custom P matrix using p_mat parameter in samc(). See the samc() documentation for details
Added the cond_passage() function, which calculates conditional mean first passage times
Added the locate() function, which functions similarly to the cellFromXY() function in the raster package. It’s used to get cell numbers from xy coords, but unlike cellFromXY(), it properly accounts for how cells are numbered when the P matrix is constructed.
Adjusted the absorption inputs to support values of 0 (i.e., no absorption). Currently, at least one cell must have a non-zero value
Fixed an issue where raster/matrix inputs containing isolated cells (individual cells neighbored by only NA values) would lead to malformed P matrices.

Added support for the use vectors of time steps in most short-term metrics. It is more computationally efficient and ergonomic to do this rather than calculating short-term metrics for each individual time step. Some key points:
- When vector inputs are used for time steps, the result is contained in a list
- The names of the entries in the list are character versions of the corresponding time step values
- Time step vectors must consist of ordered positive integers with no duplicate values
- Time step vector inputs have not been added for short-term metrics that return dense matrices
Updated the map() function to support list inputs generated by the short-term metrics. The result is a list of RasterLayers
Updated the Temporal Analysis and Animations vignettes to incorporate time step vectors
Created a Gitter community for package support. Gitter badges on the README and home pages can be used to access it.
Updated the package citation info to refer to Marx et al. (2020, DOI: 10.1111/ecog.04891)

Complete package rewrite (code dependent on v0.1.0 will not work)
samc-class for managing SAMC data
Utility functions for creating samc-class objects, checking inputs, and mapping data
Heavily optimized analytical functions for all metrics described in Fletcher et al. (2019, DOI: 10.1111/ele.13333)
- Utilizing sparse matrices
- Eigen C++ implementation via Rcpp and RcppEigen
Updated example data
Extensive documentation
Several tutorials

Created crude functions for calculating metrics in Fletcher et al. (2019, DOI: 10.1111/ele.13333)
Included example data