NEWS (original) (raw)

tealeaves (development version)

tealeaves 1.0.6

• Fixed name in inst/CITATION
• Stopped parallel evaluation in vignette
• Fixed links in README

tealeaves 1.0.5

• Updated site, vignettes, and README

tealeaves 1.0.4

• Added unit tests for parameter functions undertests/test-parameter-functions.R
• Fixed bug with crossing parameters in tleaves() that was introduced with new T_sky function. This led to crossing all parameter values with all unique values of calculatedT_sky, which was incorrect. Added unit tests to ensuring that crossing is done correctly undertests/test-tleaves-crossing.R
• Added code coverage using codecov

tealeaves 1.0.3

• Fixed bug in .get_Rabs() that would have over-written custom T_sky function.

tealeaves 1.0.2

• Added citation to published paper. Seecitation(package = "tealeaves").
• Compatible with dplyr 1.0.0
• In enviro_par(), “sky” temperature (T_sky) can now be provided directly as a values (in K) or as a function (the default).
• If parallel = TRUE in tleaves(),future uses plan("multisession") rather than plan("multiprocess").
• New vignette on making parameters functions of other parameters.
• Added full URL for CONDUCT.md in README

tealeaves 1.0.1

• constants(), enviro_par(), andleaf_par() no longer require values be provided with units. If values are provided without units, they are assigned proper units, but no unit conversion is performed. If values have units, these functions check whether units are correct and convert them to units used in the package.
• Release to be archived with revision of “Is amphistomy an adaptation to high light? Optimality models of stomatal traits along light gradients.”
• Blog post.

tealeaves 1.0.0

tealeaves implements models of leaf temperature using energy balance. It uses units to ensure that parameters are properly specified and transformed before calculations. It allows separate lower and upper surface conductances to heat and water vapor, so sensible and latent heat loss are calculated for each surface separately as in Foster and Smith (1986). It’s straightforward to model leaf temperature over environmental gradients such as light, air temperature, humidity, and wind. It can also model leaf temperature over trait gradients such as leaf size or stomatal conductance.

• Added a NEWS.md file to track changes to the package.