Coverage and other badges

.Rbuildignore

@@ -1,3 +1,4 @@
+^codecov\.yml$
 ^README\.Rmd$
 ^data-raw$
 ^.*\.Rproj$

.travis.yml

@@ -11,3 +11,6 @@ before_install:
   - mkdir -p ~/.R
   - echo "CXX14FLAGS=-O3 -mtune=native -march=native -Wno-unused-variable -Wno-unused-function  -Wno-macro-redefined" >> ~/.R/Makevars
   - echo "CXX14=g++ -std=c++1y -fPIC" >> ~/.R/Makevars
+
+after_success:
+    - Rscript -e 'covr::codecov()'

DESCRIPTION

@@ -38,7 +38,8 @@ Suggests:
     dplyr,
     tmbstan,
     knitr,
-    rmarkdown
+    rmarkdown,
+    covr
 LinkingTo: 
     TMB,
     RcppEigen

README.Rmd

@@ -15,17 +15,10 @@ knitr::opts_chunk$set(
 
 # sdmTMB
 
-**This package is not ready for use yet! I have not simulation tested the model and there's no guarantee I haven't made a mistake.**
-
-[![Travis build status](https://travis-ci.org/seananderson/sdmTMB.svg?branch=master)](https://travis-ci.org/seananderson/sdmTMB)
-
-The goal of sdmTMB is to
-
-- Be useful for our purpose of fitting high resolution species distribution models of groundfish with spatiotemporal GLMMs and estimating range shift metrics. Possibly be useful for other applications.
-- Have an interface that will be familiar to people who have used packages such as glmmTMB, lmer, or mgcv. E.g. accept formulas, use a `predict()` method, and present options as clear named arguments.
-- Not fit the kitchen sink, but do what it does elegantly. I.e. be opinionated in what it does.
-- Maintain clearly documented model code split out into functions as much as possible.
-- Adhere to tidyverse package standards where possible.
+[![Travis build status](https://travis-ci.org/pbs-assess/sdmTMB.svg?branch=master)](https://travis-ci.org/pbs-assess/sdmTMB)
+[![Coverage status](https://codecov.io/gh/pbs-assess/sdmTMB/branch/master/graph/badge.svg)](https://codecov.io/github/pbs-assess/sdmTMB?branch=master)
+ [![CRAN status](https://www.r-pkg.org/badges/version/sdmTMB)](https://cran.r-project.org/package=sdmTMB)
+[![Project Status: WIP – Initial development is in progress, but there has not yet been a stable, usable release suitable for the public.](https://www.repostatus.org/badges/latest/wip.svg)](https://www.repostatus.org/#wip)
 
 ## Installation
 
@@ -35,6 +28,12 @@ You can install sdmTMB with:
 devtools::install_github("pbs-assess/sdmTMB")
 ```
 
+## Goals of sdmTMB:
+
+- Be useful for our purpose of fitting high resolution species distribution models for groundfish with spatiotemporal GLMMs and estimating range shift metrics. Possibly be useful for other applications.
+- Have an interface that will be familiar to people who have used packages such as glmmTMB, lmer, or mgcv. E.g. accept formulas, use a `predict()` and `residuals()` method, and present options as clear named arguments.
+- Not fit the kitchen sink, but do what it does elegantly. I.e. be opinionated in what it does.
+
 ## Example
 
-The main function is `sdmTMB()`. See `?sdmTMB` and `?predict.sdmTMB` for the most complete examples.
+The main function is `sdmTMB()`. See `?sdmTMB` and `?predict.sdmTMB` for the most complete examples. More details to come...

README.md

@@ -5,32 +5,36 @@
 
 [![Travis build
 status](https://travis-ci.org/pbs-assess/sdmTMB.svg?branch=master)](https://travis-ci.org/pbs-assess/sdmTMB)
-[![Project Status: WIP – Initial development is in progress, but there has not yet been a stable, usable release suitable for the public.](https://www.repostatus.org/badges/latest/wip.svg)](https://www.repostatus.org/#wip)
+[![Coverage
+status](https://codecov.io/gh/pbs-assess/sdmTMB/branch/master/graph/badge.svg)](https://codecov.io/github/pbs-assess/sdmTMB?branch=master)
+[![CRAN
+status](https://www.r-pkg.org/badges/version/sdmTMB)](https://cran.r-project.org/package=sdmTMB)
+[![Project Status: WIP – Initial development is in progress, but there
+has not yet been a stable, usable release suitable for the
+public.](https://www.repostatus.org/badges/latest/wip.svg)](https://www.repostatus.org/#wip)
 
-The goal of sdmTMB is to
+## Installation
+
+You can install sdmTMB with:
+
+``` r
+devtools::install_github("pbs-assess/sdmTMB")
+```
+
+## Goals of sdmTMB:
 
   - Be useful for our purpose of fitting high resolution species
-    distribution models of groundfish with spatiotemporal GLMMs and
+    distribution models for groundfish with spatiotemporal GLMMs and
     estimating range shift metrics. Possibly be useful for other
     applications.
   - Have an interface that will be familiar to people who have used
     packages such as glmmTMB, lmer, or mgcv. E.g. accept formulas, use a
-    `predict()` method, and present options as clear named arguments.
+    `predict()` and `residuals()` method, and present options as clear
+    named arguments.
   - Not fit the kitchen sink, but do what it does elegantly. I.e. be
     opinionated in what it does.
-  - Maintain clearly documented model code split out into functions as
-    much as possible.
-  - Adhere to tidyverse package standards where possible.
-
-## Installation
-
-You can install sdmTMB with:
-
-``` r
-devtools::install_github("pbs-assess/sdmTMB")
-```
 
 ## Example
 
 The main function is `sdmTMB()`. See `?sdmTMB` and `?predict.sdmTMB` for
-the most complete examples or the vignette.
+the most complete examples. More details to come…

codecov.yml

@@ -0,0 +1,12 @@
+comment: false
+
+coverage:
+  status:
+    project:
+      default:
+        target: auto
+        threshold: 1%
+    patch:
+      default:
+        target: auto
+        threshold: 1%