Changed readme and vignette

griefl · Nov 15, 2021 · 6bb19e0 · 6bb19e0
1 parent d30d7cf
commit 6bb19e0
Show file tree

Hide file tree

Showing 4 changed files with 179 additions and 175 deletions.
diff --git a/.Rhistory b/.Rhistory
@@ -1,175 +1,3 @@
-expect_equal(fit$n, n)
-expect_equal(fit$resolution, floor(sqrt(n)))
-expect_equal(colSums(fit$mass_matrix), rowSums(fit$mass_matrix))
-expect_equal(NROW(fit$data), n)
-expect_equal(NCOL(fit$data), 2)
-})
-qad
-qad:::qad.data.frame()
-qad:::qad.data.frame
-n <- 100
-x <- runif(n)
-y <- runif(n)
-fit <- qad(x,y, print = FALSE)
-coef(fit)
-expect_s3_class(fit, "S3")
-test_that("coef", {
-n <- 100
-x <- runif(n)
-y <- runif(n)
-fit <- qad(x,y, print = FALSE)
-expect_s3_class(fit, "S3")
-coef(fit)
-})
-test_that("coef", {
-n <- 100
-x <- runif(n)
-y <- runif(n)
-fit <- qad(x,y, print = FALSE)
-expect_s3_class(fit, "qad")
-})
-coef(fit)
-coef(fit) ==  fit$results$coef
-fit$results
-coef(fit) ==  c(fit$results$coef, fit$results$p.values)
-test_that("coef", {
-n <- 100
-x <- runif(n)
-y <- runif(n)
-fit <- qad(x,y, print = FALSE)
-expect_s3_class(fit, "qad")
-expect_equal(coef(fit),c(fit$results$coef, fit$results$p.values))
-})
-test_that("coef", {
-n <- 100
-x <- runif(n)
-y <- runif(n)
-fit <- qad(x,y, print = FALSE)
-expect_s3_class(fit, "qad")
-expect_equal(unname(coef(fit)),c(fit$results$coef, fit$results$p.values))
-})
-coef
-coef.qad()
-coef.qad
-n <- 100
-x <- runif(n)
-y <- runif(n)
-fit <- qad(x,y, print = FALSE)
-test_that("coef", {
-expect_s3_class(fit, "qad")
-expect_equal(unname(qad::coef(fit)),c(fit$results$coef, fit$results$p.values))
-})
-test_that("coef", {
-expect_s3_class(fit, "qad")
-expect_equal(unname(coef(fit)),c(fit$results$coef, fit$results$p.values))
-})
-summary(fit)
-summary(fit)
-test <- summary(fit)
-test
-fit$results
-test_that("summary", {
-test <- summary(fit)
-expect_equal(test$SampleSize, n)
-expect_equal(test$resolution, 10)
-expect_equal(test$dependence_values, fit$results)
-})
-p <- plot(fit)
-class(p)
-test_that("plot.qad", {
-expect_equal(class(plot(fit)), c("gg", "ggplot"))
-expect_equal(class(plot(fit, addSample = TRUE)), c("gg", "ggplot"))
-expect_equal(class(plot(fit, copula = TRUE)), c("gg", "ggplot"))
-expect_equal(class(plot(fit, density = TRUE)), c("gg", "ggplot"))
-expect_equal(class(plot(fit, margins = TRUE)), c("gg", "ggplot"))
-expect_equal(class(plot(fit, panel.grid = FALSE)), c("gg", "ggplot"))
-})
-browseVignettes("lubridate")
-browseVignettes()
-qad(x,y)
-test_that("class of qad", {
-n <- 20
-x <- runif(n)
-y <- runif(n)
-expect_output(qad::qad(x,y))
-fit <- qad::qad(x,y, print = FALSE)
-expect_identical(class(fit), "qad")
-expect_equal(fit$n, n)
-expect_equal(fit$resolution, floor(sqrt(n)))
-expect_equal(colSums(fit$mass_matrix), rowSums(fit$mass_matrix))
-expect_equal(NROW(fit$data), n)
-expect_equal(NCOL(fit$data), 2)
-})
-test_that("coef.qad", {
-expect_s3_class(fit, "qad")
-expect_equal(unname(coef(fit)),c(fit$results$coef, fit$results$p.values))
-expect_output(coef(fit))
-})
-test_that("summary.qad", {
-test <- summary(fit)
-expect_equal(test$SampleSize, n)
-expect_equal(test$resolution, 10)
-expect_equal(test$dependence_values, fit$results)
-expect_output(summary(fit))
-})
-n <- 100
-x <- runif(n)
-y <- runif(n)
-z <- runif(n)
-df <- data.frame(x,y,z)
-pw_fit <- pairwise.qad(df)
-class(pw_fit)
-test_that("heatmap.qad", {
-expect_equal(heatmap.qad(pw_fit), c("gg", "ggplot2"))
-})
-test_that("heatmap.qad", {
-expect_equal(heatmap.qad(pw_fit), c("gg", "ggplot"))
-})
-heatmap.qad(pw_fit)
-test_that("heatmap.qad", {
-expect_equal(class(heatmap.qad(pw_fit)), c("gg", "ggplot"))
-})
-test_that("heatmap.qad", {
-expect_equal(class(qad::heatmap.qad(pw_fit)), c("gg", "ggplot"))
-})
-test_that("heatmap.qad", {
-expect_equal(class(qad::heatmap.qad(pw_fit, select = "dependence")), c("gg", "ggplot"))
-})
-test_that("heatmap.qad", {
-expect_equal(class(qad::heatmap.qad(pw_fit, select = "dependence")), c("gg", "ggplot"))
-expect_equal(class(qad::heatmap.qad(pw_fit, select = "dependence",
-fontsize = 5, significance = T, scale = "rel", color = "viridis", title = "test")), c("gg", "ggplot"))
-})
-test_that("heatmap.qad", {
-n <- 100
-x <- runif(n)
-y <- runif(n)
-z <- runif(n)
-df <- data.frame(x,y,z)
-pw_fit <- pairwise.qad(df)
-expect_equal(class(qad::heatmap.qad(pw_fit, select = "dependence")), c("gg", "ggplot"))
-expect_equal(class(qad::heatmap.qad(pw_fit, select = "dependence",
-fontsize = 5, significance = T, scale = "rel", color = "viridis", title = "test")), c("gg", "ggplot"))
-})
-fit$mass_matrix
-test_that("plot_density", {
-expect_equal(class(plot_density(fit$mass_matrix)), c("gg", "ggplot"))
-})
-plot_density(fit$mass_matrix)
-expect_gt(pqad(0.4, 100, R = 10, resolution = 10), 0)
-test_that("pqad", {
-expect_gt(pqad(0.4, 100, R = 10, resolution = 10), 0)
-})
-pqad(0.4, 100, R = 10, resolution = 10)
-pqad(0.2, 100, R = 10, resolution = 10)
-test_that("pqad", {
-expect_gt(pqad(0.2, 100, R = 10, resolution = 10), 0)
-})
-typeof(pqad(0.2, 100, R = 10, resolution = 10))
-test_that("pqad", {
-expect_type(pqad(0.2, 100, R = 10, resolution = 10), "double")
-})
-qqad(0.2, 100, R = 10, resolution = 10)
 test_that("pqad", {
 expect_type(pqad(0.2, 100, R = 10, resolution = 10), "double")
 expect_type(qqad(0.2, 100, R = 10, resolution = 10), "double")
@@ -510,3 +338,175 @@ vignette("qad")
 cut
 Sys.setenv(PATH = paste(Sys.getenv("PATH"), "C:\RTools40", "C:\RTools40\mingw64\bin", sep = ";"))
 devtools::install(build_vignettes = TRUE)
+n <- 100
+x <- rnorm(n)
+y <- x^2 + rnorm(n, 0, 0.1)
+plot(x,y)
+y <- x^2 + rnorm(n, 0, 1)
+plot(x,y)
+qad(x,y)
+n <- 100
+x <- rnorm(n)
+y <- x^2 + rnorm(n, 0, 1)
+plot(x,y)
+qad(x,y)
+library(qad)
+qad(x,y)
+fit <- qad(x,y)
+coef(fit)
+#Comparison with correlation
+cor(x,y, method = "pearson")
+cor(x,y, method = "spearman")
+cor(x,y, method = "kendall")
+set.seed(20211115)
+set.seed(31415)
+n <- 100
+x <- rnorm(n)
+y <- x^2 + rnorm(n, 0, 1)
+plot(x,y)
+fit <- qad(x,y)
+set.seed(3141)
+n <- 100
+x <- rnorm(n)
+y <- x^2 + rnorm(n, 0, 1)
+plot(x,y)
+set.seed(314)
+n <- 100
+x <- rnorm(n)
+y <- x^2 + rnorm(n, 0, 1)
+plot(x,y)
+fit <- qad(x,y)
+coef(fit)
+#Comparison with correlation
+cor(x,y, method = "pearson")
+cor(x,y, method = "spearman")
+cor(x,y, method = "kendall")
+test_that("zeta1 returns exact values", {
+#Example 1
+x <- c(1,2,3,4,5)
+y <- c(1,2,3,4,5)
+expect_equal(qad::zeta1(x, y, resolution = 5), 0.9)
+expect_equal(qad::zeta1(x, y, resolution = 2), 0.6)
+expect_equal(qad::zeta1(x, y, resolution = 1), 0)
+expect_equal(qad::zeta1(x, y, resolution = 10), 0.9)
+expect_equal(qad::zeta1(x,y), qad::zeta1(y,x))
+#Example 2
+x <- c(1,2,3,4,5,6,7,8,9,10)
+y <- c(1,1,1,1,3,3,1,1,1,1)
+expect_equal(qad::zeta1(x, y, resolution = 10), 0.48)
+expect_equal(qad::zeta1(y, x, resolution = 10), 0.24)
+})
+library(testthat)
+library(qad)
+test_that("zeta1 returns exact values", {
+#Example 1
+x <- c(1,2,3,4,5)
+y <- c(1,2,3,4,5)
+expect_equal(qad::zeta1(x, y, resolution = 5), 0.9)
+expect_equal(qad::zeta1(x, y, resolution = 2), 0.6)
+expect_equal(qad::zeta1(x, y, resolution = 1), 0)
+expect_equal(qad::zeta1(x, y, resolution = 10), 0.9)
+expect_equal(qad::zeta1(x,y), qad::zeta1(y,x))
+#Example 2
+x <- c(1,2,3,4,5,6,7,8,9,10)
+y <- c(1,1,1,1,3,3,1,1,1,1)
+expect_equal(qad::zeta1(x, y, resolution = 10), 0.48)
+expect_equal(qad::zeta1(y, x, resolution = 10), 0.24)
+})
+test_that("zeta1 returns exact values", {
+#Example 1
+x <- c(1,2,3,4,5)
+y <- c(1,2,3,4,5)
+expect_equal(qad::zeta1(x, y, resolution = 5), 0.9)
+expect_equal(qad::zeta1(x, y, resolution = 2), 0.6)
+expect_equal(qad::zeta1(x, y, resolution = 1), 0)
+expect_equal(qad::zeta1(x, y, resolution = 10), 0.9)
+expect_equal(qad::zeta1(x,y), qad::zeta1(y,x))
+#Example 2
+x <- c(1,2,3,4,5,6,7,8,9,10)
+y <- c(1,1,1,1,3,3,1,1,1,1)
+expect_equal(qad::zeta1(x, y, resolution = 10), 0.48)
+expect_equal(qad::zeta1(y, x, resolution = 10), 0.24)
+#Example (checkmin copula)
+N <- 10
+x <- 1:N
+y <- 1:N
+expect_equal(qad::zeta1(x,y, resolution = N), 1-1/(2*N))
+})
+test_that("zeta1 returns exact values", {
+#Example 1
+x <- c(1,2,3,4,5)
+y <- c(1,2,3,4,5)
+expect_equal(qad::zeta1(x, y, resolution = 5), 0.9)
+expect_equal(qad::zeta1(x, y, resolution = 2), 0.6)
+expect_equal(qad::zeta1(x, y, resolution = 1), 0)
+expect_equal(qad::zeta1(x, y, resolution = 10), 0.9)
+expect_equal(qad::zeta1(x,y), qad::zeta1(y,x))
+#Example 2
+x <- c(1,2,3,4,5,6,7,8,9,10)
+y <- c(1,1,1,1,3,3,1,1,1,1)
+expect_equal(qad::zeta1(x, y, resolution = 10), 0.48)
+expect_equal(qad::zeta1(y, x, resolution = 10), 0.24)
+#Example (checkmin copula)
+NN <- c(2,10,22,44,122,200)
+for(N in NN){
+N <- NN[i]
+x <- 1:N
+y <- 1:N
+expect_equal(qad::zeta1(x,y, resolution = N), 1-1/(2*N))
+expect_equal(qad::zeta1(y,x, resolution = N), 1-1/(2*N))
+}
+})
+test_that("zeta1 returns exact values", {
+#Example 1
+x <- c(1,2,3,4,5)
+y <- c(1,2,3,4,5)
+expect_equal(qad::zeta1(x, y, resolution = 5), 0.9)
+expect_equal(qad::zeta1(x, y, resolution = 2), 0.6)
+expect_equal(qad::zeta1(x, y, resolution = 1), 0)
+expect_equal(qad::zeta1(x, y, resolution = 10), 0.9)
+expect_equal(qad::zeta1(x,y), qad::zeta1(y,x))
+#Example 2
+x <- c(1,2,3,4,5,6,7,8,9,10)
+y <- c(1,1,1,1,3,3,1,1,1,1)
+expect_equal(qad::zeta1(x, y, resolution = 10), 0.48)
+expect_equal(qad::zeta1(y, x, resolution = 10), 0.24)
+#Example (checkmin copula)
+NN <- c(2,10,22,44,122,200)
+for(N in NN){
+x <- 1:N
+y <- 1:N
+expect_equal(qad::zeta1(x,y, resolution = N), 1-1/(2*N))
+expect_equal(qad::zeta1(y,x, resolution = N), 1-1/(2*N))
+}
+})
+test_that("predictions sum to one", {
+n <- 8
+x <- 1:n
+y <- x^2
+sample <- data.frame(x, y)
+qad.fit <- qad::qad(sample, print = FALSE, resolution = 4)
+pred <-qad:: predict.qad(qad.fit, values = c(1, 3, 5, 7), conditioned = "x1", pred_plot = FALSE)
+expect_equal(pred$prediction$`x1=1`, c(1,0,0,0))
+expect_equal(pred$prediction$`x1=3`, c(0,1,0,0))
+expect_equal(pred$prediction$`x1=5`, c(0,0,1,0))
+expect_equal(pred$prediction$`x1=7`, c(0,0,0,1))
+n <- 250
+x <- runif(n, -1, 1)
+y <- x^2 + runif(n, -0.1,0.1)
+qad.fit <- qad::qad(x,y, print = FALSE)
+pred <- qad::predict.qad(qad.fit, values = c(0, 0.5, -0.5), conditioned = "x1", pred_plot = FALSE)
+expect_equal(sum(pred$prediction$`x1=0`), 1)
+expect_equal(sum(pred$prediction$`x1=0.5`), 1)
+expect_equal(sum(pred$prediction$`x1=-0.5`), 1)
+})
+usethis::use_readme_rmd()
+roxygen2::roxygenise()
+check()
+library(qad)
+?qad
+library(devtools)
+build_vignettes()
+devtools:build(vignettes = TRUE)
+devtools::build(vignettes = TRUE)
+devtools::build()
diff --git a/README.Rmd b/README.Rmd
@@ -18,10 +18,12 @@ library(qad)
 ```
 
 
-# qad <a><img src='man/figures/hex.png' align="right" height="139" /></a>
+# qad <a><img src='man/figures/hex.png' align="right" height="150" /></a>
 
 <!-- badges: start -->
 [![CRAN status](https://www.r-pkg.org/badges/version/qad)](https://cran.r-project.org/package=qad)
+[![](https://cranlogs.r-pkg.org/badges/qad)](https://cran.r-project.org/package=qad)
+
 <!-- badges: end -->
 
 

diff --git a/README.md b/README.md
@@ -1,12 +1,14 @@
 
 <!-- README.md is generated from README.Rmd. Please edit that file -->
 
-# qad <a><img src='man/figures/hex.png' align="right" height="139" /></a>
+# qad <a><img src='man/figures/hex.png' align="right" height="150" /></a>
 
 <!-- badges: start -->
 
 [![CRAN
 status](https://www.r-pkg.org/badges/version/qad)](https://cran.r-project.org/package=qad)
+[![](https://cranlogs.r-pkg.org/badges/qad)](https://cran.r-project.org/package=qad)
+
 <!-- badges: end -->
 
 ------------------------------------------------------------------------

diff --git a/vignettes/qad-vignette.Rmd b/vignettes/qad-vignette.Rmd
@@ -266,7 +266,7 @@ p6
 
 ## Install qad
 
-The R-package <a href="https://cran.r-project.org/web/packages/qad/index.html">qad</a> is (freely) available on CRAN. You can download and install the current version of qad from [CRAN](https://CRAN.R-project.org) via:
+The R-package <a href="https://CRAN.R-project.org/package=qad">qad</a> is (freely) available on CRAN. You can download and install the current version of qad from [CRAN](https://CRAN.R-project.org) via:
 
 ```{r eval = F, echo = T}
 install.packages("qad")