# Tests for interval geoms # # Author: mjskay ############################################################################### library(dplyr) library(tidyr) # use a subset of RankCorr so tests are faster data(RankCorr_u_tau, package = "ggdist") RankCorr_u_tau = RankCorr_u_tau %>% filter(i %in% 1:3, .iteration %in% 1:50) %>% group_by(i) test_that("horizontal grouped pointintervals work", { skip_if_no_vdiffr() vdiffr::expect_doppelganger("grouped pointintervals (h)", RankCorr_u_tau %>% median_hdci(.width = c(.66, .95)) %>% ggplot(aes(y = i, x = u_tau, xmin = .lower, xmax = .upper)) + geom_pointinterval(show.legend = TRUE) + theme_ggdist() ) vdiffr::expect_doppelganger("grouped pointintervals (h, stat)", RankCorr_u_tau %>% ggplot(aes(y = factor(i), x = u_tau)) + stat_pointinterval( .width = c(.66, .95), arrow = arrow(angle = 45, length = unit(4, "pt"), type = "closed", ends = "both") ) ) vdiffr::expect_doppelganger("grouped pointintervals (h, reverse order)", RankCorr_u_tau %>% median_qi(.width = c(.66, .95)) %>% ggplot(aes(y = i, x = u_tau, xmin = .lower, xmax = .upper)) + geom_pointinterval() ) vdiffr::expect_doppelganger("grouped pointintervals (h, stat, reverse order)", RankCorr_u_tau %>% ggplot(aes(y = factor(i), x = u_tau)) + stat_pointinterval(.width = c(.66, .95)) ) }) test_that("grouped pointintervals work", { skip_if_no_vdiffr() forward_plot = RankCorr_u_tau %>% mean_qi(.width = c(.66, .95)) %>% ggplot(aes(x = i, y = u_tau, ymin = .lower, ymax = .upper)) + geom_pointinterval(interval_size_range = c(1,4), fatten_point = 3) vdiffr::expect_doppelganger("grouped pointintervals with custom fatten", forward_plot) forward_plot = RankCorr_u_tau %>% mean_qi(.width = c(.66, .95)) %>% ggplot(aes( x = i, y = u_tau, ymin = .lower, ymax = .upper, interval_size = fct_rev_(ordered(.width)) )) + geom_pointinterval(point_size = 3) vdiffr::expect_doppelganger("grouped, with interval_size and legend", forward_plot) stat_forward_plot = RankCorr_u_tau %>% ggplot(aes(x = i, y = u_tau)) + stat_pointinterval(.width = c(.66, .95)) vdiffr::expect_doppelganger("grouped pointintervals (stat)", stat_forward_plot) }) test_that("orientation detection on pointintervals works", { skip_if_no_vdiffr() p = tibble( v = c(1, 2), l = c(0, 1), u = c(4, 5), g = c("a", "b") ) %>% ggplot() vdiffr::expect_doppelganger("vertical, orientation detection", p + geom_pointinterval(aes(x = g, y = v, ymin = l, ymax = u), orientation = NA) ) vdiffr::expect_doppelganger("horizontal, orientation detection", p + geom_pointinterval(aes(y = g, x = v, xmin = l, xmax = u), orientation = NA) ) vdiffr::expect_doppelganger("vertical, orientation detection plus dodge", p + geom_pointinterval(aes(color = g, y = v, ymin = l, ymax = u), orientation = NA, position = "dodge") ) vdiffr::expect_doppelganger("horizontal, orientation detection, dodge", p + geom_pointinterval(aes(color = g, x = v, xmin = l, xmax = u), orientation = NA, position = "dodge") ) }) test_that("missing data is handled correctly", { skip_if_no_vdiffr() p = tibble( x = c(1,NA,1), xmin = c(NA,0,0), xmax = c(NA,2,2), y = c("a","b",NA) ) %>% ggplot(aes(x = x, xmin = xmin, xmax = xmax, y = y)) expect_warning( vdiffr::expect_doppelganger("geom_pointinterval na.rm = FALSE", p + geom_pointinterval(na.rm = FALSE) ), "Removed 1 row.+missing values" ) vdiffr::expect_doppelganger("geom_pointinterval na.rm = TRUE", p + geom_pointinterval(na.rm = TRUE) ) }) test_that("dist aesthetic can be NULLed out", { skip_if_no_vdiffr() hist_df = tibble( geom = "histinterval", x = qnorm(ppoints(100), 4, 1), dist = NA ) vdiffr::expect_doppelganger("dist aesthetic can be NULLed out", hist_df %>% ggplot(aes(y = geom, dist = dist)) + stat_pointinterval(aes(x = x, y = "pointinterval", dist = NULL)) ) }) # error on missing xmin/ymin/xmax/ymax ------------------------------------ test_that("missing min/max aesthetics are caught", { expect_error( print(newpage = FALSE, ggplot(data.frame(x = 1), aes(x = x)) + geom_pointinterval() ), "You did not specify xmin or xmax aesthetics" ) })