## ----setup, include = FALSE--------------------------------------------------- knitr::opts_chunk$set( collapse = TRUE, comment = "#>", fig.width=7, fig.height=5 ) library(dplyr) library(ggplot2) theme_set(theme_bw()) library(rticulate) ## ----load-data---------------------------------------------------------------- library(rticulate) data(tongue) tongue ## ----polar-place-------------------------------------------------------------- tongue_it05 <- filter(tongue, speaker == "it05", vowel == "a", fan_line < 38) %>% droplevels() polar_place <- polar_gam( Y ~ s(X, by = c2_place), data = tongue_it05 ) summary(polar_place) ## ----polar-multi-------------------------------------------------------------- tongue_it05 <- filter(tongue, speaker == "it05", fan_line < 38) %>% droplevels() polar_multi <- polar_gam( Y ~ s(X, by = c2_place) + s(X, by = vowel), data = tongue_it05 ) summary(polar_multi) ## ----polar-place-2------------------------------------------------------------ polar_2 <- polar_gam( Y ~ s(X) + s(X, by = c2_place) + s(TR_abs_velocity, k = 6) + ti(X, TR_abs_velocity, k = c(9, 6)) + s(X, word, bs = "fs"), data = tongue_it05 ) summary(polar_2) ## ----place-pred--------------------------------------------------------------- polar_pred <- predict_polar_gam( polar_2, values = list(TR_abs_velocity = seq(2, 24, 5)), exclude_terms = "s(X,word)" ) %>% filter(word == "paca") # filter data by choosing any value for word polar_pred ## ----place-pred-plot, fig.width=7, fig.height=5------------------------------- polar_pred %>% ggplot(aes(X, Y, colour = as.factor(TR_abs_velocity), linetype = as.factor(TR_abs_velocity))) + geom_path() + facet_grid(c2_place ~ .) ## ----ci-data------------------------------------------------------------------ polar_multi_p <- predict_polar_gam( polar_multi ) ci_data <- predict_polar_gam( polar_multi, return_ci = TRUE, ) ## ----place-pred-ci------------------------------------------------------------ polar_multi_p %>% ggplot(aes(X, Y)) + geom_polygon(data = ci_data, aes(CI_X, CI_Y, group = c2_place), alpha = 0.1) + geom_path(aes(colour = c2_place)) + facet_grid(. ~ vowel) + theme(legend.position = "top")