Problem reproducing loess animation, perhaps issue with inflate vs crossing? - r

Question

I'm trying to recreate some of the very nice animations showing the behavior of loess from David Robinson found at Variance Explained. When I try to recreate the animations there I get a different behavior with my groups than Robinson shows. In the animation the points are jumping about in a way I don't expect. I'm wondering if there is different behavior from tidyr::crossing than in the deprecated inflate function he uses from broom. Any advice on how to make the animation in last plot below appreciated.
library(lattice)
library(ggplot2)
library(broom)
theme_set(theme_bw())
mod <- loess(NOx ~ E, ethanol, degree = 1, span = .75)
fit <- broom::augment(mod)
# plot to animate with lm showing moving loess
ggplot(fit, aes(E, NOx)) +
geom_point() +
geom_line(aes(y = .fitted), color = "red")
library(dplyr)
dat <- ethanol %>%
# note use of crossing over inflate
tidyr::crossing(center = unique(ethanol$E)) %>%
mutate(dist = abs(E - center)) %>%
filter(rank(dist) / n() <= .75) %>%
mutate(weight = (1 - (dist / max(dist)) ^ 3) ^ 3)
# animate plot -- awry
p <- ggplot(dat, aes(x=E, y=NOx)) +
geom_point(aes(alpha = weight)) +
geom_smooth(aes(group = center, weight = weight), method = "lm", se = FALSE) +
geom_vline(aes(xintercept = center), lty = 2) +
geom_line(aes(y = .fitted), data = fit, color = "red")
# why so many lm fits in middle range of E that are below loess line?
# something is wrong with the groups defined by center?
p
# make the animation
library(gganimate)
p + labs(title = 'E={frame_time}') + transition_time(center)

Answer 1

Answering myself. I was missing a group_by
E.g.,
dat <- ethanol %>%
tidyr::crossing(center = unique(ethanol$E)) %>%
group_by(center) %>%
mutate(dist = abs(E - center)) %>%
filter(rank(dist) / n() <= .75) %>%
mutate(weight = (1 - (dist / max(dist)) ^ 3) ^ 3)
p <- ggplot(dat, aes(x=E, y=NOx)) +
geom_point(aes(alpha = weight)) +
geom_smooth(aes(group = center, weight = weight), method = "lm", se = FALSE) +
geom_vline(aes(xintercept = center), lty = 2) +
geom_line(aes(y = .fitted), data = fit, color = "red")
library(gganimate)
p + transition_states(center)