可以在 gganimate 中使用滚动 window 过滤器吗？
Can you have a rolling window filter in gganimate?
我希望散点图的每一帧都被另一个具有一定 bin 宽度的向量过滤，并让它在这些向量中滚动。例如，我可以通过以下方式做到这一点：
library(ggplot2)
library(gganimate)
#example data
iris <- datasets::iris
#plot x and y
g <- ggplot(iris) + geom_point(aes(x = Petal.Width,y = Petal.Length))
#filter x and y by a third value with a bin width of 2 steping through by 0.5
g + transition_filter(transition_length = 1,
filter_length = 1,
4 < Sepal.Length & Sepal.Length < 6,
4.5 < Sepal.Length & Sepal.Length < 6.5,
5 < Sepal.Length & Sepal.Length < 7,
5.5 < Sepal.Length & Sepal.Length < 7.5,
6 < Sepal.Length & Sepal.Length < 8)
但是 - 写出每个过滤条件是乏味的，我想用 ~20 binwidth 过滤不同的数据集，在 300 点范围内步进 1，所以写 100+ 过滤器是不切实际的。
还有其他方法吗？
不久前我想要这个确切的功能，但实际上在 gganimate 中没有看到任何东西可以实现，所以我写了一些可以完成工作的东西。以下是我想出的，所以我最终重建 gganimate 并包含此功能以避免使用 :::.
我不久前写了这篇文章，所以我不记得在写它时每个论点的确切意图（永远记得记录你的代码）。
这是我记得的
span : 可以在数据层内计算的表达式size : 一次显示多少数据enter_length/exit_length ：不完全记得它是如何相互关联或 size/spanrange : 子集范围retain_data_order：合乎逻辑 - 不记得为什么会出现在这里（抱歉！）
library(gganimate)
#> Loading required package: ggplot2
library(rlang)
library(tweenr)
library(stringi)
get_row_event <- gganimate:::get_row_event
is_placeholder <- gganimate:::is_placeholder
recast_event_times <- gganimate:::recast_event_times
recast_times <- gganimate:::recast_times
TransitionSpan <- ggplot2::ggproto('TransitionSpan',
TransitionEvents,
finish_data = function (self, data, params)
{
lapply(data, function(d) {
split_panel <- stri_match(d$group, regex = "^(.+)<(.*)>(.*)$")
if (is.na(split_panel[1]))
return(list(d))
d$group <- match(d$group, unique(d$group))
empty_d <- d[0, , drop = FALSE]
d <- split(d, as.integer(split_panel[, 3]))
frames <- rep(list(empty_d), params$nframes)
frames[as.integer(names(d))] <- d
frames
})
},
setup_params = function(self, data, params) {
# browser()
params$start <- get_row_event(data, params$span_quo, "start")
time_class <- if (is_placeholder(params$start))
NULL
else params$start$class
end_quo <- expr(!!params$span_quo + diff(range(!!params$span_quo))*!!params$size_quo)
params$end <- get_row_event(data, end_quo, "end",
time_class)
params$enter_length <- get_row_event(data, params$enter_length_quo,
"enter_length", time_class)
params$exit_length <- get_row_event(data, params$exit_length_quo,
"exit_length", time_class)
params$require_stat <- is_placeholder(params$start) || is_placeholder(params$end) ||
is_placeholder(params$enter_length) || is_placeholder(params$exit_length)
static = lengths(params$start$values) == 0
params$row_id <- Map(function(st, end, en, ex, s) if (s)
character(0)
else paste(st, end, en, ex, sep = "_"), st = params$start$values,
end = params$end$values, en = params$enter_length$values,
ex = params$exit_length$values, s = static)
params
},
setup_params2 = function(self, data, params, row_vars) {
late_start <- FALSE
if (is_placeholder(params$start)) {
params$start <- get_row_event(data, params$start_quo, 'start', after = TRUE)
late_start <- TRUE
} else {
params$start$values <- lapply(row_vars$start, as.numeric)
}
size <- expr(!!params$size_quo)
time_class <- params$start$class
if (is_placeholder(params$end)) {
params$end <- get_row_event(data, params$end_quo, 'end', time_class, after = TRUE)
} else {
params$end$values <- lapply(row_vars$end, as.numeric)
}
if (is_placeholder(params$enter_length)) {
params$enter_length <- get_row_event(data, params$enter_length_quo, 'enter_length', time_class, after = TRUE)
} else {
params$enter_length$values <- lapply(row_vars$enter_length, as.numeric)
}
if (is_placeholder(params$exit_length)) {
params$exit_length <- get_row_event(data, params$exit_length_quo, 'exit_length', time_class, after = TRUE)
} else {
params$exit_length$values <- lapply(row_vars$exit_length, as.numeric)
}
times <- recast_event_times(params$start, params$end, params$enter_length, params$exit_length)
params$span_size <- diff(times$start$range)*eval_tidy(size)
range <- if (is.null(params$range)) {
low <- min(unlist(Map(function(start, enter) {
start - (if (length(enter) == 0) 0 else enter)
}, start = times$start$values, enter = times$enter_length$values)))
high <- max(unlist(Map(function(start, end, exit) {
(if (length(end) == 0) start else end) + (if (length(exit) == 0) 0 else exit)
}, start = times$start$values, end = times$end$values, exit = times$exit_length$values)))
range <- c(low, high)
} else {
if (!inherits(params$range, time_class)) {
stop('range must be given in the same class as time', call. = FALSE)
}
as.numeric(params$range)
}
full_length <- diff(range)
frame_time <- recast_times(
seq(range[1], range[2], length.out = params$nframes),
time_class
)
frame_length <- full_length / params$nframes
rep_frame <- round(params$span_size/frame_length)
lowerl <- c(rep(frame_time[1],rep_frame), frame_time[2:(params$nframes-rep_frame+1)])
upperl <- c(frame_time[1:(params$nframes-rep_frame)], rep(frame_time[params$nframes-rep_frame+1], rep_frame))
start <- lapply(times$start$values, function(x) {
round((params$nframes - 1) * (x - range[1])/full_length) + 1
})
end <- lapply(times$end$values, function(x) {
if (length(x) == 0) return(numeric())
round((params$nframes - 1) * (x - range[1])/full_length) + 1
})
enter_length <- lapply(times$enter_length$values, function(x) {
if (length(x) == 0) return(numeric())
round(x / frame_length)
})
exit_length <- lapply(times$exit_length$values, function(x) {
if (length(x) == 0) return(numeric())
round(x / frame_length)
})
params$range <- range
params$frame_time <- frame_time
static = lengths(start) == 0
params$row_id <- Map(function(st, end, en, ex, s) if (s) character(0) else paste(st, end, en, ex, sep = '_'),
st = start, end = end, en = enter_length, ex = exit_length, s = static)
params$lowerl <- lowerl
params$upperl <- upperl
params$frame_span <- upperl - lowerl
params$frame_info <- data.frame(
frame_time = frame_time,
lowerl = lowerl,
upperl = upperl,
frame_span = upperl - lowerl
)
params$nframes <- nrow(params$frame_info)
params
},
expand_panel = function(self, data, type, id, match, ease, enter, exit, params, layer_index) {
#browser()
row_vars <- self$get_row_vars(data)
if (is.null(row_vars))
return(data)
data$group <- paste0(row_vars$before, row_vars$after)
start <- as.numeric(row_vars$start)
end <- as.numeric(row_vars$end)
if (is.na(end[1]))
end <- NULL
enter_length <- as.numeric(row_vars$enter_length)
if (is.na(enter_length[1]))
enter_length <- NULL
exit_length <- as.numeric(row_vars$exit_length)
if (is.na(exit_length[1]))
exit_length <- NULL
data$.start <- start
all_frames <- tween_events(data, c(ease,"linear"),
params$nframes, !!start, !!end, c(1, params$nframes),
enter, exit, !!enter_length, !!exit_length)
if(params$retain_data_order){
all_frames <- all_frames[order(as.numeric(all_frames$.id)),]
} else {
all_frames <- all_frames[order(all_frames$.start, as.numeric(all_frames$.id)),]
}
all_frames$group <- paste0(all_frames$group, '<', all_frames$.frame, '>')
all_frames$.frame <- NULL
all_frames$.start <- NULL
all_frames
})
transition_span <- function(span, size = 0.5, enter_length = NULL, exit_length = NULL, range = NULL, retain_data_order = T){
span_quo <- enquo(span)
size_quo <- enquo(size)
enter_length_quo <- enquo(enter_length)
exit_length_quo <- enquo(exit_length)
gganimate:::require_quo(span_quo, "span")
ggproto(NULL, TransitionSpan,
params = list(span_quo = span_quo,
size_quo = size_quo, range = range, enter_length_quo = enter_length_quo,
exit_length_quo = exit_length_quo,
retain_data_order = retain_data_order))
}
g <- ggplot(iris) +
geom_point(aes(x = Petal.Width,y = Petal.Length, color = Sepal.Length)) +
viridis::scale_color_viridis()
a <- g + transition_span(Sepal.Length, .1, 1, 1)
animate(a, renderer = gganimate::gifski_renderer())
由 reprex package (v2.0.0)
于 2021-08-11 创建
我希望散点图的每一帧都被另一个具有一定 bin 宽度的向量过滤，并让它在这些向量中滚动。例如，我可以通过以下方式做到这一点：
library(ggplot2)
library(gganimate)
#example data
iris <- datasets::iris
#plot x and y
g <- ggplot(iris) + geom_point(aes(x = Petal.Width,y = Petal.Length))
#filter x and y by a third value with a bin width of 2 steping through by 0.5
g + transition_filter(transition_length = 1,
filter_length = 1,
4 < Sepal.Length & Sepal.Length < 6,
4.5 < Sepal.Length & Sepal.Length < 6.5,
5 < Sepal.Length & Sepal.Length < 7,
5.5 < Sepal.Length & Sepal.Length < 7.5,
6 < Sepal.Length & Sepal.Length < 8)
但是 - 写出每个过滤条件是乏味的，我想用 ~20 binwidth 过滤不同的数据集，在 300 点范围内步进 1，所以写 100+ 过滤器是不切实际的。
还有其他方法吗？
不久前我想要这个确切的功能，但实际上在 gganimate 中没有看到任何东西可以实现，所以我写了一些可以完成工作的东西。以下是我想出的，所以我最终重建 gganimate 并包含此功能以避免使用 :::.
我不久前写了这篇文章，所以我不记得在写它时每个论点的确切意图（永远记得记录你的代码）。
这是我记得的
span: 可以在数据层内计算的表达式size: 一次显示多少数据enter_length/exit_length：不完全记得它是如何相互关联或size/spanrange: 子集范围retain_data_order：合乎逻辑 - 不记得为什么会出现在这里（抱歉！）
library(gganimate)
#> Loading required package: ggplot2
library(rlang)
library(tweenr)
library(stringi)
get_row_event <- gganimate:::get_row_event
is_placeholder <- gganimate:::is_placeholder
recast_event_times <- gganimate:::recast_event_times
recast_times <- gganimate:::recast_times
TransitionSpan <- ggplot2::ggproto('TransitionSpan',
TransitionEvents,
finish_data = function (self, data, params)
{
lapply(data, function(d) {
split_panel <- stri_match(d$group, regex = "^(.+)<(.*)>(.*)$")
if (is.na(split_panel[1]))
return(list(d))
d$group <- match(d$group, unique(d$group))
empty_d <- d[0, , drop = FALSE]
d <- split(d, as.integer(split_panel[, 3]))
frames <- rep(list(empty_d), params$nframes)
frames[as.integer(names(d))] <- d
frames
})
},
setup_params = function(self, data, params) {
# browser()
params$start <- get_row_event(data, params$span_quo, "start")
time_class <- if (is_placeholder(params$start))
NULL
else params$start$class
end_quo <- expr(!!params$span_quo + diff(range(!!params$span_quo))*!!params$size_quo)
params$end <- get_row_event(data, end_quo, "end",
time_class)
params$enter_length <- get_row_event(data, params$enter_length_quo,
"enter_length", time_class)
params$exit_length <- get_row_event(data, params$exit_length_quo,
"exit_length", time_class)
params$require_stat <- is_placeholder(params$start) || is_placeholder(params$end) ||
is_placeholder(params$enter_length) || is_placeholder(params$exit_length)
static = lengths(params$start$values) == 0
params$row_id <- Map(function(st, end, en, ex, s) if (s)
character(0)
else paste(st, end, en, ex, sep = "_"), st = params$start$values,
end = params$end$values, en = params$enter_length$values,
ex = params$exit_length$values, s = static)
params
},
setup_params2 = function(self, data, params, row_vars) {
late_start <- FALSE
if (is_placeholder(params$start)) {
params$start <- get_row_event(data, params$start_quo, 'start', after = TRUE)
late_start <- TRUE
} else {
params$start$values <- lapply(row_vars$start, as.numeric)
}
size <- expr(!!params$size_quo)
time_class <- params$start$class
if (is_placeholder(params$end)) {
params$end <- get_row_event(data, params$end_quo, 'end', time_class, after = TRUE)
} else {
params$end$values <- lapply(row_vars$end, as.numeric)
}
if (is_placeholder(params$enter_length)) {
params$enter_length <- get_row_event(data, params$enter_length_quo, 'enter_length', time_class, after = TRUE)
} else {
params$enter_length$values <- lapply(row_vars$enter_length, as.numeric)
}
if (is_placeholder(params$exit_length)) {
params$exit_length <- get_row_event(data, params$exit_length_quo, 'exit_length', time_class, after = TRUE)
} else {
params$exit_length$values <- lapply(row_vars$exit_length, as.numeric)
}
times <- recast_event_times(params$start, params$end, params$enter_length, params$exit_length)
params$span_size <- diff(times$start$range)*eval_tidy(size)
range <- if (is.null(params$range)) {
low <- min(unlist(Map(function(start, enter) {
start - (if (length(enter) == 0) 0 else enter)
}, start = times$start$values, enter = times$enter_length$values)))
high <- max(unlist(Map(function(start, end, exit) {
(if (length(end) == 0) start else end) + (if (length(exit) == 0) 0 else exit)
}, start = times$start$values, end = times$end$values, exit = times$exit_length$values)))
range <- c(low, high)
} else {
if (!inherits(params$range, time_class)) {
stop('range must be given in the same class as time', call. = FALSE)
}
as.numeric(params$range)
}
full_length <- diff(range)
frame_time <- recast_times(
seq(range[1], range[2], length.out = params$nframes),
time_class
)
frame_length <- full_length / params$nframes
rep_frame <- round(params$span_size/frame_length)
lowerl <- c(rep(frame_time[1],rep_frame), frame_time[2:(params$nframes-rep_frame+1)])
upperl <- c(frame_time[1:(params$nframes-rep_frame)], rep(frame_time[params$nframes-rep_frame+1], rep_frame))
start <- lapply(times$start$values, function(x) {
round((params$nframes - 1) * (x - range[1])/full_length) + 1
})
end <- lapply(times$end$values, function(x) {
if (length(x) == 0) return(numeric())
round((params$nframes - 1) * (x - range[1])/full_length) + 1
})
enter_length <- lapply(times$enter_length$values, function(x) {
if (length(x) == 0) return(numeric())
round(x / frame_length)
})
exit_length <- lapply(times$exit_length$values, function(x) {
if (length(x) == 0) return(numeric())
round(x / frame_length)
})
params$range <- range
params$frame_time <- frame_time
static = lengths(start) == 0
params$row_id <- Map(function(st, end, en, ex, s) if (s) character(0) else paste(st, end, en, ex, sep = '_'),
st = start, end = end, en = enter_length, ex = exit_length, s = static)
params$lowerl <- lowerl
params$upperl <- upperl
params$frame_span <- upperl - lowerl
params$frame_info <- data.frame(
frame_time = frame_time,
lowerl = lowerl,
upperl = upperl,
frame_span = upperl - lowerl
)
params$nframes <- nrow(params$frame_info)
params
},
expand_panel = function(self, data, type, id, match, ease, enter, exit, params, layer_index) {
#browser()
row_vars <- self$get_row_vars(data)
if (is.null(row_vars))
return(data)
data$group <- paste0(row_vars$before, row_vars$after)
start <- as.numeric(row_vars$start)
end <- as.numeric(row_vars$end)
if (is.na(end[1]))
end <- NULL
enter_length <- as.numeric(row_vars$enter_length)
if (is.na(enter_length[1]))
enter_length <- NULL
exit_length <- as.numeric(row_vars$exit_length)
if (is.na(exit_length[1]))
exit_length <- NULL
data$.start <- start
all_frames <- tween_events(data, c(ease,"linear"),
params$nframes, !!start, !!end, c(1, params$nframes),
enter, exit, !!enter_length, !!exit_length)
if(params$retain_data_order){
all_frames <- all_frames[order(as.numeric(all_frames$.id)),]
} else {
all_frames <- all_frames[order(all_frames$.start, as.numeric(all_frames$.id)),]
}
all_frames$group <- paste0(all_frames$group, '<', all_frames$.frame, '>')
all_frames$.frame <- NULL
all_frames$.start <- NULL
all_frames
})
transition_span <- function(span, size = 0.5, enter_length = NULL, exit_length = NULL, range = NULL, retain_data_order = T){
span_quo <- enquo(span)
size_quo <- enquo(size)
enter_length_quo <- enquo(enter_length)
exit_length_quo <- enquo(exit_length)
gganimate:::require_quo(span_quo, "span")
ggproto(NULL, TransitionSpan,
params = list(span_quo = span_quo,
size_quo = size_quo, range = range, enter_length_quo = enter_length_quo,
exit_length_quo = exit_length_quo,
retain_data_order = retain_data_order))
}
g <- ggplot(iris) +
geom_point(aes(x = Petal.Width,y = Petal.Length, color = Sepal.Length)) +
viridis::scale_color_viridis()
a <- g + transition_span(Sepal.Length, .1, 1, 1)
animate(a, renderer = gganimate::gifski_renderer())
由 reprex package (v2.0.0)
于 2021-08-11 创建