如何使用gganimate用风动画创建轮廓？

时间：2019-04-09 00:44:41

标签： r ggplot2 contour gganimate

我已经为特定日期（Click to play animation video）的每个小时创建了一个风动画。我不想显示19个点，而是想创建一个在整个区域中每小时使用这19个点进行插值/插值的轮廓图-就像使用ArcGIS和样条曲线插值工具生成的轮廓图一样。

PMcontour

以下代码显示了我用来创建每小时风动画的ggplot和gganimate。我只创建了一个小的数据框作为完整的24小时数据的子样本，因为我不熟悉将csv附加到该论坛中。 有没有办法在区域上覆盖轮廓而不是geom_point？ 

library(ggplot2)
library(ggmap)
library(gganimate)

site <- c(1:18, 1:18)    
date <- data.frame(date=c(rep(as.POSIXct("2018-06-07 00:00:00"),18),rep(as.POSIXct("2018-06-07 01:00:00"),18)))    
long <- c(171.2496,171.1985, 171.2076, 171.2236,171.2165,171.2473,171.2448,171.2416,171.2243,171.2282,171.2344,171.2153,171.2532,171.2444,171.2443,171.2330,171.2356,171.2243)   
lati <- c(-44.40450,-44.38520,-44.38530,-44.38750,-44.39195,-44.41436,-44.38798,-44.38934,-44.37958,-44.37836,-44.37336,-44.37909,-44.40801, -44.40472,-44.39558,-44.40971,-44.39577,-44.39780)    
PM <- c(57,33,25,48,34,31,52,48,31,51,44,21,61,53,49,34,60,18,41,26,28,26,26,18,32,28,27,29,22,16,34,42,37,28,33,9)    
ws <- c(0.8, 0.1, 0.4, 0.4, 0.2, 0.1, 0.4, 0.2, 0.3, 0.3, 0.2, 0.7, NaN, 0.4, 0.3, 0.4, 0.3, 0.3, 0.8, 0.2, 0.4, 0.4, 0.1, 0.5, 0.5, 0.2, 0.3, 0.3, 0.3, 0.4, NaN, 0.5, 0.5, 0.4, 0.3, 0.2)    
wd <- c(243, 274, 227, 253, 199, 327, 257, 270, 209, 225, 230, 329, NaN, 219, 189, 272, 239, 237, 237, 273, 249, 261, 233, 306, 259, 273, 218, 242, 237, 348, NaN, 221, 198, 249, 236,252  )    
PMwind <- cbind(site,date,long,lati,PM, ws, wd)

tmlat <- c(-44.425, -44.365)                
tmlon <- c(171.175, 171.285)  

tim <- get_map(location = c(lon = mean(tmlon), lat = mean(tmlat)),
               zoom = 14,
               maptype = "terrain")

ggmap(tim) + 
    geom_point(aes(x=long, y = lati, colour=PM), data=PMwind,
               size=3,alpha = .8, position="dodge", na.rm = TRUE) +     
    geom_spoke(aes(x=long, y = lati, angle = ((270 -  wd) %% 360) * pi / 180), data=PMwind, 
               radius = -PMwind$ws * .01, colour="yellow", 
               arrow = arrow(ends = "first", length = unit(0.2, "cm"))) +
    transition_states(date, transition_length = 20, state_length = 60) +
    labs(title = "{closest_state}") +
    ease_aes('linear', interval = 0.1) +
    scale_color_gradient(low = "green", high = "red")+
    theme_minimal()+
    theme(axis.text.x=element_blank(), axis.title.x=element_blank()) +
    theme(axis.text.y=element_blank(), axis.title.y=element_blank()) +
    shadow_wake(wake_length = 0.01)

1 个答案:

答案 0 :(得分：1)

这是可以做到的，但是我想说，使用当前工具远非如此简单。要从问题中的数据集过渡到动画轮廓，我们需要解决以下障碍：

  1. 我们只有几个数据点，它们不规则地分布在给定区域中。轮廓生成通常需要规则的点网格。

    2. ggplot2中的

  2. geom_contour / stat_contour对边缘的开放轮廓处理不佳。 GH的讨论，请参见here，当我们尝试对填充的多边形使用等高线时会发生什么。

  3. 与轮廓关联的多边形不一定会随着时间的流逝而持久：它们会出现，消失，分裂为多个较小的多边形，合并为较大的多边形等。这使得很难进行加格网化，这需要知道哪些元素为了正确地对它们进行插值，帧T中的T对应于帧T + 1中的哪些元素。

可以通过现有的解决方法解决前两个障碍。第三个需要一些非正统的黑客攻击。

第1部分：对不规则点进行插值

获取每个日期值的PMwind的经度/纬度/ PM值，并使用akima软件包中的interp将其内插到常规网格中。将外推设置为TRUE的双三次样条插值将为您提供40 x 40的常规网格（默认情况下，如果您希望网格更粗/更细，请更改nx / ny参数值）点具有内插的PM值。

library(dplyr)

PMwind2 <- PMwind %>%
  select(date, long, lati, PM) %>%
  tidyr::nest(-date) %>%
  mutate(data = purrr::map(data,
                           ~ akima::interp(x = .$long, y = .$lati, z = .$PM,
                                           linear = FALSE, # use spline interpolation
                                           extrap = TRUE) %>%
                             akima::interp2xyz(data.frame = TRUE))) %>%
  tidyr::unnest()

> str(PMwind2) # there are 2 x 40 x 40 observations, corresponding to 2 dates
'data.frame':   3200 obs. of  4 variables:
 $ date: POSIXct, format: "2018-06-07" "2018-06-07" "2018-06-07" ...
 $ x   : num  171 171 171 171 171 ...
 $ y   : num  -44.4 -44.4 -44.4 -44.4 -44.4 ...
 $ z   : num  31.8 31.4 31 30.6 30.3 ...

第2部分：使用替代程序包生成边缘带有闭合多边形的轮廓。

在这里，我使用了metR package中的geom_contour_fill，这是GH线程中讨论的修补程序之一。 （isoband包方法看起来也很有趣，但是它是新的，而且我还没有对其进行测试。）

library(ggplot2)
library(metR)

# define scale breaks to make sure the scale would be consistent across animated frames
scale.breaks = scales::fullseq(range(PMwind2$z), size = 10)

# define annotation layer & appropriate coord limits for map (metR's contour polygons
# don't go nicely with alpha < 1 in animation, as the order of layers could change, 
# but we can overlay the map as a semi-transparent annotation layer over the contour
# polygons, instead of having ggmap layer beneath semi-transparent contour polygons.)
map.annotation <- list(
  annotation_raster(tim %>% unlist() %>%
                      alpha(0.4) %>% # change alpha setting for map here
                      matrix(nrow = dim(tim)[1], 
                             byrow = TRUE),
                    xmin = attr(tim, "bb")$ll.lon,
                    xmax = attr(tim, "bb")$ur.lon,
                    ymin = attr(tim, "bb")$ll.lat,
                    ymax = attr(tim, "bb")$ur.lat),
  coord_quickmap(xlim = c(attr(tim, "bb")$ll.lon, attr(tim, "bb")$ur.lon),
                 ylim = c(attr(tim, "bb")$ll.lat, attr(tim, "bb")$ur.lat),
                 expand = FALSE))

p.base <- ggplot(PMwind2, aes(x = x, y = y, z = z))

# check static version of plot to verify that the geom layer works as expected
p.base + 
  geom_contour_fill(breaks = scale.breaks) +
  facet_wrap(~date) +
  map.annotation +
  scale_fill_gradient(low = "green", high = "red",
                      aesthetics = c("colour", "fill"),
                      limits = range(scale.breaks)) +
  theme_minimal()

static version

第3部分：对点值进行动画处理，而不是对轮廓线/多边形进行动画处理

在生成动画图的每一帧之后（但在将其打印/绘制到图形设备之前），获取其数据，创建一个新图（我们实际想要的图），然后发送 转到图形设备。我们可以通过将一些代码插入ggproto对象plot_frame中的函数gganimate:::Scene中来进行绘制。

Scene2 <- ggproto(
  "Scene2", gganimate:::Scene,
  plot_frame = function(self, plot, i, newpage = is.null(vp), vp = NULL, 
                        widths = NULL, heights = NULL, ...) {    
    plot <- self$get_frame(plot, i)

    # for each frame, use the plot data interpolated by gganimate to create a new plot
    new.plot <- ggplot(data = plot[["data"]][[1]],
                       aes(x = x, y = y, z = z)) + 
      geom_contour_fill(breaks = scale.breaks) +
      ggtitle(plot[["plot"]][["labels"]][["title"]]) +
      map.annotation +
      scale_fill_gradient(low = "green", high = "red",
                          limits = range(scale.breaks)) +
      theme_minimal()
    plot <- ggplotGrob(new.plot)

    # no change below
    if (!is.null(widths)) plot$widths <- widths
    if (!is.null(heights)) plot$heights <- heights
    if (newpage) grid::grid.newpage()
    grDevices::recordGraphics(
      requireNamespace("gganimate", quietly = TRUE),
      list(),
      getNamespace("gganimate")
    )
    if (is.null(vp)) {
      grid::grid.draw(plot)
    } else {
      if (is.character(vp)) seekViewport(vp)
      else pushViewport(vp)
      grid::grid.draw(plot)
      upViewport()
    }
    invisible(NULL)
  })

我们还需要定义一系列中间函数，以使动画使用此Scene2而不是原始的gganimate:::Scene。在here之前，我使用相同的方法回答了另一个问题，并讨论了这样做的利弊。

library(magrittr)

create_scene2 <- function(transition, view, shadow, ease, transmuters, nframes) {
  if (is.null(nframes)) nframes <- 100
  ggproto(NULL, Scene2, transition = transition, 
          view = view, shadow = shadow, ease = ease, 
          transmuters = transmuters, nframes = nframes)
}

ggplot_build2 <- gganimate:::ggplot_build.gganim
body(ggplot_build2) <- body(ggplot_build2) %>%
  as.list() %>%
  inset2(4,
         quote(scene <- create_scene2(plot$transition, plot$view, plot$shadow, 
                                      plot$ease, plot$transmuters, plot$nframes))) %>%
  as.call()

prerender2 <- gganimate:::prerender
body(prerender2) <- body(prerender2) %>%
  as.list() %>%
  inset2(3,
         quote(ggplot_build2(plot))) %>%
  as.call()

animate2 <- gganimate:::animate.gganim
body(animate2) <- body(animate2) %>%
  as.list() %>%
  inset2(7,
         quote(plot <- prerender2(plot, nframes_total))) %>%
  as.call()

最后，结果如下：

library(gganimate)

animate2(p.base + 
           geom_point(aes(color = z)) + # this layer will be replaced by geom_contour_fill in 
                                        # the final plot; it's here as the placeholder in 
                                        # order for gganimate to interpolate the relevant data
           transition_time(date) +
           ggtitle("{frame_time}"),
         nframes = 30, fps = 10)        # you can increase nframes for smoother transition
                                        # (which would also be much bigger in file size)

animated version

相关问题
最新问题