gganimate :: transition_time（）在不存在的观察之间转换

Question

我正试图更加熟悉gganimate软件包。这样做时，我注意到transition_time(time)似乎不一定使用time中的确切值，而是进行了填充。在下面的data.frame中，{{1 }}变量。据我了解，我希望time仅在这41个日期之间过渡。

在下面的代码中，我还使用transition_time(time)根据geom_rect中的值为背景着色。查看输出的category，当背景为白色时，df.gif似乎使用的值transition_time(time)尚无实际观察值。此外，在某些情况下，观察值似乎是“推算”的，即，在实际观察值之间存在过渡，并且在多个观察步骤之间没有观察值。

也许这不是问题，但是由于我缺乏对它实际工作方式的理解。无论如何，任何指针都非常感谢，谢谢！

time

df <- structure(list(time = structure(c(12174, 12179, 12180, 12181, 
12189, 12191, 12193, 12198, 12199, 12200, 12201, 12202, 12203, 
12205, 12206, 12207, 12208, 12209, 12210, 12211, 12212, 12213, 
12214, 12215, 12216, 12217, 12218, 12219, 12220, 12221, 12222, 
12223, 12224, 12225, 12226, 12227, 12228, 12229, 12230, 12231, 
12232), class = "Date"), lon = c(37.0615319203799, 37.0716477974754, 
37.0615319203799, 37.0923434723092, 37.0923434723092, 37.0507170659893, 
37.1042645986751, 37.1042645986751, 37.0716477974754, 37.0507170659893, 
37.0507170659893, 37.0923434723092, 37.0716477974754, 37.047738185691, 
37.0906383964751, 37.066505639265, 37.1069135660838, 37.0808814378127, 
37.066505639265, 37.0808814378127, 37.1069135660838, 37.066505639265, 
37.1069135660838, 37.0906383964751, 37.047738185691, 37.1069135660838, 
37.1069135660838, 37.0808814378127, 37.066505639265, 37.0808814378127, 
37.047738185691, 37.066505639265, 37.0906383964751, 37.047738185691, 
37.1069135660838, 37.0808814378127, 37.066505639265, 37.0906383964751, 
37.066505639265, 37.0906383964751, 37.0808814378127), lat = c(-2.7411848459376, 
-2.71292701762913, -2.7411848459376, -2.72165547518141, -2.72165547518141, 
-2.73329474303528, -2.71147633070969, -2.71147633070969, -2.71292701762913, 
-2.73329474303528, -2.73329474303528, -2.72165547518141, -2.71292701762913, 
-2.73075363771866, -2.71197727883059, -2.7343739141538, -2.71507451885925, 
-2.71061194970373, -2.7343739141538, -2.71061194970373, -2.71507451885925, 
-2.7343739141538, -2.71507451885925, -2.71197727883059, -2.73075363771866, 
-2.71507451885925, -2.71507451885925, -2.71061194970373, -2.7343739141538, 
-2.71061194970373, -2.73075363771866, -2.7343739141538, -2.71197727883059, 
-2.73075363771866, -2.71507451885925, -2.71061194970373, -2.7343739141538, 
-2.71197727883059, -2.7343739141538, -2.71197727883059, -2.71061194970373
), group = c("D", "A", "D", "E", "E", "C", "B", "B", "A", "C", 
"C", "E", "A", "C", "A", "D", "B", "E", "D", "E", "B", "D", "B", 
"A", "C", "B", "B", "E", "D", "E", "C", "D", "A", "C", "B", "E", 
"D", "A", "D", "A", "E"), category = c("High", "High", "High", 
"High", "High", "High", "High", "High", "High", "High", "High", 
"High", "High", "Low", "Low", "Low", "Low", "Low", "Low", "Low", 
"Low", "Low", "Low", "Low", "Low", "Low", "Low", "Low", "Low", 
"Low", "Low", "Low", "Low", "Low", "Low", "Low", "Low", "Low", 
"Low", "Low", "Low")), row.names = c(NA, -41L), class = c("tbl_df", 
"tbl", "data.frame"))