Barplot：爲什麼我在ggplot2中爲相同的腳本獲得一個可變間距？

我遇到了與ggplot2奇怪的事情。我有一個循環腳本，產生barplots並將它們中的每一個保存爲一個tiff文件。我不希望任何間隔之間的間距，我認爲我已經正確編寫腳本來做到這一點，但我的一些圖形顯示條形之間的髮際線，有些則沒有。因爲它是一個循環，所以它們的腳本和數據結構完全相同。這裏是一個重複的例子：Barplot：爲什麼我在ggplot2中爲相同的腳本獲得一個可變間距？

require(gridExtra); require(ggplot2); require(grid) 
prod.data1 = structure(list(date.time = structure(c(1465362000, 1465365600, 
    1465369200, 1465372800, 1465376400, 1465380000, 1465383600, 1465387200, 
    1465390800, 1465394400, 1465398000, 1465401600, 1465405200, 1465408800, 
    1465412400, 1465416000, 1465419600, 1465423200, 1465426800, 1465430400, 
    1465434000, 1465437600, 1465441200, 1465444800, 1465448400, 1465452000, 
    1465455600, 1465459200, 1465462800, 1465466400, 1465470000, 1465473600, 
    1465477200, 1465480800, 1465484400, 1465488000, 1465491600, 1465495200, 
    1465498800, 1465502400, 1465506000, 1465509600, 1465513200, 1465516800, 
    1465520400, 1465524000, 1465527600, 1465531200, 1465534800, 1465538400, 
    1465542000, 1465545600, 1465549200, 1465552800, 1465556400, 1465560000, 
    1465563600, 1465567200, 1465570800, 1465574400, 1465578000, 1465581600, 
    1465585200, 1465588800, 1465592400, 1465596000, 1465599600, 1465603200, 
    1465606800, 1465610400, 1465614000, 1465617600, 1465621200, 1465624800, 
    1465628400, 1465632000, 1465635600, 1465639200, 1465642800, 1465646400, 
    1465650000, 1465653600, 1465657200, 1465660800, 1465664400, 1465668000, 
    1465671600, 1465675200, 1465678800, 1465682400, 1465686000, 1465689600, 
    1465693200, 1465696800, 1465700400, 1465704000, 1465707600, 1465711200, 
    1465714800, 1465718400, 1465722000, 1465725600, 1465729200, 1465732800, 
    1465736400, 1465740000, 1465743600, 1465747200, 1465750800, 1465754400, 
    1465758000, 1465761600, 1465765200, 1465768800, 1465772400, 1465776000, 
    1465779600, 1465783200, 1465786800, 1465790400, 1465794000, 1465797600, 
    1465801200, 1465804800, 1465808400, 1465812000, 1465815600, 1465819200, 
    1465822800, 1465826400, 1465830000, 1465833600, 1465837200, 1465840800, 
    1465844400, 1465848000, 1465851600, 1465855200, 1465858800, 1465862400, 
    1465866000, 1465869600, 1465873200, 1465876800, 1465880400, 1465884000, 
    1465887600, 1465891200, 1465894800, 1465898400, 1465902000, 1465905600, 
    1465909200, 1465912800, 1465916400, 1465920000, 1465923600, 1465927200, 
    1465930800, 1465934400, 1465938000, 1465941600, 1465945200, 1465948800, 
    1465952400, 1465956000, 1465959600, 1465963200, 1465966800, 1465970400, 
    1465974000, 1465977600, 1465981200, 1465984800, 1465988400, 1465992000, 
    1465995600, 1465999200, 1466002800, 1466006400, 1466010000, 1466013600, 
    1466017200, 1466020800, 1466024400, 1466028000, 1466031600, 1466035200, 
    1466038800, 1466042400, 1466046000, 1466049600, 1466053200, 1466056800, 
    1466060400, 1466064000, 1466067600, 1466071200, 1466074800, 1466078400, 
    1466082000, 1466085600, 1466089200, 1466092800, 1466096400, 1466100000, 
    1466103600, 1466107200, 1466110800, 1466114400, 1466118000, 1466121600, 
    1466125200, 1466128800, 1466132400, 1466136000), class = c("POSIXct", 
    "POSIXt")), production = c(5.9, 5.9, 5.9, 5.9, 5.9, 5.9, 9.9, 
    9.9, 9.9, 9.9, 9.9, 9.9, 9.9, 9.9, 9.9, 13.4, 13.4, 13.4, 13.4, 
    13.4, 13.4, 9.9, 5.9, 5.9, 5.9, 5.9, 5.9, 5.9, 5.9, 5.9, 9.9, 
    9.9, 9.9, 9.9, 9.9, 9.9, 9.9, 9.9, 9.9, 13.4, 13.4, 13.4, 13.4, 
    13.4, 13.4, 9.9, 5.9, 5.9, 5.9, 5.9, 5.9, 5.9, 5.9, 5.9, 9.9, 
    9.9, 9.9, 9.9, 9.9, 9.9, 9.9, 9.9, 9.9, 13.4, 13.4, 13.4, 13.4, 
    13.4, 13.4, 9.9, 5.9, 5.9, 5.9, 5.9, 5.9, 5.9, 5.9, 5.9, 9.9, 
    9.9, 9.9, 9.9, 9.9, 9.9, 9.9, 9.9, 9.9, 13.4, 13.4, 13.4, 13.4, 
    13.4, 13.4, 9.9, 5.9, 5.9, 3.1, 3.1, 3.1, 3.1, 3.1, 3.1, 7.1, 
    7.1, 7.1, 7.1, 7.1, 7.1, 7.1, 7.1, 7.1, 7.1, 7.1, 7.1, 7.1, 7.1, 
    7.1, 3.1, 3.1, 3.1, 3.1, 3.1, 3.1, 3.1, 3.1, 3.1, 7.1, 7.1, 7.1, 
    7.1, 7.1, 7.1, 7.1, 7.1, 7.1, 7.1, 7.1, 7.1, 7.1, 7.1, 7.1, 3.1, 
    3.1, 3.1, 3.1, 3.1, 3.1, 3.1, 3.1, 3.1, 7.1, 7.1, 7.1, 7.1, 7.1, 
    7.1, 7.1, 7.1, 7.1, 7.1, 7.1, 7.1, 7.1, 7.1, 7.1, 3.1, 3.1, 3.1, 
    3.1, 3.1, 3.1, 3.1, 3.1, 3.1, 7.1, 7.1, 7.1, 7.1, 7.1, 7.1, 7.1, 
    7.1, 7.1, 7.1, 7.1, 7.1, 7.1, 7.1, 7.1, 3.1, 3.1, 3.1, 3.1, 3.1, 
    3.1, 3.1, 3.1, 3.1, 7.1, 7.1, 7.1, 7.1, 7.1, 7.1, 7.1, 7.1, 7.1, 
    7.1, 7.1, 7.1, 7.1, 7.1, 7.1, 3.1, 3.1, 3.1), ID = structure(c(15L, 
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    15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 
    15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 
    15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 
    15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 
    15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 
    15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 
    15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 
    15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 
    15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 
    15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 
    15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 
    15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 
    15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 
    15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 
    15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 
    15L, 15L, 15L, 15L, 15L, 15L, 15L), .Label = c("A", "B", "C","D", 
    "E", "F", "G", "H", "I", "J", "K", "L", "M", "N", "O", "P"), 
    class = "factor"), ILP = c(10.72, 
    8.66, 7.75, 7.25, 7.91, 9.12, 10.33, 12.93, 15.7, 15.72, 16.7, 
    15.34, 14.6, 14.34, 13.09, 11.52, 12.08, 13.29, 14.56, 13.74, 
    15.46, 15.37, 12.49, 11.11, 7.78, 5.92, 5.92, 5.91, 6.11, 7.01, 
    10.05, 10.49, 11.43, 11.45, 12.21, 12.79, 12.09, 11.94, 11.99, 
    10.87, 11.31, 12.08, 13.33, 13.31, 14.23, 13.01, 10.84, 10.07, 
    7.08, 5.04, 5.01, 5.06, 5.22, 6, 9.92, 10.74, 12.53, 12.43, 13.34, 
    13.24, 13.52, 12.95, 13.86, 13.09, 13.79, 12.44, 14.14, 14.05, 
    14.36, 14.45, 11.66, 10.4, 11.3366666666667, 11.3366666666667, 
    11.3366666666667, 11.3366666666667, 11.3366666666667, 11.3366666666667, 
    11.3366666666667, 11.3366666666667, 11.3366666666667, 11.3366666666667, 
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    11.3366666666667, 11.3366666666667, 11.3366666666667, 11.3366666666667, 
    11.3366666666667, 11.3366666666667, 11.3366666666667, 11.3366666666667, 
    11.3366666666667, 11.3366666666667, 11.3366666666667, 11.3366666666667, 
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    11.3366666666667, 11.3366666666667, 11.3366666666667, 11.3366666666667, 
    11.3366666666667, 11.3366666666667, 11.3366666666667, 11.3366666666667, 
    11.3366666666667, 11.3366666666667, 11.3366666666667, 11.3366666666667, 
    11.3366666666667, 11.3366666666667, 11.3366666666667, 11.3366666666667, 
    11.3366666666667, 11.3366666666667, 11.3366666666667, 11.3366666666667, 
    11.3366666666667, 11.3366666666667, 11.3366666666667, 11.3366666666667, 
    11.3366666666667, 11.3366666666667, 11.3366666666667, 11.3366666666667, 
    11.3366666666667, 11.3366666666667, 11.3366666666667, 11.3366666666667, 
    11.3366666666667, 11.3366666666667, 11.3366666666667, 11.3366666666667, 
    11.3366666666667, 11.3366666666667, 11.3366666666667, 11.3366666666667, 
    11.3366666666667, 11.3366666666667, 11.3366666666667, 11.3366666666667, 
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    11.3366666666667, 11.3366666666667, 11.3366666666667, 11.3366666666667, 
    11.3366666666667, 11.3366666666667, 11.3366666666667, 11.3366666666667, 
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    11.3366666666667, 11.3366666666667, 11.3366666666667, 11.3366666666667, 
    11.3366666666667, 11.3366666666667), Class = structure(c(2L, 2L, 
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    3L, 3L, 4L, 3L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 
    3L, 3L, 3L, 3L, 3L, 2L, 2L, 3L, 4L, 4L, 4L, 4L, 2L, 2L, 2L, 2L, 
    2L, 2L, 2L, 2L, 2L, 2L, 3L, 2L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 2L, 
    4L, 4L, 4L, 4L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
    1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
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    1L, 1L, 1L, 1L, 1L, 1L), .Label = c("NA", "Low", "Medium", 
    "High"), class = "factor")), .Names = c("date.time", "production", 
    "ID", "ILP", "Class"), row.names = 3025:3240, class = "data.frame") 

prod.data2 = structure(list(date.time = structure(c(1465362000, 1465365600, 
1465369200, 1465372800, 1465376400, 1465380000, 1465383600, 1465387200, 
1465390800, 1465394400, 1465398000, 1465401600, 1465405200, 1465408800, 
1465412400, 1465416000, 1465419600, 1465423200, 1465426800, 1465430400, 
1465434000, 1465437600, 1465441200, 1465444800, 1465448400, 1465452000, 
1465455600, 1465459200, 1465462800, 1465466400, 1465470000, 1465473600, 
1465477200, 1465480800, 1465484400, 1465488000, 1465491600, 1465495200, 
1465498800, 1465502400, 1465506000, 1465509600, 1465513200, 1465516800, 
1465520400, 1465524000, 1465527600, 1465531200, 1465534800, 1465538400, 
1465542000, 1465545600, 1465549200, 1465552800, 1465556400, 1465560000, 
1465563600, 1465567200, 1465570800, 1465574400, 1465578000, 1465581600, 
1465585200, 1465588800, 1465592400, 1465596000, 1465599600, 1465603200, 
1465606800, 1465610400, 1465614000, 1465617600, 1465621200, 1465624800, 
1465628400, 1465632000, 1465635600, 1465639200, 1465642800, 1465646400, 
1465650000, 1465653600, 1465657200, 1465660800, 1465664400, 1465668000, 
1465671600, 1465675200, 1465678800, 1465682400, 1465686000, 1465689600, 
1465693200, 1465696800, 1465700400, 1465704000, 1465707600, 1465711200, 
1465714800, 1465718400, 1465722000, 1465725600, 1465729200, 1465732800, 
1465736400, 1465740000, 1465743600, 1465747200, 1465750800, 1465754400, 
1465758000, 1465761600, 1465765200, 1465768800, 1465772400, 1465776000, 
1465779600, 1465783200, 1465786800, 1465790400, 1465794000, 1465797600, 
1465801200, 1465804800, 1465808400, 1465812000, 1465815600, 1465819200, 
1465822800, 1465826400, 1465830000, 1465833600, 1465837200, 1465840800, 
1465844400, 1465848000, 1465851600, 1465855200, 1465858800, 1465862400, 
1465866000, 1465869600, 1465873200, 1465876800, 1465880400, 1465884000, 
1465887600, 1465891200, 1465894800, 1465898400, 1465902000, 1465905600, 
1465909200, 1465912800, 1465916400, 1465920000, 1465923600, 1465927200, 
1465930800, 1465934400, 1465938000, 1465941600, 1465945200, 1465948800, 
1465952400, 1465956000, 1465959600, 1465963200, 1465966800, 1465970400, 
1465974000, 1465977600, 1465981200, 1465984800, 1465988400, 1465992000, 
1465995600, 1465999200, 1466002800, 1466006400, 1466010000, 1466013600, 
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1466082000, 1466085600, 1466089200, 1466092800, 1466096400, 1466100000, 
1466103600, 1466107200, 1466110800, 1466114400, 1466118000, 1466121600, 
1466125200, 1466128800, 1466132400, 1466136000), class = c("POSIXct", 
"POSIXt")), production = c(17.9, 17.9, 17.9, 17.9, 17.9, 17.9, 
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97.7, 76.7, 76.7, 32.2, 24.7, 24.2, 24.2, 24.2, 24.2, 24.2, 24.2, 
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24.7, 24.7, 24.7, 24.7, 24.7, 24.7, 24.7, 24.7, 24.7, 24.7, 24.7, 
24.7, 24.7, 66.2, 66.2, 67.2, 98.7, 98.7, 98.7, 57.2, 25.7, 24.7, 
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19.7, 19.7, 19.7, 19.7, 19.7, 19.7, 19.7, 61.2, 64.7, 43.2, 41.2, 
28.2, 23.2, 19.7, 19.7, 19.7, 19.7, 19.7, 19.7, 19.7, 17.9, 17.9, 
17.9, 17.9, 17.9, 17.9, 17.9, 17.9, 17.9, 17.9, 17.9, 59.4, 64.7, 
32.2, 56.2, 32.2, 23.2, 17.9, 17.9, 17.9, 17.9, 17.9, 17.9, 17.9, 
17.9, 17.9, 17.9, 17.9, 17.9, 17.9, 17.9, 17.9, 17.9, 17.9, 17.9, 
59.4, 64.7, 73.7, 56.2, 32.2, 23.2, 17.9, 17.9, 17.9, 17.9, 17.9, 
17.9, 17.9), ID = structure(c(4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 
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4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 
4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 
4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 
4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 
4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 
4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 
4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L 
), .Label = c("A", "B", "C","D", "E", "F", "G", "H", "I", "J", 
"K", "L", "M", "N", "O", "P"), class = "factor"), ILP = c(19.8, 19.06, 14.88, 
13.28, 12.3, 13.2, 18.95, 21.19, 21.37, 25, 25.75, 25.57, 25.19, 
23.31, 23.4, 22.69, 25.37, 24.96, 22.53, 20.54, 22.21, 20.26, 
18.94, 16.29, 16.89, 14.21, 12.72, 11.18, 10.26, 11.69, 15.95, 
18.23, 19.11, 19.78, 20.35, 20.15, 21.17, 22.45, 23.7, 24.04, 
25.58, 25.35, 21.73, 19.81, 20.77, 21.05, 20.58, 17.48, 16.09, 
14.15, 11.13, 10.14, 9.76, 11.16, 14.29, 18.79, 18.99, 19.45, 
19.52, 19.45, 20.38, 20.15, 21.52, 20.2, 20.96, 20.56, 18.42, 
17.33, 17.31, 16.95, 18.92, 15.59, 18.9094444444444, 18.9094444444444, 
18.9094444444444, 18.9094444444444, 18.9094444444444, 18.9094444444444, 
18.9094444444444, 18.9094444444444, 18.9094444444444, 18.9094444444444, 
18.9094444444444, 18.9094444444444, 18.9094444444444, 18.9094444444444, 
18.9094444444444, 18.9094444444444, 18.9094444444444, 18.9094444444444, 
18.9094444444444, 18.9094444444444, 18.9094444444444, 18.9094444444444, 
18.9094444444444, 18.9094444444444, 18.9094444444444, 18.9094444444444, 
18.9094444444444, 18.9094444444444, 18.9094444444444, 18.9094444444444, 
18.9094444444444, 18.9094444444444, 18.9094444444444, 18.9094444444444, 
18.9094444444444, 18.9094444444444, 18.9094444444444, 18.9094444444444, 
18.9094444444444, 18.9094444444444, 18.9094444444444, 18.9094444444444, 
18.9094444444444, 18.9094444444444, 18.9094444444444, 18.9094444444444, 
18.9094444444444, 18.9094444444444, 18.9094444444444, 18.9094444444444, 
18.9094444444444, 18.9094444444444, 18.9094444444444, 18.9094444444444, 
18.9094444444444, 18.9094444444444, 18.9094444444444, 18.9094444444444, 
18.9094444444444, 18.9094444444444, 18.9094444444444, 18.9094444444444, 
18.9094444444444, 18.9094444444444, 18.9094444444444, 18.9094444444444, 
18.9094444444444, 18.9094444444444, 18.9094444444444, 18.9094444444444, 
18.9094444444444, 18.9094444444444, 18.9094444444444, 18.9094444444444, 
18.9094444444444, 18.9094444444444, 18.9094444444444, 18.9094444444444, 
18.9094444444444, 18.9094444444444, 18.9094444444444, 18.9094444444444, 
18.9094444444444, 18.9094444444444, 18.9094444444444, 18.9094444444444, 
18.9094444444444, 18.9094444444444, 18.9094444444444, 18.9094444444444, 
18.9094444444444, 18.9094444444444, 18.9094444444444, 18.9094444444444, 
18.9094444444444, 18.9094444444444, 18.9094444444444, 18.9094444444444, 
18.9094444444444, 18.9094444444444, 18.9094444444444, 18.9094444444444, 
18.9094444444444, 18.9094444444444, 18.9094444444444, 18.9094444444444, 
18.9094444444444, 18.9094444444444, 18.9094444444444, 18.9094444444444, 
18.9094444444444, 18.9094444444444, 18.9094444444444, 18.9094444444444, 
18.9094444444444, 18.9094444444444, 18.9094444444444, 18.9094444444444, 
18.9094444444444, 18.9094444444444, 18.9094444444444, 18.9094444444444, 
18.9094444444444, 18.9094444444444, 18.9094444444444, 18.9094444444444, 
18.9094444444444, 18.9094444444444, 18.9094444444444, 18.9094444444444, 
18.9094444444444, 18.9094444444444, 18.9094444444444, 18.9094444444444, 
18.9094444444444, 18.9094444444444, 18.9094444444444, 18.9094444444444, 
18.9094444444444, 18.9094444444444, 18.9094444444444, 18.9094444444444, 
18.9094444444444, 18.9094444444444), Class = structure(c(2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 4L, 4L, 4L, 3L, 3L, 3L, 4L, 3L, 
3L, 2L, 3L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
3L, 3L, 3L, 3L, 4L, 4L, 4L, 4L, 3L, 2L, 3L, 3L, 3L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 3L, 4L, 3L, 4L, 3L, 4L, 4L, 
2L, 2L, 2L, 2L, 3L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L), .Label = c("NA", "Low", "Medium", 
"High"), class = "factor")), .Names = c("date.time", "production", 
"ID", "ILP", "Class"), row.names = 649:864, class = "data.frame") 

prod.data.list = list(prod.data1,prod.data2) 

ID = c('D','O') 
for(i in 1:length(ID)) { 
prod.data = prod.data.list[[i]] 
s=  ggplot(prod.data, aes(x=date.time, y= production, fill = Class),binwidth=0) + 
      geom_bar(stat = 'identity')+ 
      scale_fill_manual(values=c("#A8A8A8","#CCFF99", "#FFA31A", "#CC2900")) + 
      scale_x_datetime() + 
      theme(legend.position = c(0.06,0.82), legend.key.height=unit(0.5,"line"),legend.key.width=unit(0.3,"line"),legend.background = element_blank(),legend.title = element_text("Class",size=8)) 


     f= ggplot(prod.data, aes(x=date.time, y=ILP)) + 
      geom_line() + 
      geom_point() + 
      scale_x_datetime() 

tiff(filename = paste0("Prod_Price_",as.Date(now()),ID[i],".tiff"), width=7,height=4.5,units="in", pointsize=12, bg = "white", res = 150, restoreConsole = TRUE) 
     gs <- ggplotGrob(s) 
     gf<- ggplotGrob(f) 
     grid::grid.draw(rbind(gf, gs)) 
     dev.off() 
    }

而這是我所得到（兩個圖出20 的），任何想法，爲什麼我得到第二圖表條之間的髮際線空間的例子嗎？爲什麼模式如此規則？謝謝你的幫助！

First example

Second example

來源

2016-06-09 Mathieu

能否請您讓您的例子可以重現？ – Andrie

數據集非常大（爲循環中的每個迭代創建了prod.data和price.data數據框 - 我在此故意省略了10多行代碼），所以我很抱歉無法重現數據框的結構在這裏...再加上如果我從頭開始創建一些東西，你可能看不到上面剛剛描述的效果。我想了解爲什麼相同的代碼會產生不同的結果 - 如果任何人有解釋我想聽到它。 – Mathieu

如果不能使用能夠再現問題的數據和代碼，可能很難弄清楚。現在，我不認爲'binwidth = 0'會在主'ggplot'調用中執行任何操作，'binwidth'在'geom_bar'內不是一個合適的參數，因爲數據已經在您的案例中歸檔了（歸因於stat = 「同一性」'）。如果您在'geom_bar'內添加'width = 1'，會發生什麼？ – eipi10

你的問題涉及到屏幕和情節分辨率的某種組合。你的地塊實際上在每個酒吧間都有細線，但有限的屏幕和/或情節分辨率會導致出現一些空間，有些則不會。

下面是使用您的示例數據創建的兩個圖。我使用grid.arrange將它們放置並保存到一個對象中。我刪除了主題陳述，因爲我在嘗試運行它時遇到了一個錯誤，但這對您遇到的問題無關緊要（請注意，binwidth=0沒有任何影響，但我已將它留在下面的代碼中）：

pl = gridExtra::grid.arrange(
    ggplot(prod.data.list[[1]], aes(x=date.time, y= production, fill = Class),binwidth=0) + 
    geom_bar(stat = 'identity')+ 
    scale_fill_manual(values=c("#A8A8A8","#CCFF99", "#FFA31A", "#CC2900")) + 
    scale_x_datetime() + theme_bw() , 
    ggplot(prod.data.list[[2]], aes(x=date.time, y= production, fill = Class),binwidth=0) + 
    geom_bar(stat = 'identity')+ 
    scale_fill_manual(values=c("#A8A8A8","#CCFF99", "#FFA31A", "#CC2900")) + 
    scale_x_datetime() + theme_bw() 
)

好了，現在讓我們將它保存到一個PDF：

pdf("test.pdf", 8,2) 
plot(pl) 
dev.off()

注意，有充分的酒吧之間的空間：

現在看保存爲PNG由於兩項決議同積：

png("test1.png", 1000,200) 
plot(pl) 
dev.off() 

png("test2.png", 3000,600) 
plot(pl) 
dev.off()

正如你可以看到，第一個情節，在較低的分辨率顯示一些條之間的空間，而在其他情況下的空間都沒有了。更高分辨率的圖表顯示了所有的空間。

爲了擺脫空間的，在geom_bar使用width=3600（因爲你的垃圾箱有1小時= 3600秒寬，POSIXct格式以秒爲單位）。

pl2 = gridExtra::grid.arrange(
    ggplot(prod.data.list[[1]], aes(x=date.time, y= production, fill = Class)) + 
    geom_bar(stat = 'identity', width=3600)+ 
    scale_fill_manual(values=c("#A8A8A8","#CCFF99", "#FFA31A", "#CC2900")) + 
    scale_x_datetime() + theme_bw() , 
    ggplot(prod.data.list[[2]], aes(x=date.time, y= production, fill = Class)) + 
    geom_bar(stat = 'identity')+ 
    scale_fill_manual(values=c("#A8A8A8","#CCFF99", "#FFA31A", "#CC2900")) + 
    scale_x_datetime() + theme_bw() 
) 

png("test3.png", 1000, 200) 
plot(pl2) 
dev.off() 

png("test4.png", 3000, 600) 
plot(pl2) 
dev.off()

正如你可以在下面的每個地塊看到，酒吧之間的空間，現在都走在了上游面板，由於width的變化。

來源

2016-06-09 21:28:32 eipi10

謝謝Eipi10和AOsmith對此進行調查，您的解釋很有意義。我非常感謝像你這樣的知識淵博的人們花時間幫助R用戶。週末愉快 – Mathieu

注意binwidth不再geom_bar工作。從文檔：

geom_bar不再有binwidth說法 - 如果你使用它，你會得到一個警告信息，告訴你使用geom_histogram代替。

您在ggplot，而不是geom_bar管理，以避免該警告使用binwidth，這使得它很難意識到它實際上並沒有做任何事情。

在geom_bar中使用width來更改條的寬度。處理因素時，您可以使用width = 1（如問題的評論中所述）來讓酒吧之間沒有空格。使用scale_*_datetime時，情況有點不同。

根據this answer，事實證明日期時間刻度以秒爲單位，所以width = 1等於1秒的條寬。要獲得1小時的條寬（與您的數據相同），您需要的寬度爲3600.

使用此功能可以消除您在第一個示例數據集中看到的空間。

ggplot(prod.data1, aes(x=date.time, y= production, fill = Class)) + 
    geom_bar(stat = 'identity', width = 3600)+ 
    scale_fill_manual(values=c("#A8A8A8","#CCFF99", "#FFA31A", "#CC2900")) + 
    scale_x_datetime()

來源

2016-06-09 21:24:01 aosmith

Barplot：爲什麼我在ggplot2中爲相同的腳本獲得一個可變間距？

回答

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