创建一个'；水平加粗填料'；对于带有R的ggplot2条形图

我正在使用R，有一个简单的data.frame，有两列。一列是

覆盖范围

，另一列是

唯一性

。我需要生成一个类似下面的图，其中x轴是

1:length（df）

，y轴是

coverage

。我可以用这个简单的代码来构建它，但我需要添加一个特性，其中

唯一性

显示为沿x轴的渐变。我尝试了一些方法，我认为使用

填充
或
缩放颜色梯度（）
应该是答案，但对我不起作用

# barplot
library(ggplot2)
library(graphics)
barplot(df)

# more about barplot() function 
?barplot()


编辑：当前绘图


dput（新数据）
结构（列表）覆盖率=c（3.36729582998647，3.36729582998647，
3.36729582998647, 3.36729582998647, 3.36729582998647, 3.36729582998647, 
3.36729582998647, 3.93182563272433, 3.95124371858143, 3.95124371858143, 
3.93182563272433, 3.93182563272433, 3.93182563272433, 3.91202300542815, 
3.91202300542815, 3.91202300542815, 3.91202300542815, 3.93182563272433, 
3.36729582998647, 3.36729582998647, 3.36729582998647, 4.27666611901606, 
4.27666611901606, 4.29045944114839, 4.29045944114839, 4.29045944114839, 
4.29045944114839, 4.29045944114839, 4.29045944114839, 3.97029191355212, 
4.20469261939097, 4.20469261939097, 5.17048399503815, 5.17048399503815, 
5.16478597392351, 5.12396397940326, 5.24702407216049, 5.31811999384422, 
5.03695260241363, 5.03695260241363, 3.55534806148941, 3.55534806148941, 
3.55534806148941, 3.55534806148941, 3.55534806148941, 3.55534806148941, 
3.55534806148941, 3.55534806148941, 3.55534806148941, 3.55534806148941, 
3.55534806148941, 3.55534806148941, 3.55534806148941, 3.58351893845611, 
3.58351893845611, 3.58351893845611, 3.58351893845611, 3.58351893845611, 
4.66343909411207, 4.66343909411207, 4.67282883446191, 4.67282883446191, 
4.67282883446191, 4.67282883446191, 4.68213122712422, 4.68213122712422, 
4.68213122712422, 4.54329478227, 4.52178857704904, 4.52178857704904, 
4.52178857704904, 4.52178857704904, 4.52178857704904, 4.52178857704904, 
4.52178857704904, 3.71357206670431, 4.18965474202643, 4.47733681447821, 
4.47733681447821, 4.51085950651685, 4.51085950651685, 4.52178857704904, 
4.53259949315326, 4.53259949315326, 4.55387689160054, 4.56434819146784, 
5.23110861685459, 5.2257466737132, 5.2257466737132, 5.22035582507832, 
5.2040066870768, 5.20948615284142, 5.2040066870768, 5.2040066870768, 
5.29330482472449, 5.28826703069454, 5.28826703069454, 5.31811999384422, 
5.31811999384422, 5.31320597904179, 5.30826769740121, 5.31320597904179, 
5.39816270151775, 5.39816270151775, 5.39816270151775, 5.5834963087817, 
6.10479323241498, 6.10702288774225, 6.10924758276437, 6.10702288774225, 
6.10924758276437, 6.11809719804135, 6.1527326947041, 6.1527326947041, 
6.19031540585315, 6.14418563412565, 6.18620862390049, 6.18208490671663, 
6.18208490671663, 6.16961073249146, 6.20455776256869, 6.22257626807137, 
6.22455842927536, 6.23244801655052, 6.2363695902037, 6.27476202124194, 
6.27476202124194, 6.27664348934164, 6.22653666928747, 6.23048144757848, 
6.23048144757848, 6.25958146406492, 6.26339826259162, 6.33505425149806, 
6.33682573114644, 6.33859407820318, 6.34388043412633, 6.34738920965601, 
6.3456363608286, 6.36302810354046, 6.361302477573, 6.36302810354046, 
6.36818718635049, 6.36990098282823, 6.35088571671474, 6.35437004079735, 
6.35610766069589, 6.35610766069589, 6.36647044773144, 6.31716468674728, 
6.32076829425058, 6.32256523992728, 6.32256523992728, 6.31896811374643, 
6.23441072571837, 6.23441072571837, 6.25190388316589, 6.21060007702465, 
6.20657592672493, 6.27476202124194, 6.27287700654617, 6.27287700654617, 
6.2709884318583, 6.26909628370626, 6.26339826259162, 6.26339826259162, 
6.25766758788264, 6.22257626807137, 6.19440539110467, 6.28226674689601, 
6.28226674689601, 6.28226674689601, 6.29156913955832, 6.29526600143965, 
11.0455902722788, 11.0605574107758, 11.0683712350503, 11.071750274228, 
11.0739397670939, 11.0765732227783, 11.0778873545197, 11.0833110966291, 
11.0838334262309, 11.0849539777208, 11.0965005166257, 11.0927172087879, 
11.0931737881036, 11.0867626290829, 11.0878034189527, 11.0857974002258, 
11.0760935211126, 11.0667477313608, 10.9871723112865, 10.3838436594859, 
10.3461842172496, 10.2861956735217, 10.066838635698, 9.62350906446938, 
9.59960834518178, 9.58493381641726, 9.55272367519805, 9.55619700847904, 
9.55937621211763, 9.56212336983449, 9.5262454033717, 9.51332968849511, 
9.5117774096603, 9.46086560003161, 9.45727857185611, 9.45821555950958, 
9.45813751072905, 9.45602788772529, 9.44065812703839, 9.38915578944085, 
9.33308883723524, 4.30406509320417, 4.30406509320417, 4.29045944114839, 
4.27666611901606, 4.27666611901606, 4.27666611901606, 4.27666611901606, 
4.27666611901606, 4.27666611901606, 4.30406509320417, 4.31748811353631, 
4.30406509320417, 4.31748811353631, 4.31748811353631, 4.29045944114839, 
4.29045944114839, 4.29045944114839, 4.29045944114839, 4.29045944114839, 
4.30406509320417, 3.91202300542815, 3.87120101090789, 3.85014760171006, 
3.29583686600433, 3.29583686600433, 3.29583686600433, 2.94443897916644, 
2.94443897916644, 2.94443897916644, 2.94443897916644, 2.94443897916644, 
3.80666248977032, 3.80666248977032, 4.40671924726425, 5.91079664404053, 
5.90808293816893, 5.84643877505772, 5.31320597904179, 5.16478597392351, 
5.17048399503815, 5.17048399503815, 3.25809653802148, 3.25809653802148, 
3.25809653802148, 3.25809653802148, 3.25809653802148, 3.25809653802148, 
3.25809653802148, 3.25809653802148, 3.25809653802148, 3.29583686600433, 
3.29583686600433, 3.29583686600433, 3.29583686600433, 3.29583686600433, 
3.29583686600433, 3.29583686600433, 3.29583686600433, 3.29583686600433, 
3.29583686600433, 3.29583686600433, 3.29583686600433, 3.29583686600433, 
3.29583686600433, 3.29583686600433, 3.
ggplot(df, aes(1:nrow(df), uniqueness, fill = uniqueness)) + 
    geom_bar(stat = "identity")