我有2个数据框:
df1
SeqTech NMDS1 NMDS2 NMDS3 C1 C2 C3
AM.AD.1 Sanger -1.2408789 0.39893503 -0.036690753 -1.0330785 -0.009904179 -0.06261568
AM.AD.2 Sanger -0.9050894 0.55943858 -0.121985899 -1.0330785 -0.009904179 -0.06261568
AM.F10.T1 Sanger -0.9059108 0.09466239 -0.033827792 -1.0330785 -0.009904179 -0.06261568
AM.F10.T2 Sanger -0.8511172 0.21396548 -0.061612450 -1.0330785 -0.009904179 -0.06261568
DA.AD.1 Sanger -1.1390353 0.05166118 0.306245704 -1.0330785 -0.009904179 -0.06261568
DA.AD.1T Sanger -1.2072895 0.06963215 0.241758582 -1.0330785 -0.009904179 -0.06261568
DA.AD.2 Sanger -1.1279367 -0.18692443 -0.092967153 -1.0330785 -0.009904179 -0.06261568
DA.AD.3 Sanger -1.3517083 -0.03651835 0.008165075 -1.0330785 -0.009904179 -0.06261568
DA.AD.3T Sanger -1.2616186 -0.06099534 -0.016942073 -1.0330785 -0.009904179 -0.06261568
DA.AD.4 Sanger -1.2700349 0.10824017 0.150317712 -1.0330785 -0.009904179 -0.06261568
TS1_V2 Pyro454 0.2094447 -0.53605610 0.154892961 0.2750404 0.002636827 0.01667041
TS10_V2 Pyro454 0.3966404 -0.10453275 -0.016794425 0.2750404 0.002636827 0.01667041
TS100_V2 Pyro454 0.2409404 -0.19935538 -0.095123709 0.2750404 0.002636827 0.01667041
TS101.2_V2 Pyro454 0.3576462 0.78659670 -0.393325760 0.2750404 0.002636827 0.01667041
TS103_V2 Pyro454 0.6018257 -0.19066765 0.017434390 0.2750404 0.002636827 0.01667041
TS104_V2 Pyro454 0.2554765 -0.33614221 -0.009296729 0.2750404 0.002636827 0.01667041
TS105_V2 Pyro454 0.2898261 0.74827877 -0.531568414 0.2750404 0.002636827 0.01667041
TS106_V2 Pyro454 0.3539052 0.17369739 -0.181935984 0.2750404 0.002636827 0.01667041
TS107_V2 Pyro454 0.0385423 0.10432457 0.465820636 0.2750404 0.002636827 0.01667041
TS109_V2 Pyro454 0.2525936 -0.33896215 -0.173134963 0.2750404 0.002636827 0.01667041
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df2
SeqTech C1 C2 C3
1 Pyro454 0.2750404 0.002636827 0.01667041
2 Sanger -1.0330785 -0.009904179 -0.06261568
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我用它来制作二维图,例如:
ggplot(df1, aes_string(x = "NMDS1", y = "NMDS2" )) +
geom_vline(xintercept = 0, linetype="dashed", size = 0.25, color= "#999999") +
geom_hline(yintercept = 0, linetype="dashed", size = 0.25, color= "#999999") +
# sites
geom_point(size = 2, alpha=0.3, aes_string(color= "SeqTech")) +
#Centroids
geom_point(data = df2, aes_string(x="C1", y="C2", color=df2[,1]), size = 1, alpha=0.7, shape=19 ) +
# Lines
geom_segment(data = df1, aes_string(xend = "C1", yend = "C2", colour=df1$SeqTech ), alpha=0.3, linetype= "dashed" )
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所以如果我想用plotly制作类似的东西,但用2D生成3D图。我有一个制作 3D 的代码,但我不知道如何连接这些点并生成一个中心点。
plotly::plot_ly(
x=df1[,2],
y=df1[,3],
z=df1[,4],
type="scatter3d",
mode="markers",
marker=list(size=3, opacity = 0.7),
color=df1[, "SeqTech"],
hovertemplate = paste(df1[,"SeqTech"]))
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如何在plotly中添加类似于geom_segment的内容?
非常感谢 !!!
dput的df1
SeqTech NMDS1 NMDS2 NMDS3 C1 C2 C3
AM.AD.1 Sanger -1.2408789 0.39893503 -0.036690753 -1.0330785 -0.009904179 -0.06261568
AM.AD.2 Sanger -0.9050894 0.55943858 -0.121985899 -1.0330785 -0.009904179 -0.06261568
AM.F10.T1 Sanger -0.9059108 0.09466239 -0.033827792 -1.0330785 -0.009904179 -0.06261568
AM.F10.T2 Sanger -0.8511172 0.21396548 -0.061612450 -1.0330785 -0.009904179 -0.06261568
DA.AD.1 Sanger -1.1390353 0.05166118 0.306245704 -1.0330785 -0.009904179 -0.06261568
DA.AD.1T Sanger -1.2072895 0.06963215 0.241758582 -1.0330785 -0.009904179 -0.06261568
DA.AD.2 Sanger -1.1279367 -0.18692443 -0.092967153 -1.0330785 -0.009904179 -0.06261568
DA.AD.3 Sanger -1.3517083 -0.03651835 0.008165075 -1.0330785 -0.009904179 -0.06261568
DA.AD.3T Sanger -1.2616186 -0.06099534 -0.016942073 -1.0330785 -0.009904179 -0.06261568
DA.AD.4 Sanger -1.2700349 0.10824017 0.150317712 -1.0330785 -0.009904179 -0.06261568
TS1_V2 Pyro454 0.2094447 -0.53605610 0.154892961 0.2750404 0.002636827 0.01667041
TS10_V2 Pyro454 0.3966404 -0.10453275 -0.016794425 0.2750404 0.002636827 0.01667041
TS100_V2 Pyro454 0.2409404 -0.19935538 -0.095123709 0.2750404 0.002636827 0.01667041
TS101.2_V2 Pyro454 0.3576462 0.78659670 -0.393325760 0.2750404 0.002636827 0.01667041
TS103_V2 Pyro454 0.6018257 -0.19066765 0.017434390 0.2750404 0.002636827 0.01667041
TS104_V2 Pyro454 0.2554765 -0.33614221 -0.009296729 0.2750404 0.002636827 0.01667041
TS105_V2 Pyro454 0.2898261 0.74827877 -0.531568414 0.2750404 0.002636827 0.01667041
TS106_V2 Pyro454 0.3539052 0.17369739 -0.181935984 0.2750404 0.002636827 0.01667041
TS107_V2 Pyro454 0.0385423 0.10432457 0.465820636 0.2750404 0.002636827 0.01667041
TS109_V2 Pyro454 0.2525936 -0.33896215 -0.173134963 0.2750404 0.002636827 0.01667041
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您需要以某种格式准备数据以输入到绘图中,以便绘图知道哪个点是哪个点,以及哪个点应该用线连接。下面是实现它的一种方法。
library(plotly)
library(dplyr)
# create a data_frame with two record per Name/SeqTech
# This will be provided to plotly for line drawing later
plotly_data <- bind_rows(
data %>% select(Name, SeqTech, x = NMDS1, y = NMDS2, z= NMDS3),
data %>% select(Name, SeqTech, x = C1, y = C2, z= C3)) %>%
# define the group variable which will be used by plotly for line drawing
group_by(Name)
# Here is what the data look like
plotly_data %>% arrange(Name) %>% head(20)
#> Name SeqTech x y z
#> 1 AM.AD.1 Sanger -1.2408789 0.398935030 -0.036690753
#> 2 AM.AD.1 Sanger -1.0330785 -0.009904179 -0.062615680
#> 3 AM.AD.2 Sanger -0.9050894 0.559438580 -0.121985899
#> 4 AM.AD.2 Sanger -1.0330785 -0.009904179 -0.062615680
#> 5 AM.F10.T1 Sanger -0.9059108 0.094662390 -0.033827792
#> 6 AM.F10.T1 Sanger -1.0330785 -0.009904179 -0.062615680
#> 7 AM.F10.T2 Sanger -0.8511172 0.213965480 -0.061612450
#> 8 AM.F10.T2 Sanger -1.0330785 -0.009904179 -0.062615680
#> 9 DA.AD.1 Sanger -1.1390353 0.051661180 0.306245704
#> 10 DA.AD.1 Sanger -1.0330785 -0.009904179 -0.062615680
#> 11 DA.AD.1T Sanger -1.2072895 0.069632150 0.241758582
#> 12 DA.AD.1T Sanger -1.0330785 -0.009904179 -0.062615680
#> 13 DA.AD.2 Sanger -1.1279367 -0.186924430 -0.092967153
#> 14 DA.AD.2 Sanger -1.0330785 -0.009904179 -0.062615680
#> 15 DA.AD.3 Sanger -1.3517083 -0.036518350 0.008165075
#> 16 DA.AD.3 Sanger -1.0330785 -0.009904179 -0.062615680
#> 17 DA.AD.3T Sanger -1.2616186 -0.060995340 -0.016942073
#> 18 DA.AD.3T Sanger -1.0330785 -0.009904179 -0.062615680
#> 19 DA.AD.4 Sanger -1.2700349 0.108240170 0.150317712
#> 20 DA.AD.4 Sanger -1.0330785 -0.009904179 -0.062615680
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由reprex 包于 2021 年 5 月 11 日创建(v2.0.0)
使用上面的数据绘制代码
# And here is the code for line & scatter point drawing with plotly
plotly::plot_ly(data = plotly_data %>% group_by(Name),
x= ~x,
y= ~y,
z= ~z,
# as the group is defined in the data the name can be define by SeqTech
name = ~SeqTech,
type="scatter3d",
mode="lines+markers",
marker=list(size=3, opacity = 0.7),
color= ~SeqTech,
hovertemplate = ~SeqTech)
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