Hi,
this seems to work (assuming that your problem was the setting of
colours...):
--- snip ---
network %>%
ggraph(., layout = "auto") +
# This produces an error...
# geom_edge_arc(curvature=0.3, aes(width=(E(network)$weight/10),
color=c("darkblue", "red")[as.factor(edge_list$relationship)], alpha=0.5))
+
# ... this works :-)
geom_edge_arc(curvature=0.3, aes(width=E(network)$weight/10,
color=edge_list$relationship), alpha=.5) +
scale_edge_color_manual(values=c("pos"="darkblue", "neg"="red")) +
# This does not work either...
# geom_node_point(aes(size = V(network)$hub_score*200, color=
as.factor(V(network)$community))) +
# ... so try this :)
geom_node_point(aes(size = V(network)$hub_score*200,
color=V(network)$Subcategory_type)) +
geom_node_text(aes(label = V(network)$name), size=3, color="white",
repel=T)+
scale_color_scico_d(palette = "batlow")+
scale_edge_width(range = c(0.2,4))+
scale_size(range = c(0.5,15)) +
theme(plot.background = element_rect(fill = "black"),
legend.position = "right",
panel.background = element_rect(fill = "black"))
--- snip ---
At least in my data created with your code, the object "network" does not
have an attribute "community". I use the existing "Subcategory_type"
instead, because I had no time to debug this problem :-)
I do not know whether this produces what you expect or want to visualise.
HTH,
Kimmo
pe, 2024-03-22 kello 08:59 +0100, sibylle.stoec...@gmx.ch kirjoitti:
> Dear community
>
>
>
> Find enclosed the full working example.
>
>
>
> Many thanks
>
> Sibylle
>
>
>
> Test_cat.csv
>
>
> Names
>
> Subcategory_type
>
> sources.cyto
>
> source
>
> Factor
>
>
> A.A
>
> material
>
> "A"
>
> A
>
> 1
>
>
> B.B
>
> material
>
> "B"
>
> B
>
> 1
>
>
> C.C
>
> regulation
>
> "C"
>
> C
>
> 1
>
>
> D.D
>
> regulation
>
> "D"
>
> D
>
> 1
>
>
> E.E
>
> habitat
>
> "E"
>
> E
>
> 1
>
>
> F.F
>
> cultural
>
> "F"
>
> F
>
> 1
>
>
>
> Test_adjac.csv
>
>
> A.A
>
> B.B
>
> C.C
>
> D.D
>
> E.E
>
> F.F
>
>
> A.A
>
> 0
>
> 0
>
> 5
>
> 5
>
> 5
>
> 5
>
>
> B.B
>
> 4
>
> 0
>
> 1
>
> 1
>
> 1
>
> 1
>
>
> C.C
>
> 5
>
> 5
>
> 0
>
> 5
>
> 4
>
> 2
>
>
> D.D
>
> 5
>
> 0
>
> 5
>
> 0
>
> 5
>
> 3
>
>
> E.E
>
> 5
>
> 1
>
> 5
>
> 5
>
> 0
>
> 4
>
>
> F.F
>
> 1
>
> 2
>
> 3
>
> 4
>
> 5
>
> 5
>
>
>
>
>
> Edges_table-Test.csv
>
>
>
>
> Names
>
> target
>
> weight
>
> relationship
>
>
> B.B
>
> A.A
>
> 4
>
> pos
>
>
> C.C
>
> A.A
>
> 5
>
> pos
>
>
> D.D
>
> A.A
>
> 5
>
> neg
>
>
> E.E
>
> A.A
>
> 5
>
> pos
>
>
> F.F
>
> A.A
>
> 1
>
> pos
>
>
> C.C
>
> B.B
>
> 5
>
> pos
>
>
> E.E
>
> B.B
>
> 1
>
> pos
>
>
> F.F
>
> B.B
>
> 2
>
> neg
>
>
> A.A
>
> C.C
>
> 5
>
> pos
>
>
> B.B
>
> C.C
>
> 1
>
> pos
>
>
> D.D
>
> C.C
>
> 5
>
> pos
>
>
> E.E
>
> C.C
>
> 5
>
> pos
>
>
> F.F
>
> C.C
>
> 3
>
> pos
>
>
> A.A
>
> D.D
>
> 5
>
> neg
>
>
> B.B
>
> D.D
>
> 1
>
> pos
>
>
> C.C
>
> D.D
>
> 5
>
> pos
>
>
> E.E
>
> D.D
>
> 5
>
> pos
>
>
> F.F
>
> D.D
>
> 4
>
> pos
>
>
> A.A
>
> E.E
>
> 5
>
> pos
>
>
> B.B
>
> E.E
>
> 1
>
> pos
>
>
> C.C
>
> E.E
>
> 4
>
> pos
>
>
> D.D
>
> E.E
>
> 5
>
> pos
>
>
> F.F
>
> E.E
>
> 5
>
> pos
>
>
> A.A
>
> F.F
>
> 5
>
> pos
>
>
> B.B
>
> F.F
>
> 1
>
> neg
>
>
> C.C
>
> F.F
>
> 2
>
> pos
>
>
> D.D
>
> F.F
>
> 3
>
> pos
>
>
> E.E
>
> F.F
>
> 4
>
> pos
>
>
> F.F
>
> F.F
>
> 5
>
> pos
>
>
>
>
>
>
>
> #upload librairies
>
> library(circlize)
>
> library(ggplot2)
>
> library(igraph)
>
> library(tidyverse)
>
> library(RColorBrewer)
>
> library(stringi)
>
> library(scico)
>
> library(plotly)
>
> library(ggraph)
>
>
>
> #upload
>
> aes<-read.csv("Test_adjac.csv", row.names = 1)
>
> details<-read.csv("Test_cat.csv")
>
>
>
>
>
> # adjacency table
>
> aes_collapsed<-aes %>%
>
> rownames_to_column(var='Names') %>%
>
> tidyr::gather(target, weight, 1:ncol(aes)+1) %>%
>
> dplyr::filter(weight != 0) %>%
>
> mutate(weight = ifelse(weight == "-1", 0, weight)) # here 0 = negative
> values
>
>
>
> write.csv(aes_collapsed, "edges_table-Test.csv", row.names = F)
>
> edge_list<-read.csv("edges_table-Test.csv")
>
>
>
>
>
> #create network and add some necessary attributes (vertices) for the plot
>
>
>
> network <- graph_from_data_frame(aes_collapsed, directed= FALSE,
>
> vertices = details)
>
>
>
> ### network and vertex with 'subcategory_type'
>
>
>
> temp<-cluster_optimal(network)
>
> temp<-cbind(membership=temp$membership, Names=temp$name)
>
> aes_collapsed <- aes_collapsed %>%
>
> merge(temp, by="Names")
>
>
>
> network <- network %>%
>
> set_edge_attr(name = "type", value = factor(aes_collapsed$Names,
>
> ordered =
> is.ordered(V(network)$name))) %>%
>
> set_edge_attr(name = "membership", value = aes_collapsed$membership)
> %>%
>
> set_edge_attr(name = "color",
>
> value = c(viridis::viridis(21))
>
> [match(E(.)$type, c(factor(V(.)$name)))]) %>%
>
> set_vertex_attr(name = "trans_v_net", value = c(transitivity(., type =
> "local"))) %>%
>
> set_vertex_attr(name = "hub_score", value = c(hub_score(.)$vector)) %>%
>
> set_vertex_attr(name = "color",
>
> value = c(viridis::viridis((21)))
>
> [match(V(.)$name, c(factor(V(.)$name)))]) %>%
>
> set_vertex_attr(name= "community",
> value=cluster_optimal(.)$Subcategory_type)
>
>
>
> clrs<-scico(3, palette = "batlow")
>
>
>
> windowsFonts(Helvetica = windowsFont("Helvetica"))
>
>
>
> par(bg="black")
>
> network %>% plot(
>
> vertex.color=clrs[V(.)$community],
>
> vertex.size=V(.)$hub_score*20,
>
> vertex.frame.color=V(.)$color,
>
> vertex.label.color="white",
>
> vertex.label.cex=0.4,
>
> vertex.label.family="Helvetica",
>
> vertex.label.font=0.75,
>
> edge.curved=0.5,
>
> edge.width= E(.)$weight,
>
> edge.color = ifelse(edge_list$relationship == "pos", "blue", "red"),
>
> layout=layout_with_mds(.))
>
>
>
> tiff("figures/Test_network_bysubcatecory.tiff", width=1000, height=900,
> res=120)
>
> network %>%
>
> ggraph(., layout = "auto")+
>
> geom_edge_arc(curvature=0.3, aes(width=(E(network)$weight/10),
> color=c("darkblue", "red")[as.factor(edge_list$relationship)],
> alpha=0.5)) +
>
> geom_node_point(aes(size = V(network)$hub_score*200, color=
> as.factor(V(network)$community))) +
>
> geom_node_text(aes(label = V(network)$name), size=3, color="white",
> repel=T)+
>
> scale_color_scico_d(palette = "batlow")+
>
> scale_edge_width(range = c(0.2,4))+
>
> scale_size(range = c(0.5,15)) +
>
> theme(plot.background = element_rect(fill = "black"),
>
> legend.position = "right",
>
> panel.background = element_rect(fill = "black"))
>
> dev.off()
>
>
>
> -----Original Message-----
> From: R-help <r-help-boun...@r-project.org> On Behalf Of Kimmo Elo
> Sent: Thursday, March 21, 2024 10:51 AM
> To: r-help@r-project.org
> Subject: Re: [R] geom_edge & color
>
>
>
> Dear Sibylle,
>
>
>
> your example is not working! E.g. no data for "aes_collapsed".
>
>
>
> Best,
>
>
>
> Kimmo
>
>
>
> ke, 2024-03-20 kello 19:28 +0100, SIBYLLE STÖCKLI via R-help kirjoitti:
>
> > Dear community
>
> >
>
> > I am using ggraph to plot a network analysis. See part 2 in the
>
> > working example.
>
> > Besides different colors for different groups of nodes:
>
> > --> geom_node_point(aes(size = V(network)$hub_score*200, color=
>
> > as.factor(V(network)$community)))
>
> > I additionally want to consider different colors for different edge
>
> > groups The grouping is defined in the edge_list$relationship: negative
>
> > relationship = red and positive relationship = darkblue. The code is
>
> > working in the way that the groups are separated by two colors.
>
> > However, the code uses not the assigned colors. Does anyone have any
>
> > idea how to adapt the code?
>
> > --> geom_edge_arc(curvature=0.3, aes(width=(E(network)$weight/10),
>
> > color=c("darkblue", "red")[as.factor(edge_list$relationship)],
>
> > alpha=0.5)) +
>
> >
>
> > Kind regards
>
> > Sibylle
>
> >
>
> >
>
> >
>
> >
>
> > Working example
>
> >
>
> > library(circlize)
>
> > library(ggplot2)
>
> > library(igraph)
>
> > library(tidyverse)
>
> > library(RColorBrewer)
>
> > library(stringi)
>
> > library(scico)
>
> > library(plotly)
>
> > library(ggraph)
>
> >
>
> > edges_table_Test.csv
>
> >
>
> > Names target weight relationship
>
> > B.B A.A 4 pos
>
> > C.C A.A 5 pos
>
> > D.D A.A 5 neg
>
> > E.E A.A 5 neg
>
> > F.F A.A 1 pos
>
> > C.C B.B 5 pos
>
> > E.E B.B 1 pos
>
> > F.F B.B 2 pos
>
> > A.A C.C 5 pos
>
> > B.B C.C 1 pos
>
> > D.D C.C 5 pos
>
> > E.E C.C 5 pos
>
> > F.F C.C 3 pos
>
> > A.A D.D 5 neg
>
> > B.B D.D 1 neg
>
> > C.C D.D 5 neg
>
> > E.E D.D 5 neg
>
> > F.F D.D 4 neg
>
> > A.A E.E 5 neg
>
> > B.B E.E 1 neg
>
> > C.C E.E 4 neg
>
> > D.D E.E 5 neg
>
> > F.F E.E 5 pos
>
> > A.A F.F 5 pos
>
> > B.B F.F 1 pos
>
> > C.C F.F 2 pos
>
> > D.D F.F 3 pos
>
> > E.E F.F 4 pos
>
> > F.F F.F 5 pos
>
> >
>
> > edge_list<-read.csv("edges_table_Test.csv")
>
> >
>
> > network <- graph_from_data_frame(aes_collapsed, directed= FALSE,
>
> > vertices = details)
>
> >
>
> > temp<-cluster_optimal(network)
>
> > temp<-cbind(membership=temp$membership, Names=temp$name) aes_collapsed
>
> > <- aes_collapsed %>%
>
> > merge(temp, by="Names")
>
> >
>
> >
>
> > network <- network %>%
>
> > set_edge_attr(name = "type", value = factor(aes_collapsed$Names,
>
> > ordered =
>
> > is.ordered(V(network)$name))) %>%
>
> > set_edge_attr(name = "membership", value = aes_collapsed$membership)
>
> > %>%
>
> > set_edge_attr(name = "color",
>
> > value = c(viridis::viridis(5))
>
> > [match(E(.)$type, c(factor(V(.)$name)))]) %>%
>
> > set_vertex_attr(name = "trans_v_net", value = c(transitivity(., type
>
> > =
>
> > "local"))) %>%
>
> > set_vertex_attr(name = "hub_score", value = c(hub_score(.)$vector))
>
> > %>%
>
> > set_vertex_attr(name = "color",
>
> > value = c(viridis::viridis((5)))
>
> > [match(V(.)$name, c(factor(V(.)$name)))]) %>%
>
> > set_vertex_attr(name= "community",
>
> > value=cluster_optimal(.)$membership)
>
> > clrs<-scico(3, palette = "batlow")
>
> >
>
> > ### part 1: network plot
>
> > par(bg="black")
>
> > network %>% plot(
>
> > vertex.color=clrs[V(.)$community],
>
> > vertex.size=V(.)$hub_score*5,
>
> > vertex.frame.color=V(.)$color,
>
> > vertex.label.color="white",
>
> > vertex.label.cex=0.5,
>
> > vertex.label.family="Helvetica",
>
> > vertex.label.font=1,
>
> > edge.curved=0.5,
>
> > edge.width= network,
>
> > layout=layout_with_mds(.))
>
> >
>
> > ### part 2: ggraph
>
> > tiff("figures/AES_network_bymembership.tiff", width=1000, height=700,
>
> > res=120) network %>%
>
> > ggraph(., layout = "auto")+
>
> > geom_edge_arc(curvature=0.3, aes(width=(E(network)$weight/10),
>
> > color=c("darkblue", "red")[as.factor(edge_list$relationship)],
>
> > alpha=0.5)) +
>
> >
>
> > geom_node_point(aes(size = V(network)$hub_score*200, color=
>
> > as.factor(V(network)$community))) +
>
> > geom_node_text(aes(label = V(network)$name), size=5, color="white",
>
> > repel=T)+
>
> > scale_color_scico_d(palette = "batlow")+
>
> > scale_edge_width(range = c(0.2,4))+
>
> > scale_size(range = c(0.5,20)) +
>
> > #scale_edge_color_manual(values = c(scico(21, palette="batlow")))+
>
> > theme(plot.background = element_rect(fill = "black"),
>
> > legend.position = "right",
>
> > panel.background = element_rect(fill = "black"))
>
> > dev.off()
>
> >
>
> > ______________________________________________
>
> > <mailto:R-help@r-project.org> R-help@r-project.org mailing list -- To
> > UNSUBSCRIBE and more, see
>
> > <https://stat.ethz.ch/mailman/listinfo/r-help>
> > https://stat.ethz.ch/mailman/listinfo/r-help
>
> > PLEASE do read the posting guide
>
> > <http://www.R-project.org/posting-guide.html>
> > http://www.R-project.org/posting-guide.html
>
> > and provide commented, minimal, self-contained, reproducible code.
>
>
>
> ______________________________________________
>
> <mailto:R-help@r-project.org> R-help@r-project.org mailing list -- To
> UNSUBSCRIBE and more, see <https://stat.ethz.ch/mailman/listinfo/r-help>
> https://stat.ethz.ch/mailman/listinfo/r-help
>
> PLEASE do read the posting guide
> <http://www.R-project.org/posting-guide.html>
> http://www.R-project.org/posting-guide.html
>
> and provide commented, minimal, self-contained, reproducible code.
>
______________________________________________
R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
