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# Define nodes
nodes <- data.frame(name = #sources
c("Phthalates", "Phenols", " ", "Organic Solvents", #0-3 removed Parabens bc no links
"Heavy Metals", "Air Pollution", "Depression", #4-6
"Perceived Stress", "Cigarette Smoke", #7-8
"Alcohol Consumption", "Physical Activity", #9-10
"Dietary Pesticides", "Caffeine Consumption", #11-12
"Roadway Proximity", "Indoor Air Temperature", #13-14
#targets : symptoms
"Vasomotor", "Sleep", "Cognitive", "Cardiovascular", #15-18
"Uro-vaginal", "Physical", "Depressed", "Anxious",#20-23
"Metabolic", #24
#more specific symptoms
"Hot flashes", "Night sweats", #25-26
"Sleep quality", "Insomnia", "Sleep duration", #27-29
"Forgetfulness", " ", "Heart discomfort", #30-32 removed Mental exhaustion because no links
"Sexual problems", "Bladder problems", "", #33-35 removed "Vaginal dryness" bc no links
"", "Joint and muscular discomfort", "Lung function", "", #36-38 removed Physical exhaustion and Headaches bc no links
"Depressive mood", "Irritability", "Axiety", #39-41
"Body weight/BMI change", "Body fat change" #42-43
))
nodeNo <- 0:(nrow(nodes)-1)
nodeDf <- cbind(nodes, nodeNo)
#pared down symptoms
nodes <- data.frame(name = #sources
c("Phthalates", "Phenols", " ", "Organic Solvents", #0-3 removed Parabens bc no links
"Heavy Metals", "Air Pollution", "", #4-5
"", "", #6- 7 deleted broader exposures
"", "", #8-9
"Dietary Pesticides", "", #10-11
"", "", #12-13
#targets : symptoms
"Vasomotor", "Sleep disturbances", "Cognitive", "Cardiovascular", #14-17
"", "Respiratory", "Psychological", "Other",# 18-21
"Metabolic", #21
#more specific symptoms
"Hot flashes", "Night sweats", #25-26
"Sleep quality/Restless sleep", "Insomnia/Difficulty sleeping", "Sleep duration", #27-29
"Forgetfulness", " ", "Heart discomfort", #30-32 removed Mental exhaustion because no links
"", "", "", #33-35 removed "Vaginal dryness" bc no links
"", "Joint and muscular discomfort", "Lung function", "", #36-38 removed Physical exhaustion and Headaches bc no links
"Depressive mood", "Irritability", "Axiety", #39-41
"Body weight/BMI change", "Body fat change" #42-43
))
nodeNo <- 0:(nrow(nodes)-1)
nodeDf <- cbind(nodes, nodeNo)
# Define links with positive, negative, and mixed associations
links <- data.frame(source = c(
0, 3, 5, 6, 7, 8, 14,
9, 10, 12, 0, 1, 3, 5, 7, 8,
13, 10, 4, 3, 7, 10, 8, 12,
5, 7, 8, 10,
7, 8, 10, 10,
3, 4, 3, 0, 11),
target = c(
15, 15, 15, 15, 15, 15, 15,
15, 15, 15, 16, 16, 16, 16, 16, 16,
16, 16, 16, 17, 17, 17, 17, 17,
18, 18, 18, 18,
19, 19, 19, 20,
21, 21, 22, 23, 23),
value = c(
1, 1, 1, 1, 1, 1, 1,
1, 1, 1, 1, 1, 1, 1, 1, 1,
1, 1, 1, 1, 1, 1, 1, 1,
1, 1, 1, 1,
1, 1, 1, 1,
1, 1, 1, 1, 1),
association = c(
"positive", "positive", "positive", "positive", "positive", "positive", "positive",
"negative", "mixed", "mixed", "positive", "positive", "positive", "positive", "positive", "positive",
"positive", "negative", "mixed", "positive", "positive", "positive", "positive", "positive",
"positive", "positive", "positive", "negative",
"positive", "positive", "negative", "negative",
"negative", "positive", "negative", "positive", "mixed"))
write.csv(links, "~/OneDrive - California State University East Bay/Research/sankeyMenopause/links.csv", row.names = FALSE, )
links <- read.csv("~/OneDrive - California State University East Bay/Research/sankeyMenopause/linksAdd.csv", header = TRUE)
linksCondense <- read.csv("~/OneDrive - California State University East Bay/Research/sankeyMenopause/linksCondense.csv", header = TRUE)
# Add color based on association
links$color <- ifelse(links$association == "positive", "green",
ifelse(links$association == "negative", "red", "yellow"))
nodes$NodeGroup <- c(rep("blue", 15), rep("gray", 29))
color_scale <- 'd3.scaleOrdinal().domain(["green", "red", "yellow", "blue", "gray"]).range(["#009E73", "#D55E00", "#F0E442", "#5b5c63", "#5D76C3"])'
#(["#4c732a", "#8c2623", "#996e18", "#262e66", "#5b5c63"])'
nodes$x[16:24] <- nodes$x[16:24] - 0.5
# Create Sankey diagram
sankey <- sankeyNetwork(Links = links, Nodes = nodes, Source = "source", Target = "target", Value = "value", NodeID = "name", units = "T", fontSize = 12, fontFamily = "serif", nodeWidth = 20, LinkGroup = "color", colourScale = color_scale, NodeGroup = "NodeGroup", margin = list("left"=190), width = 650)
sankey # , width = 500, height = 500)
# Add custom CSS to adjust label positions/ wider distance
# htmlwidgets::onRender(sankey, '
# function(el, x) {
# d3.selectAll(".node text")
# .attr("x", function(d) {
# if (d.x + d.dx >= x.size[0] - 30) {
# return d.x + d.dx + 10; // Far right nodes
# } else {
# return d.x + d.dx + 10; // Other nodes
# }
# })
# .attr("text-anchor", "start")
# .style("font-size", "12px");
# }
# ')
#successfully puts labels all on right side
sankey$x$nodes <-
sankey$x$nodes %>%
mutate(is_source_node = name %in% links$source)
htmlwidgets::onRender(
sankey,
'
function(el,x) {
d3.select(el)
.selectAll(".node text")
.filter(function(d) { return d.is_source_node; })
.attr("x", x.options.nodeWidth)
.attr("text-anchor", "end");
d3.select(el)
.selectAll(".node text")
.filter(function(d) { return !d.is_source_node; })
.attr("x", 2+ x.options.nodeWidth)
.attr("text-anchor", "start");
}
'
)sankeyCondense <- sankeyNetwork(Links = linksCondense, Nodes = nodes, Source = "source", Target = "target", Value = "value", NodeID = "name", units = "T", fontSize = 14, fontFamily = "serif", nodeWidth = 40, LinkGroup = "color", colourScale = color_scale, NodeGroup = "NodeGroup", margin = list("left"=120), width = 600, height = 500)
# Plot the Sankey diagram
sankey#saveNetwork(sankey, "sankey.html")
# you convert it as png
#webshot("sankey.html","sankey.png", vwidth = 1200, vheight = 900)
#sankeyCondense
# Customize the legend manually
legend <- tags$div(style = "display: flex; flex-direction: column; padding-left: 10px; margin-top: 12px; font-family: serif;", # Adjust font and spacing
tags$div(style = "display: flex; align-items: center; margin-bottom: 2px;",
tags$div(style = "width: 12px; height: 12px; background-color: #009E73;"), "Positive association"),
tags$div(style = "display: flex; align-items: center; margin-bottom: 2px;",
tags$div(style = "width: 12px; height: 12px; background-color: #D55E00;"), "Negative association"),
tags$div(style = "display: flex; align-items: center; margin-bottom: 2px;",
tags$div(style = "width: 12px; height: 12px; background-color: #F0E442;"), "Mixed results")
)
# Combine the Sankey diagram and legend
sankey <- tagList(
sankey,
tags$div(style = "margin-top: -80px;", legend) # Adjust vertical position of the legend
)
# Display the combined diagram with the legend
sankey