我已经构建了下面的测试应用程序,在这里我解决了这个问题,让勾号标签作为科学注释,但现在我想减少网格线的数量,使其仅放置在“主”勾号上,即具有文本标签的勾号上。
这个问题是根据之前的讨论/评论发布的
SO question
我想找到一种既适用于二维又适用于三维平面散点图的方法,因为我同时使用这两种方法。
这是3D应用程序。
library(shiny)
library(plotly)
shinyApp(
ui = fluidPage( plotlyOutput('plot') ),
server = function(input, output) {
output$plot <- renderPlotly ({
mtcars <- rbind(mtcars, mtcars*1000, mtcars/1000) #create data with big logarithmic range
maxlog <- round(log10(max(mtcars[['mpg']][mtcars[['mpg']]>0], mtcars[['disp']][mtcars[['disp']]>0],mtcars[['cyl']][mtcars[['cyl']]>0])), digits = 0) +1 # determine max log needed
minlog <- round(log10(min(mtcars[['mpg']][mtcars[['mpg']]>0], mtcars[['disp']][mtcars[['disp']]>0],mtcars[['cyl']][mtcars[['cyl']]>0])), digits = 0) -1 # determine min log needed
logrange <- (maxlog - minlog)*9 +1 # get the distance between smallest and largest log power
tval <- sort(as.vector(sapply(seq(1,9), function(x) x*10^seq(minlog, maxlog)))) #generates a sequence of numbers in logarithmic divisions
ttxt <- rep("",length(tval)) # no label at most of the ticks
ttxt[seq(1,logrange,9)] <- formatC(tval, format = "e", digits = 2)[seq(1,logrange,9)] # every 9th tick is labelled
p <- plot_ly(source = 'ThresholdScatter')
p <- add_trace(p, data = mtcars,
x = mtcars[['mpg']],
y = mtcars[['disp']],
z = mtcars[['cyl']],
type = 'scatter3d',
mode = 'markers',
marker = list(size = 2))
p <- layout(p, autosize = F, width = 500, height = 500,
scene = list(yaxis = list(type="log",
zeroline=F, showline=T,
ticks="outside",
tickvals=tval,
ticktext=ttxt),
xaxis = list(type="log",
zeroline=F, showline=T,
ticks="outside",
tickvals=tval,
ticktext=ttxt),
zaxis = list(type="log",
zeroline=F, showline=T,
ticks="outside",
tickvals=tval,
ticktext=ttxt),
camera = list(eye = list(x = -1.5, y = 1.5, z = 1.5))))
})
}
)
相同,但在二维
library(shiny)
library(plotly)
shinyApp(
ui = fluidPage( plotlyOutput('plot') ),
server = function(input, output) {
output$plot <- renderPlotly ({
mtcars <- rbind(mtcars, mtcars*1000, mtcars/1000) #create data with big logarithmic range
maxlog <- round(log10(max(mtcars[['mpg']][mtcars[['mpg']]>0], mtcars[['disp']][mtcars[['disp']]>0])), digits = 0) +1 # determine max log needed
minlog <- round(log10(min(mtcars[['mpg']][mtcars[['mpg']]>0], mtcars[['disp']][mtcars[['disp']]>0])), digits = 0) -1 # determine min log needed
logrange <- (maxlog - minlog)*9 +1 # get the distance between smallest and largest log power
tval <- sort(as.vector(sapply(seq(1,9), function(x) x*10^seq(minlog,
maxlog)))) #generates a sequence of numbers in logarithmic divisions
ttxt <- rep("",length(tval)) # no label at most of the ticks
ttxt[seq(1,logrange,9)] <- formatC(tval, format = "e", digits = 2)[seq(1,logrange,9)] # every 9th tick is labelled
p <- plot_ly(source = 'ThresholdScatter')
p <- add_trace(p, data = mtcars,
x = mtcars[['mpg']],
y = mtcars[['disp']],
type = 'scatter',
mode = 'markers',
marker = list(size = 2))
p <- layout(p,autosize = F, width = 500, height = 500,
yaxis = list(type="log",
zeroline=F, showline=T,
ticks="outside",
tickvals=tval,
ticktext=ttxt),
xaxis = list(type="log",
zeroline=F, showline=T,
ticks="outside",
tickvals=tval,
ticktext=ttxt))
})
}
)
