Chapter 4 Scientific Charts
4.2 Contour Plots
4.2.2 Smoothing Contour Coloring
library(plotly)
fig <- plot_ly(
type = 'contour',
z = matrix(c(10, 10.625, 12.5, 15.625, 20, 5.625, 6.25, 8.125,
11.25, 15.625, 2.5, 3.125, 5, 8.125, 12.5, 0.625,
1.25, 3.125, 6.25, 10.625, 0, 0.625, 2.5, 5.625,
10), nrow=5, ncol=5),
contours = list(
coloring = 'heatmap'
)
)
fig4.4 Parallel Coordinates
4.4.1 Basic Parallel Cordinates Plots
library(plotly)
df <- read.csv("https://raw.githubusercontent.com/bcdunbar/datasets/master/iris.csv")
fig <- df %>% plot_ly(type = 'parcoords',
line = list(color = ~species_id,
colorscale = list(c(0,'red'),c(0.5,'green'),c(1,'blue'))),
dimensions = list(
list(range = c(2,4.5),
label = 'Sepal Width', values = ~sepal_width),
list(range = c(4,8),
constraintrange = c(5,6),
label = 'Sepal Length', values = ~sepal_length),
list(range = c(0,2.5),
label = 'Petal Width', values = ~petal_width),
list(range = c(1,7),
label = 'Petal Length', values = ~petal_length)
)
)
fig4.4.2 Advanced Parallel Coordinates Plot
library(plotly)
df <- read.csv("https://raw.githubusercontent.com/bcdunbar/datasets/master/parcoords_data.csv")
fig <- df %>%
plot_ly(width = 1000, height = 600)
fig <- fig %>% add_trace(type = 'parcoords',
line = list(color = ~colorVal,
colorscale = 'Jet',
showscale = TRUE,
reversescale = TRUE,
cmin = -4000,
cmax = -100),
dimensions = list(
list(range = c(~min(blockHeight),~max(blockHeight)),
constraintrange = c(100000,150000),
label = 'Block Height', values = ~blockHeight),
list(range = c(~min(blockWidth),~max(blockWidth)),
label = 'Block Width', values = ~blockWidth),
list(tickvals = c(0,0.5,1,2,3),
ticktext = c('A','AB','B','Y','Z'),
label = 'Cyclinder Material', values = ~cycMaterial),
list(range = c(-1,4),
tickvals = c(0,1,2,3),
label = 'Block Material', values = ~blockMaterial),
list(range = c(~min(totalWeight),~max(totalWeight)),
visible = TRUE,
label = 'Total Weight', values = ~totalWeight),
list(range = c(~min(assemblyPW),~max(assemblyPW)),
label = 'Assembly Penalty Weight', values = ~assemblyPW),
list(range = c(~min(HstW),~max(HstW)),
label = 'Height st Width', values = ~HstW),
list(range = c(~min(minHW),~max(minHW)),
label = 'Min Height Width', values = ~minHW),
list(range = c(~min(minWD),~max(minWD)),
label = 'Min Width Diameter', values = ~minWD),
list(range = c(~min(rfBlock),~max(rfBlock)),
label = 'RF Block', values = ~rfBlock)
)
)
fig4.5 Polar Charts
4.5.1 Basic Polar Charts
library(plotly)
fig <- plot_ly(
type = 'scatterpolar',
r = c(0,1,2,2),
theta = c(0,45,90,0),
mode = 'markers'
)
fig4.5.2 Line Polar Charts
library(plotly)
df <- read.csv("https://raw.githubusercontent.com/plotly/datasets/master/polar_dataset.csv")
fig <- plot_ly(
df,
type = 'scatterpolar',
mode = 'lines'
)
fig <- fig %>%
add_trace(
r = ~x1,
theta = ~y,
name = 'Figure8',
line = list(
color = 'peru'
)
)
fig <- fig %>%
add_trace(
r = ~x2,
theta = ~y,
name = 'Cardioid',
line = list(
color = 'darkviolet'
)
)
fig <- fig %>%
add_trace(
r = ~x3,
theta = ~y,
name = 'Hypercardioid',
line = list(
color = 'deepskyblue'
)
)
fig <- fig %>%
add_trace(
r = ~x4,
theta = ~y,
name = 'Subcardioid',
line = list(
color = 'orangered'
)
)
fig <- fig %>%
add_trace(
r = ~x5,
theta = ~y,
name = 'Supercardioid',
line = list(
color = 'green'
)
)
fig <- fig %>%
layout(
title = 'Mic Patterns',
font = list(
family = 'Arial',
size = 12,
color = '#000'
),
showlegend = F
)
fig4.5.3 Area Polar Area
library(plotly)
fig <- plot_ly(
type = 'scatterpolar',
mode = 'lines'
)
fig <- fig %>%
add_trace(
r = c(0, 1.5, 1.5, 0, 2.5, 2.5, 0),
theta = c(0, 10, 25, 0, 205, 215, 0),
fill = 'toself',
fillcolor = '#709Bff',
line = list(
color = 'black'
)
)
fig <- fig %>%
add_trace(
r = c(0, 3.5, 3.5, 0),
theta = c(0, 55, 75, 0),
fill = 'toself',
fillcolor = '#E4FF87',
line = list(
color = 'black'
)
)
fig <- fig %>%
add_trace(
r = c(0, 4.5, 4.5, 0, 4.5, 4.5, 0),
theta = c(0, 100, 120, 0, 305, 320, 0),
fill = 'toself',
fillcolor = '#FFAA70',
line = list(
color = 'black'
)
)
fig <- fig %>%
add_trace(
r = c(0, 4, 4, 0),
theta = c(0, 165, 195, 0),
fill = 'toself',
fillcolor = '#FFDF70',
line = list(
color = 'black'
)
)
fig <- fig %>%
add_trace(
r = c(0, 3, 3, 0),
theta = c(0, 262.5, 277.5, 0),
fill = 'toself',
fillcolor = '#B6FFB4',
line = list(
color = 'black'
)
)
fig <- fig %>%
layout(
polar = list(
radialaxis = list(
visible = T,
range = c(0,5)
)
),
showlegend = F
)
fig4.6 Radar Charts
4.6.1 Basic Radar Charts
library(plotly)
fig <- plot_ly(
type = 'scatterpolar',
r = c(39, 28, 8, 7, 28, 39),
theta = c('A','B','C', 'D', 'E', 'A'),
fill = 'toself'
)
fig <- fig %>%
layout(
polar = list(
radialaxis = list(
visible = T,
range = c(0,50)
)
),
showlegend = F
)
fig4.6.2 Multiple Trace Radar Charts
library(plotly)
fig <- plot_ly(
type = 'scatterpolar',
fill = 'toself'
)
fig <- fig %>%
add_trace(
r = c(39, 28, 8, 7, 28, 39),
theta = c('A','B','C', 'D', 'E', 'A'),
name = 'Group A'
)
fig <- fig %>%
add_trace(
r = c(1.5, 10, 39, 31, 15, 1.5),
theta = c('A','B','C', 'D', 'E', 'A'),
name = 'Group B'
)
fig <- fig %>%
layout(
polar = list(
radialaxis = list(
visible = T,
range = c(0,50)
)
)
)
fig