status == "healthy" && mammogram == "+ve" ~ "incorrect"),
status = fct_reorder(status,"healthy"))
d <- tibble::tibble(age = age,
status = c(rep("cancer", n*p_cancer),
rep("healthy", n*(1-p_cancer))),
mammogram = c(rep("+ve", n_c_p ),
rep("-ve", n_c_n ),
rep("+ve", n_h_p ) ,
rep("-ve", n_h_n ))
)
d <- d %>%
mutate(diagnosis = case_when(status == "cancer" && mammogram == "+ve" ~ "correct",
status == "cancer" && mammogram == "-ve" ~ "incorrect",
status == "healthy" && mammogram == "-ve" ~ "correct",
status == "healthy" && mammogram == "+ve" ~ "incorrect"),
status = fct_reorder(status,"healthy"))
g1 <- ggplot(d, aes(area = age, fill = status)) +
geom_treemap(layout="fixed") + scale_fill_brewer()
g2 <- ggplot(d, aes(area = age, fill = mammogram)) +
geom_treemap(layout="fixed") + scale_fill_brewer()
g1
g2
g1 <- ggplot(d, aes(area = age, fill = status)) +
geom_treemap() + scale_fill_brewer()
g2 <- ggplot(d, aes(area = age, fill = mammogram)) +
geom_treemap() + scale_fill_brewer()
g1
g2
d <- d %>%
mutate(diagnosis = case_when(status == "cancer" && mammogram == "+ve" ~ "correct",
status == "cancer" && mammogram == "-ve" ~ "incorrect",
status == "healthy" && mammogram == "-ve" ~ "correct",
status == "healthy" && mammogram == "+ve" ~ "incorrect"),
status = fct_reorder(status,"healthy", "cancer"),
diagnosis = fct_reorder(status,"-ve", "+ve"))
d <- d %>%
mutate(diagnosis = case_when(status == "cancer" && mammogram == "+ve" ~ "correct",
status == "cancer" && mammogram == "-ve" ~ "incorrect",
status == "healthy" && mammogram == "-ve" ~ "correct",
status == "healthy" && mammogram == "+ve" ~ "incorrect"),
status = fct_reorder(status,"healthy", "cancer"),
diagnosis = fct_reorder(diagnosis,"-ve", "+ve"))
d <- tibble::tibble(age = age,
status = c(rep("cancer", n*p_cancer),
rep("healthy", n*(1-p_cancer))),
mammogram = c(rep("+ve", n_c_p ),
rep("-ve", n_c_n ),
rep("+ve", n_h_p ) ,
rep("-ve", n_h_n ))
)
d <- d %>%
mutate(diagnosis = case_when(status == "cancer" && mammogram == "+ve" ~ "correct",
status == "cancer" && mammogram == "-ve" ~ "incorrect",
status == "healthy" && mammogram == "-ve" ~ "correct",
status == "healthy" && mammogram == "+ve" ~ "incorrect"),
status = fct_reorder(status,"healthy", "cancer"),
mammogram = fct_reorder(mammpgram,"-ve", "+ve"))
#
library(tidyverse)
library(ggbeeswarm)
# library(cowplot)
library(treemapify)
n <- 1000
age <- base::sample(35:45, n, replace=TRUE)
p_cancer <- 0.01
p_test_positive <- 0.8
p_test_false_positive <- 0.1
n_cancer <- n*p_cancer
n_c_p <- n_cancer*p_test_positive
n_c_n <- n_cancer - n_c_p
n_h_p <- (n-n_cancer)*p_test_false_positive
n_h_n <- (n-n_cancer) - n_h_p
d <- tibble::tibble(age = age,
status = c(rep("cancer", n*p_cancer),
rep("healthy", n*(1-p_cancer))),
mammogram = c(rep("+ve", n_c_p ),
rep("-ve", n_c_n ),
rep("+ve", n_h_p ) ,
rep("-ve", n_h_n ))
)
d <- d %>%
mutate(diagnosis = case_when(status == "cancer" && mammogram == "+ve" ~ "correct",
status == "cancer" && mammogram == "-ve" ~ "incorrect",
status == "healthy" && mammogram == "-ve" ~ "correct",
status == "healthy" && mammogram == "+ve" ~ "incorrect"),
status = fct_reorder(status,"healthy", "cancer"),
mammogram = fct_reorder(mammpgram,"-ve", "+ve"))
?fct_relevel
d <- d %>%
mutate(diagnosis = case_when(status == "cancer" && mammogram == "+ve" ~ "correct",
status == "cancer" && mammogram == "-ve" ~ "incorrect",
status == "healthy" && mammogram == "-ve" ~ "correct",
status == "healthy" && mammogram == "+ve" ~ "incorrect"),
status = fct_relevel(status,"healthy", "cancer"),
mammogram = fct_relevel(mammpgram,"-ve", "+ve"))
d <- d %>%
mutate(diagnosis = case_when(status == "cancer" && mammogram == "+ve" ~ "correct",
status == "cancer" && mammogram == "-ve" ~ "incorrect",
status == "healthy" && mammogram == "-ve" ~ "correct",
status == "healthy" && mammogram == "+ve" ~ "incorrect"),
status = fct_relevel(status,"healthy", "cancer"),
mammogram = fct_relevel(mammogram,"-ve", "+ve"))
g1 <- ggplot(d, aes(area = age, fill = status)) +
geom_treemap() + scale_fill_brewer()
g2 <- ggplot(d, aes(area = age, fill = mammogram)) +
geom_treemap() + scale_fill_brewer()
g1
g2
g3 <- ggplot(d, aes(area = age, fill = diagnosis)) +
geom_treemap() + scale_fill_brewer(palette = "Set2")
g3
d <- d %>%
mutate(diagnosis = case_when(status == "cancer" & mammogram == "+ve" ~ "correct",
status == "cancer" & mammogram == "-ve" ~ "incorrect",
status == "healthy" & mammogram == "-ve" ~ "correct",
status == "healthy" & mammogram == "+ve" ~ "incorrect"),
status = fct_relevel(status,"healthy", "cancer"),
mammogram = fct_relevel(mammogram,"-ve", "+ve"))
g3 <- ggplot(d, aes(area = age, fill = diagnosis)) +
geom_treemap() + scale_fill_brewer(palette = "Set2")
g3
g3 <- ggplot(d, aes(area = age, group, status, fill = diagnosis)) +
geom_treemap() + scale_fill_brewer(palette = "Set2")
g3
g3 <- ggplot(d, aes(area = age, group= status, fill = diagnosis)) +
geom_treemap() + scale_fill_brewer(palette = "Set2")
g3
g3 <- ggplot(d, aes(area = age, group= status, fill = diagnosis)) +
geom_treemap(layout="fixed") + scale_fill_brewer(palette = "Set2")
g3
g3 <- ggplot(d, aes(area = age, color= status, fill = diagnosis)) +
geom_treemap(layout="fixed") + scale_fill_brewer(palette = "Set2")
g3
g3 <- ggplot(d, aes(area = age, width= status, fill = diagnosis)) +
geom_treemap(layout="fixed") + scale_fill_brewer(palette = "Set2")
g3
?geom_treemap
g3 <- ggplot(d, aes(area = age, alpha= status, fill = diagnosis)) +
geom_treemap(layout="fixed") + scale_fill_brewer(palette = "Set2")
g3
g1
g2
g3
?ggsave()
ggsave("plot1.pdf", g1)
ggsave("plot2.pdf", g2)
ggsave("plot3.pdf", g3)
source('~/OneDrive - The University of Nottingham/teaching/2019-tutorials/2019-11-17-bayes/bayes-bee-plot.R', echo=TRUE)
ggsave("plot1.png", g1)
ggsave("plot2.png", g2)
ggsave("plot3.png", g3)
#
colorPalette <- "Set3"
g1 <- ggplot(d, aes(area = age, fill = status)) +
geom_treemap() + scale_fill_brewer(palette = colorPalette)
g2 <- ggplot(d, aes(area = age, fill = mammogram)) +
geom_treemap() + scale_fill_brewer(palette = colorPalette)
g3 <- ggplot(d, aes(area = age, alpha=status, fill = diagnosis)) +
geom_treemap(layout="fixed") + scale_fill_brewer(palette = "Set2")  +
scale_alpha_discrete(range = c(0.3, 1.o))
g3 <- ggplot(d, aes(area = age, alpha=status, fill = diagnosis)) +
geom_treemap(layout="fixed") + scale_fill_brewer(palette = "Set2")  +
scale_alpha_discrete(range = c(0.3, 1.0))
ggsave("plot1.png", g1)
ggsave("plot2.png", g2)
ggsave("plot3.png", g3)
?scale_fill_brewer
#
colorPalette <- "Accent"
g1 <- ggplot(d, aes(area = age, fill = status)) +
geom_treemap() + scale_fill_brewer(palette = colorPalette)
g2 <- ggplot(d, aes(area = age, fill = mammogram)) +
geom_treemap() + scale_fill_brewer(palette = colorPalette)
g3 <- ggplot(d, aes(area = age, alpha=status, fill = diagnosis)) +
geom_treemap(layout="fixed") + scale_fill_brewer(palette = "Set2")  +
scale_alpha_discrete(range = c(0.3, 1.0))
ggsave("plot1.png", g1)
ggsave("plot2.png", g2)
#
colorPalette <- "Dark2"
g1 <- ggplot(d, aes(area = age, fill = status)) +
geom_treemap() + scale_fill_brewer(palette = colorPalette)
g2 <- ggplot(d, aes(area = age, fill = mammogram)) +
geom_treemap() + scale_fill_brewer(palette = colorPalette)
ggsave("plot1.png", g1)
ggsave("plot2.png", g2)
#
colorPalette <- "Pastel1"
g1 <- ggplot(d, aes(area = age, fill = status)) +
geom_treemap() + scale_fill_brewer(palette = colorPalette)
g2 <- ggplot(d, aes(area = age, fill = mammogram)) +
geom_treemap() + scale_fill_brewer(palette = colorPalette)
ggsave("plot1.png", g1)
ggsave("plot2.png", g2)
#
colorPalette <- "Set3"
g1 <- ggplot(d, aes(area = age, fill = status)) +
geom_treemap() + scale_fill_brewer(palette = colorPalette)
g2 <- ggplot(d, aes(area = age, fill = mammogram)) +
geom_treemap() + scale_fill_brewer(palette = colorPalette)
ggsave("plot1.png", g1)
ggsave("plot2.png", g2)
#
colorPalette <- "Set1"
g1 <- ggplot(d, aes(area = age, fill = status)) +
geom_treemap() + scale_fill_brewer(palette = colorPalette)
g2 <- ggplot(d, aes(area = age, fill = mammogram)) +
geom_treemap() + scale_fill_brewer(palette = colorPalette)
ggsave("plot1.png", g1)
ggsave("plot2.png", g2)
g1 <- ggplot(d, aes(area = age, fill = status)) +
geom_treemap() + scale_fill_brewer()
ggsave("plot1.png", g1)
g2 <- ggplot(d, aes(area = age, fill = mammogram)) +
geom_treemap() + scale_fill_brewer()
ggsave("plot1.png", g1)
ggsave("plot2.png", g2)
g3 <- ggplot(d, aes(area = age, alpha=status, fill = diagnosis)) +
geom_treemap(layout="fixed") + scale_fill_brewer(palette = "Set2")  +
scale_alpha_discrete(range = c(0.6, 1.0))
ggsave("plot3.png", g3)
install.packages("reticulate")
library(reticulate)
use_python("/usr/local/bin/python3")
reticulate::repl_python()
knitr::opts_chunk$set(echo = TRUE)
library(reticulate)
use_python("/usr/local/bin/python3")
summary(cars)
library(tidyverse)
?qplot
qplot(speed, distance, cars)
glimpse(cars)
qplot(speed, distance, data=cars)
qplot(speed, dist, data=cars)
cars
with(cars, lm(dist~speed))
install.packages("matlabr")
install.packages("reticulate")
library("reticulate")
Sys.which("python")
library(reticulate)
use_python("/usr/local/bin/python3")
repl_python()
plumber::plumb(file='r/speech-to-text/api/define_api.R')$run()
plumber::plumb(file='r/speech-to-text/api/define_api.R')$run()
plumber::plumb(file='r/speech-to-text/api/define_api.R')$run()
plumber::plumb(file='r/speech-to-text/api/define_api.R')$run()
plumber::plumb(file='r/speech-to-text/api/define_api.R')$run()
plumber::plumb(file='r/speech-to-text/api/define_api.R')$run()
plumber::plumb(file='r/speech-to-text/api/define_api.R')$run()
plumber::plumb(file='r/speech-to-text/api/define_api.R')$run()
install.packages("tidyverse")
install.packages("tidyverse")
plumber::plumb(file='r/speech-to-text/api/define_api.R')$run()
plumber::plumb(file='r/speech-to-text/api/define_api.R')$run()
plumber::plumb(file='r/speech-to-text/api/define_api.R')$run()
plumber::plumb(file='r/speech-to-text/api/define_api.R')$run()
plumber::plumb(file='r/speech-to-text/api/define_api.R')$run()
plumber::plumb(file='r/speech-to-text/api/define_api.R')$run()
setwd()
setwd('~')
devtools::install_github('rstudio/bookdown')
install.packages("gapminder")
source('~/OneDrive - The University of Nottingham/teaching/_ug/2020-3rd-year-projects/example.R', echo=TRUE)
1+1
"asf"
124*23
meaningOfLife <- 42
meaningOfLife * 2
require(tidyverse)
require(jsonlite)
source("./perimetry_helpers.R")
setwd("~/The University of Nottingham/Anthony's PhD Team - strkvis_pub_archive/strkvis-mri/code")
require(tidyverse)
require(jsonlite)
source("./perimetry_helpers.R")
# example file
data_fname <- "../perimetry/sub-14196-perimetry-data.json"
read_medmont(data_fname) %>%
plot_medmont()
plot_medmont <- function(the_points) {
# NB-- the coord_polar step requires setting the starting point for 0 radians / 0 degrees...
# to be offset from 12 o'clock
the_points %>%
mutate(
xcoord = ecc * cos(pa),
ycoord = ecc * sin(pa)
) %>%
filter(State != "TS_UNTESTED") %>%
ggplot(aes(x = ecc, y = pa, size = Value, symbol=State)) +
geom_point(alpha = 0.9) +
coord_fixed() +
scale_colour_manual(values = c("red", "black", "gray")) + # "TS_SEEN"     "TS_UNTESTED" "TS_NOT_SEEN"
# coord_polar is kind of broken...
# https://community.rstudio.com/t/making-coord-polar-behave-like-standard-polar-coordinate-plotting/3762/6
# coord_polar(theta = "x", start = -pi/4, direction = -1) +
theme_minimal()
}
read_medmont(data_fname) %>%
plot_medmont()
the_points %>%
mutate(
xcoord = ecc * cos(pa),
ycoord = ecc * sin(pa)
) %>%
filter(State != "TS_UNTESTED") %>%
ggplot(aes(x = ecc, y = pa, size = Value, symbol=State)) +
geom_point(alpha = 0.9) +
coord_fixed() +
scale_colour_manual(values = c("red", "black", "gray")) + # "TS_SEEN"     "TS_UNTESTED" "TS_NOT_SEEN"
# coord_polar is kind of broken...
# https://community.rstudio.com/t/making-coord-polar-behave-like-standard-polar-coordinate-plotting/3762/6
coord_polar(theta = "x", start = -pi/4, direction = -1) +
theme_minimal()
plot_medmont <- function(the_points) {
# NB-- the coord_polar step requires setting the starting point for 0 radians / 0 degrees...
# to be offset from 12 o'clock
the_points %>%
mutate(
xcoord = ecc * cos(pa),
ycoord = ecc * sin(pa)
) %>%
filter(State != "TS_UNTESTED") %>%
ggplot(aes(x = ecc, y = pa, size = Value, symbol=State)) +
geom_point(alpha = 0.9) +
coord_fixed() +
scale_colour_manual(values = c("red", "black", "gray")) + # "TS_SEEN"     "TS_UNTESTED" "TS_NOT_SEEN"
# coord_polar is kind of broken...
# https://community.rstudio.com/t/making-coord-polar-behave-like-standard-polar-coordinate-plotting/3762/6
coord_polar(theta = "x", start = -pi/4, direction = -1) +
theme_minimal()
}
read_medmont(data_fname) %>%
plot_medmont()
plot_medmont <- function(the_points) {
# NB-- the coord_polar step requires setting the starting point for 0 radians / 0 degrees...
# to be offset from 12 o'clock
the_points %>%
mutate(
xcoord = ecc * cos(pa),
ycoord = ecc * sin(pa)
) %>%
filter(State != "TS_UNTESTED") %>%
ggplot(aes(x = pa, y = ecc, size = Value, symbol=State)) +
geom_point(alpha = 0.9) +
# coord_fixed() +
scale_colour_manual(values = c("red", "black", "gray")) + # "TS_SEEN"     "TS_UNTESTED" "TS_NOT_SEEN"
# coord_polar is kind of broken...
# https://community.rstudio.com/t/making-coord-polar-behave-like-standard-polar-coordinate-plotting/3762/6
coord_polar(theta = "x", start = -pi/4, direction = -1) +
theme_minimal()
}
read_medmont(data_fname) %>%
plot_medmont()
coord_polar
>coord_polar
?
coord_polar
plot_medmont <- function(the_points) {
# NB-- the coord_polar step requires setting the starting point for 0 radians / 0 degrees...
# to be offset from 12 o'clock
the_points %>%
mutate(
xcoord = ecc * cos(pa),
ycoord = ecc * sin(pa)
) %>%
filter(State != "TS_UNTESTED") %>%
ggplot(aes(x = pa, y = ecc, size = Value, symbol=State)) +
geom_point(alpha = 0.9) +
coord_fixed() +
scale_colour_manual(values = c("red", "black", "gray")) + # "TS_SEEN"     "TS_UNTESTED" "TS_NOT_SEEN"
# coord_polar is kind of broken...
# https://community.rstudio.com/t/making-coord-polar-behave-like-standard-polar-coordinate-plotting/3762/6
coord_polar(theta = "x", start = -pi/4, direction = -1) +
theme_minimal()
}
read_medmont(data_fname) %>%
plot_medmont()
plot_medmont(data)
data <- read_medmont(data_fname)
plot_medmont(data)
the_points %>%
mutate(
pa_rad = pi * pa / 180.0,
xcoord = ecc * cos(pa_rad),
ycoord = ecc * sin(pa_rad)
) %>%
filter(State != "TS_UNTESTED") %>%
ggplot(aes(x = pa_rad, y = ecc, size = Value, symbol=State)) +
geom_point(alpha = 0.9) +
coord_fixed() +
scale_colour_manual(values = c("red", "black", "gray")) + # "TS_SEEN"     "TS_UNTESTED" "TS_NOT_SEEN"
# coord_polar is kind of broken...
# https://community.rstudio.com/t/making-coord-polar-behave-like-standard-polar-coordinate-plotting/3762/6
coord_polar(theta = "x", start = -pi/4, direction = -1) +
theme_minimal()
data <- read_medmont(data_fname)
plot_medmont(data)
require(tidyverse)
require(jsonlite)
source("./perimetry_helpers.R")
# example file
data_fname <- "../perimetry/sub-14196-perimetry-data.json"
data <- read_medmont(data_fname)
plot_medmont(data)
require(tidyverse)
require(jsonlite)
source("./perimetry_helpers.R")
# example file
data_fname <- "../perimetry/sub-14196-perimetry-data.json"
data <- read_medmont(data_fname)
#' convert medmont JSON to data frame
#'
#' returns
#' list(result, the_points, d)
#'
read_medmont <- function(fname) {
# get data
j <- jsonlite::read_json(fname)
d <- fromJSON(fname)
# unpack what’s in JSON structure -----------------------------------------
exam <- d$MedmontStudioExportFile[4]
test <- exam$M600ThresholdExam$ThresholdTest$Test
# e.g.
# test$BlindSpot
# Now look for the experiment data ----------------------------------------
# test points are inside here
n_points <- parse_integer(test$TestPoints$elements)
the_points <- test$TestPoints$ThresholdTestPoint
# exporting to CSV (tidy) style format --------------------------------------
# this is how two write out a subset to CSV file...
# make sure to take last set of measurements (if it's a list)
# also length less than 5 (which is the right order of mag for ATTEMPTS, rather than points)
# if there is only 1 test, a previous version of the check didn't seem to do the right thing/
if (is_list(the_points) && length(the_points) < 5) {
the_points <- the_points[[length(the_points)]]
}
result <- the_points %>%
mutate(
ecc = parse_double(Position$Ring),
pa = parse_double(Position$Meridian),
pa_rad = pi* pa / 180,
Value = parse_double(Value)
)
}
data <- read_medmont(data_fname)
the_points %>%
mutate(
xcoord = ecc * cos(pa_rad),
ycoord = ecc * sin(pa_rad)
) %>%
filter(State != "TS_UNTESTED") %>%
ggplot(aes(x = pa_rad, y = ecc, size = Value, symbol=State)) +
geom_point(alpha = 0.9) +
scale_colour_manual(values = c("red", "black", "gray")) + # "TS_SEEN"     "TS_UNTESTED" "TS_NOT_SEEN"
# coord_polar is kind of broken...
# https://community.rstudio.com/t/making-coord-polar-behave-like-standard-polar-coordinate-plotting/3762/6
coord_polar(theta = "x", start = -pi/4, direction = -1) +
theme_minimal()
?coord_polar
source("./perimetry_helpers.R")
# example file
data_fname <- "../perimetry/sub-14196-perimetry-data.json"
data <- read_medmont(data_fname)
plot_medmont(data)
plot_medmont <- function(the_points) {
# NB-- the coord_polar step requires setting the starting point for 0 radians / 0 degrees...
# to be offset from 12 o'clock
the_points %>%
mutate(
xcoord = ecc * cos(pa_rad),
ycoord = ecc * sin(pa_rad)
) %>%
filter(State != "TS_UNTESTED") %>%
ggplot(aes(x = xcoord, y = ycoord, size = Value, symbol=State)) +
geom_point(alpha = 0.9) +
coord_fixed() +
scale_colour_manual(values = c("red", "black", "gray")) + # "TS_SEEN"     "TS_UNTESTED" "TS_NOT_SEEN"
# coord_polar is kind of broken...
# https://community.rstudio.com/t/making-coord-polar-behave-like-standard-polar-coordinate-plotting/3762/6
# coord_polar(theta = "x", start = -pi/4, direction = -1) +
theme_minimal()
}
source("./perimetry_helpers.R")
# example file
data_fname <- "../perimetry/sub-14196-perimetry-data.json"
data <- read_medmont(data_fname)
plot_medmont(data)
plot_medmont <- function(the_points) {
# NB-- the coord_polar step requires setting the starting point for 0 radians / 0 degrees...
# to be offset from 12 o'clock
the_points %>%
mutate(
xcoord = ecc * cos(pa_rad),
ycoord = ecc * sin(pa_rad)
) %>%
filter(State != "TS_UNTESTED") %>%
ggplot(aes(x = xcoord, y = ycoord, size = Value, colour=State)) +
geom_point(alpha = 0.9) +
coord_fixed() +
scale_colour_manual(values = c("red", "black", "gray")) + # "TS_SEEN"     "TS_UNTESTED" "TS_NOT_SEEN"
# coord_polar is kind of broken...
# https://community.rstudio.com/t/making-coord-polar-behave-like-standard-polar-coordinate-plotting/3762/6
# coord_polar(theta = "x", start = -pi/4, direction = -1) +
theme_minimal()
}
plot_medmont(data)
# example file
data_fname <- "../perimetry/sub-14326-perimetry-data.json"
data <- read_medmont(data_fname)
plot_medmont(data)