vignettes/intro.R

In m-clark/visibly: Functions and palettes related to visual enhancement

## ----setup, include=FALSE, cache=FALSE----------------------------------------
knitr::opts_chunk$set(
  echo = TRUE,
  message = FALSE,
  warning = FALSE,
  error = FALSE,
  collapse = TRUE,
  comment = NA,
  R.options = list(width = 220),
  dev.args = list(bg = 'transparent'),
  dev = 'png',
  fig.align = 'center',
  out.width = '75%',
  fig.asp = .75,
  cache.rebuild = FALSE,
  cache = FALSE
)

## ----example, echo=-(1:3)-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
# bc r cmd build randomly decided margins were too large when they were okay
# before
par(mar=c(.5,.5,.5,.5))
library(visibly)
create_palette('papayawhip', plot = TRUE)

## ----example2-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
palettes$Rblue

## ----use1-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
pal = create_palette('#ff5500', 
                     name = 'orange_you_glad_you_have_this_color')
library(ggplot2)

ggplot(mtcars, aes(x = wt, y = mpg)) +
  geom_point(aes(color = factor(cyl)), size = 10, alpha = .5) +
  scale_color_manual(values = pal$triadic) +
  theme_clean()

## ----use2-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
library(dplyr)

mtcars %>%
  mutate(cyl = factor(cyl)) %>%
  tidyext::num_by(wt, cyl) %>%
  ggplot(aes(x = cyl, y = Mean)) +
  geom_col(aes(fill = cyl), width = .5, alpha = .85) +
  scale_fill_manual(values = palettes$Rblue$triadic) +
  theme_clean() +
  theme(
    legend.key.size = unit(.015, 'npc'),
    axis.title.y = element_text(size = 20, hjust = -.05)
  )

## ----colorgorical, eval=F-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
#  colorgorical(
#    n = 6,
#    pairPreference = 1,
#    startPalette = list(c(10,-60, 45)),
#    output = 'hex'
#  )

## ----colorgorical-show, eval=T, echo=F------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
x = c(
  "#002B00",
  "#95C857",
  "#334D37",
  "#4EF185",
  "#378811",
  "#7FE7D3"
)

print(x)

qplot(
  x = x,
  y = 1:6,
  color = I(x),
  size = I(10)
)

## ----colorgorical2, eval=F------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
#  colorgorical(
#    n = 10,
#    perceptualDifference = .5,
#    startPalette = list(c(10, -60, 45)),
#    output = 'hex'
#  )

## ----colorgorical2-show, eval=T, echo=F-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
x = c(
  "#002B00",
  "#D57381",
  "#77CE3F",
  "#DB0EAC",
  "#2FF52B",
  "#6C208E",
  "#B1BF81",
  "#4115F9",
  "#518512",
  "#B662CA"
)

print(x)

qplot(
  x = x,
  y = 1:10,
  color = I(x),
  size = I(10)
)

## ----col2lab--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
col2lab('dodgerblue')

## ----color_contrast_checker-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
color_contrast_checker(foreground = 'blue')

## ----color_contrast_checker2----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
color_contrast_checker(foreground = 'blue', background = 'black')

## ----color_contrast_checker3----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
iris %>% 
  ggplot(aes(Petal.Length, Petal.Width, color=Species)) + 
  geom_point()

scales::show_col(scales::hue_pal()(3))

color_contrast_checker(foreground = '#F8766D', background = 'gray92')
color_contrast_checker(foreground = '#00BA38', background = 'gray92')
color_contrast_checker(foreground = '#619CFF', background = 'gray92')

## ----corrheat1------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
data('bfi', package = 'visibly')
cor_matrix = cor(bfi, use='pair')
corr_heat(cor_matrix)

## ----corrheat2------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
corr_heat(cor_matrix,
          n_factors = 2,
          psych_opts = list(fm = 'ml', rot = 'oblimin'))

## ----corrheat3------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
corr_heat(cor_matrix, pal = 'broc')

## ----corrheat3d-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
p = corr_heat(cor_matrix, three_d = TRUE, diagonal = NA)
p

## ----corrheat4------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
p = corr_heat(cor(mtcars), three_d = TRUE, ordering = 'polar')
p

## ----lm0------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
fit_lm = lm(mpg ~ ., mtcars)
plot_coefficients(fit_lm)

## ----lm1------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
fit_lm = lm(mpg ~ ., mtcars)

plot_coefficients(
  fit_lm,
  palette = 'oslo',
  order = 'decreasing',
  sd_multi = 1,
  keep_intercept = TRUE,
  ref_line = c(-1:1)
)

## ----data-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
plot_coefficients(fit_lm, plot = FALSE)

## ----fe1------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
library(lme4)

fit_mer = lmer(Reaction ~ Days + (Days|Subject), sleepstudy)

plot_coefficients(fit_mer)

## ----re1------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
plot_coefficients(fit_mer, ranef = TRUE, which_ranef = 'Subject')

## ----fe2------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
fit_mer2 = lmer(count ~ zAge + zBase * Trt + 
                  (1 | patient), 
                data = brms::epilepsy)

plot_coefficients(fit_mer2, 
                  palette = 'berlin')

## ----re_patchwork---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
plots = plot_coefficients(fit_mer, ranef = TRUE, which_ranef = 'Subject')

library(patchwork)

plots[[1]] + plots[[2]]

## ----fe_brms1, eval=FALSE-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
#  library(brms)
#  
#  fit_brms_two = brm(count ~ zAge + zBase * Trt +
#                   (1 | patient) + (1 | obs),
#                 data = epilepsy,
#                 family = poisson)
#  
#  plot_coefficients(fit_brms_two)

## ----fe_brms1_vis, echo = FALSE-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
load('../tests/testthat/brms_res.RData')
plot_coefficients(fit_brms_two)

## ----re_brms1-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
plot_coefficients(fit_brms_two, ranef = TRUE, which_ranef = 'patient') +
  theme(axis.text.x = element_text(angle = -90))

## ----gam------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
library(mgcv)

d = gamSim()

gam_model = gam(y ~ x0 + s(x1) + s(x2, bs='gp') + s(x3, bs='ps'), data=d)

plot_gam(gam_model,
         main_var = x2)

plot_gam(gam_model, 
         main_var = vars(x1, x2, x3),
         ncol = 1, 
         line_color = palettes$Rblue$Rblue, 
         ribbon_color = palettes$Rblue$complementary[2])

plot_gam_check(gam_model)

## ----gam2d, echo=-1-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
set.seed(1234)
d = gamSim(2, scale = .1)$data
gam_model = gam(y ~ s(x, z, bs='gp'), data=d)

plot_gam_2d(gam_model,
            main_var = x,
            second_var = z,
            n_plot = 200)

## ----gam3d----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
plot_gam_3d(gam_model,
            main_var = x,
            second_var = z,
            n_plot = 200)

## ----gamby, echo=-1-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
set.seed(1234)
d = gamSim(4)
gam_model = gam(y ~ s(x2, fac, bs='fs'), data=d)

plot_gam_by(gam_model,
            main_var = x2,
            by_var = fac)