From f3693000e50ee9b9506139fb6b681e9d90b5d4e9 Mon Sep 17 00:00:00 2001 From: Antoine Neuraz <5528070+aneuraz@users.noreply.github.com> Date: Mon, 18 Nov 2019 20:01:03 +0100 Subject: [PATCH] continue lab2 --- courses/img/palettes.jpg | Bin 0 -> 221878 bytes courses/lab02-perception-colors.Rmd | 265 ++++++++- courses/lab02-perception-colors.html | 401 +++++++++++++ .../figure-html/unnamed-chunk-1-1.png | Bin 0 -> 25169 bytes .../figure-html/unnamed-chunk-10-1.png | Bin 0 -> 25016 bytes .../figure-html/unnamed-chunk-11-1.png | Bin 0 -> 66776 bytes .../figure-html/unnamed-chunk-12-1.png | Bin 0 -> 45020 bytes .../figure-html/unnamed-chunk-13-1.png | Bin 0 -> 39396 bytes .../figure-html/unnamed-chunk-14-1.png | Bin 0 -> 35442 bytes .../figure-html/unnamed-chunk-15-1.png | Bin 0 -> 35442 bytes .../figure-html/unnamed-chunk-2-1.png | Bin 0 -> 26734 bytes .../figure-html/unnamed-chunk-3-1.png | Bin 0 -> 26734 bytes .../figure-html/unnamed-chunk-4-1.png | Bin 0 -> 10754 bytes 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Réaliser des plots avec les échelles suivantes sur la variable group : +- couleur +- forme +- angle +- taille +- luminosité +- courbe +- encapsulage +- remplissage + +Certaines échelles sont très simples à mettre en place (e.g. couleur, forme) mais d'autres n'existent pas directement. Il faut trouver une alternative. + +#### 2. Comparer l'efficacité des différentes échelles pour distinguer les 2 groupes + +--- +## Couleur + + +```{r, echo = F} + +dt <- generate_dataset_uniform( + dataset_size = size, + min_x = min_x, + max_x = max_x, + seed = seed +) +``` + +-- +.small[ +```{r, echo = T} + +p_color <- ggplot( data = dt, + aes(x = x, y = y, color = group)) + + geom_point(size = 3, alpha = .6) + + see::scale_color_material_d() + + vizoR::theme_void_complete() + + labs(subtitle= "Couleur") + +p_color +``` +] + + +--- +## Angle + +-- + +.small[ +```{r} +p_angle <- dt %>% + mutate(angle = ifelse(group == "group1", 0, pi / 3)) %>% + ggplot( + data = ., aes( x = x, y = y, angle = angle ) ) + + geom_spoke(radius = 0.02,size = .8, alpha = .6 ) + + theme_void_complete() + + scale_color_material_d() + + ggtitle("Angle") +p_angle +``` +] +--- +## Taille + +-- + +.small[ +```{r} +p_size <- dt %>% + mutate(size = ifelse(group == "group1", 2, 3)) %>% + ggplot( data = ., + aes( x = x,y = y,size = size)) + + geom_point(alpha = .6) + + theme_void_complete() + + scale_size(range = c(1, 3)) + + ggtitle("Taille") +p_size +``` +] + +--- +## Luminosité + +-- + +.small[ +```{r} +p_grey <- dt %>% + ggplot( + data = .,aes(x = x,y = y,color = group)) + + geom_point(size = 3, alpha = .6) + + theme_void_complete() + + #scale_color_grey() + + scale_color_grey(start=.8, end=.2)+ + ggtitle("Luminosité") +p_grey +``` +] +--- +## Courbe + +-- + +.small[ +```{r} +dt <- dt %>% + mutate(curvature = ifelse(group == "group1", 0, 1)) + +p_curve <- dt %>% + ggplot(data = .,aes(x = x,y = y,xend = x, yend = y+max_x/50, curvature = curvature)) + + #geom_curve()+ + geom_curve(data = subset(dt, group == 'group1'), curvature = 0, alpha = .7) + + geom_curve(data = subset(dt, group == 'group2'), curvature = .7, alpha = .7) + + scale_color_material_d() + + theme_void_complete() + + ggtitle("Courbe") +p_curve +``` +] +--- +## Encapsulage + +-- + +.small[ +```{r} +p_box <- dt %>% + ggplot(data = .,aes(x = x,xend = x+max_x/50,y = y,yend = y, group = group)) + + geom_point(data = subset(dt, group=='group2'),aes(x = x+max_x/100), shape = 22, size = 13) + + geom_segment() + + scale_color_material_d() + + theme_void_complete() + + ggtitle("Encapsulage") +p_box +``` +] + +--- +## Forme + +-- + +.small[ +```{r} +p_shape <- dt %>% + ggplot(data = .,aes(x = x,y = y,shape = group)) + + geom_point(size = 3, alpha = .6) + + theme_void_complete() + + ggtitle("Forme") +p_shape +``` +] +--- +## Remplissage + +-- + +.small[ +```{r} +p_fill <- dt %>% + ggplot(data = ., aes( x = x,y = y,fill = group)) + + geom_point(size = 3, shape = 21, alpha = .7) + + scale_fill_manual(values = c('group2' = 'black', 'group1' = 'white')) + + theme_void_complete() + + ggtitle("Remplissage") +p_fill +``` +] + +--- +class: full, center, middle +```{r, echo = F, out.width = '2000px'} +p_color + p_angle + + p_size + p_grey + + p_curve + p_box + + p_shape + p_fill + + plot_layout(ncol = 2) + + +``` + + +--- +class: full +### Les couleurs dans ggplot2 `display.brewer.all()` + +![:scale 80%](img/palettes.jpg) + +--- +## TODO: couleurs + +#### Charger le dataset diamonds et créer un sous-dataset aléatoire de 1000 lignes + +#### Plot carat en fonction du prix et de la couleur + +#### changer la palette par défaut vers une autre palette disponible + +--- +## TODO: couleurs 2 + +#### Plot carat en fonction du prix avec carat en double encodage + +#### Aller sur [http://colorbrewer2.org]() et trouver une palette divergente + +#### Créer une palette custom basée sur cette palette et l'appliquer au plot précédent + +#### Caler la palette sur le carat moyen + +#### Annoter le plot avec une ligne désignant le carat moyen et un texte expliquant cette ligne + + + +--- ```{r} dsamp <- diamonds[sample(nrow(diamonds), 1000), ] ggplot(dsamp, aes(carat, price)) + - geom_point(aes(colour = clarity)) + - scale_color_brewer(palette = "Set3") + geom_point(aes(colour = color)) + + scale_color_brewer(palette = "Set3") + + facet_wrap(~color) ``` ```{r} ggplot(dsamp, aes(carat, price)) + - geom_point(aes(colour = carat))) + + geom_point(aes(colour = carat)) + scale_color_distiller(palette="RdYlBu") ``` ```{r} -font_add_google("Gochi Hand", "gochi") -showtext_auto() +#showtext_auto() +#font_add_google("Schoolbell", "bell") + +font_family = "sans" annotate_color = "grey50" -font_add_google("Schoolbell", "bell") midpoint = (max(dsamp$carat)-min(dsamp$carat))/2 @@ -56,18 +291,22 @@ ggplot(dsamp, aes(carat, price)) + annotate("text", x=.78, y=15000, hjust=1, srt=40, label ="this is the midpoint", - family="bell", + family=font_family, color=annotate_color) + annotate("curve", x = .8, xend=midpoint-.01, y=15000, yend = 14000, curvature = -.5, color=annotate_color , arrow=arrow(length = unit(0.03, "npc") )) + - theme_minimal() + - theme(panel.grid.minor = element_blank(), - panel.grid.major.x = element_blank()) + ggthemes::theme_tufte() + theme_elegant() + + theme(panel.grid.minor = element_blank(), + panel.grid.major.x = element_blank(), + legend.position = "none") ``` + + + diff --git a/courses/lab02-perception-colors.html b/courses/lab02-perception-colors.html new file mode 100644 index 0000000..8b8f082 --- /dev/null +++ b/courses/lab02-perception-colors.html @@ -0,0 +1,401 @@ + + + + LAB 2: Perception et couleurs + + + + + + + + + + + + + + + + + + + diff --git a/courses/lab02-perception-colors_files/figure-html/unnamed-chunk-1-1.png b/courses/lab02-perception-colors_files/figure-html/unnamed-chunk-1-1.png new file mode 100644 index 0000000000000000000000000000000000000000..6c63bd20cc0bbfa2c379b7a4f7c7b23956b52c6d GIT binary patch literal 25169 zcmce-^Lr(G(>G3>84+KtRB;Eks1VS&2x9*jd{- zDF66wWFlc=YvN#Gq$D8>0>T*;rK)R=r;5(s?r26zHlb|I8szj#0D&AKL5(%9q0M)F zo!vHBihYIT$oS!6B6WCzlcoJVPeJUP*VmH_^uF$9KO(Aoq*eX~#w1wsl{q3R{)VT( zZ$}Zur)fMaX%=m@8zvWCw^^6jo)@iVmk>v-Wg5wG=%ASCRrFZQJB}eSp?tKlKSOe{ zAoJ7}@o9BSWdZC8aITHon<9Ta^_S<@KXNLY#qlwS>^D`$CH zcC?>wnBlyhTl?ek`$vvVk9p9oO>fC$S`Pou%kMg`v~1*u+lqZMW$`)UZ_qndHr`Em 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library(gridExtra) library(pander) library(ggmap) +library(vizoR) # https://www.andrewheiss.com/blog/2017/08/10/exploring-minards-1812-plot-with-ggplot2/ -cities <- read.table("data/minard/cities.txt", - header = TRUE, stringsAsFactors = FALSE) +data("minard_cities") -troops <- read.table("data/minard/troops.txt", - header = TRUE, stringsAsFactors = FALSE) +data("minard_troops") -temps <- read.table("data/minard/temps.txt", - header = TRUE, stringsAsFactors = FALSE) %>% - mutate(date = dmy(date)) # Convert string to actual date +data('minard_temps') -temps.nice <- temps %>% +temps.nice <- minard_temps %>% mutate(nice.label = paste0(temp, "°, ", month, ". ", day)) ``` @@ -44,12 +41,12 @@ color_troops_fw = "#DFC17E" color_troops_bw = "#252523" # No map this time march.1812.plot.simple <- ggplot() + - geom_path(data = troops, aes(x = long, y = lat, group = group, + geom_path(data = minard_troops, aes(x = long, y = lat, group = group, color = direction, size = survivors), lineend = "round") + - geom_point(data = cities, aes(x = long, y = lat), + geom_point(data = minard_cities, aes(x = long, y = lat), color = color_cities) + - geom_text_repel(data = cities, aes(x = long, y = lat, label = city), + geom_text_repel(data = minard_cities, aes(x = long, y = lat, label = city), color = color_cities, family = font_family) + scale_size(range = c(0.5, 15)) + scale_colour_manual(values = c(color_troops_fw,color_troops_bw )) + @@ -59,7 +56,7 @@ march.1812.plot.simple <- ggplot() + # Change the x-axis limits to match the simple map temps.1812.plot <- ggplot(data = temps.nice, aes(x = long, y = temp)) + geom_line() + - geom_text_repel(aes(label = nice.label), + geom_label(aes(label = nice.label), family = font_family, size = 2.5) + labs(x = NULL, y = "° Celsius") + scale_x_continuous(limits = ggplot_build(march.1812.plot.simple)$layout$panel_ranges[[1]]$x.range) + diff --git a/courses/minard.html b/courses/minard.html new file mode 100644 index 0000000..a92eacf --- /dev/null +++ b/courses/minard.html @@ -0,0 +1,552 @@ + + + + + + + + + + + + + + + +Minard + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +

+ + + + + + + +
library(tidyverse)
+
## ── Attaching packages ────────────────────────────────────────────────────────────────────────────────────────────────────────── tidyverse 1.2.1 ──
+
## ✔ ggplot2 3.2.1     ✔ purrr   0.3.3
+## ✔ tibble  2.1.3     ✔ dplyr   0.8.3
+## ✔ tidyr   1.0.0     ✔ stringr 1.4.0
+## ✔ readr   1.3.1     ✔ forcats 0.4.0
+
## ── Conflicts ───────────────────────────────────────────────────────────────────────────────────────────────────────────── tidyverse_conflicts() ──
+## ✖ dplyr::filter() masks stats::filter()
+## ✖ dplyr::lag()    masks stats::lag()
+
library(lubridate)
+
## 
+## Attaching package: 'lubridate'
+
## The following object is masked from 'package:base':
+## 
+##     date
+
library(ggmap)
+
## Google's Terms of Service: https://cloud.google.com/maps-platform/terms/.
+
## Please cite ggmap if you use it! See citation("ggmap") for details.
+
library(ggrepel)
+library(gridExtra)
+
## 
+## Attaching package: 'gridExtra'
+
## The following object is masked from 'package:dplyr':
+## 
+##     combine
+
library(pander)
+library(ggmap)
+
+# https://www.andrewheiss.com/blog/2017/08/10/exploring-minards-1812-plot-with-ggplot2/
+
+cities <- read.table("data/minard/cities.txt",
+                     header = TRUE, stringsAsFactors = FALSE)
+
+troops <- read.table("data/minard/troops.txt",
+                     header = TRUE, stringsAsFactors = FALSE)
+
+temps <- read.table("data/minard/temps.txt",
+                    header = TRUE, stringsAsFactors = FALSE) %>%
+  mutate(date = dmy(date))  # Convert string to actual date
+
+temps.nice <- temps %>%
+  mutate(nice.label = paste0(temp, "°, ", month, ". ", day))
+
font_family = "Helvetica"
+color_cities = "black" #"#DC5B44"
+
+color_troops_fw = "#DFC17E"
+color_troops_bw = "#252523"
+# No map this time
+march.1812.plot.simple <- ggplot() +
+  geom_path(data = troops, aes(x = long, y = lat, group = group, 
+                               color = direction, size = survivors),
+            lineend = "round") +
+  geom_point(data = cities, aes(x = long, y = lat),
+             color = color_cities) +
+  geom_text_repel(data = cities, aes(x = long, y = lat, label = city),
+                  color = color_cities, family = font_family) +
+  scale_size(range = c(0.5, 15)) + 
+  scale_colour_manual(values = c(color_troops_fw,color_troops_bw )) +
+  guides(color = FALSE, size = FALSE) +
+  theme_nothing()
+
+# Change the x-axis limits to match the simple map
+temps.1812.plot <- ggplot(data = temps.nice, aes(x = long, y = temp)) +
+  geom_line() +
+  geom_text_repel(aes(label = nice.label),
+            family = font_family, size = 2.5) + 
+  labs(x = NULL, y = "° Celsius") +
+  scale_x_continuous(limits = ggplot_build(march.1812.plot.simple)$layout$panel_ranges[[1]]$x.range) +
+  scale_y_continuous(position = "right") +
+  coord_cartesian(ylim = c(-35, 5)) +  # Add some space above/below
+  theme_bw(base_family = font_family) +
+  theme(panel.grid.major.x = element_blank(),
+        panel.grid.minor.x = element_blank(),
+        panel.grid.minor.y = element_blank(),
+        axis.text.x = element_blank(), axis.ticks = element_blank(),
+        panel.border = element_blank())
+
+# Combine the two plots
+both.1812.plot.simple <- rbind(ggplotGrob(march.1812.plot.simple),
+                               ggplotGrob(temps.1812.plot))
+
+# Adjust panels
+panels <- both.1812.plot.simple$layout$t[grep("panel", both.1812.plot.simple$layout$name)]
+
+# Because this plot doesn't use coord_equal, since it's not a map, we can use whatever relative numbers we want, like a 3:1 ratio
+both.1812.plot.simple$heights[panels] <- unit(c(3, 1), "null")
+
+grid::grid.newpage()
+grid::grid.draw(both.1812.plot.simple)
+

+
march.1812.europe <- c(left = -13.10, bottom = 35.75, right = 41.04, top = 61.86)
+
+march.1812.europe.map.wc <- get_stamenmap(bbox = march.1812.europe, zoom = 5,
+                                          maptype = "toner", where = "cache")
+
## Source : http://tile.stamen.com/toner/5/14/8.png
+
## Source : http://tile.stamen.com/toner/5/15/8.png
+
## Source : http://tile.stamen.com/toner/5/16/8.png
+
## Source : http://tile.stamen.com/toner/5/17/8.png
+
## Source : http://tile.stamen.com/toner/5/18/8.png
+
## Source : http://tile.stamen.com/toner/5/19/8.png
+
## Source : http://tile.stamen.com/toner/5/14/9.png
+
## Source : http://tile.stamen.com/toner/5/15/9.png
+
## Source : http://tile.stamen.com/toner/5/16/9.png
+
## Source : http://tile.stamen.com/toner/5/17/9.png
+
## Source : http://tile.stamen.com/toner/5/18/9.png
+
## Source : http://tile.stamen.com/toner/5/19/9.png
+
## Source : http://tile.stamen.com/toner/5/14/10.png
+
## Source : http://tile.stamen.com/toner/5/15/10.png
+
## Source : http://tile.stamen.com/toner/5/16/10.png
+
## Source : http://tile.stamen.com/toner/5/17/10.png
+
## Source : http://tile.stamen.com/toner/5/18/10.png
+
## Source : http://tile.stamen.com/toner/5/19/10.png
+
## Source : http://tile.stamen.com/toner/5/14/11.png
+
## Source : http://tile.stamen.com/toner/5/15/11.png
+
## Source : http://tile.stamen.com/toner/5/16/11.png
+
## Source : http://tile.stamen.com/toner/5/17/11.png
+
## Source : http://tile.stamen.com/toner/5/18/11.png
+
## Source : http://tile.stamen.com/toner/5/19/11.png
+
## Source : http://tile.stamen.com/toner/5/14/12.png
+
## Source : http://tile.stamen.com/toner/5/15/12.png
+
## Source : http://tile.stamen.com/toner/5/16/12.png
+
## Source : http://tile.stamen.com/toner/5/17/12.png
+
## Source : http://tile.stamen.com/toner/5/18/12.png
+
## Source : http://tile.stamen.com/toner/5/19/12.png
+
ggmap(march.1812.europe.map.wc) +
+  geom_path(data = troops, aes(x = long, y = lat, group = group, 
+                               color = direction, size = survivors),
+            lineend = "round") +
+  scale_size(range = c(0.5, 5)) + 
+  scale_colour_manual(values = c("#DFC17E", "#252523")) +
+  guides(color = FALSE, size = FALSE) +
+  theme_nothing()  # This is a special theme that comes with ggmap
+

+ + + + +
+ + + + + + + + + + + + + + +