From 413cd679cf29318713513fd097b7b8624314e6c0 Mon Sep 17 00:00:00 2001
From: Bruno Bonte <bruno.bonte@irstea.fr>
Date: Fri, 6 Mar 2020 10:53:22 +0100
Subject: [PATCH] en train d organiser les graph

---
 iat-leem-analysis.R | 55 ++++++++++++++++++++++++++++-----------------
 1 file changed, 35 insertions(+), 20 deletions(-)

diff --git a/iat-leem-analysis.R b/iat-leem-analysis.R
index 2bf02eb..97c80cf 100644
--- a/iat-leem-analysis.R
+++ b/iat-leem-analysis.R
@@ -8,62 +8,77 @@ library(RColorBrewer)
 #set working directory where this source file is
 setwd("/home/bruno/git/aiat")
 
+lemmDataFolder <- "~/git/interexpe-data/formated-data"
+
 #################################################################
 ## Pour ploter les distributions des temps de réactions à partir#
 #####           des résultats bruts                       #######
 #################################################################
 
-alldata <- read.table("data/alldata-expe-lem.csv",
-                   sep=",",
-                   dec= ".",
-                   header = T) %>%
+alldata <- read.csv(file.path(lemmDataFolder, "iat-data.csv")) %>%
+  mutate(trial = trial + 1) %>%
+  mutate(id = as.factor(participant.label)) %>%
   tbl_df()
 
 iat_scores <- alldata  %>%   
   filter(reactionTime < 3000) %>%
   filter(reactionTime > 300) %>%
   filter(trial == 4 | (trial == 7)) %>%
-  group_by(id) %>%
+  group_by(id, test.status) %>%
   mutate(full.sd = sd(reactionTime)) %>%
-  group_by(id, trial, full.sd) %>%
+  group_by(id, trial, full.sd, test.status, refSession.traitement) %>%
   summarise(mRT = mean(reactionTime), sdRT = sd(reactionTime)) %>%
-  gather(variable,value, -id, -full.sd, -trial) %>%
+  gather(variable,value, mRT, sdRT) %>%
   unite(block, trial, variable) %>%
   spread(block,value, sep = "") %>%
-  mutate(d = round((block7_mRT - block4_mRT) / full.sd, digits=5)) 
+  mutate(d = round((block7_mRT - block4_mRT) / full.sd, digits=5))  %>%
+  na.omit()
 
 iat_scores_train <- alldata  %>%   
   filter(reactionTime < 3000) %>%
   filter(reactionTime > 300) %>%
   filter(trial == 3 | (trial == 6)) %>%
-  group_by(id) %>%
+  group_by(id, test.status) %>%
   mutate(full.sd = sd(reactionTime)) %>%
-  group_by(id, trial, full.sd) %>%
+  group_by(id, trial, full.sd, test.status, refSession.traitement) %>%
   summarise(mRT = mean(reactionTime), sdRT = sd(reactionTime)) %>%
-  gather(variable,value, -id, -full.sd, -trial) %>%
+  gather(variable,value, mRT, sdRT) %>%
   unite(block, trial, variable) %>%
   spread(block,value, sep = "") %>%
-  mutate(d = round((block6_mRT - block3_mRT) / full.sd, digits=5)) 
+  mutate(d = round((block6_mRT - block3_mRT) / full.sd, digits=5)) %>%
+  na.omit()
 
 alldata  %>% 
+  filter(test.status != "onlyPre") %>%
   filter(reactionTime < 3000) %>%
   filter(reactionTime > 300) %>%
   filter(trial == 4 | (trial == 7)) %>%
   mutate(category = recode_factor(category, 
-                                  "A"= "Appropriation",
-                                  "P"= "Partage",
-                                  "1"= "Moi",
-                                  "2"= "PasMoi")) %>%
+                                  "A" = "Appropriation",
+                                  "P" = "Partage",
+                                  "1" = "Moi",
+                                  "2" = "PasMoi")) %>%
   mutate(trial=as.factor(trial)) %>%
-  left_join(iat_scores, by='id') %>%
-  mutate(lab = paste0("id: ", id,"\n(d=",d,")")) %>%
+  left_join(iat_scores, by=c('id', "test.status", "refSession.traitement")) %>%
+  mutate(lab = paste0( "Traitement: ",refSession.traitement, "\nid: ", id, " ", test.status, "\n(d=",d,")")) %>%
   ggplot() +
   geom_histogram(aes(x= reactionTime, fill=trial), position = "dodge") +
-  facet_wrap(~lab, scales ="free_x")   + 
+  facet_wrap(~lab, scales ="free_x")  + 
+  theme(strip.text.x = element_text(size = 5)) + 
   ggsave("per-trial-reaction-times-alldata.pdf",
          height = 21,
          width = 29.7,
-         units = "cm")
+         units = "cm") 
+
+iat_scores %>%
+  mutate(sujet = (as.factor(id))) %>%
+  mutate(when = - as.numeric(test.status)) %>%
+  ggplot() +
+  geom_bar(aes(x=sujet, y=d, fill = test.status, group = when), stat="identity", position= "dodge") + 
+  facet_wrap(~refSession.traitement, scales = "free_x") +
+  theme(axis.text.x = element_text(angle = 90, hjust = 1, vjust=0.5)) +
+  scale_fill_discrete(breaks=c("pre", "post")) +
+  ggsave("avant-apres-iat.pdf")
 
 iat_scores %>% 
   mutate(lab = (as.factor(id))) %>%
-- 
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