From 46fdf38653044e6d66cb3153cb158d9130314c01 Mon Sep 17 00:00:00 2001
From: Lucas Philippe <lucasphilippe@macbook-air-de-lucas.home>
Date: Wed, 21 Feb 2024 21:06:56 +0100
Subject: [PATCH] ajout du tp d'analyse des donnees

---
 .DS_Store                                     |  Bin 0 -> 6148 bytes
 .gitignore                                    |    4 +
 README.md                                     |   92 +-
 TP1/.DS_Store                                 |  Bin 8196 -> 8196 bytes
 TP1/__pycache__/ExpSetup.cpython-39.pyc       |  Bin 4409 -> 4409 bytes
 TP1/data/response.csv                         |    5 +
 TP2/README.md                                 |  115 +
 TP2/TP2.R                                     |  150 +
 TP2/TP2.Rproj                                 |   13 +
 TP2/mean_rep_between_densities.jpg            |  Bin 0 -> 450158 bytes
 TP2/mean_rep_between_participants.jpg         |  Bin 0 -> 541668 bytes
 TP2/mean_rep_between_repetitions.jpg          |  Bin 0 -> 449367 bytes
 TP2/mean_rep_between_tailles.jpg              |  Bin 0 -> 463723 bytes
 TP2/mean_rep_between_techniques.jpg           |  Bin 0 -> 504939 bytes
 TP2/mean_rep_between_techniques_densities.jpg |  Bin 0 -> 540408 bytes
 TP2/mean_rep_between_techniques_tailles.jpg   |  Bin 0 -> 528693 bytes
 TP2/response.csv                              | 3241 +++++++++++++++++
 17 files changed, 3532 insertions(+), 88 deletions(-)
 create mode 100644 .DS_Store
 create mode 100644 .gitignore
 create mode 100644 TP2/README.md
 create mode 100644 TP2/TP2.R
 create mode 100644 TP2/TP2.Rproj
 create mode 100644 TP2/mean_rep_between_densities.jpg
 create mode 100644 TP2/mean_rep_between_participants.jpg
 create mode 100644 TP2/mean_rep_between_repetitions.jpg
 create mode 100644 TP2/mean_rep_between_tailles.jpg
 create mode 100644 TP2/mean_rep_between_techniques.jpg
 create mode 100644 TP2/mean_rep_between_techniques_densities.jpg
 create mode 100644 TP2/mean_rep_between_techniques_tailles.jpg
 create mode 100644 TP2/response.csv

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diff --git a/.gitignore b/.gitignore
new file mode 100644
index 0000000..5b6a065
--- /dev/null
+++ b/.gitignore
@@ -0,0 +1,4 @@
+.Rproj.user
+.Rhistory
+.RData
+.Ruserdata
diff --git a/README.md b/README.md
index f832dca..84d8651 100644
--- a/README.md
+++ b/README.md
@@ -1,93 +1,9 @@
 # PHILIPPE-iihm
 
+## Auteur : PHILIPPE Lucas
 
+## Structure
 
-## Getting started
+Le dossier `TP1` comprend le TP1 et le TP2 (expÃ©rience contrÃ´lÃ©e).
 
-To make it easy for you to get started with GitLab, here's a list of recommended next steps.
-
-Already a pro? Just edit this README.md and make it your own. Want to make it easy? [Use the template at the bottom](#editing-this-readme)!
-
-## Add your files
-
-- [ ] [Create](https://docs.gitlab.com/ee/user/project/repository/web_editor.html#create-a-file) or [upload](https://docs.gitlab.com/ee/user/project/repository/web_editor.html#upload-a-file) files
-- [ ] [Add files using the command line](https://docs.gitlab.com/ee/gitlab-basics/add-file.html#add-a-file-using-the-command-line) or push an existing Git repository with the following command:
-
-```
-cd existing_repo
-git remote add origin https://gitlab.univ-lille.fr/lucas.philippe.etu/philippe-iihm.git
-git branch -M main
-git push -uf origin main
-```
-
-## Integrate with your tools
-
-- [ ] [Set up project integrations](https://gitlab.univ-lille.fr/lucas.philippe.etu/philippe-iihm/-/settings/integrations)
-
-## Collaborate with your team
-
-- [ ] [Invite team members and collaborators](https://docs.gitlab.com/ee/user/project/members/)
-- [ ] [Create a new merge request](https://docs.gitlab.com/ee/user/project/merge_requests/creating_merge_requests.html)
-- [ ] [Automatically close issues from merge requests](https://docs.gitlab.com/ee/user/project/issues/managing_issues.html#closing-issues-automatically)
-- [ ] [Enable merge request approvals](https://docs.gitlab.com/ee/user/project/merge_requests/approvals/)
-- [ ] [Set auto-merge](https://docs.gitlab.com/ee/user/project/merge_requests/merge_when_pipeline_succeeds.html)
-
-## Test and Deploy
-
-Use the built-in continuous integration in GitLab.
-
-- [ ] [Get started with GitLab CI/CD](https://docs.gitlab.com/ee/ci/quick_start/index.html)
-- [ ] [Analyze your code for known vulnerabilities with Static Application Security Testing (SAST)](https://docs.gitlab.com/ee/user/application_security/sast/)
-- [ ] [Deploy to Kubernetes, Amazon EC2, or Amazon ECS using Auto Deploy](https://docs.gitlab.com/ee/topics/autodevops/requirements.html)
-- [ ] [Use pull-based deployments for improved Kubernetes management](https://docs.gitlab.com/ee/user/clusters/agent/)
-- [ ] [Set up protected environments](https://docs.gitlab.com/ee/ci/environments/protected_environments.html)
-
-***
-
-# Editing this README
-
-When you're ready to make this README your own, just edit this file and use the handy template below (or feel free to structure it however you want - this is just a starting point!). Thanks to [makeareadme.com](https://www.makeareadme.com/) for this template.
-
-## Suggestions for a good README
-
-Every project is different, so consider which of these sections apply to yours. The sections used in the template are suggestions for most open source projects. Also keep in mind that while a README can be too long and detailed, too long is better than too short. If you think your README is too long, consider utilizing another form of documentation rather than cutting out information.
-
-## Name
-Choose a self-explaining name for your project.
-
-## Description
-Let people know what your project can do specifically. Provide context and add a link to any reference visitors might be unfamiliar with. A list of Features or a Background subsection can also be added here. If there are alternatives to your project, this is a good place to list differentiating factors.
-
-## Badges
-On some READMEs, you may see small images that convey metadata, such as whether or not all the tests are passing for the project. You can use Shields to add some to your README. Many services also have instructions for adding a badge.
-
-## Visuals
-Depending on what you are making, it can be a good idea to include screenshots or even a video (you'll frequently see GIFs rather than actual videos). Tools like ttygif can help, but check out Asciinema for a more sophisticated method.
-
-## Installation
-Within a particular ecosystem, there may be a common way of installing things, such as using Yarn, NuGet, or Homebrew. However, consider the possibility that whoever is reading your README is a novice and would like more guidance. Listing specific steps helps remove ambiguity and gets people to using your project as quickly as possible. If it only runs in a specific context like a particular programming language version or operating system or has dependencies that have to be installed manually, also add a Requirements subsection.
-
-## Usage
-Use examples liberally, and show the expected output if you can. It's helpful to have inline the smallest example of usage that you can demonstrate, while providing links to more sophisticated examples if they are too long to reasonably include in the README.
-
-## Support
-Tell people where they can go to for help. It can be any combination of an issue tracker, a chat room, an email address, etc.
-
-## Roadmap
-If you have ideas for releases in the future, it is a good idea to list them in the README.
-
-## Contributing
-State if you are open to contributions and what your requirements are for accepting them.
-
-For people who want to make changes to your project, it's helpful to have some documentation on how to get started. Perhaps there is a script that they should run or some environment variables that they need to set. Make these steps explicit. These instructions could also be useful to your future self.
-
-You can also document commands to lint the code or run tests. These steps help to ensure high code quality and reduce the likelihood that the changes inadvertently break something. Having instructions for running tests is especially helpful if it requires external setup, such as starting a Selenium server for testing in a browser.
-
-## Authors and acknowledgment
-Show your appreciation to those who have contributed to the project.
-
-## License
-For open source projects, say how it is licensed.
-
-## Project status
-If you have run out of energy or time for your project, put a note at the top of the README saying that development has slowed down or stopped completely. Someone may choose to fork your project or volunteer to step in as a maintainer or owner, allowing your project to keep going. You can also make an explicit request for maintainers.
+Le dossier `TP3` comprend l'analyse des rÃ©sultats.
\ No newline at end of file
diff --git a/TP1/.DS_Store b/TP1/.DS_Store
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diff --git a/TP1/__pycache__/ExpSetup.cpython-39.pyc b/TP1/__pycache__/ExpSetup.cpython-39.pyc
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diff --git a/TP1/data/response.csv b/TP1/data/response.csv
index 1e7a1a1..065e80e 100644
--- a/TP1/data/response.csv
+++ b/TP1/data/response.csv
@@ -3238,3 +3238,8 @@
 1603, 1, 13, 90, 18, NORMAL, 1612.5524044036865, 0
 1603, 1, 14, 90, 18, NORMAL, 1196.0630416870117, 1
 1603, 1, 15, 90, 18, NORMAL, 909.4836711883545, 0
+9, 0, 1, 30, 9, BUBBLE, 24034.497022628784, 0
+9, 0, 2, 30, 9, BUBBLE, 1729.8812866210938, 0
+9, 0, 3, 30, 9, BUBBLE, 897.9692459106445, 0
+9, 0, 4, 30, 9, BUBBLE, 2222.6080894470215, 0
+9, 0, 5, 30, 9, BUBBLE, 1909.3399047851562, 0
diff --git a/TP2/README.md b/TP2/README.md
new file mode 100644
index 0000000..7634897
--- /dev/null
+++ b/TP2/README.md
@@ -0,0 +1,115 @@
+# ExpÃ©rience contrÃ´lÃ©e et analyse des rÃ©sultats :
+
+En premier lieu, il faut ajouter en en-tÃªte du fichier response.csv :
+
+`numero utilisateur, repetition, numero sequence, densite, taille, technique, temps, erreur`
+
+Ensuite, dans R, il faut faire ceci pour importer le csv :
+
+```
+library(readr)
+data <- read_csv("response.csv")
+```
+
+Si `readr` n'est pas installÃ©, il faut faire :
+
+```
+install.packages("tidyverse")
+```
+
+Pour pouvoir voir la data il faut faire :
+
+```
+View(data)
+```
+
+Avant d'utiliser la data, il faut marquer les colonnes adÃ©quates comme des facteurs et supprimer les lignes ou l'utilisateur a fait des erreurs.
+
+La commande pour marquer les colonnes adÃ©quates comme des facteurs :
+
+```
+data_clean$numero_utilisateur <- as.factor(data_clean$numero_utilisateur)
+data_clean$densite <- as.factor(data_clean$densite)
+data_clean$taille <- as.factor(data_clean$taille)
+data_clean$technique <- as.factor(data_clean$technique)
+data_clean$repetition <- as.factor(data_clean$repetition)
+```
+
+La commande pour retirer les erreurs des utilisateurs, et les temps d'oubli des utilisateurs > 10s:
+
+```
+data_clean <- data[data$erreur == 0 & data$temps <= 10000, ]
+```
+
+Pour les graphiques, je ne vais pas parler de temps de rÃ©ponse mais de temps de rÃ©ponse moyen.
+
+Pour pouvoir faire cela, voici un exemple :
+
+```
+participant_means <- data_clean %>%
+  group_by(numero_utilisateur) %>%
+  summarise(mean_time = mean(temps, na.rm = TRUE))
+```
+
+Voici le temps de rÃ©ponse moyen entre participants.
+
+![Image d'exemple](mean_rep_between_participants.jpg)
+
+Sur ce graphique, chaque barre reprÃ©sente un participant avec son temps moyen.
+On constate qu'il y a une diffÃ©rence du temps moyen entre chaque utilisateur.
+Cela dÃ©pend Ã  la rÃ©activitÃ© de chacun ainsi Ã  la prÃ©cision pour Ã©viter les fautes.
+
+Voici le temps de rÃ©ponse moyen entre blocs/rÃ©pÃ©titions.
+
+![Image d'exemple](mean_rep_between_repetitions.jpg)
+
+Sur ce graphique, la barre de gauche reprÃ©sente la rÃ©pÃ©tition 0 et la barre de droite la rÃ©pÃ©tition 1.
+On peut constater que le temps moyen est plus faible pour la rÃ©pÃ©tition 1, on peut donc dire qu'il y a un effet d'apprentissage Ã©tant donnÃ© que la sÃ©quence des 15 bulles Ã  sÃ©lectionner reste le mÃªme.
+
+Voici le temps de rÃ©ponse moyen entre techniques.
+
+![Image d'exemple](mean_rep_between_techniques.jpg)
+
+Sur ce graphique, chaque barre correspond aux trois techniques.
+On peut constater ici que les techniques Bubble et Rope sont plus ou moins similaires en terme de temps moyen, et la technique Normal a un temps moyen bien plus elevÃ© que les deux autres.
+Cela peut s'expliquer car Bubble et Rope n'ont pas besoin d'Ãªtre dans la bulle pour Ãªtre sÃ©lectionnÃ©, il suffit juste que le curseur soit le plus proche de la bulle.
+Tandis que la technique Normal doit forcÃ©ment Ãªtre sÃ©lectionnÃ© Ã  l'intÃ©rieur de la bulle.
+
+Voici le temps moyen de rÃ©ponse entre densitÃ©s.
+
+![Image d'exemple](mean_rep_between_densities.jpg)
+
+Sur ce graphique, chaque barre correspond aux trois densitÃ©s diffÃ©rentes (30, 60, 90).
+On peut constater ici que il n'y a pas de diffÃ©rence notable sur le temps moyen lorsque l'on passe de 30 Ã  60 de densitÃ©s. Par contre, avec 90 on peut constater que le temps moyen augmente comparer aux densitÃ©s de 30 et 60.
+On peut expliquer cela parce que plus il y a de bulles dans l'application, plus il faut Ãªtre prÃ©cis.
+
+Voici le temps moyen de rÃ©ponse entre chaque tailles
+
+![Image d'exemple](mean_rep_between_tailles.jpg)
+
+Sur ce graphique, chaque barre correspond aux trois tailles diffÃ©rentes de bulles (9, 12 et 18).
+On peut constater ici que plus la taille des bulles augmentent, plus le temps moyen des rÃ©ponses est rÃ©duit.
+On peut expliquer cela par le fait que plus la taille des bulles est grosses, moins il faut Ãªtre prÃ©cis pour cliquer.
+
+
+Voici le temps moyen de rÃ©ponse entre techniques et densitÃ©s
+
+![Image d'exemple](mean_rep_between_techniques_densities.jpg)
+
+Sur ce graphique, on peut voir qu'on a trois groupements de barres (correspondant aux trois densitÃ©s : 30, 60, 90) qui contient trois barres (correspondant aux techniques : Bubble, Normal, Rope).
+On peut constater que le changement de densitÃ© affecte certaines techniques lorsqu'il y a plus de bulles/cibles.
+On peut en effet constater une augmentation du temps moyen de rÃ©ponse pour les techniques Bubble et Rope, alors que Normal stagne sur les trois densitÃ©s.
+On peut expliquer cela car Bubble et Rope sont deux techniques n'ayant pas besoin d'Ãªtre dans la bulle/cible pour Ãªtre sÃ©lectionner, mais il faut Ãªtre le plus proche possible. Le fait d'avoir plus de bulles/cibles entraÃ®nent donc de la prÃ©cision supplÃ©mentaire pour ces deux techniques.
+
+Voici le temps moyen de rÃ©ponse entre techniques et tailles de cibles.
+
+![Image d'exemple](mean_rep_between_techniques_tailles.jpg)
+
+Sur ce graphique, on peut voir qu'on a trois groupements de barres (correspondant aux tailles des bulles/cibles) qui contient trois barres (correspondant aux techniques : Bubble, Normal, Rope).
+On peut constater que le changement de taille a un impact majeur de la diminution de temps moyen de rÃ©ponse pour les trois techniques.
+On peut donc en dÃ©duire que plus la cible est grande, moins l'utilisateur doit Ãªtre prÃ©cis, ce qui raccourcit donc le temps moyen des rÃ©ponses.
+
+Conclusion :
+
+Pour conclure, pour avoir le temps de rÃ©ponse le plus bas possible, il faudrait optimiser les facteurs importants comme la densitÃ©, la taille et la technique choisit.
+Pour pouvoir Ãªtre le plus efficace possible, il faudrait une taille des bulles/cibles plus grandes, une densitÃ© plutÃ´t faible (avec une densitÃ© elevÃ©, cela pourrait augmenter la prÃ©cision et donc le temps de rÃ©ponse), et plutÃ´t choisir un style de technique comme Bubble ou Rope (de sorte Ã  choisir la cible/bulle la plus proche et non devoir sÃ©lectionner la cible).
\ No newline at end of file
diff --git a/TP2/TP2.R b/TP2/TP2.R
new file mode 100644
index 0000000..53e8fbf
--- /dev/null
+++ b/TP2/TP2.R
@@ -0,0 +1,150 @@
+library(readr)
+library(ggplot2)
+library(RColorBrewer)
+library(dplyr)
+data <- read_csv("response.csv")
+
+#View(data)
+
+data$numero_sequence <- NULL
+
+summary(data)
+
+data_clean <- data[data$erreur == 0 & data$temps <= 10000, ]
+
+View(data_clean)
+
+summary(data_clean)
+
+data_clean$numero_utilisateur <- as.factor(data_clean$numero_utilisateur)
+data_clean$densite <- as.factor(data_clean$densite)
+data_clean$taille <- as.factor(data_clean$taille)
+data_clean$technique <- as.factor(data_clean$technique)
+data_clean$repetition <- as.factor(data_clean$repetition)
+
+levels(data_clean$numero_utilisateur)
+summary(data_clean$numero_utilisateur)
+
+levels(data_clean$technique)
+summary(data_clean$technique)
+
+levels(data_clean$densite)
+summary(data_clean$densite)
+
+levels(data_clean$taille)
+summary(data_clean$taille)
+
+levels(data_clean$repetition)
+summary(data_clean$repetition)
+
+participant_means <- data_clean %>%
+  group_by(numero_utilisateur) %>%
+  summarise(mean_time = mean(temps, na.rm = TRUE))
+
+rep_between_participants <- ggplot(participant_means, aes(x=numero_utilisateur, y=mean_time, fill=numero_utilisateur)) +
+  geom_bar(stat="identity", position="dodge") +
+  scale_fill_brewer(palette = "Set1") +
+  theme_minimal() +
+  labs(title="Moyenne du temps de rÃ©ponse entre participants", x="Participant ID", y="Temps de rÃ©ponse moyen (ms)")
+
+ggsave("mean_rep_between_participants.jpg", plot = rep_between_participants, width = 11, height = 8, units = "in")
+
+repetition_means <- data_clean %>%
+  group_by(repetition) %>%
+  summarise(mean_time = mean(temps, na.rm = TRUE))
+
+rep_between_repetitions <- ggplot(repetition_means, aes(x=repetition, y=mean_time, fill=repetition)) +
+  geom_bar(stat="identity", position="dodge") +
+  scale_fill_brewer(palette = "Set1") +
+  theme_minimal() +
+  labs(title="Moyenne du temps de rÃ©ponse entre rÃ©pÃ©titions", x="RÃ©pÃ©tition", y="Temps de rÃ©ponse moyen (ms)")
+
+ggsave("mean_rep_between_repetitions.jpg", plot = rep_between_repetitions, width = 11, height = 8, units = "in")
+
+
+data_summary <- data_clean %>%
+  group_by(technique) %>%
+  summarise(temps_moyen = mean(temps, na.rm = TRUE))
+
+rep_between_techniques <- ggplot(data_summary, aes(x=technique, y=temps_moyen, fill=technique)) +
+  geom_bar(stat="identity", position="dodge") +
+  scale_fill_brewer(palette = "Set1") +
+  theme_minimal() +
+  labs(title="Moyenne du temps de rÃ©ponse par technique",
+       x="Technique",
+       y="Temps de rÃ©ponse moyen (ms)")
+
+ggsave("mean_rep_between_techniques.jpg", plot = rep_between_techniques, width = 11, height = 8, units = "in")
+
+densite_means <- data_clean %>%
+  group_by(densite) %>%
+  summarise(mean_time = mean(temps, na.rm = TRUE))
+
+rep_between_densities <- ggplot(densite_means, aes(x=densite, y=mean_time, fill=densite)) +
+  geom_col() +
+  theme_minimal() +
+  labs(title="Moyenne du temps de rÃ©ponse par densitÃ©",
+       x="DensitÃ©",
+       y="Temps de rÃ©ponse moyen (ms)") +
+  theme(legend.position="none")
+
+ggsave("mean_rep_between_densities.jpg", plot = rep_between_densities, width = 11, height = 8, units = "in")
+
+taille_means <- data_clean %>%
+  group_by(taille) %>%
+  summarise(mean_time = mean(temps, na.rm = TRUE))
+
+rep_between_tailles <- ggplot(taille_means, aes(x=taille, y=mean_time, fill=taille)) +
+  geom_col() +
+  theme_minimal() +
+  labs(title="Moyenne du temps de rÃ©ponse par taille de cible",
+       x="Taille de cible",
+       y="Temps de rÃ©ponse moyen (ms)") +
+  theme(legend.position="none")
+
+ggsave("mean_rep_between_tailles.jpg", plot = rep_between_tailles, width = 11, height = 8, units = "in")
+
+technique_densite_means <- data_clean %>%
+  group_by(technique, densite) %>%
+  summarise(mean_time = mean(temps, na.rm = TRUE))
+
+rep_between_techniques_densities <- ggplot(technique_densite_means, aes(x=densite, y=mean_time, fill=technique)) +
+  geom_col(position = position_dodge()) +
+  theme_minimal() +
+  labs(title="Moyenne du temps de rÃ©ponse par technique et densitÃ©",
+       x="DensitÃ©",
+       y="Temps de rÃ©ponse moyen (ms)") +
+  scale_fill_brewer(palette = "Set1") +
+  theme(legend.title = element_blank(), legend.position = "right")
+
+ggsave("mean_rep_between_techniques_densities.jpg", plot = rep_between_techniques_densities, width = 11, height = 8, units = "in")
+
+technique_taille_means <- data_clean %>%
+  group_by(technique, taille) %>%
+  summarise(mean_time = mean(temps, na.rm = TRUE))
+
+rep_between_techniques_tailles <- ggplot(technique_taille_means, aes(x=taille, y=mean_time, fill=technique)) +
+  geom_col(position = position_dodge()) +
+  theme_minimal() +
+  labs(title="Moyenne du temps de rÃ©ponse par technique et taille de cible",
+       x="Taille de cible",
+       y="Temps de rÃ©ponse moyen (ms)") +
+  scale_fill_brewer(palette = "Set1") +
+  theme(legend.title = element_blank(), legend.position = "right")
+
+ggsave("mean_rep_between_techniques_tailles.jpg", plot = rep_between_techniques_tailles, width = 11, height = 8, units = "in")
+
+technique_taille_means <- data_clean %>%
+  group_by(technique, taille) %>%
+  summarise(mean_time = mean(temps, na.rm = TRUE))
+
+rep_between_techniques_tailles <- ggplot(technique_taille_means, aes(x=taille, y=mean_time, fill=technique)) +
+  geom_col(position = position_dodge()) +
+  theme_minimal() +
+  labs(title="Moyenne du temps de rÃ©ponse par technique et taille de cible",
+       x="Taille de cible",
+       y="Temps de rÃ©ponse moyen (ms)") +
+  scale_fill_brewer(palette = "Set1") +
+  theme(legend.title = element_blank(), legend.position = "right")
+
+ggsave("mean_rep_between_techniques_tailles.jpg", plot = rep_between_techniques_tailles, width = 11, height = 8, units = "in")
diff --git a/TP2/TP2.Rproj b/TP2/TP2.Rproj
new file mode 100644
index 0000000..8e3c2eb
--- /dev/null
+++ b/TP2/TP2.Rproj
@@ -0,0 +1,13 @@
+Version: 1.0
+
+RestoreWorkspace: Default
+SaveWorkspace: Default
+AlwaysSaveHistory: Default
+
+EnableCodeIndexing: Yes
+UseSpacesForTab: Yes
+NumSpacesForTab: 2
+Encoding: UTF-8
+
+RnwWeave: Sweave
+LaTeX: pdfLaTeX
diff --git a/TP2/mean_rep_between_densities.jpg b/TP2/mean_rep_between_densities.jpg
new file mode 100644
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diff --git a/TP2/response.csv b/TP2/response.csv
new file mode 100644
index 0000000..12cb2a9
--- /dev/null
+++ b/TP2/response.csv
@@ -0,0 +1,3241 @@
+numero_utilisateur, repetition, numero_sequence, densite, taille, technique, temps, erreur
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+28, 0, 3, 30, 9, BUBBLE, 753.0219554901123, 0
+28, 0, 4, 30, 9, BUBBLE, 845.7729816436768, 0
+28, 0, 5, 30, 9, BUBBLE, 902.195930480957, 0
+28, 0, 6, 30, 9, BUBBLE, 684.8659515380859, 0
+28, 0, 7, 30, 9, BUBBLE, 914.7729873657227, 0
+28, 0, 8, 30, 9, BUBBLE, 634.1960430145264, 0
+28, 0, 9, 30, 9, BUBBLE, 1044.8458194732666, 0
+28, 0, 10, 30, 9, BUBBLE, 700.096845626831, 0
+28, 0, 11, 30, 9, BUBBLE, 714.7231101989746, 0
+28, 0, 12, 30, 9, BUBBLE, 868.3090209960938, 0
+28, 0, 13, 30, 9, BUBBLE, 718.256950378418, 0
+28, 0, 14, 30, 9, BUBBLE, 761.9531154632568, 0
+28, 0, 15, 30, 9, BUBBLE, 1019.5293426513672, 0
+28, 0, 1, 30, 12, BUBBLE, 15284.09194946289, 0
+28, 0, 2, 30, 12, BUBBLE, 818.4120655059814, 0
+28, 0, 3, 30, 12, BUBBLE, 645.3728675842285, 0
+28, 0, 4, 30, 12, BUBBLE, 764.9750709533691, 0
+28, 0, 5, 30, 12, BUBBLE, 799.94797706604, 0
+28, 0, 6, 30, 12, BUBBLE, 635.3421211242676, 0
+28, 0, 7, 30, 12, BUBBLE, 914.1862392425537, 0
+28, 0, 8, 30, 12, BUBBLE, 731.3640117645264, 0
+28, 0, 9, 30, 12, BUBBLE, 733.0479621887207, 0
+28, 0, 10, 30, 12, BUBBLE, 751.3017654418945, 0
+28, 0, 11, 30, 12, BUBBLE, 565.6378269195557, 0
+28, 0, 12, 30, 12, BUBBLE, 933.4621429443359, 0
+28, 0, 13, 30, 12, BUBBLE, 849.3301868438721, 0
+28, 0, 14, 30, 12, BUBBLE, 1063.5089874267578, 0
+28, 0, 15, 30, 12, BUBBLE, 835.0818157196045, 0
+28, 0, 1, 30, 18, BUBBLE, 27118.77989768982, 0
+28, 0, 2, 30, 18, BUBBLE, 683.6972236633301, 0
+28, 0, 3, 30, 18, BUBBLE, 662.0678901672363, 0
+28, 0, 4, 30, 18, BUBBLE, 915.2200222015381, 0
+28, 0, 5, 30, 18, BUBBLE, 783.4489345550537, 0
+28, 0, 6, 30, 18, BUBBLE, 716.9358730316162, 0
+28, 0, 7, 30, 18, BUBBLE, 764.8739814758301, 0
+28, 0, 8, 30, 18, BUBBLE, 633.734941482544, 0
+28, 0, 9, 30, 18, BUBBLE, 730.6520938873291, 0
+28, 0, 10, 30, 18, BUBBLE, 669.3887710571289, 0
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+1603, 1, 9, 90, 9, NORMAL, 1717.0054912567139, 0
+1603, 1, 10, 90, 9, NORMAL, 1263.8771533966064, 0
+1603, 1, 11, 90, 9, NORMAL, 1577.7392387390137, 0
+1603, 1, 12, 90, 9, NORMAL, 2109.3244552612305, 0
+1603, 1, 13, 90, 9, NORMAL, 1316.739559173584, 0
+1603, 1, 14, 90, 9, NORMAL, 3029.134750366211, 3
+1603, 1, 15, 90, 9, NORMAL, 1500.5714893341064, 0
+1603, 1, 1, 90, 12, NORMAL, 762538.17486763, 0
+1603, 1, 2, 90, 12, NORMAL, 1725.3680229187012, 0
+1603, 1, 3, 90, 12, NORMAL, 1204.7686576843262, 0
+1603, 1, 4, 90, 12, NORMAL, 1340.9414291381836, 0
+1603, 1, 5, 90, 12, NORMAL, 1764.3623352050781, 1
+1603, 1, 6, 90, 12, NORMAL, 1333.6412906646729, 1
+1603, 1, 7, 90, 12, NORMAL, 1173.448085784912, 0
+1603, 1, 8, 90, 12, NORMAL, 1276.716709136963, 0
+1603, 1, 9, 90, 12, NORMAL, 2412.9605293273926, 0
+1603, 1, 10, 90, 12, NORMAL, 965.6631946563721, 0
+1603, 1, 11, 90, 12, NORMAL, 853.1224727630615, 0
+1603, 1, 12, 90, 12, NORMAL, 1485.5124950408936, 0
+1603, 1, 13, 90, 12, NORMAL, 972.2898006439209, 0
+1603, 1, 14, 90, 12, NORMAL, 988.4324073791504, 0
+1603, 1, 15, 90, 12, NORMAL, 1709.2559337615967, 1
+1603, 1, 1, 90, 18, NORMAL, 782666.2864685059, 0
+1603, 1, 2, 90, 18, NORMAL, 916.7065620422363, 0
+1603, 1, 3, 90, 18, NORMAL, 1685.1909160614014, 1
+1603, 1, 4, 90, 18, NORMAL, 1069.6072578430176, 0
+1603, 1, 5, 90, 18, NORMAL, 1245.246171951294, 0
+1603, 1, 6, 90, 18, NORMAL, 940.8316612243652, 0
+1603, 1, 7, 90, 18, NORMAL, 1404.5073986053467, 1
+1603, 1, 8, 90, 18, NORMAL, 776.3431072235107, 0
+1603, 1, 9, 90, 18, NORMAL, 1177.1724224090576, 0
+1603, 1, 10, 90, 18, NORMAL, 1414.5281314849854, 0
+1603, 1, 11, 90, 18, NORMAL, 684.6177577972412, 0
+1603, 1, 12, 90, 18, NORMAL, 1788.9916896820068, 0
+1603, 1, 13, 90, 18, NORMAL, 1612.5524044036865, 0
+1603, 1, 14, 90, 18, NORMAL, 1196.0630416870117, 1
+1603, 1, 15, 90, 18, NORMAL, 909.4836711883545, 0
-- 
GitLab