Skip to content

Commit

Permalink
refactor
Browse files Browse the repository at this point in the history
  • Loading branch information
@rambip
rambip committed Jun 3, 2024
1 parent f4c24f7 commit a0e3c19
Showing 1 changed file with 39 additions and 134 deletions.
173 changes: 39 additions & 134 deletions site.py
View file
Original file line number Diff line number Diff line change
Expand Up @@ -48,8 +48,23 @@ def render_question(i):
render_choices(q["choices"])


def pie(values, labels):
plt.pie(values, labels=labels, autopct=lambda x:f"{x:1.1f} %")
def pie_chart(df, title, labels=None):
fig, _ = plt.subplots()
count = df.value_counts().sort_index()/N
if labels==None:
labels = count.index
plt.pie(count.values, labels=labels, autopct=lambda x:f"{x:1.1f} %")
plt.title(title)
plt.close(fig)
plot_to_img(fig)


def bar_chart(labels, values, title):
fig, _ = plt.subplots()
plt.bar(labels, values)
plt.title(title)
plt.close(fig)
plot_to_img(fig)


doc.asis('<!DOCTYPE html>')
Expand All @@ -62,183 +77,73 @@ def pie(values, labels):
text('Sondage sûreté IA')

render_question(0)
fig, ax = plt.subplots()
capabilities = ["Minecraft", "Olympiades", "meme", "musique"]
columns = data[[1,2,3,4]].fillna(0).astype(int)
values = columns.mean(axis=0)
plt.bar(capabilities, values)
plt.title('Tâches résolues')
plt.close(fig)
plot_to_img(fig)
bar_chart(capabilities, values, 'Tâches résolues')

render_question(1)
fig, ax = plt.subplots()
count = data[5].astype(float).value_counts().sort_index()/N
pie(count.values, labels=count.index)
plt.title('Elo de chatGPT')
plt.close(fig)
plot_to_img(fig)
pie_chart(data[5], 'Elo chatGPT')

render_question(2)
fig, ax = plt.subplots()
labels = ["Taille / performances", "Refus", "Raisonnement", "Connaissances"]
columns = data[[6,7,8,9]].fillna(0).astype(int)
values = columns.mean(axis=0)
plt.bar(labels, values)
plt.title('Compréhension des LLM')
plt.close(fig)
plot_to_img(fig)
bar_chart(labels, values, 'Compréhension des LLM')

render_question(3)
fig, ax = plt.subplots()
count = data[10].value_counts().sort_index()/N
pie(count.values, labels=["non", "oui"])
plt.title('RLHF')
plt.close(fig)
plot_to_img(fig)

pie_chart(data[10], "RLHF")

render_question(4)
fig, ax = plt.subplots()
count = data[11].astype(float).value_counts().sort_index()/N
plt.bar(count.index, count.values)
plt.title('Timeline openAI')
plt.close(fig)
plot_to_img(fig)
bar_chart(count.index, count.values, 'Timeline openAI')

render_question(5)
fig, ax = plt.subplots()
count = data[12].astype(float).value_counts().sort_index()/N
plt.bar(count.index, count.values)
plt.title('avis des Experts')
plt.close(fig)
plot_to_img(fig)
bar_chart(count.index, count.values, 'avis des Experts')

render_question(6)
fig, ax = plt.subplots()
count = data[13].value_counts().sort_index()/N
plt.bar(count.index, count.values)
plt.title('Risques')
plt.close(fig)
plot_to_img(fig)

bar_chart(count.index, count.values, 'Probablitité de catastrophe')

render_question(7)
fig, ax = plt.subplots()
count = data[14].value_counts().sort_index()/N
plt.bar(count.index, count.values)
plt.title('Cyber')
plt.close(fig)
plot_to_img(fig)

fig, ax = plt.subplots()
bar_chart(count.index, count.values, 'Cyber')
count = data[15].value_counts().sort_index()/N
plt.bar(count.index, count.values)
plt.title('Crash')
plt.close(fig)
plot_to_img(fig)

fig, ax = plt.subplots()
bar_chart(count.index, count.values, 'Crash')
count = data[16].value_counts().sort_index()/N
plt.bar(count.index, count.values)
plt.title('Perte contrôle')
plt.close(fig)
plot_to_img(fig)

fig, ax = plt.subplots()
bar_chart(count.index, count.values, 'Perte contrôle')
count = data[17].value_counts().sort_index()/N
plt.bar(count.index, count.values)
plt.title('Automatisation')
plt.close(fig)
plot_to_img(fig)
bar_chart(count.index, count.values, 'Automatisation')

render_question(8)
fig, ax = plt.subplots()
count = data[18].value_counts().sort_index()/N
pie(count.values, labels=["non", "oui"])
plt.title('ChatGPT')
plt.close(fig)
plot_to_img(fig)
pie_chart(data[18], "ChatGPT", labels=["non", "oui"])

render_question(9)
fig, ax = plt.subplots()
count = data[19].value_counts().sort_index()/N
pie(count.values, labels=["non", "oui"])
plt.title('API GPT4')
plt.close(fig)
plot_to_img(fig)
pie_chart(data[19], "API Publique", labels=["non", "oui"])

render_question(10)
fig, ax = plt.subplots()
count = data[20].value_counts().sort_index()/N
pie(count.values, labels=["non", "oui"])
plt.title('Sûreté IA juridique')
plt.close(fig)
plot_to_img(fig)
pie_chart(data[20], "Sûreté IA Juridique", labels=["non", "oui"])

render_question(11)
fig, ax = plt.subplots()
count = data[21].value_counts().sort_index()/N
pie(count.values, labels=["non", "oui"])
plt.title('Sûreté IA recherche')
plt.close(fig)
plot_to_img(fig)
pie_chart(data[21], "Sûreté IA recherche", labels=["non", "oui"])

render_question(12)
fig, ax = plt.subplots()
count = data[22].value_counts().sort_index()/N
pie(count.values, labels=["non", "oui"])
plt.title('ralentir création')
plt.close(fig)
plot_to_img(fig)
pie_chart(data[22], "Ralentir création", labels=["non", "oui"])

render_question(13)
fig, ax = plt.subplots()
count = data[23].value_counts().sort_index()/N
pie(count.values, labels=["non", "oui"])
plt.title('ralentir déploiement')
plt.close(fig)
plot_to_img(fig)

pie_chart(data[23], "Ralentir déploiement", labels=["non", "oui"])

render_question(14)
fig, ax = plt.subplots()
count = data[24].value_counts().sort_index()/N
pie(count.values, labels=["non", "oui"])
plt.title('EU AI Act')
plt.close(fig)
plot_to_img(fig)

fig, ax = plt.subplots()
count = data[25].value_counts().sort_index()/N
pie(count.values, labels=["non", "oui"])
plt.title('Séoul')
plt.close(fig)
plot_to_img(fig)

fig, ax = plt.subplots()
count = data[26].value_counts().sort_index()/N
pie(count.values, labels=["non", "oui"])
plt.title('PauseAI')
plt.close(fig)
plot_to_img(fig)

fig, ax = plt.subplots()
count = data[27].value_counts().sort_index()/N
pie(count.values, labels=["non", "oui"])
plt.title('CeSIA')
plt.close(fig)
plot_to_img(fig)
pie_chart(data[24], "EU AI Act", labels=["non", "oui"])
pie_chart(data[25], "Séoul", labels=["non", "oui"])
pie_chart(data[26], "PauseAI", labels=["non", "oui"])
pie_chart(data[27], "CeSIA", labels=["non", "oui"])

render_question(15)
fig, ax = plt.subplots()
count = data[28].value_counts().sort_index()/N
pie(count.values, labels=["non", "oui"])
plt.title('Cours')
plt.close(fig)
plot_to_img(fig)
pie_chart(data[28], "Cours", labels=["non", "oui"])

with open("index.html", "w") as file:
html_content = doc.getvalue()
file.write(html_content)

0 comments on commit a0e3c19

Please sign in to comment.