Finish Project

.idea/.gitignore

@@ -0,0 +1,8 @@
+# Default ignored files
+/shelf/
+/workspace.xml
+# Editor-based HTTP Client requests
+/httpRequests/
+# Datasource local storage ignored files
+/dataSources/
+/dataSources.local.xml

.idea/analytics_learning.iml

@@ -0,0 +1,19 @@
+<?xml version="1.0" encoding="UTF-8"?>
+<module type="PYTHON_MODULE" version="4">
+  <component name="Flask">
+    <option name="enabled" value="true" />
+  </component>
+  <component name="NewModuleRootManager">
+    <content url="file://$MODULE_DIR$" />
+    <orderEntry type="inheritedJdk" />
+    <orderEntry type="sourceFolder" forTests="false" />
+  </component>
+  <component name="TemplatesService">
+    <option name="TEMPLATE_CONFIGURATION" value="Jinja2" />
+    <option name="TEMPLATE_FOLDERS">
+      <list>
+        <option value="$MODULE_DIR$/templates" />
+      </list>
+    </option>
+  </component>
+</module>

.idea/inspectionProfiles/profiles_settings.xml

@@ -0,0 +1,6 @@
+<component name="InspectionProjectProfileManager">
+  <settings>
+    <option name="USE_PROJECT_PROFILE" value="false" />
+    <version value="1.0" />
+  </settings>
+</component>

.idea/misc.xml

@@ -0,0 +1,4 @@
+<?xml version="1.0" encoding="UTF-8"?>
+<project version="4">
+  <component name="ProjectRootManager" version="2" project-jdk-name="Python 3.10" project-jdk-type="Python SDK" />
+</project>

.idea/modules.xml

@@ -0,0 +1,8 @@
+<?xml version="1.0" encoding="UTF-8"?>
+<project version="4">
+  <component name="ProjectModuleManager">
+    <modules>
+      <module fileurl="file://$PROJECT_DIR$/.idea/analytics_learning.iml" filepath="$PROJECT_DIR$/.idea/analytics_learning.iml" />
+    </modules>
+  </component>
+</project>

.idea/vcs.xml

@@ -0,0 +1,6 @@
+<?xml version="1.0" encoding="UTF-8"?>
+<project version="4">
+  <component name="VcsDirectoryMappings">
+    <mapping directory="" vcs="Git" />
+  </component>
+</project>

Dockerfile

@@ -1,10 +0,0 @@
-FROM python
-
-RUN pip install flask scipy matplotlib
-# COPY chi_square.py kolmogorov_smirnov.py ./
-COPY server.py ./
-COPY templates templates
-RUN mkdir static
-
-# ENTRYPOINT ["python", "chi_square.py"]
-ENTRYPOINT ["flask", "run"]

Makefile

@@ -1,8 +0,0 @@
-run: build
-	docker compose up
-
-build:
-	docker compose build
-
-push:
-	docker compose push

chi_square.py

@@ -104,11 +104,11 @@ def index():
         plt.savefig('static/plot.png')
 
         # Render template with plot image and results
-        return render_template('chi_square.html', plot_path='static/plot.png', chisq_stat=chisq_stat, p_value=p_value)
+        return render_template('home.html', plot_path='static/plot.png', chisq_stat=chisq_stat, p_value=p_value)
 
     else:
         # Render initial form
-        return render_template('chi_square.html')
+        return render_template('home.html')
 
 if __name__ == '__main__':
     app.run(debug=True)

docker-compose.yml

@@ -1,13 +0,0 @@
-version: "3.9"
-services:
-  analytics_learning:
-    image: marcpartensky/analytics_learning
-    build: .
-    ports:
-      - "5000:5000"
-    environment:
-      FLASK_APP: server.py
-      # FLASK_APP: kolmogorov_smirnov.py
-      # FLASK_APP: chi_square.py
-      FLASK_RUN_HOST: "0.0.0.0"
-      FLASK_RUN_PORT: 5000

kolmogorov_smirnov.py

@@ -103,11 +103,11 @@ def index():
             plt.savefig('static/plot.png')
 
             # Render template with plot
-            return render_template('kolmogorov_smirnov.html', plot_url='static/plot.png')
+            return render_template('index.html', plot_url='static/plot.png')
         else:
-            return render_template('kolmogorov_smirnov.html', error=True)
+            return render_template('index.html', error=True)
     else:
-        return render_template('kolmogorov_smirnov.html')
+        return render_template('index.html')
 
 if __name__ == '__main__':
-    app.run(debug=True)
+    app.run(debug=True, port=8000)

server.py

@@ -1,95 +0,0 @@
-#!/usr/bin/env python
-
-from flask import Flask, render_template, request
-import numpy as np
-import scipy.stats as stats
-from scipy.stats import expon, gamma, norm, poisson
-import matplotlib.pyplot as plt
-
-app = Flask(__name__)
-
-# Define routes
-@app.route('/chi_square', methods=['GET', 'POST'])
-def chi_square():
-    if request.method == 'POST':
-        # Get distribution type from form submission
-        distribution_type = request.form['distribution_type']
-
-        # Generate random sample data for selected distribution
-        if distribution_type == 'normal':
-            data = np.random.normal(loc=0, scale=1, size=100)
-        elif distribution_type == 'exponential':
-            data = np.random.exponential(scale=1, size=100)
-        elif distribution_type == 'poisson':
-            data = np.random.poisson(lam=1, size=100)
-        elif distribution_type == 'gamma':
-            data = np.random.gamma(shape=2, scale=1, size=100)
-
-        # Calculate expected values for selected distribution
-        if distribution_type == 'normal':
-            expected = stats.norm(loc=np.mean(data), scale=np.std(data)).pdf(data)
-        elif distribution_type == 'exponential':
-            expected = stats.expon(scale=np.mean(data)).pdf(data)
-        elif distribution_type == 'poisson':
-            expected = stats.poisson(mu=np.mean(data)).pmf(data)
-        elif distribution_type == 'gamma':
-            expected = stats.gamma(a=np.mean(data)**2/np.var(data), scale=np.var(data)/np.mean(data)).pdf(data)
-
-        # Calculate Chi-square statistic and p-value
-        chisq_stat, p_value = stats.chisquare(f_obs=np.histogram(data, bins='auto')[0], f_exp=expected)
-
-        # Create histogram of sample data and plot expected distribution
-        plt.hist(data, bins='auto', density=True, alpha=0.7)
-        plt.plot(data, expected, 'r-', lw=2)
-        plt.title(f'{distribution_type.capitalize()} Distribution')
-        plt.xlabel('Value')
-        plt.ylabel('Density')
-        plt.savefig('static/plot.png')
-
-        # Render template with plot image and results
-        return render_template('chi_square.html', plot_path='static/plot.png', chisq_stat=chisq_stat, p_value=p_value)
-
-    else:
-        # Render initial form
-        return render_template('chi_square.html')
-
-@app.route('/kolmogorov_smirnov', methods=['GET', 'POST'])
-def kolmogorov_smirnov():
-    if request.method == 'POST':
-        # Get user input
-        distribution_type = request.form['distribution_type']
-        num_samples = int(request.form['num_samples'])
-
-        # Generate data
-        if distribution_type == 'normal':
-            data = norm.rvs(size=num_samples)
-        elif distribution_type == 'uniform':
-            data = np.random.uniform(size=num_samples)
-        elif distribution_type == 'standard':
-            data = np.random.randn(num_samples)
-        elif distribution_type == 'exponential':
-            data = expon.rvs(size=num_samples)
-        elif distribution_type == 'poisson':
-            data = poisson.rvs(mu=5, size=num_samples)
-        elif distribution_type == 'gamma':
-            data = gamma.rvs(a=5, size=num_samples)
-        else:
-            data = None
-
-        # Generate plot
-        if data is not None:
-            plt.hist(data, bins=30)
-            plt.title(f'{distribution_type.capitalize()} Distribution')
-            plt.xlabel('Value')
-            plt.ylabel('Frequency')
-            plt.savefig('static/plot.png')
-
-            # Render template with plot
-            return render_template('kolmogorov_smirnov.html', plot_url='static/plot.png')
-        else:
-            return render_template('kolmogorov_smirnov.html', error=True)
-    else:
-        return render_template('kolmogorov_smirnov.html')
-
-if __name__ == '__main__':
-    app.run(debug=True)

templates/hm.html

@@ -0,0 +1,92 @@
+<!DOCTYPE html>
+<html>
+<head>
+    <title>Statistical Analysis Application</title>
+    <style>
+        /* styles pour les boutons */
+        .btn {
+            display: inline-block;
+            padding: 12px 24px;
+            font-size: 16px;
+            font-weight: bold;
+            text-align: center;
+            text-decoration: none;
+            color: #fff;
+            background-color: #007bff;
+            border-radius: 4px;
+            transition: all 0.3s ease;
+        }
+
+        .btnn {
+            display: inline-block;
+            padding: 12px 24px;
+            font-size: 16px;
+            font-weight: bold;
+            text-align: center;
+            text-decoration: none;
+            color: #fff;
+            background-color: #007bff;
+            border-radius: 4px;
+            transition: all 0.3s ease;
+        }
+
+        .btnn:hover {
+            background-color: #0062cc;
+        }
+
+        /* styles pour le formulaire */
+        form {
+            max-width: 600px;
+            margin: 0 auto;
+            padding: 24px;
+            border: 1px solid #ddd;
+            border-radius: 4px;
+            box-shadow: 0 0 8px rgba(0, 0, 0, 0.1);
+        }
+
+        label {
+            display: block;
+            margin-bottom: 8px;
+            font-size: 16px;
+            font-weight: bold;
+        }
+
+        input[type="text"] {
+            width: 100%;
+            padding: 12px;
+            border-radius: 4px;
+            border: 1px solid #ddd;
+            font-size: 16px;
+        }
+    </style>
+</head>
+<body>
+<h1>Statistical Analysis Application</h1>
+<form action="/result" method="post">
+    <label for="test_statistique">Statistical Test</label>
+    <select name="test_statistique" id="test_statistique">
+        <option value="distribution">Distribution fitting</option>
+        <option value="t_test">Two-sample problem</option>
+        <option value="correlation_regression">Correlation/Regression</option>
+        <option value="classification">Classification</option>
+    </select>
+
+    <label for="sample_size">Sample size</label>
+    <input type="text" name="sample_size" id="sample_size" placeholder="Entrez la taille de l'échantillon">
+
+    <label for="group_size">Group size (for two-sample tests)</label>
+    <input type="text" name="group_size" id="group_size" placeholder="Entrez la taille du groupe">
+
+    <label for="significance">Meaning of results</label>
+    <select name="significance" id="significance">
+        <option value="significant">Statistically significant</option>
+        <option value="non_significant">Statistically not significant</option>
+        <option value="both">Both results</option>
+    </select>
+</form>
+<a href="http://127.0.0.1:8000">
+    <button type="submit" class="btnn">Analyze Data</button>
+</a>
+
+</body>
+</html>

templates/index.html

@@ -4,7 +4,7 @@
     <title>Plotting Distributions with Flask</title>
 </head>
 <body>
-    <h1>Plotting Distributions with Flask</h1>
+    <h1>Plotting Distributions</h1>
     {% if error %}
         <p style="color:red;">Invalid distribution type selected</p>
     {% endif %}

templates/rs.html

@@ -0,0 +1,28 @@
+<!DOCTYPE html>
+<html>
+  <head>
+    <title>Résultats de l'analyse statistique</title>
+  </head>
+  <body>
+    <h1>Résultats de l'analyse statistique</h1>
+    <p>Voici les résultats de l'analyse statistique :</p>
+    <table>
+      <tr>
+        <th>Test statistique</th>
+        <td>{{ test_statistique }}</td>
+      </tr>
+      <tr>
+        <th>Paramètres du test</th>
+        <td>{{ parametres }}</td>
+      </tr>
+      <tr>
+        <th>Résultat</th>
+        <td>{{ resultat }}</td>
+      </tr>
+      <tr>
+        <th>Conclusion</th>
+        <td>{{ conclusion }}</td>
+      </tr>
+    </table>
+  </body>
+</html>

test.py

@@ -0,0 +1,31 @@
+from flask import Flask, render_template, request
+
+app = Flask(__name__)
+
+
+# Définir la page d'accueil
+@app.route('/')
+def home():
+    return render_template('hm.html')
+
+
+# Définir la page des résultats
+@app.route('/results', methods=['POST'])
+def results():
+    # Récupérer les données entrées par l'utilisateur
+    test = request.form['test']
+    sample_size = request.form['sample_size']
+    group_size = request.form['group_size']
+    outcome_variable = request.form['outcome_variable']
+    significance = request.form['significance']
+
+    # Appeler les fonctions appropriées pour effectuer les calculs et les tests statistiques
+    # En fonction des données entrées par l'utilisateur
+
+    # Renvoyer les résultats à la page des résultats
+    return render_template('rs.html', test=test, sample_size=sample_size, group_size=group_size,
+                           outcome_variable=outcome_variable, significance=significance)
+
+
+if __name__ == '__main__':
+    app.run(debug=True)