COSMOS

To handle the form submission and make the prediction using Python, you need to create a server-side script using a web framework like Flask.

Table of Contents

• Introduction
• Installation
• Usage
• Folder Structure
• Dependencies
• Contributing
• License

Introduction

This project is a Flask web application that allows users to fill in the inputs and check whether the planet is habitable or not.

Installation

Follow these steps to set up and run the project:

1. Clone the repository:

   git clone https://github.com/Exo-planetary/flask-project.git

2. Navigate to the project directory:

   cd Cosmos

3. Install the required dependencies:

   pip install -r requirements.txt

4. Run the Flask application:

   python app.py

   The application will be accessible at http://localhost:5000/.

Usage

1. Open your web browser and go to http://localhost:5000/.

Folder Structure

Explain the purpose of each major folder in your project:

• web_app: Contains the Flask application code.
• templates: Contains HTML templates for rendering pages.
• mongodb_code: Contains utility code related to MongoDB operations.

Dependencies

List the main dependencies used in your project:

• Flask
• pymongo

Contributing

Feel free to contribute to this project by following these steps:

1. Fork the repository.
2. Create a new branch: git checkout -b feature/features
3. Commit your changes: git commit -m 'Add your features'
4. Push to the branch: git push origin feature/fetures
5. Open a pull request.

from django.test import TestCase from django.urls import reverse

3. Create a test class that inherits from `TestCase`:
```python
class IndexPageTests(TestCase):
    def test_index_page_links(self):
        # Test the links in the index page
        response = self.client.get(reverse('index'))
        self.assertEqual(response.status_code, 200)
        self.assertContains(response, '<a href="/templates/explore.html#form-section1">Radial Velocity</a>')
        self.assertContains(response, '<a href="/templates/explore.html#form-section2">Transit Method</a>')
        self.assertContains(response, '<a href="/templates/explore.html#form-section3">Direct Imaging</a>')
        self.assertContains(response, '<a href="/templates/explore.html#form-section4">Biosignature</a>')

4. In the test_index_page_links method, we make a GET request to the index page using the self.client.get method. Then we assert that the response status code is 200 (indicating a successful request) and that the response contains the expected links.

5. Finally, run the tests by executing the following command in your terminal:

   python manage.py test

Here's the updated code with the tests included:

Enter the start time (days): 0 Enter the end time (days): 10 Enter transit light curve values (comma-separated, e.g., 1.0, 0.8, 0.6, 0.9, 1.0): 1.0, 0.7, 0.4, 0.8, 1.0 Enter the transit duration (days): 2 Do you want to add realistic noise? (yes/no): no Enter depth threshold for transit confirmation: 0.2 Enter duration threshold for transit confirmation: 1.0

Test Case 1: Clear Transit Signal

Input: Start time: 0 End time: 10 Transit light curve values: 1.0, 0.8, 0.6, 0.9, 1.0 Transit duration: 2 Add noise: No Depth threshold: 0.2 Duration threshold: 1.0 Expected Output: Exoplanet presence confirmed

Test Case 2: No Transit Signal

Input: Start time: 0 End time: 10 Transit light curve values: 1.0, 1.0, 1.0, 1.0, 1.0 Transit duration: 2 Add noise: No Depth threshold: 0.2 Duration threshold: 1.0 Expected Output: No exoplanet was confirmed based on the provided transit data

Test Case 3: Noisy Signal with Thresholds Met

Input: Start time: 0 End time: 10 Transit light curve values: 1.0, 0.7, 0.4, 0.8, 1.0 Transit duration: 2 Add noise: Yes (Noise level: 0.1) Depth threshold: 0.3 Duration threshold: 1.5 Expected Output: Exoplanet presence confirmed

Test Case 4: Noisy Signal with Thresholds Not Met

Input: Start time: 0 End time: 10 Transit light curve values: 1.0, 0.7, 0.4, 0.8, 1.0 Transit duration: 2 Add noise: Yes (Noise level: 0.1) Depth threshold: 0.4 Duration threshold: 2.0 Expected Output: No exoplanet was confirmed based on the provided transit data

Test Case 5: Large Duration Transit Signal

Input: Start time: 0 End time: 20 Transit light curve values: 1.0, 0.8, 0.6, 0.4, 0.3, 0.4, 0.6, 0.8, 1.0 Transit duration: 8 Add noise: Yes (Noise level: 0.05) Depth threshold: 0.5 Duration threshold: 5.0 Expected Output: Exoplanet presence confirmed

Sample input data

sample_input = pd.DataFrame({ 'pl_orbper': [10.0], 'pl_rade': [1.5], 'pl_orbeccen': [0.1], 'pl_orbincl': [89.0], 'pl_tranmid': [2459000.0], 'pl_imppar': [0.02], 'pl_trandep': [0.01], 'pl_trandur': [2.0], 'pl_ratdor': [0.01], 'pl_ratror': [0.1], 'sy_vmag': [10.0], 'sy_kmag': [8.0] })

Standardize the sample input

sample_input_scaled = scaler.transform(sample_input)

Make predictions using the trained model

sample_output = model.predict(sample_input_scaled)

print("Sample Input:") print(sample_input) print("\nPredicted Output:") print(sample_output)