PySeas

PySeas

PySeas Purpose

The world's oceans are an untapped wealth of information that we are only barely beginning to understand. More of the ocean has been untouched by man than any other place on earth.

Using PySeas as a enVita Artist Agent

Our first application of this project is to create art with the images from these buoys, and use them to generate a tapestry of the beautiful oceans.

Previously, our code was written as shown below, as an outline for a class structure. We will keep the class structure, but we will be using a different approach to the project.

classBuoyImage:
def__init__(self, location, weather_conditions, image_data):
self.location=locationself.weather_conditions=weather_conditionsself.image_data=image_datadefget_images(self):
# Retrieve the images from the NOAA APIpassdefstitch_images(self):
# Stitch the images togetherpassdefblend_images(self):
# Blend the images over timepass# Create a GAN to generate imagesclassGAN:
def__init__(self, image_data):
self.image_data=image_datadefgenerate_images(self):
# Generate images using a GANpassdefblend_images(self):
# Blend the images over timepassclassPanoramicImage:
def__init__(self, stitched_image_data, horizon_line, time_lapse_data):
self.stitched_image_data=stitched_image_dataself.horizon_line=horizon_lineself.time_lapse_data=time_lapse_datadefblend_images(self):
# Blend the images over timepassdefdetect_horizon(self):
# Detect the horizon linepassdefcreate_time_lapse(self):
# Create a time-lapse animationpassclassWebsite:
def__init__(self, layout, content):
self.layout=layoutself.content=contentdefgenerate_html(self):
# Generate the HTML for the websitepassdefgenerate_css(self):
# Generate the CSS for the websitepassdefgenerate_javascript(self):
# Generate the JavaScript for the websitepass

Phase One: Sunrise over the Sea

Create sunsets over the sea using the images from the NOAA API.

Phase Two: The Raging of the Storm

Find images of storms and hurricanes, and create a time-lapse of the storm.

PySeas

PySeas is a Python project aimed at analyzing buoy data. The project is structured into several directories, each serving a specific purpose in the data analysis pipeline.

Directories

src: This directory contains the main scripts of the project. It includes phase_one.py and phase_two.py, which perform initial data loading, cleaning, and visualization.

notebooks: This directory contains Jupyter notebooks that demonstrate the usage of the project modules. For example, PyBuoy.ipynb shows how to use the PyBuoy module to fetch and analyze buoy data.

utils: This directory typically contains utility scripts used across the project. These can include data processing functions, helper functions, and other reusable code snippets.

How to Run the Program

• Clone the repository to your local machine.
• Navigate to the project directory.
• Install the required dependencies listed in the requirements.txt file. You can do this by running pip install -r requirements.txt in your terminal.
• Run the scripts in the src directory. For example, you can run python src/phase_one.py to execute the first phase of the data analysis pipeline.

License

PySeas is licensed under the MIT License. See LICENSE for more information.

Contributing

Contributions are welcome! Please see CONTRIBUTING.md for more information.

Acknowledgements

The Sunset Tapestry