gerg_plotting 0.0.17

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GERG Plotting

Data plotting package for GERG
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Table of Contents

1. About The Project
   • Built With
2. Getting Started
   • Dependencies
   • Installation
3. Usage
4. Contributing
5. License
6. Contact
7. Acknowledgments

About The Project

This project was created to streamline and standardize the process of generating plots at GERG.

Built With

Getting Started

There are two ways to get started

1. Create a fresh virtual environment using your favorite method and install the package
2. Use an already established virtual environment and install the package

Dependencies

I have provided a list of the dependencies and their versions below.

List of dependencies:

• python = 3.12
• numpy = 2.0.0
• pandas = 2.2.2
• matplotlib = 3.9.1
• xarray = 2024.6.0
• attrs = 23.2.0
• netcdf4 = 1.7.1.post1
• cmocean = 4.0.3
• scipy = 1.14.0
• mayavi = 4.8.2

Installation

1. Activate your virtual environment
2. Use pip to install pip install gerg_plotting

Usage

Plot data at GERG using Python.

Example: Create a histogram for U current vectors

import xarray as xr
from gerg_plotting import Buoy, Histogram

# Open in the dataset using xarray
ds = xr.open_dataset('buoy.nc')
# Convert the dataset variable to a flat pandas dataframe
df = ds['u'].to_dataframe().reset_index()

# Initialize the buoy instrument data container
buoy = Buoy(u_current=df['u'])

# Initialize the histogram plotter
hist = Histogram(instrument=buoy)
# Plot the 1-d histograms for u and v currents
hist.plot(var='u_current',bins=100)
hist.ax.set_title('Current Vector U')

Example: Create A GIf of the Map of CTD Missions

import pandas as pd
import matplotlib.pyplot as plt
from gerg_plotting.SurfacePlot import SurfacePlot
from gerg_plotting.SpatialInstruments import Bounds,CTD
from gerg_plotting.Animator import Animator

def ctd_map(cruise,df:pd.DataFrame,bounds:Bounds):
    # Select the data you wish to plot for each frame
    df_cruise = df.loc[df['Cruise']==cruise]
    # Initalize the instrument data container
    ctd = CTD(lat=df_cruise['Latitude'],
              lon=df_cruise['Longitude'],
              depth=df_cruise['CTD BinDepth (m)'],
              time=df_cruise['Date_Time'],
              temperature=df_cruise['Temp (deg C)'],
              salinity=df_cruise['Salinity (PSU)'])
    
    # Initalize the surface plot class the bounds parameter is optional
    surfaces = SurfacePlot(instrument=ctd,bounds=bounds)
    # Create a map of the sample sites
    surfaces.map()
    surfaces.ax.set_title(f'Cruise {cruise}')
    # Optional, if you would like to show the figures as they are created
    plt.show()
    # Must return the surface plot class figure attribute
    return surfaces.fig

# Read in the data
df = pd.read_csv('../test_data/ctd.csv',parse_dates=['Date_Time'])
# Create the interable to loop over during the gif creation
# In this case we are showing each cruise as individual frames
cruises = list(set(df['Cruise']))  # Get the unique cruise values and return them as a list

# Optional, but a good idea so that you can specify the viewing location
bounds = Bounds(lat_min=27,
                lat_max=31,
                lon_max=-88,
                lon_min=-94,
                depth_bottom=150,
                depth_top=None)

# Create the animation gif by generating frames from the cruises iterable and save it to the gif_filename
Animator().animate(plotting_function=ctd_map,interable=cruises,fps=1,iteration_param='cruise',gif_filename='ctd_map.gif',df=df,bounds=bounds)

Contributing

Contributions are what make the open source community such an amazing place to learn, inspire, and create. Any contributions you make are greatly appreciated.

If you have a suggestion that would make this better, please fork the repo and create a pull request. You can also simply open an issue with the tag "enhancement".

1. Fork the Project
2. Create your Feature Branch (git checkout -b feature/AmazingFeature)
3. Commit your Changes (git commit -m 'Add some AmazingFeature')
4. Push to the Branch (git push origin feature/AmazingFeature)
5. Open a Pull Request

License

Distributed under the MIT License. See LICENSE for more information.

Contact

Alec Krueger - [e-mail]

Project Link: https://github.com/alecmkrueger/gerg_plotting

Acknowledgments

• Alec Krueger, Texas A&M University, Geochemical and Environmental Research Group, [e-mail]

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