This api is built on top of the Django REST framework and can be used to fetch IMU and Ocean data captured by the Smartfin surfboard tool, analyzed and processed by UCSD's Engineers for Exploration Smartfin Research Team.
- python 3.8
- pythoon virtual environment (recommended) (set up)
- Django (3.1) (set up)
- Django REST Framework (set up)
pip install django
pip install djangorestframework
pip install -r requirements.txt
use the runserver commmand from manage.py to host the api on your local machine
python manage.py runserver
| Endpoint | HTTP Method | Result |
|---|---|---|
| ride | GET | Get list of api endpoints and functionaltiy |
| ride/rides | GET | Get list of ids of all rides currently in database |
| ride/fields | GET | Get list of ride's fields |
| Endpoint | HTTP Method | Result |
|---|---|---|
| ride/rides/rideId={str:rideId} | GET/POST/DELETE | Get, post, or delete ride data by id |
| ride/rides/rideId={str:rideId}/fields={str:fields} | GET | Get specified fields of a ride data entry. Specify multiple fields by separating them with a "," i.e. "heightSmartfin,startDate" |
| ride/rides/location={str:location} | GET | Get list of ride datas filtered by location. Location can be the name of the city or county the session took place |
| ride/rides/location={str:location}/fields={str:fields} | GET | Get list of ride data fields filtered by location. Specify multiple fields with "," separation |
| ride/rides/startDate={int:startDate}/endDate={int:endDate} | GET | Get list of ride datas that occured between the start and end date specified. Dates are formatted in unix time |
| ride/rides/startDate={int:startDate}/endDate={int:endDate}/fields={str:fields} | GET | Get list of ride datas that occured between the start and end date specified. Specify multiple fields with "," separation. Unix time dates. |
| Endpoint | HTTP Method | Result |
|---|---|---|
| rides/rideId={str:rideId}/dataframes/type={str:datatype} | GET | get a CSV file of a smartfin session's data. Datatype can be either 'motion' (IMU sensor data) or 'ocean' (ocean sensor data) |
| buoys | GET | get list of all currently deployed CDIP buoys |
import requests
response = requests.get('https://lit-sands-95859.herokuapp.com/ride')
data = response.json(){
'List api endpoints': '/',
'List ride fields': '/fields',
'Get all rides in db': '/rides',
'Get field of all rides in db': '/rides/fields=<str:fields>',
'Get single ride': '/rides/rideId=<str:rideId>',
'Filter rides by location': '/rides/location=<str:location>',
'Filter rides by date': '/rides/startDate=<str:startDate>,endDate=<str:endDate>',
'Get single ride attribute': 'rides/rideId=<str:rideId>/fields=<str:fields>',
'Get attributes of rides filtered by location': 'rides/location=<str:location>/fields=<str:fields>',
'Get attributes of rides filtered by date': 'rides/startDate=<str:startDate>,endDate=<str:endDate>/fields=<str:fields>',
'Update heights of all rides in database': 'update-heights',
'Get list of active CDIP buoys': 'buoys'
}
import requests
response = requests.get('https://lit-sands-95859.herokuapp.com/ride/rides/location={location}')
data = response.json()In the repository there is a jupyter notebook that tests all the endpoints of the API, which you can test each endpoint individually, specifying all parameters and filters.
The API allows you to download processed dataframes with IMU and Ocean data of every smartfin session collected directly from our sensors.
Contains all motion data from a smartfin session collected by the Smartfin's IMU sensors. Sample rate: 1s (1Hz) Time: Unix Time
Accelerometer:
- IMU A1: acceleration along x-axis (surfboard lengthwise direction) in m/s^2
- IMU A2: acceleration along y-axis (up/down direction) in m/s^2
- IMU A3: acceleration along z-axis (surfboard lengthwise direction) in m/s^
The rest of the fields are not used in our analysis currently, however each sensor number (1, 2, 3) correspond to the same directions as the accelerometer Gyroscope: +/- 1000 degrees/s 32.8 LSB/deg/s
- IMU G1: Negative → Roll left Positive → Roll right
- IMU G2: Positive → Left yaw/turn Negative → Right yaw/turn
- IMU G3: Positive → Upwards pitch / flip backwards Negative → Downwards pitch / flip forwards
Magnetometer Scale is +/- 32760 with signed 16-bits (+/-8180 in 14-bit mode) with full scale being +/- 4192 micro-Teslas Magnetometer: IMU M1, IMU M2, IMU M3
from io import BytesIO
import pandas as pd
csv_str = BytesIO(data['motionData'])
dataframe = pd.read_csv(csv_str)