Implementation of the SPADS shoreline prediction algorithm from the paper 'A Multiscale Approach to Shoreline Prediction' by Montano et. al. (2020).
Project description
pySPADS
re-implementation of SPADS model for coastal forecasting
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
pyspads-0.0.1.tar.gz
(16.1 kB
view details)
Built Distribution
Filter files by name, interpreter, ABI, and platform.
If you're not sure about the file name format, learn more about wheel file names.
Copy a direct link to the current filters
pyspads-0.0.1-py3-none-any.whl
(20.9 kB
view details)
File details
Details for the file pyspads-0.0.1.tar.gz.
File metadata
- Download URL: pyspads-0.0.1.tar.gz
- Upload date:
- Size: 16.1 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/5.1.1 CPython/3.11.4
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
2512cb5f1fe827a4c170bca5344a2c40bc6d23d58e234eeecf83e40dbb37cf96
|
|
| MD5 |
68814a26a352158e932e32285a22517b
|
|
| BLAKE2b-256 |
dde5cd6cf1f53c23b42c7ee10d43c7ff9c0c9b1031c8e31b15649a2d9a51ba6e
|
File details
Details for the file pyspads-0.0.1-py3-none-any.whl.
File metadata
- Download URL: pyspads-0.0.1-py3-none-any.whl
- Upload date:
- Size: 20.9 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/5.1.1 CPython/3.11.4
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
13f79d8a11522cc5a70d0900b19aa73ee623e4de71981ddacb6fd12f58c42285
|
|
| MD5 |
9a1a5a1064f656b8cc4ab25e8f637713
|
|
| BLAKE2b-256 |
a9732b5f6e9588305948954d69f0b015cdd9a362e8b567a78f9aedfc63206fe9
|