Penalized Maximum-Entropy Dasymetric Modeling (P-MEDM) in Python.
Project description
PyMEDM: Penalized Maximum-Entropy Dasymetric Modeling (P-MEDM) in Python
This is a GPU-ready Python port of PMEDMrcpp via jax and jaxopt.
References
- Leyk, S., Nagle, N. N., & Buttenfield, B. P. (2013). Maximum entropy dasymetric modeling for demographic small area estimation. Geographical Analysis, 45(3), 285-306.
- Nagle, N. N., Buttenfield, B. P., Leyk, S., & Spielman, S. (2014). Dasymetric modeling and uncertainty. Annals of the Association of American Geographers, 104(1), 80-95.
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
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
File details
Details for the file pymedm-2.2.7.tar.gz.
File metadata
- Download URL: pymedm-2.2.7.tar.gz
- Upload date:
- Size: 1.4 MB
- Tags: Source
- Uploaded using Trusted Publishing? Yes
- Uploaded via: twine/6.1.0 CPython/3.13.7
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
f7c8decd1099de25d4e66016612edbdb8d6b0580cdb955d5f6b9d64ec480554c
|
|
| MD5 |
841bfa63a899cd15970a7eb5c7f0a456
|
|
| BLAKE2b-256 |
db339dc5a8bc4e981e5006e9c6516750fc48e7239ff6a2260866ab5babee510a
|
Provenance
The following attestation bundles were made for pymedm-2.2.7.tar.gz:
Publisher:
release_to_pypi.yml on likeness-pop/pymedm
-
Statement:
-
Statement type:
https://in-toto.io/Statement/v1 -
Predicate type:
https://docs.pypi.org/attestations/publish/v1 -
Subject name:
pymedm-2.2.7.tar.gz -
Subject digest:
f7c8decd1099de25d4e66016612edbdb8d6b0580cdb955d5f6b9d64ec480554c - Sigstore transparency entry: 932892814
- Sigstore integration time:
-
Permalink:
likeness-pop/pymedm@86faa4c6f4eb8ce81e95f10d8ea5519bd9ea2ec4 -
Branch / Tag:
refs/tags/v2.2.7 - Owner: https://github.com/likeness-pop
-
Access:
public
-
Token Issuer:
https://token.actions.githubusercontent.com -
Runner Environment:
github-hosted -
Publication workflow:
release_to_pypi.yml@86faa4c6f4eb8ce81e95f10d8ea5519bd9ea2ec4 -
Trigger Event:
push
-
Statement type:
File details
Details for the file pymedm-2.2.7-py3-none-any.whl.
File metadata
- Download URL: pymedm-2.2.7-py3-none-any.whl
- Upload date:
- Size: 25.7 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? Yes
- Uploaded via: twine/6.1.0 CPython/3.13.7
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
60f1729057606f457d89d2711d2f4e3d14f43e8bb677b98d815fc5e096ee89db
|
|
| MD5 |
af9073b14ad6b0544005795fea148966
|
|
| BLAKE2b-256 |
80f6ba9a918d1202d59190c66509eabff15695aacd243339b33c6e64bca905c2
|
Provenance
The following attestation bundles were made for pymedm-2.2.7-py3-none-any.whl:
Publisher:
release_to_pypi.yml on likeness-pop/pymedm
-
Statement:
-
Statement type:
https://in-toto.io/Statement/v1 -
Predicate type:
https://docs.pypi.org/attestations/publish/v1 -
Subject name:
pymedm-2.2.7-py3-none-any.whl -
Subject digest:
60f1729057606f457d89d2711d2f4e3d14f43e8bb677b98d815fc5e096ee89db - Sigstore transparency entry: 932892888
- Sigstore integration time:
-
Permalink:
likeness-pop/pymedm@86faa4c6f4eb8ce81e95f10d8ea5519bd9ea2ec4 -
Branch / Tag:
refs/tags/v2.2.7 - Owner: https://github.com/likeness-pop
-
Access:
public
-
Token Issuer:
https://token.actions.githubusercontent.com -
Runner Environment:
github-hosted -
Publication workflow:
release_to_pypi.yml@86faa4c6f4eb8ce81e95f10d8ea5519bd9ea2ec4 -
Trigger Event:
push
-
Statement type: