Gym-style API
The domanin features a continuos state and a dicrete action space.
The environment initializes:
- cross-sectional dataset with variables X_a, X_s, Y and N observations;
- logit model fitted on the dataset, retrieving parameters \theta_0, \theta_1, \theta_2;
The agent:
- sees all patients;
- predict risk of admission \rho, using initialized parameters
- sample an action (50 possible values between -2 and 2)
- if risk > 0.2:
- replace Xa by g, where g(\rho, Xa) is obtained using the patient's risk and Xa value
- else:
- do not intervene, X_a stays the same
- give reward equal to average risk of admission, using predicted Y, initial parameters and sampled values
To install
-
cd gym-discrete
-
!pip install gym-discrete
-
import gym_discrete
-
env =gym.make('discrete-v0')
To change version
- change version to, e.g., 1.0.7 from setup.py file
- git clone https://github.com/claudia-viaro/gym-discrete.git
- cd gym-discrete
- python setup.py sdist bdist_wheel
- twine check dist/*
- twine upload --repository-url https://upload.pypi.org/legacy/ dist/*
1 maintainer
Release files for gym-discrete 1.5.6
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| gym_discrete-1.5.6.tar.gz | 4.9 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| gym_discrete-1.5.6-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 10.4 kB
Release files / gym_discrete-1.5.6.tar.gz
| Download URL | gym_discrete-1.5.6.tar.gz |
|---|---|
| Size | 4.9 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
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twine/3.4.1 importlib_metadata/4.6.1 pkginfo/1.6.1 requests/2.24.0 requests-toolbelt/0.9.1 tqdm/4.50.2 CPython/3.8.5
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Release files / gym_discrete-1.5.6-py3-none-any.whl
| Download URL | gym_discrete-1.5.6-py3-none-any.whl |
|---|---|
| Size | 5.5 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/3.4.1 importlib_metadata/4.6.1 pkginfo/1.6.1 requests/2.24.0 requests-toolbelt/0.9.1 tqdm/4.50.2 CPython/3.8.5
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