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https://github.com/kotarot/sawatabi
Sawatabi is an application framework to develop and run stream-data-oriented Ising applications with quantum annealing.
https://github.com/kotarot/sawatabi
annealing ising ising-model python quantum-annealing stream-processing streaming
Last synced: about 2 months ago
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Sawatabi is an application framework to develop and run stream-data-oriented Ising applications with quantum annealing.
- Host: GitHub
- URL: https://github.com/kotarot/sawatabi
- Owner: kotarot
- License: apache-2.0
- Created: 2020-10-06T08:40:20.000Z (about 4 years ago)
- Default Branch: main
- Last Pushed: 2021-05-08T16:06:07.000Z (over 3 years ago)
- Last Synced: 2024-09-18T19:26:00.275Z (4 months ago)
- Topics: annealing, ising, ising-model, python, quantum-annealing, stream-processing, streaming
- Language: Python
- Homepage:
- Size: 11.2 MB
- Stars: 18
- Watchers: 3
- Forks: 7
- Open Issues: 1
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
# sawatabi
[](https://pypi.org/project/sawatabi/)
[](https://pypi.org/project/sawatabi/)
[](https://github.com/kotarot/sawatabi)
[](https://github.com/kotarot/sawatabi/actions?query=workflow%3Aci)
[](https://codecov.io/gh/kotarot/sawatabi)
[](https://github.com/kotarot/sawatabi/blob/main/LICENSE)
[](https://github.com/psf/black)
Sawatabi is an application framework to develop and run stream-data-oriented Ising applications with quantum annealing.
## Visualization of a Sample Sawatabi Application
The animation shows visualization of Outlier Detection Problem and its solutions obtained by a Sawatabi application.
The Ising fomulation for the Outlier Detection Problem proposed in [1] is used.
The left figure represents continuous input event data (stream-data) where blue points mean normal values and red points mean abnormal values (outliers).
The right figure represents solutions for Outlier Detection for each window of the input stream-data.
The boxes try to cover only normal points as much as possible.
[1] V. N. Smelyanskiy, E. G. Rieffel, S. I. Knysh, C. P. Williams, M. W. Johnson, M. C. Thom, W. G. Macready, and K. L. Pudenz, "A near-term quantum computing approach for hard computational problems in space exploration," arXiv:1204.2821 [quant-ph], 2012. Available: https://arxiv.org/abs/1204.2821
## Usage
### Installation
```
pip install sawatabi
```
### Sample Applications
This section only describes a sample application of NPP (Number Partition Problem), for other sample applications please see:
https://github.com/kotarot/sawatabi/tree/main/sample/algorithm
#### To run a sample NPP (Number Partition Problem) Sawatabi application on local environment
The following application reads numbers from a local file, run continuous annealing computations to solve NPP on local environment, and writes solutions to the stdout:
```
python sample/algorithm/npp_window.py --input="tests/algorithm/numbers_100.txt"
```
#### To run a sample NPP (Number Partition Problem) Sawatabi application on Google Cloud Dataflow using Google Cloud Pub/Sub
Please prepare your GCP service account credentials as `./gcp-key.json` and open three terminals.
**[1st terminal]** The Pub/Sub publisher continuously publishes numbers to the specified Pub/Sub topic:
```
GOOGLE_APPLICATION_CREDENTIALS="./gcp-key.json" \
python sample/pubsub/publish_pubsub.py \
--project= \
--topic= \
--interval=1.0 \
--random-number
```
where
- `` is your GCP project name, and
- `` is your Google Cloud Pub/Sub topic name to publish messages (numbers) to.
**[2nd terminal]** The Pub/Sub subscriber continuously subscribes solutions from the specified Pub/Sub subscription:
```
GOOGLE_APPLICATION_CREDENTIALS="./gcp-key.json" \
python sample/pubsub/subscribe_pubsub.py \
--project= \
--subscription=
```
where
- `` is your GCP project name, and
- `` is your Google Cloud Pub/Sub subscription name to subscribe messages (solutions) from.
**[3rd terminal]** The following application reads numbers from the given Pub/Sub topic, run continuous annealing computations to solve NPP on Google Cloud Dataflow, and writes solutions to the given Pub/Sub topic:
```
GOOGLE_APPLICATION_CREDENTIALS="./gcp-key.json" \
python sample/algorithm/npp_window.py \
--project= \
--input-topic= \
--output-topic= \
--dataflow \
--dataflow-bucket=
```
where
- `` is your GCP project name,
- `` is your Google Cloud Pub/Sub topic name of input,
- `` is your Google Cloud Pub/Sub topic name of output, and
- ` is your GCS bucket name for Dataflow temporary files.
### Solvers
#### If you would like to use the D-Wave solver
Please give credentials directly to the `sawatabi.solver.DWaveSolver()` constructor arguments, or set up a config using dwave-cloud-client:
```
$ dwave config create
Configuration file not found; the default location is: /path/to/your/location/dwave.conf
Configuration file path [/path/to/your/location/dwave.conf]:
Configuration file path does not exist. Create it? [y/N]: y
Profile (create new) [prod]: dev
API endpoint URL [skip]: xxxxxxxxxxxxxxxx
Authentication token [skip]: xxxxxxxxxxxxxxxx
Default client class [skip]:
Default solver [skip]: Advantage_system1.1
Configuration saved.
```
#### If you would like to use the Fixstars GPU solver (Optigan)
Please give credentials directly to the `sawatabi.solver.OptiganSolver()` constructor arguments, or set up a API Token in `~/.optigan.yml`:
```
api:
endpoint: http://optigan.example.com/method
token: XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX
```
### For Contributions to the Sawatabi Framework
Please set up a development environment as follows:
```
python -m venv venv
source venv/bin/activate
pip install --upgrade pip
pip install --editable ".[dev]"
```
## Acknowledgement
This work is supported by the MITOU Target program from Information-technology Promotion Agency, Japan (IPA).