# ai-replication
## Checkout at: **https://pypi.org/manage/project/aireplication/releases/**
## Usage
```python
from aireplication.ultils.data import TimeSeriesGenerator, Dataset
config = {"dataset_name": "GYEONGGI2955",
"features": ["Amount of Consumption", "Temperature"],
"prediction_feature": "Amount of Consumption", # Feature to use for prediction
"input_width": 168,
"output_length": 1,
"train_ratio": 0.9
}
dataset = Dataset(dataset_name=config["dataset_name"])
# data = dataset.dataloader.export_a_single_sequence()
data = dataset.dataloader.export_the_sequence(config["features"])
print("Building time series generator...")
tsf = TimeSeriesGenerator(data=data,
config=config,
normalize_type=1,
shuffle=False)
# Get model
model = get_model(model_name=args.model_name,
config=config)
# Train model
history = model.fit(x=tsf.data_train[0], # [number_recoder, input_len, number_feature]
y=tsf.data_train[1], # [number_recoder, output_len, number_feature]
validation_data=tsf.data_valid)
```
## List of dataset is available
```yaml
config1 = {"dataset_name": "GYEONGGI2955",
"features": ["Amount of Consumption", "Temperature"],
"prediction_feature": "Amount of Consumption", # Feature to use for prediction
"input_width": 168,
"output_length": 1,
"train_ratio": 0.9
}
config2 = {"dataset_name": "CNU_ENGINEERING_7",
"features": [ "temperatures", "humidity", "pressure","energy" ] # Features to use for training
prediction_feature: "energy", # Feature to use for prediction
"input_width": 168,
"output_length": 1,
"train_ratio": 0.9
}
```
## Publishing the package
```shell
pip install twine
python setup.py sdist
twine upload dist/*
```
**- Note: Testing case:**
```shell
twine upload --repository testpypi dist/*
```
Raw data
{
"_id": null,
"home_page": "https://github.com/andrewlee1807/ai-replicate",
"name": "aireplication",
"maintainer": "",
"docs_url": null,
"requires_python": "",
"maintainer_email": "",
"keywords": "python,blackhole,aireplication",
"author": "Andrew",
"author_email": "andrewlee1807@gmail.com",
"download_url": "https://files.pythonhosted.org/packages/e4/aa/65ea223b2a434adb72f4f564eefb865012aee196ee9725e24009a125cf5a/aireplication-0.0.4.tar.gz",
"platform": null,
"description": "# ai-replication\r\n\r\n## Checkout at: **https://pypi.org/manage/project/aireplication/releases/**\r\n\r\n## Usage\r\n```python\r\nfrom aireplication.ultils.data import TimeSeriesGenerator, Dataset\r\n\r\nconfig = {\"dataset_name\": \"GYEONGGI2955\",\r\n \"features\": [\"Amount of Consumption\", \"Temperature\"],\r\n \"prediction_feature\": \"Amount of Consumption\", # Feature to use for prediction\r\n \"input_width\": 168,\r\n \"output_length\": 1,\r\n \"train_ratio\": 0.9\r\n }\r\n\r\ndataset = Dataset(dataset_name=config[\"dataset_name\"])\r\n# data = dataset.dataloader.export_a_single_sequence()\r\ndata = dataset.dataloader.export_the_sequence(config[\"features\"])\r\n\r\nprint(\"Building time series generator...\")\r\ntsf = TimeSeriesGenerator(data=data,\r\n config=config,\r\n normalize_type=1,\r\n shuffle=False)\r\n\r\n# Get model \r\nmodel = get_model(model_name=args.model_name,\r\n config=config)\r\n\r\n# Train model\r\nhistory = model.fit(x=tsf.data_train[0], # [number_recoder, input_len, number_feature]\r\n y=tsf.data_train[1], # [number_recoder, output_len, number_feature]\r\n validation_data=tsf.data_valid)\r\n```\r\n\r\n## List of dataset is available\r\n```yaml\r\nconfig1 = {\"dataset_name\": \"GYEONGGI2955\",\r\n \"features\": [\"Amount of Consumption\", \"Temperature\"],\r\n \"prediction_feature\": \"Amount of Consumption\", # Feature to use for prediction\r\n \"input_width\": 168,\r\n \"output_length\": 1,\r\n \"train_ratio\": 0.9\r\n }\r\n\r\nconfig2 = {\"dataset_name\": \"CNU_ENGINEERING_7\",\r\n \"features\": [ \"temperatures\", \"humidity\", \"pressure\",\"energy\" ] # Features to use for training\r\n prediction_feature: \"energy\", # Feature to use for prediction\r\n \"input_width\": 168,\r\n \"output_length\": 1,\r\n \"train_ratio\": 0.9\r\n }\r\n```\r\n## Publishing the package\r\n```shell\r\npip install twine\r\npython setup.py sdist\r\ntwine upload dist/*\r\n```\r\n\r\n**- Note: Testing case:**\r\n```shell\r\ntwine upload --repository testpypi dist/*\r\n```\r\n\r\n",
"bugtrack_url": null,
"license": "Apache-2.0 license",
"summary": "Private API for Andrew",
"version": "0.0.4",
"split_keywords": [
"python",
"blackhole",
"aireplication"
],
"urls": [
{
"comment_text": "",
"digests": {
"blake2b_256": "e4aa65ea223b2a434adb72f4f564eefb865012aee196ee9725e24009a125cf5a",
"md5": "d0eb8917be5e741edd55e12ab2428f46",
"sha256": "0234110b57e57b4bac9375083e138afa4306a8e08c50915279a6885227fd2dfd"
},
"downloads": -1,
"filename": "aireplication-0.0.4.tar.gz",
"has_sig": false,
"md5_digest": "d0eb8917be5e741edd55e12ab2428f46",
"packagetype": "sdist",
"python_version": "source",
"requires_python": null,
"size": 11762,
"upload_time": "2023-04-25T08:30:30",
"upload_time_iso_8601": "2023-04-25T08:30:30.762300Z",
"url": "https://files.pythonhosted.org/packages/e4/aa/65ea223b2a434adb72f4f564eefb865012aee196ee9725e24009a125cf5a/aireplication-0.0.4.tar.gz",
"yanked": false,
"yanked_reason": null
}
],
"upload_time": "2023-04-25 08:30:30",
"github": true,
"gitlab": false,
"bitbucket": false,
"github_user": "andrewlee1807",
"github_project": "ai-replicate",
"travis_ci": false,
"coveralls": false,
"github_actions": false,
"lcname": "aireplication"
}
JSON
