Metadata-Version: 2.4
Name: fink_anomaly_detection_model
Version: 0.4.67
Summary: Fink SNAD Anomaly Detection Model
Author-email: timofei.psheno@gmail.com
Requires-Python: >=3.7
Description-Content-Type: text/markdown
Requires-Dist: scikit-learn>=1.3.1
Requires-Dist: numpy==1.26.4
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Requires-Dist: onnx>=1.14.0
Requires-Dist: scipy>=1.10.1
Requires-Dist: onnx==1.16.1
Requires-Dist: skl2onnx>=1.15.0
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Requires-Dist: slack_sdk
Requires-Dist: config
Requires-Dist: configparser
Requires-Dist: fink_science==3.13.3
Requires-Dist: pyspark==3.1.3
Requires-Dist: light_curve
Requires-Dist: psutil
Requires-Dist: seaborn==0.13.2
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Dynamic: author-email
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Dynamic: summary

# Fink anomaly detection model

Здесь пока куча косяков, в обозримом будущем постараюсь их поправить

A set of modules for training models for finding anomalies in photometric data. There are currently two entry points via the console: _fink_ad_model_train_ and _get_anomaly_reactions_.

##  fink_ad_model_train

The module trains the AADForest model using expert reactions from the C055ZJJ6N2AE channels in Slack and -1001898265997 in Telegram. It creates the following files:
- _g_means.csv and _r_means.csv -- averages over the training dataset;
- _reactions_g.csv and _reactions_r.csv -- training datasets for additional training of the AADForest algorithm, based on expert reactions from Slack and Telegram channels;
- forest_g_AAD.onnx -- model for _g filter
- forest_r_AAD.onnx -- model for _r filter

**optional arguments:**

  --dataset_dir DATASET_DIR
                        Input dir for dataset (default: './lc_features_20210617_photometry_corrected.parquet')
						
  --n_jobs N_JOBS       
						Number of threads (default: -1)


**usage**: fink_ad_model_train [-h] [--dataset_dir DATASET_DIR] [--n_jobs N_JOBS]


## get_anomaly_reactions



Uploading anomaly reactions from messengers. It creates the following files:
- _reactions_g.csv and _reactions_r.csv -- training datasets for additional training of the AADForest algorithm, based on expert reactions from Slack and Telegram channels;



**optional arguments:**

  --slack_channel SLACK_CHANNEL
                        Slack Channel ID (default: 'C055ZJJ6N2AE')
  
  --tg_channel TG_CHANNEL
                        Telegram Channel ID (default: -1001898265997)

**usage**: get_anomaly_reactions [-h] [--slack_channel SLACK_CHANNEL]
                             [--tg_channel TG_CHANNEL]
