{"id":19603915,"url":"https://github.com/divelab/sensors","last_synced_at":"2025-07-23T23:02:35.216Z","repository":{"id":107289915,"uuid":"295215465","full_name":"divelab/sensors","owner":"divelab","description":null,"archived":false,"fork":false,"pushed_at":"2020-09-13T18:56:55.000Z","size":22208,"stargazers_count":1,"open_issues_count":0,"forks_count":0,"subscribers_count":0,"default_branch":"master","last_synced_at":"2025-02-26T15:48:54.163Z","etag":null,"topics":[],"latest_commit_sha":null,"homepage":null,"language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/divelab.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":null,"code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null}},"created_at":"2020-09-13T18:46:37.000Z","updated_at":"2024-05-22T20:09:49.000Z","dependencies_parsed_at":null,"dependency_job_id":"47bf1c6d-4445-4ec0-9a04-b46f89e40ec6","html_url":"https://github.com/divelab/sensors","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/divelab/sensors","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/divelab%2Fsensors","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/divelab%2Fsensors/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/divelab%2Fsensors/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/divelab%2Fsensors/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/divelab","download_url":"https://codeload.github.com/divelab/sensors/tar.gz/refs/heads/master","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/divelab%2Fsensors/sbom","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":264506242,"owners_count":23619002,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":[],"created_at":"2024-11-11T09:33:39.440Z","updated_at":"2025-07-10T00:34:55.857Z","avatar_url":"https://github.com/divelab.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"\n# Attention Based Molecule Property Prediction\n\nCreated by [Lei Cai](https://www.eecs.wsu.edu/~lcai/).\n\n## Introduction\n\nWe employ Bi-direction GRU and attention module to predict the property of a given molecule. The overal framework can be shown as \n\n![model](./figures/framework.png)\n\n\n## System requirement\n\n#### Programming language\nPython 2.7 +\n\n#### Python Packages\nTensorflow , Numpy\n\n#### Data Formate\n\nThe molecule is converted to SMILE string as input for our model.\n\nWe release the two datasets for emission and excitation prediction tasks.\n\nemission_input.txt contains SMILE strings to train the model.\nemission_output.txt contains the corresponding emission value for the molecule in emission_input.txt\n\nemission_input_test.txt contains SMILE strings to test the model.\nemission_output_test.txt contains the corresponding emission value for the molecule in emission_input_test.txt\n\n## Training \n\n#### Train the network\n\n```\npython sensor_train_emission.py --resume False --save_model True --test False\n```\n\n#### Predict the property using an existing model\n\n```\npython sensor_train_emission.py --resume True --test True --test_path \"path to the model\"\n```\n\n## Model for Prediction\n\nWe provide two well trained model for the two tasks.\n\nFor emission prediction tasks, the results can be obtained by:\n\n```\npython sensor_train_emission.py --resume True --test True --test_path ./work_dir/run1586726418/checkpoints/SensorRNN.ckpt-15\n```\n\nFor excitation prediction tasks, the results can be obtained by:\n\n```\npython sensor_train_excitation.py --resume True --test True --test_path ./work_dir/run1582060157/checkpoints/SensorRNN.ckpt-16\n```\n\n\n## Acknowlegdements\n\nPart of code borrow from https://github.com/snakeztc/NeuralDialog-CVAE. Thanks for their excellent work!\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fdivelab%2Fsensors","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fdivelab%2Fsensors","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fdivelab%2Fsensors/lists"}