Add conda environment and installation
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README.md
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README.md
@ -15,17 +15,47 @@ This repo contains notebooks and scripts demonstrating how to:
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This code is based on the [pick-benchmark](https://github.com/seisbench/pick-benchmark), the repository accompanying the paper:
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This code is based on the [pick-benchmark](https://github.com/seisbench/pick-benchmark), the repository accompanying the paper:
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[Which picker fits my data? A quantitative evaluation of deep learning based seismic pickers](https://doi.org/10.1029/2021JB023499)
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[Which picker fits my data? A quantitative evaluation of deep learning based seismic pickers](https://doi.org/10.1029/2021JB023499)
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### Before running
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### Installation method 1
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Please download and install [Mambaforge](https://github.com/conda-forge/miniforge#mambaforge) following the [official guide](https://github.com/conda-forge/miniforge#install).
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After successful installation and within the Mambaforge environment please run following commands:
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```
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git clone ssh://git@git.plgrid.pl:7999/eai/platform-demo-scripts.git
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cd platform-demo-scripts
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mambaforge env create -f environment.yml
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```
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This will create a conda environment named `platform-demo-scripts` with all required packages installed.
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To run the notebooks and scripts from this repository it is necessary to activate the `platform-demo-scripts` environment by running:
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```
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conda activate platform-demo-scripts
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```
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### Installation method 2
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Please [install Poetry](https://python-poetry.org/docs/#installation), a tool for dependency management and packaging in Python.
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Please [install Poetry](https://python-poetry.org/docs/#installation), a tool for dependency management and packaging in Python.
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Then we will use only Poetry for creating Python environment and installing dependencies.
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Then we will use only Poetry for creating Python environment and installing dependencies.
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Install all dependencies with poetry, run:
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```
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poetry install
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```
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To run the notebooks and scripts from this repository it is necessary to activate the poetry environment by running:
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```
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poetry shell
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```
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### Usage
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### Usage
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1. Install all dependencies with poetry, run:
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1. Prepare .env file with content:
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`poetry install`
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2. Prepare .env file with content:
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```
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```
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WANDB_HOST="https://epos-ai.grid.cyfronet.pl/"
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WANDB_HOST="https://epos-ai.grid.cyfronet.pl/"
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WANDB_API_KEY="your key"
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WANDB_API_KEY="your key"
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@ -33,15 +63,11 @@ Then we will use only Poetry for creating Python environment and installing depe
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WANDB_PROJECT="training_seisbench_models_on_igf_data"
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WANDB_PROJECT="training_seisbench_models_on_igf_data"
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BENCHMARK_DEFAULT_WORKER=2
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BENCHMARK_DEFAULT_WORKER=2
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3. Transform data into seisbench format. (unofficial)
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2. Transform data into seisbench format. (unofficial)
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* Download original data from the [drive](https://drive.google.com/drive/folders/1InVI9DLaD7gdzraM2jMzeIrtiBSu-UIK?usp=drive_link)
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* Download original data from the [drive](https://drive.google.com/drive/folders/1InVI9DLaD7gdzraM2jMzeIrtiBSu-UIK?usp=drive_link)
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* Run the notebook: `utils/Transforming mseeds to SeisBench dataset.ipynb`
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* Run the notebook: `utils/Transforming mseeds to SeisBench dataset.ipynb`
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4. Initialize poetry environment:
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3. Run the pipeline script:
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`poetry shell`
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5. Run the pipeline script:
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`python pipeline.py`
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`python pipeline.py`
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environment.yml
Normal file
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environment.yml
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name: platform-demo-scripts
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channels:
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- pytorch
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- nvidia
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dependencies:
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- python=3.10
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- pytorch=2.0.1
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- pytorch-cuda
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- PyYAML=6.0
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- python-dotenv=1.0.0
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- pandas=2.0.3
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- obspy=1.4.0
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- wandb=0.15.4
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- torchmetrics=0.11.4
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- pytorch-lightning
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- scikit-learn
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- openpyxl
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- jupyterlab
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- notebook
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- pip
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- pip:
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- seisbench==0.4.1
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