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A web application to validate and upload target lists with pointing simulations for PFS observation

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Subaru-PFS/spt_target_uploader

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PFS Target Uploader

The PFS Target Uploader is a web app to validate and submit the target list supplied by users with an observing time estimate by a pointing simulation.

Install

Clone the repository

git clone https://github.com/Subaru-PFS/spt_target_uploader.git
cd spt_target_uploader

Installing dependencies

pip install -r requirements.txt  # perhaps optional
pip install -e .

mkdir -p data/
mkdir -p data/temp/

Build documentation

cd docs
mkdocs build
cd ..

Run the app

pfs-uploader-cli start-app uploader \
    --allow-websocket-origin=localhost:5008 \
    --static-dirs doc="./docs/site/" \
    --static-dirs data="./data"

Open the target uploader at http://localhost:5008/ . Uploaded files will be stored under data with the following structure.

$ tree data/
data/
└── <year>
    └── <month>
        └── <year month day>-<hour minute second>-<upload_id>
            ├── README.txt
            ├── pfs_target-yyyymmdd-hhmmss-<upload_id>.zip
            ├── ppc_<upload_id>.ecsv
            ├── ppp_figure_<upload_id>.html
            ├── psl_<upload_id>.ecsv
            ├── target_<upload_id>.ecsv
            ├── target_summary_<upload_id>.ecsv
            └── <original file>

ppc, psl, and target files correspond to the lists of pointing centers, the pointing summary, and input targets, respectively. Plots are available in the ppp_figure file and all files are included in the zip file.

The path to the data directory can be controlled by the OUTPUT_DIR environment variable in .env.shared. An example of .env.shared is the following.

# OUTPUT_DIR_PREFIX must be identical to the directory value specified as `data` above.
OUTPUT_DIR="data"

Configuration

The following parameters can be set in the .env.shared file to configure the app.

# Output directory for the submitted files
OUTPUT_DIR="data"

# maximum execution time (s) to terminate the calculation (default: 900s = 15min, 0 = no limit)
# MAX_EXETIME=0

# email setting (email will be sent at each submission)
# EMAIL_FROM=
# EMAIL_TO=
# SMTP_SERVER=

# Supress output of netflow
# 0: verbose
# 1: quiet
PPP_QUIET=1

# Target clustering algorithm
# HDBSCAN or DBSCAN
CLUSTERING_ALGORITHM=HDBSCAN

# Text to be announce at the beginning (Markdown)
ANN_FILE="user_announcement.md"

# SQLite database file to be used for the duplication check of upload_id
# The file will be created under $OUTPUT_DIR
UPLOADID_DB="upload_id.sqlite"

# loggging level
# DEBUG, INFO (default), WARNING, ERROR, or CRITICAL
LOG_LEVEL="INFO"

Preparing database

When UPLOADID_DB is set, the uploader looks up $OUTPUT_DIR/$UPLOADID_DB file for the duplication check of upload_id. The following command can be used to generate the database file.

pfs-uploader-cli uid2sqlite -d $OUTPUT_DIR --db $UPLOADID_DB

If you have a list of upload_ids to be inserted into the database (upload_id.csv), you can run the command as follows.

pfs-uploader-cli uid2sqlite -d $OUTPUT_DIR --db $UPLOADID_DB upload_id.csv

The example content of upload_id.csv is as follows.

upload_id
c748124208176c40
4cd4bc355c092ad7
1b8d0c4f808972bb
2e07c75691e5ba26
c695c6b755930209

If you want to scan a directory (e.g., $OUTPUT_DIR) containing submitted uploads, you can run the command as follows.

pfs-uploader-cli uid2sqlite -d $OUTPUT_DIR --db $UPLOADID_DB --scan-dir $OUTPUT_DIR

You can remove duplicates by the following command.

pfs-uploader-cli clean-uid $OUTPUT_DIR/$UPLOADID_DB

See the manual for more options.

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A web application to validate and upload target lists with pointing simulations for PFS observation

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