Spectroscopic QUasar Extractor and redshift (z) Estimator
requirements:
- python 2.7 or 3.6
- argparse
- numpy
- pandas
- sklearn - only for training
- astropy
SQUEzE is a software package to identify quasars and estimate their redshift in a sample of spectra. The quasars id and redshif is estimated in a two-step process: 1. Generate a high completeness and low purity sample of candidates 2. Filter the candidates to improve purity while keeping a target completeness See Perez-Rafols et al. 2019 (https://arxiv.org/abs/1903.00023) for more details. Consider referencing this paper if you are using SQUEzE in your analysis.
SQUEzE can run in different modes: 1. training - Use a known sample to decide on model options 2. test - Use a known sample to assess model performance 3. operation - Apply cuts to unknown sample to build a catalogue 4. merge - Merge different candidates objects into a single candidate objects
download
git clone https://github.com/iprafols/SQUEzE.git
Add <path_to_SQUEzE>/SQUEzE/py/ to your PYTHONPATH.
It is recommended to pretrain SQUEzE using the provided results from BOSS. To do so run
cd <path_to_SQUEzE>/SQUEzE/data
tar -xzvf BOSS_train_64plates.tar.gz
cd ../bin
python pretrain_squeze.py
from the bin/ folder. This will generate a trained model named BOSS_train_64plates_model.json
stored in the data/ folder.
SQUEzE presents four modes of operation: training, test, operation, and merge. The training and test modes are used on a controlled sample where a truth table is available, and allows the code to learn or test performance of the model parameters. The operation mode is used on an uncontrolled sample to generate a quasar catalogue. The merge mode is used to join different (and possibly parallel) runs on a different mode.
Before running SQUEzE data must be formatted so that the code can use it properly. This section explains both the optional and required pre-steps to format all data correctly.
- Formatting spectra (required):
The spectra variable sets the spectra where SQUEzE will be run. Format of
the spectra must be a Spectra object (defined in py/squeze_spectra.py) containing
a set of Spectrum instances. The package provides the file `format_superset_dr12q.py´
with a working example of how to format BOSS spectra.
2.1 Formatting lines (optional):
The lines variable sets the characteristics of the lines used by the code.
For SQUEzE to use a value different from the default, it needs to be
formatted as a pandas data frame and saved into a csv file.
The package provides the file `format_lines.py´ with the instructions to
properly create this object. It is a modifyiable working example.
run
python squeze_training.py
for an explanation on the optional arguments add -h to the previous line
run
python squeze_test.py
for an explanation on the optional arguments add -h to the previous line
run
python squeze_operation.py
for an explanation on the optional arguments add -h to the previous line
run
python squeze_merge_candidates.py
for an explanation on the optional arguments add -h to the previous line