Deep Learning for Automated Spectral Classification of Supernovae
Project description
# DASH
Supernovae classifying and redshifting software: development stage
## 1. How to install:
1.1 pip install astrodash
or download from github (https://github.com/daniel-muthukrishna/DASH)
## 2. Get started with the Python Library interface:
2.1 Use the following example code:
import dash
classification = dash.Classify([filenames], [knownRedshifts])
print classification.list_best_matches(n=1) # Shows top 'n' matches for each spectrum
2.2 To open the gui from a script use:
import dash
dash.run_gui()
## 3. Get started with GUI
2.1 Run GUI/main.py
2.2 Once open, type in a known redshift
2.3 Browse for any single spectrum FITS, ASCII, dat, or two-column text file.
2.4 Click any of the best matches to view the continuum-subtracted binned spectra.
2.5 If the input spectrum is too noisy, increase the smoothing level, and click 'Re-fit with priors'
## 4. Dependencies:
Using pip will automatically install numpy, scipy, specutils, pyqtgraph, and tensorflow.
PyQt4
This can be installed with anaconda: "conda install pyqt=4" (or else independently - only needed for the GUI)
## 5. How to raise issues:
## 6. Examples
## 7. API Usage
Notes:
Current version requires an input redshift (inaccurate results if redshift is unknown)
Supernovae classifying and redshifting software: development stage
## 1. How to install:
1.1 pip install astrodash
or download from github (https://github.com/daniel-muthukrishna/DASH)
## 2. Get started with the Python Library interface:
2.1 Use the following example code:
import dash
classification = dash.Classify([filenames], [knownRedshifts])
print classification.list_best_matches(n=1) # Shows top 'n' matches for each spectrum
2.2 To open the gui from a script use:
import dash
dash.run_gui()
## 3. Get started with GUI
2.1 Run GUI/main.py
2.2 Once open, type in a known redshift
2.3 Browse for any single spectrum FITS, ASCII, dat, or two-column text file.
2.4 Click any of the best matches to view the continuum-subtracted binned spectra.
2.5 If the input spectrum is too noisy, increase the smoothing level, and click 'Re-fit with priors'
## 4. Dependencies:
Using pip will automatically install numpy, scipy, specutils, pyqtgraph, and tensorflow.
PyQt4
This can be installed with anaconda: "conda install pyqt=4" (or else independently - only needed for the GUI)
## 5. How to raise issues:
## 6. Examples
## 7. API Usage
Notes:
Current version requires an input redshift (inaccurate results if redshift is unknown)
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