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https://github.com/grburgess/cosmogrb
A cosmological GRB light curve simulator. Because, why not?
https://github.com/grburgess/cosmogrb
cosmology fermi-science grb light-curves population-synthesis simulation
Last synced: 3 months ago
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A cosmological GRB light curve simulator. Because, why not?
- Host: GitHub
- URL: https://github.com/grburgess/cosmogrb
- Owner: grburgess
- License: bsd-2-clause
- Created: 2019-10-31T02:47:08.000Z (over 5 years ago)
- Default Branch: master
- Last Pushed: 2023-01-25T15:50:51.000Z (about 2 years ago)
- Last Synced: 2024-01-29T21:12:10.697Z (about 1 year ago)
- Topics: cosmology, fermi-science, grb, light-curves, population-synthesis, simulation
- Language: Python
- Homepage: https://cosmogrb.readthedocs.io/en/latest/
- Size: 58.1 MB
- Stars: 5
- Watchers: 1
- Forks: 6
- Open Issues: 1
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
[](https://travis-ci.org/grburgess/cosmogrb)
[](https://codecov.io/gh/grburgess/cosmogrb)
## status
# cosmogrb
## Idea
This simulates a cosmological population of **GRBs** in the Universe from a given space and luminosity distribution.
### Light curves / lightcurves
After simulation, a realistic background and temporally evolving spectrum are created. These are then sampled at the single photon level, pushed through the detector responses, simulated with real dead time, and pushed into FITS Event files.
Cool?
```python
import matplotlib.pyplot as plt
%matplotlib inline
from jupyterthemes import jtplot
import cosmogrb
```
You do not have threeML installed
# Demo of Creating a GBM GRB
## Instantiate the GRB with its parameters
```python
grb = cosmogrb.GBMGRB_CPL(
ra=312.0,
dec=-62.0,
z=1.0,
peak_flux=5e-7,
alpha=-0.66,
ep=500.0,
tau=2.0,
trise=1.0,
tdecay=1.,
duration=80.0,
T0=0.1,
)
```
## Examine the latent lightcurve
```python
time = np.linspace(0, 20, 100)
grb.display_energy_integrated_light_curve(time);
```
```python
energy = np.logspace(1, 3, 100)
grb.display_energy_dependent_light_curve(time, energy, cmap='magma')
```
## Simulate the GRB
```python
grb.go(n_cores=6)
```
## Save the GRB to an HDF5 file
```python
grb.save('test_grb.h5')
```
## Reload the GRB
```python
grb_reload = cosmogrb.GRBSave.from_file('test_grb.h5')
```
```python
fig, axes = plt.subplots(4,4,sharex=True,sharey=False,figsize=(15,15))
row=0
col = 0
for key in grb_reload.keys:
ax = axes[row][col]
lightcurve = grb_reload[key]['lightcurve']
lightcurve.display_lightcurve(dt=2, ax=ax,lw=.8)
lightcurve.display_source(ax=ax,lw=.8)
lightcurve.display_background(ax=ax,lw=.8)
if col < 3:
col+=1
else:
row+=1
col=0
```
```python
fig, axes = plt.subplots(4,4,sharex=False,sharey=False,figsize=(15,15))
row=0
col = 0
for key in grb_reload.keys:
ax = axes[row][col]
lightcurve = grb_reload[key]['lightcurve']
lightcurve.display_count_spectrum(tmin=0, tmax=5, ax=ax)
lightcurve.display_count_spectrum_source(tmin=0, tmax=5, ax=ax)
lightcurve.display_count_spectrum_background(tmin=0, tmax=5, ax=ax)
if col < 3:
col+=1
else:
row+=1
col=0
```
## Convert HDF5 to standard FITS files
```python
cosmogrb.grbsave_to_gbm_fits("test_grb.h5")
!ls SynthGRB_*
```
SynthGRB_b0.fits SynthGRB_n3.fits SynthGRB_n7rsp_n7.rsp
SynthGRB_b0.rsp SynthGRB_n3.rsp SynthGRB_n8.fits
SynthGRB_b0rsp_b0.rsp SynthGRB_n3rsp_n3.rsp SynthGRB_n8.rsp
SynthGRB_b1.rsp SynthGRB_n4.fits SynthGRB_n8rsp_n8.rsp
SynthGRB_b1rsp_b1.rsp SynthGRB_n4.rsp SynthGRB_n9.fits
SynthGRB_n0.fits SynthGRB_n4rsp_n4.rsp SynthGRB_n9.rsp
SynthGRB_n0.rsp SynthGRB_n5.fits SynthGRB_n9rsp_n9.rsp
SynthGRB_n0rsp_n0.rsp SynthGRB_n5.rsp SynthGRB_na.fits
SynthGRB_n1.fits SynthGRB_n5rsp_n5.rsp SynthGRB_na.rsp
SynthGRB_n1.rsp SynthGRB_n6.fits SynthGRB_narsp_na.rsp
SynthGRB_n1rsp_n1.rsp SynthGRB_n6.rsp SynthGRB_nb.fits
SynthGRB_n2.fits SynthGRB_n6rsp_n6.rsp SynthGRB_nb.rsp
SynthGRB_n2.rsp SynthGRB_n7.fits SynthGRB_nbrsp_nb.rsp
SynthGRB_n2rsp_n2.rsp SynthGRB_n7.rsp
```python
```