def run_test_fitsexport(directory):
"""Run example analysis to test a fits data production
hap-data-fits-export crab has to be run in order to produce the example data
"""
log.info('Running test analysis of fits data')
from gammapy.data import DataStore
from gammapy.datasets import gammapy_extra
from gammapy.utils.scripts import read_yaml
from gammapy.spectrum.spectrum_pipe import run_spectrum_analysis_using_config
from gammapy.spectrum.results import SpectrumResult
s = DataStore.from_dir(directory)
print(s.info())
configfile = gammapy_extra.filename(
'test_datasets/spectrum/spectrum_analysis_example.yaml')
config = read_yaml(configfile)
config['extraction']['data']['datastore'] = directory
config['extraction']['data']['runlist'] = [23523, 23526, 23559, 23592]
fit, analysis = run_spectrum_analysis_using_config(config)
res = SpectrumResult(
fit=fit.result,
stats=analysis.observations.total_spectrum.spectrum_stats)
print(res.to_table())
def test_fill_cube():
filename = gammapy_extra.filename('test_datasets/background/bg_cube_model_test1.fits')
array = Cube.read(filename, format='table', scheme='bg_cube')
array.data = Quantity(np.zeros_like(array.data.value), 'u')
print(type(array.data))
dir = str(gammapy_extra.dir) + '/datasets/hess-crab4-hd-hap-prod2'
data_store = DataStore.from_dir(dir)
ev_list = data_store.load_all('events')
array.fill_events(ev_list)
array.write('test_background.fits', format='image', clobber=True)
def test_fill_cube():
filename = gammapy_extra.filename(
'test_datasets/background/bg_cube_model_test1.fits')
array = Cube.read(filename, format='table', scheme='bg_cube')
array.data = Quantity(np.zeros_like(array.data.value), 'u')
print(type(array.data))
dir = str(gammapy_extra.dir) + '/datasets/hess-crab4-hd-hap-prod2'
data_store = DataStore.from_dir(dir)
ev_list = data_store.load_all('events')
array.fill_events(ev_list)
array.write('test_background.fits', format='image', clobber=True)
def run_test_fitsexport(directory):
"""Run example analysis to test a fits data production
hap-data-fits-export crab has to be run in order to produce the example data
"""
log.info('Running test analysis of fits data')
from gammapy.data import DataStore
from gammapy.datasets import gammapy_extra
from gammapy.utils.scripts import read_yaml
from gammapy.spectrum.spectrum_pipe import run_spectrum_analysis_using_config
from gammapy.spectrum.results import SpectrumResult
s = DataStore.from_dir(directory)
print(s.info())
configfile = gammapy_extra.filename(
'test_datasets/spectrum/spectrum_analysis_example.yaml')
config = read_yaml(configfile)
config['extraction']['data']['datastore'] = directory
config['extraction']['data']['runlist'] = [23523, 23526, 23559, 23592]
fit, analysis = run_spectrum_analysis_using_config(config)
res = SpectrumResult(fit=fit.result, stats=analysis.observations.total_spectrum.spectrum_stats)
print(res.to_table())
"""Eventlist coordinate check.
"""
from gammapy.data import EventListDataset
from gammapy.datasets import gammapy_extra
filename = gammapy_extra.filename('test_datasets/unbundled/hess/run_0023037_hard_eventlist.fits.gz')
event_list = EventListDataset.read(filename)
print(event_list.info)
event_list.check()
"""
TODO: figure out the origin of this offset:
ALT / AZ not consistent with RA / DEC. Max separation: 726.6134257108188 arcsec
"""
"""
from astropy.coordinates import SkyCoord, Angle
from gammapy.datasets import gammapy_extra
from gammapy.image import ExclusionMask
from gammapy.data import DataStore
from gammapy.region import SkyCircleRegion
from gammapy.spectrum import SpectrumAnalysis
from gammapy.utils.energy import EnergyBounds
center = SkyCoord(83.63, 22.01, unit='deg', frame='icrs')
radius = Angle('0.3 deg')
on_region = SkyCircleRegion(pos=center, radius=radius)
bkg_method = dict(type='reflected', n_min=3)
exclusion_file = gammapy_extra.filename("datasets/exclusion_masks/"
"tevcat_exclusion.fits")
excl = ExclusionMask.from_fits(exclusion_file)
bounds = EnergyBounds.equal_log_spacing(1, 10, 40, unit='TeV')
store = gammapy_extra.filename("datasets/hess-crab4")
ds = DataStore.from_dir(store)
obs = [23523, 23559]
ana = SpectrumAnalysis(datastore=ds, obs=obs, on_region=on_region,
bkg_method=bkg_method, exclusion=excl, ebounds=bounds)
ana.write_ogip_data(outdir='ogip_data')
import matplotlib.pyplot as plt
from matplotlib.colors import LogNorm
from astropy.units import Quantity
from astropy.coordinates import Angle
from gammapy.background import Cube
from gammapy.datasets import gammapy_extra
filename = gammapy_extra.filename('test_datasets/background/bg_cube_model_test1.fits')
bg_cube_model = Cube.read(filename, format='table', scheme='bg_cube', hdu='BACKGROUND')
fig, axes = plt.subplots(nrows=1, ncols=3)
fig.set_size_inches(16, 5., forward=True)
# plot images
bg_cube_model.plot_image(energy=Quantity(0.5, 'TeV'), ax=axes[0],
style_kwargs=dict(norm=LogNorm()))
bg_cube_model.plot_image(energy=Quantity(50., 'TeV'), ax=axes[1],
style_kwargs=dict(norm=LogNorm()))
# plot spectra
bg_cube_model.plot_spectrum(coord=Angle([0., 0.], 'degree'), ax=axes[2],
style_kwargs=dict(label='(0, 0) deg'))
bg_cube_model.plot_spectrum(coord=Angle([2., 2.], 'degree'), ax=axes[2],
style_kwargs=dict(label='(2, 2) deg'))
axes[2].set_title('')
axes[2].legend()
plt.tight_layout()
plt.show()
def test_spectrum_pipe(tmpdir):
configfile = gammapy_extra.filename('test_datasets/spectrum/spectrum_pipe_example.yaml')
config = read_yaml(configfile)
config['base_config']['general']['outdir'] = str(tmpdir)
pipe = SpectrumPipe.from_config(config, auto_outdir=False)
pipe.run()
from gammapy.spectrum.tests.test_extract import obs, target, bkg
from gammapy.datasets import gammapy_extra
from gammapy.spectrum import SpectrumExtraction
import numpy as np
import astropy.units as u
outdir = gammapy_extra.filename("datasets/hess-crab4_pha")
# Restrict energy range to what is covered by HAP exporters
e_true = np.logspace(-1, 1.9, 70) * u.TeV
extraction = SpectrumExtraction(obs=obs(),
target=target(),
background=bkg(),
e_true=e_true,
)
extraction.estimate_background(extraction.background)
extraction.extract_spectrum()
extraction.observations.write(outdir, use_sherpa=True)
from gammapy.spectrum.tests.test_extract import obs, target, bkg
from gammapy.datasets import gammapy_extra
from gammapy.spectrum import SpectrumExtraction
import numpy as np
import astropy.units as u
outdir = gammapy_extra.filename("datasets/hess-crab4_pha")
# Restrict energy range to what is covered by HAP exporters
e_true = np.logspace(-1, 1.9, 70) * u.TeV
extraction = SpectrumExtraction(
obs=obs(),
target=target(),
background=bkg(),
e_true=e_true,
)
extraction.estimate_background(extraction.background)
extraction.extract_spectrum()
extraction.observations.write(outdir, use_sherpa=True)
"""
This script illustrates how to use `~gammapy.spectrum.SpectralFit`
in order to fit a model to set of OGIP data
"""
from gammapy.datasets import gammapy_extra
from gammapy.spectrum.spectrum_analysis import SpectrumFit
pha23592 = gammapy_extra.filename("datasets/hess-crab4_pha/pha_run23592.pha")
pha23526 = gammapy_extra.filename("datasets/hess-crab4_pha/pha_run23526.pha")
pha_list = [pha23592, pha23426]
fit = SpectrumFit(pha_list)
fit.model = 'PL'
fit.energy_threshold_low = '100 GeV'
fit.energy_threshold_high = '10 TeV'
fit.run(method='sherpa')
from astropy.tests.helper import assert_quantity_allclose
from gammapy.data import ObservationTable
from gammapy.datasets import gammapy_extra
from gammapy.spectrum import SpectrumFit, SpectrumGrouping, group_obs_table
obs_table_file = gammapy_extra.filename(
'datasets/hess-crab4_pha/observation_table.fits')
obs_table = ObservationTable.read(obs_table_file)
fit = SpectrumFit.from_observation_table(obs_table)
fit.model = 'PL'
fit.energy_threshold_low = '1 TeV'
fit.energy_threshold_high = '10 TeV'
fit.run(method='sherpa')
#Use each obs in one group
obs_table1 = group_obs_table(obs_table, eff_range=[90, 95], n_eff_bin=5)
obs_table1.write('grouped_table1_debug.fits', overwrite=True)
grouping = SpectrumGrouping(obs_table1)
grouping.run()
fit_band2 = SpectrumFit.from_observation_table(grouping.stacked_obs_table)
fit_band2.model = 'PL'
fit_band2.energy_threshold_low = '1 TeV'
fit_band2.energy_threshold_high = '10 TeV'
fit_band2.run(method='sherpa')
assert_quantity_allclose(fit.result.parameters["index"],
from astropy.io import fits
from gammapy.datasets import gammapy_extra
filename = gammapy_extra.filename('datasets/catalogs/fermi/gll_psch_v08.fit.gz')
hdu = fits.open(filename)['Count Map']
"""Eventlist coordinate check.
"""
from gammapy.data import EventListDataset
from gammapy.datasets import gammapy_extra
filename = gammapy_extra.filename(
'test_datasets/unbundled/hess/run_0023037_hard_eventlist.fits.gz')
event_list = EventListDataset.read(filename)
print(event_list.info)
event_list.check()
"""
TODO: figure out the origin of this offset:
ALT / AZ not consistent with RA / DEC. Max separation: 726.6134257108188 arcsec
"""
from astropy.tests.helper import assert_quantity_allclose
from gammapy.data import ObservationTable
from gammapy.datasets import gammapy_extra
from gammapy.spectrum import SpectrumFit, SpectrumObservationGrouping, group_obs_table
obs_table_file = gammapy_extra.filename(
'datasets/hess-crab4_pha/observation_table.fits')
obs_table = ObservationTable.read(obs_table_file)
fit = SpectrumFit.from_observation_table(obs_table)
fit.model = 'PL'
fit.energy_threshold_low = '1 TeV'
fit.energy_threshold_high = '10 TeV'
fit.run(method='sherpa')
#Use each obs in one group
obs_table1 = group_obs_table(obs_table, eff_range=[90, 95], n_eff_bin=5)
obs_table1.write('grouped_table1_debug.fits', overwrite=True)
grouping = SpectrumObservationGrouping(obs_table1)
grouping.run()
fit_band2 = SpectrumFit.from_observation_table(grouping.stacked_obs_table)
fit_band2.model = 'PL'
fit_band2.energy_threshold_low = '1 TeV'
fit_band2.energy_threshold_high = '10 TeV'
fit_band2.run(method='sherpa')
assert_quantity_allclose(fit.result.parameters["index"],
axes[1, 2].set_title(spec_title1)
# plot normalized models on top
plot_data_x, normed_pl = get_normed_pl(plot_data=axes[1, 2].get_lines()[0],
E_0=E_REF, norm=NORM, index=INDEX)
axes[1, 2].plot(plot_data_x, normed_pl, color='blue',
linestyle='dotted', linewidth=2,
label='model index = {}'.format(INDEX))
plot_data_x, normed_pl = get_normed_pl(plot_data=axes[1, 2].get_lines()[0],
E_0=E_REF, norm=NORM, index=INDEX + 1)
axes[1, 2].plot(plot_data_x, normed_pl, color='blue',
linestyle='dashed', linewidth=2,
label='model index = {}'.format(INDEX + 1))
axes[1, 2].legend()
plt.show()
if __name__ == '__main__':
"""Main function: define arguments and launch the whole analysis chain.
"""
input_file1 = gammapy_extra.filename('test_datasets/background/bg_cube_model_true.fits.gz')
name1 = 'true'
input_file2 = gammapy_extra.filename('test_datasets/background/bg_cube_model_reco.fits.gz')
name2 = 'reco'
plot_bg_cube_model_comparison(input_file1, name1,
input_file2, name2)
from gammapy import irf
from gammapy.utils.mpl_style import gammapy_mpl_style
# TODO: Update once this issue is resolved:
# https://github.com/astropy/astropy/issues/4140
# plt.style.use(gammapy_mpl_style)
plt.rcParams.update(gammapy_mpl_style)
fig, axes = plt.subplots(2, 4, figsize=(20, 8))
axes = axes.flat
# TODO: event list summary plots not implemented yet:
# https://github.com/gammapy/gammapy/issues/297
# hess_events_023523.fits.gz
filename = gammapy_extra.filename('test_datasets/irf/hess/pa/hess_aeff_2d_023523.fits.gz')
aeff2d = irf.EffectiveAreaTable2D.read(filename)
aeff2d.plot_energy_dependence(ax=next(axes))
aeff2d.plot_offset_dependence(ax=next(axes))
aeff = aeff2d.to_effective_area_table(offset='1 deg')
aeff.plot_area_vs_energy(ax=next(axes))
filename = gammapy_extra.filename('test_datasets/irf/hess/pa/hess_edisp_2d_023523.fits.gz')
edisp2d = irf.EnergyDispersion2D.read(filename)
edisp2d.plot_bias(ax=next(axes))
edisp2d.plot_migration(ax=next(axes))
edisp = edisp2d.to_energy_dispersion(offset='1 deg')
edisp.plot(type='matrix', ax=next(axes))