def test_load_3fgl_catalog_fits():
skydir = SkyCoord(0.0, 0.0, unit='deg', frame='galactic').icrs
rm = ROIModel(catalogs=['3FGL'], skydir=skydir, src_radius=20.0)
assert len(rm.sources) == 175
src_name = '3FGL J1747.7-2904'
assert(rm[src_name]['SpectrumType'] == 'PowerLaw')
check_src_params(rm, src_name,
['Prefactor', 'Index', 'Scale'],
[1.1100788257e-12, -2.5154423713, 2248.0983886])
src_name = '3FGL J1747.0-2828'
assert(rm[src_name]['SpectrumType'] == 'LogParabola')
check_src_params(rm, src_name,
['norm', 'alpha', 'beta', 'Eb'],
[6.2330737793e-11, 2.04547667503, 0.417130559682, 742.2312011])
src_name = '3FGL J1747.2-2958'
assert(rm[src_name]['SpectrumType'] == 'PLSuperExpCutoff')
check_src_params(rm, src_name,
['Prefactor', 'Index1', 'Index2', 'Scale', 'Cutoff'],
[2.07284068381e-11, -1.79597532749, 1.0, 1468.48669433,
3328.21728515])
rm = ROIModel(catalogs=['gll_psc_v16.fit'], skydir=skydir,
src_radius=20.0)
assert len(rm.sources) == 175
def test_load_3fgl_catalog_fits():
skydir = SkyCoord(0.0, 0.0, unit='deg', frame='galactic').icrs
rm = ROIModel(catalogs=['3FGL'], skydir=skydir, src_radius=20.0)
assert len(rm.sources) == 175
rm = ROIModel(catalogs=['gll_psc_v16.fit'], skydir=skydir, src_radius=20.0)
assert len(rm.sources) == 175
def test_write_ds9region():
skydir = SkyCoord(0.0, 0.0, unit='deg', frame='galactic').icrs
rm = ROIModel(catalogs=['3FGL'], skydir=skydir, src_radius=8.0)
assert len(rm.sources) == 62
rm.write_ds9region("test1.reg", header=True)
with open("test1.reg") as fo:
dd = fo.readlines()
assert len(dd) == 63 # including header
rm.write_ds9region("test1.reg", header=False)
with open("test1.reg") as fo:
dd = fo.readlines()
assert len(dd) == 62 # excluding header
# check free sources
free_sources = rm.get_nearby_sources("3FGL J1745.6-2859c", 1)[-1]
nfree = 0
for source in free_sources:
if 'Prefactor' in source.spectral_pars:
source.spectral_pars['Prefactor']['free'] = True
nfree += 1
nfixed = len(rm.sources) - nfree
rm.write_ds9region("test1.reg",
header=False,
free='diamond',
fixed="cross")
with open("test1.reg") as fo:
dd = fo.readlines()
ffree = np.array([1 if "diamond" in d else 0 for d in dd]).sum()
ffix = np.array([1 if "cross" in d else 0 for d in dd]).sum()
assert nfree == ffree
assert nfixed == ffix
def test_write_ds9region():
skydir = SkyCoord(0.0, 0.0, unit='deg', frame='galactic').icrs
rm = ROIModel(catalogs=['3FGL'], skydir=skydir, src_radius=8.0)
assert len(rm.sources) == 62
rm.write_ds9region("test1.reg",header=True)
with open("test1.reg") as fo:
dd = fo.readlines()
assert len(dd) == 63 # including header
rm.write_ds9region("test1.reg", header=False)
with open("test1.reg") as fo:
dd = fo.readlines()
assert len(dd) == 62 # excluding header
# check free sources
free_sources = rm.get_nearby_sources("3FGL J1745.6-2859c", 1)[-1]
nfree = 0
for source in free_sources:
if 'Prefactor' in source.spectral_pars:
source.spectral_pars['Prefactor']['free'] = True
nfree+=1
nfixed = len(rm.sources) - nfree
rm.write_ds9region("test1.reg", header=False, free='diamond', fixed="cross")
with open("test1.reg") as fo:
dd = fo.readlines()
ffree = np.array([1 if "diamond" in d else 0 for d in dd]).sum()
ffix = np.array([1 if "cross" in d else 0 for d in dd]).sum()
assert nfree == ffree
assert nfixed== ffix
def test_load_roi_from_dict(tmppath):
sources = [{'name': 'ptsrc0', 'SpectrumType': 'PowerLaw',
'ra': 121.0, 'dec': 32.56,
'Index': 2.3, 'Prefactor': 1.3E-15, 'Scale': 1452.0},
{'name': 'ptsrc1', 'SpectrumType': 'PowerLaw',
'ra': 121.0, 'dec': 32.56,
'Index': {'value': 2.3, 'scale': 2.4, 'min': 0.3, 'max': 5.7},
'Prefactor': {'value': 1.2, 'scale': 3E-12, 'min': 0.0, 'max': 5.0},
'Scale': {'value': 134.1, 'scale': 1.2, 'min': 0.0, 'max': 2000.0},
}]
roi = ROIModel(sources=sources)
src = roi['ptsrc0']
assert_allclose(src['dec'], sources[0]['dec'])
assert_allclose(src['ra'], sources[0]['ra'])
sp = src['spectral_pars']
assert_allclose(sp['Index']['value'], sources[0]['Index'])
assert_allclose(sp['Scale']['value'], 1.452)
assert_allclose(sp['Prefactor']['value'], 1.3)
for p in ['Index', 'Prefactor', 'Scale']:
if p == 'Index':
assert_allclose(sources[0][p], -src.params[p]['value'])
else:
assert_allclose(sources[0][p], src.params[p]['value'])
src = roi['ptsrc1']
sp = src['spectral_pars']
for p in ['Index', 'Prefactor', 'Scale']:
assert_allclose(sources[1][p]['value'] * sources[1][p]['scale'],
src.params[p]['value'])
def test_load_3fgl_catalog_xml():
skydir = SkyCoord(0.0, 0.0, unit='deg', frame='galactic').icrs
rm = ROIModel(catalogs=['gll_psc_v16.xml'],
extdir='Extended_archive_v15',
skydir=skydir,
src_radius=20.0)
assert len(rm.sources) == 175
def test_load_4fgldr2_catalog_fits():
#tested against web interface: https://heasarc.gsfc.nasa.gov/db-perl/W3Browse/w3query.pl
skydir = SkyCoord(0.0, 30.0, unit='deg', frame='galactic').icrs
rm = ROIModel(catalogs=['4FGL-DR2'], skydir=skydir, src_radius=20.0)
assert len(rm.sources) == 140
src_name = '4FGL J1605.1-1140'
assert(rm[src_name]['SpectrumType'] == 'PowerLaw')
check_src_params(rm, src_name,
['Prefactor', 'Index', 'Scale'],
[3.5487e-14, -2.0657, 3045.06])
src_name = '4FGL J1557.9-1404'
assert(rm[src_name]['SpectrumType'] == 'LogParabola')
check_src_params(rm, src_name,
['norm', 'alpha', 'beta', 'Eb'],
[1.7456e-13, 2.2619, 0.7502, 1771.59])
src_name = '4FGL J1623.0-0315'
assert(rm[src_name]['SpectrumType'] == 'PLSuperExpCutoff2')
prefactor = 6.4947e-13 * np.exp( 0.00669 * 1433.48 ** 0.6666667 )
#apparently, the Expfactor is supposed to be 0.006691, but the web interface says 0.00669.
check_src_params(rm, src_name,
['Prefactor', 'Index1', 'Index2', 'Expfactor', 'Scale'],
[prefactor, -1.4861, 0.6666667, 0.00669, 1433.48], rtol=1e-3)
def read_sources_from_numpy_file(npfile):
""" Open a numpy pickle file and read all the new sources into a dictionary
Parameters
----------
npfile : file name
The input numpy pickle file
Returns
-------
tab : `~astropy.table.Table`
"""
srcs = np.load(npfile).flat[0]['sources']
roi = ROIModel()
roi.load_sources(srcs.values())
return roi.create_table()
def read_sources_from_numpy_file(npfile):
""" Open a numpy pickle file and read all the new sources into a dictionary
Parameters
----------
npfile : file name
The input numpy pickle file
Returns
-------
tab : `~astropy.table.Table`
"""
srcs = np.load(npfile).flat[0]['sources']
roi = ROIModel()
roi.load_sources(srcs.values())
return roi.create_table()
def read_sources_from_yaml_file(yamlfile):
""" Open a yaml file and read all the new sources into a dictionary
Parameters
----------
yaml : file name
The input yaml file
Returns
-------
tab : `~astropy.table.Table`
"""
f = open(yamlfile)
dd = yaml.safe_load(f)
srcs = dd['sources']
f.close()
roi = ROIModel()
roi.load_sources(srcs.values())
return roi.create_table()
def read_sources_from_yaml_file(yamlfile):
""" Open a yaml file and read all the new sources into a dictionary
Parameters
----------
yaml : file name
The input yaml file
Returns
-------
tab : `~astropy.table.Table`
"""
f = open(yamlfile)
dd = yaml.load(f)
srcs = dd['sources']
f.close()
roi = ROIModel()
roi.load_sources(srcs.values())
return roi.create_table()
def test_load_3fgl_catalog_xml():
skydir = SkyCoord(0.0, 0.0, unit='deg', frame='galactic').icrs
rm = ROIModel(catalogs=['gll_psc_v16.xml'],
extdir='Extended_archive_v15',
skydir=skydir,
src_radius=20.0)
assert len(rm.sources) == 175
src_name = '3FGL J1747.2-2958'
assert (rm[src_name]['SpectrumType'] == 'PLSuperExpCutoff')
check_src_params(
rm, src_name, ['Prefactor', 'Index1', 'Index2', 'Scale', 'Cutoff'],
[1.08110111000e-10, -1.79597532749, 1.0, 585.4324476, 3328.21728515])
def test_create_roi_from_source():
rm = ROIModel.create_from_source('3FGL J2021.0+4031e',
{'catalogs': ['3FGL'], 'src_radius': 2.0})
assert len(rm.sources) == 9
src = rm.sources[0]
assert src.name == '3FGL J2021.0+4031e'
assert src['SpatialType'] == 'SpatialMap'
assert src['SourceType'] == 'DiffuseSource'
assert src['SpectrumType'] == 'PowerLaw'
assert_allclose(src['ra'], 305.26999, rtol=1E-5)
assert_allclose(src['dec'], 40.52, rtol=1E-5)
assert_allclose(src.spectral_pars['Index']['value'], 1.53, rtol=1E-4)
assert_allclose(src.spectral_pars['Prefactor']['value'] *
src.spectral_pars['Prefactor']['scale'], 0.4003659112E-12, rtol=1E-4)
assert_allclose(src.spatial_pars['Prefactor']['value'], 1.0, rtol=1E-4)
assert_allclose(src.spatial_pars['Prefactor']['scale'], 1.0, rtol=1E-4)
def test_create_roi_from_source():
rm = ROIModel.create_from_source('3FGL J2021.0+4031e',
{'catalogs': ['3FGL'], 'src_radius': 2.0})
assert len(rm.sources) == 9
src = rm.sources[0]
assert src.name == '3FGL J2021.0+4031e'
assert src['SpatialType'] == 'SpatialMap'
assert src['SourceType'] == 'DiffuseSource'
assert src['SpectrumType'] == 'PowerLaw'
assert_allclose(src['ra'], 305.26999, rtol=1E-5)
assert_allclose(src['dec'], 40.52, rtol=1E-5)
assert_allclose(src.spectral_pars['Index']['value'], 1.53, rtol=1E-4)
assert_allclose(src.spectral_pars['Prefactor']['value'] *
src.spectral_pars['Prefactor']['scale'], 0.4003659112E-12, rtol=1E-4)
assert_allclose(src.spatial_pars['Prefactor']['value'], 1.0, rtol=1E-4)
assert_allclose(src.spatial_pars['Prefactor']['scale'], 1.0, rtol=1E-4)
def test_create_roi_from_source_4fgldr2():
rm = ROIModel.create_from_source('4FGL J2021.0+4031e',
{'catalogs': ['4FGL-DR2'], 'src_radius': 2.0})
assert len(rm.sources) == 6
src = rm.sources[0]
assert src.name == '4FGL J2021.0+4031e'
assert src['SpatialType'] == 'RadialDisk'
assert src['SourceType'] == 'DiffuseSource'
assert src['SpectrumType'] == 'LogParabola'
assert_allclose(src['ra'], 305.27, rtol=1E-5)
assert_allclose(src['dec'], 40.52, rtol=1E-5)
assert_allclose(src.spectral_pars['alpha']['value'], 1.8747, rtol=1E-4)
assert_allclose(src.spectral_pars['beta']['value'] *
src.spectral_pars['beta']['scale'], 0.0606, rtol=1E-4)
assert_allclose(src.spectral_pars['norm']['value'] *
src.spectral_pars['norm']['scale'], 2.0858e-13, rtol=1E-4)
assert_allclose(src.spatial_pars['Radius']['value'], 0.63, rtol=1E-4)
assert_allclose(src.spatial_pars['DEC']['scale'], 1.0, rtol=1E-4)
def test_load_fl8y_catalog_fits():
skydir = SkyCoord(0.0, 30.0, unit='deg', frame='galactic').icrs
rm = ROIModel(catalogs=['FL8Y'], skydir=skydir, src_radius=20.0)
assert len(rm.sources) == 146
src_name = 'FL8Y J1605.1-1140'
assert (rm[src_name]['SpectrumType'] == 'PowerLaw')
check_src_params(rm, src_name, ['Prefactor', 'Index', 'Scale'],
[3.0401211875e-14, -2.06162524223, 3171.08496])
src_name = 'FL8Y J1557.9-1402'
assert (rm[src_name]['SpectrumType'] == 'LogParabola')
check_src_params(
rm, src_name, ['norm', 'alpha', 'beta', 'Eb'],
[1.4193160535e-13, 2.11492037773, 0.99977719783, 1884.4001464])
src_name = 'FL8Y J1614.5-2230'
assert (rm[src_name]['SpectrumType'] == 'PLSuperExpCutoff2')
check_src_params(rm, src_name,
['Prefactor', 'Index1', 'Index2', 'Scale', 'Expfactor'], [
2.34444495067e-11, -0.099147409200, 0.66666668653,
1415.79650878, 0.016446555033
])
def test_load_composite_source_from_xml(tmppath):
values = {
'ptsrc_dec': 52.6356,
'ptsrc_ra': 252.367,
'ptsrc_Index_value': 2.21879,
'ptsrc_Index_scale': 1.2,
'ptsrc_Index_min': 1.3,
'ptsrc_Index_max': 3.5,
'ptsrc_Prefactor_value': 0.727,
'ptsrc_Prefactor_scale': 1e-12,
'ptsrc_Prefactor_min': 0.01,
'ptsrc_Prefactor_max': 10.0,
'ptsrc_Scale_value': 1.3,
'ptsrc_Scale_scale': 1e3,
'ptsrc_Scale_min': 0.01,
'ptsrc_Scale_max': 113.0
}
xmlmodel = """
<source_library title="source_library">
<source name="CompositeSource" type="CompositeSource">
<spectrum type="ConstantValue">
<parameter free="1" max="3.402823466e+38" min="-3.402823466e+38" name="Value" scale="1" value="1" />
</spectrum>
<source_library>
<source name="SourceA" type="PointSource">
<spatialModel type="SkyDirFunction">
<parameter free="0" max="90.0" min="-90.0" name="DEC" scale="1.0" value="{ptsrc_dec}"/>
<parameter free="0" max="360.0" min="-360.0" name="RA" scale="1.0" value="{ptsrc_ra}"/>
</spatialModel>
<spectrum type="PowerLaw">
<parameter free="0" max="{ptsrc_Index_max}" min="{ptsrc_Index_min}" name="Index" scale="{ptsrc_Index_scale}" value="{ptsrc_Index_value}"/>
<parameter free="0" max="{ptsrc_Scale_max}" min="{ptsrc_Scale_min}" name="Scale" scale="{ptsrc_Scale_scale}" value="{ptsrc_Scale_value}"/>
<parameter free="0" max="{ptsrc_Prefactor_max}" min="{ptsrc_Prefactor_min}" name="Prefactor" scale="{ptsrc_Prefactor_scale}" value="{ptsrc_Prefactor_value}"/>
</spectrum>
</source>
<source name="SourceB" type="PointSource">
<spatialModel type="SkyDirFunction">
<parameter free="0" max="90.0" min="-90.0" name="DEC" scale="1.0" value="{ptsrc_dec}"/>
<parameter free="0" max="360.0" min="-360.0" name="RA" scale="1.0" value="{ptsrc_ra}"/>
</spatialModel>
<spectrum type="PowerLaw">
<parameter free="0" max="{ptsrc_Index_max}" min="{ptsrc_Index_min}" name="Index" scale="{ptsrc_Index_scale}" value="{ptsrc_Index_value}"/>
<parameter free="0" max="{ptsrc_Scale_max}" min="{ptsrc_Scale_min}" name="Scale" scale="{ptsrc_Scale_scale}" value="{ptsrc_Scale_value}"/>
<parameter free="0" max="{ptsrc_Prefactor_max}" min="{ptsrc_Prefactor_min}" name="Prefactor" scale="{ptsrc_Prefactor_scale}" value="{ptsrc_Prefactor_value}"/>
</spectrum>
</source>
</source_library>
</source>
</source_library>
""".format(**values)
root = ElementTree.fromstring(xmlmodel)
xmlfile = str(tmppath.join('test.xml'))
ElementTree.ElementTree(root).write(xmlfile)
roi = ROIModel(config={'catalogs': [xmlfile]})
src = roi['CompositeSource']
assert (type(src) == roi_model.CompositeSource)
assert (src['SpectrumType'] == 'ConstantValue')
assert (src['SpatialType'] == 'CompositeSource')
assert (src['SpatialModel'] == 'CompositeSource')
assert (src['SourceType'] == 'CompositeSource')
attribs = ['value', 'scale', 'min', 'max']
par_names = ['Index', 'Prefactor', 'Scale']
for s in src.nested_sources:
pars = s.spectral_pars
for par_name in par_names:
for x in attribs:
assert_allclose(pars[par_name][x],
values['ptsrc_%s_%s' % (par_name, x)])
def test_load_source_from_xml(tmppath):
values = {
'ptsrc_dec': 52.6356,
'ptsrc_ra': 252.367,
'ptsrc_index_value': 2.21879,
'ptsrc_index_scale': 1.2,
'ptsrc_index_min': 1.3,
'ptsrc_index_max': 3.5,
'ptsrc_prefactor_value': 0.727,
'ptsrc_prefactor_scale': 1e-12,
'ptsrc_prefactor_min': 0.01,
'ptsrc_prefactor_max': 10.0,
'ptsrc_scale_value': 1.3,
'ptsrc_scale_scale': 1e3,
'ptsrc_scale_min': 0.01,
'ptsrc_scale_max': 113.0
}
xmlmodel = """
<source_library title="source_library">
<source name="3FGL J1649.4+5238" type="PointSource">
<spatialModel type="SkyDirFunction">
<parameter free="0" max="90.0" min="-90.0" name="DEC" scale="1.0" value="{ptsrc_dec}"/>
<parameter free="0" max="360.0" min="-360.0" name="RA" scale="1.0" value="{ptsrc_ra}"/>
</spatialModel>
<spectrum type="PowerLaw">
<parameter free="0" max="{ptsrc_index_max}" min="{ptsrc_index_min}" name="Index" scale="{ptsrc_index_scale}" value="{ptsrc_index_value}"/>
<parameter free="0" max="{ptsrc_scale_max}" min="{ptsrc_scale_min}" name="Scale" scale="{ptsrc_scale_scale}" value="{ptsrc_scale_value}"/>
<parameter free="0" max="{ptsrc_prefactor_max}" min="{ptsrc_prefactor_min}" name="Prefactor" scale="{ptsrc_prefactor_scale}" value="{ptsrc_prefactor_value}"/>
</spectrum>
</source>
<source name="isodiff" type="DiffuseSource">
<spectrum ctype="-1" file="$(FERMIPY_ROOT)/data/iso_P8R2_SOURCE_V6_v06.txt" type="FileFunction">
<parameter free="0" max="1000.0" min="0.001" name="Normalization" scale="1.0" value="1.2"/>
</spectrum>
<spatialModel type="ConstantValue">
<parameter free="0" max="10" min="0" name="Value" scale="1" value="1"/>
</spatialModel>
</source>
<source name="galdiff" type="DiffuseSource">
<spectrum type="PowerLaw">
<parameter free="0" max="1.0" min="-1.0" name="Index" scale="-1" value="0.0"/>
<parameter free="0" max="1000.0" min="1000.0" name="Scale" scale="1" value="1000.0"/>
<parameter free="0" max="10.0" min="0.1" name="Prefactor" scale="1" value="1.0"/>
</spectrum>
<spatialModel file="$(FERMIPY_WORKDIR)/gll_iem_v06_extracted.fits" type="MapCubeFunction">
<parameter free="0" max="10" min="0" name="Normalization" scale="1" value="1"/>
</spatialModel>
</source>
</source_library>
""".format(**values)
root = ElementTree.fromstring(xmlmodel)
xmlfile = str(tmppath.join('test.xml'))
ElementTree.ElementTree(root).write(xmlfile)
roi = ROIModel(config={'catalogs': [xmlfile]})
src = roi['3FGL J1649.4+5238']
assert_allclose(src['dec'], values['ptsrc_dec'])
assert_allclose(src['ra'], values['ptsrc_ra'])
assert (src['SpectrumType'] == 'PowerLaw')
assert (src['SpatialType'] == 'SkyDirFunction')
assert (src['SpatialModel'] == 'PointSource')
assert (src['SourceType'] == 'PointSource')
sp = src['spectral_pars']
attribs = ['value', 'scale', 'min', 'max']
for x in attribs:
assert_allclose(sp['Index'][x], values['ptsrc_index_%s' % x])
for x in attribs:
assert_allclose(sp['Prefactor'][x], values['ptsrc_prefactor_%s' % x])
for x in attribs:
assert_allclose(sp['Scale'][x], values['ptsrc_scale_%s' % x])
assert_allclose(
src.params['Prefactor']['value'],
values['ptsrc_prefactor_value'] * values['ptsrc_prefactor_scale'])
assert_allclose(src.params['Index']['value'],
values['ptsrc_index_value'] * values['ptsrc_index_scale'])
assert_allclose(src.params['Scale']['value'],
values['ptsrc_scale_value'] * values['ptsrc_scale_scale'])
src = roi['galdiff']
assert (src['SpatialType'] == 'MapCubeFunction')
assert (src['SpatialModel'] == 'MapCubeFunction')
src = roi['isodiff']
assert (src['SpatialType'] == 'ConstantValue')
assert (src['SpatialModel'] == 'ConstantValue')
def test_load_2fhl_catalog_fits():
rm = ROIModel(catalogs=['2FHL'])
assert len(rm.sources) == 360
import yaml
import sys
from fermipy.utils import *
from fermipy.roi_model import ROIModel
roi = ROIModel({"catalogs": ["3FGL"]})
# cuts0 = [('TS_value',10000.0,None),('GLAT',5.,90.)]
# cuts1 = [('TS_value',10000.0,None),('GLAT',-90.,-5.)]
cuts0 = [("GLAT", 5.0, 90.0)]
cuts1 = [("GLAT", -90.0, -5.0)]
srcs = roi.get_sources(cuts0) + roi.get_sources(cuts1)
config = {"selection": {}}
configs = {}
for s in srcs:
if s.extended:
continue
c = copy.deepcopy(config)
c["selection"]["target"] = s.name
configs[s.name.lower().replace(" ", "_")] = c
# srcs_dict[s.name] = s
print "found ", len(configs), " sources"
config = {}
config['model'] = dict(
src_roiwidth = 10.0,
galdiff = '/nfs/slac/g/ki/ki20/cta/mdwood/fermi/diffuse/v5r0/gll_iem_v06.fits',
isodiff = '/nfs/slac/g/ki/ki20/cta/mdwood/fermi/diffuse/v5r0/iso_P8R2_SOURCE_V6_v06.txt',
catalogs = ['gll_psc_v14.fit'])
config['run'] = {}
roi = ROIModel(config['model'])
roi.load()
o = {'ts_ext' : [], 'ext_ul95' : [], 'ext' : [], 'name' : [], 'assoc' : []}
for d in sys.argv[1:]:
# results = yaml.load(open(os.path.join(d,'fit1.yaml')),Loader=yaml.CLoader)
results_file = os.path.join(d,'fit1.npy')
if not os.path.isfile(results_file):
print 'Skipping ', d
continue
