def test_getCF(self):
"""Test getCF() directly, without first processing by child classes."""
stile_args = {'ra_units': 'degrees', 'dec_units': 'degrees', 'min_sep': 0.05, 'max_sep': 1,
'sep_units': 'degrees', 'nbins': 20}
cf = stile.sys_tests.CorrelationFunctionSysTest()
dh = temp_data_handler()
lens_data = stile.ReadASCIITable('../examples/example_lens_catalog.dat',
fields={'id': 0, 'ra': 1, 'dec': 2, 'z': 3, 'g1': 4, 'g2': 5})
source_data = stile.ReadASCIITable('../examples/example_source_catalog.dat',
fields={'id': 0, 'ra': 1, 'dec': 2, 'z': 3, 'g1': 4, 'g2': 5})
lens_catalog = treecorr.Catalog(ra=numpy.array([lens_data['ra']]),
dec=numpy.array([lens_data['dec']]),
ra_units='degrees', dec_units='degrees')
source_catalog = treecorr.Catalog(ra=source_data['ra'], dec=source_data['dec'],
g1=source_data['g1'], g2=source_data['g2'],
ra_units='degrees', dec_units='degrees')
results = cf.getCF('ng', lens_catalog, source_catalog, **stile_args)
numpy.testing.assert_array_equal(*helper.FormatSame(results, self.expected_result))
results2 = cf.getCF('ng', lens_data, source_data, config=stile_args)
self.assertEqual(self.expected_result.dtype.names, results.dtype.names)
# Missing necessary data file
numpy.testing.assert_equal(results, results2)
self.assertRaises(TypeError,
cf.getCF, {}, 'ng',
file_name='../examples/example_lens_catalog.dat')
# Nonsensical correlation type
self.assertRaises(ValueError, cf.getCF, 'hello', lens_data, source_data, config=stile_args)
# Then, test a test that uses .getCF().
realshear = stile.sys_tests.GalaxyShearSysTest()
results3 = realshear(lens_data, source_data, config=stile_args)
numpy.testing.assert_equal(results, results3)
def test_WriteASCIITable(self):
"""Test the ability to write an ASCII table."""
# Must be done after test_read_ASCII_table() since it uses the read_ASCII_table function!
handle, filename = tempfile.mkstemp()
stile.file_io.WriteASCIITable(filename, self.table1)
results = stile.ReadASCIITable(filename)
# genfromtxt will cleverly figure out the last two columns are ints, which we want it to,
# but that causes problems here.
try:
numpy.testing.assert_equal(results, self.table1)
raise RuntimeError('Arrays are equal, but should not have the same format')
except AssertionError:
pass
numpy.testing.assert_equal(results.astype('f'), self.table1.astype('f'))
# check field reordering
field_list = ['f3', 'f4', 'f6', 'f0', 'f2', 'f1', 'f5']
stile.file_io.WriteASCIITable(filename, self.table1, fields=field_list)
results = stile.ReadASCIITable(filename)
numpy.testing.assert_equal(results.astype('f'), self.table1[field_list].astype('f'))
os.close(handle)
if not stile.file_io.has_fits:
# If there is a FITS handler, this table would be written as a FITS table, so we
# shouldn't check it. But otherwise these will be ASCII files, so test that
# WriteTable() is sending them through that function properly.
handle, filename = tempfile.mkstemp()
stile.file_io.WriteTable(filename, self.table1)
results = stile.ReadASCIITable(filename)
numpy.testing.assert_equal(self.table1.astype('f'), results.astype('f'))
os.close(handle)
def test_plot(self):
""" Test that the plotting routines successfully generate a plot """
stile_args = {
'ra_units': 'degrees',
'dec_units': 'degrees',
'min_sep': 0.05,
'max_sep': 1,
'sep_units': 'degrees',
'nbins': 20
}
cf = stile.sys_tests.CorrelationFunctionSysTest()
lens_data = stile.ReadASCIITable(
'../examples/example_lens_catalog.dat',
fields={
'id': 0,
'ra': 1,
'dec': 2,
'z': 3,
'g1': 4,
'g2': 5
})
source_data = stile.ReadASCIITable(
'../examples/example_source_catalog.dat',
fields={
'id': 0,
'ra': 1,
'dec': 2,
'z': 3,
'g1': 4,
'g2': 5
})
object_list = [
'GalaxyShear', 'BrightStarShear', 'StarXGalaxyShear',
'StarXStarShear'
]
for object_type in object_list:
obj = stile.CorrelationFunctionSysTest(object_type)
results = obj(lens_data, source_data, **stile_args)
pl = obj.plot(results)
self.assertIsInstance(pl, matplotlib.figure.Figure)
# Test underscore protection. If there's an underscore in the radius label somewhere,
# get rid of the non-underscore versions to make sure we hit that branch of the code,
# then test the plotting again
names = list(results.dtype.names)
names_no_units = [n.split(' [')[0] for n in names]
if 'R_nom' in names_no_units or 'R_nominal' in names_no_units:
for rname in ['meanR', '<R>', 'R']:
if rname in names_no_units:
index = names_no_units.index(rname)
names[index] = 'old_' + names[index]
results.dtype.names = names
pl = obj.plot(results)
self.assertIsInstance(pl, matplotlib.figure.Figure)
pl.savefig('examine.png')
def test_ReadASCIITable(self):
"""Test the ability to read in an ASCII table."""
# ReadASCIITable is a wrapper for numpy.genfromtxt() that turns things into formatted
# arrays if necessary, so we don't really need to test much of the functionality--just make
# sure that both natively formatted arrays (table_with_string) and natively raw arrays
# (treecorr_output) are both returned as formatted arrays.
results = stile.ReadASCIITable('test_data/TreeCorr_output.dat', comments='#')
numpy.testing.assert_equal(results, self.table1)
results = stile.ReadASCIITable('test_data/table_with_string.dat')
numpy.testing.assert_equal(results, self.table2_withstring)
results = stile.ReadTable('test_data/table_with_string.dat')
numpy.testing.assert_equal(results, self.table2_withstring)