def get_m1m2_grid(m1_range, m2_range, filtering_criteria):
"""Return a meshgrid of m1, m2, z points based on filtering criteria.
The returned meshgrid can be used to create a contour plot based on the filtering
criteria
:param m1_range:
:param m2_range:
:param filtering_criteria:
:return:
"""
xs = np.linspace(m1_range[0], m1_range[1], 1000)
ys = np.linspace(m2_range[0], m2_range[1], 1000)[::-1]
m1, m2 = np.meshgrid(xs, ys)
z = np.zeros(shape=(len(xs), len(ys)))
for nrx, loop_m1 in enumerate(tqdm(xs)):
for nry, loop_m2 in enumerate(ys):
if loop_m2 > loop_m1:
pass # by definition, we choose only m2 smaller than m1
if loop_m2 < loop_m1:
mc = conversion.component_masses_to_chirp_mass(loop_m1, loop_m2)
M = conversion.component_masses_to_total_mass(loop_m1, loop_m2)
q = conversion.component_masses_to_mass_ratio(loop_m1, loop_m2)
if filtering_criteria(loop_m1, loop_m2, mc, q, M) == 1:
z[nry][nrx] = 1
return m1, m2, z
def setUp(self):
self.search_keys = []
self.parameters = dict()
self.component_mass_pars = dict(mass_1=1.4, mass_2=1.4)
self.mass_parameters = self.component_mass_pars.copy()
self.mass_parameters[
"mass_ratio"] = conversion.component_masses_to_mass_ratio(
**self.component_mass_pars)
self.mass_parameters[
"symmetric_mass_ratio"] = conversion.component_masses_to_symmetric_mass_ratio(
**self.component_mass_pars)
self.mass_parameters[
"chirp_mass"] = conversion.component_masses_to_chirp_mass(
**self.component_mass_pars)
self.mass_parameters[
"total_mass"] = conversion.component_masses_to_total_mass(
**self.component_mass_pars)
self.component_tidal_parameters = dict(lambda_1=300, lambda_2=300)
self.all_component_pars = self.component_tidal_parameters.copy()
self.all_component_pars.update(self.component_mass_pars)
self.tidal_parameters = self.component_tidal_parameters.copy()
self.tidal_parameters[
"lambda_tilde"] = conversion.lambda_1_lambda_2_to_lambda_tilde(
**self.all_component_pars)
self.tidal_parameters[
"delta_lambda_tilde"] = conversion.lambda_1_lambda_2_to_delta_lambda_tilde(
**self.all_component_pars)
def get_m1m2_grid(m1_range, m2_range, prior, resolution):
"""Generate a grid of m1 and m2 and mark point if in prior space."""
xs = np.linspace(m1_range[0], m1_range[1], resolution)
ys = np.linspace(m2_range[0], m2_range[1], resolution)[::-1]
m1, m2 = np.meshgrid(xs, ys)
in_prior = np.zeros(shape=(len(xs), len(ys)))
for nrx, loop_m1 in enumerate(tqdm(xs)):
for nry, loop_m2 in enumerate(ys):
if loop_m2 > loop_m1:
pass # by definition, we choose only m2 smaller than m1
if loop_m2 < loop_m1:
mc = component_masses_to_chirp_mass(loop_m1, loop_m2)
q = component_masses_to_mass_ratio(loop_m1, loop_m2)
in_prior[nry][nrx] = prior.prob(
dict(chirp_mass=mc, mass_ratio=q, mass_2=loop_m2))
return m1, m2, in_prior
def get_event_status(catalogue_df):
data = []
for rowid, event in catalogue_df.iterrows():
m1 = event.mass_1_source
m2 = event.mass_2_source
mc = conversion.component_masses_to_chirp_mass(m1, m2)
M = conversion.component_masses_to_total_mass(m1, m2)
q = conversion.component_masses_to_mass_ratio(m1, m2)
data.append(
{
"event": event.commonName,
"catalog": event["catalog.shortName"],
"in_prior": contour_condition(m1, m2, mc, q, M) == 1,
"m1_source": m1,
"m2_source": m2,
"M": M,
}
)
return pd.DataFrame(data)
def test_component_masses_to_mass_ratio(self):
mass_ratio = conversion.component_masses_to_mass_ratio(self.mass_1, self.mass_2)
self.assertAlmostEqual(self.mass_ratio, mass_ratio)
