Imr phenom xhm support

dingo/gw/waveform_generator/waveform_generator.py

@@ -630,8 +630,9 @@ def generate_hplus_hcross_m(
             # Step 3: Separate negative and positive frequency parts of the modes,
             # and add contributions according to their transformation behavior under
             # phase shifts.
+
             pol_m = wfg_utils.get_polarizations_from_fd_modes_m(
-                hlm_fd, iota, parameters["phase"]
+                hlm_fd, iota, parameters["phase"], self.approximant_str
             )
 
         else:
@@ -658,9 +659,13 @@ def generate_FD_modes_LO(self, parameters):
             values.
         iota: float
         """
-        # TD approximants that are implemented in J frame. Currently tested for:
-        #   101: IMRPhenomXPHM
-        if self.approximant in [101]:
+        #  FD Waveform approximants that are implemented in either the L0 or J frame.  Currently tested for:
+        #  IMRPhenomXPHM - Modes returned in J-Frame
+        #  IMRPhenomXHM - Modes returned in L0-Frame
+
+
+        tested_approximants = ["IMRPhenomXPHM","IMRPhenomXHM"]
+        if LS.GetStringFromApproximant(self.approximant) in tested_approximants:
             parameters_lal_fd_modes = self._convert_parameters(
                 {**parameters, "f_ref": self.f_ref},
                 lal_target_function="SimInspiralChooseFDModes",
@@ -670,17 +675,18 @@ def generate_FD_modes_LO(self, parameters):
             # unpack linked list, convert lal objects to arrays
             hlm_fd = wfg_utils.linked_list_modes_to_dict_modes(hlm_fd)
             hlm_fd = {k: v.data.data for k, v in hlm_fd.items()}
-            # For the waveform models considered here (e.g., IMRPhenomXPHM), the modes
-            # are returned in the J frame (where the observer is at inclination=theta_JN,
-            # azimuth=0). In this frame, the dependence on the reference phase enters
-            # via the modes themselves. We need to convert to the L0 frame so that the
-            # dependence on phase enters via the spherical harmonics.
-            hlm_fd = frame_utils.convert_J_to_L0_frame(
-                hlm_fd,
-                parameters,
-                self,
-                spin_conversion_phase=self.spin_conversion_phase,
-            )
+
+            # For waveform models where the modes are returned in the J frame (where the observer is
+            # at an inclination=theta_JN, azimuth=0), the dependence on the reference phase enters
+            # via the modes themselves.  We need to convert to the L0 frame so that the
+            # dependence on phase enters via the spherical harmonics. 
+            if LS.GetStringFromApproximant(self.approximant) == "IMRPhenomXPHM":
+                hlm_fd = frame_utils.convert_J_to_L0_frame(
+                    hlm_fd,
+                    parameters,
+                    self,
+                    spin_conversion_phase=self.spin_conversion_phase,
+                )
             return hlm_fd, iota
         else:
             raise NotImplementedError(
@@ -713,7 +719,8 @@ def generate_TD_modes_L0(self, parameters):
         """
         # TD approximants that are implemented in L0 frame. Currently tested for:
         #   52: SEOBNRv4PHM
-        if self.approximant in [52]:
+        tested_approximants = ["SEOBNRv4PHM"]
+        if LS.GetStringFromApproximant(self.approximant) in tested_approximants:
             parameters_lal_td_modes, iota = self._convert_parameters(
                 {**parameters, "f_ref": self.f_ref},
                 lal_target_function="SimInspiralChooseTDModes",

dingo/gw/waveform_generator/wfg_utils.py

@@ -141,7 +141,7 @@ def td_modes_to_fd_modes(hlm_td, domain):
     return hlm_fd
 
 
-def get_polarizations_from_fd_modes_m(hlm_fd, iota, phase):
+def get_polarizations_from_fd_modes_m(hlm_fd, iota, phase, approximant_str = None):
     pol_m = {}
     polarizations = ["h_plus", "h_cross"]
 
@@ -152,7 +152,13 @@ def get_polarizations_from_fd_modes_m(hlm_fd, iota, phase):
 
         # In the L0 frame, we compute the polarizations from the modes using the
         # spherical harmonics below.
-        ylm = lal.SpinWeightedSphericalHarmonic(iota, np.pi / 2 - phase, -2, l, m)
+        #Some aligned spin models use phase internally to generate hlm so np.pi/2 - phase may give wrong result.
+        # It is important to understand what convention is used for a given waveform model before adding it.
+
+        if approximant_str == "IMRPhenomXHM":
+            ylm = lal.SpinWeightedSphericalHarmonic(iota, np.pi / 2, -2, l, m)
+        else:
+            ylm = lal.SpinWeightedSphericalHarmonic(iota, np.pi / 2 - phase, -2, l, m)
         ylmstar = ylm.conjugate()
 
         # Modes (l,m) are defined on domain -f_max,...,-f_min,...0,...,f_min,...,f_max.

tests/gw/waveform_generator/test_wfg_m.py

@@ -37,7 +37,7 @@ def uniform_fd_domain():
     return domain
 
 
-@pytest.fixture(params=["IMRPhenomXPHM", "SEOBNRv4PHM", "SEOBNRv5PHM", "SEOBNRv5HM"])
+@pytest.fixture(params=["IMRPhenomXPHM", "IMRPhenomXHM", "SEOBNRv4PHM", "SEOBNRv5PHM", "SEOBNRv5HM"])
 def approximant(request):
     return request.param
 
@@ -135,9 +135,9 @@ def tolerances(approximant):
 # Uncomment to test only one approximant.
 try:
     import pyseobnr
-    approximant_list = ["IMRPhenomXPHM", "SEOBNRv4PHM", "SEOBNRv5PHM", "SEOBNRv5HM"]
+    approximant_list = ["IMRPhenomXPHM", "IMRPhenomXHM", "SEOBNRv4PHM", "SEOBNRv5PHM", "SEOBNRv5HM"]
 except ImportError:
-    approximant_list = ["IMRPhenomXPHM", "SEOBNRv4PHM"]
+    approximant_list = ["IMRPhenomXPHM", "IMRPhenomXHM", "SEOBNRv4PHM"]
 @pytest.mark.parametrize("approximant", approximant_list)
 def test_generate_hplus_hcross_m(intrinsic_prior, wfg, num_evaluations, tolerances):
     mismatches = []