add conversion funtion (#173)

ml4gw/waveforms/cbc/taylorf2.py

@@ -4,6 +4,7 @@
 from ml4gw.constants import MPC_SEC, MTSUN_SI, PI
 from ml4gw.constants import EulerGamma as GAMMA
 from ml4gw.types import BatchTensor, FrequencySeries1d
+from ml4gw.waveforms.conversion import chirp_mass_and_mass_ratio_to_components
 
 
 class TaylorF2(torch.nn.Module):
@@ -60,8 +61,11 @@ def forward(
             or phic.shape[0] != inclination.shape[0]
         ):
             raise RuntimeError("Tensors should have same batch size")
-        mass2 = chirp_mass * (1.0 + mass_ratio) ** 0.2 / mass_ratio**0.6
-        mass1 = mass_ratio * mass2
+
+        mass1, mass2 = chirp_mass_and_mass_ratio_to_components(
+            chirp_mass, mass_ratio
+        )
+
         cfac = torch.cos(inclination)
         pfac = 0.5 * (1.0 + cfac * cfac)
 

ml4gw/waveforms/conversion.py

@@ -32,6 +32,23 @@ def XLALSimInspiralL_2PN(eta: BatchTensor):
     return 1.5 + eta / 6.0
 
 
+def chirp_mass_and_mass_ratio_to_components(
+    chirp_mass: BatchTensor, mass_ratio: BatchTensor
+):
+    """
+    Compute component masses from chirp mass and mass ratio.
+    Args:
+        chirp_mass: Tensor of chirp mass values
+        mass_ratio:
+            Tensor of mass ratio values, `m2 / m1`,
+            where m1 >= m2, so that mass_ratio <= 1
+    """
+    total_mass = chirp_mass * (1 + mass_ratio) ** 1.2 / mass_ratio**0.6
+    mass_1 = total_mass / (1 + mass_ratio)
+    mass_2 = mass_1 * mass_ratio
+    return mass_1, mass_2
+
+
 def bilby_spins_to_lalsim(
     theta_jn: BatchTensor,
     phi_jl: BatchTensor,

tests/waveforms/cbc/test_cbc_waveforms.py

@@ -7,6 +7,7 @@
 from torch.distributions import Uniform
 
 import ml4gw.waveforms as waveforms
+from ml4gw.waveforms.conversion import chirp_mass_and_mass_ratio_to_components
 
 
 @pytest.fixture(params=[256, 1024, 2048])
@@ -108,8 +109,9 @@ def test_taylor_f2(
     theta_jn,
     sample_rate,
 ):
-    mass_2 = chirp_mass * (1 + mass_ratio) ** 0.2 / mass_ratio**0.6
-    mass_1 = mass_ratio * mass_2
+    mass_1, mass_2 = chirp_mass_and_mass_ratio_to_components(
+        chirp_mass, mass_ratio
+    )
 
     # compare each waveform with lalsimulation
     for i in range(len(chirp_mass)):
@@ -235,9 +237,9 @@ def test_phenom_d(
     sample_rate,
     f_ref,
 ):
-    total_mass = chirp_mass * (1 + mass_ratio) ** 1.2 / mass_ratio**0.6
-    mass_1 = total_mass / (1 + mass_ratio)
-    mass_2 = mass_1 * mass_ratio
+    mass_1, mass_2 = chirp_mass_and_mass_ratio_to_components(
+        chirp_mass, mass_ratio
+    )
 
     # compare each waveform with lalsimulation
     for i in range(len(chirp_mass)):