Added code to reverse transforms for more flexibility

src/jimgw/single_event/transforms.py

@@ -4,7 +4,11 @@
 from astropy.time import Time
 
 from jimgw.single_event.detector import GroundBased2G
-from jimgw.transforms import BijectiveTransform, NtoNTransform
+from jimgw.transforms import (
+    BijectiveTransform,
+    NtoNTransform,
+    reverse_bijective_transform,
+)
 from jimgw.single_event.utils import (
     m1_m2_to_Mc_q,
     Mc_q_to_m1_m2,
@@ -20,111 +24,56 @@
 
 
 @jaxtyped(typechecker=typechecker)
-class ComponentMassesToChirpMassMassRatioTransform(BijectiveTransform):
-    """
-    Transform chirp mass and mass ratio to component masses
-
-    Parameters
-    ----------
-    name_mapping : tuple[list[str], list[str]]
-            The name mapping between the input and output dictionary.
+class SpinToCartesianSpinTransform(NtoNTransform):
     """
-
-    def __init__(
-        self,
-        name_mapping: tuple[list[str], list[str]],
-    ):
-        super().__init__(name_mapping)
-        assert (
-            "m_1" in name_mapping[0]
-            and "m_2" in name_mapping[0]
-            and "M_c" in name_mapping[1]
-            and "q" in name_mapping[1]
-        )
-
-        def named_transform(x):
-            Mc, q = m1_m2_to_Mc_q(x["m_1"], x["m_2"])
-            return {"M_c": Mc, "q": q}
-
-        self.transform_func = named_transform
-
-        def named_inverse_transform(x):
-            m1, m2 = Mc_q_to_m1_m2(x["M_c"], x["q"])
-            return {"m_1": m1, "m_2": m2}
-
-        self.inverse_transform_func = named_inverse_transform
-
-
-@jaxtyped(typechecker=typechecker)
-class ComponentMassesToChirpMassSymmetricMassRatioTransform(BijectiveTransform):
+    Spin to Cartesian spin transformation
     """
-    Transform mass ratio to symmetric mass ratio
 
-    Parameters
-    ----------
-    name_mapping : tuple[list[str], list[str]]
-            The name mapping between the input and output dictionary.
-
-    """
+    freq_ref: Float
 
     def __init__(
         self,
-        name_mapping: tuple[list[str], list[str]],
+        freq_ref: Float,
     ):
-        super().__init__(name_mapping)
-        assert (
-            "m_1" in name_mapping[0]
-            and "m_2" in name_mapping[0]
-            and "M_c" in name_mapping[1]
-            and "eta" in name_mapping[1]
+        name_mapping = (
+            ["theta_jn", "phi_jl", "theta_1", "theta_2", "phi_12", "a_1", "a_2"],
+            ["iota", "s1_x", "s1_y", "s1_z", "s2_x", "s2_y", "s2_z"],
         )
+        super().__init__(name_mapping)
+
+        self.freq_ref = freq_ref
 
         def named_transform(x):
-            Mc, eta = m1_m2_to_Mc_eta(x["m_1"], x["m_2"])
-            return {"M_c": Mc, "eta": eta}
+            iota, s1x, s1y, s1z, s2x, s2y, s2z = spin_to_cartesian_spin(
+                x["theta_jn"],
+                x["phi_jl"],
+                x["theta_1"],
+                x["theta_2"],
+                x["phi_12"],
+                x["a_1"],
+                x["a_2"],
+                x["M_c"],
+                x["q"],
+                self.freq_ref,
+                x["phase_c"],
+            )
+            return {
+                "iota": iota,
+                "s1_x": s1x,
+                "s1_y": s1y,
+                "s1_z": s1z,
+                "s2_x": s2x,
+                "s2_y": s2y,
+                "s2_z": s2z,
+            }
 
         self.transform_func = named_transform
 
-        def named_inverse_transform(x):
-            m1, m2 = Mc_eta_to_m1_m2(x["M_c"], x["q"])
-            return {"m_1": m1, "m_2": m2}
-
-        self.inverse_transform_func = named_inverse_transform
-
-
-@jaxtyped(typechecker=typechecker)
-class MassRatioToSymmetricMassRatioTransform(BijectiveTransform):
-    """
-    Transform mass ratio to symmetric mass ratio
-
-    Parameters
-    ----------
-    name_mapping : tuple[list[str], list[str]]
-            The name mapping between the input and output dictionary.
-
-    """
-
-    def __init__(
-        self,
-        name_mapping: tuple[list[str], list[str]],
-    ):
-        super().__init__(name_mapping)
-        assert "q" == name_mapping[0][0] and "eta" == name_mapping[1][0]
-
-        self.transform_func = lambda x: {"eta": q_to_eta(x["q"])}
-        self.inverse_transform_func = lambda x: {"q": eta_to_q(x["eta"])}
-
 
 @jaxtyped(typechecker=typechecker)
 class SkyFrameToDetectorFrameSkyPositionTransform(BijectiveTransform):
     """
     Transform sky frame to detector frame sky position
-
-    Parameters
-    ----------
-    name_mapping : tuple[list[str], list[str]]
-            The name mapping between the input and output dictionary.
-
     """
 
     gmst: Float
@@ -133,10 +82,10 @@ class SkyFrameToDetectorFrameSkyPositionTransform(BijectiveTransform):
 
     def __init__(
         self,
-        name_mapping: tuple[list[str], list[str]],
         gps_time: Float,
         ifos: GroundBased2G,
     ):
+        name_mapping = (["ra", "dec"], ["zenith", "azimuth"])
         super().__init__(name_mapping)
 
         self.gmst = (
@@ -146,13 +95,6 @@ def __init__(
         self.rotation = euler_rotation(delta_x)
         self.rotation_inv = jnp.linalg.inv(self.rotation)
 
-        assert (
-            "ra" in name_mapping[0]
-            and "dec" in name_mapping[0]
-            and "zenith" in name_mapping[1]
-            and "azimuth" in name_mapping[1]
-        )
-
         def named_transform(x):
             zenith, azimuth = ra_dec_to_zenith_azimuth(
                 x["ra"], x["dec"], self.gmst, self.rotation
@@ -169,63 +111,45 @@ def named_inverse_transform(x):
 
         self.inverse_transform_func = named_inverse_transform
 
+def named_m1_m2_to_Mc_q(x):
+    Mc, q = m1_m2_to_Mc_q(x["m_1"], x["m_2"])
+    return {"M_c": Mc, "q": q}
 
-@jaxtyped(typechecker=typechecker)
-class SpinToCartesianSpinTransform(NtoNTransform):
-    """
-    Spin to Cartesian spin transformation
-    """
+def named_Mc_q_to_m1_m2(x):
+    m1, m2 = Mc_q_to_m1_m2(x["M_c"], x["q"])
+    return {"m_1": m1, "m_2": m2}
 
-    freq_ref: Float
+ComponentMassesToChirpMassMassRatioTransform = BijectiveTransform((["m_1", "m_2"], ["M_c", "q"]))
+ComponentMassesToChirpMassMassRatioTransform.transform_func = named_m1_m2_to_Mc_q
+ComponentMassesToChirpMassMassRatioTransform.inverse_transform_func = named_Mc_q_to_m1_m2
 
-    def __init__(
-        self,
-        name_mapping: tuple[list[str], list[str]],
-        freq_ref: Float,
-    ):
-        super().__init__(name_mapping)
+def named_m1_m2_to_Mc_eta(x):
+    Mc, eta = m1_m2_to_Mc_eta(x["m_1"], x["m_2"])
+    return {"M_c": Mc, "eta": eta}
 
-        self.freq_ref = freq_ref
+def named_Mc_eta_to_m1_m2(x):
+    m1, m2 = Mc_eta_to_m1_m2(x["M_c"], x["eta"])
+    return {"m_1": m1, "m_2": m2}
 
-        assert (
-            "theta_jn" in name_mapping[0]
-            and "phi_jl" in name_mapping[0]
-            and "theta_1" in name_mapping[0]
-            and "theta_2" in name_mapping[0]
-            and "phi_12" in name_mapping[0]
-            and "a_1" in name_mapping[0]
-            and "a_2" in name_mapping[0]
-            and "iota" in name_mapping[1]
-            and "s1_x" in name_mapping[1]
-            and "s1_y" in name_mapping[1]
-            and "s1_z" in name_mapping[1]
-            and "s2_x" in name_mapping[1]
-            and "s2_y" in name_mapping[1]
-            and "s2_z" in name_mapping[1]
-        )
+ComponentMassesToChirpMassSymmetricMassRatioTransform = BijectiveTransform((["m_1", "m_2"], ["M_c", "eta"]))
+ComponentMassesToChirpMassSymmetricMassRatioTransform.transform_func = named_m1_m2_to_Mc_eta
+ComponentMassesToChirpMassSymmetricMassRatioTransform.inverse_transform_func = named_Mc_eta_to_m1_m2
 
-        def named_transform(x):
-            iota, s1x, s1y, s1z, s2x, s2y, s2z = spin_to_cartesian_spin(
-                x["theta_jn"],
-                x["phi_jl"],
-                x["theta_1"],
-                x["theta_2"],
-                x["phi_12"],
-                x["a_1"],
-                x["a_2"],
-                x["M_c"],
-                x["q"],
-                self.freq_ref,
-                x["phase_c"],
-            )
-            return {
-                "iota": iota,
-                "s1_x": s1x,
-                "s1_y": s1y,
-                "s1_z": s1z,
-                "s2_x": s2x,
-                "s2_y": s2y,
-                "s2_z": s2z,
-            }
+def named_q_to_eta(x):
+    return {"eta": q_to_eta(x["q"])}
+def named_eta_to_q(x):
+    return {"q": eta_to_q(x["eta"])}
+MassRatioToSymmetricMassRatioTransform = BijectiveTransform((["q"], ["eta"]))
+MassRatioToSymmetricMassRatioTransform.transform_func = named_q_to_eta
+MassRatioToSymmetricMassRatioTransform.inverse_transform_func = named_eta_to_q
 
-        self.transform_func = named_transform
+
+ChirpMassMassRatioToComponentMassesTransform = reverse_bijective_transform(
+    ComponentMassesToChirpMassMassRatioTransform
+)
+ChirpMassSymmetricMassRatioToComponentMassesTransform = reverse_bijective_transform(
+    ComponentMassesToChirpMassSymmetricMassRatioTransform
+)
+SymmetricMassRatioToMassRatioTransform = reverse_bijective_transform(
+    MassRatioToSymmetricMassRatioTransform
+)

src/jimgw/transforms.py

@@ -445,3 +445,19 @@ def __init__(
             )
             for i in range(len(name_mapping[1]))
         }
+
+
+def reverse_bijective_transform(
+    original_transform: BijectiveTransform,
+) -> BijectiveTransform:
+
+    reversed_name_mapping = (
+        original_transform.name_mapping[1],
+        original_transform.name_mapping[0],
+    )
+    reversed_transform = BijectiveTransform(name_mapping=reversed_name_mapping)
+    reversed_transform.transform_func = original_transform.inverse_transform_func
+    reversed_transform.inverse_transform_func = original_transform.transform_func
+    reversed_transform.__repr__ = lambda: f"Reversed{repr(original_transform)}"
+
+    return reversed_transform

test/integration/.gitignore

@@ -0,0 +1,2 @@
+outdir/
+figures/

test/integration/test_GW150914_D.py

@@ -1,3 +1,7 @@
+import os 
+os.environ["CUDA_VISIBLE_DEVICES"] = "0"
+os.environ["XLA_PYTHON_CLIENT_MEM_FRACTION"] = "0.10"
+
 import jax
 import jax.numpy as jnp
 
@@ -10,6 +14,8 @@
 from jimgw.single_event.transforms import ComponentMassesToChirpMassSymmetricMassRatioTransform, SkyFrameToDetectorFrameSkyPositionTransform, ComponentMassesToChirpMassMassRatioTransform
 from jimgw.single_event.utils import Mc_q_to_m1_m2
 from flowMC.strategy.optimization import optimization_Adam
+from flowMC.utils.postprocessing import plot_summary
+import optax
 
 jax.config.update("jax_enable_x64", True)
 
@@ -62,7 +68,7 @@
 )
 
 sample_transforms = [
-    ComponentMassesToChirpMassMassRatioTransform(name_mapping=[["m_1", "m_2"], ["M_c", "q"]]),
+    ComponentMassesToChirpMassMassRatioTransform,
     BoundToUnbound(name_mapping = [["M_c"], ["M_c_unbounded"]], original_lower_bound=M_c_min, original_upper_bound=M_c_max),
     BoundToUnbound(name_mapping = [["q"], ["q_unbounded"]], original_lower_bound=q_min, original_upper_bound=q_max),
     BoundToUnbound(name_mapping = [["s1_z"], ["s1_z_unbounded"]] , original_lower_bound=-1.0, original_upper_bound=1.0),
@@ -72,13 +78,13 @@
     BoundToUnbound(name_mapping = [["phase_c"], ["phase_c_unbounded"]] , original_lower_bound=0.0, original_upper_bound=2 * jnp.pi),
     BoundToUnbound(name_mapping = [["iota"], ["iota_unbounded"]], original_lower_bound=0., original_upper_bound=jnp.pi),
     BoundToUnbound(name_mapping = [["psi"], ["psi_unbounded"]], original_lower_bound=0.0, original_upper_bound=jnp.pi),
-    SkyFrameToDetectorFrameSkyPositionTransform(name_mapping = [["ra", "dec"], ["zenith", "azimuth"]], gps_time=gps, ifos=ifos),
+    SkyFrameToDetectorFrameSkyPositionTransform(gps_time=gps, ifos=ifos),
     BoundToUnbound(name_mapping = [["zenith"], ["zenith_unbounded"]], original_lower_bound=0.0, original_upper_bound=jnp.pi),
     BoundToUnbound(name_mapping = [["azimuth"], ["azimuth_unbounded"]], original_lower_bound=0.0, original_upper_bound=2 * jnp.pi),
 ]
 
 likelihood_transforms = [
-    ComponentMassesToChirpMassSymmetricMassRatioTransform(name_mapping=[["m_1", "m_2"], ["M_c", "eta"]]),
+    ComponentMassesToChirpMassSymmetricMassRatioTransform,
 ]
 
 likelihood = TransientLikelihoodFD(
@@ -89,7 +95,6 @@
     post_trigger_duration=2,
 )
 
-
 mass_matrix = jnp.eye(11)
 mass_matrix = mass_matrix.at[1, 1].set(1e-3)
 mass_matrix = mass_matrix.at[5, 5].set(1e-3)
@@ -101,7 +106,6 @@
 n_loop_training = 1
 learning_rate = 1e-4
 
-
 jim = Jim(
     likelihood,
     prior,
@@ -127,4 +131,4 @@
 
 jim.sample(jax.random.PRNGKey(42))
 jim.get_samples()
-jim.print_summary()
+jim.print_summary()