ENH: Add triangular interferometer

dingo/gw/inference/gw_samplers.py

@@ -316,7 +316,7 @@ def _initialize_transforms(self):
             # transform data, since this transform is used by the GNPE sampler as
             # well.
             RepackageStrainsAndASDS(
-                ifos=self.detectors,
+                ifos=[ifo.name for ifo in InterferometerList(self.detectors)],
                 first_index=self.domain.min_idx,
             ),
             ToTorch(device=self.model.device),

dingo/gw/training/train_builders.py

@@ -86,12 +86,16 @@ def set_train_transforms(wfd, data_settings, asd_dataset_path, omit_transforms=N
     if omit_transforms is not None:
         print("Omitting \n\t" + "\n\t".join([t.__name__ for t in omit_transforms]))
 
+    # Build detector objects
+    ifo_list = InterferometerList(data_settings["detectors"])
+    ifo_names = [ifo.name for ifo in ifo_list]
+
     # By passing the wfd domain when instantiating the noise dataset, this ensures the
     # domains will match. In particular, it truncates the ASD dataset beyond the new
     # f_max, and sets it to 1 below f_min.
     asd_dataset = ASDDataset(
         asd_dataset_path,
-        ifos=data_settings["detectors"],
+        ifos=ifo_names,
         precision="single",
         domain_update=wfd.domain.domain_dict,
     )
@@ -103,8 +107,6 @@ def set_train_transforms(wfd, data_settings, asd_dataset_path, omit_transforms=N
         data_settings["inference_parameters"] = default_inference_parameters
 
     ref_time = data_settings["ref_time"]
-    # Build detector objects
-    ifo_list = InterferometerList(data_settings["detectors"])
 
     # Build transforms.
     transforms = [
@@ -170,7 +172,7 @@ def set_train_transforms(wfd, data_settings, asd_dataset_path, omit_transforms=N
         )
     )
     transforms.append(
-        RepackageStrainsAndASDS(data_settings["detectors"], first_index=domain.min_idx)
+        RepackageStrainsAndASDS(ifo_names, first_index=domain.min_idx)
     )
     if "random_strain_cropping" in data_settings:
         transforms.append(
@@ -331,7 +333,7 @@ def build_svd_for_embedding_network(
     print(f"Truncating SVD matrices below index {wfd.domain.min_idx}.")
     print("...V matrix shapes:")
     V_rb_list = []
-    for ifo in data_settings["detectors"]:
+    for ifo in ifos:
         V = basis_dict[ifo].V
         assert np.allclose(V[: wfd.domain.min_idx], 0)
         V = V[wfd.domain.min_idx :]

dingo/pipe/main.py

@@ -176,6 +176,10 @@ def fill_in_arguments_from_model(args, perform_arg_checks=True):
         psd_dict = {}
         rng = np.random.default_rng(args.generation_seed)
         for ifo_name in args.detectors:
+            if ifo_name in asd_dataset.asds:
+                asd_key = ifo_name # normal detector, e.g. 'H1'
+            else:
+                asd_key = [ifo.name for ifo in InterferometerList([ifo_name])][0]  # 'ET'-> 'ET1' and fixing 'ET1'
             psd_path = asd_dataset.save_psd(args.outdir, ifo_name, rng=rng)
             psd_dict[ifo_name] = str(psd_path)
         args.asd_dataset = None