McIntosh Code (#174)

* added mcintosh code and moved mount_wilson code to respective folder

* renamed mount_wilson to hale

---------

Co-authored-by: Edoardo Legnaro <[email protected]>

Author: edoardolegnaro

arccnet/cli/main.py

@@ -9,9 +9,9 @@
 from collections.abc import Mapping
 
 from arccnet import load_config
-from arccnet.models.cutouts import config as config_module
-from arccnet.models.cutouts.inference import predict
-from arccnet.models.cutouts.train import run_training
+from arccnet.models.cutouts.hale import config as config_module
+from arccnet.models.cutouts.hale.inference import predict
+from arccnet.models.cutouts.hale.train import run_training
 from arccnet.pipeline.main import process_ar_catalogs, process_ars, process_flares
 from arccnet.utils.logging import get_logger
 

arccnet/models/cutouts/hale/__init__.py

@@ -12,7 +12,7 @@
 from astropy.io import fits
 
 from arccnet.models import train_utils as ut_t
-from arccnet.models.cutouts import config
+from arccnet.models.cutouts.hale import config
 from arccnet.utils.logging import get_logger
 from arccnet.visualisation import utils as ut_v
 
@@ -66,7 +66,7 @@ def run_inference(model, fits_file_path, device):
         model.eval()
         with torch.no_grad():
             data = preprocess_fits_data(fits_file_path)
-            data = data.to(device)  # Removed extra unsqueeze since preprocess already has unsqueeze
+            data = data.to(device)
             output = model(data)
         return output.cpu().numpy()
     except Exception:

arccnet/models/cutouts/config.py arccnet/models/cutouts/hale/config.pyarccnet/models/cutouts/config.py renamed to arccnet/models/cutouts/hale/config.py

@@ -4,7 +4,7 @@
 import torch
 from comet_ml import Experiment
 
-import arccnet.models.cutouts.config as config
+import arccnet.models.cutouts.hale.config as config
 import arccnet.models.dataset_utils as ut_d
 import arccnet.models.train_utils as ut_t
 import arccnet.visualisation.utils as ut_v

arccnet/models/cutouts/inference.py arccnet/models/cutouts/hale/inference.pyarccnet/models/cutouts/inference.py renamed to arccnet/models/cutouts/hale/inference.py

@@ -0,0 +1,44 @@
+import os
+
+import torchvision.transforms as v2
+
+### General ###
+resnet_version = "resnet18"
+gpu_index = 0
+epochs = 500
+patience = 15
+batch_size = 32
+num_workers = 12  # os.cpu_count()
+learning_rate = 1e-5
+random_state = 42
+
+train_transforms = v2.Compose(
+    [
+        #         v2.RandomVerticalFlip(),
+        #         v2.RandomHorizontalFlip(),
+        v2.RandomAffine(degrees=10, translate=(0.05, 0.05), scale=(0.98, 1.02)),
+    ]
+)
+
+### Teacher Forcing ###
+initial_teacher_forcing_ratio = 0.75
+min_teacher_forcing_ratio = 0.0
+teacher_forcing_decay = 0.9
+teacher_forcing = True
+
+### Dataset ###
+data_folder = os.getenv("ARCAFF_DATA_FOLDER", "../../../../../data/")
+dataset_folder = "arccnet-cutout-dataset-v20240715"
+df_name = "cutout-magnetic-catalog-v20240715.parq"
+long_limit_deg = 65
+train_size = 0.7
+val_size = 0.15
+test_size = 0.15
+
+### Logging ###
+plot_histograms = False
+
+### Comet ###
+use_comet = True
+project_name = "arcaff-mcintosh"
+workspace = "arcaff"