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Adds impact resolution #257

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Adds impact resolution #257

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f64655b
add 'core' to reco tasks for the train model tool
TjarkMiener Aug 21, 2025
3d392c4
rename task to impact
TjarkMiener Aug 21, 2025
bfd5d88
include the impact for the prediction tool
TjarkMiener Aug 22, 2025
8088947
move predict tools into separate files
TjarkMiener Aug 28, 2025
e29217b
fix imports
TjarkMiener Aug 28, 2025
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20 changes: 20 additions & 0 deletions ctlearn/core/loader.py
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Original file line number Diff line number Diff line change
Expand Up @@ -170,6 +170,14 @@ def _get_mono_item(self, batch):
)
if "energy" in self.tasks:
labels["energy"] = batch["log_true_energy"].data
if "impact" in self.tasks:
labels["impact"] = np.stack(
(
batch["true_core_x"].data,
batch["true_core_y"].data,
),
axis=1,
)
if "skydirection" in self.tasks:
labels["skydirection"] = np.stack(
(
Expand Down Expand Up @@ -222,6 +230,7 @@ def _get_stereo_item(self, batch):
features, mono_feature_vectors, stereo_feature_vectors = [], [], []
true_shower_primary_class = []
log_true_energy = []
core_x, core_y = [], []
fov_lon, fov_lat, angular_separation = [], [], []
cam_coord_offset_x, cam_coord_offset_y, cam_coord_distance = [], [], []
for group_element in batch_grouped.groups:
Expand Down Expand Up @@ -260,6 +269,9 @@ def _get_stereo_item(self, batch):
)
if "energy" in self.tasks:
log_true_energy.append(group_element["log_true_energy"].data[0])
if "impact" in self.tasks:
core_x = group_element["true_core_x"].data[0]
core_y = group_element["true_core_y"].data[0]
if "skydirection" in self.tasks:
fov_lon.append(group_element["fov_lon"].data[0])
fov_lat.append(
Expand All @@ -285,6 +297,14 @@ def _get_stereo_item(self, batch):
)
if "energy" in self.tasks:
labels["energy"] = np.array(log_true_energy)
if "impact" in self.tasks:
labels["impact"] = np.stack(
(
np.array(core_x),
np.array(core_y),
),
axis=1,
)
if "skydirection" in self.tasks:
labels["skydirection"] = np.stack(
(
Expand Down
8 changes: 5 additions & 3 deletions ctlearn/core/model.py
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Original file line number Diff line number Diff line change
Expand Up @@ -87,11 +87,12 @@ class CTLearnModel(Component):
"energy": [512, 256, 1],
"cameradirection": [512, 256, 2],
"skydirection": [512, 256, 2],
"impact": [512, 256, 2],
},
allow_none=False,
help=(
"Dictionary containing the number of neurons in the fully connected head for each "
"task ('type', 'energy', 'cameradirection', 'skydirection'). Note: The number of neurons in the last layer "
"task ('type', 'energy', 'cameradirection', 'skydirection', 'impact'). Note: The number of neurons in the last layer "
"must match the number of classes or the number of reconstructed values."
),
).tag(config=True)
Expand All @@ -102,12 +103,13 @@ class CTLearnModel(Component):
"energy": "relu",
"cameradirection": "tanh",
"skydirection": "tanh",
"impact": "tanh",
},
allow_none=False,
help=(
"Dictionary containing the activation function for the fully connected head for each "
"task ('type', 'energy', 'cameradirection', 'skydirection'). Note: The default activation functions "
"are 'relu' for 'type' and 'energy' tasks, and 'tanh' for 'cameradirection' and 'skydirection' tasks. "
"task ('type', 'energy', 'cameradirection', 'skydirection', 'impact'). Note: The default activation functions "
"are 'relu' for 'type' and 'energy' tasks, and 'tanh' for 'cameradirection', 'skydirection' and 'impact' tasks. "
"The 'type' task uses 'softmax' as the final activation function."
),
).tag(config=True)
Expand Down
3 changes: 2 additions & 1 deletion ctlearn/core/tests/test_loader.py
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Expand Up @@ -21,7 +21,7 @@ def test_data_loader(dl1_tmp_path, dl1_gamma_file):
dl1_loader = DLDataLoader(
DLDataReader=dl1_reader,
indices=[0],
tasks=["type", "energy", "cameradirection", "skydirection"],
tasks=["type", "energy", "cameradirection", "skydirection", "impact"],
batch_size=1,
)
# Get the features and labels fgrom the data loader for one batch
Expand All @@ -32,6 +32,7 @@ def test_data_loader(dl1_tmp_path, dl1_gamma_file):
and "energy" in labels
and "cameradirection" in labels
and "skydirection" in labels
and "impact" in labels
)
# Check the shape of the features
assert features["input"].shape == (1, 110, 110, 2)
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