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Save results immediately #422

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Save results immediately #422

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cba097c
Only within session for now
PierreGtch Jul 11, 2023
e3466d9
Only cross-session and cross-subject
PierreGtch Jul 11, 2023
6414029
Merge branch 'develop' into results-saving
bruAristimunha Aug 1, 2023
1b4c0b6
Merge branch 'develop' into results-saving
bruAristimunha Aug 2, 2023
135bb5e
Merge branch 'develop' into results-saving
sylvchev Aug 18, 2023
0f60c22
Merge branch 'develop' into results-saving
PierreGtch May 22, 2024
9365c53
Merge branch 'develop' into results-saving
bruAristimunha Jul 3, 2024
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4 changes: 1 addition & 3 deletions moabb/evaluations/base.py
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Original file line number Diff line number Diff line change
Expand Up @@ -159,9 +159,7 @@ def process(self, pipelines, param_grid=None):

for dataset in self.datasets:
log.info("Processing dataset: {}".format(dataset.code))
results = self.evaluate(dataset, pipelines, param_grid)
for res in results:
self.push_result(res, pipelines)
_ = self.evaluate(dataset, pipelines, param_grid)

return self.results.to_dataframe(pipelines=pipelines)

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7 changes: 5 additions & 2 deletions moabb/evaluations/evaluations.py
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Original file line number Diff line number Diff line change
Expand Up @@ -33,7 +33,6 @@
except ImportError:
_carbonfootprint = False


log = logging.getLogger(__name__)

# Numpy ArrayLike is only available starting from Numpy 1.20 and Python 3.8
Expand Down Expand Up @@ -305,6 +304,7 @@ def _evaluate_subject(self, dataset, pipelines, param_grid, subject):
if _carbonfootprint:
res["carbon_emission"] = (1000 * emissions,)
subject_results.append(res)
self.push_result(res, pipelines)

return subject_results

Expand Down Expand Up @@ -398,7 +398,7 @@ def _evaluate_learning_curve(self, dataset, pipelines):
continue
not_enough_data = False
log.info(
f"Permutation: {perm_i+1},"
f"Permutation: {perm_i + 1},"
f" Training samples: {len(subset_indices)}"
)

Expand Down Expand Up @@ -661,6 +661,8 @@ def process_subject(self, subject, param_grid, pipelines, dataset):
res["carbon_emission"] = (1000 * (emissions + emissions_grid),)

results.append(res)
self.push_result(res, pipelines)

return results

def is_valid(self, dataset):
Expand Down Expand Up @@ -859,6 +861,7 @@ def evaluate(self, dataset, pipelines, param_grid):
res["carbon_emission"] = (
1000 * (emissions + emissions_grid[name]),
)
self.push_result(res, pipelines)
yield res

def is_valid(self, dataset):
Expand Down
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