Fixed an issue in madminer.sampling
@@ -267,6 +267,7 @@ class SampleAugmenter:
self.n_parameters = len(self.parameters)
self.n_benchmarks = len(self.benchmarks)
self.n_benchmarks_phys = np.sum(np.logical_not(self.benchmark_is_nuisance))
+ self.n_nuisance_parameters = self.n_benchmarks - self.n_benchmarks_phys
logging.info("Found %s parameters:", self.n_parameters)
for key, values in six.iteritems(self.parameters):
@@ -1375,6 +1376,8 @@ class SampleAugmenter:
samples_augmented_data.append(np.zeros((n_samples, 1)))
elif definition[0] == "score":
samples_augmented_data.append(np.zeros((n_samples, self.n_parameters)))
+ elif definition[0] == "nuisance_score":
+ samples_augmented_data.append(np.zeros((n_samples, self.n_nuisance_parameters)))
largest_weight = 0.0
