From 395b79148ac1ac2327aad8946695bf6edfe2b716 Mon Sep 17 00:00:00 2001 From: Andrei Cuceu Date: Fri, 17 Nov 2023 14:24:15 -0500 Subject: [PATCH] Fix fastmc results array --- vega/analysis.py | 10 +++++----- 1 file changed, 5 insertions(+), 5 deletions(-) diff --git a/vega/analysis.py b/vega/analysis.py index 21f5206..efb5c13 100644 --- a/vega/analysis.py +++ b/vega/analysis.py @@ -182,7 +182,7 @@ def run_monte_carlo(self, fiducial_model, num_mocks=1, seed=0, scale=None): self.mc_failed_mask = [] for i in range(num_mocks): - print(f'INFO: running Monte Carlo realization {i}') + print(f'INFO: Running Monte Carlo realization {i}') sys.stdout.flush() # Create the mocks @@ -199,7 +199,7 @@ def run_monte_carlo(self, fiducial_model, num_mocks=1, seed=0, scale=None): minimizer.minimize() self.mc_failed_mask.append(False) except ValueError: - print('WARNING: minimizer failed for mock {}'.format(i)) + print('WARNING: Minimizer failed for mock {}'.format(i)) self.mc_failed_mask.append(True) self.mc_chisq.append(np.nan) self.mc_valid_minima.append(False) @@ -211,12 +211,12 @@ def run_monte_carlo(self, fiducial_model, num_mocks=1, seed=0, scale=None): self.mc_bestfits[param] = [] self.mc_bestfits[param].append([value, minimizer.errors[param]]) - for param in self.mc_bestfits.keys(): - self.mc_bestfits[param] = np.array(self.mc_bestfits[param]) - self.mc_covariances.append(minimizer.covariance) self.mc_chisq.append(minimizer.fmin.fval) self.mc_valid_minima.append(minimizer.fmin.is_valid) self.mc_valid_hesse.append(not minimizer.fmin.hesse_failed) + for param in self.mc_bestfits.keys(): + self.mc_bestfits[param] = np.array(self.mc_bestfits[param]) + self.has_monte_carlo = True