Merge pull request #1010 from rhayes777/feature/concise_issues

fix numerical ranges in concise
rhayes777 · Apr 22, 2024 · a8d0101 · a8d0101
2 parents f55f353 + 03eff31
commit a8d0101
Show file tree

Hide file tree

Showing 3 changed files with 9 additions and 4 deletions.
diff --git a/autofit/mapper/prior_model/representative.py b/autofit/mapper/prior_model/representative.py
@@ -41,6 +41,11 @@ def _find_groups(path_value_tuples, position):
             paths.append((path, value))
 
     for (before, after, value), names in groups.items():
+        try:
+            names = list(map(int, names))
+        except ValueError:
+            pass
+
         representative_key = (
             f"{min(names)} - {max(names)}" if len(set(names)) > 1 else names[0]
         )

diff --git a/autofit/text/formatter.py b/autofit/text/formatter.py
@@ -64,7 +64,7 @@ def add(self, path: Tuple[str, ...], value):
 
     @property
     def text(self):
-        return "\n".join(self.list)
+        return "\n".join(map(str, self.list))
 
     @property
     def list(self):

diff --git a/test_autofit/text/test_concise.py b/test_autofit/text/test_concise.py
@@ -35,9 +35,9 @@ def test_model_info(collection):
         == """Total Free Parameters = 3
 
 model                                                                           Collection (N=3)
-    0 - 9                                                                       Gaussian (N=3)
+    0 - 19                                                                      Gaussian (N=3)
 
-0 - 9
+0 - 19
     centre                                                                      UniformPrior [0], lower_limit = 0.0, upper_limit = 1.0
     normalization                                                               UniformPrior [1], lower_limit = 0.0, upper_limit = 1.0
     sigma                                                                       UniformPrior [2], lower_limit = 0.0, upper_limit = 1.0"""
@@ -69,7 +69,7 @@ def test_model_results(samples):
 Maximum Log Posterior                                                           1.00000000
 
 model                                                                           Collection (N=3)
-    0 - 9                                                                       Gaussian (N=3)
+    0 - 19                                                                      Gaussian (N=3)
 
 Maximum Log Likelihood Model: