Fix parameter inference for Valhalla Supermassive. (spotify#149)

rhelsing · Sep 12, 2022 · bf29495 · bf29495
1 parent d3d4a4f
commit bf29495
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Showing 2 changed files with 6 additions and 3 deletions.
diff --git a/pedalboard/pedalboard.py b/pedalboard/pedalboard.py
@@ -220,10 +220,10 @@ def __init__(self, plugin, parameter_name, search_steps: int = 1000):
  self.ranges: Dict[Tuple[float, float], Union[str, float, bool]] = {}
 
  with self.__get_cpp_parameter() as cpp_parameter:
- start_of_range: float = 0
- text_value: Optional[str] = None
-
  for fetch_slow in (False, True):
+ start_of_range: float = 0
+ text_value: Optional[str] = None
+
  self.ranges = {}
  for x in range(0, search_steps + 1):
  raw_value = x / search_steps

diff --git a/tests/test_external_plugins.py b/tests/test_external_plugins.py
@@ -420,6 +420,9 @@ def test_float_parameters(plugin_filename: str, parameter_name: str):
  _min, _max, _ = parameter_value.range
  step_size = parameter_value.step_size
  new_values = np.arange(_min, _max, step_size)
+ # Because sometimes np.arange(_min, _max) gives values _slightly outside_
+ # of [_min, _max] thanks to floating point:
+ new_values = [max(_min, min(_max, new_value)) for new_value in new_values]
 
  epsilon = parameter_value.step_size or parameter_value.approximate_step_size or 0.001