ContinuousSignalExtrema: improved detection of t_min and t_max

pierre-haessig · Jul 30, 2022 · 83c156c · 83c156c
1 parent 8118479
commit 83c156c
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Showing 2 changed files with 3 additions and 11 deletions.
diff --git a/Modelica/Blocks/Math.mo b/Modelica/Blocks/Math.mo
@@ -2557,16 +2557,8 @@ This means that:</p>
     //detect local extrema at zero derivative, just before and after a step, and at the end of the simulation
       y_min = min({pre(y_min), u, pre(u)});
       y_max = max({pre(y_max), u, pre(u)});
-      if y_min<pre(y_min) then
-        t_min=time;
-        t_max=pre(t_max);
-      elseif y_max>pre(y_max) then
-        t_min=pre(t_min);
-        t_max=time;
-      else
-        t_min=pre(t_min);
-        t_max=pre(t_max);
-      end if;
+      t_min = if y_min<pre(y_min) then time else pre(t_min);
+      t_max = if y_max>pre(y_max) then time else pre(t_max);
     end when;
     annotation (defaultComponentName="signalExtrema",
     Documentation(info="<html>

diff --git a/Modelica/Blocks/package.mo b/Modelica/Blocks/package.mo
@@ -1505,7 +1505,7 @@ whereas signalExtrema2 catches the extrema rather good due to the fact that samp
       annotation (Placement(transformation(extent={{-80,-40},{-60,-20}})));
     Modelica.Blocks.Sources.Sine amplitude(
       amplitude=1,
-      f=0.75,
+      f=1.75,
       offset=0)
       annotation (Placement(transformation(extent={{-60,-10},{-40,10}})));
     Modelica.Blocks.Math.Product product1