Merge pull request #1894 from PaulTalbot-INL/workshop_opt_2022

Workshop 2022: Grad Desc Opt

doc/workshop/optimizer/Inputs/1_grad_desc.xml

@@ -0,0 +1,110 @@
+<Simulation verbosity="debug" color="true">
+  <TestInfo>
+    <name>doc/workshop/optimizer/Inputs.GradDesc</name>
+    <author>talbpw</author>
+    <created>2022-07-13</created>
+    <classesTested>Samplers.Optimizer</classesTested>
+    <description>Workshop exercise for gradient descent with projectile</description>
+  </TestInfo>
+
+  <RunInfo>
+    <WorkingDir>GradDesc</WorkingDir>
+    <Sequence>optimize,print</Sequence>
+  </RunInfo>
+
+  <Steps>
+    <MultiRun name="optimize">
+      <Optimizer class="Optimizers" type="FiniteDifference">opter</Optimizer>
+      <Input class="DataObjects" type="PointSet">placeholder</Input>
+      <Model class="Models" type="ExternalModel">projectile</Model>
+      <SolutionExport class="DataObjects" type="PointSet">search_path</SolutionExport>
+      <Output class="DataObjects" type="PointSet">results</Output>
+    </MultiRun>
+    <IOStep name="print">
+      <Input class="DataObjects" type="PointSet">search_path</Input>
+      <Output class="OutStreams" type="Print">opt_search</Output>
+      <Output class="OutStreams" type="Plot">path</Output>
+    </IOStep>
+  </Steps>
+
+  <Models>
+    <ExternalModel ModuleToLoad="../../../../tests/framework/AnalyticModels/projectile.py" name="projectile" subType="">
+      <inputs>v0,y0,angle</inputs>
+      <outputs>r,t,ymax</outputs>
+    </ExternalModel>
+  </Models>
+
+  <Optimizers>
+    <GradientDescent name="opter">
+      <objective>r</objective>
+      <variable name="v0">
+        <distribution>v0_dist</distribution>
+        <initial>15</initial>
+      </variable>
+      <variable name="angle">
+        <distribution>ang_dist</distribution>
+        <initial>70</initial>
+      </variable>
+      <constant name="y0">0</constant>
+      <constant name="timeOption">1</constant>
+      <samplerInit>
+        <limit>1000</limit>
+        <initialSeed>42</initialSeed>
+        <type>max</type>
+        <writeSteps>every</writeSteps>
+      </samplerInit>
+      <gradient><FiniteDifference/></gradient>
+      <stepSize>
+        <GradientHistory>
+          <growthFactor>1.1</growthFactor>
+          <shrinkFactor>1.1</shrinkFactor>
+          <initialStepScale>0.9</initialStepScale>
+        </GradientHistory>
+      </stepSize>
+      <convergence>
+        <gradient>1e-2</gradient>
+        <objective>1e-1</objective>
+      </convergence>
+      <acceptance><Strict/></acceptance>
+      <TargetEvaluation class="DataObjects" type="PointSet">results</TargetEvaluation>
+    </GradientDescent>
+  </Optimizers>
+
+  <Distributions>
+    <Uniform name='v0_dist'>
+      <lowerBound>10</lowerBound>
+      <upperBound>170</upperBound>
+    </Uniform>
+    <Uniform name='ang_dist'>
+      <lowerBound>10</lowerBound>
+      <upperBound>80</upperBound>
+    </Uniform>
+  </Distributions>
+
+  <DataObjects>
+    <PointSet name="placeholder">
+      <Input>v0,angle</Input>
+    </PointSet>
+    <PointSet name="results">
+      <Input>v0,angle</Input>
+      <Output>r,t,ymax</Output>
+    </PointSet>
+    <PointSet name="search_path">
+      <Input>trajID</Input>
+      <Output>iteration,accepted,v0,angle,ymax,r</Output>
+    </PointSet>
+  </DataObjects>
+
+  <OutStreams>
+    <Print name="opt_search">
+      <type>csv</type>
+      <source>search_path</source>
+      <clusterLabel>trajID</clusterLabel>
+    </Print>
+    <Plot name="path" subType="OptPath">
+      <source>search_path</source>
+      <vars>v0,angle,ymax,r</vars>
+    </Plot>
+  </OutStreams>
+
+</Simulation>

doc/workshop/optimizer/Inputs/gold/GradDesc/opt_search_0.csv

@@ -0,0 +1,22 @@
+iteration,accepted,v0,angle,ymax,r
+0.0,first,15.0,70.0,10.1367346863,14.7578787938
+1.0,accepted,170.0,58.8502986362,1079.95412904,2610.99344312
+2.0,rejected,170.0,10.0,44.4613076349,1008.61042266
+3.0,rerun,170.0,58.8502986362,1079.95412904,2610.99344312
+4.0,rejected,170.0,13.9894478388,86.1688459615,1383.50288229
+5.0,rerun,170.0,58.8502986362,1079.95412904,2610.99344312
+6.0,rejected,170.0,16.4786446152,118.64015279,1604.2853054
+7.0,rerun,170.0,58.8502986362,1079.95412904,2610.99344312
+8.0,rejected,170.0,20.404332355,179.227012862,1927.26159917
+9.0,rerun,170.0,58.8502986362,1079.95412904,2610.99344312
+10.0,rejected,170.0,25.0022770774,263.397903877,2259.20009124
+11.0,rerun,170.0,58.8502986362,1079.95412904,2610.99344312
+12.0,rejected,170.0,28.0438357285,325.918501952,2447.33531994
+13.0,rerun,170.0,58.8502986362,1079.95412904,2610.99344312
+14.0,rejected,170.0,30.1036423604,370.934723779,2559.20892733
+15.0,rerun,170.0,58.8502986362,1079.95412904,2610.99344312
+16.0,accepted,170.0,33.3396713702,445.386886331,2708.05890812
+17.0,rejected,170.0,58.3001803453,1067.35715087,2636.8342839
+18.0,rerun,170.0,33.3396713702,445.386886331,2708.05890812
+19.0,accepted,170.0,55.3741697451,998.424177569,2757.72492746
+19.0,final,170.0,55.3741697451,998.424177569,2757.72492746