<snapdata remixID="8747515"><project name='pg4' app='Snap! 5.1, http://snap.berkeley.edu' version='1'>
  <notes/>
  <thumbnail>data:image/png;base64,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</thumbnail>
  <stage inheritance='true' id='1' volume='100' height='360' tempo='60' lines='round' width='480' name='Stage' sublistIDs='false' threadsafe='false' codify='false' color='255,255,255,1' scheduled='false' pan='0' ternary='false' costume='0'>
    <pentrails>data:image/png;base64,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</pentrails>
    <costumes>
      <list id='2' struct='atomic'/>
    </costumes>
    <sounds>
      <list id='3' struct='atomic'/>
    </sounds>
    <variables/>
    <blocks/>
    <scripts/>
    <sprites>
      <sprite x='108.54101966249664' pen='tip' id='8' y='-149.39389709296682' name='Sprite' idx='1' volume='100' rotation='1' scale='1' heading='90' costume='0' color='80,80,80,1' pan='0' draggable='true'>
        <costumes>
          <list id='9' struct='atomic'/>
        </costumes>
        <sounds>
          <list id='10' struct='atomic'/>
        </sounds>
        <blocks/>
        <variables/>
        <scripts>
          <script x='60' y='89'>
            <block s='receiveGo'/>
            <block s='gotoXY'>
              <l>0</l>
              <l>0</l>
            </block>
            <block s='down'/>
            <custom-block s='polygon sides %s side length %s'>
              <l>10</l>
              <l>60</l>
            </custom-block>
            <block s='doSetVar'>
              <l>starting point</l>
              <block s='reportNewList'>
                <list/>
              </block>
            </block>
            <custom-block s='for each %upvar of %l %cs'>
              <l>item</l>
              <block var='polygon points'/>
              <script>
                <block s='doSetVar'>
                  <l>starting point</l>
                  <block var='item'/>
                </block>
                <custom-block s='for each %upvar of %l %cs'>
                  <l>item</l>
                  <block var='polygon points'/>
                  <script>
                    <block s='up'/>
                    <block s='gotoXY'>
                      <custom-block s='x coordinate of %n'>
                        <block var='starting point'/>
                      </custom-block>
                      <custom-block s='y coordinate of %n'>
                        <block var='starting point'/>
                      </custom-block>
                    </block>
                    <block s='down'/>
                    <block s='gotoXY'>
                      <custom-block s='x coordinate of %n'>
                        <block var='item'/>
                      </custom-block>
                      <custom-block s='y coordinate of %n'>
                        <block var='item'/>
                      </custom-block>
                    </block>
                    <block s='up'/>
                  </script>
                </custom-block>
                <block s='gotoXY'>
                  <custom-block s='x coordinate of %n'>
                    <block var='starting point'/>
                  </custom-block>
                  <custom-block s='y coordinate of %n'>
                    <block var='starting point'/>
                  </custom-block>
                </block>
              </script>
            </custom-block>
          </script>
          <script x='254' y='100'>
            <block s='clear'/>
          </script>
        </scripts>
      </sprite>
      <watcher var='polygon points' x='10' color='243,118,29' style='normal' y='10' extX='129' extY='69'/>
      <watcher var='starting point' x='10' color='243,118,29' style='normal' y='175.000002' extX='80' extY='70'/>
    </sprites>
  </stage>
  <hidden/>
  <headers/>
  <code/>
  <blocks>
    <block-definition s='empty? %&apos;data&apos;' category='lists' type='predicate'>
      <header/>
      <code/>
      <translations/>
      <inputs>
        <input type='%l'/>
      </inputs>
      <script>
        <block s='doReport'>
          <block s='reportEquals'>
            <block var='data'/>
            <block s='reportNewList'>
              <list/>
            </block>
          </block>
        </block>
      </script>
    </block-definition>
    <block-definition s='for %&apos;i&apos; = %&apos;start&apos; to %&apos;end&apos; %&apos;action&apos;' category='control' type='command'>
      <header/>
      <code/>
      <translations/>
      <inputs>
        <input type='%upvar'/>
        <input type='%n'>1</input>
        <input type='%n'>10</input>
        <input type='%cs'/>
      </inputs>
      <script>
        <block s='doDeclareVariables'>
          <list>
            <l>step</l>
            <l>tester</l>
          </list>
        </block>
        <block s='doIfElse'>
          <block s='reportGreaterThan'>
            <block var='start'/>
            <block var='end'/>
          </block>
          <script>
            <block s='doSetVar'>
              <l>step</l>
              <l>-1</l>
            </block>
            <block s='doSetVar'>
              <l>tester</l>
              <block s='reifyReporter'>
                <autolambda>
                  <block s='reportLessThan'>
                    <block var='i'/>
                    <block var='end'/>
                  </block>
                </autolambda>
                <list/>
              </block>
            </block>
          </script>
          <script>
            <block s='doSetVar'>
              <l>step</l>
              <l>1</l>
            </block>
            <block s='doSetVar'>
              <l>tester</l>
              <block s='reifyReporter'>
                <autolambda>
                  <block s='reportGreaterThan'>
                    <block var='i'/>
                    <block var='end'/>
                  </block>
                </autolambda>
                <list/>
              </block>
            </block>
          </script>
        </block>
        <block s='doSetVar'>
          <l>i</l>
          <block var='start'/>
        </block>
        <block s='doUntil'>
          <block s='evaluate'>
            <block var='tester'/>
            <list/>
          </block>
          <script>
            <block s='doRun'>
              <block var='action'/>
              <list/>
            </block>
            <block s='doChangeVar'>
              <l>i</l>
              <block var='step'/>
            </block>
          </script>
        </block>
      </script>
    </block-definition>
    <block-definition s='for each %&apos;item&apos; of %&apos;data&apos; %&apos;action&apos;' category='lists' type='command'>
      <header/>
      <code/>
      <translations/>
      <inputs>
        <input type='%upvar'/>
        <input type='%l'/>
        <input type='%cs'/>
      </inputs>
      <script>
        <block s='doUntil'>
          <custom-block s='empty? %l'>
            <block var='data'/>
          </custom-block>
          <script>
            <block s='doSetVar'>
              <l>item</l>
              <block s='reportListItem'>
                <l>1</l>
                <block var='data'/>
              </block>
            </block>
            <block s='doRun'>
              <block var='action'/>
              <list>
                <block s='reportListItem'>
                  <l>1</l>
                  <block var='data'/>
                </block>
              </list>
            </block>
            <block s='doSetVar'>
              <l>data</l>
              <block s='reportCDR'>
                <block var='data'/>
              </block>
            </block>
          </script>
        </block>
      </script>
    </block-definition>
    <block-definition s='go to point %&apos;point&apos;' category='other' type='command'>
      <header/>
      <code/>
      <translations/>
      <inputs>
        <input type='%s'/>
      </inputs>
      <script>
        <block s='gotoXY'>
          <block s='reportListItem'>
            <l>1</l>
            <block var='point'/>
          </block>
          <block s='reportListItem'>
            <l>2</l>
            <block var='point'/>
          </block>
        </block>
      </script>
    </block-definition>
    <block-definition s='glide to point %&apos;point&apos;' category='pen' type='command'>
      <header/>
      <code/>
      <translations/>
      <inputs>
        <input type='%l'/>
      </inputs>
      <script>
        <block s='doGlide'>
          <l>.5</l>
          <custom-block s='x coordinate of point %l'>
            <block var='point'/>
          </custom-block>
          <custom-block s='y coordinate of point %l'>
            <block var='point'/>
          </custom-block>
        </block>
      </script>
    </block-definition>
    <block-definition s='point %&apos;x&apos; %&apos;y&apos;' category='lists' type='reporter'>
      <header/>
      <code/>
      <translations/>
      <inputs>
        <input type='%n'/>
        <input type='%n'/>
      </inputs>
      <script>
        <block s='doReport'>
          <block s='reportNewList'>
            <list>
              <block var='x'/>
              <block var='y'/>
            </list>
          </block>
        </block>
      </script>
    </block-definition>
    <block-definition s='x coordinate of point %&apos;point&apos;' category='looks' type='reporter'>
      <header/>
      <code/>
      <translations/>
      <inputs>
        <input type='%l'/>
      </inputs>
      <script>
        <block s='doReport'>
          <block s='reportListItem'>
            <l>1</l>
            <block var='point'/>
          </block>
        </block>
      </script>
    </block-definition>
    <block-definition s='y coordinate of point %&apos;point&apos;' category='looks' type='reporter'>
      <header/>
      <code/>
      <translations/>
      <inputs>
        <input type='%l'/>
      </inputs>
      <script>
        <block s='doReport'>
          <block s='reportListItem'>
            <l>2</l>
            <block var='point'/>
          </block>
        </block>
      </script>
    </block-definition>
    <block-definition s='draw shape %&apos;shape&apos;' category='pen' type='command'>
      <header/>
      <code/>
      <translations/>
      <inputs>
        <input type='%l'/>
      </inputs>
      <script>
        <block s='up'/>
        <custom-block s='for each %upvar of %l %cs'>
          <l>point</l>
          <block var='shape'/>
          <script>
            <custom-block s='glide to point %l'>
              <block var='point'/>
            </custom-block>
            <block s='down'/>
          </script>
        </custom-block>
        <custom-block s='glide to point %l'>
          <block s='reportListItem'>
            <l>1</l>
            <block var='shape'/>
          </block>
        </custom-block>
      </script>
    </block-definition>
    <block-definition s='polygon sides %&apos;sides&apos; side length %&apos;side length&apos;' category='motion' type='command'>
      <header/>
      <code/>
      <translations/>
      <inputs>
        <input type='%s'/>
        <input type='%s'/>
      </inputs>
      <script>
        <block s='doSetVar'>
          <l>polygon points</l>
          <block s='reportNewList'>
            <list/>
          </block>
        </block>
        <block s='doRepeat'>
          <block var='sides'/>
          <script>
            <block s='doAddToList'>
              <custom-block s='point %n %n'>
                <block s='xPosition'/>
                <block s='yPosition'/>
              </custom-block>
              <block var='polygon points'/>
            </block>
            <block s='forward'>
              <block var='side length'/>
            </block>
            <block s='doWait'>
              <l>.1</l>
            </block>
            <block s='turn'>
              <block s='reportQuotient'>
                <l>360</l>
                <block var='sides'/>
              </block>
            </block>
          </script>
        </block>
      </script>
    </block-definition>
    <block-definition s='polygon simple sides %&apos;sides&apos;' category='motion' type='command'>
      <header/>
      <code/>
      <translations/>
      <inputs>
        <input type='%s'/>
      </inputs>
      <script>
        <block s='doRepeat'>
          <block var='sides'/>
          <script>
            <block s='forward'>
              <l>75</l>
            </block>
            <block s='turn'>
              <block s='reportQuotient'>
                <l>360</l>
                <block var='sides'/>
              </block>
            </block>
          </script>
        </block>
      </script>
    </block-definition>
    <block-definition s='x coordinate of %&apos;point&apos;' category='operators' type='reporter'>
      <header/>
      <code/>
      <translations/>
      <inputs>
        <input type='%n'/>
      </inputs>
      <script>
        <block s='doReport'>
          <block s='reportListItem'>
            <l>1</l>
            <block var='point'/>
          </block>
        </block>
      </script>
    </block-definition>
    <block-definition s='y coordinate of %&apos;point&apos;' category='operators' type='reporter'>
      <header/>
      <code/>
      <translations/>
      <inputs>
        <input type='%n'/>
      </inputs>
      <script>
        <block s='doReport'>
          <block s='reportListItem'>
            <l>2</l>
            <block var='point'/>
          </block>
        </block>
      </script>
    </block-definition>
  </blocks>
  <variables>
    <variable name='polygon points'>
      <list id='285'>
        <item>
          <list id='286' struct='atomic'>0,0</list>
        </item>
        <item>
          <list id='287' struct='atomic'>60,0</list>
        </item>
        <item>
          <list id='288' struct='atomic'>108.54101966249664,-35.26711513754839</list>
        </item>
        <item>
          <list id='289' struct='atomic'>127.08203932499327,-92.3305061152576</list>
        </item>
        <item>
          <list id='290' struct='atomic'>108.54101966249664,-149.39389709296682</list>
        </item>
        <item>
          <list id='291' struct='atomic'>60,-184.6610122305152</list>
        </item>
        <item>
          <list id='292' struct='atomic'>0,-184.6610122305152</list>
        </item>
        <item>
          <list id='293' struct='atomic'>-48.54101966249664,-149.39389709296682</list>
        </item>
        <item>
          <list id='294' struct='atomic'>-67.08203932499327,-92.3305061152576</list>
        </item>
        <item>
          <list id='295' struct='atomic'>-48.54101966249664,-35.26711513754839</list>
        </item>
      </list>
    </variable>
    <variable name='starting point'>
      <ref id='294'/>
    </variable>
  </variables>
</project><media name="pg4" app="Snap! 5.1, http://snap.berkeley.edu" version="1"></media></snapdata>