<snapdata remixID="14282777"><project name="Sierpinski Triangle using Bitwise" app="Snap! 10.5.1, https://snap.berkeley.edu" version="2"><notes>I&apos;ve been experimenting with bitwise until I found out that you can make a sierpinski triangle using bitwise.&#xD;&#xD;I finally managed to create a perfect sierpinski triangle using just 18 blocks of code, using the "bitwise _ or _" and "mod" blocks, making this aesthetic fractal. For those who are curious, see the code!</notes><thumbnail>data:image/png;base64,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</thumbnail><scenes select="1"><scene name="Sierpinski Triangle using Bitwise"><notes>I&apos;ve been experimenting with bitwise until I found out that you can make a sierpinski triangle using bitwise.&#xD;&#xD;I finally managed to create a perfect sierpinski triangle using just 18 blocks of code, using the "bitwise _ or _" and "mod" blocks, making this aesthetic fractal. For those who are curious, see the code!</notes><hidden></hidden><headers></headers><code></code><blocks><block-definition s="for each tile sized %&apos;side&apos; %&apos;action&apos;" type="command" category="control"><comment x="0" y="0" w="144.00000000000023" collapsed="false">Divide the stage into a grid of square regions with the given side length and perform an action at the center of each.</comment><header></header><code></code><translations>de:für jede Kachel der Größe _ _&#xD;pl:dla każdego kafelka rozmiar _ _&#xD;</translations><inputs><input type="%n">20</input><input type="%ca"></input></inputs><script><block s="doDeclareVariables"><list><l>ext</l><l>dim</l><l>origin</l></list></block><block s="doSetVar"><l>ext</l><block s="reportAttributeOf"><l><option>extent</option></l><block s="reportGet"><l><option>stage</option></l></block></block></block><block s="doSetVar"><l>dim</l><block s="reportMonadic"><l><option>ceiling</option></l><block s="reportQuotient"><block var="ext"/><block var="side"/></block></block></block><block s="doSetVar"><l>origin</l><block s="reportVariadicSum"><list><block s="reportQuotient"><block var="ext"/><l>-2</l></block><block s="reportQuotient"><block s="reportDifference"><block var="ext"/><block s="reportVariadicProduct"><list><block var="dim"/><block var="side"/></list></block></block><l>2</l></block><block s="reportQuotient"><block var="side"/><l>2</l></block></list></block></block><block s="doWarp"><script><block s="doForEach"><l>coord</l><block s="reportCrossproduct"><block s="reportNumbers"><l>1</l><block var="dim"/></block></block><script><block s="doGotoObject"><block s="reportVariadicSum"><list><block var="origin"/><block s="reportVariadicProduct"><list><block s="reportDifference"><block var="coord"/><l>1</l></block><block var="side"/></list></block></list></block></block><block s="doRun"><block var="action"/><list></list></block></script></block></script></block></script></block-definition><block-definition s="for each %&apos;tile&apos; in %&apos;cols&apos; %&apos;col&apos; by %&apos;rows&apos; %&apos;row&apos; %&apos;action&apos;" type="command" category="control"><comment x="0" y="0" w="181" collapsed="false">Divide the stage into a grid of same-sized rectangles specified by the number of columns and rows and perform an action at the center of each.</comment><header></header><code></code><translations>de:für jede _ im Raster _ _ zu _ _ _&#xD;pl:dla każdego _ w _ _ po _ _ _&#xD;</translations><inputs><input type="%upvar">$_tile</input><input type="%n">20</input><input type="%upvar">$_column</input><input type="%n">15</input><input type="%upvar">$_row</input><input type="%ca"></input></inputs><script><block s="doDeclareVariables"><list><l>ext</l><l>dim</l><l>origin</l></list></block><block s="doSetVar"><l>ext</l><block s="reportAttributeOf"><l><option>extent</option></l><block s="reportGet"><l><option>stage</option></l></block></block></block><block s="doSetVar"><l>dim</l><block s="reportNewList"><list><block var="cols"/><block var="rows"/></list></block></block><block s="doSetVar"><l>tile</l><block s="reportQuotient"><block var="ext"/><block var="dim"/></block></block><block s="doSetVar"><l>origin</l><block s="reportVariadicSum"><list><block s="reportQuotient"><block var="ext"/><l>-2</l></block><block s="reportQuotient"><block var="tile"/><l>2</l></block></list></block></block><block s="doWarp"><script><block s="doForEach"><l>coord</l><block s="reportCrossproduct"><block s="reportNumbers"><l>1</l><block var="dim"/></block></block><script><block s="doGotoObject"><block s="reportVariadicSum"><list><block var="origin"/><block s="reportVariadicProduct"><list><block s="reportDifference"><block var="coord"/><l>1</l></block><block var="tile"/></list></block></list></block></block><block s="doSetVar"><l>col</l><block s="reportListItem"><l>1</l><block var="coord"/></block></block><block s="doSetVar"><l>row</l><block s="reportListItem"><l>2</l><block var="coord"/></block></block><block s="doRun"><block var="action"/><list></list></block></script></block></script></block></script></block-definition><block-definition s="render each %&apos;cell&apos; in table %&apos;table&apos; %&apos;action&apos;" type="command" category="control"><comment x="0" y="0" w="144.00000000000023" collapsed="false">Divide the stage into a grid of square regions matching the dimensions of the given table and perform an action at the center of each.</comment><header></header><code></code><translations>de:für jede _ in Tabelle _ _&#xD;pl:dla każdej _ w tabeli _ _&#xD;</translations><inputs><input type="%upvar" initial="1">$_cell</input><input type="%l" initial="1"></input><input type="%cs" initial="1"></input></inputs><script><block s="doSetVar"><l>table</l><block s="reportListAttribute"><l><option>reverse</option></l><block var="table"/></block></block><custom-block s="for each %upvar in %n %upvar by %n %upvar %ca"><l>tile</l><block s="reportListAttribute"><l><option>length</option></l><block s="reportListItem"><l>1</l><block var="table"/></block></block><l>col</l><block s="reportListAttribute"><l><option>length</option></l><block var="table"/></block><l>row</l><script><block s="doSetVar"><l>cell</l><block s="reportListItem"><block var="col"/><block s="reportListItem"><block var="row"/><block var="table"/></block></block></block><block s="doRun"><block var="action"/><list></list></block></script></custom-block></script></block-definition><block-definition s="bitwise not %&apos;a&apos;" type="reporter" category="operators"><header></header><code></code><translations></translations><inputs><input type="%n"></input></inputs><script><block s="doReport"><block s="reportApplyExtension"><l>bit_not(a)</l><list><block var="a"/></list></block></block></script></block-definition><block-definition s="bitwise %&apos;a&apos; and %&apos;b&apos;" type="reporter" category="operators"><header></header><code></code><translations></translations><inputs><input type="%n"></input><input type="%n"></input></inputs><script><block s="doReport"><block s="reportApplyExtension"><l>bit_and(a, b)</l><list><block var="a"/><block var="b"/></list></block></block></script></block-definition><block-definition s="bitwise %&apos;a&apos; or %&apos;b&apos;" type="reporter" category="operators"><header></header><code></code><translations></translations><inputs><input type="%n"></input><input type="%n"></input></inputs><script><block s="doReport"><block s="reportApplyExtension"><l>bit_or(a, b)</l><list><block var="a"/><block var="b"/></list></block></block></script></block-definition><block-definition s="bitwise %&apos;a&apos; xor %&apos;b&apos;" type="reporter" category="operators"><header></header><code></code><translations></translations><inputs><input type="%n"></input><input type="%n"></input></inputs><script><block s="doReport"><block s="reportApplyExtension"><l>bit_xor(a, b)</l><list><block var="a"/><block var="b"/></list></block></block></script></block-definition><block-definition s="bitwise left shift %&apos;a&apos; by %&apos;b&apos; bits" type="reporter" category="operators"><header></header><code></code><translations></translations><inputs><input type="%n"></input><input type="%n"></input></inputs><script><block s="doReport"><block s="reportApplyExtension"><l>bit_left_shift(a, b)</l><list><block var="a"/><block var="b"/></list></block></block></script></block-definition><block-definition s="bitwise right shift %&apos;a&apos; by %&apos;b&apos; bits" type="reporter" category="operators"><header></header><code></code><translations></translations><inputs><input type="%n"></input><input type="%n"></input></inputs><script><block s="doReport"><block s="reportApplyExtension"><l>bit_right_shift(a, b)</l><list><block var="a"/><block var="b"/></list></block></block></script></block-definition><block-definition s="bitwise unsigned right shift %&apos;a&apos; by %&apos;b&apos; bits" type="reporter" category="operators"><header></header><code></code><translations></translations><inputs><input type="%n"></input><input type="%n"></input></inputs><script><block s="doReport"><block s="reportApplyExtension"><l>bit_unsigned_right_shift(a, b)</l><list><block var="a"/><block var="b"/></list></block></block></script></block-definition></blocks><primitives></primitives><stage name="Stage" width="480" height="480" costume="0" color="255,255,255,1" tempo="60" threadsafe="false" penlog="false" volume="100" pan="0" lines="round" ternary="false" hyperops="true" codify="false" inheritance="true" sublistIDs="false" 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</pentrails><costumes><list 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