<snapdata remixID="14691453"><project name="AbstractDataType Lecture Template" app="Snap! 11.0.4, https://snap.berkeley.edu" version="2"><notes></notes><thumbnail>data:image/png;base64,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</thumbnail><scenes select="1"><scene name="AbstractDataType Lecture Template"><notes></notes><hidden></hidden><headers></headers><code></code><blocks><block-definition s="Coordinate Points, X Point: %&apos;X #&apos; Y Point: %&apos;Y #&apos;" type="reporter" category="other"><header></header><code></code><translations></translations><inputs><input type="%s" initial="1"></input><input type="%s" initial="1"></input></inputs><script><block s="doReport"><block s="reportNewList"><list><block var="X #"/><block var="Y #"/></list></block></block></script></block-definition><block-definition s="coordinate Points, X Point: %&apos;X #&apos; Y point: %&apos;Y #&apos;" type="reporter" category="motion"><header></header><code></code><translations></translations><inputs><input type="%s" initial="1"></input><input type="%s" initial="1"></input></inputs><script><block s="doReport"><block s="reportNewList"><list><block var="X #"/><block var="Y #"/></list></block></block></script></block-definition><block-definition s="Select x Corrdinate from Data Record: %&apos;Single record:&apos;" type="reporter" category="other"><header></header><code></code><translations></translations><inputs><input type="%l" initial="1"></input></inputs><script><block s="doReport"><block s="reportListItem"><l>1</l><block var="Single record:"/></block></block></script></block-definition><block-definition s="Select a y Coordinate from Data Record: %&apos;SingleData&apos;" type="reporter" category="other"><header></header><code></code><translations></translations><inputs><input type="%l" initial="1"></input></inputs><script><block s="doReport"><block s="reportListItem"><l>2</l><block var="SingleData"/></block></block></script></block-definition><block-definition s="Draw Shape: Shape Dataset: %&apos;DataSet (table)&apos;" type="command" category="other"><header></header><code></code><translations></translations><inputs><input type="%l" initial="1"></input></inputs><script><block s="doForEach"><l>item</l><block var="DataSet (table)"/><script><block s="gotoXY"><custom-block s="Select x Corrdinate from Data Record: %l"><block var="item"/></custom-block><custom-block s="Select a y Coordinate from Data Record: %l"><block var="item"/></custom-block></block><block s="doSayFor"><block var="item"/><l>2</l></block><block s="down"></block></script></block></script></block-definition></blocks><primitives></primitives><stage name="Stage" width="480" height="360" costume="1" 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" id="56"><pentrails>data:image/png;base64,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</pentrails><costumes><list id="57"><item><ref mediaID="AbstractDataType Lecture Template_Stage_cst_XY Grid"></ref></item></list></costumes><sounds><list struct="atomic" id="58"></list></sounds><variables></variables><blocks></blocks><scripts><script x="306.47783251231533" y="57.01847290640404"><block s="doForEach"><l>item</l><l/><script></script></block></script></scripts><sprites select="1"><sprite name="Sprite" idx="1" x="100" y="0" heading="90" scale="1" volume="100" pan="0" rotation="1" draggable="true" costume="0" color="80,80,80,1" pen="tip" id="67"><costumes><list struct="atomic" id="68"></list></costumes><sounds><list struct="atomic" id="69"></list></sounds><blocks></blocks><variables></variables><scripts><script x="474.3990147783252" y="124.14532019704433"><block s="reportNewList"><list><l>240</l><l>0</l><l>0</l><l>100</l><l>-240</l><l>0</l><l>240</l><l></l></list><comment w="165.3694581280788" collapsed="false">odd index numbers are x points&#xD;even index numbers are y points&#xD;draws a Triangle</comment></block></script><comment x="532.9458128078818" y="193.74384236453204" w="307.2413793103449" collapsed="false">The list of numbers is confusing because it is not obvious which numbers are x and which are y coordinates. It will also be difficult to maintain (add or delete coordinates to the lists).&#xD;It would be better to create a matrix (a list of list). Each item in the list will be a list of x and y coordinates.</comment><script x="457.0908133971866" y="54.60385878489319"><block s="reportNewList"><list><l>240</l><l>0</l><l>0</l><l>100</l><l>-240</l><l>0</l><l>0</l><l>-100</l><l>240</l><l>0</l></list><comment w="165.3694581280788" collapsed="false">odd index numbers are x points&#xD;even index numbers are y points&#xD;draws a diamond</comment></block></script><script x="26.615763546798007" y="162.39367816091948"><custom-block s="Coordinate Points, X Point: %s Y Point: %s"><l></l><l></l></custom-block></script><comment x="26.615763546798064" y="14.21510673234802" w="414.1379310344828" collapsed="false">Abstract Data Types (ADT) is a custom data type created by the programmer to provide meaning to the data in your program. It is not built into the programming language. ADT are created with custom constructor and selector functions (blocks).&#xD;ADT are a form of abstraction because they make are program easier to understand, read, and debug.</comment><comment x="516.6896551724138" y="10" w="290.9852216748768" collapsed="false">Lists and Numbers are examples of Primitive Data Types</comment><comment x="27.034482758620697" y="106.05911330049264" w="413.1527093596059" collapsed="false">Step 1: Create A Reporter block (the constructor) that will take two numbers as the domain (x and y coordinates) and output a list as the range.</comment><comment x="21.615763546798036" y="196.20689655172413" w="421.5270935960591" collapsed="false">Step 2: Create two report blocks (the selectors) that will take the list created by the contructor block as the domain and output a single number as the range (one the x coordinate the second block the y coordinate).</comment><comment x="21.1231527093596" y="319.3596059113301" w="343.69458128078816" collapsed="false">Step 3: Create a list that stores the necessary Coordinte Points to draw your specified shape </comment><comment x="534.9162561576355" y="304.58128078817737" w="304.2857142857142" collapsed="false">Step 4: Create a Draw Shape Command Block whose domain will be the list of Coordinate Points create in step 3. The command block will draw the shape on the screen by using a the for each item block and the selector blocks created in Step 2.</comment><script x="189" y="384.83333333333337"><block s="receiveGo"></block><block s="clear"></block><block s="gotoXY"><l>0</l><l>0</l></block><block s="down"></block><block s="doSetVar"><l>Diamond Shape</l><block s="reportNewList"><list><custom-block s="Coordinate Points, X Point: %s Y Point: %s"><l>100</l><l>0</l></custom-block><custom-block s="Coordinate Points, X Point: %s Y Point: %s"><l>100</l><l>100</l></custom-block><custom-block s="Coordinate Points, X Point: %s Y Point: %s"><l>0</l><l>100</l></custom-block><custom-block s="Coordinate Points, X Point: %s Y Point: %s"><l>0</l><l>0</l></custom-block><custom-block s="Coordinate Points, X Point: %s Y Point: %s"><l>100</l><l>0</l></custom-block></list></block></block><custom-block s="Draw Shape: Shape Dataset: %l"><block var="Diamond Shape"/></custom-block><block s="up"></block></script></scripts></sprite><watcher var="Diamond Shape" style="normal" x="10" y="10" color="243,118,29" extX="128.5615234375" extY="103"/></sprites></stage><variables><variable name="Diamond Shape"><list id="137"><item><list struct="atomic" id="138">100,0</list></item><item><list struct="atomic" id="139">100,100</list></item><item><list struct="atomic" id="140">0,100</list></item><item><list struct="atomic" id="141">0,0</list></item><item><list struct="atomic" id="142">100,0</list></item></list></variable></variables></scene></scenes></project><media name="AbstractDataType Lecture Template" app="Snap! 11.0.4, https://snap.berkeley.edu" version="2"><costume name="XY Grid" center-x="240" center-y="180" image="data:image/png;base64,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" mediaID="AbstractDataType Lecture Template_Stage_cst_XY Grid"/></media></snapdata>