<snapdata remixID="11239249"><project name="digits from division" app="Snap! 7, https://snap.berkeley.edu" version="2"><notes></notes><thumbnail>data:image/png;base64,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</thumbnail><scenes select="1"><scene name="digits from division"><notes></notes><hidden></hidden><headers></headers><code></code><blocks><block-definition s="USE BIGNUMS %&apos;bool&apos;" type="command" category="operators"><comment x="0" y="0" w="303.3333333333333" collapsed="false">call with True to turn on the entire Scheme numeric tower, including infinite-precision integers, exact rationals, and complex numbers; call with False to restore native JavaScript arithmetic.</comment><header></header><code></code><translations>pt:altera utilização de aritmética do Scheme para _&#xD;ca:sistema numèric d&apos;Scheme _&#xD;</translations><inputs><input type="%b"></input></inputs><script><block s="doApplyExtension"><l>src_load(url)</l><list><l>libraries/biginteger.js</l></list></block><block s="doApplyExtension"><l>src_load(url)</l><list><l>libraries/schemeNumber.js</l></list></block><block s="doApplyExtension"><l>src_load(url)</l><list><l>libraries/bignums.js</l></list></block><block s="doApplyExtension"><l>big_switch(bool)</l><list><block var="bool"/></list></block></script></block-definition><block-definition s="%&apos;n&apos; !" type="reporter" category="operators"><comment x="0" y="0" w="190.66666666666666" collapsed="false">The factorial function, to make very large numbers, to demo bignums.</comment><header></header><code></code><translations></translations><inputs><input type="%n"></input></inputs><script><block s="doReport"><block s="reportIfElse"><block s="reportEquals"><block var="n"/><l>0</l></block><l>1</l><block s="reportProduct"><block var="n"/><custom-block s="%n !"><block s="reportDifference"><block var="n"/><l>1</l></block></custom-block></block></block></block></script></block-definition><block-definition s="Scheme number %&apos;function&apos; of %&apos;number&apos;" type="reporter" category="operators"><comment x="0" y="0" w="300" collapsed="true">Provides Scheme arithmetic functions not in JavaScript</comment><header></header><code></code><translations>pt:_ de _&#xD;ca:Scheme _ de _&#xD;</translations><inputs><input type="%s" readonly="true"><options>number?&#xD;complex?&#xD;real?&#xD;rational?&#xD;integer?&#xD;exact?&#xD;inexact?&#xD;exact&#xD;inexact&#xD;finite?&#xD;infinite?&#xD;nan?&#xD;numerator&#xD;denominator&#xD;real-part&#xD;imag-part&#xD;magnitude&#xD;angle</options></input><input type="%s"></input></inputs><script><block s="doReport"><block s="reportApplyExtension"><l>big_scheme(fn, num)</l><list><block var="function"/><block var="number"/></list></block></block></script></block-definition><block-definition s="reshape as %&apos;shape&apos; $⍴-1-255-255-0 items of %&apos;data&apos;" type="reporter" category="lists"><comment x="0" y="0" w="180" collapsed="false">The first input is a shape list as in&#xD;SHAPE OF.  The output is an array with those dimensions containing  the atomic items of the second input,&#xD;repeating values if more are needed.</comment><header></header><code></code><translations></translations><inputs><input type="%l"></input><input type="%l"></input></inputs><script><block s="doReport"><block s="reportReshape"><block var="data"/><block var="shape"/></block></block></script></block-definition><block-definition s="shape of $⍴-1-255-255-0 %&apos;data&apos;" type="reporter" category="lists"><comment x="0" y="0" w="310" collapsed="false">Reports a flat list of the maximum size of the input array along&#xD;each dimension: number of rows, number of columns, etc.&#xD;&quot;Maximum&quot; because it works even if the array isn&apos;t uniformly shaped.</comment><header></header><code></code><translations></translations><inputs><input type="%l"></input></inputs><script><block s="doReport"><block s="reportListAttribute"><l><option>dimensions</option></l><block var="data"/></block></block></script></block-definition><block-definition s="max %&apos;a&apos; $⌈-1-255-255-0 %&apos;b&apos;" type="reporter" category="operators"><comment x="0" y="0" w="150.66666666666666" collapsed="false">Reports the greater of its two inputs. Works on strings too.</comment><header></header><code></code><translations></translations><inputs><input type="%s"></input><input type="%s"></input></inputs><script><block s="doReport"><block s="reportMax"><block var="a"/><block var="b"/></block></block></script></block-definition><block-definition s="flatten (ravel) $,-1-255-255-0 %&apos;data&apos;" type="reporter" category="lists"><comment x="0" y="0" w="216" collapsed="false">Reports a flat list of all the atomic elements &#xD;of sublists of the input list.</comment><header></header><code></code><translations></translations><inputs><input type="%l"></input></inputs><script><block s="doReport"><block s="reportListAttribute"><l><option>flatten</option></l><block var="data"/></block></block></script></block-definition><block-definition s="rank of $⍴⍴-1-255-255-0 %&apos;array&apos;" type="reporter" category="lists"><comment x="0" y="0" w="240" collapsed="true">Reports the number of dimensions of the input.</comment><header></header><code></code><translations></translations><inputs><input type="%l"></input></inputs><script><block s="doReport"><block s="reportListAttribute"><l><option>rank</option></l><block var="array"/></block></block></script></block-definition><block-definition s="inner product helper with %&apos;plus&apos; . %&apos;times&apos; %&apos;a&apos; $nl transposed %&apos;tb&apos;" type="reporter" category="other" helper="true"><header></header><code></code><translations></translations><inputs><input type="%repRing"></input><input type="%repRing"></input><input type="%l"></input><input type="%l"></input></inputs><script><block s="doIf"><block s="reportListIsEmpty"><block var="a"/></block><script><block s="doReport"><block s="reportNewList"><list></list></block></block></script></block><block s="doIf"><block s="reportNot"><block s="reportIsA"><block s="reportListItem"><l>1</l><block s="reportListItem"><l>1</l><block var="a"/></block></block><l><option>list</option></l></block></block><script><block s="doReport"><block s="reportCONS"><block s="reportMap"><block s="reifyReporter"><autolambda><custom-block s="generalized dotproduct %l %l with sum %repRing product %repRing"><block s="reportListItem"><l>1</l><block var="a"/></block><l/><block var="plus"/><block var="times"/></custom-block></autolambda><list></list></block><block var="tb"/></block><custom-block s="inner product helper with %repRing . %repRing %l %br transposed %l"><block var="plus"/><block var="times"/><block s="reportCDR"><block var="a"/></block><block var="tb"/></custom-block></block></block></script></block><block s="doReport"><block s="reportCONS"><custom-block s="inner product helper with %repRing . %repRing %l %br transposed %l"><block var="plus"/><block var="times"/><block s="reportListItem"><l>1</l><block var="a"/></block><block var="tb"/></custom-block><custom-block s="inner product helper with %repRing . %repRing %l %br transposed %l"><block var="plus"/><block var="times"/><block s="reportCDR"><block var="a"/></block><block var="tb"/></custom-block></block></block></script></block-definition><block-definition s="transpose $⍉-1.5-255-255-0 %&apos;array&apos;" type="reporter" category="lists"><comment x="0" y="0" w="168" collapsed="false">Takes a multidimensional array, and&#xD;reports an array whose dimensions&#xD;are reversed (as reported by&#xD;SHAPE OF).  In the case of a&#xD;two-dimensional array, does the usual transposition of rows and columns.</comment><header></header><code></code><translations></translations><inputs><input type="%l"></input></inputs><script><block s="doReport"><block s="reportApplyExtension"><l>dta_transpose(list)</l><list><block var="array"/></list></block></block></script></block-definition><block-definition s="reverse row order (column contents) $⦵-1.5-255-255-0 %&apos;list&apos;" type="reporter" category="lists"><comment x="0" y="0" w="286" collapsed="false">Reverses the order of the (toplevel) items of the input.&#xD;&#xD;If the input is a matrix, this means it reverses the order of the rows, which is a reflection through a horizontal axis, as the ⦵ symbol suggests.</comment><header></header><code></code><translations></translations><inputs><input type="%l"></input></inputs><script><block s="doReport"><block s="reportListAttribute"><l><option>reverse</option></l><block var="list"/></block></block></script></block-definition><block-definition s="multimap %&apos;function&apos; %&apos;data&apos;" type="reporter" category="other" helper="true"><comment x="0" y="0" w="215.33333333333334" collapsed="false">Like MAP, but can take any number of lists&#xD;as inputs.  The lists must all be the same size.&#xD;The function input must take a number of inputs&#xD;equal to the number of lists.  MULTIMAP calls&#xD;the function with all the first items, then all the&#xD;second items, and so on.</comment><header></header><code></code><translations></translations><inputs><input type="%repRing"></input><input type="%mult%l"></input></inputs><script><block s="doWarp"><script><block s="doDeclareVariables"><list><l>lengths</l><l>cols</l></list></block><block s="doSetVar"><l>lengths</l><block s="reportMap"><block s="reifyReporter"><autolambda><block s="reportListAttribute"><l><option>length</option></l><l/></block></autolambda><list></list></block><block var="data"/></block></block><block s="doFor"><l>i</l><l>2</l><block s="reportListAttribute"><l><option>length</option></l><block var="lengths"/></block><script><block s="doIf"><block s="reportNot"><block s="reportEquals"><block s="reportListItem"><l>1</l><block var="lengths"/></block><block s="reportListItem"><block var="i"/><block var="lengths"/></block></block></block><script><custom-block s="error %txt"><l>Non-conforming shapes.</l></custom-block></script></block></script></block><block s="doSetVar"><l>cols</l><block s="reportListAttribute"><l><option>columns</option></l><block var="data"/></block></block><block s="doReport"><block s="reportMap"><block s="reifyReporter"><autolambda><block s="evaluate"><block var="function"/><custom-block s="%s"><l></l></custom-block></block></autolambda><list></list></block><block var="cols"/></block></block></script></block></script></block-definition><block-definition s="generalized dotproduct %&apos;a&apos; %&apos;b&apos; with sum %&apos;sum&apos; product %&apos;product&apos;" type="reporter" category="other"><header></header><code></code><translations></translations><inputs><input type="%l"></input><input type="%l"></input><input type="%repRing"></input><input type="%repRing"></input></inputs><script><block s="doReport"><block s="reportCombine"><custom-block s="multimap %repRing %mult%l"><block var="product"/><list><block var="a"/><block var="b"/></list></custom-block><block var="sum"/></block></block></script></block-definition><block-definition s="inner product %&apos;a&apos; %&apos;plus&apos; $.-1-255-255-0 %&apos;times&apos; %&apos;b&apos;" type="reporter" category="lists"><comment x="0" y="0" w="252.66666666666666" collapsed="false">Computes a generalized matrix multiplication.&#xD;&#xD;In normal matrix multiplication, each cell of the result&#xD;is computed by multiplying individual numbers within&#xD;a row of the left input and a column of the right input,&#xD;and then adding those products.  In APL terms this is&#xD;+.× (&quot;plus dot times&quot;)&#xD;Any dyadic functions can replace addition and multiplication in this algorithm; a common case is&#xD;∨.∧ (&quot;or dot and&quot;)</comment><header></header><code></code><translations></translations><inputs><input type="%l"></input><input type="%repRing"></input><input type="%repRing"></input><input type="%l"></input></inputs><script><block s="doIf"><block s="reportNot"><block s="reportIsA"><block var="a"/><l><option>list</option></l></block></block><script><block s="doSetVar"><l>a</l><block s="reportNewList"><list><block var="a"/></list></block></block></script></block><block s="doIf"><block s="reportNot"><block s="reportIsA"><block var="b"/><l><option>list</option></l></block></block><script><block s="doSetVar"><l>b</l><block s="reportNewList"><list><block var="b"/></list></block></block></script></block><block s="doIf"><block s="reportAnd"><block s="reportEquals"><block s="reportListItem"><l><option>last</option></l><custom-block s="shape of $⍴-1-255-255-0 %l"><block var="a"/></custom-block></block><l>1</l></block><block s="reportGreaterThan"><block s="reportListItem"><l>1</l><custom-block s="shape of $⍴-1-255-255-0 %l"><block var="b"/></custom-block></block><l>1</l></block></block><script><block s="doDeclareVariables"><list><l>ta</l></list></block><block s="doSetVar"><l>ta</l><custom-block s="transpose $⍉-1.5-255-255-0 %l"><block var="a"/></custom-block></block><block s="doSetVar"><l>a</l><custom-block s="transpose $⍉-1.5-255-255-0 %l"><block s="reportAtomicMap"><block s="reifyReporter"><autolambda><block var="ta"/></autolambda><list></list></block><block s="reportNumbers"><l>1</l><block s="reportListItem"><l>1</l><custom-block s="shape of $⍴-1-255-255-0 %l"><block var="b"/></custom-block></block></block></block></custom-block></block></script></block><block s="doIf"><block s="reportAnd"><block s="reportGreaterThan"><block s="reportListItem"><l><option>last</option></l><custom-block s="shape of $⍴-1-255-255-0 %l"><block var="a"/></custom-block></block><l>1</l></block><block s="reportEquals"><block s="reportListItem"><l>1</l><custom-block s="shape of $⍴-1-255-255-0 %l"><block var="b"/></custom-block></block><l>1</l></block></block><script><block s="doSetVar"><l>b</l><block s="reportAtomicMap"><block s="reifyReporter"><autolambda><block var="b"/></autolambda><list></list></block><block s="reportNumbers"><l>1</l><block s="reportListItem"><l><option>last</option></l><custom-block s="shape of $⍴-1-255-255-0 %l"><block var="a"/></custom-block></block></block></block></block></script></block><block s="doReport"><custom-block s="inner product helper with %repRing . %repRing %l %br transposed %l"><block var="plus"/><block var="times"/><block var="a"/><custom-block s="transpose $⍉-1.5-255-255-0 %l"><block var="b"/></custom-block></custom-block></block></script></block-definition><block-definition s="min %&apos;a&apos; $⌊-1.2-255-255-0 %&apos;b&apos;" type="reporter" category="operators"><comment x="0" y="0" w="211.33333333333334" collapsed="true">Reports the smaller of its two inputs.</comment><header></header><code></code><translations></translations><inputs><input type="%s"></input><input type="%s"></input></inputs><script><block s="doReport"><block s="reportMin"><block var="a"/><block var="b"/></block></block></script></block-definition><block-definition s="combine in rows (reduce by column vectors) %&apos;func&apos; $/-1-255-255-0 %&apos;stuff&apos;" type="reporter" category="lists"><comment x="0" y="0" w="288.6666666666667" collapsed="false">This function has two names because there are two ways&#xD;to understand it.&#xD;&#xD;Lisp way:  A matrix is a list of rows.  This block combines the numbers in each row, producing one value for the entire row.&#xD;&#xD;APL way:  A matrix is made of vectors.  This block takes each column as a vector, and does vector arithmetic on the columns, producing one column as the result.</comment><header></header><code></code><translations></translations><inputs><input type="%repRing"></input><input type="%l"></input></inputs><script><block s="doIfElse"><block s="reportGreaterThan"><custom-block s="rank of $⍴⍴-1-255-255-0 %l"><block var="stuff"/></custom-block><l>1</l></block><script><block s="doReport"><block s="reportMap"><block s="reifyReporter"><autolambda><custom-block s="combine in rows (reduce by column vectors) %repRing $/-1-255-255-0 %l"><block var="func"/><l/></custom-block></autolambda><list></list></block><block var="stuff"/></block></block></script><script><block s="doReport"><block s="reportCombine"><block var="stuff"/><block var="func"/></block></block></script></block></script></block-definition><block-definition s="%&apos;howmany&apos; deal helper %&apos;data&apos;" type="reporter" category="other" helper="true"><header></header><code></code><translations></translations><inputs><input type="%n"></input><input type="%l"></input></inputs><script><block s="doWarp"><script><block s="doIf"><block s="reportEquals"><block var="howmany"/><l>0</l></block><script><block s="doReport"><block s="reportNewList"><list></list></block></block></script></block><block s="doDeclareVariables"><list><l>choices</l><l>index</l></list></block><block s="doSetVar"><l>choices</l><block s="reportNewList"><list></list></block></block><block s="doRepeat"><block var="howmany"/><script><block s="doSetVar"><l>index</l><block s="reportRandom"><l>1</l><block s="reportListAttribute"><l><option>length</option></l><block var="data"/></block></block></block><block s="doAddToList"><block s="reportListItem"><block var="index"/><block var="data"/></block><block var="choices"/></block><block s="doDeleteFromList"><block var="index"/><block var="data"/></block></script></block><block s="doReport"><block var="choices"/></block></script></block></script></block-definition><block-definition s="signum $×-1-255-255-0 %&apos;num&apos;" type="reporter" category="operators"><comment x="0" y="0" w="159.99999999999997" collapsed="false">Reports 1 if the input is positive,&#xD;0 if the input is zero,&#xD;or -1 if the input is negative.</comment><header></header><code></code><translations></translations><inputs><input type="%n"></input></inputs><script><block s="doIf"><block s="reportIsA"><block var="num"/><l><option>list</option></l></block><script><block s="doReport"><block s="reportMap"><block s="reifyReporter"><autolambda><custom-block s="signum $×-1-255-255-0 %n"><l></l></custom-block></autolambda><list></list></block><block var="num"/></block></block></script></block><block s="doIf"><block s="reportListContainsItem"><block s="reportNewList"><list><l>0</l><block s="reportBoolean"><l><bool>false</bool></l></block></list></block><block var="num"/></block><script><block s="doReport"><l>0</l></block></script></block><block s="doReport"><block s="reportQuotient"><block var="num"/><block s="reportMonadic"><l><option>abs</option></l><block var="num"/></block></block></block></script></block-definition><block-definition s="reciprocal $÷-1-255-255-0 %&apos;num&apos;" type="reporter" category="operators"><comment x="0" y="0" w="102.66666666666667" collapsed="false">reports 1 divided&#xD;by its input.</comment><header></header><code></code><translations></translations><inputs><input type="%n"></input></inputs><script><block s="doReport"><block s="reportQuotient"><l>1</l><block var="num"/></block></block></script></block-definition><block-definition s="roll $?-1-255-255-0 %&apos;num&apos;" type="reporter" category="operators"><comment x="0" y="0" w="180.66666666666666" collapsed="false">This block reports a random integer between 1 and its input.  To roll more than one die, use (for three dice)&#xD;roll (reshape as 3 items of 6)&#xD;APL:  ?3⍴6&#xD;Don&apos;t use reshape as 3 items of (roll 6), because that would roll one die and report 3 copies of the same random roll. </comment><header></header><code></code><translations></translations><inputs><input type="%n"></input></inputs><script><block s="doReport"><block s="reportRandom"><l>1</l><block var="num"/></block></block></script></block-definition><block-definition s="scalar? %&apos;x&apos;" type="predicate" category="other" helper="true"><comment x="0" y="0" w="199.33333333333334" collapsed="false">Reports True if the input is an APL scalar,&#xD;i.e., either an atomic (non-list) value, or&#xD;an array (list of lists) of any depth with only&#xD;one atomic item, e.g., (list (list (list (3)))).</comment><header></header><code></code><translations></translations><inputs><input type="%s"></input></inputs><script><block s="doIf"><block s="reportNot"><block s="reportIsA"><block var="x"/><l><option>list</option></l></block></block><script><block s="doReport"><block s="reportBoolean"><l><bool>true</bool></l></block></block></script></block><block s="doReport"><block s="reportEquals"><block s="reportAtomicCombine"><custom-block s="shape of $⍴-1-255-255-0 %l"><block var="x"/></custom-block><block s="reifyReporter"><autolambda><block s="reportProduct"><l></l><l></l></block></autolambda><list></list></block></block><l>1</l></block></block></script></block-definition><block-definition s="scalar-value helper %&apos;x&apos;" type="reporter" category="other" helper="true"><comment x="0" y="0" w="200.66666666666666" collapsed="false">The input must be a value for which SCALAR? reports true, i.e., either an atom or a list of any depth but only one scalar item of item of... etc.  This function returns the underlying scalar (number, etc.).</comment><header></header><code></code><translations></translations><inputs><input type="%s"></input></inputs><script><block s="doIf"><block s="reportNot"><block s="reportIsA"><block var="x"/><l><option>list</option></l></block></block><script><block s="doReport"><block var="x"/></block></script></block><block s="doReport"><custom-block s="scalar-value helper %s"><block s="reportListItem"><l>1</l><block var="x"/></block></custom-block></block></script></block-definition><block-definition s="NAND %&apos;a&apos; $⍲-1.4-255-255-0 %&apos;b&apos;" type="predicate" category="operators"><comment x="0" y="0" w="198.66666666666666" collapsed="false">Reports the not-and of its inputs, in the form&#xD;0 for false, 1 for true.</comment><header></header><code></code><translations></translations><inputs><input type="%s"></input><input type="%s"></input></inputs><script><block s="doReport"><custom-block s="NOT $&#126;-1-255-255-0 %s"><custom-block s="LCM (and) %n $∧-1.2-255-255-0 %n"><block var="a"/><block var="b"/></custom-block></custom-block></block></script></block-definition><block-definition s="NOR %&apos;a&apos; $⍱-1.4-255-255-0 %&apos;b&apos;" type="predicate" category="operators"><comment x="0" y="0" w="198.66666666666666" collapsed="false">Reports the not-and of its inputs, in the form&#xD;0 for false, 1 for true.</comment><header></header><code></code><translations></translations><inputs><input type="%s"></input><input type="%s"></input></inputs><script><block s="doReport"><custom-block s="NOT $&#126;-1-255-255-0 %s"><custom-block s="GCD (or) %n $∨-1.2-255-255-0 %n"><block var="a"/><block var="b"/></custom-block></custom-block></block></script></block-definition><block-definition s="%&apos;a&apos; ≤ %&apos;b&apos;" type="predicate" category="operators"><comment x="0" y="0" w="151.33333333333334" collapsed="true">Reports True if the left input is&#xD;less than or equal to the right input.&#xD;&#xD;Reports a Snap! Boolean, not an integer 0 or 1.</comment><header></header><code></code><translations></translations><inputs><input type="%s"></input><input type="%s"></input></inputs><script><block s="doReport"><block s="reportLessThanOrEquals"><block var="a"/><block var="b"/></block><comment w="176.66666666666666" collapsed="true">This is the primitive version.</comment></block></script></block-definition><block-definition s="%&apos;a&apos; ≥ %&apos;b&apos;" type="predicate" category="operators"><comment x="0" y="0" w="152.66666666666666" collapsed="false">Reports True if the left input is&#xD;greater than than or equal to&#xD;the right input.&#xD;&#xD;Reports a Snap! Boolean, not an integer 0 or 1.</comment><header></header><code></code><translations></translations><inputs><input type="%s"></input><input type="%s"></input></inputs><script><block s="doReport"><block s="reportGreaterThanOrEquals"><block var="a"/><block var="b"/></block></block></script></block-definition><block-definition s="XOR %&apos;a&apos; $≠-1-255-255-0 %&apos;b&apos;" type="predicate" category="operators"><comment x="0" y="0" w="190" collapsed="false">Reports False if its inputs are equal;&#xD;reports True if its inputs are not equal.&#xD;The inputs can have any non-list values.&#xD;(Lists are hyperized.)  If the inputs are&#xD;Booleans (True/False or 1/0), this is&#xD;also the exclusive-or function.</comment><header></header><code></code><translations></translations><inputs><input type="%s"></input><input type="%s"></input></inputs><script><block s="doReport"><custom-block s="%s scalar %s %s"><block var="a"/><l>≠</l><block var="b"/></custom-block></block></script></block-definition><block-definition s="zero? %&apos;n&apos;" type="predicate" category="other" helper="true"><comment x="0" y="0" w="202.66666666666666" collapsed="true">reports True iff the input is 0 or False.</comment><header></header><code></code><translations></translations><inputs><input type="%n"></input></inputs><script><block s="doReport"><block s="reportListContainsItem"><block s="reportNewList"><list><l>0</l><block s="reportBoolean"><l><bool>false</bool></l></block></list></block><block var="n"/></block></block></script></block-definition><block-definition s="truth %&apos;n&apos;" type="predicate" category="other" helper="true"><comment x="0" y="0" w="198.66666666666666" collapsed="false">Reports a Snap! Boolean False if the input&#xD;is False or 0; reports True otherwise.</comment><header></header><code></code><translations></translations><inputs><input type="%s"></input></inputs><script><block s="doIf"><block s="reportIsA"><block var="n"/><l><option>list</option></l></block><script><block s="doReport"><block s="reportMap"><block s="reifyReporter"><autolambda><custom-block s="truth %s"><l></l></custom-block></autolambda><list></list></block><block var="n"/></block></block></script></block><block s="doReport"><block s="reportIfElse"><block s="reportIsA"><block var="n"/><l><option>Boolean</option></l></block><block var="n"/><block s="reportNot"><block s="reportEquals"><block var="n"/><l>0</l></block></block></block></block></script></block-definition><block-definition s="make scalar %&apos;value&apos;" type="reporter" category="operators" helper="true"><comment x="0" y="0" w="242.66666666666666" collapsed="false">Turns list of list of ... a single scalar (e.g., ((((x)))) ) into just the scalar.  Error if called with anything else.</comment><header></header><code></code><translations></translations><inputs><input type="%l"></input></inputs><script><block s="doIf"><custom-block s="scalar? %s"><block var="value"/></custom-block><script><block s="doReport"><custom-block s="scalar-value helper %s"><block var="value"/></custom-block></block></script></block><custom-block s="error %txt"><block s="reportJoinWords"><list><l>Make scalar called with non-singleton input </l><block var="value"/></list></block></custom-block></script></block-definition><block-definition s="$⍳-1.5-255-255-0 %&apos;n&apos;" type="reporter" category="lists"><comment x="0" y="0" w="290.6666666666667" collapsed="false">If the input is a positive integer, reports a list of the numbers&#xD;from 1 to that input.  (If the input is 0, reports an empty list.)&#xD;&#xD;If the input is a list of positive integers, reports an array with&#xD;the shape specified by the input (as in ⍴ reshape) in which&#xD;each item is a list of the indices of that item in the array&#xD;(so technically the shape has one more dimension&#xD;than the input, whose size is the size of the input).&#xD;&#xD;If the input is a list that includes 0, the result is an array whose shape is the part of the input list before the 0, in which every element is empty.  If you&apos;d like some other value in every element, MD-MAP a constant function over the result.&#xD;&#xD;For list inputs, the size of the result grows very quickly, more or less the factorial of the size of the input.  Snap! will not attempt to compute a result bigger than a few million atomic items.&#xD;⍳(⍳ 9) will work (≈ 3 million atoms) but ⍳(⍳ 10) will give an error.</comment><header></header><code></code><translations></translations><inputs><input type="%n"></input></inputs><script><block s="doIfElse"><block s="reportIsA"><block var="n"/><l><option>list</option></l></block><script><block s="doIfElse"><block s="reportEquals"><custom-block s="rank of $⍴⍴-1-255-255-0 %l"><block var="n"/></custom-block><l>1</l></block><script><block s="doIfElse"><block s="reportListContainsItem"><block var="n"/><l>0</l></block><script><block s="doReport"><block s="reportReshape"><block s="reportNewList"><list></list></block><block s="reportListItem"><block s="reportNumbers"><l>1</l><block s="reportDifference"><block s="reportListIndex"><l>0</l><block var="n"/></block><l>1</l></block></block><block var="n"/></block></block></block></script><script><block s="doReport"><block s="reportReshape"><custom-block s="crossproduct %mult%l"><block s="reportAtomicMap"><block s="reifyReporter"><autolambda><block s="reportNumbers"><l>1</l><l></l></block></autolambda><list></list></block><block var="n"/></block></custom-block><block s="reportConcatenatedLists"><list><block var="n"/><block s="reportNewList"><list><block s="reportListAttribute"><l><option>length</option></l><block var="n"/></block></list></block></list></block></block></block></script></block></script><script><custom-block s="error %txt"><l>Input to ⍳ can&apos;t be a list of lists.</l></custom-block></script></block></script><script><block s="doReport"><block s="reportIfElse"><custom-block s="zero? %n"><block var="n"/></custom-block><block s="reportNewList"><list></list></block><block s="reportNumbers"><l>1</l><block var="n"/></block></block></block></script></block></script></block-definition><block-definition s="where in %&apos;vector&apos; is $⍳-1.5-255-255-0 %&apos;items&apos;" type="reporter" category="lists"><comment x="0" y="0" w="334.6666666666667" collapsed="false">If the rank of the left input is one more than the rank of the right input,&#xD;reports the index of the right input in the left input, or if not found,&#xD;reports one more than the length of the left input.&#xD;&#xD;If the rank of the left input is equal to the rank of the right input,&#xD;reports a vector of the indices of the items of the right input&#xD;in the left input (mapping this function over the right input).&#xD;&#xD;If the rank of the left input is more than that of the right input by 2 or more,&#xD;reports a vector, the location of the right input in the left in each dimension.&#xD;&#xD;It is an error if the rank of the left input is less than that of the right input.</comment><header></header><code></code><translations></translations><inputs><input type="%l"></input><input type="%s"></input></inputs><script><block s="doDeclareVariables"><list><l>result</l></list></block><block s="doIf"><block s="reportLessThan"><custom-block s="rank of $⍴⍴-1-255-255-0 %l"><block var="vector"/></custom-block><custom-block s="rank of $⍴⍴-1-255-255-0 %l"><block var="items"/></custom-block></block><script><custom-block s="error %txt"><l>Left input to ⍳ must have greater or equal rank to right input.</l></custom-block></script></block><block s="doIf"><block s="reportEquals"><custom-block s="rank of $⍴⍴-1-255-255-0 %l"><block var="vector"/></custom-block><custom-block s="rank of $⍴⍴-1-255-255-0 %l"><block var="items"/></custom-block></block><script><block s="doReport"><block s="reportMap"><block s="reifyReporter"><autolambda><custom-block s="where in %l is $⍳-1.5-255-255-0 %s"><block var="vector"/><l></l></custom-block></autolambda><list></list></block><block var="items"/></block></block></script></block><block s="doIf"><block s="reportEquals"><custom-block s="rank of $⍴⍴-1-255-255-0 %l"><block var="vector"/></custom-block><block s="reportSum"><custom-block s="rank of $⍴⍴-1-255-255-0 %l"><block var="items"/></custom-block><l>1</l></block></block><script><block s="doSetVar"><l>result</l><block s="reportListIndex"><block var="items"/><block var="vector"/></block></block><block s="doReport"><block s="reportIfElse"><custom-block s="zero? %n"><block var="result"/></custom-block><block s="reportSum"><block s="reportListAttribute"><l><option>length</option></l><block var="vector"/></block><l>1</l></block><block var="result"/></block></block></script></block><block s="doSetVar"><l>result</l><block s="reportFindFirst"><block s="reifyPredicate"><autolambda><custom-block s="%l deep contains %s"><l/><block var="items"/></custom-block></autolambda><list></list></block><block var="vector"/></block></block><block s="doIf"><block s="reportEquals"><block var="result"/><l></l></block><script><block s="doReport"><block s="reportSum"><custom-block s="shape of $⍴-1-255-255-0 %l"><block var="vector"/></custom-block><l>1</l></block></block></script></block><block s="doReport"><block s="reportCONS"><block s="reportListIndex"><block var="result"/><block var="vector"/></block><custom-block s="flatten (ravel) $,-1-255-255-0 %l"><custom-block s="where in %l is $⍳-1.5-255-255-0 %s"><block var="result"/><block var="items"/></custom-block></custom-block></block></block></script></block-definition><block-definition s="crossproduct %&apos;lists&apos;" type="reporter" category="lists"><comment x="0" y="0" w="305.3333333333333" collapsed="false">This isn&apos;t an APL function, although it&apos;s related to the outer product.&#xD;&#xD;It takes any number of lists, and reports a list of all possible tuples with one item from each of the lists.  The length of the result is the product of the lengths of the inputs.&#xD;&#xD;The result gets very big very quickly.  Snap! will refuse to do this computation if the result would be more than a few million atomic items.  (crossproduct (⍳(⍳9))) makes about 3 million atomic items; (crossproduct (⍳(⍳10))) gives an error message.</comment><header></header><code></code><translations></translations><inputs><input type="%mult%l"></input></inputs><script><block s="doReport"><block s="reportApplyExtension"><l>dta_crossproduct(list)</l><list><block var="lists"/></list></block></block></script></block-definition><block-definition s="%&apos;array&apos; deep contains %&apos;value&apos;" type="reporter" category="other" helper="true"><header></header><code></code><translations></translations><inputs><input type="%l"></input><input type="%s"></input></inputs><script><block s="doIf"><block s="reportNot"><block s="reportIsA"><block var="array"/><l><option>list</option></l></block></block><script><block s="doReport"><block s="reportBoolean"><l><bool>false</bool></l></block></block></script></block><block s="doIf"><block s="reportListContainsItem"><block var="array"/><block var="value"/></block><script><block s="doReport"><block s="reportBoolean"><l><bool>true</bool></l></block></block></script></block><block s="doReport"><custom-block s="combine in rows (reduce by column vectors) %repRing $/-1-255-255-0 %l"><block s="reifyReporter"><autolambda><block s="reportOr"><l/><l/></block></autolambda><list></list></block><block s="reportMap"><block s="reifyReporter"><autolambda><custom-block s="%l deep contains %s"><l/><block var="value"/></custom-block></autolambda><list></list></block><block var="array"/></block></custom-block></block></script></block-definition><block-definition s="which of %&apos;items&apos; $ϵ-1-255-255-0 contained in %&apos;array&apos;" type="reporter" category="lists"><comment x="0" y="0" w="214.66666666666666" collapsed="false">Reports an array of Booleans the same shape&#xD;as the left input, indicating which of the atoms&#xD;in the left input appear anywhere in the right&#xD;input.  &#xD;(The structure of the right input doesn&apos;t matter.)</comment><header></header><code></code><translations></translations><inputs><input type="%s"></input><input type="%l"></input></inputs><script><block s="doIfElse"><block s="reportIsA"><block var="items"/><l><option>list</option></l></block><script><block s="doReport"><block s="reportAtomicMap"><block s="reifyReporter"><autolambda><custom-block s="which of %s $ϵ-1-255-255-0 contained in %l"><l></l><custom-block s="flatten (ravel) $,-1-255-255-0 %l"><block var="array"/></custom-block></custom-block></autolambda><list></list></block><block var="items"/></block></block></script><script><block s="doReport"><block s="reportListContainsItem"><custom-block s="flatten (ravel) $,-1-255-255-0 %l"><block var="array"/></custom-block><block var="items"/></block></block></script></block></script></block-definition><block-definition s="catenate %&apos;left&apos; $,-1-255-255-0 %&apos;right&apos;" type="reporter" category="lists"><comment x="0" y="0" w="190.66666666666666" collapsed="false">Like append, but:&#xD;&#xD;A scalar input is treated as an array the same shape as the other input except that the last item of the shape is 1.&#xD;&#xD;If the two inputs are of different ranks,&#xD;the function is mapped over the larger ranked input.&#xD;&#xD;Catenate adds new columns, by appending to each row.</comment><header></header><code></code><translations></translations><inputs><input type="%s"></input><input type="%s"></input></inputs><script><block s="doIf"><block s="reportNot"><block s="reportIsA"><block var="left"/><l><option>list</option></l></block></block><script><block s="doIfElse"><block s="reportGreaterThan"><custom-block s="rank of $⍴⍴-1-255-255-0 %l"><block var="right"/></custom-block><l>1</l></block><script><block s="doSetVar"><l>left</l><custom-block s="reshape as %l $⍴-1-255-255-0 items of %l"><block s="reportConcatenatedLists"><list><custom-block s="drop %n $↓-1-255-255-0 from %l"><l>-1</l><custom-block s="shape of $⍴-1-255-255-0 %l"><block var="right"/></custom-block></custom-block><block s="reportNewList"><list><l>1</l></list></block></list></block><block s="reportNewList"><list><block var="left"/></list></block></custom-block></block></script><script><block s="doSetVar"><l>left</l><block s="reportNewList"><list><block var="left"/></list></block></block></script></block></script></block><block s="doIf"><block s="reportNot"><block s="reportIsA"><block var="right"/><l><option>list</option></l></block></block><script><block s="doIfElse"><block s="reportGreaterThan"><custom-block s="rank of $⍴⍴-1-255-255-0 %l"><block var="left"/></custom-block><l>1</l></block><script><block s="doSetVar"><l>right</l><custom-block s="reshape as %l $⍴-1-255-255-0 items of %l"><block s="reportConcatenatedLists"><list><custom-block s="drop %n $↓-1-255-255-0 from %l"><l>-1</l><custom-block s="shape of $⍴-1-255-255-0 %l"><block var="left"/></custom-block></custom-block><block s="reportNewList"><list><l>1</l></list></block></list></block><block s="reportNewList"><list><block var="right"/></list></block></custom-block></block></script><script><block s="doSetVar"><l>right</l><block s="reportNewList"><list><block var="right"/></list></block></block></script></block></script></block><block s="doIf"><block s="reportEquals"><custom-block s="rank of $⍴⍴-1-255-255-0 %l"><block var="left"/></custom-block><custom-block s="rank of $⍴⍴-1-255-255-0 %l"><block var="right"/></custom-block></block><script><block s="doIfElse"><block s="reportEquals"><custom-block s="rank of $⍴⍴-1-255-255-0 %l"><block var="left"/></custom-block><l>1</l></block><script><block s="doReport"><block s="reportConcatenatedLists"><list><block var="left"/><block var="right"/></list></block></block></script><script><block s="doReport"><custom-block s="multimap %repRing %mult%l"><block s="reifyReporter"><autolambda><custom-block s="catenate %s $,-1-255-255-0 %s"><l></l><l></l></custom-block></autolambda><list></list></block><list><block var="left"/><block var="right"/></list></custom-block></block></script></block></script></block><block s="doIfElse"><block s="reportLessThan"><custom-block s="rank of $⍴⍴-1-255-255-0 %l"><block var="left"/></custom-block><custom-block s="rank of $⍴⍴-1-255-255-0 %l"><block var="right"/></custom-block></block><script><block s="doReport"><block s="reportMap"><block s="reifyReporter"><autolambda><custom-block s="catenate %s $,-1-255-255-0 %s"><block var="left"/><l></l></custom-block></autolambda><list></list></block><block var="right"/></block></block></script><script><block s="doReport"><block s="reportMap"><block s="reifyReporter"><autolambda><custom-block s="catenate %s $,-1-255-255-0 %s"><l></l><block var="right"/></custom-block></autolambda><list></list></block><block var="left"/></block></block></script></block></script></block-definition><block-definition s="scalar value %&apos;value&apos;" type="reporter" category="lists"><comment x="0" y="0" w="221.33333333333334" collapsed="false">If the input is a nesting of length=1 lists, which&#xD;APL treats as a scalar (the innermost item)&#xD;for many purposes, report that innermost scalar.&#xD;Otherwise, report the input as is.&#xD;&#xD;Exposing this block for users is important because Snap! /does not/ treat such a nesting&#xD;as a scalar, so you might need to use this in&#xD;translating an APL program to Snap!.&#xD;(But the functions in the APL library already use&#xD;this block as needed.)</comment><header></header><code></code><translations></translations><inputs><input type="%s"></input></inputs><script><block s="doReport"><block s="reportIfElse"><custom-block s="scalar? %s"><block var="value"/></custom-block><custom-block s="scalar-value helper %s"><block var="value"/></custom-block><block var="value"/></block></block></script></block-definition><block-definition s="grade up $⍋-1.5-255-255-0 %&apos;array&apos;" type="reporter" category="lists"><comment x="0" y="0" w="190.66666666666666" collapsed="false">Reports a vector of indices of the items of the input, in order of the values of the items, so that&#xD;&#xD;item (grade up (foo)) of (foo)&#xD;&#xD;reports the items in sorted order, smallest to largest.  For a matrix, sorts the rows based on their first items, or if those are equal, based on their second items, etc.</comment><header></header><code></code><translations></translations><inputs><input type="%l"></input></inputs><script><block s="doReport"><block s="reportAtomicMap"><block s="reifyReporter"><autolambda><block s="reportListItem"><l><option>last</option></l><l/></block></autolambda><list></list></block><custom-block s="$flash sort %l ordering with %predRing"><custom-block s="multimap %repRing over %mult%l"><block s="reifyReporter"><autolambda><custom-block s="catenate %s $,-1-255-255-0 %s"><l></l><l></l></custom-block></autolambda><list></list></block><list><block var="array"/><custom-block s="$⍳-1.5-255-255-0 %n"><block s="reportListAttribute"><l><option>length</option></l><block var="array"/></block></custom-block></list></custom-block><block s="reifyPredicate"><autolambda><custom-block s="sort helper %l %l"><l/><l/></custom-block></autolambda><list></list></block></custom-block></block></block></script></block-definition><block-definition s="sort helper %&apos;rowA&apos; %&apos;rowB&apos;" type="reporter" category="other" helper="true"><comment x="0" y="0" w="166" collapsed="false">Compares two vectors for sorting.&#xD;Compare first items; if those are equal compare second items; etc.</comment><header></header><code></code><translations></translations><inputs><input type="%l"></input><input type="%l"></input></inputs><script><block s="doIf"><block s="reportListIsEmpty"><block var="rowA"/></block><script><block s="doReport"><block s="reportBoolean"><l><bool>true</bool></l></block></block></script></block><block s="doIf"><block s="reportListIsEmpty"><block var="rowB"/></block><script><block s="doReport"><block s="reportBoolean"><l><bool>false</bool></l></block></block></script></block><block s="doIf"><block s="reportLessThan"><block s="reportListItem"><l>1</l><block var="rowA"/></block><block s="reportListItem"><l>1</l><block var="rowB"/></block></block><script><block s="doReport"><block s="reportBoolean"><l><bool>true</bool></l></block></block></script></block><block s="doIf"><block s="reportGreaterThan"><block s="reportListItem"><l>1</l><block var="rowA"/></block><block s="reportListItem"><l>1</l><block var="rowB"/></block></block><script><block s="doReport"><block s="reportBoolean"><l><bool>false</bool></l></block></block></script></block><block s="doReport"><custom-block s="sort helper %l %l"><block s="reportCDR"><block var="rowA"/></block><block s="reportCDR"><block var="rowB"/></block></custom-block></block></script></block-definition><block-definition s="grade down $⍒-1.5-255-255-0 %&apos;array&apos;" type="reporter" category="lists"><comment x="0" y="0" w="190.66666666666666" collapsed="false">Reports a vector of indices of the items of the input, in order of the values of the items, so that&#xD;&#xD;item (grade down (foo)) of (foo)&#xD;&#xD;reports the items in sorted order, largest to smallest.  For a matrix, sorts the rows based on their first items, or if those are equal, based on their second items, etc.</comment><header></header><code></code><translations></translations><inputs><input type="%l"></input></inputs><script><block s="doReport"><block s="reportAtomicMap"><block s="reifyReporter"><autolambda><block s="reportListItem"><l><option>last</option></l><l/></block></autolambda><list></list></block><custom-block s="$flash sort %l ordering with %predRing"><custom-block s="multimap %repRing over %mult%l"><block s="reifyReporter"><autolambda><custom-block s="catenate %s $,-1-255-255-0 %s"><l></l><l></l></custom-block></autolambda><list></list></block><list><block var="array"/><custom-block s="$⍳-1.5-255-255-0 %n"><block s="reportListAttribute"><l><option>length</option></l><block var="array"/></block></custom-block></list></custom-block><block s="reifyPredicate"><autolambda><custom-block s="NOT $&#126;-1-255-255-0 %s"><custom-block s="sort helper %l %l"><l/><l/></custom-block></custom-block></autolambda><list></list></block></custom-block></block></block></script></block-definition><block-definition s="select rows (compress columns) %&apos;Booleans&apos; $/-1-255-255-0 %&apos;array&apos;" type="reporter" category="lists"><comment x="0" y="0" w="210.66666666666666" collapsed="false">The left input must be a vector of Booleans&#xD;(either Snap! form or APL form); the right input must be an array whose first dimension is equal to the length of the left input.  The block reports an array of the same rank as the right input, containing only those items (rows, for a matrix) for which the corresponding Boolean is True (or 1).</comment><header></header><code></code><translations></translations><inputs><input type="%l"></input><input type="%l"></input></inputs><script><block s="doReport"><custom-block s="rowize vector %l"><block s="reportAtomicKeep"><block s="reifyPredicate"><autolambda><custom-block s="truth %s"><block s="reportListItem"><block var="index"/><block var="Booleans"/></block></custom-block></autolambda><list><l>value</l><l>index</l></list></block><block var="array"/></block></custom-block></block></script></block-definition><block-definition s="rowize vector %&apos;vec&apos;" type="reporter" category="other" helper="true"><header></header><code></code><translations></translations><inputs><input type="%l"></input></inputs><script><block s="doReport"><block s="reportIfElse"><block s="reportAnd"><block s="reportEquals"><custom-block s="rank of $⍴⍴-1-255-255-0 %l"><block var="vec"/></custom-block><l>2</l></block><block s="reportEquals"><block s="reportListItem"><l>2</l><custom-block s="shape of $⍴-1-255-255-0 %l"><block var="vec"/></custom-block></block><l>1</l></block></block><block s="reportMap"><block s="reifyReporter"><autolambda><block s="reportListItem"><l>1</l><l/></block></autolambda><list></list></block><block var="vec"/></block><block var="vec"/></block></block></script></block-definition><block-definition s="select columns (compress rows) %&apos;bool&apos; $⌿-1.5-255-255-0 %&apos;array&apos;" type="reporter" category="lists"><comment x="0" y="0" w="219.33333333333334" collapsed="false">The left input must be a vector of Booleans&#xD;(either Snap! form or APL form); the right input must be an array whose last dimension is equal to the length of the left input.  The block reports an array of the same rank as the right input, containing only those items (columns, for a matrix) for which the corresponding Boolean is True (or 1).</comment><header></header><code></code><translations></translations><inputs><input type="%l"></input><input type="%l"></input></inputs><script><block s="doReport"><custom-block s="columnwise %repRing %l"><block s="reifyReporter"><autolambda><custom-block s="select rows (compress columns) %l $/-1-255-255-0 %l"><block var="bool"/><l/></custom-block></autolambda><list></list></block><block var="array"/></custom-block></block></script></block-definition><block-definition s="columnwise %&apos;function&apos; %&apos;data&apos;" type="reporter" category="control" helper="true"><comment x="0" y="0" w="212" collapsed="false">Turns a row-wise (in Lisp terminology) function&#xD;into a column-wise one.</comment><header></header><code></code><translations></translations><inputs><input type="%repRing"></input><input type="%l"></input></inputs><script><block s="doReport"><custom-block s="rowize vector %l"><custom-block s="transpose $⍉-1.5-255-255-0 %l"><block s="evaluate"><block var="function"/><list><custom-block s="transpose $⍉-1.5-255-255-0 %l"><block var="data"/></custom-block></list></block></custom-block></custom-block></block></script></block-definition><block-definition s="reverse column order (row contents) $⏀-1-255-255-0 %&apos;array&apos;" type="reporter" category="lists"><comment x="0" y="0" w="206" collapsed="false">Reverses the order of the columns of the input, which is a reflection through a vertical axis, as the ⏀ symbol suggests.</comment><header></header><code></code><translations></translations><inputs><input type="%l"></input></inputs><script><block s="doReport"><custom-block s="columnwise %repRing %l"><block s="reifyReporter"><autolambda><custom-block s="reverse row order (column contents) $⦵-1.5-255-255-0 %l"><l/></custom-block></autolambda><list></list></block><block var="array"/></custom-block></block></script></block-definition><block-definition s="combine in columns (reduce by row vectors) %&apos;function&apos; $⌿-1.5-255-255-0 %&apos;array&apos;" type="reporter" category="lists"><comment x="0" y="0" w="285.3333333333333" collapsed="false">This function has two names because there are two ways&#xD;to understand it.&#xD;&#xD;Lisp way:  A matrix is a list of rows.  This block turns it into a list of columns, and combines the numbers in each column, producing one value for the entire column.&#xD;&#xD;APL way:  A matrix is made of vectors.  This block takes each row as a vector, and does vector arithmetic on the rows, producing one row as the result.</comment><header></header><code></code><translations></translations><inputs><input type="%repRing"></input><input type="%l"></input></inputs><script><block s="doReport"><custom-block s="columnwise %repRing %l"><block s="reifyReporter"><autolambda><custom-block s="combine in rows (reduce by column vectors) %repRing $/-1-255-255-0 %l"><block var="function"/><l/></custom-block></autolambda><list></list></block><block var="array"/></custom-block></block></script></block-definition><block-definition s="catenate vertically %&apos;left&apos; $⍪-1.5-255-255-0 %&apos;right&apos;" type="reporter" category="lists"><comment x="0" y="0" w="190.66666666666666" collapsed="false">Like append, but:&#xD;&#xD;A scalar input is treated as a vector&#xD;of length 1.&#xD;&#xD;If the two inputs are of different ranks,&#xD;the function is mapped over the larger ranked input.&#xD;&#xD;Catenate vertically adds new rows, by appending to each column.</comment><header></header><code></code><translations></translations><inputs><input type="%s"></input><input type="%s"></input></inputs><script><block s="doIf"><block s="reportNot"><block s="reportIsA"><block var="left"/><l><option>list</option></l></block></block><script><block s="doIfElse"><block s="reportGreaterThan"><custom-block s="rank of $⍴⍴-1-255-255-0 %l"><block var="right"/></custom-block><l>1</l></block><script><block s="doSetVar"><l>left</l><custom-block s="reshape as %l $⍴-1-255-255-0 items of %l"><block s="reportConcatenatedLists"><list><block s="reportNewList"><list><l>1</l></list></block><custom-block s="drop %n $↓-1-255-255-0 from %l"><l>1</l><custom-block s="shape of $⍴-1-255-255-0 %l"><block var="right"/></custom-block></custom-block></list></block><block s="reportNewList"><list><block var="left"/></list></block></custom-block></block></script><script><block s="doSetVar"><l>left</l><block s="reportNewList"><list><block var="left"/></list></block></block></script></block></script></block><block s="doIf"><block s="reportNot"><block s="reportIsA"><block var="right"/><l><option>list</option></l></block></block><script><block s="doIfElse"><block s="reportGreaterThan"><custom-block s="rank of $⍴⍴-1-255-255-0 %l"><block var="left"/></custom-block><l>1</l></block><script><block s="doSetVar"><l>right</l><custom-block s="reshape as %l $⍴-1-255-255-0 items of %l"><block s="reportConcatenatedLists"><list><block s="reportNewList"><list><l>1</l></list></block><custom-block s="drop %n $↓-1-255-255-0 from %l"><l>1</l><custom-block s="shape of $⍴-1-255-255-0 %l"><block var="left"/></custom-block></custom-block></list></block><block s="reportNewList"><list><block var="right"/></list></block></custom-block></block></script><script><block s="doSetVar"><l>right</l><block s="reportNewList"><list><block var="right"/></list></block></block></script></block></script></block><block s="doIf"><block s="reportEquals"><custom-block s="rank of $⍴⍴-1-255-255-0 %l"><block var="left"/></custom-block><custom-block s="rank of $⍴⍴-1-255-255-0 %l"><block var="right"/></custom-block></block><script><block s="doIfElse"><block s="reportEquals"><custom-block s="rank of $⍴⍴-1-255-255-0 %l"><block var="left"/></custom-block><l>1</l></block><script><block s="doReport"><block s="reportConcatenatedLists"><list><block var="left"/><block var="right"/></list></block></block></script><script><block s="doReport"><custom-block s="transpose $⍉-1.5-255-255-0 %l"><custom-block s="catenate %s $,-1-255-255-0 %s"><custom-block s="transpose $⍉-1.5-255-255-0 %l"><block var="left"/></custom-block><custom-block s="transpose $⍉-1.5-255-255-0 %l"><block var="right"/></custom-block></custom-block></custom-block></block></script></block></script></block><block s="doIfElse"><block s="reportLessThan"><custom-block s="rank of $⍴⍴-1-255-255-0 %l"><block var="left"/></custom-block><custom-block s="rank of $⍴⍴-1-255-255-0 %l"><block var="right"/></custom-block></block><script><block s="doReport"><block s="reportMap"><block s="reifyReporter"><autolambda><custom-block s="catenate %s $,-1-255-255-0 %s"><block var="left"/><l></l></custom-block></autolambda><list></list></block><block var="right"/></block></block></script><script><block s="doReport"><block s="reportMap"><block s="reifyReporter"><autolambda><custom-block s="catenate %s $,-1-255-255-0 %s"><l></l><block var="right"/></custom-block></autolambda><list></list></block><block var="left"/></block></block></script></block></script><scripts><script x="254" y="497.7777777777774"><custom-block s="multimap %repRing %mult%l"><block s="reifyReporter"><script></script><list></list></block><list><l/><l/></list></custom-block></script></scripts></block-definition><block-definition s="%&apos;a&apos; scalar join %&apos;b&apos;" type="reporter" category="operators"><comment x="0" y="0" w="219.33333333333334" collapsed="false">A hyperblock version of JOIN.  The regular JOIN isn&apos;t hyperized because it can accept a list as input, representing it as text.</comment><header></header><code></code><translations></translations><inputs><input type="%s"></input><input type="%s"></input></inputs><script><block s="doReport"><block s="evaluate"><custom-block s="scalar -&gt; hyper %repRing"><block s="reifyReporter"><autolambda><block s="reportJoinWords"><list><l></l><l></l></list></block></autolambda><list></list></block></custom-block><list><block var="a"/><block var="b"/></list></block></block></script></block-definition><block-definition s="take %&apos;howmany&apos; $↑-1-255-255-0 from %&apos;array&apos;" type="reporter" category="lists"><comment x="0" y="0" w="272" collapsed="false">A positive left input selects the first n items of the right input.&#xD;A negative left input selects the last abs(n) items&#xD;of the right input.&#xD;&#xD;If the right input is a matrix, a numeric left input selects rows;&#xD;the left input may also be a two-item vector, in which case&#xD;the first number is applied to the rows&#xD;and the second number is applied to the columns.&#xD;Similarly for higher-dimension arrays. </comment><header></header><code></code><translations></translations><inputs><input type="%n"></input><input type="%l"></input></inputs><script><block s="doIf"><block s="reportIsA"><block var="howmany"/><l><option>number</option></l></block><script><block s="doReport"><block s="reportIfElse"><block s="reportLessThan"><block var="howmany"/><l>0</l></block><block s="reportListItem"><block s="reportSum"><custom-block s="$⍳-1.5-255-255-0 %n"><block s="reportMonadic"><l><option>abs</option></l><block var="howmany"/></block></custom-block><block s="reportSum"><block s="reportListAttribute"><l><option>length</option></l><block var="array"/></block><block var="howmany"/></block></block><block var="array"/></block><block s="reportListItem"><custom-block s="$⍳-1.5-255-255-0 %n"><block var="howmany"/></custom-block><block var="array"/></block></block></block></script></block><block s="doIf"><block s="reportGreaterThan"><custom-block s="rank of $⍴⍴-1-255-255-0 %l"><block var="howmany"/></custom-block><l>1</l></block><script><custom-block s="error %txt"><l>Left input to take can&apos;t be a matrix.</l></custom-block></script></block><block s="doIf"><block s="reportGreaterThan"><block s="reportListAttribute"><l><option>length</option></l><block var="howmany"/></block><custom-block s="rank of $⍴⍴-1-255-255-0 %l"><block var="array"/></custom-block></block><script><custom-block s="error %txt"><l>Length of item vector &gt; rank of array in take.</l></custom-block></script></block><block s="doReport"><block s="reportListItem"><block s="reportMap"><block s="reifyReporter"><autolambda><block s="reportIfElse"><block s="reportLessThan"><block var="value"/><l>0</l></block><block s="reportSum"><custom-block s="$⍳-1.5-255-255-0 %n"><block s="reportMonadic"><l><option>abs</option></l><block var="value"/></block></custom-block><block s="reportSum"><block s="reportListItem"><block var="index"/><custom-block s="shape of $⍴-1-255-255-0 %l"><block var="array"/></custom-block></block><block var="value"/></block></block><custom-block s="$⍳-1.5-255-255-0 %n"><block var="value"/></custom-block></block></autolambda><list><l>value</l><l>index</l></list></block><block var="howmany"/></block><block var="array"/></block></block></script></block-definition><block-definition s="drop %&apos;howmany&apos; $↓-1-255-255-0 from %&apos;array&apos;" type="reporter" category="lists"><comment x="0" y="0" w="306" collapsed="false">A positive left input selects all but the first n items of the right input.&#xD;A negative left input selects all but the last abs(n) items&#xD;of the right input.&#xD;&#xD;If the right input is a matrix, a numeric left input selects rows;&#xD;the left input may also be a two-item vector, in which case&#xD;the first number is applied to the rows&#xD;and the second number is applied to the columns.&#xD;Similarly for higher-dimension arrays. </comment><header></header><code></code><translations></translations><inputs><input type="%n"></input><input type="%l"></input></inputs><script><block s="doIf"><block s="reportIsA"><block var="howmany"/><l><option>number</option></l></block><script><block s="doReport"><custom-block s="take %n $↑-1-255-255-0 from %l"><block s="reportProduct"><block s="reportMonadic"><l><option>neg</option></l><custom-block s="signum $×-1-255-255-0 %n"><block var="howmany"/></custom-block></block><block s="reportDifference"><block s="reportListAttribute"><l><option>length</option></l><block var="array"/></block><block s="reportMonadic"><l><option>abs</option></l><block var="howmany"/></block></block></block><block var="array"/></custom-block></block></script></block><block s="doReport"><custom-block s="take %n $↑-1-255-255-0 from %l"><block s="reportMap"><block s="reifyReporter"><autolambda><block s="reportIfElse"><block s="reportLessThan"><block var="value"/><l>0</l></block><block s="reportSum"><block s="reportListItem"><block var="index"/><custom-block s="shape of $⍴-1-255-255-0 %l"><block var="array"/></custom-block></block><block var="value"/></block><block s="reportDifference"><block var="value"/><block s="reportListItem"><block var="index"/><custom-block s="shape of $⍴-1-255-255-0 %l"><block var="array"/></custom-block></block></block></block></autolambda><list><l>value</l><l>index</l></list></block><block var="howmany"/></block><block var="array"/></custom-block></block></script></block-definition><block-definition s="error %&apos;msg&apos;" type="command" category="control"><comment x="0" y="0" w="268.6666666666667" collapsed="false">Throw an error.&#xD;&#xD;Makes a red halo appear around the script that runs it,&#xD;with the input text shown in a speech balloon next to&#xD;the script, just like any Snap! error.&#xD;&#xD;This is useful to put in the second script of SAFELY TRY&#xD;after some other instructions to undo the partial work of&#xD;the first script.</comment><header></header><code></code><translations>pt:lança o erro _&#xD;</translations><inputs><input type="%txt"></input></inputs><script><block s="doApplyExtension"><l>err_error(msg)</l><list><block var="msg"/></list></block></script></block-definition><block-definition s="simple log base %&apos;b&apos; of %&apos;n&apos;" type="reporter" category="other" helper="true"><header></header><code></code><translations></translations><inputs><input type="%n"></input><input type="%n"></input></inputs><script><block s="doReport"><block s="reportQuotient"><block s="reportMonadic"><l><option>ln</option></l><block var="n"/></block><block s="reportMonadic"><l><option>ln</option></l><block var="b"/></block></block></block></script></block-definition><block-definition s="simple permutations of %&apos;r&apos; items out of %&apos;n&apos;" type="reporter" category="other" helper="true"><header></header><code></code><translations></translations><inputs><input type="%n"></input><input type="%n"></input></inputs><script><block s="doReport"><block s="reportIfElse"><block s="reportEquals"><block var="r"/><l>0</l></block><l>1</l><block s="reportAtomicCombine"><block s="reportNumbers"><block s="reportSum"><block s="reportDifference"><block var="n"/><block var="r"/></block><l>1</l></block><block var="n"/></block><block s="reifyReporter"><autolambda><block s="reportProduct"><l></l><l></l></block></autolambda><list></list></block></block></block></block></script></block-definition><block-definition s="simple combs %&apos;r&apos; out of %&apos;n&apos;" type="reporter" category="other" helper="true"><header></header><code></code><translations></translations><inputs><input type="%n"></input><input type="%n"></input></inputs><script><block s="doReport"><block s="reportQuotient"><custom-block s="simple permutations of %n items out of %n"><block var="r"/><block var="n"/></custom-block><custom-block s="factorial $!-1-255-255-0 %n"><block var="r"/></custom-block></block></block></script></block-definition><block-definition s="numbers from %&apos;from&apos; to %&apos;to&apos; ascending" type="reporter" category="lists"><header></header><code></code><translations></translations><inputs><input type="%n"></input><input type="%n"></input></inputs><script><block s="doReport"><block s="evaluate"><custom-block s="scalar -&gt; hyper %repRing"><block s="reifyReporter"><autolambda><custom-block s="simple numbers from %n to %n ascending"><l></l><l></l></custom-block></autolambda><list></list></block></custom-block><list><block var="from"/><block var="to"/></list></block></block></script></block-definition><block-definition s="simple gcd %&apos;a&apos; %&apos;b&apos;" type="reporter" category="other" helper="true"><header></header><code></code><translations></translations><inputs><input type="%n"></input><input type="%n"></input></inputs><script><block s="doIf"><block s="reportEquals"><block var="b"/><l>0</l></block><script><block s="doReport"><block var="a"/></block></script></block><block s="doReport"><custom-block s="simple gcd %n %n"><block var="b"/><block s="reportModulus"><block var="a"/><block var="b"/></block></custom-block></block></script></block-definition><block-definition s="de-boolean %&apos;n&apos;" type="reporter" category="other" helper="true"><header></header><code></code><translations></translations><inputs><input type="%s"></input></inputs><script><block s="doIfElse"><block s="reportIsA"><block var="n"/><l><option>list</option></l></block><script><block s="doReport"><block s="reportMap"><block s="reifyReporter"><autolambda><custom-block s="de-boolean %s"><l></l></custom-block></autolambda><list></list></block><block var="n"/></block></block></script><script><block s="doReport"><block s="reportIfElse"><custom-block s="zero? %n"><block var="n"/></custom-block><l>0</l><block s="reportIfElse"><block s="reportEquals"><block var="n"/><block s="reportBoolean"><l><bool>true</bool></l></block></block><l>1</l><block var="n"/></block></block></block></script></block></script></block-definition><block-definition s="simple lcm %&apos;a&apos; %&apos;b&apos;" type="reporter" category="other" helper="true"><header></header><code></code><translations></translations><inputs><input type="%n"></input><input type="%n"></input></inputs><script><block s="doIf"><block s="reportEquals"><block var="b"/><l>0</l></block><script><block s="doReport"><block var="b"/></block></script></block><block s="doReport"><block s="reportProduct"><block var="a"/><block s="reportQuotient"><block var="b"/><custom-block s="simple gcd %n %n"><block var="a"/><block var="b"/></custom-block></block></block></block></script></block-definition><block-definition s="simple numbers from %&apos;from&apos; to %&apos;to&apos; ascending" type="reporter" category="other" helper="true"><header></header><code></code><translations></translations><inputs><input type="%n"></input><input type="%n"></input></inputs><script><block s="doReport"><block s="reportIfElse"><block s="reportGreaterThan"><block var="from"/><block var="to"/></block><block s="reportNewList"><list></list></block><block s="reportNumbers"><block var="from"/><block var="to"/></block></block></block></script></block-definition><block-definition s="$flash sort %&apos;data&apos; ordering with %&apos;function&apos;" type="reporter" category="lists"><comment x="0" y="0" w="161.14285714285708" collapsed="false">Reports a sorted version of the list in its first input slot, using the comparison function in the second input slot.  For a list of numbers, using &lt; as the comparison function will sort from low to high; using &gt; will sort from high to low.</comment><header></header><code></code><translations>ca:ordena _ segons criteri _&#xD;</translations><inputs><input type="%l"></input><input type="%predRing"></input></inputs><script><block s="doReport"><block s="reportApplyExtension"><l>lst_sort(list, fn)</l><list><block var="data"/><block var="function"/></list></block></block></script><scripts><script x="12" y="147.55555555555554"><block s="doDeclareVariables"><list><l>even items</l><l>odd items</l><l>merge</l><l>split</l><l>copy of data</l><l>id</l></list></block><block s="doSetVar"><l>id</l><block s="reifyScript"><script><block s="doReport"><l></l></block></script><list></list></block></block><block s="doSetVar"><l>copy of data</l><block s="reportMap"><block var="id"/><block var="data"/></block></block><block s="doSetVar"><l>split</l><block s="reifyScript"><script><block s="doSetVar"><l>even items</l><block s="reportNewList"><list></list></block></block><block s="doSetVar"><l>odd items</l><block s="reportNewList"><list></list></block></block><block s="doUntil"><block s="reportListIsEmpty"><block var="copy of data"/></block><script><block s="doAddToList"><block s="reportListItem"><l>1</l><block var="copy of data"/></block><block var="odd items"/></block><block s="doDeleteFromList"><l>1</l><block var="copy of data"/></block><block s="doIf"><block s="reportNot"><block s="reportListIsEmpty"><block var="copy of data"/></block></block><script><block s="doAddToList"><block s="reportListItem"><l>1</l><block var="copy of data"/></block><block var="even items"/></block><block s="doDeleteFromList"><l>1</l><block var="copy of data"/></block></script></block></script></block></script><list></list></block></block><block s="doSetVar"><l>merge</l><block s="reifyScript"><script><block s="doIf"><block s="reportEquals"><block var="#1"/><block s="reportNewList"><list></list></block></block><script><block s="doReport"><block var="#2"/></block></script></block><block s="doIf"><block s="reportEquals"><block var="#2"/><block s="reportNewList"><list></list></block></block><script><block s="doReport"><block var="#1"/></block></script></block><block s="doIfElse"><block s="evaluate"><block var="function"/><list><block s="reportListItem"><l>1</l><block var="#1"/></block><block s="reportListItem"><l>1</l><block var="#2"/></block></list></block><script><block s="doReport"><block s="reportCONS"><block s="reportListItem"><l>1</l><block var="#1"/></block><block s="evaluate"><block var="merge"/><list><block s="reportCDR"><block var="#1"/></block><block var="#2"/></list></block></block></block></script><script><block s="doReport"><block s="reportCONS"><block s="reportListItem"><l>1</l><block var="#2"/></block><block s="evaluate"><block var="merge"/><list><block var="#1"/><block s="reportCDR"><block var="#2"/></block></list></block></block></block></script></block></script><list><l>#1</l><l>#2</l></list></block></block><block s="doIf"><block s="reportEquals"><block var="data"/><block s="reportNewList"><list></list></block></block><script><block s="doReport"><block s="reportNewList"><list></list></block></block></script></block><block s="doIf"><block s="reportEquals"><block s="reportCDR"><block var="data"/></block><block s="reportNewList"><list></list></block></block><script><block s="doReport"><block var="data"/></block></script></block><block s="doRun"><block var="split"/><list></list></block><block s="doReport"><block s="evaluate"><block var="merge"/><list><custom-block s="$flash sort %l ordering with %predRing"><block var="odd items"/><block var="function"/></custom-block><custom-block s="$flash sort %l ordering with %predRing"><block var="even items"/><block var="function"/></custom-block></list></block></block></script></scripts></block-definition><block-definition s="☠︎ linked? %&apos;data&apos;" type="predicate" category="lists" helper="true"><header></header><code></code><translations></translations><inputs><input type="%l"></input></inputs><script><block s="doReport"><block s="reportApplyExtension"><l>lst_linked(list)</l><list><block var="data"/></list></block></block></script></block-definition><block-definition s="☠︎ link %&apos;data&apos;" type="reporter" category="lists" helper="true"><header></header><code></code><translations></translations><inputs><input type="%l"></input></inputs><script><block s="doIf"><block s="reportListIsEmpty"><block var="data"/></block><script><block s="doReport"><block var="data"/></block></script></block><block s="doReport"><block s="reportCONS"><block s="reportListItem"><l>1</l><block var="data"/></block><block s="reportCDR"><block var="data"/></block></block></block></script></block-definition><block-definition s="printable %&apos;data&apos;" type="reporter" category="lists"><comment x="0" y="0" w="188.66666666666666" collapsed="false">Takes a (possibly deep) list as input,&#xD;and reports a human-readable text form &#xD;of the list (namely, Lisp notation).&#xD;&#xD;Will not work on circular lists.</comment><header></header><code></code><translations></translations><inputs><input type="%l"></input></inputs><script><block s="doIf"><block s="reportNot"><block s="reportIsA"><block var="data"/><l><option>list</option></l></block></block><script><block s="doReport"><block var="data"/></block></script></block><block s="doIf"><block s="reportListIsEmpty"><block var="data"/></block><script><block s="doReport"><l>()</l></block></script></block><block s="doReport"><block s="reportJoinWords"><list><l>(</l><block s="reportAtomicCombine"><block s="reportMap"><block s="reifyReporter"><autolambda><custom-block s="printable %l"><l/></custom-block></autolambda><list></list></block><block var="data"/></block><block s="reifyReporter"><autolambda><block s="reportJoinWords"><list><l></l><l> </l><l></l></list></block></autolambda><list></list></block></block><l>)</l></list></block></block></script></block-definition><block-definition s="%&apos;x&apos;" type="reporter" category="lists"><comment x="0" y="0" w="105.33333333333333" collapsed="false">The identity function reports its input.</comment><header></header><code></code><translations></translations><inputs><input type="%s"></input></inputs><script><block s="doReport"><block var="x"/></block></script></block-definition><block-definition s="multimap %&apos;function&apos; over %&apos;lists&apos;" type="reporter" category="lists"><comment x="0" y="0" w="267.3333333333333" collapsed="false">Takes as input a function of N inputs and N lists.&#xD;The function is called with item 1 of all the lists as its inputs, with item 2 of all the lists as its inputs, and so on.  (The lists should all be the same length.)</comment><header></header><code></code><translations></translations><inputs><input type="%repRing"></input><input type="%mult%l"></input></inputs><script><block s="doReport"><block s="reportMap"><block s="reifyReporter"><autolambda><block s="evaluate"><block var="function"/><custom-block s="%s"><l></l></custom-block></block></autolambda><list></list></block><block s="reportListAttribute"><l><option>columns</option></l><block var="lists"/></block></block></block></script></block-definition><block-definition s="scalar -&gt; hyper %&apos;func&apos;" type="reporter" category="control" helper="true"><comment x="0" y="0" w="218" collapsed="false">Takes a dyadic scalar function as input, and&#xD;hyperizes it, so that it can take lists as inputs.&#xD;&#xD;Don&apos;t use on slow functions (this has compiled map calls).  Meant for use on primitives.</comment><header></header><code></code><translations></translations><inputs><input type="%repRing"></input></inputs><script><block s="doDeclareVariables"><list><l>hyper func</l><l>scalarized</l></list></block><block s="doSetVar"><l>hyper func</l><block s="reifyReporter"><script><block s="doWarp"><script><block s="doIfElse"><custom-block s="scalar? %s"><block var="a"/></custom-block><script><block s="doIfElse"><custom-block s="scalar? %s"><block var="b"/></custom-block><script><block s="doReport"><block s="evaluate"><block var="func"/><list><custom-block s="scalar-value helper %s"><block var="a"/></custom-block><custom-block s="scalar-value helper %s"><block var="b"/></custom-block></list></block></block></script><script><block s="doSetVar"><l>scalarized</l><custom-block s="scalar-value helper %s"><block var="a"/></custom-block></block><block s="doIf"><block s="reportEquals"><l></l><block s="reportAtomicFindFirst"><block s="reifyPredicate"><autolambda><block s="reportIsA"><l></l><l><option>list</option></l></block></autolambda><list></list></block><block var="b"/></block></block><script><block s="doReport"><block s="reportAtomicMap"><block s="reifyReporter"><autolambda><block s="evaluate"><block var="func"/><list><block var="scalarized"/><l></l></list></block></autolambda><list></list></block><block var="b"/></block></block></script></block><block s="doReport"><block s="reportMap"><block s="reifyReporter"><autolambda><block s="evaluate"><block var="hyper func"/><list><block var="scalarized"/><l></l></list></block></autolambda><list></list></block><block var="b"/></block></block></script></block></script><script><block s="doIfElse"><custom-block s="scalar? %s"><block var="b"/></custom-block><script><block s="doSetVar"><l>scalarized</l><custom-block s="scalar-value helper %s"><block var="b"/></custom-block></block><block s="doIf"><block s="reportEquals"><l></l><block s="reportAtomicFindFirst"><block s="reifyPredicate"><autolambda><block s="reportIsA"><l></l><l><option>list</option></l></block></autolambda><list></list></block><block var="a"/></block></block><script><block s="doReport"><block s="reportAtomicMap"><block s="reifyReporter"><autolambda><block s="evaluate"><block var="func"/><list><l></l><block var="scalarized"/></list></block></autolambda><list></list></block><block var="a"/></block></block></script></block><block s="doReport"><block s="reportMap"><block s="reifyReporter"><autolambda><block s="evaluate"><block var="hyper func"/><list><l></l><block var="scalarized"/></list></block></autolambda><list></list></block><block var="a"/></block></block></script><script><block s="doIf"><block s="reportAnd"><block s="reportEquals"><l></l><block s="reportAtomicFindFirst"><block s="reifyPredicate"><autolambda><block s="reportIsA"><l></l><l><option>list</option></l></block></autolambda><list></list></block><block var="a"/></block></block><block s="reportEquals"><l></l><block s="reportAtomicFindFirst"><block s="reifyPredicate"><autolambda><block s="reportIsA"><l></l><l><option>list</option></l></block></autolambda><list></list></block><block var="b"/></block></block></block><script><block s="doReport"><custom-block s="multimap %repRing over %mult%l"><block var="func"/><list><block var="a"/><block var="b"/></list></custom-block></block></script></block><block s="doReport"><custom-block s="multimap %repRing over %mult%l"><block var="hyper func"/><list><block var="a"/><block var="b"/></list></custom-block></block></script></block></script></block></script></block></script><list><l>a</l><l>b</l></list></block></block><block s="doReport"><block var="hyper func"/></block></script></block-definition><block-definition s="log base %&apos;b&apos; $⍟-1.5-255-255-0 %&apos;x&apos;" type="reporter" category="operators"><comment x="0" y="0" w="212" collapsed="false">Computes logarithms in any base.&#xD;&#xD;The base is the left input.  It&apos;s usual in APL that if there&apos;s a main data input and some sort of control input, the latter comes on the left.  This is because APL syntax, unless you use parentheses, groups computations from right to left.&#xD;&#xD;APL has a monadic version of this function that computes natural logs (log to the base e).</comment><header></header><code></code><translations></translations><inputs><input type="%n"></input><input type="%n"></input></inputs><script><block s="doReport"><block s="evaluate"><custom-block s="scalar -&gt; hyper %repRing"><block s="reifyReporter"><autolambda><custom-block s="simple log base %n of %n"><l></l><l></l></custom-block></autolambda><list></list></block></custom-block><list><block var="b"/><block var="x"/></list></block></block></script></block-definition><block-definition s="combs %&apos;r&apos; at a time $!-1-255-255-0 of %&apos;n&apos;" type="reporter" category="operators"><comment x="0" y="0" w="218.66666666666666" collapsed="false">Computes the number of combinations of right-input things taken left-input at a time, otherwise known as the elements of Pascal&apos;s triangle.  This block shares the ! symbol with the monadic factorial function, because the formula for computing this function uses factorials.</comment><header></header><code></code><translations></translations><inputs><input type="%n"></input><input type="%n"></input></inputs><script><block s="doReport"><block s="evaluate"><custom-block s="scalar -&gt; hyper %repRing"><block s="reifyReporter"><autolambda><custom-block s="simple combs %n out of %n"><l></l><l></l></custom-block></autolambda><list></list></block></custom-block><list><block var="r"/><block var="n"/></list></block></block></script></block-definition><block-definition s="factorial $!-1-255-255-0 %&apos;n&apos;" type="reporter" category="operators"><comment x="0" y="0" w="172.66666666666666" collapsed="false">The factorial of a positive integer n is the product of the integers from 1 to n.&#xD;&#xD;In real APL, the domain of this function is extended beyond integers to compute the gamma function.</comment><header></header><code></code><translations></translations><inputs><input type="%n"></input></inputs><script><block s="doIfElse"><block s="reportIsA"><block var="n"/><l><option>list</option></l></block><script><block s="doReport"><block s="reportMap"><block s="reifyReporter"><autolambda><custom-block s="factorial $!-1-255-255-0 %n"><l></l></custom-block></autolambda><list></list></block><block var="n"/></block></block></script><script><block s="doReport"><block s="reportIfElse"><custom-block s="zero? %n"><block var="n"/></custom-block><l>1</l><block s="reportAtomicCombine"><block s="reportNumbers"><l>1</l><block var="n"/></block><block s="reifyReporter"><autolambda><block s="reportProduct"><l></l><l></l></block></autolambda><list></list></block></block></block></block></script></block></script></block-definition><block-definition s="%&apos;a&apos; scalar %&apos;pred&apos; %&apos;b&apos;" type="predicate" category="operators"><comment x="0" y="0" w="190" collapsed="false">Acts just like the function selected from&#xD;the pulldown menu, but hyperized, so&#xD;comparing two equal-sized lists reports&#xD;a list of the same length as the inputs,&#xD;with the results of item-by-item comparisons.</comment><header></header><code></code><translations></translations><inputs><input type="%s"></input><input type="%s" readonly="true">﹦<options>﹦&#xD;≠&#xD;identical to&#xD;and&#xD;or&#xD;is _ a _?</options></input><input type="%s"></input></inputs><script><block s="doReport"><block s="evaluate"><custom-block s="scalar -&gt; hyper %repRing"><block s="reportListItem"><block s="reportListIndex"><block var="pred"/><block s="reportNewList"><list><l>﹦</l><l>≠</l><l>identical to</l><l>and</l><l>or</l><l>is _ a _?</l></list></block></block><block s="reportNewList"><list><block s="reifyPredicate"><autolambda><block s="reportEquals"><l></l><l></l></block></autolambda><list></list></block><block s="reifyPredicate"><autolambda><block s="reportNotEquals"><l></l><l></l></block></autolambda><list></list></block><block s="reifyPredicate"><autolambda><block s="reportIsIdentical"><l></l><l></l></block></autolambda><list></list></block><block s="reifyPredicate"><autolambda><block s="reportAnd"><l/><l/></block></autolambda><list></list></block><block s="reifyPredicate"><autolambda><block s="reportOr"><l/><l/></block></autolambda><list></list></block><block s="reifyPredicate"><autolambda><block s="reportIsA"><l></l><l></l></block></autolambda><list></list></block></list></block></block></custom-block><list><block var="a"/><block var="b"/></list></block></block></script></block-definition><block-definition s="GCD (or) %&apos;a&apos; $∨-1.2-255-255-0 %&apos;b&apos;" type="reporter" category="operators"><comment x="0" y="0" w="230.66666666666666" collapsed="false">Reports the greatest common divisor of its inputs.&#xD;If the inputs are values in {0,1} then this is equivalent to the logical OR of the values, with 0=False, 1=True.  Hence the APL symbol ∨.&#xD;Also accepts Snap! Booleans as inputs.</comment><header></header><code></code><translations></translations><inputs><input type="%n"></input><input type="%n"></input></inputs><script><block s="doReport"><block s="evaluate"><custom-block s="scalar -&gt; hyper %repRing"><block s="reifyReporter"><autolambda><custom-block s="simple gcd %n %n"><l></l><l></l></custom-block></autolambda><list></list></block></custom-block><list><custom-block s="de-boolean %s"><block var="a"/></custom-block><custom-block s="de-boolean %s"><block var="b"/></custom-block></list></block></block></script></block-definition><block-definition s="LCM (and) %&apos;a&apos; $∧-1.2-255-255-0 %&apos;b&apos;" type="reporter" category="operators"><comment x="0" y="0" w="230.66666666666666" collapsed="false">Reports the least common multiple of its inputs.&#xD;If the inputs are values in {0,1} then this is equivalent to the logical AND of the values, with 0=False, 1=True.  Hence the APL symbol ∧.&#xD;Also accepts Snap! Booleans as inputs.</comment><header></header><code></code><translations></translations><inputs><input type="%n"></input><input type="%n"></input></inputs><script><block s="doReport"><block s="evaluate"><custom-block s="scalar -&gt; hyper %repRing"><block s="reifyReporter"><autolambda><custom-block s="simple lcm %n %n"><l></l><l></l></custom-block></autolambda><list></list></block></custom-block><list><custom-block s="de-boolean %s"><block var="a"/></custom-block><custom-block s="de-boolean %s"><block var="b"/></custom-block></list></block></block></script></block-definition><block-definition s="NOT $&#126;-1-255-255-0 %&apos;p&apos;" type="reporter" category="operators"><comment x="0" y="0" w="167.33333333333334" collapsed="false">Reports 1 if the input is False or 0;&#xD;otherwise reports 0.</comment><header></header><code></code><translations></translations><inputs><input type="%s"></input></inputs><script><block s="doReport"><block s="reportDifference"><l>1</l><custom-block s="signum $×-1-255-255-0 %n"><block s="reportMonadic"><l><option>abs</option></l><block var="p"/></block></custom-block></block></block></script></block-definition><block-definition s="permutations of %&apos;r&apos; items out of %&apos;n&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="evaluate"><custom-block s="scalar -&gt; hyper %repRing"><block s="reifyReporter"><autolambda><custom-block s="simple permutations of %n items out of %n"><l></l><l></l></custom-block></autolambda><list></list></block></custom-block><list><block var="r"/><block var="n"/></list></block></block></script></block-definition><block-definition s="identity $+-1-255-255-0 %&apos;x&apos;" type="reporter" category="operators"><comment x="0" y="0" w="210.00000000000003" collapsed="false">Reports its input.&#xD;This is useful to fit a value into a different-type input slot, e.g., number into list slot.</comment><header></header><code></code><translations></translations><inputs><input type="%s"></input></inputs><script><block s="doReport"><block s="reportMonadic"><l><option>id</option></l><block var="x"/></block></block></script></block-definition><block-definition s="deep map %&apos;function&apos; over %&apos;data&apos;" type="reporter" category="lists"><header></header><code></code><translations></translations><inputs><input type="%repRing"></input><input type="%l"></input></inputs><script><block s="doIfElse"><block s="reportIsA"><block var="data"/><l><option>list</option></l></block><script><block s="doReport"><block s="reportMap"><block s="reifyReporter"><autolambda><custom-block s="deep map %repRing over %l"><block var="function"/><l/></custom-block></autolambda><list></list></block><block var="data"/></block></block></script><script><block s="doReport"><block s="evaluate"><block var="function"/><list><block var="data"/></list></block></block></script></block></script></block-definition><block-definition s="%&apos;howmany&apos; deal $?-1-255-255-0 %&apos;range&apos;" type="reporter" category="operators"><comment x="0" y="0" w="177.33333333333334" collapsed="false">Report a list with left-input random integers in the range 1 to right-input.&#xD;No number appears more than once&#xD;in the result.  The left input must be less than or equal to the right input.</comment><header></header><code></code><translations></translations><inputs><input type="%n"></input><input type="%n"></input></inputs><script><block s="doReport"><block s="evaluate"><custom-block s="scalar -&gt; hyper %repRing"><block s="reifyReporter"><autolambda><custom-block s="%n deal helper %l"><l></l><block s="reportNumbers"><l>1</l><l></l></block></custom-block></autolambda><list></list></block></custom-block><list><block var="howmany"/><block var="range"/></list></block></block></script></block-definition><block-definition s="outer product %&apos;a&apos; $○.-1-255-255-0 %&apos;function&apos; %&apos;b&apos;" type="reporter" category="lists"><comment x="0" y="0" w="297.99999999999994" collapsed="false">Given two arrays A and B, reports an array whose dimensions are&#xD;APPEND(SHAPE OF (A), SHAPE OF (B))&#xD;in which each atomic item of the result is computed by applying the dyadic function input to an item of A and an item of B.</comment><header></header><code></code><translations></translations><inputs><input type="%l"></input><input type="%repRing"></input><input type="%l"></input></inputs><script><block s="doIfElse"><block s="reportIsA"><block var="a"/><l><option>list</option></l></block><script><block s="doIf"><block s="reportListIsEmpty"><block var="a"/></block><script><block s="doReport"><block s="reportNewList"><list></list></block></block></script></block><block s="doReport"><block s="reportCONS"><custom-block s="outer product %l $○.-1-255-255-0 %repRing %l"><block s="reportListItem"><l>1</l><block var="a"/></block><block var="function"/><block var="b"/></custom-block><custom-block s="outer product %l $○.-1-255-255-0 %repRing %l"><block s="reportCDR"><block var="a"/></block><block var="function"/><block var="b"/></custom-block></block></block></script><script><block s="doIfElse"><block s="reportIsA"><block var="b"/><l><option>list</option></l></block><script><block s="doIf"><block s="reportListIsEmpty"><block var="b"/></block><script><block s="doReport"><block s="reportNewList"><list></list></block></block></script></block><block s="doReport"><block s="reportCONS"><custom-block s="outer product %l $○.-1-255-255-0 %repRing %l"><block var="a"/><block var="function"/><block s="reportListItem"><l>1</l><block var="b"/></block></custom-block><custom-block s="outer product %l $○.-1-255-255-0 %repRing %l"><block var="a"/><block var="function"/><block s="reportCDR"><block var="b"/></block></custom-block></block></block></script><script><block s="doReport"><block s="evaluate"><block var="function"/><list><block var="a"/><block var="b"/></list></block></block></script></block></script></block></script></block-definition></blocks><stage name="Stage" width="1000" height="1000" costume="0" color="0,2,17,1" 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 struct="atomic" id="3010"></list></costumes><sounds><list struct="atomic" id="3011"></list></sounds><variables></variables><blocks></blocks><scripts><script x="43" y="44.166666666666686"><block s="receiveGo"></block><block s="setBackgroundColor"><color>0,2,17,1</color></block></script></scripts><sprites select="1"><watcher var="n" style="normal" x="10" y="10" color="243,118,29" hidden="true"/><watcher var="digits" style="normal" x="44" y="67.00000199999998" color="243,118,29" extX="80" extY="70.00000000000001" hidden="true"/><watcher var="d" style="normal" x="10" y="31.000001999999988" color="243,118,29" hidden="true"/><watcher var="digit length?" style="normal" x="10" y="52.00000399999999" color="243,118,29" hidden="true"/><sprite name="Sprite" idx="1" x="336.40731755687375" y="140.03429242817884" heading="342" scale="1" volume="100" pan="0" rotation="1" draggable="true" costume="0" color="56,255,135.60000000000005,1" pen="tip" id="3023"><costumes><list struct="atomic" id="3024"></list></costumes><sounds><list struct="atomic" id="3025"></list></sounds><blocks></blocks><variables></variables><scripts><script x="20" y="20"><block s="receiveGo"></block><block s="doSetVar"><l>d</l><l>49</l><comment w="90" collapsed="false">Set divisor.</comment></block><block s="doSetVar"><l>n</l><block s="reportDifference"><block var="d"/><l>1</l></block></block><block s="doSetVar"><l>digits</l><block s="reportNewList"><list></list></block></block><block s="doSetVar"><l>digit length?</l><block s="reportBoolean"><l><bool>true</bool></l></block></block><block s="gotoXY"><l>400</l><l>-100</l><comment w="90" collapsed="false">Adjust positioning.</comment></block><block s="setHeading"><l>90</l></block><block s="clear"></block><block s="show"></block><block s="down"></block><block s="setColor"><color>255,81,56,1</color><comment w="80" collapsed="false">Choose color.</comment></block><block s="setSize"><l>3</l></block><block s="doUntil"><block s="reportKeyPressed"><l><option>space</option></l></block><script><block s="doIfElse"><block s="reportEquals"><block s="reportMonadic"><l><option>floor</option></l><block s="reportQuotient"><block var="n"/><block var="d"/></block></block><l>0</l></block><script><block s="doAddToList"><l>0</l><block var="digits"/></block></script><script><block s="doAddToList"><block s="reportMonadic"><l><option>floor</option></l><block s="reportQuotient"><block var="n"/><block var="d"/></block></block><block var="digits"/></block><block s="doSetVar"><l>n</l><block s="reportDifference"><block var="n"/><block s="reportProduct"><block s="reportMonadic"><l><option>floor</option></l><block s="reportQuotient"><block var="n"/><block var="d"/></block></block><block var="d"/></block></block></block></script></block><block s="doSetVar"><l>n</l><block s="reportProduct"><block var="n"/><l>10</l></block></block><block s="setPenColorDimension"><l><option>hue</option></l><block s="reportProduct"><block s="reportListItem"><l><option>last</option></l><block var="digits"/></block><l>10</l></block></block><block s="turn"><block s="reportProduct"><block s="reportListItem"><l><option>last</option></l><block var="digits"/></block><block s="reportQuotient"><l>360</l><l>10</l></block></block></block><block s="forward"><block s="reportIfElse"><block var="digit length?"/><block s="reportProduct"><block s="reportListItem"><l><option>last</option></l><block var="digits"/></block><l>5.5</l></block><l>30</l></block><comment w="90" collapsed="false">Adjust size.</comment></block></script></block><block s="up"></block></script><script x="20" y="638.5000000000002"><block s="hide"></block><block s="gotoXY"><l>-20</l><l>0</l></block><block s="setHeading"><l>90</l></block><block s="setColor"><color>245,255,254,1</color></block><block s="write"><block s="reportJoinWords"><list><block s="reportDifference"><block var="d"/><l>1</l></block><l>/</l><block var="d"/></list></block><l>24</l><comment w="90" collapsed="false">Add legend.</comment></block></script></scripts></sprite></sprites></stage><variables><variable name="n"><l>240</l></variable><variable name="digits"><list struct="atomic" id="3170">0,9,7,9,5,9,1,8,3,6,7,3,4,6,9,3,8,7,7,5,5,1,0,2,0,4,0,8,1,6,3,2,6,5,3,0,6,1,2,2,4,4,8,9,7,9,5,9,1,8,3,6,7,3,4,6,9,3,8,7,7,5,5,1,0,2,0,4,0,8,1,6,3,2,6,5,3,0,6,1,2,2,4,4,8,9,7,9,5,9,1,8,3,6,7,3,4,6,9,3,8,7,7,5,5,1,0,2,0,4,0,8,1,6,3,2,6,5,3,0,6,1,2,2,4,4,8,9,7,9,5,9,1,8,3,6,7,3,4,6,9,3,8,7,7,5,5,1,0,2,0,4,0,8,1,6,3,2,6,5,3,0,6,1,2,2,4,4,8,9,7,9,5,9,1,8,3,6,7,3,4,6,9,3,8,7,7,5,5,1,0,2,0,4,0,8,1,6,3,2,6,5,3,0,6,1,2,2,4,4,8,9,7,9,5,9,1,8,3,6,7,3,4,6,9,3,8,7,7,5,5,1,0,2,0,4,0,8,1,6,3,2,6,5,3,0,6,1,2,2,4,4,8,9,7,9,5,9,1,8,3,6,7,3,4,6,9,3,8,7,7,5,5,1,0,2,0,4,0,8,1,6,3,2,6,5,3,0,6,1,2,2,4,4,8,9,7,9,5,9,1,8,3,6,7,3,4,6,9,3,8,7,7,5,5,1,0,2,0,4,0,8,1,6,3,2,6,5,3,0,6,1,2,2,4,4,8,9,7,9,5,9,1,8,3,6,7,3,4,6,9,3,8,7,7,5,5,1,0,2,0,4,0,8,1,6,3,2,6,5,3,0,6,1,2,2,4,4,8,9,7,9,5,9,1,8,3,6,7,3,4,6,9,3,8,7,7,5,5,1,0,2,0,4,0,8,1,6,3,2,6,5,3,0,6,1,2,2,4,4,8,9,7,9,5,9,1,8,3,6,7,3,4,6,9,3,8,7,7,5,5,1,0,2,0,4,0,8,1,6,3,2,6,5,3,0,6,1,2,2,4</list></variable><variable name="d"><l>49</l></variable><variable name="digit length?"><bool>true</bool></variable></variables></scene></scenes></project><media name="digits from division" app="Snap! 7, https://snap.berkeley.edu" version="2"></media></snapdata>