1 | dojo.provide("dojox.lang.functional.linrec"); |
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2 | |
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3 | dojo.require("dojox.lang.functional.lambda"); |
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4 | dojo.require("dojox.lang.functional.util"); |
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5 | |
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6 | // This module provides recursion combinators: |
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7 | // - a linear recursion combinator. |
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8 | |
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9 | // Acknoledgements: |
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10 | // - recursion combinators are inspired by Manfred von Thun's article |
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11 | // "Recursion Theory and Joy" |
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12 | // (http://www.latrobe.edu.au/philosophy/phimvt/joy/j05cmp.html) |
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13 | |
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14 | // Notes: |
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15 | // - recursion combinators produce a function, which implements |
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16 | // their respective recusion patterns. String lambdas are inlined, if possible. |
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17 | |
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18 | (function(){ |
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19 | var df = dojox.lang.functional, inline = df.inlineLambda, |
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20 | _x ="_x", _r_y_a = ["_r", "_y.a"]; |
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21 | |
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22 | df.linrec = function( |
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23 | /*Function|String|Array*/ cond, |
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24 | /*Function|String|Array*/ then, |
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25 | /*Function|String|Array*/ before, |
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26 | /*Function|String|Array*/ after){ |
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27 | // summary: |
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28 | // Generates a function for the linear recursion pattern. |
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29 | // All parameter functions are called in the context of "this" object. |
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30 | // cond: |
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31 | // The lambda expression, which is used to detect the termination of recursion. |
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32 | // It accepts the same parameter as the generated recursive function itself. |
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33 | // This function should return "true", if the recursion should be stopped, |
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34 | // and the "then" part should be executed. Otherwise the recursion will proceed. |
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35 | // then: |
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36 | // The lambda expression, which is called upon termination of the recursion. |
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37 | // It accepts the same parameters as the generated recursive function itself. |
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38 | // The returned value will be returned as the value of the generated function. |
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39 | // before: |
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40 | // The lambda expression, which is called before the recursive step. |
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41 | // It accepts the same parameter as the generated recursive function itself. |
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42 | // The returned value should be an array, which is used to call |
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43 | // the generated function recursively. |
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44 | // above: |
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45 | // The lambda expression, which is called after the recursive step. |
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46 | // It accepts two parameters: the returned value from the recursive step, and |
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47 | // the original array of parameters used with all other functions. |
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48 | // The returned value will be returned as the value of the generated function. |
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49 | |
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50 | var c, t, b, a, cs, ts, bs, as, dict1 = {}, dict2 = {}, |
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51 | add2dict = function(x){ dict1[x] = 1; }; |
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52 | if(typeof cond == "string"){ |
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53 | cs = inline(cond, _x, add2dict); |
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54 | }else{ |
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55 | c = df.lambda(cond); |
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56 | cs = "_c.apply(this, _x)"; |
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57 | dict2["_c=_t.c"] = 1; |
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58 | } |
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59 | if(typeof then == "string"){ |
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60 | ts = inline(then, _x, add2dict); |
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61 | }else{ |
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62 | t = df.lambda(then); |
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63 | ts = "_t.t.apply(this, _x)"; |
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64 | } |
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65 | if(typeof before == "string"){ |
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66 | bs = inline(before, _x, add2dict); |
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67 | }else{ |
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68 | b = df.lambda(before); |
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69 | bs = "_b.apply(this, _x)"; |
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70 | dict2["_b=_t.b"] = 1; |
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71 | } |
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72 | if(typeof after == "string"){ |
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73 | as = inline(after, _r_y_a, add2dict); |
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74 | }else{ |
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75 | a = df.lambda(after); |
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76 | as = "_a.call(this, _r, _y.a)"; |
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77 | dict2["_a=_t.a"] = 1; |
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78 | } |
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79 | var locals1 = df.keys(dict1), locals2 = df.keys(dict2), |
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80 | f = new Function([], "var _x=arguments,_y,_r".concat( // Function |
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81 | locals1.length ? "," + locals1.join(",") : "", |
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82 | locals2.length ? ",_t=_x.callee," + locals2.join(",") : t ? ",_t=_x.callee" : "", |
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83 | ";for(;!", |
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84 | cs, |
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85 | ";_x=", |
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86 | bs, |
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87 | "){_y={p:_y,a:_x}}_r=", |
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88 | ts, |
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89 | ";for(;_y;_y=_y.p){_r=", |
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90 | as, |
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91 | "}return _r" |
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92 | )); |
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93 | if(c){ f.c = c; } |
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94 | if(t){ f.t = t; } |
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95 | if(b){ f.b = b; } |
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96 | if(a){ f.a = a; } |
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97 | return f; |
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98 | }; |
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99 | })(); |
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100 | |
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101 | /* |
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102 | For documentation only: |
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103 | |
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104 | 1) The original recursive version: |
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105 | |
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106 | var linrec1 = function(cond, then, before, after){ |
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107 | var cond = df.lambda(cond), |
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108 | then = df.lambda(then), |
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109 | before = df.lambda(before), |
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110 | after = df.lambda(after); |
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111 | return function(){ |
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112 | if(cond.apply(this, arguments)){ |
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113 | return then.apply(this, arguments); |
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114 | } |
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115 | var args = before.apply(this, arguments); |
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116 | var ret = arguments.callee.apply(this, args); |
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117 | return after.call(this, ret, arguments); |
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118 | }; |
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119 | }; |
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120 | |
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121 | 2) The original iterative version (before minification and inlining): |
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122 | |
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123 | var linrec2 = function(cond, then, before, after){ |
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124 | var cond = df.lambda(cond), |
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125 | then = df.lambda(then), |
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126 | before = df.lambda(before), |
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127 | after = df.lambda(after); |
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128 | return function(){ |
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129 | var args = arguments, top, ret; |
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130 | // 1st part |
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131 | for(; !cond.apply(this, args); args = before.apply(this, args)){ |
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132 | top = {prev: top, args: args}; |
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133 | } |
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134 | ret = then.apply(this, args); |
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135 | //2nd part |
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136 | for(; top; top = top.prev){ |
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137 | ret = after.call(this, ret, top.args); |
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138 | } |
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139 | return ret; |
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140 | }; |
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141 | }; |
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142 | |
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143 | */ |
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