The Haskell School of Expression: Learning Functional Programming Through Multimedia

381 Pages·2010·21.783 MB·English

by  Paul Hudak

TheH asklleS choloo fE xpression
LEARNINGF UNCTIONAPL ROGRAMMING
THROUGH MULTIMEDIA
PAULH UDAK
TheH askleS lcholoo f
Expression
LEARNING FUNCTIONAL PROGRAMMING
THROUGH MULTIMEDIA
PAUL HUDAK
YalUen iversity
CA�IHRII)UGNEI VRI:S:IYI PRL�S
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www.cambridge.org
Informatoinot nh itsi tWl\e\:W .cambridge.org/9780521643382
� CambridgeU niversPriteys s2 000
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Contents
Preface pagex iii
1 ProbleSmo lving, PrograamnmdiC nagl,c ulation 1
1.1 ComputatiboynC alculatiinoH na skell 2
1.2Ex pressioVnasl,u easn,d T ypes 6
1.3 FunctiToynp esa ndT ypeS ignatures 8
1.4A bstractiAobns,t ractiAobns,t raction 10
1.4.N1a ming 10
1.4.2F unctionAabls traction 12
1.4.3Da taA bstraction 13
1.5 CodeR eusea ndM odularity 17
1.6 Bewaroef P rogramminwgi thN umbers 17
2 A Moduleo fS hapesP:a rIt 21
2.1 GeometrSihca pes 22
2.2 Areasof S hapes 25
2.3C leaninUgp 34
3 Simple Graphics 35
3.1 Basic Input/Output 36
3.2 GraphicWsi ndows 40
3.3 DrawinGgr aphics OtherT eTxhta n 42
3.4S omeE xamples 43
4 ShapeIsI D:r awinSgh apes 48
4.1 DealinWgi thD iffereCnoto rdinaStyes tems 48
4.2C onvertiSnhga petso G raphics 51
4.3 SomeE xamples 52
4.4I nR etrospect 54
s Polymorphaincd H igher-OrFduenrc tions 56
5.1P olymorphic Types 56
..
VII
viii Contents
5.2 AbstractOivoenrR ecursiDveefi nitions 58
5.2.1M api sP olymorphic 59
5.2.U2s inmga p 60
5.3 Append 63
5.3.T1h eE fficienacnydF Lxiotfy Append 64
5.4 Fold 65
5.4.H1a skell's Folds 67
5.4.W2h yT woF olds? 68
5.5 A FinaElx amplRee:v erse 69
5.6 Errors 71
6 Shape1s1 1P:e rimeteorfsS hapes 74
6.1 PerimetoefrS sh apes 74
7 Trees 81
7.1 A TreeD ataT ype 81
7.2 OperatioonnTs r ees 83
7.3 ArithmeEtxipcr essions 84
8 A Moduleo fR egions 87
8.1 TheR egioDna taT ype 87
8.2 TheM eaninogf S hapeasn dR egions 91
8.2.T1 heM eaninogf S hapes 92
8.2.T2 heE ncodionfgt heM eaninogf S hapes 93
8.2.T3h eM eaninogfR egions 96
8.2.T4 heE ncodionfgt heM eaninogf R egions 97
8.3 AlgebraciP ropertoifeR se gions 99
8.4 InR etrospect 101
9 MoreA boutH igher-OrFduenrc tions 105
9.1 Currying 105
9.2 Sections 108
9.3 AnonymouFsu nctions 110
9.4 FunctiCoonm position Ill
10 DrawinRge gions 114
10.1T heP ictuDraet a Type 115
10.2D rawingP ictures 115
10.3D ra\-\TingR egions l16
10.3.F1r omR egiontsoG raphiRcesg ionFsi:r sAtt tempt 117
10.3.F2r omR egiontsoG raphics RegSieocnosnA:dt tempt1 19
10 .3.T3r anslatSihnagp eisn tGor aphiRcesg ions 121
10 .3.4E xamples 123
Contents IX
10.4U serI nteraction 126
10.5P uttiintag l Tlo gether 127
10.5.1E xamples 128
11 Proobfy Induction 131
11.1I nductiaonndR ecur�ion 131
11.2E xampleofsL isItn duction 132
11.2.1P roviFnugn ction Equivalences 133
11.3 UsefuPlr opertoineL si sts 137
11.3.F1 unctiSotnr ictness 137
11.4I nductioonOn t heDra taT ypes 141
11.4.A1 MoreE fficieEnxtp onenti.aFtuinocnt ion 143
12 QualifieTdy pes 147
12.1E quality 148
12.2D efininYgo urO wn TypeC lasses 150
12.3I nheritance 153
12.4H askelSlt'asn daTrydp eC lasses 154
12.5D eriveIdn stances 157
12.6R easoniWnigt hT ypeC lasses 160
13 A Moduleo fS implAen imations 163
13.1W hati sa nA nimation? 163
13.2R epresentani nAgn imation 165
13.3 An Animator 167
13.4F unW ithT ypeC lasses 172
13.4.R1 isintgot heL eveolfA nimations 172
13.4.2T ypeC lassteost heR escue 172
13.4.3D efininNge w TypeC lassfeosr B ehaviors 176
13.5L iftitnotg h eL imit 177
13.6T imeT ransformation 179
L3.7A FinaElx amplAe K:a leidoscope Program 180
14 ProgramminWgi thS treams 187
14.1L azyE valuation 187
14.2R ecursiSvter eams 190
14.3S tream Diagrams 193
14.4L azyP atterns 195
14.5M emoization 198
14.6 Inductive Proopfe rItnifienLsii tset s 201
15 A Moduleo fR eactiAvnei mations 208
•
15.1F ALb yE xample 209
Contents
X
15 .1.1B asiRce activity 209
I5 .1.2E vent Choice 210
I5 .1.3R ecursiEvvee nPtr ocessing 21I
I5 .1.4E ventwsi thD ata 2I2
15 .1.5S napshot 212
15 .1.6B oolean Events 2I2
15.1.I7n tegration 213
15.2I mplementing FAL 214
15 .2.1A n ImplementatSitorna tegy 215
15 .2.2I ncremental Sampling 2I7
15.2.3F inal Refinements 219
15.2.4R epresentEivnegn ts 220
15.3T heI mplementation 220
15 .3.1B ehaviors 22I
15 .3.2E vents 225
15 .3.3A n Example 228
15.4E xtensions 229
15.4.1V ariatioonns sw itch 231
15 .4.2!\ 'louMsoet ion 232
I5 .5 Paddlebianl l TwenLtiyn es 233
16 CommunicatiWnigt ht heO utsidWeo rld 236
16.1F ileCsh,a nnelasn,d H andles 236
16.1.W1h y UseH andles? 238
16.1.C2h annels 238
16.2E xceptiHoann dling 239
16.3F irst-ClCahsasn nelasn dC oncurrency 242
17 RenderiRnega ctiAvnei mations 245
17.1P reliminaries 245
17.2R eactimate 246
17.3W indowU ser 247
18 Higher-OrTdypeers 249
18.1T heF unctoCrl ass 249
18.2T heM onadC lass 25I
18.2.1O theIrn stancoefsM onad 255
18.2.2O theMro nadiOcp erations 259
18.3 TheM onadPluCsl ass 259
18.4S tatMeo nads 261
18.5T ypeC lasTsy peE rrors 263
Contents
XI
19 An ImperatiRvoeb otL anguage 265
19.1I RLb yE xample 266
19.2R oboits a StatMeo nad 270
19.3T heI mplementaotfiI oRnLC ommands 272
19.3.1R oboOtr ientation 273
19.3.U2s intgh eP eh 274
19.3.P3l ayiWnigt hC oins 274
19.3.L4o giacn dC ontrol 274
19.4A llt heW orldi sa Grid 276
19.5R oboGtr aphics 281
19.6P uttiintag l Tlo gether 282
20 FunctionMauls icC omposition 287
20.1T heM usiDca taT ype 288
20.2H igher-LCeovneslt ructions 293
20.2.L1i neasn dC hords 293
202.2 Delaayn dR epeat 293
.
20.2.3P olyThythrns 294
20.2.4D eterminDiunrga tion 295
20.2.R5 eversing Musical Structure 295
20.2.T6 runcatPianrga UCeolm position 296
20.2.7T rills 297
20.2.P8 ercussion 298
20.3A Couploef F inaElx amples 300
20.3.C1 ascades 300
20.3.S2e lf-Sim(iFlraarc tMauls)i c 301
21 InterpretFiunngc tionMauls ic 304
21.1I nterpreMtuisnigcA : P erformance 305
21.2A n AlgebroafM usic 308
22 FromP erformantcoeM IDI 313
22.1A n IntroducttoiM oInD I 313
22.2T' heC onversiPorno cess 314
22.3P uttiIntAg l lT ogether 319
23 A Tour otfh eP reludeLMiosdtu le 321
23.1T heP reludelMiosdtu le 321
23.2S implLei sSte lectFournc tions 322
23.3I ndex-BaSseelde ctFournc tions 323
23.-tP redicate-SBealseecdtF ourn ctions 324
23.5F old-lFiuknec tions 325
23.6l ist Generators 327