mirror of
https://github.com/KevinMidboe/linguist.git
synced 2025-10-29 17:50:22 +00:00
Fix Ox implementation
Remove .h from Ox, fix `lex` typo, and add samples for Ox.
This commit is contained in:
Christian Bundy
@@ -1479,10 +1479,9 @@ Org:
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Ox:
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type: programming
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lex: oxl
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lexer: Text only
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extensions:
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- .ox
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- .h
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- .oxh
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- .oxo
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@@ -1796,7 +1795,7 @@ Red:
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extensions:
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- .red
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- .reds
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Redcode:
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extensions:
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- .cw
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@@ -382,6 +382,11 @@
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"Org": [
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".org"
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],
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"Ox": [
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".ox",
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".oxh",
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".oxo"
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],
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"Oxygene": [
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".oxygene"
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],
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@@ -712,8 +717,8 @@
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".gemrc"
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]
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},
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"tokens_total": 609975,
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"languages_total": 750,
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"tokens_total": 610981,
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"languages_total": 753,
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"tokens": {
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"ABAP": {
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"*/**": 1,
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@@ -47560,6 +47565,278 @@
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"there": 1,
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"it": 1
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},
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"Ox": {
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"#include": 2,
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"Kapital": 4,
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"(": 119,
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"L": 2,
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"const": 4,
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"N": 5,
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"entrant": 8,
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"exit": 2,
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"KP": 14,
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")": 119,
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"{": 22,
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"StateVariable": 1,
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";": 91,
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"this.entrant": 1,
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"this.exit": 1,
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"this.KP": 1,
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"actual": 2,
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"Kbar*vals/": 1,
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"-": 31,
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"upper": 3,
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"log": 2,
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".Inf": 2,
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"}": 22,
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"Transit": 1,
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"FeasA": 2,
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"decl": 3,
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"ent": 5,
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"CV": 7,
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"stayout": 3,
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"[": 25,
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"]": 25,
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"exit.pos": 1,
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"tprob": 5,
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"sigu": 2,
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"SigU": 2,
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"if": 5,
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"v": 2,
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"&&": 1,
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"return": 10,
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"<0>": 1,
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"ones": 1,
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"probn": 2,
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"Kbe": 2,
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"/sigu": 1,
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"Kb0": 2,
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"+": 14,
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"Kb2": 2,
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"*upper": 1,
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"/": 1,
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"vals": 1,
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"tprob.*": 1,
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"zeros": 4,
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".*stayout": 1,
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"FirmEntry": 6,
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"Run": 1,
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"Initialize": 3,
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"GenerateSample": 2,
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"BDP": 2,
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"BayesianDP": 1,
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"Rust": 1,
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"Reachable": 2,
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"sige": 2,
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"new": 19,
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"StDeviations": 1,
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"<0.3,0.3>": 1,
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"LaggedAction": 1,
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"d": 2,
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"array": 1,
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"Kparams": 1,
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"Positive": 4,
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"Free": 1,
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"Kb1": 1,
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"Determined": 1,
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"EndogenousStates": 1,
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"K": 3,
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"KN": 1,
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"SetDelta": 1,
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"Probability": 1,
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"kcoef": 3,
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"ecost": 3,
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"Negative": 1,
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"CreateSpaces": 1,
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"Volume": 3,
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"LOUD": 1,
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"EM": 4,
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"ValueIteration": 1,
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"//": 17,
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"Solve": 1,
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"data": 4,
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"DataSet": 1,
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"Simulate": 1,
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"DataN": 1,
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"DataT": 1,
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"FALSE": 1,
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"Print": 1,
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"ImaiJainChing": 1,
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"delta": 1,
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"*CV": 2,
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"Utility": 1,
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"u": 2,
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"ent*CV": 1,
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"*AV": 1,
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"|": 1,
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"ParallelObjective": 1,
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"obj": 18,
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"DONOTUSECLIENT": 2,
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"isclass": 1,
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"obj.p2p": 2,
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"oxwarning": 1,
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"obj.L": 1,
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"P2P": 2,
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"ObjClient": 4,
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"ObjServer": 7,
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"this.obj": 2,
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"Execute": 4,
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"basetag": 2,
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"STOP_TAG": 1,
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"iml": 1,
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"obj.NvfuncTerms": 2,
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"Nparams": 6,
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"obj.nstruct": 2,
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"Loop": 2,
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"nxtmsgsz": 2,
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"//free": 1,
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"param": 1,
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"length": 1,
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"is": 1,
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"no": 2,
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"greater": 1,
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"than": 1,
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"QUIET": 2,
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"println": 2,
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"ID": 2,
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"Server": 1,
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"Recv": 1,
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"ANY_TAG": 1,
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"//receive": 1,
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"the": 1,
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"ending": 1,
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"parameter": 1,
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"vector": 1,
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"Encode": 3,
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"Buffer": 8,
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"//encode": 1,
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"it.": 1,
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"Decode": 1,
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"obj.nfree": 1,
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"obj.cur.V": 1,
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"vfunc": 2,
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"CstrServer": 3,
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"SepServer": 3,
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"Lagrangian": 1,
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"rows": 1,
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"obj.cur": 1,
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"Vec": 1,
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"obj.Kvar.v": 1,
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"imod": 1,
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"Tag": 1,
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"obj.K": 1,
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"TRUE": 1,
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"obj.Kvar": 1,
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"PDF": 1,
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"*": 5,
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"nldge": 1,
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"ParticleLogLikeli": 1,
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"it": 5,
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"ip": 1,
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"mss": 3,
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"mbas": 1,
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"ms": 8,
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"my": 4,
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"mx": 7,
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"vw": 7,
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"vwi": 4,
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"dws": 3,
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"mhi": 3,
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"mhdet": 2,
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"loglikeli": 4,
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"mData": 4,
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"vxm": 1,
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"vxs": 1,
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"mxm": 1,
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"<": 4,
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"mxsu": 1,
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"mxsl": 1,
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"time": 2,
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"timeall": 1,
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"timeran": 1,
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"timelik": 1,
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"timefun": 1,
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"timeint": 1,
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"timeres": 1,
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"GetData": 1,
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"m_asY": 1,
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"sqrt": 1,
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"*M_PI": 1,
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"m_cY": 1,
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"determinant": 2,
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"m_mMSbE.": 2,
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"covariance": 2,
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"invert": 2,
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"of": 2,
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"measurement": 1,
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"shocks": 1,
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"m_vSss": 1,
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"m_cPar": 4,
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"m_cS": 1,
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"start": 1,
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"particles": 2,
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"m_vXss": 1,
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"m_cX": 1,
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"steady": 1,
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"state": 3,
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"and": 1,
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"policy": 2,
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"init": 1,
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"likelihood": 1,
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"//timeall": 1,
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"timer": 3,
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"for": 2,
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"sizer": 1,
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"rann": 1,
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"m_cSS": 1,
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"m_mSSbE": 1,
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"noise": 1,
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"fg": 1,
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"&": 2,
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"transition": 1,
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"prior": 1,
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"as": 1,
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"proposal": 1,
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"m_oApprox.FastInterpolate": 1,
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"interpolate": 1,
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"fy": 1,
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"m_cMS": 1,
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"evaluate": 1,
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"importance": 1,
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"weights": 2,
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"observation": 1,
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"error": 1,
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"exp": 2,
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"outer": 1,
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"/mhdet": 2,
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"sumr": 1,
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"my*mhi": 1,
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".*my": 1,
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".": 3,
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".NaN": 1,
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"can": 1,
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"happen": 1,
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"extrem": 1,
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"sumc": 1,
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"or": 1,
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"extremely": 1,
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"wrong": 1,
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"parameters": 1,
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"dws/m_cPar": 1,
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"loglikelihood": 1,
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"contribution": 1,
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"//timelik": 1,
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"/100": 1,
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"//time": 1,
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"resample": 1,
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"vw/dws": 1,
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"selection": 1,
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"step": 1,
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"in": 1,
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"c": 1,
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"on": 1,
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"normalized": 1
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},
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"Oxygene": {
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"<Project>": 1,
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"DefaultTargets=": 1,
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@@ -65923,6 +66200,7 @@
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"OpenCL": 144,
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"OpenEdge ABL": 762,
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"Org": 358,
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"Ox": 1006,
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"Oxygene": 157,
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"Parrot Assembly": 6,
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"Parrot Internal Representation": 5,
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@@ -66105,6 +66383,7 @@
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"OpenCL": 2,
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"OpenEdge ABL": 5,
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"Org": 1,
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"Ox": 3,
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"Oxygene": 1,
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"Parrot Assembly": 1,
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"Parrot Internal Representation": 1,
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@@ -66175,5 +66454,5 @@
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"YAML": 2,
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"Zephir": 2
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},
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"md5": "ef1795e3585ee02f479767c6a071eb2f"
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"md5": "a80808140f91c6a5539bdca53d5e114a"
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}
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72
samples/Ox/IJCEmet2009.oxh
Normal file
72
samples/Ox/IJCEmet2009.oxh
Normal file
@@ -0,0 +1,72 @@
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/** Replicate Imai, Jain and Ching Econometrica 2009 (incomplete).
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**/
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#include "IJCEmet2009.h"
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Kapital::Kapital(L,const N,const entrant,const exit,const KP){
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StateVariable(L,N);
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this.entrant = entrant;
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this.exit = exit;
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this.KP = KP;
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actual = Kbar*vals/(N-1);
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upper = log(actual~.Inf);
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}
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Kapital::Transit(FeasA) {
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decl ent =CV(entrant), stayout = FeasA[][exit.pos], tprob, sigu = CV(KP[SigU]);
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if (!v && !ent) return { <0>, ones(stayout) };
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tprob = ent ? probn( (upper-CV(KP[Kbe]))/sigu )
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: probn( (upper-(CV(KP[Kb0])+CV(KP[Kb2])*upper[v])) / sigu );
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tprob = tprob[1:] - tprob[:N-1];
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return { vals, tprob.*(1-stayout)+(1.0~zeros(1,N-1)).*stayout };
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}
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FirmEntry::Run() {
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Initialize();
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GenerateSample();
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BDP->BayesianDP();
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}
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FirmEntry::Initialize() {
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Rust::Initialize(Reachable,0);
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sige = new StDeviations("sige",<0.3,0.3>,0);
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entrant = new LaggedAction("entrant",d);
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KP = new array[Kparams];
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KP[Kbe] = new Positive("be",0.5);
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KP[Kb0] = new Free("b0",0.0);
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KP[Kb1] = new Determined("b1",0.0);
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KP[Kb2] = new Positive("b2",0.4);
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KP[SigU] = new Positive("sigu",0.4);
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EndogenousStates(K = new Kapital("K",KN,entrant,d,KP),entrant);
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SetDelta(new Probability("delta",0.85));
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kcoef = new Positive("kcoef",0.1);
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ecost = new Negative("ec",-0.4);
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CreateSpaces();
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}
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FirmEntry::GenerateSample() {
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Volume = LOUD;
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EM = new ValueIteration(0);
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// EM -> Solve(0,0);
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data = new DataSet(0,EM);
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data->Simulate(DataN,DataT,0,FALSE);
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data->Print("firmentry.xls");
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BDP = new ImaiJainChing("FMH",data,EM,ecost,sige,kcoef,KP,delta);
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}
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/** Capital stock can be positive only for incumbents.
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**/
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FirmEntry::Reachable() { return CV(entrant)*CV(K) ? 0 : new FirmEntry() ; }
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/** The one period return.
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<DD>
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<pre>U = </pre>
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</DD>
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**/
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FirmEntry::Utility() {
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decl ent = CV(entrant),
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u =
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ent*CV(ecost)+(1-ent)*CV(kcoef)*AV(K)
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| 0.0;
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return u;
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}
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63
samples/Ox/ParallelObjective.ox
Normal file
63
samples/Ox/ParallelObjective.ox
Normal file
@@ -0,0 +1,63 @@
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/** Client and Server classes for parallel optimization using CFMPI.**/
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#include "ParallelObjective.h"
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/** Set up MPI Client-Server support for objective optimization.
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@param obj `Objective' to parallelize
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@param DONOTUSECLIENT TRUE (default): client node does no object evaluation<br>FALSE after putting servers to work Client node does one evaluation.
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**/
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ParallelObjective(obj,DONOTUSECLIENT) {
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if (isclass(obj.p2p)) {oxwarning("P2P object already exists for "+obj.L+". Nothing changed"); return;}
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obj.p2p = new P2P(DONOTUSECLIENT,new ObjClient(obj),new ObjServer(obj));
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}
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ObjClient::ObjClient(obj) { this.obj = obj; }
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ObjClient::Execute() { }
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|
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ObjServer::ObjServer(obj) {
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this.obj = obj;
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basetag = P2P::STOP_TAG+1;
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iml = obj.NvfuncTerms;
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Nparams = obj.nstruct;
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}
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|
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/** Wait on the objective client.
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**/
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ObjServer::Loop(nxtmsgsz) {
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Nparams = nxtmsgsz; //free param length is no greater than Nparams
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if (Volume>QUIET) println("ObjServer server ",ID," Nparams ",Nparams);
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Server::Loop(Nparams);
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Recv(ANY_TAG); //receive the ending parameter vector
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obj->Encode(Buffer[:Nparams-1]); //encode it.
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}
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/** Do the objective evaluation.
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Receive structural parameter vector and `Objective::Encode`() it.
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Call `Objective::vfunc`().
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@return Nparams (max. length of next expected message);
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||||
**/
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ObjServer::Execute() {
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obj->Decode(Buffer[:obj.nfree-1]);
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Buffer = obj.cur.V[] = obj->vfunc();
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if (Volume>QUIET) println("Server Executive: ",ID," vfunc[0]= ",Buffer[0]);
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return obj.nstruct;
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}
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||||
|
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CstrServer::CstrServer(obj) { ObjServer(obj); }
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||||
|
||||
SepServer::SepServer(obj) { ObjServer(obj); }
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|
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CstrServer::Execute() {
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obj->Encode(Buffer);
|
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obj->Lagrangian(0);
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||||
return rows(Buffer = obj.cur->Vec());
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}
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||||
|
||||
/** Separable objective evaluations.
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**/
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SepServer::Execute() {
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obj.Kvar.v = imod(Tag-basetag,obj.K);
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obj->Encode(Buffer,TRUE);
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Buffer = obj.Kvar->PDF() * obj->vfunc();
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return obj.NvfuncTerms;
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}
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38
samples/Ox/particle.oxo
Normal file
38
samples/Ox/particle.oxo
Normal file
@@ -0,0 +1,38 @@
|
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nldge::ParticleLogLikeli()
|
||||
{ decl it, ip,
|
||||
mss, mbas, ms, my, mx, vw, vwi, dws,
|
||||
mhi, mhdet, loglikeli, mData,
|
||||
vxm, vxs, mxm=<>, mxsu=<>, mxsl=<>,
|
||||
time, timeall, timeran=0, timelik=0, timefun=0, timeint=0, timeres=0;
|
||||
|
||||
mData = GetData(m_asY);
|
||||
mhdet = sqrt((2*M_PI)^m_cY * determinant(m_mMSbE.^2)); // covariance determinant
|
||||
mhi = invert(m_mMSbE.^2); // invert covariance of measurement shocks
|
||||
|
||||
ms = m_vSss + zeros(m_cPar, m_cS); // start particles
|
||||
mx = m_vXss + zeros(m_cPar, m_cX); // steady state of state and policy
|
||||
|
||||
loglikeli = 0; // init likelihood
|
||||
//timeall=timer();
|
||||
for(it = 0; it < sizer(mData); it++)
|
||||
{
|
||||
mss = rann(m_cPar, m_cSS) * m_mSSbE; // state noise
|
||||
fg(&ms, ms, mx, mss); // transition prior as proposal
|
||||
mx = m_oApprox.FastInterpolate(ms); // interpolate
|
||||
fy(&my, ms, mx, zeros(m_cPar, m_cMS)); // evaluate importance weights
|
||||
my -= mData[it][]; // observation error
|
||||
|
||||
vw = exp(-0.5 * outer(my,mhi,'d')' )/mhdet; // vw = exp(-0.5 * sumr(my*mhi .*my ) )/mhdet;
|
||||
|
||||
vw = vw .== .NaN .? 0 .: vw; // no policy can happen for extrem particles
|
||||
dws = sumc(vw);
|
||||
if(dws==0) return -.Inf; // or extremely wrong parameters
|
||||
loglikeli += log(dws/m_cPar) ; // loglikelihood contribution
|
||||
//timelik += (timer()-time)/100;
|
||||
//time=timer();
|
||||
vwi = resample(vw/dws)-1; // selection step in c++
|
||||
ms = ms[vwi][]; // on normalized weights
|
||||
mx = mx[vwi][];
|
||||
}
|
||||
return loglikeli;
|
||||
}
|
||||
Reference in New Issue
Block a user