From 6b93f61d0d0d7976b7c9b02e5f531c29bc4a6e4a Mon Sep 17 00:00:00 2001 From: Stefan Dresselhaus Date: Wed, 27 Jun 2018 12:51:06 +0200 Subject: [PATCH] corrected bug, rerun test, vortrag nears completion --- simulations/enzymeCost/nutrientCost/0.1.aavg | 1 + simulations/enzymeCost/nutrientCost/0.1.avg | 20 +- simulations/enzymeCost/nutrientCost/0.1/1.avg | 2 +- simulations/enzymeCost/nutrientCost/0.1/1.log | 402 ++++++------- .../enzymeCost/nutrientCost/0.1/10.avg | 2 +- .../enzymeCost/nutrientCost/0.1/10.log | 402 ++++++------- simulations/enzymeCost/nutrientCost/0.1/2.avg | 2 +- simulations/enzymeCost/nutrientCost/0.1/2.log | 402 ++++++------- simulations/enzymeCost/nutrientCost/0.1/3.avg | 2 +- simulations/enzymeCost/nutrientCost/0.1/3.log | 402 ++++++------- simulations/enzymeCost/nutrientCost/0.1/4.avg | 2 +- simulations/enzymeCost/nutrientCost/0.1/4.log | 402 ++++++------- simulations/enzymeCost/nutrientCost/0.1/5.avg | 2 +- simulations/enzymeCost/nutrientCost/0.1/5.log | 402 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a/simulations/enzymeCost/nutrientCost/0.1/10.avg b/simulations/enzymeCost/nutrientCost/0.1/10.avg index e9cdeb0..ca099a8 100644 --- a/simulations/enzymeCost/nutrientCost/0.1/10.avg +++ b/simulations/enzymeCost/nutrientCost/0.1/10.avg @@ -1 +1 @@ -AVG,17.881925543984522,0.050400431936497264,3.1496,0.965812,1.2575999999999994,0.9852520000000001,0.517305251188738,0.006317271691890076,0.3529449968249155,0.0009269485612464996,100,100,100,100, +AVG,17.968744362334807,0.0282750714046763,3.283799999999999,0.9404459999999994,1.1446,0.9064980000000002,0.45880728495091844,0.005253298878370671,0.34888335320267905,0.0009928423969479117,100,100,99.98,99.98, diff --git a/simulations/enzymeCost/nutrientCost/0.1/10.log b/simulations/enzymeCost/nutrientCost/0.1/10.log index cb4fc36..00c4c99 100644 --- a/simulations/enzymeCost/nutrientCost/0.1/10.log +++ b/simulations/enzymeCost/nutrientCost/0.1/10.log @@ -1,202 +1,202 @@ 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-1 +1 @@ -AVG,17.838379054450105,0.050374729754077474,3.605,0.9919059999999996,1.3595999999999997,0.9768840000000003,0.560733390230724,0.006740541760859305,0.3655227855011822,0.0008664708596514431,100,100,99.98,99.98, +AVG,17.62517846483114,0.04964673179783942,2.8154000000000003,1.0359859999999999,1.5809999999999997,1.0632899999999994,0.5224348846825568,0.007340170429432223,0.3673281200477439,0.0009949338221623796,100,100,99.96,99.88, diff --git a/simulations/enzymeCost/nutrientCost/0.1/3.log b/simulations/enzymeCost/nutrientCost/0.1/3.log index 43b9ec9..2b0df0d 100644 --- a/simulations/enzymeCost/nutrientCost/0.1/3.log +++ b/simulations/enzymeCost/nutrientCost/0.1/3.log @@ -1,202 +1,202 @@ num_iter,c_sum_mu,c_sum_sigma,c_d_mu,c_d_sigma,e_d_mu,e_d_sigma,fitness_mean,fitness_sigma,percent_toxic_mean,percent_toxic_sigma,pred1,pred2,pred3,pred4 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a/simulations/enzymeCost/nutrientCost/0.1/4.avg b/simulations/enzymeCost/nutrientCost/0.1/4.avg index c648bed..845f7dd 100644 --- a/simulations/enzymeCost/nutrientCost/0.1/4.avg +++ b/simulations/enzymeCost/nutrientCost/0.1/4.avg @@ -1 +1 @@ -AVG,17.800456364463365,0.041990787582776565,2.9606,1.2112460000000005,1.0909999999999997,0.786946,0.5512215141842545,0.0071983768381623115,0.3714082216330933,0.0011476378195650482,100,100,99.84,99.98, +AVG,18.021655934490692,0.036095552277610445,3.2929999999999997,1.2017060000000002,0.9554,0.6462979999999999,0.447515529204886,0.004502509206548612,0.3653081289761922,0.0009845889197297093,100,100,99.92,99.98, diff --git a/simulations/enzymeCost/nutrientCost/0.1/4.log b/simulations/enzymeCost/nutrientCost/0.1/4.log index 62299be..2447682 100644 --- a/simulations/enzymeCost/nutrientCost/0.1/4.log +++ b/simulations/enzymeCost/nutrientCost/0.1/4.log @@ -1,202 +1,202 @@ 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a/simulations/enzymeCost/nutrientCost/0.1/8.avg b/simulations/enzymeCost/nutrientCost/0.1/8.avg index 5a729a5..fd8deb4 100644 --- a/simulations/enzymeCost/nutrientCost/0.1/8.avg +++ b/simulations/enzymeCost/nutrientCost/0.1/8.avg @@ -1 +1 @@ -AVG,17.893348750448173,0.0427504678219601,3.2472000000000008,1.1273999999999997,1.1481999999999999,0.8069819999999998,0.5285605965491889,0.006633469980665743,0.37282861541434875,0.0009441124738374814,100,100,99.9,99.96, +AVG,17.786024874436613,0.04581102041123289,3.205200000000001,1.076428,1.2973999999999994,0.9369020000000002,0.46451435638771854,0.005147702522488948,0.37791074539634356,0.0009212567007007655,100,100,99.82,99.92, diff --git a/simulations/enzymeCost/nutrientCost/0.1/8.log b/simulations/enzymeCost/nutrientCost/0.1/8.log index 97d3935..d2b60b2 100644 --- a/simulations/enzymeCost/nutrientCost/0.1/8.log +++ b/simulations/enzymeCost/nutrientCost/0.1/8.log @@ -1,202 +1,202 @@ 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a/simulations/enzymeCost/nutrientCost/0.2/2.avg b/simulations/enzymeCost/nutrientCost/0.2/2.avg index 96070b4..33a1480 100644 --- a/simulations/enzymeCost/nutrientCost/0.2/2.avg +++ b/simulations/enzymeCost/nutrientCost/0.2/2.avg @@ -1 +1 @@ -AVG,17.790337241977873,0.04418255901760136,3.6066,1.098934,0.9654,0.774518,0.5338516152496616,0.007030171150667389,0.36965357431306617,0.0008866412198157696,100,100,99.9,100, +AVG,17.494317932984284,0.04136255611123289,3.6534000000000004,1.02213,1.3648000000000002,1.0135000000000003,0.44511755922050594,0.00488466605307862,0.37044819233423903,0.0009068258458454775,100,100,99.92,99.96, diff --git a/simulations/enzymeCost/nutrientCost/0.2/2.log b/simulations/enzymeCost/nutrientCost/0.2/2.log index 9e61d17..f09942b 100644 --- a/simulations/enzymeCost/nutrientCost/0.2/2.log +++ b/simulations/enzymeCost/nutrientCost/0.2/2.log @@ -1,202 +1,202 @@ 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--- a/simulations/enzymeCost/nutrientCost/0.2/7.log +++ b/simulations/enzymeCost/nutrientCost/0.2/7.log @@ -1,202 +1,202 @@ num_iter,c_sum_mu,c_sum_sigma,c_d_mu,c_d_sigma,e_d_mu,e_d_sigma,fitness_mean,fitness_sigma,percent_toxic_mean,percent_toxic_sigma,pred1,pred2,pred3,pred4 -0,2.058845753688008,10.358043394788531,1.3899999999999997,0.41790000000000005,4.999999999999998e-2,4.750000000000001e-2,1.4909028736118548e-2,8.379602033701076e-7,6.721626683291349e-4,4.472846261677668e-5,0,0,5,7 -10,6.1344284872255015,16.719633630055544,2.2600000000000002,0.7323999999999999,1.1600000000000004,0.6144000000000001,2.4960286483822047e-2,1.2383000245846706e-4,6.155752111472175e-2,5.632176478518649e-3,0,0,19,28 -20,8.666353986201962,5.62642595544421,3.0,0.1199999999999999,0.37,0.31310000000000004,3.976676362363783e-2,3.053705156432466e-5,0.14762636876481447,2.2315558533268125e-3,0,0,51,50 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a/simulations/enzymeCost/nutrientCost/0.2/9.log +++ b/simulations/enzymeCost/nutrientCost/0.2/9.log @@ -1,202 +1,202 @@ num_iter,c_sum_mu,c_sum_sigma,c_d_mu,c_d_sigma,e_d_mu,e_d_sigma,fitness_mean,fitness_sigma,percent_toxic_mean,percent_toxic_sigma,pred1,pred2,pred3,pred4 -0,1.866183003877467,9.256153653540796,1.3500000000000003,0.36750000000000016,3.9999999999999994e-2,3.84e-2,1.4811158062093327e-2,3.105093628889322e-7,6.241188403452124e-16,2.0113577366309082e-30,0,0,7,10 -10,2.071622532224784,9.175825593044745,1.32,0.21760000000000002,1.1900000000000002,0.43389999999999984,1.4844656449543674e-2,2.7693887717456454e-7,-9.040814665716228e-16,1.5149706071836475e-29,0,0,3,0 -20,3.498241843696566,13.068739326970878,1.5299999999999998,0.3090999999999999,1.12,0.7256,1.5058677146681939e-2,3.8693649028494513e-7,-1.0902670839163384e-15,2.6335694447397634e-29,0,0,1,6 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a/simulations/enzymeCost/nutrientCost/0.4/1.avg +++ b/simulations/enzymeCost/nutrientCost/0.4/1.avg @@ -1 +1 @@ -AVG,17.70950307028353,0.04510195790786517,3.8109999999999995,1.0095220000000003,1.2510000000000003,0.994678,0.5315287942143226,0.00754895768165714,0.3677476535330371,0.0009767407973662108,100,100,99.86,99.96, +AVG,16.865740518806263,0.1295415612468825,4.3351999999999995,0.883568,1.4176,0.88082,0.35174334965832604,0.004664780918995721,0.3385283353769923,0.0008109688551574323,100,100,98.58,99.36, diff --git a/simulations/enzymeCost/nutrientCost/0.4/1.log b/simulations/enzymeCost/nutrientCost/0.4/1.log index 86936d4..b4e145f 100644 --- a/simulations/enzymeCost/nutrientCost/0.4/1.log +++ b/simulations/enzymeCost/nutrientCost/0.4/1.log @@ -1,202 +1,202 @@ num_iter,c_sum_mu,c_sum_sigma,c_d_mu,c_d_sigma,e_d_mu,e_d_sigma,fitness_mean,fitness_sigma,percent_toxic_mean,percent_toxic_sigma,pred1,pred2,pred3,pred4 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a/simulations/enzymeCost/nutrientCost/0.4/8.avg b/simulations/enzymeCost/nutrientCost/0.4/8.avg index 24ae173..6f2e7d6 100644 --- a/simulations/enzymeCost/nutrientCost/0.4/8.avg +++ b/simulations/enzymeCost/nutrientCost/0.4/8.avg @@ -1 +1 @@ -AVG,18.06676910596931,0.03495100361921244,3.3346000000000005,1.284662,1.0712000000000002,0.7543599999999998,0.48947784350137974,0.004449196533419371,0.373416053089058,0.0010833384266622907,100,100,99.94,99.96, +AVG,17.649310992239112,0.041620448890126636,3.0794,0.940874,1.2804000000000002,0.9114559999999998,0.2887601676096948,0.002044936118510982,0.3577043099815316,0.0010928847222819139,100,100,99.98,100, diff --git a/simulations/enzymeCost/nutrientCost/0.4/8.log b/simulations/enzymeCost/nutrientCost/0.4/8.log index d8d7a79..d52993b 100644 --- a/simulations/enzymeCost/nutrientCost/0.4/8.log +++ b/simulations/enzymeCost/nutrientCost/0.4/8.log @@ -1,202 +1,202 @@ 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+++ b/simulations/enzymeCost/nutrientCost/0.5/3.avg @@ -1 +1 @@ -AVG,17.743750768143787,0.040720686062542984,2.7798000000000003,1.0015700000000003,1.25,0.9707119999999999,0.5035397630590328,0.0062898002139950004,0.381879570575734,0.0010415807345998322,100,100,99.82,99.98, +AVG,0.03005221441333245,0.19324260854685552,1.0047999999999997,0.005067999999999998,0.10300000000000001,0.11123399999999999,0.018281526996337408,4.7733764446270273e-08,-9.462354535592203e-18,2.4680456366446834e-31,0,0,0.08,0, diff --git a/simulations/enzymeCost/nutrientCost/0.5/3.log b/simulations/enzymeCost/nutrientCost/0.5/3.log index 05a7912..f50fe15 100644 --- a/simulations/enzymeCost/nutrientCost/0.5/3.log +++ b/simulations/enzymeCost/nutrientCost/0.5/3.log @@ -1,202 +1,202 @@ num_iter,c_sum_mu,c_sum_sigma,c_d_mu,c_d_sigma,e_d_mu,e_d_sigma,fitness_mean,fitness_sigma,percent_toxic_mean,percent_toxic_sigma,pred1,pred2,pred3,pred4 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a/simulations/enzymeCost/nutrientCost/0.5/6.avg b/simulations/enzymeCost/nutrientCost/0.5/6.avg index a027c65..48c54ed 100644 --- a/simulations/enzymeCost/nutrientCost/0.5/6.avg +++ b/simulations/enzymeCost/nutrientCost/0.5/6.avg @@ -1 +1 @@ -AVG,18.234017860773914,0.024662001541371655,3.460599999999999,0.9952940000000001,0.8166000000000001,0.527974,0.43804328978176277,0.0034124130249759137,0.37937086135157616,0.0009130589342589018,100,100,99.88,100, +AVG,17.098226904335018,0.07135206328668912,3.9454,0.8876219999999999,1.1520000000000001,0.8286160000000001,0.26466450178473805,0.002439276721275663,0.3389794158377225,0.0008447473468415001,99.98,99.98,99.8,99.64, diff --git a/simulations/enzymeCost/nutrientCost/0.5/6.log b/simulations/enzymeCost/nutrientCost/0.5/6.log index e21dc7f..4ad5f8b 100644 --- a/simulations/enzymeCost/nutrientCost/0.5/6.log +++ b/simulations/enzymeCost/nutrientCost/0.5/6.log @@ -1,202 +1,202 @@ 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b/simulations/enzymeCost/nutrientCost/0.5/8.avg @@ -1 +1 @@ -AVG,17.915075877992212,0.03374818634908727,3.176400000000001,0.9919800000000002,1.4247999999999998,0.9874679999999997,0.4933950092131466,0.0058628811133378846,0.36423408980765487,0.0010645339941494421,100,100,99.96,100, +AVG,16.632319093286725,0.1693966745847271,4.2688,0.990936,1.0332,0.7744079999999998,0.2086371243542349,0.0013607390486764467,0.32580509426387594,0.0008306550030835831,90.92,90.92,99.48,99.84, diff --git a/simulations/enzymeCost/nutrientCost/0.5/8.log b/simulations/enzymeCost/nutrientCost/0.5/8.log index e439b86..74c2681 100644 --- a/simulations/enzymeCost/nutrientCost/0.5/8.log +++ b/simulations/enzymeCost/nutrientCost/0.5/8.log @@ -1,202 +1,202 @@ num_iter,c_sum_mu,c_sum_sigma,c_d_mu,c_d_sigma,e_d_mu,e_d_sigma,fitness_mean,fitness_sigma,percent_toxic_mean,percent_toxic_sigma,pred1,pred2,pred3,pred4 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diff --git a/simulations/enzymeCost/nutrientCost/0.6/7.avg b/simulations/enzymeCost/nutrientCost/0.6/7.avg index 37d4091..218ddc2 100644 --- a/simulations/enzymeCost/nutrientCost/0.6/7.avg +++ b/simulations/enzymeCost/nutrientCost/0.6/7.avg @@ -1 +1 @@ -AVG,17.897913695712543,0.04378068362015664,2.869999999999999,1.2097439999999997,1.2555999999999996,0.9071119999999998,0.478925021209583,0.0053047649107569594,0.36115291998127574,0.0010277411828698959,100,100,99.94,99.98, +AVG,17.03202967158189,0.08382724291246012,4.260800000000001,0.7581160000000001,0.9640000000000003,0.7539560000000001,0.20642819024610756,0.0015379591963972244,0.34506072230669216,0.0008397577214126606,99.98,99.98,99.3,99.84, diff --git a/simulations/enzymeCost/nutrientCost/0.6/7.log b/simulations/enzymeCost/nutrientCost/0.6/7.log index 13cb015..0eea106 100644 --- a/simulations/enzymeCost/nutrientCost/0.6/7.log +++ b/simulations/enzymeCost/nutrientCost/0.6/7.log @@ -1,202 +1,202 @@ 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a/simulations/enzymeCost/nutrientCost/0.7/10.avg +++ b/simulations/enzymeCost/nutrientCost/0.7/10.avg @@ -1 +1 @@ -AVG,17.74432343157445,0.06085020386726781,3.5034000000000005,0.8442060000000001,1.3559999999999997,0.9210679999999999,0.4988615781267264,0.006485022001484803,0.3757333443151276,0.0013127138215309603,99.98,99.98,99.72,99.96, +AVG,17.081984748882945,0.03677137023118706,5.1541999999999994,0.7026379999999999,0.8986,0.6473459999999999,0.16706336070051225,0.0009728917433061853,0.32799727998107114,0.0006110329349469176,99.98,99.98,99.74,99.94, diff --git a/simulations/enzymeCost/nutrientCost/0.7/10.log b/simulations/enzymeCost/nutrientCost/0.7/10.log index 1d45f30..7ca9b3f 100644 --- a/simulations/enzymeCost/nutrientCost/0.7/10.log +++ b/simulations/enzymeCost/nutrientCost/0.7/10.log @@ -1,202 +1,202 @@ num_iter,c_sum_mu,c_sum_sigma,c_d_mu,c_d_sigma,e_d_mu,e_d_sigma,fitness_mean,fitness_sigma,percent_toxic_mean,percent_toxic_sigma,pred1,pred2,pred3,pred4 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a/simulations/enzymeCost/nutrientCost/0.7/4.avg b/simulations/enzymeCost/nutrientCost/0.7/4.avg index e29f871..a773285 100644 --- a/simulations/enzymeCost/nutrientCost/0.7/4.avg +++ b/simulations/enzymeCost/nutrientCost/0.7/4.avg @@ -1 +1 @@ -AVG,17.669758648913277,0.042391798769644815,3.4495999999999993,0.9368239999999999,1.3428,0.9486840000000001,0.5009200683440662,0.006373463186279893,0.3543059843757762,0.0009109247604040943,100,100,99.98,100, +AVG,16.043669108821636,0.257821036497925,5.241000000000001,0.9970020000000004,1.0069999999999997,0.6851299999999999,0.11133175048720714,0.00033310910538085286,0.2682484232104852,0.0007297292553635201,99.96,99.96,99.9,94.82, diff --git a/simulations/enzymeCost/nutrientCost/0.7/4.log b/simulations/enzymeCost/nutrientCost/0.7/4.log index 0e54353..17aecbf 100644 --- a/simulations/enzymeCost/nutrientCost/0.7/4.log +++ b/simulations/enzymeCost/nutrientCost/0.7/4.log @@ -1,202 +1,202 @@ 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-AVG,17.662494455497093,0.03927252481136741,3.463,0.716342,1.4717999999999998,1.1366020000000001,0.5327217668173024,0.007463711384986483,0.3727457044344554,0.0009566355918126026,100,100,99.88,99.92, +AVG,12.900000608724987,2.006999929415667,3.876200000000001,0.5535459999999999,1.3578000000000001,1.2425460000000002,0.047165185063760155,5.318298826033618e-05,0.291555085100836,0.0021222088067274435,0.2,0.26,97.8,97.62, diff --git a/simulations/enzymeCost/nutrientCost/0.7/9.log b/simulations/enzymeCost/nutrientCost/0.7/9.log index 3c08116..9474252 100644 --- a/simulations/enzymeCost/nutrientCost/0.7/9.log +++ b/simulations/enzymeCost/nutrientCost/0.7/9.log @@ -1,202 +1,202 @@ num_iter,c_sum_mu,c_sum_sigma,c_d_mu,c_d_sigma,e_d_mu,e_d_sigma,fitness_mean,fitness_sigma,percent_toxic_mean,percent_toxic_sigma,pred1,pred2,pred3,pred4 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--git a/simulations/enzymeCost/nutrientCost/0.8/10.avg b/simulations/enzymeCost/nutrientCost/0.8/10.avg index eb46e02..75d138d 100644 --- a/simulations/enzymeCost/nutrientCost/0.8/10.avg +++ b/simulations/enzymeCost/nutrientCost/0.8/10.avg @@ -1 +1 @@ -AVG,17.994928085686702,0.03347842775258251,3.366200000000002,1.25647,1.1182,0.826002,0.469571162887136,0.005066109337705651,0.3796037094421136,0.0009141173980185497,100,100,100,100, +AVG,6.738682618927467,2.4235825883269717,2.8238,0.4374299999999999,1.2029999999999996,0.7952180000000001,0.03288718523557079,1.4536348394757267e-05,0.11727908759599036,0.0009723656943598527,0.1,0.1,97.08,0.96, diff --git a/simulations/enzymeCost/nutrientCost/0.8/10.log b/simulations/enzymeCost/nutrientCost/0.8/10.log index ceacd9a..e1354c2 100644 --- a/simulations/enzymeCost/nutrientCost/0.8/10.log +++ b/simulations/enzymeCost/nutrientCost/0.8/10.log @@ -1,202 +1,202 @@ 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a/simulations/enzymeCost/nutrientCost/0.8/5.avg +++ b/simulations/enzymeCost/nutrientCost/0.8/5.avg @@ -1 +1 @@ -AVG,18.031213151582932,0.02624510217402525,3.3382,0.8458780000000001,1.0745999999999998,0.78381,0.46948558145040553,0.004838636858909314,0.3676685155501179,0.0008594221156788366,100,100,99.96,100, +AVG,4.685681415704982,1.8355694952151904,2.6256,0.22435600000000006,1.0658,0.7394820000000002,0.03073001546807043,1.2411226680256736e-05,0.0823406302440433,0.0005469605782088763,0,0.02,78.06,0.56, diff --git a/simulations/enzymeCost/nutrientCost/0.8/5.log b/simulations/enzymeCost/nutrientCost/0.8/5.log index f9a20ab..81c5e1d 100644 --- a/simulations/enzymeCost/nutrientCost/0.8/5.log +++ b/simulations/enzymeCost/nutrientCost/0.8/5.log @@ -1,202 +1,202 @@ num_iter,c_sum_mu,c_sum_sigma,c_d_mu,c_d_sigma,e_d_mu,e_d_sigma,fitness_mean,fitness_sigma,percent_toxic_mean,percent_toxic_sigma,pred1,pred2,pred3,pred4 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a/simulations/enzymeCost/nutrientCost/0.8/7.avg b/simulations/enzymeCost/nutrientCost/0.8/7.avg index dfbd89f..6dd3919 100644 --- a/simulations/enzymeCost/nutrientCost/0.8/7.avg +++ b/simulations/enzymeCost/nutrientCost/0.8/7.avg @@ -1 +1 @@ -AVG,18.021550057818278,0.03803524485324607,3.0159999999999996,1.052368,1.1540000000000001,0.75592,0.46175253586490483,0.004723501339523078,0.3805157886155554,0.0014618594968687118,100,100,99.9,100, +AVG,13.122466408168991,1.1817988340577132,4.854600000000001,0.5369700000000001,1.3875999999999997,0.9365360000000001,0.04239071465911804,3.151344444516022e-05,0.2776932427680308,0.001165649426646645,0.58,0.68,98.32,99.2, diff --git a/simulations/enzymeCost/nutrientCost/0.8/7.log b/simulations/enzymeCost/nutrientCost/0.8/7.log index fa9ae69..4fc71d2 100644 --- a/simulations/enzymeCost/nutrientCost/0.8/7.log +++ b/simulations/enzymeCost/nutrientCost/0.8/7.log @@ -1,202 +1,202 @@ 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a/simulations/enzymeCost/nutrientCost/0.8/8.avg b/simulations/enzymeCost/nutrientCost/0.8/8.avg index 53cfcff..e6b2adc 100644 --- a/simulations/enzymeCost/nutrientCost/0.8/8.avg +++ b/simulations/enzymeCost/nutrientCost/0.8/8.avg @@ -1 +1 @@ -AVG,17.749571089037943,0.04858421749714802,3.3112,0.8046880000000001,1.561,1.058798,0.4894562125192611,0.006192566723391303,0.3740808136980337,0.0008967456111562182,100,100,99.94,99.96, +AVG,13.891710125746918,1.0208747759204786,4.588999999999999,0.6950700000000001,1.2382,0.9400739999999999,0.06038198246179961,0.00012261439455824562,0.25721247177774426,0.0012466952681945205,40.4,40.98,97.34,80.26, diff --git a/simulations/enzymeCost/nutrientCost/0.8/8.log b/simulations/enzymeCost/nutrientCost/0.8/8.log index e90fa01..0a5e9b5 100644 --- a/simulations/enzymeCost/nutrientCost/0.8/8.log +++ b/simulations/enzymeCost/nutrientCost/0.8/8.log @@ -1,202 +1,202 @@ 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a/simulations/enzymeCost/nutrientCost/0.9/4.avg b/simulations/enzymeCost/nutrientCost/0.9/4.avg index ab237ec..9babee3 100644 --- a/simulations/enzymeCost/nutrientCost/0.9/4.avg +++ b/simulations/enzymeCost/nutrientCost/0.9/4.avg @@ -1 +1 @@ -AVG,17.692121748728933,0.047260557085045576,3.2552000000000008,0.9452599999999997,1.439,1.057714,0.484877886007008,0.00560051547529214,0.3911187341407932,0.001179497866887188,100,100,99.82,99.88, +AVG,13.01478710826872,1.5288057886147417,3.937000000000001,1.0976139999999999,1.4589999999999999,1.0716379999999994,0.050930683405868364,6.765825205905147e-05,0.2503103015562168,0.0012132198265954975,67.12,67.12,97.62,94.68, diff --git a/simulations/enzymeCost/nutrientCost/0.9/4.log b/simulations/enzymeCost/nutrientCost/0.9/4.log index 3b58775..74b434e 100644 --- a/simulations/enzymeCost/nutrientCost/0.9/4.log +++ b/simulations/enzymeCost/nutrientCost/0.9/4.log @@ -1,202 +1,202 @@ 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a/simulations/enzymeCost/nutrientCost/1.0/7.avg b/simulations/enzymeCost/nutrientCost/1.0/7.avg index fdfcf2d..787ca4e 100644 --- a/simulations/enzymeCost/nutrientCost/1.0/7.avg +++ b/simulations/enzymeCost/nutrientCost/1.0/7.avg @@ -1 +1 @@ -AVG,18.00098595860965,0.03420034439729016,3.4344000000000006,1.0997960000000002,1.2259999999999998,0.8100160000000001,0.4496883409083392,0.004389708853725989,0.3717973766854118,0.0009751973139597517,100,100,99.94,99.98, +AVG,0.00932752238786658,0.06213161717651859,1.0014,0.0013780000000000003,0.0702,0.06524600000000001,0.018294539093957115,5.574296327908458e-08,-4.59126936666962e-18,4.939815774310667e-32,0,0,0,0.02, diff --git a/simulations/enzymeCost/nutrientCost/1.0/7.log b/simulations/enzymeCost/nutrientCost/1.0/7.log index 1a771a6..b2e4817 100644 --- a/simulations/enzymeCost/nutrientCost/1.0/7.log +++ b/simulations/enzymeCost/nutrientCost/1.0/7.log @@ -1,202 +1,202 @@ 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b/simulations/enzymeCost/nutrientCost/1.0/8.avg index 08a2d90..deeda3f 100644 --- a/simulations/enzymeCost/nutrientCost/1.0/8.avg +++ b/simulations/enzymeCost/nutrientCost/1.0/8.avg @@ -1 +1 @@ -AVG,17.95993672473177,0.03733579552566745,3.642,1.013088,0.8966000000000003,0.6229140000000001,0.4267948895489232,0.0045608828213332935,0.3685239165732424,0.0008524514231058742,100,100,99.98,99.98, +AVG,0.022267555616322876,0.15532611326920823,1.0035999999999998,0.0043279999999999985,0.11340000000000001,0.10620999999999997,0.018269358768425375,1.4035353809635196e-07,1.3797279361896062e-05,9.423063430616988e-07,0,0,0.04,0.04, diff --git a/simulations/enzymeCost/nutrientCost/1.0/8.log b/simulations/enzymeCost/nutrientCost/1.0/8.log index 33538b9..afd1ec6 100644 --- a/simulations/enzymeCost/nutrientCost/1.0/8.log +++ b/simulations/enzymeCost/nutrientCost/1.0/8.log @@ -1,202 +1,202 @@ 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diff --git a/simulations/enzymeCost/nutrientCost/plot.fish b/simulations/enzymeCost/nutrientCost/plot.fish index faea2e3..4afcd0f 100755 --- a/simulations/enzymeCost/nutrientCost/plot.fish +++ b/simulations/enzymeCost/nutrientCost/plot.fish @@ -10,16 +10,26 @@ set title '$argv[6]' set key outside right plot \ -'0.1.avg' using $argv[2]:$argv[4] title '0.1' pt 5,\ -'0.2.avg' using $argv[2]:$argv[4] title '0.2' pt 5,\ -'0.3.avg' using $argv[2]:$argv[4] title '0.3' pt 5,\ -'0.4.avg' using $argv[2]:$argv[4] title '0.4' pt 5,\ -'0.5.avg' using $argv[2]:$argv[4] title '0.5' pt 5,\ -'0.6.avg' using $argv[2]:$argv[4] title '0.6' pt 5,\ -'0.7.avg' using $argv[2]:$argv[4] title '0.7' pt 5,\ -'0.8.avg' using $argv[2]:$argv[4] title '0.8' pt 5,\ -'0.9.avg' using $argv[2]:$argv[4] title '0.9' pt 5,\ -'1.0.avg' using $argv[2]:$argv[4] title '1.0' pt 5 +'0.1.avg' using $argv[2]:$argv[4] title '0.1' pt 1 lc rgb '#ff0000',\ +'0.2.avg' using $argv[2]:$argv[4] title '0.2' pt 1 lc rgb '#ff9900',\ +'0.3.avg' using $argv[2]:$argv[4] title '0.3' pt 1 lc rgb '#ffff00',\ +'0.4.avg' using $argv[2]:$argv[4] title '0.4' pt 1 lc rgb '#99ff00',\ +'0.5.avg' using $argv[2]:$argv[4] title '0.5' pt 1 lc rgb '#00ff00',\ +'0.6.avg' using $argv[2]:$argv[4] title '0.6' pt 1 lc rgb '#00ff99',\ +'0.7.avg' using $argv[2]:$argv[4] title '0.7' pt 1 lc rgb '#00ffff',\ +'0.8.avg' using $argv[2]:$argv[4] title '0.8' pt 1 lc rgb '#0000ff',\ +'0.9.avg' using $argv[2]:$argv[4] title '0.9' pt 1 lc rgb '#9900ff',\ +'1.0.avg' using $argv[2]:$argv[4] title '1.0' pt 1 lc rgb '#ff00cc',\ +'0.1.aavg' using $argv[2]:$argv[4] title '0.1' pt 5 lc rgb '#ff0000',\ +'0.2.aavg' using $argv[2]:$argv[4] title '0.2' pt 5 lc rgb '#ff9900',\ +'0.3.aavg' using $argv[2]:$argv[4] title '0.3' pt 5 lc rgb '#ffff00',\ +'0.4.aavg' using $argv[2]:$argv[4] title '0.4' pt 5 lc rgb '#99ff00',\ +'0.5.aavg' using $argv[2]:$argv[4] title '0.5' pt 5 lc rgb '#00ff00',\ +'0.6.aavg' using $argv[2]:$argv[4] title '0.6' pt 5 lc rgb '#00ff99',\ +'0.7.aavg' using $argv[2]:$argv[4] title '0.7' pt 5 lc rgb '#00ffff',\ +'0.8.aavg' using $argv[2]:$argv[4] title '0.8' pt 5 lc rgb '#0000ff',\ +'0.9.aavg' using $argv[2]:$argv[4] title '0.9' pt 5 lc rgb '#9900ff',\ +'1.0.aavg' using $argv[2]:$argv[4] title '1.0' pt 5 lc rgb '#ff00cc'\ " | gnuplot @@ -32,5 +42,14 @@ plot \ + + + + + + + + + diff --git a/simulations/enzymeCost/nutrientCost/wrongFormula/0.1.avg b/simulations/enzymeCost/nutrientCost/wrongFormula/0.1.avg new file mode 100644 index 0000000..50f7066 --- /dev/null +++ b/simulations/enzymeCost/nutrientCost/wrongFormula/0.1.avg @@ -0,0 +1,10 @@ +AVG,17.65326335407368,0.055522535775704374,3.397800000000001,1.25277,1.3053999999999997,0.9081859999999999,0.5497050710072652,0.00793803728519213,0.3608350357930722,0.0010213981778907204,100,100,99.78,99.98, +AVG,17.799101609471403,0.03176256781818051,3.411599999999999,0.9982080000000004,1.385,0.8209179999999999,0.5459048508863509,0.00747248740185179,0.36950977875819,0.0009575426150624656,100,100,99.98,99.96, +AVG,17.838379054450105,0.050374729754077474,3.605,0.9919059999999996,1.3595999999999997,0.9768840000000003,0.560733390230724,0.006740541760859305,0.3655227855011822,0.0008664708596514431,100,100,99.98,99.98, +AVG,17.800456364463365,0.041990787582776565,2.9606,1.2112460000000005,1.0909999999999997,0.786946,0.5512215141842545,0.0071983768381623115,0.3714082216330933,0.0011476378195650482,100,100,99.84,99.98, +AVG,17.90242281860873,0.04097343951073475,3.1508,1.0306639999999998,1.2938,0.9210299999999998,0.5436017339906729,0.007069392858772682,0.3879449818596686,0.001311889882865209,100,100,99.6,99.94, 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diff --git a/simulations/enzymeCost/nutrientCost/wrongFormula/0.1/6.avg b/simulations/enzymeCost/nutrientCost/wrongFormula/0.1/6.avg new file mode 100644 index 0000000..71885ca --- /dev/null +++ b/simulations/enzymeCost/nutrientCost/wrongFormula/0.1/6.avg @@ -0,0 +1 @@ +AVG,17.728323181866223,0.036588552955066904,3.417399999999999,0.9588699999999999,1.1485999999999996,0.8384139999999998,0.5560260781775992,0.007719823101455336,0.3647973603393545,0.0007854184004274915,100,100,99.98,100, diff --git a/simulations/enzymeCost/nutrientCost/wrongFormula/0.1/6.log b/simulations/enzymeCost/nutrientCost/wrongFormula/0.1/6.log new file mode 100644 index 0000000..3e1108b --- /dev/null +++ b/simulations/enzymeCost/nutrientCost/wrongFormula/0.1/6.log @@ -0,0 +1,202 @@ +num_iter,c_sum_mu,c_sum_sigma,c_d_mu,c_d_sigma,e_d_mu,e_d_sigma,fitness_mean,fitness_sigma,percent_toxic_mean,percent_toxic_sigma,pred1,pred2,pred3,pred4 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a/simulations/enzymeCost/nutrientCost/wrongFormula/0.1/9.avg b/simulations/enzymeCost/nutrientCost/wrongFormula/0.1/9.avg new file mode 100644 index 0000000..dca5aca --- /dev/null +++ b/simulations/enzymeCost/nutrientCost/wrongFormula/0.1/9.avg @@ -0,0 +1 @@ +AVG,17.759649864211,0.035647289570480356,3.2490000000000006,1.034974,1.4741999999999995,1.278482,0.5709751385044075,0.007882279505219908,0.3532117259643893,0.0008056804571786369,100,100,99.96,100, diff --git a/simulations/enzymeCost/nutrientCost/wrongFormula/0.1/9.log b/simulations/enzymeCost/nutrientCost/wrongFormula/0.1/9.log new file mode 100644 index 0000000..85a09fa --- /dev/null +++ b/simulations/enzymeCost/nutrientCost/wrongFormula/0.1/9.log @@ -0,0 +1,202 @@ +num_iter,c_sum_mu,c_sum_sigma,c_d_mu,c_d_sigma,e_d_mu,e_d_sigma,fitness_mean,fitness_sigma,percent_toxic_mean,percent_toxic_sigma,pred1,pred2,pred3,pred4 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a/simulations/enzymeCost/nutrientCost/wrongFormula/0.2/10.avg b/simulations/enzymeCost/nutrientCost/wrongFormula/0.2/10.avg new file mode 100644 index 0000000..8c8d3a0 --- /dev/null +++ b/simulations/enzymeCost/nutrientCost/wrongFormula/0.2/10.avg @@ -0,0 +1 @@ +AVG,17.700854535126556,0.04860551291289851,3.5695999999999986,0.843468,1.3120000000000003,0.8580079999999998,0.5328943295900817,0.007242586279375352,0.3821853488581211,0.0010016575573125366,100,100,99.86,99.98, diff --git a/simulations/enzymeCost/nutrientCost/wrongFormula/0.2/10.log b/simulations/enzymeCost/nutrientCost/wrongFormula/0.2/10.log new file mode 100644 index 0000000..1132ce8 --- /dev/null +++ b/simulations/enzymeCost/nutrientCost/wrongFormula/0.2/10.log @@ -0,0 +1,202 @@ +num_iter,c_sum_mu,c_sum_sigma,c_d_mu,c_d_sigma,e_d_mu,e_d_sigma,fitness_mean,fitness_sigma,percent_toxic_mean,percent_toxic_sigma,pred1,pred2,pred3,pred4 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diff --git a/simulations/enzymeCost/nutrientCost/wrongFormula/0.2/5.avg b/simulations/enzymeCost/nutrientCost/wrongFormula/0.2/5.avg new file mode 100644 index 0000000..763ecbe --- /dev/null +++ b/simulations/enzymeCost/nutrientCost/wrongFormula/0.2/5.avg @@ -0,0 +1 @@ +AVG,17.867218759959396,0.04535799995172183,3.543200000000001,0.9098880000000003,1.0996000000000001,0.8226239999999998,0.5089694204599692,0.006565497611788834,0.36100057302945665,0.0008229067831564392,100,100,99.8,100, diff --git a/simulations/enzymeCost/nutrientCost/wrongFormula/0.2/5.log b/simulations/enzymeCost/nutrientCost/wrongFormula/0.2/5.log new file mode 100644 index 0000000..93231ee --- /dev/null +++ b/simulations/enzymeCost/nutrientCost/wrongFormula/0.2/5.log @@ -0,0 +1,202 @@ +num_iter,c_sum_mu,c_sum_sigma,c_d_mu,c_d_sigma,e_d_mu,e_d_sigma,fitness_mean,fitness_sigma,percent_toxic_mean,percent_toxic_sigma,pred1,pred2,pred3,pred4 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diff --git a/simulations/enzymeCost/nutrientCost/wrongFormula/0.4/7.avg b/simulations/enzymeCost/nutrientCost/wrongFormula/0.4/7.avg new file mode 100644 index 0000000..968bff3 --- /dev/null +++ b/simulations/enzymeCost/nutrientCost/wrongFormula/0.4/7.avg @@ -0,0 +1 @@ +AVG,17.70989237235923,0.043122695006606246,3.387199999999999,0.8213759999999998,1.6065999999999994,1.0668819999999999,0.5388208995709782,0.007318620414833106,0.36092093047406826,0.001092014318892309,100,100,99.96,99.94, diff --git a/simulations/enzymeCost/nutrientCost/wrongFormula/0.4/7.log b/simulations/enzymeCost/nutrientCost/wrongFormula/0.4/7.log new file mode 100644 index 0000000..a804b64 --- /dev/null +++ b/simulations/enzymeCost/nutrientCost/wrongFormula/0.4/7.log @@ -0,0 +1,202 @@ +num_iter,c_sum_mu,c_sum_sigma,c_d_mu,c_d_sigma,e_d_mu,e_d_sigma,fitness_mean,fitness_sigma,percent_toxic_mean,percent_toxic_sigma,pred1,pred2,pred3,pred4 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b/simulations/enzymeCost/nutrientCost/wrongFormula/0.5/10.avg new file mode 100644 index 0000000..9a84f9e --- /dev/null +++ b/simulations/enzymeCost/nutrientCost/wrongFormula/0.5/10.avg @@ -0,0 +1 @@ +AVG,17.962399005606542,0.03173116179263146,3.1442000000000005,0.9259179999999995,1.1082000000000003,0.79503,0.5045407850251997,0.005597879903411227,0.3673508791184711,0.0009201498916726272,100,100,99.9,100, diff --git a/simulations/enzymeCost/nutrientCost/wrongFormula/0.5/10.log b/simulations/enzymeCost/nutrientCost/wrongFormula/0.5/10.log new file mode 100644 index 0000000..1c071b3 --- /dev/null +++ b/simulations/enzymeCost/nutrientCost/wrongFormula/0.5/10.log @@ -0,0 +1,202 @@ +num_iter,c_sum_mu,c_sum_sigma,c_d_mu,c_d_sigma,e_d_mu,e_d_sigma,fitness_mean,fitness_sigma,percent_toxic_mean,percent_toxic_sigma,pred1,pred2,pred3,pred4 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diff --git a/simulations/enzymeCost/nutrientCost/wrongFormula/1.0/8.avg b/simulations/enzymeCost/nutrientCost/wrongFormula/1.0/8.avg new file mode 100644 index 0000000..08a2d90 --- /dev/null +++ b/simulations/enzymeCost/nutrientCost/wrongFormula/1.0/8.avg @@ -0,0 +1 @@ +AVG,17.95993672473177,0.03733579552566745,3.642,1.013088,0.8966000000000003,0.6229140000000001,0.4267948895489232,0.0045608828213332935,0.3685239165732424,0.0008524514231058742,100,100,99.98,99.98, diff --git a/simulations/enzymeCost/nutrientCost/wrongFormula/1.0/8.log b/simulations/enzymeCost/nutrientCost/wrongFormula/1.0/8.log new file mode 100644 index 0000000..33538b9 --- /dev/null +++ b/simulations/enzymeCost/nutrientCost/wrongFormula/1.0/8.log @@ -0,0 +1,202 @@ +num_iter,c_sum_mu,c_sum_sigma,c_d_mu,c_d_sigma,e_d_mu,e_d_sigma,fitness_mean,fitness_sigma,percent_toxic_mean,percent_toxic_sigma,pred1,pred2,pred3,pred4 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a/simulations/enzymeCost/nutrientCost/wrongFormula/3/6.avg b/simulations/enzymeCost/nutrientCost/wrongFormula/3/6.avg new file mode 100644 index 0000000..47bb975 --- /dev/null +++ b/simulations/enzymeCost/nutrientCost/wrongFormula/3/6.avg @@ -0,0 +1 @@ +AVG,17.972890926364304,0.02901220537126958,3.2911999999999995,0.8939760000000001,1.273,0.8919539999999997,0.31359255606155817,0.002428826184989411,0.3562614316201574,0.0009115046751751228,100,100,99.98,100, diff --git a/simulations/enzymeCost/nutrientCost/wrongFormula/3/6.log b/simulations/enzymeCost/nutrientCost/wrongFormula/3/6.log new file mode 100644 index 0000000..8fb8861 --- /dev/null +++ b/simulations/enzymeCost/nutrientCost/wrongFormula/3/6.log @@ -0,0 +1,202 @@ +num_iter,c_sum_mu,c_sum_sigma,c_d_mu,c_d_sigma,e_d_mu,e_d_sigma,fitness_mean,fitness_sigma,percent_toxic_mean,percent_toxic_sigma,pred1,pred2,pred3,pred4 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using $argv[2]:$argv[4] title '0.06' pt 5,\ -'0.08.avg' using $argv[2]:$argv[4] title '0.08' pt 5,\ -'0.10.avg' using $argv[2]:$argv[4] title '0.10' pt 5,\ -'0.12.avg' using $argv[2]:$argv[4] title '0.12' pt 5,\ -'0.14.avg' using $argv[2]:$argv[4] title '0.14' pt 5,\ -'0.16.avg' using $argv[2]:$argv[4] title '0.16' pt 5,\ -'0.18.avg' using $argv[2]:$argv[4] title '0.18' pt 5,\ -'0.20.avg' using $argv[2]:$argv[4] title '0.20' pt 5 +'0.00.avg' using $argv[2]:$argv[4] title '0.00' pt 1 lc rgb '#ff0000',\ +'0.02.avg' using $argv[2]:$argv[4] title '0.02' pt 1 lc rgb '#ff9900',\ +'0.04.avg' using $argv[2]:$argv[4] title '0.04' pt 1 lc rgb '#ffff00',\ +'0.06.avg' using $argv[2]:$argv[4] title '0.06' pt 1 lc rgb '#99ff00',\ +'0.08.avg' using $argv[2]:$argv[4] title '0.08' pt 1 lc rgb '#00ff00',\ +'0.10.avg' using $argv[2]:$argv[4] title '0.10' pt 1 lc rgb '#00ff99',\ +'0.12.avg' using $argv[2]:$argv[4] title '0.12' pt 1 lc rgb '#00ffff',\ +'0.14.avg' using $argv[2]:$argv[4] title '0.14' pt 1 lc rgb '#0099ff',\ +'0.16.avg' using $argv[2]:$argv[4] title '0.16' pt 1 lc rgb '#0000ff',\ +'0.18.avg' using $argv[2]:$argv[4] title '0.18' pt 1 lc rgb '#9900ff',\ +'0.20.avg' using $argv[2]:$argv[4] title '0.20' pt 1 lc rgb '#ff00cc',\ +'0.00.aavg' using $argv[2]:$argv[4] title '0.00' pt 5 lc rgb '#ff0000',\ +'0.02.aavg' using $argv[2]:$argv[4] title '0.02' pt 5 lc rgb '#ff9900',\ +'0.04.aavg' using $argv[2]:$argv[4] title '0.04' pt 5 lc rgb '#ffff00',\ +'0.06.aavg' using $argv[2]:$argv[4] title '0.06' pt 5 lc rgb '#99ff00',\ +'0.08.aavg' using $argv[2]:$argv[4] title '0.08' pt 5 lc rgb '#00ff00',\ +'0.10.aavg' using $argv[2]:$argv[4] title '0.10' pt 5 lc rgb '#00ff99',\ +'0.12.aavg' using $argv[2]:$argv[4] title '0.12' pt 5 lc rgb '#00ffff',\ +'0.14.aavg' using $argv[2]:$argv[4] title '0.14' pt 5 lc rgb '#0099ff',\ +'0.16.aavg' using $argv[2]:$argv[4] title '0.16' pt 5 lc rgb '#0000ff',\ +'0.18.aavg' using $argv[2]:$argv[4] title '0.18' pt 5 lc rgb '#9900ff',\ +'0.20.aavg' using $argv[2]:$argv[4] title '0.20' pt 5 lc rgb '#ff00cc'\ " | gnuplot + + + + + + + + + + + + + + + + + diff --git a/simulations/enzymeCost/staticCost/plot2.fish b/simulations/enzymeCost/staticCost/plot2.fish new file mode 100755 index 0000000..b4b527a --- /dev/null +++ b/simulations/enzymeCost/staticCost/plot2.fish @@ -0,0 +1,24 @@ +#!/usr/bin/env fish + +echo " +set datafile separator \",\" +set xlabel '$argv[1]' +set ylabel '$argv[3]' +set term png +set output '$argv[5]' +set title '$argv[6]' +set key outside right + +plot \ +'0.00.avg' using $argv[2]:$argv[4] title '0.00' pt 5,\ +'0.02.avg' using $argv[2]:$argv[4] title '0.02' pt 5,\ +'0.04.avg' using $argv[2]:$argv[4] title '0.04' pt 5,\ +'0.06.avg' using $argv[2]:$argv[4] title '0.06' pt 5,\ +'0.08.avg' using $argv[2]:$argv[4] title '0.08' pt 5,\ +'0.10.avg' using $argv[2]:$argv[4] title '0.10' pt 5,\ +'0.12.avg' using $argv[2]:$argv[4] title '0.12' pt 5,\ +'0.14.avg' using $argv[2]:$argv[4] title '0.14' pt 5,\ +'0.16.avg' using $argv[2]:$argv[4] title '0.16' pt 5,\ +'0.18.avg' using $argv[2]:$argv[4] title '0.18' pt 5,\ +'0.20.avg' using $argv[2]:$argv[4] title '0.20' pt 5 +" | gnuplot diff --git a/src/Environment.hs b/src/Environment.hs index dd9dedc..c4fb060 100644 --- a/src/Environment.hs +++ b/src/Environment.hs @@ -244,7 +244,7 @@ fitness iter ps = do nutrientsAvailable <- fmap snd <$> fromEnv soil let nutrientsLeft = (\p -> [p ! i | i <- [0..fromEnum (maxBound :: Nutrient)]]) <$> products nutrientRatio = minimum . zipWith (flip (/)) nutrientsAvailable <$> nutrientsLeft - costOfEnzymes = max 0 <$> zipWith (\s n -> 1-(s+n*ni)) staticCostOfEnzymes nutrientRatio -- cost to keep enzymes are static costs + amount of nutrient sucked out of the primary cycle + costOfEnzymes = max 0 <$> zipWith (\s n -> 1-(s+(1-n)*ni)) staticCostOfEnzymes nutrientRatio -- cost to keep enzymes are static costs + amount of nutrient sucked out of the primary cycle survivalRate = (1-) <$> dieRate return $ zip (zipWith (*) survivalRate costOfEnzymes) products diff --git a/vortrag/Makefile b/vortrag/Makefile index a1b5e82..8e77cc4 100644 --- a/vortrag/Makefile +++ b/vortrag/Makefile @@ -8,6 +8,7 @@ slides: $(INPUT) pandoc -f markdown+smart+emoji -t revealjs \ --template ./template.html \ --incremental \ + --mathjax \ --indented-code-classes=haskell \ --section-divs \ -o chemodiversity.html $(INPUT) diff --git a/vortrag/chemodiversity.html b/vortrag/chemodiversity.html index 4f63a73..52ba792 100644 --- a/vortrag/chemodiversity.html +++ b/vortrag/chemodiversity.html @@ -170,7 +170,7 @@
  • Input can be Substrate and/or Products
  • Outputs can only be Products
    • -
  • ⇒ This makes them to Edges in a graph combining the chemical compounds
    • +
  • \(\Rightarrow\) This makes them to Edges in a graph combining the chemical compounds
    • @@ -191,9 +191,9 @@
  • Predators consist of
    • a list of Compounds that can kill them
      • -
    • a fitness impact ([0..1]) as the probability of killing the plant
      • +
    • a fitness impact (\([0..1]\)) as the probability of killing the plant
    • an expected number of attacks per generation
      • -
    • a probability ([0..1]) of appearing in a single generation
      • +
    • a probability (\([0..1]\)) of appearing in a single generation
  • Predator need not necessary be biologically motivated
      @@ -223,7 +223,7 @@

      Additional rules:

      • Every “subtree” from the marked PPM is treated as a separate species (fungi, animals, …)
        -⇒ Every predator can only be affected by toxins in the same part of the tree
        • +\(\Rightarrow\) Every predator can only be affected by toxins in the same part of the tree
      • Trees can be automatically generated in a decent manner to search for environmens where specific effects may arise
      @@ -242,55 +242,172 @@

      Plants

      -

      A plant consists of …

      +

      A Plant consists of

      +
        +
      • a Genome, a simple list of genes +
          +
        • Triple of (Enzyme, Quantity, Activation)
          • +
        • without order or locality (i.e. interference of neighboring genes)
          • +
        • Quantity is just an optimization (=Int) to group identical Activations
          • +
        • Activation is a float \(\in [0..1]\) to regulate the activity of the Enzyme genetically
          • +
        • +
      • an absorbNutrients-Function to simulate various effects when absorbing nutrients out of the environment, depending on the environment (i.e. can use informations about chemistry, predators, etc.) +
          +
        • Not used in our simulation, as we only have PPM as “nutrient” and we take everything given to us.
          • +
        • +

      Metabolism simulation

      -

      Compounds are created foo..

      +

      Creation of compounds from the given resources is an iterative process:

      +
        +
      • First of all we create a conversion Matrix \(\Delta_c\) with corresponding startvector \(s_0\).
        • +

      • We now iterate \(s_i = (\mathbb{1} + \Delta_c) \cdot s_{i-1}\) for a fixed number of times (currently: \(100\)) to simulate the metabolism[2].

        +
        +

        [2]: Thats a ‘lie’, we calculate \((\mathbb{1} + \Delta_c)^{100}\) efficiently via lapack-internals

        +
        • +
      • Entries in the matrix come from the Genome: an Enzyme which converts \(i\) to \(j\) with quantity \(q\) and activity \(a\) yield \[\begin{eqnarray*} +\Delta_c[i,j] &\mathrel{+}=& q\cdot a,\\ +\Delta_c[j,i] &\mathrel{+}=& q\cdot a, \\ +\Delta_c[i,i] &\mathrel{-}=& q\cdot a, \\ +\Delta_c[j,j] &\mathrel{-}=& q\cdot a +\end{eqnarray*}.\] +
          +
        • This makes the Enzyme-reaction invertible as both ways get treated equally.
          • +
        • +
      +
      +
      +

      Metabolism-example

      +
        +

      • Given a simple Metabolism with \(1\) nutrient (first row/column) and \(2\) Enzymes in sequence, we have given \(\Delta_c\) wtih corresponding startvector \(s_0\): \[\Delta_c = 0.01 \cdot \begin{pmatrix} +-1 & 1 & 0 \\ + 1 & -2 & 1 \\ + 0 & 1 & -1 \\ +\end{pmatrix}, s_0 = \begin{pmatrix}\text{PPM:} & 3 \\ \text{Compound1:} & 0 \\ \text{Compound2:} & 0\end{pmatrix}.\]

        • +

      • In the simulation this yields us \[s_{100} \approx \begin{pmatrix}\text{PPM:} & 1 \\ \text{Compound1:} & 1 \\ \text{Compound2:} & 1\end{pmatrix},\] which is the expected outcome for an equilibrium.

        • +
      +
      +
      +

      Assumptions for metabolism simulation

      +
        +
      • All Enzymes are there from the beginning
        • +
      • All Enzyme-reactions are reversible without loss
        • +
      • static conversion-matrix for fast calculations (unsuited, if i.e. enzymes depend on catalysts)
        • +
      • One genetic enzyme corresponds to (infinitely) many real (proportional weaker) enzymes in the plant, which get controlled via the “activation” parameter
        • +

      Fitness

        -
      • Static costs of enzymes
        • -
      • Cost of active enzymes
        • +
      • We handle fitness as \(\text{survival-probability} \in [0..1]\) and model each detrimental effect as probability which get multiplied together.
        • +
      • To calculate the fitness of an individual we take three distinct effects into consideration: +
          +
        • Static costs of enzymes +
            +
          • Creating enzymes weakens the primary cycle and thus possibly beneficial traits (growth, attraction of beneficial organisms, …) \[F_s := \text{static_cost_factor} \cdot \sum_i q_i \cdot a_i \quad | \quad (e_i,q_i, a_i) \in \text{Genome}\]
            • +
          • limits the amount of dormant enzymes
            • +
          • +
        • Cost of active enzymes +
            +
          • Cost of using up nutrients \[F_e := \text{active_cost_factor} \cdot \frac{\text{Nutrients used}}{\text{Nutrients available}}\]
            • +
          • +
        • Deterrence of attackers \(F_d\) (next slide)
          • +

      Attacker

        -
      • Rate of attack ~> Paper, Formulas
        • -
      • Defenses +
      • Predators are modeled after Svennungsen et al. (2007)
        • +
      • Each predator has an expected number of attacks \(P_a\), that are poisson-distributed with impact \(P_i\).
        • +
      • Plants can defend themselves via
          -
        • single plant
          • -
        • automimicry
          • +
        • toxins that the predator is affected by with impact-probability \(D_t(P_i)\)
          • +
        • herd-immunity via effects like automimicry: \(D_{pop} = \mathbb{E}[D_t(P_i)]\)
          • +
        • +

      • All this yields the formula:

        +

        \[F_d := 1 - e^{- (D_{pop} \cdot P_a) (1-D_t(P_i))}\]

        • +
      • The attacker-model is only valid for many reasonable assumptions +
          +
        • equilibrium population dynamics
          • +
        • equal dense population
          • +
        • which individual to attack is independently chosen
          • +
        • etc. (Details in the paper linked above)

      Haploid mating

        -
      • fixed population-size (100)
        • -
      • $p(\textrm{reproduction}) = \frac{\textrm{plant-fitness}}{\textrm{total fitness in population}}$
        • -
      • Gene +
      • We hold the population-size fixed at \(100\)
        • +
      • Each plant has a reproduction-probability of \[p(\textrm{reproduction}) = \frac{\textrm{plant-fitness}}{\textrm{total fitness in population}}\] yielding a fitness-weighted distribution from that \(100\) new offspring are drawn
        • +

      • in inheritance each gene of the parent goes through different steps (with given default-values)[3]

        +
        +

        [3]: in case of quantity \(q > 1\) the process is repeated \(q\) times independently.

        +
          -
        • mutation
          • -
        • duplication
          • -
        • deletion
          • -
        • addition
          • -
        • activation-noise
          • +
        • mutation: with \(p_{mut} = 0.01\) another random enzyme is produced, but activation kept
          • +
        • duplication: with \(p_{dup} = 0.05\) the gene gets duplicated (quantity \(+1\))
          • +
        • deletion: with \(p_{del} = p_{dup}\) the gene get deleted (or quantity \(-1\))
          • +
        • addition: with \(p_{add} = 0.005\) an additional gene producing a random enzyme with activation \(0.5\) gets added as mutation from genes we do not track (i.e. primary cycle)
          • +
        • activation-noise: activation is changed by \(c_{noise} = \pm 0.01\) drawn from a uniform distribution, clamped to \([0..1]\)
      +

    • Simulations

    -

    Parameters tested

      -
    • x
      • -
    • y
      • -
    • z
      • +
    • Overall question: What parameters are necessary for chemodiversity? +
        +
      • How can we see chemodiversity?
        • +
      • We define an Enzyme \(E\) as divers, if the average of this Enzyme in the population stays below \(0.5\), so \(E_i \in E_{div} \text{iff.} \mathbb{E}[E_i] < 0.5\)
        • +
      • We can then count the number of diverse Enzymes per plant \(E_{d,p_i} = |\left\lbrace E_i | E_i \in E_{div}, E_{i,p_i} > 0.5, \right\rbrace|\)
        • +
      • +
    • To get an insight into how this behaves we observe several other parameters every generation: +
        +
      • Fitness \(\in [0..1]\)
        • +
      • Number of different compounds created
        • +
      • Amount of compounds created
        • +
      • Number of Plants theoretically resistant to predator \(i\) (i.e. can produce a toxin to defend themselves, albeit not to \(100\%\).
        • +
      • +
    +
    +
    +

    Simulations (cont.)

    +
      +
    • General setup of the simulation: +
        +
      • All using the example-environment shown before +
          +
        • 27 different compounds, 1 Nutrient (simulating the primary metabolism)
          • +
        • 7 of 27 compounds are toxic
          • +
        • at least 3 compounds are needed for total immunity
          • +
        • 4 predators
          • +
        • +
      • Duration of 2000 generations
        • +
      • +
    • Different setups tested: +
        +
      • Behavior of predators (AlwaysAttack, AttackRandom, AttackInterval Int)
        • +
      • varying \(\text{static_enzyme_cost}\) from \(0.0\) to \(0.20\) in steps of \(0.02\) +
          +
        • effectively limits the amount of maximal enzymes to \(\frac{1}{\text{static_enzyme_cost}}\)
          • +
        • +
      • varying \(\text{nutrient_impact}\) from \(0.0\) to \(1.0\) in steps of \(0.1\) +
          +
        • makes toxins less/more costly to produce
          • +
        • +
    @@ -303,6 +420,48 @@
    +
    +

    Effect of Predator-Behavior onto chemodiversity

    +
    +Graph
    Graph
    +
    +
    +
    +

    Effect of static enzyme cost

    +
    +Graph
    Graph
    +
    +
    +
    +

    Effect of static enzyme cost (cont.)

    +
    +Graph
    Graph
    +
    +
    +
    +

    Effect of static enzyme cost (cont.)

    +
    +Graph
    Graph
    +
    +
    +
    +

    Effect of nutrient-impact

    +
    +Graph
    Graph
    +
    +
    +
    +

    Effect of nutrient-impact (cont.)

    +
    +Graph
    Graph
    +
    +
    +
    +

    Effect of nutrient-impact (cont.)

    +
    +Graph
    Graph
    +
    +
    diff --git a/vortrag/css/solarized_plus.css b/vortrag/css/solarized_plus.css index 58a50eb..9350dc1 100644 --- a/vortrag/css/solarized_plus.css +++ b/vortrag/css/solarized_plus.css @@ -207,11 +207,22 @@ body { .reveal small * { vertical-align: top; } +.reveal .math { + color: #1a6091; +} + +.reveal .math.display { + margin: auto; + display: block; + width: fit-content; +} + /********************************************* * LINKS *********************************************/ .reveal a { - color: #586e75; + color: #3070a0; + font-weight:bold; text-decoration: none; -webkit-transition: color .15s ease; -moz-transition: color .15s ease; @@ -470,8 +481,7 @@ body { padding: 5px; font-size: 0.5em; left: 100px; - width: 724px; - top: 750px; + bottom: -100px; } diff --git a/vortrag/img/attackRate_E_d_mu_vs_C_mu.png b/vortrag/img/attackRate_E_d_mu_vs_C_mu.png new file mode 120000 index 0000000..d55494a --- /dev/null +++ b/vortrag/img/attackRate_E_d_mu_vs_C_mu.png @@ -0,0 +1 @@ +../../simulations/attackRate/E_d_mu_vs_C_mu.png \ No newline at end of file diff --git a/vortrag/img/attackRate_E_d_sigma_vs_C_mu.png b/vortrag/img/attackRate_E_d_sigma_vs_C_mu.png new file mode 120000 index 0000000..9da9289 --- /dev/null +++ b/vortrag/img/attackRate_E_d_sigma_vs_C_mu.png @@ -0,0 +1 @@ +../../simulations/attackRate/E_d_sigma_vs_C_mu.png \ No newline at end of file diff --git a/vortrag/img/nutrientCost_Fitness_vs_e_d_mu.png b/vortrag/img/nutrientCost_Fitness_vs_e_d_mu.png new file mode 120000 index 0000000..0f6f169 --- /dev/null +++ b/vortrag/img/nutrientCost_Fitness_vs_e_d_mu.png @@ -0,0 +1 @@ +../../simulations/enzymeCost/nutrientCost/Fitness_vs_e_d_mu.png \ No newline at end of file diff --git a/vortrag/img/nutrientCost_Fitness_vs_num_compounds.png b/vortrag/img/nutrientCost_Fitness_vs_num_compounds.png new file mode 120000 index 0000000..5c8c348 --- /dev/null +++ b/vortrag/img/nutrientCost_Fitness_vs_num_compounds.png @@ -0,0 +1 @@ +../../simulations/enzymeCost/nutrientCost/Fitness_vs_num_compounds.png \ No newline at end of file diff --git a/vortrag/img/nutrientCost_e_d_mu_vs_num_compounds.png b/vortrag/img/nutrientCost_e_d_mu_vs_num_compounds.png new file mode 120000 index 0000000..6476899 --- /dev/null +++ b/vortrag/img/nutrientCost_e_d_mu_vs_num_compounds.png @@ -0,0 +1 @@ +../../simulations/enzymeCost/nutrientCost/e_d_mu_vs_num_compounds.png \ No newline at end of file diff --git a/vortrag/img/staticCost_Fitness_vs_e_d_mu.png b/vortrag/img/staticCost_Fitness_vs_e_d_mu.png new file mode 120000 index 0000000..6d4de67 --- /dev/null +++ b/vortrag/img/staticCost_Fitness_vs_e_d_mu.png @@ -0,0 +1 @@ +../../simulations/enzymeCost/staticCost/Fitness_vs_e_d_mu.png \ No newline at end of file diff --git a/vortrag/img/staticCost_Fitness_vs_num_compounds.png b/vortrag/img/staticCost_Fitness_vs_num_compounds.png new file mode 120000 index 0000000..fa56397 --- /dev/null +++ b/vortrag/img/staticCost_Fitness_vs_num_compounds.png @@ -0,0 +1 @@ +../../simulations/enzymeCost/staticCost/Fitness_vs_num_compounds.png \ No newline at end of file diff --git a/vortrag/img/staticCost_e_d_mu_vs_num_compounds.png b/vortrag/img/staticCost_e_d_mu_vs_num_compounds.png new file mode 120000 index 0000000..79b29f8 --- /dev/null +++ b/vortrag/img/staticCost_e_d_mu_vs_num_compounds.png @@ -0,0 +1 @@ +../../simulations/enzymeCost/staticCost/e_d_mu_vs_num_compounds.png \ No newline at end of file diff --git a/vortrag/vortrag.md b/vortrag/vortrag.md index 66af79f..6d03494 100644 --- a/vortrag/vortrag.md +++ b/vortrag/vortrag.md @@ -90,8 +90,7 @@ Usage in the current Model - This is used to simulate i.e. worse growth, fertility and other things affecting the fitness of a plant. - We are not using named Compounds, but restrict to generic `Compound - 1`{.haskell}, - `Compound 2`{.haskell} ... + 1`{.haskell}, `Compound 2`{.haskell} ... - Not done, but worth exploring: - Take a "real-world" snapshot of Nutrients and Compounds and recreate them - See if the simulation follows the real world @@ -179,53 +178,175 @@ CTRL+Click for zoom! Plants ------ -A plant consists of -... +A **`Plant`{.haskell}** consists of +- a **`Genome`{.haskell}**, a simple list of genes + - Triple of `(Enzyme, Quantity, Activation)`{.haskell} + - without order or locality (i.e. interference of neighboring genes) + - `Quantity`{.haskell} is just an optimization (=Int) to group identical + `Activation`{.haskell}s + - `Activation`{.haskell} is a float $\in [0..1]$ to regulate the activity of + the `Enzyme`{.haskell} genetically +- an `absorbNutrients`{.haskell}-Function to simulate various effects when + absorbing nutrients out of the environment, depending on the environment (i.e. + *can* use informations about chemistry, predators, etc.) + - Not used in our simulation, as we only have `PPM`{.haskell} as "nutrient" + and we take everything given to us. Metabolism simulation --------------------- -Compounds are created foo.. +Creation of compounds from the given resources is an iterative process: +- First of all we create a conversion Matrix $\Delta_c$ with corresponding + startvector $s_0$. +- We now iterate $s_i = (\mathbb{1} + \Delta_c) \cdot s_{i-1}$ for a fixed number of times + (currently: $100$) to simulate the metabolism^[2]^. + + ::: footer ::: + ^[2]^: Thats a 'lie', we calculate $(\mathbb{1} + \Delta_c)^{100}$ efficiently via + `lapack`-internals + ::: + +- Entries in the matrix come from the `Genome`{.haskell}: an `Enzyme`{.haskell} which + converts $i$ to $j$ with quantity $q$ and activity $a$ yield + $$\begin{eqnarray*} + \Delta_c[i,j] &\mathrel{+}=& q\cdot a,\\ + \Delta_c[j,i] &\mathrel{+}=& q\cdot a, \\ + \Delta_c[i,i] &\mathrel{-}=& q\cdot a, \\ + \Delta_c[j,j] &\mathrel{-}=& q\cdot a + \end{eqnarray*}.$$ + - This makes the Enzyme-reaction invertible as both ways get treated equally. + +Metabolism-example +------------------ + +- Given a simple Metabolism with $1$ nutrient (first row/column) and $2$ Enzymes + in sequence, we have given $\Delta_c$ wtih corresponding startvector $s_0$: + $$\Delta_c = 0.01 \cdot \begin{pmatrix} + -1 & 1 & 0 \\ + 1 & -2 & 1 \\ + 0 & 1 & -1 \\ + \end{pmatrix}, s_0 = \begin{pmatrix}\text{PPM:} & 3 \\ \text{Compound1:} & 0 \\ \text{Compound2:} & 0\end{pmatrix}.$$ + +- In the simulation this yields us + $$s_{100} \approx \begin{pmatrix}\text{PPM:} & 1 \\ \text{Compound1:} & 1 \\ \text{Compound2:} & 1\end{pmatrix},$$ + which is the expected outcome for an equilibrium. + + +Assumptions for metabolism simulation +------------------------------------- + +- All Enzymes are there from the beginning +- All Enzyme-reactions are reversible without loss +- static conversion-matrix for fast calculations (unsuited, if i.e. enzymes + depend on catalysts) +- One genetic enzyme corresponds to (infinitely) many real (proportional weaker) + enzymes in the plant, which get controlled via the "activation" parameter Fitness ------- -- Static costs of enzymes -- Cost of active enzymes - +- We handle fitness as $\text{survival-probability} \in [0..1]$ and model each + detrimental effect as probability which get multiplied together. +- To calculate the fitness of an individual we take three distinct effects into +consideration: + - Static costs of enzymes + - Creating enzymes weakens the primary cycle and thus possibly beneficial + traits (growth, attraction of beneficial organisms, ...) + $$F_s := \text{static_cost_factor} \cdot \sum_i q_i \cdot a_i \quad | \quad (e_i,q_i, a_i) \in \text{Genome}$$ + - limits the amount of dormant enzymes + - Cost of active enzymes + - Cost of using up nutrients + $$F_e := \text{active_cost_factor} \cdot \frac{\text{Nutrients used}}{\text{Nutrients available}}$$ + - Deterrence of attackers $F_d$ (next slide) Attacker -------- -- Rate of attack ~> Paper, Formulas -- Defenses - - single plant - - automimicry +- Predators are modeled after [Svennungsen et al. (2007)](http://doi.org/10.1098/rspb.2007.0456) +- Each predator has an expected number of attacks $P_a$, that are + poisson-distributed with impact $P_i$. +- Plants can defend themselves via + - toxins that the predator is affected by with impact-probability $D_t(P_i)$ + - herd-immunity via effects like automimicry: $D_{pop} = \mathbb{E}[D_t(P_i)]$ +- All this yields the formula: + + $$F_d := 1 - e^{- (D_{pop} \cdot P_a) (1-D_t(P_i))}$$ + +- The attacker-model is only valid for many reasonable assumptions + - equilibrium population dynamics + - equal dense population + - which individual to attack is independently chosen + - etc. (Details in the paper linked above) Haploid mating -------------- -- fixed population-size (100) -- $p(\textrm{reproduction}) = \frac{\textrm{plant-fitness}}{\textrm{total fitness in population}}$ -- Gene - - mutation - - duplication - - deletion - - addition - - activation-noise +- We hold the population-size fixed at $100$ +- Each plant has a reproduction-probability of + $$p(\textrm{reproduction}) = \frac{\textrm{plant-fitness}}{\textrm{total fitness in population}}$$ + yielding a fitness-weighted distribution from that $100$ new offspring are + drawn +- in inheritance each gene of the parent goes through different steps (with + given default-values)^[3]^ + + ::::: footer + ^[3]^: in case of quantity $q > 1$ the process is repeated $q$ times + independently. + :::: + + - **mutation**: with $p_{mut} = 0.01$ another random enzyme is produced, but + activation kept + - **duplication**: with $p_{dup} = 0.05$ the gene gets duplicated (quantity $+1$) + - **deletion**: with $p_{del} = p_{dup}$ the gene get deleted (or quantity $-1$) + - **addition**: with $p_{add} = 0.005$ an additional gene producing a random + enzyme with activation $0.5$ gets added as mutation from genes we do not + track (i.e. primary cycle) + - **activation-noise**: activation is changed by $c_{noise} = \pm 0.01$ drawn from + a uniform distribution, clamped to $[0..1]$ + +:::: notes +- Default values **not** motivated in any way! +- finding out how these values influence is core! +:::: -------------------------------------------------------------------------------- Simulations ----------- -Parameters tested +- Overall question: What parameters are necessary for chemodiversity? + - How can we see chemodiversity? + - We define an Enzyme $E$ as divers, if the average of this Enzyme in the + population stays below $0.5$, so $E_i \in E_{div} \text{iff.} \mathbb{E}[E_i] < 0.5$ + - We can then count the number of diverse Enzymes per plant $E_{d,p_i} = + |\left\lbrace E_i | E_i \in E_{div}, E_{i,p_i} > 0.5, \right\rbrace|$ +- To get an insight into how this behaves we observe several other parameters + every generation: + - Fitness $\in [0..1]$ + - Number of different compounds created + - Amount of compounds created + - Number of Plants theoretically resistant to predator $i$ (i.e. **can** produce + a toxin to defend themselves, albeit not to $100\%$. + +Simulations (cont.) +------------------- + +- General setup of the simulation: + - All using the example-environment shown before + - 27 different compounds, 1 Nutrient (simulating the primary metabolism) + - 7 of 27 compounds are toxic + - at least 3 compounds are needed for total immunity + - 4 predators + - Duration of 2000 generations +- Different setups tested: + - Behavior of predators (`AlwaysAttack`{.haskell}, `AttackRandom`{.haskell}, `AttackInterval Int`{.haskell}) + - varying $\text{static_enzyme_cost}$ from $0.0$ to $0.20$ in steps of $0.02$ + - effectively limits the amount of maximal enzymes to $\frac{1}{\text{static_enzyme_cost}}$ + - varying $\text{nutrient_impact}$ from $0.0$ to $1.0$ in steps of $0.1$ + - makes toxins less/more costly to produce -- x -- y -- z -------------------------------------------------------------------------------- @@ -237,10 +358,40 @@ Results -------------------------------------------------------------------------------- - - - - +Effect of Predator-Behavior onto chemodiversity +---------------------------------------- + +![Graph](img/attackRate_E_d_mu_vs_C_mu.png) + +Effect of static enzyme cost +---------------------------- + +![Graph](img/staticCost_Fitness_vs_num_compounds.png) + +Effect of static enzyme cost (cont.) +------------------------------------ + +![Graph](img/staticCost_Fitness_vs_e_d_mu.png) + +Effect of static enzyme cost (cont.) +------------------------------------ + +![Graph](img/staticCost_e_d_mu_vs_num_compounds.png) + +Effect of nutrient-impact +------------------------- + +![Graph](img/nutrientCost_Fitness_vs_num_compounds.png) + +Effect of nutrient-impact (cont.) +--------------------------------- + +![Graph](img/nutrientCost_Fitness_vs_e_d_mu.png) + +Effect of nutrient-impact (cont.) +--------------------------------- + +![Graph](img/nutrientCost_e_d_mu_vs_num_compounds.png)