diff --git a/III/Ovodas/consts.py b/III/Ovodas/consts.py
new file mode 100644
index 0000000..45d3663
--- /dev/null
+++ b/III/Ovodas/consts.py
@@ -0,0 +1,18 @@
+# Ovodo
+# phi_p, phi_s, dphi = 10, 46, 6
+# phi_1, phi_2 = 14, 41
+# lambda_1, lambda_2 = 5, 25
+# lambda_v, lambda_r, dlambda = 0, 24, 6
+# M = 25e6
+
+# mano
+phi_p, phi_s, dphi = 13, 49, 6
+phi_1, phi_2 = 17, 44
+lambda_1, lambda_2 = 5, 25
+lambda_range = [lambda_1, 10, 16, 22, lambda_2]
+lambda_v, lambda_r, dlambda = 0, 24, 6
+M = 25e6
+
+# bendri
+lambda_range = [lambda_1, 6, 12, 18, 24, lambda_2]
+maxlambda = 26
diff --git a/III/Ovodas/krasovskio.csv b/III/Ovodas/krasovskio.csv
index 0b2558c..849212f 100644
--- a/III/Ovodas/krasovskio.csv
+++ b/III/Ovodas/krasovskio.csv
@@ -1,184 +1,184 @@
-phi,M,N,R,r,lgr,Sm,Sn,lnU,lgU,D,P
-0,6335552.9,6378245,6356863.1,6378245,6.8047012,0,111321.4,0,0,0,0
-0.5,6335557.7,6378246.6,6356866.3,6378003.8,6.8046848,55288.1,111317.2,0.00866835,0.00376462,29800,352636.9
-1,6335572.2,6378251.5,6356876,6377280.1,6.8046355,110576.4,111304.5,0.01733736,0.00752952,59601,705247.6
-1.5,6335596.4,6378259.6,6356892.2,6376074,6.8045533,165864.8,111283.5,0.02600772,0.01129501,89408,1057806.1
-2,6335630.3,6378271,6356914.9,6374385.5,6.8044383,221153.4,111254,0.03468008,0.01506137,119221,1410286.1
-2.5,6335673.9,6378285.6,6356944,6372214.9,6.8042904,276442.4,111216.1,0.04335512,0.01882889,149044,1762661.7
-3,6335727.1,6378303.5,6356979.6,6369562.2,6.8041096,331731.8,111169.8,0.05203351,0.02259787,178878,2114906.6
-3.5,6335789.9,6378324.6,6357021.7,6366427.7,6.8038958,387021.7,111115.1,0.06071593,0.02636859,208726,2466994.7
-4,6335862.4,6378348.9,6357070.1,6362811.5,6.8036491,442312.2,111052,0.06940304,0.03014136,238590,2818900
-4.5,6335944.4,6378376.4,6357125,6358714,6.8033693,497603.4,110980.5,0.07809552,0.03391645,268473,3170596.3
-5,6336036.1,6378407.2,6357186.3,6354135.4,6.8030565,552895.4,110900.6,0.08679406,0.03769418,298376,3522057.5
-5.5,6336137.2,6378441.1,6357254,6349076,6.8027105,608188.2,110812.3,0.09549933,0.04147483,328303,3873257.7
-6,6336247.9,6378478.2,6357328,6343536.3,6.8023314,663481.9,110715.6,0.10421201,0.0452587,358255,4224170.6
-6.5,6336368.1,6378518.6,6357408.4,6337516.5,6.8019191,718776.6,110610.5,0.1129328,0.04904609,388234,4574770.4
-7,6336497.7,6378562.1,6357495.1,6331017.2,6.8014735,774072.4,110497.1,0.12166237,0.0528373,418244,4925031
-7.5,6336636.7,6378608.7,6357588.1,6324038.8,6.8009945,829369.3,110375.3,0.13040143,0.05663262,448287,5274926.4
-8,6336785.1,6378658.5,6357687.3,6316581.8,6.8004821,884667.6,110245.2,0.13915066,0.06043237,478365,5624430.5
-8.5,6336942.8,6378711.4,6357792.8,6308646.8,6.7999362,939967.1,110106.7,0.14791078,0.06423683,508480,5973517.5
-9,6337109.8,6378767.4,6357904.5,6300234.2,6.7993567,995268.1,109959.8,0.15668247,0.06804633,538635,6322161.5
-9.5,6337286,6378826.6,6358022.4,6291344.8,6.7987435,1050570.6,109804.7,0.16546646,0.07186117,568832,6670336.4
-10,6337471.4,6378888.8,6358146.4,6281979.1,6.7980965,1105874.7,109641.2,0.17426346,0.07568166,599074,7018016.5
-10.5,6337665.9,6378954,6358276.4,6272137.8,6.7974156,1161180.4,109469.5,0.18307417,0.0795081,629363,7365175.9
-11,6337869.5,6379022.3,6358412.6,6261821.7,6.7967007,1216487.8,109289.4,0.19189933,0.08334082,659701,7711788.7
-11.5,6338082,6379093.6,6358554.8,6251031.4,6.7959517,1271797.1,109101.1,0.20073967,0.08718013,690092,8057829.3
-12,6338303.5,6379167.9,6358702.9,6239767.8,6.7951684,1327108.3,108904.5,0.20959592,0.09102635,720538,8403271.7
-12.5,6338533.9,6379245.2,6358857,6228031.6,6.7943508,1382421.4,108699.7,0.21846883,0.09487981,751041,8748090.4
-13,6338773.1,6379325.4,6359016.9,6215823.8,6.7934987,1437736.6,108486.6,0.22735913,0.09874082,781603,9092259.6
-13.5,6339021,6379408.6,6359182.7,6203145,6.7926119,1493053.9,108265.3,0.2362676,0.10260971,812228,9435753.7
-14,6339277.5,6379494.7,6359354.3,6189996.4,6.7916904,1548373.4,108035.8,0.24519499,0.10648683,842918,9778547.1
-14.5,6339542.6,6379583.6,6359531.6,6176378.8,6.7907339,1603695.2,107798.1,0.25414206,0.1103725,873676,10120614.2
-15,6339816.3,6379675.4,6359714.6,6162293.2,6.7897424,1659019.3,107552.3,0.26310961,0.11426705,904504,10461929.6
-15.5,6340098.3,6379770,6359903.2,6147740.7,6.7887155,1714345.9,107298.3,0.27209841,0.11817084,935405,10802467.6
-16,6340388.7,6379867.4,6360097.4,6132722.2,6.7876533,1769674.9,107036.2,0.28110927,0.1220842,966382,11142203
-16.5,6340687.4,6379967.6,6360297.1,6117238.8,6.7865554,1825006.5,106766,0.29014298,0.12600749,997438,11481110.2
-17,6340994.2,6380070.5,6360502.3,6101291.7,6.7854218,1880340.8,106487.6,0.29920036,0.12994107,1028575,11819164.1
-17.5,6341309,6380176.1,6360712.9,6084882.1,6.7842522,1935677.8,106201.2,0.30828224,0.13388527,1059796,12156339.2
-18,6341631.9,6380284.3,6360928.8,6068011,6.7830464,1991017.6,105906.8,0.31738944,0.13784048,1091105,12492610.4
-18.5,6341962.6,6380395.3,6361149.9,6050679.8,6.7818042,2046360.2,105604.3,0.32652282,0.14180706,1122503,12827952.6
-19,6342301.1,6380508.8,6361376.3,6032889.6,6.7805254,2101705.7,105293.8,0.33568324,0.14578538,1153994,13162340.5
-19.5,6342647.3,6380624.9,6361607.7,6014641.7,6.7792098,2157054.2,104975.3,0.34487154,0.14977581,1185581,13495749.1
-20,6343001.1,6380743.5,6361844.3,5995937.6,6.7778571,2212405.8,104648.9,0.35408863,0.15377874,1217267,13828153.4
-20.5,6343362.3,6380864.6,6362085.8,5976778.4,6.7764672,2267760.5,104314.5,0.36333539,0.15779455,1249055,14159528.6
-21,6343730.9,6380988.2,6362332.3,5957165.7,6.7750397,2323118.4,103972.2,0.37261272,0.16182365,1280948,14489849.6
-21.5,6344106.7,6381114.2,6362583.6,5937100.8,6.7735744,2378479.5,103622,0.38192155,0.16586642,1312950,14819091.6
-22,6344489.7,6381242.6,6362839.6,5916585.1,6.7720711,2433844,103263.9,0.3912628,0.16992327,1345062,15147230.1
-22.5,6344879.7,6381373.4,6363100.4,5895620.2,6.7705295,2489211.8,102898,0.40063743,0.17399462,1377290,15474240.1
-23,6345276.6,6381506.4,6363365.7,5874207.6,6.7689493,2544583,102524.3,0.4100464,0.17808089,1409636,15800097.2
-23.5,6345680.3,6381641.8,6363635.6,5852348.9,6.7673302,2599957.8,102142.8,0.41949068,0.18218249,1442103,16124776.7
-24,6346090.7,6381779.3,6363910,5830045.5,6.7656719,2655336.1,101753.5,0.42897127,0.18629985,1474695,16448254.3
-24.5,6346507.6,6381919.1,6364188.7,5807299.2,6.7639742,2710718,101356.5,0.43848918,0.19043343,1507415,16770505.4
-25,6346930.9,6382061,6364471.7,5784111.5,6.7622367,2766103.6,100951.8,0.44804545,0.19458367,1540267,17091505.9
-25.5,6347360.6,6382205,6364758.9,5760484.3,6.760459,2821492.8,100539.4,0.45764111,0.19875101,1573254,17411231.4
-26,6347796.3,6382351,6365050.2,5736419.1,6.7586409,2876885.9,100119.4,0.46727724,0.20293592,1606381,17729657.8
-26.5,6348238.2,6382499.1,6365345.6,5711917.8,6.7567819,2932282.8,99691.8,0.47695491,0.20713888,1639650,18046760.9
-27,6348685.9,6382649.1,6365644.9,5686982,6.7548819,2987683.6,99256.6,0.48667524,0.21136037,1673066,18362516.9
-27.5,6349139.4,6382801.1,6365948,5661613.7,6.7529402,3043088.3,98813.8,0.49643934,0.21560087,1706633,18676901.7
-28,6349598.5,6382955,6366254.9,5635814.7,6.7509567,3098497,98363.5,0.50624838,0.21986088,1740354,18989891.5
-28.5,6350063.2,6383110.6,6366565.5,5609586.9,6.7489309,3153909.7,97905.8,0.51610351,0.22414091,1774233,19301462.6
-29,6350533.1,6383268.1,6366879.6,5582932.1,6.7468623,3209326.5,97440.5,0.52600594,0.22844148,1808275,19611591.4
-29.5,6351008.3,6383427.3,6367197.2,5555852.3,6.7447507,3264747.5,96967.9,0.53595688,0.23276312,1842484,19920254.2
-30,6351488.6,6383588.2,6367518.2,5528349.6,6.7425955,3320172.6,96487.9,0.54595758,0.23710636,1876864,20227427.6
-30.5,6351973.8,6383750.8,6367842.4,5500425.8,6.7403963,3375601.9,96000.5,0.5560093,0.24147177,1911419,20533088.2
-31,6352463.7,6383914.9,6368169.9,5472083.1,6.7381527,3431035.4,95505.9,0.56611334,0.2458599,1946154,20837212.8
-31.5,6352958.3,6384080.6,6368500.4,5443323.5,6.7358641,3486473.3,95003.9,0.57627102,0.25027132,1981074,21139778
-32,6353457.4,6384247.7,6368834,5414149.1,6.7335302,3541915.5,94494.7,0.58648371,0.25470664,2016182,21440761
-32.5,6353960.8,6384416.4,6369170.4,5384562.1,6.7311504,3597362.1,93978.3,0.59675278,0.25916644,2051485,21740138.6
-33,6354468.4,6384586.4,6369509.6,5354564.7,6.7287242,3652813,93454.8,0.60707964,0.26365134,2086986,22037888
-33.5,6354980,6384757.7,6369851.5,5324158.9,6.726251,3708268.5,92924.1,0.61746576,0.26816197,2122691,22333986.5
-34,6355495.5,6384930.3,6370195.9,5293347.2,6.7237304,3763728.4,92386.3,0.6279126,0.27269898,2158605,22628411.3
-34.5,6356014.7,6385104.2,6370542.9,5262131.6,6.7211617,3819192.8,91841.5,0.63842169,0.27726302,2194732,22921139.9
-35,6356537.5,6385279.3,6370892.2,5230514.6,6.7185444,3874661.8,91289.7,0.64899458,0.28185476,2231079,23212149.9
-35.5,6357063.7,6385455.4,6371243.8,5198498.4,6.7158779,3930135.3,90730.9,0.65963286,0.28647491,2267651,23501418.9
-36,6357593.1,6385632.7,6371597.5,5166085.4,6.7131616,3985613.5,90165.2,0.67033816,0.29112416,2304453,23788924.7
-36.5,6358125.6,6385811,6371953.3,5133278,6.7103948,4041096.3,89592.6,0.68111215,0.29580325,2341491,24074645.2
-37,6358661.1,6385990.2,6372311,5100078.6,6.7075769,4096583.7,89013.2,0.69195655,0.30051291,2378771,24358558.4
-37.5,6359199.3,6386170.4,6372670.6,5066489.6,6.7047072,4152075.9,88426.9,0.70287311,0.30525391,2416300,24640642.5
-38,6359740.1,6386351.4,6373031.9,5032513.6,6.701785,4207572.7,87833.9,0.71386364,0.31002704,2454082,24920875.6
-38.5,6360283.3,6386533.3,6373394.8,4998153,6.6988095,4263074.3,87234.2,0.72492999,0.31483309,2492126,25199236.2
-39,6360828.8,6386715.8,6373759.2,4963410.4,6.6957802,4318580.6,86627.9,0.73607406,0.3196729,2530436,25475702.9
-39.5,6361376.4,6386899.1,6374125,4928288.4,6.6926961,4374091.7,86014.9,0.74729781,0.32454731,2569021,25750254.1
-40,6361926,6387083,6374492.1,4892789.5,6.6895565,4429607.6,85395.3,0.75860325,0.3294572,2607886,26022868.7
-40.5,6362477.3,6387267.5,6374860.3,4856916.3,6.6863606,4485128.2,84769.2,0.76999243,0.33440346,2647039,26293525.6
-41,6363030.2,6387452.5,6375229.7,4820671.6,6.6831075,4540653.7,84136.6,0.78146748,0.33938701,2686487,26562203.7
-41.5,6363584.6,6387638,6375600,4784058,6.6797964,4596184.1,83497.6,0.79303058,0.3444088,2726238,26828882.3
-42,6364140.2,6387823.9,6375971.1,4747078.3,6.6764264,4651719.3,82852.1,0.80468399,0.34946981,2766300,27093540.7
-42.5,6364696.9,6388010.2,6376342.9,4709735.1,6.6729965,4707259.3,82200.4,0.81643001,0.35457105,2806680,27356158.2
-43,6365254.6,6388196.8,6376715.4,4672031.4,6.6695057,4762804.2,81542.3,0.82827103,0.35971354,2847386,27616714.4
-43.5,6365813,6388383.6,6377088.3,4633969.7,6.6659532,4818353.9,80878,0.8402095,0.36489835,2888428,27875189.1
-44,6366372.1,6388570.6,6377461.7,4595553.1,6.6623378,4873908.6,80207.5,0.85224796,0.37012658,2929813,28131562.1
-44.5,6366931.5,6388757.7,6377835.3,4556784.3,6.6586585,4929468.1,79530.9,0.86438901,0.37539938,2971551,28385813.5
-45,6367491.2,6388944.9,6378209,4517666.3,6.6549141,4985032.5,78848.2,0.87663535,0.38071789,3013650,28637923.3
-45.5,6368051,6389132.1,6378582.9,4478201.9,6.6511037,5040601.8,78159.4,0.88898975,0.38608334,3056122,28887871.9
-46,6368610.7,6389319.3,6378956.6,4438394.1,6.6472259,5096176,77464.6,0.90145509,0.39149697,3098974,29135639.6
-46.5,6369170.1,6389506.4,6379330.1,4398245.9,6.6432795,5151755,76763.9,0.91403432,0.39696006,3142219,29381207.2
-47,6369729.1,6389693.3,6379703.4,4357760.4,6.6392633,5207339,76057.3,0.92673052,0.40247395,3185865,29624555.4
-63,6386389.6,6395259.3,6390822.9,2903387,6.4629049,6988506.8,50673.7,1.42081379,0.61705158,4884398,36133477.6
-63.5,6386841.8,6395410.3,6391124.6,2853618.1,6.4553958,7044240.5,49805,1.44017621,0.62546058,4950961,36293908.3
-47.5,6370287.5,6389880,6380076.3,4316940.4,6.635176,5262927.8,75344.8,0.93954684,0.40804001,3229924,29865665.1
-48,6370845.2,6390066.5,6380448.6,4275789,6.6310163,5318521.5,74626.6,0.95248656,0.41365965,3274408,30104517.4
-48.5,6371401.9,6390252.6,6380820.3,4234309.5,6.6267826,5374120,73902.6,0.96555306,0.41933437,3319327,30341093.4
-49,6371957.5,6390438.3,6381191.2,4192504.8,6.6224736,5429723.4,73173,0.97874987,0.42506566,3364694,30575374.6
-49.5,6372511.8,6390623.6,6381561.3,4150378,6.6180877,5485331.6,72437.8,0.9920806,0.43085513,3410522,30807342.6
-50,6373064.6,6390808.4,6381930.3,4107932.5,6.6136233,5540944.7,71696.9,1.00554902,0.43670439,3456823,31036979.1
-50.5,6373615.8,6390992.7,6382298.3,4065171.2,6.6090788,5596562.6,70950.6,1.01915904,0.44261514,3503611,31264265.9
-51,6374165.3,6391176.3,6382665.1,4022097.6,6.6044526,5652185.3,70198.8,1.0329147,0.44858915,3550899,31489185.1
-51.5,6374712.8,6391359.3,6383030.6,3978714.7,6.5997428,5707812.8,69441.7,1.0468202,0.45462824,3598703,31711719
-52,6375258.1,6391541.5,6383394.6,3935025.9,6.5949476,5763445,68679.2,1.06087991,0.46073429,3647037,31931850
-52.5,6375801.2,6391723,6383757.2,3891034.4,6.5900651,5819082,67911.4,1.07509837,0.46690929,3695916,32149560.6
-53,6376341.8,6391903.7,6384118,3846743.7,6.5850932,5874723.7,67138.3,1.08948027,0.47315527,3745357,32364833.7
-53.5,6376879.8,6392083.4,6384477.1,3802156.9,6.58003,5930370.2,66360.2,1.10403052,0.47947436,3795377,32577652
-54,6377415,6392262.3,6384834.3,3757277.5,6.5748733,5986021.3,65576.9,1.11875421,0.48586878,3845994,32787998.8
-54.5,6377947.3,6392440.1,6385189.6,3712108.9,6.5696207,6041677.1,64788.5,1.13365667,0.49234083,3897225,32995857.4
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+77,6396426.9,6398608,6397517.4,1439373.6,6.1581735,8550341.5,25121.8,2.16558612,0.9405021,7444737,39541776.1,7444.737
+77.5,6396669.7,6398689,6397679.3,1384929.8,6.1414278,8606161.9,24171.6,2.20511939,0.95767118,7580642,39620603.5,7580.642
+78,6396903.6,6398767,6397835.2,1330378.5,6.1239752,8661984.4,23219.5,2.24624154,0.9755303,7722010,39696391.7,7722.010
+78.5,6397128.6,6398842,6397985.2,1275723.9,6.1057567,8717808.9,22265.6,2.28908893,0.99413869,7869308,39769134.3,7869.308
+79,6397344.4,6398913.9,6398129.1,1220970.3,6.0867051,8773635.3,21310,2.33381609,1.01356345,8023069,39838825.5,8023.069
+80,6397748.8,6399048.8,6398398.7,1111183.2,6.0457856,8885293.6,19393.8,2.42964003,1.05517925,8352487,39969030.9,8352.487
+80.5,6397937.1,6399111.5,6398524.3,1056158,6.0237289,8941125.4,18433.4,2.48117171,1.07755918,8529640,40029534.5,8529.640
+79.5,6397551.2,6398982.9,6398267,1166122,6.066744,8829463.6,20352.7,2.38059915,1.03388107,8183897,39905459.5,8183.897
+81,6398116.2,6399171.2,6398643.7,1001050.9,6.0004562,8996958.7,17471.6,2.535465,1.10113845,8716287,40086965.3,8716.287
+81.5,6398285.8,6399227.8,6398756.8,945866.1,5.9758297,9052793.5,16508.5,2.59283719,1.12605488,8913518,40141318.5,8913.518
+82,6398446.1,6399281.2,6398863.7,890607.8,5.9496865,9108629.8,15544,2.65366331,1.15247133,9122623,40192589.8,9122.623
+82.5,6398596.9,6399331.5,6398964.2,835280.4,5.9218323,9164467.5,14578.4,2.71839106,1.18058223,9345140,40240774.8,9345.140
+83,6398738.2,6399378.6,6399058.4,779888.1,5.8920323,9220306.4,13611.6,2.78756089,1.21062231,9582929,40285869.8,9582.929
+83.5,6398870,6399422.5,6399146.2,724435.2,5.8599995,9276146.5,12643.8,2.86183358,1.24287853,9838259,40327870.8,9838.259
+84,6398992.1,6399463.3,6399227.7,668926.1,5.8253781,9331987.7,11675,2.94202876,1.27770685,10113950,40366774.5,10113.950
+84.5,6399104.6,6399500.8,6399302.7,613365,5.787719,9387830,10705.2,3.02918039,1.31555632,10413555,40402577.8,10413.555
+85,6399207.5,6399535,6399371.3,557756.2,5.7464444,9443673.1,9734.7,3.12461859,1.3570046,10741648,40435277.5,10741.648
+85.5,6399300.7,6399566.1,6399433.4,502104.2,5.7007938,9499517.2,8763.4,3.23009491,1.40281239,11104248,40464871.2,11104.248
+86,6399384.1,6399593.9,6399489,446413.1,5.6497369,9555362,7791.4,3.34798154,1.4540099,11509513,40491356.2,11509.513
+86.5,6399457.8,6399618.5,6399538.1,390687.4,5.5918294,9611207.5,6818.8,3.48160433,1.51204154,11968874,40514730.5,11968.874
+87,6399521.7,6399639.8,6399580.7,334931.3,5.5249557,9667053.6,5845.7,3.63583421,1.57902273,12499077,40534992.1,12499.077
+87.5,6399575.8,6399657.8,6399616.8,279149.2,5.4458363,9722900.2,4872.1,3.81822278,1.65823308,13126083,40552139.4,13126.083
+88,6399620,6399672.6,6399646.3,223345.3,5.3489769,9778747.2,3898.1,4.04142115,1.7551669,13893383,40566170.9,13893.383
+88.5,6399654.5,6399684.1,6399669.3,167524.2,5.2240775,9834594.6,2923.8,4.32914586,1.88012415,14882507,40577085.4,14882.507
+89,6399679.1,6399692.3,6399685.7,111690,5.0480144,9890442.2,1949.4,4.73464143,2.05622864,16276498,40584882.2,16276.498
+89.5,6399693.9,6399697.2,6399695.5,55847.2,4.7470013,9946290,974.7,5.42780692,2.35726659,18659426,40589560.5,18659.426
+90,6399698.8,6399698.8,6399698.8,0,inf,10002137.9,0,inf,inf,inf,40591120,inf
diff --git a/III/Ovodas/task1.py b/III/Ovodas/task1.py
index 815af8b..78ce5e4 100755
--- a/III/Ovodas/task1.py
+++ b/III/Ovodas/task1.py
@@ -1,9 +1,15 @@
 #!/usr/bin/python3
 
-from math import sin, cos, sqrt, e, log, radians, pi, degrees
+from math import sin, cos, sqrt, e, log, radians, degrees
+
+
+def sinq(x):
+    return sin(x)**2
+
+
+def sqr(x):
+    return x**2
 
-sinq = lambda x: sin(x)**2
-sqr = lambda x: x**2
 
 # duota
 B = radians(13)
@@ -35,7 +41,7 @@ r = N * cos(B)
 # Lygiagretės lanko ilgis metrais
 Sn = r/degrees(1)
 
-## Trapecijos plotas esant 1 radiano platumai
+# Trapecijos plotas esant 1 radiano platumai
 P = sqr(b)/2 * ( sin(B)/(1-e2*sinq(B)) + 1/(2*e)*log( (1+e*sin(B))/(1-e*sin(B)) ) )
 
 g = globals()
diff --git a/III/Ovodas/task2_1.py b/III/Ovodas/task2_1.py
index 9c0dea1..14d52cb 100755
--- a/III/Ovodas/task2_1.py
+++ b/III/Ovodas/task2_1.py
@@ -1,62 +1,118 @@
 #!/usr/bin/python3
 
+import sys
 import csv
-from math import degrees, radians, tan, pi, log
+
+from math import radians, degrees, tan, atan, pi, log, sin, cos
 from shapely.geometry import LineString
 import matplotlib.pyplot as plt
 
-phi_p, phi_s, dphi = 13, 49, 6
-lambda_v, lambda_r, dlambda = 0, 24, 6
-M = 25e6
+from consts import (
+        phi_p, phi_s, dphi,
+        phi_1, phi_2,
+        lambda_1, lambda_2, lambda_range,
+        lambda_v, lambda_r, dlambda,
+        M
+)
+
+
+def c(x):
+    return "{}°".format(x)
+
+
+def annotate(ax, text, point, heading):
+    ax.annotate(text, point, textcoords="offset points", xytext=heading)
+
+
+def ctg(x):
+    return cos(x)/sin(x)
+
+
+def arccot(x):
+    return atan(1/x)
+
+
+def cosec(x):
+    return 1/sin(x)
+
+
+rphi_1, rphi_2 = radians(phi_1), radians(phi_2)
+rlambda_1, rlambda_2 = radians(lambda_1), radians(lambda_2)
 phil = round((phi_p+phi_s)/2)
 nphi = int((phi_s-phi_p)/dphi)+1
 nlambda = int((lambda_r-lambda_v)/dlambda)+1
 
 # label orientations
 W, E, N, S = (-25, -5), (10, -5), (-5, 10), (-5, -20)
+SW, NE = (-10, -10), (5, 5)
 
-krasovskio = {}
+kr = {}
 with open("krasovskio.csv") as f:
     for row in csv.DictReader(f):
-        krasovskio[float(row['phi'])] = row
-betamm = float(krasovskio[phil]["r"]) * 1000 / M
+        kr[float(row['phi'])] = row
+betamm = float(kr[phil]["r"]) * 1000 / M
+
+
+def yx(lat, lon):
+    # lat - phi in degrees
+    # lon - lambda in degrees
+    phi = radians(lat)
+    U = tan(pi/4 + phi/2)
+    xmm = betamm * log(U)
+    ymm = betamm * radians(lon)
+    return (ymm, xmm)
+
 
 points = []
 for i in range(nphi):
     phid = phi_p + i*dphi
-    phi = radians(phid)
-    U = tan(pi/4 + phi/2)
-    xmm = betamm * log(U)
     on_y = []
     for j in range(nlambda):
         lambdad = lambda_v + j*dlambda
-        ymm = betamm * lambdad / degrees(1)
-        on_y.append((ymm, xmm))
-    points.append(on_y)
+        on_y.append(yx(phid, lambdad))
+    points.append(sorted(on_y))
+
 
 fig, ax = plt.subplots()
 ax.set_aspect('equal')
 ax.axis("off")
 
 
-def annotate(ax, nr, point, heading):
-    text = "{}°".format(nr)
-    ax.annotate(text, point, textcoords="offset points", xytext=heading)
-
-
 # abscises
 for i in range(nphi):
     row = [points[i][j] for j in range(nlambda)]
     ax.plot(*(LineString(row).xy), color="xkcd:black", linewidth=.5)
-    annotate(ax, phi_p+i*dphi, row[0], W)
-    annotate(ax, phi_p+i*dphi, row[-1], E)
+    annotate(ax, c(phi_p+i*dphi), row[0], W)
+    annotate(ax, c(phi_p+i*dphi), row[-1], E)
 
 # ordinates
 for i in range(nlambda):
     col = [points[j][i] for j in range(nphi)]
     ax.plot(*(LineString(col).xy), color="xkcd:black", linewidth=.5)
-    annotate(ax, lambda_v+i*dlambda, col[0], S)
-    annotate(ax, lambda_v+i*dlambda, col[-1], N)
+    annotate(ax, c(lambda_v+i*dlambda), col[0], S)
+    annotate(ax, c(lambda_v+i*dlambda), col[-1], N)
+
+# loksodroma
+A = yx(phi_1, lambda_1)
+B = yx(phi_2, lambda_2)
+loksodroma = ((A, B))
+ax.plot(*(LineString(loksodroma).xy), color="xkcd:black", linewidth=.5)
+
+# ortodroma
+ctgu = ctg(rphi_1)*tan(rphi_2)*cosec(rlambda_2-rlambda_1)-ctg(rlambda_2-rlambda_1)
+u = arccot(ctgu)
+ortodroma = []
+for lambdad in lambda_range:
+    phi_ort = atan(tan(rphi_1)*cosec(u)*sin(u-rlambda_1+radians(lambdad)))
+    ortodroma.append(yx(round(degrees(phi_ort)*2)/2, lambdad))
+ax.plot(*(LineString(ortodroma).xy), color="xkcd:black", linewidth=.5)
+
+annotate(ax, "A", A, SW)
+annotate(ax, "B", B, NE)
 
 if __name__ == '__main__':
-    plt.show()
+    if len(sys.argv) == 2:
+        plt.savefig(sys.argv[1], bbox_inches='tight')
+        print("Saved %s" % sys.argv[1])
+    else:
+        plt.show()
diff --git a/III/Ovodas/task2_2.py b/III/Ovodas/task2_2.py
new file mode 100755
index 0000000..b352b69
--- /dev/null
+++ b/III/Ovodas/task2_2.py
@@ -0,0 +1,139 @@
+#!/usr/bin/python3
+
+import sys
+import csv
+from math import radians, degrees, tan, atan, sin, cos
+
+from shapely.geometry import LineString
+import matplotlib.pyplot as plt
+
+from consts import (
+        phi_p, phi_s, dphi,
+        phi_1, phi_2,
+        lambda_1, lambda_2, lambda_range,
+        lambda_v, lambda_r, dlambda,
+        M
+)
+
+
+def c(x):
+    return "{}°".format(x)
+
+
+def annotate(ax, text, point, heading):
+    ax.annotate(text, point, textcoords="offset points", xytext=heading)
+
+
+def ctg(x):
+    return cos(x)/sin(x)
+
+
+def arccot(x):
+    return atan(1/x)
+
+
+def cosec(x):
+    return 1/sin(x)
+
+
+phi_loks = 27.308  # loksodromos platuma 12 ilgumoje interpoliavus
+
+rphi_1, rphi_2 = radians(phi_1), radians(phi_2)
+rlambda_1, rlambda_2 = radians(lambda_1), radians(lambda_2)
+phil = round((phi_p+phi_s)/2)
+nphi = int((phi_s-phi_p)/dphi)+1
+nlambda = int((lambda_r-lambda_v)/dlambda)+1
+midlambda = int(lambda_r+lambda_v)/2
+midnlambda = int((lambda_r-midlambda)/dlambda)+1
+
+# label orientations
+W, E, N, S = (-25, -5), (10, -5), (-5, 10), (-5, -20)
+SW, NE = (-10, -10), (5, 5)
+
+kr = {}
+with open("krasovskio.csv") as f:
+    for row in csv.DictReader(f):
+        kr[float(row['phi'])] = {k: float(v) for k, v in row.items()}
+
+alpha = (kr[phi_1]["lgr"]-kr[phi_2]["lgr"])/(kr[phi_2]["lgU"]-kr[phi_1]["lgU"])
+Ualpha = (10**kr[phi_p]["lgU"])**alpha
+U1alpha = (10**kr[phi_1]["lgU"])**alpha
+U2alpha = (10**kr[phi_2]["lgU"])**alpha
+C1 = (kr[phi_1]["r"]*U1alpha)/alpha
+C2 = (kr[phi_2]["r"]*U2alpha)/alpha
+if abs(C1 - C2) / C1 > 1e-6:
+    raise ValueError("too large error between C1 and C2")
+Cmm = C1 * 1000 / M
+qmm = Cmm/Ualpha
+
+
+def yx(lat, lon):
+    # lat - phi in degrees
+    # lon - lambda in degrees
+    lgU = kr[round(lat*2)/2.]["lgU"]
+    Ualpha = (10**lgU)**alpha
+    pmm = Cmm/Ualpha
+    delta = alpha * lon
+    xmm = qmm-pmm*cos(radians(delta))
+    ymm = pmm*sin(radians(delta))
+    return (ymm, xmm)
+
+
+points = []
+for i in range(nphi):
+    phid = phi_p + i*dphi
+    on_y = []
+    for j in range(midnlambda):
+        lambdad = j*dlambda
+        ymm, xmm = yx(phid, lambdad)
+        on_y.append((ymm, xmm))
+        if j > 0:
+            on_y.append((-ymm, xmm))
+    points.append(sorted(on_y))
+
+
+fig, ax = plt.subplots()
+ax.set_aspect('equal')
+ax.axis("off")
+
+
+# abscises
+for i in range(nphi):
+    row = [points[i][j] for j in range(nlambda)]
+    ax.plot(*(LineString(row).xy), color="xkcd:black", linewidth=.5)
+    annotate(ax, c(phi_p+i*dphi), row[0], W)
+    annotate(ax, c(phi_p+i*dphi), row[-1], E)
+
+# ordinates
+for i in range(nlambda):
+    col = [points[j][i] for j in range(nphi)]
+    ax.plot(*(LineString(col).xy), color="xkcd:black", linewidth=.5)
+    annotate(ax, c(lambda_v+i*dlambda), col[0], S)
+    annotate(ax, c(lambda_v+i*dlambda), col[-1], N)
+
+# loksodroma
+rmidlambda = radians(midlambda)
+A = yx(phi_1, lambda_1-midlambda)
+MidLoks = yx(phi_loks, 0)
+B = yx(phi_2, lambda_2-midlambda)
+loksodroma = ((A, MidLoks, B))
+ax.plot(*(LineString(loksodroma).xy), color="xkcd:black", linewidth=.5)
+
+# ortodroma
+ctgu = ctg(rphi_1)*tan(rphi_2)*cosec(rlambda_2-rlambda_1)-ctg(rlambda_2-rlambda_1)
+u = arccot(ctgu)
+ortodroma = []
+for lambdad in lambda_range:
+    phi_ort = atan(tan(rphi_1)*cosec(u)*sin(u-rlambda_1+radians(lambdad)))
+    ortodroma.append(yx(round(degrees(phi_ort)*2)/2, lambdad-midlambda))
+ax.plot(*(LineString(ortodroma).xy), color="xkcd:black", linewidth=.5)
+
+annotate(ax, "A", A, SW)
+annotate(ax, "B", B, NE)
+
+if __name__ == '__main__':
+    if len(sys.argv) == 2:
+        plt.savefig(sys.argv[1], bbox_inches='tight')
+        print("Saved %s" % sys.argv[1])
+    else:
+        plt.show()
diff --git a/III/Ovodas/task2_4.py b/III/Ovodas/task2_4.py
new file mode 100755
index 0000000..fb24b82
--- /dev/null
+++ b/III/Ovodas/task2_4.py
@@ -0,0 +1,40 @@
+#!/usr/bin/python3
+
+import csv
+from math import sin, cos, acos, radians, degrees, atan
+
+from consts import phi_1, lambda_1, phi_2, lambda_2
+
+
+# krasovskio
+kr = {}
+with open("krasovskio.csv") as f:
+    for row in csv.DictReader(f):
+        kr[float(row['phi'])] = {k: float(v) for k, v in row.items()}
+
+
+def sec(x):
+    return 1/cos(x)
+
+
+# konstantos/radianai
+midphi = (phi_1+phi_2)/2
+rphi_1, rphi_2 = radians(phi_1), radians(phi_2)
+rlambda_1, rlambda_2 = radians(lambda_1), radians(lambda_2)
+
+# ortodroma
+rdelta = acos(sin(rphi_1)*sin(rphi_2) + cos(rphi_1)*cos(rphi_2)*cos(rlambda_2-rlambda_1))
+delta = degrees(rdelta)
+R = 6366255.58  # rutulio spindulys iš pavyzdžio
+ortodromos_ilgis = rdelta * R
+
+# loksodroma
+D_1 = kr[phi_1]["D"]
+D_2 = kr[phi_2]["D"]
+ralpha_loks = atan(60*(lambda_2 - lambda_1) / (D_2 - D_1))
+
+loksodromos_ilgis = (rphi_2 - rphi_1) * kr[midphi]["R"] * sec(ralpha_loks)
+
+if __name__ == '__main__':
+    print("Ortodromos ilgis (m): %d" % round(ortodromos_ilgis))
+    print("Loksodromos ilgis (m): %d" % round(loksodromos_ilgis))
diff --git a/III/Ovodas/task2_5.py b/III/Ovodas/task2_5.py
new file mode 100755
index 0000000..73e6912
--- /dev/null
+++ b/III/Ovodas/task2_5.py
@@ -0,0 +1,71 @@
+#!/usr/bin/python3
+
+from shapely.geometry import LineString, box
+
+from task2_1 import (
+        loksodroma as cilindr_loksodroma,
+        ortodroma as cilindr_ortodroma,
+        yx as cilindr_yx
+)
+from task2_2 import (
+        loksodroma as kugine_loksodroma,
+        ortodroma as kugine_ortodroma
+)
+from task2_4 import loksodromos_ilgis, ortodromos_ilgis
+from consts import M, maxlambda
+
+# mastelių koeficientų lentelė
+mLentele = (
+    ((10, 16), 0.897),
+    ((16, 22), 0.919),
+    ((22, 28), 0.952),
+    ((28, 34), 1.000),
+    ((34, 40), 1.065),
+    ((40, 46), 1.152),
+    ((46, 52), 1.270),
+)
+
+# Kūginė projekcija: loksodroma
+apsk_kugine_loksodroma = LineString(kugine_loksodroma).length * M / 1000
+proc_kugine_loksodroma = 100*(loksodromos_ilgis-apsk_kugine_loksodroma)/loksodromos_ilgis
+# Kūginė projekcija: ortodroma
+apsk_kugine_ortodroma = LineString(kugine_ortodroma).length * M / 1000
+proc_kugine_ortodroma = 100*(ortodromos_ilgis-apsk_kugine_ortodroma)/apsk_kugine_ortodroma
+
+
+# Merkatoriaus projekcija (cilindrinė)
+def apsk_cilindr(linija):
+    """Apskaičiuoti duotos linijos ilgį cilindrinėje projekcijoje.
+
+    Liniją padalina į dalis pagal mLentele koordinates, ir
+    sudeda kiekvieno segmento ilgį padauginus iš koeficiento.
+    """
+    ls = LineString(linija)
+    total = 0
+    for (phifrom, phito), coeff in mLentele:
+        # stačiakampis, apribojantis liniją
+        poly = box(*cilindr_yx(phifrom, 0), *cilindr_yx(phito, maxlambda))
+        # stačiakampio ir linijos sankirta -- gauname tik liniją, kurios ilgį
+        # reikia priskaičiuoti
+        subline = ls.intersection(poly)
+        # pridedame santykinį linijos ilgį prie sumos
+        total += subline.length * coeff
+    return total * M / 1000
+
+
+matav_cilindr_ortodroma = apsk_cilindr(cilindr_ortodroma)
+proc_cilindr_ortodroma = 100*(ortodromos_ilgis-matav_cilindr_ortodroma)/ortodromos_ilgis
+matav_cilindr_loksodroma = apsk_cilindr(cilindr_loksodroma)
+proc_cilindr_loksodroma = 100*(loksodromos_ilgis-matav_cilindr_loksodroma)/loksodromos_ilgis
+
+
+tpl = """Sferinės loksodromos ilgis (m): {loksodromos_ilgis:.0f}
+Sferinės ortodromos ilgis (m): {ortodromos_ilgis:.0f}
+
+Apskaičiuotas kūginės loksodromos ilgis (m):     {apsk_kugine_loksodroma:.0f}  paklaida: {proc_kugine_loksodroma:+.2f}%
+Apskaičiuotas kūginės ortodromos ilgis (m):      {apsk_kugine_ortodroma:.0f}  paklaida: {proc_kugine_ortodroma:+.2f}%
+Apskaičiuotas cilindrinės loksodromos ilgis (m): {matav_cilindr_loksodroma:.0f}  paklaida: {proc_cilindr_loksodroma:+.2f}%
+Apskaičiuotas cilindrinės ortodromos ilgis (m):  {matav_cilindr_ortodroma:.0f}  paklaida: {proc_cilindr_ortodroma:+.2f}%"""
+
+if __name__ == '__main__':
+    print(tpl.format(**dict(locals())))