You need to apply the same transformation to the x argument of panel.lines as
you are setting up for the panel.xyplot.
--
David
Sent from my iPhone
On Apr 10, 2013, at 8:10 PM, jpm miao <miao...@gmail.com> wrote:
> Hi David,
>
> Thanks. How can I make the graph in log scale?
>
> Thanks
>
> Miao
>
>
> 2013/4/11 David Winsemius <dwinsem...@comcast.net>
>>
>> On Apr 10, 2013, at 6:11 PM, jpm miao wrote:
>>
>>> Thanks for your comments, David
>>>
>>> avg_cost_2012 and asset_2012 are numeric vectors of length 39
>>>
>>> while x2 and y1 are longer vectors whose range is about the same as
>>> (avg_cost_2012, asset_2012)
>>>
>>> I also present the data by dput below. Is it clear? Thanks,
>>
>> I've named the first object xy and the second object y1x2
>>
>> xyplot( avg_cost_2012 ~ asset_2012, data=as.data.frame(xy),
>> panel=function(x,y) {
>> panel.xyplot(x,y, type="p")
>> panel.points( x=y1x2[,'x2'], y= y1x2[,'y1'], col="red")} )
>>
>>
>>
>> Throwing in the scales argument does make the points from panel.points
>> disappear.
>>
>>
>>>
>>> Miao
>>>
>>> asset_2012 avg_cost_2012
>>> 1 3973730.0 0.0032199310
>>> 2 2391575.8 0.0034866607
>>> 3 2840943.5 0.0051450067
>>> 4 2040943.0 0.0063589398
>>> 5 1982715.2 0.0062530448
>>> 6 1618162.2 0.0054400342
>>> 7 820082.2 0.0042134623
>>> 8 1658596.8 0.0048834145
>>> 9 1762794.0 0.0062155737
>>> 10 93439.5 0.0042552036
>>> 11 218481.2 0.0069238420
>>> 12 2332477.0 0.0048621108
>>> 13 725835.5 0.0008902909
>>> 14 811575.2 0.0129624864
>>> 15 292223.0 0.0026141820
>>> 16 153862.2 0.0075244299
>>> 17 1272367.2 0.0068988788
>>> 18 734199.0 0.0098799510
>>> 19 421404.5 0.0050479335
>>> 20 189047.5 0.0048211174
>>> 21 529102.0 0.0096373243
>>> 22 56833.0 0.0061710425
>>> 23 125856.2 0.0083900410
>>> 24 598893.8 0.0066222964
>>> 25 258240.0 0.0061297368
>>> 26 159086.2 0.0088192099
>>> 27 122863.0 0.0100925693
>>> 28 404699.5 0.0081477489
>>> 29 453514.5 0.0084070531
>>> 30 545028.0 0.0060956804
>>> 31 1233365.5 0.0061105819
>>> 32 1192758.2 0.0081616218
>>> 33 147563.2 0.0083796600
>>> 34 247293.0 0.0102826553
>>> 35 1074838.2 0.0074134232
>>> 36 459227.5 0.0086199724
>>> 37 202332.0 0.0090614422
>>> 38 377401.2 0.0069230414
>>> 39 1876752.5 0.0102260772
>>>
>>> x2 y1
>>> 1 50118.72 0.012116846
>>> 2 51286.14 0.012053508
>>> 3 52480.75 0.011990503
>>> 4 53703.18 0.011927830
>>> 5 54954.09 0.011865489
>>> 6 56234.13 0.011803480
>>> 7 57543.99 0.011741804
>>> 8 58884.37 0.011680460
>>> 9 60255.96 0.011619448
>>> 10 61659.50 0.011558769
>>> 11 63095.73 0.011498421
>>> 12 64565.42 0.011438406
>>> 13 66069.34 0.011378724
>>> 14 67608.30 0.011319373
>>> 15 69183.10 0.011260355
>>> 16 70794.58 0.011201669
>>> 17 72443.60 0.011143315
>>> 18 74131.02 0.011085294
>>> 19 75857.76 0.011027605
>>> 20 77624.71 0.010970248
>>> 21 79432.82 0.010913224
>>> 22 81283.05 0.010856531
>>> 23 83176.38 0.010800171
>>> 24 85113.80 0.010744143
>>> 25 87096.36 0.010688448
>>> 26 89125.09 0.010633085
>>> 27 91201.08 0.010578054
>>> 28 93325.43 0.010523355
>>> 29 95499.26 0.010468989
>>> 30 97723.72 0.010414954
>>> 31 100000.00 0.010361253
>>> 32 102329.30 0.010307883
>>> 33 104712.85 0.010254846
>>> 34 107151.93 0.010202140
>>> 35 109647.82 0.010149768
>>> 36 112201.85 0.010097727
>>> 37 114815.36 0.010046019
>>> 38 117489.76 0.009994643
>>> 39 120226.44 0.009943599
>>> 40 123026.88 0.009892888
>>> 41 125892.54 0.009842508
>>> 42 128824.96 0.009792461
>>> 43 131825.67 0.009742747
>>> 44 134896.29 0.009693364
>>> 45 138038.43 0.009644314
>>> 46 141253.75 0.009595596
>>> 47 144543.98 0.009547211
>>> 48 147910.84 0.009499157
>>> 49 151356.12 0.009451436
>>> 50 154881.66 0.009404047
>>> 51 158489.32 0.009356991
>>> 52 162181.01 0.009310267
>>> 53 165958.69 0.009263875
>>> 54 169824.37 0.009217815
>>> 55 173780.08 0.009172087
>>> 56 177827.94 0.009126692
>>> 57 181970.09 0.009081629
>>> 58 186208.71 0.009036899
>>> 59 190546.07 0.008992500
>>> 60 194984.46 0.008948434
>>> 61 199526.23 0.008904700
>>> 62 204173.79 0.008861299
>>> 63 208929.61 0.008818229
>>> 64 213796.21 0.008775492
>>> 65 218776.16 0.008733088
>>> 66 223872.11 0.008691015
>>> 67 229086.77 0.008649275
>>> 68 234422.88 0.008607867
>>> 69 239883.29 0.008566791
>>> 70 245470.89 0.008526048
>>> 71 251188.64 0.008485636
>>> 72 257039.58 0.008445558
>>> 73 263026.80 0.008405811
>>> 74 269153.48 0.008366396
>>> 75 275422.87 0.008327314
>>> 76 281838.29 0.008288565
>>> 77 288403.15 0.008250147
>>> 78 295120.92 0.008212062
>>> 79 301995.17 0.008174309
>>> 80 309029.54 0.008136888
>>> 81 316227.77 0.008099799
>>> 82 323593.66 0.008063043
>>> 83 331131.12 0.008026619
>>> 84 338844.16 0.007990528
>>> 85 346736.85 0.007954768
>>> 86 354813.39 0.007919341
>>> 87 363078.05 0.007884246
>>> 88 371535.23 0.007849483
>>> 89 380189.40 0.007815053
>>> 90 389045.14 0.007780955
>>> 91 398107.17 0.007747189
>>> 92 407380.28 0.007713756
>>> 93 416869.38 0.007680654
>>> 94 426579.52 0.007647885
>>> 95 436515.83 0.007615449
>>> 96 446683.59 0.007583344
>>> 97 457088.19 0.007551572
>>> 98 467735.14 0.007520132
>>> 99 478630.09 0.007489024
>>> 100 489778.82 0.007458249
>>> 101 501187.23 0.007427806
>>> 102 512861.38 0.007397695
>>> 103 524807.46 0.007367916
>>> 104 537031.80 0.007338470
>>> 105 549540.87 0.007309356
>>> 106 562341.33 0.007280574
>>> 107 575439.94 0.007252125
>>> 108 588843.66 0.007224007
>>> 109 602559.59 0.007196222
>>> 110 616595.00 0.007168770
>>> 111 630957.34 0.007141649
>>> 112 645654.23 0.007114861
>>> 113 660693.45 0.007088405
>>> 114 676082.98 0.007062281
>>> 115 691830.97 0.007036490
>>> 116 707945.78 0.007011031
>>> 117 724435.96 0.006985904
>>> 118 741310.24 0.006961109
>>> 119 758577.58 0.006936647
>>> 120 776247.12 0.006912517
>>> 121 794328.23 0.006888719
>>> 122 812830.52 0.006865254
>>> 123 831763.77 0.006842120
>>> 124 851138.04 0.006819320
>>> 125 870963.59 0.006796851
>>> 126 891250.94 0.006774714
>>> 127 912010.84 0.006752910
>>> 128 933254.30 0.006731438
>>> 129 954992.59 0.006710299
>>> 130 977237.22 0.006689491
>>> 131 1000000.00 0.006669016
>>> 132 1023292.99 0.006648873
>>> 133 1047128.55 0.006629063
>>> 134 1071519.31 0.006609585
>>> 135 1096478.20 0.006590438
>>> 136 1122018.45 0.006571625
>>> 137 1148153.62 0.006553143
>>> 138 1174897.55 0.006534994
>>> 139 1202264.43 0.006517177
>>> 140 1230268.77 0.006499692
>>> 141 1258925.41 0.006482540
>>> 142 1288249.55 0.006465720
>>> 143 1318256.74 0.006449232
>>> 144 1348962.88 0.006433076
>>> 145 1380384.26 0.006417253
>>> 146 1412537.54 0.006401762
>>> 147 1445439.77 0.006386603
>>> 148 1479108.39 0.006371777
>>> 149 1513561.25 0.006357282
>>> 150 1548816.62 0.006343120
>>> 151 1584893.19 0.006329291
>>> 152 1621810.10 0.006315793
>>> 153 1659586.91 0.006302628
>>> 154 1698243.65 0.006289795
>>> 155 1737800.83 0.006277294
>>> 156 1778279.41 0.006265126
>>> 157 1819700.86 0.006253290
>>> 158 1862087.14 0.006241786
>>> 159 1905460.72 0.006230614
>>> 160 1949844.60 0.006219775
>>> 161 1995262.31 0.006209268
>>> 162 2041737.94 0.006199093
>>> 163 2089296.13 0.006189251
>>> 164 2137962.09 0.006179740
>>> 165 2187761.62 0.006170562
>>> 166 2238721.14 0.006161717
>>> 167 2290867.65 0.006153203
>>> 168 2344228.82 0.006145022
>>> 169 2398832.92 0.006137173
>>> 170 2454708.92 0.006129656
>>> 171 2511886.43 0.006122472
>>> 172 2570395.78 0.006115620
>>> 173 2630267.99 0.006109100
>>> 174 2691534.80 0.006102913
>>> 175 2754228.70 0.006097057
>>> 176 2818382.93 0.006091534
>>> 177 2884031.50 0.006086343
>>> 178 2951209.23 0.006081485
>>> 179 3019951.72 0.006076959
>>> 180 3090295.43 0.006072765
>>> 181 3162277.66 0.006068903
>>> 182 3235936.57 0.006065374
>>> 183 3311311.21 0.006062176
>>> 184 3388441.56 0.006059311
>>> 185 3467368.50 0.006056779
>>> 186 3548133.89 0.006054579
>>> 187 3630780.55 0.006052710
>>> 188 3715352.29 0.006051175
>>> 189 3801893.96 0.006049971
>>> 190 3890451.45 0.006049100
>>> 191 3981071.71 0.006048561
>>> 192 4073802.78 0.006048354
>>> 193 4168693.83 0.006048480
>>> 194 4265795.19 0.006048937
>>> 195 4365158.32 0.006049727
>>> 196 4466835.92 0.006050850
>>> 197 4570881.90 0.006052304
>>> 198 4677351.41 0.006054091
>>> 199 4786300.92 0.006056210
>>> 200 4897788.19 0.006058662
>>> 201 5011872.34 0.006061445
>>>
>>> To use dput function to present the data
>>> > dput(cbind(avg_cost_2012, asset_2012))
>>> structure(c(0.00321993102627396, 0.00348666071050862, 0.00514500670171978,
>>> 0.00635893976088426, 0.00625304477271035, 0.00544003417356045,
>>> 0.00421346233925224, 0.00488341453548038, 0.00621557372817221,
>>> 0.00425520359585793, 0.00692384201718875, 0.00486211080732891,
>>> 0.00089029087751351, 0.0129624864137572, 0.00261418199497039,
>>> 0.00752442992607212, 0.00689887882046544, 0.00987995102314728,
>>> 0.00504793348921874, 0.00482111735730959, 0.00963732431899178,
>>> 0.00617104252791857, 0.0083900410469978, 0.00662229644462707,
>>> 0.00612973679503377, 0.00881920986708858, 0.0100925692602712,
>>> 0.0081477488720749, 0.00840705306981286, 0.00609568037628165,
>>> 0.0061105818615996, 0.00816162181738723, 0.00837965998751208,
>>> 0.0102826552802113, 0.0074134231730932, 0.00861997236733968,
>>> 0.00906144215028246, 0.00692304142052871, 0.0102260771876649,
>>> 3973730, 2391575.75, 2840943.5, 2040943, 1982715.25, 1618162.25,
>>> 820082.25, 1658596.75, 1762794, 93439.5, 218481.25, 2332477,
>>> 725835.5, 811575.25, 292223, 153862.25, 1272367.25, 734199, 421404.5,
>>> 189047.5, 529102, 56833, 125856.25, 598893.75, 258240, 159086.25,
>>> 122863, 404699.5, 453514.5, 545028, 1233365.5, 1192758.25, 147563.25,
>>> 247293, 1074838.25, 459227.5, 202332, 377401.25, 1876752.5), .Dim = c(39L,
>>> 2L), .Dimnames = list(NULL, c("avg_cost_2012", "asset_2012")))
>>>
>>> > dput(cbind(avg_cost_2012, asset_2012))
>>> structure(c(0.00321993102627396, 0.00348666071050862, 0.00514500670171978,
>>> 0.00635893976088426, 0.00625304477271035, 0.00544003417356045,
>>> 0.00421346233925224, 0.00488341453548038, 0.00621557372817221,
>>> 0.00425520359585793, 0.00692384201718875, 0.00486211080732891,
>>> 0.00089029087751351, 0.0129624864137572, 0.00261418199497039,
>>> 0.00752442992607212, 0.00689887882046544, 0.00987995102314728,
>>> 0.00504793348921874, 0.00482111735730959, 0.00963732431899178,
>>> 0.00617104252791857, 0.0083900410469978, 0.00662229644462707,
>>> 0.00612973679503377, 0.00881920986708858, 0.0100925692602712,
>>> 0.0081477488720749, 0.00840705306981286, 0.00609568037628165,
>>> 0.0061105818615996, 0.00816162181738723, 0.00837965998751208,
>>> 0.0102826552802113, 0.0074134231730932, 0.00861997236733968,
>>> 0.00906144215028246, 0.00692304142052871, 0.0102260771876649,
>>> 3973730, 2391575.75, 2840943.5, 2040943, 1982715.25, 1618162.25,
>>> 820082.25, 1658596.75, 1762794, 93439.5, 218481.25, 2332477,
>>> 725835.5, 811575.25, 292223, 153862.25, 1272367.25, 734199, 421404.5,
>>> 189047.5, 529102, 56833, 125856.25, 598893.75, 258240, 159086.25,
>>> 122863, 404699.5, 453514.5, 545028, 1233365.5, 1192758.25, 147563.25,
>>> 247293, 1074838.25, 459227.5, 202332, 377401.25, 1876752.5), .Dim = c(39L,
>>> 2L), .Dimnames = list(NULL, c("avg_cost_2012", "asset_2012")))
>>> > dput(cbind(y1,x2))
>>> structure(c(0.0121168460097573, 0.0120535083414464, 0.0119905029411228,
>>> 0.0119278298087863, 0.011865488944437, 0.0118034803480749, 0.0117418040197,
>>> 0.0116804599593122, 0.0116194481669117, 0.0115587686424983,
>>> 0.0114984213860722,
>>> 0.0114384063976332, 0.0113787236771814, 0.0113193732247168,
>>> 0.0112603550402394,
>>> 0.0112016691237491, 0.0111433154752461, 0.0110852940947302,
>>> 0.0110276049822015,
>>> 0.0109702481376601, 0.0109132235611057, 0.0108565312525386,
>>> 0.0108001712119587,
>>> 0.010744143439366, 0.0106884479347604, 0.010633084698142,
>>> 0.0105780537295108,
>>> 0.0105233550288669, 0.01046898859621, 0.0104149544315404,
>>> 0.010361252534858,
>>> 0.0103078829061627, 0.0102548455454547, 0.0102021404527338,
>>> 0.0101497676280001,
>>> 0.0100977270712536, 0.0100460187824943, 0.00999464276172216,
>>> 0.00994359900893722, 0.00989288752413946, 0.0098425083073289,
>>> 0.00979246135850551, 0.00974274667766932, 0.0096933642648203,
>>> 0.00964431411995847, 0.00959559624308384, 0.0095472106341964,
>>> 0.00949915729329613, 0.00945143622038305, 0.00940404741545717,
>>> 0.00935699087851848, 0.00931026660956695, 0.00926387460860262,
>>> 0.00921781487562548, 0.00917208741063551, 0.00912669221363276,
>>> 0.00908162928461716, 0.00903689862358877, 0.00899250023054757,
>>> 0.00894843410549355, 0.0089047002484267, 0.00886129865934705,
>>> 0.00881822933825459, 0.00877549228514933, 0.00873308750003123,
>>> 0.00869101498290033, 0.00864927473375661, 0.00860786675260009,
>>> 0.00856679103943074, 0.00852604759424859, 0.00848563641705362,
>>> 0.00844555750784583, 0.00840581086662524, 0.00836639649339183,
>>> 0.00832731438814562, 0.00828856455088657, 0.00825014698161472,
>>> 0.00821206168033005, 0.00817430864703257, 0.0081368878817223,
>>> 0.00809979938439918, 0.00806304315506327, 0.00802661919371454,
>>> 0.00799052750035301, 0.00795476807497865, 0.00791934091759149,
>>> 0.0078842460281915, 0.0078494834067787, 0.0078150530533531,
>>> 0.00778095496791469,
>>> 0.00774718915046345, 0.00771375560099939, 0.00768065431952253,
>>> 0.00764788530603284, 0.00761544856053037, 0.00758334408301507,
>>> 0.00755157187348694, 0.00752013193194602, 0.00748902425839228,
>>> 0.00745824885282571, 0.00742780571524633, 0.00739769484565418,
>>> 0.00736791624404916, 0.00733846991043136, 0.00730935584480073,
>>> 0.0072805740471573, 0.00725212451750105, 0.00722400725583199,
>>> 0.00719622226215011, 0.00716876953645541, 0.00714164907874794,
>>> 0.00711486088902762, 0.0070884049672945, 0.00706228131354857,
>>> 0.00703648992778981, 0.00701103081001822, 0.00698590396023384,
>>> 0.00696110937843665, 0.00693664706462666, 0.00691251701880381,
>>> 0.00688871924096819, 0.00686525373111974, 0.00684212048925849,
>>> 0.00681931951538441, 0.0067968508094975, 0.00677471437159781,
>>> 0.00675291020168529, 0.00673143829975996, 0.00671029866582183,
>>> 0.00668949129987087, 0.0066690162019071, 0.00664887337193053,
>>> 0.00662906280994112, 0.00660958451593892, 0.0065904384899239,
>>> 0.00657162473189606, 0.00655314324185539, 0.00653499401980194,
>>> 0.00651717706573567, 0.00649969237965659, 0.00648253996156468,
>>> 0.00646571981145995, 0.00644923192934242, 0.00643307631521209,
>>> 0.00641725296906895, 0.00640176189091297, 0.00638660308074418,
>>> 0.00637177653856259, 0.00635728226436819, 0.00634312025816097,
>>> 0.00632929051994092, 0.00631579304970808, 0.00630262784746244,
>>> 0.00628979491320396, 0.00627729424693267, 0.00626512584864858,
>>> 0.00625328971835167, 0.00624178585604192, 0.00623061426171939,
>>> 0.00621977493538403, 0.00620926787703585, 0.00619909308667488,
>>> 0.00618925056430109, 0.00617974030991447, 0.00617056232351507,
>>> 0.00616171660510281, 0.00615320315467778, 0.00614502197223991,
>>> 0.00613717305778924, 0.00612965641132575, 0.00612247203284944,
>>> 0.00611561992236033, 0.0061091000798584, 0.00610291250534367,
>>> 0.00609705719881611, 0.00609153416027573, 0.00608634338972257,
>>> 0.00608148488715655, 0.00607695865257775, 0.00607276468598614,
>>> 0.00606890298738169, 0.00606537355676445, 0.00606217639413439,
>>> 0.00605931149949152, 0.00605677887283583, 0.00605457851416734,
>>> 0.00605271042348603, 0.00605117460079189, 0.00604997104608494,
>>> 0.00604909975936518, 0.00604856074063263, 0.00604835398988726,
>>> 0.00604847950712906, 0.00604893729235803, 0.00604972734557423,
>>> 0.0060508496667776, 0.00605230425596814, 0.00605409111314588,
>>> 0.00605621023831082, 0.00605866163146293, 0.00606144529260223,
>>> 50118.7233627273, 51286.1383991365, 52480.7460249772, 53703.1796370253,
>>> 54954.0873857625, 56234.1325190349, 57543.9937337157, 58884.365535559,
>>> 60255.9586074358, 61659.5001861482, 63095.7344480193, 64565.4229034656,
>>> 66069.3448007596, 67608.2975391982, 69183.0970918936, 70794.5784384139,
>>> 72443.5960074991, 74131.0241300918, 75857.7575029184, 77624.7116628693,
>>> 79432.8234724282, 81283.05161641, 83176.3771102671, 85113.8038202378,
>>> 87096.3589956081, 89125.0938133746, 91201.083935591, 93325.4300796992,
>>> 95499.2586021437, 97723.7220955811, 1e+05, 102329.299228075,
>>> 104712.85480509, 107151.930523761, 109647.819614319, 112201.845430196,
>>> 114815.362149688, 117489.755493953, 120226.443461741, 123026.877081238,
>>> 125892.541179417, 128824.955169313, 131825.673855641, 134896.288259165,
>>> 138038.426460289, 141253.754462276, 144543.977074593, 147910.838816821,
>>> 151356.124843621, 154881.661891248, 158489.319246111, 162181.009735893,
>>> 165958.690743756, 169824.365246175, 173780.082874938, 177827.941003892,
>>> 181970.085860998, 186208.713666287, 190546.071796325, 194984.459975805,
>>> 199526.231496888, 204173.794466953, 208929.613085404, 213796.208950223,
>>> 218776.162394955, 223872.113856834, 229086.765276777, 234422.881531992,
>>> 239883.291901949, 245470.891568503, 251188.643150958, 257039.578276886,
>>> 263026.799189538, 269153.480392691, 275422.870333817, 281838.293126445,
>>> 288403.150312661, 295120.922666639, 301995.172040202, 309029.543251359,
>>> 316227.766016838, 323593.656929628, 331131.121482591, 338844.156139203,
>>> 346736.850452532, 354813.389233575, 363078.054770102, 371535.229097173,
>>> 380189.396320561, 389045.14499428, 398107.170553498, 407380.277804113,
>>> 416869.383470336, 426579.518801593, 436515.832240167, 446683.592150963,
>>> 457088.189614875, 467735.141287198, 478630.092322638, 489778.819368447,
>>> 501187.233627272, 512861.383991365, 524807.460249773, 537031.796370253,
>>> 549540.873857625, 562341.325190349, 575439.937337157, 588843.65535559,
>>> 602559.586074358, 616595.001861482, 630957.344480194, 645654.229034656,
>>> 660693.448007596, 676082.975391982, 691830.970918936, 707945.784384139,
>>> 724435.960074991, 741310.241300918, 758577.575029184, 776247.116628693,
>>> 794328.234724282, 812830.5161641, 831763.771102671, 851138.038202376,
>>> 870963.589956081, 891250.938133746, 912010.83935591, 933254.300796992,
>>> 954992.586021437, 977237.220955811, 1e+06, 1023292.99228075,
>>> 1047128.5480509, 1071519.30523761, 1096478.19614319, 1122018.45430197,
>>> 1148153.62149688, 1174897.55493953, 1202264.43461741, 1230268.77081238,
>>> 1258925.41179417, 1288249.55169313, 1318256.73855641, 1348962.88259165,
>>> 1380384.26460289, 1412537.54462276, 1445439.77074593, 1479108.38816821,
>>> 1513561.24843621, 1548816.61891248, 1584893.19246111, 1621810.09735893,
>>> 1659586.90743756, 1698243.65246175, 1737800.82874938, 1778279.41003892,
>>> 1819700.85860998, 1862087.13666287, 1905460.71796325, 1949844.59975805,
>>> 1995262.31496888, 2041737.94466953, 2089296.13085404, 2137962.08950223,
>>> 2187761.62394955, 2238721.13856834, 2290867.65276777, 2344228.81531992,
>>> 2398832.91901949, 2454708.91568503, 2511886.43150958, 2570395.78276886,
>>> 2630267.99189538, 2691534.80392691, 2754228.70333817, 2818382.93126445,
>>> 2884031.50312661, 2951209.22666639, 3019951.72040202, 3090295.43251359,
>>> 3162277.66016838, 3235936.56929628, 3311311.21482591, 3388441.56139203,
>>> 3467368.50452532, 3548133.89233576, 3630780.54770102, 3715352.29097173,
>>> 3801893.96320561, 3890451.4499428, 3981071.70553498, 4073802.77804113,
>>> 4168693.83470336, 4265795.18801593, 4365158.32240167, 4466835.92150963,
>>> 4570881.89614875, 4677351.41287198, 4786300.92322638, 4897788.19368447,
>>> 5011872.33627272), .Dim = c(201L, 2L), .Dimnames = list(NULL,
>>> c("y1", "x2")))
>>>
>>>
>>>
>>>
>>> 2013/4/11 David Winsemius <dwinsem...@comcast.net>
>>>>
>>>> On Apr 10, 2013, at 12:44 AM, jpm miao wrote:
>>>>
>>>>> Hi David,
>>>>>
>>>>> Many thanks. I try to follow your example and code as follows:
>>>>>
>>>>> xyplot( avg_cost_2012 ~ asset_2012,
>>>>> panel=function(x,y) {
>>>>> panel.xyplot(x,y, type="p")
>>>>> panel.lines(x2, y1, col="red")},scales=list(x=list(log=10)))
>>>>>
>>>>> However, I do see the points "p" of "avg_cost_2012 ~ asset_2012", but do
>>>>> not see the line for y1 against x2. y1 and x1 are numeric vectors of the
>>>>> same size. How can I fix it?
>>>>
>>>> Without seeing the data it is difficult to enumerate the possible errors
>>>> you could be making.
>>>>
>>>> I say again:
>>>>
>>>> Your example was not presented in a form that lent itself to easy editing.
>>>> Please learn to use dput to present data structures.
>>>>
>>>> -- David
>>>>
>>>>
>>>>
>>>>>
>>>>> Thnaks
>>>>>
>>>>> Miao
>>>>>
>>>>>
>>>>> 2013/4/10 David Winsemius <dwinsem...@comcast.net>
>>>>>
>>>>> On Apr 9, 2013, at 8:21 PM, jpm miao wrote:
>>>>>
>>>>> Thank you very much.
>>>>>
>>>>> Could it be done in Lattice package?
>>>>>
>>>>>
>>>>>
>>>>> Your example was not presented in a form that lent itself to easy
>>>>> editing. Please learn to use dput to present data structures:
>>>>>
>>>>> xyplot( 4:6 ~ 1:3,
>>>>> panel=function(x,y) {
>>>>> panel.xyplot(x,y, type="l")
>>>>> panel.points(x=c(1.1, 2.1), y=c(4.1, 5.1), col="red") } )
>>>>>
>>>>> --
>>>>> David.
>>>>>
>>>>>
>>>>> Thanks,
>>>>>
>>>>> Miao
>>>>>
>>>>>
>>>>> 2013/4/10 Janesh Devkota <janesh.devk...@gmail.com>
>>>>>
>>>>> Hi,
>>>>>
>>>>> This should be fairly easy by using base R graphics.
>>>>>
>>>>> Lets suppose your first data is represented by (x1,y1) and second data is
>>>>> represented by (x2,y2)
>>>>>
>>>>> You can use the following command.
>>>>> plot(x1,y1,type="l")
>>>>> points(x2,y2)
>>>>>
>>>>> Hope it helps.
>>>>>
>>>>>
>>>>> On Tue, Apr 9, 2013 at 8:24 PM, jpm miao <miao...@gmail.com> wrote:
>>>>>
>>>>> Hi,
>>>>>
>>>>> How can I plot two curves with distinct x and y vectors? I would like
>>>>> to
>>>>> join one of them by regular lines and plot the other just by points (no
>>>>> lines). Can it be done in regular R graphic tools, say "plot" function?
>>>>> Can it be done in Lattice package, say "xyplot" function?
>>>>>
>>>>> Thanks,
>>>>>
>>>>> Miao
>>>>>
>>>>> My data look like this: two curves with different vector size
>>>>>
>>>>> x y
>>>>> 3973730 0.00322 2391576 0.003487 2840944 0.005145 2040943 0.006359
>>>>> 1982715 0.006253 1618162 0.00544 820082.3 0.004213 1658597 0.004883
>>>>> 1762794 0.006216 93439.5 0.004255 218481.3 0.006924 2332477 0.004862
>>>>> 725835.5 0.00089 811575.3 0.012962 292223 0.002614 153862.3 0.007524
>>>>> 1272367 0.006899 734199 0.00988 421404.5 0.005048 189047.5 0.004821
>>>>> 529102 0.009637 56833 0.006171 125856.3 0.00839 598893.8 0.006622
>>>>> 258240
>>>>> 0.00613 159086.3 0.008819 122863 0.010093 404699.5 0.008148 453514.5
>>>>> 0.008407 545028 0.006096 1233366 0.006111 1192758 0.008162 147563.3
>>>>> 0.00838 247293 0.010283 1074838 0.007413 459227.5 0.00862 202332
>>>>> 0.009061 377401.3 0.006923 1876753 0.010226
>>>>> and
>>>>> x y
>>>>> 50118.72 0.012117 51286.14 0.012054 52480.75 0.011991 53703.18
>>>>> 0.011928
>>>>> 54954.09 0.011865 56234.13 0.011803 57543.99 0.011742 58884.37 0.01168
>>>>> 60255.96 0.011619 61659.5 0.011559 63095.73 0.011498 64565.42 0.011438
>>>>> 66069.34 0.011379 67608.3 0.011319 69183.1 0.01126
>>>>>
>>>>> [[alternative HTML version deleted]]
>>>>>
>>>>> ______________________________________________
>>>>> R-help@r-project.org mailing list
>>>>> https://stat.ethz.ch/mailman/listinfo/r-help
>>>>> PLEASE do read the posting guide
>>>>> http://www.R-project.org/posting-guide.html
>>>>> and provide commented, minimal, self-contained, reproducible code.
>>>>>
>>>>>
>>>>>
>>>>>
>>>>> [[alternative HTML version deleted]]
>>>>>
>>>>> ______________________________________________
>>>>> R-help@r-project.org mailing list
>>>>> https://stat.ethz.ch/mailman/listinfo/r-help
>>>>> PLEASE do read the posting guide
>>>>> http://www.R-project.org/posting-guide.html
>>>>> and provide commented, minimal, self-contained, reproducible code.
>>>>>
>>>>> David Winsemius, MD
>>>>> Alameda, CA, USA
>>>>
>>>> David Winsemius, MD
>>>> Alameda, CA, USA
>>
>> David Winsemius, MD
>> Alameda, CA, USA
>
[[alternative HTML version deleted]]
______________________________________________
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