In [19]:
library(spatstat)
library(sp)
In [2]:
px <- rnorm(500, mean=0.5, sd=0.15)
py <- rnorm(500, mean=0.5, sd=0.15)
print(px); print(py)
[1] 0.43972706 0.77715339 0.43844081 0.12349688 0.38516789 0.57288640
[7] 0.70632392 0.52287629 0.36686613 0.54634356 0.57670745 0.59501405
[13] 0.45290081 0.42362328 0.51456954 0.50116533 0.43019524 0.55665006
[19] 0.52203858 0.30116270 0.49090713 0.47366151 0.58333560 0.63996882
[25] 0.42946343 0.54136818 0.74054412 0.41112628 0.31699564 0.46259115
[31] 0.57613604 0.86740602 0.60858618 0.56690093 0.42661791 0.36783416
[37] 0.51120576 0.50829966 0.62603535 0.49586224 0.32464885 0.68986477
[43] 0.37463215 0.68140319 0.45015503 0.54709922 0.42218267 0.50075290
[49] 0.63014318 0.52992533 0.70881130 0.29710511 0.32909955 0.09898820
[55] 0.56609114 0.54704772 0.48571976 0.48044801 0.63206007 0.45839458
[61] 0.44023845 0.25493688 0.44183864 0.73059048 0.87606019 0.45818138
[67] 0.43840009 0.41265479 0.53012359 0.40046349 0.21378175 0.36261879
[73] 0.35731742 0.50222369 0.81478210 0.52792851 0.83529257 0.79432831
[79] 0.59658258 0.49184505 0.59111297 0.55120780 0.38427533 0.57156810
[85] 0.38519515 0.51576080 0.62018990 0.47604333 0.36376275 0.68360127
[91] 0.30283773 0.75248136 0.55683907 0.38704694 0.22274767 0.69887006
[97] 0.45040104 0.51636452 0.62112335 0.44632158 0.43799969 0.60609487
[103] 0.42534238 0.42749687 0.53831166 0.61860898 0.43846410 0.42415447
[109] 0.41678170 0.49843575 0.68830025 0.45455826 0.66408695 0.59960372
[115] 0.55517135 0.37525815 0.48765584 0.17790914 0.46578526 0.46483961
[121] 0.36736532 0.69471449 0.21413624 0.43895092 0.22426703 0.64506766
[127] 0.69190073 0.83336609 0.55478321 0.44887439 0.44355097 0.54882959
[133] 0.45568359 0.43643635 0.59087033 0.38600050 0.62695468 0.45704612
[139] 0.48817111 0.47917308 0.61965660 0.58846722 0.69936772 0.57926540
[145] 0.44746047 0.60676174 0.63754826 0.43796437 0.60356451 0.40124417
[151] 0.66053105 0.48147688 0.48327221 0.38361231 0.67477213 0.42658335
[157] 0.34501158 0.37145883 0.37325317 0.74634772 0.57317987 0.39816322
[163] 0.61944584 0.65129645 0.62916699 0.54757959 0.32587083 0.61908251
[169] 0.51339449 0.48223799 0.32246779 0.30454161 0.45959579 0.50767392
[175] 0.33890266 0.74171972 0.91513821 0.79034937 0.62138274 0.50008890
[181] 0.55024666 0.61120506 0.40418899 0.56336950 0.75440966 0.41547775
[187] 0.57202251 0.35161170 0.87278486 0.15964823 0.41388741 0.68809974
[193] 0.72162525 0.53180006 0.36994961 0.48592361 0.40883712 0.42439340
[199] 0.47156591 0.48033460 0.53542444 0.39255558 0.38021351 0.44177365
[205] 0.31223856 0.64821212 0.40766531 0.32954699 0.65760747 0.45650294
[211] 0.53646518 0.65244253 0.45890900 0.61277505 0.45476510 0.74142190
[217] 0.48446449 0.67149592 0.54161098 0.34425589 0.75524689 0.24485046
[223] 0.65563903 0.39645433 0.55988038 0.40107743 0.46427814 0.70902642
[229] 0.42655121 0.48131976 0.59409482 0.36408113 0.33346713 0.43977198
[235] 0.49097841 0.37557839 0.68958565 0.34240678 0.59224868 0.53629491
[241] 0.55357677 0.07729696 0.52609881 0.75735390 0.65748048 0.51303630
[247] 0.53723823 0.41078801 0.36734985 0.60297865 0.44778717 0.37387240
[253] 0.17524413 0.29221279 0.38068122 0.35080243 0.53316425 0.61637691
[259] 0.37396798 0.43888650 0.66442919 0.40584669 0.58695662 0.59312507
[265] 0.64977791 0.55746232 0.76001699 0.29312701 0.45968716 0.40472073
[271] 0.28342954 0.32369580 0.43570161 0.61788870 0.24034104 0.55466014
[277] 0.22778913 0.56122232 0.36826517 0.70260607 0.38424886 0.56370941
[283] 0.62375782 0.37096597 0.60447374 0.60296419 0.58105866 0.47270296
[289] 0.91548659 0.41445158 0.53071016 0.43051237 0.77634597 0.33255513
[295] 0.57373170 0.95787544 0.35286752 0.38747158 0.45639545 0.43417617
[301] 0.62070271 0.43390624 0.40346202 0.60650705 0.72115264 0.63104685
[307] 0.34435900 0.68081700 0.45815227 0.45166135 0.45520460 0.26363561
[313] 0.63953406 0.43412313 0.71544476 0.46044190 0.68741199 0.66145084
[319] 0.55889766 0.49916933 0.62022717 0.38379802 0.35215546 0.22122410
[325] 0.22421868 0.60196195 0.53729144 0.49869632 0.40320030 0.61737098
[331] 0.39226773 0.60387551 0.32375094 0.47497579 0.66774681 0.45046901
[337] 0.33760539 0.61235800 0.60695718 0.61541346 0.51884259 0.57556837
[343] 0.59107255 0.56751013 0.75739536 0.30849444 0.44712186 0.89274088
[349] 0.49341740 0.53875716 0.43910251 0.35935129 0.46913405 0.22909097
[355] 0.62327821 0.58523631 0.34463960 0.45914807 0.56391098 0.42917076
[361] 0.57608907 0.55301380 0.72727484 0.31495766 0.30545660 0.54269915
[367] 0.67565457 0.51743082 0.89918139 0.25851620 0.24071726 0.54387773
[373] 0.49143925 0.22537104 0.55280769 0.39198146 0.25558540 0.36153509
[379] 0.67712558 0.58933877 0.71762641 0.50400266 0.54587266 0.41821237
[385] 0.52502180 0.36657156 0.63332385 0.66333883 0.33953532 0.49174639
[391] 0.46589980 0.44828095 0.39452595 0.47640375 0.55432124 0.61486883
[397] 0.49266208 0.57250396 0.84879978 0.37597307 0.37916033 0.46940368
[403] 0.62404241 0.42047415 0.57541255 0.47423367 0.51073570 0.48463131
[409] 0.75852191 0.42085716 0.51487115 0.22435291 0.67339139 0.37965484
[415] 0.70160485 0.51586871 0.69107898 0.59835833 0.86525681 0.51124952
[421] 0.41712674 0.63075767 0.60710058 0.18870730 0.71080300 0.52248834
[427] 0.43984745 0.28521501 0.29561229 0.50548504 0.38554575 0.36904027
[433] 0.60810905 0.44855988 0.57346395 0.84179891 0.31622914 0.57166030
[439] 0.40677431 0.67796477 0.63543765 0.44053568 0.80121622 0.42852318
[445] 0.47048823 0.34666938 0.50563098 0.68789652 0.39192766 0.07672919
[451] 0.58656277 0.66197089 0.43251037 0.28878220 0.33580430 0.48423974
[457] 0.23850132 0.74837517 0.62865878 0.22352838 0.54046137 0.27451684
[463] 0.43123463 0.65867443 0.19625557 0.88105306 0.33985106 0.44407693
[469] 0.43314781 0.59639656 0.80670549 0.21252133 0.52648095 0.62141250
[475] 0.51301178 0.55912137 0.46742303 0.56909666 0.57770410 0.51518063
[481] 0.42768230 0.43609011 0.49139974 0.39923642 0.80467999 0.40349701
[487] 0.40025493 0.24842075 0.49093780 0.63876274 0.46383276 0.59277175
[493] 0.41222051 0.50400862 0.67422375 0.43051111 0.56170895 0.59854836
[499] 0.54431128 0.37835407
[1] 0.65525956 0.25796223 0.61589549 0.67246535 0.72237750 0.33465754
[7] 0.17489990 0.31693309 0.57421747 0.37245485 0.53557633 0.38202591
[13] 0.39652788 0.39962674 0.41708818 0.27950751 0.49099822 0.38678258
[19] 0.09891741 0.44473644 0.41392477 0.65828890 0.30483908 0.38155813
[25] 0.41756299 0.38196397 0.45561536 0.42893190 0.56455159 0.46986504
[31] 0.60815647 0.68521571 0.37096296 0.64631862 0.52919018 0.75192622
[37] 0.73170377 0.51826637 0.26084479 0.26260063 0.71216362 0.67724350
[43] 0.36100043 0.63291850 0.45077808 0.50542707 0.29996393 0.31888410
[49] 0.53377722 0.58210634 0.38706556 0.44353889 0.27801275 0.30209855
[55] 0.47358264 0.30169788 0.37385102 0.77086034 0.39804694 0.58819515
[61] 0.17510660 0.65250023 0.38735580 0.29095099 0.47434801 0.47885121
[67] 0.82340803 0.31206386 0.43879730 0.52250878 0.55823719 0.48984853
[73] 0.58207701 0.64693676 0.40228387 0.67278533 0.51966185 0.35768042
[79] 0.45944268 0.66953360 0.54805623 0.40699542 0.66894552 0.46547710
[85] 0.58207449 0.53543551 0.37575842 0.48671771 0.36677023 0.22411988
[91] 0.41840202 0.46333592 0.58213597 0.31664006 0.25915489 0.54595226
[97] 0.50783564 0.35812759 0.40760392 0.81911762 0.51027753 0.51024473
[103] 0.70931376 0.69625220 0.47471139 0.77059694 0.58065969 0.47783825
[109] 0.28586391 0.43580905 0.56907203 0.76953081 0.54197871 0.24345089
[115] 0.36521700 0.67924769 0.66492415 0.38337569 0.62665713 0.62092780
[121] 0.67736358 0.35710580 0.52882201 0.66237965 0.58923523 0.43342562
[127] 0.45529260 0.50098481 0.40275050 0.67751675 0.61828250 0.53597523
[133] 0.39235314 0.56962768 0.36618803 0.33723248 0.58510832 0.57798220
[139] 0.47977640 0.53096116 0.74584980 0.49813564 0.45233981 0.55928435
[145] 0.30714096 0.34539490 0.41032123 0.47393220 0.81644390 0.26933324
[151] 0.22883298 0.43316105 0.52109901 0.63605213 0.46424049 0.56687705
[157] 0.32490843 0.37533312 0.48071153 0.45485464 0.58298509 0.36390977
[163] 0.73858839 0.40477749 0.54548584 0.53623549 0.69226531 0.35568529
[169] 0.53270960 0.70931079 0.26583232 0.21839731 0.53243935 0.34618795
[175] 0.57169823 0.28424078 0.35686683 0.44103434 0.64450085 0.77893129
[181] 0.45098161 0.50338550 0.28259383 0.63155917 0.44369569 0.50354698
[187] 0.47254893 0.69162727 0.27227786 0.46923957 0.31096576 0.59753104
[193] 0.55842458 0.59437632 0.59210009 0.21310981 -0.01020090 0.41862686
[199] 0.56905948 0.44035734 0.11634918 0.59241763 0.66479739 0.24110624
[205] 0.51143195 0.44012146 0.41363613 0.50093459 0.63705319 0.66241215
[211] 0.50872171 0.56698193 0.60479089 0.49627656 0.36933227 0.11229864
[217] 0.69885000 0.48021428 0.35226528 0.69325801 0.31047802 0.26466390
[223] 0.25676042 0.38960682 0.34611664 0.41060502 0.58896593 0.43684734
[229] 0.31788919 0.51041924 0.56813545 0.52174046 0.58107350 0.26360326
[235] 0.41176818 0.58651598 0.61867167 0.54388312 0.64122135 0.22997846
[241] 0.46799327 0.85848781 0.59498522 0.70593949 0.56250880 0.10474003
[247] 0.65727024 0.36190177 0.41561541 0.32921293 0.35106192 0.78863750
[253] 0.65904646 0.86706435 0.19674714 0.70858640 0.51279380 0.30571882
[259] 0.39339011 0.53877017 0.27630945 0.62709234 0.76604454 0.25310745
[265] 0.51596582 0.42653205 0.58389124 0.24672135 0.72385105 0.57480297
[271] 0.49911044 0.29558683 0.31785178 0.63821530 0.53699201 0.50488374
[277] 0.34364247 0.78134007 0.50411277 0.14602160 0.35984070 0.71887107
[283] 0.42646965 0.53219424 0.65431279 0.48036456 0.53792093 0.57461322
[289] 0.19462122 0.84743160 0.54661287 0.56614476 0.58042371 0.51004266
[295] 0.60413009 0.53033492 0.62756173 0.54318267 0.41424643 0.81220717
[301] 0.41183957 0.46573275 0.41426463 0.97449819 0.34110525 0.57718716
[307] 0.43485594 0.41894094 0.59407688 0.77827961 0.76751545 0.39243029
[313] 0.56249854 0.69388110 0.42373287 0.56086343 0.51563916 0.66918888
[319] 0.40421050 0.56885891 0.40814325 0.67865924 0.74933911 0.59690876
[325] 0.51700259 0.61337334 0.26368993 0.70683444 0.35630493 0.61296205
[331] 0.29096290 0.59136037 0.51042158 0.60966431 0.54631247 0.46057551
[337] 0.43678963 0.41562604 0.49588102 0.52255596 0.51379887 0.43675952
[343] 0.34506054 0.57406286 0.47187748 0.34823365 0.40377427 0.40511823
[349] 0.38613788 0.57827549 0.45063924 0.47432362 0.48721950 0.43973055
[355] 0.72848367 0.37350741 0.34212345 0.44455524 0.19073709 0.52661533
[361] 0.30640110 0.53856021 0.25398806 0.36784179 0.32971222 0.39219305
[367] 0.35215788 0.60192883 0.47508542 0.48158767 0.79096682 0.38287128
[373] 0.02644576 0.59269909 0.60952417 0.24808474 0.46137003 0.33842896
[379] 0.54998990 0.44434566 0.54687290 0.45258095 0.60539162 0.63475143
[385] 0.30792869 0.74543570 0.78128924 0.73734186 0.36944480 0.53055163
[391] 0.51487713 0.41248578 0.65967465 0.59652402 0.42195782 0.65838785
[397] 0.34444204 0.33733797 0.62580118 0.98979158 0.32815638 0.39058915
[403] 0.47096363 0.45025688 0.44899149 0.54653142 0.68739920 0.38140666
[409] 0.44863995 0.37518322 0.53414573 0.25615449 0.27187205 0.59329157
[415] 0.72442171 0.30968542 0.34114486 0.28826095 0.47097276 0.49505890
[421] 0.50426603 0.38027442 0.70957531 0.70144016 0.31187781 0.67896957
[427] 0.70011698 0.67955893 0.49215468 0.40198856 0.71875031 0.49656631
[433] 0.45558320 0.55704180 0.57818915 0.45261296 0.57622418 0.33765949
[439] 0.61453421 0.56433432 0.27009812 0.61157561 0.54738456 0.77188975
[445] 0.54923949 0.71251008 0.43419974 0.48376244 0.59418816 0.82989921
[451] 0.31121682 0.46811432 0.33642147 0.36227318 0.59334413 0.60675484
[457] 0.54656512 0.59480529 0.39325751 0.39778284 0.60704010 0.35164753
[463] 0.55329989 0.52007036 0.56483151 0.48298640 0.62755879 0.75736350
[469] 0.57800755 0.48592482 0.55052628 0.53620172 0.05340268 0.45569202
[475] 0.68563663 0.71134636 0.65684529 0.58396646 0.80063388 0.26308544
[481] 0.43039534 0.50122269 0.43746648 0.54365742 0.76061186 0.40624553
[487] 0.44672481 0.52004212 0.46427715 0.70057409 0.31713835 0.60301355
[493] 0.50292942 0.27349486 0.45497777 0.44498214 0.65391658 0.47315087
[499] 0.46417803 0.75442023
In [23]:
pz <- as.data.frame(rep(1, 500))
colnames(pz) <- c("pz")
In [4]:
pnt <- ppp(px, py, c(0,1), c(0,1))
print(pnt)
Warning message:
In ppp(px, py, c(0, 1), c(0, 1)): 1 point was rejected as lying outside the specified window
Planar point pattern: 499 points
window: rectangle = [0, 1] x [0, 1] units
*** 1 illegal point stored in attr(,“rejects”) ***
In [8]:
plot(pnt, type="p")
Warning message:
In plot.ppp(pnt, type = "p"): 1 illegal points also plotted
Error in file(con, "rb"): コネクションを開くことができません
In [9]:
print(density(pnt))
real-valued pixel image
128 x 128 pixel array (ny, nx)
enclosing rectangle: [0, 1] x [0, 1] units
In [10]:
plot(density(pnt), 0.1)
Error in file(con, "rb"): コネクションを開くことができません
In [16]:
plot(density(pnt), 0.1)
contour(density(pnt), add=T)
Error in file(con, "rb"): コネクションを開くことができません
In [17]:
plot(pnt, type="p", add=T)
Error in plot.xy(xy.coords(x, y), type = type, ...): plot.new has not been called yet
In [20]:
pnt_xy <- cbind(px, py)
pnt_sp <- SpatialPoints(data.frame(px, py))
class(pnt_sp)
Out[20]:
'SpatialPoints'
In [24]:
pnt_spdf <- SpatialPointsDataFrame(pnt_sp, pz)
class(pnt_spdf)
Out[24]:
'SpatialPointsDataFrame'
In [25]:
print(pnt_spdf)
coordinates pz
1 (0.4397271, 0.6552596) 1
2 (0.7771534, 0.2579622) 1
3 (0.4384408, 0.6158955) 1
4 (0.1234969, 0.6724654) 1
5 (0.3851679, 0.7223775) 1
6 (0.5728864, 0.3346575) 1
7 (0.7063239, 0.1748999) 1
8 (0.5228763, 0.3169331) 1
9 (0.3668661, 0.5742175) 1
10 (0.5463436, 0.3724549) 1
11 (0.5767074, 0.5355763) 1
12 (0.5950141, 0.3820259) 1
13 (0.4529008, 0.3965279) 1
14 (0.4236233, 0.3996267) 1
15 (0.5145695, 0.4170882) 1
16 (0.5011653, 0.2795075) 1
17 (0.4301952, 0.4909982) 1
18 (0.5566501, 0.3867826) 1
19 (0.5220386, 0.09891741) 1
20 (0.3011627, 0.4447364) 1
21 (0.4909071, 0.4139248) 1
22 (0.4736615, 0.6582889) 1
23 (0.5833356, 0.3048391) 1
24 (0.6399688, 0.3815581) 1
25 (0.4294634, 0.417563) 1
26 (0.5413682, 0.381964) 1
27 (0.7405441, 0.4556154) 1
28 (0.4111263, 0.4289319) 1
29 (0.3169956, 0.5645516) 1
30 (0.4625911, 0.469865) 1
31 (0.576136, 0.6081565) 1
32 (0.867406, 0.6852157) 1
33 (0.6085862, 0.370963) 1
34 (0.5669009, 0.6463186) 1
35 (0.4266179, 0.5291902) 1
36 (0.3678342, 0.7519262) 1
37 (0.5112058, 0.7317038) 1
38 (0.5082997, 0.5182664) 1
39 (0.6260354, 0.2608448) 1
40 (0.4958622, 0.2626006) 1
41 (0.3246488, 0.7121636) 1
42 (0.6898648, 0.6772435) 1
43 (0.3746322, 0.3610004) 1
44 (0.6814032, 0.6329185) 1
45 (0.450155, 0.4507781) 1
46 (0.5470992, 0.5054271) 1
47 (0.4221827, 0.2999639) 1
48 (0.5007529, 0.3188841) 1
49 (0.6301432, 0.5337772) 1
50 (0.5299253, 0.5821063) 1
51 (0.7088113, 0.3870656) 1
52 (0.2971051, 0.4435389) 1
53 (0.3290995, 0.2780128) 1
54 (0.0989882, 0.3020985) 1
55 (0.5660911, 0.4735826) 1
56 (0.5470477, 0.3016979) 1
57 (0.4857198, 0.373851) 1
58 (0.480448, 0.7708603) 1
59 (0.6320601, 0.3980469) 1
60 (0.4583946, 0.5881951) 1
61 (0.4402384, 0.1751066) 1
62 (0.2549369, 0.6525002) 1
63 (0.4418386, 0.3873558) 1
64 (0.7305905, 0.290951) 1
65 (0.8760602, 0.474348) 1
66 (0.4581814, 0.4788512) 1
67 (0.4384001, 0.823408) 1
68 (0.4126548, 0.3120639) 1
69 (0.5301236, 0.4387973) 1
70 (0.4004635, 0.5225088) 1
71 (0.2137817, 0.5582372) 1
72 (0.3626188, 0.4898485) 1
73 (0.3573174, 0.582077) 1
74 (0.5022237, 0.6469368) 1
75 (0.8147821, 0.4022839) 1
76 (0.5279285, 0.6727853) 1
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116 (0.3752582, 0.6792477) 1
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118 (0.1779091, 0.3833757) 1
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120 (0.4648396, 0.6209278) 1
121 (0.3673653, 0.6773636) 1
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128 (0.8333661, 0.5009848) 1
129 (0.5547832, 0.4027505) 1
130 (0.4488744, 0.6775168) 1
131 (0.443551, 0.6182825) 1
132 (0.5488296, 0.5359752) 1
133 (0.4556836, 0.3923531) 1
134 (0.4364364, 0.5696277) 1
135 (0.5908703, 0.366188) 1
136 (0.3860005, 0.3372325) 1
137 (0.6269547, 0.5851083) 1
138 (0.4570461, 0.5779822) 1
139 (0.4881711, 0.4797764) 1
140 (0.4791731, 0.5309612) 1
141 (0.6196566, 0.7458498) 1
142 (0.5884672, 0.4981356) 1
143 (0.6993677, 0.4523398) 1
144 (0.5792654, 0.5592844) 1
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150 (0.4012442, 0.2693332) 1
151 (0.660531, 0.228833) 1
152 (0.4814769, 0.4331611) 1
153 (0.4832722, 0.521099) 1
154 (0.3836123, 0.6360521) 1
155 (0.6747721, 0.4642405) 1
156 (0.4265834, 0.566877) 1
157 (0.3450116, 0.3249084) 1
158 (0.3714588, 0.3753331) 1
159 (0.3732532, 0.4807115) 1
160 (0.7463477, 0.4548546) 1
161 (0.5731799, 0.5829851) 1
162 (0.3981632, 0.3639098) 1
163 (0.6194458, 0.7385884) 1
164 (0.6512965, 0.4047775) 1
165 (0.629167, 0.5454858) 1
166 (0.5475796, 0.5362355) 1
167 (0.3258708, 0.6922653) 1
168 (0.6190825, 0.3556853) 1
169 (0.5133945, 0.5327096) 1
170 (0.482238, 0.7093108) 1
171 (0.3224678, 0.2658323) 1
172 (0.3045416, 0.2183973) 1
173 (0.4595958, 0.5324394) 1
174 (0.5076739, 0.346188) 1
175 (0.3389027, 0.5716982) 1
176 (0.7417197, 0.2842408) 1
177 (0.9151382, 0.3568668) 1
178 (0.7903494, 0.4410343) 1
179 (0.6213827, 0.6445009) 1
180 (0.5000889, 0.7789313) 1
181 (0.5502467, 0.4509816) 1
182 (0.6112051, 0.5033855) 1
183 (0.404189, 0.2825938) 1
184 (0.5633695, 0.6315592) 1
185 (0.7544097, 0.4436957) 1
186 (0.4154778, 0.503547) 1
187 (0.5720225, 0.4725489) 1
188 (0.3516117, 0.6916273) 1
189 (0.8727849, 0.2722779) 1
190 (0.1596482, 0.4692396) 1
191 (0.4138874, 0.3109658) 1
192 (0.6880997, 0.597531) 1
193 (0.7216252, 0.5584246) 1
194 (0.5318001, 0.5943763) 1
195 (0.3699496, 0.5921001) 1
196 (0.4859236, 0.2131098) 1
197 (0.4088371, -0.0102009) 1
198 (0.4243934, 0.4186269) 1
199 (0.4715659, 0.5690595) 1
200 (0.4803346, 0.4403573) 1
201 (0.5354244, 0.1163492) 1
202 (0.3925556, 0.5924176) 1
203 (0.3802135, 0.6647974) 1
204 (0.4417737, 0.2411062) 1
205 (0.3122386, 0.511432) 1
206 (0.6482121, 0.4401215) 1
207 (0.4076653, 0.4136361) 1
208 (0.329547, 0.5009346) 1
209 (0.6576075, 0.6370532) 1
210 (0.4565029, 0.6624121) 1
211 (0.5364652, 0.5087217) 1
212 (0.6524425, 0.5669819) 1
213 (0.458909, 0.6047909) 1
214 (0.612775, 0.4962766) 1
215 (0.4547651, 0.3693323) 1
216 (0.7414219, 0.1122986) 1
217 (0.4844645, 0.69885) 1
218 (0.6714959, 0.4802143) 1
219 (0.541611, 0.3522653) 1
220 (0.3442559, 0.693258) 1
221 (0.7552469, 0.310478) 1
222 (0.2448505, 0.2646639) 1
223 (0.655639, 0.2567604) 1
224 (0.3964543, 0.3896068) 1
225 (0.5598804, 0.3461166) 1
226 (0.4010774, 0.410605) 1
227 (0.4642781, 0.5889659) 1
228 (0.7090264, 0.4368473) 1
229 (0.4265512, 0.3178892) 1
230 (0.4813198, 0.5104192) 1
231 (0.5940948, 0.5681355) 1
232 (0.3640811, 0.5217405) 1
233 (0.3334671, 0.5810735) 1
234 (0.439772, 0.2636033) 1
235 (0.4909784, 0.4117682) 1
236 (0.3755784, 0.586516) 1
237 (0.6895857, 0.6186717) 1
238 (0.3424068, 0.5438831) 1
239 (0.5922487, 0.6412214) 1
240 (0.5362949, 0.2299785) 1
241 (0.5535768, 0.4679933) 1
242 (0.07729696, 0.8584878) 1
243 (0.5260988, 0.5949852) 1
244 (0.7573539, 0.7059395) 1
245 (0.6574805, 0.5625088) 1
246 (0.5130363, 0.10474) 1
247 (0.5372382, 0.6572702) 1
248 (0.410788, 0.3619018) 1
249 (0.3673499, 0.4156154) 1
250 (0.6029786, 0.3292129) 1
251 (0.4477872, 0.3510619) 1
252 (0.3738724, 0.7886375) 1
253 (0.1752441, 0.6590465) 1
254 (0.2922128, 0.8670643) 1
255 (0.3806812, 0.1967471) 1
256 (0.3508024, 0.7085864) 1
257 (0.5331642, 0.5127938) 1
258 (0.6163769, 0.3057188) 1
259 (0.373968, 0.3933901) 1
260 (0.4388865, 0.5387702) 1
261 (0.6644292, 0.2763094) 1
262 (0.4058467, 0.6270923) 1
263 (0.5869566, 0.7660445) 1
264 (0.5931251, 0.2531074) 1
265 (0.6497779, 0.5159658) 1
266 (0.5574623, 0.426532) 1
267 (0.760017, 0.5838912) 1
268 (0.293127, 0.2467214) 1
269 (0.4596872, 0.723851) 1
270 (0.4047207, 0.574803) 1
271 (0.2834295, 0.4991104) 1
272 (0.3236958, 0.2955868) 1
273 (0.4357016, 0.3178518) 1
274 (0.6178887, 0.6382153) 1
275 (0.240341, 0.536992) 1
276 (0.5546601, 0.5048837) 1
277 (0.2277891, 0.3436425) 1
278 (0.5612223, 0.7813401) 1
279 (0.3682652, 0.5041128) 1
280 (0.7026061, 0.1460216) 1
281 (0.3842489, 0.3598407) 1
282 (0.5637094, 0.7188711) 1
283 (0.6237578, 0.4264696) 1
284 (0.370966, 0.5321942) 1
285 (0.6044737, 0.6543128) 1
286 (0.6029642, 0.4803646) 1
287 (0.5810587, 0.5379209) 1
288 (0.472703, 0.5746132) 1
289 (0.9154866, 0.1946212) 1
290 (0.4144516, 0.8474316) 1
291 (0.5307102, 0.5466129) 1
292 (0.4305124, 0.5661448) 1
293 (0.776346, 0.5804237) 1
294 (0.3325551, 0.5100427) 1
295 (0.5737317, 0.6041301) 1
296 (0.9578754, 0.5303349) 1
297 (0.3528675, 0.6275617) 1
298 (0.3874716, 0.5431827) 1
299 (0.4563955, 0.4142464) 1
300 (0.4341762, 0.8122072) 1
301 (0.6207027, 0.4118396) 1
302 (0.4339062, 0.4657327) 1
303 (0.403462, 0.4142646) 1
304 (0.606507, 0.9744982) 1
305 (0.7211526, 0.3411053) 1
306 (0.6310469, 0.5771872) 1
307 (0.344359, 0.4348559) 1
308 (0.680817, 0.4189409) 1
309 (0.4581523, 0.5940769) 1
310 (0.4516613, 0.7782796) 1
311 (0.4552046, 0.7675154) 1
312 (0.2636356, 0.3924303) 1
313 (0.6395341, 0.5624985) 1
314 (0.4341231, 0.6938811) 1
315 (0.7154448, 0.4237329) 1
316 (0.4604419, 0.5608634) 1
317 (0.687412, 0.5156392) 1
318 (0.6614508, 0.6691889) 1
319 (0.5588977, 0.4042105) 1
320 (0.4991693, 0.5688589) 1
321 (0.6202272, 0.4081432) 1
322 (0.383798, 0.6786592) 1
323 (0.3521555, 0.7493391) 1
324 (0.2212241, 0.5969088) 1
325 (0.2242187, 0.5170026) 1
326 (0.601962, 0.6133733) 1
327 (0.5372914, 0.2636899) 1
328 (0.4986963, 0.7068344) 1
329 (0.4032003, 0.3563049) 1
330 (0.617371, 0.6129621) 1
331 (0.3922677, 0.2909629) 1
332 (0.6038755, 0.5913604) 1
333 (0.3237509, 0.5104216) 1
334 (0.4749758, 0.6096643) 1
335 (0.6677468, 0.5463125) 1
336 (0.450469, 0.4605755) 1
337 (0.3376054, 0.4367896) 1
338 (0.612358, 0.415626) 1
339 (0.6069572, 0.495881) 1
340 (0.6154135, 0.522556) 1
341 (0.5188426, 0.5137989) 1
342 (0.5755684, 0.4367595) 1
343 (0.5910726, 0.3450605) 1
344 (0.5675101, 0.5740629) 1
345 (0.7573954, 0.4718775) 1
346 (0.3084944, 0.3482337) 1
347 (0.4471219, 0.4037743) 1
348 (0.8927409, 0.4051182) 1
349 (0.4934174, 0.3861379) 1
350 (0.5387572, 0.5782755) 1
351 (0.4391025, 0.4506392) 1
352 (0.3593513, 0.4743236) 1
353 (0.469134, 0.4872195) 1
354 (0.229091, 0.4397305) 1
355 (0.6232782, 0.7284837) 1
356 (0.5852363, 0.3735074) 1
357 (0.3446396, 0.3421235) 1
358 (0.4591481, 0.4445552) 1
359 (0.563911, 0.1907371) 1
360 (0.4291708, 0.5266153) 1
361 (0.5760891, 0.3064011) 1
362 (0.5530138, 0.5385602) 1
363 (0.7272748, 0.2539881) 1
364 (0.3149577, 0.3678418) 1
365 (0.3054566, 0.3297122) 1
366 (0.5426991, 0.392193) 1
367 (0.6756546, 0.3521579) 1
368 (0.5174308, 0.6019288) 1
369 (0.8991814, 0.4750854) 1
370 (0.2585162, 0.4815877) 1
371 (0.2407173, 0.7909668) 1
372 (0.5438777, 0.3828713) 1
373 (0.4914393, 0.02644576) 1
374 (0.225371, 0.5926991) 1
375 (0.5528077, 0.6095242) 1
376 (0.3919815, 0.2480847) 1
377 (0.2555854, 0.46137) 1
378 (0.3615351, 0.338429) 1
379 (0.6771256, 0.5499899) 1
380 (0.5893388, 0.4443457) 1
381 (0.7176264, 0.5468729) 1
382 (0.5040027, 0.4525809) 1
383 (0.5458727, 0.6053916) 1
384 (0.4182124, 0.6347514) 1
385 (0.5250218, 0.3079287) 1
386 (0.3665716, 0.7454357) 1
387 (0.6333238, 0.7812892) 1
388 (0.6633388, 0.7373419) 1
389 (0.3395353, 0.3694448) 1
390 (0.4917464, 0.5305516) 1
391 (0.4658998, 0.5148771) 1
392 (0.448281, 0.4124858) 1
393 (0.394526, 0.6596747) 1
394 (0.4764037, 0.596524) 1
395 (0.5543212, 0.4219578) 1
396 (0.6148688, 0.6583879) 1
397 (0.4926621, 0.344442) 1
398 (0.572504, 0.337338) 1
399 (0.8487998, 0.6258012) 1
400 (0.3759731, 0.9897916) 1
401 (0.3791603, 0.3281564) 1
402 (0.4694037, 0.3905891) 1
403 (0.6240424, 0.4709636) 1
404 (0.4204742, 0.4502569) 1
405 (0.5754125, 0.4489915) 1
406 (0.4742337, 0.5465314) 1
407 (0.5107357, 0.6873992) 1
408 (0.4846313, 0.3814067) 1
409 (0.7585219, 0.44864) 1
410 (0.4208572, 0.3751832) 1
411 (0.5148712, 0.5341457) 1
412 (0.2243529, 0.2561545) 1
413 (0.6733914, 0.2718721) 1
414 (0.3796548, 0.5932916) 1
415 (0.7016048, 0.7244217) 1
416 (0.5158687, 0.3096854) 1
417 (0.691079, 0.3411449) 1
418 (0.5983583, 0.288261) 1
419 (0.8652568, 0.4709728) 1
420 (0.5112495, 0.4950589) 1
421 (0.4171267, 0.504266) 1
422 (0.6307577, 0.3802744) 1
423 (0.6071006, 0.7095753) 1
424 (0.1887073, 0.7014402) 1
425 (0.710803, 0.3118778) 1
426 (0.5224883, 0.6789696) 1
427 (0.4398475, 0.700117) 1
428 (0.285215, 0.6795589) 1
429 (0.2956123, 0.4921547) 1
430 (0.505485, 0.4019886) 1
431 (0.3855457, 0.7187503) 1
432 (0.3690403, 0.4965663) 1
433 (0.6081091, 0.4555832) 1
434 (0.4485599, 0.5570418) 1
435 (0.5734639, 0.5781892) 1
436 (0.8417989, 0.452613) 1
437 (0.3162291, 0.5762242) 1
438 (0.5716603, 0.3376595) 1
439 (0.4067743, 0.6145342) 1
440 (0.6779648, 0.5643343) 1
441 (0.6354376, 0.2700981) 1
442 (0.4405357, 0.6115756) 1
443 (0.8012162, 0.5473846) 1
444 (0.4285232, 0.7718898) 1
445 (0.4704882, 0.5492395) 1
446 (0.3466694, 0.7125101) 1
447 (0.505631, 0.4341997) 1
448 (0.6878965, 0.4837624) 1
449 (0.3919277, 0.5941882) 1
450 (0.07672919, 0.8298992) 1
451 (0.5865628, 0.3112168) 1
452 (0.6619709, 0.4681143) 1
453 (0.4325104, 0.3364215) 1
454 (0.2887822, 0.3622732) 1
455 (0.3358043, 0.5933441) 1
456 (0.4842397, 0.6067548) 1
457 (0.2385013, 0.5465651) 1
458 (0.7483752, 0.5948053) 1
459 (0.6286588, 0.3932575) 1
460 (0.2235284, 0.3977828) 1
461 (0.5404614, 0.6070401) 1
462 (0.2745168, 0.3516475) 1
463 (0.4312346, 0.5532999) 1
464 (0.6586744, 0.5200704) 1
465 (0.1962556, 0.5648315) 1
466 (0.8810531, 0.4829864) 1
467 (0.3398511, 0.6275588) 1
468 (0.4440769, 0.7573635) 1
469 (0.4331478, 0.5780076) 1
470 (0.5963966, 0.4859248) 1
471 (0.8067055, 0.5505263) 1
472 (0.2125213, 0.5362017) 1
473 (0.5264809, 0.05340268) 1
474 (0.6214125, 0.455692) 1
475 (0.5130118, 0.6856366) 1
476 (0.5591214, 0.7113464) 1
477 (0.467423, 0.6568453) 1
478 (0.5690967, 0.5839665) 1
479 (0.5777041, 0.8006339) 1
480 (0.5151806, 0.2630854) 1
481 (0.4276823, 0.4303953) 1
482 (0.4360901, 0.5012227) 1
483 (0.4913997, 0.4374665) 1
484 (0.3992364, 0.5436574) 1
485 (0.80468, 0.7606119) 1
486 (0.403497, 0.4062455) 1
487 (0.4002549, 0.4467248) 1
488 (0.2484207, 0.5200421) 1
489 (0.4909378, 0.4642772) 1
490 (0.6387627, 0.7005741) 1
491 (0.4638328, 0.3171384) 1
492 (0.5927718, 0.6030135) 1
493 (0.4122205, 0.5029294) 1
494 (0.5040086, 0.2734949) 1
495 (0.6742237, 0.4549778) 1
496 (0.4305111, 0.4449821) 1
497 (0.5617089, 0.6539166) 1
498 (0.5985484, 0.4731509) 1
499 (0.5443113, 0.464178) 1
500 (0.3783541, 0.7544202) 1
In [28]:
plot(pnt_spdf)
Error in file(con, "rb"): コネクションを開くことができません
In [29]:
quadratcount(pnt, nx=2, ny=2)
Out[29]:
x
y [0,0.5) [0.5,1]
[0.5,1] 138 108
[0,0.5) 116 137
In [30]:
quadratcount(pnt, nx=2, ny=2)/(0.5^2)
Out[30]:
x
y [0,0.5) [0.5,1]
[0.5,1] 552 432
[0,0.5) 464 548
In [31]:
plot(pnt, type="p")
Warning message:
In plot.ppp(pnt, type = "p"): 1 illegal points also plotted
Error in file(con, "rb"): コネクションを開くことができません
In [37]:
plot(pnt, type="p")
plot(quadratcount(pnt, nx=2, ny=2), add=T, col="red")
Warning message:
In plot.ppp(pnt, type = "p"): 1 illegal points also plotted
Error in file(con, "rb"): コネクションを開くことができません
In [34]:
quadratcount(pnt, nx=4, ny=4)
Out[34]:
x
y [0,0.25) [0.25,0.5) [0.5,0.75) [0.75,1]
[0.75,1] 3 15 8 1
[0.5,0.75) 14 106 89 10
[0.25,0.5) 9 99 107 17
[0,0.25) 0 8 12 1
In [35]:
quadratcount(pnt, nx=4, ny=4)/(0.25^2)
Out[35]:
x
y [0,0.25) [0.25,0.5) [0.5,0.75) [0.75,1]
[0.75,1] 48 240 128 16
[0.5,0.75) 224 1696 1424 160
[0.25,0.5) 144 1584 1712 272
[0,0.25) 0 128 192 16
In [36]:
plot(pnt, type="p")
plot(quadratcount(pnt, nx=4, ny=4), add=T, col="red")
Warning message:
In plot.ppp(pnt, type = "p"): 1 illegal points also plotted
Error in file(con, "rb"): コネクションを開くことができません
In [38]:
poly1 <- cbind(
c(0, 0.75, 0.75, 0.5, 0.5, 0.25, 0.25, 0, 0),
c(0, 0, 0.25, 0.25, 0.5, 0.5, 0.75, 0.75, 0)
)
poly2 <- cbind(
c(0.25, 0.75, 0.75, 0.25, 0.25),
c(0.5, 0.5, 0.75, 0.75, 0.5)
)
poly3 <- cbind(
c(0.75, 1, 1, 0.75, 0.75, 0.5, 0.5, 0.75, 0.75),
c(0, 0, 0.75, 0.75, 0.5, 0.5, 0.25, 0.25, 0)
)
poly4 <- cbind(
c(0, 1, 1, 0, 0),
c(0.75, 0.75, 1, 1, 0.75)
)
poly1_pl <- Polygons(list(Polygon(poly1)), "poly1")
poly2_pl <- Polygons(list(Polygon(poly2)), "poly2")
poly3_pl <- Polygons(list(Polygon(poly3)), "poly3")
poly4_pl <- Polygons(list(Polygon(poly4)), "poly4")
In [39]:
poly_sp <- SpatialPolygons(list(poly1_pl, poly2_pl, poly3_pl, poly4_pl))
poly_spdf <- SpatialPolygonsDataFrame(poly_sp, data.frame(c(1:4), row.names=c("poly1", "poly2", "poly3", "poly4")))
In [40]:
plot(poly_spdf)
Error in file(con, "rb"): コネクションを開くことができません
In [42]:
plot(poly_spdf)
plot(pnt, type="p", add=T)
Warning message:
In plot.ppp(pnt, type = "p", add = T): 1 illegal points also plotted
Error in file(con, "rb"): コネクションを開くことができません
In [48]:
pnt_spdf
Out[48]:
coordinates pz
1 (0.4397271, 0.6552596) 1
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462 (0.2745168, 0.3516475) 1
463 (0.4312346, 0.5532999) 1
464 (0.6586744, 0.5200704) 1
465 (0.1962556, 0.5648315) 1
466 (0.8810531, 0.4829864) 1
467 (0.3398511, 0.6275588) 1
468 (0.4440769, 0.7573635) 1
469 (0.4331478, 0.5780076) 1
470 (0.5963966, 0.4859248) 1
471 (0.8067055, 0.5505263) 1
472 (0.2125213, 0.5362017) 1
473 (0.5264809, 0.05340268) 1
474 (0.6214125, 0.455692) 1
475 (0.5130118, 0.6856366) 1
476 (0.5591214, 0.7113464) 1
477 (0.467423, 0.6568453) 1
478 (0.5690967, 0.5839665) 1
479 (0.5777041, 0.8006339) 1
480 (0.5151806, 0.2630854) 1
481 (0.4276823, 0.4303953) 1
482 (0.4360901, 0.5012227) 1
483 (0.4913997, 0.4374665) 1
484 (0.3992364, 0.5436574) 1
485 (0.80468, 0.7606119) 1
486 (0.403497, 0.4062455) 1
487 (0.4002549, 0.4467248) 1
488 (0.2484207, 0.5200421) 1
489 (0.4909378, 0.4642772) 1
490 (0.6387627, 0.7005741) 1
491 (0.4638328, 0.3171384) 1
492 (0.5927718, 0.6030135) 1
493 (0.4122205, 0.5029294) 1
494 (0.5040086, 0.2734949) 1
495 (0.6742237, 0.4549778) 1
496 (0.4305111, 0.4449821) 1
497 (0.5617089, 0.6539166) 1
498 (0.5985484, 0.4731509) 1
499 (0.5443113, 0.464178) 1
500 (0.3783541, 0.7544202) 1
In [44]:
over(pnt_spdf, poly_spdf, fn=colSums)
Error in FUN(X[[i]], ...): 'x' must be an array of at least two dimensions
In [49]:
area.poly_spdf <- c(0.25^2*6, 0.25^2*2, 0.25^2*4, 0.25^2*4)
In [51]:
over(pnt_spdf, poly_spdf, fn=colSums)/area.poly_spdf
Error in FUN(X[[i]], ...): 'x' must be an array of at least two dimensions
In [84]:
library(sp)
x = c(0.5, 0.5, 1.0, 1.5)
y = c(1.5, 0.5, 0.5, 0.5)
xy = cbind(x,y)
dimnames(xy)[[1]] = c("a", "b", "c", "d")
pts = SpatialPoints(xy)
xpol = c(0,1,1,0,0)
ypol = c(0,0,1,1,0)
pol = SpatialPolygons(list(
Polygons(list(Polygon(cbind(xpol-1.05,ypol))), ID="x1"),
Polygons(list(Polygon(cbind(xpol,ypol))), ID="x2"),
Polygons(list(Polygon(cbind(xpol,ypol - 1.0))), ID="x3"), Polygons(list(Polygon(cbind(xpol + 1.0, ypol))), ID="x4"),Polygons(list(Polygon(cbind(xpol+.4, ypol+.1))), ID="x5")))
In [85]:
plot(pol)
Error in file(con, "rb"): コネクションを開くことができません
In [86]:
pts = SpatialPoints(xy)
plot(pts)
Error in file(con, "rb"): コネクションを開くことができません
In [87]:
x = c(0.5, 0.5, 1.0, 1.5)
y = c(1.5, 0.5, 0.5, 0.5)
xy = cbind(x,y)
In [88]:
over(pts, pol)
Out[88]:
- a
- NA
- b
- 5
- c
- 5
- d
- NA
In [83]:
over(pts, pol, returnList = TRUE)
Out[83]:
- $a
- $b
- 2
- 5
- $c
- 2
- 4
- 5
- $dh
- 4
In [89]:
class(pol)
Out[89]:
'SpatialPolygons'
In [90]:
zdf = data.frame(z1 = 1:4, z2=4:1, f = c("a", "a", "b", "b"),
row.names = c("a", "b", "c", "d"))
zdf
Out[90]:
z1 z2 f a 1 4 a b 2 3 a c 3 2 b d 4 1 b
In [91]:
ptsdf = SpatialPointsDataFrame(pts, zdf)
zpl = data.frame(z = c(10, 15, 25, 3, 0), zz=1:5,
f = c("z", "q", "r", "z", "q"), row.names = c("x1", "x2", "x3", "x4", "x5"))
zpl
Out[91]:
z zz f x1 10 1 z x2 15 2 q x3 25 3 r x4 3 4 z x5 0 5 q
In [92]:
poldf = SpatialPolygonsDataFrame(pol, zpl)
In [93]:
over(pts, poldf)
Out[93]:
z zz f a NA NA NA b 15 2 q c 15 2 q d NA NA NA
In [94]:
class(pts)
Out[94]:
'SpatialPoints'
In [95]:
class(poldf)
Out[95]:
'SpatialPolygonsDataFrame'
In [96]:
plot(poldf)
Error in file(con, "rb"): コネクションを開くことができません
In [ ]:
Content source: NlGG/SpatialStatistics
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