在heatplot ggplot瓷砖之间的空白区域

本文介绍了在heatplot ggplot瓷砖之间的空白区域的处理方法，对大家解决问题具有一定的参考价值，需要的朋友们下面随着小编来一起学习吧！ 问题描述 29岁程序员，3月因学历无情被辞！ 我有使用ggplot2生成的这个热图。 我想要做的是在用大写字母列出的变量和以小写字母列出的变量以便分开这两个类别。我仍然希望瓷砖的宽度相等。 我用来生成图的代码是： ggplot（mockdata，aes（variable，Measurement））+ geom_tile（aes（fill = mockdata $ plotval），color =dark red）+ scale_fill_gradient2（limits = c（-20,20），high = firebrick3，low =dodgerblue4）+ theme_minimal（）+ theme（axis.text.x = element_text（size = 28，angle = 90），axis.text.y = element_text（size = 28） ）+ labs（title =，x =，y =，fill =） 我的数据如下所示： >头（mockdata）测量变量Pval effect >方向plotval类别21 20 A 4.511987e + 04 > -0.004892941 -1 -4.6543678实测22 19 A 3.436853e-08 0.054344854 1 7.4638390实测23 18 A 1.465755e + 00 0.355139910 1 -0.1660613实测24 > 17 A 7.006222e-04 -0.079390247 -1 3.1545161测得25 > 16 A 4.705051e-04 -0.017708611 -1 3.3274357测得26 > 15 A 2.301113e + 03 -0.022934623 -1 -3.3619379测量的 PS。虽然这完全是另一个问题，但我也想编辑图例，使其范围从0到20不等，并且分成两个垂直方向，一边显示红色渐变和蓝色渐变。 非常感谢您的帮助。 $ b 编辑：根据请求输出输出 dput（mockdata）$ （测量=结构（c（20L，19L，18L，17L， 16L，15L，14L，13L，12L，11L，10L，9L，8L，7L，6L，5L，4L） ，3L， 2L，1L，20L，19L，18L，17L，16L，15L，14L，13L，12L，11L，10L， 9L，8L，7L，6L，5L，4L，3L ，2L，1L，20L，19L，18L，17L，16L， 15L，14L，13L，12L，11L，10L，9L，8L，7L，6L，5L，4L，3L，2L， b 1L，20L，19L，18L，17L，16L，15L，14L，13L，12L，11L，10L，9L， 8L，7L，6L，5L，4L，3L，2L，1L，20L，19L 18L，17L，16L，15L， 14L，13L，12L，11L，10L，9L，8L，7L，6L，5L，4L，3L，2L，1L， 20L，19L，18L ，17L，16L，15L，14L，13L，12L，11L，10L，9L，8L， 7L，6L，5L，4L，3L，2L，1L，20L，19L，18L，17L，16L，15L ，14L， 13L，12L，11L，10L，9L，8L，7L，6L，5L，4L，3L，2L，1L，20L， 19L，18L，17L，16L，15L，14L ，13L，12L，11L，10L，9L，8L，7L， 6L，5L，4L，3L，2L，1L，20L，19L，18L，17L，16L，15L，14L，13L， b 12L，11L，10 L，9L，8L，7L，6L，5L，4L，3L，2L，1L），标签= c（1，2，3，4，5 6，7，8，9，10，11，12，13，，14，15，16，17 ，18，19，20，21，22，23，24，25，26，27，28 29，30，31，32，33，34，35，，36，37，38，39，40 （1L，1L，1L，1L，1L，1L，1L，1L，1L，1L，1L，1L，1L，1L，1L，1L，1L， 1L，1L， 1L，1L，1L，2L，2L，2L，2L，2L，2L，2L，2L，2L，2L，2L，2L，2L， 2L，2L， 2L，2L，2L，2L，3L，3L，3L，3L，3L，3L，3L，3L，3L，3L，3L，3L，3L，3L，3L，3L，3L， 3L，4L，4L，4L，4L，4L，4L，4L，4L，4L，4L，4L，4L，4L，4L，4L，4L，4L，4L，4L，4L，4L，4L， $ 5L，5L，5L，5L，5L，5L，5L，5L，5L，5L，5L，5L，5L，5L，5L，5L， 5L，5L，5L，6L，6L， 6L，6L，6L，6L，6L，6L，6L，6L，6L，6L， 6L，6L，6L，6L，6L，6L，6L，7L，7L，7L，7L，7L，7L， 7L，7L，7L， 7L，7L，7L，7L，7L，7L，7L，7L，7L，7L，7L，7L，8L，8L，8L，8L，8L， 8L， 8L，8L，8L，8L，8L，8L，8L，8L，8L，8L，8L，8L，9L，9B， 9L，9L，9L，9L，9L，9L， 9L，9L，9L）。标签= c（A，B，C，a，b，c ，d，e，f），class =factor），Pval = c（45119.8699435164,3.43685309800565e-08， 1.46575455003134,0.000700622204341352,0.000470505115493356， 2301.1126328306，4.54797845872279e-09，2.82713540460051，7.27455376527109， 0.000708124149686762，2.42898037459018，129.848099736546，0.199979430821282， 3.14108095159057，1.27073870790998，107.060952494286，5853.27997745224， 0.0742582348172777，0.179994821770633，896.77644657471，23.2401456908433， 1.04257158400361e-05，0.818717078694074，0.000516863241751892， 0.445544049614064，37.9699212955842，4.87750761132064，0.138732186303325， 0.0185924820003653，30.8203248121754，2.40190754411345，61.2579350060232， 6.44618209352764，1047821.38958175，704454.528072486，1184.40676026588， 9.27799786552194,244051 0.746539605，375048.779613815，9134.54101073437， 3.11905288061898e-08，2.00150860109179e-05，7.0931638758186e-05， 2.43242155771004，1602.73424833609，6.02923321145412，3.21794638623681， 39545.9388361236，475.781444413131，455.686197237482，4.67829129583755， 909.58298359142，2.02989433872695e-12，0.000760836775114312， 0.000112864936813818，0.00189775331609849，0.0815921243521161， 31.0427655620544，64.1785732227039，0.00217933417639979，0.32663419999951， 2.54891270451988e-07，8.48612397192046e-08，0.370184441863085 ， 0.0773444299723239，1580.93083600716，25.4862794021994，30.2642707469218， 224.214639928028，14.7414363362227，18.0511919451453，21037.258121794， 21659.968905852，17721957.0100965，41240.6588986806，111.028537460958， 21.7975275086975，276.44178388089，171.535750708364，6.54776065462672， 151.823636593007，77.7232628471612，378439.528032194,8.9932059191815e-10， 7.49689679316569e-08，0.0155924907385915， 1032.31959077079，69.010587250471， 3136.70323628637，249713.871697334，19360.5708508639，40.7258690163879， 0.0162957051889601，1.02869393872855e-06，0.025268197376688， 0.528481476061038，0.982629085096339，9.45655313066933e-07，4.57557582847333e-05， 7.45403294058092e-05,4.53918933391971 3.30530837062386e-13 0.630234341296706 9.82668496529192e-08 8.53389810467837e-08 9.02891336492619 5451.02888390797 3.90681590706977 329.545150676593 103.491400305633 697.038514954349 222.73520900148 ，10798.3042798457， 21.0644243649671，43176.6607108169，4235.53654423626，3100.32036580987， 0.474678829666085，6.40621457829452，122.637549472055，43.0666245228938， 12.0250322640284，61440.278302552，6788575.58160297，51.9360282881212， 769.96899739087，7.59005145509618e-09， 2.43526615569376e-14， 7.39725489778816e-07，0.000232784090617743，2.71678851958226e-05， 7.42801688358956e-06，0.000419885957835749，13.5780839769886 ， 3.32442709394189，0.335486082296544，3.94230896978352，1.46425278783307， 8.69549979650646，596385.229504125，0.000115943040096764，3628.23773839244， 49454.7726336256，0.000504974333790079，0.00995546823577904， 0.233933121119438，0.363364289185792，9193.93256769758，354.456908896329， 5661.68504768727，0.121589829029783,940.93343158607,2.03003608173289e-18， 0.0149649659043151,4.52682955802236e-10，7.15334079727642e-09， 0.000310851843411754,1.93389728243117e-06,2.03883508956486e-07， 0.00284517176384008， 540.061334125012，21318282.1015595，14894.4660549342， 0.000266471541489485，0.246672590081899，0.102617416010794，30584.5294303485， 1.6644151457974，0.274144521451231，5.61250055231602，801087.819256331， 649321.765215902，1.09526223361541，3.19905699111348e-05，0.383890848761449， 895.643897487244 ，2.68459116542856,26.4804232740359,5.94041739131986， 1.53119475830081e-07），效应= c（-0.0048929408170183,0 0.0543448544236634， 0.355139910284011，-0.0793902472151885，-0.0177086113171934， -0.0229346227548993，0.0859476877708055，0.0616530901499479， 0.0255808327961239，0.0587050814255305，0.0141476490245787，0.016845032477233， 0.0534824934671667，0.109055235276048，0.111112652283139，0.0234941463950778， 0.0509358202565552，0.0252735688725701，0.0359067099796669，0.00562271637183446， 0.0507704293161921，0.17283228087345，0.16140675832248，-0.0818286747635847， -0.00755469414427661，-0.0104447567093411，-0.128088271682644， -0.0534210973538898，-0.373370146687058，-0.0158548424704536 ， -0.0748163315974356，-0.0904460324042191，-0.0028512716452736， 0.014271561838011，-0.00190156753813359，-0.0239279177026479， -0.0094336807819733，0.0222425549129021，0.0292506342181443， 0.0325754202368439，0.0148015986703938，0.0421882264651577，0.423260142208342， 0.0203382101649578，0.00402969463133637，0.0866038959569813， -0.012618 0724522637，-0.00101624925914612,0.0424729539424711， 0.0109268890743347，-0.100768815837666，-0.00606344260837149， -0.0909174554780339，-0.0959700647301915，-0.0768705808220001， -0.0662807953036616，-0.00706464147110935，-0.0260825101925435， - 0.116360501719279，-0.0685817739681672，0.0190371136722137， 0.314176452865903，0.0852019981707266，-0.109955683402951，-0.0429494359040651， -0.018893257986317，0.0359280715736875，-0.00777719486360404， 0.0268854711195253，0.035717165605315，-0.0185632636448169，0.00219893106540​​051， -0.0575168050187894，-0.0268860255228866，-0.0120997481434518， -0.0174770295188239，-0.0365387268315564，0.00427667014560775， 0.0290413811465955，-0.0303874959875708，0.0494496371834744， -0.0172878730121681，-0.0596619493875312，0.0674472930186462， 0.0581172695200586， 0.0352865160196343，-0.0390338901505756， 0.0201101954340249，0.0968644367520139，-0.00587675128187206， -0.09902230127504 21，-0.022532243059551，-0.109508938534005， -0.0828800247402709，-0.0224991372217077，-0.0864470271893071， -0.0120276456354962，-0.171616504240665，-0.0405716645109222， -0.150207882114913,0.019187309212901,0.083618216547288,0.312977089073896， -0.116708039798045，-0.0727212548658722，-0.0334904589242441， 0.0250211767009604，-0.0262773156800457，-0.00638328497889965， 0.0207436409328599，0.00526977878443117，0.0121248749949723， 0.0372084648778052，0.0119773388777849，0.0299841410899367，0.0179852238184209， 0.00615922907815808， 0.0923011852715508，0.0286655081413075， 0.0615892570124506，-0.040101427234219，0.00471273799312188， -0.0695325837078327，-0.0194435878635383，-0.0113447270023325， -0.052896201189637，0.15391622949438，0.0625317280746324，0.305195811975115， 0.0175140430499281，0.0944330305254164，0.125486034995771 ，0.204097960624017， 0.0139041133925463，0.115503245160239，0.0744749299835659，0.03094011 53645095， 0.0774734185854047，0.128577840642144，-0.00523940764293137， -0.0826725654792668，0.00061718469555555，-0.139447399226457， -0.015892803158233，-0.0776351210087576，-0.114375795737603， 0.506655172546014，0.0139569906287469，0.032593809131997，0.0838209562382717， 0.026889024005808，0.114847700394033，0.0344957168306127，0.309849172983949， 0.224583305802426，0.0920680732068372，0.20205450223499，0.129261938040113， 0.118741527574873，0.0666598681717314，-0.0259685736746482，-0.00493768230442141， -0.0513043909367941，-0.0228292902998043，-0.125120892334107 ， -0.0354061460089046，-0.145910823420589，-0.0505094213129978， -0.357522550450534，-0.0492725484140125，-0.00672879449498781， -0.00498836470563034，0.0857101915123005，0.245202106389044， 0.0652610111098569，0.00803793757485241，0.0456354806905821， 0.0567597911088563,0.155069881077418,0.0398552868265476），方向= c（-1， 1,1,1，-1，-1,1,1 ，1,1,1,1,1,1,1,1,1,1,1,1,1， 1,1，-1，-1，-1，-1，-1，-1， -1，-1，-1，-1，-1,1，-1，-1，-1， 1,1,1,1,1,1,1,1,1，-1 ，-1,1,1，-1，-1，-1，-1，-1， -1，-1，-1，-1，-1,1,1,1，-1 ，-1，-1,1，-1,1,1，-1,1， -1，-1，-1，-1，-1,1,1，-1,1， - 1，-1,1,1,1,1,1,1，-1， -1，-1，-1，-1，-1，-1，-1，-1， - 1，-1,1,1,1，-1，-1，-1， 1，-1，-1,1,1,1,1,1,1,1,1,1， 1,1,1,1,1，-1，-1， -1,1,1,1,1,1,1,1,1,1,1,1,1,1 ，-1，-1,1，-1，-1， -1，-1,1,1,1,1,1,1,1,1,1,1,1,1 ，1，-1，-1，-1， -1，-1，-1，-1，-1，-1，-1，-1，-1,1,1,1,1 ，1,1,1,1）， plotval = c（-4.65436783913808,7.4638390305887，-0.166061251006543， 3.15451610300161,3.3743565041216,3.36193787665198,8.34218160099397， -0.45134660936061，-0.861806358039495,3.14989059429165 ， -0.385424005854277，-2.11343559832442,0.699014672037075， -0.497079129132047，-0.104056259146589，-2。 02963110287305， -3.7673992980343，1.12925537854411，0.744739988834407，-2.95268419318977， -1.36623884628847，4.98189411623867，0.0868661499973576， 3.28662435286223，0.351109352101632，-1.57943969693098，-0.68819795578​​0953， 0.857822769551858，1.73066263028667， - 1.48883721139058，-0.380556286225031， -1.78716235272839，-0.809302569419764，-6.02028725962301， -5.84785296501876，-3.073500877557，-0.967454268269813，-5.38748192000237， -5.57408775663275，-3.96068672995749，7.50597726212444，4.69864253925926， 4.14916000637992，-0.386038843759309，-3.20486151733282， -0.780262082752201，-0.507578804102515，-4.59710189032113， -2.67740750044583，-2.65866587397551，-0.670087259849411， 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2.54589150999432，-2.732443084933，-7.32875220486331，-4.17302493900107， 3.57434916575198，0.607879106033299，0.98877892542788，-4.48550180288597， -0.221261659119412 ，0.562020428705443，-0.749156396749516， -5.90368012822885，-5.81245996063456，-0.039518112762786， 4.49497802290257,0.415792240525927，-2.95213537116121，-0.428878156658466， -1.42292492276573，-0.773816960869839,6.81496956627369），测量，测量，测量，测量，测量，测量，测量，测量，测量， 测量测量测量测量测量测量测量测量测量测量 测量，测量，测量，测量，测量，测量，测量，测量，测量测量，测量，测量，测量，测量，测量，测量，测量，测量，测量 测量测量测量测量测量测量测量测量测量测量测量，测量，测量，测量，测量，测量，测量，测量，测量，测量 ，派生的，派生的，派生的，派生的，派生的，派生的，派生的，派生的派生，派生，派生，派生，派生，派生，派生，派生，衍生 ，派生，派生，派生，派生，派生，派生，派生，派生，衍生派生，派生，派生，派生，派生，派生，派生，衍生 ，派生，派生 ，衍生，衍生，派生，派生，派生，派生，派生，派生，衍生派生，派生，派生，派生，派生，派生，派生，派生 ，派生的，派生的，派生的，派生的，派生的，派生的，派生的，派生的派生，派生，派生，派生，派生，派生，派生，派生，衍生 ，派生，派生，派生，派生，派生，派生，派生，派生，衍生派生，派生，派生，派生，派生，派生，派生，衍生 ，派生的，派生的，派生的，派生的，派生的，派生的，衍生的，派生的 ，.Names = c（Measurement，variable，Pval， （21L， 22L，23L，24L，25L，26L，27L，28L，29L，30L，31L，32L ，33L，34L， 35L，36L，37L，38L，39L，40L，61L，62L，63L，64L，65L，66L，67L， 68L，69L，70L，71L，72L，73L ，74L，75L，76L，77L，78L，79L，80L， 101L，102L，103L，104L，105L，106L，107L，108L，109L，110L，111L，$ b $ 112L，113L，114L ，115L，116L，117L，118L，119L，120L，141L，142L， 143L，144L，145L，146L，147L，148L，149L，150L，151L，152L，153L，$ b $ 154L，155L ，156L，157L，158L，159L，160L，181L，182L，183L，184L， 185L，186L，187L，188L，189L，190L，191L，192L，193L，194L，195L， 196L ，197L，198L，199L，200L，221L，222L，223L，224L，225L，226L， 227L，228L，229L，230L，231L，232L，233L，234L，235L，236L，237L， b 238L，239L，240L，261L，262L，263L，264L，265L，266L，267L，268L， 269L，270L，271L，272L，273L，274L，275L，276L，277L，278L，279L， b $ b 280L，301L，302L，303L，304L，305L，306L，307L，308L，309L，310L， 311L，312L，313L，314L，315L，316L，317L，318L，319L，320L，341L， 342L，343L，344L，345L，346L，347L，348L，349L，350L，351L， 352L， 353L，354L，355L，356L，357L，358L，359L，360L），class =data.frame） 解决方案 选项1 使用构面 mockdata $ type = ifelse（mockdata $ variable％in％LETTERS [1：3]，1，2） ggplot mockdata）+ facet_wrap（〜type，scales ='free_x'）+ geom_tile（aes（variable，Measurement，fill = mockdata $ plotval），color =dark red）+ scale_fill_gradient2（limits = c（-20,20），high =firebrick3，low =dodgerblue4）+ theme_minimal（）+ theme（axis.text.x = element_text（size = 28） ，angle = 90），axis.text.y = element_text（size = 28））+ labs（title =，x =，y =，fill =） 选项3 另一种解决方案是为每个类别创建单独的图并将它们排列在一起。在这里，我使用 cowplot :: plot_grid 将它们放在一起，它允许我们设置相对宽度（我们希望它们的方式）（尽管您可能需要稍微调整rel_widths值以获得它只是正确的）： library（cowplot） p1 scale_fill_gradient2（limits = c（-20，20）=1），]）+ geom_tile ，high =firebrick3，low =dodgerblue4）+ theme_minimal（）+ 主题（axis.text.x = element_text（size = 28，angle = 90），axis.text.y = element_text（size = 28）， legend.position =none）+ labs（title =，x =，y =，fill =） p2 geom_tile（aes（variable，Measurement，fill = plotval），color =dark red ）+ scale_fill_gradient2（limits = c（-20,20），high =firebrick3，low =dodgerblue4）+ theme_minimal（）+ theme（axis.text。 X = element_te xt（size = 28，angle = 90），axis.text.y = element_blank（））+ labs（title =，x =，y =，fill =） plot_grid（p1，p2，nrow = 1，rel_widths = c（1,2）） 选项4 数据中的一个额外因素级别，位于要分隔的列之间，然后以白色为该列绘制图块。 mockdata = rbind（mockdata， data.frame（Measurement = 1：20， variable =， Pval = NA， effect = NA，方向= NA， plotval = 0， category =Measured）） mockdata $ variable = factor（mockdata $ variable，levels = c（A， B，C，，a，b，c，d，e，f）） ggplot（mockdata，aes变量，度量））+ geom_tile（fill = NA，color = NA）+ geom_tile（data = mockdata [which（mockdata $ variable ==），]，fill =white， color =white）+ geom_tile（data = mockdata [which（mockdata $ variable！=），]，aes（fill = plotval），color =dark red）+ scale_fill_gradient2 （limits = c（-20,20），high =firebrick3，low =dodgerblue4）+ theme_minimal（）+ theme（axis.text.x = element_text（size = 28，角度= 90），axis.text.y = element_text（size = 28））+ labs（title =，x =，y =，fill =） I have this heatplot that I've generated using ggplot2.What I would like to do is to add white space between the variables listed in capital letters and the variables listed in lower case letters so as to separate these two categories. I still want the tiles to be of equal width.The code I've used to generate the plot is: ggplot(mockdata, aes(variable, Measurement)) + geom_tile(aes(fill = mockdata$plotval), colour = "dark red") + scale_fill_gradient2(limits=c(-20, 20),high = "firebrick3", low = "dodgerblue4") + theme_minimal() + theme(axis.text.x=element_text(size=28, angle=90), axis.text.y=element_text(size=28)) + labs(title="", x="", y="", fill="")And my data looks as follows:> head(mockdata) Measurement variable Pval effect> direction plotval category 21 20 A 4.511987e+04> -0.004892941 -1 -4.6543678 Measured 22 19 A 3.436853e-08 0.054344854 1 7.4638390 Measured 23 18 A 1.465755e+00 0.355139910 1 -0.1660613 Measured 24> 17 A 7.006222e-04 -0.079390247 -1 3.1545161 Measured 25> 16 A 4.705051e-04 -0.017708611 -1 3.3274357 Measured 26> 15 A 2.301113e+03 -0.022934623 -1 -3.3619379 MeasuredPS. While it is strictly another question, I would also like to edit the legend so that it ranges simply from 0-20 and is split in two vertically, showing on one side the red gradient and the blue gradient on the other.Thank you very much for your help.Edit: dput output as requested dput(mockdata)structure(list(Measurement = structure(c(20L, 19L, 18L, 17L,16L, 15L, 14L, 13L, 12L, 11L, 10L, 9L, 8L, 7L, 6L, 5L, 4L, 3L,2L, 1L, 20L, 19L, 18L, 17L, 16L, 15L, 14L, 13L, 12L, 11L, 10L,9L, 8L, 7L, 6L, 5L, 4L, 3L, 2L, 1L, 20L, 19L, 18L, 17L, 16L,15L, 14L, 13L, 12L, 11L, 10L, 9L, 8L, 7L, 6L, 5L, 4L, 3L, 2L,1L, 20L, 19L, 18L, 17L, 16L, 15L, 14L, 13L, 12L, 11L, 10L, 9L,8L, 7L, 6L, 5L, 4L, 3L, 2L, 1L, 20L, 19L, 18L, 17L, 16L, 15L,14L, 13L, 12L, 11L, 10L, 9L, 8L, 7L, 6L, 5L, 4L, 3L, 2L, 1L,20L, 19L, 18L, 17L, 16L, 15L, 14L, 13L, 12L, 11L, 10L, 9L, 8L,7L, 6L, 5L, 4L, 3L, 2L, 1L, 20L, 19L, 18L, 17L, 16L, 15L, 14L,13L, 12L, 11L, 10L, 9L, 8L, 7L, 6L, 5L, 4L, 3L, 2L, 1L, 20L,19L, 18L, 17L, 16L, 15L, 14L, 13L, 12L, 11L, 10L, 9L, 8L, 7L,6L, 5L, 4L, 3L, 2L, 1L, 20L, 19L, 18L, 17L, 16L, 15L, 14L, 13L,12L, 11L, 10L, 9L, 8L, 7L, 6L, 5L, 4L, 3L, 2L, 1L), .Label = c("1","2", "3", "4", "5", "6", "7", "8", "9", "10", "11", "12", "13","14", "15", "16", "17", "18", "19", "20", "21", "22", "23", "24","25", "26", "27", "28", "29", "30", "31", "32", "33", "34", "35","36", "37", "38", "39", "40"), class = "factor"), variable = structure(c(1L,1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,2L, 2L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L,3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 4L, 4L, 4L, 4L, 4L,4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 5L,5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L,5L, 5L, 5L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L,6L, 6L, 6L, 6L, 6L, 6L, 6L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L,7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 8L, 8L, 8L, 8L, 8L,8L, 8L, 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-2.732443084933, -7.32875220486331, -4.17302493900107, 3.57434916575198, 0.607879106033299, 0.98877892542788, -4.48550180288597, -0.221261659119412, 0.562020428705443, -0.749156396749516, -5.90368012822885, -5.81245996063456, -0.039518112762786, 4.49497802290257, 0.415792240525927, -2.95213537116121, -0.428878156658466, -1.42292492276573, -0.773816960869839, 6.81496956627369), category = c("Measured", "Measured", "Measured", "Measured", "Measured", "Measured", "Measured", "Measured", "Measured", "Measured", "Measured", "Measured", "Measured", "Measured", "Measured", "Measured", "Measured", "Measured", "Measured", "Measured", "Measured", "Measured", "Measured", "Measured", "Measured", "Measured", "Measured", "Measured", "Measured", "Measured", "Measured", "Measured", "Measured", "Measured", "Measured", "Measured", "Measured", "Measured", "Measured", "Measured", "Measured", "Measured", "Measured", "Measured", "Measured", "Measured", "Measured", "Measured", "Measured", "Measured", 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"Derived", "Derived", "Derived", "Derived", "Derived", "Derived", "Derived", "Derived", "Derived", "Derived", "Derived", "Derived", "Derived", "Derived", "Derived", "Derived", "Derived", "Derived", "Derived", "Derived", "Derived", "Derived", "Derived", "Derived", "Derived", "Derived", "Derived", "Derived", "Derived", "Derived", "Derived", "Derived", "Derived", "Derived", "Derived", "Derived", "Derived", "Derived", "Derived", "Derived")), .Names = c("Measurement", "variable", "Pval","effect", "direction", "plotval", "category"), row.names = c(21L,22L, 23L, 24L, 25L, 26L, 27L, 28L, 29L, 30L, 31L, 32L, 33L, 34L,35L, 36L, 37L, 38L, 39L, 40L, 61L, 62L, 63L, 64L, 65L, 66L, 67L,68L, 69L, 70L, 71L, 72L, 73L, 74L, 75L, 76L, 77L, 78L, 79L, 80L,101L, 102L, 103L, 104L, 105L, 106L, 107L, 108L, 109L, 110L, 111L,112L, 113L, 114L, 115L, 116L, 117L, 118L, 119L, 120L, 141L, 142L,143L, 144L, 145L, 146L, 147L, 148L, 149L, 150L, 151L, 152L, 153L,154L, 155L, 156L, 157L, 158L, 159L, 160L, 181L, 182L, 183L, 184L,185L, 186L, 187L, 188L, 189L, 190L, 191L, 192L, 193L, 194L, 195L,196L, 197L, 198L, 199L, 200L, 221L, 222L, 223L, 224L, 225L, 226L,227L, 228L, 229L, 230L, 231L, 232L, 233L, 234L, 235L, 236L, 237L,238L, 239L, 240L, 261L, 262L, 263L, 264L, 265L, 266L, 267L, 268L,269L, 270L, 271L, 272L, 273L, 274L, 275L, 276L, 277L, 278L, 279L,280L, 301L, 302L, 303L, 304L, 305L, 306L, 307L, 308L, 309L, 310L,311L, 312L, 313L, 314L, 315L, 316L, 317L, 318L, 319L, 320L, 341L,342L, 343L, 344L, 345L, 346L, 347L, 348L, 349L, 350L, 351L, 352L,353L, 354L, 355L, 356L, 357L, 358L, 359L, 360L), class = "data.frame") 解决方案 Option 1Use facetsmockdata$type = ifelse(mockdata$variable %in% LETTERS[1:3], "1", "2")ggplot(mockdata) + facet_wrap(~ type, scales='free_x') + geom_tile(aes(variable, Measurement, fill = mockdata$plotval), colour = "dark red") + scale_fill_gradient2(limits=c(-20, 20),high = "firebrick3", low = "dodgerblue4") + theme_minimal() + theme(axis.text.x=element_text(size=28, angle=90), axis.text.y=element_text(size=28)) + labs(title="", x="", y="", fill="")Although this is not quite perfect, because dropping the unused x-axis categories from each facet requires specifying scales='free_x' - which unfortunately does not keep the boxes the same width in each facet.Option2To remedy this we can also set space="free_x" in facet_grid. Which I think gives what you are looking for:ggplot(mockdata) + facet_grid(~ type, scales='free_x', space="free_x") + geom_tile(aes(variable, Measurement, fill = mockdata$plotval), colour = "dark red") + scale_fill_gradient2(limits=c(-20, 20),high = "firebrick3", low = "dodgerblue4") + theme_minimal() + theme(axis.text.x=element_text(size=28, angle=90), axis.text.y=element_text(size=28)) + labs(title="", x="", y="", fill="")Option 3An alternative solution is to create separate plots for each category, and arrange them together. Here I put them together using cowplot::plot_grid, which allows us to set the relative widths how we want them (although you may need to tweak the rel_widths values a bit to get it just right):library(cowplot)p1 <- ggplot(mockdata[which(mockdata$type=="1"),]) + geom_tile(aes(variable, Measurement, fill = plotval), colour = "dark red") + scale_fill_gradient2(limits=c(-20, 20), high = "firebrick3", low = "dodgerblue4") + theme_minimal() + theme(axis.text.x=element_text(size=28, angle=90), axis.text.y=element_text(size=28), legend.position="none") + labs(title="", x="", y="", fill="")p2 <- ggplot(mockdata[which(mockdata$type=="2"),]) + geom_tile(aes(variable, Measurement, fill = plotval), colour = "dark red") + scale_fill_gradient2(limits=c(-20, 20),high = "firebrick3", low = "dodgerblue4") + theme_minimal() + theme(axis.text.x=element_text(size=28, angle=90), axis.text.y=element_blank()) + labs(title="", x="", y="", fill="")plot_grid(p1,p2, nrow = 1, rel_widths = c(1,2))Option 4You can create an extra factor level in the data, which lies between the columns you want to separate, and then plot tiles for that column in white.mockdata = rbind(mockdata, data.frame(Measurement=1:20, variable="", Pval = NA, effect = NA, direction = NA, plotval = 0, category = "Measured"))mockdata$variable = factor(mockdata$variable, levels = c("A", "B", "C", "", "a", "b", "c", "d", "e","f"))ggplot(mockdata, aes(variable, Measurement)) + geom_tile(fill = NA, colour = NA) + geom_tile(data = mockdata[which(mockdata$variable==""),], fill = "white", colour = "white") + geom_tile(data = mockdata[which(mockdata$variable!=""),], aes(fill = plotval), colour = "dark red") + scale_fill_gradient2(limits=c(-20, 20),high = "firebrick3", low = "dodgerblue4") + theme_minimal() + theme(axis.text.x=element_text(size=28, angle=90), axis.text.y=element_text(size=28)) + labs(title="", x="", y="", fill="") 这篇关于在heatplot ggplot瓷砖之间的空白区域的文章就介绍到这了，希望我们推荐的答案对大家有所帮助，也希望大家多多支持！ 上岸，阿里云！