facet violin plot with ggplot2 trying to use space

Question

I am trying to produce a set of violin plots in separate facets, I have two categorical variables; one (Thres) which I am using to split the data into separate facets and a second one (NSNP) that I am using within each facet to plot separate violin plots for each condition.

I manage to produce the faceted graph fine but there are some combinations of the two categorical variables that are empty, producing gaps in some of the facets.

When I run the code below I get 7 facets and in the top 6 facets I don't have any values at 0 and on the bottom facet I don't have any values for 1-3 so there are gaps in the graphs. What I want to do is alter the y axis (or x as these graphs are flipped) of the facets so that the gaps don't appear. I thought this would be possible with scale = "free_x", then space = "free_x would adjust the size of the facets to the proportion of the number of violin plots. However this is not working.

Below is the code used to plot this graph and a subset of the data:

mydat3<-structure(list(values = c(0.095859549802147, 0.0464175342967273, 
0.0645501085582447, 0.0561315693403545, 0.0877787999642726, 0.0642197694344365, 
0.0572295087554683, 0.0443288995522364, 0.222621590122593, 0.0740180403310751, 
0.0374859692788302, 0.0649844262623869, 0.0477535429985445, 0.0578778559220613, 
0.124747971382994, 0.0420499183212924, 0.0608272849856844, 0.109997854535794, 
0.040810873046286, 0.0355291667607834, 0.0423016408325608, 0.0640249415590838, 
0.0631025124242698, 0.0411585961572307, 0.136957487216637, 0.0387811092625465, 
0.0718037442496459, 0.116606405377969, 0.0528890074588327, 0.0499231878553924, 
0.0534992620063799, 0.0947230498828188, 0.0883366814920039, 0.11384526623344, 
0.0687251526902865, 0.0357594877478181, 0.0375677751221073, 0.119793765548604, 
0.0500635079856242, 0.0757449093875329, 0.0463374386715252, 0.0583236969356681, 
0.0604792057680754, 0.0434423378024008, 0.052136262404202, 0.0430064406231872, 
0.0444112355025033, 0.0418896505775744, 0.0757469496352429, 0.0758996304800777, 
0.0428211439773155, 0.0492493504318606, 0.0460689699781013, 0.0350046476282005, 
0.0887832511289573, 0.0356368589361509, 0.0688351644690967, 0.0600420393848446, 
0.0477733282447943, 0.0502100159694551, 0.0787171457052969, 0.0751271656818236, 
0.0531879475355363, 0.0382722034225811, 0.035657219042404, 0.0389456460835204, 
0.0829960042140691, 0.0402727425198968, 0.0525990459535811, 0.0947979557634847, 
0.095130322005081, 0.0551447680805923, 0.055276571931073, 0.0556015731060283, 
0.0527454033481276, 0.0876700035871922, 0.0391599523515732, 0.0680024630785036, 
0.0905942423608025, 0.0639705989556369, 0.0590999197252122, 0.0814456268099261, 
0.0634189563885887, 0.0990217355953055, 0.0797654619911409, 0.045421303951918, 
0.0517178455574364, 0.0386867009753076, 0.0850274903685002, 0.0445797895112061, 
0.116564307393344, 0.038772531323172, 0.0621098771850116, 0.0348079128242265, 
0.10267105504507, 0.0715667696309822, 0.0438896766810641, 0.066568373657306, 
0.144406789469503, 0.0511856755979947, 0.0591439320668585, 0.0639941302879705, 
0.0564336074213047, 0.0504141098122474, 0.0532264855281964, 0.118145668980743, 
0.0491686829848695, 0.0625301117449126, 0.0353124997786777, 0.0756394390521888, 
0.0440626375469502, 0.0739048800419004, 0.0755801825925368, 0.0479095569739974, 
0.0366314438481509, 0.0615842885408238, 0.0363103805418523, 0.10642984356638, 
0.0764325237077806, 0.0509339599422938, 0.0393960284693845, 0.0373715456967969, 
0.0573340180311538, 0.0758040570580679, 0.0397290988766974, 0.0793429331504033, 
0.124620160674225, 0.0732741719432426, 0.0370684018084896, 0.0476385737967006, 
0.0597815734883134, 0.0562108125435101, 0.158564982549544, 0.0617660377137849, 
0.071804618279066, 0.0368174737649545, 0.0647498178876398, 0.0732395320154573, 
0.0814831305316639, 0.0612397928970058, 0.0959496476808134, 0.0459966223425876, 
0.0541987769424167, 0.0860931786221091, 0.0736220596207053, 0.0363665246832541, 
0.0874935850613301, 0.0525685223267564, 0.0529802277676731, 0.0652507657024711, 
0.0670781253098693, 0.0733998516445914, 0.0891335745005303, 0.0358838922328816, 
0.0353689609691281, 0.0955191513612327, 0.0350167098226862, 0.0628618588604291, 
0.0894348094605337, 0.0775709383187923, 0.0564545046951287, 0.0590306428878671, 
0.0431026022687549, 0.0352473914227291, 0.0824650449374406, 0.0433132254279204, 
0.0903319052544356, 0.0725367709023878, 0.074030363918439, 0.0358618642485878, 
0.0528328796271687, 0.0500283680499483, 0.0449320705005457, 0.0614653031170808, 
0.040769843945677, 0.143428459338737, 0.0698243152427977, 0.0477887900201451, 
0.0747315421364465, 0.119311284945825, 0.0352643913256084, 0.0784914420073424, 
0.0491393826410522, 0.0355805581325951, 0.15570636077347, 0.035497104091947, 
0.0574371100825385, 0.0353842603034302, 0.037352604229049, 0.0391887921986735, 
0.0797965714402714, 0.0620930251697114, 0.0415559243262849, 0.0692348409636982, 
0.0481644739268709, 0.0379875120963265, 0.0642578402415982, 0.0663484169892082, 
0.0546726909263926, 0.108776260865374), NSNP = structure(c(2L, 
3L, 4L, 3L, 3L, 2L, 4L, 2L, 4L, 3L, 2L, 2L, 2L, 4L, 4L, 3L, 2L, 
2L, 2L, 4L, 2L, 4L, 2L, 2L, 4L, 2L, 3L, 2L, 4L, 2L, 2L, 4L, 4L, 
4L, 3L, 1L, 1L, 3L, 2L, 2L, 2L, 2L, 2L, 2L, 3L, 4L, 4L, 2L, 2L, 
2L, 4L, 2L, 2L, 4L, 4L, 4L, 3L, 4L, 3L, 3L, 2L, 3L, 2L, 1L, 4L, 
4L, 2L, 4L, 2L, 3L, 2L, 1L, 3L, 3L, 3L, 4L, 4L, 4L, 2L, 4L, 2L, 
4L, 3L, 2L, 3L, 4L, 4L, 4L, 3L, 2L, 3L, 4L, 3L, 2L, 3L, 2L, 3L, 
3L, 4L, 2L, 2L, 2L, 2L, 4L, 4L, 2L, 2L, 4L, 2L, 4L, 3L, 3L, 3L, 
2L, 1L, 4L, 3L, 2L, 4L, 3L, 2L, 2L, 3L, 2L, 1L, 3L, 3L, 2L, 2L, 
2L, 2L, 3L, 2L, 2L, 3L, 4L, 2L, 2L, 4L, 4L, 2L, 3L, 2L, 3L, 3L, 
2L, 2L, 2L, 4L, 2L, 2L, 3L, 3L, 4L, 3L, 3L, 2L, 3L, 3L, 2L, 2L, 
3L, 2L, 3L, 2L, 3L, 3L, 3L, 4L, 1L, 3L, 3L, 3L, 2L, 4L, 4L, 2L, 
3L, 3L, 3L, 2L, 3L, 2L, 3L, 2L, 4L, 1L, 4L, 1L, 1L, 2L, 3L, 2L, 
1L, 2L, 4L, 2L, 4L, 3L, 4L), .Label = c("1", "2", "3", "4"), class = "factor"), 
    Thres = structure(c(2L, 4L, 4L, 6L, 4L, 3L, 3L, 2L, 6L, 4L, 
    5L, 3L, 3L, 2L, 5L, 4L, 1L, 5L, 1L, 3L, 3L, 1L, 1L, 2L, 1L, 
    2L, 3L, 5L, 1L, 4L, 3L, 1L, 3L, 5L, 3L, 7L, 7L, 3L, 6L, 1L, 
    2L, 3L, 2L, 6L, 1L, 3L, 4L, 2L, 4L, 2L, 1L, 3L, 2L, 6L, 3L, 
    4L, 5L, 3L, 2L, 3L, 3L, 4L, 2L, 7L, 6L, 6L, 4L, 1L, 6L, 5L, 
    6L, 7L, 4L, 4L, 5L, 2L, 4L, 1L, 3L, 3L, 4L, 5L, 4L, 4L, 4L, 
    2L, 5L, 2L, 6L, 6L, 6L, 5L, 5L, 4L, 3L, 5L, 2L, 3L, 3L, 5L, 
    6L, 2L, 2L, 5L, 4L, 4L, 4L, 3L, 2L, 1L, 5L, 2L, 6L, 3L, 7L, 
    3L, 1L, 1L, 1L, 4L, 1L, 5L, 5L, 3L, 7L, 1L, 5L, 6L, 1L, 6L, 
    1L, 1L, 5L, 4L, 3L, 3L, 2L, 2L, 4L, 5L, 3L, 6L, 5L, 3L, 5L, 
    3L, 5L, 5L, 5L, 6L, 4L, 5L, 3L, 5L, 2L, 5L, 1L, 4L, 1L, 4L, 
    3L, 4L, 3L, 6L, 5L, 1L, 4L, 3L, 1L, 7L, 6L, 4L, 3L, 5L, 5L, 
    1L, 3L, 4L, 5L, 6L, 4L, 2L, 2L, 4L, 4L, 2L, 7L, 4L, 7L, 7L, 
    1L, 4L, 6L, 7L, 4L, 5L, 4L, 3L, 1L, 3L), .Label = c("0.8", 
    "0.82", "0.84", "0.86", "0.88", "0.9", "All"), class = "factor")), .Names = c("values", 
"NSNP", "Thres"), row.names = c(417387L, 987453L, 1120252L, 1589400L, 
971693L, 615757L, 847346L, 410925L, 1608540L, 1014470L, 1205725L, 
685241L, 663860L, 544104L, 1352348L, 978475L, 98571L, 1195361L, 
143201L, 829504L, 641176L, 341040L, 169825L, 425417L, 276036L, 
408672L, 720953L, 1191303L, 286624L, 903611L, 622910L, 327340L, 
790653L, 1396838L, 718503L, 82077L, 88491L, 749871L, 1454937L, 
121248L, 384249L, 653470L, 360233L, 1494330L, 239841L, 864825L, 
1074417L, 410545L, 920891L, 400393L, 326761L, 641876L, 401975L, 
1653154L, 822327L, 1053389L, 1240346L, 794594L, 486644L, 768056L, 
621590L, 1035600L, 394602L, 28528L, 1679232L, 1629924L, 919937L, 
332013L, 1414295L, 1317675L, 1473269L, 54407L, 1004545L, 992729L, 
1239328L, 550396L, 1088133L, 335236L, 670946L, 779868L, 920505L, 
1387472L, 1036523L, 909955L, 1006071L, 601045L, 1408820L, 598883L, 
1523182L, 1427672L, 1560314L, 1332208L, 1276817L, 880601L, 693423L, 
1157790L, 467721L, 768804L, 859699L, 1209937L, 1430736L, 372811L, 
394230L, 1369202L, 1054401L, 941276L, 877757L, 810209L, 385949L, 
284348L, 1317120L, 495510L, 1544732L, 652690L, 86507L, 846850L, 
217125L, 131391L, 286462L, 992319L, 151147L, 1226911L, 1305568L, 
632777L, 77445L, 252553L, 1288795L, 1467461L, 145905L, 1496846L, 
94403L, 234111L, 1177327L, 888364L, 737615L, 861742L, 398363L, 
356937L, 1127527L, 1337220L, 655199L, 1529402L, 1216012L, 756415L, 
1257172L, 637334L, 1202243L, 1212484L, 1342293L, 1411642L, 882076L, 
1246269L, 736798L, 1385152L, 452031L, 1239335L, 113083L, 1044007L, 
254527L, 875129L, 605332L, 1023917L, 644542L, 1574340L, 1192809L, 
180477L, 1010220L, 692625L, 298466L, 59057L, 1521617L, 1034449L, 
738916L, 1179635L, 1349147L, 337861L, 674869L, 995497L, 1230818L, 
1588357L, 901193L, 444274L, 397085L, 1018475L, 953867L, 520349L, 
37323L, 1070478L, 51129L, 527L, 160676L, 994120L, 1493324L, 19218L, 
873355L, 1362670L, 869612L, 817322L, 209286L, 788913L), class = "data.frame")

library(ggplot2)

ggplot(mydat3, aes(x=NSNP, y=values)) +geom_violin(aes(fill = NSNP)) + facet_grid(Thres ~ ., scale = "free_x", space = "free") + coord_flip() +opts(strip.text.y = theme_text()) + scale_x_discrete(breaks = c(1,2,3,4), labels = c("0", "1", "2", "3"))+ xlab("Up to N SNPs adjusted") + ylab("Standard Error of Beta Coefficient")+opts(legend.position = "none")

Thanks