Я бы хотел, чтобы на моей карте тепла было больше оттенков. Может ли кто-нибудь помочь мне в этом? Я также добавил сводку моего набора матричных данных.
Код тепловой карты, который я использовал, выглядит следующим образом:
heatmap.2(matrix,
Rowv = NA,
main = "Cost Rankings Per DRG Definiion (Darker Shade = More Expensive) ",
xlab = "DRG Definition ID",
ylab = "States",
Colv = NA,
scale = "column",
col = coul,
key = FALSE,
margins = c(5,5),
cexRow = 0.9,
cexCol = 0.9,
trace = "none")
Резюме набора данных матрицы выглядит следующим образом:
> dput(head(matrix,4))
matrix <- structure(c(156023.01, 934292.2, 565543.16, 859246.77, NA, 647281.97,
243467.03, 222016.05, 279984.88, 1785117.72, 1210217.08, 1738388.11,
277346.4, 3231424.9, 1784411.7, 2539940.3, 39613, 1146810.7,
529727.86, 986997.67, 29115.06, 1411979.35, 664273.27, 668479.85,
16767.96, 252979.91, 129183.95, 194504.99, 12812.02, 341007.53,
217723.31, 332953.97, 97131.88, 1128489.3, 282132.58, 668881.61,
20812.06, 429211.14, 256513.98, 811319.88, 17672.06, 778513.41,
376581.5, 883744.04, 66327.99, 1895388.92, 1139218.24, 1770164.66,
NA, 693016.78, 552007.41, 483426.1, NA, 307001.14, 219478.09,
235900.24, 420942.2, 3237765.7, 2324077.5, 3454459.9, 170549.8,
4283642.2, 1847497.8, 2111693.5, 80660.06, 2899429.18, 1182813.4,
868823.54, 21812, 1623755.28, 750785.96, 255470.21, 176095.6,
3042375.8, 2571992.4, 3845886.7, 212915.5, 4328484.6, 2354857.9,
2539054.7, 12795.97, 1428190.5, 845619.16, 739186.61, NA, 1088842.33,
276199.76, 354687.38, 14492.04, 1030805.76, 662401.33, 201840.91,
150853.3, 1650354.2, 1062210.5, 1191047.2, 93799.96, 1971933.46,
1004648.69, 942096.11, 53320.05, 607153.18, 536816.15, 675263.5,
449583.08, 1566839.43, 1216058.46, 1328317.78, 480714.9, 4432956,
2923127.9, 3734036.4, 30351.03, 1845418.4, 490566.1, 887689.86,
16899.87, 1417434.85, 537916.35, 957364.87, 119628.09, 554514.83,
503740.9, 735597.21, 60498.78, 1570577.33, 831183.79, 1284620.01,
69819, 1056405.42, 527309.68, 834961.1, 21140.01, 305148.39,
242055.17, 344205.12, 17556.07, 1373699.99, 575169.49, 946223.42,
120249.7, 3356762.9, 1830277.9, 1718258.6, 173518.6, 5074740.2,
2559276.8, 3491265, 243682.9, 4208010.3, 2177208.7, 2206312.8,
NA, 1164790.25, 734920.03, 385705.88, NA, 621862.56, 224061.47,
522187.25, NA, 420800.25, 142957.08, 89689.84, 68628, 1598802.4,
1007628.56, 1392052.55, 79459.91, 2167594.41, 1331532.99, 1787127.24,
80123.96, 1938321.88, 1367553.22, 1591825.51, 45644.95, 1846231.61,
845857.62, 799940.15, NA, 1743574.39, 483080.63, 488160.78, 22002.93,
1176770.78, 615141.82, 822419.76, 142209.15, 1812647.04, 786067.87,
1386309.67, 157990.4, 2685450.6, 1340283, 2853758.4, 97889.07,
1061083.38, 472556.81, 854388.81, 8565, 265924.46, 181199.06,
385888.2, NA, 567851.31, 392844.96, 565664.86, 203578.2, 1348414.4,
689989.1, 744118.2, 223589.1, 2988292, 1905895.2, 2254702.6,
NA, 460544.17, 140055.94, 184764.15, 44512, 958991.29, 734571.16,
1304339.5, 102656.06, 532474.07, 490331.13, 631933.61, 23193.11,
1322236.32, 415219.48, 577760.96, 289623.7, 6196698.2, 2691164.3,
3177288.4, 14978.88, 416428.11, 237793.89, 490808.12, 12587.9,
1015188.63, 427300.91, 718612.47, 27119.99, 794509.58, 313906.99,
629300.12, NA, 586226.22, 313110.32, 368281.97, 324313, 5000112.2,
2627556.1, 6328867.9, 101877.93, 1309521.19, 336968.01, 756488.94,
3443081, NA, NA, 26893877, 279713.2, 2260306.77, 715682.74, 1102111.17,
130221.96, 511929.23, 459850.58, 700773.81, 125233.9, 2377996.8,
1422292.5, 2330577.8, 12795.97, 518757.02, 515278.91, 618813.29,
163937.1, 1974857.3, 1676696.6, 3153277.4, NA, 405244.61, 238980.44,
278851, 135444.01, 981475.9, 526980.36, 764349.78, NA, 323890.23,
115054.89, 196663.15, NA, 444982.29, 335713.04, 313231.83, 235511.7,
3305858.6, 1296704.2, 2488698.1, NA, 580699.06, 449820.87, 410445.08,
34358.09, 1280896.67, 622115.43, 668290.15, 42067.62, 1362265.93,
748922.71, 1056568.71, 97188.08, 2612222.56, 1242745.79, 1366078.34,
117417.9, 2473766.6, 2048573.4, 1876080.3, 102559.6, 3149369,
2145636.7, 2414000.4, NA, 467014.79, 236454.04, 101899.06, 35960.04,
1760857.28, 1162040.99, 961624.76, 167320.9, 4204619.6, 1946831,
2103738, 32832.06, 878445, 625553.25, 1276837.06, NA, 356360.58,
293533.81, 567421.3, NA, 399723.77, 190391.18, 203457.08, 17524.08,
2140499.87, 741313.57, 593964.5, 502218.4, 5504568.4, 2482709.2,
4211229.8, 18708, 467092.41, 349188.9, 924921.44, 239522.08,
759303.93, 512292.32, 953998.01, 1158785.1, 11099233.1, 7970719.5,
13551004.4, 316024.5, 3121648.4, 1856544.4, 4538276.4, 20075.97,
738001.2, 368133.88, 57265.05, 60165.82, 908034.41, 594996, 720468.54,
24470.14, 547284.37, 312695.13, 85743.16, 19392.96, 878525.54,
397145.31, 351113.64, 92456.64, 2751536.61, 946755.13, 1783122.25,
NA, 778701.49, 277180.9, 721653.54), .Dim = c(4L, 100L), .Dimnames =
list(
c("AK", "AL", "AR", "AZ"), c("039 ", "057 ", "064 ", "065 ",
"066 ", "069 ", "092 ", "100 ", "101 ", "175 ", "176 ", "177 ",
"178 ", "180 ", "189 ", "190 ", "191 ", "192 ", "193 ", "194 ",
"195 ", "202 ", "207 ", "208 ", "234 ", "243 ", "246 ", "247 ",
"252 ", "253 ", "269 ", "280 ", "281 ", "282 ", "286 ", "287 ",
"291 ", "292 ", "293 ", "300 ", "305 ", "308 ", "309 ", "310 ",
"312 ", "313 ", "314 ", "329 ", "330 ", "331 ", "371 ", "372 ",
"377 ", "378 ", "379 ", "389 ", "390 ", "391 ", "392 ", "393 ",
"394 ", "418 ", "439 ", "460 ", "469 ", "470 ", "473 ", "480 ",
"481 ", "482 ", "483 ", "536 ", "552 ", "563 ", "602 ", "603 ",
"637 ", "638 ", "640 ", "641 ", "682 ", "683 ", "684 ", "689 ",
"690 ", "698 ", "699 ", "811 ", "812 ", "853 ", "854 ", "870 ",
"871 ", "872 ", "897 ", "917 ", "918 ", "948 ", "981 ", "982 "
)))