library(smps)
data("my_data")
str(my_data)
## 'data.frame': 432 obs. of 108 variables:
## $ Time : Factor w/ 432 levels "26/1/2013 0:00",..: 1 2 3 4 5 6 7 8 9 10 ...
## $ X14.6 : num 27393 31047 36137 33007 27651 ...
## $ X15.1 : num 26204 34661 37409 31984 26345 ...
## $ X15.7 : num 25220 35277 35012 31267 25566 ...
## $ X16.3 : num 25819 31987 34805 28874 25760 ...
## $ X16.8 : num 24974 32601 35361 28993 25597 ...
## $ X17.5 : num 25376 32194 35349 28487 25423 ...
## $ X18.1 : num 25330 31129 34793 29773 25152 ...
## $ X18.8 : num 25885 30635 35873 28281 23328 ...
## $ X19.5 : num 25425 30659 39081 27967 24068 ...
## $ X20.2 : num 24666 30432 41410 29033 24604 ...
## $ X20.9 : num 24804 31174 41826 27446 24509 ...
## $ X21.7 : num 23731 30975 43151 28142 25482 ...
## $ X22.5 : num 24502 29641 42619 28270 25833 ...
## $ X23.3 : num 24650 30145 43349 28395 25358 ...
## $ X24.1 : num 23596 30479 42121 28127 24014 ...
## $ X25 : num 24051 30061 39618 27955 25756 ...
## $ X25.9 : num 24583 31096 38796 28784 25896 ...
## $ X26.9 : num 24897 27738 42975 28572 25562 ...
## $ X27.9 : num 25342 29937 41774 28141 24897 ...
## $ X28.9 : num 26568 31921 44037 29375 26774 ...
## $ X30 : num 26440 32112 45057 29525 27318 ...
## $ X31.1 : num 27705 32465 45251 31177 27370 ...
## $ X32.2 : num 26996 34146 47222 30016 28296 ...
## $ X33.4 : num 28163 33793 46819 31889 28288 ...
## $ X34.6 : num 27743 34096 48882 32295 29305 ...
## $ X35.9 : num 29278 35232 47981 31875 28882 ...
## $ X37.2 : num 28587 35849 49107 32932 30200 ...
## $ X38.5 : num 29455 37041 50719 32359 30610 ...
## $ X40 : num 31269 37702 51056 34492 30898 ...
## $ X41.4 : num 30283 38281 52157 33798 30604 ...
## $ X42.9 : num 31541 39211 52819 34451 31874 ...
## $ X44.5 : num 30828 38821 52035 34902 32879 ...
## $ X46.1 : num 31964 38659 51876 34298 32178 ...
## $ X47.8 : num 32573 39788 51641 34052 32228 ...
## $ X49.6 : num 31116 40798 52268 34365 32499 ...
## $ X51.4 : num 32524 39272 51982 34832 32921 ...
## $ X53.3 : num 32327 40443 52656 33546 31500 ...
## $ X55.2 : num 31674 39108 52203 32887 30715 ...
## $ X57.3 : num 31056 38077 52569 32007 30742 ...
## $ X59.4 : num 30760 38213 50726 30572 29802 ...
## $ X61.5 : num 29905 37618 51105 29077 28519 ...
## $ X63.8 : num 30154 36147 49294 28938 27459 ...
## $ X66.1 : num 27786 35113 47807 25765 25615 ...
## $ X68.5 : num 27254 32618 44692 25508 24396 ...
## $ X71 : num 26019 32574 43081 24034 23839 ...
## $ X73.7 : num 23548 30457 41225 21934 22854 ...
## $ X76.4 : num 22505 28780 39429 21140 21200 ...
## $ X79.1 : num 21524 27119 36815 19278 20328 ...
## $ X82 : num 19108 24585 35272 18734 19384 ...
## $ X85.1 : num 18154 23598 31560 18341 18037 ...
## $ X88.2 : num 16617 22394 29478 16396 17380 ...
## $ X91.4 : num 15856 20817 28665 15870 16639 ...
## $ X94.7 : num 16032 19636 28074 15115 15604 ...
## $ X98.2 : num 14018 19251 25859 14225 15398 ...
## $ X101.8: num 13765 17941 25354 13251 14777 ...
## $ X105.5: num 13740 16745 22308 12534 13708 ...
## $ X109.4: num 11833 16773 19425 11389 12730 ...
## $ X113.4: num 10845 15591 17264 10808 12595 ...
## $ X117.6: num 11083 14828 15375 10469 11538 ...
## $ X121.9: num 10558 13564 14723 9852 10529 ...
## $ X126.3: num 9566 13693 14114 9447 10000 ...
## $ X131 : num 8995 12479 12769 9085 9073 ...
## $ X135.8: num 8488 11839 12220 8695 8734 ...
## $ X140.7: num 7845 12307 10987 8537 8018 ...
## $ X145.9: num 7875 11250 10321 8030 7782 ...
## $ X151.2: num 7621 10238 9589 7518 7660 ...
## $ X156.8: num 7727 10173 8425 7114 7639 ...
## $ X162.5: num 7142 8922 8545 6901 7014 ...
## $ X168.5: num 7003 9245 7493 6335 6729 ...
## $ X174.7: num 6695 9179 7793 6589 6707 ...
## $ X181.1: num 6328 8073 7133 6384 6634 ...
## $ X187.7: num 6581 7475 6967 6273 6526 ...
## $ X194.6: num 5826 6891 6723 5874 6483 ...
## $ X201.7: num 5380 7361 7016 5659 5625 ...
## $ X209.1: num 5646 6673 6004 5458 5701 ...
## $ X216.7: num 5277 5392 5551 5050 4935 ...
## $ X224.7: num 4368 5406 5101 4591 4755 ...
## $ X232.9: num 4176 4826 4647 3711 3840 ...
## $ X241.4: num 3429 3819 3755 3199 3277 ...
## $ X250.3: num 3083 3207 3670 2940 2960 ...
## $ X259.5: num 2199 2658 2692 2427 2309 ...
## $ X269 : num 2214 2608 2311 2043 2213 ...
## $ X278.8: num 1519 1944 1973 1521 1595 ...
## $ X289 : num 956 1358 1284 1321 1302 ...
## $ X299.6: num 811 911 996 1003 905 ...
## $ X310.6: num 713 872 919 794 802 ...
## $ X322 : num 534 645 668 622 466 ...
## $ X333.8: num 357 482 555 282 502 ...
## $ X346 : num 206 321 444 355 346 ...
## $ X358.7: num 233 230 420 279 297 ...
## $ X371.8: num 255 258 303 189 139 ...
## $ X385.4: num 229 205 197 168 227 ...
## $ X399.5: num 111 164 277 178 157 ...
## $ X414.2: num 97 103.9 93.7 157.8 38.2 ...
## $ X429.4: num 75.6 124.8 174.1 37.5 62 ...
## $ X445.1: num 99.7 75 137.8 62.8 50.7 ...
## $ X461.4: num 64.1 89.8 51.3 38.5 76.5 ...
## $ X478.3: num 24.6 13.1 91.6 24.6 37.7 ...
## [list output truncated]
## Time X14.6 X15.1 X15.7 X16.3 X16.8 X17.5 X18.1
## 1 26/1/2013 0:00 27392.60 26203.60 25219.60 25818.53 24973.97 25376.35 25330.22
## 2 26/1/2013 0:10 31047.28 34661.20 35277.07 31987.20 32600.58 32193.78 31128.92
## 3 26/1/2013 0:20 36136.68 37409.15 35012.03 34804.53 35361.32 35349.00 34792.60
## 4 26/1/2013 0:30 33006.95 31983.53 31267.40 28873.65 28992.78 28486.97 29773.35
## 5 26/1/2013 0:40 27651.03 26344.67 25565.62 25760.05 25597.08 25423.15 25152.10
## 6 26/1/2013 0:50 25031.03 24491.15 25206.40 24488.50 23408.55 25162.00 25020.45
## X18.8 X19.5 X20.2 X20.9 X21.7 X22.5 X23.3 X24.1
## 1 25884.50 25425.28 24666.38 24803.95 23730.55 24502.30 24650.30 23596.47
## 2 30635.17 30658.78 30432.40 31173.90 30974.95 29641.20 30145.33 30479.28
## 3 35872.95 39080.62 41410.20 41826.12 43150.70 42618.80 43349.12 42121.28
## 4 28281.05 27966.53 29033.28 27446.00 28142.35 28269.90 28395.30 28126.97
## 5 23327.75 24068.03 24603.65 24508.55 25482.15 25832.55 25357.60 24014.38
## 6 24343.25 23316.53 23857.28 24196.30 23647.47 23194.83 22203.72 23501.62
## X25 X25.9 X26.9 X27.9 X28.9 X30 X31.1 X32.2
## 1 24051.30 24582.92 24897.22 25342.08 26567.95 26439.70 27704.92 26995.58
## 2 30061.03 31096.08 27737.78 29936.97 31920.75 32112.45 32464.95 34146.10
## 3 39618.30 38796.47 42975.47 41774.40 44036.62 45056.85 45250.53 47222.32
## 4 27955.22 28783.90 28571.78 28140.60 29374.95 29525.03 31177.20 30015.53
## 5 25755.90 25896.30 25562.38 24897.25 26773.58 27317.72 27370.35 28295.88
## 6 23257.97 23927.85 22994.55 24323.92 25543.42 25081.53 24464.03 25008.60
## X33.4 X34.6 X35.9 X37.2 X38.5 X40 X41.4 X42.9
## 1 28162.60 27742.55 29278.47 28586.78 29455.28 31268.95 30283.10 31541.33
## 2 33793.30 34095.88 35231.85 35849.05 37040.97 37702.03 38281.20 39211.25
## 3 46819.38 48881.68 47980.55 49107.20 50719.28 51055.97 52157.47 52818.70
## 4 31889.12 32294.78 31874.62 32931.68 32359.00 34492.43 33798.40 34450.88
## 5 28287.62 29304.70 28881.53 30199.83 30609.75 30897.78 30604.40 31874.28
## 6 25964.30 27698.40 27603.22 27882.65 28390.58 29352.72 30053.42 29562.05
## X44.5 X46.1 X47.8 X49.6 X51.4 X53.3 X55.2 X57.3
## 1 30828.08 31964.00 32573.33 31115.60 32524.42 32327.00 31674.08 31055.78
## 2 38821.00 38658.80 39788.00 40797.57 39272.35 40443.30 39108.35 38077.18
## 3 52035.18 51875.75 51641.43 52267.55 51982.47 52656.45 52203.38 52568.53
## 4 34902.47 34297.53 34052.20 34365.07 34832.25 33545.97 32886.95 32007.12
## 5 32879.30 32177.62 32227.92 32499.25 32921.45 31499.78 30714.75 30741.70
## 6 30664.30 30375.92 30035.53 30682.60 30530.92 30917.53 29746.80 28969.80
## X59.4 X61.5 X63.8 X66.1 X68.5 X71 X73.7 X76.4
## 1 30759.78 29904.72 30153.62 27785.90 27254.30 26019.28 23548.47 22504.85
## 2 38212.82 37618.22 36147.22 35112.55 32617.83 32574.40 30456.95 28780.42
## 3 50725.97 51105.20 49294.05 47807.40 44692.35 43081.10 41224.55 39429.22
## 4 30572.15 29077.20 28938.08 25764.75 25508.17 24034.20 21934.22 21139.90
## 5 29802.10 28518.80 27459.25 25614.65 24395.62 23839.15 22853.90 21200.38
## 6 27633.65 27546.53 26016.35 24439.42 23732.55 23057.40 20610.88 19922.15
## X79.1 X82 X85.1 X88.2 X91.4 X94.7 X98.2 X101.8
## 1 21524.08 19107.92 18153.50 16617.35 15856.35 16032.15 14018.15 13765.40
## 2 27119.08 24584.88 23597.65 22394.00 20816.83 19635.60 19251.15 17940.50
## 3 36815.32 35271.95 31559.67 29478.30 28664.65 28073.72 25858.92 25353.78
## 4 19278.10 18733.78 18340.88 16396.22 15869.50 15114.92 14224.52 13250.52
## 5 20328.10 19383.70 18036.97 17379.50 16638.70 15604.17 15398.48 14776.77
## 6 19176.58 17403.00 16951.88 16103.90 15733.00 14547.55 13863.62 12877.55
## X105.5 X109.4 X113.4 X117.6 X121.9 X126.3 X131 X135.8
## 1 13739.62 11832.75 10845.13 11083.08 10558.138 9566.115 8994.605 8487.830
## 2 16745.40 16773.45 15590.70 14827.98 13564.075 13693.450 12478.895 11839.205
## 3 22308.35 19424.50 17263.90 15375.17 14723.100 14113.850 12769.100 12220.278
## 4 12533.85 11388.88 10808.26 10468.77 9851.735 9446.673 9085.397 8695.380
## 5 13708.15 12730.42 12594.85 11538.27 10528.990 10000.347 9073.305 8733.505
## 6 12072.85 12184.48 11458.60 10336.02 9490.677 9582.272 8857.500 8618.470
## X140.7 X145.9 X151.2 X156.8 X162.5 X168.5 X174.7 X181.1
## 1 7845.070 7874.752 7621.210 7726.938 7141.700 7003.007 6694.552 6328.307
## 2 12306.585 11250.270 10237.987 10173.085 8922.150 9244.872 9179.055 8073.330
## 3 10987.392 10320.630 9588.817 8425.253 8544.840 7493.448 7792.898 7133.278
## 4 8537.478 8030.068 7517.980 7113.865 6901.368 6335.215 6588.927 6383.993
## 5 8018.377 7781.642 7660.330 7638.637 7014.320 6728.910 6706.905 6633.762
## 6 8008.795 7814.222 7045.252 6956.440 6447.880 6104.370 6156.712 5732.370
## X187.7 X194.6 X201.7 X209.1 X216.7 X224.7 X232.9 X241.4
## 1 6580.690 5825.995 5380.403 5645.900 5277.278 4368.172 4175.847 3428.880
## 2 7475.462 6891.465 7360.927 6672.712 5391.792 5406.470 4825.802 3818.693
## 3 6967.290 6722.755 7016.453 6004.137 5550.945 5101.377 4647.292 3754.710
## 4 6273.488 5874.023 5659.485 5457.837 5050.477 4590.870 3711.485 3199.105
## 5 6526.315 6482.545 5625.302 5701.335 4935.483 4755.358 3840.035 3277.318
## 6 5619.248 5695.285 5696.373 5357.852 4939.302 4739.790 4263.460 3584.830
## X250.3 X259.5 X269 X278.8 X289 X299.6 X310.6 X322
## 1 3082.733 2198.782 2214.160 1518.828 956.2415 811.0148 712.6380 533.5457
## 2 3207.105 2658.260 2607.892 1943.697 1357.8500 910.9602 872.4937 644.8452
## 3 3670.242 2692.205 2310.543 1972.930 1284.1625 996.1840 919.3658 668.4925
## 4 2940.345 2426.745 2043.220 1520.975 1321.2925 1003.1650 794.4863 622.4645
## 5 2959.600 2309.260 2212.838 1594.943 1302.2025 904.7358 801.9932 465.9200
## 6 2754.608 2204.782 2014.128 1614.445 1156.8520 999.3487 637.6340 498.8213
## X333.8 X346 X358.7 X371.8 X385.4 X399.5 X414.2 X429.4
## 1 356.7615 205.7224 232.9565 255.0505 228.60650 110.69062 97.00670 75.57348
## 2 481.7797 320.9937 229.8113 258.2534 204.53585 164.10270 103.89525 124.75272
## 3 555.3678 444.3755 420.0557 302.9250 197.01423 277.42025 93.74980 174.06100
## 4 281.5408 355.3115 279.0503 189.1463 168.24335 178.47682 157.81975 37.50747
## 5 502.0710 345.6025 296.5500 139.1213 226.72435 157.23882 38.21028 62.01125
## 6 424.8595 289.8057 186.0948 251.6007 41.93525 83.52655 109.46412 37.63637
## X445.1 X461.4 X478.3 X495.8 X514 X532.8 X552.3 X572.5
## 1 99.66270 64.11430 24.58170 37.728675 30.91285 17.29682 23.70365 72.03625
## 2 74.96462 89.75995 13.08985 72.216425 61.82565 55.03055 55.84450 51.51800
## 3 137.79792 51.29145 91.62895 89.202500 98.71350 123.81890 55.84437 57.11600
## 4 62.83342 38.46860 24.58170 41.441083 54.24065 27.51525 27.92225 28.55800
## 5 50.72913 76.46510 37.67155 24.455133 44.47295 17.29682 37.03768 15.56175
## 6 62.39810 102.37745 64.06087 1.620432 27.12030 31.05442 37.66477 72.03637
## X593.5 X615.3 X637.8 X661.2
## 1 46.64787 26.24875 90.47760 30.65015
## 2 58.63638 64.02125 60.31850 61.30040
## 3 28.99710 11.55855 98.42535 53.45355
## 4 3.15220 26.24875 60.31845 27.58513
## 5 20.80297 52.49750 30.15920 58.23540
## 6 0.00000 14.72510 0.00000 12.26005
##View(my_data)
prepared_data <- prepare_data(my_data)
## Update: converting data from wide to long format...
## Update: wide to long format conversion complete...
## Update: the data has 1 runs of consecutive measurements. I will interpolate each run separately...
## Update: preparing to interpolate...
## Update: now working on run 1 ...
## Update: run 1 will be divided into 22 chunks for interpolation...
## [1] "Update: Interpolating chunk 1 of 22 chunks..."
## [1] "Update: Interpolating chunk 2 of 22 chunks..."
## [1] "Update: Interpolating chunk 3 of 22 chunks..."
## [1] "Update: Interpolating chunk 4 of 22 chunks..."
## [1] "Update: Interpolating chunk 5 of 22 chunks..."
## [1] "Update: Interpolating chunk 6 of 22 chunks..."
## [1] "Update: Interpolating chunk 7 of 22 chunks..."
## [1] "Update: Interpolating chunk 8 of 22 chunks..."
## [1] "Update: Interpolating chunk 9 of 22 chunks..."
## [1] "Update: Interpolating chunk 10 of 22 chunks..."
## [1] "Update: Interpolating chunk 11 of 22 chunks..."
## [1] "Update: Interpolating chunk 12 of 22 chunks..."
## [1] "Update: Interpolating chunk 13 of 22 chunks..."
## [1] "Update: Interpolating chunk 14 of 22 chunks..."
## [1] "Update: Interpolating chunk 15 of 22 chunks..."
## [1] "Update: Interpolating chunk 16 of 22 chunks..."
## [1] "Update: Interpolating chunk 17 of 22 chunks..."
## [1] "Update: Interpolating chunk 18 of 22 chunks..."
## [1] "Update: Interpolating chunk 19 of 22 chunks..."
## [1] "Update: Interpolating chunk 20 of 22 chunks..."
## [1] "Update: Interpolating chunk 21 of 22 chunks..."
## [1] "Update: Interpolating chunk 22 of 22 chunks..."
## Update: interpolation complete.
## Update: Data preparation complete.
## Time Diameter dN_dlogDp_log
## 1 2013-01-26 00:00:00 14.6 4.437633
## 2 2013-01-26 00:03:20 14.6 4.455763
## 3 2013-01-26 00:06:40 14.6 4.473893
## 4 2013-01-26 00:10:00 14.6 4.492023
## 5 2013-01-26 00:13:20 14.6 4.513998
## 6 2013-01-26 00:16:40 14.6 4.535973
## 'data.frame': 900624 obs. of 3 variables:
## $ Time : POSIXct, format: "2013-01-26 00:00:00" "2013-01-26 00:03:20" ...
## $ Diameter : num 14.6 14.6 14.6 14.6 14.6 14.6 14.6 14.6 14.6 14.6 ...
## $ dN_dlogDp_log: num 4.44 4.46 4.47 4.49 4.51 ...
## Warning: Removed 6960 rows containing missing values (geom_rect).
