From c55aa5025d88c811bb093c43aa369a7cdcc07fd9 Mon Sep 17 00:00:00 2001 From: martinbruckner Date: Fri, 26 Jul 2019 12:46:30 +0000 Subject: [PATCH] new results for BRA Soyabeans --- fabio_SPA.R | 10 +- output/results_spa_2013_BRA_Soyabeans.csv | 2260 +++++++++++++++++++-- sankey/main.R => sankeys.R | 30 +- 3 files changed, 2131 insertions(+), 169 deletions(-) rename sankey/main.R => sankeys.R (93%) diff --git a/fabio_SPA.R b/fabio_SPA.R index 93289e2..518d562 100644 --- a/fabio_SPA.R +++ b/fabio_SPA.R @@ -109,25 +109,25 @@ spa5 <- function(p,x,D,cutoff){ # Level 2 L2 <- data.frame() for(i in 1:nrow(L1)){ - print(paste(i,"/",nrow(L1))) + print(paste("L2:",i,"/",nrow(L1))) L2 <- rbind(L2, spa(L1[i,],D,cutoff*L0$value,level=2)) } # Level 3 L3 <- data.frame() for(i in 1:nrow(L2)){ - print(paste(i,"/",nrow(L2))) + print(paste("L3:",i,"/",nrow(L2))) L3 <- rbind(L3, spa(L2[i,],D,cutoff*L0$value,level=3)) } # Level 4 L4 <- data.frame() for(i in 1:nrow(L3)){ - print(paste(i,"/",nrow(L3))) + print(paste("L4:",i,"/",nrow(L3))) L4 <- rbind(L4, spa(L3[i,],D,cutoff*L0$value,level=4)) } # Level 5 L5 <- data.frame() for(i in 1:nrow(L4)){ - print(paste(i,"/",nrow(L4))) + print(paste("L5:",i,"/",nrow(L4))) L5 <- rbind(L5, spa(L4[i,],D,cutoff*L0$value,level=5)) } return(rbind(L0,L1,L2,L3,L4,L5)) @@ -183,7 +183,7 @@ rm(B); gc() country <- "BRA" product <- "Cattle" product <- "Soyabeans" -cutoff <- 0.001 +cutoff <- 0.0001 #---------------------------------------- country <- "IDN" product <- "Wood fuel" diff --git a/output/results_spa_2013_BRA_Soyabeans.csv b/output/results_spa_2013_BRA_Soyabeans.csv index 4b08e56..7f90e38 100644 --- a/output/results_spa_2013_BRA_Soyabeans.csv +++ b/output/results_spa_2013_BRA_Soyabeans.csv @@ -6,75 +6,209 @@ L0,L1,L2,L3,L4,L5,value 2101,2177,,,,,170422.186702318 2101,2181,,,,,117619.87722782 2101,2182,,,,,272099.596542102 +2101,2183,,,,,13790.0332470035 +2101,2191,,,,,57038.029726143 2101,3921,,,,,271455.283126483 2101,3969,,,,,4035866.54297912 2101,3982,,,,,18488323.6884702 2101,3997,,,,,865868.589830401 +2101,3998,,,,,48139.3176276682 +2101,3999,,,,,8620.12547402064 +2101,4000,,,,,10230.5283655842 2101,4001,,,,,1911740.1077592 2101,4002,,,,,396356.989260439 +2101,4003,,,,,72111.6036183071 +2101,4004,,,,,43449.3243434231 +2101,4005,,,,,17020.4694276209 +2101,4008,,,,,26181.8349943339 2101,4011,,,,,224504.91922837 +2101,4372,,,,,15080.7063768946 +2101,5789,,,,,22542.3413443963 2101,5802,,,,,103526.625846555 +2101,6322,,,,,27753.4411083674 +2101,6452,,,,,32340.8571186134 +2101,7219,,,,,52464.4527832407 2101,7232,,,,,217309.911631455 +2101,7752,,,,,17035.9244747881 +2101,9429,,,,,14456.4863994834 +2101,9442,,,,,66716.8313511249 +2101,9832,,,,,12692.0458075834 +2101,9949,,,,,41734.596630447 2101,9962,,,,,184602.113687209 +2101,9981,,,,,9260.00518823563 +2101,10469,,,,,76285.4583687569 2101,10482,,,,,290681.892643266 +2101,11249,,,,,44060.9515631864 2101,11262,,,,,177288.730005232 +2101,12809,,,,,16266.4459751313 +2101,12822,,,,,64252.4087852027 +2101,13589,,,,,25581.3602831035 2101,13602,,,,,120018.44648953 +2101,13617,,,,,9855.05542938173 +2101,13621,,,,,13202.5652504086 +2101,13622,,,,,16686.1740618748 2101,14499,,,,,164392.650543753 2101,14512,,,,,657710.600174199 +2101,15669,,,,,54056.5441083157 2101,15682,,,,,240775.74001171 +2101,16839,,,,,58556.7396705495 2101,16852,,,,,274010.524338768 +2101,16871,,,,,8952.38483585505 +2101,17762,,,,,23318.4777486039 +2101,18009,,,,,13835.8725465223 +2101,18022,,,,,46280.8623909839 +2101,18789,,,,,58348.2583730439 2101,18802,,,,,259324.300216462 +2101,18822,,,,,30742.0410566196 2101,19829,,,,,315797.728313432 2101,19842,,,,,1390683.5772181 2101,20869,,,,,163332.001938365 2101,20882,,,,,679117.271217411 2101,21129,,,,,151252.440649038 2101,21142,,,,,655584.245475684 +2101,21662,,,,,28941.3787219345 +2101,21779,,,,,17511.4416081426 +2101,21792,,,,,77828.7412035135 +2101,21922,,,,,14163.1983928287 2101,22299,,,,,92254.7037182831 2101,22312,,,,,375662.36145841 +2101,22332,,,,,8732.86702328473 +2101,22511,,,,,8540.12933902569 +2101,22559,,,,,30376.4135000289 2101,22572,,,,,122274.257766285 +2101,23092,,,,,13696.4328692218 +2101,23222,,,,,18184.7136437778 +2101,23241,,,,,21164.6197312735 +2101,33850,,,,,20434.2005258585 2101,34777,,,,,1818322.73120543 2101,34791,,,,,1931131.56839154 +2101,34816,,,,,19289.7013924066 +2101,34833,,,,,30958.0377607337 2101,34841,,,,,169246.624973106 2101,34847,,,,,111797.353290198 +2101,34897,,,,,20470.0317957531 +2101,34921,,,,,28291.5731635517 +2101,34923,,,,,80736.2867131014 +2101,34928,,,,,10522.6542655668 2101,34939,,,,,160575.291992552 2101,34952,,,,,9234818.02263721 -2101,0,,,,,1861579.20295464 +2101,0,,,,,242796.225449817 +2101,2101,2101,,,,17091.7681166924 2101,2101,2149,,,,102188.560830417 2101,2101,2162,,,,398848.725061152 +2101,2101,3969,,,,57137.1955280304 2101,2101,3982,,,,261745.76248348 +2101,2101,3997,,,,12258.4090409987 +2101,2101,4001,,,,27065.1834426579 +2101,2101,14512,,,,9311.44247779598 +2101,2101,19842,,,,19688.4011458112 +2101,2101,20882,,,,9614.50431989975 +2101,2101,21142,,,,9281.33891939603 +2101,2101,34777,,,,25742.6404762276 +2101,2101,34791,,,,27339.7152355021 2101,2101,34952,,,,130740.597441983 -2101,2101,0,,,,313747.632813991 +2101,2101,0,,,,99217.0341109789 +2101,2149,31046,,,,12117.9484025598 2101,2149,31050,,,,148970.838533825 +2101,2149,31059,,,,18066.3195651225 +2101,2149,31077,,,,9352.65109446777 +2101,2149,31078,,,,25174.7870862714 +2101,2149,31079,,,,9694.86607109827 +2101,2149,31080,,,,21764.5162288103 +2101,2149,31081,,,,25210.8083211807 +2101,2149,31083,,,,10396.7336001934 +2101,2149,31084,,,,11069.407976228 +2101,2149,31085,,,,14348.7465386659 2101,2149,31578,,,,1534186.77502243 +2101,2149,31614,,,,36986.7955638936 +2101,2149,31617,,,,75682.4460430034 +2101,2149,31646,,,,22944.2223149305 2101,2149,31650,,,,246335.076245473 2101,2149,31652,,,,1080688.21855542 +2101,2149,31678,,,,66817.825405985 +2101,2149,31850,,,,17344.4178277669 +2101,2149,33850,,,,18541.4536128555 2101,2149,34764,,,,114851.349865172 +2101,2149,34768,,,,10826.9980019085 +2101,2149,34774,,,,52961.6015365051 2101,2149,34777,,,,2790844.12784694 2101,2149,34791,,,,92861.201520243 +2101,2149,34795,,,,40757.5497107137 +2101,2149,34827,,,,14938.9365103823 2101,2149,34831,,,,128904.804965246 -2101,2149,0,,,,1080412.15001272 +2101,2149,34833,,,,60736.4945303637 +2101,2149,34834,,,,17018.1615795328 +2101,2149,34867,,,,16957.0581943494 +2101,2149,34871,,,,52577.2840481486 +2101,2149,34906,,,,9533.24693566089 +2101,2149,34927,,,,8722.27456443392 +2101,2149,34932,,,,13599.3309173151 +2101,2149,34936,,,,12279.7872802825 +2101,2149,34938,,,,11625.3074552549 +2101,2149,34952,,,,69297.9676038258 +2101,2149,0,,,,293066.205491007 2101,2162,2177,,,,4538702.68551316 2101,2162,2181,,,,3132465.68990523 2101,2162,2182,,,,7246586.80568312 2101,2162,2183,,,,367257.703604145 2101,2162,2191,,,,1519043.16981108 +2101,2162,4127,,,,14691.3829595419 +2101,2162,4132,,,,25110.0313913898 +2101,2162,4141,,,,10828.0170705119 +2101,2162,4517,,,,8572.58303560532 +2101,2162,4521,,,,49843.4341659024 +2101,2162,4523,,,,25916.0125518066 +2101,2162,4531,,,,9044.89888312031 +2101,2162,5167,,,,10954.1729510039 2101,2162,5171,,,,249876.547334598 +2101,2162,5172,,,,16045.2600316433 +2101,2162,5181,,,,20924.5565010491 +2101,2162,5687,,,,13114.3514581356 +2101,2162,5691,,,,21601.8949324625 +2101,2162,5692,,,,19788.8835019511 +2101,2162,5701,,,,11038.6295244469 +2101,2162,5822,,,,10937.3877933437 2101,2162,6467,,,,403518.482043288 2101,2162,6471,,,,732727.416190663 2101,2162,6472,,,,404327.903237858 +2101,2162,6473,,,,26525.0502263994 2101,2162,6481,,,,267273.284238007 2101,2162,7247,,,,95204.9541094359 2101,2162,7251,,,,625231.225324131 2101,2162,7252,,,,133766.056470433 +2101,2162,7253,,,,12652.4835269437 2101,2162,7261,,,,111143.573940348 +2101,2162,7377,,,,9830.77169634955 +2101,2162,7382,,,,16057.7195938072 +2101,2162,7391,,,,31638.02361694 +2101,2162,8937,,,,15704.5736022585 +2101,2162,8941,,,,29433.8114887659 +2101,2162,8951,,,,10488.9530611521 2101,2162,9327,,,,258301.456025982 +2101,2162,9328,,,,19081.407217112 2101,2162,9331,,,,176764.359258963 2101,2162,9332,,,,225360.755124927 +2101,2162,9333,,,,14949.902112254 +2101,2162,9341,,,,21588.6824766417 +2101,2162,9457,,,,77760.1963339937 +2101,2162,9459,,,,12022.8353119464 +2101,2162,9460,,,,14250.6073517962 2101,2162,9462,,,,340364.141892675 +2101,2162,9463,,,,9559.17259784835 2101,2162,9471,,,,94565.2721665821 +2101,2162,9717,,,,52253.7633851693 +2101,2162,9721,,,,35470.1591463084 +2101,2162,9722,,,,9489.89835453812 +2101,2162,9731,,,,23581.796420171 +2101,2162,9977,,,,56426.3010912832 2101,2162,9981,,,,131779.184518249 +2101,2162,9982,,,,62653.2548635428 +2101,2162,9988,,,,13926.9193308595 +2101,2162,9991,,,,32248.8801320269 +2101,2162,10497,,,,47283.131049034 2101,2162,10501,,,,90162.9961869813 +2101,2162,10502,,,,62828.0767915421 +2101,2162,10511,,,,59131.5648859459 2101,2162,11277,,,,372644.544950943 2101,2162,11281,,,,403198.841531872 2101,2162,11282,,,,137880.06760657 @@ -83,111 +217,446 @@ L0,L1,L2,L3,L4,L5,value 2101,2162,14527,,,,131058.657672041 2101,2162,14531,,,,807870.727560242 2101,2162,14532,,,,385843.458774694 +2101,2162,14533,,,,14448.9860098032 2101,2162,14541,,,,158651.739124625 +2101,2162,16741,,,,27820.0612442351 +2101,2162,16742,,,,16868.0260887413 +2101,2162,16751,,,,13276.7170304762 +2101,2162,16871,,,,14201.7051749279 +2101,2162,17777,,,,18189.0244899003 +2101,2162,17781,,,,53396.5147155794 +2101,2162,17782,,,,26396.7859810757 +2101,2162,17783,,,,17274.3422827618 +2101,2162,17791,,,,41801.7888063443 +2101,2162,18037,,,,43447.1964761664 2101,2162,18041,,,,97160.5590569266 +2101,2162,18042,,,,67169.8463101241 +2101,2162,18043,,,,10381.6605276139 +2101,2162,18051,,,,55478.8553193744 +2101,2162,19207,,,,11728.4920463875 +2101,2162,19211,,,,8732.69027517354 +2101,2162,19212,,,,9423.04301085109 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+2101,3982,4002,4021,31016,0,12031.8673872104 +2101,3982,4011,4001,4017,34791,15885.2514336672 +2101,3982,4011,4001,4017,0,72.2551515238389 +2101,19842,19861,19881,19861,0,9159.70403668723 +2101,19842,19861,19881,26710,34913,19781.346791753 +2101,19842,19861,19881,26710,0,5517.74455334283 +2101,20882,20897,20922,33017,0,9827.11844824775 +2101,20882,20901,20921,33017,0,8598.04006272604 diff --git a/sankey/main.R b/sankeys.R similarity index 93% rename from sankey/main.R rename to sankeys.R index 45ee970..763925d 100644 --- a/sankey/main.R +++ b/sankeys.R @@ -1,31 +1,29 @@ library(tidyverse) # library(RColorBrewer) -setwd("sankey") - # control panel ---------------------------------------------------------------- # set the precision used to cut off flows to either [rest] or RoW # depending on if the flow goes to final demand (then RoW) or not ([rest]) -precision <- 0.5*1e-2 # 0,5% precision +precision <- 0.5*1e-2 # 0.5% precision -country <- c("BRA", "IDN")[2] -item <- c("Cattle", "Soyabeans", "Oil, palm fruit", "Wood")[4] +country <- c("BRA", "IDN")[1] +item <- c("Cattle", "Soyabeans", "Oil, palm fruit", "Wood")[2] # get data -------------------------------------------------------------------- if(item == "Wood"){ - data_1 <- read.csv(paste0("../output/results_spa_2013_", country, "_Industrial roundwood, coniferous.csv")) - data_2 <- read.csv(paste0("../output/results_spa_2013_", country, "_Industrial roundwood, non-coniferous.csv")) - data_3 <- read.csv(paste0("../output/results_spa_2013_", country, "_Wood fuel.csv")) + data_1 <- read.csv(paste0("./output/results_spa_2013_", country, "_Industrial roundwood, coniferous.csv")) + data_2 <- read.csv(paste0("./output/results_spa_2013_", country, "_Industrial roundwood, non-coniferous.csv")) + data_3 <- read.csv(paste0("./output/results_spa_2013_", country, "_Wood fuel.csv")) data <- rbind(data_1, data_2, data_3) } else { - data <- read.csv(paste0("../output/results_spa_2013_", country, "_", item ,".csv")) + data <- read.csv(paste0("./output/results_spa_2013_", country, "_", item ,".csv")) } # get the index to know the meaning of the codes in data # the relevant column is called "X" -index <- read.csv("../input/index.csv") +index <- read.csv("./input/index.csv") # prepare data ---------------------------------------------------------------- @@ -286,16 +284,14 @@ p <- plotly::plot_ly( size = 12, color = "black" ), - node = node_list, - link = link_list -) %>% + ) %>% plotly::layout( - title = sprintf("FABIO SPA for %s (%s) - land footprint %.2e ha", - item, - country, - total_sum), + # title = sprintf("FABIO SPA for %s (%s) - land footprint %.2e ha", + # item, + # country, + # total_sum), # paper_bgcolor = "green", xaxis = list(showgrid = F, zeroline = F, showticklabels = F), yaxis = list(showgrid = F, zeroline = F, showticklabels = F)