提交: f6b0276471cc646ec99f7a1f8808d859faf9f481 - myprojects-hg-reborn (hg)

Commit MetaInfo

• 修订版: f6b0276471cc646ec99f7a1f8808d859faf9f481 (tree)
• 时间: 2017-03-21 07:26:17
• 作者: Lorenzo Isella <lorenzo.isella@gmai...>
• Commiter: Lorenzo Isella

Log Message

I added a more sophisticated example.

更改概述

• modified: R-codes/riverplot.R

差异

diff -r 5469297872fb -r f6b0276471cc R-codes/riverplot.R
--- a/R-codes/riverplot.R	Sun Mar 19 21:52:48 2017 +0100
+++ b/R-codes/riverplot.R	Mon Mar 20 23:26:17 2017 +0100
@@ -4,101 +4,105 @@
 library(sankey)
 library(dplyr)
 
-## tab <- readRDS("movement_data.RDS")
+
+source("/home/lorenzo/myprojects-hg/R-codes/stat_lib.R")
 
 
-tab <- structure(list(home = c("AU", "RU", "AU", "AU", "AR", "AU", "UY", 
-"IN", "US", "FR", "FR", "RU", "ES", "BE", "FR", "ES", "ES", "US", 
-"DE", "CA", "PL", "IT", "FR", "AU", "SE", "UK", "SE", "PL", "FR", 
-"NL", "ES", "NL", "ES", "BR", "FR", "NL", "JP", "HU", "DE", "AU", 
-"ES", "IN", "CH", "PL", "FR", "DE", "FR", "FR", "HU", "ES", "IT", 
-"UK", "FR", "SE", "DE", "FR", "DE", "ES", "NL", "UK", "ES", "CH", 
-"SE", "DE", "FR", "ES", "US", "DE", "AU", "FR", "IT", "IT", "JP", 
-"ES", "CH", "ES", "AR", "HU", "AT", "ES", "FR", "IN", "AU", "NZ", 
-"UK", "AU", "CA", "ES", "PL", "IN", "UK", "US", "FR", "BE", "DE", 
-"ES", "PL", "IE", "BE", "FR", "CH", "RU", "HU", "ES", "FR", "EL", 
-"IE", "UK", "SI", "DE", "DE", "IT", "EG", "ES", "IT", "IT", "AT", 
-"ES", "IT", "ES", "ES", "PL", "FR", "IT", "IE", "DE", "NL", "HU", 
-"CA", "MD", "DE", "CU", "DE", "PT", "NL", "PL", "DE", "DE", "DE", 
-"PL", "FR", "AR", "NL", "ES", "EL", "FR", "ES", "DE", "NL", "ES", 
-"DE", "ES", "US", "EL", "FR", "ES", "FR", "UK", "IT", "JP", "CA", 
-"US", "FR", "IE", "IT", "CZ", "ES", "DE", "AU", "TR", "FR", "FR", 
-"CH", "SE", "FR", "FR", "BE", "BE", "US", "IT", "IT", "FI", "DE", 
-"NL", "IL", "US", "FR", "FI", "IN", "FI", "SK", "DE", "ES", "UK", 
-"UK", "FR", "DE", "SK", "ES", "ES", "DE", "FR", "DE", "JP", "FR", 
-"US", "ES", "SE", "US", "ES", "UK", "SE", "MX", "NL", "CA", "BE", 
-"IE", "UK", "FR", "PT", "ES", "CH", "SE", "IT", "HU", "US", "UK", 
-"NL", "AT", "ES", "CA", "ES", "FR", "NL", "DE", "IN", "RU", "NL", 
-"FR", "NL", "ES", "US", "SE", "FR", "FR", "IL", "US", "DE", "US", 
-"IT", "AU", "DE", "IE", "AU", "RU", "JP", "FR", "UK", "DE", "AR", 
-"FR", "ES", "SK", "IT", "SE"), host = c("DE", "FR", "UK", "UK", 
-"CH", "IE", "IT", "FI", "DE", "FR", "FR", "RU", "ES", "BE", "FR", 
-"FR", "DE", "UK", "UK", "DK", "UK", "FR", "DE", "SE", "UK", "DE", 
-"UK", "SE", "BE", "NL", "IT", "NO", "CH", "ES", "FR", "UK", "UK", 
-"FR", "UK", "SE", "UK", "CH", "UK", "DE", "SE", "UK", "FR", "DE", 
-"PT", "UK", "FR", "SE", "UK", "UK", "ES", "UK", "SE", "UK", "NL", 
-"DE", "UK", "DE", "ES", "DK", "CH", "ES", "FR", "UK", "UK", "UK", 
-"ES", "IT", "UK", "UK", "UK", "UK", "BE", "FR", "BE", "UK", "FR", 
-"UK", "ES", "NO", "ES", "FR", "UK", "DE", "UK", "UK", "ES", "UK", 
-"UK", "CH", "IE", "UK", "DE", "UK", "NL", "UK", "UK", "CZ", "SE", 
-"UK", "UK", "DE", "DK", "UK", "ES", "IL", "UK", "CH", "FI", "UK", 
-"FR", "UK", "DE", "ES", "FR", "UK", "DE", "UK", "DE", "FR", "UK", 
-"CH", "UK", "FI", "FR", "FR", "UK", "IT", "UK", "PT", "CH", "ES", 
-"CH", "NO", "CH", "UK", "CH", "UK", "CH", "CH", "EL", "CH", "UK", 
-"UK", "UK", "UK", "FR", "UK", "CH", "DE", "UK", "IE", "UK", "DK", 
-"UK", "ES", "UK", "FR", "FR", "UK", "UK", "SI", "ES", "UK", "SE", 
-"UK", "CH", "UK", "DE", "CH", "ES", "UK", "CH", "PT", "FR", "UK", 
-"CH", "UK", "CH", "UK", "UK", "UK", "UK", "CH", "UK", "DE", "DE", 
-"FR", "UK", "UK", "ES", "UK", "DE", "CZ", "NL", "UK", "CH", "IE", 
-"UK", "UK", "DE", "UK", "UK", "UK", "UK", "ES", "CA", "ES", "UK", 
-"DE", "SE", "CH", "ES", "FR", "UK", "IE", "UK", "UK", "CH", "IT", 
-"UK", "FR", "NL", "NO", "AT", "ES", "UK", "UK", "CH", "FR", "UK", 
-"DE", "NL", "ES", "DK", "UK", "UK", "SE", "DE", "DE", "FR", "FR", 
-"CH", "UK", "NL", "ES", "UK", "UK", "UK", "UK", "UK", "UK", "FR", 
-"FR", "UK", "SI", "ES", "DK", "NL", "UK", "UK"), author = c(2, 
-4, 5, 7, 8, 9, 10, 11, 12, 15, 16, 17, 18, 19, 22, 23, 24, 26, 
-27, 28, 29, 30, 31, 32, 36, 37, 39, 40, 41, 42, 43, 47, 48, 50, 
-51, 52, 55, 56, 58, 60, 61, 62, 65, 66, 67, 68, 69, 70, 71, 72, 
-73, 75, 77, 79, 80, 81, 82, 84, 85, 86, 88, 89, 90, 91, 92, 93, 
-96, 99, 101, 102, 103, 104, 108, 109, 110, 111, 112, 113, 114, 
-115, 116, 118, 119, 120, 122, 123, 125, 126, 128, 129, 130, 131, 
-134, 136, 138, 139, 140, 141, 142, 145, 147, 148, 149, 150, 152, 
-154, 156, 157, 160, 161, 164, 165, 166, 167, 169, 171, 172, 173, 
-174, 175, 177, 178, 182, 183, 184, 186, 190, 192, 193, 194, 195, 
-196, 199, 200, 202, 203, 204, 205, 206, 208, 209, 210, 211, 212, 
-213, 214, 216, 217, 221, 222, 223, 224, 225, 226, 227, 229, 232, 
-233, 234, 235, 236, 237, 238, 240, 241, 242, 244, 245, 247, 248, 
-250, 251, 252, 254, 255, 258, 259, 261, 262, 266, 267, 270, 272, 
-273, 274, 275, 276, 277, 278, 279, 280, 281, 282, 283, 287, 288, 
-289, 290, 291, 292, 293, 294, 295, 296, 298, 300, 303, 304, 305, 
-307, 308, 309, 310, 312, 313, 314, 316, 317, 318, 319, 320, 327, 
-328, 329, 330, 331, 332, 334, 336, 337, 339, 340, 341, 342, 343, 
-344, 346, 347, 348, 349, 350, 352, 355, 357, 358, 359, 362, 363, 
-364, 365, 366, 368, 369, 372, 374, 376, 377, 378, 379, 380, 381, 
-383, 385, 386, 387)), .Names = c("home", "host", "author"), row.names = c(2L, 
-3L, 4L, 6L, 7L, 8L, 9L, 10L, 11L, 12L, 13L, 14L, 15L, 16L, 17L, 
-18L, 19L, 20L, 21L, 22L, 23L, 24L, 25L, 26L, 28L, 29L, 30L, 31L, 
-32L, 33L, 34L, 35L, 36L, 38L, 39L, 40L, 41L, 42L, 43L, 44L, 45L, 
-46L, 49L, 50L, 51L, 52L, 53L, 54L, 55L, 56L, 57L, 58L, 59L, 60L, 
-61L, 62L, 63L, 64L, 65L, 66L, 67L, 68L, 69L, 70L, 71L, 72L, 73L, 
-74L, 75L, 76L, 77L, 78L, 80L, 81L, 82L, 83L, 84L, 85L, 86L, 87L, 
-88L, 89L, 90L, 91L, 92L, 93L, 94L, 95L, 96L, 97L, 98L, 99L, 100L, 
-101L, 102L, 103L, 104L, 105L, 106L, 107L, 108L, 109L, 110L, 111L, 
-112L, 113L, 114L, 115L, 117L, 118L, 119L, 120L, 121L, 122L, 123L, 
-125L, 126L, 127L, 128L, 129L, 130L, 131L, 132L, 133L, 134L, 135L, 
-136L, 137L, 138L, 139L, 140L, 141L, 142L, 143L, 144L, 145L, 146L, 
-147L, 148L, 150L, 151L, 152L, 153L, 154L, 155L, 156L, 158L, 159L, 
-160L, 161L, 162L, 163L, 164L, 165L, 166L, 167L, 170L, 171L, 172L, 
-173L, 174L, 175L, 176L, 177L, 178L, 179L, 180L, 181L, 182L, 183L, 
-184L, 185L, 186L, 187L, 188L, 189L, 190L, 191L, 192L, 194L, 195L, 
-196L, 197L, 198L, 199L, 200L, 201L, 202L, 203L, 204L, 205L, 206L, 
-207L, 208L, 210L, 211L, 212L, 213L, 214L, 215L, 216L, 217L, 218L, 
-219L, 220L, 222L, 223L, 224L, 225L, 226L, 227L, 228L, 229L, 231L, 
-232L, 233L, 235L, 236L, 237L, 238L, 239L, 240L, 241L, 242L, 243L, 
-244L, 245L, 246L, 247L, 248L, 249L, 250L, 251L, 252L, 253L, 254L, 
-255L, 256L, 257L, 258L, 259L, 260L, 261L, 262L, 263L, 264L, 265L, 
-266L, 267L, 268L, 269L, 270L, 271L, 272L, 273L, 274L, 275L, 276L, 
-277L, 278L, 279L, 280L, 282L, 283L, 284L), class = "data.frame")
+tab <- readRDS("movement_data.RDS")
+
+
+## tab <- structure(list(home = c("AU", "RU", "AU", "AU", "AR", "AU", "UY", 
+## "IN", "US", "FR", "FR", "RU", "ES", "BE", "FR", "ES", "ES", "US", 
+## "DE", "CA", "PL", "IT", "FR", "AU", "SE", "UK", "SE", "PL", "FR", 
+## "NL", "ES", "NL", "ES", "BR", "FR", "NL", "JP", "HU", "DE", "AU", 
+## "ES", "IN", "CH", "PL", "FR", "DE", "FR", "FR", "HU", "ES", "IT", 
+## "UK", "FR", "SE", "DE", "FR", "DE", "ES", "NL", "UK", "ES", "CH", 
+## "SE", "DE", "FR", "ES", "US", "DE", "AU", "FR", "IT", "IT", "JP", 
+## "ES", "CH", "ES", "AR", "HU", "AT", "ES", "FR", "IN", "AU", "NZ", 
+## "UK", "AU", "CA", "ES", "PL", "IN", "UK", "US", "FR", "BE", "DE", 
+## "ES", "PL", "IE", "BE", "FR", "CH", "RU", "HU", "ES", "FR", "EL", 
+## "IE", "UK", "SI", "DE", "DE", "IT", "EG", "ES", "IT", "IT", "AT", 
+## "ES", "IT", "ES", "ES", "PL", "FR", "IT", "IE", "DE", "NL", "HU", 
+## "CA", "MD", "DE", "CU", "DE", "PT", "NL", "PL", "DE", "DE", "DE", 
+## "PL", "FR", "AR", "NL", "ES", "EL", "FR", "ES", "DE", "NL", "ES", 
+## "DE", "ES", "US", "EL", "FR", "ES", "FR", "UK", "IT", "JP", "CA", 
+## "US", "FR", "IE", "IT", "CZ", "ES", "DE", "AU", "TR", "FR", "FR", 
+## "CH", "SE", "FR", "FR", "BE", "BE", "US", "IT", "IT", "FI", "DE", 
+## "NL", "IL", "US", "FR", "FI", "IN", "FI", "SK", "DE", "ES", "UK", 
+## "UK", "FR", "DE", "SK", "ES", "ES", "DE", "FR", "DE", "JP", "FR", 
+## "US", "ES", "SE", "US", "ES", "UK", "SE", "MX", "NL", "CA", "BE", 
+## "IE", "UK", "FR", "PT", "ES", "CH", "SE", "IT", "HU", "US", "UK", 
+## "NL", "AT", "ES", "CA", "ES", "FR", "NL", "DE", "IN", "RU", "NL", 
+## "FR", "NL", "ES", "US", "SE", "FR", "FR", "IL", "US", "DE", "US", 
+## "IT", "AU", "DE", "IE", "AU", "RU", "JP", "FR", "UK", "DE", "AR", 
+## "FR", "ES", "SK", "IT", "SE"), host = c("DE", "FR", "UK", "UK", 
+## "CH", "IE", "IT", "FI", "DE", "FR", "FR", "RU", "ES", "BE", "FR", 
+## "FR", "DE", "UK", "UK", "DK", "UK", "FR", "DE", "SE", "UK", "DE", 
+## "UK", "SE", "BE", "NL", "IT", "NO", "CH", "ES", "FR", "UK", "UK", 
+## "FR", "UK", "SE", "UK", "CH", "UK", "DE", "SE", "UK", "FR", "DE", 
+## "PT", "UK", "FR", "SE", "UK", "UK", "ES", "UK", "SE", "UK", "NL", 
+## "DE", "UK", "DE", "ES", "DK", "CH", "ES", "FR", "UK", "UK", "UK", 
+## "ES", "IT", "UK", "UK", "UK", "UK", "BE", "FR", "BE", "UK", "FR", 
+## "UK", "ES", "NO", "ES", "FR", "UK", "DE", "UK", "UK", "ES", "UK", 
+## "UK", "CH", "IE", "UK", "DE", "UK", "NL", "UK", "UK", "CZ", "SE", 
+## "UK", "UK", "DE", "DK", "UK", "ES", "IL", "UK", "CH", "FI", "UK", 
+## "FR", "UK", "DE", "ES", "FR", "UK", "DE", "UK", "DE", "FR", "UK", 
+## "CH", "UK", "FI", "FR", "FR", "UK", "IT", "UK", "PT", "CH", "ES", 
+## "CH", "NO", "CH", "UK", "CH", "UK", "CH", "CH", "EL", "CH", "UK", 
+## "UK", "UK", "UK", "FR", "UK", "CH", "DE", "UK", "IE", "UK", "DK", 
+## "UK", "ES", "UK", "FR", "FR", "UK", "UK", "SI", "ES", "UK", "SE", 
+## "UK", "CH", "UK", "DE", "CH", "ES", "UK", "CH", "PT", "FR", "UK", 
+## "CH", "UK", "CH", "UK", "UK", "UK", "UK", "CH", "UK", "DE", "DE", 
+## "FR", "UK", "UK", "ES", "UK", "DE", "CZ", "NL", "UK", "CH", "IE", 
+## "UK", "UK", "DE", "UK", "UK", "UK", "UK", "ES", "CA", "ES", "UK", 
+## "DE", "SE", "CH", "ES", "FR", "UK", "IE", "UK", "UK", "CH", "IT", 
+## "UK", "FR", "NL", "NO", "AT", "ES", "UK", "UK", "CH", "FR", "UK", 
+## "DE", "NL", "ES", "DK", "UK", "UK", "SE", "DE", "DE", "FR", "FR", 
+## "CH", "UK", "NL", "ES", "UK", "UK", "UK", "UK", "UK", "UK", "FR", 
+## "FR", "UK", "SI", "ES", "DK", "NL", "UK", "UK"), author = c(2, 
+## 4, 5, 7, 8, 9, 10, 11, 12, 15, 16, 17, 18, 19, 22, 23, 24, 26, 
+## 27, 28, 29, 30, 31, 32, 36, 37, 39, 40, 41, 42, 43, 47, 48, 50, 
+## 51, 52, 55, 56, 58, 60, 61, 62, 65, 66, 67, 68, 69, 70, 71, 72, 
+## 73, 75, 77, 79, 80, 81, 82, 84, 85, 86, 88, 89, 90, 91, 92, 93, 
+## 96, 99, 101, 102, 103, 104, 108, 109, 110, 111, 112, 113, 114, 
+## 115, 116, 118, 119, 120, 122, 123, 125, 126, 128, 129, 130, 131, 
+## 134, 136, 138, 139, 140, 141, 142, 145, 147, 148, 149, 150, 152, 
+## 154, 156, 157, 160, 161, 164, 165, 166, 167, 169, 171, 172, 173, 
+## 174, 175, 177, 178, 182, 183, 184, 186, 190, 192, 193, 194, 195, 
+## 196, 199, 200, 202, 203, 204, 205, 206, 208, 209, 210, 211, 212, 
+## 213, 214, 216, 217, 221, 222, 223, 224, 225, 226, 227, 229, 232, 
+## 233, 234, 235, 236, 237, 238, 240, 241, 242, 244, 245, 247, 248, 
+## 250, 251, 252, 254, 255, 258, 259, 261, 262, 266, 267, 270, 272, 
+## 273, 274, 275, 276, 277, 278, 279, 280, 281, 282, 283, 287, 288, 
+## 289, 290, 291, 292, 293, 294, 295, 296, 298, 300, 303, 304, 305, 
+## 307, 308, 309, 310, 312, 313, 314, 316, 317, 318, 319, 320, 327, 
+## 328, 329, 330, 331, 332, 334, 336, 337, 339, 340, 341, 342, 343, 
+## 344, 346, 347, 348, 349, 350, 352, 355, 357, 358, 359, 362, 363, 
+## 364, 365, 366, 368, 369, 372, 374, 376, 377, 378, 379, 380, 381, 
+## 383, 385, 386, 387)), .Names = c("home", "host", "author"), row.names = c(2L, 
+## 3L, 4L, 6L, 7L, 8L, 9L, 10L, 11L, 12L, 13L, 14L, 15L, 16L, 17L, 
+## 18L, 19L, 20L, 21L, 22L, 23L, 24L, 25L, 26L, 28L, 29L, 30L, 31L, 
+## 32L, 33L, 34L, 35L, 36L, 38L, 39L, 40L, 41L, 42L, 43L, 44L, 45L, 
+## 46L, 49L, 50L, 51L, 52L, 53L, 54L, 55L, 56L, 57L, 58L, 59L, 60L, 
+## 61L, 62L, 63L, 64L, 65L, 66L, 67L, 68L, 69L, 70L, 71L, 72L, 73L, 
+## 74L, 75L, 76L, 77L, 78L, 80L, 81L, 82L, 83L, 84L, 85L, 86L, 87L, 
+## 88L, 89L, 90L, 91L, 92L, 93L, 94L, 95L, 96L, 97L, 98L, 99L, 100L, 
+## 101L, 102L, 103L, 104L, 105L, 106L, 107L, 108L, 109L, 110L, 111L, 
+## 112L, 113L, 114L, 115L, 117L, 118L, 119L, 120L, 121L, 122L, 123L, 
+## 125L, 126L, 127L, 128L, 129L, 130L, 131L, 132L, 133L, 134L, 135L, 
+## 136L, 137L, 138L, 139L, 140L, 141L, 142L, 143L, 144L, 145L, 146L, 
+## 147L, 148L, 150L, 151L, 152L, 153L, 154L, 155L, 156L, 158L, 159L, 
+## 160L, 161L, 162L, 163L, 164L, 165L, 166L, 167L, 170L, 171L, 172L, 
+## 173L, 174L, 175L, 176L, 177L, 178L, 179L, 180L, 181L, 182L, 183L, 
+## 184L, 185L, 186L, 187L, 188L, 189L, 190L, 191L, 192L, 194L, 195L, 
+## 196L, 197L, 198L, 199L, 200L, 201L, 202L, 203L, 204L, 205L, 206L, 
+## 207L, 208L, 210L, 211L, 212L, 213L, 214L, 215L, 216L, 217L, 218L, 
+## 219L, 220L, 222L, 223L, 224L, 225L, 226L, 227L, 228L, 229L, 231L, 
+## 232L, 233L, 235L, 236L, 237L, 238L, 239L, 240L, 241L, 242L, 243L, 
+## 244L, 245L, 246L, 247L, 248L, 249L, 250L, 251L, 252L, 253L, 254L, 
+## 255L, 256L, 257L, 258L, 259L, 260L, 261L, 262L, 263L, 264L, 265L, 
+## 266L, 267L, 268L, 269L, 270L, 271L, 272L, 273L, 274L, 275L, 276L, 
+## 277L, 278L, 279L, 280L, 282L, 283L, 284L), class = "data.frame")
 
 
 
@@ -132,54 +136,54 @@
 tab_un$weight <- weight$n
 
 
-## classification <- read.csv("country-classification.csv")
+classification <- read.csv("country-classification.csv")
 
 
-classification <- structure(list(Country.codes = structure(c(25L, 57L, 22L, 4L, 
-40L, 35L, 15L, 16L, 8L, 2L, 21L, 49L, 29L, 41L, 17L, 34L, 36L, 
-43L, 14L, 52L, 24L, 51L, 23L, 45L, 5L, 38L, 13L, 19L, 30L, 20L, 
-44L, 1L, 3L, 6L, 7L, 9L, 10L, 12L, 18L, 27L, 26L, 28L, 31L, 32L, 
-33L, 39L, 42L, 46L, 53L, 54L, 55L, 56L, 58L, 59L, 11L, 37L, 50L, 
-48L, 47L), .Label = c("AR", "AT", "AU", "BE", "BG", "BR", "CA", 
-"CH", "CL", "CN", "CU", "CV", "CY", "CZ", "DE", "DK", "EE", "EG", 
-"EL", "ES", "FI", "FR", "HR", "HU", "IE", "IL", "IN", "IR", "IS", 
-"IT", "JP", "KH", "KR", "LT", "LU", "LV", "MD", "MT", "MX", "NL", 
-"NO", "NZ", "PL", "PT", "RO", "RU", "SA", "SB", "SE", "SGP", 
-"SI", "SK", "SY", "TN", "TR", "UA", "UK", "US", "UY"), class = "factor"), 
-    Country.Name = structure(c(27L, 57L, 20L, 4L, 37L, 33L, 21L, 
-    16L, 52L, 3L, 19L, 51L, 24L, 39L, 18L, 32L, 31L, 40L, 15L, 
-    46L, 23L, 47L, 11L, 42L, 6L, 34L, 14L, 22L, 29L, 50L, 41L, 
-    1L, 2L, 5L, 8L, 9L, 10L, 13L, 17L, 25L, 28L, 26L, 30L, 7L, 
-    49L, 35L, 38L, 43L, 53L, 54L, 55L, 56L, 59L, 58L, 12L, 36L, 
-    45L, 44L, 48L), .Label = c("ARGENTINA", "AUSTRALIA", "AUSTRIA", 
-    "BELGIUM", "BRAZIL", "BULGARIA", "CAMBODIA", "CANADA", "CHILE", 
-    "CHINA", "CROATIA", "CUBA", "CV", "CYPRUS", "CZECH REPUBLIC", 
-    "DENMARK", "EGYPT", "ESTONIA", "FINLAND", "FRANCE", "GERMANY", 
-    "GREECE", "HUNGARY", "ICELAND", "INDIA", "IRAN", "IRELAND", 
-    "ISRAEL", "ITALY", "JAPAN", "LATVIA", "LITHUANIA", "LUXEMBOURG", 
-    "MALTA", "MEXICO", "MOLDOVA", "NETHERLANDS", "NEW ZEALAND", 
-    "NORWAY", "POLAND", "PORTUGAL", "ROMANIA", "RUSSIA", "SERBIA", 
-    "SINGAPORE", "SLOVAKIA", "SLOVENIA", "SOUTH AFRICA", "SOUTH KOREA", 
-    "SPAIN", "SWEDEN", "SWITZERLAND", "SYRIA", "TUNISIA", "TURKEY", 
-    "UKRAINE", "UNITED KINGDOM", "URUGUAY", "USA"), class = "factor"), 
-    Country.codes.1 = structure(c(25L, 57L, 22L, 4L, 40L, 35L, 
-    15L, 16L, 8L, 2L, 21L, 49L, 29L, 41L, 17L, 34L, 36L, 43L, 
-    14L, 52L, 24L, 51L, 23L, 45L, 5L, 38L, 13L, 19L, 30L, 20L, 
-    44L, 1L, 3L, 6L, 7L, 9L, 10L, 12L, 18L, 27L, 26L, 28L, 31L, 
-    32L, 33L, 39L, 42L, 46L, 53L, 54L, 55L, 56L, 58L, 59L, 11L, 
-    37L, 50L, 48L, 47L), .Label = c("AR", "AT", "AU", "BE", "BG", 
-    "BR", "CA", "CH", "CL", "CN", "CU", "CV", "CY", "CZ", "DE", 
-    "DK", "EE", "EG", "EL", "ES", "FI", "FR", "HR", "HU", "IE", 
-    "IL", "IN", "IR", "IS", "IT", "JP", "KH", "KR", "LT", "LU", 
-    "LV", "MD", "MT", "MX", "NL", "NO", "NZ", "PL", "PT", "RO", 
-    "RU", "SA", "SB", "SE", "SGP", "SI", "SK", "SY", "TN", "TR", 
-    "UA", "UK", "US", "UY"), class = "factor"), Region.code = c(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, 
-    3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 
-    3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L)), .Names = c("Country.codes", 
-"Country.Name", "Country.codes.1", "Region.code"), class = "data.frame", row.names = c(NA, 
--59L))
+## classification <- structure(list(Country.codes = structure(c(25L, 57L, 22L, 4L, 
+## 40L, 35L, 15L, 16L, 8L, 2L, 21L, 49L, 29L, 41L, 17L, 34L, 36L, 
+## 43L, 14L, 52L, 24L, 51L, 23L, 45L, 5L, 38L, 13L, 19L, 30L, 20L, 
+## 44L, 1L, 3L, 6L, 7L, 9L, 10L, 12L, 18L, 27L, 26L, 28L, 31L, 32L, 
+## 33L, 39L, 42L, 46L, 53L, 54L, 55L, 56L, 58L, 59L, 11L, 37L, 50L, 
+## 48L, 47L), .Label = c("AR", "AT", "AU", "BE", "BG", "BR", "CA", 
+## "CH", "CL", "CN", "CU", "CV", "CY", "CZ", "DE", "DK", "EE", "EG", 
+## "EL", "ES", "FI", "FR", "HR", "HU", "IE", "IL", "IN", "IR", "IS", 
+## "IT", "JP", "KH", "KR", "LT", "LU", "LV", "MD", "MT", "MX", "NL", 
+## "NO", "NZ", "PL", "PT", "RO", "RU", "SA", "SB", "SE", "SGP", 
+## "SI", "SK", "SY", "TN", "TR", "UA", "UK", "US", "UY"), class = "factor"), 
+##     Country.Name = structure(c(27L, 57L, 20L, 4L, 37L, 33L, 21L, 
+##     16L, 52L, 3L, 19L, 51L, 24L, 39L, 18L, 32L, 31L, 40L, 15L, 
+##     46L, 23L, 47L, 11L, 42L, 6L, 34L, 14L, 22L, 29L, 50L, 41L, 
+##     1L, 2L, 5L, 8L, 9L, 10L, 13L, 17L, 25L, 28L, 26L, 30L, 7L, 
+##     49L, 35L, 38L, 43L, 53L, 54L, 55L, 56L, 59L, 58L, 12L, 36L, 
+##     45L, 44L, 48L), .Label = c("ARGENTINA", "AUSTRALIA", "AUSTRIA", 
+##     "BELGIUM", "BRAZIL", "BULGARIA", "CAMBODIA", "CANADA", "CHILE", 
+##     "CHINA", "CROATIA", "CUBA", "CV", "CYPRUS", "CZECH REPUBLIC", 
+##     "DENMARK", "EGYPT", "ESTONIA", "FINLAND", "FRANCE", "GERMANY", 
+##     "GREECE", "HUNGARY", "ICELAND", "INDIA", "IRAN", "IRELAND", 
+##     "ISRAEL", "ITALY", "JAPAN", "LATVIA", "LITHUANIA", "LUXEMBOURG", 
+##     "MALTA", "MEXICO", "MOLDOVA", "NETHERLANDS", "NEW ZEALAND", 
+##     "NORWAY", "POLAND", "PORTUGAL", "ROMANIA", "RUSSIA", "SERBIA", 
+##     "SINGAPORE", "SLOVAKIA", "SLOVENIA", "SOUTH AFRICA", "SOUTH KOREA", 
+##     "SPAIN", "SWEDEN", "SWITZERLAND", "SYRIA", "TUNISIA", "TURKEY", 
+##     "UKRAINE", "UNITED KINGDOM", "URUGUAY", "USA"), class = "factor"), 
+##     Country.codes.1 = structure(c(25L, 57L, 22L, 4L, 40L, 35L, 
+##     15L, 16L, 8L, 2L, 21L, 49L, 29L, 41L, 17L, 34L, 36L, 43L, 
+##     14L, 52L, 24L, 51L, 23L, 45L, 5L, 38L, 13L, 19L, 30L, 20L, 
+##     44L, 1L, 3L, 6L, 7L, 9L, 10L, 12L, 18L, 27L, 26L, 28L, 31L, 
+##     32L, 33L, 39L, 42L, 46L, 53L, 54L, 55L, 56L, 58L, 59L, 11L, 
+##     37L, 50L, 48L, 47L), .Label = c("AR", "AT", "AU", "BE", "BG", 
+##     "BR", "CA", "CH", "CL", "CN", "CU", "CV", "CY", "CZ", "DE", 
+##     "DK", "EE", "EG", "EL", "ES", "FI", "FR", "HR", "HU", "IE", 
+##     "IL", "IN", "IR", "IS", "IT", "JP", "KH", "KR", "LT", "LU", 
+##     "LV", "MD", "MT", "MX", "NL", "NO", "NZ", "PL", "PT", "RO", 
+##     "RU", "SA", "SB", "SE", "SGP", "SI", "SK", "SY", "TN", "TR", 
+##     "UA", "UK", "US", "UY"), class = "factor"), Region.code = c(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, 
+##     3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 
+##     3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L)), .Names = c("Country.codes", 
+## "Country.Name", "Country.codes.1", "Region.code"), class = "data.frame", row.names = c(NA, 
+## -59L))
 
 
 edges <- select(tab_un, c(home, host))
@@ -200,11 +204,21 @@
 
 nodes$size <- c(as.numeric(nodes.out), as.numeric(nodes.in))
 
-res <- make_sankey(nodes=nodes, edges = edges)
+## res <- make_sankey(nodes=nodes, edges = edges)
 
-pdf("riverplot.pdf")
-sankey(res)
-dev.off()
+## pdf("riverplot.pdf")
+## sankey(res)
+## dev.off()
+
+
+nodes.country <- nodes
+edges.country <- edges
+
+edges.country$host <- substrRight(edges.country$host, 2)
+
+edges.country$home <- substrRight(edges.country$home, 2)
+
+
 
 #####################################################################
 #####################################################################
@@ -241,6 +255,27 @@
 tab$host[tab$host %in% sel_row  ] <- "RoW"
 
 
+edges.country$home <- edges.country$host
+
+
+edges.country$home[edges.country$home %in% sel_fp ] <- "FP"
+edges.country$home[edges.country$home %in% sel_esif ] <- "ESIF"
+edges.country$home[edges.country$home %in% sel_row ] <- "RoW"
+
+
+### the starting point of the country edges is the *host* country
+## because I am not representing a movement of people from a place to another
+## but just breaking up the macro destination area by country.
+
+edges.country$home <- paste("to",edges.country$home, sep=" " )
+
+
+
+## what matters is the total flow that reaches every country, so I aggregate the
+## edges.country every time the couple home-host country is the same.
+
+edges.country <- aggregate(weight ~ home +  host, data=edges.country, sum)
+
 
 nodes.out <- table(tab$home)
 nodes.in <- table(tab$host)
@@ -301,9 +336,55 @@
 dev.off()
 
 
+#########################################################################
+#########################################################################
+#########################################################################
+#########################################################################
+#########################################################################
+#########################################################################
 
 
 
+edges <- rbind(edges, edges.country)
+
+
+sel <- grep("to", nodes.country$ID)
+
+nodes.country <- nodes.country[sel, ]
+
+nodes.country$ID <- substrRight(nodes.country$ID, 2)
+
+nodes.country$col <- "red"
+
+
+
+sel_fp <- classification$Country.codes[classification$Region.code==1]
+
+sel_fp <- as.character(sel_fp)
+
+
+sel_esif <- classification$Country.codes[classification$Region.code==2]
+
+sel_esif <- as.character(sel_esif)
+
+
+sel_row <- classification$Country.codes[classification$Region.code==3]
+
+sel_row <- as.character(sel_row)
+
+
+
+nodes.country$col[nodes.country$ID  %in%  sel_esif] <- "blue"
+nodes.country$col[nodes.country$ID  %in%  sel_row] <- "darkgreen"
+
+nodes <- rbind(nodes, nodes.country)
+
+
+res <- make_sankey(nodes=nodes, edges = edges)
+
+pdf("riverplot_macro_complete.pdf")
+sankey(res)
+dev.off()
 
 
 print("So far so good")