fenix: fenix

biom_survey_map_modas = function (baseDat, outFolder = ".", outFile = "ModaPrincipal.png", 
                                      xlim = c(-86, -70), ylim = c(-21, -3), Pch = 16, Cols = 1, 
                                      PalCols = colorRampPalette(c("red", "yellow", "green", "blue")), 
                                      Moda = 1, CexPoint = 0.9, widthFig = 700, heightFig = 820, 
                                      legend2 = F, posX = NULL, posY = NULL, Add = FALSE, save = FALSE, 
                                      Label = FALSE, spType = "Anchoveta,anchovetaperuana,peladilla", 
                                      lenUnits = "cm", portImport = 1, addIsoAreas = F, Legend = TRUE, 
                                      LatTck = 2, n_perfil = 1) 
{
  if (is.null(outFolder)) {
    outFolder <- getwd()
  }
  if (save) {
    png(filename = file.path(outFolder, outFile), width = widthFig, 
        height = heightFig, units = "px", res = 130)
  }
  par(mar = c(4, 4, 1, 1), oma = c(0, 0, 0, 0))
  mapa_peru(xlim = xlim, ylim = ylim, area_iso = addIsoAreas, 
            n_perfil = n_perfil)
  rbPal = PalCols
  baseDat = baseDat[which(baseDat[, "NOMBRE_COMERCIAL"] == 
                            spType), ]
  baseDat$indLance = paste0(baseDat[, "EMBARCACION"], baseDat[, 
                                                              "REO_NNUMLAN"])
  indLance2 = unique(baseDat$indLance)
  tmpout = NULL
  for (i in seq_along(indLance2)) {
    temp_biom = subset(x = baseDat, subset = baseDat$indLance == 
                         indLance2[i])
    temp_biom = temp_biom[order(temp_biom$LONGITUD_ESPECIE, 
                                decreasing = F), ]
    marcas <- seq(1, 20, by = 0.5)
    freq <- rep(0, length(marcas))
    ubicacionMarcas <- which(marcas %in% temp_biom$LONGITUD_ESPECIE)
    freq[ubicacionMarcas] <- temp_biom$FREC_SIMPLE
    getModa <- modas(x = matrix(freq, nrow = 1), Lmin = 1, 
                     Lmax = 20, dL = 0.5, umbral = 5)
    tmp2 = data.frame(lon = temp_biom[1, "LONGITUD_INICIAL"], 
                      lat = temp_biom[1, "LATITUD_INICIAL"], midlen = getModa[1])
    tmpout = rbind(tmpout, tmp2)
  }
  tmpout = tmpout[tmpout$midlen > 1.5,]
  require(RColorBrewer)
  require(fields)
  cols5 = brewer.pal(n = 9, name = "Greens")[3:7]
  cols3 = brewer.pal(n = 9, name = "Blues")[3:7]
  cols4 = brewer.pal(n = 9, name = "Oranges")[3:7]
  cols6 = brewer.pal(n = 9, name = "Greys")[3:6]
  scale.color3 = designer.colors(79, cols3)
  scale.color4 = designer.colors(40, cols4)
  scale.color5 = designer.colors(25, cols5)
  scale.color6 = designer.colors(56, cols6)
  scale.color2 = c(scale.color3, scale.color4, scale.color5, 
                   scale.color6)
  tmpout2 = tmpout[complete.cases(tmpout), ]
  tmpout2$indCol = scale.color2[round(tmpout2$midlen, 1) * 
                                  10]
  
  if (Label) {
    text(x = tmpout$lon, y = tmpout$lat, labels = tmpout$midlen, 
         col = Cols[1], cex = CexPoint)
  }
  else {
    points(x = tmpout2$lon, y = tmpout2$lat, pch = Pch, 
           col = tmpout2$indCol, cex = CexPoint)
    if (Legend) {
      if (isTRUE(legend2)) {
        posX = posX + (n_perfil - 1) * -3
        posY = posY
        diffX = 0.2
        diffY = 3
      }
      else {
        posX = -84 + (n_perfil - 1) * -3
        posY = -19.5
        diffX = 0.3
        diffY = 7
      }
      legend.krige(x.leg = c(posX, posX + diffX), y.leg = c(posY, 
                                                            posY + diffY), scale.vals = c(8, 12, 14.5), 
                   values = 0:20, vertical = T, col = scale.color2, 
                   offset.leg = 1)
      text(x = (posX + diffX/2), y = (posY + diffY) * 
             0.95, labels = paste0("Modas (cm)"), cex = 0.8, 
           font = 2)
    }
  }
  if (save) {
    dev.off()
  }
}

# biom_survey_map_modas = function(baseDat, outFolder = ".", outFile = "ModaPrincipal.png", xlim=c(-86,-70), ylim=c(-21, -3), Pch = 16,
#                       Cols = 1, PalCols = colorRampPalette(c('red', "yellow", "green", 'blue')), Moda = 1, umbral = 0,
#                       CexPoint = 0.9, widthFig = 700, heightFig = 820, legend2 = F, posX = NULL, posY = NULL,
#                       Add = FALSE, save = FALSE, Label = FALSE,  
#                       spType = "Anchoveta,anchovetaperuana,peladilla",
#                       nameVar	=	"NOMBRE_COMERCIAL",				
#                       nameLance	=	"REO_NNUMLAN",	nameFrec	=	"FREC_SIMPLE",
#                       lenUnits = "cm", portImport = 1, addIsoAreas = F, Legend = TRUE, LatTck = 2, n_perfil = 1){
#   
#   if(is.null(outFolder)){
#     outFolder <- getwd()
#   }
#   if(save){
#     png(filename = file.path(outFolder, outFile), width = widthFig, height = heightFig,
#         units = "px", res = 130)
#   }
#   par(mar = c(4,4,1,1), oma = c(0,0,0,0))
#   mapa_peru(xlim = xlim, ylim = ylim, area_iso = addIsoAreas, n_perfil = n_perfil)
#   # ------------------------------
#   
#   rbPal = PalCols
#   
#   baseDat = baseDat[which(baseDat[, "NOMBRE_COMERCIAL"] == spType), ]
#   baseDat$indLance = paste0(baseDat[, "EMBARCACION"], baseDat[, "REO_NNUMLAN"])
#   indLance2 = unique(baseDat$indLance)
#   
#   tmpout = NULL
#   for(i in seq_along(indLance2)){
#     ## opcion 2 si hay mesetas solo ubica moda en la meseta principal
#     temp_biom = subset(x = baseDat, subset = baseDat$indLance ==
#                          indLance2[i])
#     temp_biom = temp_biom[order(temp_biom$LONGITUD_ESPECIE,
#                                 decreasing = F), ]
#     marcas <- seq(1, 20, by = 0.5)
#     freq <- rep(0, length(marcas))
#     ubicacionMarcas <- which(marcas %in% temp_biom$LONGITUD_ESPECIE)
#     freq[ubicacionMarcas] <- temp_biom[[nameFrec]]
#     getModa <- modas(x = matrix(freq, nrow = 1), Lmin = 1,
#                      Lmax = 20, dL = 0.5, umbral = umbral)
#     tmp2 = data.frame(lon = temp_biom[1, "LONGITUD_INICIAL"],
#                       lat = temp_biom[1, "LATITUD_INICIAL"], midlen = getModa[1])
#     tmpout = rbind(tmpout, tmp2)
#                    
#     ## opcion 1 si hay mesetas las reconoce como modas  
#     
#     # temp_biom = subset(x = baseDat, subset = baseDat$indLance == indLance2[i])
#     # 
#     # midlen = estimarModaAnch(len = temp_biom[, "LONGITUD_ESPECIE"], freq = temp_biom[, "FREC_SIMPLE"],
#     #                          tol = 0, nmodes = 4, maxFreq = 0)
#     # tmp2 = data.frame(lon = temp_biom[1, "LONGITUD_INICIAL"], lat = temp_biom[1, "LATITUD_INICIAL"],
#     #                   midlen = midlen$modas[Moda])
#     # tmpout = rbind(tmpout, tmp2)
#   }
#   require(RColorBrewer)
#   require(fields)
#   cols5 = brewer.pal(n = 9, name = "Greens")[3:7]
#   cols3 = brewer.pal(n = 9, name = "Blues")[3:7]
#   cols4 = brewer.pal(n = 9, name = "Oranges")[3:7]
#   cols6 = brewer.pal(n = 9, name = "Greys")[3:6]
# 
#   
#   scale.color3 = designer.colors(79, cols3)
#   scale.color4 = designer.colors(40, cols4)
#   scale.color5 = designer.colors(25, cols5)
#   scale.color6 = designer.colors(56, cols6)
#   # 
#   scale.color2 = c(scale.color3, scale.color4, scale.color5, scale.color6)
#   tmpout2 = tmpout[complete.cases(tmpout), ]
#   tmpout2$indCol = scale.color2[round(tmpout2$midlen,1)*10]
#   if(Label){
#     text(x = tmpout$lon, y = tmpout$lat, labels = tmpout$midlen,
#          col = Cols[1], cex = CexPoint)
#   } else {
#     points(x = tmpout2$lon, y = tmpout2$lat, pch = Pch, col = tmpout2$indCol, cex = CexPoint)
#     if(Legend){
# 
#       if(isTRUE(legend2)){
#         posX = posX + (n_perfil-1)*-3
#         posY = posY
#         diffX = 0.2
#         diffY = 3
#       }else{
#         posX = -84 + (n_perfil-1)*-3
#         posY = -19.5
#         diffX = 0.3
#         diffY = 7
#       }
#       
#       legend.krige(x.leg = c(posX, posX+diffX), y.leg = c(posY, posY+diffY), scale.vals = c(8,12,14.5),
#                    values = 0:20, vertical=T, col = scale.color2,
#                    offset.leg = 1)
#       
#       text(x = (posX+diffX/2), y = (posY+diffY)*0.95, labels = paste0("Modas (cm)"),
#            cex = 0.8, font = 2)
#     }
#   }
#   if(save){
#     dev.off()
#   }
#   
# }