IP33-data-conversion-for-viewer/R/ip33_convert_vector.R at main · OBAMANEXT/IP33-data-conversion-for-viewer · GitHub

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library(dplyr)
library(tidyr)
library(sf)
library(terra)
library(ggplot2)
library(patchwork)
library(zip)

# Converting results of IP33 to spatial data for inclusion in data viewer.

# ---------- Copepod data_2018to20.csv ----------

# Read the data file.

file1 <- "Copepod data_2018to20.csv"

df1 <- read.csv(paste0("data/",file1), sep=",", header=T)

shp1 <- sf::st_as_sf(df1, coords = c("lon","lat"), crs=4326)

# Plot the data.

p1 <- ggplot() +
  geom_sf(data = shp1, aes(colour=cop_abun_m3), size=0.2) +
  scale_x_continuous(breaks=c(-6,-4,-2,0)) +
  scale_y_continuous(breaks=c(49,50,51,52)) +
  theme_minimal()  +
  scale_color_distiller(palette = "Spectral")

ggsave(p1, filename="plot/Copepod data_2018to20.png",
       height=12, width=16, units="cm", dpi=300)

# ---------- Fish acoustic abd data 2018to20_copy4OBAMA.csv ----------

# Read the data file.

file2 <- "Fish acoustic abd data 2018to20_copy4OBAMA.csv"

df2 <- read.csv(paste0("data/",file2), sep=",", header=T)

shp2 <- sf::st_as_sf(df2, coords = c("longiture","latitud"), crs=4326)

# Plot the data.

p2 <- ggplot() +
  geom_sf(data = shp2, aes(colour=abundance_indv_m2), size=0.2) +
  theme_minimal()  +
  scale_x_continuous(breaks=c(-6,-4,-2,0)) +
  scale_y_continuous(breaks=c(49,50,51,52)) +
  facet_wrap(taxa~., ncol=3) +
  theme(legend.position.inside = c(0.85, 0.2),
        legend.position = "inside")  +
  scale_color_distiller(palette = "Spectral")

ggsave(p2, filename="plot/Fish acoustic abd data 2018to20_copy4OBAMA.png",
       height=12, width=16, units="cm", dpi=300)

# ---------- trawl_fish abd_size quantileranges_copy_OBAMAIP33.csv ----------

# Read the data file.

file3 <- "trawl_fish abd_size quantileranges_copy_OBAMAIP33.csv"

df3 <- read.csv(paste0("data/",file3), sep=",", header=T)

shp3 <- sf::st_as_sf(df3, coords = c("lon","lat"), crs=4326)

# Plot the data.

p3a <- ggplot() +
  geom_sf(data = shp3, aes(colour=pct_below_Q1), size=1) +
  theme_minimal() +
  scale_x_continuous(breaks=c(-6,-4,-2,0)) +
  scale_y_continuous(breaks=c(49,50,51,52)) +
  facet_wrap(fldMainSpeciesCode~., ncol=2) +
  theme(legend.position = "bottom",
        legend.title = element_text(size=rel(0.8))) +
  scale_color_distiller(palette = "Spectral", direction = 1)

p3b <- ggplot() +
  geom_sf(data = shp3, aes(colour=pct_above_Q3), size=1) +
  theme_minimal() +
  scale_x_continuous(breaks=c(-6,-4,-2,0)) +
  scale_y_continuous(breaks=c(49,50,51,52)) +
  facet_wrap(fldMainSpeciesCode~., ncol=2) +
  theme(legend.position = "bottom",
        legend.title = element_text(size=rel(0.8))) +
  scale_color_distiller(palette = "Spectral")

p3 <- p3a + p3b

ggsave(p3, filename="plot/trawl_fish abd_size quantileranges_copy_OBAMAIP33.png",
       height=16, width=16, units="cm", dpi=300)

# ---------- Save shape files ----------

# Some of the column names need to be shortened before saving as shape file.
# We will keep a record of the changes and store them in a text file.

# > names(shp1)
# [1] "X" "bindatetime"  "cop_abun_m3" "copepod_length_geomean_mm"
# [5] "Lifeform_large_copepod.....2mm" "lifeform_small_copepod....2mm"  "geometry"

names_dat1 <- names(shp1)
names(shp1) <- c("id","datetime", "abund_m3", "len_mm", "n_large", "n_small", "geometry")
names_shp1 <- names(shp1)

# > names(shp2)
# [1] "date" "time" "taxa" "instrument" "abundance_indv_m2" "X"
# [7] "X.1" "X.2" "X.3" "geometry"

names_dat2 <- names(shp2)
names(shp2)[names(shp2)=="abundance_indv_m2"] <- "abund_m2"
names_shp2 <- names(shp2)

# > names(shp3)
# [1] "X" "fldCruiseName" "fldCruiseStationNumber" "fldMainSpeciesCode"  "year"
# [6] "fldDateTimeShot" "total_fish" "pct_below_Q1" "pct_above_Q3"  "geometry"

names_dat3 <- names(shp3)
names(shp3) <- c("id","cruisename", "stn_no", "spcs_code", "year",
                 "time", "tot_fish", "pct_lt_Q1","pct_gt_Q3", "geometry")
names_shp3 <- names(shp3)

file1 <- rep("Copepod data_2018to20.shp", length(names_shp1))
file2 <- rep("Fish acoustic abd data 2018to20_copy4OBAMA.shp", length(names_shp2))
file3 <- rep("trawl_fish abd_size quantileranges_copy_OBAMAIP33.shp", length(names_shp3))

df <- data.frame(file = c(file1, file2, file3),
                 column_shape=c(names_shp1,names_shp2,names_shp3),
                 column_data=c(names_dat1,names_dat2,names_dat3))

# save the table with column names

write.table(df, file = "shp/columns_renamed.csv", row.names = F, sep=",")

# save the shape files

sf::st_write(shp1, "shp/Copepod data_2018to20.shp", append=F)
sf::st_write(shp2, "shp/Fish acoustic abd data 2018to20_copy4OBAMA.shp", append=F)
sf::st_write(shp3, "shp/trawl_fish abd_size quantileranges_copy_OBAMAIP33.shp", append=F)


# ----------  Zip the files ----------

# Collect shape files and png files in a zip file.

files_plot <- list.files(path="plot", full.names = T)
files_shp <- list.files(path="shp", full.names = T)

files_zip <- c(files_shp, files_plot)

zip(zipfile="obama_next_ip33.zip", files=files_zip)