ch 2 update

SampleData-master/.gitattributes

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+# Auto detect text files and perform LF normalization
+* text=auto

SampleData-master/CMIP_land/CMIP_land.cpg

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+UTF-8

SampleData-master/CMIP_land/CMIP_land.prj

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+GEOGCS["GCS_WGS_1984",DATUM["D_WGS_1984",SPHEROID["WGS_1984",6378137.0,298.257223563]],PRIMEM["Greenwich",0.0],UNIT["Degree",0.0174532925199433]]

SampleData-master/CMIP_land/CMIP_land.shp.xml

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+<?xml version="1.0" encoding="UTF-8"?>
+<metadata xml:lang="en"><Esri><CreaDate>20200813</CreaDate><CreaTime>23083700</CreaTime><ArcGISFormat>1.0</ArcGISFormat><SyncOnce>TRUE</SyncOnce><DataProperties><lineage><Process ToolSource="c:\program files (x86)\arcgis\desktop10.4\ArcToolbox\Toolboxes\Data Management Tools.tbx\CalculateField" Date="20200717" Time="180529">CalculateField CMIP6_land2 V4 !FID! PYTHON_9.3 #</Process><Process ToolSource="c:\program files (x86)\arcgis\desktop10.4\ArcToolbox\Toolboxes\Data Management Tools.tbx\CalculateField" Date="20200717" Time="180540">CalculateField CMIP6_land2 V4 !FID!+1 PYTHON_9.3 #</Process></lineage></DataProperties></Esri></metadata>

SampleData-master/README.md

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+# SampleData-master
+ Sample dataset for large-scale data visualization workshop.

SampleData-master/USA_states/cb_2018_us_state_5m.cpg

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+UTF-8

SampleData-master/USA_states/cb_2018_us_state_5m.prj

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+GEOGCS["GCS_North_American_1983",DATUM["D_North_American_1983",SPHEROID["GRS_1980",6378137,298.257222101]],PRIMEM["Greenwich",0],UNIT["Degree",0.017453292519943295]]

SampleData-master/functions/mat2ras.R

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+mat2ras=function(mat, Longitude, Latitude, plot_ind){
+# Converts a matrix to raster using Lat-long vectors and 2-d matrix of the dataset.
+
+  #Import libraries
+require(reshape2)
+require(maps)
+
+row.names(mat)=Longitude #Assign rownames as Longitude
+colnames(mat)=Latitude   #Assign colnames as Latitudes
+xyz=melt(mat)            # Create an X-Y-Z dataframe
+ncol=length(Longitude)
+nrow= length(Latitude)
+
+colnames(xyz)= c("x", "y", "z")
+
+# Create a sample raster 
+dat = raster(
+  xmn = 1, xmx = ncol,
+  ymn = 1, ymx = nrow,
+  nrows = nrow, 
+  ncols = ncol,
+  vals = xyz$z)
+
+library(maps)
+# specify CRS to be used
+crs.latlon = CRS("+proj=longlat +datum=WGS84")
+nrow = dim(dat)[1]
+ncol = dim(dat)[2]
+
+# get extent of the domain
+ext = extent(xyz[, c('x', 'y')])
+
+# create a raster for extent with nrow and ncol
+rast = raster(
+  ext, nrow = nrow, ncol = ncol,
+  crs = crs.latlon)
+
+# rasterize the data values
+rast = rasterize(
+  xyz[, c('x', 'y')], rast,
+  xyz[, 'z'], fun=mean)
+
+if (plot_ind==TRUE){
+  plot(rast)
+}
+return(rast)
+}

SampleData-master/functions/robin_ras.R

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+robin_ras=function(ras, map_col,name,brk,lim,na.rm=T){
+#############################################
+# ======================================================================================
+# Create a simple world map in Robinson projection with labeled graticules using ggplot
+# ======================================================================================
+#Source code edited from: 
+#https://seethedatablog.wordpress.com/2016/12/23/r-simple-world-map-robinson-ggplot/
+
+# Set a working directory with setwd() or work with an RStudio project
+# __________ Set libraries
+library(rgdal)      # for spTransform() & project()
+library(ggplot2)    # for ggplot()
+
+# __________ Load ready to use data from GitHub
+load(url("https://github.com/valentinitnelav/RandomScripts/blob/master/NaturalEarth.RData?raw=true"))
+# This will load 6 objects:
+#   xbl.X & lbl.Y are two data.frames that contain labels for graticule lines
+#       They can be created with the code at this link: 
+#       https://gist.github.com/valentinitnelav/8992f09b4c7e206d39d00e813d2bddb1
+#   NE_box is a SpatialPolygonsDataFrame object and represents a bounding box for Earth 
+#   NE_countries is a SpatialPolygonsDataFrame object representing countries 
+#   NE_graticules is a SpatialLinesDataFrame object that represents 10 dg latitude lines and 20 dg longitude lines
+#           (for creating graticules check also the graticule package or gridlines fun. from sp package)
+#           (or check this gist: https://gist.github.com/valentinitnelav/a7871128d58097e9d227f7a04e00134f)
+#   NE_places - SpatialPointsDataFrame with city and town points
+#   NOTE: data downloaded from http://www.naturalearthdata.com/
+#         here is a sample script how to download, unzip and read such shapefiles:
+#         https://gist.github.com/valentinitnelav/a415f3fbfd90f72ea06b5411fb16df16
+
+# __________ Project from long-lat (unprojected data) to Robinson projection
+# spTransform() is used for shapefiles and project() in the case of data frames
+# for more PROJ.4 strings check the followings
+#   http://proj4.org/projections/index.html
+#   https://epsg.io/
+
+PROJ <- "+proj=robin +lon_0=0 +x_0=0 +y_0=0 +ellps=WGS84 +datum=WGS84 +units=m +no_defs" 
+# or use the short form "+proj=robin"
+NE_countries_rob  <- spTransform(NE_countries, CRSobj = PROJ)
+NE_graticules_rob <- spTransform(NE_graticules, CRSobj = PROJ)
+NE_box_rob        <- spTransform(NE_box, CRSobj = PROJ)
+
+# project long-lat coordinates for graticule label data frames 
+# (two extra columns with projected XY are created)
+prj.coord <- rgdal::project(cbind(lbl.Y$lon, lbl.Y$lat), proj=PROJ)
+lbl.Y.prj <- cbind(prj.coord, lbl.Y)
+names(lbl.Y.prj)[1:2] <- c("X.prj","Y.prj")
+
+prj.coord <- rgdal::project(cbind(lbl.X$lon, lbl.X$lat), proj=PROJ)
+lbl.X.prj <- cbind(prj.coord, lbl.X)
+names(lbl.X.prj)[1:2] <- c("X.prj","Y.prj")
+pr <- projectRaster(ras, crs=PROJ, method='bilinear',res=36000)
+
+# IMPORT SHAPEFILE
+cropped <- crop(x = pr, y = extent(NE_countries_rob))
+masked <- mask(x = cropped, mask = NE_countries_rob)
+#plot(masked)
+
+test_spdf <- as(masked, "SpatialPixelsDataFrame")
+test_df <- as.data.frame(test_spdf)
+colnames(test_df) <- c("value", "x", "y")
+
+# __________ Plot layers
+plt=ggplot() +
+  # add Natural Earth countries projected to Robinson, give black border and fill with gray
+  geom_polygon(data=NE_countries_rob, aes(long,lat, group=group), 
+               colour="black", fill="gray80", size = 0.25) +
+  # Note: "Regions defined for each Polygons" warning has to do with fortify transformation. Might get deprecated in future!
+  # alternatively, use use map_data(NE_countries) to transform to data frame and then use project() to change to desired projection.
+  # add Natural Earth box projected to Robinson
+  geom_polygon(data=NE_box_rob, aes(x=long, y=lat), colour="black", fill="transparent", size = 0.25) +
+  # add graticules projected to Robinson
+  geom_path(data=NE_graticules_rob, aes(long, lat, group=group), linetype="dotted", color="grey50", size = 0.25) +
+  # add graticule labels - latitude and longitude
+  geom_text(data = lbl.Y.prj[c(TRUE, FALSE),], aes(x = X.prj, y = Y.prj, label = lbl), color="grey50", size=2.5) +
+  geom_text(data = lbl.X.prj[c(TRUE, FALSE),], aes(x = X.prj, y = Y.prj, label = lbl), color="grey50", size=2.5) +
+  # the default, ratio = 1 in coord_fixed ensures that one unit on the x-axis is the same length as one unit on the y-axis
+  coord_fixed(ratio = 1) +
+  geom_tile(data=test_df, aes(x=x, y=y, fill=value),alpha=1)+
+  scale_fill_gradientn(colors=
+                       rev(map_col),
+                       name = " ",
+                       na.value = "transparent",
+                       #labels=c("Minimum",0.5,"Maximum"),
+                       breaks=brk,
+                       limits=lim)+
+  geom_polygon(data=NE_countries_rob, aes(long,lat, group=group), 
+               colour="black", fill="transparent", size = 0.25) +
+  # remove the background and default gridlines
+  theme_void()+
+  theme(plot.title = element_text(hjust = 0.5,size =12, face = "bold"),
+        legend.position="bottom",
+        legend.key.width=unit(1.8, "cm"),
+        legend.key.height=unit(0.4, "cm"),
+        legend.text=element_text(size=16))+
+  ggtitle(name)
+plt
+
+# REFERENCES:
+# This link was useful for graticule idea
+#   http://stackoverflow.com/questions/38532070/how-to-add-lines-of-longitude-and-latitude-on-a-map-using-ggplot2
+# Working with shapefiles, projections and world maps in ggplot
+#   http://rpsychologist.com/working-with-shapefiles-projections-and-world-maps-in-ggplot
+return(plt)
+}
+