#
#  File:
#    TRANS_masking.py
#
#  Synopsis:
#    Illustrates how to mask data
#
#  Categories:
#    map plot
#    contour plot
#
#  Author:
#    Karin Meier-Fleischer, based on NCL example
#  
#  Date of initial publication:
#    September 2018
#
#  Description:
#    This example shows how to mask data. Xarray is used to 
#    read the NetCDF file, but PyNIO can also be used.
#    See the lines commented with ###.
#
#  Effects illustrated:
#    o  Drawing contours on a map
#    o  Using manual levels
#    o  Change map resolution
#    o  Using area specifiers
# 
#  Output:
#    A single visualization is produced.
#
#  Notes: The data for this example can be downloaded from 
#    http://www.ncl.ucar.edu/Document/Manuals/NCL_User_Guide/Data/
#   
'''
  Transition Guide Python Example: TRANS_masking.py

  -  Drawing contours on a map
  -  Using manual levels
  -  Change map resolution
  -  Using area specifiers

  18-09-11  kmf
'''
import Ngl
import xarray as xr
###import Nio
import os

#-- countries where contours should appear
#-- too small countries: "Monaco","San Marino","Vatican City"
mask_specs = ["Albania","Andorra","Armenia", \
              "Austria","Azerbaijan","Belarus","Belgium", \
              "Bosnia and Herzegovina","Bulgaria","Croatia", \
              "Cyprus","Czech Republic","Denmark","Estonia", \
              "Finland","France","Georgia","Germany","Greece", \
              "Hungary","Iceland","Ireland","Italy","Kazakhstan", \
              "Latvia","Liechtenstein","Lithuania","Luxembourg", \
              "Macedonia","Malta","Moldova","Montenegro", \
              "Netherlands","Norway","Poland","Portugal","Romania", \
              "Russia","Serbia","Slovakia","Slovenia", \
              "Spain","Sweden","Switzerland","Turkey","Ukraine", \
              "United Kingdom"]

#--  open file and read variables
f    = xr.open_dataset("rectilinear_grid_3D.nc")
var  = f.t[0,0,:,:].values
lat  = f.lat.values
lon  = f.lon.values

### PyNIO
###f    = Nio.open_file("rectilinear_grid_3D.nc", "r")
###var  = f.variables["t"][0,0,:,:]
###lat  = f.variables["lat"][:]
###lon  = f.variables["lon"][:]

#-- start the graphics
wks = Ngl.open_wks("png",os.path.basename(__file__).split('.')[0])

minlat =  30.0
maxlat =  80.0
minlon = -12.0
maxlon =  35.0

#-- resource settings
res                    =  Ngl.Resources()
res.nglFrame           =  False

res.cnFillOn           =  True              #-- turn on contour level fill
res.cnFillPalette      = "cmp_b2r"          #-- choose color map
res.cnLinesOn          =  False             #-- don't draw contour lines
res.cnLineLabelsOn     =  False             #-- turn off contour line labels
res.cnLevelSelectionMode = "ManualLevels"   #-- use manual contour line levels
res.cnMinLevelValF     =  250.0             #-- contour min. value
res.cnMaxLevelValF     =  300.0             #-- contour max. value
res.cnLevelSpacingF    =    2.5             #-- contour interval
res.cnFillDrawOrder    = "Predraw"          #-- contours first; then fills                          

res.lbBoxMinorExtentF  =  0.2               #-- height of labelbar boxes
res.lbOrientation   = "horizontal"          #-- horizontal labelbar
res.lbLabelFontHeightF = 0.014

res.mpDataBaseVersion  = "MediumRes"        #-- alias to Ncarg4_1
res.mpDataSetName      = "Earth..4"
res.mpLimitMode        = "LatLon"
res.mpMinLatF          =  minlat
res.mpMaxLatF          =  maxlat
res.mpMinLonF          =  minlon
res.mpMaxLonF          =  maxlon
res.mpGridAndLimbOn      =  False

res.mpFillOn              = True            #-- turn on map fill
res.mpOutlineBoundarySets = "National"
res.mpFillBoundarySets    = "NoBoundaries"
res.mpAreaMaskingOn       =  True
res.mpMaskAreaSpecifiers  =  mask_specs
res.mpFillAreaSpecifiers  = ["land","water"]
res.mpSpecifiedFillColors = ["gray65","gray85","gray65"]  #-- Land,Ocean,InlandWater

res.sfXArray           =  lon
res.sfYArray           =  lat

#-- viewport resources
res.nglMaximize        =  False             #-- don't maximize plot
res.vpYF               =  0.9               #-- start y-position of viewport
res.vpWidthF           =  0.65              #-- width of viewport
res.vpHeightF          =  0.65              #-- height of viewport

#-- create the contour plot
plot = Ngl.contour_map(wks,var,res)

#-- Retrieve some resources from map for adding labels
vpx  = Ngl.get_float(plot.map,'vpXF')
vpy  = Ngl.get_float(plot.map,'vpYF')
vpw  = Ngl.get_float(plot.map,'vpWidthF')
fnth = Ngl.get_float(plot.map,'tmXBLabelFontHeightF')

#-- write variable long_name and units to the plot
txres               = Ngl.Resources()
txres.txFontHeightF = fnth

txres.txJust  = "CenterLeft"
Ngl.text_ndc(wks,f.t.long_name,vpx,vpy+0.02,txres)
###Ngl.text_ndc(wks,f.variables["t"].attributes['long_name'],vpx,vpy+0.02,txres)

txres.txJust  = "CenterRight"
Ngl.text_ndc(wks,f.t.units,vpx+vpw,vpy+0.02,txres)
###Ngl.text_ndc(wks,f.variables["t"].attributes['units'],vpx,vpy+0.02,txres)

Ngl.frame(wks)