def tricolour(wks, xll, yll, height):
#
# Colors
#
blue_index = Ngl.new_color(wks, 0.00, 0.15, 0.50)
white_index = Ngl.new_color(wks, 1.00, 1.00, 1.00)
red_index = Ngl.new_color(wks, 1.00, 0.10, 0.14)
width = 1.5 * height
xx = numpy.zeros(5, 'f')
yy = numpy.zeros(5, 'f')
#
# Draw blue bar.
#
xx = [xll, xll + width / 3., xll + width / 3., xll, xll]
yy = [yll, yll, yll + height, yll + height, yll]
pres = Ngl.Resources()
pres.gsFillColor = blue_index
Ngl.polygon_ndc(wks, xx, yy, pres)
#
# Draw white bar.
#
xx = [xll+width/3., xll + 2.*width/3., xll + 2.*width/3., \
xll+width/3., xll+width/3.]
pres.gsFillColor = white_index
Ngl.polygon_ndc(wks, xx, yy, pres)
#
# Draw red bar.
#
xx = [xll+2.*width/3., xll + width, xll + width, \
xll+2.*width/3., xll+2.*width/3.]
pres.gsFillColor = red_index
Ngl.polygon_ndc(wks, xx, yy, pres)
xx = [xll, xll + width, xll + width, xll, xll]
#
# Perimeter.
#
pres.gsLineColor = 1
Ngl.polyline_ndc(wks, xx, yy, pres)
wks = Ngl.open_wks(wks_type,"ngl05p")
#----------- Begin first plot -----------------------------------------
resources = Ngl.Resources()
resources.sfXCStartV = float(min(psl_lon))
resources.sfXCEndV = float(max(psl_lon))
resources.sfYCStartV = float(min(psl_lat))
resources.sfYCEndV = float(max(psl_lat))
map = Ngl.contour_map(wks,psl,resources)
#----------- Begin second plot -----------------------------------------
ic = Ngl.new_color(wks,0.75,0.75,0.75) # Add gray to the color map
resources.mpProjection = "Orthographic" # Change the map projection.
resources.mpCenterLonF = 180. # Rotate the projection.
resources.mpFillOn = True # Turn on map fill.
resources.mpFillColors = [0,-1,ic,-1] # Fill land and leave oceans
# and inland water transparent.
resources.vpXF = 0.1 # Change the size and location of the
resources.vpYF = 0.9 # plot on the viewport.
resources.vpWidthF = 0.7
resources.vpHeightF = 0.7
mnlvl = 0 # Minimum contour level.
mxlvl = 28 # Maximum contour level.
spcng = 2 # Contour level spacing.
# # Draw an orthographic map centered at lat/lon = (70.,-10.). # Don't advance the frame, since we want to add wind barbs. # mpres = Ngl.Resources() # # Define size of map in frame. # mpres.mpShapeMode = "FreeAspect" mpres.vpXF = 0.06 mpres.vpYF = 0.94 mpres.vpWidthF = 0.42 mpres.vpHeightF = 0.42 mpres.nglFrame = False gray_index = Ngl.new_color(wks, 0.7, 0.7, 0.7) cyan_index = Ngl.new_color(wks, 0.5, 0.9, 0.9) mpres.mpFillAreaSpecifiers = ["Water", "Land"] mpres.mpSpecifiedFillColors = [cyan_index, gray_index] mpres.mpLimitMode = "LatLon" mpres.mpMinLonF = -40. mpres.mpMaxLonF = 20. mpres.mpMinLatF = 55. mpres.mpMaxLatF = 85. mpres.mpCenterLatF = 70. mpres.mpCenterLonF = -10. mpres.mpPerimOn = True mpres.mpProjection = "Orthographic" mpres.tiMainString = "Winds from the south" mpres.tiMainFont = "Helvetica-Bold"
mpres.cnFillColors = [8,17,30,50,65,95,120,134,152,161]
mpres.pmTickMarkDisplayMode = "Never" # Don't draw tickmark border.
mpres.lbOrientation = "Horizontal" # put labelbar at bottom
mpres.pmLabelBarSide = "Bottom" # and horizontal
mpres.lbTitleString = "Sea Surface Temperature Change (~S~o~N~C)"
mpres.lbTitlePosition = "Bottom"
mpres.lbTitleFontHeightF = 0.015
mpres.lbLabelFontHeightF = 0.015
mpres.pmLabelBarOrthogonalPosF = 0.025
map = Ngl.contour_map(wks,sst,mpres) # Draw the first contours/map.
Ngl.define_colormap(wks,"WhViBlGrYeOrRe") # set colormap for 2nd contours
igray = Ngl.new_color(wks,0.8,0.8,0.8) # add gray
# Set up new contour resources
mpres.sfXArray = Lon
mpres.sfYArray = Lat
mpres.cnMinLevelValF = 500. # min contour level
mpres.cnMaxLevelValF = 3500. # max contour level
mpres.cnLevelSpacingF = 500. # contour spacing
mpres.cnFillColors = [20,17,14,12,10,8,6,4]
mpres.lbOrientation = "Vertical" # vertical labelbar on
mpres.pmLabelBarSide = "Left" # left side
mpres.lbTitleString = "Ice Sheet Elevation (m)"
mpres.lbTitlePosition = "Left"
delx_0, delx_1, dely_0, dely_1 = 0.245, 0.235, 0.22, 0.15
x[0], y[0] = 0.015 + delx_0*(i%4), 0.90 - (i/4)*dely_0
x[1], y[1] = x[0] + delx_1 , y[0]
x[2], y[2] = x[1] , y[1] - dely_1
x[3], y[3] = x[0] , y[2]
x[4], y[4] = x[0] , y[0]
#
# Convert the integer color values obtained from the
# named color chart (as entered above) to floating
# point numbers in the range 0. to 1. (as required
# by "Ngl.new_color").
#
r, g, b = colors[i][0]/255., colors[i][1]/255., colors[i][2]/255.
poly_res.gsFillColor = Ngl.new_color(wks, r, g, b)
#
# Draw a white outline if the color is black, otherwise draw a colored box.
#
if (labels[i] == "Black"):
Ngl.polyline_ndc(wks, x, y, poly_res)
else:
Ngl.polygon_ndc(wks, x, y, poly_res)
#
# Label the boxes.
#
text_res.txFontHeightF = 0.017
Ngl.text_ndc(wks, labels[i], 0.5*(x[0]+x[1]), y[0] + 0.0125, text_res)
rgb_label = "R=%4.2f G=%4.2f B=%4.2f" % (r, g, b)
text_res.txFontHeightF = 0.015
Ngl.text_ndc(wks, rgb_label, 0.5*(x[0]+x[1]), y[3] - 0.0125, text_res)
def plot_oope_map(data, figname, size_class=None, percentage=1):
''' Draws 2D OOPE maps.
:param xarray.Dataset data: 2D OOPE array. Dims must be (y, x, comm, size)
:param str figname: Name of the figure file (must end by .png or .pdf)
:param list size_class: Size classes to output (in m)
:param float percentage: percentage used to saturate colorbar from percentile.
Colorbar is saturated from values of the (X) and (100 - X) percentile.
:return: None
'''
if size_class is None:
size_class = [1e-3, 1e-2, 1e-1, 1]
# sort size class in ascending order, and add 0 and infinity as size bounds
size_class = np.sort(size_class)
if size_class[0] != 0:
size_class = np.concatenate(([0], size_class), axis=0)
if size_class[-1] != np.Inf:
size_class = np.concatenate((size_class, [np.Inf]), axis=0)
# Check that the OOPE dataset has 4 dimensions (i.e. no time dimension)
ndims = len(data['OOPE'].dims)
if ndims != 4:
message = 'Data must have dimensions of size (lat, lon, comm, wei)'
print(message)
sys.exit(0)
# Recover data variables
length = data['length'].values
oope = data['OOPE'].values
lon = data['longitude'][:].values
lat = data['latitude'][:].values
comm = data['community'][:].values.astype(np.int)
# mask oope where land
oope = np.ma.masked_where(np.isnan(oope), oope)
comm_string = misc.extract_community_names(data)
if figname.endswith('png'):
form = 'png'
elif figname.endswith('pdf'):
form = 'pdf'
else:
message = 'Figure name should end with png or pdf'
print(message)
sys.exit(0)
# opens the document
wks = Ngl.open_wks(form, figname)
# set the document colormap
# resngl = Ngl.Resources()
# resngl.wkColorMap = 'precip2_15lev'
# Ngl.set_values(wks, resngl)
# Add gray to the workspace
Ngl.new_color(wks, 0.7, 0.7, 0.7)
# init the plot resources
# For a detailed description, see https://www.ncl.ucar.edu/Document/Graphics/Resources/
res = Ngl.Resources()
# not necessary, just a good habit
res.nglDraw = False
res.nglFrame = False
# Set map resources.
res.mpLimitMode = "LatLon" # limit map via lat/lon
res.mpMinLatF = lat.min() # map area
res.mpMaxLatF = lat.max() # latitudes
res.mpMinLonF = lon.min() # and
res.mpMaxLonF = lon.max() # longitudes
res.mpFillOn = True
res.mpLandFillColor = "LightGray"
res.mpOceanFillColor = -1
res.mpInlandWaterFillColor = "LightBlue"
res.mpGeophysicalLineThicknessF = 1 # thickness of coastlines
# coordinates for contour plots
res.sfXArray = lon
res.sfYArray = lat
res.cnFillOn = True # filled contour
res.cnLinesOn = False # no lines
res.cnLineLabelsOn = False # no labels
res.cnInfoLabelOn = False # no info about contours
res.cnFillMode = 'CellFill' # contourf=AreaFill, pcolor="CellFill" or "RasterFill"
res.lbOrientation = "Horizontal" # colorbar orientation
res.lbLabelFontHeightF = 0.012 # colorbar label fontsize
res.lbTitlePosition = "Bottom" # position of colorbar title
res.lbTitleFontHeightF = 0.012 # title font height
# res.cnFillPalette = "wgne15"
res.cnFillPalette = "WhiteBlueGreenYellowRed"
txres = Ngl.Resources()
txres.txJust = "BottomCenter"
txres.txFontHeightF = 0.02
res.cnLevelSelectionMode = 'ExplicitLevels'
res.cnMaxLevelCount = 41
res.mpGridAndLimbOn = True
# Equations are complicated with NCARG
# see https://www.ncl.ucar.edu/Applications/fcodes.shtml
res.lbTitleString = "OOPE (J.kg~S~-1~N~.m~S~-2~N~)" # title of colorbar
# Loop over communities
for icom in comm:
# Loop over size classes
for isize in xrange(0, len(size_class) - 1):
# Extract sizes comprised between the size class bound
iw = np.nonzero((length >= size_class[isize]) & (length < size_class[isize+1]))[0]
if iw.size == 0:
continue
# Integrate OOPE for the given community and given size class
temp = oope[:, :, icom, iw]
temp = np.sum(temp, axis=-1)
# Finds the colorbar limits
cmin, cmax = misc.find_percentile(temp, percentage=1)
# draw the contour maps
# defines the contour
res.cnLevels = np.linspace(cmin, cmax, res.cnMaxLevelCount)
mapplot = Ngl.contour_map(wks, temp, res)
# add title
title = 'Community=%s, %.2E m <= L < %.2E m' % (comm_string[icom], size_class[isize], size_class[isize + 1])
Ngl.text_ndc(wks, title, 0.5, 0.85, txres)
# draws the map
Ngl.draw(mapplot)
# add a page to the pdf output
Ngl.frame(wks)
