%
%  This example code illustrates how to access and visualize NSIDC
%  AMSR_E Daily Ocean version 4 L3 HDF-EOS2 Grid file in MATLAB.
%
%  If you have any questions, suggestions, comments on this example, 
% please use the HDF-EOS Forum (http://hdfeos.org/forums). 
% 
%  If you would like to see an  example of any other NASA HDF/HDF-EOS
% data product that is not listed in the HDF-EOS  Comprehensive Examples 
% page (http://hdfeos.org/zoo), feel free to contact us at 
% eoshelp@hdfgroup.org or post it at the HDF-EOS Forum 
% (http://hdfeos.org/forums).
%
% Usage:save this script and run (without .m at the end)
%
%  $matlab -nosplash -nodesktop -r AMSR_E_L3_DailyOcean_V04_20020619_hdf
%
% Tested under: MATLAB R2018b
% Last updated: 2019-01-04

import matlab.io.hdfeos.*
import matlab.io.hdf4.*

% Opening the HDF-EOS2 Grid File
FILE_NAME = 'AMSR_E_L3_DailyOcean_V04_20020619.hdf';
file_id = gd.open(FILE_NAME, 'rdonly');

% Reading Data from a Data Field
GRID_NAME = 'GlobalGrid';
grid_id = gd.attach(file_id, GRID_NAME);

DATAFIELD_NAME = 'High_res_cloud';
data1 = gd.readField(grid_id, DATAFIELD_NAME, [], [], []);

% Convert M-D data to 2-D data
data = data1;

% Convert the data to double type for plot
data = double(data);

% Transpose the data to match the map projection
data = data';

% Get information about the spatial extents of the grid.
[xdimsize, ydimsize, upleft, lowright] = gd.gridInfo(grid_id);

% We need to readjust the limits of latitude and longitude.
% HDF-EOS is using DMS(DDDMMMSSS.SS) format to represent degrees.
% So to calculate the lat and lon in degree, one needs to convert minutes
% and seconds into degrees. 

% The following is the detailed description on how to calculate the latitude and longitude range based on lowright and upleft.
% One should observe the fact that 1 minute is 60 seconds and 1 degree is 60 minutes. 

% First calculate the difference of .SS between lowright and upleft:
lowright_ss = lowright * 100 - floor(lowright) * 100;
upleft_ss = upleft * 100 - floor(upleft) * 100;
dss = lowright_ss - upleft_ss;

% Then calculate the difference of SSS between lowright and upleft:
lowright_s = mod(floor(lowright),1000);
upleft_s = mod(floor(upleft),1000);

ds =lowright_s - upleft_s +dss/100;

% Then calculate the difference of MMM between lowright and upleft:

lowright_m = mod(floor(lowright/1000),1000);
upleft_m = mod(floor(upleft/1000),1000);

dm = lowright_m-upleft_m + ds/60;

% Then calculate the difference of DDD between lowright and upleft:
lowright_d = floor(lowright/1000000);
upleft_d = floor(upleft/1000000);
dd = lowright_d-upleft_d + dm/60;

lat_limit = dd(2);
lon_limit = dd(1);

% We need to calculate the grid space interval between two adjacent points

scaleX = lon_limit/xdimsize;
scaleY = lat_limit/ydimsize;

% By default HDFE_CENTER is assumed for the offset value, which assigns 0.5 to both offsetX and offsetY.
offsetX = 0.5;
offsetY = 0.5;

% Since this grid is using geographic projection, the latitude and longitude value will be calculated based on the formula:
% (i+offsetX)*scaleX+leftX  for longitude and (i+offsetY)*scaleY+leftY for latitude.

for i = 0:(xdimsize-1)
    lon_value(i+1) = (i+offsetX)*(scaleX) + upleft_d(1);
end

for j = 0:(ydimsize-1)
    lat_value(j+1) = (j+offsetY)*(scaleY) + upleft_d(2);
end

% Convert the data to double type for plot
lon = double(lon_value);
lat = double(lat_value);

% Detach Grid object.
gd.detach(grid_id);
gd.close(file_id);

% Reading attributes from the data field
SD_id = sd.start(FILE_NAME, 'rdonly');
DATAFIELD_NAME = 'High_res_cloud';
sds_index = sd.nameToIndex(SD_id, DATAFIELD_NAME);
sds_id = sd.select(SD_id, sds_index);

% Read units from the data field.
units_index = sd.findAttr(sds_id, 'Unit');
units = sd.readAttr(sds_id, units_index);

% Read scale_factor from the data field.
scale_index = sd.findAttr(sds_id, 'Scale');
scale = sd.readAttr(sds_id, scale_index);
scale = double(scale);

% Terminate access to the corresponding data set.
sd.endAccess(sds_id);

% Close the file.
sd.close(SD_id);

% Handle fill value.
data(data==-9999) = NaN;

% Apply scale factor.
data = data*scale;

% Plot the data using contourfm and axesm
latlim = [floor(min(min(lat))),ceil(max(max(lat)))];
lonlim = [floor(min(min(lon))),ceil(max(max(lon)))];
min_data = floor(min(min(data)));
max_data = ceil(max(max(data)));

f = figure('Name', FILE_NAME, 'Renderer', 'zbuffer', ...
           'Position', [0,0,800,600], 'visible', 'off');

axesm('MapProjection','eqdcylin','Frame','on','Grid','on', ...
      'MapLatLimit', latlim,'MapLonLimit',lonlim, ...
      'MeridianLabel','on','ParallelLabel','on', ...
      'MLabelParallel','south');
coast = load('coast.mat');

surfacem(lat,lon,data);
colormap('Jet');
caxis([min(min(data)) max(max(data))]); 
h = colorbar('YTick', min(min(data)):0.2:max(max(data)));

plotm(coast.lat,coast.long,'k')
tightmap;

title({FILE_NAME; 'HIgh res cloud'}, 'Interpreter', 'None', ...
      'FontSize',12,'FontWeight','bold');

set (get(h, 'title'), 'string', units, 'FontSize',12,'FontWeight','bold');

saveas(f,[FILE_NAME '.m.png']);
exit;