# -*- coding: utf-8 -*-

"""

Created on Sun Apr 30 00:35:32 2017

@author: kkrao

"""

from __future__ import division

from IPython import get_ipython

get_ipython().magic('reset -sf')

import numpy as np

import pandas as pd

import matplotlib

from mpl_toolkits.basemap import Basemap

import matplotlib.pyplot as plt

import numpy.ma as ma

import scipy.io

import os

import arcpy

from osgeo import gdal

from osgeo import gdal_array

from osgeo import osr

from arcpy.sa import *

arcpy.env.overwriteOutput=True

MyDir = 'D:/Krishna/Project/data/RS_data' #Type the path to your data

Dir_CA='D:/Krishna/Project/data/Mort_Data/CA'

Dir_fig='D:/Krishna/Project/figures'

Dir_mort='D:/Krishna/Project/data/Mort_Data/CA_Mortality_Data'

year_range=range(2005,2016)

date_range=range(1,367,1)

scale_factor=1e4

pass_type = 'D'; #Type the overpass: 'A' or 'D'

param = 'tc10'; #Type the parameter

factor = 1e-0; #Type the multiplier associated with the factor

bnds = [0.0,3.0]; #Type the lower and upper bounds of the parameter

fid = open(MyDir+'/anci/MLLATLSB','rb');

late= np.fromfile(fid,dtype=np.int32).reshape((586,1383))

fid.close()

fid = open(MyDir+'/anci/MLLONLSB','rb');

lone= np.fromfile(fid,dtype=np.int32).reshape((586,1383))

fid.close()

late = [i*1e-5 for i in late];

lone = [i*1e-5 for i in lone]

latcorners=[32,42.5]

loncorners=[-125,-113.5]

nrows=int(np.shape(late)[0])

ncols=int(np.shape(late)[1])

y=np.asarray(lone)

y=y.flatten()

x=np.asarray(late)

x=x.flatten()

grid_x, grid_y = np.mgrid[90:-90.25:-0.25, -180:180.25:0.25]

xmin,ymin,xmax,ymax = [np.min(grid_y),np.min(grid_x),np.max(grid_y),np.max(grid_x)]

for k in year_range:

year = '%s' %k #Type the year

print('Processing data for year '+year+' ...')

for j in date_range:

date='%03d'%j

fname=MyDir+'/'+param+'/'+year+'/AMSRU_Mland_'+year+date+pass_type+'.'+param

if os.path.isfile(fname):

fid = open(fname,'rb');

data=np.fromfile(fid)

fid.close()

for i in list(range(len(data))):

if data[i]<=0.0:

data[i]=np.nan

data = [i*factor for i in data];

data = -np.log(data)

from mkgrid_global import mkgrid_global

datagrid = mkgrid_global(data)

datagridm = ma.masked_invalid(datagrid)

from scipy.interpolate import griddata

z=np.asarray(datagridm)

z=z.flatten()

grid_z = griddata((y,x), z, (grid_y, grid_x), method='linear')

grid_z = ma.masked_invalid(grid_z)

nrows,ncols = np.shape(grid_z)

nrows=np.int(nrows)

ncols=np.int(ncols)

xres = (xmax-xmin)/(ncols-1)

yres = (ymax-ymin)/(nrows-1)

geotransform=(xmin,xres,0,ymax,0, -yres)

arcpy.env.workspace=Dir_fig

os.chdir(Dir_fig)

output_raster = gdal.GetDriverByName('GTiff').Create('VOD_%s_%s_%s.tif' %(year,date,pass_type),ncols, nrows, 1 ,gdal.GDT_Float32,) # Open the file

output_raster.SetGeoTransform(geotransform) # Specify its coordinates

srs = osr.SpatialReference() # Establish its coordinate encoding

srs.ImportFromEPSG(4326) # This one specifies WGS84 lat long.

# Anyone know how to specify the

# IAU2000:49900 Mars encoding?

output_raster.SetProjection( srs.ExportToWkt() ) # Exports the coordinate system

# to the file

output_raster.GetRasterBand(1).WriteArray(grid_z) # Writes my array to the raster

output_raster.FlushCache()

output_raster = None

arcpy.Clip_management('VOD_%s_%s_%s.tif' %(year,date,pass_type), "#",'VOD_%s_%s_%s_clip.tif' %(year,date,pass_type),Dir_CA+'/'+"CA.shp", "0", "ClippingGeometry")

##mapping algebra * 10000

inRaster = 'VOD_%s_%s_%s_clip.tif'%(year,date,pass_type)

arcpy.CheckOutExtension("Spatial")

outRaster = Raster(inRaster)*scale_factor

outRaster.save(Dir_fig+'/'+'VOD_%s_%s_%s_clip_map.tif'%(year,date,pass_type))

##copy raster

inRaster=outRaster

pixel_type='16_BIT_UNSIGNED'

arcpy.CopyRaster_management(inRaster, 'VOD_%s_%s_%s_clip_map_copy.tif'%(year,date,pass_type), pixel_type='16_BIT_UNSIGNED',nodata_value='0')

##make raster table

inRaster='VOD_%s_%s_%s_clip_map_copy.tif'%(year,date,pass_type)

arcpy.BuildRasterAttributeTable_management(inRaster, "Overwrite")