def main_program(shuffi, isCrossValidation):
list_all_test = shuffi[0]
list_all_station = shuffi[1]
global D
#time.sleep(100)
print len(list_all_station)
trend_curve = generateGlobalMatrix(date_from, date_to, list_all_station)
D = generateDistanceMatrix(list_all_station)
area_id = 0
genModelForArea(area_id, list_all_station, list_data, G, D)
reGenerateSemiMatrix(list_all_station)
print 'GLOBAL DATA'
print global_data
derivation = np.zeros([row,col])
result = np.zeros([row,col])
for i in xrange(0,row):
#print i
for j in xrange(0, col):
#print i, j
point = (minLat + i*shift,minLon + j*shift)
f.write(str(i)+' '+ str(j)+ ':'+ str(point) +'\n')
#if isInVietnam(point):
result[i][j], derivation[i][j] = krigeOne(point, neighbor, list_all_station, list_data, G, D)
trendValue = getTrendValue(trend_curve, point[0], point[1])
#print trendValue
result[i][j] = result[i][j] + trendValue
#exportGeotiff('filename', raster, row, col, shift, minLon, minLat)
if isCrossValidation == False:
exportGeotiff('t08_GEOTIFF_simple_kriging_one_model', result, row, col, shift, minLon, minLat )
saveAsPng(result)
saveAsPng(derivation)
if isCrossValidation:
return calculateSE(result, list_all_test, minLat, minLon, shift, date_to)
def main_program(shuffi, isCrossValidation):
f_se = open("Moiseture_f_se.txt", "a")
f_se.write("Moiseture_se statistic\n")
f_da = open("Moiseture_f_da.txt", "a")
f_da.write("Moiseture_da statistic\n")
list_all_test = shuffi[0]
list_all_station = shuffi[1]
global D
# time.sleep(100)
print len(list_all_station)
trend_curve = generateGlobalMatrix(date_from, date_to, list_all_station)
D = generateDistanceMatrix(list_all_station)
area_id = 0
genModelForArea(area_id, list_all_station, list_data, G, D)
reGenerateSemiMatrix(list_all_station)
print "GLOBAL DATA"
print global_data
derivation = np.zeros([row, col])
result = np.zeros([row, col])
result_kri_backup = np.zeros([row, col])
for i in xrange(0, row):
# print i
for j in xrange(0, col):
# print i, j
point = (minLat + i * shift, minLon + j * shift)
f.write(str(i) + " " + str(j) + ":" + str(point) + "\n")
result[i][j], derivation[i][j] = krigeOne(point, neighbor, list_all_station, list_data, G, D)
trendValue = getTrendValue(trend_curve, point[0], point[1])
# print trendValue
result[i][j] = result[i][j] + trendValue
result_kri_backup[i][j] = result[i][j]
# DATA ASSIMILATION: assimilate
# if sate_lite_value[i][j] != 0:
# result[i][j] = assimilate(result[i][j], derivation[i][j], sate_lite_value[i][j], sate_lite_deri[i][j], f_da)
# Assimilate with Utility.assimilate
if isCrossValidation == False:
exportGeotiff("Moiseture__GEOTIFF_universal_kriging", result, row, col, shift, minLon, minLat)
exportGeotiff("Moiseture__GEOTIFF_universal_kriging_derivation", derivation, row, col, shift, minLon, minLat)
saveAsPng(result)
saveAsPng(derivation)
f_da.close()
f_se.close()
if isCrossValidation:
return calculateSE(
result, result_kri_backup, list_all_test, minLat, minLon, shift, date_to, f, sate_lite_value, f_se
)