def plot_period(list_h,list_value, area_id):
list_period_value= []
list_period_h = []
d = 10
size_h = len(list_h)
for x in xrange(0,int(max(list_h)//10)):
mean = 0
total = 0
for y in xrange(0,size_h):
if (list_h[y] > d*x) and (list_h[y] < d*(x+1)):
total = total +1
mean = mean + list_value[y]
if total >0:
list_period_value.append(mean/total)
list_period_h.append(d*x)
plt.subplot(3, 2, 1)
plt.plot(list_h, list_value, 'r.')
plt.title('A tale of x subplots')
plt.ylabel('Semi-variogram')
plt.subplot(3, 2, 2)
plt.plot(list_period_h, list_period_value, 'r.')
#plt.plot(list_h, list_value, 'r.')
plt.xlabel('Distance (km)')
plt.ylabel('Semi-variogram PERIOD')
#spherical
a0,c0, mse_sph = opt('spherical', list_period_h, list_period_value)
#a0,c0, mse_sph = opt('spherical', list_h, list_value)
print 'a0=',a0, ' c0=', c0, ' mse_sph = ', mse_sph
plt.subplot(3, 2, 5)
list_spherical = []
list_h = sorted(list_h)
for h in list_h :
list_spherical.append(spherical( h, a0, c0))
#if spherical( h, a0, c0) != c0:
# print spherical( h, a0, c0)
plt.plot(list_h, list_spherical, 'r-')
plt.xlabel('Distance (km)')
plt.ylabel('Semi-variogram- SPHERICAL')
#plt.savefig(os.path.splitext(os.path.basename('temp_semi_all_station_thang_2'))[0] + '.png')
sph = [a0, c0]
global_data[area_id] = sph
if LOG:
plt.show()
def krigeOne(point, neighbor, list_all_station, list_data, G, D):
#print 'KRIGE ONE'
list_station = list_all_station
#Cal distances from current point to all others
item0 = (0, point[0], point[1])
meteo_size = len(list_station)
list_d = []
#cal all distance from point to others stations
for i in xrange(0,meteo_size):
#Cal distance one-one
item1 = list_station[i]
d = haversine(item0[2], item0[1] ,item1[2], item1[1])
newitem = (item1[0], d, item1[3], item1[1], item1[2])#id, distance, temp, lat, lon
list_d.append(newitem)
#Sort by distance, get n first nearest neighbors
sorted_list = sorted(list_d, key=itemgetter(1))
list_neighbor = sorted_list[:neighbor]
#print list_neighbor
K1 = np.zeros([neighbor, neighbor])
K = np.zeros([neighbor, neighbor])
k = np.zeros([neighbor, 1])
k_semi = np.zeros([neighbor, 1])
T = []# list of temp of neighbor station at interpolate time
string = ''
i = 0
for item in list_neighbor:
if LOG:
f.write('getting T\n')
#Nhiet do 1 thang cua tram item
#print len(list_data)
t = list_data[item[0]-1]
trendValue = getTrendValue(trend_curve, item[3], item[4])
#print trend_curve, trendValue
if LOG:
f.write(str(t) + '\n')
t_size = len(t)
T.append(t[t_size - 1] - trendValue)
j = 0
string = string + str(item[0])
#print item
#Area key = 0, because of we have only one model for all
a0, c0 = global_data[0][0], global_data[0][1]
h = item[1]#distance
k[i][0] = semiToCov( h, a0, c0)
k_semi[i][0] = spherical(h, a0, c0)
for sub_item in list_neighbor:
string = string+' ' + str(sub_item[0])
#print i, j
K1[i][j] = G_COV[item[0]-1][sub_item[0]-1]
K [j][i] = K1[i][j]#Inverse of K1
j = j + 1
string = string + '\n'
i = i + 1
if LOG:
f.write('T: ' + str(T) + '\n')
f.write('neighbors list: \n' + string + '\n')
#print string
#print k
#print K
f.write('K: \n' + str(K) +' \n')
f.write('k: \n' + str(k) +' \n')
weight = np.dot(K,k)
if LOG:
f.write('ori-weight: \n' + str(weight) +' \n')
if sum(weight) == 0:
if LOG:
f.write('NOT RELATED\n')
weight[:] = 1 #assign the same weight for all elements
weight = weight/sum(weight)
krige = np.dot(T, weight)
f.write('nor-weight: \n' + str(weight) +' \n')
f.write('T: \n' + str(T)+' \n')
f.write('krige: ' + str(krige)+' \n')
#print krige
#print krige[0],' ',
#print k
weight = inverseMatrix(weight)
derivation = np.dot(weight, k_semi)
f.write('derivation: ' + str(derivation[0][0])+' \n')
#time.sleep(2)
return krige[0], derivation[0][0]