def __init__(self, src_grid_file_name, dst_grid_file_name, online_flag, realdata_file_name, k, pole_flag): Interp.__init__(self, src_grid_file_name, dst_grid_file_name, online_flag, realdata_file_name) self.power = 1 self.eps = 1.0e-6 self.nearest_k = k self.idw_obj = Search(self.stree_base_obj, self.stree) self.pole_flag = pole_flag
def _numMatches(parseTree, data, name='a'):
_calls = []
def _cb():
_calls.append(True)
i = Interp(parseTree, _cb)
try:
i.receive(data)
except ParseError as e:
return 0
return len(_calls)
def find_idw_neighbors(self, dst_point):
indx, lst = self.idw_obj.find_nearest_k(dst_point, self.nearest_k * 4)
# there may be bugs.
if Interp.check_all_masks(self, indx[0:self.nearest_k], self.nearest_k):
indx = []
lst = []
else:
indx, lst = self.select_k(indx, lst, self.nearest_k)
return indx, lst
class many(object):
def __init__(self, interp, rule):
rule.success = [self._store, setRule(node=rule)]
self.interp = Interp(rule)
self.gathered = []
@property
def need(self):
return self.interp.current.need
def receive(self, data, previous):
try:
self.interp.receive(data)
except ParseError:
return self.interp._ix, self.gathered
return None, None
def _store(self, interp, rv):
self.gathered.append(rv)
class many(object):
def __init__(self, interp, rule):
rule.success = [self._store, setRule(node=rule)]
self.interp = Interp(rule)
self.gathered = []
@property
def need(self):
return self.interp.current.need
def receive(self, data, previous):
try:
self.interp.receive(data)
except ParseError:
return self.interp._ix, self.gathered
return None, None
def _store(self, interp, rv):
self.gathered.append(rv)
def remap_entry(src_file, dst_file, alg_name, real_data_file, offline_flag, pole_flag, rank, size, comm, neighbor_num = 4):
name = str(alg_name)
name = name[name.index('.') + 1 : name.index('>') - 1]
if offline_flag:
if name == 'Idw':
test_obj = alg_name(src_file, dst_file, False, real_data_file, neighbor_num, pole_flag)
else:
test_obj = alg_name(src_file, dst_file, False, real_data_file, pole_flag)
else:
if name == 'Idw':
test_obj = alg_name(src_file, dst_file, False, real_data_file, neighbor_num, pole_flag)
else:
test_obj = alg_name(src_file, dst_file, True, real_data_file, pole_flag)
test_obj.dst_distribute(rank, size)
test_obj.interp()
test_obj.dst_merge(rank, comm)
if rank == 0:
Interp.compact_remap_matrix(test_obj)
if offline_flag:
test_obj.gen_remap_matrix_file()
else:
#test_obj.gen_remap_matrix_file()
remap_result = test_obj.remap()
print remap_result
def remap(self): remap_result = Interp.remap(self) return remap_result
def interp(self):
#print self.dst_grid_center_lon[0]
#print self.dst_grid_center_lat[0]
#point = (self.dst_grid_center_lon[0], self.dst_grid_center_lat[0])
#point = (0.0, 0.0)
n = len(self.dst_grid_center_lon)
for i in xrange(n):
# ignore masked pnt
if self.dst_grid_imask[i] == 0:
print 'My mask is zero!'
self.remap_matrix.append([])
self.remap_matrix_indx.append([])
continue
# debug recovery function
#dst_point = (357.625, -82.375)
dst_point = (self.dst_grid_center_lon[i],
self.dst_grid_center_lat[i])
indx, lst = self.bilinearbox_obj.find_nearest_k(dst_point, 4)
# suppose atom grid has no mask
# case ocn2atm, a atm cell with a land cell below
if Interp.check_all_masks(self, indx, 4):
print 'It must be a land cell.'
self.remap_matrix.append([])
self.remap_matrix_indx.append([])
continue
# decide if dst pnt is coincide with a src pnt
local_wgt = []
if dst_point in lst:
print 'coincide'
for item in lst:
if item == dst_point:
local_wgt.append(1.0)
else:
local_wgt.append(0.0)
Interp.check_wgt(self, local_wgt)
Interp.check_wgtsum(self, local_wgt)
# set remap_matrix and remap_matrix_indx objs
self.remap_matrix.append(local_wgt)
indx = Interp.indx_recovery(self, indx)
self.remap_matrix_indx.append(indx)
continue
# find a bilinear box
outside_flag, full_flag, bilinear_box_indx, bilinear_box = self.bilinearbox_obj.find_nearest_box(
dst_point)
# can not find 4 cells with no masks
# use idw algorithm instead
if not full_flag:
bilinear_solver = Idw_Solver(dst_point, bilinear_box, 1.0e-6,
1)
bilinear_solver.solve()
bilinear_box_indx = Interp.indx_recovery(
self, bilinear_box_indx)
Interp.check_wgt(self, bilinear_solver.wgt_lst)
Interp.check_wgtsum(self, bilinear_solver.wgt_lst)
self.remap_matrix.append(bilinear_solver.wgt_lst)
self.remap_matrix_indx.append(bilinear_box_indx)
continue
predict_flag = False
# if can not be contained or bounding rect is a triangle
# deciding a triangle by checking if three of them is collinearion
if outside_flag or self.check_triangle(bilinear_box):
predict_flag = True
print 'predictor case.'
#bilinear_solver = Bilinear_Predictor(dst_point, bilinear_box)
#bilinear_solver.predict()
bilinear_solver = Idw_Solver(dst_point, bilinear_box, 1.0e-6,
1)
bilinear_solver.solve()
# print debug info in detail
if outside_flag:
print 'outside'
if not is_convex_quadrangle(bilinear_box):
print 'it is a non-convex quadrangle, so it must be outside.'
else:
print 'trully meaning extrapolation.'
else:
print 'it is a bounding triangle box.'
else:
print dst_point
print bilinear_box
print 'normal case'
bilinear_solver = Bilinear_Solver(dst_point, bilinear_box)
branch = self.switch(bilinear_box)
if branch == 1:
bilinear_solver.solve_bilinear_case1()
if branch == 2:
bilinear_solver.solve_bilinear_case2()
if branch == 3:
bilinear_solver.solve_bilinear_case3()
# transferm ghost bilinear_box_indx to original
bilinear_box_indx = Interp.indx_recovery(self, bilinear_box_indx)
print dst_point
print bilinear_box
print bilinear_box_indx
print bilinear_solver.wgt_lst
print ''
# store result into objs
#self.interp_wgt = bilinear_solver.wgt_lst
#self.interp_box_indx = bilinear_box_indx
#self.interp_box = bilinear_box
if not predict_flag:
Interp.check_wgt(self, bilinear_solver.wgt_lst)
Interp.check_wgtsum(self, bilinear_solver.wgt_lst)
# set remap_matrix and remap_matrix_indx objs
self.remap_matrix.append(bilinear_solver.wgt_lst)
self.remap_matrix_indx.append(bilinear_box_indx)
print 'remap_matrix size is:'
print len(self.remap_matrix)
# compact remap matrix, gen remap_src_indx and remap_dst_indx
print 'Compacting remap matrix...'
Interp.compact_remap_matrix(self)
print 'Compacting finished!'
def __init__(self, src_grid_file_name, dst_grid_file_name, online_flag,
realdata_file_name):
Interp.__init__(self, src_grid_file_name, dst_grid_file_name,
online_flag, realdata_file_name)
self.bilinearbox_obj = Bilinearbox(self.stree_base_obj, self.stree)
def remap(self):
remap_result = Interp.remap(self)
return remap_result
#test_obj = Bilinear('../../../grid/T42_Gaussian_POP43/T42_Gaussian.nc', '../../../grid/More/ne30np4-t2.nc', False, '../../../data/real/T42_Gaussian_Grid/T42_avXa2c_a_Faxa_lwdn-0007-08.nc', False)
#test_obj = Bilinear('../../../grid/T42_Gaussian_POP43/T42_Gaussian.nc', '../../../grid/More/Ocean_1v1_triplepole.nc', False, '../../../data/real/T42_Gaussian_Grid/T42_avXa2c_a_Faxa_lwdn-0007-08.nc', False)
>>>>>>> independent
#test_obj = Bilinear('../../../grid/More/Ocean_1v1_triplepole.nc', '../../../grid/T42_Gaussian_POP43/T42_Gaussian.nc', False, '../../../data/real/T42_Gaussian_Grid/T42_avXa2c_a_Faxa_lwdn-0007-08.nc', False)
#test_obj = Bilinear('../../../grid/T42_Gaussian_POP43/T42_Gaussian.nc', '../../../grid/More/Ocean_1v1_triplepole.nc', False, '../../../data/real/T42_Gaussian_Grid/T42_avXa2c_a_Faxa_lwdn-0007-08.nc', False)
#test_obj = Bilinear('../../../grid/More/atmos_fv_0.9v1.25_for_SCRIP.nc', '../../../grid/T42_Gaussian_POP43/POP43.nc', False, '../../../data/real/T42_Gaussian_Grid/T42_avXa2c_a_Faxa_lwdn-0007-08.nc', False)
test_obj = Bilinear('../../../grid/realdataT42_masked.nc', '../../../grid/realdataPOP43.nc', False, '../../../data/real/T42_Gaussian_Grid/T42_avXa2c_a_Faxa_lwdn-0007-08.nc', False)
#test_obj = Bilinear('../../../grid/T42_Gaussian.nc', '../../../grid/Gamil_128x60_Grid.nc', False, '../../../data/real/T42_Gaussian_Grid/T42_avXa2c_a_Faxa_lwdn-0006-12.nc', False)
#test_obj = Bilinear('../../../grid/T42_Gaussian_POP43/POP43.nc', '../../../grid/T42_Gaussian_POP43/T42_Gaussian.nc')
print test_obj.dst_grid_size
print test_obj.dst_grid_dims
print test_obj.dst_grid_corners
print test_obj.dst_grid_rank
print len(test_obj.dst_grid_center_lat)
# for mpi use
test_obj.dst_distribute(rank, size)
test_obj.interp()
# for mpi use
test_obj.dst_merge(rank, comm)
if rank == 0:
# compact remap matrix, gen remap_src_indx and remap_dst_indx
print 'Compacting remap matrix...'
Interp.compact_remap_matrix(test_obj)
print 'Compacting finished!'
test_obj.gen_remap_matrix_file()
start = time.time()
remap_result = test_obj.remap()
end = time.time()
print end - start
print remap_result
def create_interp():
return Interp()
def __init__(self, interp, rule):
rule.success = [self._store, setRule(node=rule)]
self.interp = Interp(rule)
self.gathered = []
def interp(self):
n = len(self.dst_grid_center_lon)
# traverse dst pnt
for i in xrange(n):
# ignore masked pnt
if self.dst_grid_imask[i] == 0:
print 'My mask is zero!'
self.remap_matrix.append([])
self.remap_matrix_indx.append([])
continue
dst_point = (self.dst_grid_center_lon[i], self.dst_grid_center_lat[i])
neighbor_indx, neighbor_lst = self.find_idw_neighbors(dst_point)
# suppose atm grid has no mask
# case ocn2atm, a atm cell with a land cell below
if not neighbor_indx:
print 'It must be a land cell.'
self.remap_matrix.append([])
self.remap_matrix_indx.append([])
continue
# better wish, but disappointed
# tackle pole region
if self.pole_flag:
if dst_point[1] > self.pole_north_bnd:
print 'Tackling pole region'
idw_solver = Pole_Solver(dst_point, self.pole_north, self.nearest_k)
idw_solver.solve()
idw_box_indx = self.pole_north_indx[0:self.nearest_k]
idw_box_indx = Interp.indx_recovery(self, idw_box_indx)
self.remap_matrix.append(idw_solver.wgt_lst)
self.remap_matrix_indx.append(idw_box_indx)
continue
if dst_point[1] < self.pole_south_bnd:
print 'Tackling pole region'
idw_solver = Pole_Solver(dst_point, self.pole_south, self.nearest_k)
idw_solver.solve()
idw_box_indx = self.pole_south_indx[0:self.nearest_k]
idw_box_indx = Interp.indx_recovery(self, idw_box_indx)
self.remap_matrix.append(idw_solver.wgt_lst)
self.remap_matrix_indx.append(idw_box_indx)
continue
# normal case, init idw_solver
idw_solver = Idw_Solver(dst_point, neighbor_lst, self.eps, self.power)
# decide if dst pnt is coincide with a src pnt
if dst_point in neighbor_lst:
print 'coincide'
for item in neighbor_lst:
if item == dst_point:
idw_solver.wgt_lst.append(1.0)
else:
idw_solver.wgt_lst.append(0.0)
else:
# solve normal case
idw_solver.solve()
print neighbor_indx
# transform ghost indx to original
neighbor_indx = Interp.indx_recovery(self, neighbor_indx)
print neighbor_indx
print ''
print dst_point
print neighbor_lst
print neighbor_indx
print idw_solver.wgt_lst
# store result into objs
#self.interp_wgt = idw_solver.wgt_lst
#self.interp_box_indx = neighbor_indx
#self.interp_box = neighbor_lst
# set remap_matrix and remap_matrix_indx objs
self.remap_matrix.append(idw_solver.wgt_lst)
self.remap_matrix_indx.append(neighbor_indx)
if len(idw_solver.wgt_lst) != len(neighbor_indx):
print idw_solver.wgt_lst
print neighbor_indx
print 'ERRORRRR'
sys.exit()
print 'remap_matrix size is:'
print len(self.remap_matrix)
def __init__(self, interp, rule):
rule.success = [self._store, setRule(node=rule)]
self.interp = Interp(rule)
self.gathered = []
def __init__(self, src_grid_file_name, dst_grid_file_name, online_flag, realdata_file_name): Interp.__init__(self, src_grid_file_name, dst_grid_file_name, online_flag, realdata_file_name) self.bilinearbox_obj = Bilinearbox(self.stree_base_obj, self.stree)
def interp(self):
#print self.dst_grid_center_lon[0]
#print self.dst_grid_center_lat[0]
#point = (self.dst_grid_center_lon[0], self.dst_grid_center_lat[0])
#point = (0.0, 0.0)
n = len(self.dst_grid_center_lon)
for i in xrange(n):
# ignore masked pnt
if self.dst_grid_imask[i] == 0:
print 'My mask is zero!'
self.remap_matrix.append([])
self.remap_matrix_indx.append([])
continue
# debug recovery function
#dst_point = (357.625, -82.375)
dst_point = (self.dst_grid_center_lon[i], self.dst_grid_center_lat[i])
indx, lst = self.bilinearbox_obj.find_nearest_k(dst_point, 4)
# suppose atom grid has no mask
# case ocn2atm, a atm cell with a land cell below
if Interp.check_all_masks(self, indx, 4):
print 'It must be a land cell.'
self.remap_matrix.append([])
self.remap_matrix_indx.append([])
continue
# decide if dst pnt is coincide with a src pnt
local_wgt = []
if dst_point in lst:
print 'coincide'
for item in lst:
if item == dst_point:
local_wgt.append(1.0)
else:
local_wgt.append(0.0)
Interp.check_wgt(self, local_wgt)
Interp.check_wgtsum(self, local_wgt)
# set remap_matrix and remap_matrix_indx objs
self.remap_matrix.append(local_wgt)
indx = Interp.indx_recovery(self, indx)
self.remap_matrix_indx.append(indx)
continue
# find a bilinear box
outside_flag, full_flag, bilinear_box_indx, bilinear_box = self.bilinearbox_obj.find_nearest_box(dst_point)
# can not find 4 cells with no masks
# use idw algorithm instead
if not full_flag:
bilinear_solver = Idw_Solver(dst_point, bilinear_box, 1.0e-6, 1)
bilinear_solver.solve()
bilinear_box_indx = Interp.indx_recovery(self, bilinear_box_indx)
Interp.check_wgt(self, bilinear_solver.wgt_lst)
Interp.check_wgtsum(self, bilinear_solver.wgt_lst)
self.remap_matrix.append(bilinear_solver.wgt_lst)
self.remap_matrix_indx.append(bilinear_box_indx)
continue
predict_flag = False
# if can not be contained or bounding rect is a triangle
# deciding a triangle by checking if three of them is collinearion
if outside_flag or self.check_triangle(bilinear_box):
predict_flag = True
print 'predictor case.'
#bilinear_solver = Bilinear_Predictor(dst_point, bilinear_box)
#bilinear_solver.predict()
bilinear_solver = Idw_Solver(dst_point, bilinear_box, 1.0e-6, 1)
bilinear_solver.solve()
# print debug info in detail
if outside_flag:
print 'outside'
if not is_convex_quadrangle(bilinear_box):
print 'it is a non-convex quadrangle, so it must be outside.'
else:
print 'trully meaning extrapolation.'
else:
print 'it is a bounding triangle box.'
else:
print dst_point
print bilinear_box
print 'normal case'
bilinear_solver = Bilinear_Solver(dst_point, bilinear_box)
branch = self.switch(bilinear_box)
if branch == 1:
bilinear_solver.solve_bilinear_case1()
if branch == 2:
bilinear_solver.solve_bilinear_case2()
if branch == 3:
bilinear_solver.solve_bilinear_case3()
# transferm ghost bilinear_box_indx to original
bilinear_box_indx = Interp.indx_recovery(self, bilinear_box_indx)
print dst_point
print bilinear_box
print bilinear_box_indx
print bilinear_solver.wgt_lst
print ''
# store result into objs
#self.interp_wgt = bilinear_solver.wgt_lst
#self.interp_box_indx = bilinear_box_indx
#self.interp_box = bilinear_box
if not predict_flag:
Interp.check_wgt(self, bilinear_solver.wgt_lst)
Interp.check_wgtsum(self, bilinear_solver.wgt_lst)
# set remap_matrix and remap_matrix_indx objs
self.remap_matrix.append(bilinear_solver.wgt_lst)
self.remap_matrix_indx.append(bilinear_box_indx)
print 'remap_matrix size is:'
print len(self.remap_matrix)
# compact remap matrix, gen remap_src_indx and remap_dst_indx
print 'Compacting remap matrix...'
Interp.compact_remap_matrix(self)
print 'Compacting finished!'
def create_interp(self):
return Interp()