values[i] = num_replications2[subset][j]
i = i+1
repl_counts.append(num_replications2[subset][j])
for l in range(num_replications2[subset][j]):
# fill dummy var
values[i] = 45678.
i = i+1
# debug
print('values[:10]: ', values[:10].tolist()) #numpy.where(values != 0)]))
print('values[-10:]: ', values[-10:].tolist()) #numpy.where(values != 0)]))
# do the encoding to binary format
bufr.kdata = numpy.array(repl_counts)
print('bufr.kdata = ', bufr.kdata.tolist())
bufr.encode_data(values, cvals)
# get an instance of the RawBUFRFile class
bf1 = RawBUFRFile()
output_bufr_file = 'dummy_bufr_file.bfr'
# open the file for writing
bf1.open(output_bufr_file, 'wb')
# write the encoded BUFR message
bf1.write_raw_bufr_msg(bufr.encoded_message)
# close the file
bf1.close()
##############################
def create_bufr_file(output_bufr_file, template):
# #[ create bufr file
'''
and use this BUFR template to create a test BUFR message
'''
from pybufr_ecmwf.bufr_interface_ecmwf import BUFRInterfaceECMWF
bufr = BUFRInterfaceECMWF(verbose=True)
# fill sections 0, 1, 2 and 3
num_subsets = 2
bufr.fill_sections_0123(bufr_code_centre=98, # ECMWF
bufr_obstype=3, # sounding
bufr_subtype=253, # L2B
bufr_table_local_version=1,
bufr_table_master=0,
bufr_table_master_version=15,
bufr_code_subcentre=0, # L2B processing facility
num_subsets=num_subsets,
bufr_compression_flag=0)
# 64=compression/0=no compression
# determine information from sections 0123 to construct the BUFR table
# names expected by the ECMWF BUFR library and create symlinks to the
# default tables if needed
bufr.setup_tables(table_b_to_use='B'+TABLE_NAME,
table_d_to_use='D'+TABLE_NAME)
bufr.register_and_expand_descriptors(template)
# activate this one if the encoding crashes without clear cause:
# bufr.estimated_num_bytes_for_encoding = 25000
# retrieve the length of the expanded descriptor list
exp_descr_list_length = bufr.ktdexl
print "exp_descr_list_length = ", exp_descr_list_length
# fill the values array with some dummy varying data
num_values = num_subsets*bufr.max_nr_expanded_descriptors
values = numpy.zeros(num_values, dtype=numpy.float64) # this is the default
# note: these two must be identical for now, otherwise the
# python to fortran interface breaks down. This also ofcourse is the
# cause of the huge memory use of cvals in case num_values is large.
num_cvalues = num_values
cvals = numpy.zeros((num_cvalues, 80), dtype=numpy.character)
cvals_index = 0
repl_counts = []
for subset in range(num_subsets):
# note that python starts counting with 0, unlike fortran,
# so there is no need to take (subset-1)
print 'subset,exp_descr_list_length = ', subset, exp_descr_list_length
i = subset*exp_descr_list_length
# fill the message with some dummy data
# fill year, month, day
for val in [2014, 3, 19]: # fill the header
values[i] = val+subset
i += 1
# fill prod_name
txt = 'filename{}.txt'.format(subset)
cvals[cvals_index, :] = ' '
for icval, cval in enumerate(txt):
cvals[cvals_index, icval] = cval
# values[i] = cvals_index * 1000 + 64 # len(txt)
values[i] = (cvals_index+1) * 1000 + len(txt)
i += 1
cvals_index = cvals_index + 1
for val in [5.1+0.1*subset, 55.2-0.01*subset, 23., 45., 73., 82.]:
bufr.verify_in_range(i, val)
values[i] = val
i += 1
if USE_DELAYED_REPLICATION:
# set actual delayed replication repeats
num_repl = 3 + 2*subset
print 'num_repl = ', num_repl
values[i] = num_repl
i += 1
repl_counts.append(num_repl)
# fill the replicated variable
for irepl in range(num_repl):
val = 12.+subset*0.1 + irepl*0.01
bufr.verify_in_range(i, val)
values[i] = val
i += 1
# do the encoding to binary format
bufr.kdata = numpy.array(repl_counts)
print 'bufr.kdata = ', bufr.kdata
bufr.encode_data(values, cvals)
print 'DEBUG: values = ', values
from pybufr_ecmwf.raw_bufr_file import RawBUFRFile
# get an instance of the RawBUFRFile class
bf1 = RawBUFRFile()
# open the file for writing
bf1.open(output_bufr_file, 'wb')
# write the encoded BUFR message
bf1.write_raw_bufr_msg(bufr.encoded_message)
# close the file
bf1.close()
# set actual delayed replication number
values[i] = num_replications2[subset][j]
i = i + 1
repl_counts.append(num_replications2[subset][j])
for l in range(num_replications2[subset][j]):
# fill dummy var
values[i] = 45678.
i = i + 1
# debug
print('values: ', list(values)) #numpy.where(values != 0)]))
# do the encoding to binary format
bufr.kdata = numpy.array(repl_counts)
print('bufr.kdata = ', bufr.kdata)
bufr.encode_data(values, cvals)
# get an instance of the RawBUFRFile class
bf1 = RawBUFRFile()
output_bufr_file = 'dummy_bufr_file.bfr'
# open the file for writing
bf1.open(output_bufr_file, 'wb')
# write the encoded BUFR message
bf1.write_raw_bufr_msg(bufr.encoded_message)
# close the file
bf1.close()
##############################
def create_bufr_file(output_bufr_file, template):
# #[ create bufr file
'''
and use this BUFR template to create a test BUFR message
'''
from pybufr_ecmwf.bufr_interface_ecmwf import BUFRInterfaceECMWF
bufr = BUFRInterfaceECMWF(verbose=True)
# fill sections 0, 1, 2 and 3
num_subsets = 2
bufr.fill_sections_0123(bufr_code_centre=98, # ECMWF
bufr_obstype=3, # sounding
bufr_subtype=253, # L2B
bufr_table_local_version=1,
bufr_table_master=0,
bufr_table_master_version=15,
bufr_code_subcentre=0, # L2B processing facility
num_subsets=num_subsets,
bufr_compression_flag=0)
# 64=compression/0=no compression
# determine information from sections 0123 to construct the BUFR table
# names expected by the ECMWF BUFR library and create symlinks to the
# default tables if needed
bufr.setup_tables(table_b_to_use='B'+TABLE_NAME,
table_d_to_use='D'+TABLE_NAME)
bufr.register_and_expand_descriptors(template)
# activate this one if the encoding crashes without clear cause:
# bufr.estimated_num_bytes_for_encoding = 25000
# retrieve the length of the expanded descriptor list
exp_descr_list_length = bufr.ktdexl
print "exp_descr_list_length = ", exp_descr_list_length
# fill the values array with some dummy varying data
num_values = num_subsets*bufr.max_nr_expanded_descriptors
values = numpy.zeros(num_values, dtype=numpy.float64) # this is the default
# note: these two must be identical for now, otherwise the
# python to fortran interface breaks down. This also ofcourse is the
# cause of the huge memory use of cvals in case num_values is large.
num_cvalues = num_values
cvals = numpy.zeros((num_cvalues, 80), dtype=numpy.character)
cvals_index = 0
repl_counts = []
for subset in range(num_subsets):
# note that python starts counting with 0, unlike fortran,
# so there is no need to take (subset-1)
print 'subset,exp_descr_list_length = ', subset, exp_descr_list_length
i = subset*exp_descr_list_length
# fill the message with some dummy data
# fill year, month, day
for val in [2014, 3, 19]: # fill the header
values[i] = val+subset
i += 1
# fill prod_name
# this is not python2.6 compatible
#txt = 'filename{}.txt'.format(subset)
txt = 'filename'+str(subset)+'.txt'
cvals[cvals_index, :] = ' '
for icval, cval in enumerate(txt):
cvals[cvals_index, icval] = cval
# values[i] = cvals_index * 1000 + 64 # len(txt)
values[i] = (cvals_index+1) * 1000 + len(txt)
i += 1
cvals_index = cvals_index + 1
for val in [5.1+0.1*subset, 55.2-0.01*subset, 23., 45., 73., 82.]:
bufr.verify_in_range(i, val)
values[i] = val
i += 1
if USE_DELAYED_REPLICATION:
# set actual delayed replication repeats
num_repl = 3 + 2*subset
print 'num_repl = ', num_repl
values[i] = num_repl
i += 1
repl_counts.append(num_repl)
# fill the replicated variable
for irepl in range(num_repl):
val = 12.+subset*0.1 + irepl*0.01
bufr.verify_in_range(i, val)
values[i] = val
i += 1
# do the encoding to binary format
bufr.kdata = numpy.array(repl_counts)
print 'bufr.kdata = ', bufr.kdata
bufr.encode_data(values, cvals)
print 'DEBUG: values = ', values
from pybufr_ecmwf.raw_bufr_file import RawBUFRFile
# get an instance of the RawBUFRFile class
bf1 = RawBUFRFile()
# open the file for writing
bf1.open(output_bufr_file, 'wb')
# write the encoded BUFR message
bf1.write_raw_bufr_msg(bufr.encoded_message)
# close the file
bf1.close()