def tag_geoloc_component(geoloc_str):
"""Tag a geocode locality input component string and make a list.
USAGE:
[word_list, tag_list] = tag_geoloc_component(loc_str)
ARGUMENTS:
geoloc_str A string containing the geocode and/or locality components
DESCRIPTION:
This routines cleans the input string and extracts words, numbers and
separators into a list. Each element of this list is assigned one or more
tags. A 'greedy tagger' is applied, which cheques sequences of list
elements in the name lookup table (longer sequences first) and replaces
them with the string and tag from the lookup-table if found.
The routine returns two lists: words and their tags
"""
# First, split input string into elements at spaces - - - - - - - - - - - - -
#
org_list = geoloc_str.split() # The original list from the input string
inout.log_message(" Initial word list: " + str(org_list), "v2")
tag_list = [] # The initially empty list of tags
word_list = [] # The initially empty list of words
while org_list != []: # As long as not all elements have been processed
tmp_list = org_list[: config.geoloc_dict_seq_len] # Extract longest sub-list
tmp_val = [] # Start with empty value
tmp_key = tuple(tmp_list)
while tmp_key != (): # As long as key not empty and not found in lookup
if config.geoloc_lookup_dict.has_key(tmp_key):
tmp_val = config.geoloc_lookup_dict[tmp_key]
break
tmp_key = tmp_key[:-1] # Remove last element in key
if tmp_val != []: # A value has been found in the dictionary
tmp_len = len(tmp_key) # Length of found sequence
if tmp_val[0] != "": # it's not an empty value
word_list.append(tmp_val[0]) # Append corrected word (or sequence)
tag_list.append(tmp_val[1]) # Append tag or tags
else: # No value has been found in the lookup dictionary, try other tags
tmp_val = org_list[0] # Value is first element in the original list
tmp_len = 1
if tmp_val.isdigit(): # Element is a number
word_list.append(tmp_val)
if len(tmp_val) == 4:
tag_list.append("N4")
else:
tag_list.append("NU")
elif (not tmp_val.isalpha()) and tmp_val.isalnum(): # Alpha-numeric
word_list.append(tmp_val)
tag_list.append("AN")
elif tmp_val == "-": # Element is a hyphen
word_list.append(tmp_val)
tag_list.append("HY")
elif tmp_val == ",": # Element is a comma
word_list.append(tmp_val)
tag_list.append("CO")
elif tmp_val == "|": # Element is a vertical bar
word_list.append(tmp_val)
tag_list.append("VB")
else: # An unknown element
word_list.append(tmp_val)
tag_list.append("UN")
# Finally remove the processed elements from the original element list
#
org_list = org_list[tmp_len:] # Remove processed elements
return [word_list, tag_list]
# Check if definition of input components is correct with file types
#
input_values = input_component.values()
input_len = -1 # Length of the input (either in number of fields (CSV and TAB
# files) or in characters (COL files)
output_keys = output_field.keys() # Check if 'original_input' is in output
# fields, and if so check for correctness
for k in output_keys:
if (k[:14] == 'original_input'):
v = k[14:].strip()
if (v != ''): # There is a field or column range given
if (v[0] == '[') and (v[-1] == ']'):
v = v[1:-1] # Remove brackets
else:
inout.log_message('Wrong input component definition: '+str(k) + \
' for "original_input" output field','err')
raise Exception()
if (v[0] == '(') and (v[-1] == ')'): # It's a tuple
v = v[1:-1] # Remove tuple brackets
v = v.split(',') # Make a list
for i in range(len(v)):
v[i] = int(v[i]) # Make integers
if (len(v) == 1): # One integer only, must be a field number
input_values.append(v) # Append 'original_input' field number
elif (len(v) == 2): # Two integers, must be a column range
input_values.append([(v[0],v[1])]) # Append as a tuple
else:
inout.log_message('Wrong input component value: '+str(k) + \
' for "original_input" output field','err')
raise Exception()
def get_geoloc_hmm(word_list, tag_list):
"""Process input using a HMM to extract geocode and locality output fields.
USAGE:
geoloc_dict = get_geoloc_hmm(word_list, tag_list)
ARGUMENTS:
word_list List of words as produces with clean_tag_locality()
tag_list Corresponding list of tags as produces with
clean_tag_locality()
DESCRIPTION:
The routine returns a dictionary with the parsed and extracted output
fields for both the locality and geocode components. A Hidden Markov Model
(HMM) is used for this task.
The dictionary returned can contain the following key words:
- wayfare_number
- wayfare_name
- wayfare_qualifier
- wayfare_type
- unit_number
- unit_type
- property_name
- institution_name
- institution_type
- postaddress_number
- postaddress_type
- locality_name
- locality_qualifier
- postcode
- territory
- country
- geoloc_hmm_proba (the probability returned by the Viterbi algorithm for
the most likely HMM state seqence)
"""
# First, create all permutations of the input tag sequence
#
tag_list_seq = mymath.perm_tag_sequence(tag_list)
msg = [" Input tag sequence: " + str(tag_list), " Output tag sequences:"]
for t in tag_list_seq:
msg.append(" " + str(t))
inout.log_message(msg, "v2")
# Now give all tag sequences to the HMM - - - - - - - - - - - - - - - - - - -
# and keep the one with highest probability
#
max_prob = -1.0
best_obs_seq = []
best_tag_list = []
for t in tag_list_seq:
[obs_seq, prob] = config.geoloc_hmm.viterbi(t)
if prob > max_prob:
best_obs_seq = obs_seq
best_tag_list = t
max_prob = prob
inout.log_message(" Probability " + str(prob) + " for sequence " + str(t), "v2")
inout.log_message(
[" Best observation sequence: " + str(best_obs_seq), " with tag sequence: " + str(best_tag_list)],
"v2",
)
# Now process the observation sequence and add elements into dictionary - - -
#
tag_list_len = len(tag_list)
norm_max_prob = max_prob / float(tag_list_len) # Normalise max. probability
geoloc_dict = {"geoloc_hmm_proba": [str(norm_max_prob)]}
list_len = len(word_list)
for i in range(list_len): # Loop over words and states
w = word_list[i]
s = best_obs_seq[i]
# Do not output commas, vertical bars and hyphens - - - - - - - - - - - -
#
if w in ["|", ",", "-", "/"]:
pass
elif s == "wfnu": # Wayfare number - - - - - - - - - - - - - - - - - - -
v = geoloc_dict.get("wayfare_number", [])
v.append(w)
geoloc_dict.update({"wayfare_number": v})
elif s in ["wfna1", "wfna2", "wfna3"]: # Wayfare name - - - - - - - - - -
v = geoloc_dict.get("wayfare_name", [])
v.append(w)
geoloc_dict.update({"wayfare_name": v})
elif s == "wfql": # Wayfare qualifier - - - - - - - - - - - - - - - - -
v = geoloc_dict.get("wayfare_qualifier", [])
v.append(w)
geoloc_dict.update({"wayfare_qualifier": v})
elif s == "wfty": # Wayfare type - - - - - - - - - - - - - - - - - - - -
v = geoloc_dict.get("wayfare_type", [])
v.append(w)
geoloc_dict.update({"wayfare_type": v})
elif s == "unnu": # Unit number - - - - - - - - - - - - - - - - - - - -
v = geoloc_dict.get("unit_number", [])
v.append(w)
geoloc_dict.update({"unit_number": v})
elif s == "unty": # Unit type - - - - - - - - - - - - - - - - - - - - -
v = geoloc_dict.get("unit_type", [])
v.append(w)
geoloc_dict.update({"unit_type": v})
elif s in ["prna1", "prna2"]: # Property name - - - - - - - - - - - - - -
v = geoloc_dict.get("property_name", [])
v.append(w)
geoloc_dict.update({"property_name": v})
elif s in ["inna1", "inna2"]: # Institution name - - - - - - - - - - - -
v = geoloc_dict.get("institution_name", [])
v.append(w)
geoloc_dict.update({"institution_name": v})
elif s == "inty": # Institution type - - - - - - - - - - - - - - - - - -
v = geoloc_dict.get("institution_type", [])
v.append(w)
geoloc_dict.update({"institution_type": v})
elif s == "panu": # Postal address number - - - - - - - - - - - - - - -
v = geoloc_dict.get("postaddress_number", [])
v.append(w)
geoloc_dict.update({"postaddress_number": v})
elif s == "paty": # Postal address type - - - - - - - - - - - - - - - -
v = geoloc_dict.get("postaddress_type", [])
v.append(w)
geoloc_dict.update({"postaddress_type": v})
elif s in ["loc1", "loc2"]: # Locality name - - - - - - - - - - - - - - -
v = geoloc_dict.get("locality_name", [])
v.append(w)
geoloc_dict.update({"locality_name": v})
elif s == "locql": # Locality qualifier - - - - - - - - - - - - - - - -
v = geoloc_dict.get("locality_qualifier", [])
v.append(w)
geoloc_dict.update({"locality_qualifier": v})
elif s == "pc": # Postcode - - - - - - - - - - - - - - - - - - - - - - -
v = geoloc_dict.get("postcode", [])
v.append(w)
geoloc_dict.update({"postcode": v})
elif s in ["ter1", "ter2"]: # Territory - - - - - - - - - - - - - - - - -
v = geoloc_dict.get("territory", [])
v.append(w)
geoloc_dict.update({"territory": v})
elif s in ["cntr1", "cntr2"]: # Country - - - - - - - - - - - - - - - - -
v = geoloc_dict.get("country", [])
v.append(w)
geoloc_dict.update({"country": v})
else: # Should never happen
msg = [
"This should never happen!",
" Tag: " + str(s),
" Word: " + w,
" Word list: " + str(word_list),
" tag list: " + str(tag_list),
]
inout.log_message(msg, "warn")
# Check if concatenated locality and territory words are in lookup-table - -
#
if geoloc_dict.has_key("locality_name"):
loc = geoloc_dict["locality_name"]
if len(loc) > 1: # Locality contains more than one word
loc_tuple = tuple(loc) # Make it a tuple
if config.geoloc_lookup_dict.has_key(loc_tuple):
new_loc = config.geoloc_lookup_dict[loc_tuple][0]
geoloc_dict.update({"locality_name": [new_loc]})
if geoloc_dict.has_key("territory"):
terr = geoloc_dict["territory"]
if len(terr) > 1: # Territory contains more than one word
terr_tuple = tuple(terr) # Make it a tuple
if config.geoloc_lookup_dict.has_key(terr_tuple):
new_terr = config.geoloc_lookup_dict[terr_tuple][0]
geoloc_dict.update({"territory": [new_terr]})
if geoloc_dict.has_key("country"):
cntr = geoloc_dict["country"]
if len(cntr) > 1: # Country contains more than one word
cntr_tuple = tuple(cntr) # Make it a tuple
if config.geoloc_lookup_dict.has_key(cntr_tuple):
new_cntr = config.geoloc_lookup_dict[cntr_tuple][0]
geoloc_dict.update({"country": [new_cntr]})
# Finally do some tests on the output fields - - - - - - - - - - - - - - - -
#
geoloc_items = geoloc_dict.items()
# Check if a value list has more than three elements, if so print out
#
for i in geoloc_items:
if len(i[1]) > 3:
inout.log_message(
"Geocode/locality output field " + str(i[0]) + " contains more than three elements: " + str(i[1]),
"warn",
)
# Check if 'number' elements only contain (alpha-) numerical values - - - - -
# and also check how many numbers in an element
#
if geoloc_dict.has_key("wayfare_number"): # Check how many wayfare numbers
v = geoloc_dict["wayfare_number"]
if len(v) > 2:
inout.log_message("More than two wayfare numbers: " + str(v), "warn")
for i in v:
if i.isalpha(): # Element contains only letters
inout.log_message("Wayfare number element contains no digits: " + str(v), "warn")
break # Exit for loop
if geoloc_dict.has_key("unit_number"): # Check how many unit numbers
v = geoloc_dict["unit_number"]
if len(v) > 1:
inout.log_message("More than one unit numbers: " + str(v), "warn")
for i in v:
if i.isalpha(): # Element contains only letters
inout.log_message("Unit number element contains no digits: " + str(v), "warn")
break # Exit for loop
if geoloc_dict.has_key("postaddress_number"): # Check postaddress numbers
v = geoloc_dict["postaddress_number"]
if len(v) > 1:
inout.log_message("More than one postaddress numbers: " + str(v), "warn")
for i in v:
if i.isalpha(): # Element contains only letters
inout.log_message("Postaddress number element contains no digits: " + str(v), "warn")
break # Exit for loop
# Check if 'type' elements contain one word only - - - - - - - - - - - - - -
# if it's a known type word
#
if geoloc_dict.has_key("wayfare_type"): # Check wayfare type
v = geoloc_dict["wayfare_type"]
if len(v) > 1:
inout.log_message("More than one wayfare type: " + str(v), "warn")
for i in v:
i = i.split("_")
i = tuple(i) # Make it a tuple
if (not config.geoloc_lookup_dict.has_key((i))) or (
config.geoloc_lookup_dict.has_key((i)) and (config.geoloc_lookup_dict[(i)][1].find("WT") < 0)
):
inout.log_message("Wayfare type word is not known: " + str(v), "warn")
break # Exit for loop
if geoloc_dict.has_key("unit_type"): # Check unit type
v = geoloc_dict["unit_type"]
if len(v) > 1:
inout.log_message("More than one unit type: " + str(v), "warn")
for i in v:
i = i.split("_")
i = tuple(i) # Make it a tuple
if (not config.geoloc_lookup_dict.has_key((i))) or (
config.geoloc_lookup_dict.has_key((i)) and (config.geoloc_lookup_dict[(i)][1].find("UT") < 0)
):
inout.log_message("Unit type word is not known: " + str(v), "warn")
break # Exit for loop
if geoloc_dict.has_key("institution_type"): # Check institution type
v = geoloc_dict["institution_type"]
if len(v) > 1:
inout.log_message("More than one institution type: " + str(v), "warn")
for i in v:
i = i.split("_")
i = tuple(i) # Make it a tuple
if (not config.geoloc_lookup_dict.has_key((i))) or (
config.geoloc_lookup_dict.has_key((i)) and (config.geoloc_lookup_dict[(i)][1].find("IT") < 0)
):
inout.log_message("Institution type word is not known: " + str(v), "warn")
break # Exit for loop
if geoloc_dict.has_key("postaddress_type"): # Check postaddress type
v = geoloc_dict["postaddress_type"]
if len(v) > 2:
inout.log_message("More than two postaddress type: " + str(v), "warn")
for i in v:
i = i.split("_")
i = tuple(i) # Make it a tuple
if (not config.geoloc_lookup_dict.has_key((i))) or (
config.geoloc_lookup_dict.has_key((i)) and (config.geoloc_lookup_dict[(i)][1].find("PA") < 0)
):
inout.log_message("Postaddress type word is not known: " + str(v), "warn")
break # Exit for loop
# Check if 'qualifier' elements only contain known qualifier words - - - - -
#
if geoloc_dict.has_key("wayfare_qualifier"): # Check wayfare qualifier
v = geoloc_dict["wayfare_qualifier"]
for i in v:
if (not config.geoloc_lookup_dict.has_key((i,))) or (
config.geoloc_lookup_dict.has_key((i,)) and (config.geoloc_lookup_dict[(i,)][1].find("LQ") < 0)
):
inout.log_message("Wayfare qualifier word is not known: " + str(v), "warn")
break # Exit for loop
if geoloc_dict.has_key("locality_qualifier"): # Check locality qualifier
v = geoloc_dict["locality_qualifier"]
for i in v:
if (not config.geoloc_lookup_dict.has_key((i,))) or (
config.geoloc_lookup_dict.has_key((i,)) and (config.geoloc_lookup_dict[(i,)][1].find("LQ") < 0)
):
inout.log_message("Locality qualifier word is not known: " + str(v), "warn")
break # Exit for loop
return geoloc_dict
def trainhmm():
"""Main routine, open file, read lines, train HMM and save it to file.
USAGE:
trainhmm()
ARGUMENTS:
None
DESCRIPTION:
Main routine, see description of module above.
"""
# Process command line arguments and check for correctness - - - - - - - - -
#
if (len(config.options) < 3):
print '***** Error: %s needs at least four arguments:'% (sys.argv[0])
print '***** - Name of the project module'
print '***** - Tagging mode: "name" or "locality"'
print '***** - Input training file name'
print '***** - HMM output file name'
print '***** plus options'
raise Exception()
if (config.options[1] == config.options[2]):
print '*** Error: Input and output files must differ'
print '*** Input training file name:', config.options[1]
print '*** HMM output file name: ', config.options[1]
raise Exception()
in_file_name = config.options[1]
hmm_file_name = config.options[2]
# Get tagging mode/lookup-tables used - - - - - - - - - - - - - - - - - - - -
#
tag_mode = config.options[0]
if (tag_mode in ['name','na','n']):
tag_mode = 'name'
elif (tag_mode in ['locality','lolty','loc','l']):
tag_mode = 'loc'
else:
print '***** Error: Illegal tagging mode:', tag_mode
print '***** Must be either "name" or "locality"'
raise Exception()
# Check for optional arguments and process if any - - - - - - - - - - - - - -
#
config.verbose = 0 # Default: No verbose output
config.logging = 0 # Default: No logging into a file
smoothing = None # Default: No smoothing
config.nowarn = 0 # Deactivate no warning flag (print/log warning
# messages)
if (len(config.options) > 3):
options = config.options[3:]
while (options != []): # Do a loop processing all options
if (options[0] == '-nowarn'):
config.nowarn = 1 # Activate no warning flag
options = options[1:] # Remove processed '-nowarn' option
elif (options[0] == '-v1'):
config.verbose = 1 # Set to verbose output level 1
options = options[1:] # Remove processed '-v1' option
elif (options[0] == '-v2'):
config.verbose = 2 # Set to verbose output level 2
options = options[1:] # Remove processed '-v2' option
elif (options[0] == '-l'):
config.logging = 1
if (len(options) > 1):
if (options[1][0] != '-'): # Not another option, must be a file name
config.log_file = options[1] # Get name of log file
options = options[1:] # Remove file_name
options = options[1:] # Remove processed -'l' option only
try:
f_log = open(config.log_file,'a') # Test if file is appendable
except:
print '***** Error ********************',
print '***** Cannot write to log file: '+config.log_file
raise IOError()
# Write (append) header to log file
#
f_log.write(os.linesep)
f_log.write('##################################################')
f_log.write("############"+os.linesep)
f_log.write("#"+os.linesep)
f_log.write("# 'pyTrainHMM.py - Version 0.1' process started at: ")
f_log.write(time.ctime(time.time())+os.linesep)
f_log.write("#"+os.linesep)
f_log.write("# Input file name: "+in_file_name+os.linesep)
f_log.write("# HMM file name: "+hmm_file_name+os.linesep)
f_log.write(os.linesep)
f_log.close()
elif (options[0] == '-s'):
smoothing = 1 # Set to do a HMM smoothing
smoothing = options[1]
if (smoothing in ['l','la','lap','laplac','laplace']):
smoothing = 'laplace'
elif (smoothing in ['a','ad','abs','absd','absdis','absdisc',\
'absdiscount']):
smoothing = 'absdiscount'
else: # Illegal value
print "*** Error: Illegal value for 'smoothing' argument:", smoothing
print "*** Possible are: 'laplace' or 'absdiscount'"
raise Exception()
options = options[2:] # Remove processed option
else:
print '*** Error: Illegal option:', options[0]
raise Exception()
# Get HMM states and observations from configuration module - - - - - - - - -
#
if (tag_mode == 'name'):
state_list = config.name_hmm_states
obser_list = config.name_hmm_obser
else:
state_list = config.geoloc_hmm_states
obser_list = config.geoloc_hmm_obser
# Open input file - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
#
try:
f_in = open(in_file_name,'r')
except:
inout.log_message('Cannot open input file: '+in_file_name,'err')
raise IOError()
line_count = 0 # Counter for lines read
rec_count = 0 # Counter for training records read
# Read lines, discard comment lines and process training data lines - - - - -
#
training_data = [] # List of training records
train_list = [] # List of training sequences (dictionaries), extracted from
# training data
for line in xreadlines.xreadlines(f_in):
if (line[0] != '#') and (line.strip() != ''):
# Line must contain a training record
line = line.strip() # Remove line separators
config.curr_line = line # Make a copy of the unprocessed current line
line_list = line.split(',') # Split into a list of elements
line_data = [] # Training data list for one training record
inout.log_message(['Record number: '+str(rec_count)],'v1')
config.curr_line_no = line_count # Store current line number
for elem in line_list:
[k,v] = elem.split(':') # Split into key and value
tag = k.strip()
state = v.strip()
line_data.append((state,tag))
if (state not in state_list):
msg = ['Illegal state name in training record: '+state, \
'Line: '+str(line_count)+', record: '+str(rec_count), \
'Possible values: '+str(state_list)]
inout.log_message(msg,'err')
raise Exception()
if (tag not in obser_list):
msg = ['Illegal observation (tag) name in training record: '+tag, \
'Line: '+str(line_count)+', record: '+str(rec_count), \
'Possible values: '+str(obser_list)]
inout.log_message(msg,'err')
raise Exception()
inout.log_message(' Training record '+str(rec_count)+':'+ \
str(line_data),'v1')
train_list.append(line_data)
rec_count += 1
inout.log_message('','v1') # Print empty lines between records
line_count += 1
# Close input file - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
#
f_in.close()
inout.log_message('','v1') # Print empty lines between records
# Initalise HMM and train it with training data - - - - - - - - - - - - - - -
#
myhmm = simplehmm.hmm(state_list, obser_list)
myhmm.train(train_list,smoothing)
myhmm.print_hmm()
# Save trained HMM - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
#
myhmm.save_hmm(hmm_file_name)
inout.log_message(['Read '+str(line_count)+' lines, processed '+ \
str(rec_count)+' training records', 'End.'],'v1')
def tagdata():
"""Main routine, open file, read lines, tag data records, write to out-file.
USAGE:
tagdata()
ARGUMENTS:
None
DESCRIPTION:
Main routine, see description of module above.
"""
# Process command line arguments and check for correctness - - - - - - - - -
#
if (len(config.options) < 5):
print '***** Error: %s needs at least six arguments:'% (sys.argv[0])
print '***** - Name of the project module'
print '***** - Tagging mode: "name" or "locality"'
print '***** - Output training file name'
print '***** - Start of block with training records'
print '***** - End of block with training records'
print '***** - Number of training records'
print '***** plus options'
raise Exception()
if (config.in_file_name == config.options[2]):
print '***** Error: Input and output files must differ'
print '***** Input file name: ', config.in_file_name
print '***** Output training file name:', config.options[2]
raise Exception()
first_rec = int(config.options[2])
last_rec = int(config.options[3])
num_rec = int(config.options[4])
in_file_name = config.in_file_name
out_file_name = config.options[1]
# Check record number values - - - - - - - - - - - - - - - - - - - - - - - -
#
if (int(first_rec) >= int(last_rec)) or \
((int(num_rec)-1) > (int(last_rec)-int(first_rec))):
print '***** Error: Illegal values for training records block:'
print '***** - Start of block with training records:', first_rec
print '***** - End of block with training records: ', last_rec
print '***** - Number of training records: ', num_rec
raise Exception()
rec_range = last_rec-first_rec-1 # Range of records in input file
# Open input file and check number of available records - - - - - - - - - - -
#
try:
f_in = open(in_file_name,'r')
except:
inout.log_message('Cannot open input file: '+in_file_name,'err')
raise IOError()
line_count = 0
for line in f_in.xreadlines():
line_count += 1
f_in.close()
if (last_rec > line_count): # Illegal value for last record
print '***** Error: Illegal values for last training records:', last_rec
print '***** File only contains',line_count, 'lines/records'
raise Exception()
# Get tagging mode/lookup-tables used - - - - - - - - - - - - - - - - - - - -
#
tag_mode = config.options[0]
if (tag_mode in ['name','na','n']):
tag_mode = 'name'
elif (tag_mode in ['locality','localty','loc','l']):
tag_mode = 'loc'
else:
print '***** Error: Illegal tagging mode:', tag_mode
print '***** Must be either "name" or "locality"'
raise Exception()
# Check for optional arguments and process if any - - - - - - - - - - - - - -
#
config.verbose = 0 # Default: No verbose output
config.logging = 0 # Default: No logging into a file
hmm_file_name = None # Default: Do not use HMM to standardise training
# records
retag_file_name = None # Default: Do not retag an existing training file
config.nowarn = 0 # Deactivate no warning flag (print/log warning
# messages)
freqs_file_name = None # Default: Do not write frequencies, no -freqs option
if (len(config.options) > 5):
options = config.options[5:]
while (options != []): # Do a loop processing all options
if (options[0] == '-nowarn'):
config.nowarn = 1 # Activate no warning flag
options = options[1:] # Remove processed '-nowarn' option
elif (options[0] == '-v1'):
config.verbose = 1 # Set to verbose output level 1
options = options[1:] # Remove processed '-v1' option
elif (options[0] == '-v2'):
config.verbose = 2 # Set to verbose output level 2
options = options[1:] # Remove processed '-v2' option
elif (options[0] == '-l'):
config.logging = 1
if (len(options) > 1):
if (options[1][0] != '-'): # Not another option, must be a file name
config.log_file = options[1] # Get name of log file
options = options[1:] # Remove file_name
options = options[1:] # Remove processed -'l' option only
try:
f_log = open(config.log_file,'a') # Test if file is appendable
except:
print '***** Error ********************',
print '***** Cannot write to log file: '+config.log_file
raise IOError()
# Write (append) header to log file
#
f_log.write(os.linesep)
f_log.write('##################################################')
f_log.write('############'+os.linesep)
f_log.write('#'+os.linesep)
f_log.write("# 'pyTagData.py - Version 0.1' process started at: ")
f_log.write(time.ctime(time.time())+os.linesep)
f_log.write('#'+os.linesep)
f_log.write("# Input file name: "+in_file_name+os.linesep)
f_log.write("# Output file name: "+out_file_name+os.linesep)
f_log.write("# Tagging mode: "+tag_mode+os.linesep)
f_log.write(os.linesep)
f_log.close()
elif (options[0] == '-hmm'):
hmm_file_name = options[1] # Get file name of the HMM to use
if (hmm_file_name == out_file_name):
print '***** Error: HMM file name is the same as output file name!'
raise Exception()
try:
f_in = open(hmm_file_name,'r') # Test if file is available
except:
print '***** Error: Cannot open HMM file specified in "-hmm"',
print 'option:', hmm_file_name
raise IOError()
f_in.close()
options = options[2:] # Remove processed '-hmm' option and file name
elif (options[0] == '-retag'):
if (hmm_file_name == None) and ('-hmm' not in options):
print '***** Error: "-retag" option can only be used together with',
print '"-hmm" option (which is not given).'
raise Exception()
retag_file_name = options[1] # Get file name of the already-tagged
# file to re-process
if (retag_file_name == out_file_name):
print '***** Error: Retag file name is the same as output file name!'
raise Exception()
elif (retag_file_name == in_file_name):
print '***** Error: Retag file name is the same as input file name!'
raise Exception()
elif (retag_file_name == hmm_file_name):
print '***** Error: Retag file name is the same as HMM file name!'
raise Exception()
try:
f_in = open(retag_file_name,'r') # Test if file is available
# Now gather record numbers and previous tags/states, as well as the
# original header information. Use a simple state machine to do this.
#
tagged_recs = {}
cleaned_recs = {}
original_header_lines = []
state = -1 # Header lines state
prevline = ''
for line in f_in.xreadlines(): # Read training file and process it
line = line.strip()
if (state == -1) and (len(line) == 0): # End of header lines
state = 0
prevline = line
continue
if (state == -1) and (len(line) > 0) and (line[0] == "#"):
original_header_lines.append("# " + line)
prevline = line
continue
sline = line.split(' ')
if (len(sline) > 2) and (len(sline[2]) > 3) and (sline[0] == '#') \
and (sline[2][0] == '(') and (sline[2][-2:] == '):'):
try:
rec = int(sline[1]) # Original record number
tagged_recs[rec] = None
cleaned_recs[rec] = None
state = 1
except:
pass
prevline = line
continue
if (state == 1) and (len(line) > 0) and (line[0] != '#'):
tagged_recs[rec] = line
cleaned_recs[rec] = prevline
state = 0
prevline = line
continue
if (state == 1) and (len(line) > 0):
prevline = line
continue
f_in.close()
tagged_recs_keys = tagged_recs.keys()
num_rec = len(tagged_recs_keys) # Override specified numbers
first_rec = 0
last_rec = line_count
except:
print '***** Error: Cannot open tagged training file specified',
print 'in "-retag" option:', retag_file_name
raise IOError()
options = options[2:] # Remove processed '-retag' option and file name
elif (options[0][:5] == '-freq'):
if (hmm_file_name == None) and ('-hmm' not in options):
print '***** Error: "-feqs" option can only be used together with',
print '"-hmm" option (which is not given).'
raise Exception()
freqs_file_name = options[1] # File name to write the frequencies to
if (freqs_file_name == out_file_name):
print '***** Error: Frequency file name is the same as output',
print 'file name!'
raise Exception()
elif (freqs_file_name == in_file_name):
print '***** Error: Frequency file name is the same as input',
print 'file name!'
raise Exception()
elif (freqs_file_name == hmm_file_name):
print '***** Error: Frequency file name is the same as HMM',
print 'file name!'
raise Exception()
options = options[2:] # Remove processed '-freqs' option and file name
try: # Check if file writing is possible
freqs_out = open(freqs_file_name,'w')
freqs_out.close()
except:
print '***** Error: Cannot write to frequency output file specified',
print 'in "-freqs" option:', freqs_file_name
raise IOError()
else:
print '***** Error: Illegal option:', options[0]
raise Exception()
# If specified initalise and load Hidden Markov Model (HMM) - - - - - - - - -
#
if (hmm_file_name != None):
myhmm = simplehmm.hmm([],[]) # Create new empty HMM object
myhmm.load_hmm(hmm_file_name)
myhmm.print_hmm() # Print HMM (according to verbose and logging level)
# Open output file and write header - - - - - - - - - - - - - - - - - - - - -
#
try:
f_out = open(out_file_name,'w')
except:
inout.log_message('Cannot open output file: '+out_file_name,'err')
raise IOError()
f_out.write("# Tagged training data written by 'pyTagData.py -"+ \
" Version 0.1'"+os.linesep)
f_out.write('#'+os.linesep)
f_out.write('# Created '+time.ctime(time.time())+os.linesep)
f_out.write('#'+os.linesep)
f_out.write('# Input file name: '+in_file_name+os.linesep)
f_out.write('# Output file name: '+out_file_name+os.linesep)
f_out.write('#'+os.linesep)
f_out.write('# Parameters:'+os.linesep)
f_out.write('# - Start of block with training records: '+str(first_rec)+ \
os.linesep)
f_out.write('# - End of block with training records: '+str(last_rec)+ \
os.linesep)
f_out.write('# - Number of training records: '+str(num_rec)+ \
os.linesep)
if (hmm_file_name != None):
f_out.write('#'+os.linesep)
f_out.write("# - Using HMM file '"+hmm_file_name+"' for standardisation"+ \
os.linesep)
if (retag_file_name != None):
f_out.write('#'+os.linesep)
f_out.write("# - Reprocessing training file '"+retag_file_name+"'"+ \
os.linesep)
f_out.write("# Header lines from original training file follow:" + \
os.linesep)
for header_line in original_header_lines:
f_out.write(header_line + os.linesep)
if (freqs_file_name != None):
f_out.write('#'+os.linesep)
f_out.write("# - Tag/state pattern frequencies written to file '" + \
freqs_file_name + os.linesep)
f_out.write('#'+'-'*70+os.linesep)
f_out.write(os.linesep)
rec_count = 0 # Number of selected records
num_rec_left = num_rec # Number of records to be selected left
rec_selected = {} # Dictionary of all record numbers that were selected
seq_freqs = {} # Dict to hold examples of tag/state patterns
unchanged_loop_cnt = 0 # Counter of how many loops have been done
# without new records being selected
prev_num_rec_left = num_rec # Number of records left in the previous
# interation
# Due to the random nature of selecting records, and because sometimes - - -
# a selected component can be empty (and is thus not used for training)
# more than one iteration over the input data set is carried out. In each
# iteration, records are selected randomly.
#
while (rec_count < num_rec): # Loop until 'num_rec' records selected
# Open input file - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
#
try:
f_in = open(in_file_name,'r')
except:
inout.log_message('Cannot open input file: '+in_file_name,'err')
raise IOError()
line_read = 0 # Number of read lines
# Skip to start of training block - - - - - - - - - - - - - - - - - - - - -
#
if (first_rec > 0):
for i in range(first_rec):
f_in.readline()
while (rec_count < num_rec) and (line_read <= (last_rec-first_rec)):
line = f_in.readline()
if ((retag_file_name != None) and (line_read in tagged_recs_keys)) or \
((retag_file_name == None) and \
(num_rec_left >= random.randrange(0,rec_range,1))):
line = line.strip() # Remove line separators
config.curr_line = line # Make a copy of the unprocessed current line
line = line.lower() # Make all characters lower case
inout.log_message(['Record number: '+str(line_read+first_rec)],'v1')
config.curr_line_no = line_read+first_rec # Store current line number
# Process line and extract content into components (name, geocode, etc)
#
[name_comp, geocode_comp, locality_comp, date1_comp, date2_comp] = \
inout.process_line(line)
# Select component and process it - - - - - - - - - - - - - - - - - - -
#
if (tag_mode == 'name'):
if (type(name_comp) == types.ListType):
component = name_comp[0].strip()+' '+name_comp[1].strip()
else:
component = name_comp.strip()
else: # Locality component
component = geocode_comp.strip()+' '+locality_comp.strip()
if (component != '') and \
(not rec_selected.has_key((line_read+first_rec))):
if (tag_mode == 'name'):
inout.log_message(' Name component: |'+component+'|','v1')
component = name.clean_name_component(component)
[word_list, tag_list] = name.tag_name_component(component)
else: # Locality component
inout.log_message(' Locality component: |'+component+'|','v1')
component = locality.clean_geoloc_component(component)
[word_list, tag_list] = locality.tag_geoloc_component(component)
if (tag_list != []): # Only process non-empty tag lists
# Append record number into dictionary of processed records
#
rec_selected.update({(line_read+first_rec):(line_read+first_rec)})
# Create all permutation sequences of this tag list - - - - - - - -
#
tag_seq = mymath.perm_tag_sequence(tag_list)
inout.log_message([' Word list: '+str(word_list), \
' Tag list: '+str(tag_list), \
' Tag sequences:'],'v2')
# Do HMM processing - - - - - - - - - - - - - - - - - - - - - - - -
#
if (hmm_file_name != None):
state_seq = [] # List containing computed HMM state sequences
max_prob = -1.0 # maximal probability for a sequence
max_seq_no = -1 # Number of the seq. with the max. probablity
# Now give tag sequences to the HMMs to compute state sequences
#
i = 0
for t in tag_seq:
[obs_seq, prob] = myhmm.viterbi(t)
state_seq.append(obs_seq)
if (prob > max_prob):
max_prob = prob
max_seq_no = i
i += 1
# Write original component and resulting tag sequences to output
#
f_out.write('# '+str(line_read+first_rec)+' ('+str(rec_count)+ \
'): |'+component+'|'+os.linesep) # Commented original
num_len = len(str(line_read+first_rec))+len(str(rec_count))+6
f_out.write('#'+num_len*' '+'|'+' '.join(word_list)+'|'+os.linesep)
for i in range(len(tag_seq)):
# Convert each tag sequence into a string for file output
#
seq_string = ' '
if (hmm_file_name != None) and (i != max_seq_no):
seq_string = '# ' # Comment sequences with not max. probability
for j in range(len(tag_seq[i])):
if (hmm_file_name != None):
seq_string = seq_string+' '+tag_seq[i][j]+':'+ \
state_seq[i][j]+','
else:
seq_string = seq_string+' '+tag_seq[i][j]+':,'
f_out.write(seq_string[:-1]+os.linesep) # Write without , at end
inout.log_message(' '+seq_string[:-1],'v2')
if (hmm_file_name != None):
f_out.write('# Maximum Viterbi probability: %0.5f'% \
(max_prob) + os.linesep)
inout.log_message('Maximum Viterbi probability: %0.5f'% \
(max_prob), 'v2')
if (retag_file_name != None) and (tagged_recs[line_read] != None):
if (tagged_recs[line_read].strip() != seq_string[:-1].strip()):
f_out.write("# Note: ***** Changed *****" + os.linesep)
inout.log_message(' Note:' + \
' ***** Changed *****','v2')
f_out.write('# Was: ' + tagged_recs[line_read]+os.linesep)
# Write commented original tag sequence
inout.log_message('Original tag sequence: '+ \
tagged_recs[line_read],'v2')
f_out.write(os.linesep) # Write an empty line
inout.log_message('','v1') # Print empty lines between records
if (hmm_file_name != None):
seq_key = seq_string[:-1] # Add sequence to dictionary
if (seq_freqs.has_key(seq_key)):
seq_freqs[seq_key].append(['|'+' '.join(word_list)+'|', \
max_prob])
else:
seq_freqs[seq_key] = [['|'+' '.join(word_list)+'|', \
max_prob]]
rec_count += 1
# Print process indicator message
#
if (config.proc_ind >= 0) and (rec_count > 0):
if (rec_count % config.proc_ind == 0):
print 'Processed line', rec_count, 'of', num_rec
line_read += 1
f_in.close()
num_rec_left = num_rec - rec_count
if (prev_num_rec_left == num_rec_left): # No new records selected
unchanged_loop_cnt += 1
prev_num_rec_left = num_rec_left # Set to current value
if (unchanged_loop_cnt > 5): # Do five loops maximal without selecting
# new records
config.curr_line_no = -1 # Set to illegal/empty values, as warning is
config.curr_line = '' # not related to the current input line
inout.log_message(['Can not select more than '+str(rec_count)+ \
' records for training.', \
'This is probably due to empty input components.', \
'Please reduce value of "num_rec" or increase ' + \
'range','between "first_rec" and "last_rec".'],'warn')
break
if (num_rec_left < 10): # Only 10 records left to select
num_rec_left = num_rec+1 # Set to more than 100% probablity
elif (num_rec_left < (num_rec / 100.0)): # Less than 1% records left
num_rec_left = int(num_rec / 100.0) # Set to 1%
f_out.close()
# If specified, save Viterbi frequencies to a file - - - - - - - - - - - - -
#
if (freqs_file_name != None):
freqs_out = open(freqs_file_name,'w') # Open frequency file for writing
freqs_out.write('# Frequency listing of tag/state patterns written by')
freqs_out.write('"pyTagData.py - Version 0.1"'+os.linesep)
freqs_out.write('#'+os.linesep)
freqs_out.write('# Created '+time.ctime(time.time())+os.linesep)
freqs_out.write('#'+os.linesep)
freqs_out.write("# Input file name: "+in_file_name+os.linesep)
freqs_out.write("# Output file name: "+out_file_name+os.linesep)
freqs_out.write(os.linesep)
freqs_out.write('# Parameters:'+os.linesep)
freqs_out.write('# - Start of block with training records: '+ \
str(first_rec)+os.linesep)
freqs_out.write('# - End of block with training records: '+ \
str(last_rec)+os.linesep)
freqs_out.write('# - Number of training records: '+ \
str(num_rec)+os.linesep)
if (hmm_file_name != None):
freqs_out.write('#'+os.linesep)
freqs_out.write("# - Using HMM file '"+hmm_file_name+ \
"' for standardisation"+os.linesep)
if (retag_file_name != None):
freqs_out.write('#'+os.linesep)
freqs_out.write("# - Reprocessing training file '"+retag_file_name+ \
"'"+os.linesep)
freqs_out.write('#'+'-'*70+os.linesep)
freqs_out.write(os.linesep)
sorted_seq_freqs = [] # Now sort sequences according to their fruequencies
for key in seq_freqs.keys():
sorted_seq_freqs.append((len(seq_freqs[key]),key))
sorted_seq_freqs.sort()
for skey in sorted_seq_freqs:
key = skey[1]
freqs_out.write('# Pattern: '+str(key)+os.linesep)
freqs_out.write('# Frequency: '+str(skey[0])+os.linesep)
examples = seq_freqs[key]
freqs_out.write('# Maximum Viterbi probability: '+ \
str(examples[0][1])+os.linesep)
freqs_out.write('# Examples: '+os.linesep)
for example in examples:
freqs_out.write('# '+str(example[0])+os.linesep)
freqs_out.write(str(key)+os.linesep)
freqs_out.write(os.linesep)
freqs_out.close()
inout.log_message(['Read '+str(line_read)+' lines, processed '+ \
str(rec_count)+' lines', 'End.'],'v1')
def get_geoloc_hmm(word_list, tag_list):
"""Process input using a HMM to extract geocode and locality output fields.
USAGE:
geoloc_dict = get_geoloc_hmm(word_list, tag_list)
ARGUMENTS:
word_list List of words as produces with clean_tag_locality()
tag_list Corresponding list of tags as produces with
clean_tag_locality()
DESCRIPTION:
The routine returns a dictionary with the parsed and extracted output
fields for both the locality and geocode components. A Hidden Markov Model
(HMM) is used for this task.
The dictionary returned can contain the following key words:
- wayfare_number
- wayfare_name
- wayfare_qualifier
- wayfare_type
- unit_number
- unit_type
- property_name
- institution_name
- institution_type
- postaddress_number
- postaddress_type
- locality_name
- locality_qualifier
- postcode
- territory
- country
- geoloc_hmm_proba (the probability returned by the Viterbi algorithm for
the most likely HMM state seqence)
"""
# First, create all permutations of the input tag sequence
#
tag_list_seq = mymath.perm_tag_sequence(tag_list)
msg = [' Input tag sequence: ' + str(tag_list), ' Output tag sequences:']
for t in tag_list_seq:
msg.append(' ' + str(t))
inout.log_message(msg, 'v2')
# Now give all tag sequences to the HMM - - - - - - - - - - - - - - - - - - -
# and keep the one with highest probability
#
max_prob = -1.0
best_obs_seq = []
best_tag_list = []
for t in tag_list_seq:
[obs_seq, prob] = config.geoloc_hmm.viterbi(t)
if (prob > max_prob):
best_obs_seq = obs_seq
best_tag_list = t
max_prob = prob
inout.log_message(
' Probability ' + str(prob) + ' for sequence ' + str(t), 'v2')
inout.log_message([
' Best observation sequence: ' + str(best_obs_seq),
' with tag sequence: ' + str(best_tag_list)
], 'v2')
# Now process the observation sequence and add elements into dictionary - - -
#
tag_list_len = len(tag_list)
norm_max_prob = max_prob / float(
tag_list_len) # Normalise max. probability
geoloc_dict = {'geoloc_hmm_proba': [str(norm_max_prob)]}
list_len = len(word_list)
for i in range(list_len): # Loop over words and states
w = word_list[i]
s = best_obs_seq[i]
# Do not output commas, vertical bars and hyphens - - - - - - - - - - - -
#
if (w in ['|', ',', '-', '/']):
pass
elif (s == 'wfnu'
): # Wayfare number - - - - - - - - - - - - - - - - - - -
v = geoloc_dict.get('wayfare_number', [])
v.append(w)
geoloc_dict.update({'wayfare_number': v})
elif (s in ['wfna1', 'wfna2',
'wfna3']): # Wayfare name - - - - - - - - - -
v = geoloc_dict.get('wayfare_name', [])
v.append(w)
geoloc_dict.update({'wayfare_name': v})
elif (s == 'wfql'
): # Wayfare qualifier - - - - - - - - - - - - - - - - -
v = geoloc_dict.get('wayfare_qualifier', [])
v.append(w)
geoloc_dict.update({'wayfare_qualifier': v})
elif (s == 'wfty'
): # Wayfare type - - - - - - - - - - - - - - - - - - - -
v = geoloc_dict.get('wayfare_type', [])
v.append(w)
geoloc_dict.update({'wayfare_type': v})
elif (s == 'unnu'
): # Unit number - - - - - - - - - - - - - - - - - - - -
v = geoloc_dict.get('unit_number', [])
v.append(w)
geoloc_dict.update({'unit_number': v})
elif (s == 'unty'
): # Unit type - - - - - - - - - - - - - - - - - - - - -
v = geoloc_dict.get('unit_type', [])
v.append(w)
geoloc_dict.update({'unit_type': v})
elif (s in ['prna1',
'prna2']): # Property name - - - - - - - - - - - - - -
v = geoloc_dict.get('property_name', [])
v.append(w)
geoloc_dict.update({'property_name': v})
elif (s in ['inna1',
'inna2']): # Institution name - - - - - - - - - - - -
v = geoloc_dict.get('institution_name', [])
v.append(w)
geoloc_dict.update({'institution_name': v})
elif (s == 'inty'
): # Institution type - - - - - - - - - - - - - - - - - -
v = geoloc_dict.get('institution_type', [])
v.append(w)
geoloc_dict.update({'institution_type': v})
elif (s == 'panu'
): # Postal address number - - - - - - - - - - - - - - -
v = geoloc_dict.get('postaddress_number', [])
v.append(w)
geoloc_dict.update({'postaddress_number': v})
elif (s == 'paty'
): # Postal address type - - - - - - - - - - - - - - - -
v = geoloc_dict.get('postaddress_type', [])
v.append(w)
geoloc_dict.update({'postaddress_type': v})
elif (s in ['loc1',
'loc2']): # Locality name - - - - - - - - - - - - - - -
v = geoloc_dict.get('locality_name', [])
v.append(w)
geoloc_dict.update({'locality_name': v})
elif (s == 'locql'
): # Locality qualifier - - - - - - - - - - - - - - - -
v = geoloc_dict.get('locality_qualifier', [])
v.append(w)
geoloc_dict.update({'locality_qualifier': v})
elif (s == 'pc'
): # Postcode - - - - - - - - - - - - - - - - - - - - - - -
v = geoloc_dict.get('postcode', [])
v.append(w)
geoloc_dict.update({'postcode': v})
elif (s in ['ter1',
'ter2']): # Territory - - - - - - - - - - - - - - - - -
v = geoloc_dict.get('territory', [])
v.append(w)
geoloc_dict.update({'territory': v})
elif (s in ['cntr1',
'cntr2']): # Country - - - - - - - - - - - - - - - - -
v = geoloc_dict.get('country', [])
v.append(w)
geoloc_dict.update({'country': v})
else: # Should never happen
msg = ['This should never happen!', ' Tag: '+str(s), ' Word: '+w, \
' Word list: '+str(word_list), \
' tag list: '+str(tag_list)]
inout.log_message(msg, 'warn')
# Check if concatenated locality and territory words are in lookup-table - -
#
if (geoloc_dict.has_key('locality_name')):
loc = geoloc_dict['locality_name']
if (len(loc) > 1): # Locality contains more than one word
loc_tuple = tuple(loc) # Make it a tuple
if (config.geoloc_lookup_dict.has_key(loc_tuple)):
new_loc = config.geoloc_lookup_dict[loc_tuple][0]
geoloc_dict.update({'locality_name': [new_loc]})
if (geoloc_dict.has_key('territory')):
terr = geoloc_dict['territory']
if (len(terr) > 1): # Territory contains more than one word
terr_tuple = tuple(terr) # Make it a tuple
if (config.geoloc_lookup_dict.has_key(terr_tuple)):
new_terr = config.geoloc_lookup_dict[terr_tuple][0]
geoloc_dict.update({'territory': [new_terr]})
if (geoloc_dict.has_key('country')):
cntr = geoloc_dict['country']
if (len(cntr) > 1): # Country contains more than one word
cntr_tuple = tuple(cntr) # Make it a tuple
if (config.geoloc_lookup_dict.has_key(cntr_tuple)):
new_cntr = config.geoloc_lookup_dict[cntr_tuple][0]
geoloc_dict.update({'country': [new_cntr]})
# Finally do some tests on the output fields - - - - - - - - - - - - - - - -
#
geoloc_items = geoloc_dict.items()
# Check if a value list has more than three elements, if so print out
#
for i in geoloc_items:
if (len(i[1]) > 3):
inout.log_message('Geocode/locality output field '+ str(i[0])+ \
' contains more than three elements: '+str(i[1]),'warn')
# Check if 'number' elements only contain (alpha-) numerical values - - - - -
# and also check how many numbers in an element
#
if (geoloc_dict.has_key('wayfare_number')
): # Check how many wayfare numbers
v = geoloc_dict['wayfare_number']
if (len(v) > 2):
inout.log_message('More than two wayfare numbers: ' + str(v),
'warn')
for i in v:
if (i.isalpha()): # Element contains only letters
inout.log_message('Wayfare number element contains no digits: '+ \
str(v),'warn')
break # Exit for loop
if (geoloc_dict.has_key('unit_number')): # Check how many unit numbers
v = geoloc_dict['unit_number']
if (len(v) > 1):
inout.log_message('More than one unit numbers: ' + str(v), 'warn')
for i in v:
if (i.isalpha()): # Element contains only letters
inout.log_message('Unit number element contains no digits: '+str(v),\
'warn')
break # Exit for loop
if (geoloc_dict.has_key('postaddress_number')
): # Check postaddress numbers
v = geoloc_dict['postaddress_number']
if (len(v) > 1):
inout.log_message('More than one postaddress numbers: ' + str(v),
'warn')
for i in v:
if (i.isalpha()): # Element contains only letters
inout.log_message('Postaddress number element contains no digits: '+ \
str(v),'warn')
break # Exit for loop
# Check if 'type' elements contain one word only - - - - - - - - - - - - - -
# if it's a known type word
#
if (geoloc_dict.has_key('wayfare_type')): # Check wayfare type
v = geoloc_dict['wayfare_type']
if (len(v) > 1):
inout.log_message('More than one wayfare type: ' + str(v), 'warn')
for i in v:
i = i.split('_')
i = tuple(i) # Make it a tuple
if (not config.geoloc_lookup_dict.has_key((i))) or \
(config.geoloc_lookup_dict.has_key((i)) and \
(config.geoloc_lookup_dict[(i)][1].find('WT') < 0)):
inout.log_message('Wayfare type word is not known: ' + str(v),
'warn')
break # Exit for loop
if (geoloc_dict.has_key('unit_type')): # Check unit type
v = geoloc_dict['unit_type']
if (len(v) > 1):
inout.log_message('More than one unit type: ' + str(v), 'warn')
for i in v:
i = i.split('_')
i = tuple(i) # Make it a tuple
if (not config.geoloc_lookup_dict.has_key((i))) or \
(config.geoloc_lookup_dict.has_key((i)) and \
(config.geoloc_lookup_dict[(i)][1].find('UT') < 0)):
inout.log_message('Unit type word is not known: ' + str(v),
'warn')
break # Exit for loop
if (geoloc_dict.has_key('institution_type')): # Check institution type
v = geoloc_dict['institution_type']
if (len(v) > 1):
inout.log_message('More than one institution type: ' + str(v),
'warn')
for i in v:
i = i.split('_')
i = tuple(i) # Make it a tuple
if (not config.geoloc_lookup_dict.has_key((i))) or \
(config.geoloc_lookup_dict.has_key((i)) and \
(config.geoloc_lookup_dict[(i)][1].find('IT') < 0)):
inout.log_message(
'Institution type word is not known: ' + str(v), 'warn')
break # Exit for loop
if (geoloc_dict.has_key('postaddress_type')): # Check postaddress type
v = geoloc_dict['postaddress_type']
if (len(v) > 2):
inout.log_message('More than two postaddress type: ' + str(v),
'warn')
for i in v:
i = i.split('_')
i = tuple(i) # Make it a tuple
if (not config.geoloc_lookup_dict.has_key((i))) or \
(config.geoloc_lookup_dict.has_key((i)) and \
(config.geoloc_lookup_dict[(i)][1].find('PA') < 0)):
inout.log_message(
'Postaddress type word is not known: ' + str(v), 'warn')
break # Exit for loop
# Check if 'qualifier' elements only contain known qualifier words - - - - -
#
if (geoloc_dict.has_key('wayfare_qualifier')): # Check wayfare qualifier
v = geoloc_dict['wayfare_qualifier']
for i in v:
if (not config.geoloc_lookup_dict.has_key((i,))) or \
(config.geoloc_lookup_dict.has_key((i,)) and \
(config.geoloc_lookup_dict[(i,)][1].find('LQ') < 0)):
inout.log_message('Wayfare qualifier word is not known: '+str(v), \
'warn')
break # Exit for loop
if (geoloc_dict.has_key('locality_qualifier')): # Check locality qualifier
v = geoloc_dict['locality_qualifier']
for i in v:
if (not config.geoloc_lookup_dict.has_key((i,))) or \
(config.geoloc_lookup_dict.has_key((i,)) and \
(config.geoloc_lookup_dict[(i,)][1].find('LQ') < 0)):
inout.log_message('Locality qualifier word is not known: '+str(v), \
'warn')
break # Exit for loop
return geoloc_dict
def tag_geoloc_component(geoloc_str):
"""Tag a geocode locality input component string and make a list.
USAGE:
[word_list, tag_list] = tag_geoloc_component(loc_str)
ARGUMENTS:
geoloc_str A string containing the geocode and/or locality components
DESCRIPTION:
This routines cleans the input string and extracts words, numbers and
separators into a list. Each element of this list is assigned one or more
tags. A 'greedy tagger' is applied, which cheques sequences of list
elements in the name lookup table (longer sequences first) and replaces
them with the string and tag from the lookup-table if found.
The routine returns two lists: words and their tags
"""
# First, split input string into elements at spaces - - - - - - - - - - - - -
#
org_list = geoloc_str.split() # The original list from the input string
inout.log_message(' Initial word list: ' + str(org_list), 'v2')
tag_list = [] # The initially empty list of tags
word_list = [] # The initially empty list of words
while (org_list != []): # As long as not all elements have been processed
tmp_list = org_list[:config.
geoloc_dict_seq_len] # Extract longest sub-list
tmp_val = [] # Start with empty value
tmp_key = tuple(tmp_list)
while (tmp_key !=
()): # As long as key not empty and not found in lookup
if (config.geoloc_lookup_dict.has_key(tmp_key)):
tmp_val = config.geoloc_lookup_dict[tmp_key]
break
tmp_key = tmp_key[:-1] # Remove last element in key
if (tmp_val != []): # A value has been found in the dictionary
tmp_len = len(tmp_key) # Length of found sequence
if (tmp_val[0] != ''): # it's not an empty value
word_list.append(
tmp_val[0]) # Append corrected word (or sequence)
tag_list.append(tmp_val[1]) # Append tag or tags
else: # No value has been found in the lookup dictionary, try other tags
tmp_val = org_list[
0] # Value is first element in the original list
tmp_len = 1
if (tmp_val.isdigit()): # Element is a number
word_list.append(tmp_val)
if (len(tmp_val) == 4):
tag_list.append('N4')
else:
tag_list.append('NU')
elif (not tmp_val.isalpha()
) and tmp_val.isalnum(): # Alpha-numeric
word_list.append(tmp_val)
tag_list.append('AN')
elif (tmp_val == '-'): # Element is a hyphen
word_list.append(tmp_val)
tag_list.append('HY')
elif (tmp_val == ','): # Element is a comma
word_list.append(tmp_val)
tag_list.append('CO')
elif (tmp_val == '|'): # Element is a vertical bar
word_list.append(tmp_val)
tag_list.append('VB')
else: # An unknown element
word_list.append(tmp_val)
tag_list.append('UN')
# Finally remove the processed elements from the original element list
#
org_list = org_list[tmp_len:] # Remove processed elements
return [word_list, tag_list]
def tagdata():
"""Main routine, open file, read lines, tag data records, write to out-file.
USAGE:
tagdata()
ARGUMENTS:
None
DESCRIPTION:
Main routine, see description of module above.
"""
# Process command line arguments and check for correctness - - - - - - - - -
#
if (len(config.options) < 5):
print '***** Error: %s needs at least six arguments:' % (sys.argv[0])
print '***** - Name of the project module'
print '***** - Tagging mode: "name" or "locality"'
print '***** - Output training file name'
print '***** - Start of block with training records'
print '***** - End of block with training records'
print '***** - Number of training records'
print '***** plus options'
raise Exception()
if (config.in_file_name == config.options[2]):
print '***** Error: Input and output files must differ'
print '***** Input file name: ', config.in_file_name
print '***** Output training file name:', config.options[2]
raise Exception()
first_rec = int(config.options[2])
last_rec = int(config.options[3])
num_rec = int(config.options[4])
in_file_name = config.in_file_name
out_file_name = config.options[1]
# Check record number values - - - - - - - - - - - - - - - - - - - - - - - -
#
if (int(first_rec) >= int(last_rec)) or \
((int(num_rec)-1) > (int(last_rec)-int(first_rec))):
print '***** Error: Illegal values for training records block:'
print '***** - Start of block with training records:', first_rec
print '***** - End of block with training records: ', last_rec
print '***** - Number of training records: ', num_rec
raise Exception()
rec_range = last_rec - first_rec - 1 # Range of records in input file
# Open input file and check number of available records - - - - - - - - - - -
#
try:
f_in = open(in_file_name, 'r')
except:
inout.log_message('Cannot open input file: ' + in_file_name, 'err')
raise IOError()
line_count = 0
for line in f_in.xreadlines():
line_count += 1
f_in.close()
if (last_rec > line_count): # Illegal value for last record
print '***** Error: Illegal values for last training records:', last_rec
print '***** File only contains', line_count, 'lines/records'
raise Exception()
# Get tagging mode/lookup-tables used - - - - - - - - - - - - - - - - - - - -
#
tag_mode = config.options[0]
if (tag_mode in ['name', 'na', 'n']):
tag_mode = 'name'
elif (tag_mode in ['locality', 'localty', 'loc', 'l']):
tag_mode = 'loc'
else:
print '***** Error: Illegal tagging mode:', tag_mode
print '***** Must be either "name" or "locality"'
raise Exception()
# Check for optional arguments and process if any - - - - - - - - - - - - - -
#
config.verbose = 0 # Default: No verbose output
config.logging = 0 # Default: No logging into a file
hmm_file_name = None # Default: Do not use HMM to standardise training
# records
retag_file_name = None # Default: Do not retag an existing training file
config.nowarn = 0 # Deactivate no warning flag (print/log warning
# messages)
freqs_file_name = None # Default: Do not write frequencies, no -freqs option
if (len(config.options) > 5):
options = config.options[5:]
while (options != []): # Do a loop processing all options
if (options[0] == '-nowarn'):
config.nowarn = 1 # Activate no warning flag
options = options[1:] # Remove processed '-nowarn' option
elif (options[0] == '-v1'):
config.verbose = 1 # Set to verbose output level 1
options = options[1:] # Remove processed '-v1' option
elif (options[0] == '-v2'):
config.verbose = 2 # Set to verbose output level 2
options = options[1:] # Remove processed '-v2' option
elif (options[0] == '-l'):
config.logging = 1
if (len(options) > 1):
if (options[1][0] !=
'-'): # Not another option, must be a file name
config.log_file = options[1] # Get name of log file
options = options[1:] # Remove file_name
options = options[1:] # Remove processed -'l' option only
try:
f_log = open(config.log_file,
'a') # Test if file is appendable
except:
print '***** Error ********************',
print '***** Cannot write to log file: ' + config.log_file
raise IOError()
# Write (append) header to log file
#
f_log.write(os.linesep)
f_log.write(
'##################################################')
f_log.write('############' + os.linesep)
f_log.write('#' + os.linesep)
f_log.write(
"# 'pyTagData.py - Version 0.1' process started at: ")
f_log.write(time.ctime(time.time()) + os.linesep)
f_log.write('#' + os.linesep)
f_log.write("# Input file name: " + in_file_name + os.linesep)
f_log.write("# Output file name: " + out_file_name +
os.linesep)
f_log.write("# Tagging mode: " + tag_mode + os.linesep)
f_log.write(os.linesep)
f_log.close()
elif (options[0] == '-hmm'):
hmm_file_name = options[1] # Get file name of the HMM to use
if (hmm_file_name == out_file_name):
print '***** Error: HMM file name is the same as output file name!'
raise Exception()
try:
f_in = open(hmm_file_name,
'r') # Test if file is available
except:
print '***** Error: Cannot open HMM file specified in "-hmm"',
print 'option:', hmm_file_name
raise IOError()
f_in.close()
options = options[
2:] # Remove processed '-hmm' option and file name
elif (options[0] == '-retag'):
if (hmm_file_name == None) and ('-hmm' not in options):
print '***** Error: "-retag" option can only be used together with',
print '"-hmm" option (which is not given).'
raise Exception()
retag_file_name = options[
1] # Get file name of the already-tagged
# file to re-process
if (retag_file_name == out_file_name):
print '***** Error: Retag file name is the same as output file name!'
raise Exception()
elif (retag_file_name == in_file_name):
print '***** Error: Retag file name is the same as input file name!'
raise Exception()
elif (retag_file_name == hmm_file_name):
print '***** Error: Retag file name is the same as HMM file name!'
raise Exception()
try:
f_in = open(retag_file_name,
'r') # Test if file is available
# Now gather record numbers and previous tags/states, as well as the
# original header information. Use a simple state machine to do this.
#
tagged_recs = {}
cleaned_recs = {}
original_header_lines = []
state = -1 # Header lines state
prevline = ''
for line in f_in.xreadlines(
): # Read training file and process it
line = line.strip()
if (state == -1) and (len(line)
== 0): # End of header lines
state = 0
prevline = line
continue
if (state == -1) and (len(line) > 0) and (line[0]
== "#"):
original_header_lines.append("# " + line)
prevline = line
continue
sline = line.split(' ')
if (len(sline) > 2) and (len(sline[2]) > 3) and (sline[0] == '#') \
and (sline[2][0] == '(') and (sline[2][-2:] == '):'):
try:
rec = int(sline[1]) # Original record number
tagged_recs[rec] = None
cleaned_recs[rec] = None
state = 1
except:
pass
prevline = line
continue
if (state
== 1) and (len(line) > 0) and (line[0] != '#'):
tagged_recs[rec] = line
cleaned_recs[rec] = prevline
state = 0
prevline = line
continue
if (state == 1) and (len(line) > 0):
prevline = line
continue
f_in.close()
tagged_recs_keys = tagged_recs.keys()
num_rec = len(
tagged_recs_keys) # Override specified numbers
first_rec = 0
last_rec = line_count
except:
print '***** Error: Cannot open tagged training file specified',
print 'in "-retag" option:', retag_file_name
raise IOError()
options = options[
2:] # Remove processed '-retag' option and file name
elif (options[0][:5] == '-freq'):
if (hmm_file_name == None) and ('-hmm' not in options):
print '***** Error: "-feqs" option can only be used together with',
print '"-hmm" option (which is not given).'
raise Exception()
freqs_file_name = options[
1] # File name to write the frequencies to
if (freqs_file_name == out_file_name):
print '***** Error: Frequency file name is the same as output',
print 'file name!'
raise Exception()
elif (freqs_file_name == in_file_name):
print '***** Error: Frequency file name is the same as input',
print 'file name!'
raise Exception()
elif (freqs_file_name == hmm_file_name):
print '***** Error: Frequency file name is the same as HMM',
print 'file name!'
raise Exception()
options = options[
2:] # Remove processed '-freqs' option and file name
try: # Check if file writing is possible
freqs_out = open(freqs_file_name, 'w')
freqs_out.close()
except:
print '***** Error: Cannot write to frequency output file specified',
print 'in "-freqs" option:', freqs_file_name
raise IOError()
else:
print '***** Error: Illegal option:', options[0]
raise Exception()
# If specified initalise and load Hidden Markov Model (HMM) - - - - - - - - -
#
if (hmm_file_name != None):
myhmm = simplehmm.hmm([], []) # Create new empty HMM object
myhmm.load_hmm(hmm_file_name)
myhmm.print_hmm() # Print HMM (according to verbose and logging level)
# Open output file and write header - - - - - - - - - - - - - - - - - - - - -
#
try:
f_out = open(out_file_name, 'w')
except:
inout.log_message('Cannot open output file: ' + out_file_name, 'err')
raise IOError()
f_out.write("# Tagged training data written by 'pyTagData.py -"+ \
" Version 0.1'"+os.linesep)
f_out.write('#' + os.linesep)
f_out.write('# Created ' + time.ctime(time.time()) + os.linesep)
f_out.write('#' + os.linesep)
f_out.write('# Input file name: ' + in_file_name + os.linesep)
f_out.write('# Output file name: ' + out_file_name + os.linesep)
f_out.write('#' + os.linesep)
f_out.write('# Parameters:' + os.linesep)
f_out.write('# - Start of block with training records: '+str(first_rec)+ \
os.linesep)
f_out.write('# - End of block with training records: '+str(last_rec)+ \
os.linesep)
f_out.write('# - Number of training records: '+str(num_rec)+ \
os.linesep)
if (hmm_file_name != None):
f_out.write('#' + os.linesep)
f_out.write("# - Using HMM file '"+hmm_file_name+"' for standardisation"+ \
os.linesep)
if (retag_file_name != None):
f_out.write('#' + os.linesep)
f_out.write("# - Reprocessing training file '"+retag_file_name+"'"+ \
os.linesep)
f_out.write("# Header lines from original training file follow:" + \
os.linesep)
for header_line in original_header_lines:
f_out.write(header_line + os.linesep)
if (freqs_file_name != None):
f_out.write('#' + os.linesep)
f_out.write("# - Tag/state pattern frequencies written to file '" + \
freqs_file_name + os.linesep)
f_out.write('#' + '-' * 70 + os.linesep)
f_out.write(os.linesep)
rec_count = 0 # Number of selected records
num_rec_left = num_rec # Number of records to be selected left
rec_selected = {} # Dictionary of all record numbers that were selected
seq_freqs = {} # Dict to hold examples of tag/state patterns
unchanged_loop_cnt = 0 # Counter of how many loops have been done
# without new records being selected
prev_num_rec_left = num_rec # Number of records left in the previous
# interation
# Due to the random nature of selecting records, and because sometimes - - -
# a selected component can be empty (and is thus not used for training)
# more than one iteration over the input data set is carried out. In each
# iteration, records are selected randomly.
#
while (rec_count < num_rec): # Loop until 'num_rec' records selected
# Open input file - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
#
try:
f_in = open(in_file_name, 'r')
except:
inout.log_message('Cannot open input file: ' + in_file_name, 'err')
raise IOError()
line_read = 0 # Number of read lines
# Skip to start of training block - - - - - - - - - - - - - - - - - - - - -
#
if (first_rec > 0):
for i in range(first_rec):
f_in.readline()
while (rec_count < num_rec) and (line_read <= (last_rec - first_rec)):
line = f_in.readline()
if ((retag_file_name != None) and (line_read in tagged_recs_keys)) or \
((retag_file_name == None) and \
(num_rec_left >= random.randrange(0,rec_range,1))):
line = line.strip() # Remove line separators
config.curr_line = line # Make a copy of the unprocessed current line
line = line.lower() # Make all characters lower case
inout.log_message(
['Record number: ' + str(line_read + first_rec)], 'v1')
config.curr_line_no = line_read + first_rec # Store current line number
# Process line and extract content into components (name, geocode, etc)
#
[name_comp, geocode_comp, locality_comp, date1_comp, date2_comp] = \
inout.process_line(line)
# Select component and process it - - - - - - - - - - - - - - - - - - -
#
if (tag_mode == 'name'):
if (type(name_comp) == types.ListType):
component = name_comp[0].strip(
) + ' ' + name_comp[1].strip()
else:
component = name_comp.strip()
else: # Locality component
component = geocode_comp.strip(
) + ' ' + locality_comp.strip()
if (component != '') and \
(not rec_selected.has_key((line_read+first_rec))):
if (tag_mode == 'name'):
inout.log_message(
' Name component: |' + component + '|', 'v1')
component = name.clean_name_component(component)
[word_list,
tag_list] = name.tag_name_component(component)
else: # Locality component
inout.log_message(
' Locality component: |' + component + '|', 'v1')
component = locality.clean_geoloc_component(component)
[word_list,
tag_list] = locality.tag_geoloc_component(component)
if (tag_list != []): # Only process non-empty tag lists
# Append record number into dictionary of processed records
#
rec_selected.update({
(line_read + first_rec): (line_read + first_rec)
})
# Create all permutation sequences of this tag list - - - - - - - -
#
tag_seq = mymath.perm_tag_sequence(tag_list)
inout.log_message([' Word list: '+str(word_list), \
' Tag list: '+str(tag_list), \
' Tag sequences:'],'v2')
# Do HMM processing - - - - - - - - - - - - - - - - - - - - - - - -
#
if (hmm_file_name != None):
state_seq = [
] # List containing computed HMM state sequences
max_prob = -1.0 # maximal probability for a sequence
max_seq_no = -1 # Number of the seq. with the max. probablity
# Now give tag sequences to the HMMs to compute state sequences
#
i = 0
for t in tag_seq:
[obs_seq, prob] = myhmm.viterbi(t)
state_seq.append(obs_seq)
if (prob > max_prob):
max_prob = prob
max_seq_no = i
i += 1
# Write original component and resulting tag sequences to output
#
f_out.write('# '+str(line_read+first_rec)+' ('+str(rec_count)+ \
'): |'+component+'|'+os.linesep) # Commented original
num_len = len(str(line_read + first_rec)) + len(
str(rec_count)) + 6
f_out.write('#' + num_len * ' ' + '|' +
' '.join(word_list) + '|' + os.linesep)
for i in range(len(tag_seq)):
# Convert each tag sequence into a string for file output
#
seq_string = ' '
if (hmm_file_name != None) and (i != max_seq_no):
seq_string = '# ' # Comment sequences with not max. probability
for j in range(len(tag_seq[i])):
if (hmm_file_name != None):
seq_string = seq_string+' '+tag_seq[i][j]+':'+ \
state_seq[i][j]+','
else:
seq_string = seq_string + ' ' + tag_seq[i][
j] + ':,'
f_out.write(seq_string[:-1] +
os.linesep) # Write without , at end
inout.log_message(' ' + seq_string[:-1], 'v2')
if (hmm_file_name != None):
f_out.write('# Maximum Viterbi probability: %0.5f'% \
(max_prob) + os.linesep)
inout.log_message('Maximum Viterbi probability: %0.5f'% \
(max_prob), 'v2')
if (retag_file_name !=
None) and (tagged_recs[line_read] != None):
if (tagged_recs[line_read].strip() !=
seq_string[:-1].strip()):
f_out.write("# Note: ***** Changed *****" +
os.linesep)
inout.log_message(' Note:' + \
' ***** Changed *****','v2')
f_out.write('# Was: ' +
tagged_recs[line_read] +
os.linesep)
# Write commented original tag sequence
inout.log_message('Original tag sequence: '+ \
tagged_recs[line_read],'v2')
f_out.write(os.linesep) # Write an empty line
inout.log_message(
'', 'v1') # Print empty lines between records
if (hmm_file_name != None):
seq_key = seq_string[:
-1] # Add sequence to dictionary
if (seq_freqs.has_key(seq_key)):
seq_freqs[seq_key].append(['|'+' '.join(word_list)+'|', \
max_prob])
else:
seq_freqs[seq_key] = [['|'+' '.join(word_list)+'|', \
max_prob]]
rec_count += 1
# Print process indicator message
#
if (config.proc_ind >= 0) and (rec_count > 0):
if (rec_count % config.proc_ind == 0):
print 'Processed line', rec_count, 'of', num_rec
line_read += 1
f_in.close()
num_rec_left = num_rec - rec_count
if (prev_num_rec_left == num_rec_left): # No new records selected
unchanged_loop_cnt += 1
prev_num_rec_left = num_rec_left # Set to current value
if (unchanged_loop_cnt > 5): # Do five loops maximal without selecting
# new records
config.curr_line_no = -1 # Set to illegal/empty values, as warning is
config.curr_line = '' # not related to the current input line
inout.log_message(['Can not select more than '+str(rec_count)+ \
' records for training.', \
'This is probably due to empty input components.', \
'Please reduce value of "num_rec" or increase ' + \
'range','between "first_rec" and "last_rec".'],'warn')
break
if (num_rec_left < 10): # Only 10 records left to select
num_rec_left = num_rec + 1 # Set to more than 100% probablity
elif (num_rec_left < (num_rec / 100.0)): # Less than 1% records left
num_rec_left = int(num_rec / 100.0) # Set to 1%
f_out.close()
# If specified, save Viterbi frequencies to a file - - - - - - - - - - - - -
#
if (freqs_file_name != None):
freqs_out = open(freqs_file_name,
'w') # Open frequency file for writing
freqs_out.write('# Frequency listing of tag/state patterns written by')
freqs_out.write('"pyTagData.py - Version 0.1"' + os.linesep)
freqs_out.write('#' + os.linesep)
freqs_out.write('# Created ' + time.ctime(time.time()) + os.linesep)
freqs_out.write('#' + os.linesep)
freqs_out.write("# Input file name: " + in_file_name + os.linesep)
freqs_out.write("# Output file name: " + out_file_name + os.linesep)
freqs_out.write(os.linesep)
freqs_out.write('# Parameters:' + os.linesep)
freqs_out.write('# - Start of block with training records: '+ \
str(first_rec)+os.linesep)
freqs_out.write('# - End of block with training records: '+ \
str(last_rec)+os.linesep)
freqs_out.write('# - Number of training records: '+ \
str(num_rec)+os.linesep)
if (hmm_file_name != None):
freqs_out.write('#' + os.linesep)
freqs_out.write("# - Using HMM file '"+hmm_file_name+ \
"' for standardisation"+os.linesep)
if (retag_file_name != None):
freqs_out.write('#' + os.linesep)
freqs_out.write("# - Reprocessing training file '"+retag_file_name+ \
"'"+os.linesep)
freqs_out.write('#' + '-' * 70 + os.linesep)
freqs_out.write(os.linesep)
sorted_seq_freqs = [
] # Now sort sequences according to their fruequencies
for key in seq_freqs.keys():
sorted_seq_freqs.append((len(seq_freqs[key]), key))
sorted_seq_freqs.sort()
for skey in sorted_seq_freqs:
key = skey[1]
freqs_out.write('# Pattern: ' + str(key) + os.linesep)
freqs_out.write('# Frequency: ' + str(skey[0]) + os.linesep)
examples = seq_freqs[key]
freqs_out.write('# Maximum Viterbi probability: '+ \
str(examples[0][1])+os.linesep)
freqs_out.write('# Examples: ' + os.linesep)
for example in examples:
freqs_out.write('# ' + str(example[0]) + os.linesep)
freqs_out.write(str(key) + os.linesep)
freqs_out.write(os.linesep)
freqs_out.close()
inout.log_message(['Read '+str(line_read)+' lines, processed '+ \
str(rec_count)+' lines', 'End.'],'v1')
def trainhmm():
"""Main routine, open file, read lines, train HMM and save it to file.
USAGE:
trainhmm()
ARGUMENTS:
None
DESCRIPTION:
Main routine, see description of module above.
"""
# Process command line arguments and check for correctness - - - - - - - - -
#
if (len(config.options) < 3):
print '***** Error: %s needs at least four arguments:' % (sys.argv[0])
print '***** - Name of the project module'
print '***** - Tagging mode: "name" or "locality"'
print '***** - Input training file name'
print '***** - HMM output file name'
print '***** plus options'
raise Exception()
if (config.options[1] == config.options[2]):
print '*** Error: Input and output files must differ'
print '*** Input training file name:', config.options[1]
print '*** HMM output file name: ', config.options[1]
raise Exception()
in_file_name = config.options[1]
hmm_file_name = config.options[2]
# Get tagging mode/lookup-tables used - - - - - - - - - - - - - - - - - - - -
#
tag_mode = config.options[0]
if (tag_mode in ['name', 'na', 'n']):
tag_mode = 'name'
elif (tag_mode in ['locality', 'lolty', 'loc', 'l']):
tag_mode = 'loc'
else:
print '***** Error: Illegal tagging mode:', tag_mode
print '***** Must be either "name" or "locality"'
raise Exception()
# Check for optional arguments and process if any - - - - - - - - - - - - - -
#
config.verbose = 0 # Default: No verbose output
config.logging = 0 # Default: No logging into a file
smoothing = None # Default: No smoothing
config.nowarn = 0 # Deactivate no warning flag (print/log warning
# messages)
if (len(config.options) > 3):
options = config.options[3:]
while (options != []): # Do a loop processing all options
if (options[0] == '-nowarn'):
config.nowarn = 1 # Activate no warning flag
options = options[1:] # Remove processed '-nowarn' option
elif (options[0] == '-v1'):
config.verbose = 1 # Set to verbose output level 1
options = options[1:] # Remove processed '-v1' option
elif (options[0] == '-v2'):
config.verbose = 2 # Set to verbose output level 2
options = options[1:] # Remove processed '-v2' option
elif (options[0] == '-l'):
config.logging = 1
if (len(options) > 1):
if (options[1][0] !=
'-'): # Not another option, must be a file name
config.log_file = options[1] # Get name of log file
options = options[1:] # Remove file_name
options = options[1:] # Remove processed -'l' option only
try:
f_log = open(config.log_file,
'a') # Test if file is appendable
except:
print '***** Error ********************',
print '***** Cannot write to log file: ' + config.log_file
raise IOError()
# Write (append) header to log file
#
f_log.write(os.linesep)
f_log.write(
'##################################################')
f_log.write("############" + os.linesep)
f_log.write("#" + os.linesep)
f_log.write(
"# 'pyTrainHMM.py - Version 0.1' process started at: ")
f_log.write(time.ctime(time.time()) + os.linesep)
f_log.write("#" + os.linesep)
f_log.write("# Input file name: " + in_file_name + os.linesep)
f_log.write("# HMM file name: " + hmm_file_name + os.linesep)
f_log.write(os.linesep)
f_log.close()
elif (options[0] == '-s'):
smoothing = 1 # Set to do a HMM smoothing
smoothing = options[1]
if (smoothing in ['l', 'la', 'lap', 'laplac', 'laplace']):
smoothing = 'laplace'
elif (smoothing in ['a','ad','abs','absd','absdis','absdisc',\
'absdiscount']):
smoothing = 'absdiscount'
else: # Illegal value
print "*** Error: Illegal value for 'smoothing' argument:", smoothing
print "*** Possible are: 'laplace' or 'absdiscount'"
raise Exception()
options = options[2:] # Remove processed option
else:
print '*** Error: Illegal option:', options[0]
raise Exception()
# Get HMM states and observations from configuration module - - - - - - - - -
#
if (tag_mode == 'name'):
state_list = config.name_hmm_states
obser_list = config.name_hmm_obser
else:
state_list = config.geoloc_hmm_states
obser_list = config.geoloc_hmm_obser
# Open input file - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
#
try:
f_in = open(in_file_name, 'r')
except:
inout.log_message('Cannot open input file: ' + in_file_name, 'err')
raise IOError()
line_count = 0 # Counter for lines read
rec_count = 0 # Counter for training records read
# Read lines, discard comment lines and process training data lines - - - - -
#
training_data = [] # List of training records
train_list = [
] # List of training sequences (dictionaries), extracted from
# training data
for line in xreadlines.xreadlines(f_in):
if (line[0] != '#') and (line.strip() != ''):
# Line must contain a training record
line = line.strip() # Remove line separators
config.curr_line = line # Make a copy of the unprocessed current line
line_list = line.split(',') # Split into a list of elements
line_data = [] # Training data list for one training record
inout.log_message(['Record number: ' + str(rec_count)], 'v1')
config.curr_line_no = line_count # Store current line number
for elem in line_list:
[k, v] = elem.split(':') # Split into key and value
tag = k.strip()
state = v.strip()
line_data.append((state, tag))
if (state not in state_list):
msg = ['Illegal state name in training record: '+state, \
'Line: '+str(line_count)+', record: '+str(rec_count), \
'Possible values: '+str(state_list)]
inout.log_message(msg, 'err')
raise Exception()
if (tag not in obser_list):
msg = ['Illegal observation (tag) name in training record: '+tag, \
'Line: '+str(line_count)+', record: '+str(rec_count), \
'Possible values: '+str(obser_list)]
inout.log_message(msg, 'err')
raise Exception()
inout.log_message(' Training record '+str(rec_count)+':'+ \
str(line_data),'v1')
train_list.append(line_data)
rec_count += 1
inout.log_message('', 'v1') # Print empty lines between records
line_count += 1
# Close input file - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
#
f_in.close()
inout.log_message('', 'v1') # Print empty lines between records
# Initalise HMM and train it with training data - - - - - - - - - - - - - - -
#
myhmm = simplehmm.hmm(state_list, obser_list)
myhmm.train(train_list, smoothing)
myhmm.print_hmm()
# Save trained HMM - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
#
myhmm.save_hmm(hmm_file_name)
inout.log_message(['Read '+str(line_count)+' lines, processed '+ \
str(rec_count)+' training records', 'End.'],'v1')
# Check if definition of input components is correct with file types
#
input_values = input_component.values()
input_len = -1 # Length of the input (either in number of fields (CSV and TAB
# files) or in characters (COL files)
output_keys = output_field.keys() # Check if 'original_input' is in output
# fields, and if so check for correctness
for k in output_keys:
if (k[:14] == 'original_input'):
v = k[14:].strip()
if (v != ''): # There is a field or column range given
if (v[0] == '[') and (v[-1] == ']'):
v = v[1:-1] # Remove brackets
else:
inout.log_message('Wrong input component definition: '+str(k) + \
' for "original_input" output field','err')
raise Exception()
if (v[0] == '(') and (v[-1] == ')'): # It's a tuple
v = v[1:-1] # Remove tuple brackets
v = v.split(',') # Make a list
for i in range(len(v)):
v[i] = int(v[i]) # Make integers
if (len(v) == 1): # One integer only, must be a field number
input_values.append(v) # Append 'original_input' field number
elif (len(v) == 2): # Two integers, must be a column range
input_values.append([(v[0], v[1])]) # Append as a tuple
else:
inout.log_message('Wrong input component value: '+str(k) + \
' for "original_input" output field','err')
raise Exception()
def standard():
"""Main routine, open file, read lines, standardise them and write into file.
USAGE:
standard()
ARGUMENTS:
None
DESCRIPTION:
Main routine, see description of module above.
"""
# Process command line arguments and check for correctness - - - - - - - - -
#
if (len(config.options) < 2):
print '***** Error: %s needs at least three arguments:'% (sys.argv[0])
print '***** - Name of the project module'
print '***** - Number of the first record to be processed'
print '***** - Number of records to be processed'
print '***** plus options'
raise Exception()
first_rec = int(config.options[0])
num_rec = int(config.options[1])
in_file_name = config.in_file_name
out_file_name = config.out_file_name
# Check for optional arguments and process if any - - - - - - - - - - - - - -
#
config.verbose = 0 # Default: No verbose output
config.logging = 0 # Default: No logging into a file
write_header = 0 # Write header (output field names) to output file
# (default: Don't)
config.nowarn = 0 # Deactivate no warning flag (print/log warning messages)
if (len(config.options) > 2):
options = config.options[2:]
while (options != []): # Do a loop processing all options
if (options[0] == '-nowarn'):
config.nowarn = 1 # Activate no warning flag
options = options[1:] # Remove processed '-nowarn' option
elif (options[0] == '-v1'):
config.verbose = 1 # Set to verbose output level 1
options = options[1:] # Remove processed '-v1' option
elif (options[0] == '-v2'):
config.verbose = 2 # Set to verbose output level 2
options = options[1:] # Remove processed '-v2' option
elif (options[0] == '-l'):
config.logging = 1
if (len(options) > 1):
if (options[1][0] != '-'): # Not another option, must be a file name
config.log_file = options[1] # Get name of log file
options = options[1:] # Remove file_name
options = options[1:] # Remove processed -'l' option only
try:
f_log = open(config.log_file,'a') # Test if file is appendable
except:
print '***** Error ********************',
print '***** Cannot write to log file:', config.log_file
raise IOError()
# Write (append) header to log file
#
f_log.write(os.linesep)
f_log.write('##################################################')
f_log.write("############"+os.linesep)
f_log.write("#"+os.linesep)
f_log.write("# 'pyStandard.py - Version 0.1' process started at: ")
f_log.write(time.ctime(time.time())+os.linesep)
f_log.write("#"+os.linesep)
f_log.write("# Input file name: "+in_file_name+os.linesep)
f_log.write("# Output file name: "+out_file_name+os.linesep)
f_log.write(os.linesep)
f_log.close()
elif (options[0] == '-h'):
write_header = 1
options = options[1:] # Remove processed -'h' option
elif (options[0] == '-hmm-name'):
hmm_name_file = options[1] # Get file name of the name HMM to use
try:
f_in = open(hmm_name_file,'r') # Test if file is available
except:
print '***** Error ********************',
print '***** Cannot open HMM file in "-hmm-name" option:',
print hmm_name_file
raise IOError()
f_in.close()
options = options[2:] # Remove processed option and file name
config.name_standard_method = 'hmm'
config.name_hmm_file_name = hmm_name_file
config.name_hmm = simplehmm.hmm([],[]) # Create new empty HMM object
config.name_hmm.load_hmm(config.name_hmm_file_name)
elif (options[0] == '-hmm-loc'):
hmm_loc_file = options[1] # Get file name of the locality HMM to use
try:
f_in = open(hmm_loc_file,'r') # Test if file is available
except:
print '***** Error ********************',
print '***** Cannot open HMM file in "-hmm-loc" option:',
print hmm_loc_file
raise IOError()
f_in.close()
options = options[2:] # Remove processed option and file name
config.geoloc_standard_method == 'hmm'
config.geoloc_hmm_file_name = hmm_loc_file
config.geoloc_hmm = simplehmm.hmm([],[]) # Create new HMM object
config.geoloc_hmm.load_hmm(config.geoloc_hmm_file_name)
else:
print '***** Error: Illegal option:', options[0]
raise Exception()
# Open input file and check number of available records - - - - - - - - - - -
#
try:
f_in = open(in_file_name,'r')
except:
inout.log_message('Cannot open input file: '+in_file_name,'err')
raise IOError()
line_count = 0
for line in f_in.xreadlines():
line_count += 1
f_in.close()
if ((first_rec+num_rec) > line_count): # Illegal value for last record
print '***** Error: Illegal values for number of records to process:',
print num__rec, ', with start record:', start_rec
print '***** File only contains',line_count, 'lines/records'
raise Exception()
# Open files - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
#
try:
f_in = open(in_file_name,'r')
except:
inout.log_message('Cannot open input file: '+in_file_name,'err')
raise IOError()
try:
f_out = open(out_file_name,'w')
except:
inout.log_message('Cannot open output file: '+out_file_name,'err')
raise IOError()
# Write header (name of output fields) into output file - - - - - - - - - - -
#
if (write_header == 1):
header_dict = {}
for n in config.output_field_names:
header_dict.update({n:n}) # Dictionary where values are field names
header_line = inout.compose_line(header_dict,header=1)
f_out.write(header_line+os.linesep)
# Skip over records - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
#
if (first_rec > 0):
for i in range(first_rec):
f_in.readline()
# Read lines, process them and write into output files - - - - - - - - - - -
#
line_read = 0 # Number of read lines
while (line_read < num_rec): # Loop until 'num_rec' records processed
line = f_in.readline()
# Print process indicator message
#
if (config.proc_ind >= 0) and (line_read > 0): # Only print if activated
if (line_read % config.proc_ind == 0):
print 'Processed line', line_read, 'of', num_rec
line = line.strip() # Remove line separators
config.curr_line = line # Make a copy of the unprocessed current line
line = line.lower() # Make all characters lower case
inout.log_message(['Record '+str(line_read+first_rec)],'v1')
config.curr_line_no = line_read+first_rec # Store current line number
# Process line and extract content into components (name, geocode, etc.)
#
[name_comp, geocode_comp, locality_comp, date1_comp, date2_comp] = \
inout.process_line(line)
# Make a local empty working copy of the output field dictionary - - - - -
#
output_fields = config.output_field.copy()
output_fields_keys = output_fields.keys()
for k in output_fields_keys:
output_fields[k] = '' # Set all fields to an empty string
# Standardise name component - - - - - - - - - - - - - - - - - - - - - - -
#
if (type(name_comp) == types.ListType): # Givenname and surname separate
givenname_comp = name_comp[0].strip()
surname_comp = name_comp[1].strip()
if (givenname_comp != ''): # There is a givenname - - - - - - - - - - -
inout.log_message(' Givenname component: |'+givenname_comp+'|','v1')
givenname_comp = name.clean_name_component(givenname_comp)
[name_list, tag_list] = name.tag_name_component(givenname_comp)
output_fields['gender_guess'] = name.get_gender_guess(name_list, \
tag_list)
[name_list, tag_list, output_fields['title']] = \
name.get_title(name_list, tag_list)
[output_fields['givenname'], output_fields['alt_givenname']] = \
name.get_name_component(name_list, tag_list, 'gname')
if (surname_comp != ''): # There is a surname - - - - - - - - - - - - -
inout.log_message(' Surname component: |'+surname_comp+'|','v1')
surname_comp = name.clean_name_component(surname_comp)
[name_list, tag_list] = name.tag_name_component(surname_comp)
[output_fields['surname'], output_fields['alt_surname']] = \
name.get_name_component(name_list, tag_list, 'sname')
elif (name_comp.strip() != ''): # Given- and surname both in one field - -
inout.log_message(' Name component: |'+name_comp+'|','v1')
name_comp = name.clean_name_component(name_comp)
[name_list, tag_list] = name.tag_name_component(name_comp)
output_fields['gender_guess'] = name.get_gender_guess(name_list,tag_list)
[name_list, tag_list, output_fields['title']] = \
name.get_title(name_list, tag_list)
if (config.name_standard_method == 'rules'):
name_dict = name.get_names_rules(name_list, tag_list, 'gname')
elif (config.name_standard_method == 'hmm'):
name_dict = name.get_names_hmm(name_list, tag_list)
else:
inout.log_message('Illegal name standardisation method:'+ \
config.name_standard_method,'err')
raise Exception()
for (field,value) in name_dict.items(): # Assign to output dictionary
output_fields[field] = value
# Standardise geocode and locality components using HMM - - - - - - - - - -
#
if (config.geoloc_standard_method == 'hmm') and \
((geocode_comp.strip() != '') or (locality_comp.strip() != '')):
geoloc_comp = geocode_comp.strip()+' '+locality_comp.strip()
inout.log_message(' Geocode and locality component: |'+geoloc_comp+'|',\
'v1')
geoloc_comp = locality.clean_geoloc_component(geoloc_comp)
[geoloc_words, geoloc_tags] = locality.tag_geoloc_component(geoloc_comp)
if (geoloc_words != []): # Component not empty, do HMM standardisation
geoloc_dict = locality.get_geoloc_hmm(geoloc_words,geoloc_tags)
for (field,value) in geoloc_dict.items(): # Assign to output dictionary
output_fields[field] = value
# Standardise geocode component using rules - - - - - - - - - - - - - - - -
#
elif (config.geoloc_standard_method == 'rules') and \
(geocode_comp.strip() != ''):
inout.log_message(' Geocode component: |'+geocode_comp+'|','v1')
### TO BE DONE
inout.log_message('Rules based standardisation for geocode is' + \
'not implemented yet','err')
raise Exception()
# Standardise locality component using rules - - - - - - - - - - - - - - -
#
elif (config.geoloc_standard_method == 'rules') and \
(locality_comp.strip() != ''):
inout.log_message(' Locality component: |'+locality_comp+'|','v1')
### TO BE FINALISED
inout.log_message('Rules based standardisation for locality is' + \
'not implemented yet','err')
raise Exception()
# locality_comp = locality.clean_geoloc_component(locality_comp)
# [loc_words, loc_tags] = locality.tag_geoloc_component(locality_comp)
#
# [terr,loc_words2,loc_tags2] = locality.get_territory(loc_words,loc_tags)
# if (terr != ''):
# output_fields['territory'] = terr
#
# [pc,loc_words3,loc_tags3] = locality.get_postcode(loc_words2,loc_tags2)
# if (pc != ''):
# output_fields['postcode'] = pc
#
# [loc_name, loc_quali, loc_words4, loc_tags4] = \
# locality.get_localityname_qualifier(loc_words3, loc_tags3)
# if (loc_name != ''):
# output_fields['locality_name'] = loc_name
# if (loc_quali != ''):
# output_fields['locality_quali'] = loc_quali
#
# if (loc_words4 != []): # Not all words are standardised yet
# print ' # Remaining word list:', loc_words4 ###### TEST
# print ' # Remaining tag list: ', loc_tags4 ###### TEST
# Standardise date strings - - - - - - - - - - - - - - - - - - - - - - - -
#
if (date1_comp != ''):
inout.log_message(' Date1 component: |'+date1_comp+'|','v1')
[day1,month1,year1,status1] = date.parse_datestr(date1_comp)
if (day1 != -1):
output_fields['day1'] = str(day1)
if (month1 != -1):
output_fields['month1'] = str(month1)
if (year1 != -1):
output_fields['year1'] = str(year1)
if (date2_comp != ''):
inout.log_message(' Date2 component: |'+date2_comp+'|','v1')
[day2,month2,year2,status2] = date.parse_datestr(date2_comp)
if (day2 != -1):
output_fields['day2'] = str(day2)
if (month2 != -1):
output_fields['month2'] = str(month2)
if (year2 != -1):
output_fields['year2'] = str(year2)
# Create log message of output fields - - - - - - - - - - - - - - - - - - -
#
msg = [' Standardised record output fields:']
for (field,value) in output_fields.items():
if (value != '') and (value != []):
msg.append(' '+field+':'+str(value))
inout.log_message(msg,'v1')
# Save standardised record into output field
#
out_line = inout.compose_line(output_fields)
f_out.write(out_line+os.linesep)
# Increment line counter and go to beginning of loop - - - - - - - - - - -
#
line_read += 1
inout.log_message('','v1') # Print empty lines between records
# Close files - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
#
f_in.close()
f_out.close()
msg = ['','Number of warnings: '+str(config.num_warning), \
'Number of corrected word spillings: '+str(config.num_word_spills)]
inout.log_message(msg,'v1')
print msg[1]
print msg[2]
inout.log_message('End.','v1')
def standard():
"""Main routine, open file, read lines, standardise them and write into file.
USAGE:
standard()
ARGUMENTS:
None
DESCRIPTION:
Main routine, see description of module above.
"""
# Process command line arguments and check for correctness - - - - - - - - -
#
if (len(config.options) < 2):
print '***** Error: %s needs at least three arguments:' % (sys.argv[0])
print '***** - Name of the project module'
print '***** - Number of the first record to be processed'
print '***** - Number of records to be processed'
print '***** plus options'
raise Exception()
first_rec = int(config.options[0])
num_rec = int(config.options[1])
in_file_name = config.in_file_name
out_file_name = config.out_file_name
# Check for optional arguments and process if any - - - - - - - - - - - - - -
#
config.verbose = 0 # Default: No verbose output
config.logging = 0 # Default: No logging into a file
write_header = 0 # Write header (output field names) to output file
# (default: Don't)
config.nowarn = 0 # Deactivate no warning flag (print/log warning messages)
if (len(config.options) > 2):
options = config.options[2:]
while (options != []): # Do a loop processing all options
if (options[0] == '-nowarn'):
config.nowarn = 1 # Activate no warning flag
options = options[1:] # Remove processed '-nowarn' option
elif (options[0] == '-v1'):
config.verbose = 1 # Set to verbose output level 1
options = options[1:] # Remove processed '-v1' option
elif (options[0] == '-v2'):
config.verbose = 2 # Set to verbose output level 2
options = options[1:] # Remove processed '-v2' option
elif (options[0] == '-l'):
config.logging = 1
if (len(options) > 1):
if (options[1][0] !=
'-'): # Not another option, must be a file name
config.log_file = options[1] # Get name of log file
options = options[1:] # Remove file_name
options = options[1:] # Remove processed -'l' option only
try:
f_log = open(config.log_file,
'a') # Test if file is appendable
except:
print '***** Error ********************',
print '***** Cannot write to log file:', config.log_file
raise IOError()
# Write (append) header to log file
#
f_log.write(os.linesep)
f_log.write(
'##################################################')
f_log.write("############" + os.linesep)
f_log.write("#" + os.linesep)
f_log.write(
"# 'pyStandard.py - Version 0.1' process started at: ")
f_log.write(time.ctime(time.time()) + os.linesep)
f_log.write("#" + os.linesep)
f_log.write("# Input file name: " + in_file_name + os.linesep)
f_log.write("# Output file name: " + out_file_name +
os.linesep)
f_log.write(os.linesep)
f_log.close()
elif (options[0] == '-h'):
write_header = 1
options = options[1:] # Remove processed -'h' option
elif (options[0] == '-hmm-name'):
hmm_name_file = options[
1] # Get file name of the name HMM to use
try:
f_in = open(hmm_name_file,
'r') # Test if file is available
except:
print '***** Error ********************',
print '***** Cannot open HMM file in "-hmm-name" option:',
print hmm_name_file
raise IOError()
f_in.close()
options = options[2:] # Remove processed option and file name
config.name_standard_method = 'hmm'
config.name_hmm_file_name = hmm_name_file
config.name_hmm = simplehmm.hmm(
[], []) # Create new empty HMM object
config.name_hmm.load_hmm(config.name_hmm_file_name)
elif (options[0] == '-hmm-loc'):
hmm_loc_file = options[
1] # Get file name of the locality HMM to use
try:
f_in = open(hmm_loc_file, 'r') # Test if file is available
except:
print '***** Error ********************',
print '***** Cannot open HMM file in "-hmm-loc" option:',
print hmm_loc_file
raise IOError()
f_in.close()
options = options[2:] # Remove processed option and file name
config.geoloc_standard_method == 'hmm'
config.geoloc_hmm_file_name = hmm_loc_file
config.geoloc_hmm = simplehmm.hmm([],
[]) # Create new HMM object
config.geoloc_hmm.load_hmm(config.geoloc_hmm_file_name)
else:
print '***** Error: Illegal option:', options[0]
raise Exception()
# Open input file and check number of available records - - - - - - - - - - -
#
try:
f_in = open(in_file_name, 'r')
except:
inout.log_message('Cannot open input file: ' + in_file_name, 'err')
raise IOError()
line_count = 0
for line in f_in.xreadlines():
line_count += 1
f_in.close()
if ((first_rec + num_rec) > line_count): # Illegal value for last record
print '***** Error: Illegal values for number of records to process:',
print num__rec, ', with start record:', start_rec
print '***** File only contains', line_count, 'lines/records'
raise Exception()
# Open files - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
#
try:
f_in = open(in_file_name, 'r')
except:
inout.log_message('Cannot open input file: ' + in_file_name, 'err')
raise IOError()
try:
f_out = open(out_file_name, 'w')
except:
inout.log_message('Cannot open output file: ' + out_file_name, 'err')
raise IOError()
# Write header (name of output fields) into output file - - - - - - - - - - -
#
if (write_header == 1):
header_dict = {}
for n in config.output_field_names:
header_dict.update({n:
n}) # Dictionary where values are field names
header_line = inout.compose_line(header_dict, header=1)
f_out.write(header_line + os.linesep)
# Skip over records - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
#
if (first_rec > 0):
for i in range(first_rec):
f_in.readline()
# Read lines, process them and write into output files - - - - - - - - - - -
#
line_read = 0 # Number of read lines
while (line_read < num_rec): # Loop until 'num_rec' records processed
line = f_in.readline()
# Print process indicator message
#
if (config.proc_ind >= 0) and (line_read >
0): # Only print if activated
if (line_read % config.proc_ind == 0):
print 'Processed line', line_read, 'of', num_rec
line = line.strip() # Remove line separators
config.curr_line = line # Make a copy of the unprocessed current line
line = line.lower() # Make all characters lower case
inout.log_message(['Record ' + str(line_read + first_rec)], 'v1')
config.curr_line_no = line_read + first_rec # Store current line number
# Process line and extract content into components (name, geocode, etc.)
#
[name_comp, geocode_comp, locality_comp, date1_comp, date2_comp] = \
inout.process_line(line)
# Make a local empty working copy of the output field dictionary - - - - -
#
output_fields = config.output_field.copy()
output_fields_keys = output_fields.keys()
for k in output_fields_keys:
output_fields[k] = '' # Set all fields to an empty string
# Standardise name component - - - - - - - - - - - - - - - - - - - - - - -
#
if (type(name_comp) == types.ListType
): # Givenname and surname separate
givenname_comp = name_comp[0].strip()
surname_comp = name_comp[1].strip()
if (givenname_comp !=
''): # There is a givenname - - - - - - - - - - -
inout.log_message(
' Givenname component: |' + givenname_comp + '|', 'v1')
givenname_comp = name.clean_name_component(givenname_comp)
[name_list, tag_list] = name.tag_name_component(givenname_comp)
output_fields['gender_guess'] = name.get_gender_guess(name_list, \
tag_list)
[name_list, tag_list, output_fields['title']] = \
name.get_title(name_list, tag_list)
[output_fields['givenname'], output_fields['alt_givenname']] = \
name.get_name_component(name_list, tag_list, 'gname')
if (surname_comp !=
''): # There is a surname - - - - - - - - - - - - -
inout.log_message(
' Surname component: |' + surname_comp + '|', 'v1')
surname_comp = name.clean_name_component(surname_comp)
[name_list, tag_list] = name.tag_name_component(surname_comp)
[output_fields['surname'], output_fields['alt_surname']] = \
name.get_name_component(name_list, tag_list, 'sname')
elif (name_comp.strip() !=
''): # Given- and surname both in one field - -
inout.log_message(' Name component: |' + name_comp + '|', 'v1')
name_comp = name.clean_name_component(name_comp)
[name_list, tag_list] = name.tag_name_component(name_comp)
output_fields['gender_guess'] = name.get_gender_guess(
name_list, tag_list)
[name_list, tag_list, output_fields['title']] = \
name.get_title(name_list, tag_list)
if (config.name_standard_method == 'rules'):
name_dict = name.get_names_rules(name_list, tag_list, 'gname')
elif (config.name_standard_method == 'hmm'):
name_dict = name.get_names_hmm(name_list, tag_list)
else:
inout.log_message('Illegal name standardisation method:'+ \
config.name_standard_method,'err')
raise Exception()
for (field,
value) in name_dict.items(): # Assign to output dictionary
output_fields[field] = value
# Standardise geocode and locality components using HMM - - - - - - - - - -
#
if (config.geoloc_standard_method == 'hmm') and \
((geocode_comp.strip() != '') or (locality_comp.strip() != '')):
geoloc_comp = geocode_comp.strip() + ' ' + locality_comp.strip()
inout.log_message(' Geocode and locality component: |'+geoloc_comp+'|',\
'v1')
geoloc_comp = locality.clean_geoloc_component(geoloc_comp)
[geoloc_words,
geoloc_tags] = locality.tag_geoloc_component(geoloc_comp)
if (geoloc_words !=
[]): # Component not empty, do HMM standardisation
geoloc_dict = locality.get_geoloc_hmm(geoloc_words,
geoloc_tags)
for (field, value
) in geoloc_dict.items(): # Assign to output dictionary
output_fields[field] = value
# Standardise geocode component using rules - - - - - - - - - - - - - - - -
#
elif (config.geoloc_standard_method == 'rules') and \
(geocode_comp.strip() != ''):
inout.log_message(' Geocode component: |' + geocode_comp + '|',
'v1')
### TO BE DONE
inout.log_message('Rules based standardisation for geocode is' + \
'not implemented yet','err')
raise Exception()
# Standardise locality component using rules - - - - - - - - - - - - - - -
#
elif (config.geoloc_standard_method == 'rules') and \
(locality_comp.strip() != ''):
inout.log_message(' Locality component: |' + locality_comp + '|',
'v1')
### TO BE FINALISED
inout.log_message('Rules based standardisation for locality is' + \
'not implemented yet','err')
raise Exception()
# locality_comp = locality.clean_geoloc_component(locality_comp)
# [loc_words, loc_tags] = locality.tag_geoloc_component(locality_comp)
#
# [terr,loc_words2,loc_tags2] = locality.get_territory(loc_words,loc_tags)
# if (terr != ''):
# output_fields['territory'] = terr
#
# [pc,loc_words3,loc_tags3] = locality.get_postcode(loc_words2,loc_tags2)
# if (pc != ''):
# output_fields['postcode'] = pc
#
# [loc_name, loc_quali, loc_words4, loc_tags4] = \
# locality.get_localityname_qualifier(loc_words3, loc_tags3)
# if (loc_name != ''):
# output_fields['locality_name'] = loc_name
# if (loc_quali != ''):
# output_fields['locality_quali'] = loc_quali
#
# if (loc_words4 != []): # Not all words are standardised yet
# print ' # Remaining word list:', loc_words4 ###### TEST
# print ' # Remaining tag list: ', loc_tags4 ###### TEST
# Standardise date strings - - - - - - - - - - - - - - - - - - - - - - - -
#
if (date1_comp != ''):
inout.log_message(' Date1 component: |' + date1_comp + '|', 'v1')
[day1, month1, year1, status1] = date.parse_datestr(date1_comp)
if (day1 != -1):
output_fields['day1'] = str(day1)
if (month1 != -1):
output_fields['month1'] = str(month1)
if (year1 != -1):
output_fields['year1'] = str(year1)
if (date2_comp != ''):
inout.log_message(' Date2 component: |' + date2_comp + '|', 'v1')
[day2, month2, year2, status2] = date.parse_datestr(date2_comp)
if (day2 != -1):
output_fields['day2'] = str(day2)
if (month2 != -1):
output_fields['month2'] = str(month2)
if (year2 != -1):
output_fields['year2'] = str(year2)
# Create log message of output fields - - - - - - - - - - - - - - - - - - -
#
msg = [' Standardised record output fields:']
for (field, value) in output_fields.items():
if (value != '') and (value != []):
msg.append(' ' + field + ':' + str(value))
inout.log_message(msg, 'v1')
# Save standardised record into output field
#
out_line = inout.compose_line(output_fields)
f_out.write(out_line + os.linesep)
# Increment line counter and go to beginning of loop - - - - - - - - - - -
#
line_read += 1
inout.log_message('', 'v1') # Print empty lines between records
# Close files - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
#
f_in.close()
f_out.close()
msg = ['','Number of warnings: '+str(config.num_warning), \
'Number of corrected word spillings: '+str(config.num_word_spills)]
inout.log_message(msg, 'v1')
print msg[1]
print msg[2]
inout.log_message('End.', 'v1')
