def _draw_af_hist_(path, records_filter = allow_all_filter):
"""Draws histogram of authorship."""
af_count = {} #dict{author: count}
for i,record in enumerate(zbl_io.read_zbl_records(open(path))):
if i%100000 == 0: print i," records considered" #progress bar
if not record.has_key("af") or not records_filter(record):
continue
afs = zbl_io.unpack_multivalue_field(record["af"])
afs_ok = list( af for af in afs if af!='-' )
for af in afs_ok:
af_count[af] = af_count.get(af, 0) + 1
print len(af_count), " authors found."
print max(af_count.values()), " = max"
print min(af_count.values()), " = min"
avg_af_values = avg(af_count.values())
print round(avg_af_values, 2), " = avg"
print round(std(af_count.values()), 2), " = std"
print sum(1 for af in af_count.values() if af > avg_af_values) , " authors above avg"
print sum(1 for af in af_count.values() if af < avg_af_values) , " authors below avg"
n, bins, patches = plt.hist(af_count.values(), bins = max(af_count.values()), normed=False, log=True, alpha=0.75)
plt.xlabel("Liczba wystapien w rekordach")
plt.ylabel("Liczba autorow")
plt.show()
def _draw_af_hist_(path, records_filter=allow_all_filter):
"""Draws histogram of authorship."""
af_count = {} #dict{author: count}
for i, record in enumerate(zbl_io.read_zbl_records(open(path))):
if i % 100000 == 0: print i, " records considered" #progress bar
if not record.has_key("af") or not records_filter(record):
continue
afs = zbl_io.unpack_multivalue_field(record["af"])
afs_ok = list(af for af in afs if af != '-')
for af in afs_ok:
af_count[af] = af_count.get(af, 0) + 1
print len(af_count), " authors found."
print max(af_count.values()), " = max"
print min(af_count.values()), " = min"
avg_af_values = avg(af_count.values())
print round(avg_af_values, 2), " = avg"
print round(std(af_count.values()), 2), " = std"
print sum(1 for af in af_count.values()
if af > avg_af_values), " authors above avg"
print sum(1 for af in af_count.values()
if af < avg_af_values), " authors below avg"
n, bins, patches = plt.hist(af_count.values(),
bins=max(af_count.values()),
normed=False,
log=True,
alpha=0.75)
plt.xlabel("Liczba wystapien w rekordach")
plt.ylabel("Liczba autorow")
plt.show()
def _report_af_quality_(path, records_filter=allow_all_filter):
"""Prints report about authors' identities quality."""
afs_len = []
afs_ok_len = []
for i, record in enumerate(zbl_io.read_zbl_records(open(path))):
if i % 100000 == 0: print i, " records considered" #progress bar
if not record.has_key("af") or not records_filter(record):
continue
afs = zbl_io.unpack_multivalue_field(record["af"])
afs_ok = list(af for af in afs if af != '-')
afs_len.append(len(afs))
afs_ok_len.append(len(afs_ok))
afs_ok_frac = list(
float(m) / float(l) for m, l in zip(afs_ok_len, afs_len))
print max(afs_len), "\n", round(avg(afs_len),
2), "\n", round(std(afs_len), 2)
print max(afs_ok_len), "\n", round(avg(afs_ok_len),
2), "\n", round(std(afs_ok_len), 2)
print round(max(afs_ok_frac),
2), "\n", round(avg(afs_ok_frac),
2), "\n", round(std(afs_ok_frac), 2)
def extract_fieldvalue2ids(zbl_generator, multivalue_field_name = "af", empty_value = "-", container = list):
"""Returns dictionary{field-value: container-of-identified-ids-that-have-this-value}.
>>> r1 = {'an':'1', 'af': zbl_io.pack_multivalue_field(['a1','-','a2']) }
>>> r2 = {'an':'2', 'af': zbl_io.pack_multivalue_field(['-','a2','a1']) }
>>> r3 = {'an':'3', 'af': zbl_io.pack_multivalue_field(['a3', '-']) }
>>> r4 = {'an':'4', 'af': zbl_io.pack_multivalue_field(['a3', '-', 'a2'])}
>>> sorted(list(extract_fieldvalue2ids([r1,r2,r3]).iteritems()))
[('a1', ['1', '2']), ('a2', ['1', '2']), ('a3', ['3'])]
>>> sorted(list(extract_fieldvalue2ids([r1,r2,r3,r4]).iteritems()))
[('a1', ['1', '2']), ('a2', ['1', '2', '4']), ('a3', ['3', '4'])]
"""
af2ids = {}
skipped = 0
novals = 0
for i,zbl in enumerate(zbl_generator):
if i%10000==0: logging.info("[extract_fieldvalue2ids]"+str(i)+" records processed")
if not multivalue_field_name in zbl:
skipped = skipped + 1
continue
zbl_id = zbl[zbl_io.ZBL_ID_FIELD]
afs = zbl_io.unpack_multivalue_field(zbl[multivalue_field_name])
afs_ok = list(af for af in afs if af!=empty_value)
if len(afs_ok)==0: novals = novals + 1
for af in afs_ok:
af2ids[af] = af2ids.get(af, []) + [zbl_id]
logging.info("[extract_fieldvalue2ids] "+str(i)+" records processed")
logging.info("[extract_fieldvalue2ids] "+str(skipped)+" records skipped")
logging.info("[extract_fieldvalue2ids] "+str(novals)+" records with only empty values in field")
fv2ids = dict( (id,container(ids)) for id,ids in af2ids.iteritems())
logging.info("[extract_fieldvalue2ids] "+str(len(fv2ids))+" authors found.")
return fv2ids
def update(self, zbl_generator, \
msc_predicate = lambda msc: MSC_ORDINARY_LEAF_PATTERN_RE.match(msc)):
logging.info("[MscModel.update] building msc2lists")
for zbl in zbl_generator:############
msc_codes = zbl_io.unpack_multivalue_field(zbl['mc'])
zbl_id = zbl[zbl_io.ZBL_ID_FIELD]
_update_(self.msc2zblidlist, msc_codes, zbl_id, msc_predicate)
_update_(self.mscprim2zblidlist, msc_codes[:1], zbl_id, msc_predicate)
_update_(self.mscsec2zblidlist, msc_codes[1:], zbl_id, msc_predicate)
self._update_counts_()
def count_msc_occurences(file, records_filter=lambda x: True, field_name="mc"):
"""Counts number of occurrences of MSC codes in ZBL file.
Returns dictionary{code_name: count}"""
counts = {}
for record in zbl_io.read_zbl_records(file):
if not records_filter(record) or not record.has_key(field_name):
continue
codes = zbl_io.unpack_multivalue_field(record[field_name])
for code in codes:
counts[code] = counts.get(code, 0) + 1
return counts
def update(self, zbl_generator, \
msc_predicate = lambda msc: MSC_ORDINARY_LEAF_PATTERN_RE.match(msc)):
logging.info("[MscModel.update] building msc2lists")
for zbl in zbl_generator: ############
msc_codes = zbl_io.unpack_multivalue_field(zbl['mc'])
zbl_id = zbl[zbl_io.ZBL_ID_FIELD]
_update_(self.msc2zblidlist, msc_codes, zbl_id, msc_predicate)
_update_(self.mscprim2zblidlist, msc_codes[:1], zbl_id,
msc_predicate)
_update_(self.mscsec2zblidlist, msc_codes[1:], zbl_id,
msc_predicate)
self._update_counts_()
def count_msc_occurences(file, records_filter = lambda x: True, field_name = "mc"):
"""Counts number of occurrences of MSC codes in ZBL file.
Returns dictionary{code_name: count}"""
counts = {}
for record in zbl_io.read_zbl_records(file):
if not records_filter(record) or not record.has_key(field_name):
continue
codes = zbl_io.unpack_multivalue_field(record[field_name])
for code in codes:
counts[code] = counts.get(code, 0) + 1
return counts
def group_zbl_by_msc(zbl_generator, \
msc_primary_predicate = lambda mscprim: MSC_ORDINARY_LEAF_PATTERN_RE.match(mscprim), \
zbl_extract = lambda zbl: zbl[zbl_io.ZBL_ID_FIELD]):
"""Returns dictionary{msc-primary-code: list-of-extracted-by-zbl_extract(zbl)-values}.
When msc_primary_predicate(msc_primary_code)==False record will be skipped.
"""
msc2zbllist = {}
for zbl in zbl_generator:
msc_primary_code = zbl_io.unpack_multivalue_field(zbl['mc'])[0]
if not msc_primary_predicate(msc_primary_code): continue
zbllist = msc2zbllist.get(msc_primary_code, [])
zbllist.append( zbl_extract(zbl) )
msc2zbllist[msc_primary_code] = zbllist
return msc2zbllist
def group_zbl_by_msc(zbl_generator, \
msc_primary_predicate = lambda mscprim: MSC_ORDINARY_LEAF_PATTERN_RE.match(mscprim), \
zbl_extract = lambda zbl: zbl[zbl_io.ZBL_ID_FIELD]):
"""Returns dictionary{msc-primary-code: list-of-extracted-by-zbl_extract(zbl)-values}.
When msc_primary_predicate(msc_primary_code)==False record will be skipped.
"""
msc2zbllist = {}
for zbl in zbl_generator:
msc_primary_code = zbl_io.unpack_multivalue_field(zbl['mc'])[0]
if not msc_primary_predicate(msc_primary_code): continue
zbllist = msc2zbllist.get(msc_primary_code, [])
zbllist.append(zbl_extract(zbl))
msc2zbllist[msc_primary_code] = zbllist
return msc2zbllist
def _draw_mc_hist(path, records_filter = allow_all_filter):
"""Draws histogram of MSC codes occurrence in records."""
mc_counts = []
for i,record in enumerate(zbl_io.read_zbl_records(open(path))):
if i%100000 == 0: print i," records considered" #progress bar
if not record.has_key("mc") or not records_filter(record):
continue
mc = zbl_io.unpack_multivalue_field(record["mc"])
mc_counts.append(len(mc))
print len(mc_counts), " record found."
print max(mc_counts), " = max"
print min(mc_counts), " = min"
print round(avg(mc_counts), 2), " = avg"
print round(std(mc_counts), 2), " = std"
n, bins, patches = plt.hist(mc_counts, bins = max(mc_counts), normed=False, alpha=0.75)
plt.xlabel("Liczba kodow MSC w rekordzie")
plt.ylabel("Liczba rekordow")
plt.show()
def _report_af_quality_(path, records_filter = allow_all_filter):
"""Prints report about authors' identities quality."""
afs_len = []
afs_ok_len = []
for i,record in enumerate(zbl_io.read_zbl_records(open(path))):
if i%100000 == 0: print i," records considered" #progress bar
if not record.has_key("af") or not records_filter(record):
continue
afs = zbl_io.unpack_multivalue_field(record["af"])
afs_ok = list( af for af in afs if af!='-' )
afs_len.append(len(afs))
afs_ok_len.append(len(afs_ok))
afs_ok_frac = list( float(m)/float(l) for m,l in zip(afs_ok_len, afs_len) )
print max(afs_len), "\n", round(avg(afs_len),2), "\n", round(std(afs_len),2)
print max(afs_ok_len), "\n", round(avg(afs_ok_len),2), "\n", round(std(afs_ok_len),2)
print round(max(afs_ok_frac),2), "\n", round(avg(afs_ok_frac),2), "\n", round(std(afs_ok_frac),2)
def extract_fieldvalue2ids(zbl_generator,
multivalue_field_name="af",
empty_value="-",
container=list):
"""Returns dictionary{field-value: container-of-identified-ids-that-have-this-value}.
>>> r1 = {'an':'1', 'af': zbl_io.pack_multivalue_field(['a1','-','a2']) }
>>> r2 = {'an':'2', 'af': zbl_io.pack_multivalue_field(['-','a2','a1']) }
>>> r3 = {'an':'3', 'af': zbl_io.pack_multivalue_field(['a3', '-']) }
>>> r4 = {'an':'4', 'af': zbl_io.pack_multivalue_field(['a3', '-', 'a2'])}
>>> sorted(list(extract_fieldvalue2ids([r1,r2,r3]).iteritems()))
[('a1', ['1', '2']), ('a2', ['1', '2']), ('a3', ['3'])]
>>> sorted(list(extract_fieldvalue2ids([r1,r2,r3,r4]).iteritems()))
[('a1', ['1', '2']), ('a2', ['1', '2', '4']), ('a3', ['3', '4'])]
"""
af2ids = {}
skipped = 0
novals = 0
for i, zbl in enumerate(zbl_generator):
if i % 10000 == 0:
logging.info("[extract_fieldvalue2ids]" + str(i) +
" records processed")
if not multivalue_field_name in zbl:
skipped = skipped + 1
continue
zbl_id = zbl[zbl_io.ZBL_ID_FIELD]
afs = zbl_io.unpack_multivalue_field(zbl[multivalue_field_name])
afs_ok = list(af for af in afs if af != empty_value)
if len(afs_ok) == 0: novals = novals + 1
for af in afs_ok:
af2ids[af] = af2ids.get(af, []) + [zbl_id]
logging.info("[extract_fieldvalue2ids] " + str(i) + " records processed")
logging.info("[extract_fieldvalue2ids] " + str(skipped) +
" records skipped")
logging.info("[extract_fieldvalue2ids] " + str(novals) +
" records with only empty values in field")
fv2ids = dict((id, container(ids)) for id, ids in af2ids.iteritems())
logging.info("[extract_fieldvalue2ids] " + str(len(fv2ids)) +
" authors found.")
return fv2ids
def _draw_mc_hist(path, records_filter=allow_all_filter):
"""Draws histogram of MSC codes occurrence in records."""
mc_counts = []
for i, record in enumerate(zbl_io.read_zbl_records(open(path))):
if i % 100000 == 0: print i, " records considered" #progress bar
if not record.has_key("mc") or not records_filter(record):
continue
mc = zbl_io.unpack_multivalue_field(record["mc"])
mc_counts.append(len(mc))
print len(mc_counts), " record found."
print max(mc_counts), " = max"
print min(mc_counts), " = min"
print round(avg(mc_counts), 2), " = avg"
print round(std(mc_counts), 2), " = std"
n, bins, patches = plt.hist(mc_counts,
bins=max(mc_counts),
normed=False,
alpha=0.75)
plt.xlabel("Liczba kodow MSC w rekordzie")
plt.ylabel("Liczba rekordow")
plt.show()
def _update_docmodel_(zbl):
if not "mc" in zbl: return
docid = zbl[zbl_io.ZBL_ID_FIELD]
msc_codes = zbl_io.unpack_multivalue_field(zbl['mc'])
docid2primcode[docid] = msc_codes[0]
docid2seccodes[docid] = msc_codes[1:]
def _update_docmodel_(zbl):
if not "mc" in zbl: return
docid = zbl[zbl_io.ZBL_ID_FIELD]
msc_codes = zbl_io.unpack_multivalue_field(zbl['mc'])
docid2primcode[docid] = msc_codes[0]
docid2seccodes[docid] = msc_codes[1:]
except:
print "First argument expected: zbl-file-path."
sys.exit(-1)
#l - low level, m - medium level, h - highest level of MSC tree
print "MIN_COUNT_MSC=",MIN_COUNT_MSC
print "NUM_TRIES=",NUM_TRIES
print "VALID_LEAF_PATTERN_RE=",VALID_LEAF_PATTERN_RE
print "must_have_fields=",must_have_fields
print "zbl_path=",zbl_path
print "Building list of msc-primary-codes that should be considered..."
start = time.clock()
msc2count = {}
for i,zbl in enumerate(_get_zbl_generator_(zbl_path, must_have_fields)):
if i%10000 == 0: print "",i,"records processed in",(time.clock()-start),"s ->",sum(msc2count.values()),"kept"
msc_codes = [ zbl_io.unpack_multivalue_field(zbl['mc'])[0] ] #only primary
for msc in msc_codes:
#print msc,"->",(not VALID_LEAF_PATTERN_RE.match(msc) is None)
if not VALID_LEAF_PATTERN_RE.match(msc) is None:
msc2count[msc] = msc2count.get(msc, 0)+1
print "Filtering for with MIN_COUNT_MSC:",MIN_COUNT_MSC," out of", sum(msc2count.values())
msc2count = dict((msc,count) for msc,count in msc2count.iteritems() if count>=MIN_COUNT_MSC)
print "Building mapping msc2ix"
msc2ix = dict((msc,ix) for ix,msc in enumerate(msc2count))
ix2msc = dict((ix,msc) for msc,ix in msc2ix.iteritems())
leaves = list( msc2ix )
num_leaves = len(leaves)
print "Building MSC tree out of", num_leaves, "leaves"
msc_tree = trees.build_msctree(msc2ix.keys(), msc2ix)
#print str(trees.map_tree_leaves(msc_tree, ix2msc))[:400]