def __init__(self):
bh = BackupHandler(
relative_path('experimental/code_suggest/output/backup'))
elem_counts = bh.load('elem_pyplot_counts_0404')
self.all_elems = set(elem_counts.keys())
self.all_elem_counts = elem_counts
self.enormer = ElementNormalizer()
def __init__(self):
plot_commands = get_plot_commands()
pyplot_fu = get_pyplot_fu()
self.plot_commands = plot_commands
self.nonplot_commands = [
f for f in pyplot_fu.keys() if not f in plot_commands
]
print 'CodeSuggest: extracted %d plot commands' % len(plot_commands)
# Load all code examples of plotting commands from db into memory
# These are generated by index_examples.py
print 'CodeSuggest: Loading code examples and pregenerated SVGs...'
db = sqlite3.connect(relative_path('demo/data/code.sqlite3'))
cursor = db.cursor()
cursor.execute("SELECT func_id, code, svg FROM example")
code_example_lookup = {} # [func_id] = [(code, svg)]
count_code_examples = 0
for func_id, code, svg in cursor.fetchall():
count_code_examples += 1
if not func_id in code_example_lookup:
code_example_lookup[func_id] = []
code_example_lookup[func_id].append({'code': code, 'svg': svg})
# Sort it again
for func_id in code_example_lookup:
code_example_lookup[func_id] = sorted(
code_example_lookup[func_id],
key=lambda x: get_effective_code_len(x['code']))
self.code_example_lookup = code_example_lookup
print 'CodeSuggest: Loaded %d code examples (with svgs)...' % count_code_examples
db.close()
# Load element_index generated by experimental/code_suggest/mine_argvs.py
# bh = BackupHandler(relative_path('demo/data'))
# self.element_index = bh.load('element_index')
# print 'Loaded element_index with %d keys'%len(self.element_index)
# Load element value counts
bh2 = BackupHandler(
relative_path('experimental/code_suggest/output/backup'))
self.elem_val_counts = bh2.load(
'elem_pyplot_value_counts_0404') # [elem][val] = count
for elem_id in self.elem_val_counts:
self.elem_val_counts[elem_id] = sorted(
self.elem_val_counts[elem_id].items(), key=lambda x: -x[1])
self.func_position_finder = FuncPositionFinder()
def __init__(self):
plot_commands = get_plot_commands()
pyplot_fu = get_pyplot_fu()
self.plot_commands = plot_commands
self.nonplot_commands = [f for f in pyplot_fu.keys() if not f in plot_commands]
print 'CodeSuggest: extracted %d plot commands'%len(plot_commands)
# Load all code examples of plotting commands from db into memory
# These are generated by index_examples.py
print 'CodeSuggest: Loading code examples and pregenerated SVGs...'
db = sqlite3.connect(relative_path('demo/data/code.sqlite3'))
cursor = db.cursor()
cursor.execute("SELECT func_id, code, svg FROM example")
code_example_lookup = {} # [func_id] = [(code, svg)]
count_code_examples = 0
for func_id, code, svg in cursor.fetchall():
count_code_examples += 1
if not func_id in code_example_lookup:
code_example_lookup[func_id] = []
code_example_lookup[func_id].append({'code': code, 'svg':svg})
# Sort it again
for func_id in code_example_lookup:
code_example_lookup[func_id] = sorted(
code_example_lookup[func_id],
key=lambda x:get_effective_code_len(x['code']))
self.code_example_lookup = code_example_lookup
print 'CodeSuggest: Loaded %d code examples (with svgs)...'%count_code_examples
db.close()
# Load element_index generated by experimental/code_suggest/mine_argvs.py
# bh = BackupHandler(relative_path('demo/data'))
# self.element_index = bh.load('element_index')
# print 'Loaded element_index with %d keys'%len(self.element_index)
# Load element value counts
bh2 = BackupHandler(relative_path('experimental/code_suggest/output/backup'))
self.elem_val_counts = bh2.load('elem_pyplot_value_counts_0404') # [elem][val] = count
for elem_id in self.elem_val_counts:
self.elem_val_counts[elem_id] = sorted(
self.elem_val_counts[elem_id].items(), key=lambda x:-x[1])
self.func_position_finder = FuncPositionFinder()
def code_examples():
"""
Yield code examples.
"""
global all_codes1, all_codes2, all_codes3
# 15770 code examples mined from SO answers in threads that are tagged
# "matplotlib".
if not all_codes1:
print 'Loading SO code examples...'
bh1 = BackupHandler(relative_path('experimental/code_suggest'))
all_codes1 = bh1.load('all_codes')
print '%d examples from SO'%len(all_codes1)
for code in all_codes1:
yield code
# print 'WARNING: mine_element.py ignoring all GitHub code examples...'
# """
if not all_codes2:
# 8732 code examples (including 395 IPython Notebook files) mined from
# GitHub repositories that contain "matplotlib".
print 'Loading GitHub code examples...'
bh2 = BackupHandler(relative_path('experimental/code_suggest/output/backup'))
all_codes2 = bh2.load('all_codes_github_1k_repo_0322')
print '%d examples from GitHub'%len(all_codes2)
for code in all_codes2:
yield code
# """
if not all_codes3:
# 21993 code examples extracted by Shiyan from the Web
print 'Loading Web code examples'
bh3 = BackupHandler(relative_path('experimental/mining/output'))
all_codes3 = bh3.load('codes_shiyan_0331_web')
print '%d examples from Web Shiyan'%len(all_codes3)
for code in all_codes3:
yield code
def __init__(self):
bh = BackupHandler(relative_path('experimental/code_suggest/output/backup'))
elem_counts = bh.load('elem_pyplot_counts_0404')
self.all_elems = set(elem_counts.keys())
self.all_elem_counts = elem_counts
self.enormer = ElementNormalizer()
from codemend.models.extract_so_code import load_threads, Thread, Answer
from codemend import BackupHandler, relative_path
if __name__ == '__main__':
bh_dir = relative_path('models/output/backup')
bh = BackupHandler(bh_dir)
try:
threads = bh.load('mpl_threads')
except AssertionError:
threads = list(load_threads(
qfilter="Tags LIKE '%<matplotlib>%' AND AnswerCount > 0 AND Score >= 0",
afilter="Score >= 0 ORDER BY Score DESC LIMIT 3"))
bh.save('mpl_threads', threads)
with open(relative_path('models/output/mpl_so_titles.txt'), 'w') as writer:
for t in threads:
writer.write('%d\t%s\n'%(t.qid, t.qtitle.encode('utf-8')))
# Step 1:
# Copied from annotate_code_with_api.py
with open('../../models/output/mpl_code_blocks.txt') as reader:
content = reader.read()
content = content.decode('utf-8')
content = content.replace("<", "<")
content = content.replace(">", ">")
content = content.replace("&", "&")
sompl_blocks = content.split('\n\n\n') # stackoverflow matplotlib code blocks
print 'There are %d code examples from mpl stackoverflow'%len(sompl_blocks)
# Step 2:
bh = BackupHandler('.')
cookbook_segs = bh.load('cookbook_segs')
cookbook_blocks = []
for tag, p in cookbook_segs:
if tag == 'CODE':
cookbook_blocks.append(p)
print 'There are %d code examples from matplotlib cookbook'%len(cookbook_blocks)
all_codes = sompl_blocks + cookbook_blocks
print 'There are %d code blocks in total'%(len(all_codes))
# Step 3:
counters = {}
counter_names = ['syntax_errors', 'unsafes', 'timeouts', 'exec_errors',
elem_counts[f, a, v] += 1
return is_useful
if __name__ == '__main__':
counters = defaultdict(int)
md5s = set()
all_codes = []
fu, _ = get_fu_fau()
elem_counts = defaultdict(int) # [elem] = count
bh = BackupHandler(
relative_path('experimental/code_suggest/output/backup'))
for root, dirs, files in os.walk(
relative_path('mining/output/github-matplotlib-repos')):
if '.git' in root: continue
for file_name in files:
counters['count_file'] += 1
if counters['count_file'] % 1000 == 0:
print 'Processed %d files - Useful files: %d' % (
counters['count_file'], counters['count_useful_files'])
file_path = os.path.join(root, file_name)
from codemend.models.extract_so_code import load_threads, Thread, Answer
from codemend import BackupHandler, relative_path
if __name__ == '__main__':
bh_dir = relative_path('models/output/backup')
bh = BackupHandler(bh_dir)
try:
threads = bh.load('mpl_threads')
except AssertionError:
threads = list(
load_threads(
qfilter=
"Tags LIKE '%<matplotlib>%' AND AnswerCount > 0 AND Score >= 0",
afilter="Score >= 0 ORDER BY Score DESC LIMIT 3"))
bh.save('mpl_threads', threads)
with open(relative_path('models/output/mpl_so_titles.txt'), 'w') as writer:
for t in threads:
writer.write('%d\t%s\n' % (t.qid, t.qtitle.encode('utf-8')))
example also has its corresponding generated SVGs.
The table is like this:
(func_id, code, svg)
There are at most 20 (shortest) examples per func_id.
"""
import sqlite3
from codemend import BackupHandler, relative_path
if __name__ == '__main__':
print 'Reading SVGs and code examples. Takes 7.3 seconds...'
bh = BackupHandler('.')
svgs = bh.load('svgs')
all_codes = bh.load('all_codes')
plotcommands_examples = bh.load(
'plotcommands_examples') # [plot_command] = [example_idx]
db = sqlite3.connect(relative_path('demo/data/code.sqlite3'))
cursor = db.cursor()
cursor.executescript("""
DROP TABLE IF EXISTS example;
CREATE TABLE example (
func_id TEXT NOT NULL,
code TEXT NOT NULL,
svg TEXT
called.
- #3: Not recommending elements that occur too infrequently.
- #4: When a function is not used before, and its argv is recommended, we strip
the "@", and recommend the function first, followed by the argv. e.g.
[pie@0, pie] => [pie, pie@0].
"""
from codemend import BackupHandler, relative_path
from codemend.demo.code_suggest import get_plot_commands
from codemend.models.baseline2 import SuggestItem
plot_commands = get_plot_commands()
plot_commands_set = set(plot_commands)
bh = BackupHandler(relative_path('experimental/code_suggest/output/backup'))
elem_counts = bh.load('elem_pyplot_counts_0404')
def prune(used_elems, suggest_elems):
for elem in used_elems:
assert isinstance(elem, basestring)
for elem in suggest_elems:
assert isinstance(elem, SuggestItem), type(elem)
used_elems_set = set(used_elems)
used_funcs = map(get_func_name, used_elems)
used_funcs_set = set(used_funcs)
has_used_plot_commands = any(
map(lambda x: x in plot_commands_set, used_funcs))
def __init__(self):
bh = BackupHandler(relative_path('demo/data'))
self.pos_ave = bh.load('pos_ave')
print 'FuncPositionFinder: loaded %d average positions for functions'%len(self.pos_ave)
def __init__(self, w2v_model, all_elem_counts, maxngram=1,
name=None, use_lemma=True,
heuristic=False, use_coke=False):
"""
w2v_model can be a binary vectors file, or a loaded gensim model instance.
"""
self.maxngram = maxngram
self.name = name
self.use_lemma = use_lemma
assert isinstance(all_elem_counts, dict)
self.all_elem_counts = all_elem_counts
self.heuristic = heuristic
self.use_coke = use_coke
if isinstance(w2v_model, basestring):
self.model = load_gensim_from_binary_file(w2v_model)
self.model.filename = w2v_model.split('/')[-1]
if not self.name:
self.name = self.model.filename
else:
assert isinstance(w2v_model, Word2Vec)
self.model = w2v_model
if not self.name:
if hasattr(self.model, 'filename'):
self.name = self.model.filename
self.model.init_sims() # normalize the vectors
self.enormer = ElementNormalizer()
if self.use_coke:
bh = BackupHandler(relative_path('models/output/backup'))
coke_file = 'coke_0329'
if not bh.exists(coke_file):
raise ValueError('Coke file does not exist: %s'%coke_file)
self.coke = bh.load(coke_file)
print 'Trying to load element indexes from cache ...'
bh = BackupHandler(relative_path('models/output/backup'))
elem_index_backup_name = self.model.filename + '_elem_index'
if bh.exists(elem_index_backup_name):
self.idfs, self.elems, self.elem_lookup, self.vecmat = bh.load(elem_index_backup_name)
else:
print 'Word2vecBaseline building element indexes...'
fu, fau = get_fu_fau()
self.idfs = self.get_idf(fu.values() + fau.values())
self.elems = sorted(self.all_elem_counts.keys())
self.elem_lookup = dict((y,x) for (x,y) in enumerate(self.elems))
vecs = []
for e in self.elems:
u = doc_serve.get_training_doc(e, True)
v = self.get_bow_representation(u)
vecs.append(v)
self.vecmat = np.array(vecs)
assert self.vecmat.shape == (len(self.elems), self.model.vector_size)
bh.save(elem_index_backup_name, (self.idfs, self.elems, self.elem_lookup, self.vecmat))
print 'Finished building indexes.'
train_pairs.append((merged_utter, astunparse.unparse(call_node)))
unique_train_pairs = list(set(train_pairs))
print 'total_block', total_block
print 'total_grammatical', total_grammatical
print 'total_call_nodes', total_call_nodes
print 'total_matched_funcs', total_matched_funcs, '(total train pairs)'
print 'total_matched_args', total_matched_args
print 'total_unique_train_pairs', len(unique_train_pairs)
return unique_train_pairs
if __name__ == '__main__':
bh = BackupHandler(relative_path('models/output/backup'))
# Step 1
fu, fau = get_fu_fau()
# Step 2
with open(relative_path('models/output/mpl_code_blocks.txt')) as reader:
content = reader.read()
content = content.decode('utf-8')
content = content.replace("<", "<")
content = content.replace(">", ">")
content = content.replace("&", "&")
blocks = content.split('\n\n\n')
def get_effective_code_len(code):
"""
Number of characters in a code example. Not counting lines with "import"
"""
lines = code.split('\n')
lines = filter(lambda x: 'import' not in x.split(), lines)
return len('\n'.join(lines))
if __name__ == '__main__':
print 'Reading SVGs and code examples. Takes 7.3 seconds...'
bh = BackupHandler('.')
svgs = bh.load('svgs')
all_codes = bh.load('all_codes')
print 'Loading functions that are plotting commands'
# Copied from code_suggest.py
import csv
import pattern.en
# Load csv file of pyplot summary
pyplot_fu = {} # [func] = utter
print 'CodeSuggest: Loading pyplot fu...'
with open('../../docstring_parse/pyplot_fu.csv', 'rb') as csvfile:
reader = csv.reader(csvfile)
def __init__(self,
w2v_model,
all_elem_counts,
maxngram=1,
name=None,
use_lemma=True,
heuristic=False,
use_coke=False):
"""
w2v_model can be a binary vectors file, or a loaded gensim model instance.
"""
self.maxngram = maxngram
self.name = name
self.use_lemma = use_lemma
assert isinstance(all_elem_counts, dict)
self.all_elem_counts = all_elem_counts
self.heuristic = heuristic
self.use_coke = use_coke
if isinstance(w2v_model, basestring):
self.model = load_gensim_from_binary_file(w2v_model)
self.model.filename = w2v_model.split('/')[-1]
if not self.name:
self.name = self.model.filename
else:
assert isinstance(w2v_model, Word2Vec)
self.model = w2v_model
if not self.name:
if hasattr(self.model, 'filename'):
self.name = self.model.filename
self.model.init_sims() # normalize the vectors
self.enormer = ElementNormalizer()
if self.use_coke:
bh = BackupHandler(relative_path('models/output/backup'))
coke_file = 'coke_0329'
if not bh.exists(coke_file):
raise ValueError('Coke file does not exist: %s' % coke_file)
self.coke = bh.load(coke_file)
print 'Trying to load element indexes from cache ...'
bh = BackupHandler(relative_path('models/output/backup'))
elem_index_backup_name = self.model.filename + '_elem_index'
if bh.exists(elem_index_backup_name):
self.idfs, self.elems, self.elem_lookup, self.vecmat = bh.load(
elem_index_backup_name)
else:
print 'Word2vecBaseline building element indexes...'
fu, fau = get_fu_fau()
self.idfs = self.get_idf(fu.values() + fau.values())
self.elems = sorted(self.all_elem_counts.keys())
self.elem_lookup = dict((y, x) for (x, y) in enumerate(self.elems))
vecs = []
for e in self.elems:
u = doc_serve.get_training_doc(e, True)
v = self.get_bow_representation(u)
vecs.append(v)
self.vecmat = np.array(vecs)
assert self.vecmat.shape == (len(self.elems),
self.model.vector_size)
bh.save(elem_index_backup_name,
(self.idfs, self.elems, self.elem_lookup, self.vecmat))
print 'Finished building indexes.'
# Copied from annotate_code_with_api.py
with open('../../models/output/mpl_code_blocks.txt') as reader:
content = reader.read()
content = content.decode('utf-8')
content = content.replace("<", "<")
content = content.replace(">", ">")
content = content.replace("&", "&")
sompl_blocks = content.split(
'\n\n\n') # stackoverflow matplotlib code blocks
print 'There are %d code examples from mpl stackoverflow' % len(
sompl_blocks)
# Step 2:
bh = BackupHandler('.')
cookbook_segs = bh.load('cookbook_segs')
cookbook_blocks = []
for tag, p in cookbook_segs:
if tag == 'CODE':
cookbook_blocks.append(p)
print 'There are %d code examples from matplotlib cookbook' % len(
cookbook_blocks)
all_codes = sompl_blocks + cookbook_blocks
print 'There are %d code blocks in total' % (len(all_codes))
# Step 3:
counters = {}
elif isinstance(v, ast.Name):
kvs.append((k, v.id))
elif isinstance(v, ast.Tuple) \
or isinstance(v, ast.Dict) \
or isinstance(v, ast.List):
kvs.append((k, astunparse.unparse(v).strip()))
return func_name, kvs
if __name__ == '__main__':
# Step 1.
fu, fau = get_fu_fau()
# Step 2.
bh = BackupHandler(relative_path('experimental/code_suggest'))
all_codes = bh.load('all_codes')
print 'There are %d code examples in total'%len(all_codes)
# Step 3.
f_counts = defaultdict(int) # [f] = count
fa_counts = defaultdict(int) # [f,a] = count
fav_counts = defaultdict(int) # [f,a,v] = count
for code in all_codes:
try:
node = ast.parse(code)
except SyntaxError:
continue
calls = findCallNodes(node)
for call in calls:
def transform_and_filter(elem):
"""
Cleaning is performed to reduce sparsity:
- pylab.xxx --> plt.xxx (if the function exists in pyplot)
- various add_subplot.xxx --> plt.gca.xxx (see stype.tsv)
- only plt.* are kept
Returns: cleaned elem or None
"""
elem = enormer.simplify(elem)
if elem.startswith('plt.'):
return elem
else:
return None
if __name__ == '__main__':
coke_counts = defaultdict(int)
count = 0
for code in code_examples():
count += 1
if count % 1000 == 0:
print '%d ... unique_cokes=%d'%(count, len(coke_counts))
for x, y in get_cokes(code):
coke_counts[x,y] += 1
bh = BackupHandler(relative_path('models/output/backup'))
bh.save('coke_0329', coke_counts)
def __init__(self):
bh = BackupHandler(relative_path('demo/data'))
self.pos_ave = bh.load('pos_ave')
print 'FuncPositionFinder: loaded %d average positions for functions' % len(
self.pos_ave)
train_pairs.append((merged_utter, astunparse.unparse(call_node)))
unique_train_pairs = list(set(train_pairs))
print 'total_block', total_block
print 'total_grammatical', total_grammatical
print 'total_call_nodes', total_call_nodes
print 'total_matched_funcs', total_matched_funcs, '(total train pairs)'
print 'total_matched_args', total_matched_args
print 'total_unique_train_pairs', len(unique_train_pairs)
return unique_train_pairs
if __name__ == '__main__':
bh = BackupHandler(relative_path('models/output/backup'))
# Step 1
fu, fau = get_fu_fau()
# Step 2
with open(relative_path('models/output/mpl_code_blocks.txt')) as reader:
content = reader.read()
content = content.decode('utf-8')
content = content.replace("<", "<")
content = content.replace(">", ">")
content = content.replace("&", "&")
blocks = content.split('\n\n\n')
elem_counts[f,a] += 1
elem_counts[f,a,v] += 1
return is_useful
if __name__ == '__main__':
counters = defaultdict(int)
md5s = set()
all_codes = []
fu, _ = get_fu_fau()
elem_counts = defaultdict(int) # [elem] = count
bh = BackupHandler(relative_path('experimental/code_suggest/output/backup'))
for root, dirs, files in os.walk(
relative_path('mining/output/github-matplotlib-repos')):
if '.git' in root: continue
for file_name in files:
counters['count_file'] += 1
if counters['count_file'] % 1000 == 0:
print 'Processed %d files - Useful files: %d'%(
counters['count_file'], counters['count_useful_files'])
file_path = os.path.join(root, file_name)
elif isinstance(v, ast.Name):
kvs.append((k, v.id))
elif isinstance(v, ast.Tuple) \
or isinstance(v, ast.Dict) \
or isinstance(v, ast.List):
kvs.append((k, astunparse.unparse(v).strip()))
return func_name, kvs
if __name__ == '__main__':
# Step 1.
fu, fau = get_fu_fau()
# Step 2.
bh = BackupHandler(relative_path('experimental/code_suggest'))
all_codes = bh.load('all_codes')
print 'There are %d code examples in total' % len(all_codes)
# Step 3.
f_counts = defaultdict(int) # [f] = count
fa_counts = defaultdict(int) # [f,a] = count
fav_counts = defaultdict(int) # [f,a,v] = count
for code in all_codes:
try:
node = ast.parse(code)
except SyntaxError:
continue
calls = findCallNodes(node)
for call in calls:
this code
3. take average per function
Output:
- a dictionary: [function] = average_position
average position: between 0 (beginning of code) and 1 (end of code).
"""
import ast
from collections import defaultdict
from codemend import BackupHandler, relative_path
from codemend.models.annotate_code_with_api import get_fu_fau, findCallNodes, extractCallComponents
fu, fau = get_fu_fau()
bh = BackupHandler(relative_path('experimental/code_suggest'))
all_codes = bh.load('all_codes')
print 'There are %d code examples in total'%len(all_codes)
pos_sum = defaultdict(float) # [f] = sum
pos_cnt = defaultdict(int) # [f] = count
for code in all_codes:
try:
node = ast.parse(code)
except SyntaxError:
continue
calls = findCallNodes(node)
called_funcs = [extractCallComponents(x)[0] for x in calls]
called_funcs = filter(lambda x: x in fu, called_funcs)
if len(calls) < 3:
continue
if elem_id.startswith('plt.'):
element_pyplot_counts[elem_id] += 1
val = get_countable_value(e.val_node, varmap, enormer)
if val: element_pyplot_value_counts[elem_id][val] += 1
for elem_id in element_pyplot_value_counts:
element_pyplot_value_counts[elem_id] = dict(element_pyplot_value_counts[elem_id])
element_pyplot_value_counts = dict(element_pyplot_value_counts)
print 'Processed %d code examples'%count
print 'There are %d unique elements'%len(element_counts)
print 'There are %d unique pyplot elements'%len(element_pyplot_counts)
for k in counters:
print '%s: %d'%(k, counters[k])
bh = BackupHandler(relative_path('experimental/code_suggest/output/backup'))
# Change logs:
# - 0322: using raw format
# - 0327: using Element, tracking return type and variable assignments and
# import aliases.
# - 0404: fixed issue with dict as positional argument;
# added element_value_counts;
# added Shiyan's example.
bh.save('elem_counts_0404', element_counts)
bh.save('elem_pyplot_counts_0404', element_pyplot_counts)
bh.save('elem_pyplot_value_counts_0404', element_pyplot_value_counts)
"""
Log:
# 0327
def get_effective_code_len(code):
"""
Number of characters in a code example. Not counting lines with "import"
"""
lines = code.split('\n')
lines = filter(lambda x: 'import' not in x.split(), lines)
return len('\n'.join(lines))
if __name__ == '__main__':
print 'Reading SVGs and code examples. Takes 7.3 seconds...'
bh = BackupHandler('.')
svgs = bh.load('svgs')
all_codes = bh.load('all_codes')
print 'Loading functions that are plotting commands'
# Copied from code_suggest.py
import csv
import pattern.en
# Load csv file of pyplot summary
pyplot_fu = {} # [func] = utter
print 'CodeSuggest: Loading pyplot fu...'
with open('../../docstring_parse/pyplot_fu.csv', 'rb') as csvfile:
reader = csv.reader(csvfile)
next(reader, None) # skip the header
for f, u in reader:
if not u:
def transform_and_filter(elem):
"""
Cleaning is performed to reduce sparsity:
- pylab.xxx --> plt.xxx (if the function exists in pyplot)
- various add_subplot.xxx --> plt.gca.xxx (see stype.tsv)
- only plt.* are kept
Returns: cleaned elem or None
"""
elem = enormer.simplify(elem)
if elem.startswith('plt.'):
return elem
else:
return None
if __name__ == '__main__':
coke_counts = defaultdict(int)
count = 0
for code in code_examples():
count += 1
if count % 1000 == 0:
print '%d ... unique_cokes=%d' % (count, len(coke_counts))
for x, y in get_cokes(code):
coke_counts[x, y] += 1
bh = BackupHandler(relative_path('models/output/backup'))
bh.save('coke_0329', coke_counts)
from codemend import BackupHandler, relative_path
from codemend.models.element import ElementNormalizer
from codemend.models.word2vec_util import load_gensim_from_binary_file
from codemend.models.bimodal2 import BiModal
from codemend.experimental.code_suggest.mine_element import code_examples
if __name__ == '__main__':
bh = BackupHandler(relative_path('experimental/code_suggest/output/backup'))
elem_counts = bh.load('elem_pyplot_counts_0404')
all_elems = sorted(elem_counts.keys())
all_elems_counts = elem_counts
enormer = ElementNormalizer()
w2v_model = load_gensim_from_binary_file(
relative_path('models/output/vectors-so-text-python-lemma-win5.bin')) # <-- note the change here!!
model = BiModal(all_elems, all_elems_counts, w2v_model, code_examples, enormer,
threads=None, alpha=0.05, window=5, negative=20,
additive=0, multiply=0, concat=1,
epoch=1, rand_parent_doc=True,
hint_pvecs_init=True, hint_rvecs_init=False,
neg_sample_used_elem=False)
model.save(relative_path('models/output/bi2-0410-t.model'))
# Changes:
# bi2-test -- lastest gold version for user study
# bi2-0410-a -- epoch=10, fixed stopwords (e.g., excluding bar from stopwords) -- this is vanilla
# bi2-0410-b -- epoch=1, quick check if setting is all right.
# bi2-0410-c -- epoch=10, replicating bi2-0410-a
# bi2-0410-d -- epoch=1, randomly with-parent doc
# bi2-0410-e -- epoch=5, randomly with-parent doc
example also has its corresponding generated SVGs.
The table is like this:
(func_id, code, svg)
There are at most 20 (shortest) examples per func_id.
"""
import sqlite3
from codemend import BackupHandler, relative_path
if __name__ == '__main__':
print 'Reading SVGs and code examples. Takes 7.3 seconds...'
bh = BackupHandler('.')
svgs = bh.load('svgs')
all_codes = bh.load('all_codes')
plotcommands_examples = bh.load('plotcommands_examples') # [plot_command] = [example_idx]
db = sqlite3.connect(relative_path('demo/data/code.sqlite3'))
cursor = db.cursor()
cursor.executescript("""
DROP TABLE IF EXISTS example;
CREATE TABLE example (
func_id TEXT NOT NULL,
code TEXT NOT NULL,
svg TEXT
);