def remove_subtree(self, nid):
"""
Return a subtree deleted from this tree. If nid is None, an
empty tree is returned.
For the original tree, this method is similar to
`remove_node(self,nid)`, because given node and its children
are removed from the original tree in both methods.
For the returned value and performance, these two methods are
different:
`remove_node` returns the number of deleted nodes;
`remove_subtree` returns a subtree of deleted nodes;
You are always suggested to use `remove_node` if your only to
delete nodes from a tree, as the other one need memory
allocation to store the new tree.
"""
st = Tree()
if nid is None:
return st
if not self.contains(nid):
raise NodeIDAbsentError("Node '%s' is not in the tree" % nid)
st.root = nid
parent = self[nid].bpointer
self[nid].bpointer = None # reset root parent for the new tree
removed = []
for id in self.expand_tree(nid):
removed.append(id)
for id in removed:
st._nodes.update({id: self._nodes.pop(id)})
# Update its parent info
self.__update_fpointer(parent, nid, Node.DELETE)
return st
class Conversation:
def __init__(self, tweet):
self.root_tweet = tweet
self.conversation_tree = Tree()
self.conversation_tree.create_node(tweet, tweet)
self.depth = int()
self.tweets_id = list()
self.tweets_id.append(tweet)
self.width = int()
def add_replay(self, tweet, parent_tweet):
self.conversation_tree.create_node(tweet, tweet, parent=parent_tweet)
self.tweets_id.append(tweet)
def set_depth(self):
self.depth = self.conversation_tree.depth() + 1
def find_depth(self):
return self.depth
def get_tweets_id(self):
return self.tweets_id
def set_width(self):
self.width = len(self.tweets_id)
def find_width(self):
return self.width
def get_conversation_tree(self):
return self.conversation_tree
def test_paste_tree(self):
new_tree = Tree()
new_tree.create_node("Jill", "jill")
new_tree.create_node("Mark", "mark", parent="jill")
self.tree.paste("jane", new_tree)
self.assertEqual("jill" in self.tree.is_branch("jane"), True)
self.tree.remove_node("jill")
def main():
try:
conf = open(args.config, 'r')
tempConf = yaml.load_all(conf)
for line in tempConf:
list_path = line["ListPath"]
write_missed = line["WriteMissed"]
pack_list_file = open(list_path, "r+")
pack_list = json.load(pack_list_file)
checked = check(pack_list, write_missed)
tree = Tree()
tree.create_node(cur_time, "root")
generate_tree(checked, tree, "root")
print "\n"
tree.show()
print "\n"
except KeyboardInterrupt:
print '\nThe process was interrupted by the user'
raise SystemExit
def test_02_get_hierarchy_for_module_returns_single_node_when_nothing_depend_on_module(self, mock_client):
"""
Test that get_hierarchy_for_module returns a single node tree structure if no dependent modules are found
:param mock_client: A mocked out version of erppeek.Client
:return:
"""
# Mock Up
mock_dp = DependencyGraph
orig_mod_search = mock_dp.module_search
orig_dep_search = mock_dp.dependency_search
orig_client_search = mock_client.search
mock_dp.module_search = MagicMock(return_value=[666])
mock_dp.dependency_search = MagicMock(return_value=[])
mock_dg = mock_dp('valid_module')
test_hierarchy = Tree()
test_hierarchy.create_node('valid_module', 'valid_module')
self.assertEqual(mock_dg.hierarchy.to_json(), test_hierarchy.to_json(), 'get_hierarchy_for_module did not return [] when finding no dependent modules')
# Mock Down
mock_client.stop()
mock_dp.module_search.stop()
mock_client.search.stop()
mock_client.search = orig_client_search
mock_dp.dependency_search.stop()
mock_dp.module_search = orig_mod_search
mock_dp.dependency_search = orig_dep_search
def print_prob_val(self, fname="OutTree.txt"):
n_tree = Tree(tree=self.tree)
for node in n_tree.nodes:
node = n_tree.get_node(node)
node.tag = "{tag} - {val} - {prob}".format(tag=node.tag, val=node.data[0], prob=node.data[1])
n_tree.save2file(fname)
self.tree = None
class Scansion(object):
"""
.src : list of strings
"""
#///////////////////////////////////////////////////////////////////////////
def __init__(self, source_file):
"""
Scansion.__init__
source_file : (src) source file's name.
"""
self.htree = Tree()
self.src = []
# creating root node (level 0) :
self.htree.create_node(tag = "root",
identifier = "root",
data = Hypothesis(htree = self.htree,
level=0,
language=None,
src=source_file))
# calling root node :
msg(0, "Calling the root node.")
stop = False
while not stop:
leaves_to_be_extended = [leave for leave in self.htree.leaves() if not leave.data.dead]
for leave in leaves_to_be_extended:
leave.data.go_on()
if len(leaves_to_be_extended)==0:
stop = True
class TreePipeline(object):
def open_spider(self, spider):
self.tree = Tree()
self.tree.create_node("root", "root")
def process_item(self, item, spider):
lst = item['text']
lst = [x.strip() for x in [y.replace('...', '') for y in lst]]
item['pagetitle'] = item['pagetitle'].replace('...', '')
lst[-1] = item['pagetitle']
for idx, elem in enumerate(lst):
if idx == 0:
previous = "root"
else:
previous = "|".join(lst[:idx])
elem = "|".join(lst[:idx + 1])
# elem = elem.replace('...', '')
elem = elem.encode('utf-8').decode('utf-8')
if not self.tree.contains(elem):
print "Adding node %s" % elem
self.tree.create_node(elem, elem, parent=previous)
# self.tree.show()
return item
def close_spider(self, spider):
self.tree.show()
with open(makepath('data/cats/tree.json'), 'w') as outfile:
outfile.write(self.tree.to_json())
self.tree.save2file(makepath('data/cats/tree.tree'))
def parse_xml(path):
tree = ET.parse(path)
bill_list = []
destination = "console"
# eg: (cox, "*****@*****.**") (rent, 2000)
# / \ & / \
# (Evan, 0.5) (Jason, 0.5) (Evan, 0.45) (Jason, 0.55)
for bill in tree.findall("bill"):
billname = bill.get("name")
bill_tree = Tree()
bill_value = bill.get("fixed")
if bill_value is None:
bill_value = bill.get("from_email")
bill_tree.create_node(tag=billname, identifier=billname, data=bill_value)
for user in bill.findall("user"):
username = user.get("name")
ratio = user.get("ratio")
bill_tree.create_node(tag=username, identifier=username, parent=billname, data=ratio)
bill_list.append(bill_tree)
# Get the location to dump our results
for d in tree.findall("output"):
destination = d.get("destination")
return (bill_list, destination)
def test_show_data_property(self):
new_tree = Tree()
class Flower(object):
def __init__(self, color):
self.color = color
new_tree.create_node("Jill", "jill", data=Flower("white"))
new_tree.show(data_property="color")
def build_directory_tree(service):
print colored("*** Building directory tree ***", 'blue')
# initialize a new directory structure
directory = Tree()
directory.create_node("Root", "root")
page_token = None
while True:
try:
param = {}
if page_token:
param['pageToken'] = page_token
# Get children of folderID
children = service.children().list(folderId='root', **param).execute()
# For each child in folder, get ID, name and Type
# and write to the directory tree
for child in children.get('items', []):
try:
file__ = service.files().get(fileId=child['id']).execute()
directory.create_node(file__['title'], child['id'], parent = 'root', data=node('root', child['id'], file__['title'], file__['mimeType']))
except errors.HttpError, error:
print 'An error occurred: %s' % error
# Get next page token for current folderID
page_token = children.get('nextPageToken')
if not page_token:
break
except errors.HttpError, error:
print colored('An error occurred: %s', 'red') % error
break
def visit_root(self, node, tree=None):
tree = Tree()
root = repr(node)
tree.create_node(root, root)
for child in node.children:
tree = self.visit(child, tree=tree)
return tree
def _get_random_tree(self, start, max_depth=999):
"""
Returns a random tree from PCFG starting with symbol 'start'
depth: the maximum depth of tree
"""
t = Tree()
t.create_node(ParseNode(start,''))
# get ids of not expanded nonterminals in tree
nodes_to_expand, depth = self.__get_nodes_to_expand_and_depth(t)
while len(nodes_to_expand) > 0:
# for each non terminal, choose a random rule and apply it
for node in nodes_to_expand:
symbol = t[node].tag.symbol
# if tree exceeded the allowed depth, expand nonterminals
# using rules from terminating_rule_ids
if depth >= (max_depth-1):
# choose from rules for nonterminal from terminating_rule_ids
rhsix = np.random.choice(self.grammar.terminating_rule_ids[symbol], size=1)
else:
# choose from rules for nonterminal according to production probabilities
rhsix = np.random.choice(len(self.grammar.rules[symbol]), p=self.grammar.prod_probabilities[symbol], size=1)
t[node].tag.rule = rhsix[0] # index of production rule used when expanding this node
rhs = self.grammar.rules[symbol][rhsix[0]]
for s in rhs:
t.create_node(tag=ParseNode(s,''), parent=node)
nodes_to_expand, depth = self.__get_nodes_to_expand_and_depth(t)
return t
def __init__(self, id, opcode, op_array, context):
""" Create a tree representaiton of an Opcode
Arguments :
id : The id representing the new OPcode
opcode : An OPcode struct
op_array : The op_array of the OPcode
context : An OPcacheParser instance
"""
Tree.__init__(self)
# Identifier to be used by the tree and nodes
id_with_hash = str(hash(str(op_array))) + "_" + id
# OP name
op = OPcodeParser.get_opcode_name(opcode['opcode'])
# Parser
context = OPcodeParser(context)
# Parse operands and result
(op1, op2, result) = context.parse_operands(opcode, op_array)
# Create nodes
op1_node = Node("Operand 1: " + op1, id_with_hash + "_op1")
op2_node = Node("Operand 2: " + op2, id_with_hash + "_op2")
result_node = Node("Result: " + result, id_with_hash + "_result")
# Link nodes to tree
self.create_node(id + ": " + op, id_with_hash + "_opcode")
self.add_node(op1_node, parent=id_with_hash + "_opcode")
self.add_node(op2_node, parent=id_with_hash + "_opcode")
self.add_node(result_node, parent=id_with_hash + "_opcode")
def create_trees(BP, Roots, NT, n):
for bp in BP[n-1,0]:
if bp.name in Roots:
print '\nTree'
t = Tree()
create_tree(t, bp, 0, 1)
t.show(key=lambda x: x.identifier)
def merge_trees(t1, t2, tick): t = Tree() identifier = -tick # using negative numbers as identifiers, positive numbers are ids for the leaf nodes name = "new_cluster_%s" % tick t.create_node(name, identifier) t.paste(identifier, t1) t.paste(identifier, t2) return t, name
def create_tree(indexed_titles, root, children=None):
t = Tree()
identifier = indexed_titles[root]
t.create_node(root, identifier)
if children:
for sub_tree in children:
t.paste(identifier, sub_tree)
return t
def build_conversation(cursor):
conversation_roots = postgres_queries.find_conversations_root(cursor)
conversation_list = list()
for root in conversation_roots:
conversation_tree = Tree()
conversation_tree.create_node(root[0], root[0])
search_children(root[0], conversation_tree, cursor)
conversation_list.append(conversation_tree)
return conversation_list
def compare_actual_folder_with_tree(self, root: path, tree: Tree):
root_name = tree.root
root_path = root.joinpath(root_name)
print(root_path)
self.assertTrue(root_path.exists(), "The path {} should exist, but doesn't".format(root_path))
children = tree.children(root_name)
for children in children:
subtree = tree.subtree(children.identifier)
self.compare_actual_folder_with_tree(root_path, subtree)
def create_powerset_tree(self):
tree = Tree(None)
for idx, s in enumerate(self.object_sets):
if idx == 0:
tree.create_node((s, self.get_max_timeset(s)), s)
else:
parent_index = frozenset(sorted(list(s)[0:-1]))
tree.create_node((s, self.get_max_timeset(s)), s, parent_index)
return tree
def setUp(self):
tree = Tree()
tree.create_node("Hárry", "hárry")
tree.create_node("Jane", "jane", parent="hárry")
tree.create_node("Bill", "bill", parent="hárry")
tree.create_node("Diane", "diane", parent="jane")
tree.create_node("George", "george", parent="bill")
self.tree = tree
def test_all_nodes_itr(self):
"""
tests: Tree.all_nodes_iter
Added by: William Rusnack
"""
new_tree = Tree()
self.assertEqual(len(new_tree.all_nodes_itr()), 0)
nodes = list()
nodes.append(new_tree.create_node('root_node'))
nodes.append(new_tree.create_node('second', parent=new_tree.root))
for nd in new_tree.all_nodes_itr():
self.assertTrue(nd in nodes)
def to_tree(ts):
"""
:param ts: list of stuff to be treed
:return: treelib.Tree with the stuff after zf78 and putted in the tree.
"""
tree = Tree()
tree.create_node("root", 0, data=list([0,0.0]))
coded = encode(ts)
for i, word in enumerate(coded):
tree.create_node(word[1],i+1,parent=word[0], data=list([0,0.0]))
return tree
def load(self, path2file):
self.id_EDUs = []
self.EDU = {}
self.treeNS = Tree()
self.tree = Tree()
# nombre max d'espace pour init id_parents
with open(path2file, "r") as f:
max_space = 0
nb_line = 0
for i, line in enumerate(f):
nb_space = 0
for c in line:
if c == " ":
nb_space += 1
else:
break
if nb_space > max_space:
max_space = nb_space
nb_line += 1
with open(path2file, "r") as f:
id_parents = [0] * max_space
NS_parents = [0] * max_space
for i, line in enumerate(f):
# nombre d'espace détermine le parent
nb_space = 0
for c in line:
if c == " ":
nb_space += 1
else:
break
space = nb_space / 2
id_parents[space] = i
parent = id_parents[space - 1]
reg = "\(([\w\-\[\]]+)|(_!.+!_)" # récupération du contenu
match = re.findall(reg, line)[0]
if match[0] == "":
content = match[1] # feuille EDU
self.id_EDUs.append(i)
# print content
self.EDU[i] = re.findall("_!(.*)!_", content)
else:
content = match[0]
reg2 = "\[(N|S)\]" # récupération NS
match2 = re.findall(reg2, content)
NS_parents[space] = match2 # ['N','S']
# création du noeud
if i == 0:
self.tree.create_node(content, 0)
self.treeNS.create_node("Root", 0)
else:
id_NS = len(self.tree.is_branch(parent)) # 0 ou 1 car arbre binaire
self.tree.create_node(content, i, parent=parent)
self.treeNS.create_node(NS_parents[space - 1][id_NS], i, parent=parent)
def build_header_tree(self):
header_tree = Tree()
root_field = ReportDefinitionField()
root_field.alias = 'root'
root_field.header = 'Root'
root_field.sub_fields = self.report_definition.fields
self.__build_header_tree(header_tree, None, root_field)
self.__prepare_header_data(header_tree, header_tree.get_node(header_tree.root))
return header_tree
def types_of_conversation():
conversation_amount = postgres_queries.find_annotated_conversation_number()
conversation_list = list()
depth_dict = dict()
depth_dict_long = dict()
depth_dict_short = dict()
number_of_tweets_dict = dict()
for i in range (0, conversation_amount + 1, 1):
conversation_tree = Tree()
converastion = postgres_queries.find_conversation(i)
for tweet in converastion:
if tweet[1] is None:
conversation_tree.create_node(tweet[0], tweet[0])
build_conversation(tweet[0], converastion, conversation_tree)
depth = conversation_tree.depth() + 1
number_of_tweets = len(conversation_tree.all_nodes())
#short/long
if number_of_tweets >=20:
if depth in depth_dict_long:
depth_dict_long[depth] += 1
else:
depth_dict_long[depth] = 1
else:
if depth in depth_dict_short:
depth_dict_short[depth] += 1
else:
depth_dict_short[depth] = 1
if number_of_tweets in number_of_tweets_dict:
number_of_tweets_dict[number_of_tweets] += 1
else:
number_of_tweets_dict[number_of_tweets] = 1
if depth in depth_dict:
depth_dict[depth] += 1
else:
depth_dict[depth] = 1
conversation_list.append(conversation_tree)
#print depth_dict
print 'Depth of a conversation'
for depth, count in depth_dict.iteritems():
print depth, '\t', count
print 'Number of tweets in a conversation'
for number, count in number_of_tweets_dict.iteritems():
print number, '\t', count
print 'Depth of a long conversation'
for depth, count in depth_dict_long.iteritems():
print depth, '\t', count
print 'Depth of a short conversation'
for depth, count in depth_dict_short.iteritems():
print depth, '\t', count
return conversation_list
def test_export_with_minus_in_filename(self):
tree = Tree()
tree.create_node('Example Node', 'example-node')
expected = """\
digraph tree {
\t"example-node" [label="Example Node", shape=circle]
}"""
export_to_dot(tree, 'id_with_minus.dot')
self.assertTrue(os.path.isfile('id_with_minus.dot'), "The file id_with_minus.dot could not be found.")
generated = self.read_generated_output('id_with_minus.dot')
self.assertEqual(expected, generated, "The generated file content is not the expected one")
os.remove('id_with_minus.dot')
def test_unicode_filename(self):
tree = Tree()
tree.create_node('Node 1', 'node_1')
export_to_dot(tree, 'ŕʩϢ.dot')
expected = """\
digraph tree {
\t"node_1" [label="Node 1", shape=circle]
}"""
self.assertTrue(os.path.isfile('ŕʩϢ.dot'), "The file ŕʩϢ.dot could not be found.")
generated = self.read_generated_output('ŕʩϢ.dot')
self.assertEqual(expected, generated, "The generated file content is not the expected one")
os.remove('ŕʩϢ.dot')
def create_tree(adict):
tree = Tree()
if type(adict) is dict:
# print ("procdessing dict to tree...")
root = list(adict.keys())[0]
# print (root)
tree.create_node(timestamp_node(root), root, data=time())
for node in list(adict.values()):
# print ("processing a node of the dict values")
if type(node) is dict:
newTree = create_tree(node)
tree.paste(root, newTree)
elif type(node) is list:
for item in node:
newTree = create_tree(item)
tree.paste(root, newTree)
else:
tree.create_node(timestamp_node(node),
node,
parent=root,
data=time())
else:
tree.create_node(timestamp_node(adict), adict, data=time())
return tree
def tree_build_from_list(containers):
"""
Build a tree based on a unsorted list.
Build a tree of containers based on an unsorted list of containers.
Example:
--------
>>> containers = [
{
"childContainerKey": null,
"configlets": [],
"devices": [],
"imageBundle": "",
"key": "root",
"name": "Tenant",
"parentName": null
},
{
"childContainerKey": null,
"configlets": [
"veos3-basic-configuration"
],
"devices": [
"veos-1"
],
"imageBundle": "",
"key": "container_43_840035860469981",
"name": "staging",
"parentName": "Tenant"
}]
>>> print(tree_build_from_list(containers=containers))
{"Tenant": {"children": [{"Fabric": {"children": [{"Leaves": {"children": ["MLAG01", "MLAG02"]}}, "Spines"]}}]}}
Parameters
----------
containers : dict, optional
Container topology to create on CVP, by default None
Returns
-------
json
tree topology
"""
# Create tree object
tree = Tree() # Create the base node
previously_created = list()
# Create root node to mimic CVP behavior
tree.create_node("Tenant", "Tenant")
# Iterate for first level of containers directly attached under root.
for cvp_container in containers:
if cvp_container['parentName'] == None:
continue
elif cvp_container['parentName'] in ['Tenant']:
previously_created.append(cvp_container['name'])
tree.create_node(cvp_container['name'],
cvp_container['name'],
parent=cvp_container['parentName'])
# Loop since expected tree is not equal to number of entries in container topology
while len(tree.all_nodes()) < len(containers):
for cvp_container in containers:
if tree.contains(
cvp_container['parentName']
): #and cvp_container['parentName'] not in ['Tenant']
try:
tree.create_node(cvp_container['name'],
cvp_container['name'],
parent=cvp_container['parentName'])
except:
continue
return tree.to_json()
# https://treelib.readthedocs.io/en/latest/examples.html#advanced-usage
def walkTree(tree, rootNode, path):
d = list(map(lambda x: x.tag, tree.children(rootNode)))
d.sort()
for z in d:
path = walkTree(tree, z, path + z)
return path
input = list(map(lambda x: x.strip(), open("test_input.txt").readlines()))
tree = Tree()
tree.create_node("root", "root")
# first figure out how many steps there are and then sort them
# by their name
for lines in input:
(l1, l2) = (lines[5], lines[36])
print(lines)
if tree.contains(l1) and tree.contains(l2):
tree.move_node(l2, l1)
elif tree.contains(l1) and not tree.contains(l2):
tree.create_node(l2, l2, parent=l1)
elif not tree.contains(l1) and tree.contains(l2):
# get the root for l2 and make that the root for l1
# then move l2 under l1
tree.create_node(l1, l1, parent=tree.parent(l2))
# with urllib.request.urlopen('http://www.image-net.org/api/xml/structure_released.xml') as response:
# html = response.read()
# f11 = open('treetext.txt','wb')
# f11.write(html)
# f11.close()
f11 = open(
'/usr/local/apps/profiles-rest-api/android-model403/treetext.txt',
'rb')
html = f11.read()
f11.close()
tree = ElementTree(fromstring(html))
root = tree.getroot()
synsetTree = Tree()
synsetTree.create_node('Entity', 'fall11', data=Confidence(0, 0))
for synset in root.iter('synset'):
for child in synset:
if child.get('wnid') in synsetTree._nodes:
continue
synsetTree.create_node(child.get('words'),
child.get('wnid'),
parent=synset.get('wnid'),
data=Confidence(0, 0))
# synsetTree.show()
#treeDog = synsetTree.subtree('n02087122')
treeDog = synsetTree
def init_root_list(self, examples, mode='train'):
"""
init batch tree list
:param sen: training data
:param label: ground truth label
:param id_list: id list is used to map the raw feature extracted by raw_sen
"""
keep_prob = self.config['keep_prob'] if mode == 'train' else 1.0
self.batch_size = len(examples)
self.trees = [Tree() for _ in range(self.batch_size)]
self.sen_list = [e.sen for e in examples]
self.label_list = [e.label for e in examples]
self.char_list = [e.char for e in examples]
self.pos_list = [e.pos for e in examples]
# in tf version, no sorting by length
data = batchify_with_label(self.sen_list, self.char_list,
self.label_list)
self.fw_seq_tensor, self.bw_seq_tensor, self.word_seq_lengths = data[
0], data[1], data[2]
self.char_seq_tensor, self.char_seq_lengths = data[3], data[4]
self.label_seq_tensor = data[5]
self.max_seq_len = self.word_seq_lengths.max().item()
self.feature_seq_tensor = batchify_feature(
char_seq_tensor=self.char_seq_tensor,
word_seq_lengths=self.word_seq_lengths,
pos_list=self.pos_list,
feature_dim=self.config['raw_feature_dim'])
# print('********** check ***********')
# print(self.fw_seq_tensor.shape, self.bw_seq_tensor.shape)
# print(self.word_seq_lengths)
# print(self.max_seq_len)
# print(self.feature_seq_tensor.shape)
# reshape tensors to [b*t, d]
# self.fw_seq_tensor = np.reshape(
# self.fw_seq_tensor, [self.batch_size*self.max_seq_len, -1])
# self.bw_seq_tensor = np.reshape(
# self.bw_seq_tensor, [self.batch_size*self.max_seq_len, -1])
# self.feature_seq_tensor = np.reshape(
# self.feature_seq_tensor, [self.batch_size*self.max_seq_len, -1])
# self.fc_output_data = self.pv_model.get_fc_output(
# fw_word=self.fw_seq_tensor, bw_word=self.bw_seq_tensor,
# extra_fea=self.feature_seq_tensor, keep_prob=keep_prob)
# print('obtain fc_output, type', self.fc_output_data.shape, type(self.fc_output_data))
# self.fc_output_data = np.reshape(
# self.fc_output_data, [self.batch_size, self.max_seq_len, -1])
# print('reshape fc_output', self.fc_output_data.shape)
root_node_list = []
root_init = [[] for _ in range(4)]
for i in range(len(self.trees)):
root_node = self.trees[i].create_node(identifier='root',
data=Node())
# TODO: check visit_num of init node is 0 or 1 ?????
root_node.data.num = 0
root_node.data.index = i
root_node_list.append(root_node)
root_init[0].append(root_node)
root_init[1].append(self.fw_seq_tensor[i][0])
root_init[2].append(self.bw_seq_tensor[i][0])
root_init[3].append(self.feature_seq_tensor[i][0])
probs = self.pv_model.get_policy(fw_word=np.array(root_init[1]),
bw_word=np.array(root_init[2]),
extra_fea=np.array(root_init[3]),
keep_prob=keep_prob)
for i in range(len(probs)):
self.expand(root_init[0][i], probs[i])
del root_init
gc.collect()
return root_node_list
def analyze(token):
def getNext():
i = 0
while True:
yield i
i += 1
import pandas as pd
from collections import deque
from treelib import Tree, Node
import re
tokens = []
for l in token:
s = re.split(r' ', l)
tokens.append(s[0])
tokens.append('$')
test = deque(tokens)
rr = {
'r1': 'E=E+T',
'r2': 'E=T',
'r3': 'T=T*F',
'r4': 'T=F',
'r5': 'F=(E)',
'r6': 'F=i'
}
class CompiledError(StandardError):
def __init__(self, arg):
self.arg = arg
def __str__(self):
return self.arg
state = [0]
symbolic = ['$']
ast = []
table = pd.read_csv('table.csv', index_col=0, na_filter=False)
ltest = len(test)
while (len(test) != 0):
if test[0] not in table.columns:
raise CompiledError('%s, unrecognized token at %d' %
(test[0], ltest - len(test)))
ins = table.loc[state[-1], test[0]]
if len(ins) == 0:
raise CompiledError('%s complie failed at %d, unexpected token' %
(test[0], ltest - len(test)))
if ins[0] == 's':
state.append(int(ins[1:]))
tree = Tree()
tree.create_node(test[0], getNext())
ast.append(tree)
symbolic.append(test.popleft())
elif ins[0] == 'r':
rule = rr[ins]
print rule
li = list(rule)
li.reverse()
temptree = []
for i in li:
if i != '=':
symbolic.pop()
state.pop()
temptree.append(ast.pop())
else:
break
symb = rule[:rule.find('=')]
symbolic.append(symb)
state.append(int(table.loc[state[-1], symbolic[-1]]))
tree = Tree()
ii = getNext()
tree.create_node(symb, ii)
for tri in temptree:
tree.paste(ii, tri)
ast.append(tree)
elif ins == 'AC':
print 'succeed'
tree = ast.pop()
tree.show()
return
raise CompiledError('%s compiled failed at %d, unexpected token' %
(test[0], ltest - len(test)))
def ID3(data):
tree = Tree()
return __ID3(tree, data, None, None, None, {}, 0)
def help_func_block(grammar, tokens, root_name="block", function=None):
#go line by line
#if }
#return tree
#if {
#recursive help_func_block
#grab up to till first ;
#call expression handeler on that sub list
#returns a tree which is appended
tree = Tree()
root_node = Node(tag=root_name)
tree.add_node(root_node, parent=None)
func_flag_no_init = 0
func_flag_init = 0
func_flag = 0
front_index = 0
num_tokens_to_skip = 0
i = 0
while (i < len(tokens)):
if (tokens[i][0] == "}"):
return [tree, num_tokens_to_skip + 1]
elif (tokens[i][0] == "{"):
result = help_func_block(grammar,
tokens[i + 1:],
function=function)
front_index += 1 + result[1]
i += 1 + result[1]
num_tokens_to_skip += 1 + result[1]
tree.paste(root_node.identifier, result[0])
elif (tokens[i][0] in ["if", "while"]):
if_node = Node(tag=tokens[i][0])
tree.add_node(if_node, parent=root_node)
if_cond = Node(tag="condition")
tree.add_node(if_cond, parent=if_node)
first_bracket = -1
for token in tokens[i:]:
if (token[0] == '{'):
first_bracket = tokens.index(token)
break
elif (token[0] == '}'):
# Break to throw error if unmatched
break
if (first_bracket < 0):
raise Exception(tokens[i][0] + " without body '{' on line " +
str(tokens[i][2]))
cond_result = help_func_expression(grammar,
tokens[i + 2:first_bracket - 1],
function=function)
body_result = help_func_block(grammar,
tokens[first_bracket + 1:],
root_name="condition_body",
function=function)
# Increment i, num_tokens_to_skip, and front_index
if_skip = 1 # if/while
if_skip += 1 # opening bracket
if_skip += 2 # parens
if_skip += cond_result[1]
if_skip += body_result[1]
num_tokens_to_skip += if_skip
front_index += if_skip
i += if_skip
tree.paste(if_cond.identifier, cond_result[0])
tree.paste(if_node.identifier, body_result[0])
elif (tokens[i][0] == "return"):
result = help_func_return(grammar, tokens[i:], function=function)
front_index += result[1]
i += result[1]
num_tokens_to_skip += result[1]
tree.paste(root_node.identifier, result[0])
elif (tokens[i][0] == ";"):
back_index = i
expr_tokens = tokens[front_index:back_index]
# Remove leading and trailing ( and )
while (len(expr_tokens) > 0
and (expr_tokens[0][0] == '(' or expr_tokens[0][0] == ')')):
expr_tokens.pop(0)
num_tokens_to_skip += 1
while (len(expr_tokens) > 0 and
(expr_tokens[-1][0] == '(' or expr_tokens[-1][0] == ')')):
expr_tokens.pop(-1)
num_tokens_to_skip += 1
if (len(expr_tokens) > 0):
if (len(expr_tokens) == 2
and expr_tokens[0][1] == 'typeSpecifier'
and expr_tokens[1][1] == 'ID'):
func_flag = 1
func_flag_no_init = 1
# print("This is a variable declaration with no intilization")
var_type = expr_tokens[0][0]
var_name = expr_tokens[1][0]
__symbol_tables[function][var_name] = var_type
expr_tokens.pop(0)
elif (len(expr_tokens) > 2
and expr_tokens[0][1] == 'typeSpecifier'
and expr_tokens[1][1] == 'ID'
and expr_tokens[2][1] == '='):
func_flag = 1
# print("This is a variable declaration with intilization")
var_type = expr_tokens[0][0]
var_name = expr_tokens[1][0]
__symbol_tables[function][var_name] = var_type
expr_tokens.pop(0)
if (func_flag == 1):
tmp_tree = Tree()
tmp_tree_root = Node(tag=var_type)
tmp_tree.add_node(tmp_tree_root, parent=None)
tmp_tree.add_node(Node(tag=var_name), parent=tmp_tree_root)
result = help_func_expression(grammar,
expr_tokens,
function=function)
if (func_flag == 1):
result[1] += 1
front_index = back_index + 1
i += 1
num_tokens_to_skip += 1 + result[1]
if (func_flag_no_init != 1):
tree.paste(root_node.identifier, result[0])
if (func_flag == 1):
# pass
tree.paste(root_node.identifier, tmp_tree)
func_flag_no_init = 0
func_flag_init = 0
func_flag = 0
tmp_tree = None
else:
i += 1
# Iterated through tokens without closing '}'
raise Exception(errors.ERR_NO_BLOCK_END + " on line " +
str(tokens[i - 1][2]))
def help_func_funDeclaration(grammar, tokens):
#first token is return type
#the next token is the name
#the third token is the (
#sometime after that should be a
#)
assert (len(tokens) >= 4)
tree = Tree()
# organization nodes
return_node = Node(tag="return_type")
params_node = Node(tag="params")
body_node = Node(tag="func_body")
# create root node
if (tokens[1][0] == "_start"):
raise Exception("Function name _start is reserved for assembly")
elif (tokens[1][0] == "main"):
tokens[1][0] = "_start"
func_name = tokens[1][0]
func_root = Node(tag="func:" + func_name)
return_type = Node(tag=tokens[0][0])
# Create symbol subtable
__symbol_tables[func_name] = {}
# Assemble basic subtree
tree.add_node(func_root, parent=None)
tree.add_node(return_node, parent=func_root)
tree.add_node(params_node, parent=func_root)
tree.add_node(return_type, parent=return_node)
# Create and add params nodes
params = []
var_case = 0 # 0 = empty, 1 = void, 2 = variables
for i in range(3, len(tokens), 3):
if (i == 3 and tokens[i][0] == 'void'):
var_case = 1
break
elif (tokens[i][0] == ")"):
break
else:
try:
params.append((tokens[i][0], tokens[i + 1][0]))
# i+0 = type
# i+1 = name
# i+3 = comma if it exists
var_case = 2
except:
raise Exception(errors.ERR_BAD_FUNC_PAR + " '" + tokens[i][0] +
"' on line " + str(tokens[i][2]))
if (tokens[i + 2][0] != ','):
break
for param in params:
type_node = Node(tag=param[0])
name_node = Node(tag=param[1])
tree.add_node(type_node, parent=params_node)
tree.add_node(name_node, parent=type_node)
#check grammar rules
# Create and add body
body_tokens = []
skip_tokens = 0
if (var_case % 3 == 0):
# Empty parameters
body_tokens = tokens[5:]
skip_tokens = 5
pass
elif (var_case % 3 == 1):
# Void parameter
body_tokens = tokens[6:]
skip_tokens = 6
pass
elif (var_case % 3 == 2):
# Has paremeters
body_tokens = tokens[4 + (3 * (len(params))):]
skip_tokens = 4 + (3 * (len(params)))
pass
#call help_func_block
#parser_out = run_parser(body_tokens, grammar, look_for_brace=True, root_name="func_body") #may be off by one
block_out = help_func_block(grammar,
body_tokens,
root_name="func_body",
function=func_name)
body_tree = block_out[0]
skip_tokens += block_out[1]
tree.paste(func_root.identifier, body_tree)
return [tree, skip_tokens]
def help_func_expression(grammar, tokens, function=None):
tokens_skip = 0
# Remove leading and trailing ( and )
while (len(tokens) > 0 and (tokens[0][0] == '(' or tokens[0][0] == ')')):
tokens.pop(0)
tokens_skip += 1
while (len(tokens) > 0 and (tokens[-1][0] == '(' or tokens[-1][0] == ')')):
tokens.pop()
tokens_skip += 1
# Check for subexpression denoted by parentheses
op_depth = []
depth = 0
paren_open = -1
paren_close = -1
for i in range(len(tokens)):
if (tokens[i][0] == ';'):
break # End of expression
elif (tokens[i][0] == '('):
depth += 1
paren_open = i
elif (tokens[i][0] == ')'):
paren_close = i
depth -= 1
op_depth.append(depth)
# Find the lowest precedence operator
lowest_prec_op = []
op_precedence = {
"&&": 50,
"||": 40,
"shiftop": 35,
"mulop": 30,
"sumop": 20,
"relop": 10,
"=": 0,
"+=": 0,
"-=": 0,
"*=": 0,
"\=": 0,
"%=": 0
}
for token in tokens:
if (token[0] == ';'):
break
elif (token[1] in op_precedence):
if (len(lowest_prec_op) == 0):
lowest_prec_op = token
else:
cur_token_depth = op_depth[tokens.index(token)]
lowest_prec_depth = op_depth[tokens.index(lowest_prec_op)]
if (cur_token_depth < lowest_prec_depth):
# Higher depth guarantees replacement
lowest_prec_op = token
elif (cur_token_depth == lowest_prec_depth
and op_precedence[token[1]] <=
op_precedence[lowest_prec_op[1]]):
# To replace, must be on same depth and lower precedence
lowest_prec_op = token
if (len(lowest_prec_op) == 0):
# Check if "expression" is just a single constant
if (len(tokens) > 1 and tokens[0][1] == "ID" and tokens[1][1] == "("):
# Create node with function name
tree = Tree()
if (tokens[0][0] == "_start"):
raise Exception(
"Function name _start is reserved for assembly")
elif (tokens[0][0] == "main"):
tokens[0][0] = "_start"
call_node = Node(tag="func:" + tokens[0][0])
tree.add_node(call_node, parent=None)
tokens_skip += 2
# Children of node are function parameters
# Iterate through tokens to find each parameter
# Parameters split on ',' with depth=0
depth = 0
token_depth = []
end_point = -1
for i in range(2, len(tokens)):
tokens_skip += 1
if (tokens[i][0] == "("):
depth += 1
elif (tokens[i][0] == ")"):
depth -= 1
token_depth.append(depth)
if (depth < 0):
# End ) found
end_point = i
break
if (end_point < 0):
end_point = len(tokens)
#raise Exception("No ending ')' for function call '" +
# tokens[0][0] + "'")
# Find split points for the expressions
split_points = [2]
for i in range(len(token_depth)):
if (token_depth[i] == 0 and tokens[i + 2][0] == ','):
split_points.append(i + 3)
split_points.append(end_point)
func_params = []
for i in range(len(split_points) - 1):
# print([split_points[i], split_points[i+1]])
func_params.append(tokens[split_points[i]:split_points[i + 1]])
# Add parameters to tree
for p in func_params:
# Needs to call expression handler to evaluate parameters
# - Currently, operators in function calls are lower prec than the function for some reason
# - Exceptions caused by nesting function calls
param_node = Node(tag=p[0][0])
tree.add_node(param_node, parent=call_node)
return [tree, tokens_skip]
elif ((tokens[0][1] == "NUMCONST" or tokens[0][1] == "FLOATCONST"
or tokens[0][1] == "CHARCONST" or tokens[0][1] == "STRINGCONST"
or tokens[0][1] == "true" or tokens[0][1] == "false"
or tokens[0][1] == "ID")):
# Check for no-parameter function
if (tokens[0][0] in __symbol_tables.keys()):
# Found a function call without parameters
tokens_skip += 1
tree = Tree()
if (tokens[0][0] == "_start"):
raise Exception(
"Function name _start is reserved for assembly")
elif (tokens[0][0] == "main"):
tokens[0][0] = "_start"
value_node = Node(tag="func:" + tokens[0][0])
tree.add_node(value_node, parent=None)
return [tree, tokens_skip]
else:
# Expression is a constant or named variable
tokens_skip += 1
tree = Tree()
value_node = Node(tag=tokens[0][0])
tree.add_node(value_node, parent=None)
return [tree, tokens_skip]
else:
raise Exception("Unknown token sequence: " + str(tokens))
# Lowest precedence operator found
# Lowest precedence operator is root.
tree = Tree()
op_node = Node(tag=lowest_prec_op[0])
tree.add_node(op_node, parent=None)
# Recursive calls to make left and right subtrees
tokens_skip += 1
tokens_l = tokens[:tokens.index(lowest_prec_op)]
tokens_r = tokens[tokens.index(lowest_prec_op) + 1:]
has_tokens_l = False
for token in tokens_l:
if (token[0] != '(' and token[0] != ')'):
has_tokens_l = True
break
has_tokens_r = False
for token in tokens_r:
if (token[0] != '(' and token[0] != ')'):
has_tokens_r = True
break
if (len(tokens_l) > 0 and has_tokens_l):
expr_l = help_func_expression(grammar, tokens_l, function=function)
tree.paste(op_node.identifier, expr_l[0])
tokens_skip += expr_l[1]
else:
tokens_skip += len(tokens_l)
if (len(tokens_r) > 0 and has_tokens_r):
expr_r = help_func_expression(grammar, tokens_r, function=function)
tree.paste(op_node.identifier, expr_r[0])
tokens_skip += expr_r[1]
else:
tokens_skip += len(tokens_r)
return [tree, tokens_skip]
def help_func_selectionStmt(grammar, tokens):
# Called only by the help_func_manager
# PLACEHOLDER RETURN STATEMENT
tree = Tree()
tree.add_node(Node(tag="Placeholder Selection"), parent=None)
return [tree, 0]
def __init__(self, max_id=0):
self.tree = Tree()
def create(self,words_list,postags_list,arcs_list):
# 输入三个list
# 第一个是words_list 词语序列，词序
# 第二个词性
# 第三个是依存关系，这个也是用于构建树的关键
tree = Tree()
# 使用一层层的搭建技术
# 我们设定五个层
layer1 = []
layer2 = []
layer3 = []
layer4 = []
# layer5 = []
# print('words_list' + str(words_list))
# print('arcs_list'+str(arcs_list))
# 首节点
for i in range(len(arcs_list)):
arc_head = arcs_list[i].split(':')[0]
# 首节点
if int(arc_head) == 0:
HED_id = i
# layer1层
for i in range(len(arcs_list)):
arc_head = arcs_list[i].split(':')[0]
if int(arc_head) - 1 == int(HED_id):
node = {'node' + str(i) : 'HED'}
layer1.append(node)
# layer2层
for i in range(len(arcs_list)):
arc_head = arcs_list[i].split(':')[0]
# 说明有arc_head在layer1中，那就是这个点在layer2中
for lay in layer1:
if int(list(lay.keys())[0].lstrip('node')) == int(arc_head) - 1:
node = {'node' + str(i) : list(lay.keys())[0]}
layer2.append(node)
# layer3层
for i in range(len(arcs_list)):
arc_head = arcs_list[i].split(':')[0]
# 说明有arc_head在layer2中，那就是这个点在layer3中
for lay in layer2:
if int(list(lay.keys())[0].lstrip('node')) == int(arc_head) - 1:
node = {'node' + str(i): list(lay.keys())[0]}
layer3.append(node)
# layer4层
for i in range(len(arcs_list)):
arc_head = arcs_list[i].split(':')[0]
# 说明有arc_head在layer3中，那就是这个点在layer4中
for lay in layer3:
if int(list(lay.keys())[0].lstrip('node')) == int(arc_head) - 1:
node = {'node' + str(i): list(lay.keys())[0]}
layer4.append(node)
# print(layer1)
# print(layer2)
# print(layer3)
# print(layer4)
# 四层都构建完毕
# 下面就根据一层层的搭建树
# 首先创建根节点
if not tree.contains('HED'):
tree.create_node(str(HED_id) + ' ' + words_list[int(HED_id)],
'HED',
data=postags_list[int(HED_id)] + ' ' + arcs_list[int(HED_id)].split(':')[1])
# layer1
for lay in layer1:
nodename = list(lay.keys())[0]
parent = list(lay.values())[0]
tree.create_node(
nodename.lstrip('node') + ' ' + words_list[int(nodename.lstrip('node'))],
nodename,
parent=parent,
data=postags_list[int(nodename.lstrip('node'))] + ' ' + arcs_list[int(nodename.lstrip('node'))].split(':')[1])
# layer2
for lay in layer2:
nodename = list(lay.keys())[0]
parent = list(lay.values())[0]
tree.create_node(
nodename.lstrip('node') + ' ' + words_list[int(nodename.lstrip('node'))],
nodename,
parent=parent,
data=postags_list[int(nodename.lstrip('node'))] + ' ' + arcs_list[int(nodename.lstrip('node'))].split(':')[1])
# layer3
for lay in layer3:
nodename = list(lay.keys())[0]
parent = list(lay.values())[0]
tree.create_node(
nodename.lstrip('node') + ' ' + words_list[int(nodename.lstrip('node'))],
nodename,
parent=parent,
data=postags_list[int(nodename.lstrip('node'))] + ' ' + arcs_list[int(nodename.lstrip('node'))].split(':')[1])
# layer4
for lay in layer4:
nodename = list(lay.keys())[0]
parent = list(lay.values())[0]
tree.create_node(
nodename.lstrip('node') + ' ' + words_list[int(nodename.lstrip('node'))],
nodename,
parent=parent,
data=postags_list[int(nodename.lstrip('node'))] + ' ' + arcs_list[int(nodename.lstrip('node'))].split(':')[1])
return tree
def test_modify_node_identifier_recursively(self):
tree = Tree()
tree.create_node("Harry", "harry")
tree.create_node("Jane", "jane", parent="harry")
n = tree.get_node("jane")
self.assertTrue(n.identifier == 'jane')
# Success to modify
tree.update_node(n.identifier, identifier='xyz')
self.assertTrue(tree.get_node("jane") is None)
self.assertTrue(tree.get_node("xyz").identifier == 'xyz')
def load_tree(target_file):
with open(target_file, 'r') as infile:
dictionary = json.load(infile)
return __dictionary_to_tree(dictionary, Tree())
def help_func_varDeclaration(grammar, tokens):
# Called only by the help_func_manager
# PLACEHOLDER RETURN STATEMENT
tree = Tree()
tree.add_node(Node(tag="Placeholder Var Dec"), parent=None)
return [tree, 0]
def configure_tree_topology(self, root, degree=2, remove=False):
"""Configures the cluster's network topology as a tree.
The tree consists of the specified root node and the nodes,
which build the subtrees. The childrens are incrementally chosen,
in other words, sequentially as specified in the config file.
Arguments:
root {integer} -- The tree's root node.
Keyword Arguments:
degree {integer} -- The maximum number of children (default: {2})
remove {boolean} -- Remove the configuration (default: {False})
"""
self.logger.info("Configuring tree topology...")
tree = Tree()
root_node = self.topology.get_node(root)
tree.create_node(root_node.name, root_node.node_id)
parent_node = root
for nodex in self.topology.nodes:
if nodex.node_id == root_node.node_id:
continue
if len(tree.children(parent_node)) >= degree:
if parent_node == root and root != 0:
parent_node = 0
elif parent_node + 1 == root:
parent_node += 2
else:
parent_node += 1
tree.create_node(nodex.name, nodex.node_id, parent_node)
self.logger.info("The following tree will be configured:")
tree.show()
for nodex in self.topology.nodes:
self.logger.debug("%s:", nodex.name)
subtree = tree.subtree(nodex.node_id)
for nodey in self.topology.nodes:
if nodex.node_id == nodey.node_id:
continue
if subtree.contains(nodey.node_id):
children = tree.children(nodex.node_id)
for child in children:
if (child.identifier == nodey.node_id
or tree.is_ancestor(child.identifier,
nodey.node_id)):
nodex.add_forwarding(
nodey,
self.topology.get_node(child.identifier))
break
elif tree.parent(nodex.node_id) != None:
nodex.add_forwarding(
nodey,
self.topology.get_node(
tree.parent(nodex.node_id).identifier))
if not self.testing:
self.topology.send_forwarding_tables(remove)
class RAMSTKDataModel(object): # pragma: no cover
"""
This is the meta-class for all RAMSTK Data Models.
:ivar tree: the :class:`treelib.Tree` that will contain the
structure of the RAMSTK module being modeled..
:ivar dao: the :class:`ramstk.dao.DAO` object used to communicate
with the RAMSTK Program database.
"""
def __init__(self, dao):
"""
Initialize an RAMSTK data model instance.
:param dao: the data access object for communicating with the
RAMSTK Program database.
:type dao: :class:`ramstk.dao.DAO.DAO`
"""
# Initialize private dictionary attributes.
# Initialize private list attributes.
# Initialize private scalar attributes.
self._last_id = None
# Initialize public dictionary attributes.
# Initialize public list attributes.
# Initialize public scalar attributes.
self.dao = dao
self.tree = Tree()
self.last_id = None
# Add the root to the Tree(). This is neccessary to allow multiple
# entries at the top level as there can only be one root in a treelib
# Tree(). Manipulation and viewing of a RAMSTK module tree needs to
# ignore the root of the tree.
try:
self.tree.create_node(tag=self._tag, identifier=0, parent=None)
except (tree.MultipleRootError, tree.NodeIDAbsentError,
tree.DuplicatedNodeIdError):
pass
def do_select(self, node_id, **kwargs): # pylint: disable=unused-argument
"""
Retrieve the instance of the RAMSTK<MODULE> model for the Node ID passed.
:param int node_id: the Node ID of the data package to retrieve.
:return: the instance of the RAMSTK<MODULE> class that was requested
or None if the requested Node ID does not exist.
"""
try:
_entity = self.tree.get_node(node_id).data
except AttributeError:
_entity = None
except tree.NodeIDAbsentError:
_entity = None
return _entity
def do_select_all(self, **kwargs): # pylint: disable=unused-argument
"""
Retrieve and build the RAMSTK Module tree.
:return: an SQLAlchemy session instance.
:rtype:
"""
_root = self.tree.root
for _node in self.tree.children(_root):
self.tree.remove_node(_node.identifier)
return self.dao.RAMSTK_SESSION(
bind=self.dao.engine, autoflush=False, expire_on_commit=False)
def do_insert(self, **kwargs):
"""
Add the list of RAMSTK<MODULE> instance to the RAMSTK Program database.
:param list entities: the list of RAMSTK<MODULE> entities to add to the
RAMSTK Program database.
:return: (_error_code, _msg); the error code and associated message.
:rtype: (int, str)
"""
_entities = kwargs['entities']
_session = self.dao.RAMSTK_SESSION(
bind=self.dao.engine, autoflush=False, expire_on_commit=False)
_error_code, _msg = self.dao.db_add(_entities, _session)
_session.close()
return _error_code, _msg
def do_delete(self, node_id):
"""
Delete the instance of RAMSTK<MODULE> from the RAMSTK Program database.
:param int node_id entity: the ID of the RAMSTK<MODULE> record to be
removed from the RAMSTK Program database.
:return: (_error_code, _msg); the error code and associated message.
:rtype: (int, str)
"""
_msg = ''
_session = self.dao.RAMSTK_SESSION(
bind=self.dao.engine, autoflush=False, expire_on_commit=False)
try:
_entity = self.tree.get_node(node_id).data
_error_code, _msg = self.dao.db_delete(_entity, _session)
if _error_code == 0:
self.tree.remove_node(node_id)
except AttributeError:
_error_code = 2005
_session.close()
return _error_code, _msg
def do_update(self, node_id):
"""
Update the RAMSTK<MODULE> instance in the RAMSTK Program database.
:param entity: the RAMSTK<MODULE> instance to update in the RAMSTK Program
database.
:return: (_error_code, _msg); the error code and associated message.
:rtype: (int, str)
"""
_error_code = 0
_msg = ''
_session = self.dao.RAMSTK_SESSION(
bind=self.dao.engine,
autoflush=True,
autocommit=False,
expire_on_commit=False)
try:
_entity = self.tree.get_node(node_id).data
if _entity is not None:
_session.add(_entity)
_error_code, _msg = self.dao.db_update(_session)
except AttributeError:
_error_code = 1
_msg = ('RAMSTK ERROR: Attempted to save non-existent '
'entity with Node ID {0:s}.').format(str(node_id))
_session.close()
return _error_code, _msg
# Anjie Wang
# node.py
import zmq
import time
import sys
import threading
import config
from treelib import Node, Tree
# lieutenant don't start sending msg until they receive general's cmd (flag=True)
flag = False
# tree for storing received msg
tree = Tree()
cur_sum = 0
cur_round = 0
list = []
# identity of actor
identity = ""
lock = threading.Lock()
# change the msg of "attack/retreat" if the lieutenant if faulty
def process_msg(msg):
global identity
if identity == "lf":
# faulty lieutenant
return "retreat " + msg.split(" ", 1)[1]
else:
return msg
def __init__(self):
self.mfest = load_manifest("../chapters.yaml")
self.books = {}
self.chaps = {}
for adef in self.mfest:
for defheader, defs in adef.items():
if not defheader.startswith("BOOK_"):
self.chaps[defheader] = defs
else:
self.books[defheader] = defs
#
# nested dict approach, not working very well
'''
for title, bookchaps in self.books.items():
print ("BOOK: {title}".format(title=title))
print ("+" * 80)
book = {title: bookchaps}
pprint (book)
print ("-" * 80)
pprint (expand_def(book, self.chaps))
print ("*" * 80)
#pprint(books)
'''
#
# tree approach, better
self.treechap = {}
for title, chap in self.chaps.items():
self.treechap[title] = create_tree({title: chap})
self.treebook = {}
for title, book in self.books.items():
self.treebook[title] = create_tree({title: book})
for title, tree in self.treebook.items():
# tree.show()
for node in tree.expand_tree(mode=Tree.DEPTH):
# print ("+", node)
realtag = node
if type(realtag) is Node:
realtag = node.tag
if "|" in realtag:
realtag = realtag.split("|")[1]
if realtag.startswith("$ref:"):
chapkey = realtag.split("$ref:")[1]
newtree = Tree(tree=self.treechap[chapkey], deep=True)
# move up its children to replace totally the root
subtree = newtree.subtree(
newtree.children(newtree.root)[0].tag)
newtree = subtree
for anode in tree.children(node):
origtag = anode.tag
if "|" in origtag:
origtag = anode.tag.split("|")[1]
# print (origtag)
newtree.create_node(timestamp_node(origtag),
origtag,
parent=newtree.root,
data=time())
# find parent node of the node to be replaced
parent = tree.parent(node)
# use the old timestamp data to preserve insertion order
newtree.get_node(
newtree.root).data = tree.get_node(node).data
# remove old node
tree.remove_subtree(node)
# replace with new expanded node
tree.paste(parent.identifier, newtree)
def __init__(self):
Tree.__init__(self)
class StepParse:
def __init__(self):
pass
def load_step(self, step_filename):
self.nauo_lines = []
self.prod_def_lines = []
self.prod_def_form_lines = []
self.prod_lines = []
self.filename = os.path.splitext(step_filename)[0]
line_hold = ''
line_type = ''
# Find all search lines
with open(step_filename) as f:
for line in f:
# TH: read pointer of lines as they are read, so if the file has text wrap it will notice and add it to the following lines
index = re.search("#(.*)=", line)
if index:
# TH: if not none then it is the start of a line so read it
# want to hold line until it has checked next line
# if next line is a new indexed line then save previous line
if line_hold:
if line_type == 'nauo':
self.nauo_lines.append(line_hold)
elif line_type == 'prod_def':
self.prod_def_lines.append(line_hold)
elif line_type == 'prod_def_form':
self.prod_def_form_lines.append(line_hold)
elif line_type == 'prod':
self.prod_lines.append(line_hold)
line_hold = ''
line_type = ''
prev_index = True # TH rememeber previous line had an index
if 'NEXT_ASSEMBLY_USAGE_OCCURRENCE' in line:
line_hold = line.rstrip()
line_type = 'nauo'
elif ('PRODUCT_DEFINITION ' in line
or 'PRODUCT_DEFINITION(' in line):
line_hold = line.rstrip()
line_type = 'prod_def'
elif 'PRODUCT_DEFINITION_FORMATION' in line:
line_hold = line.rstrip()
line_type = 'prod_def_form'
elif ('PRODUCT ' in line or 'PRODUCT(' in line):
line_hold = line.rstrip()
line_type = 'prod'
else:
prev_index = False
#TH: if end of file and previous line was held
if 'ENDSEC;' in line:
if line_hold:
if line_type == 'nauo':
self.nauo_lines.append(line_hold)
elif line_type == 'prod_def':
self.prod_def_lines.append(line_hold)
elif line_type == 'prod_def_form':
self.prod_def_form_lines.append(line_hold)
elif line_type == 'prod':
self.prod_lines.append(line_hold)
line_hold = ''
line_type = ''
else:
#TH: if not end of file
line_hold = line_hold + line.rstrip()
self.nauo_refs = []
self.prod_def_refs = []
self.prod_def_form_refs = []
self.prod_refs = []
# TH: added 'replace(","," ").' to replace ',' with a space to make the spilt easier if there are not spaces inbetween the words'
# Find all (# hashed) line references and product names
# TH: it might be worth finding a different way of extracting data we do want rather than fixes to get rid of the data we don't
for j in range(len(self.nauo_lines)):
self.nauo_refs.append([
el.rstrip(',')
for el in self.nauo_lines[j].replace(",", " ").replace(
"=", " ").split() if el.startswith('#')
])
for j in range(len(self.prod_def_lines)):
self.prod_def_refs.append([
el.rstrip(',') for el in self.prod_def_lines[j].replace(
",", " ").replace("=", " ").split() if el.startswith('#')
])
for j in range(len(self.prod_def_form_lines)):
self.prod_def_form_refs.append([
el.rstrip(',') for el in self.prod_def_form_lines[j].replace(
",", " ").replace("=", " ").split() if el.startswith('#')
])
for j in range(len(self.prod_lines)):
self.prod_refs.append([
el.strip(',')
for el in self.prod_lines[j].replace(",", " ").replace(
"(", " ").replace("=", " ").split() if el.startswith('#')
])
self.prod_refs[j].append(self.prod_lines[j].split("'")[1])
# Get first two items in each sublist (as third is shape ref)
#
# First item is 'PRODUCT_DEFINITION' ref
# Second item is 'PRODUCT_DEFINITION_FORMATION <etc>' ref
self.prod_all_refs = [el[:2] for el in self.prod_def_refs]
# Match up all references down to level of product name
for j in range(len(self.prod_all_refs)):
# Add 'PRODUCT_DEFINITION' ref
for i in range(len(self.prod_def_form_refs)):
if self.prod_def_form_refs[i][0] == self.prod_all_refs[j][1]:
self.prod_all_refs[j].append(self.prod_def_form_refs[i][1])
break
# Add names from 'PRODUCT_DEFINITION' lines
for i in range(len(self.prod_refs)):
if self.prod_refs[i][0] == self.prod_all_refs[j][2]:
self.prod_all_refs[j].append(self.prod_refs[i][2])
break
# Find all parent and child relationships (3rd and 2nd item in each sublist)
self.parent_refs = [el[1] for el in self.nauo_refs]
self.child_refs = [el[2] for el in self.nauo_refs]
# Find distinct parts and assemblies via set operations; returns list, so no repetition of items
self.all_type_refs = set(self.child_refs) | set(self.parent_refs)
self.ass_type_refs = set(self.parent_refs)
self.part_type_refs = set(self.child_refs) - set(self.parent_refs)
# Get first two items in each sublist (as third is shape ref)
#
# First item is 'PRODUCT_DEFINITION' ref
# Second item is 'PRODUCT_DEFINITION_FORMATION <etc>' ref
self.prod_all_refs = [el[:2] for el in self.prod_def_refs]
# Match up all references down to level of product name
for j in range(len(self.prod_all_refs)):
# Add 'PRODUCT_DEFINITION' ref
for i in range(len(self.prod_def_form_refs)):
if self.prod_def_form_refs[i][0] == self.prod_all_refs[j][1]:
self.prod_all_refs[j].append(self.prod_def_form_refs[i][1])
break
# Add names from 'PRODUCT_DEFINITION' lines
for i in range(len(self.prod_refs)):
if self.prod_refs[i][0] == self.prod_all_refs[j][2]:
self.prod_all_refs[j].append(self.prod_refs[i][2])
break
# Find all parent and child relationships (3rd and 2nd item in each sublist)
self.parent_refs = [el[1] for el in self.nauo_refs]
self.child_refs = [el[2] for el in self.nauo_refs]
# Find distinct parts and assemblies via set operations; returns list, so no repetition of items
self.all_type_refs = set(self.child_refs) | set(self.parent_refs)
self.ass_type_refs = set(self.parent_refs)
self.part_type_refs = set(self.child_refs) - set(self.parent_refs)
#TH: find root node
self.root_type_refs = set(self.parent_refs) - set(self.child_refs)
self.create_dict()
def show_values(self):
# TH: basic testing, if needed these could be spilt up
print(self.nauo_lines)
print(self.prod_def_lines)
print(self.prod_def_form_lines)
print(self.prod_lines)
print(self.nauo_refs)
print(self.prod_def_refs)
print(self.prod_def_form_refs)
print(self.prod_refs)
def create_dict(self):
# TH: links nauo number with a name and creates dict
self.part_dict = {}
for part in self.all_type_refs:
for sublist in self.prod_def_refs:
if sublist[0] == part:
prod_loc = '#' + re.findall('\d+', sublist[1])[0]
pass
for sublist in self.prod_def_form_refs:
if sublist[0] == prod_loc:
prod_loc = '#' + str(re.findall('\d+', sublist[1])[0])
pass
for sublist in self.prod_refs:
if sublist[0] == prod_loc:
part_name = sublist[2]
self.part_dict[part] = part_name
def create_tree(self):
#TH: create tree diagram in newick format
#TH: find root node
self.tree = Tree()
#TH: check if there are any parts to make a tree from, if not don't bother
if self.part_dict == {}:
return
root_node_ref = list(self.root_type_refs)[0]
self.tree.create_node(self.part_dict[root_node_ref], 0)
#TH: created root node now fill in next layer
#TH: create dict for tree, as each node needs a unique name
i = [0] # itirates through nodes
self.tree_dict = {}
self.tree_dict[i[0]] = root_node_ref
def tree_next_layer(self, parent):
root_node = self.tree_dict[i[0]]
for line in self.nauo_refs:
if line[1] == root_node:
i[0] += 1
self.tree_dict[i[0]] = str(line[2])
self.tree.create_node(self.part_dict[line[2]],
i[0],
parent=parent)
tree_next_layer(self, i[0])
tree_next_layer(self, 0)
def print_tree(self):
try:
self.tree.show()
except:
self.create_tree()
self.tree.show()
def tree_to_json(self, save_to_file=False, filename='file', path=''):
#TH: return json format tree, can also save to file
if self.tree.size() != 0:
data = self.tree.to_json()
j = json.loads(data)
if save_to_file == True:
if path:
file_path = os.path.join(path, filename)
else:
file_path = filename
with open(file_path + '.json', 'w') as outfile:
json.dump(j, outfile)
return data
else:
print("no tree to print")
return
from Helper.Source import connect_to_db
Conn_Odin = connect_to_db()
# Submission of interest
AllSubmissions = pd.read_sql_query("select * from Submission_Info", Conn_Odin)
AllSubmissions[["ID_Submission", "Title"]].tail(60)
SubmissionOfInterest = "kboh0h"
Temp_Query = "select CI.ID_Comment, CI.ID_ParentID, CI.created_utc from Comment_Information CI " +\
"where ID_Submission= '{}'".format(SubmissionOfInterest)
AllComments = pd.read_sql_query(Temp_Query, Conn_Odin)
AllComments2 = AllComments.copy()
AllComments2["created_utc"] = pd.to_datetime(AllComments2.created_utc)
AllComments2 = AllComments2.sort_values("created_utc").reset_index(drop=True)
tree1 = Tree()
tree1.create_node(identifier=SubmissionOfInterest) # root node
for CommentIndex in range(len(AllComments2)):
# CommentIndex=0
ChildID = AllComments2.iloc[CommentIndex]["ID_Comment"]
ParentID = AllComments2.iloc[CommentIndex]["ID_ParentID"]
try:
tree1.create_node(identifier=ChildID, parent=ParentID)
except:
print("An exception occurred")
tree1.show()
tree1.paths_to_leaves()
len(tree1.paths_to_leaves())
class AcquisitionChainIter(object):
def __init__(self, acquisition_chain, parallel_prepare=True):
self.__sequence_index = -1
self._parallel_prepare = parallel_prepare
self.__acquisition_chain_ref = weakref.ref(acquisition_chain)
# set all slaves into master
for master in (x for x in acquisition_chain._tree.expand_tree()
if isinstance(x, AcquisitionMaster)):
del master.slaves[:]
master.slaves.extend(
acquisition_chain._tree.get_node(master).fpointer)
# create iterators tree
self._tree = Tree()
self._root_node = self._tree.create_node("acquisition chain", "root")
device2iter = dict()
for dev in acquisition_chain._tree.expand_tree():
if not isinstance(dev, (AcquisitionDevice, AcquisitionMaster)):
continue
dev_node = acquisition_chain._tree.get_node(dev)
parent = device2iter.get(dev_node.bpointer, "root")
try:
it = iter(dev)
except TypeError:
one_shot = self.acquisition_chain._device2one_shot_flag.get(
dev, True)
dev_iter = DeviceIterator(dev, one_shot)
else:
dev_iter = DeviceIteratorWrapper(it)
device2iter[dev] = dev_iter
self._tree.create_node(tag=dev.name,
identifier=dev_iter,
parent=parent)
@property
def acquisition_chain(self):
return self.__acquisition_chain_ref()
def prepare(self, scan, scan_info):
preset_tasks = list()
if self.__sequence_index == 0:
preset_tasks.extend([
gevent.spawn(preset.prepare)
for preset in self.acquisition_chain._presets_list
])
scan.prepare(scan_info, self.acquisition_chain._tree)
self._execute("_prepare",
wait_between_levels=not self._parallel_prepare)
if self.__sequence_index == 0:
gevent.joinall(preset_tasks, raise_error=True)
def start(self):
if self.__sequence_index == 0:
preset_tasks = [
gevent.spawn(preset.start)
for preset in self.acquisition_chain._presets_list
]
gevent.joinall(preset_tasks, raise_error=True)
self._execute("_start")
def stop(self):
self._execute("stop", master_to_slave=True, wait_all_tasks=True)
preset_tasks = [
gevent.spawn(preset.stop)
for preset in self.acquisition_chain._presets_list
]
gevent.joinall(preset_tasks) # wait to call all stop on preset
gevent.joinall(preset_tasks, raise_error=True)
def next(self):
self.__sequence_index += 1
gevent.joinall([
gevent.spawn(dev_iter.wait_ready)
for dev_iter in self._tree.expand_tree() if dev_iter is not 'root'
],
raise_error=True)
try:
if self.__sequence_index:
for dev_iter in self._tree.expand_tree():
if dev_iter is 'root':
continue
dev_iter.next()
except StopIteration: # should we stop all devices?
for acq_dev_iter in (
x for x in self._tree.expand_tree()
if x is not 'root' and isinstance(x.device, (
AcquisitionDevice, AcquisitionMaster))):
if hasattr(acq_dev_iter, 'wait_reading'):
acq_dev_iter.wait_reading()
dispatcher.send("end", acq_dev_iter.device)
raise
return self
def _execute(self,
func_name,
master_to_slave=False,
wait_between_levels=True,
wait_all_tasks=False):
tasks = list()
prev_level = None
if master_to_slave:
devs = list(self._tree.expand_tree(mode=Tree.WIDTH))[1:]
else:
devs = reversed(list(self._tree.expand_tree(mode=Tree.WIDTH))[1:])
for dev in devs:
node = self._tree.get_node(dev)
level = self._tree.depth(node)
if wait_between_levels and prev_level != level:
gevent.joinall(tasks, raise_error=True)
tasks = list()
prev_level = level
func = getattr(dev, func_name)
tasks.append(gevent.spawn(func))
# ensure that all tasks are executed
# (i.e: don't raise the first exception on stop)
if wait_all_tasks:
gevent.joinall(tasks)
gevent.joinall(tasks, raise_error=True)
def depth_cost(G: nx.Graph, T: tl.Tree):
return T.depth()
def tree_build_from_dict(containers=None):
"""
Build a tree based on a unsorted dictConfig(config).
Build a tree of containers based on an unsorted dict of containers.
Example:
--------
>>> containers = {'Fabric': {'parent_container': 'Tenant'},
'Leaves': {'configlets': ['container_configlet'],
'devices': ['veos01'],
'images': ['4.22.0F'],
'parent_container': 'Fabric'},
'MLAG01': {'configlets': ['container_configlet'],
'devices': ['veos01'],
'images': ['4.22.0F'],
'parent_container': 'Leaves'},
'MLAG02': {'configlets': ['container_configlet'],
'devices': ['veos01'],
'images': ['4.22.0F'],
'parent_container': 'Leaves'},
'Spines': {'configlets': ['container_configlet'],
'devices': ['veos01'],
'images': ['4.22.0F'],
'parent_container': 'Fabric'}}
>>> print(tree_build_from_dict(containers=containers))
{"Tenant": {"children": [{"Fabric": {"children": [{"Leaves": {"children": ["MLAG01", "MLAG02"]}}, "Spines"]}}]}}
Parameters
----------
containers : dict, optional
Container topology to create on CVP, by default None
Returns
-------
json
tree topology
"""
# Create tree object
tree = Tree() # Create the base node
previously_created = list()
# Create root node to mimic CVP behavior
tree.create_node("Tenant", "Tenant")
# Iterate for first level of containers directly attached under root.
for container_name, container_info in containers.items():
if container_info['parent_container'] in ['Tenant']:
previously_created.append(container_name)
tree.create_node(container_name,
container_name,
parent=container_info['parent_container'])
# Loop since expected tree is not equal to number of entries in container topology
while len(tree.all_nodes()) < len(containers) + 1:
for container_name, container_info in containers.items():
if tree.contains(
container_info['parent_container']
) and container_info['parent_container'] not in ['Tenant']:
try:
tree.create_node(container_name,
container_name,
parent=container_info['parent_container'])
except:
continue
return tree.to_json()
#!/usr/bin/env python
import click
import hashlib
from treelib import Node, Tree
merkle_tree = Tree()
merkle_tree.create_node('root', 'root')
def merkle(hashList):
"""
Calculate the Merkle Root recursively
"""
# If a single name then return the hash
if len(hashList) == 1:
return hashList[0]
newHashList = []
# Process pairs. For odd length, the last is skipped
for i in range(0, len(hashList) - 1, 2):
new_node = hash2(hashList[i], hashList[i + 1])
newHashList.append(new_node)
# If odd, hash last item twice
if len(hashList) % 2 == 1:
odd_node = hash2(hashList[-1], hashList[-1])
newHashList.append(odd_node)
return merkle(newHashList)
def setUp(self):
tree = Tree()
tree.create_node("Hárry", "hárry")
tree.create_node("Jane", "jane", parent="hárry")
tree.create_node("Bill", "bill", parent="hárry")
tree.create_node("Diane", "diane", parent="jane")
tree.create_node("George", "george", parent="bill")
# Hárry
# |-- Jane
# |-- Diane
# |-- Bill
# |-- George
self.tree = tree
self.copytree = Tree(self.tree, True)
class TreeT(object):
def __init__(self, max_id=0):
self.tree = Tree()
def from_ptb_to_tree(self, line, max_id=0, leaf_id=1, parent_id=None):
# starts by ['(', 'pos']
pos_tag = line[1]
if parent_id is None:
pos_id = 0
else:
pos_id = max_id
max_id += 1
self.tree.create_node(pos_tag, pos_id, parent_id, TreeData())
parent_id = pos_id
total_offset = 2
if line[2] != '(':
# sub-tree is leaf
# line[0:3] = ['(', 'pos', 'word', ')']
word_tag = line[2]
self.tree.create_node(word_tag, leaf_id, parent_id, TreeData())
return 4, max_id, leaf_id + 1
line = line[2:]
while line[0] != ')':
offset, max_id, leaf_id = self.from_ptb_to_tree(
line, max_id, leaf_id, parent_id)
total_offset += offset
line = line[offset:]
return total_offset + 1, max_id, leaf_id
def add_height(self, tree_dep):
for n in self.tree.all_nodes():
n.data.leaves = []
for leaf in self.tree.leaves():
lid = leaf.identifier
hid = tree_dep[lid]
if hid == self.tree.root:
self.tree[lid].data.height = self.tree.depth(self.tree[lid])
for cid in [
p for p in self.tree.paths_to_leaves() if lid in p
][0]:
self.tree[cid].data.leaves += [lid]
else:
height = -1
cid = lid
cond = True
while cond:
self.tree[cid].data.leaves += [lid]
height += 1
cid = self.tree.parent(cid).identifier
cid_leaves = [l.identifier for l in self.tree.leaves(cid)]
cid_l_dep = [tree_dep[l] for l in cid_leaves if l != lid]
cond = set(cid_l_dep).issubset(set(cid_leaves))
self.tree[lid].data.height = height
x_nodes = [
n.identifier for n in self.tree.all_nodes() if n.data.leaves == []
]
for x_node in x_nodes[::-1]:
min_id = min(self.tree.children(x_node),
key=lambda c: c.data.height)
_lid = min_id.data.leaves[0]
self.tree[_lid].data.height += 1
self.tree[x_node].data.leaves += [_lid]
return True
def _from_tree_to_ptb(self, nid):
nid = self.tree.subtree(nid).root
if self.tree[nid].is_leaf():
return ' (' + self.tree[nid].tag + ' ' + self.tree[
nid].data.word + ')'
res = ' (' + self.tree[nid].tag
for c_nid in sorted(self.tree.children(nid),
key=lambda x: x.identifier):
res += self._from_tree_to_ptb(c_nid.identifier)
return res + ')'
def from_tree_to_ptb(self):
return self._from_tree_to_ptb(self.tree.root)
def from_tag_to_tree(self, tag, word, pos_id=0):
parent_id = None
for tag_nodes in tag:
if tag_nodes[0] in [CL, CR]:
c_side = tag_nodes[0]
_tag_nodes = tag_nodes[1:] if len(tag_nodes) > 1 else ['']
else:
c_side = ''
_tag_nodes = tag_nodes
self.tree.create_node(_tag_nodes[0],
pos_id,
parent=parent_id,
data=TreeData(comb_side=c_side))
parent_id = pos_id
pos_id += 1
for tag_node in _tag_nodes[1:]:
self.tree.create_node(tag_node[1:],
pos_id,
parent=parent_id,
data=TreeData(miss_side=tag_node[0]))
pos_id += 1
for l in self.tree.leaves():
if l.data.miss_side == '':
l.data.word = word
break
return pos_id
@memoize
def is_combine_to(self, side):
return self.tree[self.tree.root].data.comb_side == side
@memoize
def is_combine_right(self):
return self.is_combine_to(CR)
@memoize
def is_combine_left(self):
return self.is_combine_to(CL)
@memoize
def is_complete_tree(self):
return all([n.data.miss_side == '' for n in self.tree.all_nodes()])
@memoize
def get_missing_leaves_to(self, miss_val, side):
return [
l.identifier for l in self.tree.leaves(self.tree.root)
if l.data.miss_side == side and l.tag == miss_val
]
@memoize
def get_missing_leaves_left(self, miss_val):
return self.get_missing_leaves_to(miss_val, L)
@memoize
def get_missing_leaves_right(self, miss_val):
return self.get_missing_leaves_to(miss_val, R)
@memoize
def root_tag(self):
return self.tree[self.tree.root].tag
@memoize
def is_no_missing_leaves(self):
return all(
[l.data.miss_side == '' for l in self.tree.leaves(self.tree.root)])
@memoize
def combine_tree(self, _tree, comb_leaf):
self.tree.paste(comb_leaf, _tree.tree)
self.tree.link_past_node(comb_leaf)
return self
def tree_to_path(self, nid, path):
# Stop condition
if self.tree[nid].is_leaf():
path[nid] = []
return nid, self.tree[nid].data.height
# Recursion
flag = CR
for child in self.tree.children(nid):
cid = child.identifier
leaf_id, height = self.tree_to_path(cid, path)
if (height == 0):
# Reached end of path can add flag
path[leaf_id].insert(0, flag)
# path[leaf_id].append(flag)
if height > 0:
path[leaf_id].insert(0, nid)
# only single child will have height>0
# and its value will be the one that is returned
# to the parent
ret_leaf_id, ret_height = leaf_id, height - 1
# once we reached a height>0, it means that
# this path includes the parent, and thus flag
# direction should flip
flag = CL
return ret_leaf_id, ret_height
def path_to_tags(self, path):
tags = []
for p in path:
_res = []
_p = copy.copy(p)
if _p[0] in [CL, CR]:
_res.append(_p[0])
_p = _p[1:]
while _p[:-1]:
el_p = _p.pop(0)
_res.append(self.tree[el_p].tag)
for c in self.tree.children(el_p):
if c.identifier != _p[0]:
_res.append(R + c.tag if c.identifier > _p[0] else L +
c.tag)
_res.append(self.tree[_p[0]].tag)
tags.append(_res)
return tags
def path_to_words(self, path):
return [self.tree[k].tag for k in path]
def from_tree_to_tag(self):
path = {}
self.tree_to_path(self.tree.root, path)
return {
'tags': self.path_to_tags(path.values()),
'words': self.path_to_words(path.keys())
}
def from_ptb_to_tag(self, line, max_id, depend):
self.from_ptb_to_tree(line, max_id)
self.add_height(depend)
path = {}
self.tree_to_path(self.tree.root, path)
return self.path_to_tags(path.values())
def testUnjsonify():
tree = Tree()
tree.create_node('home', 'home')
tree.create_node('phone', 'phone', parent='home')
tree.create_node('laptop', 'laptop', parent='home')
tree.create_node('screen', 'screen', parent='laptop')
tree.create_node(19, 19, parent='home')
tree.create_node((1, 2), (1, 2), parent='screen')
j = tree.to_json()
unjsonify(j).show()
def test_subtree(self):
subtree_copy = Tree(self.tree.subtree("jane"), deep=True)
self.assertEqual(subtree_copy.parent("jane") is None, True)
subtree_copy["jane"].tag = "Sweeti"
self.assertEqual(self.tree["jane"].tag == "Jane", True)
self.assertEqual(subtree_copy.level("diane"), 1)
self.assertEqual(subtree_copy.level("jane"), 0)
self.assertEqual(self.tree.level("jane"), 1)