def test_tree2():
"""Tree2."""
root = Node("root")
s0 = Node("sub0", parent=root, edge=2)
Node("sub0B", parent=s0, foo=4, edge=109)
Node("sub0A", parent=s0, edge="")
s1 = Node("sub1", parent=root, edge="")
Node("sub1A", parent=s1, edge=7)
Node("sub1B", parent=s1, edge=8)
s1c = Node("sub1C", parent=s1, edge=22)
Node("sub1Ca", parent=s1c, edge=42)
def nodenamefunc(node):
return '%s:%s' % (node.name, node.depth)
def edgeattrfunc(node, child):
return 'label="%s:%s"' % (node.name, child.name)
r = RenderTreeGraph(root,
options=["rankdir=LR;"],
nodenamefunc=nodenamefunc,
nodeattrfunc=lambda node: "shape=box",
edgeattrfunc=edgeattrfunc)
r.to_dotfile(join(GENPATH, "tree2.dot"))
assert cmp(join(GENPATH, "tree2.dot"), join(REFPATH, "tree2.dot"))
def plot_tree(self,
filepath,
edge_prop_metric=None,
node_label_func=None,
node_shape_func=None):
"""
Function that is returning the dotprogram and saving the png in filepath.
:param filepath: Path of the file
:param node_metric_col_print_dict: Dict of what we want to print in the node
and in which format.
The structure of the Dict is: {'metric_name': {'type': type, 'digits': digits}}
type must be in ['float', 'percent', 'int']
:param edge_prop_metric: Metric to compute the proportion on each edge
:param node_label_func: Function to be apply to each node to get the label
:param node_shape_func: Function to be apply to each node to get the shape
:return: dotprogram in a string format
"""
render_tree = \
RenderTreeGraph(node=self.tree,
nodeattrfunc=lambda node:
self._get_node_attr(node,
node_label_func,
node_shape_func),
edgeattrfunc=lambda node, child:
self._get_edge_attr(node, child, edge_prop_metric))
render_tree.to_picture(filepath)
return self._to_dot(render_tree)
def get_category(save_img=None):
url = f'{trace_parts_url}/en/search/traceparts-classification-mechanical-components?CatalogPath=TRACEPARTS%3ATP01'
r = requests.get(url)
if r.status_code == 200:
soup = BeautifulSoup(r.text, 'html.parser')
root = Node('Mechanical components')
node = root
prev_level = 1
for cat in soup.find_all('span', {'class': 'treeview-node-title'}):
levels = cat.get('title').split('>')
levels = [c.strip() for c in levels]
if levels[0] == 'Mechanical components' and len(levels) > 1:
depth = len(levels) - prev_level
prev_level = len(levels)
if depth <= 0:
for i in range(abs(depth) + 1):
node = node.parent
node = Node(levels[-1], parent=node)
for pre, fill, node in RenderTree(root):
print("%s%s" % (pre, node.name))
if save_img:
RenderTreeGraph(root).to_picture(save_img)
else:
raise ConnectionError
def __init__(self, ast, filename=None):
self.root_node = None
self.keys = {}
self.nodes = deque([])
self.nodes_keys = {}
self.built(ast)
RenderTreeGraph(self.nodes[0]).to_picture(filename=filename)
def run():
hero = [CARDS['Ah'], CARDS['Qd']]
villain = [CARDS['2s'], CARDS['2d']]
board_test = [CARDS['Ad'], CARDS['Ac'], CARDS['As']]
root = Node('Root')
initial_game_state = {
'pot_size': 2,
'betting_lead': True,
'hero_stack': 97,
'last_bet': 0,
'raised': False,
'reraised': False,
'folded': False,
'villain_folded': False,
'line': []
}
game = PokerGame(None, hero, villain, None, board=board_test)
for i in range(N):
game.set_board(board_test)
game_state = copy.deepcopy(initial_game_state)
game.simulate_round(FLOP, game_state, root, initial=True)
RenderTreeGraph(root).to_picture("tree.png")
for pre, fill, node in RenderTree(root):
print("%s%s (%s) (%s) (%s) (%s)" %
(pre, str(node.name).split(":")[-1], node.get_value(),
node.get_value("regret"), node.get_value("regretSum"),
node.get_value("strategyNOT")))
def dot_render(self):
Nodes = [Node(self._nodes[0]._long_description)]
for i in range(len(self._nodes) - 1):
Nodes.append(
Node(self._nodes[i + 1]._long_description,
parent=Nodes[self._parents[i]]))
for Line in RenderTreeGraph(Nodes[0]):
print(Line)
def img_tree_visualize(data):
'''
Render tree to filename
:filename: data['config']['review_base_filename'] + tree
:format: png
'''
directory = data['config']['report_directory'] + "/img/"
filename = directory + "%s_%s.png" % (
data['config']['review_base_filename'], "tree")
RenderTreeGraph(data['tree']).to_picture(filename)
def test_tree_png():
"""Tree to png."""
root = Node("root")
s0 = Node("sub0", parent=root)
Node("sub0B", parent=s0)
Node("sub0A", parent=s0)
s1 = Node("sub1", parent=root)
Node("sub1A", parent=s1)
Node("sub1B", parent=s1)
s1c = Node("sub1C", parent=s1)
Node("sub1Ca", parent=s1c)
RenderTreeGraph(root).to_picture(join(GENPATH, "tree1.png"))
def test_tree1():
"""Tree1."""
root = Node("root")
s0 = Node("sub0", parent=root)
Node("sub0B", parent=s0)
Node("sub0A", parent=s0)
s1 = Node("sub1", parent=root)
Node("sub1A", parent=s1)
Node("sub1B", parent=s1)
s1c = Node("sub1C", parent=s1)
Node(99, parent=s1c)
RenderTreeGraph(root).to_dotfile(join(GENPATH, "tree1.dot"))
assert cmp(join(GENPATH, "tree1.dot"), join(REFPATH, "tree1.dot"))
def plot_BKtree(tree, pic_path: str = ""):
try:
from anytree import Node, RenderTree
except:
raise ImportError(
"The anytree module seems to not be installed in your environment.\nTo be able to use this method, you'll have to install it."
)
check_types([(
"pic_path",
pic_path,
[str],
)])
try:
import shutil
screen_columns = shutil.get_terminal_size().columns
except:
import os
screen_rows, screen_columns = os.popen("stty size", "r").read().split()
print("-" * int(screen_columns))
print("Bisection Levels: {}".format(max(tree["bisection_level"])))
print("Number of Centers: {}".format(len(tree["center_id"])))
print("Total Size: {}".format(max(tree["cluster_size"])))
print("-" * int(screen_columns))
tree_nodes = {}
for idx in range(len(tree["center_id"])):
tree_nodes[tree["center_id"][idx]] = Node(
"[{}] (Size = {} | Score = {})".format(
tree["center_id"][idx],
tree["cluster_size"][idx],
round(tree["withinss"][idx] / tree["totWithinss"][idx], 2),
))
for idx, node_id in enumerate(tree["center_id"]):
if (tree["left_child"][idx] in tree_nodes
and tree["right_child"][idx] in tree_nodes):
tree_nodes[node_id].children = [
tree_nodes[tree["left_child"][idx]],
tree_nodes[tree["right_child"][idx]],
]
for pre, fill, node in RenderTree(tree_nodes[0]):
print("%s%s" % (pre, node.name))
if pic_path:
from anytree.dotexport import RenderTreeGraph
RenderTreeGraph(tree_nodes[0]).to_picture(pic_path)
if isnotebook():
from IPython.core.display import HTML, display
display(HTML("<img src='{}'>".format(pic_path)))
def plot_tree(tree, metric: str = "probability", pic_path: str = ""):
try:
from anytree import Node, RenderTree
except:
raise Exception(
"You must install the anytree module to be able to plot trees.")
check_types([("metric", metric, [str], False),
("pic_path", pic_path, [str], False)])
try:
import shutil
screen_columns = shutil.get_terminal_size().columns
except:
import os
screen_rows, screen_columns = os.popen('stty size', 'r').read().split()
tree_id, nb_nodes, tree_depth, tree_breadth = tree["tree_id"][0], len(
tree["node_id"]), max(tree["node_depth"]), sum(
[1 if item else 0 for item in tree["is_leaf"]])
print("-" * int(screen_columns))
print("Tree Id: {}".format(tree_id))
print("Number of Nodes: {}".format(nb_nodes))
print("Tree Depth: {}".format(tree_depth))
print("Tree Breadth: {}".format(tree_breadth))
print("-" * int(screen_columns))
tree_nodes = {}
for idx in range(nb_nodes):
op = "<" if not (tree["is_categorical_split"][idx]) else "="
if (tree["is_leaf"][idx]):
tree_nodes[tree["node_id"][idx]] = Node(
'[{}] => {} ({} = {})'.format(
tree["node_id"][idx], tree["prediction"][idx], metric,
tree["probability/variance"][idx]))
else:
tree_nodes[tree["node_id"][idx]] = Node('[{}] ({} {} {} ?)'.format(
tree["node_id"][idx], tree["split_predictor"][idx], op,
tree["split_value"][idx]))
for idx, node_id in enumerate(tree["node_id"]):
if not (tree["is_leaf"][idx]):
tree_nodes[node_id].children = [
tree_nodes[tree["left_child_id"][idx]],
tree_nodes[tree["right_child_id"][idx]]
]
for pre, fill, node in RenderTree(tree_nodes[1]):
print("%s%s" % (pre, node.name))
if (pic_path):
from anytree.dotexport import RenderTreeGraph
RenderTreeGraph(tree_nodes[1]).to_picture(pic_path)
if (isnotebook()):
from IPython.core.display import HTML, display
display(HTML("<img src='{}'>".format(pic_path)))
def printTree(edges_list):
# create root
root = Node("Root")
for (node1, node2) in edges_list:
Node(node2, parent=find_by_attr(root, node1))
for pre, _, node in RenderTree(root):
print("%s%s" % (pre, node.name))
# Print to file --- GRAPVIZ MUST BE INSTALLED!!!
installed_packages = [
"%s" % i.key for i in pip.get_installed_distributions()
]
if 'graphviz' in installed_packages:
RenderTreeGraph(root).to_picture("../Outputs/Part3/tree.png")
print('Tree generated correctly')
def buildMap(bnde, resources):
#print "ENtre a buildMap con ",bnde
#print bnde
#print "tipo ",type(bnde)
bnode = simplenode(bnde, parent=None)
bnode.setFPath()
#print "<resources>\n",'\n'.join(resources),'\n</resources>'
for res in resources:
resource = res.split('//')[1]
# Que pasa cuando no tiene el protocolo? tengo que ver si se realizo lo anterior
dirlist = resource.split('/')[1:]
agrega(bnode, dirlist)
dom = ''.join(parseurls.getDomain(bnode.getUrl()).split('://')[1]).replace(
'www.', '')
try:
RenderTreeGraph(bnode).to_picture(dom + '.jpg')
except:
print 'Cant write sitemap imagefile'
return bnode
def main(argv):
inputUrl = ''
inputDepth = 0
try:
opts, args = getopt.getopt(argv, "hu:d:", ["rootUrl=", "depth="])
except getopt.GetoptError:
print('index.py -u <url> -d <depth>')
sys.exit(2)
for opt, arg in opts:
if opt == '-h':
print('index.py -u <url> -d <depth>')
sys.exit()
elif opt in ("-u", "--rootUrl"):
inputUrl = arg
elif opt in ("-d", "--depth"):
inputDepth = int(arg)
print('Input url --> ', inputUrl)
print('Depth --> ', inputDepth)
rootNode = Node(inputUrl)
iterative_deepening_search(rootNode, inputDepth)
print("--------------------------------------------")
print("Finalizando com >>>Iterative Deepening Search<<<<!")
print("--------------------------------------------")
print("Estrutura da árvore")
print("--------------------------------------------")
print(RenderTree(rootNode, style=DoubleStyle()).by_attr())
#
# for pre, fill, node in RenderTree(rootNode):
# print("%s%s" % (pre, node.name))
#
#
RenderTreeGraph(rootNode).to_picture("tree.png")
def render_tree(tree, filepath):
"""Wrapper around rendering trees into `png` or `dot` formats. Tree are
rendered from the root node.
Args:
tree (NodeMixin):
filepath (str|Path):
"""
from anytree.dotexport import RenderTreeGraph
tree = RenderTreeGraph(tree.root)
base, ext = os.path.splitext(filepath)
if ext == '.png':
tree.to_picture(filename=filepath)
elif ext == '.dot':
tree.to_dotfile(filename=filepath)
else:
raise Exception
def save_to_file(self, filename):
def edgeattrfunc(node, child):
return 'label=' + str(child.value)
def nodeattrfunc(node):
attr = 'shape='
if node.is_leaf:
attr += 'ellipse'
else:
attr += 'rectangle'
return attr
def nodenamefunc(node):
name = node.name
if node.is_root:
name += '\n' + 'Height(%d)' % node.height
name += '\n' + 'id(%d)' % node._id
return name
RenderTreeGraph(self.tree,
nodeattrfunc=nodeattrfunc,
edgeattrfunc=edgeattrfunc,
nodenamefunc=nodenamefunc).to_picture(filename)
def render_image(self, name):
RenderTreeGraph(self.root).to_picture(name)
# We define the impurity degree of a node u as: ImpurityDeg(u) = |L(v) : v ∈ N(u), L(u) 6= L(v)|
# where L(u) is the label, and N(u) is the neighborhood of (the nodes adjacent to) node u.
def neighborhood_impurity(node, data):
return
# Main program
if len(sys.argv) < 3:
sys.stderr.write("Syntax : python %s json_file function_name\n" %
sys.argv[0])
else:
with open(sys.argv[1]) as data_file:
data = json.load(data_file)
requested_node = find_node(data, sys.argv[2])
entry_node = find_node(data, "external node")
root = Node("Entry node")
tree = generate_tree(entry_node, data, root)
for pre, fill, node in RenderTree(tree):
print("%s%s" % (pre, node.name))
from anytree.dotexport import RenderTreeGraph
RenderTreeGraph(tree).to_picture("Callgraph.png")
print("\nThe results for node", sys.argv[2], "are:")
print("Node degree (out, in):", node_degree(requested_node, data))
print("Node path length:", node_path_length(tree))
dot_graph = nx.drawing.nx_agraph.read_dot(sys.argv[1])
data = json_graph.node_link_data(dot_graph)
data['links'] = [{
'source': data['nodes'][link['source']]['id'],
'target': data['nodes'][link['target']]['id']
} for link in data['links']]
with open(sys.argv[2]) as cvss3_file:
cvss3_data = json.load(cvss3_file)
interface = sys.argv[3] if len(sys.argv) > 3 else "external node"
entry_node = find_node(data, interface)
root = Node(interface)
tree = generate_tree(entry_node, root)
results_json = {}
RenderTreeGraph(tree).to_picture(sys.argv[1] + "_callgraph.png")
# For testing purposes only -- Displays the current tree
# for pre, fill, node in RenderTree(tree):
# print("%s%s" % (pre, node.name))
for node in data["nodes"]:
if "label" in node:
node_name = node['label']
else:
node_name = node['id']
generate_json(node['id'])
with open(sys.argv[1] + '_node_attributes.json', 'w') as fp:
json.dump(results_json, fp)
#for pre, _, node in RenderTree(top):
# treestr = u"%s%s" % (pre, node.name)
# print(treestr.ljust(8), node.state_number)
def print_as_tabs(prev_state,next_state,input_label,output_label):
print(str(prev_state) + "\t" + str(next_state) + "\t"+ str(input_label) + "\t" + str(output_label))
# In[222]:
p=PreOrderIter(top)
p=itertools.islice(p,1,None) #pass root
print_as_tabs(0,1,"<s>","<s>")
print_as_tabs(1,0,"<eps>","<eps>")
print_as_tabs(0,2,"</s>","</s>")
print_as_tabs(2,0,"<eps>","<eps>")
print_as_tabs(0,3,"<unk>","<unk>")
print_as_tabs(3,0,"<eps>","<eps>")
for n in p:
parent_state_number=n.parent.state_number
if n.parent.state_number!=0:
parent_state_number+=3
print_as_tabs(parent_state_number,n.state_number+3,n.name,n.name)
if n.is_leaf:
print_as_tabs(n.state_number+3,0,"+PRN","#")
print("0")
RenderTreeGraph(top).to_picture("udo.png")
if isSafe(tup, pos - 1):
subNode = Node(tup, parent=initial_node, depth=pos)
if pos < len(initial_node.name):
generate_children(subNode, pos + 1)
# generate_tree creates the initial node specified by length and creates the children
def generate_tree(length):
initial_tuple = (-1, ) * length
initial_node = Node(initial_tuple, depth=0)
generate_children(initial_node)
return initial_node
def solutions(root):
for child in root.children:
if child.depth == len(root.name):
solution.append(child.name)
solutions(child)
test_tree = generate_tree(8)
solutions(test_tree)
print solution
print boardIsSafe((0, 2, 4, 1, 3))
# for pre,fill, node in RenderTree(test_tree):
# print("%s%s" % (pre,node.name))
RenderTreeGraph(test_tree).to_picture("state_tree_3.png")
# Hit rock bottom, node does not contain text
# Record this node, then return
if v: print("_0_\nheading: {}\t level:{}".format(nodeHead(node),node.level))
newNode = Node(nodeHead(node), parent=lastNode)
else:
# Node has something which could be children. Recursively call this function for all legitimate node-children
lastNode = Node(nodeHead(node), parent=lastNode)
for nextNode in node.content:
if isNode(nextNode) and isinstance(nextNode, PyOrgMode.OrgElement):
gobbleBranch(nextNode,lastNode)
return
# Traverse the tree
gobbleBranch(trunk,lastNode)
# The location of the root node is a bit off
actualRoot = root.children[0]
actualRoot.name = "Org File Root"
# Render the tree in text
for pre, fill, node in RenderTree(actualRoot):
# two ways to do the same thing
#print("{}{}".format(pre.encode('utf-8'), node.name.encode('utf-8')))
print("%s%s" % (pre, node.name))
# Render the tree as an image
from anytree.dotexport import RenderTreeGraph
RenderTreeGraph(actualRoot).to_picture(args.image)
# Source tangled from org_tree.org
#plt.show()
plt.savefig('outputs/maptile.png')
if __name__ == '__main__':
REGIONS_URI = './data/bounds_coahuila.tsv'
FOSAS_URI = './data/OperativosdeCampo2017-2020.xlsx'
geodf = build_geodf(REGIONS_URI)
### creating a geographic tree from geo-data frame
geotree = build_geotree(geodf)
### initial tree
RenderTreeGraph(geotree).to_picture("outputs/inittree.png")
### loading findings data
geotree.load_findings(FOSAS_URI)
### query geoparser ws with findings data
geotree.geoparse_findings()
### final tree
RenderTreeGraph(geotree).to_picture("outputs/finaltree.png")
### save new data
tree_df = tree_as_df(geotree)
tree_df.to_file('outputs/spatial_data.json', driver="GeoJSON")
### save map
error()
check_point(FACTOR[1], followset=FACTOR[0], patron_follow=ID_NUM)
return temp
# PROGRAMA PRINCIPAL
actualizar_token()
raiz = programa()
if not os.path.exists(directorio_sintactico):
os.makedirs(directorio_sintactico)
with open(directorio_sintactico + os.path.sep + ARBOL_TXT,
"w") as archivo_arbol:
archivo_arbol.write(str(RenderTree(raiz, style=AsciiStyle())))
if os.name == 'posix':
RenderTreeGraph(raiz, nodeattrfunc=lambda node: "shape = box").to_picture(
directorio_sintactico + os.path.sep + ARBOL_PNG)
elif os.name == 'nt':
RenderTreeGraph(raiz, nodeattrfunc=lambda node: "shape = box").to_dotfile(
directorio_sintactico + os.path.sep + ARBOL_DOT)
comando = "dot " + directorio_sintactico + os.path.sep + ARBOL_DOT + " -T png -o " + directorio_sintactico + os.path.sep + ARBOL_PNG
startupinfo = subprocess.STARTUPINFO()
startupinfo.dwFlags |= subprocess.STARTF_USESHOWWINDOW
subprocess.call(comando, startupinfo=startupinfo)
with open(directorio_sintactico + os.path.sep + "errores_sintacticos.txt",
"w") as archivo_errores_sintacticos:
for error in errores:
archivo_errores_sintacticos.write(error + '\n')
def renderTreeGraph(self):
# graphic needs to be installed for the next line!
RenderTreeGraph(self.root).to_picture("tree.png")
soup = drink_soup(url)
#common_classes,class_to_class_list_map = find_common_classes(url)
#common_ids = find_common_id_bases(soup)
#common_classes.sort(key=lambda x: x[1], reverse=True)
#single_parent_classes = OrderedDict()
#for common_class in common_classes:
# parent_classes = find_common_parent_classes(soup, class_to_class_list_map[common_class[0]])
# if len(parent_classes)==1:
# single_parent_classes[common_class] = parent_classes[0][0]
homes = soup.find_all(class_="HomeCardV2 card-frame")
home_ex = homes[0]
home_tree = find_base_info(home_ex, "--")
print_tree(home_tree)
RenderTreeGraph(home_tree).to_picture("test.png")
def get_facts(tree):
facts = []
for pre, fill, node in RenderTree(home_tree):
if node.name != "":
for sibling in node.siblings:
if sibling.name != "":
facts.append(
tuple(
sorted((node.name, sibling.name),
cmp=locale.strcoll,
reverse=True)))
facts = list(set(facts))
return facts
def generate_dotfile(self, name):
RenderTreeGraph(self.root).to_dotfile(name)
for course in coursesInFile:
courses[course['course_code']] = course
selectedCourse = ''
print('--------------Welcome to the UCalgary Prerequisites Wizard!-----------')
selectedCourse = input(
'Select a UCalgary course you want to generate a prerequisites-tree from:')
prerequisitesTree = getPrerequisites(selectedCourse, courses)
importer = DictImporter()
root = importer.import_(prerequisitesTree)
RenderTreeGraph(root).to_picture("tree.png")
print('`tree.png` has been generated.')
if sys.platform == 'win32':
subprocess.Popen(['start', 'tree.png'], shell=True)
elif sys.platform == 'darwin':
subprocess.Popen(['open', 'tree.png'])
else:
try:
subprocess.Popen(['xdg-open', 'tree.png'])
except OSError:
print('Can\'t open file in system.')
# er, think of something else to try
# xdg-open *should* be supported by recent Gnome, KDE, Xfce
# H(y_col) - H(y_col|column)
d[c] = h - self.get_info_gain_byc(c)
return max(d, key=d.get)
## Generate Decision Tree
def train_decision_tree(self,node):
c = self.get_max_info_gain()
for v in pd.unique(self.dataset[c]):
gb = self.dataset[self.dataset[c] == v].groupby(self.label)
curr_node = Node('%s-%s' % (c, v), parent=node)
if len(self.dataset.columns) > 2:
if len(gb) == 1:
Node(self.dataset[self.dataset[c] == v].groupby(c)[self.label].first().iloc[0], parent=curr_node)
else:
self.dataset = self.dataset[self.dataset[c] == v].drop(c, axis=1)
self.train_decision_tree(curr_node)
else:
Node(self.dataset[self.dataset[c] == v].groupby(self.label).size().idxmax(), parent=curr_node)
if __name__ == "__main__":
df = pd.read_csv('Decision Tree\Dataset\dataset_training.csv')
print(df)
Decision_Tree = Decision_Tree(df,'Infected')
root_node = Decision_Tree.create()
for pre, fill, node in RenderTree(root_node):
print("%s%s" % (pre, node.name))
RenderTreeGraph(root_node).to_picture("decision_tree_id3.png")
parent=node)
print('bot', next_node.name)
explore_frontier(next_node, 'Top')
if left == ' ' and direction != 'Left':
next_node = Node('(' + str(yCord) + ',' + str(xCord - 1) + ')',
parent=node)
print('left', next_node.name)
explore_frontier(next_node, 'Right')
if right == ' ' and direction != 'Right':
next_node = Node('(' + str(yCord) + ',' + str(xCord + 1) + ')',
parent=node)
print('right', next_node.name)
explore_frontier(next_node, 'Left')
if __name__ == "__main__":
#sys.setrecursionlimit(1000)
medium_maze = input_to_array('./Inputs/mediumMaze.txt')
for line in medium_maze:
print(line)
start = find_starting_position(medium_maze)
print(start)
start_node = Node(str(start))
visitedNodes = []
explore_frontier(start_node, 'None')
for pre, fill, node in RenderTree(start_node):
print("%s%s" % (pre, node.name))
RenderTreeGraph(start_node).to_picture("tree.png")
