def draw_clusters(self, pydot_graph):
clusters = {}
for node_name, pydot_node in self.pydot_nodes.items():
separator = self.__prefs['cluster_name_separator']
if node_name.find(separator) > 0:
cluster_name = node_name[0:node_name.find(separator)]
else:
cluster_name = node_name
# Dot doesn't handle well clusters with names that contain '-'
cluster_name = cluster_name.replace('-', '_')
is_new_cluster = True
for name, cluster in clusters.items():
if name == cluster_name:
is_new_cluster = False
cluster.add_node(pydot_node)
break
if is_new_cluster:
cluster = pydot.Cluster(cluster_name, label=cluster_name)
clusters[cluster_name] = cluster
# print("creating cluster: ", cluster_name)
cluster.add_node(pydot_node)
for cluster in clusters.values():
# for clusters of size 1, we don't want to draw a cluster box
if len(cluster.get_nodes()) == 1:
pydot_graph.add_node(cluster.get_nodes()[0])
else:
pydot_graph.add_subgraph(cluster)
def _create_base_dot(self, subheading):
dot = pydot.Dot("NOC", graph_type="digraph", strict=True)
dot.set_prog("neato")
dot.set_node_defaults(shape="none",
fontsize=14,
margin=0,
fontname="Arial")
dot.set_edge_defaults(fontsize=13, fontname="Arial")
# dot.set_page('11.7,8.3!')
# dot.set_margin(0.5)
# dot.set_ratio('fill')
dot.set_rankdir("LR")
dot.set_fontname("Arial")
dot.set_nodesep(0.3)
dot.set_splines("spline")
sg = pydot.Cluster() # 'physical', label='Physical')
# sg.set_color('gray80')
sg.set_style("invis")
# sg.set_labeljust('l')
dot.add_subgraph(sg)
title = pydot.Node(
"title",
shape="none",
label=self._title_label(self.opts.get("name"), subheading),
)
title.set_pos("0,0!")
title.set_fontsize(18)
dot.add_node(title)
return dot, sg
def _add_bundle(bundle):
count[2] += 1
subdot = pydot.Cluster(
graph_name='c%d' % count[2], URL='"%s"' % bundle.identifier.uri
)
if use_labels:
if bundle.label == bundle.identifier:
bundle_label = '"%s"' % six.text_type(bundle.label)
else:
# Fancier label if both are different. The label will be
# the main node text, whereas the identifier will be a
# kind of suptitle.
bundle_label = ('<%s<br />'
'<font color="#333333" point-size="10">'
'%s</font>>')
bundle_label = bundle_label % (
six.text_type(bundle.label),
six.text_type(bundle.identifier)
)
subdot.set_label('"%s"' % six.text_type(bundle_label))
else:
subdot.set_label('"%s"' % six.text_type(bundle.identifier))
_bundle_to_dot(subdot, bundle)
dot.add_subgraph(subdot)
return subdot
def gen_sub_block_graph(block_port_obj):
nonlocal hblock_port_name, sblock_name, sblock_port_name
if len(block_port_obj) == 2:
sblock_name = block_port_obj[0].local.name
sblock_port_name = sblock_name + '_' + block_port_obj[1].local.name
sblock_port_label = block_port_obj[1].local.name
if not file_graph.get_subgraph('cluster_' + sblock_name):
sblock_graph = pydotplus.Cluster(graph_name=sblock_name,
graph_type='digraph',
label=sblock_name)
file_graph.add_subgraph(sblock_graph)
sblock_graph = file_graph.get_subgraph('cluster_' + sblock_name)[0]
if not sblock_graph.get_node(sblock_port_name):
sblock_port = pydotplus.Node(name=sblock_port_name,
label=sblock_port_label,
shape='circle')
sblock_graph.add_node(
sblock_port
) # Hopefully, this updates the file_graph as well? Yes, seems to.
else:
hblock_port_name = block_port_obj[0].local.name
def draw_subgraphs(self, tplgy, pydot_graph):
nodes = []
tplgy.traverse(lambda node: nodes.append(node))
clusters = {}
for node in nodes:
pydot_node = self.pydot_nodes[node.name]
if not hasattr(node, 'subgraph'):
pydot_graph.add_node(pydot_node)
continue
cluster_name = str(node.subgraph)
if cluster_name in clusters:
cluster = clusters[cluster_name]
else:
# New subgraph
cluster = pydot.Cluster(cluster_name,
label=cluster_name,
style="filled")
clusters[cluster_name] = cluster
cluster.add_node(pydot_node)
for _, cluster in clusters.items():
pydot_graph.add_subgraph(cluster)
pydot_graph.write_raw('debug.dot')
def _get_subgraph(plan: Plan):
dot = pydot.Cluster(_sanitise_name(plan.name), label="Grid %s" % plan.name)
for n in plan.nodes():
if n.name is None:
raise Exception(
"Nodes must all be named! {} is missing a name".format(n))
node = pydot.Node(n.name, label=_node_label(n))
dot.add_node(node)
for u, v, edgedata in plan.edges():
edge = pydot.Edge(u.name, v.name)
label = "{}A".format(edgedata["current"])
if edgedata["phases"] == 3:
colour = COLOUR_THREEPHASE
label += " 3ϕ"
else:
colour = COLOUR_SINGLEPHASE
if edgedata.get("csa"):
label += " {}mm²".format(edgedata["csa"])
if edgedata.get("cable_lengths"):
label += "\n{} ({}m spare)".format(
" + ".join(str(l) + "m" for l in edgedata["cable_lengths"]),
sum(edgedata["cable_lengths"]) - edgedata["length"],
)
if not edgedata.get("logical"):
edge.set_label(label)
edge.set_tailport("{}-{}".format(edgedata["current"],
edgedata["phases"]))
edge.set_headport("input")
edge.set_color(colour)
dot.add_edge(edge)
return dot
def draw_tree():
from PIL import ImageTk, Image as Image_PIL
class ResizingCanvas(Canvas):
def __init__(self,parent,**kwargs):
Canvas.__init__(self,parent,**kwargs)
self.bind("<Configure>", self.on_resize)
self.height = self.winfo_reqheight()
self.width = self.winfo_reqwidth()
# self.bind_all("<MouseWheel>", self.on_mousewheel)
def on_resize(self,event):
new_width = self.master.winfo_width()
new_height = self.master.winfo_height()
#colors
col_f='#ff4e5c'
col_m='#1c3144'
col_w='#9d7a7d'
#
top = tk.Tk()
top.iconbitmap(f'{main_f}2683232.ico')
Grid.rowconfigure(top, 0, weight=1)
Grid.columnconfigure(top, 0, weight=1)
top.geometry("900x480")
top.wm_title("Tree")
frame = tk.Frame(top)
frame.grid(row=0, column=0, sticky=N+S+E+W)
#scrollbars
xscrollbar = tk.Scrollbar(frame, orient=tk.HORIZONTAL)
xscrollbar.grid(row=1, column=0, sticky="EW")
yscrollbar = tk.Scrollbar(frame)
yscrollbar.grid(row=0, column=1, sticky="NS")
canvas = ResizingCanvas(frame, xscrollcommand=xscrollbar.set, yscrollcommand=yscrollbar.set)
canvas.grid(row=0, column=0, sticky="EWNS")
canvas.configure(bg='white')
# Image
import pydotplus as pdt
import time
df=pddf(backend_app.view(), columns=c_header)
for c in ['id',
'mother_id',
'father_id',
'spouse_id',
'generation',
'cluster',
'gender' ]:
df[c]=to_numeric(df[c], downcast='integer',errors='coerce')
min_level=int(df['generation'].min())
max_level=int(df['generation'].max())
g = pdt.Dot(graph_type='digraph', compound='true', rankdir='TB',newrank = 'true')
i=0
edges = []
nodes=[]
# create all edges
from ast import literal_eval as make_tuple
nl=max_level-min_level+1
s=[None]*(max_level+1)
for i in range(min_level,max_level+1):
s = pdt.Subgraph(i,rank='same')
for j in df.loc[df['generation']==i, 'id'].values :
s.add_node(pdt.Node(f"{df.loc[df['id']==j, 'id'].values[0]}"))
g.add_subgraph(s)
min_cl=int(df['cluster'].min())
max_cl=int(df['cluster'].max())
nl=max_cl-min_cl+1
ss=[None]*(max_cl+1)
for i in range(min_cl,max_cl+1):
ss = pdt.Cluster(f'c1_{i}', color="white",rankdir="TB")
for j in df.loc[df['cluster']==i, 'id'].values :
ss.add_node(pdt.Node(f"{df.loc[df['id']==j, 'id'].values[0]}"))
g.add_subgraph(ss)
for i in range(df.shape[0]):
m=df.loc[i, 'mother_id']
f=df.loc[i, 'father_id']
nod=pdt.Node(f"{df.loc[i, 'id']}", shape='record', color=col_m, style='rounded')
if m in df['id'].values: g.add_edge(pdt.Edge(pdt.Node(f"{df.loc[df['id']==m, 'id'].values[0]}"), nod, color=col_f))
if f in df['id'].values: g.add_edge(pdt.Edge(pdt.Node(f"{df.loc[df['id']==f, 'id'].values[0]}"), nod, color=col_m))
if notnull(df.loc[i, 'spouse_id']):
who=to_numeric(df.loc[i, 'spouse_id'], downcast='integer', errors='coerce')
if who in df['id'].values:
g.add_edge(pdt.Edge(pdt.Node(f"{df.loc[df['id']==who, 'id'].values[0]}"), nod, dir='none',color=col_w)) #label='m',
for i in range(df.shape[0]):
cc=col_f
if df.loc[i, 'gender']==1: cc=col_m
sstr=f"{df.loc[i, 'name']}"
if notnull(df.loc[i, 'surname']): sstr=f"{sstr} {df.loc[i, 'surname']}"
if notnull(df.loc[i, 'date_birth']):
if isinstance(df.loc[i, 'date_birth'], int) or isinstance(df.loc[i, 'date_birth'], str):
sstr=f"{sstr}\nB: {df.loc[i, 'date_birth']}"
else:
sstr=f"{sstr}\nB: {df.loc[i, 'date_birth'].strftime('%d %b %Y') }" # %H:%M:%S
d=df.loc[i, 'date_death']
# import numpy as np
if notnull(d):
# print("ddd" , isna(d), isnull(d), d, type(d) )
sstr=f"{sstr}\nD: {d}"
if notnull(df.loc[i, 'place_birth']):
sstr=f"{sstr}\nPoB: {df.loc[i, 'place_birth']} ({df.loc[i, 'country_birth']})"
if not (isnull(df.loc[i, 'comments']) or df.loc[i, 'comments']==''):
sstr=f"{sstr}\nComments: {df.loc[i, 'comments']}"
nod=pdt.Node(f"{df.loc[i, 'id']}", label=sstr, shape='box', color=cc, style='rounded')
g.add_node(nod)
import io
buf = io.BytesIO()
g.write_png(buf)
# plt.savefig(buf, format='png')
buf.seek(0)
img_g = Image_PIL.open(buf)
img = ImageTk.PhotoImage(img_g, master=frame)
canvas.create_image(0, 0, image=img)
#scrollconfig
canvas.config(scrollregion=canvas.bbox(tk.ALL))
xscrollbar.config(command=canvas.xview)
yscrollbar.config(command=canvas.yview)
frame.grid(row=0, column=0)
frame.grid_rowconfigure(0, weight=1)
frame.grid_columnconfigure(0, weight=1)
#menu
menubar = Menu(top)
top.config(menu=menubar)
menu = Menu(menubar)
def file_save():
from tkinter.filedialog import asksaveasfilename
f = asksaveasfilename(title = "Select file",filetypes = (("png files","*.png"),("all files","*.*")), defaultextension='.png')
if f is None: # asksaveasfile return `None` if dialog closed with "cancel".
return
img_g.save(f)
menu.add_command(label='Save',command=file_save)
menu.add_command(label='Close',command=top.destroy)
# menu.add_command(label="Exit", command=window.quit)
menubar.add_cascade(label="File", menu=menu)
top.mainloop()
def draw_words(G, words, chainWords, filename):
func.print_info("drawing words onto graph")
colours = ["blue", "yellow", "seagreen", "crimson", "magenta", "cyan","darkorchid4", "peru", "cadetblue1", "magenta", "indianred2", "plum", "brown", "skyblue", "darkgreen", "darkolivegreen2", "darkslategray1", "dodgerblue", "gold", "green", "hotpink1", "indianred2", "maroon3","plum", "yellow", "tan1", "steelblue1", "violetred", "blueviolet", "darkgoldenrod", "darkorange", "olivedrab3", "palevioletred", "skyblue", "yellowgreen", "seagreen", "peru", "moccasin", "cadetblue","burlywood1", "chartreuse3", "darksalmon", "blue", "aquamarine", "brown", "blueviolet", "cadetblue1", "chocolate", "crimson", "darkgreen", "darkolivegreen2", "darkslategray1", "deeppink", "dodgerblue", "gold", "green", "hotpink1", "maroon3", "yellow", "tan1", "steelblue1", "violetred", "blueviolet", "darkgoldenrod", "darkorange", "olivedrab3", "palevioletred", "yellowgreen", "seagreen", "magenta", "peru", "moccasin", "lightpink", "darkslategray1","cadetblue","burlywood1", "chartreuse3", "darksalmon","blue", "aquamarine", "brown", "blueviolet", "cadetblue1", "chocolate", "crimson", "cyan", "darkgreen", "darkolivegreen2", "darkorchid4", "deeppink", "dodgerblue", "gold", "green", "hotpink1", "cyan","indianred2", "maroon3","plum", "yellow", "tan1", "steelblue1", "violetred", "blueviolet", "darkgoldenrod", "darkorange", "olivedrab3", "palevioletred", "skyblue", "yellowgreen", "moccasin", "lightpink", "cadetblue","burlywood1", "chartreuse3", "blueviolet", "darksalmon","blue", "brown", "blueviolet", "cadetblue1", "chocolate","chocolate", "darkorchid4", "crimson", "cyan", "darkgreen", "darkolivegreen2", "darkorchid4", "darkslategray1", "deeppink", "dodgerblue", "gold", "green", "hotpink1", "indianred2", "maroon3","plum", "aquamarine","tan1", "steelblue1", "violetred", "blueviolet", "darkgoldenrod", "darkorange", "olivedrab3", "palevioletred", "skyblue", "yellowgreen", "seagreen", "magenta", "peru", "moccasin", "lightpink", "cadetblue","burlywood1", "chartreuse3", "darksalmon","blue", "aquamarine", "brown", "blueviolet", "cadetblue1", "chocolate", "crimson", "cyan", "darkgreen", "darkolivegreen2", "darkorchid4", "darkslategray1", "deeppink", "deeppink", "lightpink", "dodgerblue", "gold", "green", "hotpink1", "indianred2", "maroon3","plum", "yellow", "tan1", "steelblue1", "violetred", "blueviolet", "darkgoldenrod", "darkorange", "olivedrab3", "palevioletred", "skyblue", "yellowgreen", "seagreen", "magenta", "peru", "moccasin", "lightpink", "cadetblue","burlywood1", "chartreuse3", "darksalmon",]
subsets = [x for x in words for y in words if y is not x and set(x).issubset(y)]
words_clean = []
for word in words:
if word not in subsets:
words_clean.append(word)
words_clean.append(func.control_wires)
if len(words_clean) <= len(colours):
H = nx.nx_pydot.to_pydot(G)
P = nx.nx_pydot.to_pydot(G)
counter = 0
I = pydotplus.Cluster("Inputs")
O = pydotplus.Cluster("Outputs")
for word in words_clean:
S = pydotplus.Cluster("word" + str(counter), style="filled", color=colours[counter])
for node in word:
S.add_node(pydotplus.Node(node))
if node.startswith("INPUT"):
I.add_node(pydotplus.Node(node))
if node.startswith("OUTPUT"):
O.add_node(pydotplus.Node(node))
if node not in [x.get_name() for x in P.get_nodes()]:
n = P.get_node("\"" + node + "\"")[0]
else:
n = P.get_node(node)[0]
n.set_style("filled")
n.set_color(colours[counter])
H.add_subgraph(S)
#~ H.add_subgraph(O)
#~ H.add_subgraph(I)
#~ P.add_subgraph(I)
#~ P.add_subgraph(O)
#@todo: fix clustering of primary inputs and outputs...
counter = counter +1
for word in chainWords:
for node in word:
if node not in [x.get_name() for x in P.get_nodes()]:
n = P.get_node("\"" + node + "\"")[0]
else:
n = P.get_node(node)[0]
#~ n.set_style("filled")
n.set_color(colours[counter])
counter = counter +1
H.write_raw("wordGraphs/" + filename + ".dot")
P.write_raw("wordGraphs/" +filename + "2.dot")
else:
print("Not enough colors to properly draw word Graph")
input()
func.print_info("Finished drawring words onto graph")
return
def make_graph(data,
show_edge_labels=True,
vertical=True,
orthogonal_lines=False):
"""
Returns the visualization object of the imported bpmn-graph.
Parameters
----------
data: DataContainer
Object that contains a graph read from the file.
show_edge_labels: boolean, default=False
If True, edges' labels are displayed in the graph.
vertical: boolean, default=True
If True, the direction from the first to the last nodes goes from up to down.
orthogonal_lines: boolean, default=False
If true, draws edges that can bend at 90 degrees only, uses splines otherwise.
Returns
-------
pydotplus_graph: pydotplus.Dot
Graph that can be visualized.
"""
pydot_node_id_dict = {} # {id: pydotplus.Node(), ...}
all_local_nodes = [
obj for obj in data.all_objects.values()
if isinstance(obj, LocalNode)
]
all_local_edges = [
obj for obj in data.all_objects.values()
if isinstance(obj, LocalEdge)
]
pydot_graph = pydotplus.Dot(strict=True)
cluster_dict = {
obj.id: pydotplus.Cluster(obj.id, color='lightblue')
for obj in all_local_nodes if not obj.is_separate_node
}
# Adding normal (separate) nodes to clusters (subgraphs)
for node in all_local_nodes:
if node.is_separate_node:
node_graph = cluster_dict[
node.parent_node.
id] if node.parent_node.id in cluster_dict else pydot_graph
PydotPlusGraphMaker._create_pydot_node(node, node_graph,
pydot_node_id_dict)
# Adding subgraphs to each other (in case one subgraph is inside another)
proc_list = list(data.all_objects[k] for k in cluster_dict.keys())
ready_subgraphs = set()
while len(proc_list) != 0:
proc = proc_list.pop(0)
subgraph_list = proc.get_subgraph_objects()
if not set(subgraph_list).issubset(ready_subgraphs):
proc_list.append(proc) # work on it later
else: # add it to upper pydot_graph
upper_proc = proc.parent_node
upper_graph = pydot_graph if upper_proc is None else cluster_dict[
upper_proc.id]
upper_graph.add_subgraph(cluster_dict[proc.id])
ready_subgraphs.add(proc)
# Modify names because graphviz can work incorrectly with specific symbols
for graph in [pydot_graph] + list(cluster_dict.values()):
graph.set_name(PydotPlusGraphMaker._modify_id(graph.get_name()))
for n in graph.get_nodes():
n.set_name(PydotPlusGraphMaker._modify_id(n.get_name()))
# Create pydotplus.Edges
for edge in all_local_edges:
if edge.type == 'attachedToRef':
color = 'pink'
else:
color = 'black'
e = pydotplus.Edge(pydot_node_id_dict[edge.source_node.id],
pydot_node_id_dict[edge.target_node.id],
color=color)
if show_edge_labels:
e.set('label', '\n'.join(edge.get_object_names()))
pydot_graph.add_edge(e)
if not vertical:
pydot_graph.set('rankdir', 'LR')
if orthogonal_lines:
pydot_graph.set('splines', 'ortho')
return pydot_graph
def draw_tree():
from PIL import ImageTk, Image as Image_PIL
c_header=['id',
'name',
'surname',
'date_birth',
'date_death',
'mother_id',
'father_id',
'spouse_id',
'generation',
'cluster',
'gender',
'place_birth',
'country_birth',
'country',
'comments'
]
# Image
import pydotplus as pdt
import time
# import pandas as pd
df=pddf(backend.view(), columns=c_header)
for c in ['id',
'mother_id',
'father_id',
'spouse_id',
'generation',
'cluster',
'gender' ]:
df[c]=to_numeric(df[c], downcast='integer',errors='coerce')
# df[c]=df[c].astype(int)
# df=pd.read_excel('c:/a_tree/gen_tree.xlsx', sheet_name=nn)
# print(df)
min_level=int(df['generation'].min())
max_level=int(df['generation'].max())
g = pdt.Dot(graph_type='digraph', compound='true', rankdir='TB',newrank = 'true')
i=0
edges = []
nodes=[]
# create all edges
#edges = [(1,2), (1,3), (2,4), (2,5), (3,5)]
#nodes = [(1, "A", "r"), (2, "B", "g"), (3, "C", "g"), (4, "D", "r"), (5, "E", "g")]
#for e in edges:
# g.add_edge(pdt.Edge(e[0], e[1], color=e[2]))
#
#for n in nodes:
# node = pdt.Node(name=n[0], label= n[1], fillcolor=n[2], style="filled" )
# g.add_node(node)
#
#
from ast import literal_eval as make_tuple
nl=max_level-min_level+1
s=[None]*(max_level+1)
for i in range(min_level,max_level+1):
s = pdt.Subgraph(i,rank='same')
for j in df.loc[df['generation']==i, 'id'].values :
# s.add_node(pdt.Node(f"{df.loc[df['id']==j, 'Name'].values[0]} {df.loc[df['id']==j, 'Surname'].values[0]}"))
s.add_node(pdt.Node(f"{df.loc[df['id']==j, 'id'].values[0]}"))
g.add_subgraph(s)
#min_cl=df['Cluster2'].min()
#max_cl=df['Cluster2'].max()
#nl=max_cl-min_cl+1
#ss=[None]*(max_cl+1)
#for i in range(min_cl,max_cl+1):
# if i>0:
# ss = pdt.Cluster(f'c2_{i}', color="blue",rankdir="TB")
# for j in df.loc[df['Cluster2']==i, 'id'].values :
# # s.add_node(pdt.Node(f"{df.loc[df['id']==j, 'Name'].values[0]} {df.loc[df['id']==j, 'Surname'].values[0]}"))
# ss.add_node(pdt.Node(f"{df.loc[df['id']==j, 'id'].values[0]}"))
# g.add_subgraph(ss)
min_cl=int(df['cluster'].min())
max_cl=int(df['cluster'].max())
nl=max_cl-min_cl+1
ss=[None]*(max_cl+1)
for i in range(min_cl,max_cl+1):
ss = pdt.Cluster(f'c1_{i}', color="white",rankdir="TB")
for j in df.loc[df['cluster']==i, 'id'].values :
# s.add_node(pdt.Node(f"{df.loc[df['id']==j, 'Name'].values[0]} {df.loc[df['id']==j, 'Surname'].values[0]}"))
ss.add_node(pdt.Node(f"{df.loc[df['id']==j, 'id'].values[0]}"))
g.add_subgraph(ss)
for i in range(df.shape[0]):
m=df.loc[i, 'mother_id']
f=df.loc[i, 'father_id']
# if m in df['id'].values: edges.append((i,df.loc[df['id']==m, 'Name'].index[0],'orange'))
# if f in df['id'].values: edges.append((i,df.loc[df['id']==f, 'Name'].index[0],'blue'))
# nodes.append((i, df.loc[i, 'Name'], 'blue'))
# nod=pdt.Node(f"{df.loc[i, 'id']}",label=f"{df.loc[i, 'Name']} {df.loc[i, 'Surname']}", shape='record', color="blue", style='rounded')
nod=pdt.Node(f"{df.loc[i, 'id']}", shape='record', color="blue", style='rounded')
if m in df['id'].values: g.add_edge(pdt.Edge(pdt.Node(f"{df.loc[df['id']==m, 'id'].values[0]}"), nod, color='orange'))
if f in df['id'].values: g.add_edge(pdt.Edge(pdt.Node(f"{df.loc[df['id']==f, 'id'].values[0]}"), nod, color='#066dba'))
if notnull(df.loc[i, 'spouse_id']):
# rel=df.loc[i, 'relation to']
# # tuple(map(int, re.findall(r'[0-9]+', rel)))
# rel=rel.replace('(','').replace(')','').split(',')
# who=pd.to_numeric(rel[0]).astype(int)
who=to_numeric(df.loc[i, 'spouse_id'], downcast='integer', errors='coerce')
# how=rel[1]
# g.add_edge(pdt.Edge(pdt.Node(f"{df.loc[df['id']==who, 'Name'].values[0]} {df.loc[df['id']==who, 'Surname'].values[0]}"), nod, dir='none',color='#bf3fbf')) #label='m',
if who in df['id'].values:
# print('yes')
g.add_edge(pdt.Edge(pdt.Node(f"{df.loc[df['id']==who, 'id'].values[0]}"), nod, dir='none',color='#bf3fbf')) #label='m',
for i in range(df.shape[0]):
cc='orange'
if df.loc[i, 'gender']==1: cc='#066dba'
sstr=f"{df.loc[i, 'name']}"
if notnull(df.loc[i, 'surname']): sstr=f"{sstr} {df.loc[i, 'surname']}"
if notnull(df.loc[i, 'date_birth']):
if isinstance(df.loc[i, 'date_birth'], int) or isinstance(df.loc[i, 'date_birth'], str):
sstr=f"{sstr}\nB: {df.loc[i, 'date_birth']}"
else:
sstr=f"{sstr}\nB: {df.loc[i, 'date_birth'].strftime('%d %b %Y') }" # %H:%M:%S
d=df.loc[i, 'date_death']
# import numpy as np
if notnull(d):
# print("ddd" , isna(d), isnull(d), d, type(d) )
sstr=f"{sstr}\nD: {d}"
if notnull(df.loc[i, 'place_birth']):
sstr=f"{sstr}\nPoB: {df.loc[i, 'place_birth']} ({df.loc[i, 'country_birth']})"
if not (isnull(df.loc[i, 'comments']) or df.loc[i, 'comments']==''):
sstr=f"{sstr}\nComments: {df.loc[i, 'comments']}"
nod=pdt.Node(f"{df.loc[i, 'id']}", label=sstr, shape='box', color=cc, style='rounded')
# nod=pdt.Node(f"{df.loc[i, 'id']}", label=f"{df.loc[i, 'Name']} {df.loc[i, 'Surname']}\nB: {df.loc[i, 'DoB']}\nD: {df.loc[i, 'DoD']}\nPoB: {df.loc[i, 'Place of Birth']} ({df.loc[i, 'Country of Birth']})", shape='box', color=cc, style='rounded')
g.add_node(nod)
import io
buf = io.BytesIO()
g.write_png(buf)
# plt.savefig(buf, format='png')
buf.seek(0)
import base64
buf_img64 = base64.b64encode(buf.getvalue())
# buf_im_str= u'data:img/jpeg;base64,'+buf_img64.decode('utf-8')
buf_im_str=buf_img64.decode("utf-8")
# img_g = Image_PIL.open(buf)
# img=Img_IP(g.create_png())
# img=g.create_png()
# return send_file(buf, mimetype='image/PNG')
# print (buf_img64)
# return render_template('image.html' , img= buf_img64.decode('ascii'))
return render_template('image.html' , img= buf_im_str)
if __name__ == '__main__':
# Generate library from file
lib = gen_library("libs.edg")
file_graph = pydotplus.Dot()
# Find hierarchy blocks in the library
for name, elt in lib.root.members.items():
# If hierarchy block, then generate a visualizer file.
if elt.HasField('hierarchy_block'):
for hport_name, _ in elt.hierarchy_block.ports.items():
hport = pydotplus.Node(name=hport_name, shape='circle')
file_graph.add_node(hport)
for link_name, _ in elt.hierarchy_block.links.items():
if not file_graph.get_subgraph('cluster_' + link_name):
link_graph = pydotplus.Cluster(graph_name=link_name,
graph_type='graph',
label=link_name)
source = pydotplus.Node(name=link_name + '_source',
label='source',
shape='circle')
sink = pydotplus.Node(name=link_name + '_sinks',
label='sinks',
shape='circle')
link_graph.add_node(source)
link_graph.add_node(sink)
file_graph.add_subgraph(link_graph)
gen_visualizer(elt, name)