[FIX] core: remove useless graph class
closes odoo/odoo#38967 Signed-off-by: Xavier Dollé (xdo) <xdo@odoo.com>
This commit is contained in:
Xavier-Do
@@ -23,7 +23,7 @@ from odoo import api, fields, models, tools, _
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from odoo.exceptions import ValidationError
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from odoo.http import request
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from odoo.modules.module import get_resource_from_path, get_resource_path
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from odoo.tools import config, graph, ConstantMapping, pycompat, apply_inheritance_specs, locate_node
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from odoo.tools import config, ConstantMapping, pycompat, apply_inheritance_specs, locate_node
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from odoo.tools.convert import _fix_multiple_roots
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from odoo.tools.json import scriptsafe as json_scriptsafe
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from odoo.tools.safe_eval import safe_eval
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@@ -1159,79 +1159,6 @@ actual arch.
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""" Open a view for editing the translations of field 'arch_db'. """
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return self.env['ir.translation'].translate_fields('ir.ui.view', self.id, 'arch_db')
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@api.model
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def graph_get(self, id, model, node_obj, conn_obj, src_node, des_node, label, scale):
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def rec_name(rec):
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return (rec.name if 'name' in rec else
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rec.x_name if 'x_name' in rec else
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None)
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nodes = []
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nodes_name = []
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transitions = []
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start = []
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tres = {}
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labels = {}
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no_ancester = []
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blank_nodes = []
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Model = self.env[model]
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Node = self.env[node_obj]
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for model_key, model_value in Model._fields.items():
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if model_value.type == 'one2many':
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if model_value.comodel_name == node_obj:
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_Node_Field = model_key
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_Model_Field = model_value.inverse_name
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for node_key, node_value in Node._fields.items():
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if node_value.type == 'one2many':
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if node_value.comodel_name == conn_obj:
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# _Source_Field = "Incoming Arrows" (connected via des_node)
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if node_value.inverse_name == des_node:
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_Source_Field = node_key
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# _Destination_Field = "Outgoing Arrows" (connected via src_node)
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if node_value.inverse_name == src_node:
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_Destination_Field = node_key
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record = Model.browse(id)
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for line in record[_Node_Field]:
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if line[_Source_Field] or line[_Destination_Field]:
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nodes_name.append((line.id, rec_name(line)))
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nodes.append(line.id)
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else:
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blank_nodes.append({'id': line.id, 'name': rec_name(line)})
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if 'flow_start' in line and line.flow_start:
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start.append(line.id)
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elif not line[_Source_Field]:
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no_ancester.append(line.id)
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for t in line[_Destination_Field]:
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transitions.append((line.id, t[des_node].id))
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tres[str(t['id'])] = (line.id, t[des_node].id)
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label_string = ""
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if label:
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for lbl in safe_eval(label):
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if tools.ustr(lbl) in t and tools.ustr(t[lbl]) == 'False':
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label_string += ' '
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else:
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label_string = label_string + " " + tools.ustr(t[lbl])
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labels[str(t['id'])] = (line.id, label_string)
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g = graph(nodes, transitions, no_ancester)
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g.process(start)
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g.scale(*scale)
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result = g.result_get()
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results = {}
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for node_id, node_name in nodes_name:
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results[str(node_id)] = result[node_id]
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results[str(node_id)]['name'] = node_name
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return {'nodes': results,
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'transitions': tres,
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'label': labels,
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'blank_nodes': blank_nodes,
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'node_parent_field': _Model_Field}
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@api.model
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def _validate_custom_views(self, model):
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"""Validate architecture of custom views (= without xml id) for a given model.
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@@ -8,7 +8,6 @@ from . import pdf
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from .config import config
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from .misc import *
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from .translate import *
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from .graph import graph
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from .image import *
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from .sql import *
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from .float_utils import *
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@@ -1,755 +0,0 @@
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#!/usr/bin/env python
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# -*- coding: utf-8 -*-
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# Part of Odoo. See LICENSE file for full copyright and licensing details.
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import operator
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import math
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class graph(object):
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def __init__(self, nodes, transitions, no_ancester=None):
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"""Initialize graph's object
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@param nodes list of ids of nodes in the graph
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@param transitions list of edges in the graph in the form (source_node, destination_node)
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@param no_ancester list of nodes with no incoming edges
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"""
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self.nodes = nodes or []
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self.edges = transitions or []
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self.no_ancester = no_ancester or {}
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trans = {}
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for t in transitions:
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trans.setdefault(t[0], [])
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trans[t[0]].append(t[1])
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self.transitions = trans
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self.result = {}
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def init_rank(self):
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"""Computes rank of the nodes of the graph by finding initial feasible tree
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"""
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self.edge_wt = {}
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for link in self.links:
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self.edge_wt[link] = self.result[link[1]]['x'] - self.result[link[0]]['x']
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tot_node = len(self.partial_order)
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#do until all the nodes in the component are searched
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while self.tight_tree()<tot_node:
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list_node = []
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list_edge = []
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for node in self.nodes:
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if node not in self.reachable_nodes:
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list_node.append(node)
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for edge in self.edge_wt:
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if edge not in self.tree_edges:
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list_edge.append(edge)
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slack = 100
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for edge in list_edge:
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if ((edge[0] in self.reachable_nodes and edge[1] not in self.reachable_nodes) or
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(edge[1] in self.reachable_nodes and edge[0] not in self.reachable_nodes)):
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if slack > self.edge_wt[edge]-1:
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slack = self.edge_wt[edge]-1
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new_edge = edge
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if new_edge[0] not in self.reachable_nodes:
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delta = -(self.edge_wt[new_edge]-1)
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else:
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delta = self.edge_wt[new_edge]-1
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for node in self.result:
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if node in self.reachable_nodes:
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self.result[node]['x'] += delta
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for edge in self.edge_wt:
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self.edge_wt[edge] = self.result[edge[1]]['x'] - self.result[edge[0]]['x']
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self.init_cutvalues()
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def tight_tree(self):
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self.reachable_nodes = []
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self.tree_edges = []
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self.reachable_node(self.start)
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return len(self.reachable_nodes)
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def reachable_node(self, node):
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"""Find the nodes of the graph which are only 1 rank apart from each other
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"""
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if node not in self.reachable_nodes:
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self.reachable_nodes.append(node)
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for edge in self.edge_wt:
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if edge[0]==node:
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if self.edge_wt[edge]==1:
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self.tree_edges.append(edge)
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if edge[1] not in self.reachable_nodes:
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self.reachable_nodes.append(edge[1])
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self.reachable_node(edge[1])
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def init_cutvalues(self):
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"""Initialize cut values of edges of the feasible tree.
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Edges with negative cut-values are removed from the tree to optimize rank assignment
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"""
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self.cut_edges = {}
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self.head_nodes = []
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i=0
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for edge in self.tree_edges:
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self.head_nodes = []
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rest_edges = []
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rest_edges += self.tree_edges
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del rest_edges[i]
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self.head_component(self.start, rest_edges)
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i+=1
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positive = 0
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negative = 0
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for source_node in self.transitions:
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if source_node in self.head_nodes:
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for dest_node in self.transitions[source_node]:
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if dest_node not in self.head_nodes:
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negative+=1
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else:
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for dest_node in self.transitions[source_node]:
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if dest_node in self.head_nodes:
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positive+=1
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self.cut_edges[edge] = positive - negative
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def head_component(self, node, rest_edges):
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"""Find nodes which are reachable from the starting node, after removing an edge
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"""
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if node not in self.head_nodes:
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self.head_nodes.append(node)
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for edge in rest_edges:
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if edge[0]==node:
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self.head_component(edge[1],rest_edges)
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def process_ranking(self, node, level=0):
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"""Computes initial feasible ranking after making graph acyclic with depth-first search
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"""
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if node not in self.result:
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self.result[node] = {'y': None, 'x':level, 'mark':0}
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else:
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if level > self.result[node]['x']:
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self.result[node]['x'] = level
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if self.result[node]['mark']==0:
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self.result[node]['mark'] = 1
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for sec_end in self.transitions.get(node, []):
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self.process_ranking(sec_end, level+1)
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def make_acyclic(self, parent, node, level, tree):
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"""Computes Partial-order of the nodes with depth-first search
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"""
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if node not in self.partial_order:
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self.partial_order[node] = {'level':level, 'mark':0}
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if parent:
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tree.append((parent, node))
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if self.partial_order[node]['mark']==0:
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self.partial_order[node]['mark'] = 1
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for sec_end in self.transitions.get(node, []):
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self.links.append((node, sec_end))
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self.make_acyclic(node, sec_end, level+1, tree)
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return tree
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def rev_edges(self, tree):
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"""reverse the direction of the edges whose source-node-partail_order> destination-node-partail_order
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to make the graph acyclic
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"""
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Is_Cyclic = False
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i=0
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for link in self.links:
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src = link[0]
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des = link[1]
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edge_len = self.partial_order[des]['level'] - self.partial_order[src]['level']
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if edge_len < 0:
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del self.links[i]
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self.links.insert(i, (des, src))
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self.transitions[src].remove(des)
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self.transitions.setdefault(des, []).append(src)
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Is_Cyclic = True
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elif math.fabs(edge_len) > 1:
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Is_Cyclic = True
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i += 1
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return Is_Cyclic
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def exchange(self, e, f):
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"""Exchange edges to make feasible-tree optimized
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:param e: edge with negative cut-value
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:param f: new edge with minimum slack-value
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"""
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del self.tree_edges[self.tree_edges.index(e)]
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self.tree_edges.append(f)
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self.init_cutvalues()
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def enter_edge(self, edge):
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"""Finds a new_edge with minimum slack value to replace an edge with negative cut-value
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@param edge edge with negative cut-value
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"""
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self.head_nodes = []
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rest_edges = []
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rest_edges += self.tree_edges
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del rest_edges[rest_edges.index(edge)]
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self.head_component(self.start, rest_edges)
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if edge[1] in self.head_nodes:
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l = []
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for node in self.result:
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if node not in self.head_nodes:
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l.append(node)
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self.head_nodes = l
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slack = 100
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new_edge = edge
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for source_node in self.transitions:
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if source_node in self.head_nodes:
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for dest_node in self.transitions[source_node]:
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if dest_node not in self.head_nodes:
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if slack>(self.edge_wt[edge]-1):
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slack = self.edge_wt[edge]-1
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new_edge = (source_node, dest_node)
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return new_edge
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def leave_edge(self):
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"""Returns the edge with negative cut_value(if exists)
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"""
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if self.critical_edges:
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for edge in self.critical_edges:
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self.cut_edges[edge] = 0
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for edge in self.cut_edges:
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if self.cut_edges[edge]<0:
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return edge
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return None
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def finalize_rank(self, node, level):
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self.result[node]['x'] = level
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for destination in self.optimal_edges.get(node, []):
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self.finalize_rank(destination, level+1)
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def normalize(self):
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"""The ranks are normalized by setting the least rank to zero.
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"""
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least_rank = min(x['x'] for x in self.result.values())
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if least_rank!=0:
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for node in self.result:
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self.result[node]['x']-=least_rank
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def make_chain(self):
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"""Edges between nodes more than one rank apart are replaced by chains of unit
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length edges between temporary nodes.
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"""
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for edge in self.edge_wt:
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if self.edge_wt[edge]>1:
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self.transitions[edge[0]].remove(edge[1])
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start = self.result[edge[0]]['x']
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end = self.result[edge[1]]['x']
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for rank in range(start+1, end):
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if not self.result.get((rank, 'temp'), False):
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self.result[(rank, 'temp')] = {'y': None, 'x': rank, 'mark': 0}
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for rank in range(start, end):
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if start==rank:
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self.transitions[edge[0]].append((rank+1, 'temp'))
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elif rank==end-1:
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self.transitions.setdefault((rank, 'temp'), []).append(edge[1])
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else:
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self.transitions.setdefault((rank, 'temp'), []).append((rank+1, 'temp'))
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def init_order(self, node, level):
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"""Initialize orders the nodes in each rank with depth-first search
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"""
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if not self.result[node]['y']:
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self.result[node]['y'] = self.order[level]
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self.order[level] += 1
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for sec_end in self.transitions.get(node, []):
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if node!=sec_end:
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self.init_order(sec_end, self.result[sec_end]['x'])
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def order_heuristic(self):
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for i in range(12):
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self.wmedian()
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def wmedian(self):
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"""Applies median heuristic to find optimized order of the nodes with in their ranks
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"""
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for level in self.levels:
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node_median = []
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nodes = self.levels[level]
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for node in nodes:
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node_median.append((node, self.median_value(node, level-1)))
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sort_list = sorted(node_median, key=operator.itemgetter(1))
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new_list = [tuple[0] for tuple in sort_list]
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self.levels[level] = new_list
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order = 0
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for node in nodes:
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self.result[node]['y'] = order
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order +=1
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def median_value(self, node, adj_rank):
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"""Returns median value of a vertex , defined as the median position of the adjacent vertices
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@param node node to process
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@param adj_rank rank 1 less than the node's rank
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"""
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adj_nodes = self.adj_position(node, adj_rank)
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l = len(adj_nodes)
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m = l // 2
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if l==0:
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return -1.0
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elif l%2 == 1:
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return adj_nodes[m]#median of the middle element
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elif l==2:
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return (adj_nodes[0]+adj_nodes[1])/2
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else:
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left = adj_nodes[m-1] - adj_nodes[0]
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right = adj_nodes[l-1] - adj_nodes[m]
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return ((adj_nodes[m-1]*right) + (adj_nodes[m]*left))/(left+right)
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def adj_position(self, node, adj_rank):
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"""Returns list of the present positions of the nodes adjacent to node in the given adjacent rank.
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@param node node to process
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@param adj_rank rank 1 less than the node's rank
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"""
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pre_level_nodes = self.levels.get(adj_rank, [])
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adj_nodes = []
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if pre_level_nodes:
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for src in pre_level_nodes:
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if self.transitions.get(src) and node in self.transitions[src]:
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adj_nodes.append(self.result[src]['y'])
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return adj_nodes
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def preprocess_order(self):
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levels = {}
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for r in self.partial_order:
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l = self.result[r]['x']
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levels.setdefault(l,[])
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levels[l].append(r)
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self.levels = levels
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def graph_order(self):
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"""Finds actual-order of the nodes with respect to maximum number of nodes in a rank in component
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"""
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mid_pos = 0.0
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max_level = max(len(x) for x in self.levels.values())
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for level in self.levels:
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if level:
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no = len(self.levels[level])
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factor = (max_level - no) * 0.10
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||||
list = self.levels[level]
|
||||
list.reverse()
|
||||
|
||||
if no%2==0:
|
||||
first_half = list[no // 2:]
|
||||
factor = -factor
|
||||
else:
|
||||
first_half = list[no // 2 + 1:]
|
||||
if max_level==1:#for the case when horizontal graph is there
|
||||
self.result[list[no // 2]]['y'] = mid_pos + (self.result[list[no // 2]]['x']%2 * 0.5)
|
||||
else:
|
||||
self.result[list[no // 2]]['y'] = mid_pos + factor
|
||||
|
||||
last_half = list[:no // 2]
|
||||
|
||||
i=1
|
||||
for node in first_half:
|
||||
self.result[node]['y'] = mid_pos - (i + factor)
|
||||
i += 1
|
||||
|
||||
i=1
|
||||
for node in last_half:
|
||||
self.result[node]['y'] = mid_pos + (i + factor)
|
||||
i += 1
|
||||
else:
|
||||
self.max_order += max_level+1
|
||||
mid_pos = self.result[self.start]['y']
|
||||
|
||||
|
||||
def tree_order(self, node, last=0):
|
||||
mid_pos = self.result[node]['y']
|
||||
l = self.transitions.get(node, [])
|
||||
l.reverse()
|
||||
no = len(l)
|
||||
|
||||
rest = no%2
|
||||
first_half = l[no // 2 + rest:]
|
||||
last_half = l[:no // 2]
|
||||
|
||||
for i, child in enumerate(first_half):
|
||||
self.result[child]['y'] = mid_pos - (i+1 - (0 if rest else 0.5))
|
||||
|
||||
if self.transitions.get(child, False):
|
||||
if last:
|
||||
self.result[child]['y'] = last + len(self.transitions[child])/2 + 1
|
||||
last = self.tree_order(child, last)
|
||||
|
||||
if rest:
|
||||
mid_node = l[no // 2]
|
||||
self.result[mid_node]['y'] = mid_pos
|
||||
|
||||
if self.transitions.get(mid_node, False):
|
||||
if last:
|
||||
self.result[mid_node]['y'] = last + len(self.transitions[mid_node])/2 + 1
|
||||
if node!=mid_node:
|
||||
last = self.tree_order(mid_node)
|
||||
else:
|
||||
if last:
|
||||
self.result[mid_node]['y'] = last + 1
|
||||
self.result[node]['y'] = self.result[mid_node]['y']
|
||||
mid_pos = self.result[node]['y']
|
||||
|
||||
i=1
|
||||
last_child = None
|
||||
for child in last_half:
|
||||
self.result[child]['y'] = mid_pos + (i - (0 if rest else 0.5))
|
||||
last_child = child
|
||||
i += 1
|
||||
if self.transitions.get(child, False):
|
||||
if last:
|
||||
self.result[child]['y'] = last + len(self.transitions[child])/2 + 1
|
||||
if node!=child:
|
||||
last = self.tree_order(child, last)
|
||||
|
||||
if last_child:
|
||||
last = self.result[last_child]['y']
|
||||
|
||||
return last
|
||||
|
||||
|
||||
def process_order(self):
|
||||
"""Finds actual-order of the nodes with respect to maximum number of nodes in a rank in component
|
||||
"""
|
||||
|
||||
if self.Is_Cyclic:
|
||||
max_level = max(len(x) for x in self.levels.values())
|
||||
|
||||
if max_level%2:
|
||||
self.result[self.start]['y'] = (max_level+1)/2 + self.max_order + (self.max_order and 1)
|
||||
else:
|
||||
self.result[self.start]['y'] = max_level /2 + self.max_order + (self.max_order and 1)
|
||||
|
||||
self.graph_order()
|
||||
|
||||
else:
|
||||
self.result[self.start]['y'] = 0
|
||||
self.tree_order(self.start, 0)
|
||||
min_order = math.fabs(min(x['y'] for x in self.result.values()))
|
||||
|
||||
index = self.start_nodes.index(self.start)
|
||||
same = False
|
||||
|
||||
roots = []
|
||||
if index>0:
|
||||
for start in self.start_nodes[:index]:
|
||||
same = True
|
||||
for edge in self.tree_list[start][1:]:
|
||||
if edge in self.tree_list[self.start]:
|
||||
continue
|
||||
else:
|
||||
same = False
|
||||
break
|
||||
if same:
|
||||
roots.append(start)
|
||||
|
||||
if roots:
|
||||
min_order += self.max_order
|
||||
else:
|
||||
min_order += self.max_order + 1
|
||||
|
||||
for level in self.levels:
|
||||
for node in self.levels[level]:
|
||||
self.result[node]['y'] += min_order
|
||||
|
||||
if roots:
|
||||
roots.append(self.start)
|
||||
one_level_el = self.tree_list[self.start][0][1]
|
||||
base = self.result[one_level_el]['y']# * 2 / (index + 2)
|
||||
|
||||
|
||||
no = len(roots)
|
||||
first_half = roots[:no // 2]
|
||||
|
||||
if no%2==0:
|
||||
last_half = roots[no // 2:]
|
||||
else:
|
||||
last_half = roots[no // 2 + 1:]
|
||||
|
||||
factor = -math.floor(no // 2)
|
||||
for start in first_half:
|
||||
self.result[start]['y'] = base + factor
|
||||
factor += 1
|
||||
|
||||
if no%2:
|
||||
self.result[roots[no // 2]]['y'] = base + factor
|
||||
factor +=1
|
||||
|
||||
for start in last_half:
|
||||
self.result[start]['y'] = base + factor
|
||||
factor += 1
|
||||
|
||||
self.max_order = max(x['y'] for x in self.result.values())
|
||||
|
||||
def find_starts(self):
|
||||
"""Finds other start nodes of the graph in the case when graph is disconnected
|
||||
"""
|
||||
rem_nodes = []
|
||||
for node in self.nodes:
|
||||
if not self.partial_order.get(node):
|
||||
rem_nodes.append(node)
|
||||
cnt = 0
|
||||
while True:
|
||||
if len(rem_nodes)==1:
|
||||
self.start_nodes.append(rem_nodes[0])
|
||||
break
|
||||
else:
|
||||
count = 0
|
||||
new_start = rem_nodes[0]
|
||||
largest_tree = []
|
||||
|
||||
for node in rem_nodes:
|
||||
self.partial_order = {}
|
||||
tree = self.make_acyclic(None, node, 0, [])
|
||||
if len(tree)+1 > count:
|
||||
count = len(tree) + 1
|
||||
new_start = node
|
||||
largest_tree = tree
|
||||
else:
|
||||
if not largest_tree:
|
||||
new_start = rem_nodes[0]
|
||||
rem_nodes.remove(new_start)
|
||||
|
||||
self.start_nodes.append(new_start)
|
||||
|
||||
|
||||
for edge in largest_tree:
|
||||
if edge[0] in rem_nodes:
|
||||
rem_nodes.remove(edge[0])
|
||||
if edge[1] in rem_nodes:
|
||||
rem_nodes.remove(edge[1])
|
||||
|
||||
if not rem_nodes:
|
||||
break
|
||||
|
||||
|
||||
def rank(self):
|
||||
"""Finds the optimized rank of the nodes using Network-simplex algorithm
|
||||
"""
|
||||
self.levels = {}
|
||||
self.critical_edges = []
|
||||
self.partial_order = {}
|
||||
self.links = []
|
||||
self.Is_Cyclic = False
|
||||
|
||||
self.tree_list[self.start] = self.make_acyclic(None, self.start, 0, [])
|
||||
self.Is_Cyclic = self.rev_edges(self.tree_list[self.start])
|
||||
self.process_ranking(self.start)
|
||||
self.init_rank()
|
||||
|
||||
#make cut values of all tree edges to 0 to optimize feasible tree
|
||||
e = self.leave_edge()
|
||||
|
||||
while e :
|
||||
f = self.enter_edge(e)
|
||||
if e==f:
|
||||
self.critical_edges.append(e)
|
||||
else:
|
||||
self.exchange(e,f)
|
||||
e = self.leave_edge()
|
||||
|
||||
#finalize rank using optimum feasible tree
|
||||
# self.optimal_edges = {}
|
||||
# for edge in self.tree_edges:
|
||||
# source = self.optimal_edges.setdefault(edge[0], [])
|
||||
# source.append(edge[1])
|
||||
|
||||
# self.finalize_rank(self.start, 0)
|
||||
|
||||
#normalization
|
||||
self.normalize()
|
||||
for edge in self.edge_wt:
|
||||
self.edge_wt[edge] = self.result[edge[1]]['x'] - self.result[edge[0]]['x']
|
||||
|
||||
def order_in_rank(self):
|
||||
"""Finds optimized order of the nodes within their ranks using median heuristic
|
||||
"""
|
||||
|
||||
self.make_chain()
|
||||
self.preprocess_order()
|
||||
self.order = {}
|
||||
max_rank = max(x for x in self.levels)
|
||||
|
||||
for i in range(max_rank+1):
|
||||
self.order[i] = 0
|
||||
|
||||
self.init_order(self.start, self.result[self.start]['x'])
|
||||
|
||||
for level in self.levels:
|
||||
self.levels[level].sort(key=lambda x: self.result[x]['y'])
|
||||
|
||||
self.order_heuristic()
|
||||
self.process_order()
|
||||
|
||||
def process(self, starting_node):
|
||||
"""Process the graph to find ranks and order of the nodes
|
||||
|
||||
@param starting_node node from where to start the graph search
|
||||
"""
|
||||
|
||||
self.start_nodes = starting_node or []
|
||||
self.partial_order = {}
|
||||
self.links = []
|
||||
self.tree_list = {}
|
||||
|
||||
if self.nodes:
|
||||
if self.start_nodes:
|
||||
#add dummy edges to the nodes which does not have any incoming edges
|
||||
tree = self.make_acyclic(None, self.start_nodes[0], 0, [])
|
||||
|
||||
for node in self.no_ancester:
|
||||
for sec_node in self.transitions.get(node, []):
|
||||
if sec_node in self.partial_order:
|
||||
self.transitions[self.start_nodes[0]].append(node)
|
||||
break
|
||||
|
||||
self.partial_order = {}
|
||||
tree = self.make_acyclic(None, self.start_nodes[0], 0, [])
|
||||
|
||||
|
||||
# if graph is disconnected or no start-node is given
|
||||
#than to find starting_node for each component of the node
|
||||
if len(self.nodes) > len(self.partial_order):
|
||||
self.find_starts()
|
||||
|
||||
self.max_order = 0
|
||||
#for each component of the graph find ranks and order of the nodes
|
||||
for s in self.start_nodes:
|
||||
self.start = s
|
||||
self.rank() # First step:Netwoek simplex algorithm
|
||||
self.order_in_rank() #Second step: ordering nodes within ranks
|
||||
|
||||
|
||||
def __str__(self):
|
||||
result = ''
|
||||
for l in self.levels:
|
||||
result += 'PosY: ' + str(l) + '\n'
|
||||
for node in self.levels[l]:
|
||||
result += '\tPosX: '+ str(self.result[node]['y']) + ' - Node:' + str(node) + "\n"
|
||||
return result
|
||||
|
||||
|
||||
def scale(self, maxx, maxy, nwidth=0, nheight=0, margin=20):
|
||||
"""Computes actual co-ordiantes of the nodes
|
||||
"""
|
||||
|
||||
#for flat edges ie. source an destination nodes are on the same rank
|
||||
for src in self.transitions:
|
||||
for des in self.transitions[src]:
|
||||
if self.result[des]['x'] - self.result[src]['x'] == 0:
|
||||
self.result[src]['x'] += 0.08
|
||||
self.result[des]['x'] -= 0.08
|
||||
|
||||
factorX = maxx + nheight
|
||||
factorY = maxy + nwidth
|
||||
|
||||
for node in self.result:
|
||||
self.result[node]['y'] = (self.result[node]['y']) * factorX + margin
|
||||
self.result[node]['x'] = (self.result[node]['x']) * factorY + margin
|
||||
|
||||
|
||||
def result_get(self):
|
||||
return self.result
|
||||
|
||||
if __name__=='__main__':
|
||||
starting_node = ['profile'] # put here nodes with flow_start=True
|
||||
nodes = ['project','account','hr','base','product','mrp','test','profile']
|
||||
transitions = [
|
||||
('profile','mrp'),
|
||||
('mrp','project'),
|
||||
('project','product'),
|
||||
('mrp','hr'),
|
||||
('mrp','test'),
|
||||
('project','account'),
|
||||
('project','hr'),
|
||||
('product','base'),
|
||||
('account','product'),
|
||||
('account','test'),
|
||||
('account','base'),
|
||||
('hr','base'),
|
||||
('test','base')
|
||||
]
|
||||
|
||||
radius = 20
|
||||
g = graph(nodes, transitions)
|
||||
g.process(starting_node)
|
||||
g.scale(radius*3,radius*3, radius, radius)
|
||||
|
||||
from PIL import Image
|
||||
from PIL import ImageDraw
|
||||
img = Image.new("RGB", (800, 600), "#ffffff")
|
||||
draw = ImageDraw.Draw(img)
|
||||
|
||||
result = g.result_get()
|
||||
node_res = {}
|
||||
for node in nodes:
|
||||
node_res[node] = result[node]
|
||||
|
||||
for name, node in node_res.items():
|
||||
|
||||
draw.arc( (int(node['y']-radius), int(node['x']-radius),int(node['y']+radius), int(node['x']+radius) ), 0, 360, (128,128,128))
|
||||
draw.text( (int(node['y']), int(node['x'])), str(name), (128,128,128))
|
||||
|
||||
|
||||
for t in transitions:
|
||||
draw.line( (int(node_res[t[0]]['y']), int(node_res[t[0]]['x']),int(node_res[t[1]]['y']),int(node_res[t[1]]['x'])),(128,128,128) )
|
||||
img.save("graph.png", "PNG")
|
||||
Reference in New Issue
Block a user