我从哪里得到尾随的 0 或 9？我在每一步都检查了没有出现舍入问题，并且得到了正确的结果。但是，当我将此数字添加到图表时，会出现舍入问题。
我的完整代码如下：
from __future__ import division
from math import sqrt
import networkx as nx
import numpy as np
from decimal import Decimal
n=4 #n is the nummber of steps in the graph.
a = np.array([ 1.1656, 1.0125, 0.8594])
g=nx.DiGraph() #I initiate the graph
#f2 checks for equal nodes and removes them
def f2(seq):
checked = []
for e in seq:
if (e not in checked):
checked.append(e)
return np.asarray(checked)
root = np.array([1])
existing_nodes = np.array([1])
previous_step_nodes = np.array([1])
nodes_to_add =np.empty(0)
clean = np.array([1])
for step in range(1,n):
nodes_to_add=np.empty(0)
for values in previous_step_nodes:
nodes_to_add = np.append(nodes_to_add,values*a)
print "--------"
print "*****nodes to add ****" + str(f2(np.round(nodes_to_add,4)))
print "clean = " + str(clean) + "\n"
#Up to here, the code generates the nodes I will need
# This for loop makes the edges and adds the nodes.
for node in clean:
for next_node in np.round(node*a,4):
print str(node ) + " " + str( next_node)
g.add_edge(np.round(node,4), np.round(next_node,4))
# g.add_edge(Decimal(np.round(node,4)).quantize(Decimal('1.0000')), Decimal(np.round(next_node,4)).quantize(Decimal('1.0000')))
previous_step_nodes = f2(nodes_to_add)
clean = f2(np.round(previous_step_nodes,4))
# g.add_nodes_from(clean)
print "\n step" + str(step) + " \n"
print " Current Step :" + "Number of nodes = " + str(len(f2(np.round(previous_step_nodes,4))))
print clean
print "How many nodes are there ? " +str(len(g.nodes()))
这段代码工作并打印出一个非常简洁的图形描述，这正是我想要的。但是，当我打印节点列表时，要检查图形是否仅包含我需要的节点数，我得到：
How many nodes are there ? 22
[1, 0.88109999999999999, 1.0143, 1.038, 0.74780000000000002,
1.1801999999999999, 1.3755999999999999, 1.0142, 0.8609,
0.88100000000000001, 0.85940000000000005, 1.1656,
1.1950000000000001, 1.0125, 1.5835999999999999, 1.0017,
0.87009999999999998, 1.1676,
0.63480000000000003, 0.73860000000000003, 1.3586, 1.0251999999999999]
这显然是一个使我的程序无用的问题。0.88109999999999999 和 0.88100000000000001 是同一个节点。
因此，在检查了几天的 stackoverflow 之后，我得出的结论是，解决该问题的唯一方法是使用 Decimal()。所以，我更换了：
g.add_edge(np.round(node,4), np.round(next_node,4))
和
g.add_edge(Decimal(np.round(node,4)).quantize(Decimal('1.0000')),
Decimal(np.round(next_node,4)).quantize(Decimal('1.0000')))
然而，结果并不是我所期望的：因为
0.88109999999999999 = 0.8811
0.88100000000000001 =0.8810,
所以 Python 仍然认为它们是不同的数字。
理想情况下，我不希望使用 Decimal() 使代码复杂化，并且希望截断小数点，以便 0.88109999999999999 = 0.88100000000000001 = 0.8810 但我不知道如何解决这个问题。
感谢您的回复，我已经更新了我的代码。我接受了使用 f2 的建议：
def f2(seq):
near_equal = lambda x, y: abs(x - y) < 1.e-5
checked = []
for e in seq:
if all([not near_equal(e, x) for x in checked]):
checked.append(e)
return np.asarray(checked)
我删除了所有 numpy.round() 因为如果我可以删除“相似”的节点，那么我根本不需要任何舍入。
但是，python仍然无法区分节点：
g.nodes() 打印出 23 个节点，而应该只有 20 个：（注意：我在更改容差级别 1.e-5 时尝试过，但没有得到不同的结果）
有多少个节点？23
[0.63474091729864457, 0.73858020442900385, 0.74781245698436638,
0.85940689107605128, 0.86088399667008808, 0.86088399667008819,
0.87014947721450187, 0.88102634567968308, 0.88102634567968319,
1, 1.00171875, 1.0125, 1.0142402343749999, 1.02515625,
1.0379707031249998, 1.1655931089239486, 1.1675964720799117,
1.180163022785498, 1.1949150605703167, 1.358607295570996,
1.3755898867656333, 1.3755898867656335, 1.5835833014513552]
这是因为：0.86088399667008808、0.86088399667008819；0.88102634567968308、0.88102634567968319 和 1.3755898867656333、1.3755898867656335 仍被视为不同的节点。
完整代码：
from __future__ import division
from math import sqrt
import networkx as nx
import numpy as np
import matplotlib.pyplot as plt
mu1 = 0.05; sigma1= 0.25
n=4
a0=1
a1 = 1 + mu1/n + sigma1*sqrt(3)/sqrt(2*n)
a2 = 1 + mu1/n
a3 = 1 + mu1 /n - sigma1*sqrt(3)/sqrt(2*n)
a = np.array([a1,a2,a3])
print " a = " + str(a)
g=nx.DiGraph() #I initiate the graph
def f2(seq):
near_equal = lambda x, y: abs(x - y) < 1.e-5
checked = []
for e in seq:
if all([not near_equal(e, x) for x in checked]):
checked.append(e)
return np.asarray(checked)
root = np.array([1])
existing_nodes = np.array([1])
previous_step_nodes = np.array([1])
nodes_to_add =np.empty(0)
clean = np.array([1])
print "________________This Makes the Nodes____________________________________"
for step in range(1,n):
nodes_to_add=np.empty(0)
for values in previous_step_nodes:
nodes_to_add = np.append(nodes_to_add,values*a)
print "--------"
print "*****nodes to add ****" + str(f2(nodes_to_add))
print "clean = " + str(clean) + "\n"
#Up to here, the code generates the nodes I will need
# This for loop makes the edges and adds the nodes.
for node in clean:
for next_node in node*a:
print str(node ) + " " + str( next_node)
g.add_edge(node, next_node)
previous_step_nodes = f2(nodes_to_add)
clean = f2(previous_step_nodes)
# g.add_nodes_from(clean)
print "\n step" + str(step) + " \n"
print " Current Step :" + "Number of nodes = " + str(len(f2(previous_step_nodes)))
print clean
print "______________End of the Nodes_________________________________"
print "How many nodes are there ? " +str(len(g.nodes()))
print sorted(g.nodes())
结果：
有多少个节点？23 [0.63474091729864457, 0.73858020442900385, 0.74781245698436638, 0.85940689107605128, 0.86088399667008808, 0.86088399667008819, 0.87014947721450187, 0.88102634567968308, 0.88102634567968319, 1, 1.00171875, 1.0125, 1.0142402343749999, 1.02515625, 1.0379707031249998, 1.1655931089239486, 1.1675964720799117, 1.180163022785498, 1.1949150605703167, 1.358607295570996, 1.3755898867656333, 1.3755898867656335, 1.5835833014513552]