我想使用python中的networkx分析工具对沿道路网络（保存为Road_Network.shp）的单元格（Available.tif）与中心商务区（Town_centres.shp）之间的距离进行分析。我正在使用anaconda提示符，由于某种原因，系统会提示我权限被拒绝错误（IO Errno：13）。
我尝试在另一台计算机（即我自己的个人笔记本电脑）上运行脚本，以确定这是否确实是权限问题。但是，系统提示我输入相同的错误号（errno 13）。我还关闭了所有打开的文件夹，以允许保存新的.txt文件。
这是脚本：
Calculate_fdist_values
Module intends to calculate the distances from all possible sites within the
study area producing a lookup table (fdist_lookup). Unfortunatly NetworkX greatly increases
the running time, therefore instead of calculating a performance in fdist each
iteration of the optimisation, we instead refer the development sites to this
lookup table (fdist_lookup)
"""
import networkx as nx
import rasterIO
import numpy as np
data_folder = "C:/Users/bXXXXX/Desktop/fdist/Data/"
# Road network which forms the path
Road_Network = nx.read_shp(data_folder+'NPH_Road_Network.shp')
# The CBD point file which we are calculating the shortest path distance to
CBD_Nodes = nx.read_shp(data_folder+'NPH_Town_Centres.shp')
# Extracting the dataset for potential sites to calculate fdist from each one
file_pointer = rasterIO.opengdalraster(data_folder+'NPH_Available.tif')
Available = rasterIO.readrasterband(file_pointer,1)
# Extracting the geotrans which is necessary for caluclating the centroids
# of potential development sites
d,X,Y,p,geotrans= rasterIO.readrastermeta(file_pointer)
def Generate_Development_Sites(Available_Sites):
# Calculates a list of all the sites which we want to calculate the
# shortest pathfdist_values_Available.csv to.
Sites_to_Calc = []
for x in range(0,X):
for y in range(0,Y):
siteyx = (y,x)
if Available_Sites[siteyx] == 1:
Sites_to_Calc.append(siteyx)
return Sites_to_Calc
def Conv_2_Coords(list_of_sites, geo_t_params):
# Calculates the geographical reference point of a centroid for each
# possible development site
# Inputs are y,x
# NOTE: Need to somehow check the y and x are the right way round
count= 0 #
array = []
site_nodes = []
for site in list_of_sites:
y = site[0]
x = site[1]
# coord = coord of raster corner + (cell_coord * cell_size) + (cell_size/2)
x_coord = geo_t_params[0] + (x*geo_t_params[1]) + (geo_t_params[1]/2)
y_coord = geo_t_params[3] - (y*geo_t_params[1]) + (geo_t_params[5]/2)
#print y_coord, x_coord
# Have to work in x and y I think
node_coord=(x_coord, y_coord)
site_nodes.append(node_coord)
a = [count, x_coord, y_coord, x, y]
array.append(a)
count += 1
np.savetxt("P:/GrantRich/netwx/Results/", array, delimiter = ',')
print "saved"
return site_nodes
def calc_closest(new_node, node_list):
best_diff = 10000
closest_node=[0,0]
for comp_node in node_list.nodes():
diff = (abs(comp_node[0]-new_node[0])+abs(comp_node[1]-new_node[1]))
if abs(diff) < best_diff:
best_diff = diff
closest_node = comp_node
return closest_node
def Add_CBD_Nodes_To_Network(node_list,network):
# Adds an edge between the node and the node calculated to be closest
for node in node_list:
# Calculate the closest road node
closest_node= calc_closest(node, network)
network.add_node(node) #adds node to network
network.add_edge(node,closest_node) #adds edge between nodes
def Add_Nodes_To_Network(node_list,network):
# Adds an edge between the node and the node calculated to be closest
for node in node_list:
# Calculate the closest road node
closest_node= calc_closest(node, network)
network.add_node(node) #adds node to network
network.add_edge(node,closest_node) #adds edge between nodes
def Add_Edges(g, node, closest_node):
# Add node to the network then add an edge
g.add_node(node)
g.add_edge(node, closest_node)
return g
def Calculate_Fitness(Development_Sites, CBD_Nodes, Road_Network, geo_t_params):
print "Beginning"
# Convert the sites into their coordinates
Dev_Nodes = Conv_2_Coords(Development_Sites, geo_t_params)
#Add CBD and development sites to the road network
# Gets rid of any direction restrictions
Road_Network=Road_Network.to_undirected()
# Add the CBD_Nodes to the road network
Add_Nodes_To_Network(CBD_Nodes, Road_Network)
Add_Nodes_To_Network(Dev_Nodes, Road_Network)
print "Calculating Shortest Distances for ", len(Dev_Nodes), " sites"
# Calcuate the shortest distance from each site to a CBD then return average
fdist_list = []
for Dev_Site in Dev_Nodes:
shrtst_dist=10000
for CBD in CBD_Nodes:
try:
dist = nx.shortest_path_length(Road_Network,Dev_Site,CBD, weight='Dist')
if dist<shrtst_dist:
shrtst_dist=dist
except nx.NetworkXNoPath:
print "Ne path pet"
print "Site: ", Dev_Site, " fdist = ", shrtst_dist
fdist_list.append( shrtst_dist)
fdist_list
return fdist_list
if __name__ == '__main__':
print "Generating Sites to Calculate"
Sites_to_Calculate = Generate_Development_Sites(Available)
fdist_values =Calculate_Fitness(Sites_to_Calculate, CBD_Nodes, Road_Network, geotrans)
print "Ran"
for x in range(0,len(fdist_values)):
print "(", Sites_to_Calculate[x],",", fdist_values[x], "),"
结果应包括一个.txt文件，其中包含节点对列表以及每个节点对之间的距离。但是，系统提示我以下错误消息：
(GDAL) C:\Users\b6051089\Desktop\fdist\Script>python Calculate_fdist_values.py
Generating Sites to Calculate
Beginning
Traceback (most recent call last):
File "Calculate_fdist_values.py", line 148, in <module>
fdist_values =Calculate_Fitness(Sites_to_Calculate, CBD_Nodes, Road_Network, geotrans)
File "Calculate_fdist_values.py", line 117, in Calculate_Fitness
Dev_Nodes = Conv_2_Coords(Development_Sites, geo_t_params)
File "Calculate_fdist_values.py", line 73, in Conv_2_Coords
np.savetxt("C:/Users/b6051089/Desktop/fdist/Results/", array, delimiter = ',')
File "C:\Users\b6051089\AppData\Local\conda\conda\envs\GDAL\lib\site-packages\numpy\lib\npyio.py", line 1307, in savetxt
open(fname, 'wt').close()
IOError: [Errno 13] Permission denied: 'C:/Users/b6051089/Desktop/fdist/Results/'
有什么想法吗？
答案 0 :(得分：0)
所以我在Conv_2_Coords
np.savetxt("P:/GrantRich/netwx/Results/", array, delimiter = ',')
与错误消息中的np.savetxt语句不完全匹配
np.savetxt("C:/Users/b6051089/Desktop/fdist/Results/", array, delimiter = ',')
所以我想您已经从某台机器移到了另一台机器上。但是，在两种情况下都没有文件名，只有路径。没有文件名，您将告诉numpy写入目录，而不是目录中的文件。因此将语句更改为
np.savetxt("C:/Users/b6051089/Desktop/fdist/Results/results.csv", array, delimiter = ',')
或类似的东西应该适合您。