问题描述
我正在用python编写脚本来处理NetCDF文件，但是在创建变量时遇到了一些问题，这是代码的一部分:
I am writing a script in python for handling NetCDF files, but I am facing some issues in creating variables, here is the part of the code:
stepnumber_var = ofl.createVariable("step_number", "i",("step_number",))
stepnumber_var.standard_name = "step_number"
atomNumber_var = ofl.createVariable("atom_number", "i", ("atom_number",))
atomNumber_var.standard_name = "atom__number"
但是给我这个错误:
Traceback (most recent call last):
File "sub_avg.py", line 141, in <module>
atomNumber_var = ofl.createVariable("atom_number", "i", ("atom_number",))
IOError: netcdf: NetCDF: Invalid dimension ID or name
我的问题是，为什么第一个变量创建没有问题，而第二个变量却不起作用?
My question is, why the first variable is created without any problem and the second doesn't work?
谢谢
这是完整的代码
from array import array
import os
import sys
import math
import string as st
import numpy as N
from Scientific.IO.NetCDF import NetCDFFile as S
if len(sys.argv) < 2:
sys.exit( "No input file found. \nPlease privide NetCDF trajectory input file" )
#######################
## Open NetCDF file ###
#######################
infl = S(sys.argv[1], 'r')
file = sys.argv[1]
title,ext = file.split(".")
#for v in infl.variables: # Lists the variables in file
# print(v)
#################################################################################
# Variable "configurations" has the structure [step_number, atom_number, x y z] #
#################################################################################
varShape = infl.variables['configuration'].shape # This gets the shape of the variable, i.e. the dimension in terms of elements
nSteps = varShape[0]
nAtoms = varShape[1]
coordX_atom = N.zeros((nSteps,nAtoms))
coordY_atom = N.zeros((nSteps,nAtoms))
coordZ_atom = N.zeros((nSteps,nAtoms))
sumX = [0] * nAtoms
sumY = [0] * nAtoms
sumZ = [0] * nAtoms
######################################################
# 1) Calculate the average structure fron trajectory #
######################################################
for i in range(0, 3):
for j in range(0, 3):
coordX_atom[i][j] = infl.variables["configuration"][i,j,0]
coordY_atom[i][j] = infl.variables["configuration"][i,j,1]
coordZ_atom[i][j] = infl.variables["configuration"][i,j,2]
sumX[j] = sumX[j] + coordX_atom[i][j]
sumY[j] = sumY[j] + coordY_atom[i][j]
sumZ[j] = sumZ[j] + coordZ_atom[i][j]
avgX = [0] * nAtoms
avgY = [0] * nAtoms
avgZ = [0] * nAtoms
for j in range(0, 3):
avgX[j] = sumX[j]/nSteps
avgY[j] = sumY[j]/nSteps
avgZ[j] = sumZ[j]/nSteps
##############################################################
# 2) Subtract average structure to each atom and for each frame #
##############################################################
for i in range(0, 3):
for j in range(0, 3):
coordX_atom[i][j] = infl.variables["configuration"][i,j,0] - avgX[j]
coordY_atom[i][j] = infl.variables["configuration"][i,j,1] - avgY[j]
coordZ_atom[i][j] = infl.variables["configuration"][i,j,2] - avgZ[j]
#######################################
# 3) Write new NetCDF trajectory file #
#######################################
ofl = S(title + "_subAVG.nc", "a")
############################################################
# Get information of variables contained in the NetCDF input file
#############################################################
i = 0
for v in infl.variables:
varNames = [v for v in infl.variables]
i += 1
#############################################
# Respectively get, elements names in variable, dimension of elements and lenght of the array variableNames
##############################################
for v in infl.variables["box_size"].dimensions:
boxSizeNames = [v for v in infl.variables["box_size"].dimensions]
for v in infl.variables["box_size"].shape:
boxSizeShape = [v for v in infl.variables["box_size"].shape]
boxSizeLenght = boxSizeNames.__len__()
print boxSizeLenght
for v in infl.variables["step"].dimensions:
stepNames = [v for v in infl.variables["step"].dimensions]
for v in infl.variables["step"].shape:
stepShape = [v for v in infl.variables["box_size"].shape]
stepLenght = stepNames.__len__()
print stepLenght
for v in infl.variables["configuration"].dimensions:
configurationNames = [v for v in infl.variables["configuration"].dimensions]
for v in infl.variables["configuration"].shape:
configurationShape = [v for v in infl.variables["configuration"].shape]
configurationLenght = configurationNames.__len__()
print configurationLenght
for v in infl.variables["description"].dimensions:
descriptionNames = [v for v in infl.variables["description"].dimensions]
for v in infl.variables["description"].shape:
descriptionShape = [v for v in infl.variables["description"].shape]
descriptionLenght = descriptionNames.__len__()
print descriptionLenght
for v in infl.variables["time"].dimensions:
timeNames = [v for v in infl.variables["time"].dimensions]
for v in infl.variables["time"].shape:
timeShape = [v for v in infl.variables["time"].shape]
timeLenght = timeNames.__len__()
print timeLenght
#Get Box size
xBox = infl.variables["box_size"][0,0]
yBox = infl.variables["box_size"][0,1]
zBox = infl.variables["box_size"][0,2]
# Get description lenght
description_lenghtLenght = infl.variables["description"][:]
############################################################
# Create Dimensions
############################################################
stepnumber_var = ofl.createVariable("step_number", "i",("step_number",))
stepnumber_var.standard_name = "step_number"
atomNumber_var = ofl.createVariable("atom_number", "i", ("atom_number",))
atomNumber_var.standard_name = "atom__number"
#
#xyz_var = ofl.createVariable("xyz", "f",("xyz",))
#xyz_var.units = "nanometers"
#xyz_var.standard_name = "xyz"
#
#configuration_var = ofl.createVariable("configuration", "f", ("step_number", "atom_number", "xyz"))
#configuration_var.units = "nanometers"
#configuration_var.standard_name = "configuration"
#
#print configuration_var.shape
#step_var = ofl.createVariable("box_size_lenght", 3)
#configuration_var = ofl.createVariable("atom_number", nAtoms)
#description_var = ofl.createVariable("xyz", 3)
#time_var = ofl.createVariable(description_lenght, description_lenghtLenght)
#
#a = infl.variables["step_number"].dimensions.keys()
#print a
谢谢！
推荐答案
这可能是图书馆试图提供帮助"的情况(有关详细信息，请参见我的文章结尾，但我无法确认).要解决此问题，您应在创建变量之前使用以下内容为atom_number和step_number显式创建尺寸(假设我正确理解了nSteps和nAtoms):
This may be a case of a library trying to be "helpful" (see the end of my post for details, but I can't confirm it). To fix this, you should explicitly create dimensions for atom_number and step_number, by using the following before you create the variables (assuming I am understanding nSteps and nAtoms correctly):
ofl.createDimension("step_number"，nSteps)ofl.createDimension("atom_number"，nAtoms)
ofl.createDimension("step_number", nSteps)ofl.createDimension("atom_number", nAtoms)
如果您是netCDF的新手，我建议您看一下netcdf4-python软件包
If you are new to netCDF, I might suggest looking at either the netcdf4-python package,
http://unidata.github.io/netcdf4-python/
:
http://docs.scipy.org/doc/scipy/reference/io.html
可能会发生什么:问题似乎是当您创建变量step_number时，该库正试图通过创建长度不受限制的step_number维来提供帮助.但是，netcdf-3文件中只能有一个无限制的尺寸，因此有用的技巧"不起作用.
What might be going on: it looks like the issue is that when you create the variable step_number, the library is trying to be helpful by creating a step_number dimension with unlimited length. However, you can only have one unlimited dimension in a netcdf-3 file, so the helpful "trick" does not work.
这篇关于Python NetCDF IOError:netcdf:NetCDF:无效的维度ID或名称的文章就介绍到这了，希望我们推荐的答案对大家有所帮助，也希望大家多多支持！