根据计算自动选择文件名，然后将它们导入 python
Choose File names automatically based on a calculation and then import them to python
我已经 运行 陷入困境，我不知道如何继续。我从我的 CFD 模拟中生成了大量原始数据。所有原始数据都将采用文本格式。文本文件的格式为 "hA-'timestep'.txt"，其中 A 等于 0,1,2,3,4,5,6,7,8,9。例如 h1-0500.txt 将引用第 500 次沿 h1 获得的数据 step.All hA 的文件将保存在一个文件夹中。在我的 post 处理中，我想在不同的 流时间 导入文件并进行一些分析。我写了一个代码，它将根据一些需要流动时间作为用户输入的方程来计算时间步长。
我想做的是导入所有那些对应于通过 equation.For 示例计算的特定 timestep 的文件，如果我输入 2400对于流动时间，那么方程式将给我的时间步长为 16144。我希望与该时间步长对应的那些文件名自动 imported.Please 参见下面的代码。
我已经上传了16144对应的文件，如何根据计算出来的时间步长自动选择文件名。目前从等式中获取时间步后，我必须手动更改文件名。如果有人可以指导我，我将不胜感激。
Samplefiles
# Notes about the Simulation#
# Total No. of Time Steps completed = 16152
# No. of Time Steps completed in HPC = 165
# Flow Time before HPC = 3.1212s
# Total Flow time of Fill Cycle = 2401.2s
import numpy as np
from matplotlib import pyplot as plt
import os
FT_init = 3.1212
delt = 0.15 # Timestep size
TS_init = 165
flowtime = input("Enter the flow time required: ") # This is user input. Timestep will be calculated based on the flow time entered.
timestep = (flowtime-FT_init)/delt
timestep = round(timestep + TS_init)
print timestep
def xlineplots(X1,Y1,V1,Tr1):
plt.figure(1)
plt.plot(X1,Tr1)
plt.legend(['h0','h3','h5','h7','h9'],loc=0)
plt.ylabel('Tracer Concentration')
plt.xlabel('X (m)')
plt.title('Tracer Concentration Variation along the Tank width')
plt.figtext(0.6,0.6,"Flow Time = 2400s",style= 'normal',alpha = 0.5)
plt.figtext(0.6,0.55,"Case: ddn110B",style= 'normal')
plt.savefig('hp1.png', format='png', dpi=600)
plt.figure(2)
plt.plot(X1,V1)
plt.legend(['h0','h3','h5','h7','h9'],loc=0)
plt.ylabel('V (m/s)')
plt.xlabel('X (m)')
plt.title('Vertical Velocity Variation along the Tank width')
plt.figtext(0.6,0.6,"Flow Time = 2400s",style= 'normal',alpha = 0.5)
plt.figtext(0.6,0.55,"Case: ddn110B",style= 'normal',alpha = 0.5)
plt.savefig('hv1.png', format='png', dpi=600)
path1='Location of the Directory' # Location where the files are located
filename1=np.array(['h0-16144.txt','h3-16144.txt','h5-16144.txt','h7-16144.txt','h9-16144.txt'])
for i in filename1:
format_name= i
data1 = os.path.join(path1,format_name)
data2 = np.loadtxt(data1,skiprows=1)
data2 = data2[data2[:,1].argsort()]
X1 = data2[:,1] # Assign x-coordinate from the imported text file
Y1 = data2[:,2] # Assign y-coordinate from the imported text file
V1 = data2[:,4] # Assign y-velocity from the imported text file
Tr1 = data2[:,5] # Assign Tracer Concentration from the imported text file
xlineplots(X1,Y1,V1,Tr1)
错误信息：
Enter the flow time required: 1250
8477
timestep: 8477
file(s) found: ['E:/Fall2015/Research/CFD/ddn110B/Transfer/xline\h0-8477.txt', 'E:/Fall2015/Research/CFD/ddn110B/Transfer/xline\h1-8477.txt', 'E:/Fall2015/Research/CFD/ddn110B/Transfer/xline\h2-8477.txt', 'E:/Fall2015/Research/CFD/ddn110B/Transfer/xline\h3-8477.txt', 'E:/Fall2015/Research/CFD/ddn110B/Transfer/xline\h4-8477.txt', 'E:/Fall2015/Research/CFD/ddn110B/Transfer/xline\h5-8477.txt', 'E:/Fall2015/Research/CFD/ddn110B/Transfer/xline\h6-8477.txt', 'E:/Fall2015/Research/CFD/ddn110B/Transfer/xline\h7-8477.txt', 'E:/Fall2015/Research/CFD/ddn110B/Transfer/xline\h8-8477.txt', 'E:/Fall2015/Research/CFD/ddn110B/Transfer/xline\h9-8477.txt']
working in: E:/Fall2015/Research/CFD/ddn110B/Transfer/xline on: h0-8477
Traceback (most recent call last):
File "<ipython-input-52-0503f720722f>", line 54, in <module>
data2 = np.loadtxt(filename, skiprows=1)
File "E:\WinPython-64bit-2.7.10.3\python-2.7.10.amd64\lib\site-packages\numpy\lib\npyio.py", line 691, in loadtxt
fh = iter(open(fname, 'U'))
IOError: [Errno 2] No such file or directory: 'h9-8477.txt'
我希望我明白你的意思，但不是很清楚。当用户输入时间步长时，只有与该时间步长对应的文件才会被加载并进一步用于您的绘图功能：
我考虑了以下结构：
project/
| cfd_plot.py
+ sample/
| | h0-16144.txt
| | h1-16144.txt
| | h3-16144.txt
| | h0-25611.txt
| | h1-25611.txt
| | <...>
这里是cfd_plot.py
from __future__ import print_function
import numpy as np
from matplotlib import pyplot as plt
import os
import re
# pth is a path for plt to save the image
def xlineplots(X1, Y1, V1, Tr1n, pth):
_, ax = plt.subplots()
ax.plot(X1, Tr1)
ax.legend(['h0', 'h3', 'h5', 'h7', 'h9'], loc=0)
ax.set_ylabel('Tracer Concentration')
ax.set_xlabel('X (m)')
ax.set_title('Tracer Concentration Variation along the Tank width')
plt.figtext(.6, .6, "Flow Time = 2400s", style='normal', alpha=.5)
plt.figtext(.6, .55, "Case: ddn110B", style='normal')
plt.savefig(pth + '-hp1.png', format='png', dpi=600)
_, ax = plt.subplots()
ax.plot(X1, V1)
ax.legend(['h0', 'h3', 'h5', 'h7', 'h9'], loc=0)
ax.set_ylabel('V (m/s)')
ax.set_xlabel('X (m)')
ax.set_title('Vertical Velocity Variation along the Tank width')
plt.figtext(.6, .6, "Flow Time = 2400s", style='normal', alpha=.5)
plt.figtext(.6, .55, "Case: ddn110B", style='normal', alpha=.5)
plt.savefig(pth + '-hv1.png', format='png', dpi=600)
FT_init = 3.1212
delt = .15 # Timestep size
TS_init = 165
flowtime = input("Enter the flow time required: ")
timestep = (int(flowtime) - FT_init) / delt
timestep = round(timestep + TS_init)
reps = ['sample'] # location where the files are located
# first simple version
# files = []
# for rep in reps: # recursive search for the files that match the timestep
# for dirpath, dirnames, filenames in os.walk(rep):
# for filename in [f for f in filenames if str(timestep) in f and f.endswith('.txt')]:
# files.append(os.path.join(dirpath, filename))
# second version, using regular expressions
reg_exp = '^.*-({:d})\.txt'.format(timestep)
files = []
for rep in reps: # recursive search for the files that match the timestep
for dirpath, dirnames, filenames in os.walk(rep):
for filename in [f for f in filenames if re.search(reg_exp, f)]:
files.append(os.path.join(dirpath, filename))
print('timestep:', timestep)
print('file(s) found: ', files)
for file in files:
directory = os.path.dirname(file) # directory of the .txt file
name = os.path.splitext(os.path.basename(file))[0] # basename of the .txt file
print('working in:', directory, 'on:', name)
data2 = np.loadtxt(file, skiprows=1)
data2 = data2[data2[:, 1].argsort()]
X1 = data2[:, 1] # Assign x-coordinate from the imported text file
Y1 = data2[:, 2] # Assign y-coordinate from the imported text file
V1 = data2[:, 4] # Assign y-velocity from the imported text file
Tr1 = data2[:, 5] # Assign Tracer Concentration from the imported text file
# here you can give directory + name or just name to xlineplots
xlineplots(X1, Y1, V1, Tr1, os.path.join(directory, name))
# xlineplots(X1, Y1, V1, Tr1, name)
更新：进行了一些编辑（评论）
UPDATE2: 在文件搜索中使用正则表达式，过滤器是 '^.*-({:d})\.txt'.format(timestep):
^ match beginning of the line
.* match any character (except newline), zero or multiple times
- match the character -
({:d}) match the timestep, formatted as an integer
\. match the character .
txt match characters txt
生成文件名或查找与特定模式匹配的文件名有问题吗？
我可以修改你的代码：
hs = [0,3,5,7,9]
timestep = 16144
filenames = ['h%s-%s'%(h, timestep) for h in hs]
for name in filenames:
fname = op.path.join(path1, name)
try:
data = np.loadtxt(fname, skiprows=1)
except IOError:
# cannot open this file, most likely because it does not exist
# continue with the next
continue
...
在这里，我将生成具有所需格式的文件名，并在可能的情况下加载和使用每个文件名。
我可以将 glob 或 re 应用于目录列表进行搜索，但我的 try-except 方法没有任何问题。很好 Python 风格。
==========================
这是使用 glob 的示例（在 Ipython 会话中）：
首先是一个带有一堆文件的测试目录（用`touch创建）：
In [9]: ls testdir
h1-123.txt h12-1234.txt h2-123.txt h2-124.txt h3-124.txt h343.txt
In [10]: import glob
一般搜索以 h 开头，以 .txt:
结尾的文件
In [11]: glob.glob('testdir/h*.txt')
Out[11]:
['testdir/h2-124.txt',
'testdir/h3-124.txt',
'testdir/h12-1234.txt',
'testdir/h343.txt',
'testdir/h1-123.txt',
'testdir/h2-123.txt']
将其缩小为 2 个由破折号分隔的字段
In [12]: glob.glob('testdir/h*-*.txt')
Out[12]:
['testdir/h2-124.txt',
'testdir/h3-124.txt',
'testdir/h12-1234.txt',
'testdir/h1-123.txt',
'testdir/h2-123.txt']
将第一个字段限制为单个字符
In [13]: glob.glob('testdir/h?-*.txt')
Out[13]:
['testdir/h2-124.txt',
'testdir/h3-124.txt',
'testdir/h1-123.txt',
'testdir/h2-123.txt']
对于特定的 'time' 字符串：
In [14]: glob.glob('testdir/h?-123.txt')
Out[14]: ['testdir/h1-123.txt', 'testdir/h2-123.txt']
可以使用字符串格式创建搜索字符串
In [15]: times=123
In [16]: glob.glob('testdir/h?-%s.txt'%times)
==========================
使用 os 和 re 我可以像这样搜索：
In [28]: import os
In [29]: import re
In [30]: filelist=os.listdir('./testdir')
In [31]: [n for n in filelist if re.match('h[1-9]-123',n) is not None]
Out[31]: ['h1-123.txt', 'h2-123.txt']
======================
如果文件名中必须包含 4 位数字（或其他数字），则使用类似：
'h%d-%04d'%(3,123) # 'h3-0123'
'testdir/h?-%04d.txt'%times
无论您使用 try、glob 还是 re.
，您都需要这种填充
我已经 运行 陷入困境，我不知道如何继续。我从我的 CFD 模拟中生成了大量原始数据。所有原始数据都将采用文本格式。文本文件的格式为 "hA-'timestep'.txt"，其中 A 等于 0,1,2,3,4,5,6,7,8,9。例如 h1-0500.txt 将引用第 500 次沿 h1 获得的数据 step.All hA 的文件将保存在一个文件夹中。在我的 post 处理中，我想在不同的 流时间 导入文件并进行一些分析。我写了一个代码，它将根据一些需要流动时间作为用户输入的方程来计算时间步长。
我想做的是导入所有那些对应于通过 equation.For 示例计算的特定 timestep 的文件，如果我输入 2400对于流动时间，那么方程式将给我的时间步长为 16144。我希望与该时间步长对应的那些文件名自动 imported.Please 参见下面的代码。
我已经上传了16144对应的文件，如何根据计算出来的时间步长自动选择文件名。目前从等式中获取时间步后，我必须手动更改文件名。如果有人可以指导我，我将不胜感激。 Samplefiles
# Notes about the Simulation#
# Total No. of Time Steps completed = 16152
# No. of Time Steps completed in HPC = 165
# Flow Time before HPC = 3.1212s
# Total Flow time of Fill Cycle = 2401.2s
import numpy as np
from matplotlib import pyplot as plt
import os
FT_init = 3.1212
delt = 0.15 # Timestep size
TS_init = 165
flowtime = input("Enter the flow time required: ") # This is user input. Timestep will be calculated based on the flow time entered.
timestep = (flowtime-FT_init)/delt
timestep = round(timestep + TS_init)
print timestep
def xlineplots(X1,Y1,V1,Tr1):
plt.figure(1)
plt.plot(X1,Tr1)
plt.legend(['h0','h3','h5','h7','h9'],loc=0)
plt.ylabel('Tracer Concentration')
plt.xlabel('X (m)')
plt.title('Tracer Concentration Variation along the Tank width')
plt.figtext(0.6,0.6,"Flow Time = 2400s",style= 'normal',alpha = 0.5)
plt.figtext(0.6,0.55,"Case: ddn110B",style= 'normal')
plt.savefig('hp1.png', format='png', dpi=600)
plt.figure(2)
plt.plot(X1,V1)
plt.legend(['h0','h3','h5','h7','h9'],loc=0)
plt.ylabel('V (m/s)')
plt.xlabel('X (m)')
plt.title('Vertical Velocity Variation along the Tank width')
plt.figtext(0.6,0.6,"Flow Time = 2400s",style= 'normal',alpha = 0.5)
plt.figtext(0.6,0.55,"Case: ddn110B",style= 'normal',alpha = 0.5)
plt.savefig('hv1.png', format='png', dpi=600)
path1='Location of the Directory' # Location where the files are located
filename1=np.array(['h0-16144.txt','h3-16144.txt','h5-16144.txt','h7-16144.txt','h9-16144.txt'])
for i in filename1:
format_name= i
data1 = os.path.join(path1,format_name)
data2 = np.loadtxt(data1,skiprows=1)
data2 = data2[data2[:,1].argsort()]
X1 = data2[:,1] # Assign x-coordinate from the imported text file
Y1 = data2[:,2] # Assign y-coordinate from the imported text file
V1 = data2[:,4] # Assign y-velocity from the imported text file
Tr1 = data2[:,5] # Assign Tracer Concentration from the imported text file
xlineplots(X1,Y1,V1,Tr1)
错误信息：
Enter the flow time required: 1250
8477
timestep: 8477
file(s) found: ['E:/Fall2015/Research/CFD/ddn110B/Transfer/xline\h0-8477.txt', 'E:/Fall2015/Research/CFD/ddn110B/Transfer/xline\h1-8477.txt', 'E:/Fall2015/Research/CFD/ddn110B/Transfer/xline\h2-8477.txt', 'E:/Fall2015/Research/CFD/ddn110B/Transfer/xline\h3-8477.txt', 'E:/Fall2015/Research/CFD/ddn110B/Transfer/xline\h4-8477.txt', 'E:/Fall2015/Research/CFD/ddn110B/Transfer/xline\h5-8477.txt', 'E:/Fall2015/Research/CFD/ddn110B/Transfer/xline\h6-8477.txt', 'E:/Fall2015/Research/CFD/ddn110B/Transfer/xline\h7-8477.txt', 'E:/Fall2015/Research/CFD/ddn110B/Transfer/xline\h8-8477.txt', 'E:/Fall2015/Research/CFD/ddn110B/Transfer/xline\h9-8477.txt']
working in: E:/Fall2015/Research/CFD/ddn110B/Transfer/xline on: h0-8477
Traceback (most recent call last):
File "<ipython-input-52-0503f720722f>", line 54, in <module>
data2 = np.loadtxt(filename, skiprows=1)
File "E:\WinPython-64bit-2.7.10.3\python-2.7.10.amd64\lib\site-packages\numpy\lib\npyio.py", line 691, in loadtxt
fh = iter(open(fname, 'U'))
IOError: [Errno 2] No such file or directory: 'h9-8477.txt'
我希望我明白你的意思，但不是很清楚。当用户输入时间步长时，只有与该时间步长对应的文件才会被加载并进一步用于您的绘图功能：
我考虑了以下结构：
project/
| cfd_plot.py
+ sample/
| | h0-16144.txt
| | h1-16144.txt
| | h3-16144.txt
| | h0-25611.txt
| | h1-25611.txt
| | <...>
这里是cfd_plot.py
from __future__ import print_function
import numpy as np
from matplotlib import pyplot as plt
import os
import re
# pth is a path for plt to save the image
def xlineplots(X1, Y1, V1, Tr1n, pth):
_, ax = plt.subplots()
ax.plot(X1, Tr1)
ax.legend(['h0', 'h3', 'h5', 'h7', 'h9'], loc=0)
ax.set_ylabel('Tracer Concentration')
ax.set_xlabel('X (m)')
ax.set_title('Tracer Concentration Variation along the Tank width')
plt.figtext(.6, .6, "Flow Time = 2400s", style='normal', alpha=.5)
plt.figtext(.6, .55, "Case: ddn110B", style='normal')
plt.savefig(pth + '-hp1.png', format='png', dpi=600)
_, ax = plt.subplots()
ax.plot(X1, V1)
ax.legend(['h0', 'h3', 'h5', 'h7', 'h9'], loc=0)
ax.set_ylabel('V (m/s)')
ax.set_xlabel('X (m)')
ax.set_title('Vertical Velocity Variation along the Tank width')
plt.figtext(.6, .6, "Flow Time = 2400s", style='normal', alpha=.5)
plt.figtext(.6, .55, "Case: ddn110B", style='normal', alpha=.5)
plt.savefig(pth + '-hv1.png', format='png', dpi=600)
FT_init = 3.1212
delt = .15 # Timestep size
TS_init = 165
flowtime = input("Enter the flow time required: ")
timestep = (int(flowtime) - FT_init) / delt
timestep = round(timestep + TS_init)
reps = ['sample'] # location where the files are located
# first simple version
# files = []
# for rep in reps: # recursive search for the files that match the timestep
# for dirpath, dirnames, filenames in os.walk(rep):
# for filename in [f for f in filenames if str(timestep) in f and f.endswith('.txt')]:
# files.append(os.path.join(dirpath, filename))
# second version, using regular expressions
reg_exp = '^.*-({:d})\.txt'.format(timestep)
files = []
for rep in reps: # recursive search for the files that match the timestep
for dirpath, dirnames, filenames in os.walk(rep):
for filename in [f for f in filenames if re.search(reg_exp, f)]:
files.append(os.path.join(dirpath, filename))
print('timestep:', timestep)
print('file(s) found: ', files)
for file in files:
directory = os.path.dirname(file) # directory of the .txt file
name = os.path.splitext(os.path.basename(file))[0] # basename of the .txt file
print('working in:', directory, 'on:', name)
data2 = np.loadtxt(file, skiprows=1)
data2 = data2[data2[:, 1].argsort()]
X1 = data2[:, 1] # Assign x-coordinate from the imported text file
Y1 = data2[:, 2] # Assign y-coordinate from the imported text file
V1 = data2[:, 4] # Assign y-velocity from the imported text file
Tr1 = data2[:, 5] # Assign Tracer Concentration from the imported text file
# here you can give directory + name or just name to xlineplots
xlineplots(X1, Y1, V1, Tr1, os.path.join(directory, name))
# xlineplots(X1, Y1, V1, Tr1, name)
更新：进行了一些编辑（评论）
UPDATE2: 在文件搜索中使用正则表达式，过滤器是 '^.*-({:d})\.txt'.format(timestep):
^ match beginning of the line
.* match any character (except newline), zero or multiple times
- match the character -
({:d}) match the timestep, formatted as an integer
\. match the character .
txt match characters txt
生成文件名或查找与特定模式匹配的文件名有问题吗？
我可以修改你的代码：
hs = [0,3,5,7,9]
timestep = 16144
filenames = ['h%s-%s'%(h, timestep) for h in hs]
for name in filenames:
fname = op.path.join(path1, name)
try:
data = np.loadtxt(fname, skiprows=1)
except IOError:
# cannot open this file, most likely because it does not exist
# continue with the next
continue
...
在这里，我将生成具有所需格式的文件名，并在可能的情况下加载和使用每个文件名。
我可以将 glob 或 re 应用于目录列表进行搜索，但我的 try-except 方法没有任何问题。很好 Python 风格。
==========================
这是使用 glob 的示例（在 Ipython 会话中）：
首先是一个带有一堆文件的测试目录（用`touch创建）：
In [9]: ls testdir
h1-123.txt h12-1234.txt h2-123.txt h2-124.txt h3-124.txt h343.txt
In [10]: import glob
一般搜索以 h 开头，以 .txt:
In [11]: glob.glob('testdir/h*.txt')
Out[11]:
['testdir/h2-124.txt',
'testdir/h3-124.txt',
'testdir/h12-1234.txt',
'testdir/h343.txt',
'testdir/h1-123.txt',
'testdir/h2-123.txt']
将其缩小为 2 个由破折号分隔的字段
In [12]: glob.glob('testdir/h*-*.txt')
Out[12]:
['testdir/h2-124.txt',
'testdir/h3-124.txt',
'testdir/h12-1234.txt',
'testdir/h1-123.txt',
'testdir/h2-123.txt']
将第一个字段限制为单个字符
In [13]: glob.glob('testdir/h?-*.txt')
Out[13]:
['testdir/h2-124.txt',
'testdir/h3-124.txt',
'testdir/h1-123.txt',
'testdir/h2-123.txt']
对于特定的 'time' 字符串：
In [14]: glob.glob('testdir/h?-123.txt')
Out[14]: ['testdir/h1-123.txt', 'testdir/h2-123.txt']
可以使用字符串格式创建搜索字符串
In [15]: times=123
In [16]: glob.glob('testdir/h?-%s.txt'%times)
==========================
使用 os 和 re 我可以像这样搜索：
In [28]: import os
In [29]: import re
In [30]: filelist=os.listdir('./testdir')
In [31]: [n for n in filelist if re.match('h[1-9]-123',n) is not None]
Out[31]: ['h1-123.txt', 'h2-123.txt']
======================
如果文件名中必须包含 4 位数字（或其他数字），则使用类似：
'h%d-%04d'%(3,123) # 'h3-0123'
'testdir/h?-%04d.txt'%times
无论您使用 try、glob 还是 re.