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<p>好吧。我有一些Matlab的背景知识,现在我转向Python。
我在64位Linux上的Pythnon 2.6.5下有这段代码,它在目录中滚动,找到名为'通用数据.dat,从中检索一些数据并将它们缝合到新的数据集中:</p>
<pre><code>import pylab as p
import os, re
import linecache as ln
def LoadGenomeMeanSize(arg, dirname, files):
for file in files:
filepath = os.path.join(dirname, file)
if filepath == os.path.join(dirname,'GeneralData.dat'):
data = p.genfromtxt(filepath)
if data[-1,4] != 0.0: # checking if data set is OK
data_chopped = data[1000:-1,:] # removing some of data
Grand_mean = data_chopped[:,2].mean()
Grand_STD = p.sqrt((sum(data_chopped[:,4]*data_chopped[:,3]**2) + sum((data_chopped[:,2]-Grand_mean)**2))/sum(data_chopped[:,4]))
else:
break
if filepath == os.path.join(dirname,'ModelParams.dat'):
l = re.split(" ", ln.getline(filepath, 6))
turb_param = float(l[2])
arg.<a href="https://www.cnpython.com/list/append" class="inner-link">append</a>((Grand_mean, Grand_STD, turb_param))
GrandMeansData = []
os.path.walk(os.getcwd(), LoadGenomeMeanSize, GrandMeansData)
GrandMeansData = sorted(GrandMeansData, key=lambda data_sort: data_sort[2])
TheMeans = p.zeros((len(GrandMeansData), 3 ))
i = 0
for item in GrandMeansData:
TheMeans[i,0] = item[0]
TheMeans[i,1] = item[1]
TheMeans[i,2] = item[2]
i += 1
print TheMeans # just checking...
# later do some computation on TheMeans in NumPy
</code></pre>
<p>它让我想起了这个(尽管我发誓这是一个月的自我):</p>
^{pr2}$
<p>好吧。。。所以我去读了一下,得出了一个全局变量:</p>
<pre><code>import pylab as p
import os, re
import linecache as ln
Grand_mean = p.nan
Grand_STD = p.nan
def LoadGenomeMeanSize(arg, dirname, files):
for file in files:
global Grand_mean
global Grand_STD
filepath = os.path.join(dirname, file)
if filepath == os.path.join(dirname,'GeneralData.dat'):
data = p.genfromtxt(filepath)
if data[-1,4] != 0.0: # checking if data set is OK
data_chopped = data[1000:-1,:] # removing some of data
Grand_mean = data_chopped[:,2].mean()
Grand_STD = p.sqrt((sum(data_chopped[:,4]*data_chopped[:,3]**2) + sum((data_chopped[:,2]-Grand_mean)**2))/sum(data_chopped[:,4]))
else:
break
if filepath == os.path.join(dirname,'ModelParams.dat'):
l = re.split(" ", ln.getline(filepath, 6))
turb_param = float(l[2])
arg.append((Grand_mean, Grand_STD, turb_param))
GrandMeansData = []
os.path.walk(os.getcwd(), LoadGenomeMeanSize, GrandMeansData)
GrandMeansData = sorted(GrandMeansData, key=lambda data_sort: data_sort[2])
TheMeans = p.zeros((len(GrandMeansData), 3 ))
i = 0
for item in GrandMeansData:
TheMeans[i,0] = item[0]
TheMeans[i,1] = item[1]
TheMeans[i,2] = item[2]
i += 1
print TheMeans # just checking...
# later do some computation on TheMeans in NumPy
</code></pre>
<p>它不提供错误消息。甚至给了一个包含数据的文件。。。但数据是大错特错了!我通过运行命令手动检查了其中一些:</p>
<pre><code>import pylab as p
data = p.genfromtxt(filepath)
data_chopped = data[1000:-1,:]
Grand_mean = data_chopped[:,2].mean()
Grand_STD = p.sqrt((sum(data_chopped[:,4]*data_chopped[:,3]**2) \
+ sum((data_chopped[:,2]-Grand_mean)**2))/sum(data_chopped[:,4]))
</code></pre>
<p>在选定的文件上。它们是不同的:-(</p>
<p>1)谁能给我解释一下怎么了?在</p>
<p>2)有人知道解决办法吗?在</p>
<p>我将非常感谢您的帮助:-)</p>
<p>干杯,
PTR</p>