我是 Python 新手……这是我的问题。对于我在 Python 中测试的优化子例程，我需要解析一个带有数字的 csv 文件。
因此 csv 文件的格式为：
Support load summary for anchor at node 5,
Load combination,FX (N),FY (N),FZ (N),MX (Nm),MY (Nm),MZ (Nm),,
Sustained,-3,-2679,120,2012,164,69,,
Operating1,1472,2710,-672,-4520,8743,-2047,,
Maximum,1472,2710,120,2012,8743,69,,
Minimum,-3,-2679,-672,-4520,164,-2047,,
Support load summary for anchor at node 40,
Load combination,FX (N),FY (N),FZ (N),MX (Nm),MY (Nm),MZ (Nm),,
Sustained,9,-3872,-196,-91,854,-3914,,
Operating1,-2027,-8027,3834,-7573,-9102,-6323,,
Maximum,9,-3872,3834,-91,854,-3914,,
Minimum,-2027,-8027,-196,-7573,-9102,-6323,,
Support load summary for anchor at node 125,
Load combination,FX (N),FY (N),FZ (N),MX (Nm),MY (Nm),MZ (Nm),,
Sustained,-7,-2448,76,264,83,1320,,
Operating1,556,-3771,-3162,-6948,-1367,1272,,
Maximum,556,-2448,76,264,83,1320,,
Minimum,-7,-3771,-3162,-6948,-1367,1272,,
Support load summary for Hanger at node 10,
Load combination,Load (N),,
Sustained,-3668,,
Operating1,-13876,,
Maximum,-3668,,
Minimum,-13876,,
Support load summary for Hanger at node 20B,
Load combination,Load (N),,
Sustained,-14305,,
Operating1,-13359,,
Maximum,-13359,,
Minimum,-14305,,
Support load summary for restraint at node 115B,
Load combination,FX (N),FY (N),FZ (N),,
Sustained,,-5655,,,
Operating1,3696,,
Maximum,,3696,,,
Minimum,,-5655,,,
我的代码主要在以开头的行上工作
Operating1,
Maximum,
Minimum,
工作（成本函数）是对这些关键字之一之后的所有数字进行总计（代数）。有时您可以在上面的数据文件中看到，第二列或第三列中只有一个数字。（见数据文件的结尾），有时，像下面的文件片段一样根本没有数字（见下面的 Operating1 行）。
Support load summary for Hanger at node 115B,
Load combination,Load (N),,
Sustained,-5188,,
Operating1,,,
Maximum,,,
Minimum,-5188,,
我正在使用 np.genfromtxt()。效果很好，除非我遇到列中值少于 4 个或有时根本没有值的行。
我在 genfromtxt() 上使用 sum() - 请参阅代码。当只有一个值时，我使用了 float()。当没有时，我试图识别并分配零给总数。我可以为每种情况进行自定义，但我想知道是否有一种通用的、更抽象的方法来读取和汇总不可预测的情况下的数字。
另外，我尝试了“missing_values”和“filling_values”，但它们似乎不起作用。如何计算文件中非零列的数量？
到目前为止，这是部分代码：
def optimize(fn, optflag):
modeltotals = []
i=0
csv1 = []
j = 1 # line # count
for line in csv.reader(filelist) :
temp = repr(line)
if "Support load summary" in temp :
csv1.append(line) # just making another list of actionable lines for future use
if (d): print "\n", line
continue
if (optflag == "ope") : # optimize on Operating loads
if "Operating1" in temp:
csv1.append(line)
if (len(line) > 4):
modeltotals.append(sum(np.genfromtxt(line[1:], delimiter=",")))
if (d): print "Sum of OPE Loads:", modeltotals[i], "\n"
elif (len(line) > 0 and len(line) <= 4):
if (d): print "line=", line, "length", len(line)
line1 = np.genfromtxt(line[1:], delimiter=",")
if not line1: # meaning if array is empty
modeltotals.append(0)
else:
modeltotals.append(np.genfromtxt(line[1:], delimiter=",", missing_values=[0,0,0,0]))
if (d): print "OPE Max:", modeltotals[i],"\n"
i +=1
elif (optflag == "minmax") : #optimize on all loads, min and max.
#print "i=", i
if "Maximum" in temp:
csv1.append(line)
if (len(line) > 4):
modeltotals.append(sum(np.genfromtxt(line[1:], delimiter=",")))
if (d): print "Sum of Maxs:", modeltotals[i]
elif (len(line) <= 4):
#line1 = np.genfromtxt(line[1:], delimiter=",", filling_values = 0)
#modeltotals.append(sum(line1))
if (d): print "line=", line, "length", len(line)
line1 = np.genfromtxt(line[1:], delimiter=",")
print "line1 =", line1
if not line1: # meaning if array is empty
modeltotals.append(0)
else:
modeltotals.append(np.genfromtxt(line[1:], delimiter=",", filling_values = 0))
if (d): print "Max:", modeltotals[i]
i+=1
elif "Minimum" in temp:
csv1.append(line)
if (len(line) > 4):
#print "#", j, "line", line
modeltotals.append(sum(np.genfromtxt(line[1:], delimiter=",")))
if (d): print "Sum of Mins:", modeltotals[i]
elif (len(line) > 0 and len(line) <= 4):
if (d): print "line=", line, "length", len(line)
line1 = np.genfromtxt(line[1:], delimiter=",")
if not line1: # meaning if array is empty
modeltotals.append(0)
else:
modeltotals.append(np.genfromtxt(line[1:], delimiter=","))
if (d): print "Min:", modeltotals[i]
i +=1
j+=1
if len(modeltotals) > 0:
print modeltotals
average = float(sum(modeltotals))/len(modeltotals) #sometimes error here
else:
return "000" # error, seems like no file was analyzed
if (d):
print "Current model mean =", average
del csv1[:]
return abs(average)
我在不同文件中遇到的几个错误是相似的：
['Support load summary for restraint at node 20B', '']
Traceback (most recent call last):
File "sor4.py", line 190, in <module>
modelmean[filename] = optimize(filename, args.optimizeon)
File "sor4.py", line 107, in optimize
modeltotals.append(sum(np.genfromtxt(line[1:], delimiter=",")))
TypeError: iteration over a 0-d array
另一个错误是“无法转换为标量”。
我了解这些错误，但对如何巧妙处理它们的 Python 知之甚少。对不起，很长的帖子；我会更好地更简洁地介绍信息。正如这里的另一位海报所说，我将不胜感激地接受您的回答。谢谢你。