[英]Reading a file with Fortran formatted small floats, using numpy
I am trying to read a data file written by a Fortran program, in which every once in a while there is a very small float like 0.3299880-104
. 我正在尝试读取由Fortran程序编写的数据文件,其中每隔一段时间会有一个非常小的浮点数,例如
0.3299880-104
。 The error message is: 错误消息是:
>np.loadtxt(filename, usecols = (1,))
File "/home/anaconda2/lib/python2.7/site-packages/numpy/lib/npyio.py", line 928, in loadtxt
items = [conv(val) for (conv, val) in zip(converters, vals)]
File "/home/anaconda2/lib/python2.7/site-packages/numpy/lib/npyio.py", line 659, in floatconv
return float(x)
ValueError: invalid literal for float(): 0.3299880-104
Can I do something to make Numpy able to read this data file anyway? 我是否可以做一些事情使Numpy仍然能够读取此数据文件?
As @agentp mentioned in the comments, one approach would be to use the converters=
argument to np.genfromtxt
to insert the e
characters before casting to float: 正如@agentp在评论中提到的那样,一种方法是使用
np.genfromtxt
的converters=
参数在强制转换为float之前插入e
字符:
import numpy as np
# some example strings
strings = "0.3299880-104 0.3299880+104 0.3299880"
# create a "dummy file" (see http://stackoverflow.com/a/11970414/1461210)
try:
from StringIO import StringIO # Python2
f = StringIO(strings)
except ImportError:
from io import BytesIO # Python3
f = BytesIO(strings.encode())
c = lambda s: float(s.decode().replace('+', 'e').replace('-', 'e-'))
data = np.genfromtxt(f, converters=dict(zip(range(3), [c]*3)))
print(repr(data))
# array([ 3.29988000e-105, 3.29988000e+103, 3.29988000e-001])
声明:本站的技术帖子网页,遵循CC BY-SA 4.0协议,如果您需要转载,请注明本站网址或者原文地址。任何问题请咨询:yoyou2525@163.com.