高精度打印numpy.float64 [英] Printing numpy.float64 with full precision

问题描述

打印numpy.float64并将其转换为字符串的正确/可接受的方法是什么?我注意到仅使用print或str()会损失一些精度.但是，repr保持完整精度.例如:

What is the proper/accepted way to print and convert a numpy.float64 to a string? I've noticed just using print or str() will lose some precision. However, repr maintains the full precision. For example:

>>> import numpy
>>> print numpy.float64('6374.345407799015')
6374.3454078
>>> print repr(numpy.float64('6374.345407799015'))
6374.3454077990154

1. 我假设仅调用print就会转换为对float64对象的调用str().那么numpy.float64的__str__()是用'%s' % (float(self))之类实现的还是用Python内置的float()强制将float64转换?为此，我试图快速查看numpy来源，但并没有立即发现正在发生的事情.

1. I assume that just calling print turns into calling str() on the float64 object. So is __str__() for numpy.float64 implemented with something like '%s' % (float(self)) or somehow casts the float64 with Python's built-in float()? I tried to quickly look around the numpy source for this but wasn't immediately obvious what was happening.

我一直认为repr()应该返回有效的Python代码，而eval()可以使用该代码重新创建对象.这是公认的惯例吗?幸运的是，在这种情况下，numpy没有遵循此约定，因为repr()仅将原始数字作为字符串而不是像"numpy.float64('6374.345407799015')"这样的字符串返回.

I've always thought repr() should return valid Python code that could be used by eval() to re-create the object. Is this an accepted convention? Luckily in this case numpy does not follow this convention because repr() returns just the raw number as a string instead of something like "numpy.float64('6374.345407799015')".

因此，所有这些使我感到困惑.将numpy.float64转换为字符串和/或打印它同时又确保始终具有相同的全精度的正确方法是什么?

So, all of this confuses me. What is the correct way to convert a numpy.float64 to a string and/or print it while guaranteeing you always have the same, full precision?

推荐答案

astype方法效果很好:

>>> numpy.float64('6374.345407799015').astype(str)
'6374.345407799015'

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