numpy-discussion

[Numpy-discussion] help! type 'float64scalar' is not type 'float'

[Sebastian H. <ha...@ms...>]

Hi!
I just finished maybe a total of 5 hours tracking down a nasty bug.
So I thought I would share this:
I'm keeping a version of (old) SciPy's 'plt' module around.
(I know about matplotlib - anyway - ...)
I changed the code some time ago from Numeric to numarray - no problem.
Now I switched to numpy ... and suddenly the zooming does not work 
anymore: it always zooms to "full view".

Finally I traced the problem down to a utility function:
"is_number" - it is simply implemented as
def is_number(val):
     return (type(val) in [type(0.0),type(0)])

As I said - now I finally saw that I always got
False since the type of my number (0.025) is
  <type 'float64scalar'>
and that's neither <type 'float'> nor <type 'int'>

OK - how should this have been done right ?

Anyway, I'm excited about the new numpy
and am looking forward to it's progress
Thanks,
Sebastian Haase

Re: [Numpy-discussion] help! type 'float64scalar' is not type 'float'

[Robert K. <rob...@gm...>]

Sebastian Haase wrote:
> Hi!
> I just finished maybe a total of 5 hours tracking down a nasty bug.
> So I thought I would share this:
> I'm keeping a version of (old) SciPy's 'plt' module around.
> (I know about matplotlib - anyway - ...)
> I changed the code some time ago from Numeric to numarray - no problem.
> Now I switched to numpy ... and suddenly the zooming does not work 
> anymore: it always zooms to "full view".
> 
> Finally I traced the problem down to a utility function:
> "is_number" - it is simply implemented as
> def is_number(val):
>      return (type(val) in [type(0.0),type(0)])
> 
> As I said - now I finally saw that I always got
> False since the type of my number (0.025) is
>   <type 'float64scalar'>
> and that's neither <type 'float'> nor <type 'int'>
> 
> OK - how should this have been done right ?

It depends on how is_number() is actually used. Probably the best thing to do 
would be to take a step back and reorganize whatever is calling it to not 
require specific types.

Quick-and-dirty: use isinstance() instead since float64scalar inherits from 
float. However, float32scalar does not, so this is not a real solution, just a 
hack to get you on your merry way.

-- 
Robert Kern

"I have come to believe that the whole world is an enigma, a harmless enigma
  that is made terrible by our own mad attempt to interpret it as though it had
  an underlying truth."
   -- Umberto Eco

Re: [Numpy-discussion] help! type 'float64scalar' is not type 'float'

[Travis O. <oli...@ie...>]

Sebastian Haase wrote:
> Hi!
> I just finished maybe a total of 5 hours tracking down a nasty bug.
>
> Finally I traced the problem down to a utility function:
> "is_number" - it is simply implemented as
> def is_number(val):
>      return (type(val) in [type(0.0),type(0)])
>
> As I said - now I finally saw that I always got
> False since the type of my number (0.025) is
>   <type 'float64scalar'>
> and that's neither <type 'float'> nor <type 'int'>
>
> OK - how should this have been done right ?
>
>   

Code that depends on specific types like this is going to be hard to 
maintain in Python because many types could reasonably act like a 
number.   I do see code like this pop up from time to time and it will 
bite you more with NumPy (which has a whole slew of scalar types).

The scalar-types are in a hierarchy and so you could replace the code with

def is_number(val):
      return isinstance(val, (int, float, numpy.number))

But, this will break with other "scalar-types" that it really should 
work with.   It's best to look at what is calling is_number and think 
about what it wants to do with the object and just try it and catch the 
exception.

-Travis

Re: [Numpy-discussion] help! type 'float64scalar' is not type 'float'

[Sebastian H. <ha...@ms...>]

Travis Oliphant wrote:
> Sebastian Haase wrote:
>> Hi!
>> I just finished maybe a total of 5 hours tracking down a nasty bug.
>>
>> Finally I traced the problem down to a utility function:
>> "is_number" - it is simply implemented as
>> def is_number(val):
>>      return (type(val) in [type(0.0),type(0)])
>>
>> As I said - now I finally saw that I always got
>> False since the type of my number (0.025) is
>>   <type 'float64scalar'>
>> and that's neither <type 'float'> nor <type 'int'>
>>
>> OK - how should this have been done right ?
>>
>>   
> 
> Code that depends on specific types like this is going to be hard to 
> maintain in Python because many types could reasonably act like a 
> number.   I do see code like this pop up from time to time and it will 
> bite you more with NumPy (which has a whole slew of scalar types).
> 
> The scalar-types are in a hierarchy and so you could replace the code with
> 
> def is_number(val):
>      return isinstance(val, (int, float, numpy.number))
> 
> But, this will break with other "scalar-types" that it really should 
> work with.   It's best to look at what is calling is_number and think 
> about what it wants to do with the object and just try it and catch the 
> exception.
> 
> -Travis
> 

Thanks,
I just found
numpy.isscalar() and numpy.issctype()   ?
These sound like they would do what I need - what is the difference 
between the two ?
(I found that issctype worked OK while isscalar gave some exception in 
some cases !? )

- Sebastian

Re: [Numpy-discussion] help! type 'float64scalar' is not type 'float'

[Travis O. <oli...@ie...>]

Sebastian Haase wrote:
> Thanks,
> I just found
> numpy.isscalar() and numpy.issctype()   ?
> These sound like they would do what I need - what is the difference 
> between the two ?
>   
Oh, yeah. 

numpy.issctype works with type objects
numpy.isscalar works with instances

Neither of them distinguish between scalars and "numbers." 

If you get errors with isscalar it would be nice to know what they are.

-Travis

Re: [Numpy-discussion] =?iso-8859-1?q?help!_type_=27float64scalar=27_?= =?iso-8859-1?q?is_not_type=09=27float=27?=

[Sebastian H. <ha...@ms...>]

On Wednesday 02 August 2006 22:43, Travis Oliphant wrote:
> Sebastian Haase wrote:
> > Thanks,
> > I just found
> > numpy.isscalar() and numpy.issctype()   ?
> > These sound like they would do what I need - what is the difference
> > between the two ?
>
> Oh, yeah.
>
> numpy.issctype works with type objects
> numpy.isscalar works with instances
>
> Neither of them distinguish between scalars and "numbers."
>
> If you get errors with isscalar it would be nice to know what they are.

I'm still trying to reproduce the exception, but here is a first comparison 
that - honestly - does not make much sense to me:
(type vs. instance seems to get mostly the same results  and why is there a 
difference with a string ('12') )

>>> N.isscalar(12) 
True
>>> N.issctype(12)
True

>>> N.isscalar('12')
True
>>> N.issctype('12')
False

>>> N.isscalar(N.array([1]))
False
>>> N.issctype(N.array([1]))
True

>>> N.isscalar(N.array([1]).dtype)
False
>>> N.issctype(N.array([1]).dtype)
False

  # apparently new 'scalars' have a dtype attribute !
>>> N.isscalar(N.array([1])[0].dtype)
False
>>> N.issctype(N.array([1])[0].dtype)
False

>>> N.isscalar(N.array([1])[0])
True
>>> N.issctype(N.array([1])[0])
True 

-Sebastian

Re: [Numpy-discussion] help! type 'float64scalar' is not type 'float'

[Christopher B. <Chr...@no...>]

Sebastian Haase wrote:
> Finally I traced the problem down to a utility function:
> "is_number" - it is simply implemented as
> def is_number(val):
>      return (type(val) in [type(0.0),type(0)])

> OK - how should this have been done right ?

Well, as others have said, python is uses "duck typing", so you really 
shouldn't be checking for specific types anyway -- if whatever is passed 
in acts like it should, that's all you need not know. However, sometimes 
it does make sense to catch the error sooner, rather than later, so that 
it can be obvious, or handled properly, or give a better error message, 
or whatever.

In this case, I still use a "duck typing" approach: I don't need to know 
exactly what type it is, I just need to know that I can use it in the 
way I want, and an easy way to do that is to turn it into a known type:

def is_number(val):
     try:
	float(val)
	return True
     except ValueError:
	return False

Though more often, I'd just call float on it, and pass that along, 
rather than explicitly checking

This works at least with numpy float64scalar and float32scalar, and it 
should work with all numpy scalar types, except perhaps the long types 
that don't fit into a Python float.

it'll also turn string into floats if it can, which may or may not be 
what you want.

-Chris





-- 
Christopher Barker, Ph.D.
Oceanographer
                                     		
NOAA/OR&R/HAZMAT         (206) 526-6959   voice
7600 Sand Point Way NE   (206) 526-6329   fax
Seattle, WA  98115       (206) 526-6317   main reception

Chr...@no...

Re: [Numpy-discussion] help! type 'float64scalar' is not type 'float'

[Sebastian H. <ha...@ms...>]

On Thursday 03 August 2006 13:19, Travis Oliphant wrote:
> Sebastian Haase wrote:
> >On Wednesday 02 August 2006 22:43, Travis Oliphant wrote:
> >>Sebastian Haase wrote:
> >>>Thanks,
> >>>I just found
> >>>numpy.isscalar() and numpy.issctype()   ?
> >>>These sound like they would do what I need - what is the difference
> >>>between the two ?
> >>
> >>Oh, yeah.
> >>
> >>numpy.issctype works with type objects
> >>numpy.isscalar works with instances
> >>
> >>Neither of them distinguish between scalars and "numbers."
> >>
> >>If you get errors with isscalar it would be nice to know what they are.
> >
> >I'm still trying to reproduce the exception, but here is a first
> > comparison that - honestly - does not make much sense to me:
> >(type vs. instance seems to get mostly the same results  and why is there
> > a difference with a string ('12') )
>
> These routines are a little buggy.  I've cleaned them up in SVN to
> reflect what they should do.    When the dtype object came into
> existence a lot of what the scalar types where being used for was no
> longer needed.   Some of these functions weren't updated to deal with
> the dtype objects correctly either.
>
> This is what you get now:
>  >>> import numpy as N
>  >>> N.isscalar(12)
>
> True
>
>  >>> N.issctype(12)
>
> False
>
>  >>> N.isscalar('12')
>
> True
>
>  >>> N.issctype('12')
>
> False
>
>  >>> N.isscalar(N.array([1]))
>
> False
>
>  >>> N.issctype(N.array([1]))
>
> False
>
>  >>> N.isscalar(N.array([1]).dtype)
>
> False
>
>  >>> N.issctype(N.array([1]).dtype)
>
> True
>
>  >>> N.isscalar(N.array([1])[0].dtype)
>
> False
>
>  >>> N.issctype(N.array([1])[0].dtype)
>
> True
>
>  >>> N.isscalar(N.array([1])[0])
>
> True
>
>  >>> N.issctype(N.array([1])[0])
>
> False
>
>
> -Travis

Great!
Just wanted to point out that '12' is a scalar  - 
I suppose that's what it is. 

 (To determine if something is a number it seems 
best to implement a try: ... except: ... something like float(x)  - as Chris 
has suggested )

-S.