CSV methodology
Peter Otten
__peter__ at web.de
Tue Sep 16 07:22:02 EDT 2014
jayte wrote:
> On Mon, 15 Sep 2014 09:29:02 +0200, Peter Otten <__peter__ at web.de> wrote:
>
>>jayte wrote:
>>
>>> Sorry, I neglected to mention the values' significance. The MXP program
>>> uses the "distance estimate" algorithm in its fractal data generation.
>>> The values are thus, for each point in a 1778 x 1000 image:
>>>
>>> Distance, (an extended double)
>>> Iterations, (a 16 bit int)
>>> zc_x, (a 16 bit int)
>>> zc_y (a 16 bit int)
>>>
>>
>>Probably a bit too early in your "Python career",
>
> Absolutely, just thought it would be interesting to start experimenting,
> while learning (plus, can't help but be anxious) <g>
>
>> but you can read raw data
>>with numpy. Something like
>>
>>with open(filename, "rb") as f:
>> a = numpy.fromfile(f, dtype=[
>> ("distance", "f16"),
>> ("iterations", "i2"),
>> ("zc_x", "i2"),
>> ("zc_y", "i2"),
>> ]).reshape(1778, 1000)
>>
>>might do, assuming "extended double" takes 16 bytes.
>
> Will try. Double extended precision is ten bytes, but I assume
> changing the "f16" to "f10" would account for that...
Unfortunately it seems that numpy doesn't support "f10"
>>> numpy.dtype("f8")
dtype('float64')
>>> numpy.dtype("f16")
dtype('float128')
>>> numpy.dtype("f10")
dtype('float32') # looks strange to me
But you better ask for confirmation (and possible workarounds) in a
specialist forum.
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