[SciPy-User] leastsq returns bizarre, not fitted, output for float values

[josef.pktd at gmail.com]

On Thu, Jun 10, 2010 at 11:15 AM, Charles R Harris
<charlesr.harris at gmail.com> wrote:
>
>
> On Thu, Jun 10, 2010 at 8:10 AM, Charles R Harris
> <charlesr.harris at gmail.com> wrote:
>>
>>
>> On Thu, Jun 10, 2010 at 8:02 AM, Matthieu Rigal <rigal at rapideye.de> wrote:
>>>
>>> OK, I've found the bug...
>>>
>>> Somehow the leastsq function is not working if both data sets are float
>>> 32
>>> type.
>>> By just adding following line the problem is solved :
>>> aX = numpy.asarray(aX, dtype=numpy.float64)
>>>
>>> Is it a known bug ? Should I add it to the bug tracker ?
>>>
>>> Best regards,
>>> Matthieu
>>>
>>
>> I think you should open a ticket and include a simple example.
>>
>
> I also note that the documentation of leastsq is totally screwed up and the
> covariance returned is not the covariance, nor is it the currently
> documented Jacobian.

cov_x is the raw covariance, what's wrong with the explanation

I never figured out how to get the Jacobian directly, and am not sure
about the details of the jacobian calculation

Josef

>
> Chuck
>
>
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