[Numpy-discussion] numpy.polynomial.chebyshev (not) in the docs
josef.pktd@gmai...
josef.pktd@gmai...
Tue Feb 9 20:52:35 CST 2010
On Tue, Feb 9, 2010 at 9:30 PM, David Goldsmith <d.l.goldsmith@gmail.com> wrote:
> Are you talking about absence in the Wiki or absence in a NumPy executable.
> They're in the former (I've been editing them), and they're in 1.4.0 of the
> latter:
I have them in numpy 1.4, I see them in the doceditor, but not in
http://docs.scipy.org/doc/numpy/search.html?q=chebychev&check_keywords=yes&area=default
or search for chebfit
I think they are not added to the html docs because they are not
referenced in any rst file.
That's a different issue from having them in the source and the
doceditor application.
Josef
>
>>>> import numpy as N
>>>> N.version.version
> '1.4.0'
>>>> from numpy.polynomial import chebyshev as C
>>>> help(C.chebfit)
> Help on function chebfit in module numpy.polynomial.chebyshev:
>
> chebfit(x, y, deg, rcond=None, full=False)
> Least squares fit of Chebyshev series to data.
>
> Fit a Chebyshev series ``p(x) = p[0] * T_{deq}(x) + ... + p[deg] *
> T_{0}(x)`` of degree `deg` to points `(x, y)`. Returns a vector of
> coefficients `p` that minimises the squared error.
>
> Parameters
> ----------
> x : array_like, shape (M,)
> x-coordinates of the M sample points ``(x[i], y[i])``.
> y : array_like, shape (M,) or (M, K)
> y-coordinates of the sample points. Several data sets of sample
> points sharing the same x-coordinates can be fitted at once by
> passing in a 2D-array that contains one dataset per column.
> Etc.
>
> What version of NumPy are you running?
>
> DG
>
> On Tue, Feb 9, 2010 at 4:40 PM, <josef.pktd@gmail.com> wrote:
>>
>> Similar to the recfunctions, I also don't find the new chebychev
>> polynomials in the docs.
>>
>> Are they linked from any rst file?
>>
>> A search in the online sphinx html docs comes up empty, and
>>
>> http://docs.scipy.org/numpy/docs/numpy-docs/reference/routines.poly.rst/#routines-poly
>> doesn't link to the new functions.
>>
>> The docstrings look nice but maybe nobody sees them.
>>
>> Josef
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>
>
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