incremental histogram
I have coded in c++ a histogram object that can be used as: h += my_sample or h += my_vector This is very useful in simulations which are looping and developing results incrementally. It would me great to have such a feature in numpy.
On 03/05/2010 16:02, Neal Becker wrote:
I have coded in c++ a histogram object that can be used as:
h += my_sample
or
h += my_vector
This is very useful in simulations which are looping and developing results incrementally. It would me great to have such a feature in numpy.
Neal, I like the idea of a faster np.histogram / histogramdd; but it would have to be compatible with numpy and pylab or at least a clear, documented subset (doc first). Some Wibnis, wouldn't it be nice ifs, for WibniHistogram: - gui with realtime zoom / upsample / smooth: must exist, physicists ? - adaptive binning, e.g. percentiles then uniform - interpolate: fill holes, then *linear or spline += data is nice, but seems orthogonal to histogramming -- why not just subclass histogram ? cheers -- denis
denis wrote:
On 03/05/2010 16:02, Neal Becker wrote:
I have coded in c++ a histogram object that can be used as:
h += my_sample
or
h += my_vector
This is very useful in simulations which are looping and developing results incrementally. It would me great to have such a feature in numpy.
Neal, I like the idea of a faster np.histogram / histogramdd; but it would have to be compatible with numpy and pylab or at least a clear, documented subset (doc first).
The point is not to be faster, it's to be incremental.
Some Wibnis, wouldn't it be nice ifs, for WibniHistogram: - gui with realtime zoom / upsample / smooth: must exist, physicists ? - adaptive binning, e.g. percentiles then uniform - interpolate: fill holes, then *linear or spline
+= data is nice, but seems orthogonal to histogramming -- why not just subclass histogram ?
I thought np histogram was a function, not a class? To be incremental, it has to have state, and so should be a class.
On 04/05/2010 14:09, Neal Becker wrote:
denis wrote:
Neal, I like the idea of a faster np.histogram / histogramdd; but it would have to be compatible with numpy and pylab or at least a clear, documented subset (doc first).
The point is not to be faster, it's to be incremental.
OK, different points: I'd like it to be very fast and leverage it
Some Wibnis, wouldn't it be nice ifs, for WibniHistogram: - gui with realtime zoom / upsample / smooth: must exist, physicists ? - adaptive binning, e.g. percentiles then uniform - interpolate: fill holes, then *linear or spline
Do any of these make sense / resonate ?
+= data is nice, but seems orthogonal to histogramming -- why not just subclass histogram ?
I thought np histogram was a function, not a class? To be incremental, it has to have state, and so should be a class.
Yes you're right. Is it worth making into a class, with C or Cython ?
participants (2)
-
denis -
Neal Becker