Hi all,
I've noticed a change in numpy.histogram2d between (possibly very much)
older versions and the current one: The function can no longer handle
the situation where bin edges decrease instead of increasing monotonically.
The reason for this seems to be the handling of outliers histogramdd,
see the output of minimal example below.
If I understand correctly, this is the only place where histogramdd
implicitly assumes monotonically increasing bin edges. If so, this could
be fixed to work with increasing and decreasing bin edges by taking
abs(dedges[i]).min() when calculating the rounding precision. If not, it
might be more consistent, and produce a more meaningful error message,
if histogram2d asserted that bin edges increase monotonically and
otherwise raised an AttributeError as the 1-d histogram() function does
in that case (see below)
Matthias
In [1]: import numpy
In [2]: numpy.__version__
Out[2]: '1.5.1'
In [3]: ascending=numpy.array([0,1])
In [4]: descending=numpy.array([1,0])
In [5]: numpy.histogram2d([0.5],[0.5],bins=(ascending,ascending))
Out[5]: (array([[ 1.]]), array([ 0., 1.]), array([ 0., 1.]))
In [6]: numpy.histogram2d([0.5],[0.5],bins=(descending,descending))
Warning: invalid value encountered in log10
---------------------------------------------------------------------------
ValueError Traceback (most recent call last)
/lib/python2.6/site-packages/numpy/lib/twodim_base.pyc in histogram2d(x,
y, bins, range, normed, weights)
613 xedges = yedges = asarray(bins, float)
614 bins = [xedges, yedges]
--> 615 hist, edges = histogramdd([x,y], bins, range, normed, weights)
616 return hist, edges[0], edges[1]
617
/lib/python2.6/site-packages/numpy/lib/function_base.pyc in
histogramdd(sample, bins, range, normed, weights)
312 for i in arange(D):
313 # Rounding precision
--> 314 decimal = int(-log10(dedges[i].min())) +6
315 # Find which points are on the rightmost edge.
316 on_edge = where(around(sample[:,i], decimal) ==
around(edges[i][-1],
ValueError: cannot convert float NaN to integer
Behavior of the 1-d histogram()
In [8]: numpy.histogram([0.5],bins=ascending)
Out[8]: (array([1]), array([0, 1]))
In [9]: numpy.histogram([0.5],bins=descending)
---------------------------------------------------------------------------
AttributeError Traceback (most recent call last)
/lib/python2.6/site-packages/numpy/lib/function_base.pyc in histogram(a,
bins, range, normed, weights)
160 if (np.diff(bins) < 0).any():
161 raise AttributeError(
--> 162 'bins must increase monotonically.')
163
164 # Histogram is an integer or a float array depending on the
weights.
AttributeError: bins must increase monotonically.