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(8) 
From: Eric Firing <efiring@ha...>  20080503 18:08:13

Manuel Metz wrote: > Hi, > while adding the stephistogram I learned about the change of > numpy.histogram. As MPL trunk relies in numpy 1.1, I think its a good > idea to switch to the new histogram, i.e. use "new=True". Indeed, this > is required to be able to allow to give binedges, which is possible > with MPL 0.91. > However, while keeping API compatibility on the one hand by allowing > to provide binedges, this step also breaks API compatibility since the > definition of bins has changed: > > numpy 1.0.4 > > In [1]:from numpy import * > In [2]:random.seed(18) > In [3]:x = random.random(100) > In [4]:histogram(x, bins=array([0,0.1,0.2])) > Out[4]:(array([11, 11, 78]), array([ 0. , 0.1, 0.2])) > > numpy 1.1.0.dev5106' > > In [1]:from numpy import * > In [2]:random.seed(18) > In [3]:x = random.random(100) > In [4]: histogram(x, bins=array([0,0.1,0.2]),new=True) > Out[4]: (array([11, 11]), array([ 0. , 0.1, 0.2])) > > > How should this be handled? Follow numpy, breaking API compatibility and > point to the API change of histogram? Or keeping API compatibility with > MPL0.91 and write a wrapper function? > > I would prefer the first option... I strongly agree. Eric > > Manuel 
From: Manuel Metz <mmetz@as...>  20080503 16:57:39

Here's the link to the numpy wiki: http://projects.scipy.org/scipy/numpy/roadmap#Semanticchangeforhistogram Manuel Metz wrote: > Hi, > while adding the stephistogram I learned about the change of > numpy.histogram. As MPL trunk relies in numpy 1.1, I think its a good > idea to switch to the new histogram, i.e. use "new=True". Indeed, this > is required to be able to allow to give binedges, which is possible > with MPL 0.91. > However, while keeping API compatibility on the one hand by allowing > to provide binedges, this step also breaks API compatibility since the > definition of bins has changed: > > numpy 1.0.4 > > In [1]:from numpy import * > In [2]:random.seed(18) > In [3]:x = random.random(100) > In [4]:histogram(x, bins=array([0,0.1,0.2])) > Out[4]:(array([11, 11, 78]), array([ 0. , 0.1, 0.2])) > > numpy 1.1.0.dev5106' > > In [1]:from numpy import * > In [2]:random.seed(18) > In [3]:x = random.random(100) > In [4]: histogram(x, bins=array([0,0.1,0.2]),new=True) > Out[4]: (array([11, 11]), array([ 0. , 0.1, 0.2])) > > > How should this be handled? Follow numpy, breaking API compatibility and > point to the API change of histogram? Or keeping API compatibility with > MPL0.91 and write a wrapper function? > > I would prefer the first option... > > Manuel > 
From: Manuel Metz <mmetz@as...>  20080503 16:35:46

Hi, while adding the stephistogram I learned about the change of numpy.histogram. As MPL trunk relies in numpy 1.1, I think its a good idea to switch to the new histogram, i.e. use "new=True". Indeed, this is required to be able to allow to give binedges, which is possible with MPL 0.91. However, while keeping API compatibility on the one hand by allowing to provide binedges, this step also breaks API compatibility since the definition of bins has changed: numpy 1.0.4 In [1]:from numpy import * In [2]:random.seed(18) In [3]:x = random.random(100) In [4]:histogram(x, bins=array([0,0.1,0.2])) Out[4]:(array([11, 11, 78]), array([ 0. , 0.1, 0.2])) numpy 1.1.0.dev5106' In [1]:from numpy import * In [2]:random.seed(18) In [3]:x = random.random(100) In [4]: histogram(x, bins=array([0,0.1,0.2]),new=True) Out[4]: (array([11, 11]), array([ 0. , 0.1, 0.2])) How should this be handled? Follow numpy, breaking API compatibility and point to the API change of histogram? Or keeping API compatibility with MPL0.91 and write a wrapper function? I would prefer the first option... Manuel 