On 07/29/2015 10:34 PM, Paul Hobson wrote:
> See the following example:
>
> import matplotlib as mpl
> c = mpl.cm.get_cmap()
> bnorm = mpl.colors.BoundaryNorm([0,1,2], c.N)
> nnorm = mpl.colors.Normalize(0, 2)
>
> # This works:
> In [8]: c(nnorm(1.1))
> Out[8]: (0.64199873497786197, 1.0, 0.32574320050600891, 1.0)
>
> # This doesn't:
> In [9]: c(bnorm(1.1))
> (...)
> TypeError: 'numpy.int16' object does not support item assignment
>
> # But this works:
> In [10]: c(bnorm([1.1]))
> Out[10]: array([[ 0.5, 0. , 0. , 1. ]])
>
> From the doc I would expect BoundaryNorm and Normalize to work the
> same
> way. I find the error sent by BoundaryNorm quite misleading.
>
> Should I fill a bug report for this?
>
>
> Fabien,
>
> What happens if your force the boundaries to floats? By that I mean:
> bnorm = mpl.colors.BoundaryNorm([0.0, 1.0, 2.0], c.N)
> -Paul
Thanks Paul,
it doesn't change anything. The problem is related to the variable iret
which is of shape (): the assignment fails at L1281 in colors.py. Here
is the code:
def __call__(self, x, clip=None):
if clip is None:
clip = self.clip
x = ma.asarray(x) # <--- doesnt guarantee 1D
mask = ma.getmaskarray(x)
xx = x.filled(self.vmax + 1)
if clip:
np.clip(xx, self.vmin, self.vmax)
iret = np.zeros(x.shape, dtype=np.int16) # <--- x.shape = ()
for i, b in enumerate(self.boundaries):
iret[xx >= b] = i
if self._interp:
scalefac = float(self.Ncmap - 1) / (self.N - 2)
iret = (iret * scalefac).astype(np.int16)
iret[xx < self.vmin] = -1 # <--- error
iret[xx >= self.vmax] = self.Ncmap
ret = ma.array(iret, mask=mask)
if ret.shape == () and not mask:
ret = int(ret)
return ret
It should be easy to fix by changing
iret = np.zeros(x.shape, dtype=np.int16)
to:
iret = np.atleast1d(np.zeros(x.shape, dtype=np.int16))
But this would lead to an output which is never a scalar even if a
scalar is given as input. Is that a problem?
Cheers,
Fabien
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