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ipython 7.26.0
numpy 1.21.2
python 3.9.6
vigra 1.11.1 from "conda install -c conda-forge vigra"
gcc 4.8.5 20150623 (Red Hat 4.8.5-44)
import numpy as np
import vigra as v
test = np.random.rand(3,10,20,30) #test.dtype is float64
array = v.VigraArray(test, axistags=v.defaultAxistags('cxyz')) #array.dtype is float32
divarray=v.filters.gaussianDivergence(array) #works fine
view = v.taggedView(test, axistags=v.defaultAxistags('cxyz')) #view.dtype is float64
print(type(vview)==type(varray)) #outputs True
divview = v.filters.gaussianDivergence(view) #ValueError, see below
<ipython-input-14-410d6fe7acbf> in <module>
----> 1 divview = v.filters.gaussianDivergence(view)
ValueError: No C++ overload matches the arguments. This can have three reasons:
* The array arguments may have an unsupported element type. You may need
to convert your array(s) to another element type using 'array.astype(...)'.
The function currently supports the following types:
float32, float64
* The dimension of your array(s) is currently unsupported (consult the
function's documentation for information about supported dimensions).
* You provided an unrecognized argument, or an argument with incorrect type
(consult the documentation for valid function signatures).
Additional overloads can easily be added in the vigranumpy C++ sources.
Please submit an issue at http://github.com/ukoethe/vigra/ to let us know
what you need (or a pull request if you solved it on your own :-).
Type 'help(vigra.filters.gaussianDivergence)' to get full documentation.
The types of the inputs to the function vigra.filters.gaussianDivergence all have the same type at least in the python/vigranumpy interface. So why is there no overload for one (view), but for the other (not view, new array) it works?
The text was updated successfully, but these errors were encountered:
ipython 7.26.0
numpy 1.21.2
python 3.9.6
vigra 1.11.1 from "conda install -c conda-forge vigra"
gcc 4.8.5 20150623 (Red Hat 4.8.5-44)
The types of the inputs to the function vigra.filters.gaussianDivergence all have the same type at least in the python/vigranumpy interface. So why is there no overload for one (view), but for the other (not view, new array) it works?
The text was updated successfully, but these errors were encountered: