Comments (3)
This is indeed weird.
Could you please do the following:
- print the array flags before and after the call to
ascontiguousarray
and post it here - post the conda env you are using (
conda list
) here
Also, you mentioned that you get a seg-fault with different numpy versions earlier.
Can you also reproduce this with such an easy example?
from cluster_tools.
I just checked and for me this runs without any issues (DON'T need the ascontiguousarray
).
I am using vigra 1.11.1 and numpy 1.15.4 from conda-forge and
z5py / nifty build from recent master.
So I assume that this is some subtle numpy incompatibility issue.
Should be fixed once nifty is on conda-forge and the conda env has proper numpy version pinning.
See conda-forge/staged-recipes#7763
from cluster_tools.
Sorry for the late reply.
print the array flags before and after the call to
ascontiguousarray
and post it here
Before:
C_CONTIGUOUS : True
F_CONTIGUOUS : True
OWNDATA : True
WRITEABLE : True
ALIGNED : True
WRITEBACKIFCOPY : False
UPDATEIFCOPY : False
After:
C_CONTIGUOUS : True
F_CONTIGUOUS : True
OWNDATA : False
WRITEABLE : True
ALIGNED : True
WRITEBACKIFCOPY : False
UPDATEIFCOPY : False
So, in the version it works, OWNDATA is False and in the version where it doesn't work, OWNDATA is True. That seems to be the only difference in the flags. It even says it is contiguous before I run ascontiguousarray
.
post the conda env you are using (
conda list
) here
This is the conda environment where I see the 'did not match C++ signature' error:
# Name Version Build Channel
asn1crypto 0.24.0 py37_1003 conda-forge
backcall 0.1.0 py_0 conda-forge
blas 1.1 openblas conda-forge
blosc 1.15.1 hf484d3e_1002 conda-forge
boost 1.68.0 py37h8619c78_1001 conda-forge
boost-cpp 1.68.0 h11c811c_1000 conda-forge
botocore 1.12.82 py_0
bzip2 1.0.6 h14c3975_5
ca-certificates 2018.11.29 ha4d7672_0 conda-forge
certifi 2018.11.29 py37_1000 conda-forge
cffi 1.12.1 py37h9745a5d_0 conda-forge
cloudpickle 0.7.0 py_0
cryptography 2.5 py37h1ba5d50_0
cycler 0.10.0 py_1 conda-forge
cytoolz 0.9.0.1 py37h14c3975_1001 conda-forge
dask-core 1.1.1 py_0
dbus 1.13.6 h746ee38_0
decorator 4.3.2 py_0 conda-forge
docutils 0.14 py37_1001 conda-forge
expat 2.2.6 he6710b0_0
fftw 3.3.8 h7b6447c_3
fontconfig 2.13.0 h9420a91_0
freetype 2.9.1 h8a8886c_1
glib 2.56.2 hd408876_0
gst-plugins-base 1.14.0 hbbd80ab_1
gstreamer 1.14.0 hb453b48_1
h5py 2.8.0 py37hfb8609e_1004 conda-forge
hdf5 1.10.3 hba1933b_1001 conda-forge
icu 58.2 h9c2bf20_1
idna 2.8 py37_1000 conda-forge
imageio 2.5.0 py37_0 conda-forge
intel-openmp 2019.1 144
ipykernel 5.1.0 py37h24bf2e0_1002 conda-forge
ipython 7.3.0 py37h24bf2e0_0 conda-forge
ipython_genutils 0.2.0 py_1 conda-forge
jedi 0.13.2 py37_1000 conda-forge
jmespath 0.9.3 py_1 conda-forge
jpeg 9c h14c3975_1001 conda-forge
jupyter_client 5.2.4 py_1 conda-forge
jupyter_core 4.4.0 py_0 conda-forge
kiwisolver 1.0.1 py37h6bb024c_1002 conda-forge
libedit 3.1.20181209 hc058e9b_0
libffi 3.2.1 hd88cf55_4
libgcc-ng 8.2.0 hdf63c60_1
libgfortran-ng 7.3.0 hdf63c60_0
libopenblas 0.3.3 h5a2b251_3
libpng 1.6.36 hbc83047_0
libsodium 1.0.16 h1bed415_0
libstdcxx-ng 8.2.0 hdf63c60_1
libtiff 4.0.10 h2733197_2
libuuid 1.0.3 h1bed415_2
libxcb 1.13 h1bed415_1
libxml2 2.9.9 he19cac6_0
lockfile 0.12.2 py_1 conda-forge
luigi 2.8.3 py37_1000 conda-forge
matplotlib-base 3.0.2 py37h167e16e_1002 conda-forge
mkl 2019.1 144
ncurses 6.1 he6710b0_1
networkx 2.2 py_1 conda-forge
nifty v0.4.1 py37_0 cpape
numpy 1.16.1 py37_blas_openblash1522bff_0 [blas_openblas] conda-forge
numpy-base 1.15.4 py37h2f8d375_0
olefile 0.46 py_0 conda-forge
openblas 0.3.3 h9ac9557_1001 conda-forge
openlibm 0.6.0 h14c3975_1000 conda-forge
openssl 1.1.1a h14c3975_1000 conda-forge
parso 0.3.4 py_0 conda-forge
pcre 8.42 h439df22_0
pexpect 4.6.0 py37_1000 conda-forge
pickleshare 0.7.5 py37_1000 conda-forge
pillow 5.4.1 py37h00a061d_1000 conda-forge
pip 19.0.2 py37_0 conda-forge
prompt_toolkit 2.0.8 py_0
ptyprocess 0.6.0 py37_1000 conda-forge
pycparser 2.19 py_0 conda-forge
pygments 2.3.1 py_0 conda-forge
pyopenssl 19.0.0 py37_0 conda-forge
pyparsing 2.3.1 py_0 conda-forge
pyqt 5.9.2 py37h05f1152_2
pysocks 1.6.8 py37_1002 conda-forge
python 3.7.2 h0371630_0
python-daemon 2.2.1 py37_0
python-dateutil 2.8.0 py_0 conda-forge
pytz 2018.9 py_0 conda-forge
pywavelets 1.0.1 py37h3010b51_1000 conda-forge
pyzmq 17.1.2 py37he6710b0_2
qt 5.9.7 h5867ecd_1
readline 7.0 h7b6447c_5
scikit-image 0.14.2 py37hf484d3e_1 conda-forge
scikit-learn 0.20.2 py37_blas_openblashebff5e3_1400 [blas_openblas] conda-forge
scipy 1.2.1 py37_blas_openblash1522bff_0 [blas_openblas] conda-forge
setuptools 40.8.0 py37_0 conda-forge
sip 4.19.8 py37hf484d3e_1000 conda-forge
six 1.12.0 py37_1000 conda-forge
sqlite 3.26.0 h7b6447c_0
tk 8.6.9 h84994c4_1000 conda-forge
toolz 0.9.0 py_1 conda-forge
tornado 4.5.3 py37h14c3975_1001 conda-forge
traitlets 4.3.2 py37_1000 conda-forge
urllib3 1.24.1 py37_1000 conda-forge
vigra 1.11.1 py37hb287d74_1007 conda-forge
wcwidth 0.1.7 py_1 conda-forge
wheel 0.33.0 py37_0 conda-forge
xz 5.2.4 h14c3975_4
z5py 1.4.1 py37h9082789_1 conda-forge
zeromq 4.3.1 he6710b0_3
zlib 1.2.11 h7b6447c_3
zstd 1.3.7 h0b5b093_0
Also, you mentioned that you get a seg-fault with different numpy versions earlier.
Can you also reproduce this with such an easy example?
Yes, actually the same exact code from above reproduces that error. The conda environment where I see the segfault is:
# Name Version Build Channel
asn1crypto 0.24.0 py37_1003 conda-forge
blas 1.0 mkl
blosc 1.15.1 hf484d3e_1002 conda-forge
boost 1.68.0 py37h8619c78_1001 conda-forge
boost-cpp 1.68.0 h11c811c_1000 conda-forge
botocore 1.12.96 py_0 conda-forge
bzip2 1.0.6 h14c3975_1002 conda-forge
ca-certificates 2018.11.29 ha4d7672_0 conda-forge
certifi 2018.11.29 py37_1000 conda-forge
cffi 1.12.1 py37h9745a5d_0 conda-forge
cloudpickle 0.7.0 py_0 conda-forge
cryptography 2.5 py37hb7f436b_1 conda-forge
cycler 0.10.0 py_1 conda-forge
cytoolz 0.9.0.1 py37h14c3975_1001 conda-forge
dask-core 1.1.1 py_0 conda-forge
decorator 4.3.2 py_0 conda-forge
docutils 0.14 py37_1001 conda-forge
fftw 3.3.8 h14c3975_1002 conda-forge
freetype 2.9.1 h94bbf69_1005 conda-forge
h5py 2.8.0 py37hfb8609e_1004 conda-forge
hdf5 1.10.3 hba1933b_1001 conda-forge
icu 58.2 hf484d3e_1000 conda-forge
idna 2.8 py37_1000 conda-forge
imageio 2.5.0 py37_0 conda-forge
intel-openmp 2019.1 144
jmespath 0.9.3 py_1 conda-forge
jpeg 9c h14c3975_1001 conda-forge
kiwisolver 1.0.1 py37h6bb024c_1002 conda-forge
libffi 3.2.1 hf484d3e_1005 conda-forge
libgcc-ng 7.3.0 hdf63c60_0 conda-forge
libgfortran-ng 7.2.0 hdf63c60_3 conda-forge
libpng 1.6.36 h84994c4_1000 conda-forge
libstdcxx-ng 7.3.0 hdf63c60_0 conda-forge
libtiff 4.0.10 h648cc4a_1001 conda-forge
lockfile 0.12.2 py_1 conda-forge
luigi 2.8.3 py37_1000 conda-forge
matplotlib-base 3.0.2 py37h167e16e_1002 conda-forge
mkl 2019.1 144
mkl_fft 1.0.10 py37h14c3975_1 conda-forge
mkl_random 1.0.2 py37h637b7d7_2 conda-forge
ncurses 6.1 hf484d3e_1002 conda-forge
networkx 2.2 py_1 conda-forge
nifty v0.4.1 py37_0 cpape
numpy 1.15.4 py37h7e9f1db_0
numpy-base 1.15.4 py37hde5b4d6_0
olefile 0.46 py_0 conda-forge
openblas 0.3.3 h9ac9557_1001 conda-forge
openssl 1.0.2p h14c3975_1002 conda-forge
pillow 5.4.1 py37h00a061d_1000 conda-forge
pip 19.0.2 py37_0 conda-forge
pycparser 2.19 py_0 conda-forge
pyopenssl 19.0.0 py37_0 conda-forge
pyparsing 2.3.1 py_0 conda-forge
pysocks 1.6.8 py37_1002 conda-forge
python 3.7.0 hd21baee_1006 conda-forge
python-daemon 2.2.1 py37_0
python-dateutil 2.8.0 py_0 conda-forge
pywavelets 1.0.1 py37h3010b51_1000 conda-forge
readline 7.0 hf8c457e_1001 conda-forge
scikit-image 0.14.2 py37hf484d3e_1 conda-forge
scikit-learn 0.20.2 py37hd81dba3_0
scipy 1.2.0 py37h7c811a0_0
setuptools 40.8.0 py37_0 conda-forge
six 1.12.0 py37_1000 conda-forge
sqlite 3.26.0 h67949de_1000 conda-forge
tk 8.6.9 h84994c4_1000 conda-forge
toolz 0.9.0 py_1 conda-forge
tornado 4.5.3 py37h14c3975_1001 conda-forge
urllib3 1.24.1 py37_1000 conda-forge
vigra 1.11.1 py37hb287d74_1007 conda-forge
wheel 0.33.0 py37_0 conda-forge
xz 5.2.4 h14c3975_1001 conda-forge
z5py 1.4.1 py37h9082789_0 conda-forge
zlib 1.2.11 h14c3975_1004 conda-forge
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