TypeError: ufunc 'isnan' not supported for the input types... ?

mhmtgenc commented 3 months ago

I get this error and don't really know how to overcome this; " TypeError: ufunc 'isnan' not supported for the input types, and the inputs could not be safely coerced to any supported types according to the casting rule ''safe'"

WisecondorX predict V350244378_L02_58.npz /data/storeData/project/1_Projects/NIPT/Analiz/niptref_20240730.npz V350244378_L02_58_2 --bed --plot [INFO - 2024-07-30 14:08:01]: Starting CNA prediction [INFO - 2024-07-30 14:08:01]: Importing data ... [INFO - 2024-07-30 14:08:01]: Normalizing autosomes ... [INFO - 2024-07-30 14:08:11]: Normalizing gonosomes ... [INFO - 2024-07-30 14:08:14]: Executing circular binary segmentation ... Warning message: package ‘DNAcopy’ was built under R version 4.0.3 Traceback (most recent call last): File "/home/MegaBOLT/miniconda3/bin/WisecondorX", line 10, in sys.exit(main()) File "/home/MegaBOLT/miniconda3/lib/python3.8/site-packages/wisecondorX/main.py", line 410, in main args.func(args) File "/home/MegaBOLT/miniconda3/lib/python3.8/site-packages/wisecondorX/main.py", line 240, in tool_test results['results_c'] = exec_cbs(rem_input, results) File "/home/MegaBOLT/miniconda3/lib/python3.8/site-packages/wisecondorX/predict_tools.py", line 247, in exec_cbs segment_z = get_z_score(results_c, results) File "/home/MegaBOLT/miniconda3/lib/python3.8/site-packages/wisecondorX/overall_tools.py", line 98, in get_z_score null_segments = [np.ma.average(np.ma.masked_array(x, np.isnan(x)), weights=segment_w) for x in np.transpose(segment_nr)] File "/home/MegaBOLT/miniconda3/lib/python3.8/site-packages/wisecondorX/overall_tools.py", line 98, in null_segments = [np.ma.average(np.ma.masked_array(x, np.isnan(x)), weights=segment_w) for x in np.transpose(segment_nr)] TypeError: ufunc 'isnan' not supported for the input types, and the inputs could not be safely coerced to any supported types according to the casting rule ''safe''

I have NIPT sample and just created reference npz with over 300 sample both male and female.

Thanks in advance.

koen-swaerts commented 3 months ago

Hi,

I got a similar error, which is probably related:

WisecondorX predict M1.npz refset/ref_M/reference_M_b25000.npz M1_predict_M --bed --plot --gender M --seed 123 [INFO - 2024-07-30 14:26:01]: Starting CNA prediction [INFO - 2024-07-30 14:26:01]: Importing data ... [INFO - 2024-07-30 14:26:02]: Normalizing autosomes ... [INFO - 2024-07-30 14:26:37]: Normalizing gonosomes ... [INFO - 2024-07-30 14:26:47]: Executing circular binary segmentation ... Traceback (most recent call last): File "/conda/envs/wisecondor/bin/WisecondorX", line 10, in sys.exit(main()) File "/conda/envs/wisecondor/lib/python3.9/site-packages/wisecondorx/main.py", line 487, in main args.func(args) File "/conda/envs/wisecondor/lib/python3.9/site-packages/wisecondorx/main.py", line 275, in tool_test results["results_c"] = exec_cbs(rem_input, results) File "/conda/envs/wisecondor/lib/python3.9/site-packages/wisecondorx/predict_tools.py", line 258, in exec_cbs segment_z = get_z_score(results_c, results) File "/conda/envs/wisecondor/lib/python3.9/site-packages/wisecondorx/overall_tools.py", line 106, in get_z_score null_segments = [ File "/conda/envs/wisecondor/lib/python3.9/site-packages/wisecondorx/overall_tools.py", line 107, in np.ma.average(np.ma.masked_array(x, np.isnan(x)), weights=segment_w) TypeError: ufunc 'isnan' not supported for the input types, and the inputs could not be safely coerced to any supported types according to the casting rule ''safe''

I'm using wisecondorx as CNVseq tool (samples of 5x coverage).

Thanks

koen-swaerts commented 3 months ago

I tried a lot of combo's to make it work, currently only downgrading to 1.2.5 seems to work for me (below the conda yml of my environment).

name: wisecondor channels:

bioconda
conda-forge
defaults dependencies:
_libgcc_mutex=0.1=conda_forge
_openmp_mutex=4.5=2_gnu
_r-mutex=1.0.1=anacondar_1
_sysroot_linux-64_curr_repodata_hack=3=h69a702a_16
alsa-lib=1.2.12=h4ab18f5_0
attr=2.5.1=h166bdaf_1
binutils_impl_linux-64=2.40=ha1999f0_7
bioconductor-dnacopy=1.76.0=r43h9913872_1
brotli=1.1.0=hd590300_1
brotli-bin=1.1.0=hd590300_1
bwidget=1.9.14=ha770c72_1
bzip2=1.0.8=h4bc722e_7
c-ares=1.32.3=h4bc722e_0
ca-certificates=2024.7.4=hbcca054_0
cairo=1.18.0=h3faef2a_0
certifi=2024.7.4=pyhd8ed1ab_0
contourpy=1.2.1=py39h7633fee_0
curl=8.8.0=he654da7_1
cycler=0.12.1=pyhd8ed1ab_0
dbus=1.13.6=h5008d03_3
expat=2.6.2=h59595ed_0
font-ttf-dejavu-sans-mono=2.37=hab24e00_0
font-ttf-inconsolata=3.000=h77eed37_0
font-ttf-source-code-pro=2.038=h77eed37_0
font-ttf-ubuntu=0.83=h77eed37_2
fontconfig=2.14.2=h14ed4e7_0
fonts-conda-ecosystem=1=0
fonts-conda-forge=1=0
fonttools=4.53.1=py39hcd6043d_0
freetype=2.12.1=h267a509_2
fribidi=1.0.10=h36c2ea0_0
gcc_impl_linux-64=14.1.0=h3c94d91_0
gettext=0.22.5=h59595ed_2
gettext-tools=0.22.5=h59595ed_2
gfortran_impl_linux-64=14.1.0=he4a1faa_0
glib=2.80.2=hf974151_0
glib-tools=2.80.2=hb6ce0ca_0
graphite2=1.3.13=h59595ed_1003
gst-plugins-base=1.24.4=h9ad1361_0
gstreamer=1.24.4=haf2f30d_0
gxx_impl_linux-64=14.1.0=h2879b86_0
harfbuzz=8.5.0=hfac3d4d_0
icu=73.2=h59595ed_0
importlib-resources=6.4.0=pyhd8ed1ab_0
importlib_resources=6.4.0=pyhd8ed1ab_0
joblib=1.4.2=pyhd8ed1ab_0
kernel-headers_linux-64=3.10.0=h4a8ded7_16
keyutils=1.6.1=h166bdaf_0
kiwisolver=1.4.5=py39h7633fee_1
krb5=1.21.3=h659f571_0
lame=3.100=h166bdaf_1003
lcms2=2.16=hb7c19ff_0
ld_impl_linux-64=2.40=hf3520f5_7
lerc=4.0.0=h27087fc_0
libasprintf=0.22.5=h661eb56_2
libasprintf-devel=0.22.5=h661eb56_2
libblas=3.9.0=23_linux64_openblas
libbrotlicommon=1.1.0=hd590300_1
libbrotlidec=1.1.0=hd590300_1
libbrotlienc=1.1.0=hd590300_1
libcap=2.69=h0f662aa_0
libcblas=3.9.0=23_linux64_openblas
libclang-cpp15=15.0.7=default_h127d8a8_5
libclang13=18.1.7=default_h087397f_0
libcups=2.3.3=h4637d8d_4
libcurl=8.8.0=hca28451_1
libdeflate=1.20=hd590300_0
libedit=3.1.20191231=he28a2e2_2
libev=4.33=hd590300_2
libevent=2.1.12=hf998b51_1
libexpat=2.6.2=h59595ed_0
libffi=3.4.2=h7f98852_5
libflac=1.4.3=h59595ed_0
libgcc-devel_linux-64=14.1.0=h5d3d1c9_100
libgcc-ng=14.1.0=h77fa898_0
libgcrypt=1.11.0=h4ab18f5_1
libgettextpo=0.22.5=h59595ed_2
libgettextpo-devel=0.22.5=h59595ed_2
libgfortran-ng=14.1.0=h69a702a_0
libgfortran5=14.1.0=hc5f4f2c_0
libglib=2.80.2=hf974151_0
libgomp=14.1.0=h77fa898_0
libgpg-error=1.50=h4f305b6_0
libiconv=1.17=hd590300_2
libjpeg-turbo=3.0.0=hd590300_1
liblapack=3.9.0=23_linux64_openblas
libllvm15=15.0.7=hb3ce162_4
libllvm18=18.1.7=hb77312f_0
libnghttp2=1.58.0=h47da74e_1
libnsl=2.0.1=hd590300_0
libogg=1.3.5=h4ab18f5_0
libopenblas=0.3.27=pthreads_hac2b453_1
libopus=1.3.1=h7f98852_1
libpng=1.6.43=h2797004_0
libpq=16.3=ha72fbe1_0
libsanitizer=14.1.0=hcba0ae0_0
libsndfile=1.2.2=hc60ed4a_1
libsqlite=3.46.0=hde9e2c9_0
libssh2=1.11.0=h0841786_0
libstdcxx-devel_linux-64=14.1.0=h5d3d1c9_100
libstdcxx-ng=14.1.0=hc0a3c3a_0
libsystemd0=255=h3516f8a_1
libtiff=4.6.0=h1dd3fc0_3
libuuid=2.38.1=h0b41bf4_0
libvorbis=1.3.7=h9c3ff4c_0
libwebp-base=1.4.0=hd590300_0
libxcb=1.15=h0b41bf4_0
libxcrypt=4.4.36=hd590300_1
libxkbcommon=1.7.0=h662e7e4_0
libxml2=2.12.7=hc051c1a_1
libzlib=1.2.13=h4ab18f5_6
lz4-c=1.9.4=hcb278e6_0
make=4.3=hd18ef5c_1
matplotlib=3.8.4=py39hf3d152e_2
matplotlib-base=3.8.4=py39h10d1fc8_2
mpg123=1.32.6=h59595ed_0
munkres=1.0.7=py_1
mysql-common=8.3.0=hf1915f5_4
mysql-libs=8.3.0=hca2cd23_4
ncurses=6.5=h59595ed_0
nspr=4.35=h27087fc_0
nss=3.100=hca3bf56_0
numpy=1.26.4=py39h474f0d3_0
openjpeg=2.5.2=h488ebb8_0
openssl=3.3.1=h4bc722e_2
packaging=24.1=pyhd8ed1ab_0
pango=1.54.0=h84a9a3c_0
pcre2=10.43=hcad00b1_0
pillow=10.3.0=py39h90c7501_0
pip=24.0=pyhd8ed1ab_0
pixman=0.43.2=h59595ed_0
ply=3.11=pyhd8ed1ab_2
pthread-stubs=0.4=h36c2ea0_1001
pulseaudio-client=17.0=hb77b528_0
pyparsing=3.1.2=pyhd8ed1ab_0
pyqt=5.15.9=py39h52134e7_5
pyqt5-sip=12.12.2=py39h3d6467e_5
pysam=0.22.0=py39hcada746_1
python=3.9.19=h0755675_0_cpython
python-dateutil=2.9.0=pyhd8ed1ab_0
python_abi=3.9=4_cp39
qt-main=5.15.8=hc9dc06e_21
r-base=4.3.3=hf0d99cb_1
r-jsonlite=1.8.8=r43hb1dbf0f_1
r-png=0.1_8=r43h21f035c_2
readline=8.2=h8228510_1
scikit-learn=1.4.2=py39h40c85ba_1
scipy=1.13.1=py39haf93ffa_0
sed=4.8=he412f7d_0
setuptools=71.0.4=pyhd8ed1ab_0
sip=6.7.12=py39h3d6467e_0
six=1.16.0=pyh6c4a22f_0
sysroot_linux-64=2.17=h4a8ded7_16
threadpoolctl=3.5.0=pyhc1e730c_0
tk=8.6.13=noxft_h4845f30_101
tktable=2.10=h8bc8fbc_6
toml=0.10.2=pyhd8ed1ab_0
tomli=2.0.1=pyhd8ed1ab_0
tornado=6.4.1=py39hd3abc70_0
tzdata=2024a=h0c530f3_0
unicodedata2=15.1.0=py39hd1e30aa_0
wheel=0.43.0=pyhd8ed1ab_1
wisecondorx=1.2.5=pyh5e36f6f_0
xcb-util=0.4.0=hd590300_1
xcb-util-image=0.4.0=h8ee46fc_1
xcb-util-keysyms=0.4.0=h8ee46fc_1
xcb-util-renderutil=0.3.9=hd590300_1
xcb-util-wm=0.4.1=h8ee46fc_1
xkeyboard-config=2.42=h4ab18f5_0
xorg-kbproto=1.0.7=h7f98852_1002
xorg-libice=1.1.1=hd590300_0
xorg-libsm=1.2.4=h7391055_0
xorg-libx11=1.8.9=h8ee46fc_0
xorg-libxau=1.0.11=hd590300_0
xorg-libxdmcp=1.1.3=h7f98852_0
xorg-libxext=1.3.4=h0b41bf4_2
xorg-libxrender=0.9.11=hd590300_0
xorg-libxt=1.3.0=hd590300_1
xorg-renderproto=0.11.1=h7f98852_1002
xorg-xextproto=7.3.0=h0b41bf4_1003
xorg-xf86vidmodeproto=2.3.1=h7f98852_1002
xorg-xproto=7.0.31=h7f98852_1007
xz=5.2.6=h166bdaf_0
zipp=3.19.2=pyhd8ed1ab_0
zlib=1.2.13=h4ab18f5_6
zstd=1.5.6=ha6fb4c9_0 prefix: /conda/envs/wisecondor

koen-swaerts commented 2 months ago

This issue on 1.2.7 is fixed in https://github.com/CenterForMedicalGeneticsGhent/WisecondorX/pull/123 @matthdsm can we close this now?

matthdsm commented 2 months ago

Fixed in v1.2.8, thanks to @koen-swaerts

mhmtgenc commented 2 months ago

Thank you @koen-swaerts

koen-swaerts commented 2 months ago

@mhmtgenc if you got an error now, use the correct versions of the tools with the installation: conda install -y -c bioconda -c conda-forge wisecondorx=1.2.8 r-jsonlite=1.8.8 bioconductor-dnacopy=1.76.0 scipy=1.13.0 scikit-learn=1.4.2 pysam=0.22.0 numpy=1.26.4 matplotlib=3.8.4 pandas=2.2.2

CenterForMedicalGeneticsGhent / WisecondorX

TypeError: ufunc 'isnan' not supported for the input types... ? #122