Thank you for the software. It worked well with my nanopore data (R.9.4.1, Guppy v5, super accurate basecalling configuration), until I tried
--sequencing-type=long_read. Any ideas?
/fs03/ie79/Zarul/status_nanopore/C002_D1/.snakemake/conda/4555c0c8960801d84920076de87e12a0_/lib/python3.11/site-packages/SemiBin/long_read_cluster.py:77: RuntimeWarning: divide by zero encountered in log
embedding_new = np.concatenate((embedding, np.log(depth)), axis=1)
Traceback (most recent call last):
File "/fs03/ie79/Zarul/status_nanopore/C002_D1/.snakemake/conda/4555c0c8960801d84920076de87e12a0_/bin/SemiBin", line 10, in <module>
sys.exit(main1())
^^^^^^^
File "/fs03/ie79/Zarul/status_nanopore/C002_D1/.snakemake/conda/4555c0c8960801d84920076de87e12a0_/lib/python3.11/site-packages/SemiBin/main.py", line 1482, in main1
main2(args, is_semibin2=False)
File "/fs03/ie79/Zarul/status_nanopore/C002_D1/.snakemake/conda/4555c0c8960801d84920076de87e12a0_/lib/python3.11/site-packages/SemiBin/main.py", line 1455, in main2
single_easy_binning(
File "/fs03/ie79/Zarul/status_nanopore/C002_D1/.snakemake/conda/4555c0c8960801d84920076de87e12a0_/lib/python3.11/site-packages/SemiBin/main.py", line 1183, in single_easy_binning
binning_long(**binning_kwargs)
File "/fs03/ie79/Zarul/status_nanopore/C002_D1/.snakemake/conda/4555c0c8960801d84920076de87e12a0_/lib/python3.11/site-packages/SemiBin/main.py", line 1061, in binning_long
cluster_long_read(model,
File "/fs03/ie79/Zarul/status_nanopore/C002_D1/.snakemake/conda/4555c0c8960801d84920076de87e12a0_/lib/python3.11/site-packages/SemiBin/long_read_cluster.py", line 101, in cluster_long_read
dist_matrix = kneighbors_graph(
^^^^^^^^^^^^^^^^^
File "/fs03/ie79/Zarul/status_nanopore/C002_D1/.snakemake/conda/4555c0c8960801d84920076de87e12a0_/lib/python3.11/site-packages/sklearn/neighbors/_graph.py", line 122, in kneighbors_graph
).fit(X)
^^^^^^
File "/fs03/ie79/Zarul/status_nanopore/C002_D1/.snakemake/conda/4555c0c8960801d84920076de87e12a0_/lib/python3.11/site-packages/sklearn/base.py", line 1151, in wrapper
return fit_method(estimator, *args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/fs03/ie79/Zarul/status_nanopore/C002_D1/.snakemake/conda/4555c0c8960801d84920076de87e12a0_/lib/python3.11/site-packages/sklearn/neighbors/_unsupervised.py", line 178, in fit
return self._fit(X)
^^^^^^^^^^^^
File "/fs03/ie79/Zarul/status_nanopore/C002_D1/.snakemake/conda/4555c0c8960801d84920076de87e12a0_/lib/python3.11/site-packages/sklearn/neighbors/_base.py", line 498, in _fit
X = self._validate_data(X, accept_sparse="csr", order="C")
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/fs03/ie79/Zarul/status_nanopore/C002_D1/.snakemake/conda/4555c0c8960801d84920076de87e12a0_/lib/python3.11/site-packages/sklearn/base.py", line 604, in _validate_data
out = check_array(X, input_name="X", **check_params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/fs03/ie79/Zarul/status_nanopore/C002_D1/.snakemake/conda/4555c0c8960801d84920076de87e12a0_/lib/python3.11/site-packages/sklearn/utils/validation.py", line 959, in check_array
_assert_all_finite(
File "/fs03/ie79/Zarul/status_nanopore/C002_D1/.snakemake/conda/4555c0c8960801d84920076de87e12a0_/lib/python3.11/site-packages/sklearn/utils/validation.py", line 124, in _assert_all_finite
_assert_all_finite_element_wise(
File "/fs03/ie79/Zarul/status_nanopore/C002_D1/.snakemake/conda/4555c0c8960801d84920076de87e12a0_/lib/python3.11/site-packages/sklearn/utils/validation.py", line 173, in _assert_all_finite_element_wise
raise ValueError(msg_err)
ValueError: Input X contains infinity or a value too large for dtype('float32')./fs03/ie79/Zarul/status_nanopore/C002_D1/.snakemake/conda/4555c0c8960801d84920076de87e12a0_/lib/python3.11/site-packages/SemiBin/long_read_cluster.py:77: RuntimeWarning: divide by zero encountered in log
embedding_new = np.concatenate((embedding, np.log(depth)), axis=1)
Traceback (most recent call last):
File "/fs03/ie79/Zarul/status_nanopore/C002_D1/.snakemake/conda/4555c0c8960801d84920076de87e12a0_/bin/SemiBin", line 10, in <module>
sys.exit(main1())
^^^^^^^
File "/fs03/ie79/Zarul/status_nanopore/C002_D1/.snakemake/conda/4555c0c8960801d84920076de87e12a0_/lib/python3.11/site-packages/SemiBin/main.py", line 1482, in main1
main2(args, is_semibin2=False)
File "/fs03/ie79/Zarul/status_nanopore/C002_D1/.snakemake/conda/4555c0c8960801d84920076de87e12a0_/lib/python3.11/site-packages/SemiBin/main.py", line 1455, in main2
single_easy_binning(
File "/fs03/ie79/Zarul/status_nanopore/C002_D1/.snakemake/conda/4555c0c8960801d84920076de87e12a0_/lib/python3.11/site-packages/SemiBin/main.py", line 1183, in single_easy_binning
binning_long(**binning_kwargs)
File "/fs03/ie79/Zarul/status_nanopore/C002_D1/.snakemake/conda/4555c0c8960801d84920076de87e12a0_/lib/python3.11/site-packages/SemiBin/main.py", line 1061, in binning_long
cluster_long_read(model,
File "/fs03/ie79/Zarul/status_nanopore/C002_D1/.snakemake/conda/4555c0c8960801d84920076de87e12a0_/lib/python3.11/site-packages/SemiBin/long_read_cluster.py", line 101, in cluster_long_read
dist_matrix = kneighbors_graph(
^^^^^^^^^^^^^^^^^
File "/fs03/ie79/Zarul/status_nanopore/C002_D1/.snakemake/conda/4555c0c8960801d84920076de87e12a0_/lib/python3.11/site-packages/sklearn/neighbors/_graph.py", line 122, in kneighbors_graph
).fit(X)
^^^^^^
File "/fs03/ie79/Zarul/status_nanopore/C002_D1/.snakemake/conda/4555c0c8960801d84920076de87e12a0_/lib/python3.11/site-packages/sklearn/base.py", line 1151, in wrapper
return fit_method(estimator, *args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/fs03/ie79/Zarul/status_nanopore/C002_D1/.snakemake/conda/4555c0c8960801d84920076de87e12a0_/lib/python3.11/site-packages/sklearn/neighbors/_unsupervised.py", line 178, in fit
return self._fit(X)
^^^^^^^^^^^^
File "/fs03/ie79/Zarul/status_nanopore/C002_D1/.snakemake/conda/4555c0c8960801d84920076de87e12a0_/lib/python3.11/site-packages/sklearn/neighbors/_base.py", line 498, in _fit
X = self._validate_data(X, accept_sparse="csr", order="C")
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/fs03/ie79/Zarul/status_nanopore/C002_D1/.snakemake/conda/4555c0c8960801d84920076de87e12a0_/lib/python3.11/site-packages/sklearn/base.py", line 604, in _validate_data
out = check_array(X, input_name="X", **check_params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/fs03/ie79/Zarul/status_nanopore/C002_D1/.snakemake/conda/4555c0c8960801d84920076de87e12a0_/lib/python3.11/site-packages/sklearn/utils/validation.py", line 959, in check_array
_assert_all_finite(
File "/fs03/ie79/Zarul/status_nanopore/C002_D1/.snakemake/conda/4555c0c8960801d84920076de87e12a0_/lib/python3.11/site-packages/sklearn/utils/validation.py", line 124, in _assert_all_finite
_assert_all_finite_element_wise(
File "/fs03/ie79/Zarul/status_nanopore/C002_D1/.snakemake/conda/4555c0c8960801d84920076de87e12a0_/lib/python3.11/site-packages/sklearn/utils/validation.py", line 173, in _assert_all_finite_element_wise
raise ValueError(msg_err)
ValueError: Input X contains infinity or a value too large for dtype('float32').
It seems there is a very big number that can not be represented by 'float32'. Can you check the biggest value in the depth column of the data.csv file? Thanks!
Hello SemiBin developers,
Thank you for the software. It worked well with my nanopore data (R.9.4.1, Guppy v5, super accurate basecalling configuration), until I tried
--sequencing-type=long_read
. Any ideas?Command:
Log: