Error with install

[dnolin13]

Hello,
I believe VIBRANT installed properly (got the "VIBRANT v1.2.1 is good to go!" message with the test) but also got this repeated error:
/home/delaney/miniconda3/lib/python3.9/site-packages/sklearn/utils/multiclass.py:13: DeprecationWarning: Please use spmatrixfrom thescipy.sparsenamespace, thescipy.sparse.basenamespace is deprecated. from scipy.sparse.base import spmatrix /home/delaney/miniconda3/lib/python3.9/site-packages/sklearn/linear_model/least_angle.py:30: DeprecationWarning:np.floatis a deprecated alias for the builtinfloat. To silence this warning, use floatby itself. Doing this will not modify any behavior and is safe. If you specifically wanted the numpy scalar type, usenp.float64here. Deprecated in NumPy 1.20; for more details and guidance: https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations method='lar', copy_X=True, eps=np.finfo(np.float).eps, /home/delaney/miniconda3/lib/python3.9/site-packages/sklearn/linear_model/least_angle.py:167: DeprecationWarning:np.floatis a deprecated alias for the builtinfloat. To silence this warning, use floatby itself. Doing this will not modify any behavior and is safe. If you specifically wanted the numpy scalar type, usenp.float64 here. Deprecated in NumPy 1.20; for more details and guidance: https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations method='lar', copy_X=True, eps=np.finfo(np.float).eps,

I am going to move forward because I think it should run okay, but just wanted to check to make sure. Thanks!

[KrisKieft]

Hi, yes this is just a version depreciation warning with numpy (not an error). Everything should run as intended.

[dnolin13]

Awesome thank you! I am having one other issue, I ran the VIBRANT_setup.py, but VIBRANT does not seem to be running, the logs all show this error:

M_CDHIT_ID98_aS0.8.fa$ more VIBRANT_log_run_2015_07_500M_CDHIT_ID98_aS0.8.log VIBRANT error: could not identify KEGG HMM files in database directory. Please run VIBRANT_setup.py. VIBRANT error: could not identify KEGG HMM files in database directory. Please run VIBRANT_setup.py. VIBRANT error: could not identify KEGG HMM files in database directory. Please run VIBRANT_setup.py.

the setup log says everything is okay, and the examples work fine:

`(base) delaney@ada:~/software/VIBRANT/databases$ more VIBRANT_setup.log
This script will download, extract subsets and press HMM profiles for VIBRANT.
This process will require ~20GB of temporary free storage space, but the final size requirement is ~11GB in the f
orm of pressed HMM databases.
Please be patient. This only needs to be run once and will take a few minutes.

Verifying Pfam, KEGG and VOG source websites are available for download ...

Downloading HMM profiles for Pfam, KEGG and VOG from their source websites ...

Unzipping profiles ...

Concatenating individual profiles ...

Extracting profiles used for VIBRANT ...

Retrieved 19182 HMMs.

Retrieved 10033 HMMs.

Pressing profiles used for VIBRANT ...
Working... Working... Working... done.
Pressed and indexed 17929 HMMs (17929 names and 17929 accessions).
Models pressed into binary file: Pfam-A_v32.HMM.h3m
SSI index for binary model file: Pfam-A_v32.HMM.h3i
Profiles (MSV part) pressed into: Pfam-A_v32.HMM.h3f
Profiles (remainder) pressed into: Pfam-A_v32.HMM.h3p
done.
Pressed and indexed 19182 HMMs (19182 names).
Models pressed into binary file: VOGDB94_phage.HMM.h3m
SSI index for binary model file: VOGDB94_phage.HMM.h3i
Profiles (MSV part) pressed into: VOGDB94_phage.HMM.h3f
Profiles (remainder) pressed into: VOGDB94_phage.HMM.h3p
done.
Pressed and indexed 10033 HMMs (10033 names).
Models pressed into binary file: KEGG_profiles_prokaryotes.HMM.h3m
SSI index for binary model file: KEGG_profiles_prokaryotes.HMM.h3i
Profiles (MSV part) pressed into: KEGG_profiles_prokaryotes.HMM.h3f
Profiles (remainder) pressed into: KEGG_profiles_prokaryotes.HMM.h3p

Done with databases. Several new databases are now in this folder.

Verying correct dependency versions ...

VIBRANT Caution: running a version of Scikit-Learn lower than v0.21.3 will likely cause issues. With pip you can
update by running "pip install --upgrade scikit-learn==0.21.3".

This script will download, extract subsets and press HMM profiles for VIBRANT.
This process will require ~20GB of temporary free storage space, but the final size requirement is ~11GB in the f
orm of pressed HMM databases.
Please be patient. This only needs to be run once and will take a few minutes.

Verifying Pfam, KEGG and VOG source websites are available for download ...

Downloading HMM profiles for Pfam, KEGG and VOG from their source websites ...

Unzipping profiles ...

Concatenating individual profiles ...

Extracting profiles used for VIBRANT ...

Retrieved 19182 HMMs.

Retrieved 10033 HMMs.

Pressing profiles used for VIBRANT ...

Done with databases. Several new databases are now in this folder.

Verying correct dependency versions ...

VIBRANT v1.2.1 is good to go!
See example_data/ for quick test files.`

This was the only output on the command line when I run the programme:

`(base) delaney@ada:~/SPOT_virome_depth_profiles/quals_subset_depth_profile/06_assembly_results/megahit/Clustered_98ID_aS80$ /home/delaney/software/VI
BRANT/VIBRANT_run.py -i 2013_01_150M_CDHIT_ID98_aS0.8.fa -t 20 -folder /home/delaney/SPOT_virome_depth_profiles/quals_subset_depth_profile/15_VIBRANT_Output_bySample/2013_01_150M_CDHIT -l 1000 -d /home/delaney/software/VIBRANT/databases

/home/delaney/miniconda3/lib/python3.9/site-packages/sklearn/utils/multiclass.py:13: DeprecationWarning: Please use spmatrix from the scipy.sparse namespace, the scipy.sparse.base namespace is deprecated.
from scipy.sparse.base import spmatrix
/home/delaney/miniconda3/lib/python3.9/site-packages/sklearn/linear_model/least_angle.py:30: DeprecationWarning: np.float is a deprecated alias for the builtin float. To silence this warning, use float by itself. Doing this will not modify any behavior and is safe. If you specifically wanted the numpy scalar type, use np.float64 here.
Deprecated in NumPy 1.20; for more details and guidance: https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations
method='lar', copy_X=True, eps=np.finfo(np.float).eps,
/home/delaney/miniconda3/lib/python3.9/site-packages/sklearn/linear_model/least_angle.py:167: DeprecationWarning: np.float is a deprecated alias for the builtin float. To silence this warning, use float by itself. Doing this will not modify any behavior and is safe. If you specifically wanted the numpy scalar type, use np.float64 here.
Deprecated in NumPy 1.20; for more details and guidance: https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations
method='lar', copy_X=True, eps=np.finfo(np.float).eps,
/home/delaney/miniconda3/lib/python3.9/site-packages/sklearn/linear_model/least_angle.py:284: DeprecationWarning: np.float is a deprecated alias for the builtin float. To silence this warning, use float by itself. Doing this will not modify any behavior and is safe. If you specifically wanted the numpy scalar type, use np.float64 here.
Deprecated in NumPy 1.20; for more details and guidance: https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations
eps=np.finfo(np.float).eps, copy_Gram=True, verbose=0,
/home/delaney/miniconda3/lib/python3.9/site-packages/sklearn/linear_model/least_angle.py:862: DeprecationWarning: np.float is a deprecated alias for the builtin float. To silence this warning, use float by itself. Doing this will not modify any behavior and is safe. If you specifically wanted the numpy scalar type, use np.float64 here.
Deprecated in NumPy 1.20; for more details and guidance: https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations
eps=np.finfo(np.float).eps, copy_X=True, fit_path=True,
/home/delaney/miniconda3/lib/python3.9/site-packages/sklearn/linear_model/least_angle.py:1101: DeprecationWarning: np.float is a deprecated alias for the builtin float. To silence this warning, use float by itself. Doing this will not modify any behavior and is safe. If you specifically wanted the numpy scalar type, use np.float64 here.
Deprecated in NumPy 1.20; for more details and guidance: https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations
eps=np.finfo(np.float).eps, copy_X=True, fit_path=True,
/home/delaney/miniconda3/lib/python3.9/site-packages/sklearn/linear_model/least_angle.py:1127: DeprecationWarning: np.float is a deprecated alias for the builtin float. To silence this warning, use float by itself. Doing this will not modify any behavior and is safe. If you specifically wanted the numpy scalar type, use np.float64 here.
Deprecated in NumPy 1.20; for more details and guidance: https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations
eps=np.finfo(np.float).eps, positive=False):
/home/delaney/miniconda3/lib/python3.9/site-packages/sklearn/linear_model/least_angle.py:1362: DeprecationWarning: np.float is a deprecated alias for the builtin float. To silence this warning, use float by itself. Doing this will not modify any behavior and is safe. If you specifically wanted the numpy scalar type, use np.float64 here.
Deprecated in NumPy 1.20; for more details and guidance: https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations
max_n_alphas=1000, n_jobs=None, eps=np.finfo(np.float).eps,
/home/delaney/miniconda3/lib/python3.9/site-packages/sklearn/linear_model/least_angle.py:1602: DeprecationWarning: np.float is a deprecated alias for the builtin float. To silence this warning, use float by itself. Doing this will not modify any behavior and is safe. If you specifically wanted the numpy scalar type, use np.float64 here.
Deprecated in NumPy 1.20; for more details and guidance: https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations
max_n_alphas=1000, n_jobs=None, eps=np.finfo(np.float).eps,
/home/delaney/miniconda3/lib/python3.9/site-packages/sklearn/linear_model/least_angle.py:1738: DeprecationWarning: np.float is a deprecated alias for the builtin float. To silence this warning, use float by itself. Doing this will not modify any behavior and is safe. If you specifically wanted the numpy scalar type, use np.float64 here.
Deprecated in NumPy 1.20; for more details and guidance: https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations
eps=np.finfo(np.float).eps, copy_X=True, positive=False):
/home/delaney/miniconda3/lib/python3.9/site-packages/sklearn/utils/optimize.py:18: DeprecationWarning: Please use line_search_wolfe2 from the scipy.optimize namespace, the scipy.optimize.linesearch namespace is deprecated.
from scipy.optimize.linesearch import line_search_wolfe2, line_search_wolfe1
/home/delaney/miniconda3/lib/python3.9/site-packages/sklearn/utils/optimize.py:18: DeprecationWarning: Please use line_search_wolfe1 from the scipy.optimize namespace, the scipy.optimize.linesearch namespace is deprecated.
from scipy.optimize.linesearch import line_search_wolfe2, line_search_wolfe1
/home/delaney/miniconda3/lib/python3.9/site-packages/sklearn/decomposition/online_lda.py:29: DeprecationWarning: np.float is a deprecated alias for the builtin float. To silence this warning, use float by itself. Doing this will not modify any behavior and is safe. If you specifically wanted the numpy scalar type, use np.float64 here.
Deprecated in NumPy 1.20; for more details and guidance: https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations
EPS = np.finfo(np.float).eps
`

any help would be really greatly appreciated, thank you!!! this programme is so great

[MrTomRod]

My advice: Just use the docker container: https://hub.docker.com/r/staphb/vibrant/

[Horse4Truin]

I got the same question, and i even can't finish python3 VIBRANT_run.py -i example_data/mixed_example.fasta with VIBRANT error: could not identify KEGG HMM files in database directory. Please run VIBRANT_setup.py. in the file VIBRANT_log_run_mixed_example.log, as i follow the advice,run the VIBRANT_setup.py again , i got the feedback

VIBRANT v1.2.1 is good to go!
See example_data/ for quick test files.

as i run python3 VIBRANT_run.py -i example_data/mixed_example.fasta , things not change

so what's the problem?