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I would very much like to use the tool, but ran into some issues during installation with conda.
I followed the conda installation instructions:
conda create -n graphmb -c conda-forge make cmake libgcc python=3.7 pip tensorflow
conda activate graphmb
pip install graphmb
But this ran into the following error:
ERROR: Ignored the following yanked versions: 0.2.0rc0, 0.2.0rc1, 0.2.0rc2, 0.2.0
ERROR: Ignored the following versions that require a different python version: 0.2.0rc5 Requires-Python >=3.8; 0.2.0rc6 Requires-Python >=3.8; 0.2.1 Requires-Python >=3.8; 0.2.2 Requires-Python >=3.8; 0.2.3 Requires-Python >=3.8; 0.2.4 Requires-Python >=3.8; 0.2.5 Requires-Python >=3.8
ERROR: Could not find a version that satisfies the requirement graphmb (from versions: 0.2.0rc3, 0.2.0rc4)
ERROR: No matching distribution found for graphmb
I tried to re-install by manually setting python version to 3.8, but this produced the following error when running the tool:
Traceback (most recent call last):
File "/data/brbloemen/mambaforge/envs/graphmb/bin/graphmb", line 8, in <module>
sys.exit(main())
File "/data/brbloemen/mambaforge/envs/graphmb/lib/python3.8/site-packages/graphmb/main.py", line 442, in main
dataset.read_assembly()
File "/data/brbloemen/mambaforge/envs/graphmb/lib/python3.8/site-packages/graphmb/contigsdataset.py", line 151, in read_assembly
self.read_depths()
File "/data/brbloemen/mambaforge/envs/graphmb/lib/python3.8/site-packages/graphmb/contigsdataset.py", line 495, in read_depths
self.node_depths = np.ones(len(self.node_names), dtype=np.float)
File "/data/brbloemen/mambaforge/envs/graphmb/lib/python3.8/site-packages/numpy/__init__.py", line 305, in __getattr__
raise AttributeError(__former_attrs__[attr])
AttributeError: module 'numpy' has no attribute 'float'.
`np.float` was a deprecated alias for the builtin `float`. To avoid this error in existing code, 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.
The aliases was originally deprecated in NumPy 1.20; for more details and guidance see the original release note at:
https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations
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