Merge pull request #739 from lilleswing/quiet-travis (4b37071e) · Commits · 钟慕尧 / deepchem

README.md

+2 −2

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		@@ -56,7 +56,7 @@ git clone https://github.com/deepchem/deepchem.git # Clone deepchem source
		cd deepchem
		bash scripts/install_deepchem_conda.sh deepchem
		source activate deepchem
		pip install tensorflow-gpu==1.0.1 # If you want GPU support
		pip install tensorflow-gpu==1.2.1 # If you want GPU support
		python setup.py install # Manual install
		nosetests -v deepchem --nologcapture # Run tests
		```
		@@ -110,7 +110,7 @@ conda install -c deepchem -c rdkit -c conda-forge -c omnia deepchem=1.2.0
		contact your local sysadmin to work out a custom installation. If your
		version of Linux is recent, then the following command will work:
		```
		pip install tensorflow-gpu
		pip install tensorflow-gpu==1.2.1
		```

		9. `deepchem`: Clone the `deepchem` github repo:

+1 −1

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		@@ -224,7 +224,7 @@ class RFConvexHullPocketFinder(BindingPocketFinder):
		print("About to download trained model.")
		# TODO(rbharath): Shift refined to full once trained.
		call((
		"wget -c http://deepchem.io.s3-website-us-west-1.amazonaws.com/trained_models/pocket_random_refined_RF.tar.gz"
		"wget -nv -c http://deepchem.io.s3-website-us-west-1.amazonaws.com/trained_models/pocket_random_refined_RF.tar.gz"
		).split())
		call(("tar -zxvf pocket_random_refined_RF.tar.gz").split())
		call(("mv pocket_random_refined_RF %s" % (self.base_dir)).split())

+2 −2

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		@@ -41,7 +41,7 @@ class VinaGridRFDocker(Docker):
		self.base_dir = tempfile.mkdtemp()
		print("About to download trained model.")
		call((
		"wget -c http://deepchem.io.s3-website-us-west-1.amazonaws.com/trained_models/random_full_RF.tar.gz"
		"wget -nv -c http://deepchem.io.s3-website-us-west-1.amazonaws.com/trained_models/random_full_RF.tar.gz"
		).split())
		call(("tar -zxvf random_full_RF.tar.gz").split())
		call(("mv random_full_RF %s" % (self.base_dir)).split())
		@@ -79,7 +79,7 @@ class VinaGridDNNDocker(object):
		self.base_dir = tempfile.mkdtemp()
		print("About to download trained model.")
		call((
		"wget -c http://deepchem.io.s3-website-us-west-1.amazonaws.com/trained_models/random_full_DNN.tar.gz"
		"wget -nv -c http://deepchem.io.s3-website-us-west-1.amazonaws.com/trained_models/random_full_DNN.tar.gz"
		).split())
		call(("tar -zxvf random_full_DNN.tar.gz").split())
		call(("mv random_full_DNN %s" % (self.base_dir)).split())

+3 −3

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		@@ -66,7 +66,7 @@ class VinaPoseGenerator(PoseGenerator):
		print("Vina not available. Downloading")
		# TODO(rbharath): May want to move this file to S3 so we can ensure it's
		# always available.
		wget_cmd = "wget -c http://vina.scripps.edu/download/autodock_vina_1_1_2_linux_x86.tgz"
		wget_cmd = "wget -nv -c http://vina.scripps.edu/download/autodock_vina_1_1_2_linux_x86.tgz"
		call(wget_cmd.split())
		print("Downloaded Vina. Extracting")
		download_cmd = "tar xzvf autodock_vina_1_1_2_linux_x86.tgz"
		@@ -157,8 +157,8 @@ class VinaPoseGenerator(PoseGenerator):
		if not dry_run:
		print("About to call Vina")
		call(
		"%s --config %s --log %s --out %s" %
		(self.vina_cmd, conf_file, log_file, out_pdbqt),
		"%s --config %s --log %s --out %s" % (self.vina_cmd, conf_file,
		log_file, out_pdbqt),
		shell=True)
		# TODO(rbharath): Convert the output pdbqt to a pdb file.

+1 −1

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		@@ -28,7 +28,7 @@ class TestPoseScoring(unittest.TestCase):
		def setUp(self):
		"""Downloads dataset."""
		call(
		"wget -c http://deepchem.io.s3-website-us-west-1.amazonaws.com/featurized_datasets/core_grid.tar.gz".
		"wget -nv -c http://deepchem.io.s3-website-us-west-1.amazonaws.com/featurized_datasets/core_grid.tar.gz".
		split())
		call("tar -zxvf core_grid.tar.gz".split())
		self.core_dataset = dc.data.DiskDataset("core_grid/")