simple job running api

examples/job/NH3BH3.xyz

@@ -0,0 +1,13 @@
+8
+
+N       0.00000000       0.00000000      -0.81474153 frag=Donor
+B      -0.00000000      -0.00000000       0.83567034 frag=Acceptor
+H       0.47608351      -0.82460084      -1.14410295 frag=Donor
+H       0.47608351       0.82460084      -1.14410295 frag=Donor
+H      -0.95216703       0.00000000      -1.14410295 frag=Donor
+H      -0.58149793       1.00718395       1.13712667 frag=Acceptor
+H      -0.58149793      -1.00718395       1.13712667 frag=Acceptor
+H       1.16299585      -0.00000000       1.13712667 frag=Acceptor
+
+frag_Donor = 1, 3, 4, 5
+frag_Acceptor = 2, 6, 7, 8

examples/job/asc.xyz

@@ -0,0 +1,20 @@
+18
+
+C      -0.94127539      -5.26718347      -3.96828713
+C      -0.33238494      -3.88895689      -3.84308606
+N      -1.16865847      -2.97724681      -3.25523725
+N      -0.51040403      -1.76570770      -2.89744287
+C      -0.49687631      -1.56835550      -1.52557810
+N       0.39218754      -0.61181473      -1.15607414
+C       0.35907326      -0.02567442       0.17168965
+O       0.75362497      -3.58468600      -4.28757501
+S      -1.50149713      -2.38418510      -0.51048053
+H      -0.26790316      -5.90833092      -4.53215794
+H      -1.90174898      -5.20338615      -4.47736764
+H      -1.10247419      -5.69106602      -2.97752780
+H      -1.72914011      -3.25140398      -2.42926272
+H       0.39417088      -1.76840521      -3.37017404
+H       0.80737342      -0.05086076      -1.88509623
+H      -0.16787989      -0.71881141       0.83076065
+H      -0.16753334       0.93360314       0.15490937
+H       1.37850078       0.12634418       0.52991953

examples/job/conformer_workflow.py

@@ -0,0 +1,33 @@
+from tcutility.job import ADFJob, DFTBJob, CRESTJob
+import os
+
+j = os.path.join
+
+mol_name = 'Pentane'
+
+with CRESTJob(wait_for_finish=True) as crest_job:
+    crest_job.molecule('pentane.xyz')
+    crest_job.md_length(0.2)
+    crest_job.md_temperature(1000)
+    crest_job.sbatch(p='tc', n=64)
+    crest_job.rundir = f'calculations/{mol_name}'
+    crest_job.name = 'CREST'
+
+for i, xyzfile in enumerate(crest_job.get_conformer_xyz()):
+    with DFTBJob() as dftb_job:
+        dftb_job.molecule(xyzfile)
+        dftb_job.sbatch(p='tc', n=8)
+        dftb_job.optimization()
+        dftb_job.rundir = f'calculations/{mol_name}/DFTB'
+        dftb_job.name = f'conformer_{i}'
+        dftb_job.dependency(crest_job)
+
+    with ADFJob() as adf_job:
+        adf_job.molecule(dftb_job.output_mol_path)
+        adf_job.sbatch(p='tc', n=32)
+        adf_job.optimization()
+        adf_job.functional('BLYP-D3(BJ)')
+        adf_job.basis_set('TZ2P')
+        adf_job.rundir = f'calculations/{mol_name}/ADF'
+        adf_job.name = f'conformer_{i}'
+        adf_job.dependency(dftb_job)

examples/job/dmso.xyz

@@ -0,0 +1,12 @@
+10
+
+C       1.38960000      -0.86360000      -0.19670000
+S       0.00000000       0.15470000       0.37120000
+O       0.00000000       1.39000000      -0.33110000
+C      -1.38960000      -0.86360000      -0.19670000
+H       2.32850000      -0.38010000       0.07300000
+H       1.33760000      -1.84480000       0.27520000
+H       1.33760000      -0.97800000      -1.27940000
+H      -1.33770000      -1.84480000       0.27520000
+H      -2.32850000      -0.38010000       0.07300000
+H      -1.33760000      -0.97800000      -1.27940000

examples/job/fragment_calculation.py

@@ -0,0 +1,101 @@
+from tcutility.job import ADFFragmentJob
+from tcutility import molecule
+
+# this example will demonstrate how you may separate two fragments from each other
+
+'''
+The NH3BH3.xyz file looks like this:
+
+	8
+
+	N       0.00000000       0.00000000      -0.81474153 frag=Donor  # method 1
+	B      -0.00000000      -0.00000000       0.83567034 frag=Acceptor
+	H       0.47608351      -0.82460084      -1.14410295 frag=Donor
+	H       0.47608351       0.82460084      -1.14410295 frag=Donor
+	H      -0.95216703       0.00000000      -1.14410295 frag=Donor
+	H      -0.58149793       1.00718395       1.13712667 frag=Acceptor
+	H      -0.58149793      -1.00718395       1.13712667 frag=Acceptor
+	H       1.16299585      -0.00000000       1.13712667 frag=Acceptor
+
+	frag_Donor = 1, 3, 4, 5  # method 2
+	frag_Acceptor = 2, 6, 7, 8
+'''
+
+# a simple donor-acceptor complex with randomly ordered atoms
+# the atoms have tags with them that denote the fragment they belong to
+# two ways are presented. first is to put the tags on the atoms
+# second is to put the tags at the bottom in a list
+mol = molecule.load('NH3BH3.xyz')  # load the molecule using our own function. This also loads meta-data
+
+
+# ### Method 1 ### #
+'''
+The first method uses the atom flags defined in the xyz file. 
+This reads anything after the atom definition, for example it 
+will read the frag= part and store it as atom.flags.frag.
+'''
+fragment_names = set(atom.flags.frag for atom in mol)  # store fragment names here
+fragment_atoms = {name: [] for name in fragment_names}  # store atoms here
+
+for atom in mol:
+	# get the fragment the atom belongs to and add it to the list
+	fragment_atoms[atom.flags.frag].append(atom)
+
+with ADFFragmentJob(test_mode=True) as job1:
+	# add the fragments to the job one by one
+	for fragment_name, atoms in fragment_atoms.items():
+		job1.add_fragment(atoms, fragment_name)
+
+	# set the job settings
+	job1.functional('BLYP')
+	job1.basis_set('TZ2P')
+
+
+# ### Method 2 ### #
+'''
+This method uses the molecular flags defined below the atom definitions.
+The flags are stored as mol.flags.frag_Donor and mol.flags.frag_Acceptor. 
+They both hold a list of integers which we will first turn into lists of atoms.
+'''
+frag_flags = {flag.removeprefix('frag_'): data for flag, data in mol.flags.items() if flag.startswith('frag_')}
+frag_atoms = {frag: [mol[i] for i in x] for frag, x in frag_flags.items()}
+
+with ADFFragmentJob(test_mode=True) as job2:
+	# add the fragments to the job one by one
+	for fragment_name, atoms in fragment_atoms.items():
+		job2.add_fragment(atoms, fragment_name)
+
+	# set the job settings
+	job2.functional('BLYP')
+	job2.basis_set('TZ2P')
+
+
+# ### Method 3 ### #
+'''
+This method is similar to method 2, but we can now supply a molecule to the 
+parent job and then define the fragments based on atom indices.
+'''
+fragment_indices = {flag.removeprefix('frag_'): x for flag, x in mol.flags.items() if flag.startswith('frag_')}
+
+with ADFFragmentJob(test_mode=True) as job3:
+	job3.molecule(mol)
+	for fragment_name, indices in fragment_indices.items():
+		job3.add_fragment(indices, fragment_name)
+
+	# set the job settings
+	job3.functional('BLYP')
+	job3.basis_set('TZ2P')
+
+
+# check the fragments for each method
+print('# ### Method 1 ### #')
+print(job1.childjobs)
+[print(frag_name, j._molecule) for frag_name, j in job1.childjobs.items()]
+
+print('# ### Method 2 ### #')
+print(job2.childjobs)
+[print(frag_name, j._molecule) for frag_name, j in job2.childjobs.items()]
+
+print('# ### Method 3 ### #')
+print(job3.childjobs)
+[print(frag_name, j._molecule) for frag_name, j in job3.childjobs.items()]

examples/job/orca.py

@@ -0,0 +1,11 @@
+from tcutility.job import ORCAJob
+
+with ORCAJob() as job:
+    job.molecule('water.xyz')
+    job.sbatch(p='tc', n=32, mem=20000)
+    job.name = 'ORCA_opt'
+    job.rundir = 'calculations/water'
+    job.add_preamble('export ORCA_FP=“/scistor/tc/dra480/bin/orca500/orca”')
+    job.add_preamble('export PATH=“/scistor/tc/dra480/bin/ompi411/bin:$PATH”')
+    job.add_preamble('export LD_LIBRARY_PATH=“/scistor/tc/dra480/bin/ompi411/lib/:$LD_LIBRARY_PATH”')
+    job.optimization()

examples/job/pentane.xyz

@@ -0,0 +1,19 @@
+17
+
+C      -3.15949327      -3.86575292       0.05080059
+C      -1.90503885      -3.00170042      -0.08117712
+C      -0.62815719      -3.84327295       0.02578951
+C       0.62931287      -2.97271947      -0.08042531
+C       1.90308216      -3.80822038       0.05065497
+H      -3.19112018      -4.61909694      -0.73782948
+H      -4.05227778      -3.24389872      -0.02716694
+H      -3.17357396      -4.37413682       1.01637198
+H      -1.90577930      -2.23902163       0.70606675
+H      -1.92042079      -2.48298781      -1.04645116
+H      -0.61922411      -4.59370909      -0.77263971
+H      -0.62231135      -4.37535085       0.98379862
+H       0.61272553      -2.21090984       0.70740609
+H       0.63282656      -2.45317624      -1.04532480
+H       2.78158417      -3.16643350      -0.02770312
+H       1.95110047      -4.56045507      -0.73823929
+H       1.92918836      -4.31640544       1.01606843

examples/job/qcg.py

@@ -0,0 +1,11 @@
+from tcutility.job import QCGJob
+
+with QCGJob() as job:
+    job.molecule('asc.xyz')
+    job.solvent('dmso.xyz')
+    job.rundir = 'calculations/ASC'
+    job.name = 'QCG'
+    job.md_length(5)
+    job.md_temperature(1000)
+    job.sbatch(p='tc', n=32)
+    job.ensemble_mode('MTD')

examples/job/screen_functionals.py

@@ -0,0 +1,31 @@
+from tcutility.job import ADFJob
+from tcutility.data import functionals
+from tcutility import results, log
+from yutility import pathfunc
+
+# run the calculations:
+available_functionals = functionals.get_available_functionals()
+for functional_name, functional_info in available_functionals.items():
+    with ADFJob(test_mode=True) as job:
+        # load your ams version
+        job.add_preamble('module load ams/2023.101')
+        # load your molecule
+        job.molecule('molecule.xyz')
+
+        # sort calculation by their category
+        job.rundir = f'DFT_screening/{functional_info.category}'
+        job.name = functional_info.path_safe_name
+
+        # slurm settings
+        job.sbatch(p='tc', ntasks_per_node=32)
+
+        # ADF settings
+        job.functional(functional_name)
+        job.basis_set('TZ2P')
+
+# analyse the results
+rows = []
+for rundir, path_data in pathfunc.match('DFT_screening', '{category}/{functional_name}').items():
+    res = results.read(rundir)
+    rows.append(res.status.code)
+log.table(rows, ['Status'])

examples/job/water.xyz

@@ -0,0 +1,5 @@
+3
+
+O      -1.00054733      -2.19438222       0.00000000
+H      -1.05209811      -2.99168159      -0.53221822
+H      -0.84589501      -2.43142270       0.91733008