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https://github.com/TREX-CoE/trexio.git
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Update the wheels scripts and add benzene data
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4
.github/workflows/build-wheels.yml
vendored
4
.github/workflows/build-wheels.yml
vendored
@ -152,7 +152,7 @@ jobs:
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working-directory: python
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- name: Install Python dependencies
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run: pip install --upgrade pip setuptools build delocate
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run: pip install --upgrade pip setuptools build delocate pytest
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- name: Build wheel for a given version of CPython
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run: |
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@ -169,7 +169,7 @@ jobs:
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working-directory: python
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- name: Test the wheel
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run: python test_api.py
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run: pytest -v test_api.py
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working-directory: python/test
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- name: Upload produced wheels as artifacts
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@ -82,11 +82,14 @@ function build_wheel_for_py()
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# install the produced manylinux wheel in the virtual environment
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python3 -m pip install wheelhouse/trexio-${TR_VERSION}-${CPYTHON}-manylinux*.whl
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# install pytest for testing
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pip install pytest
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# run test script
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cd test && python3 test_api.py && cd ..
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pytest -v test/test_api.py
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# cleaning
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rm -rf -- dist/ build/ trexio.egg-info/
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rm -- test_file_py.h5 unsafe_test_file_py.h5
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# deactivate the current environment
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deactivate
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46
python/test/benzene_data.py
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python/test/benzene_data.py
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@ -0,0 +1,46 @@
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# for the nucleus group
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nucleus_num = 12
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point_group = 'D6h'
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nucleus_label = ['C', 'C', 'C', 'C', 'C', 'C', 'H', 'H', 'H', 'H', 'H', 'H']
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nucleus_charge = [6., 6., 6., 6., 6., 6., 1., 1., 1., 1., 1., 1.]
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nucleus_coord = [
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[ 0.00000000 , 1.39250319 , 0.00000000 ],
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[-1.20594314 , 0.69625160 , 0.00000000 ],
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[-1.20594314 , -0.69625160 , 0.00000000 ],
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[ 0.00000000 , -1.39250319 , 0.00000000 ],
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[ 1.20594314 , -0.69625160 , 0.00000000 ],
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[ 1.20594314 , 0.69625160 , 0.00000000 ],
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[-2.14171677 , 1.23652075 , 0.00000000 ],
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[-2.14171677 , -1.23652075 , 0.00000000 ],
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[ 0.00000000 , -2.47304151 , 0.00000000 ],
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[ 2.14171677 , -1.23652075 , 0.00000000 ],
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[ 2.14171677 , 1.23652075 , 0.00000000 ],
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[ 0.00000000 , 2.47304151 , 0.00000000 ],
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]
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# for the basis_nucleus_index
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basis_shell_num = 24
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nucleus_index = [i for i in range(basis_shell_num)]
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# for sparse AO_INT_2E
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ao_num = 600
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# prepare the sparse data representation
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num_integrals = 100
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indices = [i for i in range(num_integrals*4)]
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values = [(3.14 + float(i)) for i in range(num_integrals)]
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# for determinants
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mo_num = 150
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int64_num = int((mo_num - 1)/64 + 1)
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# prepate the CI data
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det_num = 2000
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dets = [i for i in range(det_num * int64_num * 2)]
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coeffs = [float(i/det_num) for i in range(det_num)]
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coeffs_s2 = [float(i*2/det_num) for i in range(det_num)]
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det_test = [1, 2, 3, 2, 1, 3]
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