diff --git a/basic.ipynb b/basic.ipynb new file mode 100644 index 0000000..5d4ad37 --- /dev/null +++ b/basic.ipynb @@ -0,0 +1 @@ +{"metadata":{"kernelspec":{"display_name":"Python 3 (ipykernel)","language":"python","name":"python3"},"language_info":{"codemirror_mode":{"name":"ipython","version":3},"file_extension":".py","mimetype":"text/x-python","name":"python","nbconvert_exporter":"python","pygments_lexer":"ipython3","version":"3.11.0"}},"nbformat_minor":4,"nbformat":4,"cells":[{"cell_type":"code","source":"import os\nimport subprocess\nimport matplotlib.pyplot as plt\nimport numpy as np\nfrom ase.build import bulk\nfrom ase.io import write\nfrom adis_tools.parsers import parse_pw\nfrom pyiron_base.project.delayed import draw","metadata":{"trusted":true},"outputs":[],"execution_count":1},{"cell_type":"code","source":"def write_input(input_dict, working_directory=\".\"):\n filename = os.path.join(working_directory, 'input.pwi')\n os.makedirs(working_directory, exist_ok=True)\n write(\n filename=filename, \n images=input_dict[\"structure\"], \n Crystal=True, \n kpts=input_dict[\"kpts\"], \n input_data={\n 'calculation': input_dict[\"calculation\"],\n 'occupations': 'smearing',\n 'degauss': input_dict[\"smearing\"],\n }, \n pseudopotentials=input_dict[\"pseudopotentials\"],\n tstress=True, \n tprnfor=True\n )","metadata":{"trusted":true},"outputs":[],"execution_count":2},{"cell_type":"code","source":"def collect_output(working_directory=\".\"):\n output = parse_pw(os.path.join(working_directory, 'pwscf.xml'))\n return {\n \"structure\": output['ase_structure'],\n \"energy\": output[\"energy\"],\n \"volume\": output['ase_structure'].get_volume(),\n }","metadata":{"trusted":true},"outputs":[],"execution_count":3},{"cell_type":"code","source":"def generate_structures(structure, strain_lst): \n structure_lst = []\n for strain in strain_lst:\n structure_strain = structure.copy()\n structure_strain.set_cell(\n structure_strain.cell * strain**(1/3), \n scale_atoms=True\n )\n structure_lst.append(structure_strain)\n return structure_lst","metadata":{"trusted":true},"outputs":[],"execution_count":4},{"cell_type":"code","source":"","metadata":{"trusted":true},"outputs":[],"execution_count":null},{"cell_type":"code","source":"","metadata":{"trusted":true},"outputs":[],"execution_count":null},{"cell_type":"code","source":"def plot_energy_volume_curve(volume_lst, energy_lst):\n plt.plot(volume_lst, energy_lst)\n plt.xlabel(\"Volume\")\n plt.ylabel(\"Energy\")\n plt.savefig(\"evcurve.png\")","metadata":{"trusted":true},"outputs":[],"execution_count":5},{"cell_type":"code","source":"pseudopotentials = {\"Al\": \"Al.pbe-n-kjpaw_psl.1.0.0.UPF\"}","metadata":{"trusted":true},"outputs":[],"execution_count":6},{"cell_type":"markdown","source":"# Structure optimization ","metadata":{}},{"cell_type":"code","source":"structure = bulk(\n name=\"Al\",\n a=4.05,\n cubic=True,\n)","metadata":{"trusted":true},"outputs":[],"execution_count":7},{"cell_type":"code","source":"write_input(\n input_dict={\n \"structure\": structure, \n \"pseudopotentials\": pseudopotentials, \n \"kpts\": (3, 3, 3),\n \"calculation\": \"vc-relax\",\n \"smearing\": 0.02,\n },\n working_directory=\"mini\",\n)","metadata":{"trusted":true},"outputs":[],"execution_count":8},{"cell_type":"code","source":"subprocess.check_output(\"mpirun -np 1 pw.x -in input.pwi > output.pwo\", cwd=\"mini\", shell=True)","metadata":{"trusted":true},"outputs":[{"name":"stderr","text":"[jupyter-materialdigital-2dadis2023-2dtr15o25f:00389] mca_base_component_repository_open: unable to open mca_btl_openib: librdmacm.so.1: cannot open shared object file: No such file or directory (ignored)\nNote: The following floating-point exceptions are signalling: IEEE_INVALID_FLAG\n","output_type":"stream"},{"execution_count":9,"output_type":"execute_result","data":{"text/plain":"b''"},"metadata":{}}],"execution_count":9},{"cell_type":"code","source":"output = collect_output(working_directory=\"mini\")\noutput","metadata":{"trusted":true},"outputs":[{"execution_count":10,"output_type":"execute_result","data":{"text/plain":"{'structure': Atoms(symbols='Al4', pbc=True, cell=[4.045637215947182, 4.045637215947182, 4.045637215947182]),\n 'energy': -1074.9365262253457,\n 'volume': 66.21567448237923}"},"metadata":{}}],"execution_count":10},{"cell_type":"markdown","source":"# Generate Structures","metadata":{}},{"cell_type":"code","source":"number_of_strains = 5 \nstructure_lst = generate_structures(\n structure=output['structure'], \n strain_lst=np.linspace(0.9, 1.1, number_of_strains),\n)\nstructure_lst","metadata":{"trusted":true},"outputs":[{"execution_count":11,"output_type":"execute_result","data":{"text/plain":"[Atoms(symbols='Al4', pbc=True, cell=[3.906019785962478, 3.906019785962478, 3.906019785962478]),\n Atoms(symbols='Al4', pbc=True, cell=[3.9770538443183843, 3.9770538443183843, 3.9770538443183843]),\n Atoms(symbols='Al4', pbc=True, cell=[4.045637215947182, 4.045637215947182, 4.045637215947182]),\n Atoms(symbols='Al4', pbc=True, cell=[4.111970927283303, 4.111970927283303, 4.111970927283303]),\n Atoms(symbols='Al4', pbc=True, cell=[4.176230852372533, 4.176230852372533, 4.176230852372533])]"},"metadata":{}}],"execution_count":11},{"cell_type":"markdown","source":"# Energy Volume Curve ","metadata":{}},{"cell_type":"code","source":"energy_lst, volume_lst = [], []\nfor i, structure_strain in enumerate(structure_lst):\n write_input(\n input_dict={\n \"structure\": structure_strain, \n \"pseudopotentials\": pseudopotentials, \n \"kpts\": (3, 3, 3),\n \"calculation\": \"scf\",\n \"smearing\": 0.02,\n },\n working_directory=\"strain_\" + str(i),\n )\n subprocess.check_output(\n \"mpirun -np 1 pw.x -in input.pwi > output.pwo\", \n cwd=\"strain_\" + str(i), \n shell=True\n )\n output = collect_output(working_directory=\"strain_\" + str(i))\n energy_lst.append(output[\"energy\"])\n volume_lst.append(output[\"volume\"])","metadata":{"trusted":true},"outputs":[{"name":"stderr","text":"[jupyter-materialdigital-2dadis2023-2dtr15o25f:00397] mca_base_component_repository_open: unable to open mca_btl_openib: librdmacm.so.1: cannot open shared object file: No such file or directory (ignored)\nNote: The following floating-point exceptions are signalling: IEEE_INVALID_FLAG\n[jupyter-materialdigital-2dadis2023-2dtr15o25f:00405] mca_base_component_repository_open: unable to open mca_btl_openib: librdmacm.so.1: cannot open shared object file: No such file or directory (ignored)\nNote: The following floating-point exceptions are signalling: IEEE_INVALID_FLAG\n[jupyter-materialdigital-2dadis2023-2dtr15o25f:00413] mca_base_component_repository_open: unable to open mca_btl_openib: librdmacm.so.1: cannot open shared object file: No such file or directory (ignored)\nNote: The following floating-point exceptions are signalling: IEEE_INVALID_FLAG\n[jupyter-materialdigital-2dadis2023-2dtr15o25f:00421] mca_base_component_repository_open: unable to open mca_btl_openib: librdmacm.so.1: cannot open shared object file: No such file or directory (ignored)\nNote: The following floating-point exceptions are signalling: IEEE_INVALID_FLAG\n[jupyter-materialdigital-2dadis2023-2dtr15o25f:00429] mca_base_component_repository_open: unable to open mca_btl_openib: librdmacm.so.1: cannot open shared object file: No such file or directory (ignored)\nNote: The following floating-point exceptions are signalling: IEEE_INVALID_FLAG\n","output_type":"stream"}],"execution_count":12},{"cell_type":"code","source":"plot_energy_volume_curve(\n volume_lst=volume_lst, \n energy_lst=energy_lst\n)","metadata":{"trusted":true},"outputs":[{"output_type":"display_data","data":{"text/plain":"
","image/png":"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"},"metadata":{}}],"execution_count":13},{"cell_type":"code","source":"","metadata":{"trusted":true},"outputs":[],"execution_count":null}]} \ No newline at end of file