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update test
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tests/aims/test_flows/test_eos.py

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# mapping from job name to directory containing test files
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ref_paths = {
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"Relaxation calculation 1": "double-relax-si/relax-1",
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"Relaxation calculation 2": "double-relax-si/relax-2",
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"Relaxation calculation 1 EOS equilibrium relaxation": "double-relax-si/relax-1",
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"Relaxation calculation 2 EOS equilibrium relaxation": "double-relax-si/relax-2",
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"Relaxation calculation (fixed cell) deformation 0": "eos-si/0",
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"Relaxation calculation (fixed cell) deformation 1": "eos-si/1",
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"Relaxation calculation (fixed cell) deformation 2": "eos-si/2",

tutorials/grueneisen_workflow.ipynb

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"from atomate2.vasp.sets.core import StaticSetGenerator, TightRelaxSetGenerator"
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]
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},
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{
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"cell_type": "markdown",
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"id": "3",
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"metadata": {},
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"source": [
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"# Grüneisen Workflow Tutorial with VASP"
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]
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},
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{
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"cell_type": "markdown",
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"id": "4",
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"metadata": {},
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"source": [
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"## Background\n",
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"The Grüneisen workflow is based on the implementation in Phonopy.\n",
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"\n",
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"If you want to read more about Phonopy, please read Togo’s paper: https://doi.org/10.7566/JPSJ.92.012001"
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]
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},
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{
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"cell_type": "markdown",
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"id": "5",
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"metadata": {},
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"source": [
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"## Let's run the workflow\n",
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"Now, we load a structure and other important functions and classes for running the Grüneisen workflow."
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "6",
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"id": "3",
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"metadata": {},
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"outputs": [],
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"source": [
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "7",
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"id": "4",
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"metadata": {},
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"outputs": [],
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"source": [
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "8",
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"id": "5",
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"metadata": {},
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"outputs": [],
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"source": [
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},
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{
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"cell_type": "markdown",
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"id": "9",
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"id": "6",
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"metadata": {},
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"source": [
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"Then one can use the `GruneisenMaker` to generate a `Flow`."
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "10",
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"id": "7",
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"metadata": {},
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"outputs": [],
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"source": [
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"flow = GruneisenMaker(\n",
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" symprec=1e-4,\n",
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" bulk_relax_maker=phonon_bulk_relax_maker_isif3,\n",
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" phonon_maker=PhononMaker(\n",
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" generate_frequencies_eigenvectors_kwargs={\"tmin\": 0, \"tmax\": 1000, \"tstep\": 10},\n",
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" generate_frequencies_eigenvectors_kwargs={\n",
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" \"tmin\": 0,\n",
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" \"tmax\": 1000,\n",
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" \"tstep\": 10,\n",
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" },\n",
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" min_length=10,\n",
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" bulk_relax_maker=None,\n",
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" born_maker=None,\n",
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},
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{
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"cell_type": "markdown",
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"id": "11",
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"id": "8",
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"metadata": {},
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"source": [
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"The Grüneisen parameter workflow will perform 3 different phonon runs at 3 different volumes at and around the equilibrium to compute the mode Grüneisen values."
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "12",
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"id": "9",
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"metadata": {},
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"outputs": [],
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"source": [
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},
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{
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"cell_type": "markdown",
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"id": "10",
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"metadata": {},
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"We now run the flow with `run_locally`. We mock the run here. Normally, you would simply use `run_locally` without the `with mock_vasp`"
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "11",
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"metadata": {},
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"outputs": [],
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"source": [
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "12",
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"source": [
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "16",
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"id": "13",
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"metadata": {},
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"outputs": [],
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"source": [

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