{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"id": "e839a5d8-dd7e-422a-83de-e430eca88dd7",
"metadata": {},
"outputs": [],
"source": [
"from pyscf import gto, lib, scf, df, ao2mo\n",
"import numpy as np\n",
"import scipy\n",
"\n",
"np.set_printoptions(16, suppress=False, linewidth=300)"
]
},
{
"cell_type": "code",
"execution_count": 2,
"id": "a382f595-53a0-4258-9eb7-7f422be99ca3",
"metadata": {},
"outputs": [],
"source": [
"mol = mol_tzvp = gto.Mole(atom=\"O; H 1 0.94; H 1 0.94 2 104.5\", basis=\"def2-TZVP\").build()"
]
},
{
"cell_type": "code",
"execution_count": 3,
"id": "955ad945-276a-4cc7-b82c-8b6912612409",
"metadata": {},
"outputs": [],
"source": [
"mol_jk = gto.Mole(atom=\"O; H 1 0.94; H 1 0.94 2 104.5\", basis=\"def2-universal-jkfit\").build()"
]
},
{
"cell_type": "code",
"execution_count": 4,
"id": "0994d915-9945-45c1-a866-60d43aecc773",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"(11.25500947854174, (43, 113))"
]
},
"execution_count": 4,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"out = gto.intor_cross(\"int1e_ovlp\", mol_tzvp, mol_jk)\n",
"lib.fp(out.T), out.shape"
]
},
{
"cell_type": "code",
"execution_count": 5,
"id": "95393f49-5dd3-45f4-b4ca-5c813c5c529f",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"(10.435234769997802, (946, 113, 3))"
]
},
"execution_count": 5,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"out = df.incore.aux_e2(mol_tzvp, mol_jk, \"int3c2e_ip2\", \"s2ij\")\n",
"out_c = out.transpose(0, 2, 1)\n",
"lib.fp(out_c), out_c.shape[::-1]"
]
},
{
"cell_type": "code",
"execution_count": 6,
"id": "bd26d67b-bca2-4837-842f-ffe98974056d",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"(7.422726471473346, (43, 113))"
]
},
"execution_count": 6,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"out = gto.intor_cross(\"int1e_ovlp\", mol_tzvp, mol_jk)\n",
"lib.fp(out), out.shape"
]
},
{
"cell_type": "code",
"execution_count": 7,
"id": "24992402-b8af-4ecc-9253-579bfba389f4",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"(15.423815120360992, (3, 946, 113))"
]
},
"execution_count": 7,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"out = df.incore.aux_e2(mol_tzvp, mol_jk, \"int3c2e_ip2\", \"s2ij\")\n",
"lib.fp(out), out.shape"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "1ddba5ed-d7a0-4d41-a91f-efc23ce4c92a",
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": 8,
"id": "efccdfe3-b7f1-4c6b-b13d-aa33b389b18e",
"metadata": {},
"outputs": [],
"source": [
"coords_chg = np.asarray([[0, 1, 2], [2, 0, 1], [0, 2, 1]])"
]
},
{
"cell_type": "code",
"execution_count": 9,
"id": "35da31c5-dc11-4269-b62c-8dc208052fc3",
"metadata": {},
"outputs": [],
"source": [
"mol_chg = gto.fakemol_for_charges(coords_chg)"
]
},
{
"cell_type": "code",
"execution_count": 10,
"id": "60afecc3-e36e-4a83-82eb-3dca08c6ccef",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"(-0.12650556883004238, (43, 3))"
]
},
"execution_count": 10,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"out = gto.intor_cross(\"int1e_ovlp\", mol_tzvp, mol_chg)\n",
"lib.fp(out), out.shape"
]
},
{
"cell_type": "code",
"execution_count": 11,
"id": "fb6dd265-431b-4134-8756-c1591e9ed101",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"(0.0707265752256318, (43, 3))"
]
},
"execution_count": 11,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"exp_chg = 1.0\n",
"mol_chg = gto.fakemol_for_charges(coords_chg, exp_chg)\n",
"out = gto.intor_cross(\"int1e_ovlp\", mol_tzvp, mol_chg)\n",
"lib.fp(out), out.shape"
]
},
{
"cell_type": "code",
"execution_count": 12,
"id": "eb5318a8-c437-4c93-b172-b8f73d023633",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"(0.0424629237780389, (43, 3))"
]
},
"execution_count": 12,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"exp_chg = [1.0, 2.5, 4.9]\n",
"mol_chg = gto.fakemol_for_charges(coords_chg, exp_chg)\n",
"out = gto.intor_cross(\"int1e_ovlp\", mol_tzvp, mol_chg)\n",
"lib.fp(out), out.shape"
]
},
{
"cell_type": "code",
"execution_count": 13,
"id": "bea44cdc-0e5c-40de-87e1-6f20c5f6d909",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"(-0.054460537334674264, (43, 1))"
]
},
"execution_count": 13,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"coord = np.asarray([[0., 1., 2.]])\n",
"exp_chg = [1.0, 2.5, 4.9]\n",
"coef_chg = [2.8, 3.3, 0.7]\n",
"mol_chg = gto.fakemol_for_cgtf_charge(coord, exp_chg, coef_chg)\n",
"out = gto.intor_cross(\"int1e_ovlp\", mol_tzvp, mol_chg)\n",
"lib.fp(out), out.shape"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "d4f6338a-ff03-47d0-a404-c0c1fe9563e9",
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": null,
"id": "d793fb90-1999-460e-9952-ed48839daa70",
"metadata": {},
"outputs": [],
"source": []
}
],
"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",
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}
},
"nbformat": 4,
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}