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Removed deprecated test examples
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‎notebooks/Example4_md/Example2_atomistic/.gitignore renamed to ‎notebooks/Example21_qtag/.gitignore

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.ipynb_checkpoints
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*.xyz
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.ipynb_checkpoints
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qtag*

‎notebooks/Example21_qtag/LibraQTAG-Python.ipynb

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{
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"cells": [
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{
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"cell_type": "code",
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"execution_count": 1,
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"id": "a803e43a",
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"metadata": {},
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"outputs": [
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{
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"name": "stderr",
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"output_type": "stream",
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"text": [
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"/home/alexey/Conda/Miniconda3/envs/libra/lib/python3.6/importlib/_bootstrap.py:219: RuntimeWarning: to-Python converter for std::vector<std::vector<int, std::allocator<int> >, std::allocator<std::vector<int, std::allocator<int> > > > already registered; second conversion method ignored.\n",
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" return f(*args, **kwds)\n",
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"/home/alexey/Conda/Miniconda3/envs/libra/lib/python3.6/importlib/_bootstrap.py:219: RuntimeWarning: to-Python converter for boost::python::detail::container_element<std::vector<std::vector<int, std::allocator<int> >, std::allocator<std::vector<int, std::allocator<int> > > >, unsigned long, boost::python::detail::final_vector_derived_policies<std::vector<std::vector<int, std::allocator<int> >, std::allocator<std::vector<int, std::allocator<int> > > >, false> > already registered; second conversion method ignored.\n",
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" return f(*args, **kwds)\n",
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"/home/alexey/Conda/Miniconda3/envs/libra/lib/python3.6/importlib/_bootstrap.py:219: RuntimeWarning: to-Python converter for std::vector<std::vector<float, std::allocator<float> >, std::allocator<std::vector<float, std::allocator<float> > > > already registered; second conversion method ignored.\n",
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" return f(*args, **kwds)\n",
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"/home/alexey/Conda/Miniconda3/envs/libra/lib/python3.6/importlib/_bootstrap.py:219: RuntimeWarning: to-Python converter for boost::python::detail::container_element<std::vector<std::vector<float, std::allocator<float> >, std::allocator<std::vector<float, std::allocator<float> > > >, unsigned long, boost::python::detail::final_vector_derived_policies<std::vector<std::vector<float, std::allocator<float> >, std::allocator<std::vector<float, std::allocator<float> > > >, false> > already registered; second conversion method ignored.\n",
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" return f(*args, **kwds)\n",
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"/home/alexey/Conda/Miniconda3/envs/libra/lib/python3.6/importlib/_bootstrap.py:219: RuntimeWarning: to-Python converter for std::vector<std::vector<double, std::allocator<double> >, std::allocator<std::vector<double, std::allocator<double> > > > already registered; second conversion method ignored.\n",
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" return f(*args, **kwds)\n",
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"/home/alexey/Conda/Miniconda3/envs/libra/lib/python3.6/importlib/_bootstrap.py:219: RuntimeWarning: to-Python converter for boost::python::detail::container_element<std::vector<std::vector<double, std::allocator<double> >, std::allocator<std::vector<double, std::allocator<double> > > >, unsigned long, boost::python::detail::final_vector_derived_policies<std::vector<std::vector<double, std::allocator<double> >, std::allocator<std::vector<double, std::allocator<double> > > >, false> > already registered; second conversion method ignored.\n",
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" return f(*args, **kwds)\n",
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"/home/alexey/Conda/Miniconda3/envs/libra/lib/python3.6/importlib/_bootstrap.py:219: RuntimeWarning: to-Python converter for std::vector<std::vector<std::complex<double>, std::allocator<std::complex<double> > >, std::allocator<std::vector<std::complex<double>, std::allocator<std::complex<double> > > > > already registered; second conversion method ignored.\n",
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" return f(*args, **kwds)\n",
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"/home/alexey/Conda/Miniconda3/envs/libra/lib/python3.6/importlib/_bootstrap.py:219: RuntimeWarning: to-Python converter for boost::python::detail::container_element<std::vector<std::vector<std::complex<double>, std::allocator<std::complex<double> > >, std::allocator<std::vector<std::complex<double>, std::allocator<std::complex<double> > > > >, unsigned long, boost::python::detail::final_vector_derived_policies<std::vector<std::vector<std::complex<double>, std::allocator<std::complex<double> > >, std::allocator<std::vector<std::complex<double>, std::allocator<std::complex<double> > > > >, false> > already registered; second conversion method ignored.\n",
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" return f(*args, **kwds)\n"
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]
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}
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],
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"source": [
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"import numpy as np\n",
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"import math\n",
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"import matplotlib.pyplot as plt\n",
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"import imageio\n",
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"import os\n",
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"import time\n",
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"import sys\n",
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"\n",
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"from liblibra_core import *\n",
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"import libra_py.models.Holstein as Holstein\n",
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"import util.libutil as comn\n",
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"from libra_py import data_outs\n",
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"import libra_py.data_savers as data_savers\n",
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"\n",
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"import libra_py.dynamics.qtag.qtag_calc as qtag_calc\n",
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"import libra_py.dynamics.qtag.qtag_init as qtag_init\n",
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"import libra_py.dynamics.qtag.qtag_mom as qtag_mom\n",
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"import libra_py.dynamics.qtag.qtag_prop as qtag_prop\n",
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"import libra_py.dynamics.qtag.save as save"
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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": 2,
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"id": "fc9c9952",
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"metadata": {},
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"outputs": [],
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"source": [
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"class tmp:\n",
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" pass\n",
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"\n",
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"#Holstein5 from libra_py/models/Hostein.py\n",
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"def holstein_mimic(q, params, full_id):\n",
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" critical_params = [\"E_n\", \"x_n\", \"k_n\" ]\n",
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" default_params = { \"V\": [ [0.001, 0.001, 0.001, 0.001], [0.001, 0.001, 0.001, 0.001],\n",
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" [0.001, 0.001, 0.001, 0.001], [0.001, 0.001, 0.001, 0.001] ],\n",
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" \"alpha\": [ [0.00, 0.00, 0.00, 0.00], [0.00, 0.00, 0.00, 0.00],\n",
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" [0.00, 0.00, 0.00, 0.00], [0.00, 0.00, 0.00, 0.00] ],\n",
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" \"x_nm\": [ [0.00, 0.00, 0.00, 0.00], [0.00, 0.00, 0.00, 0.00],\n",
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" [0.00, 0.00, 0.00, 0.00], [0.00, 0.00, 0.00, 0.00] ],\n",
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" }\n",
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" comn.check_input(params, default_params, critical_params)\n",
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"\n",
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" E_n = params[\"E_n\"]\n",
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" x_n = params[\"x_n\"]\n",
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" k_n = params[\"k_n\"]\n",
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" V = params[\"V\"]\n",
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" alpha = params[\"alpha\"]\n",
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" x_nm = params[\"x_nm\"]\n",
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" \n",
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" n = len(E_n)\n",
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"\n",
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" Hdia = CMATRIX(n,n)\n",
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" Sdia = CMATRIX(n,n)\n",
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" d1ham_dia = CMATRIXList(); d1ham_dia.append( CMATRIX(n,n) )\n",
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" dc1_dia = CMATRIXList(); dc1_dia.append( CMATRIX(n,n) )\n",
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"\n",
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" #indx = 0\n",
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" Id = Cpp2Py(full_id)\n",
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" indx = Id[-1]\n",
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"\n",
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" x = q.col(indx).get(0)\n",
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"\n",
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" Sdia.identity()\n",
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"\n",
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" for i in range(n):\n",
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" Hdia.set(i,i, (E_n[i] + 0.5*k_n[i]*(x - x_n[i])**2) * (1.0+0.0j) )\n",
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"\n",
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" for i in range(n):\n",
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" for j in range(n):\n",
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" if i!=j:\n",
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" Hdia.set(i,j, V[i][j] * math.exp(-alpha[i][j] * (x-x_nm[i][j])**2 ) * (1.0+0.0j) )\n",
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"\n",
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" for k in [0]:\n",
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" # d Hdia / dR_0\n",
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" for i in range(n):\n",
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" d1ham_dia[k].set(i,i, (k_n[i] * (x - x_n[i]))*(1.0+0.0j) )\n",
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"\n",
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" for k in [0]:\n",
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" for i in range(n):\n",
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" for j in range(n):\n",
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" if i!=j:\n",
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" d1ham_dia[k].set(i,j, -2.0*alpha[i][j] * (x-x_nm[i][j]) * V[i][j] * math.exp(-alpha[i][j] * (x-x_nm[i][j])**2 ) * (1.0+0.0j) )\n",
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"\n",
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" obj = tmp()\n",
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" obj.ham_dia = Hdia\n",
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" obj.ovlp_dia = Sdia\n",
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" obj.d1ham_dia = d1ham_dia\n",
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" obj.dc1_dia = dc1_dia\n",
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"\n",
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" return obj"
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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": 3,
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"id": "5cbf0e12",
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"metadata": {},
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"outputs": [],
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"source": [
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"def compute_model(q, model_params, full_id):\n",
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"\n",
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" model = model_params[\"model\"]\n",
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" res = None\n",
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" \n",
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" if model==1:\n",
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" #res = Holstein.Holstein2(q, model_params, full_id)\n",
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" res = holstein_mimic(q, model_params, full_id)\n",
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" else:\n",
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" print(\"Unrecognized model! Check for correct model import statement.\")\n",
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"\n",
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" return res"
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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": 4,
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"id": "7ebfd1ca",
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"metadata": {},
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"outputs": [],
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"source": [
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"def run_qtag(dyn_params, _compute_model, _model_params, prefix):\n",
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"\n",
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" default_params = {\n",
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" \"hdf5_output_level\":-1, \"prefix\":prefix, \"use_compression\":0, \"compression_level\":[0,0,0], \n",
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" \"mem_output_level\":4, \"txt2_output_level\":0, \"properties_to_save\": [], \"progress_frequency\": 1\n",
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" }\n",
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" critical_params = []\n",
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" \n",
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" comn.check_input(dyn_params, default_params, critical_params)\n",
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"# qtag_checks.user_input(dyn_params, model_params)\n",
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" #Define function objects to be used in various parts of the calculation...\n",
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" #initialize, basis_props, vapprox, mom_calc, propagate = qtag_checks.assign_fobj(qtag_params)\n",
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"\n",
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" #basis_props = qtag_checks.set_basis_updates(dyn_params)\n",
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" \n",
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" #Rename variables locally for convenience...\n",
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" ndof = dyn_params[\"ndof\"]\n",
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" nstates = dyn_params[\"nstates\"]\n",
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" active_state = dyn_params[\"active_state\"]\n",
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" nsteps = dyn_params[\"nsteps\"]\n",
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" dt = dyn_params[\"dt\"]\n",
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" mass = dyn_params[\"mass\"]\n",
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" iM = dyn_params[\"iM\"]\n",
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" #iM = MATRIX(1, 1); iM.set(0,0, 1.0);\n",
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"\n",
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" #Initialize the basis parameters {q,p,a,s} and create initial b-matrix...\n",
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" ntraj, qpas = qtag_init.initialize(dyn_params)\n",
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"\n",
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" #Create initial projection vector b...\n",
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" bt = qtag_init.coeffs(dyn_params, qpas, active_state)\n",
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"\n",
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" #Initialize savers...\n",
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" dyn_params['prefix'] = prefix\n",
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" properties_to_save = dyn_params['properties_to_save']\n",
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" _savers = save.init_qtag_savers(dyn_params, _model_params, nsteps, ntraj, ndof, nstates)\n",
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" \n",
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" #Start simulation and walltime variables...\n",
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" walltime_start = time.time()\n",
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" t=0.0\n",
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"\n",
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" \n",
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" ham = nHamiltonian(nstates, nstates, ndof)\n",
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" ham.add_new_children(nstates, nstates, ndof, ntraj) \n",
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" ham.init_all(2,1)\n",
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" _model_params.update({\"timestep\":0})\n",
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" \n",
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" ovlp = CMATRIX(ntraj, ntraj)\n",
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" hmat = CMATRIX(ntraj, ntraj)\n",
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" \n",
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" coeff = CMATRIX(nstates, ntraj)\n",
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" \n",
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" \n",
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" for step in range(nsteps):\n",
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" \n",
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" qtag_hamiltonian_and_overlap(qpas[0], qpas[1], qpas[2], qpas[3], coeff, \n",
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" Py2Cpp_int(qpas[4]), iM, ham, \n",
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" _compute_model, _model_params, dyn_params,\n",
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" ovlp, hmat)\n",
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" \n",
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" #Compute the new coefficient vector c_new...\n",
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" ct_new = qtag_calc.basis_diag(ntraj,dt,hmat,ovlp,bt)\n",
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" \n",
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" etot = qtag_calc.energy(ct_new,hmat)\n",
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" pops = qtag_calc.norm(qpas[4],ct_new,ovlp,\n",
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" [state for state in range(nstates)])\n",
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"\n",
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" print(etot)\n",
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" #Update the basis parameters according to the new wavefunction (ct_new)...\n",
222+
" qpas, bt = qtag_prop.propagate(dyn_params, qpas, ct_new, pops)\n",
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" \n",
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" save.save_qtag_data(_savers, dyn_params, step, etot, 0, pops, \n",
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" ct_new, qpas[0], qpas[1], qpas[2], qpas[3]) \n",
226+
" if _savers[\"txt2_saver\"]!=None:\n",
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" _savers[\"txt2_saver\"].save_data_txt( F\"{prefix}\", properties_to_save, \"a\", 0)\n",
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" \n",
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" print(pops)\n",
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" walltime_end = time.time()\n",
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" print(\"Total wall time: \",walltime_end-walltime_start)\n"
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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": 5,
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"id": "1f3c7126",
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"[[2, -0.03], [1, -0.02], [0, 0.01]]"
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]
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},
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"execution_count": 5,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"merge_sort([ [0, 0.01], [1, -0.02], [2, -0.03 ]])"
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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": 6,
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"id": "7119d8e8",
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"metadata": {
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"scrolled": true
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},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"15.050030925787372\n",
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" step= 0\n",
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"15.050030925787382\n",
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"15.050030925787397\n",
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"15.05003092578742\n",
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"15.050030925787441\n",
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"15.050030925787452\n",
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"15.050030925787473\n",
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"15.05003092578749\n",
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"15.050030925787501\n",
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"15.050030925787519\n",
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"15.050030925787526\n",
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"15.050030925787553\n",
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"15.050030925787569\n",
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"15.05003092578759\n",
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"15.050030925787606\n",
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"15.050030925787624\n",
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"15.050030925787647\n",
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"15.050030925787663\n",
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"15.050030925787684\n",
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"15.050030925787706\n",
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"[0.8743601549642422, 8.70075639668817e-09]\n",
289+
"Total wall time: 0.24504971504211426\n"
290+
]
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}
292+
],
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"source": [
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"iM = MATRIX(1, 1); iM.set(0,0, 1.0);\n",
295+
"\n",
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"#Parameters for general simulation\n",
297+
"dyn_params = {\n",
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" \"ndof\" : 1, \"nstates\" : 2, \"active_state\" : 0,\n",
299+
" \"dt\":10., \"nsteps\":20, \"mass\":[1.0], \"iM\":iM,\n",
300+
" \"hdf5_output_level\" : 0, \"txt2_output_level\": 3, \n",
301+
" \"properties_to_save\" : [\"time\",\"Etot\",\"pops\",\"q\"],\n",
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" \"init_placement\":0, \"grid_dims\" : [5], \"alp_scl\":[6.0], \"rho_cut\":1e-12,\n",
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" \"q_update_method\" : 1, \"p_update_method\" : 1, \"a_update_method\" : 1, \"s_update_method\" : 0,\n",
304+
" \"q_sync_method\":1, \"p_sync_method\":0, \"a_sync_method\":0, \"s_sync_method\":0,\n",
305+
" \"wfc_q0\" : [-2.0], \"wfc_p0\" : [0.0], \"wfc_a0\" : [1.0], \"wfc_s0\" : [0.0],\n",
306+
" \"decpl_den\" : 0.3,\n",
307+
" \"mom_calc_type\" : 1, \"linfit_beta\" : 1e-3,\n",
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" \"qtag_pot_approx_method\":0\n",
309+
"}\n",
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"\n",
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"#Potential parameters for Holstein5\n",
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"model_params = {\n",
313+
" \"model\":1,\n",
314+
" \"E_n\":[0.0,15.8114],\n",
315+
" \"x_n\":[0.0,1.0],\n",
316+
" \"k_n\":[10.0,10.0],\n",
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" \"V\":[[0.0,1.0],[1.0,0.0]],\n",
318+
" \"alpha\":[[0.0,1.5811],[1.5811,0.0]],\n",
319+
" \"x_nm\":[[0.0,2.0],[2.0,0.0]]\n",
320+
"}\n",
321+
"\n",
322+
"run_qtag(dyn_params, compute_model, model_params, \"qtag\")"
323+
]
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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": "c98981c9",
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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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"metadata": {
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"kernelspec": {
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"display_name": "Python 3",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.6.13"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 5
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}

‎notebooks/Example4_md/Example1_lattice/.gitignore

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