From 8e5b7d74612e9b7fcafeccc8fdffc5ff5937f51e Mon Sep 17 00:00:00 2001
From: Kostas Vilkelis <kostasvilkelis@gmail.com>
Date: Fri, 23 Feb 2024 01:50:14 +0100
Subject: [PATCH] example nb of current interface
---
examples/testInterface.ipynb | 105 +++++++++++++++++++++++++++++++++++
1 file changed, 105 insertions(+)
create mode 100644 examples/testInterface.ipynb
diff --git a/examples/testInterface.ipynb b/examples/testInterface.ipynb
new file mode 100644
index 0000000..bccafb5
--- /dev/null
+++ b/examples/testInterface.ipynb
@@ -0,0 +1,105 @@
+{
+ "cells": [
+ {
+ "cell_type": "code",
+ "execution_count": 1,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "import numpy as np\n",
+ "from codes import utils, model, solvers"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 2,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "def random_guess(vectors, int_model):\n",
+ " \"\"\"\n",
+ " Generate random guess.\n",
+ "\n",
+ " Parameters:\n",
+ " -----------\n",
+ " vectors : list of tuples\n",
+ " Hopping vectors for the mean-field corrections.\n",
+ " \"\"\"\n",
+ " scale = 0.1*(1+np.max(np.abs([*int_model.values()])))\n",
+ " return utils.generate_guess(\n",
+ " vectors=vectors,\n",
+ " ndof=len([*int_model.values()][0]),\n",
+ " scale=scale\n",
+ " )"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 3,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "array([ 4.81536544e-01, 6.41071801e-03, -1.76048506e-07, ...,\n",
+ " 0.00000000e+00, 1.33679796e-06, 0.00000000e+00])"
+ ]
+ },
+ "execution_count": 3,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "U0 = 1\n",
+ "nk = 100\n",
+ "filling = 2\n",
+ "\n",
+ "hopp = np.kron(np.array([[0, 1], [0, 0]]), np.eye(2))\n",
+ "tb_model = {(0,): hopp + hopp.T.conj(), (1,): hopp, (-1,): hopp.T.conj()}\n",
+ "int_model = {\n",
+ " (0,): U0 * np.kron(np.eye(2), np.ones((2, 2))),\n",
+ "}\n",
+ "\n",
+ "testModel = model.MfModel(tb_model, int_model, filling)\n",
+ "guess = utils.tb2grid(random_guess(tb_model.keys(), int_model), nk)\n",
+ "solvers.kspace_solver(testModel, guess)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": []
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": []
+ }
+ ],
+ "metadata": {
+ "kernelspec": {
+ "display_name": "base",
+ "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": "3.11.7"
+ }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}
--
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