From 23e9612baadfb2f2a30966832e514f548881343f Mon Sep 17 00:00:00 2001
From: Amir Mirzanejad <aqm6884@psu.edu>
Date: Fri, 8 Sep 2023 12:08:16 -0400
Subject: [PATCH] Delete PES_of_Hamiltonian.ipynb
---
PES_of_Hamiltonian.ipynb | 119 ---------------------------------------
1 file changed, 119 deletions(-)
delete mode 100644 PES_of_Hamiltonian.ipynb
diff --git a/PES_of_Hamiltonian.ipynb b/PES_of_Hamiltonian.ipynb
deleted file mode 100644
index d71a580..0000000
--- a/PES_of_Hamiltonian.ipynb
+++ /dev/null
@@ -1,119 +0,0 @@
-{
- "cells": [
- {
- "cell_type": "code",
- "execution_count": 33,
- "id": "c1bacd2c-a5c0-4cd4-b78d-9728220c136c",
- "metadata": {},
- "outputs": [
- {
- "data": {
- "text/html": [
- "<iframe\n",
- " scrolling=\"no\"\n",
- " width=\"1220px\"\n",
- " height=\"1820\"\n",
- " src=\"iframe_figures/figure_33.html\"\n",
- " frameborder=\"0\"\n",
- " allowfullscreen\n",
- "></iframe>\n"
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- }
- ],
- "source": [
- "# improt dependecies\n",
- "import plotly\n",
- "import scipy.ndimage\n",
- "import numpy as np\n",
- "import scipy\n",
- "import plotly.io as pio\n",
- "import plotly.graph_objects as go\n",
- "\n",
- "# Assuming Energy values from 'HubbardModelTriqs.ipynb' are stored in 'Energies_U_0.npy' file \n",
- "Enegies_U_0 = np.load(\"Energies_U_0.npy\")\n",
- "\n",
- "# Apply the Gaussian filter\n",
- "sigma = [0.1, 0.1]\n",
- "data_smooth_U = scipy.ndimage.gaussian_filter(Enegies_U_0[:,:,0], sigma)\n",
- "data_smooth_1_U = scipy.ndimage.gaussian_filter(Enegies_U_0[:,:,1], sigma)\n",
- "data_smooth_2_U = scipy.ndimage.gaussian_filter(Enegies_U_0[:,:,2], sigma)\n",
- "\n",
- "data_smooth = Enegies_U_0[:,:,0]\n",
- "data_smooth_1 = Enegies_U_0[:,:,1]\n",
- "data_smooth_2 = Enegies_U_0[:,:,2]\n",
- "\n",
- "colorscale1 = [[0, 'yellow'], [1, 'darkorange']]\n",
- "colorscale2 = [[0, 'darkorange'], [1, '#FF9912']]\n",
- "colorscale3 = [[0, '#FF9912'], [1, '#FF6103']]\n",
- "\n",
- "fig = go.Figure()\n",
- "\n",
- "# Add surface trace without contours, using the smoothed data\n",
- "fig.add_trace(go.Surface(z=data_smooth_U, colorscale=colorscale1))\n",
- "fig.add_trace(go.Surface(z=data_smooth_1_U, colorscale=colorscale2))\n",
- "fig.add_trace(go.Surface(z=data_smooth_2_U, colorscale=colorscale3))\n",
- "\n",
- "# Generate x and y indices\n",
- "x = np.arange(0, data_smooth.shape[1])\n",
- "y = np.arange(0, data_smooth.shape[0])\n",
- "\n",
- "# Add lines that correspond to constant x values\n",
- "for i in range(data_smooth.shape[0]):\n",
- " fig.add_trace(go.Scatter3d(x=np.full_like(y, i), y=y, z=data_smooth[:, i], mode='lines', \n",
- " line=dict(color='black', width=5), showlegend=False)) \n",
- "for i in range(data_smooth.shape[0]):\n",
- " fig.add_trace(go.Scatter3d(x=np.full_like(y, i), y=y, z=data_smooth_1[:, i], mode='lines', \n",
- " line=dict(color='black', width=3), showlegend=False))\n",
- "for i in range(data_smooth.shape[0]):\n",
- " fig.add_trace(go.Scatter3d(x=np.full_like(y, i), y=y, z=data_smooth_2[:, i], mode='lines', \n",
- " line=dict(color='black', width=3), showlegend=False))\n",
- "\n",
- "# Adjust position of camera \n",
- "camera_params = dict(up=dict(x=1.25,y=0,z=1),center=dict(x=0,y=0,z=0),eye=dict(x=2.9,y=-2.1,z=0.5)) \n",
- "\n",
- "fig.update_layout(scene_camera=camera_params)\n",
- "\n",
- "fig.update_layout(title='PES of Hamiltonian for U = 0', autosize=True,\n",
- " scene = dict(xaxis = dict(title='', title_font_family=\"Arial\", title_font_color='black', title_font_size=25), \n",
- " yaxis = dict(title='', title_font_family=\"Arial\", title_font_color='black', title_font_size=25),\n",
- " zaxis = dict(title='', title_font_family=\"Arial\", title_font_color='black', title_font_size=25, \n",
- " tickfont=dict(size=15), range=[-3.1,-1]),),\n",
- " width=1200, height=1800, margin=dict(l=60, r=60, b=60, t=90))\n",
- "\n",
- "fig.show()"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "id": "beaf20ba-ea31-4a8b-87cd-ffa142c41e2c",
- "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",
- "version": "3.10.8"
- }
- },
- "nbformat": 4,
- "nbformat_minor": 5
-}
--
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