Merge pull request #5 from eimrek/release/2.0.0

Release/2.0.0

.gitignore

@@ -3,3 +3,4 @@ dist/*
 *.pyc
 .ipynb_checkpoints
 .vscode
+*.itx

README.md

@@ -19,6 +19,8 @@ Python 3 (tested with 3.6 - 3.9) environment is required with the following libr
 * Atomistic simulation environment: `ase` (3.18.1)
 * Python Tight Binding: `pythtb` (1.7.2)
 
+Note: the dependencies will be automatically installed via `pip`.
+
 ### Installation
 
 Option 1) Install the library and dependencies hosted on PyPI:

example.ipynb

@@ -58,7 +58,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "mfh_model.run_mfh(u = 3.0, print_iter=False, plot=False)"
+    "mfh_model.run_mfh(u = 3.0, print_iter=False, plot=True)"
    ]
   },
   {
@@ -69,7 +69,7 @@
    },
    "outputs": [],
    "source": [
-    "mfh_model.report(num_orb=2, sts_h=10.0, sts_broad=0.05)"
+    "mfh_model.pp.report(num_orb=2, sts_h=8.0, sts_broad=0.05)"
    ]
   },
   {
@@ -81,13 +81,36 @@
     "# Visualize one specific orbital\n",
     "\n",
     "spin = 0\n",
-    "index = 0\n",
+    "index = 12\n",
     "print(\"Orbital index: %d, spin %d\" % (index, spin))\n",
     "print(\"Energy: %.6f eV\" % mfh_model.evals[spin][index])\n",
-    "mfh_model.plot_mo_eigenvector(mo_index=index, spin=spin)\n",
     "\n",
-    "# corresponding eigenvector (each element corresponds in order to atoms defined in geom/mfh_model.ase_geom)\n",
-    "evec = mfh_model.evecs[spin][index]"
+    "# corresponding eigenvector\n",
+    "evec = mfh_model.evecs[spin][index]\n",
+    "\n",
+    "# Visualize eigenvector\n",
+    "mfh_model.pp.plot_mo_eigenvector(mo_index=index, spin=spin)\n",
+    "\n",
+    "# Visualize the orbital squared\n",
+    "mfh_model.pp.plot_orb_squared_map(plt.gca(), evec)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Export a map in .itx format"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "sts_map, extent = mfh_model.pp.calc_sts_map(energy=1.42, broadening=0.1, h=5.0)\n",
+    "\n",
+    "tbmfh.create_itx(data=sts_map, extent=extent, wavename=\"sts_map\", filename=\"example.itx\")"
    ]
   },
   {
@@ -172,7 +195,7 @@
     "# \"open shell\" case, normal MFH\n",
     "mfh_model = tbmfh.MeanFieldHubbardModel(geom, [2.7, 0.1, 0.4], charge=0, multiplicity=1)\n",
     "mfh_model.run_mfh(u = 3.0, print_iter=False, plot=False)\n",
-    "mfh_model.calculate_natural_orbitals()\n",
+    "mfh_model.pp.calculate_natural_orbitals()\n",
     "\n",
     "# \"closed shell\" case (just tight-binding)\n",
     "tb_model = tbmfh.MeanFieldHubbardModel(geom, [2.7, 0.1, 0.4], charge=0, multiplicity=1)\n",
@@ -193,15 +216,15 @@
     "    \n",
     "    fig, axs = plt.subplots(nrows=1, ncols=7, figsize=(7 * mfh_model.figure_size[0], mfh_model.figure_size[1]))\n",
     "    \n",
-    "    mfh_model.plot_no_eigenvector(i_mo, ax=axs[0])\n",
-    "    mfh_model.plot_orb_squared_map(axs[1], mfh_model.no_evecs[i_mo], h=h)\n",
+    "    mfh_model.pp.plot_no_eigenvector(i_mo, ax=axs[0])\n",
+    "    mfh_model.pp.plot_orb_squared_map(axs[1], mfh_model.pp.no_evecs[i_mo], h=h)\n",
     "    \n",
-    "    mfh_model.plot_mo_eigenvector(i_mo, spin=0, ax=axs[2])\n",
-    "    mfh_model.plot_mo_eigenvector(i_mo, spin=1, ax=axs[3])\n",
-    "    mfh_model.plot_sts_map(axs[4], mfh_model.evals[0, i_mo], h=h)\n",
+    "    mfh_model.pp.plot_mo_eigenvector(i_mo, spin=0, ax=axs[2])\n",
+    "    mfh_model.pp.plot_mo_eigenvector(i_mo, spin=1, ax=axs[3])\n",
+    "    mfh_model.pp.plot_sts_map(axs[4], mfh_model.evals[0, i_mo], h=h)\n",
     "    \n",
-    "    tb_model.plot_mo_eigenvector(i_mo, spin=0, ax=axs[5])\n",
-    "    tb_model.plot_sts_map(axs[6], tb_model.evals[0, i_mo], h=h)\n",
+    "    tb_model.pp.plot_mo_eigenvector(i_mo, spin=0, ax=axs[5])\n",
+    "    tb_model.pp.plot_sts_map(axs[6], tb_model.evals[0, i_mo], h=h)\n",
     "    \n",
     "    plt.subplots_adjust(wspace=0.0, hspace=0)\n",
     "    plt.show()"
@@ -231,7 +254,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.7.9"
+   "version": "3.8.8"
   },
   "toc": {
    "base_numbering": 1,

setup.py

@@ -5,7 +5,7 @@
 
 setuptools.setup(
     name="tb-mean-field-hubbard",
-    version="1.5.1",
+    version="2.0.0",
     author="Kristjan Eimre",
     author_email="[email protected]",
     description="Package to run tight-binding mean field hubbard calculations",
@@ -25,5 +25,6 @@
         "matplotlib",
         "ase",
         "pythtb",
+        'igor-tools @ git+https://[email protected]/nanotech-empa/igor-tools@main#egg=igor-tools',
     ],
 )

tb_mean_field_hubbard/__init__.py

@@ -1,3 +1,4 @@
 from .mfh import MeanFieldHubbardModel
+from .utils import create_itx
 
-__version__ = "1.5.1"
+__version__ = "2.0.0"