Merge pull request #96 from Exabyte-io/feature/SOF-7232

Feature/SOF-7232

other/materials_designer/Introduction.ipynb

@@ -0,0 +1,37 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Materials Transformations with Python Notebooks\n",
+    "\n",
+    "## Overview\n",
+    "\n",
+    "This Jupyter Lite distribution contains pre-configured examples of materials transformations including simple ones like creation of supercell or a surface, and more complex like creating an interface with Zur and McGill Superlattice matching algorithm\n",
+    "\n",
+    "## Examples\n",
+    "\n",
+    "### 1. Interface creation with Zur and McGill Superlattice algorithm\n",
+    "\n",
+    "[This file](zsl_interface_generation.ipynb) helps creating interface between two materials by finding matching superlattices and selecting optimal variants by size-strain trade-off. (Link to the lattice match algorithm: https://doi.org/10.1063/1.333084)\n",
+    "\n",
+    "### Definition for communication\n",
+    "\n",
+    "[definitions.py](definitions.py)\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": []
+  }
+ ],
+ "metadata": {
+  "language_info": {
+   "name": "python"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}

other/materials_designer/definitions.py

@@ -0,0 +1,132 @@
+from IPython.display import display, Javascript
+import json
+
+
+def set_materials(materials):
+    """
+    This function takes a Python object, serializes it to JSON, and sends it to the host environment
+    through a JavaScript function defined in the JupyterLite extension `data_bridge`.
+
+    Args:
+        materials (object): The Python object to be sent to the host environment.
+    """
+    python_data = materials
+    serialized_data = json.dumps({"materials": python_data})
+    js_code = f"""
+    (function() {{
+        window.sendDataToHost({serialized_data})
+        console.log({serialized_data})
+    }})();
+    """
+
+    display(Javascript(js_code))
+    print("materials sent")
+
+
+def get_materials():
+    """
+    This function requests materials from the host environment through a JavaScript function defined in the JupyterLite
+    extension `data_bridge`. The materials are then returned to the Python environment.
+    """
+    js_code = """
+    (function() {
+        if (window.requestDataFromHost) {
+            window.requestDataFromHost();
+            
+        } else {
+            console.error('requestDataFromHost function is not defined on the window object.');
+        }
+    })();
+    """
+
+    display(Javascript(js_code))
+    print("materials requested")
+
+
+from pymatgen.core import Structure, Lattice
+
+
+def to_pymatgen(material_data):
+    """
+    Convert material object in ESSE format to a pymatgen Structure object.
+
+    Args:
+        material_data (dict): A dictionary containing the material information in ESSE format.
+
+    Returns:
+        Structure: A pymatgen Structure object.
+    """
+
+    # Extract lattice information
+    lattice_params = material_data["lattice"]
+    lattice_vectors = lattice_params["vectors"]
+    a = lattice_vectors["a"]
+    b = lattice_vectors["b"]
+    c = lattice_vectors["c"]
+
+    # Create a Lattice
+    lattice = Lattice([a, b, c])
+
+    # Extract the basis information
+    basis = material_data["basis"]
+    elements = [element["value"] for element in basis["elements"]]
+    coordinates = [coord["value"] for coord in basis["coordinates"]]
+
+    # Assuming that the basis units are fractional since it's a crystal basis
+    coords_are_cartesian = basis["units"].lower() != "crystal"
+
+    # Create the Structure
+    structure = Structure(lattice, elements, coordinates, coords_are_cartesian=coords_are_cartesian)
+
+    return structure
+
+
+def from_pymatgen(structure: Structure):
+    """
+    Convert a pymatgen Structure object to a material object in ESSE format.
+
+    Args:
+        structure (Structure): A pymatgen Structure object.
+
+    Returns:
+        dict: A dictionary containing the material information in ESSE format.
+    """
+    basis = {
+        "elements": [{"id": i, "value": str(site.specie)} for i, site in enumerate(structure.sites)],
+        "coordinates": [{"id": i, "value": list(site.frac_coords)} for i, site in enumerate(structure.sites)],
+        "units": "crystal",
+        "cell": structure.lattice.matrix.tolist(),
+        "constraints": [],  # Assuming there are no constraints
+    }
+
+    # Extract lattice information
+    lattice = {
+        "a": structure.lattice.a,
+        "b": structure.lattice.b,
+        "c": structure.lattice.c,
+        "alpha": structure.lattice.alpha,
+        "beta": structure.lattice.beta,
+        "gamma": structure.lattice.gamma,
+        "units": {"length": "angstrom", "angle": "degree"},
+        "type": "FCC",  # You need a way to determine the lattice type
+        "vectors": {
+            "a": structure.lattice.matrix[0].tolist(),
+            "b": structure.lattice.matrix[1].tolist(),
+            "c": structure.lattice.matrix[2].tolist(),
+            "alat": 1,  # This seems to be a scaling factor; adjust if necessary
+            "units": "angstrom",
+        },
+    }
+
+    # Combine into a material dictionary
+    material = {
+        "name": structure.formula,
+        "basis": basis,
+        "lattice": lattice,
+        "isNonPeriodic": not structure.is_ordered,
+        "_id": "",
+        "metadata": {"boundaryConditions": {"type": "bc2", "offset": 0}},
+        "isUpdated": True,
+    }
+
+    return material