{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
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]
}
],
"source": [
"!pip install matgraphdb\n",
"!pip install ipykernel"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# 03 - Graph Generators in MatGraphDB\n",
"\n",
"In this notebook, we'll learn how to:\n",
"\n",
"1. Create node generator\n",
"2. Add the node generator to the graph\n",
"3. Create edge generator\n",
"4. Add the edge generator to the graph\n",
"5. Defining dependencies between generators\n",
"\n",
"We'll use the `MatGraphDB` class from `matgraphdb` to demonstrate these features. If you haven't already installed `matgraphdb`, run the previous cell.\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## 1. Download example data\n",
"\n",
"For this tutorial, we will start from example materials data. You can download the data by running the following cell. which downloads the data from the [MatGraphDB GitHub repository](https://github.com/romerogroup/MatGraphDB/tree/main/examples/example_data)."
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Data already exists in ./test_data/materials\n"
]
}
],
"source": [
"import os\n",
"from matgraphdb.utils.general_utils import download_test_data\n",
"\n",
"save_path = \"./test_data/materials\"\n",
"if os.path.exists(save_path) and len(os.listdir(save_path)) > 0:\n",
" print(f\"Data already exists in {save_path}\")\n",
" file_path = os.path.join(save_path, \"materials_0.parquet\")\n",
"else:\n",
" file_path = download_test_data(save_path)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Next, we can load the materials data into `MatGraphDB` on initialization. We do this by providing a `MaterialStore` instance to the `materials_store` argument."
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"MatGraphDB initialized at: MatGraphDB\n",
"============================================================\n",
"GRAPH DATABASE SUMMARY\n",
"============================================================\n",
"Name: MatGraphDB\n",
"Storage path: MatGraphDB\n",
"└── Repository structure:\n",
" ├── nodes/ (MatGraphDB\\nodes)\n",
" ├── edges/ (MatGraphDB\\edges)\n",
" ├── edge_generators/ (MatGraphDB\\edge_generators)\n",
" ├── node_generators/ (MatGraphDB\\node_generators)\n",
" └── graph/ (MatGraphDB\\graph)\n",
"\n",
"############################################################\n",
"NODE DETAILS\n",
"############################################################\n",
"Total node types: 1\n",
"------------------------------------------------------------\n",
"• Node type: materials\n",
" - Number of nodes: 1000\n",
" - Number of features: 136\n",
" - db_path: MatGraphDB\\nodes\\materials\n",
"------------------------------------------------------------\n",
"\n",
"############################################################\n",
"EDGE DETAILS\n",
"############################################################\n",
"Total edge types: 0\n",
"------------------------------------------------------------\n",
"\n",
"############################################################\n",
"NODE GENERATOR DETAILS\n",
"############################################################\n",
"Total node generators: 0\n",
"------------------------------------------------------------\n",
"\n",
"############################################################\n",
"EDGE GENERATOR DETAILS\n",
"############################################################\n",
"Total edge generators: 0\n",
"------------------------------------------------------------\n",
"\n"
]
}
],
"source": [
"import os\n",
"import shutil\n",
"\n",
"from matgraphdb import MatGraphDB, MaterialStore\n",
"\n",
"storage_path = \"MatGraphDB\"\n",
"if os.path.exists(storage_path):\n",
" shutil.rmtree(storage_path)\n",
"\n",
"materials_dir = os.path.dirname(file_path)\n",
"material_store = MaterialStore(storage_path=materials_dir)\n",
"mdb = MatGraphDB(storage_path=storage_path, materials_store=material_store)\n",
"\n",
"print(\"MatGraphDB initialized at:\", storage_path)\n",
"\n",
"print(mdb.summary())"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Generators\n",
"\n",
"A **Generator** is a callable (function) that returns a [PyArrow Table](https://arrow.apache.org/docs/python/api/table.html) of either nodes or edges. By adding a generator to `MatGraphDB`, you can:\n",
"\n",
"1. Register the generator, so it can be re-run on demand.\n",
"2. Optionally specify arguments/kwargs to pass into the generator.\n",
"3. Automatically store the output in a **NodeStore** or **EdgeStore** with the same name as the generator function (or a custom name, if you prefer).\n",
"\n",
"This is especially handy for generating nodes from external data sources or from computational routines.\n",
"\n",
"In the following sections we will create custom node and edge generators. These can be create by wrapping existing functions with the `node_generator` or `edge_generator` decorators.\n",
"\n",
"These can be imported like:\n",
"\n",
"```python\n",
"from matgraphdb import node_generator, edge_generator\n",
"```"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Element Node Generator\n",
"\n",
"\n",
"#### 1. Define the Generator\n",
"\n",
"In our first example, we will create a node generator that creates element nodes. \n",
"\n",
"As mentioned above to create a node generator, we will wrap an existing function with the `node_generator` decorator. The function name will be the name of the node type.\n",
"\n",
"```python\n",
"@node_generator\n",
"def elements():\n",
" ...\n",
"```\n",
"\n",
"For this example, we will import an existing periodic table data from the `matgraphdb` package. This is a dataframe with 118 rows representing 118 elements of the periodic table. We have also added some transformations to the data to make it more useful for our purposes."
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
" long_name symbol abundance_universe abundance_solar \\\n",
"0 Hydrogen H 7.500000e+01 7.500000e+01 \n",
"1 Helium He 2.300000e+01 2.300000e+01 \n",
"2 Lithium Li 6.000000e-07 6.000000e-09 \n",
"3 Beryllium Be 1.000000e-07 1.000000e-08 \n",
"4 Boron B 1.000000e-07 2.000000e-07 \n",
".. ... ... ... ... \n",
"113 Flerovium Fl 0.000000e+00 0.000000e+00 \n",
"114 Moscovium Mc 0.000000e+00 0.000000e+00 \n",
"115 Livermorium Lv 0.000000e+00 0.000000e+00 \n",
"116 Tennessine Ts 0.000000e+00 0.000000e+00 \n",
"117 Oganesson Og 0.000000e+00 0.000000e+00 \n",
"\n",
" abundance_meteor abundance_crust abundance_ocean abundance_human \\\n",
"0 2.400000 1.500000e-01 1.100000e+01 1.000000e+01 \n",
"1 0.000000 5.500000e-07 7.200000e-10 0.000000e+00 \n",
"2 0.000170 1.700000e-03 1.800000e-05 3.000000e-06 \n",
"3 0.000003 1.900000e-04 6.000000e-11 4.000000e-08 \n",
"4 0.000160 8.600000e-04 4.400000e-04 7.000000e-05 \n",
".. ... ... ... ... \n",
"113 0.000000 0.000000e+00 0.000000e+00 0.000000e+00 \n",
"114 0.000000 0.000000e+00 0.000000e+00 0.000000e+00 \n",
"115 0.000000 0.000000e+00 0.000000e+00 0.000000e+00 \n",
"116 0.000000 0.000000e+00 0.000000e+00 0.000000e+00 \n",
"117 0.000000 0.000000e+00 0.000000e+00 0.000000e+00 \n",
"\n",
" adiabatic_index allotropes ... \\\n",
"0 5-Jul Dihydrogen ... \n",
"1 3-May None ... \n",
"2 None None ... \n",
"3 None None ... \n",
"4 None Alpha Rhombohedral Boron, Beta Rhombohedral Bo... ... \n",
".. ... ... ... \n",
"113 None None ... \n",
"114 None None ... \n",
"115 None None ... \n",
"116 None None ... \n",
"117 None None ... \n",
"\n",
" is_halogen is_lanthanoid is_metal is_metalloid is_noble_gas \\\n",
"0 False False False False False \n",
"1 False False False False True \n",
"2 False False True False False \n",
"3 False False True False False \n",
"4 False False False True False \n",
".. ... ... ... ... ... \n",
"113 False False False False False \n",
"114 False False False False False \n",
"115 False False False False False \n",
"116 False False False False False \n",
"117 False False False False True \n",
"\n",
" is_post_transition_metal is_quadrupolar is_rare_earth_metal \\\n",
"0 False True False \n",
"1 False False False \n",
"2 False True False \n",
"3 False True False \n",
"4 False True False \n",
".. ... ... ... \n",
"113 False False False \n",
"114 False False False \n",
"115 False False False \n",
"116 False False False \n",
"117 False False False \n",
"\n",
" experimental_oxidation_states ionization_energies \n",
"0 [] [1312.0] \n",
"1 [] [2372.3, 5250.5] \n",
"2 [1] [520.2, 7298.1, 11815.0] \n",
"3 [2] [899.5, 1757.1, 14848.7, 21006.6] \n",
"4 [3] [800.6, 2427.1, 3659.7, 25025.8, 32826.7] \n",
".. ... ... \n",
"113 [2] [832.2, 1600.0, 3370.0, 4400.0, 5850.0] \n",
"114 [3] [538.3, 1760.0, 2650.0, 4680.0, 5720.0] \n",
"115 [-2] [663.9, 1330.0, 2850.0, 3810.0, 6080.0] \n",
"116 [-1] [736.9, 1435.4, 2161.9, 4012.9, 5076.4] \n",
"117 [] [860.1, 1560.0] \n",
"\n",
"[118 rows x 98 columns]\n"
]
}
],
"source": [
"import pandas as pd\n",
"from matgraphdb import node_generator\n",
"from matgraphdb.utils.config import PKG_DIR\n",
"\n",
"BASE_ELEMENT_FILE = os.path.join(\n",
" PKG_DIR, \"utils\", \"chem_utils\", \"resources\", \"imputed_periodic_table_values.parquet\"\n",
")\n",
"\n",
"\n",
"# Define the generator with the @node_generator decorator\n",
"@node_generator\n",
"def elements(base_file=BASE_ELEMENT_FILE):\n",
" \"\"\"\n",
" Creates Element nodes from a local file (CSV or Parquet).\n",
" Returns a Pandas DataFrame (or PyArrow Table) with one row per element.\n",
" \"\"\"\n",
"\n",
" try:\n",
" # Read the file\n",
" file_ext = os.path.splitext(base_file)[-1][\n",
" 1:\n",
" ].lower() # e.g. \"parquet\" or \"csv\"\n",
" if file_ext == \"parquet\":\n",
" df = pd.read_parquet(base_file)\n",
" elif file_ext == \"csv\":\n",
" df = pd.read_csv(base_file)\n",
" else:\n",
" raise ValueError(\"base_file must be a parquet or csv file\")\n",
"\n",
" # Apply some transformations\n",
" # Example transformations\n",
" df[\"oxidation_states\"] = df[\"oxidation_states\"].apply(\n",
" lambda x: x.replace(\"]\", \"\").replace(\"[\", \"\")\n",
" )\n",
" df[\"oxidation_states\"] = df[\"oxidation_states\"].apply(\n",
" lambda x: \",\".join(x.split())\n",
" )\n",
" df[\"oxidation_states\"] = df[\"oxidation_states\"].apply(\n",
" lambda x: eval(\"[\" + x + \"]\")\n",
" )\n",
" df[\"experimental_oxidation_states\"] = df[\"experimental_oxidation_states\"].apply(\n",
" lambda x: eval(x)\n",
" )\n",
" df[\"ionization_energies\"] = df[\"ionization_energies\"].apply(lambda x: eval(x))\n",
"\n",
" except Exception as e:\n",
" print(f\"Error reading element file: {e}\")\n",
" return None\n",
"\n",
" return df # Return the transformed dataframe\n",
"\n",
"\n",
"df = elements()\n",
"\n",
"print(df)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"#### 2. Add the Generator to the MatGraphDB\n",
"\n",
"Now that we have defined the generator, we can add it to the `MatGraphDB` instance. We do this by calling the `add_node_generator` method. Here we give the function, the arguments, and the kwargs. We also have the option to run the generator immediately or later. Default is True.\n",
"\n",
"The node generator will be stored in the `node_generator_store` of the `MatGraphDB` instance.\n",
"\n"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"============================================================\n",
"GENERATOR STORE SUMMARY\n",
"============================================================\n",
"• Number of generators: 1\n",
"Storage path: MatGraphDB\\node_generators\n",
"\n",
"\n",
"############################################################\n",
"METADATA\n",
"############################################################\n",
"• class: GeneratorStore\n",
"• class_module: matgraphdb.core.generator_store\n",
"\n",
"############################################################\n",
"GENERATOR DETAILS\n",
"############################################################\n",
"• Columns:\n",
" - generator_func\n",
" - generator_kwargs.base_file\n",
" - generator_name\n",
" - id\n",
"\n",
"• Generator names:\n",
" - elements\n",
"\n"
]
}
],
"source": [
"mdb.add_node_generator(\n",
" generator_func=elements,\n",
" generator_args={},\n",
" generator_kwargs={\"base_file\": BASE_ELEMENT_FILE},\n",
" run_immediately=False, # We have the option to run the generator immediately or later. Default is True.\n",
")\n",
"\n",
"# Check the node generators in the MatGraphDB\n",
"\n",
"print(mdb.node_generator_store)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Running a Node Generator Later\n",
"\n",
"Now we can run the node generator with `mdb.run_node_generator(generator_name)`.\n"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>long_name</th>\n",
" <th>symbol</th>\n",
" <th>abundance_universe</th>\n",
" <th>abundance_solar</th>\n",
" <th>abundance_meteor</th>\n",
" <th>abundance_crust</th>\n",
" <th>abundance_ocean</th>\n",
" <th>abundance_human</th>\n",
" <th>adiabatic_index</th>\n",
" <th>allotropes</th>\n",
" <th>...</th>\n",
" <th>is_halogen</th>\n",
" <th>is_lanthanoid</th>\n",
" <th>is_metal</th>\n",
" <th>is_metalloid</th>\n",
" <th>is_noble_gas</th>\n",
" <th>is_post_transition_metal</th>\n",
" <th>is_quadrupolar</th>\n",
" <th>is_rare_earth_metal</th>\n",
" <th>experimental_oxidation_states</th>\n",
" <th>ionization_energies</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>Hydrogen</td>\n",
" <td>H</td>\n",
" <td>7.500000e+01</td>\n",
" <td>7.500000e+01</td>\n",
" <td>2.400000</td>\n",
" <td>1.500000e-01</td>\n",
" <td>1.100000e+01</td>\n",
" <td>1.000000e+01</td>\n",
" <td>5-Jul</td>\n",
" <td>Dihydrogen</td>\n",
" <td>...</td>\n",
" <td>False</td>\n",
" <td>False</td>\n",
" <td>False</td>\n",
" <td>False</td>\n",
" <td>False</td>\n",
" <td>False</td>\n",
" <td>True</td>\n",
" <td>False</td>\n",
" <td>[]</td>\n",
" <td>[1312.0]</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>Helium</td>\n",
" <td>He</td>\n",
" <td>2.300000e+01</td>\n",
" <td>2.300000e+01</td>\n",
" <td>0.000000</td>\n",
" <td>5.500000e-07</td>\n",
" <td>7.200000e-10</td>\n",
" <td>0.000000e+00</td>\n",
" <td>3-May</td>\n",
" <td>None</td>\n",
" <td>...</td>\n",
" <td>False</td>\n",
" <td>False</td>\n",
" <td>False</td>\n",
" <td>False</td>\n",
" <td>True</td>\n",
" <td>False</td>\n",
" <td>False</td>\n",
" <td>False</td>\n",
" <td>[]</td>\n",
" <td>[2372.3, 5250.5]</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>Lithium</td>\n",
" <td>Li</td>\n",
" <td>6.000000e-07</td>\n",
" <td>6.000000e-09</td>\n",
" <td>0.000170</td>\n",
" <td>1.700000e-03</td>\n",
" <td>1.800000e-05</td>\n",
" <td>3.000000e-06</td>\n",
" <td>None</td>\n",
" <td>None</td>\n",
" <td>...</td>\n",
" <td>False</td>\n",
" <td>False</td>\n",
" <td>True</td>\n",
" <td>False</td>\n",
" <td>False</td>\n",
" <td>False</td>\n",
" <td>True</td>\n",
" <td>False</td>\n",
" <td>[1]</td>\n",
" <td>[520.2, 7298.1, 11815.0]</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>Beryllium</td>\n",
" <td>Be</td>\n",
" <td>1.000000e-07</td>\n",
" <td>1.000000e-08</td>\n",
" <td>0.000003</td>\n",
" <td>1.900000e-04</td>\n",
" <td>6.000000e-11</td>\n",
" <td>4.000000e-08</td>\n",
" <td>None</td>\n",
" <td>None</td>\n",
" <td>...</td>\n",
" <td>False</td>\n",
" <td>False</td>\n",
" <td>True</td>\n",
" <td>False</td>\n",
" <td>False</td>\n",
" <td>False</td>\n",
" <td>True</td>\n",
" <td>False</td>\n",
" <td>[2]</td>\n",
" <td>[899.5, 1757.1, 14848.7, 21006.6]</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>Boron</td>\n",
" <td>B</td>\n",
" <td>1.000000e-07</td>\n",
" <td>2.000000e-07</td>\n",
" <td>0.000160</td>\n",
" <td>8.600000e-04</td>\n",
" <td>4.400000e-04</td>\n",
" <td>7.000000e-05</td>\n",
" <td>None</td>\n",
" <td>Alpha Rhombohedral Boron, Beta Rhombohedral Bo...</td>\n",
" <td>...</td>\n",
" <td>False</td>\n",
" <td>False</td>\n",
" <td>False</td>\n",
" <td>True</td>\n",
" <td>False</td>\n",
" <td>False</td>\n",
" <td>True</td>\n",
" <td>False</td>\n",
" <td>[3]</td>\n",
" <td>[800.6, 2427.1, 3659.7, 25025.8, 32826.7]</td>\n",
" </tr>\n",
" <tr>\n",
" <th>...</th>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>113</th>\n",
" <td>Flerovium</td>\n",
" <td>Fl</td>\n",
" <td>0.000000e+00</td>\n",
" <td>0.000000e+00</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000e+00</td>\n",
" <td>0.000000e+00</td>\n",
" <td>0.000000e+00</td>\n",
" <td>None</td>\n",
" <td>None</td>\n",
" <td>...</td>\n",
" <td>False</td>\n",
" <td>False</td>\n",
" <td>False</td>\n",
" <td>False</td>\n",
" <td>False</td>\n",
" <td>False</td>\n",
" <td>False</td>\n",
" <td>False</td>\n",
" <td>[2]</td>\n",
" <td>[832.2, 1600.0, 3370.0, 4400.0, 5850.0]</td>\n",
" </tr>\n",
" <tr>\n",
" <th>114</th>\n",
" <td>Moscovium</td>\n",
" <td>Mc</td>\n",
" <td>0.000000e+00</td>\n",
" <td>0.000000e+00</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000e+00</td>\n",
" <td>0.000000e+00</td>\n",
" <td>0.000000e+00</td>\n",
" <td>None</td>\n",
" <td>None</td>\n",
" <td>...</td>\n",
" <td>False</td>\n",
" <td>False</td>\n",
" <td>False</td>\n",
" <td>False</td>\n",
" <td>False</td>\n",
" <td>False</td>\n",
" <td>False</td>\n",
" <td>False</td>\n",
" <td>[3]</td>\n",
" <td>[538.3, 1760.0, 2650.0, 4680.0, 5720.0]</td>\n",
" </tr>\n",
" <tr>\n",
" <th>115</th>\n",
" <td>Livermorium</td>\n",
" <td>Lv</td>\n",
" <td>0.000000e+00</td>\n",
" <td>0.000000e+00</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000e+00</td>\n",
" <td>0.000000e+00</td>\n",
" <td>0.000000e+00</td>\n",
" <td>None</td>\n",
" <td>None</td>\n",
" <td>...</td>\n",
" <td>False</td>\n",
" <td>False</td>\n",
" <td>False</td>\n",
" <td>False</td>\n",
" <td>False</td>\n",
" <td>False</td>\n",
" <td>False</td>\n",
" <td>False</td>\n",
" <td>[-2]</td>\n",
" <td>[663.9, 1330.0, 2850.0, 3810.0, 6080.0]</td>\n",
" </tr>\n",
" <tr>\n",
" <th>116</th>\n",
" <td>Tennessine</td>\n",
" <td>Ts</td>\n",
" <td>0.000000e+00</td>\n",
" <td>0.000000e+00</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000e+00</td>\n",
" <td>0.000000e+00</td>\n",
" <td>0.000000e+00</td>\n",
" <td>None</td>\n",
" <td>None</td>\n",
" <td>...</td>\n",
" <td>False</td>\n",
" <td>False</td>\n",
" <td>False</td>\n",
" <td>False</td>\n",
" <td>False</td>\n",
" <td>False</td>\n",
" <td>False</td>\n",
" <td>False</td>\n",
" <td>[-1]</td>\n",
" <td>[736.9, 1435.4, 2161.9, 4012.9, 5076.4]</td>\n",
" </tr>\n",
" <tr>\n",
" <th>117</th>\n",
" <td>Oganesson</td>\n",
" <td>Og</td>\n",
" <td>0.000000e+00</td>\n",
" <td>0.000000e+00</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000e+00</td>\n",
" <td>0.000000e+00</td>\n",
" <td>0.000000e+00</td>\n",
" <td>None</td>\n",
" <td>None</td>\n",
" <td>...</td>\n",
" <td>False</td>\n",
" <td>False</td>\n",
" <td>False</td>\n",
" <td>False</td>\n",
" <td>True</td>\n",
" <td>False</td>\n",
" <td>False</td>\n",
" <td>False</td>\n",
" <td>[]</td>\n",
" <td>[860.1, 1560.0]</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>118 rows × 98 columns</p>\n",
"</div>"
],
"text/plain": [
" long_name symbol abundance_universe abundance_solar \\\n",
"0 Hydrogen H 7.500000e+01 7.500000e+01 \n",
"1 Helium He 2.300000e+01 2.300000e+01 \n",
"2 Lithium Li 6.000000e-07 6.000000e-09 \n",
"3 Beryllium Be 1.000000e-07 1.000000e-08 \n",
"4 Boron B 1.000000e-07 2.000000e-07 \n",
".. ... ... ... ... \n",
"113 Flerovium Fl 0.000000e+00 0.000000e+00 \n",
"114 Moscovium Mc 0.000000e+00 0.000000e+00 \n",
"115 Livermorium Lv 0.000000e+00 0.000000e+00 \n",
"116 Tennessine Ts 0.000000e+00 0.000000e+00 \n",
"117 Oganesson Og 0.000000e+00 0.000000e+00 \n",
"\n",
" abundance_meteor abundance_crust abundance_ocean abundance_human \\\n",
"0 2.400000 1.500000e-01 1.100000e+01 1.000000e+01 \n",
"1 0.000000 5.500000e-07 7.200000e-10 0.000000e+00 \n",
"2 0.000170 1.700000e-03 1.800000e-05 3.000000e-06 \n",
"3 0.000003 1.900000e-04 6.000000e-11 4.000000e-08 \n",
"4 0.000160 8.600000e-04 4.400000e-04 7.000000e-05 \n",
".. ... ... ... ... \n",
"113 0.000000 0.000000e+00 0.000000e+00 0.000000e+00 \n",
"114 0.000000 0.000000e+00 0.000000e+00 0.000000e+00 \n",
"115 0.000000 0.000000e+00 0.000000e+00 0.000000e+00 \n",
"116 0.000000 0.000000e+00 0.000000e+00 0.000000e+00 \n",
"117 0.000000 0.000000e+00 0.000000e+00 0.000000e+00 \n",
"\n",
" adiabatic_index allotropes ... \\\n",
"0 5-Jul Dihydrogen ... \n",
"1 3-May None ... \n",
"2 None None ... \n",
"3 None None ... \n",
"4 None Alpha Rhombohedral Boron, Beta Rhombohedral Bo... ... \n",
".. ... ... ... \n",
"113 None None ... \n",
"114 None None ... \n",
"115 None None ... \n",
"116 None None ... \n",
"117 None None ... \n",
"\n",
" is_halogen is_lanthanoid is_metal is_metalloid is_noble_gas \\\n",
"0 False False False False False \n",
"1 False False False False True \n",
"2 False False True False False \n",
"3 False False True False False \n",
"4 False False False True False \n",
".. ... ... ... ... ... \n",
"113 False False False False False \n",
"114 False False False False False \n",
"115 False False False False False \n",
"116 False False False False False \n",
"117 False False False False True \n",
"\n",
" is_post_transition_metal is_quadrupolar is_rare_earth_metal \\\n",
"0 False True False \n",
"1 False False False \n",
"2 False True False \n",
"3 False True False \n",
"4 False True False \n",
".. ... ... ... \n",
"113 False False False \n",
"114 False False False \n",
"115 False False False \n",
"116 False False False \n",
"117 False False False \n",
"\n",
" experimental_oxidation_states ionization_energies \n",
"0 [] [1312.0] \n",
"1 [] [2372.3, 5250.5] \n",
"2 [1] [520.2, 7298.1, 11815.0] \n",
"3 [2] [899.5, 1757.1, 14848.7, 21006.6] \n",
"4 [3] [800.6, 2427.1, 3659.7, 25025.8, 32826.7] \n",
".. ... ... \n",
"113 [2] [832.2, 1600.0, 3370.0, 4400.0, 5850.0] \n",
"114 [3] [538.3, 1760.0, 2650.0, 4680.0, 5720.0] \n",
"115 [-2] [663.9, 1330.0, 2850.0, 3810.0, 6080.0] \n",
"116 [-1] [736.9, 1435.4, 2161.9, 4012.9, 5076.4] \n",
"117 [] [860.1, 1560.0] \n",
"\n",
"[118 rows x 98 columns]"
]
},
"execution_count": 6,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# Here we run the node generator. Notice how we do not need pass the arguments or kwargs, this information is stored in the node generator store.\n",
"# However, we can override the arguments or kwargs if we want to.\n",
"mdb.run_node_generator(\"elements\")"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Lets check the node store for the elements.\n"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"============================================================\n",
"NODE STORE SUMMARY\n",
"============================================================\n",
"Node type: elements\n",
"• Number of nodes: 118\n",
"• Number of features: 99\n",
"Storage path: MatGraphDB\\nodes\\elements\n",
"\n",
"\n",
"############################################################\n",
"METADATA\n",
"############################################################\n",
"• class: NodeStore\n",
"• class_module: matgraphdb.core.nodes\n",
"• node_type: elements\n",
"• name_column: id\n",
"\n",
"############################################################\n",
"NODE DETAILS\n",
"############################################################\n",
"• Columns:\n",
" - abundance_crust\n",
" - abundance_human\n",
" - abundance_meteor\n",
" - abundance_ocean\n",
" - abundance_solar\n",
" - abundance_universe\n",
" - adiabatic_index\n",
" - allotropes\n",
" - appearance\n",
" - atomic_mass\n",
" - atomic_number\n",
" - block\n",
" - boiling_point\n",
" - classifications_cas_number\n",
" - classifications_cid_number\n",
" - classifications_dot_hazard_class\n",
" - classifications_dot_numbers\n",
" - classifications_rtecs_number\n",
" - coefficient_of_linear_thermal_expansion\n",
" - conductivity_electric\n",
" - conductivity_thermal\n",
" - cpk_hex\n",
" - critical_pressure\n",
" - critical_temperature\n",
" - crystal_structure\n",
" - density_stp\n",
" - discovered_by\n",
" - discovered_location\n",
" - discovered_year\n",
" - electrical_resistivity\n",
" - electrical_type\n",
" - electron_affinity\n",
" - electron_configuration\n",
" - electron_configuration_semantic\n",
" - electronegativity_pauling\n",
" - energy_levels\n",
" - experimental_oxidation_states\n",
" - extended_group\n",
" - gas_phase\n",
" - group\n",
" - half_life\n",
" - hardness_brinell\n",
" - hardness_mohs\n",
" - hardness_vickers\n",
" - heat_fusion\n",
" - heat_molar\n",
" - heat_specific\n",
" - heat_vaporization\n",
" - id\n",
" - ionization_energies\n",
" - is_actinoid\n",
" - is_alkali\n",
" - is_alkaline\n",
" - is_chalcogen\n",
" - is_halogen\n",
" - is_lanthanoid\n",
" - is_metal\n",
" - is_metalloid\n",
" - is_noble_gas\n",
" - is_post_transition_metal\n",
" - is_quadrupolar\n",
" - is_rare_earth_metal\n",
" - isotopes_known\n",
" - isotopes_stable\n",
" - isotopic_abundances\n",
" - lattice_angles\n",
" - lattice_constants\n",
" - lifetime\n",
" - long_name\n",
" - magnetic_susceptibility_mass\n",
" - magnetic_susceptibility_molar\n",
" - magnetic_susceptibility_volume\n",
" - magnetic_type\n",
" - melting_point\n",
" - modulus_bulk\n",
" - modulus_shear\n",
" - modulus_young\n",
" - molar_volume\n",
" - neutron_cross_section\n",
" - neutron_mass_absorption\n",
" - oxidation_states\n",
" - period\n",
" - phase\n",
" - poisson_ratio\n",
" - quantum_numbers\n",
" - radius_calculated\n",
" - radius_covalent\n",
" - radius_empirical\n",
" - radius_vanderwaals\n",
" - refractive_index\n",
" - series\n",
" - source\n",
" - space_group_name\n",
" - space_group_number\n",
" - speed_of_sound\n",
" - summary\n",
" - superconduction_temperature\n",
" - symbol\n",
" - valence_electrons\n",
"\n"
]
}
],
"source": [
"element_node_store = mdb.get_node_store(\"elements\")\n",
"print(element_node_store)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Material-Element Edge Generator\n",
"\n",
"#### 1. Define the Generator\n",
"\n",
"An **edge generator** is similar to a node generator but returns a PyArrow Table describing edges. Each generated edge must have at least these fields:\n",
"\n",
"- `source_id` (int)\n",
"- `source_type` (string)\n",
"- `target_id` (int)\n",
"- `target_type` (string)\n",
"\n",
"Additionally, edge_generators must have the corresponding node_stores in the `MatGraphDB` instance as an argument. This is to ensure that the ids of the nodes are valid and in the correct node store. \n",
"\n",
"For edges we use the `edge_generator` decorator.\n"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {},
"outputs": [],
"source": [
"from matgraphdb import edge_generator\n",
"import pyarrow as pa\n",
"\n",
"\n",
"@edge_generator\n",
"def material_element_has(\n",
" material_store, element_store\n",
"): # We have the material_store and element_store as an argument\n",
" try:\n",
" connection_name = \"has\"\n",
"\n",
" # We select only the necessary columns from the node stores\n",
" material_table = material_store.read_nodes(\n",
" columns=[\"id\", \"core.material_id\", \"core.elements\"]\n",
" )\n",
" element_table = element_store.read_nodes(columns=[\"id\", \"symbol\"])\n",
"\n",
" # We rename for utility purposes\n",
" material_table = material_table.rename_columns(\n",
" {\"id\": \"source_id\", \"core.material_id\": \"material_name\"}\n",
" )\n",
" material_table = material_table.append_column(\n",
" \"source_type\", pa.array([\"material\"] * material_table.num_rows)\n",
" )\n",
"\n",
" element_table = element_table.rename_columns({\"id\": \"target_id\"})\n",
" element_table = element_table.append_column(\n",
" \"target_type\", pa.array([\"elements\"] * element_table.num_rows)\n",
" )\n",
"\n",
" # We convert the tables to pandas for easier manipulation\n",
" material_df = material_table.to_pandas()\n",
" element_df = element_table.to_pandas()\n",
"\n",
" # We create a map of the element symbols to the target_id for quick lookup\n",
" element_target_id_map = {\n",
" row[\"symbol\"]: row[\"target_id\"] for _, row in element_df.iterrows()\n",
" }\n",
"\n",
" # We create a dictionary to store the edge data\n",
" table_dict = {\n",
" \"source_id\": [],\n",
" \"source_type\": [],\n",
" \"target_id\": [],\n",
" \"target_type\": [],\n",
" \"edge_type\": [],\n",
" \"name\": [],\n",
" \"weight\": [],\n",
" }\n",
"\n",
" # We iterate over the material nodes\n",
" for _, row in material_df.iterrows():\n",
" # We get the elements composing the material\n",
" elements = row[\"core.elements\"]\n",
" source_id = row[\"source_id\"]\n",
" material_name = row[\"material_name\"]\n",
" if elements is None:\n",
" continue\n",
"\n",
" # We iterate over the elements\n",
" for element in elements:\n",
" # We get the target_id for the element\n",
" target_id = element_target_id_map[element]\n",
"\n",
" # We append the edge data to the dictionary. Here we could also define the reverse edge as well.\n",
" table_dict[\"source_id\"].append(source_id)\n",
" table_dict[\"source_type\"].append(material_store.node_type)\n",
" table_dict[\"target_id\"].append(target_id)\n",
" table_dict[\"target_type\"].append(element_store.node_type)\n",
" table_dict[\"edge_type\"].append(connection_name)\n",
"\n",
" name = f\"{material_name}_{connection_name}_{element}\"\n",
" table_dict[\"name\"].append(name)\n",
" table_dict[\"weight\"].append(1.0)\n",
"\n",
" # edge_table = ParquetDB.construct_table(table_dict)\n",
"\n",
" # logger.debug(\n",
" # f\"Created material-element-has relationships. Shape: {edge_table.shape}\"\n",
" # )\n",
" df = pd.DataFrame(table_dict)\n",
" except Exception as e:\n",
" print(f\"Error creating material-element-has relationships: {e}\")\n",
"\n",
" return df"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"#### 2. Add the Generator to the MatGraphDB\n",
"\n",
"Now that we have defined the generator, we can add it to the `MatGraphDB` instance. We do this by calling the `add_edge_generator` method.\n",
"\n",
"The edge generator will be stored in the `edge_generator_store` of the `MatGraphDB` instance.\n"
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {},
"outputs": [],
"source": [
"element_store = mdb.get_node_store(\"elements\")\n",
"material_store = mdb.get_node_store(\"materials\")\n",
"\n",
"mdb.add_edge_generator(\n",
" generator_func=material_element_has,\n",
" generator_args={\n",
" \"material_store\": material_store,\n",
" \"element_store\": element_store,\n",
" },\n",
" generator_kwargs={},\n",
" run_immediately=True,\n",
")"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Lets check the edge generator store."
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"============================================================\n",
"GENERATOR STORE SUMMARY\n",
"============================================================\n",
"• Number of generators: 1\n",
"Storage path: MatGraphDB\\edge_generators\n",
"\n",
"\n",
"############################################################\n",
"METADATA\n",
"############################################################\n",
"• class: GeneratorStore\n",
"• class_module: matgraphdb.core.generator_store\n",
"\n",
"############################################################\n",
"GENERATOR DETAILS\n",
"############################################################\n",
"• Columns:\n",
" - generator_args.element_store\n",
" - generator_args.material_store\n",
" - generator_func\n",
" - generator_name\n",
" - id\n",
"\n",
"• Generator names:\n",
" - material_element_has\n",
"\n"
]
}
],
"source": [
"print(mdb.edge_generator_store)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Let's check to see if the edge created the edges in the edge store."
]
},
{
"cell_type": "code",
"execution_count": 11,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"============================================================\n",
"EDGE STORE SUMMARY\n",
"============================================================\n",
"Edge type: material_element_has\n",
"• Number of edges: 3348\n",
"• Number of features: 8\n",
"Storage path: MatGraphDB\\edges\\material_element_has\n",
"\n",
"\n",
"############################################################\n",
"METADATA\n",
"############################################################\n",
"• class: EdgeStore\n",
"• class_module: matgraphdb.core.edges\n",
"\n",
"############################################################\n",
"EDGE DETAILS\n",
"############################################################\n",
"• Columns:\n",
" - edge_type\n",
" - id\n",
" - name\n",
" - source_id\n",
" - source_type\n",
" - target_id\n",
" - target_type\n",
" - weight\n",
"\n"
]
}
],
"source": [
"edge_store = mdb.get_edge_store(\"material_element_has\")\n",
"print(edge_store)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Updates to node stores.\n",
"\n",
"By default, when node and edge generators are added their argument store dependencies are added to the `MatGraphDB` instance. This means that when parent stores are updated, the geneator will run and update their corresponding stores.\n",
"\n",
"These stores are stored in the `MatGraphDB/generator_dependency.json` file.\n"
]
},
{
"cell_type": "code",
"execution_count": 12,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
" id\n",
"0 0\n",
"2025-02-11 10:52:11 - matgraphdb.materials.nodes.materials - INFO - Deleting data [0]\n",
"2025-02-11 10:52:11 - matgraphdb.materials.nodes.materials - INFO - Data deleted successfully.\n",
"2025-02-11 10:52:11 - matgraphdb.core.graph_db - INFO - Running dependent generators: materials\n",
"2025-02-11 10:52:11 - matgraphdb.core.graph_db - INFO - Running dependent generator: material_element_has\n",
"2025-02-11 10:52:12 - matgraphdb.core.graph_db - INFO - Removing existing edge store: material_element_has\n",
"2025-02-11 10:52:12 - matgraphdb.core.graph_db - INFO - Removing edge store of type material_element_has\n",
"2025-02-11 10:52:12 - matgraphdb.core.graph_db - INFO - Running dependent generators: material_element_has\n",
"2025-02-11 10:52:12 - matgraphdb.core.graph_db - INFO - Creating edges of type 'material_element_has'\n",
"2025-02-11 10:52:12 - matgraphdb.core.graph_db - INFO - Creating new EdgeStore for type: material_element_has\n",
"2025-02-11 10:52:12 - matgraphdb.core.edges - INFO - Successfully created edges\n",
"2025-02-11 10:52:12 - matgraphdb.core.graph_db - INFO - Running dependent generators: material_element_has\n",
"2025-02-11 10:52:12 - matgraphdb.core.graph_db - INFO - Running dependent generators: material_element_has\n",
"2025-02-11 10:52:12 - matgraphdb.materials.core - INFO - Reading materials.\n",
"Empty DataFrame\n",
"Columns: [id]\n",
"Index: []\n"
]
}
],
"source": [
"materials_df = mdb.read_materials(columns=[\"id\"], ids=[0]).to_pandas()\n",
"print(materials_df)\n",
"\n",
"mdb.delete_materials(ids=[0])\n",
"\n",
"materials_df = mdb.read_materials(columns=[\"id\"], ids=[0]).to_pandas()\n",
"print(materials_df)"
]
},
{
"cell_type": "code",
"execution_count": 13,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"============================================================\n",
"EDGE STORE SUMMARY\n",
"============================================================\n",
"Edge type: material_element_has\n",
"• Number of edges: 3345\n",
"• Number of features: 8\n",
"Storage path: MatGraphDB\\edges\\material_element_has\n",
"\n",
"\n",
"############################################################\n",
"METADATA\n",
"############################################################\n",
"• class: EdgeStore\n",
"• class_module: matgraphdb.core.edges\n",
"\n",
"############################################################\n",
"EDGE DETAILS\n",
"############################################################\n",
"• Columns:\n",
" - edge_type\n",
" - id\n",
" - name\n",
" - source_id\n",
" - source_type\n",
" - target_id\n",
" - target_type\n",
" - weight\n",
"\n"
]
}
],
"source": [
"edge_store = mdb.get_edge_store(\"material_element_has\")\n",
"print(edge_store)"
]
},
{
"cell_type": "code",
"execution_count": 14,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
" edge_type id name source_id source_type target_id \\\n",
"0 has 0 mp-1222351_has_F 1 materials 8 \n",
"1 has 1 mp-1222351_has_Fe 1 materials 25 \n",
"2 has 2 mp-1222351_has_Li 1 materials 2 \n",
"3 has 3 mp-651087_has_F 2 materials 8 \n",
"4 has 4 mp-651087_has_Gd 2 materials 63 \n",
"... ... ... ... ... ... ... \n",
"3340 has 3340 mp-2714707_has_Al 999 materials 12 \n",
"3341 has 3341 mp-2714707_has_Na 999 materials 10 \n",
"3342 has 3342 mp-2714707_has_O 999 materials 7 \n",
"3343 has 3343 mp-2714707_has_S 999 materials 15 \n",
"3344 has 3344 mp-2714707_has_Zn 999 materials 29 \n",
"\n",
" target_type weight \n",
"0 elements 1.0 \n",
"1 elements 1.0 \n",
"2 elements 1.0 \n",
"3 elements 1.0 \n",
"4 elements 1.0 \n",
"... ... ... \n",
"3340 elements 1.0 \n",
"3341 elements 1.0 \n",
"3342 elements 1.0 \n",
"3343 elements 1.0 \n",
"3344 elements 1.0 \n",
"\n",
"[3345 rows x 8 columns]\n"
]
}
],
"source": [
"df = edge_store.read_edges().to_pandas()\n",
"print(df)"
]
},
{
"cell_type": "code",
"execution_count": 15,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"============================================================\n",
"GRAPH DATABASE SUMMARY\n",
"============================================================\n",
"Name: MatGraphDB\n",
"Storage path: MatGraphDB\n",
"└── Repository structure:\n",
" ├── nodes/ (MatGraphDB\\nodes)\n",
" ├── edges/ (MatGraphDB\\edges)\n",
" ├── edge_generators/ (MatGraphDB\\edge_generators)\n",
" ├── node_generators/ (MatGraphDB\\node_generators)\n",
" └── graph/ (MatGraphDB\\graph)\n",
"\n",
"############################################################\n",
"NODE DETAILS\n",
"############################################################\n",
"Total node types: 2\n",
"------------------------------------------------------------\n",
"• Node type: materials\n",
" - Number of nodes: 999\n",
" - Number of features: 136\n",
" - Columns:\n",
" - bonding.cutoff_method.bond_connections\n",
" - bonding.electric_consistent.bond_connections\n",
" - bonding.electric_consistent.bond_orders\n",
" - bonding.geometric_consistent.bond_connections\n",
" - bonding.geometric_consistent.bond_orders\n",
" - bonding.geometric_electric_consistent.bond_connections\n",
" - bonding.geometric_electric_consistent.bond_orders\n",
" - chargemol.bond_connections\n",
" - chargemol.bond_orders\n",
" - chargemol.cubed_moments\n",
" - chargemol.fourth_moments\n",
" - chargemol.squared_moments\n",
" - chemenv.coordination_environments_multi_weight\n",
" - chemenv.coordination_multi_connections\n",
" - chemenv.coordination_multi_numbers\n",
" - core.atomic_numbers\n",
" - core.cartesian_coords\n",
" - core.density\n",
" - core.density_atomic\n",
" - core.elements\n",
" - core.energy_per_atom\n",
" - core.formula\n",
" - core.formula_pretty\n",
" - core.frac_coords\n",
" - core.is_gap_direct\n",
" - core.is_magnetic\n",
" - core.is_metal\n",
" - core.is_stable\n",
" - core.lattice\n",
" - core.material_id\n",
" - core.nelements\n",
" - core.nsites\n",
" - core.species\n",
" - core.volume\n",
" - dielectric.e_electronic\n",
" - dielectric.e_ij_max\n",
" - dielectric.e_ionic\n",
" - dielectric.e_total\n",
" - dielectric.n\n",
" - elasticity.compliance_tensor_ieee_format\n",
" - elasticity.compliance_tensor_raw\n",
" - elasticity.debye_temperature\n",
" - elasticity.elastic_tensor_ieee_format\n",
" - elasticity.elastic_tensor_raw\n",
" - elasticity.g_reuss\n",
" - elasticity.g_voigt\n",
" - elasticity.g_vrh\n",
" - elasticity.homogeneous_poisson\n",
" - elasticity.k_reuss\n",
" - elasticity.k_voigt\n",
" - elasticity.k_vrh\n",
" - elasticity.order\n",
" - elasticity.sound_velocity_acoustic\n",
" - elasticity.sound_velocity_longitudinal\n",
" - elasticity.sound_velocity_optical\n",
" - elasticity.sound_velocity_total\n",
" - elasticity.sound_velocity_transverse\n",
" - elasticity.state\n",
" - elasticity.thermal_conductivity_cahill\n",
" - elasticity.thermal_conductivity_clarke\n",
" - elasticity.universal_anisotropy\n",
" - elasticity.warnings\n",
" - elasticity.young_modulus\n",
" - electronic_structure.band_gap\n",
" - electronic_structure.cbm\n",
" - electronic_structure.dos_energy_up\n",
" - electronic_structure.efermi\n",
" - electronic_structure.vbm\n",
" - feature_vectors.element_fraction\n",
" - feature_vectors.element_property\n",
" - feature_vectors.sine_coulomb_matrix\n",
" - feature_vectors.xrd_pattern\n",
" - grain_boundaries.grain_boundaries\n",
" - has_props.absorption\n",
" - has_props.bandstructure\n",
" - has_props.charge_density\n",
" - has_props.chemenv\n",
" - has_props.dielectric\n",
" - has_props.dos\n",
" - has_props.elasticity\n",
" - has_props.electronic_structure\n",
" - has_props.eos\n",
" - has_props.grain_boundaries\n",
" - has_props.insertion_electrodes\n",
" - has_props.magnetism\n",
" - has_props.materials\n",
" - has_props.oxi_states\n",
" - has_props.phonon\n",
" - has_props.piezoelectric\n",
" - has_props.provenance\n",
" - has_props.substrates\n",
" - has_props.surface_properties\n",
" - has_props.thermo\n",
" - has_props.xas\n",
" - id\n",
" - magnetism.num_magnetic_sites\n",
" - magnetism.num_unique_magnetic_sites\n",
" - magnetism.ordering\n",
" - magnetism.total_magnetization\n",
" - magnetism.total_magnetization_normalized_vol\n",
" - magnetism.types_of_magnetic_species\n",
" - metadata.last_updated\n",
" - metadata.theoretical\n",
" - oxidation_states.method\n",
" - oxidation_states.possible_species\n",
" - oxidation_states.possible_valences\n",
" - structure.@class\n",
" - structure.@module\n",
" - structure.charge\n",
" - structure.lattice.a\n",
" - structure.lattice.alpha\n",
" - structure.lattice.b\n",
" - structure.lattice.beta\n",
" - structure.lattice.c\n",
" - structure.lattice.gamma\n",
" - structure.lattice.matrix\n",
" - structure.lattice.pbc\n",
" - structure.lattice.volume\n",
" - structure.sites\n",
" - surface_properties.shape_factor\n",
" - surface_properties.surface_anisotropy\n",
" - surface_properties.weighted_surface_energy\n",
" - surface_properties.weighted_surface_energy_EV_PER_ANG2\n",
" - surface_properties.weighted_work_function\n",
" - symmetry.crystal_system\n",
" - symmetry.number\n",
" - symmetry.point_group\n",
" - symmetry.symbol\n",
" - symmetry.symprec\n",
" - symmetry.version\n",
" - symmetry.wyckoffs\n",
" - thermo.decomposes_to\n",
" - thermo.energy_above_hull\n",
" - thermo.equilibrium_reaction_energy_per_atom\n",
" - thermo.formation_energy_per_atom\n",
" - thermo.uncorrected_energy_per_atom\n",
" - db_path: MatGraphDB\\nodes\\materials\n",
"------------------------------------------------------------\n",
"• Node type: elements\n",
" - Number of nodes: 118\n",
" - Number of features: 99\n",
" - Columns:\n",
" - abundance_crust\n",
" - abundance_human\n",
" - abundance_meteor\n",
" - abundance_ocean\n",
" - abundance_solar\n",
" - abundance_universe\n",
" - adiabatic_index\n",
" - allotropes\n",
" - appearance\n",
" - atomic_mass\n",
" - atomic_number\n",
" - block\n",
" - boiling_point\n",
" - classifications_cas_number\n",
" - classifications_cid_number\n",
" - classifications_dot_hazard_class\n",
" - classifications_dot_numbers\n",
" - classifications_rtecs_number\n",
" - coefficient_of_linear_thermal_expansion\n",
" - conductivity_electric\n",
" - conductivity_thermal\n",
" - cpk_hex\n",
" - critical_pressure\n",
" - critical_temperature\n",
" - crystal_structure\n",
" - density_stp\n",
" - discovered_by\n",
" - discovered_location\n",
" - discovered_year\n",
" - electrical_resistivity\n",
" - electrical_type\n",
" - electron_affinity\n",
" - electron_configuration\n",
" - electron_configuration_semantic\n",
" - electronegativity_pauling\n",
" - energy_levels\n",
" - experimental_oxidation_states\n",
" - extended_group\n",
" - gas_phase\n",
" - group\n",
" - half_life\n",
" - hardness_brinell\n",
" - hardness_mohs\n",
" - hardness_vickers\n",
" - heat_fusion\n",
" - heat_molar\n",
" - heat_specific\n",
" - heat_vaporization\n",
" - id\n",
" - ionization_energies\n",
" - is_actinoid\n",
" - is_alkali\n",
" - is_alkaline\n",
" - is_chalcogen\n",
" - is_halogen\n",
" - is_lanthanoid\n",
" - is_metal\n",
" - is_metalloid\n",
" - is_noble_gas\n",
" - is_post_transition_metal\n",
" - is_quadrupolar\n",
" - is_rare_earth_metal\n",
" - isotopes_known\n",
" - isotopes_stable\n",
" - isotopic_abundances\n",
" - lattice_angles\n",
" - lattice_constants\n",
" - lifetime\n",
" - long_name\n",
" - magnetic_susceptibility_mass\n",
" - magnetic_susceptibility_molar\n",
" - magnetic_susceptibility_volume\n",
" - magnetic_type\n",
" - melting_point\n",
" - modulus_bulk\n",
" - modulus_shear\n",
" - modulus_young\n",
" - molar_volume\n",
" - neutron_cross_section\n",
" - neutron_mass_absorption\n",
" - oxidation_states\n",
" - period\n",
" - phase\n",
" - poisson_ratio\n",
" - quantum_numbers\n",
" - radius_calculated\n",
" - radius_covalent\n",
" - radius_empirical\n",
" - radius_vanderwaals\n",
" - refractive_index\n",
" - series\n",
" - source\n",
" - space_group_name\n",
" - space_group_number\n",
" - speed_of_sound\n",
" - summary\n",
" - superconduction_temperature\n",
" - symbol\n",
" - valence_electrons\n",
" - db_path: MatGraphDB\\nodes\\elements\n",
"------------------------------------------------------------\n",
"\n",
"############################################################\n",
"EDGE DETAILS\n",
"############################################################\n",
"Total edge types: 1\n",
"------------------------------------------------------------\n",
"• Edge type: material_element_has\n",
" - Number of edges: 3345\n",
" - Number of features: 8\n",
" - Columns:\n",
" - edge_type\n",
" - id\n",
" - name\n",
" - source_id\n",
" - source_type\n",
" - target_id\n",
" - target_type\n",
" - weight\n",
" - db_path: MatGraphDB\\edges\\material_element_has\n",
"------------------------------------------------------------\n",
"\n",
"############################################################\n",
"NODE GENERATOR DETAILS\n",
"############################################################\n",
"Total node generators: 1\n",
"------------------------------------------------------------\n",
"• Generator: elements\n",
"Generator Args:\n",
" - generator_func: [<function wrapper at 0x00000273649D3790>]\n",
" - generator_kwargs.base_file: ['C:\\\\Users\\\\lllang\\\\Desktop\\\\Current_Projects\\\\MatGraphDB\\\\matgraphdb\\\\utils\\\\chem_utils\\\\resources\\\\imputed_periodic_table_values.parquet']\n",
" - generator_name: ['elements']\n",
" - id: [0]\n",
"Generator Kwargs:\n",
" - base_file: ['C:\\\\Users\\\\lllang\\\\Desktop\\\\Current_Projects\\\\MatGraphDB\\\\matgraphdb\\\\utils\\\\chem_utils\\\\resources\\\\imputed_periodic_table_values.parquet']\n",
"------------------------------------------------------------\n",
"\n",
"############################################################\n",
"EDGE GENERATOR DETAILS\n",
"############################################################\n",
"Total edge generators: 1\n",
"------------------------------------------------------------\n",
"• Generator: material_element_has\n",
"Generator Args:\n",
" - element_store: MatGraphDB\\nodes\\elements\n",
" - material_store: MatGraphDB\\nodes\\materials\n",
"Generator Kwargs:\n",
"------------------------------------------------------------\n",
"\n"
]
}
],
"source": [
"print(mdb)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## 6. Summary\n",
"\n",
"In this notebook, we showed how to define custom node and edge generators and showed how to run them."
]
}
],
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