raw_data/material/M020/xrd_vis_mp.py

import os

from matminer.datasets import load_dataset
from mp_api.client import MPRester
from pymatgen.analysis.diffraction.xrd import XRDCalculator

import pymatviz as pmv
from pymatviz.enums import ElemColorScheme, Key
from pymatgen.symmetry.analyzer import SpacegroupAnalyzer

import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
from tqdm import tqdm

MP_API_KEY = ""
MID = ["mp-353", "mp-661", "mp-856", "mp-1000", "mp-1479", "mp-2284", "mp-2294", "mp-10044", "mp-10086", "mp-10910", "mp-18905", "mp-23231", "mp-36526", "mp-861883", "mp-862786"]

xrd_calculator = XRDCalculator(wavelength='CuKa')
patterns = {}

for mid in tqdm(MID):
    # if os.path.exists(f"{mid}-xrd.png"):
    #     print(f"{mid}-xrd.png already exists, skipping...")
    #     continue

    with MPRester(MP_API_KEY) as mpr:
        structure = mpr.get_structure_by_material_id(mid)

    sga = SpacegroupAnalyzer(structure)
    conventional_structure = sga.get_conventional_standard_structure()

    xrd_pattern = xrd_calculator.get_pattern(conventional_structure, scaled=False)
    patterns[mid] = xrd_pattern

    plt.figure(figsize=(12, 6))
    bar_width = 0.5
    x = xrd_pattern.x
    y = xrd_pattern.y / np.max(xrd_pattern.y) * 100
    plt.bar(x, y, width=bar_width, color='black')

    plt.xlabel('2 Theta (degrees)', fontsize=14)
    plt.ylabel('Intensity (a.u.)', fontsize=14)

    plt.xticks(fontsize=12)
    plt.yticks(fontsize=12)

    plt.grid(axis='y', linestyle='--', alpha=0.7)

    plt.gca().spines['top'].set_linewidth(0.5)
    plt.gca().spines['right'].set_linewidth(0.5)

    plt.tight_layout()
    plt.savefig(f"{mid}-xrd.png", dpi=300, bbox_inches='tight')
    plt.close()


for _ in tqdm(range(5)):
    mids = np.random.choice(MID, 3, replace=False)
    mids = sorted(mids)

    combined_pattern = {}
    for mid in mids:
        pattern = patterns[mid]
        for two_theta, intensity in zip(pattern.x, pattern.y):
            if two_theta in combined_pattern:
                combined_pattern[two_theta] += intensity
            else:
                combined_pattern[two_theta] = intensity

    combined_pattern_list = [(k, v) for k, v in combined_pattern.items()]
    combined_pattern_list.sort(key=lambda x: x[0])
    x = np.array([item[0] for item in combined_pattern_list])
    y = np.array([item[1] for item in combined_pattern_list])
    y = y / np.max(y) * 100

    plt.figure(figsize=(12, 6))
    bar_width = 0.5
    plt.bar(x, y, width=bar_width, color='black')

    plt.xlabel('2 Theta (degrees)', fontsize=14)
    plt.ylabel('Intensity (a.u.)', fontsize=14)

    plt.xticks(fontsize=12)
    plt.yticks(fontsize=12)

    plt.grid(axis='y', linestyle='--', alpha=0.7)

    plt.gca().spines['top'].set_linewidth(0.5)
    plt.gca().spines['right'].set_linewidth(0.5)

    plt.tight_layout()
    plt.savefig(f"{'_'.join(mids)}-xrd.png", dpi=300, bbox_inches='tight')
    plt.close()