import os import re import numpy as np import pandas as pd def get_external_lib(): script_dir = os.path.dirname(os.path.abspath(__file__)) # パスは XRD_GUI.py から見た相対パスに注意 module_path = os.path.join(os.path.dirname(script_dir), "XRD_GUI_lib.py") if os.path.isfile(module_path): import importlib.util spec = importlib.util.spec_from_file_location("XRD_GUI_lib", module_path) lib = importlib.util.module_from_spec(spec) spec.loader.exec_module(lib) return lib print("GUI_XRD_Lib is not found") return None XRD_GUI_lib = get_external_lib() def parse_xrd_file(filepath, external_lib=None): """ XRDデータファイルを解析する（純粋なロジックのみ）。 Args: filepath (str): ファイルパス external_lib: XRD_GUI_lib オブジェクト（外部パーサーを使用する場合） Returns: tuple: (sample_name, angles, intensities, error_msg) 成功時は error_msg は None。失敗時は (None, None, None, "エラー内容") を返す。 """ sample_name = os.path.splitext(os.path.basename(filepath))[0] angles = [] intensities = [] # --- 1. 外部ライブラリ (XRD_GUI_lib) の試行 --- if external_lib is not None and hasattr(external_lib, "parse_xrd"): try: # 外部ライブラリの結果を取得 res_name, res_angles, res_intensities = external_lib.parse_xrd(filepath) return res_name, res_angles, res_intensities, None except Exception as e: # 外部エラーを記録して内蔵パーサーへ（呼び出し側に伝えるためのフラグを立てても良い） print(f"DEBUG: 外部パーサー失敗、内蔵へフォールバック: {e}") # --- 2. 内蔵パーサーロジック --- start_reading_keywords = ["Step", "ScanSpeed"] reading_data = False try: with open(filepath, 'r', encoding='utf-8', errors='ignore') as f: for line_number, line in enumerate(f): line = line.strip() if not line: continue if not reading_data: if line.startswith("Sample"): parts = line.split('\t', 1) if len(parts) > 1: sample_name = parts[1].strip() if any(keyword in line for keyword in start_reading_keywords): reading_data = True continue try: parts = line.replace(',', ' ').split() if len(parts) >= 2: angles.append(float(parts[0])) intensities.append(float(parts[1])) else: break except (ValueError, IndexError): break if not angles or not intensities: return None, None, None, f"ファイル '{os.path.basename(filepath)}' から有効な数値データを抽出できませんでした。" return sample_name, np.array(angles), np.array(intensities), None except FileNotFoundError: return None, None, None, f"ファイルが見つかりません: {filepath}" except Exception as e: return None, None, None, f"ファイルの読み込み中に予期せぬエラーが発生しました: {e}" def parse_reference_file(filepath, external_lib=None, wavelength=None): # wavelength引数を追加 if external_lib is not None and hasattr(external_lib, "parse_reference"): try: # 波長を引数に追加して呼び出す name, pos, inten, hkls, raw = external_lib.parse_reference( filepath, xmin=0.0, xmax=120.0, wavelength=wavelength ) if pos is not None and len(pos) > 0: return name, np.array(pos), np.array(inten), hkls, raw except Exception as e: print(f"外部パーサー parse_reference 失敗: {e}") return parse_reference_plaintext(filepath) def parse_reference_plaintext(filepath,external_lib=None): reference_name = os.path.splitext(os.path.basename(filepath))[0] positions = [] intensities = [] hkls = [] raw_indices = [] reading_data = False idx_2theta = None idx_I = None bad_rows = 0 total_rows = 0 def is_unit_token(tok: str) -> bool: tok = tok.strip() return tok.startswith("(") and tok.endswith(")") def to_float_safe(s: str) -> float: # 変な文字が混ざっても数値だけ抜いてfloat化 s2 = re.sub(r"[^0-9eE\+\-\.]", "", s) if s2 in ("", ".", "-", "+"): raise ValueError return float(s2) try: with open(filepath, "r", encoding="utf-8", errors="ignore") as f: for line in f: line = line.strip() if not line: continue parts = line.split() if len(parts) < 3: continue # --- ヘッダ検出 --- if (not reading_data) and ("h" in [p.lower() for p in parts]) and ("k" in [p.lower() for p in parts]) and ("l" in [p.lower() for p in parts]): header_clean = [p for p in parts if not is_unit_token(p)] header_lower = [p.lower() for p in header_clean] idx_I = None for i, p in enumerate(header_lower): if p == "i" or p == "intensity": idx_I = i break idx_2theta = None for i, p in enumerate(header_clean): pl = p.lower() if ("2θ" in p) or ("2theta" in pl) or ("theta" in pl) or ("2th" in pl): idx_2theta = i break # 2θが取れない場合は I の左を採用（あなたの形式に強い） if idx_2theta is None and idx_I is not None and idx_I - 1 >= 0: idx_2theta = idx_I - 1 # I が取れない場合は 2θ の右 if idx_I is None and idx_2theta is not None and idx_2theta + 1 < len(header_clean): idx_I = idx_2theta + 1 print(f"[Header] idx_2theta={idx_2theta}, idx_I={idx_I}, header_clean={header_clean}") reading_data = True continue if not reading_data: continue # --- データ行 --- try: h = int(parts[0]); k = int(parts[1]); l = int(parts[2]) except Exception: continue if idx_2theta is None or idx_I is None: continue # 列数不足はスキップ（breakしない） if len(parts) <= max(idx_2theta, idx_I): bad_rows += 1 continue total_rows += 1 try: pos_val = to_float_safe(parts[idx_2theta]) int_val = to_float_safe(parts[idx_I]) except Exception: bad_rows += 1 continue positions.append(pos_val) intensities.append(int_val) hkls.append(f"({h} {k} {l})") raw_indices.append({"h": h, "k": k, "l": l, "i": -(h + k)}) if not positions: print(f"[WARN] no peaks parsed: total_rows={total_rows}, bad_rows={bad_rows}") return None, None, None, None, None positions = np.array(positions, dtype=float) intensities = np.array(intensities, dtype=float) # ref表示用に正規化 maxI = float(np.max(intensities)) if intensities.size else 1.0 intensities = intensities / maxI if maxI > 0 else np.zeros_like(intensities) print(f"[Parsed] N={len(positions)} 2theta(min,max)=({positions.min():.2f},{positions.max():.2f}) bad_rows={bad_rows}") return reference_name, positions, intensities, hkls, raw_indices except Exception as e: print(f"Parse error (parse_reference_plaintext): {e}") return None, None, None, None, None