Source code for mantidimaging.helper

# Copyright (C) 2024 ISIS Rutherford Appleton Laboratory UKRI
# SPDX - License - Identifier: GPL-3.0-or-later
Module for commonly used functions across the modules.
from __future__ import annotations

import logging
import sys
from datetime import datetime
from pathlib import Path

from PyQt5.QtCore import QSettings

from import ImageStack

[docs] def initialise_logging(arg_level: str) -> None: log_formatter = logging.Formatter("%(asctime)s [%(name)s:L%(lineno)d] %(levelname)s: %(message)s") settings = QSettings() setting_level = settings.value("logging/log_level", defaultValue="INFO") if arg_level: log_level = logging.getLevelName(arg_level) else: log_level = logging.getLevelName(setting_level) # Capture all warnings logging.captureWarnings(True) # Remove default handlers root_logger = logging.getLogger() root_logger.handlers = [] # Stdout handler console_handler = logging.StreamHandler(sys.stdout) console_handler.setFormatter(log_formatter) root_logger.addHandler(console_handler) # File handler log_directory = Path(settings.value("logging/log_dir", defaultValue="")) if log_directory != Path(""): filename = f"mantid_imaging_{'%Y-%m-%d_%H-%M-%S')}.log" if not log_directory.exists(): log_directory.mkdir() file_log = logging.FileHandler(log_directory / filename) file_log.setFormatter(log_formatter) root_logger.addHandler(file_log) # Default log level for mantidimaging only logging.getLogger('mantidimaging').setLevel(log_level) perf_logger = logging.getLogger('perf') perf_logger.setLevel(100) perf_logger.propagate = False if settings.value("logging/performance_log", defaultValue=False, type=bool): perf_logger.setLevel(1) perf_logger.addHandler(console_handler) if log_directory != Path(""): perf_logger.addHandler(file_log)
[docs] def check_data_stack(data, expected_dims=3, expected_class=ImageStack): """ Make sure the data has expected dimensions and class. """ if data is None: raise ValueError("Data is a None type.") if not isinstance(data, expected_class): raise ValueError( f"Invalid data type. It must be an {expected_class.__name__} object. Instead found: {type(data).__name__}") if expected_dims != raise ValueError(f"Invalid data format. It does not have 3 dimensions. Shape: {}")