Python setup_logger示例

示例#1

from ai4materials.dataprocessing.preprocessing import prepare_dataset_STEM  ### YBC
#from ai4materials.descriptors.diffraction2d import Diffraction2D
from ai4materials.utils.utils_config import set_configs
from ai4materials.utils.utils_config import setup_logger
from ai4materials.utils.utils_crystals import create_supercell
from ai4materials.utils.utils_crystals import create_vacancies
from ai4materials.wrappers import calc_descriptor
from ai4materials.wrappers import load_descriptor
import os.path
from sklearn import preprocessing
import numpy as np
from PIL import Image

# set configs
configs = set_configs(main_folder='./')
logger = setup_logger(configs, level='INFO', display_configs=False)

# setup folder and files
dataset_folder = os.path.join(configs['io']['main_folder'], 'my_datasets')
desc_file_name = 'fcc_bcc_hcp_example'

# calculate the descriptor for the list of structures
images_list = []
targets_list = []

f_list = open("list_shuf_test.txt", 'r')
while True:
    line = f_list.readline()

    if not line:
        break

示例#2

    from ai4materials.utils.utils_config import set_configs
    from ai4materials.utils.utils_config import setup_logger
    from ai4materials.utils.utils_data_retrieval import read_ase_db
    from ai4materials.wrappers import load_descriptor
    from ai4materials.wrappers import calc_model
    from ai4materials.wrappers import calc_descriptor
    from ai4materials.descriptors.atomic_features import AtomicFeatures
    from ai4materials.descriptors.atomic_features import get_table_atomic_features
    from ai4materials.utils.utils_config import get_data_filename
    from ai4materials.visualization.viewer import read_control_file
    import numpy as np
    import pandas as pd

    # modify this path if you want to save the calculation results in another location
    configs = set_configs(main_folder='./l1_l0_example')
    logger = setup_logger(configs, level='INFO')

    # setup folder and files
    lookup_file = os.path.join(configs['io']['main_folder'], 'lookup.dat')
    materials_map_plot_file = os.path.join(configs['io']['main_folder'],
                                           'binaries_l1_l0_map_prl2015.png')

    # define descriptor - atomic features in this case
    kwargs = {'energy_unit': 'eV', 'length_unit': 'angstrom'}
    descriptor = AtomicFeatures(configs=configs, **kwargs)

    # =============================================================================
    # Descriptor calculation
    # =============================================================================

    desc_file_name = 'atomic_features_binaries'

示例#3

文件： ai4STEM_train_CNN.py 项目： yobc401/ai4STEM

from functools import partial
from ai4materials.utils.utils_config import set_configs
from ai4materials.dataprocessing.preprocessing import load_dataset_from_file
from ai4materials.models.cnn_architectures import cnn_nature_comm_ziletti2018
from ai4materials.models.cnn_architectures import cnn_architecture_ai4STEM # YBC
from ai4materials.models.cnn_nature_comm_ziletti2018 import load_datasets
from ai4materials.models.STEM_CNN_segmentation import train_neural_network #YBC
from ai4materials.utils.utils_config import setup_logger
from sklearn import preprocessing
import numpy as np
import os

configs = set_configs()
logger = setup_logger(configs, level='DEBUG', display_configs=False)
#dataset_folder = configs['io']['main_folder']
dataset_folder = os.path.join(configs['io']['main_folder'], 'my_datasets')

# =============================================================================
# Download the dataset from the online repository and load it
# =============================================================================

#x_pristine, y_pristine, dataset_info_pristine, x_vac25, y_vac25, dataset_info_vac25 = load_datasets(dataset_folder)

train_set_name = 'STEM_monocrystalline_train'
path_to_x_pristine = os.path.join(dataset_folder, train_set_name + '_x.pkl')
path_to_y_pristine = os.path.join(dataset_folder, train_set_name + '_y.pkl')
path_to_summary_pristine = os.path.join(dataset_folder, train_set_name + '_summary.json')

test_set_name = 'STEM_monocrystalline_test'
path_to_x_vac25 = os.path.join(dataset_folder, test_set_name + '_x.pkl')
path_to_y_vac25 = os.path.join(dataset_folder, test_set_name + '_y.pkl')

示例#4

    def test_setup_logger(self):
        logger = setup_logger(configs=None, level=None, display_configs=False)

        self.assertIsInstance(logger, logging.Logger)