本文整理汇总了Python中status.Status.load_backup方法的典型用法代码示例。如果您正苦于以下问题：Python Status.load_backup方法的具体用法？Python Status.load_backup怎么用？Python Status.load_backup使用的例子？那么恭喜您, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类status.Status的用法示例。
在下文中一共展示了Status.load_backup方法的1个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的Python代码示例。
示例1: __init__
# 需要导入模块: from status import Status [as 别名]
# 或者: from status.Status import load_backup [as 别名]
class Train:
def __init__(self, cfg, default_ans=False, backup=False, logged=False):
self.workingdir = os.path.dirname(os.path.realpath(sys.argv[0]))
# some mappings
self.tree_organism_map = {} # node --> list of organisms which were mapped to that node
self.organism_tree_map = {} # organism --> closest node on the tree
self.organism_file_map = {} # organism --> list of files including sequences
self.organisms = set() # all organisms available
self.nodes = [] # selected organisms = nodes on the taxonomic tree
self.genomes_excluded = [] # genomes that have not been considered during computation
self.organisms_invalid = set() # organisms with a lack of mapping // or that have been mapped to the root
self.sqlite_taxonomy = None # SQLite database including the NCBI taxonomy
self.config = cfg # contains all settings
# # # # # # # Advanced training options # # # # # # # # # # # # # #
# learning
self.loss_function = 1 # 0:0/1 loss, 1:path loss
self.z_standardization = 1 # 0:no standardization, 1:z standardization
self.misc_nodes = 1 # 0:no misc nodes, 1:add misc nodes
self.n_frags_per_node = 0.0 # number of fragments per node
self.yes = default_ans # say yes to every question?
self.tree_file = ""
self.backup = backup
self.stat = None
self.backupdir = None
if not logged:
# this will write a file to cwd
logmethods.initialise('train.log')
self.log = logging.getLogger('train') # better root ?
def from_backup(self, backupdir):
assert os.path.isdir(backupdir)
my_log = logging.getLogger('backup')
if self.backup:
my_log.warning('The backup will be produced but can not be used for another run.')
self.stat = Status(logged=True)
try:
self.stat.load_backup(backupdir)
except SystemExit:
my_log.critical('Could not load backup from:\n{}'.format(backupdir))
sys.exit(1)
pipeline_position = self.stat.variables["status"]
if pipeline_position == 6:
my_log.critical("Please re-run the pipeline.. "
"There is no secure way to find the correct point to start from")
sys.exit(1)
# init all variables
for variable_name in self.stat.variables:
val = self.stat.variables[variable_name]
setattr(self, variable_name, val) # same as self.variable_name = val
self.sqlite_taxonomy = taxonomy_ncbi.TaxonomyNcbi(self.config.ncbi_tax_db)
if pipeline_position < 1:
self.process_ncbi()
if pipeline_position < 2:
self.tree_process()
if pipeline_position < 3:
self.map_genomes_on_tree()
if pipeline_position < 4:
self.generate_seq(done_files=self.stat.files.keys())
if pipeline_position < 5:
self.sample_specific(done_files=self.stat.files.keys())
if pipeline_position < 6:
self.generate_kmer_features()
if pipeline_position < 7:
self.build_models()
def main_processing(self):
"""
all steps of the training pipeline
- processing ncbi sequences
- tree processing (copying newick tree or building tree from a clade list)
- mapping genomes on this tree
- generating fragments from the sequences
- dealing with sample specific data
- generating kmer features
- building models
"""
if not self.config.settings["only_models"]:
# if you do not want to build only models, check if the project directory is empty
if len(os.listdir(self.config.settings["project_dir"])) != 0:
self.log.warning("The project directory is not empty, this can result in unpredictable behavior.")
if self.yes:
answer = "y"
#.........这里部分代码省略.........