from __future__ import print_function, division import collections import enum import numpy as np import pandas as pd from . import vartype from ajustador.helpers.loggingsystem import getlogger import logging logger = getlogger(__name__) logger.setLevel(logging.INFO) class ErrorCalc(enum.IntEnum): normal = 1 relative = 2 "If 'b' (measurement) is 0, limit to this value" RELATIVE_MAX_RATIO = 10 NAN_REPLACEMENT = 1.5 def sub_mes_dev(reca, recb): ''' Calculates difference and root over sum of squares of deviation of raca and racb. ''' logger.debug("{} {}".format(type(reca), type(recb))) if isinstance(reca, vartype.vartype): assert reca == vartype.vartype.nan return vartype.vartype.nan if isinstance(recb, vartype.vartype): assert recb == vartype.vartype.nan
import shutil import subprocess import glob import re import pickle import multiprocessing import numpy as np import cma # _features holds all feature classes. from . import loader, features as _features, fitnesses, utilities from ajustador.helpers.loggingsystem import getlogger #SRIRAM 02152018 import logging logger = getlogger(__name__) #SRIRAM 02152018 logger.setLevel(logging.INFO) def filtereddict(**kwargs): return dict((k,v) for (k,v) in kwargs.items() if v is not None) _exe = None def exe_map(single=False, do_async=False): if single and not do_async: return map else: global _exe if _exe is None: _exe = multiprocessing.Pool(multiprocessing.cpu_count() * 1) if do_async: