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:
