Delete sas_temper

#!/usr/bin/env python

r"""

sas_temper

__main__.py:  this is where the action happens

Oak Ridge National Laboratory, 2020

"""

import sys

import copy

import time as tm

import os

import numpy as np

# these are from this particular project

import sas_temper.sas_temper_config as sa_config

import sas_temper.modelconfig as modelconfig

import sas_temper.parse_conf as parse_conf

import sas_temper.output as output

import sas_temper.sas_temper_engine as engine

import sas_temper.sas_data as sas_data

# will need to import material from sasview.src.sas.sascalc directories

#   the directories are all useful, but are not simple files in themselves

 # see if the program has been called correctly

if len(sys.argv) < 2:

    raise Exception("No configuration file was specified")

# parse the configuration file for the parameters

#modelConf = modelconfig.ModelConfig()

#sasTemperConf = sa_config.SAConfiguration()

sasTemperConf, modelConf = parse_conf.parse_config(sys.argv[1])

# Get the data from the data file

experimentalData = sas_data.SAData(sasTemperConf.datafile,sasTemperConf.qmin,sasTemperConf.qmax)

# This is the outer control loop to generate the set of results

results = np.empty(sasTemperConf.models, "object")

models = np.empty(sasTemperConf.models, "object")

models_usm = np.empty(sasTemperConf.models, "object")

# seed the random number generator

np.random.seed(int(tm.time()) + int(os.getpid()))

# this loop creates the set of models

for i in range(0,sasTemperConf.models):

    results[i], models[i], models_usm[i] = engine.sa_control(sasTemperConf,modelConf,experimentalData)

    #output the results of the single fitting

    output.outputSingleRes(sasTemperConf, experimentalData, models[i], i, results[i])

# and output the analysis of the set of models found

output.outputSetRes(sasTemperConf, results)