Replace sas-temper

from distutils.core import setup

#!/usr/bin/env python

"""

sas_temper

__main__.py:  this is where the action happens

REQUIREMENTS_DOT_TXT="requirements.txt"

Oak Ridge National Laboratory, 2020

def required_packages():

    return [format_dependency(dep) for dep in requirements_txt()]

"""

def format_dependency(dependency):

    package = dependency.split('#egg=')[-1]

    return package.replace('-','==')

import sys

import copy

import time as tm

import os

import numpy as np

def requirements_txt():

    with open(REQUIREMENTS_DOT_TXT) as f:

        return f.read().splitlines()

# these are from this particular project

import sas_temper

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

def external_dependency_links():

    return filter(is_external_dependency, requirements_txt())

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

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

def is_external_dependency(dependency):

    return dependency.startswith('git')

setup(

    name='sas_temper',

    version='0.3.0',

    description='SAS data analysis using simulated annealing and reproducibility characterization.  Uses sasmodels package',

    packages=['sas_temper'],

    scripts=['scripts/sas-temper'],

    instal_requires=required_packages(),

    dependency_link=external_dependency_links(),

    package_data={'': [REQUIREMENTS_DOT_TXT]}

    )

 # 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()))

# add a little feedback to the user

print('model started:', end='', flush=True)

# 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])

    # add a little feedback to the user            

    print('#', end='', flush=True)

# and output the analysis of the set of models found

output.outputSetRes(sasTemperConf, results)

# add a little feedback to the user

print(" done")