#!/usr/bin/env python

import matplotlib.pyplot as plt

import numpy as np

import logging

import correlator

import build_corr

import pylab

import argparse

import os

import zfactor

import fakecor

from fitfunctions import * # noqa

import inspect

import sys

if __name__ == "__main__":

parser = argparse.ArgumentParser(description="Generate a fake correlator")

parser.add_argument("-o", "--output_stub", type=str, required=True,

help="stub of name to write output to")

parser.add_argument("-cfg", "--configs", type=int, required=False, default=50,

help="number of configs to make")

parser.add_argument("-t", "--times", type=int, required=False, default=20,

help="number of times")

parser.add_argument("-z", "--overlapsfile", type=str, required=True,

help="file to read the zfactors")

parser.add_argument("-m", "--masses", type=float, nargs="+", required=True,

help="list of masses for each level")

parser.add_argument("-v", "--verbose", action="store_true",

help="increase output verbosity")

args = parser.parse_args()

if args.verbose:

logging.basicConfig(format='%(levelname)s: %(message)s', level=logging.DEBUG)

logging.debug("Verbose debuging mode activated")

else:

logging.basicConfig(format='%(levelname)s: %(message)s', level=logging.INFO)

N = len(args.masses)

raw_Zs = zfactor.read_coeffs_file(args.overlapsfile)

assert len(raw_Zs)==N*N, "Length missmatch in levels and coeffs"

print raw_Zs

Zs = np.matrix(raw_Zs.identities.values.reshape((N, N))).T

print Zs

print "blah"

for i in range(N):

for j in range(N):

print "Correlator_{}{}".format(i,j)

amps = [Zs[i,level]*Zs[j,level] for level in range(N)]

print "newaps", amps

cor = fakecor.make_fake_cor(args.configs, args.times, amps, args.masses)

cor.writefullfile(args.output_stub+"{}_{}".format(i,j), comp=True)

logging.info("done")