#!/usr/bin/env python
"""
usage: %prog bed_file_1 bed_file_2 out_file
    -1, --cols1=N,N,N,N: Columns for chr, start, end, strand in first file
    -2, --cols2=N,N,N,N,N: Columns for chr, start, end, strand, name/value in second file
"""

import collections
import sys
#import numpy
from galaxy import eggs
import pkg_resources
pkg_resources.require( "bx-python" )
from galaxy.tools.util.galaxyops import *
from bx.cookbook import doc_optparse


#export PYTHONPATH=~/galaxy/lib/
#running command python WeightedAverage.py interval_interpolate.bed value_interpolate.bed interpolate_result.bed

def stop_err(msg):
    sys.stderr.write(msg)
    sys.exit()


def FindRate(chromosome, start_stop, dictType):
    OverlapList = []
    for tempO in dictType[chromosome]:
        DatabaseInterval = [tempO[0], tempO[1]]
        Overlap = GetOverlap( start_stop, DatabaseInterval )
        if Overlap > 0:
            OverlapList.append([Overlap, tempO[2]])
    
    if len(OverlapList) > 0:
        SumRecomb = 0
        SumOverlap = 0
        for member in OverlapList:
            SumRecomb += member[0]*member[1]
            SumOverlap += member[0]
        averageRate = SumRecomb/SumOverlap
        return averageRate
    else:
        return 'NA'


def GetOverlap(a, b):
    return min(a[1], b[1])-max(a[0], b[0])


options, args = doc_optparse.parse( __doc__ )

try:
    chr_col_1, start_col_1, end_col_1, strand_col1 = parse_cols_arg( options.cols1 )
    chr_col_2, start_col_2, end_col_2, strand_col2, name_col_2 = parse_cols_arg( options.cols2 )
    input1, input2, input3 = args
except Exception, eee:
    print eee
    stop_err( "Data issue: click the pencil icon in the history item to correct the metadata attributes." )

fd2 = open(input2)
lines2 = fd2.readlines()
RecombChrDict = collections.defaultdict(list)

skipped = 0
for line in lines2:
    temp = line.strip().split()
    try:
        assert float(temp[int(name_col_2)])
    except:
        skipped += 1
        continue
    tempIndex = [int(temp[int(start_col_2)]), int(temp[int(end_col_2)]), float(temp[int(name_col_2)])]
    RecombChrDict[temp[int(chr_col_2)]].append(tempIndex)

print "Skipped %d features with invalid values" % (skipped)

fd1 = open(input1)
lines = fd1.readlines()
finalProduct = ''
for line in lines:
    temp = line.strip().split('\t')
    chromosome = temp[int(chr_col_1)]
    start = int(temp[int(start_col_1)])
    stop = int(temp[int(end_col_1)])
    start_stop = [start, stop]
    RecombRate = FindRate( chromosome, start_stop, RecombChrDict )
    try:
        RecombRate = "%.4f" % (float(RecombRate))
    except:
        RecombRate = RecombRate
    finalProduct += line.strip()+'\t'+str(RecombRate)+'\n'
fdd = open(input3, 'w')
fdd.writelines(finalProduct)
fdd.close()