# Path: lib/util.py
# STATUS_NORMAL=1
# STATUS_MAX_MEMORY_EXCEEDED=2
# STATUS_MAX_RUNTIME_EXCEEDED=3
# MAX_LEN_OUT = 10000
# def runAndMeasure(command,detailed=True,maxtime=0,maxmem=0):
# def runSimple(command):
# def runAndMeasureInternal(return_queue,command,maxtime=0,maxmem=0):
# def runInternal(control_queue,command,max_memory):
# def measureProcess(queue, initial_pids, command, measurement_interval=1, max_runtime=0, max_memory=0, debug=False):
# 	def extendTargets(targets, proc):
# 	def killTargets(targets):
# 	def updateTargets(targets, metrics):
# 	def updateMetrics(target, metrics):
# def loadConfig(name, parent_dir="", already_included=[]):
# def setCallDir(d):
# def setRootDir(d):
# def enterCallDir():
# def enterRootDir():
# def getRootDir():
# def nl2br(text):
# def msg(text="", level=1):
# def yes_no(b):
# def md5(text):
# def merge(x, y):
# def formatFilesize(n):
# def percent(val, base, offset=0):
# def abs_path(path):
# def get_sam_header_line_count(filename):
# def is_sam_sorted(filename):
# def sort_sam(filename,threads=1):
# def sort_sam_picard(filename,threads=-1):
# def line_count(filename):
# def sanitize_string(s):
# def makeExportDropdown(plot_id,csv_filename):
# def parseMD(md,seq):


from stats import *
from sam import *
from lib import util
	import sys
							self.stats.not_found += 1
							self.export_read("fail", sam_comp.getCurr(), sam_comp.getCurr(), "not_found")
						continue

			self.doCompareRows(sam_test.getCurr(), sam_comp.getCurr())

		while sam_test.next():
			self.stats.not_found_comparison += 1
			self.stats.total_testee += 1

			if not warned_comp_end:
				self.warn("Unexpectedly reached end of gold standard", self.comparison_filename,
						  sam_test.getCurr().qname)
				warned_comp_end = True

		#Sum up mapping quality threshold read counts
		correct_sum = 0
		wrong_sum = 0
		for i in range(254, -1, -1):
			self.stats.mapq_cumulated[i]["correct"] += self.stats.mapq_cumulated[i + 1]["correct"]
			self.stats.mapq_cumulated[i]["wrong"] += self.stats.mapq_cumulated[i + 1]["wrong"]

		self.stats.computeMeasures()

	def doCompareRows(self, row_testee, row_comp):
		if row_testee.is_unmapped:
			self.stats.not_mapped += 1
			self.export_read("fail", row_testee, row_comp, "unmapped")
			return


# Path: lib/util.py
# STATUS_NORMAL=1
# STATUS_MAX_MEMORY_EXCEEDED=2
# STATUS_MAX_RUNTIME_EXCEEDED=3
# MAX_LEN_OUT = 10000
# def runAndMeasure(command,detailed=True,maxtime=0,maxmem=0):
# def runSimple(command):
# def runAndMeasureInternal(return_queue,command,maxtime=0,maxmem=0):
# def runInternal(control_queue,command,max_memory):
# def measureProcess(queue, initial_pids, command, measurement_interval=1, max_runtime=0, max_memory=0, debug=False):
# 	def extendTargets(targets, proc):
# 	def killTargets(targets):
# 	def updateTargets(targets, metrics):
# 	def updateMetrics(target, metrics):
# def loadConfig(name, parent_dir="", already_included=[]):
# def setCallDir(d):
# def setRootDir(d):
# def enterCallDir():
# def enterRootDir():
# def getRootDir():
# def nl2br(text):
# def msg(text="", level=1):
# def yes_no(b):
# def md5(text):
# def merge(x, y):
# def formatFilesize(n):
# def percent(val, base, offset=0):
# def abs_path(path):
# def get_sam_header_line_count(filename):
# def is_sam_sorted(filename):
# def sort_sam(filename,threads=1):
# def sort_sam_picard(filename,threads=-1):
# def line_count(filename):
# def sanitize_string(s):
# def makeExportDropdown(plot_id,csv_filename):
# def parseMD(md,seq):


# Path: lib/evaluator.py
from stats import *
from sam import *
from lib import util
	import sys

							self.stats.not_found += 1
							self.export_read("fail", sam_comp.getCurr(), sam_comp.getCurr(), "not_found")
						continue

			self.doCompareRows(sam_test.getCurr(), sam_comp.getCurr())

		while sam_test.next():
			self.stats.not_found_comparison += 1
			self.stats.total_testee += 1

			if not warned_comp_end:
				self.warn("Unexpectedly reached end of gold standard", self.comparison_filename,
						  sam_test.getCurr().qname)
				warned_comp_end = True

		#Sum up mapping quality threshold read counts
		correct_sum = 0
		wrong_sum = 0
		for i in range(254, -1, -1):
			self.stats.mapq_cumulated[i]["correct"] += self.stats.mapq_cumulated[i + 1]["correct"]
			self.stats.mapq_cumulated[i]["wrong"] += self.stats.mapq_cumulated[i + 1]["wrong"]

		self.stats.computeMeasures()

	def doCompareRows(self, row_testee, row_comp):
		if row_testee.is_unmapped:
			self.stats.not_mapped += 1
			self.export_read("fail", row_testee, row_comp, "unmapped")
			return


		edit_distance = len(util.parseMD(row_comp.getTag("MD"),row_comp.seq))