# result generator for dejavu

# TODO: Don't work very well with musics with special chars.
# use test file on the format below, with no special chars and only one "-" to separate artist from song

import os, subprocess, json, re, sys
import logging, time
from os import listdir
from os.path import isfile, join
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.animation as animation
from optparse import OptionParser

#####
### 	Test files are in specific format:
###		'artist_name'-'song_name'_'start_time'_'duration'sec.wav
#####

DEFAULT_FS = 44100
DEFAULT_WINDOW_SIZE = 4096
DEFAULT_OVERLAP_RATIO = 0.5

#FIELD_SONG_ID 				= 'song_id'
FIELD_SONG_NAME				= 'song_name'
FIELD_CONFIDENCE			= 'confidence'
FIELD_QUERY_TIME			= 'match_time'
FIELD_OFFSET				= 'offset'

# Parse options 

usage = "usage: %prog [options] DEJAVU_PATH TEST_FOLDER"
parser = OptionParser(usage=usage, version="%prog 1.1")

parser.add_option("--no-log",
				  action="store_false",
                  dest="log",
                  default=True,
                  help='Disables logging'
                  )
parser.add_option("--log-file",
                  dest="log_file",
                  default="results-compare.log",
                  metavar="LOG_FILE",
                  help='Set the path and filename of the log file'
                  )
parser.add_option("--test-seconds",
				  action="append",
                  dest="test_seconds",
                  default=[],
                  metavar="Xsec",
                  help='Appends seconds to test suit'
                  )
parser.add_option("--results-folder",
				  action="store",
                  dest="results_folder",
                  metavar="FOLDER",
                  help='Sets the path where the results are saved'
                  )

(options, args) = parser.parse_args()

if len(args) != 2:
	parser.error("wrong number of arguments")

if len(options.test_seconds) == 0:
	options.test_seconds = ['1sec','2sec','3sec','4sec','5sec','6sec','7sec','8sec','9sec','10sec']

if options.log == True:
	logging.basicConfig( filename=options.log_file, level=logging.DEBUG )

if options.results_folder != "" and options.results_folder[len(options.results_folder)-1] != '/':
	options.results_folder += "/"

def log_msg(msg):
	if options.log == True:
		logging.debug(msg)

class DejavuTest (object):
	def __init__(self, folder, seconds):
		super(DejavuTest, self).__init__()

		self.test_folder = folder
		self.test_seconds = seconds
		self.test_songs = []
		self.test_files = [ f for f in listdir(self.test_folder) if isfile(join(self.test_folder,f)) 
			and re.findall("[0-9]*sec",f)[0] in self.test_seconds ]
		self.n_columns = len(self.test_seconds)
		self.n_lines = len(self.test_files) / self.n_columns 

		# variable match results (yes, no, invalid)
		self.result_match = [[0 for x in xrange(self.n_columns)] for x in xrange(self.n_lines)] 

		# variable match precision (if matched in the corrected time)
		self.result_matching_times = [[0 for x in xrange(self.n_columns)] for x in xrange(self.n_lines)] 

		# variable mahing time (query time) 
		self.result_query_duration = [[0 for x in xrange(self.n_columns)] for x in xrange(self.n_lines)] 

		# variable confidence
		self.result_match_confidence = [[0 for x in xrange(self.n_columns)] for x in xrange(self.n_lines)] 

		self.begin()

	def get_column_id ( self,secs ):
		for i, sec in enumerate(self.test_seconds):
			if secs == sec:
				return i

	def get_line_id ( self,artist, song ):
		elem = artist + " - " + song

		for i, s in enumerate(self.test_songs):
			if elem == s:
				return i

		self.test_songs.append(elem)
		return len(self.test_songs)-1

	def begin(self):
		for f in self.test_files:
			log_msg('--------------------------------------------------')
			log_msg('file: %s' % f)
			# get column 
			col = self.get_column_id(re.findall("[0-9]*sec",f)[0])

			# get artist and song
			artist = re.findall("^[^\-]+",f)
			artist = artist[0].rstrip()

			song = re.findall("\-[^\_]+",f)
			song = song[0].lstrip("- ")

			line = self.get_line_id ( artist, song)

			result = subprocess.check_output([args[0], 'recognize', 'file', self.test_folder+"/"+f])
			log_msg('RESULT: %s' % result.strip() )

			if result.strip() == "None":
				log_msg('No match')
				self.result_match[line][col] = 'no'
				self.result_matching_times[line][col] = 0
				self.result_query_duration[line][col] = 0
				self.result_match_confidence[line][col] = 0
			
			else:
				result = result.strip()
				result = result.replace(" \'", ' "')
				result = result.replace("{\'", '{"')
				result = result.replace("\':", '":')
				result = result.replace("\',", '",')

				result = json.loads(result)

				artist_result = re.findall("^[^\-]+",result[FIELD_SONG_NAME])
				artist_result = artist_result[0].rstrip()

				song_result = re.findall("\-[^\_]+",result[FIELD_SONG_NAME])
				song_result = song_result[0].lstrip("- ")

				log_msg('artist: %s' % artist)
				log_msg('artist_result: %s' % artist_result)
				log_msg('song: %s' % song)
				log_msg('song_result: %s' % song_result)

				if artist_result != artist or song_result != song:
					log_msg('invalid match')
					self.result_match[line][col] = 'invalid'
					self.result_matching_times[line][col] = 0
					self.result_query_duration[line][col] = 0
					self.result_match_confidence[line][col] = 0
				else:
					log_msg('correct match')
					self.result_match[line][col] = 'yes'
					self.result_query_duration[line][col] = round(result[FIELD_QUERY_TIME],3)
					self.result_match_confidence[line][col] = result[FIELD_CONFIDENCE]

					song_start_time = re.findall("\_[^\_]+",f)
					song_start_time = song_start_time[0].lstrip("_ ")

					#result_start_time = round((result[FIELD_SONG_DURATION] * result[FIELD_OFFSET]) / float(result[FIELD_SONG_SPEC_DURATION]), 0)
					result_start_time = round((result[FIELD_OFFSET] * DEFAULT_WINDOW_SIZE * DEFAULT_OVERLAP_RATIO) / (DEFAULT_FS),0)

					self.result_matching_times[line][col] = int(result_start_time) - int(song_start_time)
					if (abs(self.result_matching_times[line][col]) == 1):
						self.result_matching_times[line][col] = 0

					log_msg('query duration: %s' % round(result[FIELD_QUERY_TIME],3))
					log_msg('confidence: %s' % result[FIELD_CONFIDENCE])
					log_msg('song start_time: %s' % song_start_time)
					log_msg('result start time: %s' % result_start_time)
					if (self.result_matching_times[line][col] == 0):
						log_msg('accurate match')
					else:
						log_msg('inaccurate match')
			log_msg('--------------------------------------------------\n')

print "obtaining results from dejavu"
log_msg('obtaining results from dejavu')
tm = time.time()
djv = DejavuTest(args[1], options.test_seconds)
print "finished obtaining results from dejavu in %s" % (time.time() - tm)
log_msg("finished obtaining results from dejavu in %s" % (time.time() - tm))

tests_n_lines = djv.n_lines
tests_n_columns = djv.n_columns # len(options.test_seconds)
tests = 1 # djv
n_secs = len(options.test_seconds) # = tests.n_columns

# set result variables -> 4d variables
all_match_counter = [[[0 for x in xrange(tests)] for x in xrange(3)] for x in xrange(n_secs)]
all_matching_times_counter = [[[0 for x in xrange(tests)] for x in xrange(2)] for x in xrange(n_secs)]
all_query_duration = [[[0 for x in xrange(tests)] for x in xrange(tests_n_lines)] for x in xrange(n_secs)]
all_match_confidence = [[[0 for x in xrange(tests)] for x in xrange(tests_n_lines)] for x in xrange(n_secs)]

# agroup results by seconds
for line in range(0, tests_n_lines):
	for col in range(0, tests_n_columns):
		# for dejavu
		all_query_duration[col][line][0] = djv.result_query_duration[line][col]
		all_match_confidence[col][line][0] = djv.result_match_confidence[line][col]

		djv_match_result = djv.result_match[line][col]

		if djv_match_result == 'yes':
			all_match_counter[col][0][0] += 1
		elif djv_match_result == 'no':
			all_match_counter[col][1][0] += 1
		else:
			all_match_counter[col][2][0] += 1

		djv_match_acc = djv.result_matching_times[line][col]

		if djv_match_acc == 0 and djv_match_result == 'yes':
			all_matching_times_counter[col][0][0] += 1
		elif djv_match_acc != 0:
			all_matching_times_counter[col][1][0] += 1

def autolabel(rects,ax):
    # attach some text labels
    for rect in rects:
        height = rect.get_height()
        ax.text(rect.get_x()+rect.get_width()/2., 1.05*height, '%d'%int(height),
                ha='center', va='bottom')

def autolabeldoubles(rects,ax):
    # attach some text labels
    for rect in rects:
        height = rect.get_height()
        ax.text(rect.get_x()+rect.get_width()/2., 1.05*height, '%s'%round(float(height),3),
                ha='center', va='bottom')

def create_plots(name,results):
	for sec in range(0,n_secs):
		ind = np.arange(tests_n_lines) #
		width = 0.25       # the width of the bars

		fig = plt.figure()
		ax = fig.add_subplot(111)
		ax.set_xlim([-1*width, 2*width])

		means_dvj = [x[0] for x in results[sec]]
		rects1 = ax.bar(ind, means_dvj, width, color='r')

		# add some
		ax.set_ylabel(name)
		ax.set_title("%s %s Results" % (options.test_seconds[sec],name)) 
		ax.set_xticks(ind+width)

		labels = [0 for x in range(0,tests_n_lines)]
		for x in range(0,tests_n_lines):
			labels[x] = "song %s" % (x+1)
		ax.set_xticklabels( labels )

		box = ax.get_position()
		ax.set_position([box.x0, box.y0, box.width * 0.75, box.height])

		#ax.legend( (rects1[0]), ('Dejavu'), loc='center left', bbox_to_anchor=(1, 0.5))

		if name == 'Confidence':
			autolabel(rects1,ax)
		else:
			autolabeldoubles(rects1,ax)

		plt.grid()

		fig_name = "%s%s_%s.png" % (options.results_folder,name,options.test_seconds[sec])
		fig.savefig(fig_name)

create_plots('Confidence',all_match_confidence)
create_plots('Query duration',all_query_duration)

for sec in range(0,n_secs):
	ind = np.arange(3) #
	width = 0.25       # the width of the bars

	fig = plt.figure()
	ax = fig.add_subplot(111)
	ax.set_xlim([-1*width, 2.75])

	means_dvj = [round(x[0]*100/tests_n_lines,1) for x in all_match_counter[sec]]
	rects1 = ax.bar(ind, means_dvj, width, color='r')

	# add some
	ax.set_ylabel('Matching Percentage')
	ax.set_title('%s Matching Percentage' % options.test_seconds[sec])
	ax.set_xticks(ind+width)

	labels = ['yes','no','invalid']
	ax.set_xticklabels( labels )

	box = ax.get_position()
	ax.set_position([box.x0, box.y0, box.width * 0.75, box.height])

	#ax.legend( (rects1[0]), ('Dejavu'), loc='center left', bbox_to_anchor=(1, 0.5))
	autolabeldoubles(rects1,ax)

	plt.grid()

 	fig_name = "%smatching_perc_%s.png" % (options.results_folder,options.test_seconds[sec])
 	fig.savefig(fig_name)

for sec in range(0,n_secs):
	ind = np.arange(2) #
	width = 0.25       # the width of the bars

	fig = plt.figure()
	ax = fig.add_subplot(111)
	ax.set_xlim([-1*width, 1.75])

	div = all_match_counter[sec][0][0]
	if div == 0 :
		div = 1000000

	means_dvj = [round(x[0]*100/div,1) for x in all_matching_times_counter[sec]]
	rects1 = ax.bar(ind, means_dvj, width, color='r')

	# add some
	ax.set_ylabel('Matching Accuracy')
	ax.set_title('%s Matching Times Accuracy' % options.test_seconds[sec])
	ax.set_xticks(ind+width)

	labels = ['yes','no']
	ax.set_xticklabels( labels )

	box = ax.get_position()
	ax.set_position([box.x0, box.y0, box.width * 0.75, box.height])

	#ax.legend( (rects1[0]), ('Dejavu'), loc='center left', bbox_to_anchor=(1, 0.5))
	autolabeldoubles(rects1,ax)

	plt.grid()

 	fig_name = "%smatching_acc_%s.png" % (options.results_folder,options.test_seconds[sec])
 	fig.savefig(fig_name)