def RMSFlux(fileName):
song = onset.Song(fileName)
song.FindAlphaPeak(0, 0.8)
rms = []
quiet = []
len_samp = 5 * song.sampfreq
for i in range((len(song.data) // len_samp)):
start = i * len_samp
end = i * len_samp + len_samp
power = onset.GetRMS(song.data[start:end])
rms.append([start/song.sampfreq, power])
for i in range(len(rms)-1):
a = rms[i + 1][1]
b = rms[i][1]
if b - a > 10:
quiet.append(rms[i + 1])
before = int(quiet[0][0]*song.sampfreq) - int(5*song.sampfreq)
len_samp = int(0.5*song.sampfreq)
zoomRMS = []
for i in range(11):
start = before + len_samp * i
end = before + len_samp * i + len_samp
power = onset.GetRMS_100(song.data[start:end])
zoomRMS.append([start, power])
print(start, power)
def Tempo(fileName):
song = onset.Song(fileName)
print("RMS:", song.GetRMS(), "dB")
tr = song.CalculateThreshold_RMS()
song.FindAlphaPeak(0, tr)
song.peakAlphaIndex = TruePeak(song)
print("Peak: ", song.peakAlphaIndex, song.peakAlphaIndex / song.sampfreq, "seconds.")
bpms = onset.GetBPMS_All(song, tr)
print("BPMS:",bpms)
def SampleProfile(file, resolution):
audio = onset.Song(wavfile.read("songs/samples/" + file))
limits = [240,1680]
note = audio.data[0:resolution]
onset.PlotNote(note, audio.sampfreq, limits[0], limits[len(limits)-1], file.split(".")[0] + ".png")
freqs, fft = onset.CalculateFFT_dB(note, audio.sampfreq, limits[0], limits[len(limits)-1])
x, y = onset.GetSpectrumPeaks(freqs, fft)
print(x,y)
freq, amp = onset.GetTopFrequencies(x,y,8)
plt.figure(figsize = (20,10))
plt.xticks(freq)
plt.scatter(freq,amp)
plt.xlim(limits[0],limits[1])
plt.ylim(10,30)
plt.savefig("sp_" + file.split(".")[0] + ".png")
plt.show()
# -*- coding: utf-8 -*-
"""
GET FREQUENCY AND ENERGY SEQUENCE AND PARSONS CODE
@author: albertovaldez
"""
import onset
import parsons
import easygram as ez
import getBPM_Bass as bpmb
import mp3
songName = "spectre.mp3"
plotPath, csvPath = "PCP/plots/", "PCP/csv/"
wavFile = mp3.toWAV(songName, "mp3/")
song = onset.Song(wavFile)
tr = onset.CalculateThreshold_RMS(song.data)
#bpms = bpmb.GetBPM(song, tr)
bpm_user = int(input("Enter selected BPM: \n"))
#SONG THRESHOLD FOR ALPHA PEAK, 0.0 if cut, 0.1 if instant, 0.5 if soft fade in, 0.8 if loud fade in
songTR = 0.8
noteTR = 0.7
alphaPeak = song.FindAlphaPeak(0, songTR)
bpm, measure, unitSize = bpm_user, 4, 0.25
#freqBands = [i*60 for i in range(5,26)] # Melody/Lead use continuous
#freqBands = [i*60 for i in range(2,6)] # Body/Snare use step
#freqBands = [9000, 16000] # High/Hats need custom de-peak process
freqBands = [i * 60 for i in range(0, 3)] # Bass/Kick use continuous
def Song(file):
p = Path(file)
directory = str(p.parent) + "/"
if ".mp3" in file:
wavFile = toWAV(file)
song = onset.Song(wavFile)
else:
song = onset.Song(file)
songName = file.split("/")[-1:][0]
print(songName)
u1 = int(input(("Press 1 if your song has no fade-in, Press 2 if the fade-in is quiet. Press 3 if the fade-in is loud.\n")))
if u1 == 1:
songTR = 0.1
elif u1 == 2:
songTR = 0.5
elif u1 == 3:
songTR = 0.8
else:
songTR = 0.8
alphaPeak = song.FindAlphaPeak(0,songTR)
u2 = str(input("Press 1 to get a list of suggested BPMs. Press any other key to skip:\n"))
if u2 == "1":
bpmb.GetBPM(song, onset.CalculateThreshold_RMS(song.data))
bpm_user = float(input("Enter selected BPM: \n"))
measure_user = int(input("Enter how many beats are in a bar: \n"))
bpm, measure = bpm_user, measure_user
maxBars = int((song.length_seconds * (1/(60/bpm)) / measure ))
print("Song duration in bars: " + str(maxBars))
def Melody():
noteThreshold = 0.6
unitSize = 0.25
print("\nObtaining Melody...")
# Continuous, Peaks, 4 by 4, unit 0.25
x_all, y_energy, z_freq = [],[],[]
freqBands = [300,1800]
barBlock = 4
for i in range(maxBars//barBlock):
barNum = i*barBlock
x,y,z = ez.GetNotesPeaks3D_Continuous(freqBands, song, bpm, barNum, barNum+barBlock, measure, unitSize, noteThreshold)
offset = i*barBlock*measure*(1/unitSize)
for j in range(len(y)):
x_all.append(x[j] + offset)
y_energy.append(y[j])
z_freq.append(z[j])
peaks = []
for i in x_all:
peaks.append(i * (60/bpm)*unitSize * song.sampfreq)
onset.SavePeaks(peaks, song.sampfreq, 1, song.peakAlphaIndex, directory + "peaksMelody" + "_" + songName.split(".")[0] + ".csv")
pc_e,pc_f = parsons.GetPCode(x_all, y_energy),parsons.GetPCode(x_all, z_freq)
x = [i*unitSize for i in x_all]
ez.PlotComplete(x, pc_e, pc_f, bpm, maxBars, measure, unitSize, freqBands, directory, "plotMelody_" + songName, noteThreshold, song.GetRMS(), alphaPeak)
parsons.SaveCSV3D(x, pc_e,pc_f, directory, "dataMelody_" + songName)
print("Done.")
def Snare():
noteThreshold = 0.6
unitSize = 0.5
print("\nObtaining Snare...")
# Step, Peaks, 4 by 4, unit 0.5
x_all, y_energy, z_freq = [],[],[]
freqBands = [120,300]
barBlock = 4
for i in range(maxBars//barBlock):
barNum = i*barBlock
x,y,z = ez.GetNotesPeaks3D_Step(freqBands, song, bpm, barNum, barNum+barBlock, measure, unitSize, noteThreshold)
offset = i*barBlock*measure*(1/unitSize)
for j in range(len(y)):
x_all.append(x[j] + offset)
y_energy.append(y[j])
z_freq.append(z[j])
peaks = []
for i in x_all:
peaks.append(i * (60/bpm)*unitSize * song.sampfreq)
onset.SavePeaks(peaks, song.sampfreq, 1, song.peakAlphaIndex, directory + "peaksSnare" + "_" + songName.split(".")[0] + ".csv")
pc_e,pc_f = parsons.GetPCode(x_all, y_energy),parsons.GetPCode(x_all, z_freq)
x = [i*unitSize for i in x_all]
ez.PlotComplete(x, pc_e, pc_f, bpm, maxBars, measure, unitSize, freqBands, directory, "plotSnare_" + songName, noteThreshold, song.GetRMS(), alphaPeak)
parsons.SaveCSV3D(x, pc_e,pc_f, directory, "dataSnare_" + songName)
print("Done.")
def Bass():
noteThreshold = 0.7
unitSize = 0.25
print("\nObtaining Bass...")
# Continuous, Peaks, all bars, unit 0.25
x_all, y_energy, z_freq = [],[],[]
freqBands = [0,120]
barBlock = maxBars
for i in range(maxBars//barBlock):
barNum = i*barBlock
x,y,z = ez.GetNotesPeaks3D_Continuous(freqBands, song, bpm, barNum, barNum+barBlock, measure, unitSize, noteThreshold)
offset = i*barBlock*measure*(1/unitSize)
for j in range(len(y)):
x_all.append(x[j] + offset)
y_energy.append(y[j])
z_freq.append(z[j])
peaks = []
for i in x_all:
peaks.append(i * (60/bpm)*unitSize * song.sampfreq)
onset.SavePeaks(peaks, song.sampfreq, 1, song.peakAlphaIndex, directory + "peaksBass" + "_" + songName.split(".")[0] + ".csv")
pc_e,pc_f = parsons.GetPCode(x_all, y_energy),parsons.GetPCode(x_all, z_freq)
x = [i*unitSize for i in x_all]
ez.PlotComplete(x, pc_e, pc_f, bpm, maxBars, measure, unitSize, freqBands, directory, "plotBass_" + songName, noteThreshold, song.GetRMS(), alphaPeak)
parsons.SaveCSV3D(x, pc_e,pc_f, directory, "dataBass_" + songName)
print("Done.")
def Hats():
noteThreshold = 0.7
unitSize = 0.25
print("\nObtaining HiHats...")
# Continuous, Peaks, all bars, unit 0.25
x_all, y_energy, z_freq = [],[],[]
freqBands = [9000,16000]
barBlock = maxBars
for i in range(maxBars//barBlock):
barNum = i*barBlock
x,y,z = ez.GetNotesPeaks3D_Continuous_Sum(freqBands, song, bpm, barNum, barNum+barBlock, measure, unitSize, noteThreshold)
offset = i*barBlock*measure*(1/unitSize)
for j in range(len(y)):
x_all.append(x[j] + offset)
y_energy.append(y[j])
z_freq.append(z[j])
peaks = []
for i in x_all:
peaks.append(i * (60/bpm)*unitSize * song.sampfreq)
onset.SavePeaks(peaks, song.sampfreq, 1, song.peakAlphaIndex, directory + "peaksHats" + "_" + songName.split(".")[0] + ".csv")
pc_e,pc_f = parsons.GetPCode(x_all, y_energy),parsons.GetPCode(x_all, z_freq)
x = [i*unitSize for i in x_all]
ez.PlotComplete(x, pc_e, pc_f, bpm, maxBars, measure, unitSize, freqBands, directory, "plotHats_" + songName, noteThreshold, song.GetRMS(), alphaPeak)
parsons.SaveCSV3D(x, pc_e,pc_f, directory, "dataHats_" + songName)
print("Done.")
Melody()
Snare()
Bass()
Hats()
os.remove(wavFile)
def Song(file):
try:
os.mkdir(file.split(".")[0])
except:
pass
p = Path(file)
#directory = str(p.parent) + "/"
directory = file.split(".")[0] + "/"
song = onset.Song(file)
songName = file.split("/")[-1:][0]
print(songName)
u1 = int(input(("Press 1 if your song has no fade-in, Press 2 if the fade-in is quiet. Press 3 if the fade-in is loud. Press 4 if the fade-in is very loud.\n")))
if u1 == 1:
songTR = 0.1
elif u1 == 2:
songTR = 0.5
elif u1 == 3:
songTR = 0.8
elif u1 == 4:
songTR = 0.96
else:
songTR = 0.5
alphaPeak = song.FindAlphaPeak(0,songTR)
print("Song starts at " + str(alphaPeak) + " seconds.")
'''
u2 = str(input("Press 1 to get a list of suggested BPMs. Press any other key to skip:\n"))
if u2 == "1":
onset.GetBPMS(song, song.CalculateThreshold_RMS())
'''
bpm_user = float(input("Enter selected BPM: \n"))
measure_user = int(input("Enter how many beats are in a bar: \n"))
bpm, measure = bpm_user, measure_user
maxBars = int((song.length_seconds * (1/(60/bpm)) / measure ))
print("Song duration in bars: " + str(maxBars))
def Melody():
noteThreshold = 0.5
unitSize = 0.25
# Continuous, Peaks, 4 by 4, unit 0.25
x_all, y_energy, z_freq = [],[],[]
freqBands = [300,1800]
barBlock = 4
for i in range(maxBars//barBlock):
barNum = i*barBlock
x,y,z = ez.GetNotesPeaks3D_Continuous(freqBands, song, bpm, barNum, barNum+barBlock, measure, unitSize, noteThreshold)
offset = i*barBlock*measure*(1/unitSize)
for j in range(len(y)):
x_all.append(x[j] + offset)
y_energy.append(y[j])
z_freq.append(z[j])
peaks = [i * (60/bpm) * unitSize * song.sampfreq for i in x_all]
onset.SavePeaks(peaks, song.sampfreq, 1, song.peakAlphaIndex, directory + "peaksMelody.csv")
pc_e,pc_f = parsons.GetPCode(x_all, y_energy),parsons.GetPCode(x_all, z_freq)
x = [i*unitSize for i in x_all]
ez.PlotComplete(x, pc_e, pc_f, bpm, maxBars, measure, unitSize, freqBands, directory, "plotMelody.png", noteThreshold, song.GetRMS(), alphaPeak)
parsons.SaveCSV5D(x, pc_e,pc_f,y_energy,z_freq,directory, "dataMelody.csv")
print("Done.")
def Snare():
noteThreshold = 0.5
unitSize = 0.5
# Step, Peaks, 4 by 4, unit 0.5
x_all, y_energy, z_freq = [],[],[]
freqBands = [120,300]
barBlock = 4
for i in range(maxBars//barBlock):
barNum = i*barBlock
x,y,z = ez.GetNotesPeaks3D_Step(freqBands, song, bpm, barNum, barNum+barBlock, measure, unitSize, noteThreshold)
offset = i*barBlock*measure*(1/unitSize)
for j in range(len(y)):
x_all.append(x[j] + offset)
y_energy.append(y[j])
z_freq.append(z[j])
peaks = []
for i in x_all:
peaks.append(i * (60/bpm)*unitSize * song.sampfreq)
onset.SavePeaks(peaks, song.sampfreq, 1, song.peakAlphaIndex, directory + "peaksSnare.csv")
pc_e,pc_f = parsons.GetPCode(x_all, y_energy),parsons.GetPCode(x_all, z_freq)
x = [i*unitSize for i in x_all]
ez.PlotComplete(x, pc_e, pc_f, bpm, maxBars, measure, unitSize, freqBands, directory,"plotSnare.png", noteThreshold, song.GetRMS(), alphaPeak)
parsons.SaveCSV5D(x, pc_e,pc_f,y_energy,z_freq,directory, "dataSnare.csv")
print("Done.")
def Bass():
noteThreshold = 0.5
unitSize = 0.25
# Continuous, Peaks, all bars, unit 0.25
x_all, y_energy, z_freq = [],[],[]
freqBands = [0,120]
barBlock = maxBars
for i in range(maxBars//barBlock):
barNum = i*barBlock
x,y,z = ez.GetNotesPeaks3D_Continuous(freqBands, song, bpm, barNum, barNum+barBlock, measure, unitSize, noteThreshold)
offset = i*barBlock*measure*(1/unitSize)
for j in range(len(y)):
x_all.append(x[j] + offset)
y_energy.append(y[j])
z_freq.append(z[j])
peaks = []
for i in x_all:
peaks.append(i * (60/bpm)*unitSize * song.sampfreq)
onset.SavePeaks(peaks, song.sampfreq, 1, song.peakAlphaIndex, directory + "peaksBass.csv")
pc_e,pc_f = parsons.GetPCode(x_all, y_energy),parsons.GetPCode(x_all, z_freq)
x = [i*unitSize for i in x_all]
ez.PlotComplete(x, pc_e, pc_f, bpm, maxBars, measure, unitSize, freqBands, directory, "plotBass.png", noteThreshold, song.GetRMS(), alphaPeak)
parsons.SaveCSV5D(x, pc_e,pc_f,y_energy,z_freq,directory, "dataBass.csv")
print("Done.")
def Hats():
noteThreshold = 0.5
unitSize = 0.25
# Continuous, Peaks, all bars, unit 0.25
x_all, y_energy, z_freq = [],[],[]
freqBands = [9000,16000]
barBlock = maxBars
for i in range(maxBars//barBlock):
barNum = i*barBlock
x,y,z = ez.GetNotesPeaks3D_Continuous_Sum(freqBands, song, bpm, barNum, barNum+barBlock, measure, unitSize, noteThreshold)
offset = i*barBlock*measure*(1/unitSize)
for j in range(len(y)):
x_all.append(x[j] + offset)
y_energy.append(y[j])
z_freq.append(z[j])
peaks = []
for i in x_all:
peaks.append(i * (60/bpm)*unitSize * song.sampfreq)
onset.SavePeaks(peaks, song.sampfreq, 1, song.peakAlphaIndex, directory + "peaksHats.csv")
pc_e,pc_f = parsons.GetPCode(x_all, y_energy),parsons.GetPCode(x_all, z_freq)
x = [i*unitSize for i in x_all]
ez.PlotComplete(x, pc_e, pc_f, bpm, maxBars, measure, unitSize, freqBands, directory, "plotHats.png", noteThreshold, song.GetRMS(), alphaPeak)
parsons.SaveCSV5D(x, pc_e,pc_f,y_energy,z_freq,directory, "dataHats.csv")
print("Done.")
print("\nObtaining Melody...")
Melody()
print("\nObtaining Snare...")
Snare()
print("\nObtaining Bass...")
Bass()
print("\nObtaining HiHats...")
Hats()
snaps.Density(directory)
snaps.RateOfChange(directory)
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
GET FREQUENCY AND ENERGY SEQUENCE AND PARSONS CODE
@author: albertovaldez
"""
import onset
import parsons
import easygram as ez
import getBPM_Bass as bpmb
songName = "spectre.mp3"
plotPath, csvPath = "PCP/plots/", "PCP/csv/"
song = onset.Song("songs/" + songName)
tr = onset.CalculateThreshold_RMS(song.data)
#bpms = bpmb.GetBPM(song, tr)
bpm_user = int(input("Enter selected BPM: \n"))
#SONG THRESHOLD FOR ALPHA PEAK, 0.0 if cut, 0.1 if instant, 0.5 if soft fade in, 0.8 if loud fade in
songTR = 0.8
noteTR = 0.7
alphaPeak = song.FindAlphaPeak(0,songTR)
bpm, measure, unitSize = bpm_user, 4, 0.25
#freqBands = [i*60 for i in range(5,26)] # Melody/Lead use continuous
#freqBands = [i*60 for i in range(2,6)] # Body/Snare use step
#freqBands = [9000, 16000] # High/Hats need custom de-peak process
freqBands = [i*60 for i in range(0,3)] # Bass/Kick use continuous
def RMSFluxStart(fileName):
song = onset.Song(fileName)
rms = song.GetRMS()
print("RMS:", rms)
x,y = [],[]
on = []
len_samp = 5 * song.sampfreq
total = 60 * song.sampfreq
for i in range(total // len_samp):
start = i * len_samp
end = i * len_samp + len_samp
power = onset.GetRMS(song.data[start:end])
x.append(start/song.sampfreq)
y.append(power)
# 5 SECOND RULE
for i in range(len(y)-1):
a = y[i]
b = y[i + 1]
if abs(a) - abs(b) > 9:
on = [x[i+1],y[i+1]]
break
intro = on[0] * song.sampfreq // 2
unit = song.sampfreq
length = 5
x, y = [],[]
print(intro/song.sampfreq)
for i in range(length):
start = int(intro + (unit * i))
end = start + unit
chunkRMS = onset.GetRMS(song.data[start:end])
x.append(start)
y.append(chunkRMS)
for i in range(len(y)-1):
a = y[i]
b = y[i + 1]
if abs(a) - abs(b) > 9:
on = [x[i+1], y[i+1]]
break
print(max(y), x[y.index(max(y))])
intro = on[0]
unit = song.sampfreq // 20
length = 20
x, y = [],[]
for i in range(length):
start = int(intro + (unit * i))
end = start + unit
chunkRMS = onset.GetRMS(song.data[start:end])
x.append(start)
y.append(chunkRMS)
print(max(y), x[y.index(max(y))])
intro = x[y.index(max(y))] - 8192
unit = 1024
length = 8
x, y = [],[]
for i in range(length):
start = int(intro + (unit * i))
end = start + unit
chunkRMS = onset.GetRMS(song.data[start:end])
x.append(start)
y.append(chunkRMS)
print(max(y), x[y.index(max(y))])
plt.plot(x,y)
"""
Created on Mon Jul 20 17:19:41 2020
@author: albertovaldezquinto
"""
import librosa
import librosa.display
import numpy as np
import matplotlib.pyplot as plt
import onset
from scipy import stats
audioPath = "drums.wav"
song = onset.Song(audioPath)
rms = onset.GetRMS(song.data)
print("RMS:", rms, "dB")
data = song.data
sr = song.sampfreq
tempo, beats = librosa.beat.beat_track(y=data, sr=sr, units="samples")
print("BPM", tempo)
def GetBeatFrequencySnapshot(x, chunkSize, filterLow, filterHigh):
chunksInData = len(x) // chunkSize
frequencies = np.empty(0)
energies = np.empty(0)
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
@author: albertovaldez
"""
import onset
from scipy.io import wavfile
songName = "cut.wav"
song = onset.Song(wavfile.read("songs/" + songName))
tr = onset.CalculateThreshold_RMS(song.data)
song.FindAlphaPeak(0,tr)
song.GetNoteOnset(unit = 4096, chunk_size = 4096, threshold_ratio = tr, HPF = 960, LPF = 1080, base = 10)
song.GetPeaks(x = 4096)
onset.SavePeaks(song.pks, song.sampfreq, 1, 0, "peaks.csv")
song.PlotPeaks()
def GetSimpleSpectrogram_FromNotes(limits):
multiband = []
for i in range(len(song.notes)):
start, end = song.notes[i][0], song.notes[i][0] + 4096
chunk = song.data[start:end]
freqs, fft = onset.CalculateFFT_dB(chunk, song.sampfreq, limits[0], limits[len(limits)-1])
#x, y = onset.GetSpectrumPeaks(freqs, fft)
x, y = freqs, fft
freqBandsAmp = onset.FrequencyBands(x,y,limits)
files = []
for file in os.listdir("/Volumes/AV5 HD B/02Samples/Music/RGM/Funky Panda"):
if ".mp3" in file:
files.append("/Volumes/AV5 HD B/02Samples/Music/RGM/Funky Panda/" +
file)
data = []
csv = "Song, Low, Mid, High, Total, RMS"
with open("data.csv", "w+") as file:
file.write(csv)
for file in files:
print(file)
try:
song = onset.Song(file)
tr = song.CalculateThreshold_RMS()
song.FindAlphaPeak(0, tr)
rms = song.GetRMS()
print("RMS:", rms, "Threshold:", tr, "Alpha Peak:",
song.peakAlphaIndex / song.sampfreq)
FindEnding(song)
sl = int((song.length / song.sampfreq) * 1000) / 1000
print("Song Length, seconds", sl)
notes = EasyOnsets(song, [0, 120], 2048, tr)
low = int((len(notes) * 4 / sl) * 1000) / 1000
notes = EasyOnsets(song, [300, 1800], 2048, tr)
mid = int((len(notes) / sl) * 1000) / 1000
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Wed Jul 1 18:30:55 2020
@author: albertovaldez
"""
import onset
song = onset.Song("songs/axtasia_closer.wav")
song.FindAlphaPeak(0, 0.5)
tr = onset.CalculateThreshold_RMS(song.data)
tr = 0.8
song.GetNoteOnset(unit=2048,
chunk_size=2048,
threshold_ratio=tr,
HPF=0,
LPF=120,
base=10)
song.GetPeaks(x=0)
bpm1, bpm2 = song.GetBPM(), song.GetBPM_PKS()
print(bpm1, bpm2)
onset.SavePeaks(song.pks, song.sampfreq, 1, -song.peakAlpha,
"reaper/Files/peaks.csv")
bpm = 60 / (onset.mode(d) / song.sampfreq
) #Convert deltas from sample to seconds to bpm
while bpm < bpmMin or bpm > bpmMax: #Reduce BPM to beats approximation
if bpm < bpmMin:
bpm = bpm * 2
elif bpm > bpmMax:
bpm = bpm / 2
return int(bpm * 100) / 100
for i in os.listdir(outputFolder):
if ".DS_Store" != i:
for j in os.listdir(outputFolder / i):
if stemName in j:
song = onset.Song(str(outputFolder / i / stemName))
tr = song.CalculateThreshold_RMS(
) # Tries to compensate, as a manual limiter
indexes = np.where(
song.data > tr)[0] # Get samples higher than threshold
hop = 2048 # Separate positions of samples. Using frame size for FFT, value can change, 2048 is 40 milliseconds
peaks = indexes[np.where(np.diff(indexes) > hop)[0] + 1]
if len(peaks) > 4:
bpm = GetBPM(peaks)
print(i, bpm)
else:
bpms, peaks = onset.GetBPMS(song, tr, 120)
bpm = bpms[0][1] + 0.0069