# --Description:[tatmos][Preview]選択したオブジェクトの原音のレベルをチェックしマーカーデータ作成
import pyaudio
import wave
import time
import numpy as np
import scipy.signal as sp
import cri.atomcraft.project as acproject
import cri.atomcraft.debug as acdebug
from struct import unpack

#ndarrayの内容出力を省略しない
#np.set_printoptions(threshold=np.inf)

p = pyaudio.PyAudio()

#カレント言語
user_settings = acproject.get_user_settings()["data"]
language_setting = acproject.get_value(user_settings, "CurrentLanguageSetting")["data"]
language = acproject.get_value(language_setting, "OutputSuffix")["data"]
print(language)
languageFolderJa = "/ja/"
languageFolderEn = "/en/"

#言語マテリアルを得る
def getLanguageMaterial(tmplinkMaterialPath):
    #acdebug.log("Target Path:\"{0}\"".format(tmplinkMaterialPath ))
    linkMaterialPath = tmplinkMaterialPath

    #言語フォルダーのマテリアルパスに変更
    if language == "_ja":
        linkMaterialPath = tmplinkMaterialPath.replace(languageFolderEn,languageFolderJa)
    else:
        linkMaterialPath = tmplinkMaterialPath.replace(languageFolderJa,languageFolderEn)

    #言語フォルダーのマテリアルに変更
    resultMaterial = acproject.get_object_from_path(linkMaterialPath)
    #acdebug.log("resultMaterial :\"{0}\"".format(resultMaterial["succeed"] ))
    #acdebug.log("resultMaterial :\"{0}\"".format(resultMaterial["data"] ))
    if resultMaterial["data"]:
        #acdebug.log("resultMaterial :\"{0}\"".format(linkMaterialPath ))
        linkMaterial = resultMaterial["data"]
    else:
        #acdebug.warning("Not Found Target Path:\"{0}\"".format(linkMaterialPath ))
        linkMaterial = acproject.get_object_from_path(tmplinkMaterialPath)["data"] #みつからない時
    return linkMaterial


#--------

#選択中のウェーブフォームリージョンまたはキューを得る
selectedWaveformRegions = acproject.get_selected_objects("WaveformRegion")["data"]
selectedCues = acproject.get_selected_objects("Cue")["data"]

selectedMaterial = None
selectedCue = None

if len(selectedCues) > 0:
    selectedWaveformRegions = acproject.find_objects(selectedCues[0],"WaveformRegion")["data"]
    selectedCue = selectedCues[0]
else:
    selectedCue = acproject.get_parent(selectedWaveformRegions[0],"Cue")["data"]

if len(selectedWaveformRegions) > 0:
    selectedMaterial = acproject.get_value(selectedWaveformRegions[0], "LinkMaterial")["data"]

#言語違いマテリアルを得る
selectedMaterial = getLanguageMaterial(acproject.get_object_path(selectedMaterial)["data"] )

if not selectedMaterial:
    acdebug.warning("解析するウェーブフォームリージョンまたはキューを選択してください。")
    sys.exit()

print(acproject.get_value(selectedMaterial, "Name")["data"])

input_path = acproject.get_value(selectedMaterial, "SrcFileAbsolutePath")["data"]

if not input_path:
    acdebug.warning("マテリアルのパスがみつかりません。")
    sys.exit()

print("Path:" + str(input_path))

#--------
#ファイルを開く
wf = wave.open(input_path, "rb")

buf = wf.readframes(-1)    #全部bufferに読む

wf.close()

#データ解析
if wf.getsampwidth() == 2: #16bit波形
    ndarray = np.frombuffer(buf, dtype='int16')    #2byteごとに配列化 (-32768 - 32767)
elif  wf.getsampwidth() == 3:#24bit波形
    read_frames = wf.getnframes()
    nbyte = wf.getsampwidth()
    data = [unpack("<i",
            bytearray([0]) + buf[nbyte * idx: nbyte * (idx + 1)])[0]
            for idx in range(read_frames)]
    ndarray = np.array(data, dtype='int16')
elif samplewidth == 4:# 32bit (未確認)
    ndarray = np.frombuffer(buf, dtype='int32')


#ステレオ時は左のみ
if wf.getnchannels() == 2:
    ndarray = ndarray[0::2]

N = 64 #解析するデータ数

BIN = 1#調査するBIN



#ndarrayの長さを得る
print(len(ndarray))
#あまり分を足す
padding = N - len(ndarray) % N
print(padding)
ndarray = np.append(ndarray,np.zeros(padding))
#print(len(ndarray))
#print(len(ndarray) / N)
#均等に分割
ndarray = np.split(ndarray, len(ndarray) / N)

#処理単位が何msecか
msec_per_frame = N / wf.getframerate() * 1000
print("msec_per_frame " + str(msec_per_frame))

#all = ""
amp_all = []

currentMsec = 0
for frame in ndarray:   #処理フレームごとにFFT
    # FFT
    wave_y = np.fft.fft(frame)
    wave_y = np.abs(wave_y) / N * 2 #周期を得るために絶対値 データ数で割って2倍にして正規化
    amp_all.append(wave_y[:int(N / 2) + 1][BIN]) # 特定のバンドのみ
    currentMsec += msec_per_frame

# ピークのみ抽出        
amp_all = np.array(amp_all)
maxid = sp.argrelmax(amp_all, order=100) #最大値

#---------
# マーカーの作成
for id in maxid[0]:
    new_marker = acproject.create_object(selectedCue,"CallbackMarker","mk" + str(id))["data"]
    acproject.set_value(new_marker, "MarkerStartTime", id*msec_per_frame)   
    acproject.set_value(new_marker, "CallbackTag", str(amp_all[id]))    

#---------
#Debug
#for id in maxid[0]:
#    all += "{} : {}\n".format(id*msec_per_frame ,str(amp_all[id]))


##ファイルに解析内容を保存
#sample_file = open("C:\MyDearest\peak.txt", mode="w")
#try:
#    sample_file.write(str(all))
#finally:
#    sample_file.close()

p.terminate()