## Sc final

## input
index_vocal.json [frame, putch]
index_feature.json ？？？？
index_link.txt
index_groundtruth.txt => ans

## output
onset(sec) offset(sec) pitch

## grading
A = 實際正確的音個數
B = 做出來正確的音個數
C = 滿足條件的音個數
=====> (2*C) / (A+B)

## DP

int arrayA[][max_column]
for j = 1~n
    for i = 1~m
        A(j, i) = abs(noteVec(1,j)-pv(1,i));

int arrayB[][max_column];
B(1,1) = A(1,1);
for i = 2:m
    B(1,i) = B(1,i-1)+A(1,i);

for j = 2:n
    for k = 1:j-1
    B(j,k) = 10000000;
    
for j = 2:n
    for i = 2:m
        if B(j, i-1) < B(j-1, i-1)
            B(j, i) = A(j, i) + B(j, i-1);
        else
            B(j, i) = A(j, i) + B(j-1, i-1);

minDist = B(1,m);
for j = 2:n
    if B(j,m) < minDist
        minDist = B(j,m);

output = minDist;

## DP in C

## DP
int A[][max_column]
for(int i = 0 ; i < n ; i++)
    for(int j = 0 ; j < m ; j++)
        A[i][j] = abs(noteVec[i]-pv[j]);

int B[][max_column];
B[0][0] = A[0][0];
for(int j = 1 ; j < m ; j++)
    B[0][j] = B[0][j-1]+A[0][j];

for(int i = 1 ; i < n ; i++)
    for(int k = 0 ; k < i ; k++)
    B[i][k] = 10000000;
    
for(int i = 1 ; i < n ; i++)
    for(int j = 1 ; j < m ; j++)
        if B[i][j-1] < B[i-1][j-1]
            B[i][j] = A[i][j] + B[i][j-1];
        else
            B[i][j] = A[i][j] + B[i-1][j-1];

int minDist = B[0][m];
for(int i = 1 ; i < n ; i++)
    if B[i][m] < minDist
        minDist = B[i][m];

//output = minDist;

## main

import numpy as np
import math
import json

frame = 0.032
p = 2 # pitch 正負可能的值
k = 1.5 #高或低於平均視為分段
t = 0 #時間
z = 0.1

output_list = []

def READ():
    index = input()
    vocal_file = index + "_vocal.json"
    feature_file = index + "_feature.json"
    
    with open(vocal_file, 'r') as read_file:
        vocal_data = json.load(read_file)
    with open(feature_file, 'r') as read_file:
        feature_data = json.load(read_file)
    return vocal_data, feature_data


def CAL_AVE(data_list):
    total = 0
    n = 0
    for data in data_list:
        total += data[1]
        n += 1
    return (total / n)

def DP(data_list, average_pitch):
 
    p1 = math.floor(average_pitch - p) #無條件捨去
    p2 = math.ceil(average_pitch + p) #無條件進位
    p_list = list(range(p1, p2+1))
    
    n = len(p_list) #y軸個數
    m = len(data_list) #x軸個數

    table = np.zeros((n, m)) #A
    dp_table = np.zeros((n, m)) #B

    for i in range(n):
        for j in range(m):
            table[i][j] = abs(p_list[i] - data_list[j][1])
    dp_table[0][0] = table[0][0]
    for j in range(1, m):
        dp_table[0][j] = dp_table[0][j-1] + table[0][j]
    for i in range(1, n):
        for j in range(0, i):
            if j == m:
                break
            dp_table[i][j] = float("inf")
    for i in range(1, n):
        for j in range(1, m):
            if dp_table[i][j-1] < dp_table[i-1][j-1]:
                dp_table[i][j] = table[i][j] + dp_table[i][j-1];
            else:
                dp_table[i][j] = table[i][j] + dp_table[i-1][j-1];

    best_pitch = average_pitch
    mindis = dp_table[0][m-1];
    for i in range(1, n):
        if dp_table[i][m-1] < mindis:
            mindis = dp_table[i][m-1]
            best_pitch = p_list[i]

    start_time = data_list[0][0]
    end_time = data_list[m-1][0]

    output_list.append([start_time, end_time, best_pitch])
    return
     

vocal_data, feature_data = READ()

#print(feature_data['zcr'])
data_list = []
average_pitch = 0
for now_data in vocal_data:
    sec = now_data[0]
    pitch = now_data[1]
    if pitch == 0:
        if (len(data_list) != 0):
            DP(data_list, average_pitch)
            data_list.clear()
            average_pitch = 0
        continue
    
    if average_pitch != 0 and abs(pitch - average_pitch) > k: #分段
        DP(data_list, average_pitch)
        data_list.clear()
        average_pitch = 0
    
    data_list.append(now_data)
    average_pitch = CAL_AVE(data_list)
    #print("(", now_data[0], ", ", now_data[1], ")")

if (len(data_list) != 0):
    DP(data_list, average_pitch)

for output in output_list:
    print(output[0], " ", output[1], " ", output[2])