인프런 커뮤니티 질문&답변

강의를 듣고 직접 RNN을 구현하는 것을 시도했습니다.

 

하나의 물체를 다른 위치에서 촬영하고 각 사진마다 물체 좌표값(x,y)을 추출했습니다.

얻은 좌표값을 이용해서 실제 3D 좌표(x,y,z)로 예측하는 것을 만들려고 합니다.

 

제가 생각한 모델구성은 아래와 같습니다.

하지만, 모델을 구현해보니 좌표값이 1개만 출력되고

출력된 값이 무엇을 예측하고 나왔는지 모르겠습니다.

 

어디를 수정해야 x,y,z값이  출력되나요?

 

아래는 사용된 소스 및 데이터 일부입니다.

import numpy as np
import pandas as pd

import torch
from sklearn.model_selection import train_test_split
import torch.nn as nn
import torch.optim as optim

import matplotlib.pyplot as plt

#데이터 불러오기
path = r"redball_Data.csv"
df = pd.read_csv(path)
df_suffled = df.sample(frac=1).reset_index()

#텐서 데이터 만들기
x = df_suffled[['x1','y1','x2','y2','x3','y3','x4','y4','x5','y5','x6','y6','x7','y7','x8','y8']].values
y = df_suffled[['x','y','z']].values
print(x.shape)

x = x.reshape(len(x),8,2) #2d to 3d
print(x.shape)
print(y.shape)

device = torch.device("cuda:0" if torch.cuda.is_available() else "cpu")
xt = torch.FloatTensor(x).to(device)
yt = torch.FloatTensor(y).to(device)

x_train, x_test, y_train, y_test = train_test_split(xt,yt,test_size=0.2)
print(f"x_train {x_train.shape} | x_test {x_test.shape} | y_train {y_train.shape} | y_test {y_test.shape}")

train = torch.utils.data.TensorDataset(x_train, y_train)
test = torch.utils.data.TensorDataset(x_test, y_test)

batch_size = 1000
train_loader = torch.utils.data.DataLoader(dataset=train, batch_size=batch_size, shuffle=False)
test_loader = torch.utils.data.DataLoader(dataset=test, batch_size=batch_size, shuffle=False)




#Hyperparameter setting
# RNN
print(f"input_size : {xt.size(2)}")
input_size = xt.size(2)
num_layers = 2
hidden_size = 8
sequence_length = xt.size(1)

#Create Model
class VanillaRNN(nn.Module):
    def __init__(self, input_size, hidden_size, sequence_length, num_layers, device):
        super(VanillaRNN, self).__init__()
        self.device = device
        self.hidden_size = hidden_size
        self.num_layers = num_layers
        self.rnn = nn.RNN(input_size, hidden_size, num_layers, batch_first=True)
        self.fc = nn.Sequential(nn.Linear(hidden_size * sequence_length, 3), nn.ReLU()) #1 => 3으로 수정

    def forward(self, x):
        h0 = torch.zeros(self.num_layers, x.size()[0], self.hidden_size).to(self.device)  # 초기 hidden state 설정
        out, _ = self.rnn(x, h0)  # out: RNN의 마지막 레이어로 부터 나온 output feature 반환, hn: hidden state 반환
        out = out.reshape(out.shape[0], -1)  # many to many 전략
        out = self.fc(out)
        return out

model = VanillaRNN(input_size=input_size,
                   hidden_size=hidden_size,
                   sequence_length=sequence_length,
                   num_layers=num_layers,
                   device=device).to(device)

criterion = nn.MSELoss()

lr = 1e-3
num_epochs = 800
optimizer = optim.Adam(model.parameters(), lr=lr)

#Learn Model
loss_graph = []
n = len(train_loader)

for epoch in range(num_epochs):
    running_loss = 0.0

    for data in train_loader:
        seq, target = data  # 배치 데이터
        out = model(seq)
        loss = criterion(out, target)

        optimizer.zero_grad()
        loss.backward()
        optimizer.step()
        running_loss += loss.item()

    loss_graph.append(running_loss / n)
    if epoch % 50 == 0:
        print('[epoch: %d] loss: %.4f' % (epoch, running_loss / n))

plt.figure(figsize=(20,10))
plt.plot(loss_graph)
plt.show()





def plotting(train_loader, test_loader, actual):
    with torch.no_grad():
        train_pred = []
        test_pred = []

        for data in train_loader:
            seq, target = data  # 배치 데이터
            # print(seq.size())
            out = model(seq)
            train_pred += out.cpu().numpy().tolist()

        for data in test_loader:
            seq, target = data  # 배치 데이터
            # print(seq.size())
            out = model(seq)
            test_pred += out.cpu().numpy().tolist()
    total = train_pred + test_pred
    plt.figure(figsize=(20, 10))
    plt.plot(np.ones(100) * len(train_pred), np.linspace(0, 1, 100), '--', linewidth=0.6)
    plt.plot(actual, '--')
    plt.plot(total, 'b', linewidth=0.6)

    plt.legend(['train boundary', 'actual', 'prediction'])
    plt.show()


plotting(train_loader, test_loader, y[:500,0])

 

 

 

x1,y1,x2,y2,x3,y3,x4,y4,x5,y5,x6,y6,x7,y7,x8,y8,x,z,y
0,0,1554.5,639.5,1022,561.5,0,0,0,0,0,0,516,580,291.5,778,2,1.5,-8.5
0,0,1478.5,630.5,975,567.5,0,0,0,0,0,0,465.5,591,303.5,811.5,3,1.5,-8.5
0,0,1407,621.5,926,573,0,0,0,0,0,0,410.5,603,317.5,849,4,1.5,-8.5
0,0,1338.5,614,874.5,579,0,0,0,0,0,0,351,615.5,333.5,893,5,1.5,-8.5
0,0,1274,606,821.5,585,0,0,0,0,1865.5,679.5,286.5,629.5,352.5,945,6,1.5,-8.5
0,0,1212,599,765,592,0,0,1516.5,1073.5,1780.5,661,216,644.5,375,1006.5,7,1.5,-8.5
0,0,1154,592,707,599,0,0,1544,1006.5,1703,644.5,138.5,661,403,1073.5,8,1.5,-8.5
0,0,1097.5,585,645,606,0,0,1566.5,945,1632.5,629.5,53.5,679.5,0,0,9,1.5,-8.5
0,0,1044.5,579,580.5,614,0,0,1585.5,893,1568,615.5,0,0,0,0,10,1.5,-8.5
0,0,993,573,512,621.5,0,0,1601.5,849,1508.5,603,0,0,0,0,11,1.5,-8.5
0,0,944,567.5,440.5,630.5,0,0,1615.5,811.5,1453.5,591,0,0,0,0,12,1.5,-8.5
0,0,897,561.5,364.5,639.5,0,0,1627,778,1403,580,0,0,0,0,13,1.5,-8.5
0,0,882,566.5,368.5,647.5,0,0,1572.5,768.5,1384,583.5,0,0,0,0,13,1.5,-8
0,0,929.5,572.5,446,638,0,0,1557,800,1434.5,595,0,0,0,0,12,1.5,-8
0,0,979.5,578,519,629.5,0,0,1539,836,1489,607,0,0,0,0,11,1.5,-8
0,0,1031,584.5,588.5,620.5,0,0,1519,878,1548,619.5,0,0,0,0,10,1.5,-8
0,0,1085,591,654.5,613,0,0,1495,927,1612.5,634.5,71.5,686.5,0,0,9,1.5,-8
0,0,1142,598,717,605,0,0,1466,985,1683.5,650,157.5,667,487.5,1055.5,8,1.5,-8
0,0,1202,605,777,598,0,0,1431.5,1055.5,1761.5,667,235.5,650,453,985,7,1.5,-8
0,0,1264.5,613,833.5,591,0,0,0,0,1847.5,686.5,306.5,634.5,424,927,6,1.5,-8
0,0,1330.5,620.5,888,584.5,0,0,0,0,0,0,371,619.5,400,878,5,1.5,-8
0,0,1400,629.5,939.5,578,0,0,0,0,0,0,430,607,380,836,4,1.5,-8
0,0,1473,638,989.5,572.5,0,0,0,0,0,0,484.5,595,362,800,3,1.5,-8
0,0,1550.5,647.5,1037,566.5,0,0,0,0,0,0,535,583.5,346.5,768.5,2,1.5,-8
0,0,1546.5,656,1052.5,571.5,0,0,0,0,0,0,555,587,399,759,2,1.5,-7.5
0,0,1467.5,646,1004.5,577.5,0,0,0,0,0,0,504.5,598.5,418,789,3,1.5,-7.5
0,0,1392.5,637,954.5,584,0,0,0,0,0,0,450,611,439.5,824,4,1.5,-7.5
0,0,1322,628.5,901.5,590,0,0,0,0,1916.5,714,391,624.5,463.5,863.5,5,1.5,-7.5
0,0,1254.5,619.5,846.5,597,29.5,1072.5,0,0,1828.5,692.5,326.5,639,492.5,910.5,6,1.5,-7.5
0,0,1191,611.5,789,604,0,0,1352,1031,1742,673,255,655,526.5,965,7,1.5,-7.5
0,0,1130,604,728,611.5,0,0,1392.5,965,1664,655,177,673,567,1031,8,1.5,-7.5
1889.5,1072.5,1072,597,664.5,619.5,0,0,1426.5,910.5,1592.5,639,90.5,692.5,0,0,9,1.5,-7.5
0,0,1017.5,590,597,628.5,0,0,1455.5,863.5,1528,624.5,2.5,714,0,0,10,1.5,-7.5
0,0,964.5,584,526.5,637,0,0,1479.5,824,1469,611,0,0,0,0,11,1.5,-7.5
0,0,914.5,577.5,451.5,646,0,0,1501,789,1414.5,598.5,0,0,0,0,12,1.5,-7.5
0,0,866.5,571.5,372.5,656,0,0,1520,759,1364,587,0,0,0,0,13,1.5,-7.5
0,0,850,576.5,377,665,0,0,1469,750,1344,591,0,0,0,0,13,1.5,-7
0,0,899,583,457.5,655,0,0,1447.5,779,1394,602.5,0,0,0,0,12,1.5,-7
0,0,950,589,534,645,0,0,1423,812.5,1448.5,615.5,0,0,0,0,11,1.5,-7
1882,997,1003,596,606,635.5,0,0,1395,850,1507.5,629,14,722,0,0,10,1.5,-7
1802.5,1038.5,1059,603,674.5,626.5,0,0,1362,894,1572.5,644,110.5,699.5,698.5,1074.5,9,1.5,-7
1711,1075.5,1117.5,610.5,739.5,618.5,0,0,1323.5,946,1643.5,661,197,679.5,642,1008.5,8,1.5,-7
0,0,1179.5,618.5,801.5,610.5,208,1075.5,1277,1008.5,1722,679.5,275.5,661,595.5,946,7,1.5,-7
0,0,1244.5,626.5,860,603,116.5,1038.5,1221.5,1074.5,1808.5,699.5,346.5,644,557,894,6,1.5,-7
0,0,1313,635.5,916,596,37,997,0,0,1905,722,411.5,629,524,850,5,1.5,-7
0,0,1385,645,969,589,0,0,0,0,0,0,470.5,615.5,496,812.5,4,1.5,-7
0,0,1461.5,655,1020,583,0,0,0,0,0,0,525,602.5,471.5,779,3,1.5,-7
0,0,1542,665,1069,576.5,0,0,0,0,0,0,575,591,450,750.5,2,1.5,-7
0,0,1538,674.5,1085.5,582,0,0,0,0,0,0,596,594,498.5,741.5,2,1.5,-6.5
0,0,1455,664,1036.5,588,0,0,0,0,0,0,546,606.5,523,769.5,3,1.5,-6.5
0,0,1377.5,653,985,595,43.5,931,0,0,0,0,492,619.5,550.5,800.5,4,1.5,-6.5
0,0,1303,643.5,931,602,115.5,964.5,0,0,1885,730,432.5,633.5,581.5,837,5,1.5,-6.5
0,0,1233.5,634.5,874,609.5,195,1002.5,1146,1057.5,1788,706.5,368,649.5,618.5,879,6,1.5,-6.5
1530,1079,1167.5,625.5,814.5,617.5,284.5,1044.5,1207.5,987,1701,685.5,296.5,666.5,661,928.5,7,1.5,-6.5
1634.5,1044.5,1104.5,617.5,751.5,625.5,389,1079,1258,928.5,1622,666.5,218,685.5,711.5,987,8,1.5,-6.5
1724,1002.5,1045,609.5,685.5,634.5,0,0,1300.5,879,1551,649.5,131,706.5,773,1057.5,9,1.5,-6.5
1803.5,964.5,988,602,616,643.5,0,0,1337.5,837,1486.5,633.5,34,730,0,0,10,1.5,-6.5
1875.5,931,934,595,541.5,653,0,0,1368.5,800.5,1427,619.5,0,0,0,0,11,1.5,-6.5
0,0,882.5,588,464,664,0,0,1396,769.5,1373,606.5,0,0,0,0,12,1.5,-6.5
0,0,833.5,582,381,674.5,0,0,1420.5,741.5,1323,594,0,0,0,0,13,1.5,-6.5
1917,849.5,816,587.5,385.5,684.5,0,0,1373.5,733,1302,598,0,0,0,0,13,1.5,-6
1870.5,876,866,594,470,673,0,0,1347,760,1351.5,611,0,0,0,0,12,1.5,-6
1805,904.5,918,601,550.5,662,0,0,1316.5,790,1405.5,624.5,0,0,0,0,11,1.5,-6
1733,935,973,609,625.5,652,0,0,1282,825,1464.5,638.5,54,738.5,0,0,10,1.5,-6
1653,969.5,1030.5,616.5,697,642.5,0,0,1242.5,864.5,1529,655,152,714,844,1033,9,1.5,-6
1564,1007.5,1090.5,624.5,764,633.5,455,1050.5,1196,911.5,1600.5,672.5,240,692.5,778,966.5,8,1.5,-6
1464,1050.5,1155,633.5,828.5,624.5,355,1007.5,1141,966.5,1679,692.5,318.5,672.5,723,911.5,7,1.5,-6
0,0,1222,642.5,888.5,616.5,266,969.5,1075.5,1033,1767,714,390,655,676.5,864.5,6,1.5,-6
0,0,1293.5,652,946,608.5,186,935,0,0,1865,738.5,454.5,638.5,637,825,5,1.5,-6
0,0,1368.5,662,1001,601,114,904.5,0,0,0,0,513.5,624.5,602.5,790,4,1.5,-6
0,0,1449,673,1053,594,48.5,876,0,0,0,0,567.5,611,572,759.5,3,1.5,-6
0,0,1533.5,684.5,1103,587.5,2,849.5,0,0,0,0,617,598,545.5,733,2,1.5,-6
0,0,1528.5,695,1121,593,53.5,830,0,0,0,0,639,602,590.5,725,2,1.5,-5.5
0,0,1441.5,682.5,1071,600,113.5,854,0,0,0,0,589.5,615,619.5,750.5,3,1.5,-5.5
0,0,1360,671.5,1018,607.5,179,880,0,0,0,0,536,628.5,652,780,4,1.5,-5.5
0,0,1282.5,661,962.5,615.5,251,908.5,924.5,1075.5,1843,746.5,477,644,689,813,5,1.5,-5.5
1290.5,1057,1210,651,903.5,623.5,330.5,940,1009,1009.5,1745,721.5,412,660,732,851.5,6,1.5,-5.5
1401.5,1013.5,1142,641,842.5,632.5,419,974.5,1079,947.5,1656.5,699,341.5,678.5,781.5,895.5,7,1.5,-5.5
1500,974.5,1076.5,632.5,777.5,641,517.5,1013.5,1137.5,895.5,1577.5,678.5,262.5,699,840,947.5,8,1.5,-5.5
1588.5,940,1015,623.5,709,651,628.5,1057,1187,851.5,1507,660,174,721.5,909.5,1009.5,9,1.5,-5.5
1668,908.5,956.5,615.5,636.5,661,0,0,1229.5,813,1442,644,76,746.5,994.5,1075.5,10,1.5,-5.5
1740,880,901,607.5,559,671.5,0,0,1267,780,1383,628.5,0,0,0,0,11,1.5,-5.5
1805.5,854,848,600,477.5,682.5,0,0,1299.5,751,1329.5,615,0,0,0,0,12,1.5,-5.5
1865.5,830,798,593,390.5,695,0,0,1328.5,725,1280,602,0,0,0,0,13,1.5,-5.5
1806.5,811.5,779,599.5,395,706,0,0,1285,717,1257.5,606,0,0,0,0,13,1.5,-5
1746,833,830,606.5,484.5,693.5,0,0,1254,742,1306.5,619.5,0,0,0,0,12,1.5,-5
1680,857.5,883.5,614.5,568,681.5,0,0,1219.5,770,1360,633.5,0,0,0,0,11,1.5,-5
1608.5,883.5,939.5,622.5,647,670,805,1063,1179.5,801.5,1418.5,649,98,755.5,1060.5,1059,10,1.5,-5
1529,912.5,999,631,721.5,659,683,1019,1134,838,1483,666,197,729.5,972,988.5,9,1.5,-5
1441.5,944,1062,640,791,649.5,574.5,979,1082,880,1554.5,685,285.5,706,899,930,8,1.5,-5
1344.5,979,1128,649.5,857.5,640,477.5,944,1020,930,1633.5,706,364.5,685,837,880,7,1.5,-5
1236,1019,1197.5,659,920,631,390,912.5,947,988.5,1722,729.5,436,666,785,838,6,1.5,-5
1114,1063,1272,670,979.5,622.5,310.5,883.5,858.5,1059,1821,755.5,500.5,649,739.5,801.5,5,1.5,-5
0,0,1351,681.5,1035.5,614.5,239,857.5,0,0,0,0,559,633.5,700,770,4,1.5,-5
0,0,1434.5,693.5,1089,606.5,173,833,0,0,0,0,612.5,619.5,665,742,3,1.5,-5
0,0,1524,706,1140,599.5,112.5,811.5,0,0,0,0,661.5,606,634,717,2,1.5,-5
0,0,1518.5,718,1160,605.5,168,794,0,0,0,0,684.5,610.5,675.5,710,2,1.5,-4.5
0,0,1426.5,704.5,1108.5,613.5,228,814.5,0,0,0,0,636,624,709,734,3,1.5,-4.5
935,1067.5,1341,691.5,1054.5,621.5,294,836.5,0,0,1908.5,796,582.5,638.5,745.5,760.5,4,1.5,-4.5
1068,1024.5,1260.5,679.5,997,629.5,365.5,860.5,797,1035,1797.5,765,524.5,654,787,791,5,1.5,-4.5
1187,984,1184.5,668.5,936.5,638.5,444,887,888.5,968,1698,737.5,460,672,835,826,6,1.5,-4.5
1293,948.5,1113.5,658,873,648,530.5,916.5,964.5,912.5,1609.5,713,388.5,691.5,890.5,866,7,1.5,-4.5
1388.5,916.5,1046,648,805.5,658,626,948.5,1028.5,866,1530.5,691.5,309.5,713,954.5,912.5,8,1.5,-4.5
1475,887,982,638.5,734.5,668.5,732,984,1084,826,1459,672,221,737.5,1030.5,968.5,9,1.5,-4.5
1553.5,860.5,922,629.5,659,679.5,851,1024.5,1132,791,1394.5,654,121.5,765,1122,1035,10,1.5,-4.5
1625,836.5,864.5,621.5,578,691.5,984,1067.5,1173.5,760.5,1336.5,638.5,10.5,796,0,0,11,1.5,-4.5
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1148,692.5,655.5,740.5,843,835,1158.5,765.5,715,697.5,1072.5,727,458,899.5,1604.5,842,10,1.5,1
1080.5,705,727.5,756.5,941.5,813,1069.5,748.5,653,720,1131,752.5,559,854.5,1502,805.5,9,1.5,1
1008.5,719,804.5,774,1031,792.5,987,733.5,584,744.5,1197,782,646,815.5,1413,773,8,1.5,1
932,733.5,887.5,792.5,1114.5,774,910.5,719,506,773,1273,815.5,722,782,1335,744.5,7,1.5,1
849.5,748.5,977.5,813,1191.5,756.5,838.5,705,417,805.5,1360,854.5,788,752.5,1266,720,6,1.5,1
760.5,765.5,1076,835,1263.5,740.5,771,692.5,314.5,842,1461,899.5,846.5,727,1204,697.5,5,1.5,1
665,784,1182.5,859.5,1330,725.5,708,680.5,197,885,1580,952,899,703.5,1148.5,677.5,4,1.5,1
561.5,803.5,1299.5,885.5,1392.5,711,648.5,669,58,935,1722.5,1015.5,945.5,683,1098.5,659,3,1.5,1
449.5,824.5,1428.5,914.5,1450.5,698.5,592.5,659,0,0,1890,1078.5,987.5,664,1053,642.5,2,1.5,1
441,806.5,1416,942,1486,709.5,620,650,0,0,0,0,1020.5,670,1081,637.5,2,1.5,1.5
549.5,786,1282,910.5,1427.5,723.5,675.5,660,28,918,1682.5,1038.5,979.5,689.5,1127,653.5,3,1.5,1.5
650,768,1161,882,1364.5,738.5,733.5,671,166,870.5,1539.5,971.5,933.5,711,1178,671,4,1.5,1.5
743.5,751.5,1051.5,855.5,1297,754.5,796,682,283.5,830,1420.5,915.5,882.5,735,1234,690.5,5,1.5,1.5
830,735.5,950.5,832,1224,771.5,862,694.5,385,794.5,1320,868.5,825,762,1296.5,712,6,1.5,1.5
910.5,721,858.5,810.5,1146,790,933,707,474,763.5,1234,828,760,792.5,1366,736.5,7,1.5,1.5
986,707,773,790,1060.5,810.5,1008.5,721,553,736.5,1159,792.5,685,828,1445,763.5,8,1.5,1.5
1057,694.5,695,771.5,968.5,832,1089,735.5,622.5,712,1094,762,599,868.5,1534,794.5,9,1.5,1.5
1123,682,622,754.5,867.5,855.5,1175.5,751.5,685,690.5,1036.5,735,498.5,915.5,1635.5,830,10,1.5,1.5
1185.5,670.5,554.5,738.5,758,882,1269,768,741,671,985.5,711,379.5,971.5,1753,870.5,11,1.5,1.5
1243.5,660,491.5,723.5,637,910.5,1369.5,786,792,653.5,939.5,689.5,236.5,1038.5,1891,918,12,1.5,1.5
1299.5,650,433,709.5,503,942,1478,806.5,838,637.5,898.5,670,0,0,0,0,13,1.5,1.5
1273,642,395,721.5,516.5,972,1486,789,810.5,632.5,864.5,676,0,0,0,0,13,1.5,2
1218.5,651,454.5,736.5,655.5,938,1380.5,770.5,764,648.5,904,696.5,279,1063,1911,901.5,12,1.5,2
1160.5,661.5,518,752.5,780.5,906.5,1282.5,753.5,712.5,665,949,718,422.5,992,1782.5,856.5,11,1.5,2
1099.5,672,586,769,894.5,878,1192,737.5,656,684,999,743.5,541.5,932.5,1666,817.5,10,1.5,2
1034,683.5,660,787.5,997.5,852.5,1107.5,723,593,705,1055.5,771.5,641,883,1564,784,9,1.5,2
965,695.5,740,807.5,1092,829,1028.5,709,523,728,1119.5,803.5,726,840,1475,754.5,8,1.5,2
890.5,709,827,829,1178.5,807.5,954,695.5,444,754.5,1193,840,799.5,803.5,1396,728,7,1.5,2
811.5,722.5,921.5,852.5,1259,787.5,885,683.5,355,784,1278,883,863.5,771.5,1326,705,6,1.5,2
727,737.5,1024.5,878,1333,769,819.5,672,253,817.5,1377.5,932.5,920,743.5,1263,684,5,1.5,2
636.5,753.5,1138,906.5,1401,752.5,758.5,661.5,136.5,856.5,1496.5,992,970.5,718,1206.5,665,4,1.5,2
538.5,770.5,1263.5,938,1464.5,736.5,700.5,651,8,901.5,1640,1063,1015,696.5,1155,648.5,3,1.5,2
433,789,1402.5,972,1524,721.5,646,642,0,0,0,0,1054.5,676,1108.5,632.5,2,1.5,2
425.5,773,1387,1005.5,1564,734.5,670.5,634,0,0,0,0,1090,682.5,1135.5,627.5,2,1.5,2.5
528,755.5,1242.5,967.5,1504,749.5,725,643,0,0,1591,1077.5,1051,703.5,1182,643,3,1.5,2.5
623,739.5,1113,933,1440,767,782,653,108.5,843,1450.5,1013.5,1007.5,726,1234.5,659.5,4,1.5,2.5
712,724.5,995.5,902.5,1370.5,785,842.5,663,224.5,806.5,1332.5,950.5,959,752.5,1291,677.5,5,1.5,2.5
794.5,710.5,889.5,874.5,1296,804.5,906.5,673.5,326,774,1233.5,898,904,781.5,1354.5,698,6,1.5,2.5
872,697.5,792.5,849,1215,826,974.5,685.5,415,745.5,1149.5,853.5,841.5,815,1425,720,7,1.5,2.5
944.5,685.5,704,826,1126.5,849,1047,697.5,494,720,1077.5,815,769.5,853.5,1504,745.5,8,1.5,2.5
1012.5,673.5,623,804.5,1029.5,874.5,1124.5,710.5,564.5,697.5,1015,781.5,685.5,898,1593,774,9,1.5,2.5
1076.5,663,548.5,785,923.5,902.5,1207,724.5,628,677.5,960,752.5,586.5,950.5,1694.5,806.5,10,1.5,2.5
1137,653,479,767,806,933,1296,739.5,684.5,659.5,911.5,726,468.5,1013.5,1810.5,843,11,1.5,2.5
1194,643,415,749.5,676.5,967.5,1391,755.5,737,643.5,868,703.5,329,1077.5,0,0,12,1.5,2.5
1248.5,634,355,734.5,532,1005.5,1493.5,773,783.5,627.5,829,682.5,0,0,0,0,13,1.5,2.5
1225,626.5,312.5,747.5,549,1042,1500,757.5,758,623.5,793,688.5,0,0,0,0,13,1.5,3
1171.5,635,372.5,764.5,699.5,1000,1400.5,741.5,710,638.5,830.5,710.5,0,0,0,0,12,1.5,3
1115,644,437.5,782.5,834,962.5,1308,726.5,658,654,872,734.5,517.5,1036.5,1837.5,831,11,1.5,3
1055,654,507.5,801.5,955,929,1221.5,712,600.5,671.5,919.5,761.5,634.5,969.5,1722,795.5,10,1.5,3
992,664,583,823,1064,898.5,1141,699,537,691,973,792,732,914.5,1621,764,9,1.5,3
925.5,675.5,665.5,846,1163,871,1065,686.5,466,713,1034,827,814.5,867,1532,737,8,1.5,3
854,686.5,756,871,1253.5,846,993.5,675,387,737,1104.5,867,885,827,1453,713,7,1.5,3
778,699.5,855,898.5,1336,823,927,664,298,764,1187,914.5,946,792,1382,691.5,6,1.5,3
697.5,712,964,929,1411.5,801.5,864,654,197,795.5,1284.5,969.5,999.5,761.5,1318.5,671.5,5,1.5,3
611,726.5,1085,962.5,1481.5,782.5,804,644,81.5,831,1401.5,1036.5,1047,734.5,1261,654,4,1.5,3
518.5,741.5,1219.5,1000,1546.5,764.5,747.5,635,0,0,0,0,1088.5,710.5,1209,638,3,1.5,3
419,757.5,1370.5,1042,1606.5,747.5,694,626.5,0,0,0,0,1126,688.5,1161,623.5,2,1.5,3
412.5,743.5,1351,1074,1651.5,762,716.5,619.5,0,0,0,0,1164,695.5,1186.5,618.5,2,1.5,3.5
509,728.5,1194.5,1036,1591,780,769.5,627.5,0,0,0,0,1127.5,718,1234,633.5,3,1.5,3.5
599.5,714,1054.5,994.5,1526,799.5,825.5,636.5,56,818.5,1349.5,1061,1087,742.5,1287,648.5,4,1.5,3.5
683.5,701,929.5,957.5,1455.5,820,884,645.5,170.5,785,1233.5,990,1041.5,771,1344.5,666,5,1.5,3.5
763,688.5,818,924.5,1378.5,843,946,655,271.5,755,1138,931,990,802.5,1408.5,684.5,6,1.5,3.5
837,676.5,716.5,895,1295,867.5,1012,666,360.5,729,1057,881.5,931,839,1479.5,705.5,7,1.5,3.5
907,666,624,867.5,1202.5,895,1082,676.5,439.5,705.5,988,839,862,881.5,1558.5,729,8,1.5,3.5
973,655,540.5,843,1101,924.5,1156,688.5,510.5,684.5,929,802.5,781,931,1647.5,755,9,1.5,3.5
1035,645.5,463.5,820,989.5,957.5,1235.5,701,574.5,665.5,877.5,771,685.5,990,1748.5,785,10,1.5,3.5
1094,636.5,393,799.5,864.5,994.5,1319.5,714,632,648.5,832,742.5,569.5,1061,1863,818.5,11,1.5,3.5
1149.5,627.5,328,780,724.5,1036,1410,728.5,685,633.5,791.5,718,0,0,0,0,12,1.5,3.5
1202.5,619.5,267.5,762,568,1074,1506.5,743.5,732.5,618.5,755,695.5,0,0,0,0,13,1.5,3.5
1180.5,612.5,219.5,777,0,0,1512.5,730.5,708.5,614.5,716,702.5,0,0,0,0,13,1.5,4
1128.5,620.5,279.5,796.5,752.5,1071,1418.5,716,660,628.5,750.5,726,0,0,0,0,12,1.5,4
1073.5,628.5,345.5,817,898,1030,1330.5,702.5,607,643.5,789.5,751.5,627,1076.5,1888,807.5,11,1.5,4
1015.5,637.5,417,840,1027,989.5,1248,690.5,548.5,660,833,781,739.5,1011.5,1773.5,775,10,1.5,4
954,647,494.5,864.5,1142,953.5,1171,678.5,485,678.5,883.5,814,833.5,949,1673.5,746.5,9,1.5,4
889.5,657,579.5,891,1246,920.5,1098,667,413.5,698.5,940.5,852.5,911.5,897,1584.5,721,8,1.5,4
821,667,673,920.5,1339.5,891,1029.5,657,334.5,721,1007,897,978.5,852.5,1505.5,698.5,7,1.5,4
748,678.5,776.5,953.5,1424.5,864.5,965,647,245.5,746.5,1085.5,949,1035.5,814,1434.5,678.5,6,1.5,4
671,690.5,892,989.5,1502,840,903.5,637.5,145.5,775,1179.5,1011.5,1086,781,1370.5,660,5,1.5,4
588.5,702.5,1021,1030,1573.5,817,845.5,628.5,31.5,807.5,1292,1076.5,1129.5,751.5,1312,643.5,4,1.5,4
500.5,716,1166.5,1071,1639.5,796.5,790.5,620.5,0,0,0,0,1168.5,726,1259,628.5,3,1.5,4
406.5,730.5,0,0,1699.5,777,738.5,612.5,0,0,0,0,1203,702.5,1210.5,614.5,2,1.5,4
400.5,718,0,0,1751,794,759,605.5,0,0,0,0,1243.5,710,1234.5,610.5,2,1.5,4.5
492.5,704.5,0,0,1691,814.5,810.5,613.5,0,0,0,0,1210,734,1283,623.5,3,1.5,4.5
578,691.5,984,1067.5,1625,836.5,864.5,621.5,10.5,796,0,0,1173.5,760.5,1336.5,638.5,4,1.5,4.5
659,679.5,851,1024.5,1553.5,860.5,922,629.5,121.5,765,1122,1035,1132,791,1394.5,654,5,1.5,4.5
734.5,668.5,732,984,1475,887,982,638.5,221,737.5,1030.5,968.5,1084,826,1459,672,6,1.5,4.5
805.5,658,626,948.5,1388.5,916.5,1046,648,309.5,713,954.5,912.5,1028.5,866,1530.5,691.5,7,1.5,4.5
873,648,530.5,916.5,1293,948.5,1113.5,658,388.5,691.5,890.5,866,964.5,912.5,1609.5,713,8,1.5,4.5
936.5,638.5,444,887,1187,984,1184.5,668.5,460,672,835,826,888.5,968,1698,737.5,9,1.5,4.5
997,629.5,365.5,860.5,1068,1024.5,1260.5,679.5,524.5,654,787,791,797,1035,1797.5,765,10,1.5,4.5
1054.5,621.5,294,836.5,935,1067.5,1341,691.5,582.5,638.5,745.5,760.5,0,0,1908.5,796,11,1.5,4.5
1108.5,613.5,228,814.5,0,0,1426.5,704.5,636,624,709,734,0,0,0,0,12,1.5,4.5
1160,605.5,168,794,0,0,1518.5,718,684.5,610.5,675.5,710,0,0,0,0,13,1.5,4.5
1140,599.5,112.5,811.5,0,0,1524,706,661.5,606,634,717,0,0,0,0,13,1.5,5
1089,606.5,173,833,0,0,1434.5,693.5,612.5,619.5,665,742,0,0,0,0,12,1.5,5
1035.5,614.5,239,857.5,0,0,1351,681.5,559,633.5,699.5,770,0,0,0,0,11,1.5,5
979.5,622.5,310.5,883.5,1114,1063,1272,670,500.5,649,739.5,801.5,858.5,1059,1821,755.5,10,1.5,5
920,631,390,912.5,1236,1019,1197.5,659,436,666,785,838,947,988.5,1722,729.5,9,1.5,5
857.5,640,477.5,944,1344.5,979,1128,649.5,364.5,685,837,880,1020,930,1633.5,706,8,1.5,5
791,649.5,574.5,979,1441.5,944,1061.5,640,285.5,706,899,930,1082,880,1554.5,685,7,1.5,5
721.5,659,683,1019,1529,912.5,999,631,197,729.5,972,988.5,1134,838,1483,666,6,1.5,5
647,670,805,1063,1608.5,883.5,939.5,622.5,98,755.5,1060.5,1059,1179.5,801.5,1418.5,649,5,1.5,5
568,681.5,0,0,1680,857.5,883.5,614.5,0,0,0,0,1219.5,770,1360,633.5,4,1.5,5
484.5,693.5,0,0,1746,833,830,606.5,0,0,0,0,1254,742,1306.5,619.5,3,1.5,5
395,706,0,0,1806.5,811.5,779,599.5,0,0,0,0,1285,717,1257.5,606,2,1.5,5
390.5,695,0,0,1865.5,830,798,593,0,0,0,0,1328.5,725,1280,602,2,1.5,5.5
477.5,682.5,0,0,1805.5,854,848,600,0,0,0,0,1299.5,751,1329.5,615,3,1.5,5.5
559,671.5,0,0,1740,880,901,607.5,0,0,0,0,1267,780,1383,628.5,4,1.5,5.5
636.5,661,0,0,1668,908.5,956.5,615.5,76,746.5,994.5,1075.5,1229.5,813,1442,644,5,1.5,5.5
709,651,628.5,1057,1588.5,940,1015,623.5,174,721.5,910,1009.5,1187,851.5,1507,660,6,1.5,5.5
777.5,641,517.5,1013.5,1500,974.5,1076.5,632.5,262.5,699,840,947.5,1137.5,895.5,1577.5,678.5,7,1.5,5.5
842.5,632.5,419,974.5,1401.5,1013.5,1142,641,341.5,678.5,781.5,895.5,1079,947.5,1656.5,699,8,1.5,5.5
903.5,623.5,330.5,940,1290.5,1057,1210,651,412,660,732,851.5,1009,1009.5,1745,721.5,9,1.5,5.5
962.5,615.5,251,908.5,0,0,1282.5,661,477,644,689,813,924.5,1075.5,1843,746.5,10,1.5,5.5
1018,607.5,179,880,0,0,1360,671.5,536,628.5,652,780,0,0,0,0,11,1.5,5.5
1071,600,113.5,854,0,0,1441.5,682.5,589.5,615,619.5,750.5,0,0,0,0,12,1.5,5.5
1121,593,53.5,830,0,0,1528.5,695,639,602,590.5,725,0,0,0,0,13,1.5,5.5
1103,587.5,2,849.5,0,0,1533.5,684.5,617,598,545.5,733,0,0,0,0,13,1.5,6
1053,594,48.5,876,0,0,1449,673,567.5,611,572,759.5,0,0,0,0,12,1.5,6
1001,601,114,904.5,0,0,1368.5,662,513.5,624.5,602.5,790,0,0,0,0,11,1.5,6
946,608.5,186,935,0,0,1293.5,652,454.5,638.5,637,825,0,0,1865,738.5,10,1.5,6
888.5,616.5,266,969.5,0,0,1222,642.5,390,655,676.5,864.5,1075.5,1033,1767,714,9,1.5,6
828.5,624.5,355,1007.5,1464,1050.5,1155,633.5,318.5,672.5,723,911.5,1141,966.5,1679,692.5,8,1.5,6
764,633.5,455,1050.5,1564,1007.5,1090.5,624.5,240,692.5,778,966.5,1196,911.5,1600.5,672.5,7,1.5,6
697,642.5,0,0,1653,969.5,1030.5,616.5,152,714,844,1033,1242.5,864.5,1529,655,6,1.5,6
625.5,652,0,0,1733,935,973,609,54,738.5,0,0,1282,825,1464.5,638.5,5,1.5,6
550.5,662,0,0,1805,904.5,918,601,0,0,0,0,1316.5,790,1405.5,624.5,4,1.5,6
470,673,0,0,1870.5,876,866,594,0,0,0,0,1347,760,1351.5,611,3,1.5,6
385.5,684.5,0,0,1917,849.5,816,587.5,0,0,0,0,1373.5,733,1302,598,2,1.5,6
381,674.5,0,0,0,0,833.5,582,0,0,0,0,1420.5,741.5,1323,594,2,1.5,6.5
464,664,0,0,0,0,882.5,588,0,0,0,0,1396,769.5,1373,606.5,3,1.5,6.5
541.5,653,0,0,1875.5,931,934,595,0,0,0,0,1368.5,800.5,1427,619.5,4,1.5,6.5
616,643.5,0,0,1803.5,964.5,988,602,34,730,0,0,1337.5,837,1486.5,633.5,5,1.5,6.5
685.5,634.5,0,0,1724,1002.5,1045,609.5,131,706.5,773,1057.5,1300.5,879,1551,649.5,6,1.5,6.5
751.5,625.5,389,1079,1634.5,1044.5,1104.5,617.5,218,685.5,711.5,987,1258,928.5,1622.5,666.5,7,1.5,6.5
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874,609.5,195,1002.5,0,0,1233.5,634.5,368,649.5,618.5,879,1146,1057.5,1788,706.5,9,1.5,6.5
931,602,115.5,964.5,0,0,1303,643.5,432.5,633.5,581.5,837,0,0,1885,730,10,1.5,6.5
985,595,43.5,931,0,0,1377.5,653,492,619.5,550.5,800.5,0,0,0,0,11,1.5,6.5
1036.5,588,0,0,0,0,1455,664,546,606.5,523,769.5,0,0,0,0,12,1.5,6.5
1085.5,582,0,0,0,0,1538,674.5,596,594,498.5,741.5,0,0,0,0,13,1.5,6.5
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1020,583,0,0,0,0,1461.5,655,525,602.5,471.5,779,0,0,0,0,12,1.5,7
969,589,0,0,0,0,1385,645,470.5,615.5,496,812.5,0,0,0,0,11,1.5,7
916,596,37,997,0,0,1313,635.5,411.5,629,524,850,0,0,1905,722,10,1.5,7
860,603,116.5,1038.5,0,0,1244.5,626.5,346.5,644,557,894,1221.5,1074.5,1808.5,699.5,9,1.5,7
801.5,610.5,208,1075.5,0,0,1179.5,618.5,275.5,661,595.5,946,1277,1008.5,1722,679.5,8,1.5,7
739.5,618.5,0,0,1711,1075.5,1117.5,610.5,197,679.5,642,1008.5,1323.5,946,1643.5,661,7,1.5,7
674.5,626.5,0,0,1802.5,1038.5,1059,603,110.5,699.5,698.5,1074.5,1362,894,1572.5,644,6,1.5,7
606,635.5,0,0,1882,997,1003,596,14,722,0,0,1395,850,1507.5,629,5,1.5,7
534,645,0,0,0,0,950,589,0,0,0,0,1423,812.5,1448.5,615.5,4,1.5,7
457.5,655,0,0,0,0,899,583,0,0,0,0,1447.5,779,1394,602.5,3,1.5,7
377,665,0,0,0,0,850,576.5,0,0,0,0,1469,750,1344,591,2,1.5,7
372.5,656,0,0,0,0,866.5,571.5,0,0,0,0,1520,759,1364,587,2,1.5,7.5
451.5,646,0,0,0,0,914.5,577.5,0,0,0,0,1501,789,1414.5,598.5,3,1.5,7.5
526.5,637,0,0,0,0,964.5,584,0,0,0,0,1479.5,824,1469,611,4,1.5,7.5
597,628.5,0,0,0,0,1017.5,590,2.5,714,0,0,1455.5,863.5,1528,624.5,5,1.5,7.5
664.5,619.5,0,0,1889.5,1072.5,1072,597,90.5,692.5,0,0,1426.5,910.5,1592.5,639,6,1.5,7.5
728,611.5,0,0,0,0,1130,604,177,673,567,1031,1392.5,965,1664,655,7,1.5,7.5
789,604,0,0,0,0,1191,611.5,255,655,526.5,965,1352,1031,1742,673,8,1.5,7.5
846.5,597,29.5,1072.5,0,0,1254.5,619.5,326.5,639,492.5,910.5,0,0,1828.5,692.5,9,1.5,7.5
901.5,590,0,0,0,0,1322,628.5,391,624.5,463.5,863.5,0,0,1916.5,714,10,1.5,7.5
954.5,584,0,0,0,0,1392.5,637,450,611,439.5,824,0,0,0,0,11,1.5,7.5
1004.5,577.5,0,0,0,0,1467.5,646,504.5,598.5,418,789,0,0,0,0,12,1.5,7.5
1052.5,571.5,0,0,0,0,1546.5,656,555,587,399,759,0,0,0,0,13,1.5,7.5
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