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Newnius 2020-05-02 17:31:33 +08:00
parent c2a1e9156e
commit d305fd31f3
2 changed files with 21 additions and 20 deletions
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31
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10
serve.py
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@ -136,14 +136,15 @@ def predict(job, seq):
'value': 0, 'value': 0,
} }
df = pd.read_csv('./data/' + job + '.csv', usecols=['seq', 'value'])
df = df.tail(int(models[job]['batch_size']) * 2 - 1)
df = df.append(data, ignore_index=True)
batch_size = int(models[job]['batch_size']) batch_size = int(models[job]['batch_size'])
df = pd.read_csv('./data/' + job + '.csv', usecols=['seq', 'value'])
df = df.tail(batch_size * 2 - 1)
df = df.append(data, ignore_index=True)
# transform data to be stationary # transform data to be stationary
raw_values = df.values raw_values = df.values
print(raw_values)
diff_values = difference(raw_values, 1)[batch_size:] diff_values = difference(raw_values, 1)[batch_size:]
# transform data to be supervised learning # transform data to be supervised learning
lag = 4 lag = 4
@ -151,6 +152,7 @@ def predict(job, seq):
supervised_values = supervised.values supervised_values = supervised.values
test = supervised_values test = supervised_values
print(test)
test = test.reshape(test.shape[0], test.shape[1]) test = test.reshape(test.shape[0], test.shape[1])
test_scaled = models[job]['scaler'].transform(test) test_scaled = models[job]['scaler'].transform(test)