From 2dce59044658e9c4bf402b33cb46f9b445c97791 Mon Sep 17 00:00:00 2001 From: Newnius Date: Sat, 2 May 2020 19:48:21 +0800 Subject: [PATCH] update --- .idea/workspace.xml | 52 ++++++++++++++++++++++----------------------- serve.py | 16 +++----------- 2 files changed, 28 insertions(+), 40 deletions(-) diff --git a/.idea/workspace.xml b/.idea/workspace.xml index c5105eb..46ffb18 100644 --- a/.idea/workspace.xml +++ b/.idea/workspace.xml @@ -1,9 +1,7 @@ - - - + @@ -229,7 +227,7 @@ - + @@ -270,12 +268,12 @@ - @@ -401,21 +399,21 @@ - - + + - - - + + + - - + + @@ -424,8 +422,8 @@ - - + + diff --git a/serve.py b/serve.py index 42a6336..94ac1b9 100644 --- a/serve.py +++ b/serve.py @@ -97,11 +97,7 @@ def train_models(job): # transform data to be supervised learning lag = 4 supervised = timeseries_to_supervised(diff_values, lag) - print(supervised) - print(type(supervised)) - print(supervised.shape) supervised_values = supervised.values - print(supervised_values) batch_size = 32 if supervised_values.shape[0] < 100: @@ -161,21 +157,13 @@ def predict(job, seq): # transform data to be stationary raw_values = df.values - print(raw_values) diff_values = difference(raw_values, 1) - print(diff_values) # transform data to be supervised learning lag = 4 supervised = timeseries_to_supervised(diff_values, lag) - print(type(supervised)) - print(supervised) supervised_values = supervised[-batch_size:] - print(type(supervised_values)) - print(supervised_values) - print(supervised_values.shape) test = supervised_values.values - print(test) test = test.reshape(test.shape[0], test.shape[1]) test_scaled = scaler.transform(test) @@ -198,7 +186,7 @@ def predict(job, seq): rmse = sqrt(mean_squared_error(raw_values[-batch_size:], predictions)) print(predictions, raw_values[-batch_size:]) - return 1, True + return predictions[-1], True class MyHandler(BaseHTTPRequestHandler): @@ -223,6 +211,8 @@ class MyHandler(BaseHTTPRequestHandler): if not success: msg = {'code': 2, 'error': "Job " + job + " not exist"} + else: + msg = {'code': 2, 'error': "", "total": pred} except Exception as e: track = traceback.format_exc() print(track)