ARIMA Prediction

COVID-19/Prediction/Prediction.sln

@@ -3,7 +3,9 @@ Microsoft Visual Studio Solution File, Format Version 12.00
 # Visual Studio Version 16
 VisualStudioVersion = 16.0.30804.86
 MinimumVisualStudioVersion = 10.0.40219.1
-Project("{888888A0-9F3D-457C-B088-3A5042F75D52}") = "Prediction", "Prediction\Prediction.pyproj", "{FE4194E6-8A95-4B93-968D-ED4305D7F944}"
+Project("{888888A0-9F3D-457C-B088-3A5042F75D52}") = "Holt_Winters", "Prediction\Holt_Winters.pyproj", "{FE4194E6-8A95-4B93-968D-ED4305D7F944}"
+EndProject
+Project("{888888A0-9F3D-457C-B088-3A5042F75D52}") = "Holt_Linear_Trend", "Prediction\Holt_Linear_Trend.pyproj", "{3F8A3B3F-C79E-412C-8EE4-DA8FF5DB31A6}"
 EndProject
 Global
 	GlobalSection(SolutionConfigurationPlatforms) = preSolution
@@ -13,6 +15,8 @@ Global
 	GlobalSection(ProjectConfigurationPlatforms) = postSolution
 		{FE4194E6-8A95-4B93-968D-ED4305D7F944}.Debug|Any CPU.ActiveCfg = Debug|Any CPU
 		{FE4194E6-8A95-4B93-968D-ED4305D7F944}.Release|Any CPU.ActiveCfg = Release|Any CPU
+		{3F8A3B3F-C79E-412C-8EE4-DA8FF5DB31A6}.Debug|Any CPU.ActiveCfg = Debug|Any CPU
+		{3F8A3B3F-C79E-412C-8EE4-DA8FF5DB31A6}.Release|Any CPU.ActiveCfg = Release|Any CPU
 	EndGlobalSection
 	GlobalSection(SolutionProperties) = preSolution
 		HideSolutionNode = FALSE

COVID-19/Prediction/Prediction/Holt_Linear_Trend.py

@@ -0,0 +1,122 @@
+import pandas as pd              
+import datetime as DT
+import numpy as np
+import matplotlib.pyplot as plt
+import matplotlib.dates as mdates
+import math
+import statsmodels.api as sm
+from sklearn.metrics import mean_squared_error
+
+#打开数据文件
+dataset = pd.read_csv('E:\dase intro\COVID-19Analysis\COVID-19\covid-19-all.csv')
+
+#数据预处理
+def parse_ymd(s):
+	year_s, mon_s, day_s = s.split('-')
+	return datetime.datetime(int(year_s), int(mon_s), int(day_s)).strftime("%Y-%m-%d")
+dataset = dataset.fillna(0)
+dataset['Date'] = pd.to_datetime(dataset['Date'])
+dataset = dataset[['Country/Region','Confirmed','Recovered','Deaths','Date']].groupby(['Country/Region','Date']).sum().reset_index()
+
+#取出中、美的数据
+CN = dataset[dataset['Country/Region'] == 'China']
+CN.index = pd.Index(pd.date_range('2020-01-22','2020-12-09',freq = '1D'))  
+US = dataset[dataset['Country/Region'] == 'US']
+US.index = pd.Index(pd.date_range('2020-01-22','2020-12-09',freq = '1D'))  
+
+#划分训练集、测试集
+trainCN = CN[CN['Date'] < '2020-11-01 ']  
+testCN = CN[CN['Date'] >= '2020-11-01']
+
+trainUS = US[US['Date'] < '2020-11-01 ']  
+testUS = US[US['Date'] >= '2020-11-01']
+
+#自回归移动平均模型（ARIMA）
+yCNARIMA = testCN.copy()
+yUSARIMA = testUS.copy()
+
+#训练模型
+fitCNconfirmed = sm.tsa.statespace.SARIMAX(trainCN.Confirmed).fit()
+fitCNrecovered = sm.tsa.statespace.SARIMAX(trainCN['Recovered']).fit()
+fitCNdeaths = sm.tsa.statespace.SARIMAX(trainCN['Deaths']).fit()
+
+fitUSconfirmed = sm.tsa.statespace.SARIMAX(trainUS.Confirmed,trend='ct').fit()
+fitUSrecovered = sm.tsa.statespace.SARIMAX(trainUS['Recovered']).fit()
+fitUSdeaths = sm.tsa.statespace.SARIMAX(trainUS['Deaths']).fit()
+
+#测试
+yCNARIMA['SARIMAconfirmed'] = fitCNconfirmed.predict(start="2020-11-01", end="2020-12-09", dynamic=True)
+yCNARIMA['SARIMArecovered'] = fitCNrecovered.predict(start="2020-11-01", end="2020-12-09", dynamic=True)
+yCNARIMA['SARIMAdeaths'] = fitCNdeaths.predict(start="2020-11-01", end="2020-12-09", dynamic=True)
+
+yUSARIMA['SARIMAconfirmed'] = fitUSconfirmed.predict(start="2020-11-01", end="2020-12-09")
+yUSARIMA['SARIMArecovered'] = fitUSrecovered.predict(start="2020-11-01", end="2020-12-09", dynamic=True)
+yUSARIMA['SARIMAdeaths'] = fitUSdeaths.predict(start="2020-11-01", end="2020-12-09", dynamic=True)
+
+#预测将来七天
+forecastCNARIMA = pd.DataFrame({'Date':['2020-12-10','2020-12-11','2020-12-12','2020-12-13','2020-12-14','2020-12-15','2020-12-16']})
+forecastUSARIMA = pd.DataFrame({'Date':['2020-12-10','2020-12-11','2020-12-12','2020-12-13','2020-12-14','2020-12-15','2020-12-16']})
+
+forecastCNARIMA['Date'] = pd.to_datetime(forecastCNARIMA['Date'], format='%Y/%m/%d').values.astype('datetime64[h]')  
+forecastCNARIMA['confirmedPred'] = fitCNconfirmed.predict(start="2020-12-10", end="2020-12-16", dynamic=True)
+forecastCNARIMA['recoveredPred'] = fitCNrecovered.predict(start="2020-12-10", end="2020-12-16", dynamic=True)
+forecastCNARIMA['deathsPred'] = fitCNdeaths.predict(start="2020-12-10", end="2020-12-16", dynamic=True)
+
+forecastUSARIMA['Date'] = pd.to_datetime(forecastUSARIMA['Date'], format='%Y/%m/%d').values.astype('datetime64[h]')  
+forecastUSARIMA['confirmedPred'] = fitUSconfirmed.predict(start="2020-12-10", end="2020-12-16", dynamic=True)
+forecastUSARIMA['recoveredPred'] = fitUSrecovered.predict(start="2020-12-10", end="2020-12-16", dynamic=True)
+forecastUSARIMA['deathsPred'] = fitUSdeaths.predict(start="2020-12-10", end="2020-12-16", dynamic=True)
+
+#RMSE
+rmseCNARIMACon = pow(mean_squared_error(np.asarray(testCN['Confirmed']), np.asarray(yCNARIMA['SARIMAconfirmed'])),0.05)
+rmseCNARIMARec = pow(mean_squared_error(np.asarray(testCN['Recovered']), np.asarray(yCNARIMA['SARIMArecovered'])),0.05)
+rmseCNARIMADea = pow(mean_squared_error(np.asarray(testCN['Deaths']), np.asarray(yCNARIMA['SARIMAdeaths'])),0.5)
+
+rmseUSARIMACon = pow(mean_squared_error(np.asarray(testUS['Confirmed']), np.asarray(yUSARIMA['SARIMAconfirmed'])),0.05)
+rmseUSARIMARec = pow(mean_squared_error(np.asarray(testUS['Recovered']), np.asarray(yUSARIMA['SARIMArecovered'])),0.05)
+rmseUSARIMADea = pow(mean_squared_error(np.asarray(testUS['Deaths']), np.asarray(yUSARIMA['SARIMAdeaths'])),0.05)
+
+#可视化
+fig = plt.figure()
+axCNARIMA = fig.add_subplot(211)
+axCNARIMA.set_title("ARIMA (CN)",verticalalignment="bottom",fontsize="13")
+
+CN.index = pd.Index(pd.date_range('2020-01-22','2020-12-09',freq = '1D'))  
+yCNARIMA.index = pd.Index(pd.date_range('2020-11-01','2020-12-09',freq = '1D'))  
+forecastCNARIMA.index = pd.Index(pd.date_range('2020-12-10','2020-12-16',freq = '1D'))  
+
+axCNARIMA.plot(CN['Confirmed'],label="confirmed",linestyle=":")
+axCNARIMA.plot(CN['Recovered'],label="recovered",linestyle=":")
+axCNARIMA.plot(CN['Deaths'],label="deaths",linestyle=":")
+
+axCNARIMA.plot(yCNARIMA['SARIMAconfirmed'],label="confirmed test")
+axCNARIMA.plot(yCNARIMA['SARIMArecovered'],label="recovered test")
+axCNARIMA.plot(yCNARIMA['SARIMAdeaths'],label="deaths test")
+
+axCNARIMA.plot(forecastCNARIMA['confirmedPred'],label="confirmed prediction")
+axCNARIMA.plot(forecastCNARIMA['recoveredPred'],label="recovered prediction")
+axCNARIMA.plot(forecastCNARIMA['deathsPred'],label="deaths prediction")
+
+axUSARIMA = fig.add_subplot(212)
+axUSARIMA.set_title("ARIMA (US)",verticalalignment="bottom",fontsize="13")
+
+US.index = pd.Index(pd.date_range('2020-01-22','2020-12-09',freq = '1D'))  
+yUSARIMA.index = pd.Index(pd.date_range('2020-11-01','2020-12-09',freq = '1D'))  
+forecastUSARIMA.index = pd.Index(pd.date_range('2020-12-10','2020-12-16',freq = '1D'))  
+
+axUSARIMA.plot(US['Confirmed'],label="confirmed",linestyle=":")
+axUSARIMA.plot(US['Recovered'],label="recovered",linestyle=":")
+axUSARIMA.plot(US['Deaths'],label="deaths",linestyle=":")
+
+axUSARIMA.plot(yUSARIMA['SARIMAconfirmed'],label="confirmed test")
+axUSARIMA.plot(yUSARIMA['SARIMArecovered'],label="recovered test")
+axUSARIMA.plot(yUSARIMA['SARIMAdeaths'],label="deaths test")
+
+axUSARIMA.plot(forecastUSARIMA['confirmedPred'],label="confirmed prediction")
+axUSARIMA.plot(forecastUSARIMA['recoveredPred'],label="recovered prediction")
+axUSARIMA.plot(forecastUSARIMA['deathsPred'],label="deaths prediction")
+
+plt.tight_layout()
+plt.gcf().autofmt_xdate()
+plt.legend(labelspacing=0.05)
+plt.show()

COVID-19/Prediction/Prediction/Holt_Linear_Trend.pyproj

@@ -0,0 +1,37 @@
+<Project DefaultTargets="Build" xmlns="http://schemas.microsoft.com/developer/msbuild/2003" ToolsVersion="4.0">
+  <PropertyGroup>
+    <Configuration Condition=" '$(Configuration)' == '' ">Debug</Configuration>
+    <SchemaVersion>2.0</SchemaVersion>
+    <ProjectGuid>3f8a3b3f-c79e-412c-8ee4-da8ff5db31a6</ProjectGuid>
+    <ProjectHome>
+    </ProjectHome>
+    <StartupFile>
+    </StartupFile>
+    <SearchPath>
+    </SearchPath>
+    <WorkingDirectory>.</WorkingDirectory>
+    <OutputPath>.</OutputPath>
+    <Name>Holt_Linear_Trend</Name>
+    <RootNamespace>ARIMA</RootNamespace>
+  </PropertyGroup>
+  <PropertyGroup Condition=" '$(Configuration)' == 'Debug' ">
+    <DebugSymbols>true</DebugSymbols>
+    <EnableUnmanagedDebugging>false</EnableUnmanagedDebugging>
+  </PropertyGroup>
+  <PropertyGroup Condition=" '$(Configuration)' == 'Release' ">
+    <DebugSymbols>true</DebugSymbols>
+    <EnableUnmanagedDebugging>false</EnableUnmanagedDebugging>
+  </PropertyGroup>
+  <ItemGroup>
+    <Compile Include="Holt_Linear_Trend.py" />
+  </ItemGroup>
+  <Import Project="$(MSBuildExtensionsPath32)\Microsoft\VisualStudio\v$(VisualStudioVersion)\Python Tools\Microsoft.PythonTools.targets" />
+  <!-- Uncomment the CoreCompile target to enable the Build command in
+       Visual Studio and specify your pre- and post-build commands in
+       the BeforeBuild and AfterBuild targets below. -->
+  <!--<Target Name="CoreCompile" />-->
+  <Target Name="BeforeBuild">
+  </Target>
+  <Target Name="AfterBuild">
+  </Target>
+</Project>

COVID-19/Prediction/Prediction/Prediction.py → COVID-19/Prediction/Prediction/Holt_Winters.py

@@ -18,7 +18,7 @@ dataset = dataset.fillna(0)
 dataset['Date'] = pd.to_datetime(dataset['Date'])
 dataset = dataset[['Country/Region','Confirmed','Recovered','Deaths','Date']].groupby(['Country/Region','Date']).sum().reset_index()
 
-#取出中、美、俄的数据
+#取出中、美的数据
 CN = dataset[dataset['Country/Region'] == 'China']
 CN.index = pd.Index(pd.date_range('2020-01-22','2020-12-09',freq = '1D'))  
 US = dataset[dataset['Country/Region'] == 'US']

COVID-19/Prediction/Prediction/Prediction.pyproj → COVID-19/Prediction/Prediction/Holt_Winters.pyproj

@@ -3,13 +3,14 @@
     <Configuration Condition=" '$(Configuration)' == '' ">Debug</Configuration>
     <SchemaVersion>2.0</SchemaVersion>
     <ProjectGuid>fe4194e6-8a95-4b93-968d-ed4305d7f944</ProjectGuid>
-    <ProjectHome>.</ProjectHome>
-    <StartupFile>Prediction.py</StartupFile>
+    <ProjectHome>
+    </ProjectHome>
+    <StartupFile>Holt_Winters.py</StartupFile>
     <SearchPath>
     </SearchPath>
     <WorkingDirectory>.</WorkingDirectory>
     <OutputPath>.</OutputPath>
-    <Name>Prediction</Name>
+    <Name>Holt_Winters</Name>
     <RootNamespace>Prediction</RootNamespace>
   </PropertyGroup>
   <PropertyGroup Condition=" '$(Configuration)' == 'Debug' ">
@@ -21,7 +22,7 @@
     <EnableUnmanagedDebugging>false</EnableUnmanagedDebugging>
   </PropertyGroup>
   <ItemGroup>
-    <Compile Include="Prediction.py" />
+    <Compile Include="Holt_Winters.py" />
   </ItemGroup>
   <Import Project="$(MSBuildExtensionsPath32)\Microsoft\VisualStudio\v$(VisualStudioVersion)\Python Tools\Microsoft.PythonTools.targets" />
   <!-- Uncomment the CoreCompile target to enable the Build command in