public override async Task ProcessItem(dynamic eventData)
{
// Ensure this is a correctly-formatted event for ML; ignore it otherwise
if (eventData == null || eventData.deviceid == null || eventData.cycle == null ||
eventData.sensor9 == null || eventData.sensor11 == null || eventData.sensor14 == null || eventData.sensor15 == null)
{
return;
}
// The experiment theoretically supports multiple inputs at once,
// even though we only get one value at a time, so the request
// requires an array of inputs
MLRequest mlRequest = new MLRequest(ML_REQUEST_COLUMNS, new string[, ]
{
{
// The id is required to be numeric, so we hash the actual device id
eventData.deviceid.ToString().GetHashCode().ToString(),
// The remaining entries are string representations of the numeric values
eventData.cycle.ToString(),
eventData.sensor9.ToString(),
eventData.sensor11.ToString(),
eventData.sensor14.ToString(),
eventData.sensor15.ToString()
}
}
);
HttpClient http = new HttpClient();
http.DefaultRequestHeaders.Authorization = new AuthenticationHeaderValue("Bearer", _configurationProvider.GetConfigurationSettingValue("MLApiKey"));
http.BaseAddress = new Uri(_configurationProvider.GetConfigurationSettingValue("MLApiUrl") + ML_ENDPOINT);
HttpResponseMessage response = await http.PostAsJsonAsync("", mlRequest);
if (response.IsSuccessStatusCode)
{
MLResponse result = JsonConvert.DeserializeObject <MLResponse>(await response.Content.ReadAsStringAsync());
RulTableEntity entry = new RulTableEntity
{
PartitionKey = eventData.deviceid.ToString(),
RowKey = eventData.cycle.ToString(),
// Extract the single relevant RUL value from the JSON output
Rul = result.Results["data"].value.Values[0, RUL_COLUMN],
// Since the simulator might replay data, ensure we can overwrite table values
ETag = "*"
};
// We don't need a data model to represent the result of this operation,
// so we use a stub table/model convertor
await AzureTableStorageHelper.DoTableInsertOrReplaceAsync <object, RulTableEntity>(entry, (RulTableEntity e) => null,
_configurationProvider.GetConfigurationSettingValue("eventHub.StorageConnectionString"),
_configurationProvider.GetConfigurationSettingValue("MLResultTableName"));
}
else
{
throw new Exception(string.Format("The ML request failed with status code: {0}", response.StatusCode));
}
}
public override async Task ProcessItem(dynamic eventData)
{
// Ensure this is a correctly-formatted event for ML; ignore it otherwise
if (eventData == null || eventData.deviceid == null || eventData.cycle == null ||
eventData.sensor9 == null || eventData.sensor11 == null || eventData.sensor14 == null || eventData.sensor15 == null)
{
return;
}
// The experiment theoretically supports multiple inputs at once,
// even though we only get one value at a time, so the request
// requires an array of inputs
MLRequest mlRequest = new MLRequest(ML_REQUEST_COLUMNS, new string[,]
{
{
// The id is required to be numeric, so we hash the actual device id
eventData.deviceid.ToString().GetHashCode().ToString(),
// The remaining entries are string representations of the numeric values
eventData.cycle.ToString(),
eventData.sensor9.ToString(),
eventData.sensor11.ToString(),
eventData.sensor14.ToString(),
eventData.sensor15.ToString()
}
}
);
HttpClient http = new HttpClient();
http.DefaultRequestHeaders.Authorization = new AuthenticationHeaderValue("Bearer", _configurationProvider.GetConfigurationSettingValue("MLApiKey"));
http.BaseAddress = new Uri(_configurationProvider.GetConfigurationSettingValue("MLApiUrl") + ML_ENDPOINT);
HttpResponseMessage response = await http.PostAsJsonAsync("", mlRequest);
if (response.IsSuccessStatusCode)
{
MLResponse result = JsonConvert.DeserializeObject<MLResponse>(await response.Content.ReadAsStringAsync());
RulTableEntity entry = new RulTableEntity
{
PartitionKey = eventData.deviceid.ToString(),
RowKey = eventData.cycle.ToString(),
// Extract the single relevant RUL value from the JSON output
Rul = result.Results["data"].value.Values[0, RUL_COLUMN],
// Since the simulator might replay data, ensure we can overwrite table values
ETag = "*"
};
// We don't need a data model to represent the result of this operation,
// so we use a stub table/model convertor
await AzureTableStorageHelper.DoTableInsertOrReplaceAsync<object, RulTableEntity>(entry, (RulTableEntity e) => null,
_configurationProvider.GetConfigurationSettingValue("eventHub.StorageConnectionString"),
_configurationProvider.GetConfigurationSettingValue("MLResultTableName"));
}
else
{
throw new Exception(string.Format("The ML request failed with status code: {0}", response.StatusCode));
}
}
public async Task <string> GetRULAsync(string deviceId, string cycle, string sensor9, string sensor11, string sensor14, string sensor15)
{
// The experiment theoretically supports multiple inputs at once,
// even though we only get one value at a time, so the request
// requires an array of inputs
MLRequest mlRequest = new MLRequest(ML_REQUEST_COLUMNS, new string[, ]
{
{
// The id is required to be numeric, so we hash the actual device id
deviceId,
// The remaining entries are string representations of the numeric values
cycle,
sensor9,
sensor11,
sensor14,
sensor15
}
}
);
HttpClient http = new HttpClient();
http.DefaultRequestHeaders.Authorization = new AuthenticationHeaderValue("Bearer", _configurationProvider.GetConfigurationSettingValue("MLApiKey"));
http.BaseAddress = new Uri(_configurationProvider.GetConfigurationSettingValue("MLApiUrl") + ML_ENDPOINT);
HttpResponseMessage response = await http.PostAsJsonAsync("", mlRequest);
if (response.IsSuccessStatusCode)
{
MLResponse result = JsonConvert.DeserializeObject <MLResponse>(await response.Content.ReadAsStringAsync());
return(result.Results["data"].value.Values[0, RUL_COLUMN]);
}
else
{
throw new Exception(string.Format("The AML request failed with status code: {0}", response.StatusCode));
}
}
[HttpGet]
public async Task <MLResponse> GetData()
{
var balanceController = new BalanceController();
balanceController.SetToken(base.GetToken());
var balanceHistory = await balanceController.GetHistory(DateTime.Today.AddYears(-6).ToString("yyyyMMdd"), DateTime.Today.ToString("yyyyMMdd"));
if (balanceHistory == null)
{
return(null);
}
foreach (var item in balanceHistory)
{
{
item.TransacionAmountDecimal = decimal.Parse(item.transaction_amount);
item.DateDateTime = DateTime.ParseExact(item.date, "yyyyMMdd", CultureInfo.CurrentCulture);
}
}
var firstDate = balanceHistory.OrderBy(x => x.DateDateTime).First().DateDateTime;
var lastMonthTransactions = balanceHistory.Where(x => x.DateDateTime > DateTime.Now.AddMonths(-3)).Count() / 3;
var lastMonthBalance = balanceHistory.Where(x => x.DateDateTime > DateTime.Now.AddDays(-30)).Sum(x => x.TransacionAmountDecimal);
var lastLastMonthBalance = balanceHistory.Where(x => x.DateDateTime > DateTime.Now.AddDays(-60) && x.DateDateTime <= DateTime.Now.AddDays(-30)).Sum(x => x.TransacionAmountDecimal);
var balanceTrend = 0;
if (lastMonthBalance > lastLastMonthBalance)
{
balanceTrend = 1;
}
else if (lastMonthBalance < lastLastMonthBalance)
{
balanceTrend = -1;
}
var investmentController = new InvestimentoController();
investmentController.SetToken(base.GetToken());
var investment_trend = await investmentController.EvolucaoInvestimento(DateTime.Now.AddYears(-6).ToString("yyyyMMdd"), DateTime.Now.ToString("yyyyMMdd"));
var has_investment = await investmentController.TemInvestimento();
var random = new Random();
var r = new MLRequest();
r.Inputs.input1.ColumnNames.Add("qtd_trans_mes");
r.Inputs.input1.ColumnNames.Add("tempo_casa");
r.Inputs.input1.ColumnNames.Add("tendencia_saldo");
r.Inputs.input1.ColumnNames.Add("investidor");
r.Inputs.input1.ColumnNames.Add("tendencia_investimento");
r.Inputs.input1.ColumnNames.Add("idade");
r.Inputs.input1.ColumnNames.Add("encerrou_conta");
var goHorseList = new List <string>();
goHorseList.Add(lastMonthTransactions.ToString());
goHorseList.Add(((int)DateTime.Now.Subtract(firstDate.Date).Days / 30).ToString());
goHorseList.Add(balanceTrend.ToString());
goHorseList.Add(has_investment? "1" : "0");
goHorseList.Add(investment_trend.ToString());
goHorseList.Add(random.Next(18, 41).ToString());
goHorseList.Add("0");
r.Inputs.input1.Values.Add(goHorseList);
var client = new HttpClient();
var requestBody = JsonConvert.SerializeObject(r);
client.DefaultRequestHeaders.Add("Authorization", "Bearer Rt/+xjyxpGNaIC70ICZblBsmp1afPTnWLO+yxH4Kv1DVfmSVm6PXGMOP0NEARk1jKBMskFchoGk5fQvn5wPimw==");
var mlResponse = await client.PostAsync("https://ussouthcentral.services.azureml.net/workspaces/271e2f65c2a4436989e58d57c424a6ba/services/cf18fd70e61e4bfbb8771adb6924d6d4/execute?api-version=2.0&details=true", new StringContent(requestBody, Encoding.UTF8, "application/json"));
return(JsonConvert.DeserializeObject <MLResponse>(await mlResponse.Content.ReadAsStringAsync()));
}
