async Task MakePredictionRequest(MediaFile file)
{
var client = new System.Net.Http.HttpClient();
client.DefaultRequestHeaders.Add("Prediction-Key", "49918e8a54e64e948382c2657e5343e3");
string url = "https://southcentralus.api.cognitive.microsoft.com/customvision/v1.0/Prediction/70c2cbca-16cb-4848-a9fb-f959ce7686fc/image?iterationId=f3042f17-a2a7-4670-b0f9-ee3ef66ea57a";
System.Net.Http.HttpResponseMessage response;
byte[] byteData = GetImageAsByteArray(file);
using (var content = new ByteArrayContent(byteData))
{
content.Headers.ContentType = new MediaTypeHeaderValue("application/octet-stream");
response = await client.PostAsync(url, content);
if (response.IsSuccessStatusCode)
{
var responseString = await response.Content.ReadAsStringAsync();
EvaluationModel responseModel = JsonConvert.DeserializeObject <EvaluationModel>(responseString);
double max = responseModel.Predictions.Max(m => m.Probability);
TagLabel.Text = (max >= 0.5) ? "THIS PERSON IS LIKELY AN ALIEN" : "NOT AN ALIEN, YOU'RE SAFE";
}
//Get rid of file once we have finished using it
file.Dispose();
}
}
public RepositoryResponse LoadEmpNominationDetails(long ID, string nominationID, string empNum)
{
baseModel = new RepositoryResponse();
try
{
using (objSOMEntities = new SOMEntities())
using (objIPEntities = new IntranetPortalEntities())
{
EmpMaster a = new EmpMaster();
Nomination c = new Nomination();
var _NomDetails = (from em in objIPEntities.EmpMasters.AsEnumerable()
join nom in objSOMEntities.Nominations.AsEnumerable() on em.EmployeeNumber equals nom.EmployeeNumber.ToString()
where nom.IsActive == true && nom.NominationId == nominationID && em.EmployeeNumber == empNum
select new { em, nom }).OrderByDescending(r => r.nom.ID).FirstOrDefault();
var _data = objSOMEntities.Evaluations.Where(r => r.ID == ID && r.IsActive == true).FirstOrDefault();
EvaluationModel model = ConvertEvaluation_DB2Model(_NomDetails.em, _data, _NomDetails.nom, 1);
baseModel = new RepositoryResponse {
success = true, message = "Get Evaluation details Successfully", Data = model
};
}
}
catch (Exception ex)
{
baseModel = new RepositoryResponse {
success = false, message = ex.ToString()
};
}
return(baseModel);
}
public ActionResult Create(EvaluationModel Model)
{
Authentication("EVAF");
try
{
tblEvaluationHeader tbl = new tblEvaluationHeader();
tbl.AccedamicYear = DateTime.Now.Year.ToString();
tbl.CreatedBy = USession.User_Id;
tbl.CreatedDate = DateTime.Today;
tbl.EvaluationDescription = Model.EvaluationDescription;
tbl.EvaluationType = Model.EvaluationType;
tbl.isActive = "Y";
tbl.TestPaperFee = Model.TestPaperFee;
tbl.SchoolId = USession.School_Id;
Connection.tblEvaluationHeaders.Add(tbl);
Connection.SaveChanges();
dropdowns();
return(RedirectToAction("Create"));
}
catch
{
return(View());
}
}
async Task MakePredictionRequest(MediaFile file)
{
var client = new HttpClient();
client.DefaultRequestHeaders.Add("Prediction-Key", "4609999dc6134d9d8faa66f6d90b66ce");
string url = "https://southcentralus.api.cognitive.microsoft.com/customvision/v1.0/Prediction/204bc4e4-a878-4f13-a349-17986d43538c/image";
HttpResponseMessage response;
byte[] byteData = GetImageAsByteArray(file);
using (var content = new ByteArrayContent(byteData))
{
content.Headers.ContentType = new MediaTypeHeaderValue("application/octet-stream");
response = await client.PostAsync(url, content);
if (response.IsSuccessStatusCode)
{
var responseString = await response.Content.ReadAsStringAsync();
EvaluationModel responseModel = JsonConvert.DeserializeObject <EvaluationModel>(responseString);
double max = responseModel.Predictions.Max(m => m.Probability);
TagLabel.Text = (max >= 0.5) ? "BigCat" : "Not BigCat";
}
file.Dispose();
}
}
// GET: User/Edit/5
public async Task <IActionResult> Edit(long id)
{
EvaluationModel evals = await _evaluationService.GetAsync(HttpContext.Session, id);
CompteModel compte = _compteService.GetConnectedCompte(HttpContext.Session);
SujetModel sujets = await _sujetService.GetAsync(HttpContext.Session, id);
List <UserModel> lstUser = await _userService.GetListUserByManagerAsync(HttpContext.Session, compte.User.Id.GetValueOrDefault(0));
var lstUserByEval = (await _evaluationService.GetListUserByEvalAsync(HttpContext.Session, evals.Id.GetValueOrDefault(0))).Select(s => new {
Id = s.Id,
Nom = s.Nom,
Prenom = s.Prenom,
Selected = true
}).ToList();
var listUserTolal =
lstUser.Where(w => lstUserByEval == null || lstUserByEval.Where(x => x.Id == w.Id).Count() == 0)
.Select(s => new {
Id = s.Id,
Nom = s.Nom,
Prenom = s.Prenom,
Selected = false
}).Concat(lstUserByEval).ToList();
//for(int i = 0; i < listUserTolal.Count();i++) { }
ViewBag.lstUser = listUserTolal ?? new[] {
new { Id = (long?)0,
Nom = "",
Prenom = "",
Selected = false }
}.ToList();
List <SujetModel> lstsujet = await _sujetService.GetListAsync(HttpContext.Session);
var lstSujetsByEval = (await _evaluationService.GetListSujetByEvalAsync(HttpContext.Session, evals.Id.GetValueOrDefault(0))).Select(s => new {
Id = s.Id,
Titre = s.Titre,
Selected = true
}).ToList();
var listTotal =
lstsujet.Where(w => lstSujetsByEval == null || lstSujetsByEval.Where(x => x.Id == w.Id).Count() == 0)
.Select(s => new {
Id = s.Id,
Titre = s.Titre,
Selected = false
}).Concat(lstSujetsByEval).ToList();
//for(int i = 0; i < listUserTolal.Count();i++) { }
ViewBag.lstsujet = listTotal ?? new[] {
new { Id = (long?)0,
Titre = "",
Selected = false }
}.ToList();
ViewData.Model = evals;
return(View());
}
async Task MakePrediction(MediaFile image)
{
var client = new HttpClient {
DefaultRequestHeaders = { { "Prediction-Key", "0e0a735690e14bccafd0ac94acd572e5" } }
};
const string apiUrl = "https://southcentralus.api.cognitive.microsoft.com/customvision/v1.0/Prediction/3f3b150a-e19c-4acb-ae03-5d7078f5c288/image?iterationId=ec6c19e5-4f8e-4385-87c5-3754f8ce4102";
var dataInBytes = ImageToByteArray(image);
List <string> prediction = null;
using (var content = new ByteArrayContent(dataInBytes))
{
content.Headers.ContentType = new MediaTypeHeaderValue("application/octet-stream");
var response = await client.PostAsync(apiUrl, content);
if (response.IsSuccessStatusCode)
{
var responseString = await response.Content.ReadAsStringAsync();
EvaluationModel responseContent = JsonConvert.DeserializeObject <EvaluationModel>(responseString);
prediction = responseContent.Predictions.Where(p => p.Probability > 0.7).Select(p => p.Tag).ToList();
}
else
{
await DisplayAlert("Error", "Something went wrong, please try again\n" + response.StatusCode, "OK");
return;
}
_predictions = prediction;
}
}
async Task MakePredictionRequest(MediaFile file)
{
var client = new HttpClient();
client.DefaultRequestHeaders.Add("Prediction-Key", "bf91ca6d1e614b6ead6193761c9ede2d");
string url = "https://southcentralus.api.cognitive.microsoft.com/customvision/v1.0/Prediction/bcb49c89-078b-4a5c-a127-7027e82f974e/image?iterationId=3ced66ed-a8ef-46c7-a28a-db3d9b0118d0";
HttpResponseMessage response;
byte[] byteData = GetImageAsByteArray(file);
using (var content = new ByteArrayContent(byteData))
{
content.Headers.ContentType = new MediaTypeHeaderValue("application/octet-stream");
response = await client.PostAsync(url, content);
if (response.IsSuccessStatusCode)
{
var responseString = await response.Content.ReadAsStringAsync();
EvaluationModel responseModel = JsonConvert.DeserializeObject <EvaluationModel>(responseString);
double max = responseModel.Predictions.Max(m => m.Probability);
TagLabel.Text = (max >= 0.5) ? "NMD" : "NOT NMD";
}
//Get rid of file once we have finished using it
file.Dispose();
}
}
async Task MakePredictionRequest(MediaFile file)
{
var client = new HttpClient();
client.DefaultRequestHeaders.Add("Prediction-Key", "e255f72dcb9b4f69917f05309ab246d2");
string url = "https://southcentralus.api.cognitive.microsoft.com/customvision/v1.0/Prediction/f4777059-a48b-4ab0-b43f-d585c83e164e/image?iterationId=92c71ce9-4e94-4ced-a344-031e5939af17";
HttpResponseMessage response;
byte[] byteData = GetImageAsByteArray(file);
using (var content = new ByteArrayContent(byteData))
{
content.Headers.ContentType = new MediaTypeHeaderValue("application/octet-stream");
response = await client.PostAsync(url, content);
if (response.IsSuccessStatusCode)
{
var responseString = await response.Content.ReadAsStringAsync();
EvaluationModel responseModel = JsonConvert.DeserializeObject <EvaluationModel>(responseString);
double max = responseModel.Predictions.Max(m => m.Probability);
TagLabel.Text = (max >= 0.5) ? "This is a photo of rice (Probability: " + max + ")." : " This is not a photo of rice (Probability: " + max + ").";
file.Dispose();
}
}
}
public ActionResult EvaluationPopupValues(string ID)
{
long _id = long.Parse(ID);
_evaluationRepo = new EvaluationRepo();
_repoResponse = new RepositoryResponse();
if (_id > 0)
{
_repoResponse = _evaluationRepo.LoadEvaluationDataByID(_id);
}
//else
//{
// _repoResponse = _evaluationRepo.LoadEmpNominationDetails(_id, long.Parse(nominationID), empNum);
//}
if (_repoResponse.success == true)
{
EvaluationModel model = new EvaluationModel();
model = _repoResponse.Data;
//return JSon(model);
return(Json(new { success = _repoResponse.success, message = _repoResponse.message, data = model }));
}
else
{
EvaluationModel model = new EvaluationModel();
return(Json(new { success = _repoResponse.success, message = _repoResponse.message, data = model }));
}
}
public ActionResult AddOrUpdate(EvaluationModel model)
{
if (!ModelState.IsValid)
{
return(View(model));
}
var isCreated = model.Id == Guid.Empty;
var evaluation = new Evaluations();
if (!isCreated)
{
evaluation = EvaluationRepository.GetById(model.Id);
}
evaluation.Date = model.Date;
evaluation.Classroom_Id = model.ClassroomId;
evaluation.Classrooms = ClassroomRepository.GetById(model.ClassroomId);
evaluation.User_Id = model.UserId;
evaluation.Users = UserRepository.GetById(model.UserId);
evaluation.TotalPoint = model.TotalPoint;
evaluation.Periods = PeriodRepository.GetById(model.PeriodId);
if (isCreated)
{
EvaluationRepository.Add(evaluation);
}
EvaluationRepository.Save();
return(Redirect(Url.Action("Get", "Evaluation", new { id = evaluation.Id })));
}
async Task MakePredictionRequest(MediaFile file)
{
var client = new HttpClient();
client.DefaultRequestHeaders.Add("Prediction-Key", "9edb926f637d4217a56323b6538e14a4");
string url = "https://southcentralus.api.cognitive.microsoft.com/customvision/v1.0/Prediction/29e9309a-cc47-4123-b301-edaa3047ff89/image?iterationId=c8d11c4e-4192-4cef-8291-127ad9a74fcc";
HttpResponseMessage response;
byte[] byteData = GetImageAsByteArray(file);
using (var content = new ByteArrayContent(byteData))
{
content.Headers.ContentType = new MediaTypeHeaderValue("application/octet-stream");
response = await client.PostAsync(url, content);
if (response.IsSuccessStatusCode)
{
var responseString = await response.Content.ReadAsStringAsync();
EvaluationModel responseModel = JsonConvert.DeserializeObject <EvaluationModel>(responseString);
double max = responseModel.Predictions.Max(m => m.Probability);
TagLabel.Text = (max >= 0.2) ? "SuperHero" : "Not SuperHero";
}
//Get rid of file once we have finished using it
file.Dispose();
}
}
private static void CrossValidate()
{
var evaluationModel = new EvaluationModel(LoadModel());
var result = evaluationModel.Evaluate();
Console.WriteLine(result);
Console.ReadKey();
}
private async Task MakePredictionRequest(MediaFile file)
{
try
{
Contract.Ensures(Contract.Result <Task>() != null);
var client = new HttpClient();
client.DefaultRequestHeaders.Add("Prediction-Key", "9b2cd115e674489c892a12aa9b4747f2");
string url = "https://southcentralus.api.cognitive.microsoft.com/customvision/v1.0/Prediction/9ced7a98-a868-45b5-a7ca-e9112877744a/image?iterationId=decd2fad-4dfe-4c98-a7f3-7b82e1b058e6";
HttpResponseMessage response;
byte[] byteData = GetImageAsByteArray(file);
using (var content = new ByteArrayContent(byteData))
{
content.Headers.ContentType = new MediaTypeHeaderValue("application/octet-stream");
response = await client.PostAsync(url, content);
if (response.IsSuccessStatusCode)
{
var responseString = await response.Content.ReadAsStringAsync();
EvaluationModel responseModel = JsonConvert.DeserializeObject <EvaluationModel>(responseString);
List <Prediction> predictions = responseModel.Predictions;
foreach (Prediction prediction in predictions)
{
if (prediction.Probability >= 0.8)
{
var locator = CrossGeolocator.Current;
locator.DesiredAccuracy = 50;
var position = await locator.GetPositionAsync(10000);
foodLabel.Text = prediction.Tag;
shareButton.IsVisible = true;
unsentModel = new FoodLocationModel()
{
Title = prediction.Tag,
Longitude = (float)position.Longitude,
Latitude = (float)position.Latitude
};
file.Dispose();
return;
}
}
foodLabel.Text = "What is this? Is this even food?";
}
//Get rid of file once we have finished using it
file.Dispose();
}
} catch (Exception e)
{
Console.WriteLine("{0} Exception caught", e);
}
}
public ActionResult DeleteEvaluationDetail(string EvaluationDetailSeqNo, string EvaluationNo)
{
EvaluationModel Model = new EvaluationModel();
Model.EvaluationDetailSeqNo = long.Parse(EvaluationDetailSeqNo);
Model.EvaluationNo = long.Parse(EvaluationNo);
Model.SchoolId = USession.School_Id;
return(PartialView("DeleteEvaluationDetail", Model));
}
public ActionResult Create(EvaluationModel eval)
{
HttpClient client = new HttpClient();
client.BaseAddress = new Uri("http://localhost:9080/UserManager-web/");
var result = client.PostAsJsonAsync <EvaluationModel>("api/evaluations", eval).Result;
return(RedirectToAction("Index"));
}
public static void EvalGeneCscc()
{
var models = MostCommonGene(LoadGeneCsccTrainingModel());
foreach (var model in models)
{
var evaluationModel = new EvaluationModel(model);
Console.WriteLine(evaluationModel.Evaluate());
}
Console.ReadKey();
}
public IActionResult AddReport([FromBody] EvaluationModel evaluation)
{
var report = _dataService.AddReport(evaluation.evaluation_id, evaluation.report);
if (report == null)
{
return(NotFound());
}
return(Ok(report));
}
public ActionResult Edit(EvaluationModel evaluation)
{
HttpClient Client = new HttpClient();
Client.BaseAddress = new Uri("http://localhost:9080/UserManager-web/");
Client.DefaultRequestHeaders.Accept.Add(new MediaTypeWithQualityHeaderValue("application/json"));
// EvaluationModel eval = evaluation;
HttpResponseMessage result = Client.PutAsJsonAsync <EvaluationModel>("api/evaluations/" + evaluation.id, evaluation).Result;
return(RedirectToAction("Index"));
}
/// <summary>
///
/// </summary>
/// <param name="sender"></param>
/// <param name="e"></param>
protected void InsertEvaluationByGroup(object sender, DirectEventArgs e)
{
try
{
if (!string.IsNullOrEmpty(hdfGroupFilter.Text))
{
var criterionModels = CriterionController.GetAll(null, Convert.ToInt32(hdfGroupFilter.Text), false,
KpiStatus.Active, null, null, null);
//create new all employee
var records = RecordController.GetAll(null, null, DepartmentIds, RecordType.Default, null, null);
foreach (var criterion in criterionModels)
{
foreach (var item in records)
{
var model = new EvaluationModel()
{
RecordId = item.Id,
CriterionId = criterion.Id,
Month = DateTime.Now.Month,
Year = DateTime.Now.Year,
Value = ""
};
//get value
GetValueCriterionWorkbook(model, criterion, Convert.ToInt32(hdfGroupFilter.Text));
//check exist
var evaluation = EvaluationController.CheckExist(model.RecordId, model.CriterionId, model.Month, model.Year);
if (evaluation != null)
{
model.Id = evaluation.Id;
//update
EvaluationController.Update(model);
}
else
{
//create
EvaluationController.Create(model);
}
}
}
//hide window
wdEvaluation.Hide();
// reload grid
gpEvaluation.Reload();
}
}
catch (Exception exception)
{
Dialog.ShowError(exception);
}
}
async Task MakePredictionRequest(MediaFile file)
{
var client = new HttpClient();
client.DefaultRequestHeaders.Add("Prediction-Key", "c318d58e642d4da0a94252bbbd87a76e");
string url = "https://southcentralus.api.cognitive.microsoft.com/customvision/v1.0/Prediction/ceeb2fc1-b383-407e-88cb-f1ec50db4054/image?iterationId=db0244c3-7eeb-4ba9-80b0-4ea7ff96df89";
HttpResponseMessage response;
byte[] byteData = GetImageAsByteArray(file);
using (var content = new ByteArrayContent(byteData))
{
content.Headers.ContentType = new MediaTypeHeaderValue("application/octet-stream");
response = await client.PostAsync(url, content);
if (response.IsSuccessStatusCode)
{
var responseString = await response.Content.ReadAsStringAsync();
EvaluationModel responseModel = JsonConvert.DeserializeObject <EvaluationModel>(responseString);
double max = responseModel.Predictions.Max(m => m.Probability);
foreach (var item in responseModel.Predictions)
{
if (max <= 0.5)
{
await DisplayAlert("Wow", "Hmm, I can't really tell.", "Ok");
break;
}
else if (item.Tag == "male" && item.Probability > 0.7)
{
await DisplayAlert("Wow", "Hmm, I think this is a male.", "Ok");
break;
}
else if (item.Tag == "female" && item.Probability > 0.7)
{
await DisplayAlert("Wow", "Hmm, I think this is a female.", "Ok");
break;
}
}
}
//Get rid of file once we have finished using it
file.Dispose();
}
}
async Task MakePredictionRequest(MediaFile file)
{
Contract.Ensures(Contract.Result <Task>() != null);
var client = new HttpClient();
client.DefaultRequestHeaders.Add("Prediction-Key", "4acc8969a66e4e6a8566c55658bbe9d2");
string url = "https://southcentralus.api.cognitive.microsoft.com/customvision/v1.1/Prediction/ce6463c9-a4b5-4af6-aed2-18babd9f8483/image?iterationId=1ddec163-8098-4387-b095-fa55183c512e";
HttpResponseMessage response;
byte[] byteData = GetImageAsByteArray(file);
using (var content = new ByteArrayContent(byteData))
{
content.Headers.ContentType = new MediaTypeHeaderValue("application/octet-stream");
response = await client.PostAsync(url, content);
if (response.IsSuccessStatusCode)
{
var responseString = await response.Content.ReadAsStringAsync();
EvaluationModel responseModel = JsonConvert.DeserializeObject <EvaluationModel>(responseString);
double max = responseModel.Predictions.Max(m => m.Probability);
if (max >= 0.5)
{
TagLabel.Text = "There is a heavy traffic in TinFactory";
await CrossTextToSpeech.Current.Speak(TagLabel.Text);
await Navigation.PushAsync(new TrafficEvaluationPage());
// CrossLocalNotifications.Current.Show("Alert", "We have send the informaton to local concen autheroties");
}
else
{
TagLabel.Text = " There is no heavy Traffic in Tin Factory";
await CrossTextToSpeech.Current.Speak(TagLabel.Text);
await Navigation.PushAsync(new TrafficEvaluationPage());
}
}
//Get rid of file once we have finished using it
file.Dispose();
}
}
/// <summary>
///
/// </summary>
/// <param name="model"></param>
/// <param name="criterion"></param>
/// <param name="groupId"></param>
private static void GetValueCriterionWorkbook(EvaluationModel model, CriterionModel criterion, int?groupId)
{
var empArgument =
EmployeeArgumentController.GetAll(null, null, groupId, model.RecordId, model.Month, model.Year, null, null);
var workbook = new WorkBook {
AutoCalc = false
};
foreach (var argument in empArgument)
{
switch (argument.ValueType)
{
case KpiValueType.String:
workbook.setText($"{argument.ArgumentCalculateCode}1", argument.Value);
break;
case KpiValueType.Number:
workbook.setNumber($"{argument.ArgumentCalculateCode}1",
double.TryParse(argument.Value, out var parseResultNumber) ? parseResultNumber : 0);
break;
case KpiValueType.Percent:
workbook.setFormula($"{argument.ArgumentCalculateCode}1",
double.TryParse(argument.Value, out var parseResultPercent) ? $"{parseResultPercent} * 0.01" : "0");
break;
case KpiValueType.Formula:
workbook.setFormula($"{argument.ArgumentCalculateCode}1", argument.Value.TrimStart('='));
break;
}
}
workbook.setFormula("A1", criterion.Formula.TrimStart('='));
workbook.recalc();
switch (criterion.ValueType)
{
case KpiValueType.Number:
model.Value = workbook.getNumber("A1").ToString("#,##0.##");
break;
case KpiValueType.Percent:
model.Value = (workbook.getNumber("A1") * 100).ToString("0.00");
break;
default:
model.Value = workbook.getText("A1");
break;
}
}
async Task MakePredictionRequest(MediaFile file)
{
var client = new HttpClient();
client.DefaultRequestHeaders.Add("Prediction-Key", "6b188bd282ac425a8e3755635c55f37e");
string url = "https://southcentralus.api.cognitive.microsoft.com/customvision/v1.0/Prediction/34669e80-95d0-4bc7-8062-1f1d94f76082/image?iterationId=a7ea51b3-732b-4588-b424-3a2b7af7c800";
HttpResponseMessage response;
byte[] byteData = GetImageAsByteArray(file);
using (var content = new ByteArrayContent(byteData))
{
content.Headers.ContentType = new MediaTypeHeaderValue("application/octet-stream");
response = await client.PostAsync(url, content);
if (response.IsSuccessStatusCode)
{
var responseString = await response.Content.ReadAsStringAsync();
EvaluationModel responseModel = JsonConvert.DeserializeObject <EvaluationModel>(responseString);
var probability = responseModel.Predictions.OrderByDescending(probabilityH => probabilityH.Probability);
var output_result = probability.Take(1).Single();
BarIndicator.IsVisible = true;
if (output_result.Probability > 0.5)
{
TagLabel.Text = output_result.Tag;
AzureManager.AzureManagerInstance.SetIngredient(output_result.Tag);
await BarIndicator.ProgressTo(1, 80, Easing.Linear);
BarIndicator.IsVisible = false;
BarIndicator.ProgressTo(0, 80, Easing.Linear);
Globals.exist = true;
}
else
{
await BarIndicator.ProgressTo(1, 80, Easing.Linear);
TagLabel.Text = "Doesn't exist in the database";
BarIndicator.IsVisible = false;
BarIndicator.ProgressTo(0, 80, Easing.Linear);
}
}
file.Dispose();
}
}
private Evaluation ConvertEvaluation_Model2DB(EvaluationModel model, string _loggedInUserID, bool isSubmit)
{
Evaluation db = new Evaluation();
if (model != null)
{
db.AheadOfPlan = model.AheadOfPlan;
db.AsPerPlan = model.AsPerPlan;
db.BasedOnInstruction = model.BasedOnInstruction;
db.BreakthroughImprovement = model.BreakthroughImprovement;
db.CoordiantionWithInTheDept = model.CoordiantionWithInTheDept;
db.CoordinationWithAnotherFunction = model.CoordinationWithAnotherFunction;
db.CoordinationWithMultipleFunctions = model.CoordinationWithMultipleFunctions;
db.Delayed = model.Delayed;
db.EmployeeNumber = model.EmployeeNumber;
db.NominationID = model.NominationID;
db.EvaluatorID = model.EvaluatorID;
db.FollowedUp = model.FollowedUp;
db.ID = model.ID;
db.Implemented = model.Implemented;
db.ImplementedInAllApplicableAreas = model.ImplementedInAllApplicableAreas;
db.ImplementedPartially = model.ImplementedPartially;
db.ImprovementFromCurrentSituation = model.ImprovementFromCurrentSituation;
db.IsActive = true;
db.Participated = model.Participated;
db.PreventionOfaFailure = model.PreventionOfaFailure;
db.ProactiveIdeaGeneratedBySelf = model.ProactiveIdeaGeneratedBySelf;
db.ReactiveIdeaDrivenBySituation = model.ReactiveIdeaDrivenBySituation;
db.ScopeIdentified = model.ScopeIdentified;
if (isSubmit)
{
db.Status = (int)NominationStatus.Evaluators_Assign_TQC;
}
else
{
db.Status = (int)NominationStatus.Evaluators_Save;
}
db.TotalScore = int.Parse(model.TotalScore);
db.CreatedBy = _loggedInUserID;;
}
return(db);
}
async Task MakePredictionRequest(MediaFile file)
{
HttpClient client = new HttpClient();
client.DefaultRequestHeaders.Add("Prediction-Key", "c11b49980c4f42e0a34b8820a0607713");
string url = "https://southcentralus.api.cognitive.microsoft.com/customvision/v1.0/Prediction/d094d72a-8e5e-48e5-bfb1-d5b8be2f070c/image?iterationId=ec824ab3-e526-4b65-9662-b69f1069954a";
HttpResponseMessage response;
byte[] byteData = GetImageAsByteArray(file);
using (ByteArrayContent content = new ByteArrayContent(byteData))
{
content.Headers.ContentType = new MediaTypeHeaderValue("application/octet-stream");
TagLabel.Text = "Processing...";
response = await client.PostAsync(url, content);
if (response.IsSuccessStatusCode)
{
string responseString = await response.Content.ReadAsStringAsync();
EvaluationModel responseModel = JsonConvert.DeserializeObject <EvaluationModel>(responseString);
String predictionData = "";
Prediction mostProbable = null;
foreach (Prediction prediction in responseModel.Predictions)
{
predictionData += prediction.Tag + " with probability " + prediction.Probability + "\n";
if (mostProbable == null || mostProbable.Probability < prediction.Probability)
{
mostProbable = prediction;
}
}
TagLabel.Text = (mostProbable != null && mostProbable.Probability > 0.5d) ?
"It is a " + mostProbable.Tag + "!" :
"No result";
TagLabel.Text = TagLabel.Text + "\n\n" + predictionData;
file.Dispose();
}
else
{
TagLabel.Text = "Operation Failed! " + response.StatusCode;
}
}
}
public async Task ExecuteAsync(ICommandUpdateFascicleData command)
{
_logger.WriteInfo(new LogMessage($"{command.CommandName} is arrived"), LogCategories);
FascicleBuildModel fascicleBuildModel = command.ContentType.ContentTypeValue;
FascicleModel fascicleModel = fascicleBuildModel.Fascicle;
try
{
if (RetryPolicyEvaluation != null && !string.IsNullOrEmpty(RetryPolicyEvaluation.ReferenceModel))
{
_logger.WriteDebug(new LogMessage("Load reference model from RetryPolicyEvaluation"), LogCategories);
fascicleModel = JsonConvert.DeserializeObject <FascicleModel>(RetryPolicyEvaluation.ReferenceModel, _serializerSettings);
}
else
{
_logger.WriteDebug(new LogMessage("Generate new RetryPolicyEvaluation model"), LogCategories);
RetryPolicyEvaluation = new EvaluationModel();
}
_logger.WriteInfo(new LogMessage($"Cancel requested for fascicle {fascicleModel.Title}/{fascicleModel.UniqueId}-{fascicleModel.FascicleObject}"), LogCategories);
_logger.WriteDebug(new LogMessage($"Cancel requested from WorkflowName {fascicleBuildModel.WorkflowName} and IdWorkflowActivity {fascicleBuildModel.IdWorkflowActivity}"), LogCategories);
if (!RetryPolicyEvaluation.Steps.Any(f => f.Name == "ENTITY_UPDATED"))
{
Fascicle updatedFascicle = await UpdateData(fascicleBuildModel, fascicleModel);
_logger.WriteInfo(new LogMessage($"Fascicle {updatedFascicle.GetTitle()} has been updated"), LogCategories);
RetryPolicyEvaluation.Steps.Add(new StepModel()
{
Name = "ENTITY_UPDATED",
LocalReference = JsonConvert.SerializeObject(fascicleModel, _serializerSettings)
});
_logger.WriteDebug(new LogMessage("Set ENTITY_UPDATED RetryPolicyEvaluation"), LogCategories);
}
else
{
StepModel fascicleStatus = RetryPolicyEvaluation.Steps.First(f => f.Name == "ENTITY_UPDATED");
fascicleModel = JsonConvert.DeserializeObject <FascicleModel>(fascicleStatus.LocalReference);
_logger.WriteDebug(new LogMessage("Load fascicle entity from RetryPolicyEvaluation ENTITY_UPDATED"), LogCategories);
}
}
catch (Exception ex)
{
RetryPolicyEvaluation.ReferenceModel = JsonConvert.SerializeObject(fascicleModel, _serializerSettings);
_logger.WriteError(ex, LogCategories);
throw new ServiceBusEvaluationException(RetryPolicyEvaluation);
}
}
public ActionResult AddOrUpdate(Guid?Id, Guid?classroomId)
{
var model = new EvaluationModel();
model.Date = DateTime.Now;
if (Id.HasValue)
{
model = EvaluationModel.ToModel(EvaluationRepository.GetById(Id.Value));
}
if (classroomId.HasValue)
{
model.ClassroomId = classroomId.Value;
}
return(View(model));
}
/// <summary>
///
/// </summary>
/// <param name="sender"></param>
/// <param name="e"></param>
protected void EvaluationClick(object sender, DirectEventArgs e)
{
try
{
if (!string.IsNullOrEmpty(hdfId.Text))
{
//create new all employee
var records = RecordController.GetAll(null, null, DepartmentIds, RecordType.Default, null, null);
var criterion = CriterionController.GetById(Convert.ToInt32(hdfId.Text));
foreach (var item in records)
{
var model = new EvaluationModel()
{
RecordId = item.Id,
CriterionId = Convert.ToInt32(hdfId.Text),
Month = DateTime.Now.Month,
Year = DateTime.Now.Year,
Value = ""
};
//get value
GetValueCriterionWorkbook(model, criterion, null);
//check exist
var evaluation = EvaluationController.CheckExist(model.RecordId, model.CriterionId, model.Month, model.Year);
if (evaluation != null)
{
model.Id = evaluation.Id;
//update
EvaluationController.Update(model);
}
else
{
//create
EvaluationController.Create(model);
}
}
}
}
catch (Exception exception)
{
Dialog.ShowError(exception);
}
}
public ActionResult DeleteEvaluationHeader(EvaluationModel Model)
{
try
{
// Model.SchoolId="121127";
string evalNo = Model.EvaluationNo.ToString();
Connection.SMGTModifyEvaluationHeaderStatus(Model.SchoolId, evalNo);
// Connection.tblHouses.
Connection.SaveChanges();
return(Json(Model.SchoolId, JsonRequestBehavior.AllowGet));
}
catch
{
return(Json("Error", JsonRequestBehavior.AllowGet));
}
}
public async Task ExecuteAsync(ICommandUpdateDossierData command)
{
_logger.WriteInfo(new LogMessage($"{command.CommandName} is arrived"), LogCategories);
Dossier dossier = command.ContentType.ContentTypeValue;
try
{
if (RetryPolicyEvaluation != null && !string.IsNullOrEmpty(RetryPolicyEvaluation.ReferenceModel))
{
_logger.WriteDebug(new LogMessage("Load reference model from RetryPolicyEvaluation"), LogCategories);
dossier = JsonConvert.DeserializeObject <Dossier>(RetryPolicyEvaluation.ReferenceModel, _serializerSettings);
}
else
{
_logger.WriteDebug(new LogMessage("Generate new RetryPolicyEvaluation model"), LogCategories);
RetryPolicyEvaluation = new EvaluationModel();
}
if (!RetryPolicyEvaluation.Steps.Any(f => f.Name == STEP_UPDATE_DOSSIER))
{
Dossier updatedDossier = await UpdateDossierEntity(dossier);
_logger.WriteInfo(new LogMessage($"Dossier {updatedDossier.GetTitle()} has been updated"), LogCategories);
RetryPolicyEvaluation.Steps.Add(new StepModel()
{
Name = STEP_UPDATE_DOSSIER,
LocalReference = JsonConvert.SerializeObject(updatedDossier, _serializerSettings)
});
}
else
{
StepModel messageStatus = RetryPolicyEvaluation.Steps.First(f => f.Name == STEP_UPDATE_DOSSIER);
dossier = JsonConvert.DeserializeObject <Dossier>(messageStatus.LocalReference);
}
}
catch (Exception ex)
{
RetryPolicyEvaluation.ReferenceModel = JsonConvert.SerializeObject(dossier, _serializerSettings);
_logger.WriteError(ex, LogCategories);
throw new ServiceBusEvaluationException(RetryPolicyEvaluation);
}
}
public IEnumerable<EvaluationModel> GenerateEvaluationModel(List<AssetBase> assets) {
List<EvaluationModel> models = new List<EvaluationModel>();
Ratios ratios = assets.GetAverageRatiosFor<InternationalEquity>();
Recommendation expected = assets.GetAverageExpectedFor<InternationalEquity>();
foreach (EvaluationInfo evaluation in Enum.GetValues(typeof(EvaluationInfo))) {
EvaluationModel eachModel = new EvaluationModel { title = edisRepo.GetEnumDescription(evaluation) };
switch (evaluation) {
case EvaluationInfo.OneYearReturn:
eachModel.actual += ratios.OneYearReturn;
eachModel.expected += expected.OneYearReturn == null ? 0 : (double)expected.OneYearReturn;
break;
case EvaluationInfo.FiveYearReturn:
eachModel.actual += ratios.FiveYearReturn;
eachModel.expected += expected.FiveYearTotalReturn == null ? 0 : (double)expected.OneYearReturn;
break;
case EvaluationInfo.DebtEquityRatio:
eachModel.actual += ratios.DebtEquityRatio;
eachModel.expected += expected.DebtEquityRatio;
break;
case EvaluationInfo.EpsGrowth:
eachModel.actual += ratios.EpsGrowth;
eachModel.expected += expected.EpsGrowth;
break;
case EvaluationInfo.DividendYield:
eachModel.actual += ratios.DividendYield;
eachModel.expected += expected.DividendYield;
break;
case EvaluationInfo.Frank:
eachModel.actual += ratios.Frank;
eachModel.expected += expected.Frank;
break;
case EvaluationInfo.InterestCover:
eachModel.actual += ratios.InterestCover;
eachModel.expected += expected.InterestCover;
break;
case EvaluationInfo.PriceEarningRatio:
eachModel.actual += ratios.PriceEarningRatio;
eachModel.expected += expected.PriceEarningRatio;
break;
case EvaluationInfo.ReturnOnAsset:
eachModel.actual += ratios.ReturnOnAsset;
eachModel.expected += expected.ReturnOnAsset;
break;
case EvaluationInfo.ReturnOnEquity:
eachModel.actual += ratios.ReturnOnEquity;
eachModel.expected += expected.ReturnOnEquity;
break;
}
models.Add(eachModel);
}
return models;
}
public IEnumerable<EvaluationModel> GetEvaluationModel_Client()
{
Client client = edisRepo.GetClientSync(User.Identity.GetUserId(), DateTime.Now);
ClientGroup clientGroup = edisRepo.GetClientGroupSync(client.ClientGroupId, DateTime.Now);
if (clientGroup.MainClientId == client.Id)
{
List<GroupAccount> groupAccounts = edisRepo.GetAccountsForClientGroupSync(clientGroup.ClientGroupNumber, DateTime.Now);
List<ClientAccount> clientAccounts = edisRepo.GetAccountsForClientSync(client.ClientNumber, DateTime.Now);
EvaluationModel model1 = new EvaluationModel { title = "One Year Return" };
EvaluationModel model3 = new EvaluationModel { title = "Debt Equity Ratio" };
EvaluationModel model4 = new EvaluationModel { title = "Eps Growth" };
EvaluationModel model5 = new EvaluationModel { title = "Dividend Yield" };
EvaluationModel model6 = new EvaluationModel { title = "Franking" };
EvaluationModel model7 = new EvaluationModel { title = "Interest Cover" };
EvaluationModel model8 = new EvaluationModel { title = "Price Earning Ratio" };
EvaluationModel model9 = new EvaluationModel { title = "Return On Asset" };
EvaluationModel model10 = new EvaluationModel { title = "Return On Equity" };
foreach (var account in groupAccounts)
{
List<AssetBase> assets = account.GetAssetsSync();
Ratios ratios = assets.GetAverageRatiosFor<InternationalEquity>();
Recommendation expected = assets.GetAverageExpectedFor<InternationalEquity>();
model1.actual += ratios.OneYearReturn;
model1.expected += expected.OneYearReturn == null ? 0 : (double)expected.OneYearReturn;
model3.actual += ratios.DebtEquityRatio;
model3.expected += expected.DebtEquityRatio;
model4.actual += ratios.EpsGrowth;
model4.expected += expected.EpsGrowth;
model5.actual += ratios.DividendYield;
model5.expected += expected.DividendYield;
model6.actual += ratios.Frank;
model6.expected += expected.Frank;
model7.actual += ratios.InterestCover;
model7.expected += expected.InterestCover;
model8.actual += ratios.PriceEarningRatio;
model8.expected += expected.PriceEarningRatio;
model9.actual += ratios.ReturnOnAsset;
model9.expected += expected.ReturnOnAsset;
model10.actual += ratios.ReturnOnEquity;
model10.expected += expected.ReturnOnEquity;
}
foreach (var account in clientAccounts)
{
List<AssetBase> assets = account.GetAssetsSync();
Ratios ratios = assets.GetAverageRatiosFor<InternationalEquity>();
Recommendation expected = assets.GetAverageExpectedFor<InternationalEquity>();
model1.actual += ratios.OneYearReturn;
model1.expected += expected.OneYearReturn == null ? 0 : (double)expected.OneYearReturn;
model3.actual += ratios.DebtEquityRatio;
model3.expected += expected.DebtEquityRatio;
model4.actual += ratios.EpsGrowth;
model4.expected += expected.EpsGrowth;
model5.actual += ratios.DividendYield;
model5.expected += expected.DividendYield;
model6.actual += ratios.Frank;
model6.expected += expected.Frank;
model7.actual += ratios.InterestCover;
model7.expected += expected.InterestCover;
model8.actual += ratios.PriceEarningRatio;
model8.expected += expected.PriceEarningRatio;
model9.actual += ratios.ReturnOnAsset;
model9.expected += expected.ReturnOnAsset;
model10.actual += ratios.ReturnOnEquity;
model10.expected += expected.ReturnOnEquity;
}
List<EvaluationModel> models = new List<EvaluationModel>();
models.Add(model1);
models.Add(model3);
models.Add(model4);
models.Add(model5);
models.Add(model6);
models.Add(model7);
models.Add(model8);
models.Add(model9);
models.Add(model10);
return models;
}
else
{
List<ClientAccount> accounts = edisRepo.GetAccountsForClientSync(client.ClientNumber, DateTime.Now);
EvaluationModel model1 = new EvaluationModel { title = "One Year Return" };
EvaluationModel model3 = new EvaluationModel { title = "Debt Equity Ratio" };
EvaluationModel model4 = new EvaluationModel { title = "Eps Growth" };
EvaluationModel model5 = new EvaluationModel { title = "Dividend Yield" };
EvaluationModel model6 = new EvaluationModel { title = "Franking" };
EvaluationModel model7 = new EvaluationModel { title = "Interest Cover" };
EvaluationModel model8 = new EvaluationModel { title = "Price Earning Ratio" };
EvaluationModel model9 = new EvaluationModel { title = "Return On Asset" };
EvaluationModel model10 = new EvaluationModel { title = "Return On Equity" };
foreach (var account in accounts)
{
List<AssetBase> assets = account.GetAssetsSync();
Ratios ratios = assets.GetAverageRatiosFor<InternationalEquity>();
Recommendation expected = assets.GetAverageExpectedFor<InternationalEquity>();
model1.actual += ratios.OneYearReturn;
model1.expected += expected.OneYearReturn == null ? 0 : (double)expected.OneYearReturn;
model3.actual += ratios.DebtEquityRatio;
model3.expected += expected.DebtEquityRatio;
model4.actual += ratios.EpsGrowth;
model4.expected += expected.EpsGrowth;
model5.actual += ratios.DividendYield;
model5.expected += expected.DividendYield;
model6.actual += ratios.Frank;
model6.expected += expected.Frank;
model7.actual += ratios.InterestCover;
model7.expected += expected.InterestCover;
model8.actual += ratios.PriceEarningRatio;
model8.expected += expected.PriceEarningRatio;
model9.actual += ratios.ReturnOnAsset;
model9.expected += expected.ReturnOnAsset;
model10.actual += ratios.ReturnOnEquity;
model10.expected += expected.ReturnOnEquity;
}
List<EvaluationModel> models = new List<EvaluationModel>();
models.Add(model1);
models.Add(model3);
models.Add(model4);
models.Add(model5);
models.Add(model6);
models.Add(model7);
models.Add(model8);
models.Add(model9);
models.Add(model10);
return models;
}
}
