public static Dictionary <string, Tuple <double, double, double> > start()
{
Console.WriteLine(Test.bayesianFormula(Tuple.Create(31.2298850574713, 567.819679755498), 0));
var stopwatch = new Stopwatch();
stopwatch.Start();
//------------
HashSet <string> classifierGrams = new HashSet <string>();
List <Document> documents = new List <Document>();
Dictionary <string, Tuple <double, double, double> > valuesForEachClass = new Dictionary <string, Tuple <double, double, double> >();
prepareDocuments(documents, classifierGrams);
Tuple <List <Document>, List <Document> > datas = Likelihood.splitTrainingTestData(documents);
Console.WriteLine(classifierGrams.Count);
var meanAndVariances = Likelihood.training(datas.Item1, classifierGrams);
valuesForEachClass = Test.test(datas.Item2, meanAndVariances, classifierGrams);
//------------
stopwatch.Stop();
var elapsed_time = stopwatch.ElapsedMilliseconds;
Console.WriteLine(elapsed_time);
return(valuesForEachClass);
}
public override void Setup(IEvolutionState state, IParameter paramBase)
{
base.Setup(state, paramBase);
IParameter def = DefaultBase;
_generateMax = state.Parameters.GetBoolean(paramBase.Push(P_GEN_MAX), def.Push(P_GEN_MAX), false);
if (!Likelihood.Equals(1.0))
{
state.Output.Warning(
"UniquePipeline given a likelihood other than 1.0. This is nonsensical and will be ignored.",
paramBase.Push(P_LIKELIHOOD),
def.Push(P_LIKELIHOOD));
}
// How often do we retry if we find a duplicate?
NumDuplicateRetries = state.Parameters.GetInt(
paramBase.Push(P_RETRIES), def.Push(P_RETRIES), 0);
if (NumDuplicateRetries < 0)
{
state.Output.Fatal(
"The number of retries for duplicates must be an integer >= 0.\n",
paramBase.Push(P_RETRIES), def.Push(P_RETRIES));
}
}
private static float ConvertLikelyhood(Likelihood likelihood)
{
switch (likelihood)
{
case Likelihood.Unknown:
return(0);
case Likelihood.VeryLikely:
return(1);
case Likelihood.Likely:
return(.80F);
case Likelihood.Possible:
return(.60F);
case Likelihood.Unlikely:
return(.40F);
case Likelihood.VeryUnlikely:
return(.20F);
default:
return(0);
}
}
public void bTest()
{
int[] o = { 0, 0, 1, 0, 0, 0, 0, 0, 0, 0 };
HMM_QPN model = new HMM_QPN("G:/аспирантура/Programs/10.12.12/HSMPQApplication/m_1.txt");
Likelihood target = new Likelihood(o, model);
int i = 0; // TODO: инициализация подходящего значения
int d = 10; // TODO: инициализация подходящего значения
int t = 8; // TODO: инициализация подходящего значения
double expected = 0.03774874F; // TODO: инициализация подходящего значения
double actual;
//actual = target.b(i, d, t);
//Assert.AreEqual(expected, actual);
i = 0; // TODO: инициализация подходящего значения
d = 10; // TODO: инициализация подходящего значения
t = 13; // TODO: инициализация подходящего значения
expected = 0.2097152F; // TODO: инициализация подходящего значения
actual = 0;
//actual = target.b(i, d, t);
//Assert.AreEqual(expected, actual);
// Assert.Inconclusive("Проверьте правильность этого метода теста.");
int[] o1 = { 0, 0 };
Likelihood target1 = new Likelihood(o1, model);
i = 0; // TODO: инициализация подходящего значения
d = 10; // TODO: инициализация подходящего значения
t = 2; // TODO: инициализация подходящего значения
expected = 0.2097152F; // TODO: инициализация подходящего значения
actual = 0;
actual = target1.b(i, d, t);
Assert.AreEqual(expected, actual);
Assert.Inconclusive("Проверьте правильность этого метода теста.");
}
public void LikelihoodConstructorTest()
{
int[] o = null; // TODO: инициализация подходящего значения
HMM_QPN model = null; // TODO: инициализация подходящего значения
Likelihood target = new Likelihood(o, model);
Assert.Inconclusive("TODO: реализуйте код для проверки целевого объекта");
}
public ActionResult RemoveLikelihood(ADDB context, int id)
{
Likelihood likelihoodToRemove = context.Likelihoods.Find(id);
context.Likelihoods.Remove(likelihoodToRemove);
return(RedirectToAction("Index"));
}
public void CreateLikelihood(ADDB context, Likelihood likelihood)
{
//deal with duplicate entries
var duplicates = context.Likelihoods.Where(m => m.AnimalId == likelihood.AnimalId && m.DiseaseId == likelihood.DiseaseId && m.SignId == likelihood.SignId);
if (duplicates.Count() > 0)
{
return; // do not add anything if we already have a likelihood for the same animal, disease and sign
}
context.Likelihoods.Add(likelihood);
context.SaveChanges();
}
public override void Setup(IEvolutionState state, IParameter paramBase)
{
base.Setup(state, paramBase);
IParameter def = DefaultBase;
if (!Likelihood.Equals(1.0))
{
state.Output.Warning("ReproductionPipeline given a likelihood other than 1.0. This is nonsensical and will be ignored.",
paramBase.Push(P_LIKELIHOOD),
def.Push(P_LIKELIHOOD));
}
}
public List <double> compute()
{
List <double> result = new List <double>();
for (int i = step; i <= maxSize; i += step)
{
Likelihood ls = new Likelihood(SequenceUtils <int> .getSubsequence(sequence.Sequence, 0, i), model.Model);
double value = ls.FullProbability(i);
result.Add(value);
}
return(result);
}
public void FullProbabilityTest()
{
int[] o = null; // TODO: инициализация подходящего значения
HMM_QPN model = null; // TODO: инициализация подходящего значения
Likelihood target = new Likelihood(o, model); // TODO: инициализация подходящего значения
int t = 0; // TODO: инициализация подходящего значения
double expected = 0F; // TODO: инициализация подходящего значения
double actual;
actual = target.FullProbability(t);
Assert.AreEqual(expected, actual);
Assert.Inconclusive("Проверьте правильность этого метода теста.");
}
public override void Setup(IEvolutionState state, IParameter paramBase)
{
base.Setup(state, paramBase);
IParameter def = DefaultBase;
_numTimes = state.Parameters.GetInt(paramBase.Push(P_NUMTIMES), def.Push(P_NUMTIMES), 1);
if (_numTimes < 1)
{
state.Output.Fatal("CheckingPipeline must have a num-times value >= 1.",
paramBase.Push(P_NUMTIMES),
def.Push(P_NUMTIMES));
}
if (!Likelihood.Equals(1.0))
{
state.Output.Warning(
"CheckingPipeline given a likelihood other than 1.0. This is nonsensical and will be ignored.",
paramBase.Push(P_LIKELIHOOD),
def.Push(P_LIKELIHOOD));
}
}
public static Windows.UI.Color GetColor(this Likelihood likelihood)
{
switch (likelihood)
{
case Likelihood.VERY_LIKELY:
return(Colors.Crimson);
case Likelihood.LIKELY:
return(Colors.Red);
case Likelihood.POSSIBLE:
return(Colors.LightCoral);
case Likelihood.UNLIKELY:
return(Colors.Green);
case Likelihood.VERY_UNLIKELY:
return(Colors.Lime);
default:
return(Colors.White);
}
}
public static InspectTemplate Create(
string projectId,
string templateId,
string displayName,
string description,
Likelihood likelihood,
int maxFindings,
bool includeQuote)
{
var client = DlpServiceClient.Create();
var request = new CreateInspectTemplateRequest
{
ParentAsProjectName = new ProjectName(projectId),
InspectTemplate = new InspectTemplate
{
DisplayName = displayName,
Description = description,
InspectConfig = new InspectConfig
{
MinLikelihood = likelihood,
Limits = new InspectConfig.Types.FindingLimits
{
MaxFindingsPerRequest = maxFindings
},
IncludeQuote = includeQuote
},
},
TemplateId = templateId
};
var response = client.CreateInspectTemplate(request);
Console.WriteLine($"Successfully created template {response.Name}.");
return(response);
}
public static DlpJob InspectGCS(
string projectId,
Likelihood minLikelihood,
int maxFindings,
bool includeQuote,
IEnumerable <InfoType> infoTypes,
IEnumerable <CustomInfoType> customInfoTypes,
string bucketName,
string topicId,
string subscriptionId)
{
var inspectJob = new InspectJobConfig
{
StorageConfig = new StorageConfig
{
CloudStorageOptions = new CloudStorageOptions
{
FileSet = new CloudStorageOptions.Types.FileSet {
Url = $"gs://{bucketName}/*.txt"
},
BytesLimitPerFile = 1073741824
},
},
InspectConfig = new InspectConfig
{
InfoTypes = { infoTypes },
CustomInfoTypes = { customInfoTypes },
ExcludeInfoTypes = false,
IncludeQuote = includeQuote,
Limits = new FindingLimits
{
MaxFindingsPerRequest = maxFindings
},
MinLikelihood = minLikelihood
},
Actions =
{
new Google.Cloud.Dlp.V2.Action
{
// Send results to Pub/Sub topic
PubSub = new Google.Cloud.Dlp.V2.Action.Types.PublishToPubSub
{
Topic = topicId,
}
}
}
};
// Issue Create Dlp Job Request
var client = DlpServiceClient.Create();
var request = new CreateDlpJobRequest
{
InspectJob = inspectJob,
Parent = new LocationName(projectId, "global").ToString(),
};
// We need created job name
var dlpJob = client.CreateDlpJob(request);
// Get a pub/sub subscription and listen for DLP results
var fireEvent = new ManualResetEventSlim();
var subscriptionName = new SubscriptionName(projectId, subscriptionId);
var subscriber = SubscriberClient.CreateAsync(subscriptionName).Result;
subscriber.StartAsync(
(pubSubMessage, cancellationToken) =>
{
// Given a message that we receive on this subscription, we should either acknowledge or decline it
if (pubSubMessage.Attributes["DlpJobName"] == dlpJob.Name)
{
fireEvent.Set();
return(Task.FromResult(SubscriberClient.Reply.Ack));
}
return(Task.FromResult(SubscriberClient.Reply.Nack));
});
// We block here until receiving a signal from a separate thread that is waiting on a message indicating receiving a result of Dlp job
if (fireEvent.Wait(TimeSpan.FromMinutes(1)))
{
// Stop the thread that is listening to messages as a result of StartAsync call earlier
subscriber.StopAsync(CancellationToken.None).Wait();
// Now we can inspect full job results
var job = client.GetDlpJob(new GetDlpJobRequest {
DlpJobName = new DlpJobName(projectId, dlpJob.Name)
});
// Inspect Job details
Console.WriteLine($"Processed bytes: {job.InspectDetails.Result.ProcessedBytes}");
Console.WriteLine($"Total estimated bytes: {job.InspectDetails.Result.TotalEstimatedBytes}");
var stats = job.InspectDetails.Result.InfoTypeStats;
Console.WriteLine("Found stats:");
foreach (var stat in stats)
{
Console.WriteLine($"{stat.InfoType.Name}");
}
return(job);
}
throw new InvalidOperationException("The wait failed on timeout");
}
public static JobTrigger Create(
string projectId,
string bucketName,
Likelihood minLikelihood,
int maxFindings,
bool autoPopulateTimespan,
int scanPeriod,
IEnumerable <InfoType> infoTypes,
string triggerId,
string displayName,
string description)
{
var dlp = DlpServiceClient.Create();
var jobConfig = new InspectJobConfig
{
InspectConfig = new InspectConfig
{
MinLikelihood = minLikelihood,
Limits = new FindingLimits
{
MaxFindingsPerRequest = maxFindings
},
InfoTypes = { infoTypes }
},
StorageConfig = new StorageConfig
{
CloudStorageOptions = new CloudStorageOptions
{
FileSet = new FileSet
{
Url = $"gs://{bucketName}/*"
}
},
TimespanConfig = new TimespanConfig
{
EnableAutoPopulationOfTimespanConfig = autoPopulateTimespan
}
}
};
var jobTrigger = new JobTrigger
{
Triggers =
{
new Trigger
{
Schedule = new Schedule
{
RecurrencePeriodDuration = new Google.Protobuf.WellKnownTypes.Duration
{
Seconds = scanPeriod * 60 * 60 * 24
}
}
}
},
InspectJob = jobConfig,
Status = Status.Healthy,
DisplayName = displayName,
Description = description
};
var response = dlp.CreateJobTrigger(
new CreateJobTriggerRequest
{
ParentAsProjectName = new ProjectName(projectId),
JobTrigger = jobTrigger,
TriggerId = triggerId
});
Console.WriteLine($"Successfully created trigger {response.Name}");
return(response);
}
private void CountProbBtn_Click(object sender, EventArgs e)
{
HMM_QPN Model = new HMM_QPN(label1.Text);
if (Model.IsCorrect() == 1)
{
int smbnubmer = 10;
if (textBox2.Text != "")
{
try
{
smbnubmer = int.Parse(textBox2.Text);
}
catch (Exception)
{
}
}
;
int[] res = new int[smbnubmer + 1];
try
{
res = HMM_PSM.GetOutputSequence(label2.Text, smbnubmer);
}
catch (Exception)
{
MessageBox.Show("Желаемая длина последовательности превышает размер файла");
return;
}
panel3.Enabled = false;
if (radioButton1.Checked)
{
//try
//{
Likelihood lk = new Likelihood(res, Model);
//label3.Text = lk.Probability(res.Length - 1).ToString();
label3.Text = lk.FullProbability(res.Length - 1).ToString();
//}
//catch (Exception)
// { MessageBox.Show("В процессе расчета возникла ошибка!"); };
panel3.Enabled = true;
}
else
{
if (radioButton2.Checked)
{
LikelihoodSimple lk = new LikelihoodSimple(res, Model);
//label3.Text = lk.Probability(res.Length - 1).ToString();
label3.Text = lk.Probability(res.Length - 1).ToString();
panel3.Enabled = true;
}
else
{
if (tbSegmentNumber.Text != "")
{
int segment_size = 0;
if (Int32.TryParse(tbSegmentNumber.Text, out segment_size))
{
LikelihoodSplit ls = new LikelihoodSplit(segment_size);
double [] result = ls.calculateSplitedLikelihood(Model, res);
double total = 0;
tbSplitResultDetails.Text = "";
for (int i = 0; i < result.Length; i++)
{
tbSplitResultDetails.Text += "P[O(" + i * segment_size + "," + ((i + 1) * segment_size) + ")] = " + result[i] + "\r\n";
total += result[i];
}
label3.Text = (total / result.Length).ToString();
panel3.Enabled = true;
}
else
{
MessageBox.Show("Размер сегмента разбиения должен быть целым");
}
}
else
{
MessageBox.Show("Задайте размер сегмента разбиения");
}
}
}
}
else
{
MessageBox.Show("Модель задана некорректно");
}
}
public static bool MeetsThreshold(this Likelihood input, Likelihood minThreshold)
{
return((int)input >= (int)minThreshold);
}
public ActionResult InsertNewLikelihood(ADDB context, Likelihood likelihood)
{
CreateLikelihood(context, likelihood);
return(RedirectToAction("Index"));
}
public static object Inspect(
string projectId,
Likelihood minLikelihood,
int maxFindings,
bool includeQuote,
IEnumerable <FieldId> identifyingFields,
IEnumerable <InfoType> infoTypes,
IEnumerable <CustomInfoType> customInfoTypes,
string datasetId,
string tableId)
{
var inspectJob = new InspectJobConfig
{
StorageConfig = new StorageConfig
{
BigQueryOptions = new BigQueryOptions
{
TableReference = new Google.Cloud.Dlp.V2.BigQueryTable
{
ProjectId = projectId,
DatasetId = datasetId,
TableId = tableId,
},
IdentifyingFields =
{
identifyingFields
}
},
TimespanConfig = new StorageConfig.Types.TimespanConfig
{
StartTime = Timestamp.FromDateTime(System.DateTime.UtcNow.AddYears(-1)),
EndTime = Timestamp.FromDateTime(System.DateTime.UtcNow)
}
},
InspectConfig = new InspectConfig
{
InfoTypes = { infoTypes },
CustomInfoTypes = { customInfoTypes },
Limits = new FindingLimits
{
MaxFindingsPerRequest = maxFindings
},
ExcludeInfoTypes = false,
IncludeQuote = includeQuote,
MinLikelihood = minLikelihood
},
Actions =
{
new Google.Cloud.Dlp.V2.Action
{
// Save results in BigQuery Table
SaveFindings = new Google.Cloud.Dlp.V2.Action.Types.SaveFindings
{
OutputConfig = new OutputStorageConfig
{
Table = new Google.Cloud.Dlp.V2.BigQueryTable
{
ProjectId = projectId,
DatasetId = datasetId,
TableId = tableId
}
}
},
}
}
};
// Issue Create Dlp Job Request
var client = DlpServiceClient.Create();
var request = new CreateDlpJobRequest
{
InspectJob = inspectJob,
ParentAsProjectName = new ProjectName(projectId),
};
// We need created job name
var dlpJob = client.CreateDlpJob(request);
var jobName = dlpJob.Name;
// Make sure the job finishes before inspecting the results.
// Alternatively, we can inspect results opportunistically, but
// for testing purposes, we want consistent outcome
var finishedJob = EnsureJobFinishes(projectId, jobName);
var bigQueryClient = BigQueryClient.Create(projectId);
var table = bigQueryClient.GetTable(datasetId, tableId);
// Return only first page of 10 rows
Console.WriteLine("DLP v2 Results:");
var firstPage = table.ListRows(new ListRowsOptions {
StartIndex = 0, PageSize = 10
});
foreach (var item in firstPage)
{
Console.WriteLine($"\t {item[""]}");
}
return(finishedJob);
}
private void saveDocument()
{
newRiskPlanModel.ProjectName = Project_Name_tbx.Text;
List <Information> informations = new List <Information>();
Information information = new Information();
var DocumentID = Document_Information_dgv.Rows[0].Cells[1].Value.ToString();
var DocumentOwner = Document_Information_dgv.Rows[1].Cells[1].Value.ToString();
var IssueDate = Document_Information_dgv.Rows[2].Cells[1].Value.ToString();
var LastSavedDate = Document_Information_dgv.Rows[3].Cells[1].Value.ToString();
var FileName = Document_Information_dgv.Rows[4].Cells[1].Value.ToString();
information.DocumentID = DocumentID;
information.DocumentOwner = DocumentOwner;
information.IssueDate = IssueDate;
information.LastSavedDate = LastSavedDate;
information.FileName = FileName;
newRiskPlanModel.Information = information;
List <History> histories = new List <History>();
int Document_HistoryRowCount = Document_History_dgv.RowCount;
for (int i = 0; i < Document_HistoryRowCount - 1; i++)
{
History history = new History();
var Version = Document_History_dgv.Rows[i].Cells[0].Value?.ToString() ?? "";
var IsDate = Document_History_dgv.Rows[i].Cells[1].Value?.ToString() ?? "";
var Changes = Document_History_dgv.Rows[i].Cells[2].Value?.ToString() ?? "";
history.Version = Version;
history.IssueDate = IsDate;
history.Changes = Changes;
histories.Add(history);
}
newRiskPlanModel.Histories = histories;
List <Approval> approvals = new List <Approval>();
int approvalCount = Document_Approvals_dgv.RowCount;
for (int i = 0; i < Document_HistoryRowCount - 1; i++)
{
Approval approval = new Approval();
var Role = Document_Approvals_dgv.Rows[i].Cells[0].Value?.ToString() ?? "";
var Name = Document_Approvals_dgv.Rows[i].Cells[1].Value?.ToString() ?? "";
var Signature = Document_Approvals_dgv.Rows[i].Cells[2].Value?.ToString() ?? "";
var Date = Document_Approvals_dgv.Rows[i].Cells[3].Value?.ToString() ?? "";
approval.Name = Name;
approval.Role = Role;
approval.Signature = Signature;
approval.Date = Date;
approvals.Add(approval);
}
newRiskPlanModel.Approvals = approvals;
newRiskPlanModel.Categories = Categories_tbx.Text;
List <Risk> risks = new List <Risk>();
int riskCount = Risks_dgv.RowCount;
for (int i = 0; i < riskCount - 1; i++)
{
Risk risk = new Risk();
var RiskCategory = Risks_dgv.Rows[i].Cells[0].Value?.ToString() ?? "";
var RiskDescription = Risks_dgv.Rows[i].Cells[1].Value?.ToString() ?? "";
var ID = Risks_dgv.Rows[i].Cells[2].Value?.ToString() ?? "";
risk.RiskCategory = RiskCategory;
risk.RiskDescription = RiskDescription;
risk.ID = ID;
risks.Add(risk);
}
newRiskPlanModel.Risks = risks;
List <Likelihood> likelihoods = new List <Likelihood>();
int LikelihoodrowCount = Likelihood_dgv.RowCount;
for (int i = 0; i < LikelihoodrowCount - 1; i++)
{
Likelihood likelihood = new Likelihood();
var Title = Likelihood_dgv.Rows[i].Cells[0].Value?.ToString() ?? "";
var Score = Likelihood_dgv.Rows[i].Cells[1].Value?.ToString() ?? "";
var Description = Likelihood_dgv.Rows[i].Cells[2].Value?.ToString() ?? "";
likelihood.Title = Title;
likelihood.Score = Score;
likelihood.Description = Description;
likelihoods.Add(likelihood);
}
newRiskPlanModel.Likelihoods = likelihoods;
List <Impact> impacts = new List <Impact>();
int impactrowCount = Impact_dgv.RowCount;
for (int i = 0; i < impactrowCount - 1; i++)
{
Impact impact = new Impact();
var Title = Impact_dgv.Rows[i].Cells[0].Value?.ToString() ?? "";
var Score = Impact_dgv.Rows[i].Cells[1].Value?.ToString() ?? "";
var Description = Impact_dgv.Rows[i].Cells[2].Value?.ToString() ?? "";
impact.Title = Title;
impact.Score = Score;
impact.Description = Description;
impacts.Add(impact);
}
newRiskPlanModel.Impacts = impacts;
List <Priority> priorities = new List <Priority>();
int PriorityrowCount = Priority_dgv.RowCount;
for (int i = 0; i < PriorityrowCount - 1; i++)
{
Priority priority = new Priority();
var ID = Priority_dgv.Rows[i].Cells[0].Value?.ToString() ?? "";
var LikelihoodScore = Priority_dgv.Rows[i].Cells[1].Value?.ToString() ?? "";
var ImpactScore = Priority_dgv.Rows[i].Cells[2].Value?.ToString() ?? "";
var PriorityScore = Priority_dgv.Rows[i].Cells[3].Value?.ToString() ?? "";
var PriorityRating = Priority_dgv.Rows[i].Cells[4].Value?.ToString() ?? "";
priority.ID = ID;
priority.LikelihoodScore = LikelihoodScore;
priority.ImpactScore = ImpactScore;
priority.PriorityScore = PriorityScore;
priority.PriorityRating = PriorityRating;
priorities.Add(priority);
}
newRiskPlanModel.Priorities = priorities;
List <Schedule> schedules = new List <Schedule>();
int SchedulerowCount = Schedule_dgv.RowCount;
for (int i = 0; i < SchedulerowCount - 1; i++)
{
Schedule schedule = new Schedule();
var Rating = Schedule_dgv.Rows[i].Cells[0].Value?.ToString() ?? "";
var ID = Schedule_dgv.Rows[i].Cells[1].Value?.ToString() ?? "";
var PrevalantiveActions = Schedule_dgv.Rows[i].Cells[2].Value?.ToString() ?? "";
var ActionResource1 = Schedule_dgv.Rows[i].Cells[3].Value?.ToString() ?? "";
var ActionDate1 = Schedule_dgv.Rows[i].Cells[4].Value?.ToString() ?? "";
var ContingentActions = Schedule_dgv.Rows[i].Cells[5].Value?.ToString() ?? "";
var ActionResource2 = Schedule_dgv.Rows[i].Cells[6].Value?.ToString() ?? "";
var ActionDate2 = Schedule_dgv.Rows[i].Cells[7].Value?.ToString() ?? "";
schedule.Rating = Rating;
schedule.ID = ID;
schedule.PrevalantiveActions = PrevalantiveActions;
schedule.ActionResource1 = ActionResource1;
schedule.ActionDate1 = ActionDate1;
schedule.ContingentActions = ContingentActions;
schedule.ActionResource2 = ActionResource2;
schedule.ActionDate2 = ActionDate2;
schedules.Add(schedule);
}
newRiskPlanModel.Schedules = schedules;
newRiskPlanModel.Assumptions = Assumptions_tbx.Text;
newRiskPlanModel.Constraints = Constraints_tbx.Text;
newRiskPlanModel.Activities = Activities_tbx.Text;
newRiskPlanModel.Roles = Roles_tbx.Text;
newRiskPlanModel.Documents = Documents_tbx.Text;
newRiskPlanModel.Appendix = Appendix_tbx.Text;
List <VersionControl <RiskPlanModel> .DocumentModel> documentModels = versionControl.DocumentModels;
//MessageBox.Show(JsonConvert.SerializeObject(newRiskPlanModel), "save", MessageBoxButtons.OK);
if (!versionControl.isEqual(currentRiskPlanModel, newRiskPlanModel))
{
VersionControl <RiskPlanModel> .DocumentModel documentModel = new VersionControl <RiskPlanModel> .DocumentModel(newRiskPlanModel, DateTime.Now, VersionControl <RiskPlanModel> .generateID());
documentModels.Add(documentModel);
versionControl.DocumentModels = documentModels;
string json = JsonConvert.SerializeObject(versionControl);
currentRiskPlanModel = JsonConvert.DeserializeObject <RiskPlanModel>(JsonConvert.SerializeObject(newRiskPlanModel));
JsonHelper.saveDocument(json, Settings.Default.ProjectID, "RiskPlan");
MessageBox.Show("Risk plan saved successfully", "save", MessageBoxButtons.OK);
}
}
