public ListResults Browse(ListResultsRequest listResultsRequest)
{
HttpWebRequest request = CatalogRequestBuilder.ConstructListRequest(apiKey, listResultsRequest);
ListResults listResults = ProcessBodylessRequest(request).ToObject <ListResults>();
return(listResults);
}
IEnumerator UploadBestResultsGet()
{
string url = "https://www.neoblast-official.com/sportquiz/getBestRecord.php?hash=neo";
using (UnityWebRequest webRequest = UnityWebRequest.Get(url))
{
yield return(webRequest.SendWebRequest());
if (webRequest.isNetworkError)
{
Debug.Log(": Error: " + webRequest.error);
}
else
{
string result = webRequest.downloadHandler.text;
ListResults tmp_objects = JsonUtility.FromJson <ListResults>(result);
string text = "";
for (int i = 0; i < tmp_objects.results.Length; i++)
{
text += tmp_objects.results[i].name + "\n";
}
userNames.GetComponent <Text>().text = text;
text = "";
for (int i = 0; i < tmp_objects.results.Length; i++)
{
text += tmp_objects.results[i].highscore + "\n";
}
userScores.GetComponent <Text>().text = text;
}
}
}
public void TestBrowse()
{
ListResultsRequest listResultsRequest = new ListResultsRequest();
listResultsRequest.Type = EnumTypes.ListType.DEFAULT;
listResultsRequest.CategoryId = "3135";
listResultsRequest.IncludeAttributes = true;
listResultsRequest.Offset = 10;
listResultsRequest.Limit = 10;
listResultsRequest.DataOutputs = new EnumTypes.DataOutputType[] {
EnumTypes.DataOutputType.PRODUCTS,
EnumTypes.DataOutputType.CATEGORIES,
EnumTypes.DataOutputType.REFINEMENTS
};
listResultsRequest.Offers = new EnumTypes.OfferType[] {
EnumTypes.OfferType.ALL
};
ListResults listResults = client.Browse(listResultsRequest);
Assert.IsTrue(listResults.TotalResultSize > 0);
Assert.IsNotNull(listResults.Categories);
Assert.IsTrue(listResults.Categories.Count > 0);
Assert.IsNotNull(listResults.Products);
Assert.IsTrue(listResults.Products.Count > 0);
Assert.IsNotNull(listResults.RefinementGroups);
Assert.IsTrue(listResults.RefinementGroups.Count > 0);
}
public double[] VoltageOf(String circuitName)
{
if (!ListResults[0].CircuitProperties.ContainsKey(circuitName))
{
return(null);
}
return(ListResults.Select(l => l.CircuitProperties[circuitName].volts).ToArray());
}
private void ListResults_DoubleClick(object sender, MouseEventArgs e)
{
int index = ListResults.IndexFromPoint(e.Location);
if (index != System.Windows.Forms.ListBox.NoMatches)
{
System.Diagnostics.Process.Start(ListResults.SelectedItem.ToString());
}
}
public async Task <IActionResult> Get()
{
var forecasts = await this.temperaturesReadServices.GetCurrentTemperatures();
ListResults results = new ListResults();
results.Date = DateTime.UtcNow;
results.Forecasts = forecasts;
return(Ok(results));
}
//private static ListResults CreateDataOLE()
//{
// string dir = Directory.GetCurrentDirectory();
//}
private static ListResults CreateData()
{
//Create COM Objects. Create a COM object for everything that is referenced
string dir = Directory.GetCurrentDirectory();
Excel.Application xlApp = new Excel.Application();
Excel.Workbook xlWorkbook = xlApp.Workbooks.Open(Path.GetFullPath(Path.Combine(dir, @"..\..\Excel\EuroMillions.xlsx")));
Excel._Worksheet xlWorksheet = xlWorkbook.Sheets[1];
Excel.Range xlRange = xlWorksheet.UsedRange;
int rowCount = xlRange.Rows.Count;
int colCount = xlRange.Columns.Count;
ListResults results = new ListResults();
Stopwatch stopwatch = new Stopwatch();
stopwatch.Start();
for (int i = 2; i <= rowCount; i++)
{
List <int> numbers = new List <int>();
for (int j = 2; j <= colCount - 2; j++)
{
var cell = xlRange.Cells[i, j];
var number = Convert.ToInt32(cell.Value2);
if (number >= 1)
{
numbers.Add(number);
}
}
if (numbers.Count == 5)
{
results.Add(new Results
(
numbers[0],
numbers[1],
numbers[2],
numbers[3],
numbers[4]
));
}
else
{
Console.Write("Something didnt get counted");
}
}
stopwatch.Stop();
return(results);
}
private void SearchBox_PreviewKeyDown(object sender, KeyEventArgs e)
{
if (e.Key == Key.Enter || e.Key == Key.Return)
{
Search_Click(this, null);
}
if (e.Key == Key.Tab && this.Model.SearchResults.Count > 0)
{
ListResults.Focus();
}
}
private void Dev_DummyData_Click(object sender, MouseButtonEventArgs e)
{
ListResults.Clear();
var dummyData = new Dino[] {
new Dino {
Location = new Position {
Lat = 10, Lon = 10
}, Type = "Testificate", Name = "10,10"
},
new Dino {
Location = new Position {
Lat = 90, Lon = 10
}, Type = "Testificate", Name = "90,10"
},
new Dino {
Location = new Position {
Lat = 10, Lon = 90
}, Type = "Testificate", Name = "10,90"
},
new Dino {
Location = new Position {
Lat = 90, Lon = 90
}, Type = "Testificate", Name = "90,90"
},
new Dino {
Location = new Position {
Lat = 50, Lon = 50
}, Type = "Testificate", Name = "50,50"
},
};
var rnd = new Random();
foreach (var result in dummyData)
{
result.Id = (ulong)rnd.Next();
DinoViewModel vm = new DinoViewModel(result)
{
Color = Colors.Green
};
ListResults.Add(vm);
}
var cv = (CollectionView)CollectionViewSource.GetDefaultView(ListResults);
cv.Refresh();
}
private void UpdateSearchResults(IList <SearchCriteria> searches)
{
if (searches == null || searches.Count == 0)
{
ListResults.Clear();
}
else
{
// Find dinos that match the given searches
var found = new List <Dino>();
var sourceDinos = ShowTames ? arkReader.TamedDinos : arkReader.WildDinos;
var total = 0;
foreach (var search in searches)
{
if (String.IsNullOrWhiteSpace(search.Species))
{
foreach (var speciesDinos in sourceDinos.Values)
{
found.AddRange(speciesDinos);
total += speciesDinos.Count;
}
}
else
{
if (sourceDinos.ContainsKey(search.Species))
{
var dinoList = sourceDinos[search.Species];
found.AddRange(dinoList.Where(d => search.Matches(d)));
total += dinoList.Count;
}
}
}
ListResults.Clear();
foreach (var result in found)
{
ListResults.Add(result);
}
ShowCounts = true;
ResultTotalCount = ShowTames ? sourceDinos.Sum(species => species.Value.Count()) : total;
ResultMatchingCount = ListResults.Count;
}
((CollectionViewSource)Resources["OrderedResults"]).View.Refresh();
TriggerNameSearch(true);
}
protected void GetSelectedRecords(object sender, EventArgs e)
{
DataTable dt = new DataTable();
dt.Columns.AddRange(new DataColumn[6] {
new DataColumn("Name"), new DataColumn("ProductCode"), new DataColumn("OEM"), new DataColumn("Manufacturer"), new DataColumn("Price"), new DataColumn("Comment")
});
foreach (GridViewRow row in GridView1.Rows)
{
if (row.RowType == DataControlRowType.DataRow)
{
CheckBox chkRow = (row.Cells[0].FindControl("chkRow") as CheckBox);
if (chkRow.Checked)
{
string CarBrands = row.Cells[1].Text;
SqlDataAdapter da = new SqlDataAdapter(@"select * from goods where comment in(N'" + CarBrands + "') ", con);
DataTable tmp_dt = new DataTable();
da.Fill(tmp_dt);
//con.Close();
for (int i = 0; i < tmp_dt.Rows.Count; i++)
{
string products_name = tmp_dt.Rows[i]["name"].ToString();
string products_code = tmp_dt.Rows[i]["product_code"].ToString();
string products_oem = tmp_dt.Rows[i]["OEM"].ToString();
string products_manufacturer = tmp_dt.Rows[i]["manufacturer"].ToString();
string products_price = tmp_dt.Rows[i]["price"].ToString();
string products_comment = tmp_dt.Rows[i]["comment"].ToString();
dt.Rows.Add(products_name, products_code, products_oem, products_manufacturer, products_price, products_comment);
}
//string country = (row.Cells[2].FindControl("lblCountry") as Label).Text;
Response.Write("<script type='text/javascript'>alert('" + CarBrands + " - !!!')</script>");
dt.Rows.Add(CarBrands);
}
}
}
ListResults.DataSource = dt;
ListResults.DataBind();
}
private void UpdateSearchResults(IList <SearchCriteria> searches)
{
if (searches == null || searches.Count == 0)
{
ListResults.Clear();
}
else
{
// Find dinos that match the given searches
var found = new List <Dino>();
var reader = ShowTames ? arkReaderTamed : arkReaderWild;
foreach (var search in searches)
{
if (String.IsNullOrWhiteSpace(search.Species))
{
foreach (var speciesDinos in reader.FoundDinos.Values)
{
found.AddRange(speciesDinos);
}
}
else
{
if (reader.FoundDinos.ContainsKey(search.Species))
{
var dinoList = reader.FoundDinos[search.Species];
found.AddRange(dinoList.Where(d => search.Matches(d)));
}
}
}
ListResults.Clear();
foreach (var result in found)
{
ListResults.Add(result);
}
}
((CollectionViewSource)Resources["OrderedResults"]).View.Refresh();
TriggerNameSearch(true);
}
/*
* make async
*/
private void CallToApi(string query)
{
try
{
string response = APICaller.Call("https://api.themoviedb.org/3/search/movie?api_key=1a9755b22a226ad22bb40fc91e9ed04a", "&query=" + query);
_resultsModel = JsonConvert.DeserializeObject <ResultsModel>(response);
Console.WriteLine("response here: " + response);
Console.WriteLine("results model: " + _resultsModel.results.Count);
ImageBackground = new BitmapImage(new Uri("https://image.tmdb.org/t/p/original/" + _resultsModel.results[0].backdrop_path));
_resultsModel.results.ForEach(delegate(Result s)
{
ListResults.Add(s);
});
RaisePropertyChanged("ListResults");
}
catch (JsonReaderException e)
{
Console.WriteLine(e.StackTrace);
}
}
public ListFilesHandler(string backend, Options options, ListResults result)
{
m_backendurl = backend;
m_options = options;
m_result = result;
}
private async Task GenerateCalibrationPoints()
{
IsLoading = true;
try
{
StatusDetailText = "...converting";
StatusText = "Processing saved ARK (for calibration)";
var boxes = await arkReader.PerformCalibrationRead(Properties.Settings.Default.SaveFile);
if (boxes.Count == 0)
{
MessageBox.Show(@"Map calibration requires storage boxes named 'Calibration: XX.X, YY.Y', " +
"where XX.X and YY.Y are read from the GPS when standing on top of the box. " +
"At least 4 are required for a calculation but 16+ are recommended!",
"Calibration Boxes", MessageBoxButton.OK, MessageBoxImage.Information);
return;
}
var rnd = new Random();
foreach (var(pos, name) in boxes)
{
var dino = new Dino {
Location = pos, Type = "Calibration", Name = name, Id = (ulong)rnd.Next()
};
var vm = new DinoViewModel(dino)
{
Color = Colors.Blue
};
ListResults.Add(vm);
}
((CollectionViewSource)Resources["OrderedResults"]).View.Refresh();
StatusText = "ARK processing completed";
StatusDetailText = $"{boxes.Count} valid calibration boxes located";
if (boxes.Count >= 4)
{
var((xO, xD, xC), (yO, yD, yC)) = CalculateCalibration(boxes.Select(p => p.pos).ToArray());
var warning = (xC < 0.99 || yC < 0.99) ? "\nWARNING: Correlation is poor - add more boxes!\n" : "";
var result = MessageBox.Show("UE->LatLon conversion...\n" +
"\n" +
$"X: {xO:F2} + x / {xD:F3} (correlation {xC:F5})\n" +
$"Y: {yO:F2} + y / {yD:F3} (correlation {yC:F5})\n" +
warning +
"\nOpen Calibration window with these presets?", "Calibration Box Results", MessageBoxButton.YesNo);
if (MessageBoxResult.Yes == result)
{
var win = new CalibrationWindow(new Calibration
{
Bounds = new Bounds(),
Filename = MapCalibration.Filename,
LonOffset = xO,
LonDivisor = xD,
LatOffset = yO,
LatDivisor = yD,
});
Dispatcher.Invoke(() => win.ShowDialog());
}
}
}
catch (Exception ex)
{
StatusText = "ARK processing failed";
StatusDetailText = "";
MessageBox.Show(ex.Message, "Savegame Read Error", MessageBoxButton.OK, MessageBoxImage.Exclamation);
}
finally
{
IsLoading = false;
}
}
//public int V1 { get; private set; }
//public int V2 { get; private set; }
//public int V3 { get; private set; }
//public int V4 { get; private set; }
//public int V5 { get; private set; }
static void Main(string[] args)
{
//Create COM Objects. Create a COM object for everything that is referenced
//ListResults results = CreateDataOLE();
ListResults results = CreateData();
var deep = 20;
var network = new BasicNetwork();
network.AddLayer(new BasicLayer(null, true, 5 * deep));
network.AddLayer(new BasicLayer(new ActivationSigmoid(), true, 5 * 5 * deep));
network.AddLayer(new BasicLayer(new ActivationSigmoid(), true, 5 * 5 * deep));
network.AddLayer(new BasicLayer(new ActivationLinear(), true, 5));
network.Structure.FinalizeStructure();
var learningInput = new double[deep][];
for (int i = 0; i < deep; ++i)
{
learningInput[i] = new double[deep * 6];
for (int j = 0, k = 0; j < deep; ++j)
{
var idx = 2 * deep - i - j;
var data = results[idx];
learningInput[i][k++] = data.V1;
learningInput[i][k++] = data.V2;
learningInput[i][k++] = data.V3;
learningInput[i][k++] = data.V4;
learningInput[i][k++] = data.V5;
}
}
var learningOutput = new double[deep][];
for (int i = 0; i < deep; ++i)
{
var idx = deep - 1 - i;
var data = results[idx];
learningOutput[i] = new double[5]
{
data.V1,
data.V2,
data.V3,
data.V4,
data.V5,
};
}
var trainingSet = new BasicMLDataSet(learningInput, learningOutput);
var train = new ResilientPropagation(network, trainingSet);
train.NumThreads = Environment.ProcessorCount;
START : network.Reset();
RETRY:
var step = 0;
do
{
train.Iteration();
Console.WriteLine("Train Error: {0}", train.Error);
++step;
}while (train.Error > 0.001 && step < 20);
var passedCount = 0;
for (var i = 0; i < deep; ++i)
{
var should = new Results(learningOutput[i]);
var inputn = new BasicMLData(6 * deep);
Array.Copy(learningInput[i], inputn.Data, inputn.Data.Length);
var comput = new Results(((BasicMLData)network.Compute(inputn)).Data);
var passed = should.ToString() == comput.ToString();
if (passed)
{
Console.ForegroundColor = ConsoleColor.Green;
++passedCount;
}
else
{
Console.ForegroundColor = ConsoleColor.Red;
}
Console.WriteLine("{0} {1} {2} {3}", should.ToString().PadLeft(17, ' '), passed ? "==" : "!=",
comput.ToString().PadRight(17, ' '),
passed ? "PASS" : "FAIL");
Console.ResetColor();
}
var input = new BasicMLData(5 * deep);
for (int i = 0, k = 0; i < deep; ++i)
{
var idx = deep - 1 - i;
var data = results[idx];
input.Data[k++] = data.V1;
input.Data[k++] = data.V2;
input.Data[k++] = data.V3;
input.Data[k++] = data.V4;
input.Data[k++] = data.V5;
}
var perfect = results[0];
var predict = new Results(((BasicMLData)network.Compute(input)).Data);
Console.ForegroundColor = ConsoleColor.Yellow;
Console.WriteLine("Predict: {0}", predict);
Console.ResetColor();
if (predict.IsOut())
{
goto START;
}
if ((double)passedCount < (deep * (double)9 / (double)10) || !predict.IsValid())
{
goto RETRY;
}
Console.WriteLine("Press any key for close...");
Console.ReadKey(true);
}
public override IDictionary <string, object> BuildResultsForDisplay()
{
IDictionary <string, object> dict = base.BuildResultsForDisplay();
PM_MMAnalyser analyser = this.Analyser as PM_MMAnalyser;
int pp = analyser.Motor.Rotor.p;
// to open fem file
dict.Add("OpenResults", analyser.Path_ToAnalysisVariant);
dict.Add("psiD(Id)", new ListPointD(ListResults.Select(p => p.Idq.d).ToArray(), ListResults.Select(p => p.FluxLinkage_dq.d).ToArray()));
dict.Add("psiQ(Iq)", new ListPointD(ListResults.Select(p => p.Idq.q).ToArray(), ListResults.Select(p => p.FluxLinkage_dq.q).ToArray()));
dict.Add("Ld(I)", new ListPointD(ListResults.Where(p => p.Idq.d < 0).Select(p => p.Idq.Magnitude).ToArray(),
ListResults.Where(p => p.Idq.d < 0).Select(p => p.Ldq.d).ToArray()));
dict.Add("Lq(I)", new ListPointD(ListResults.Where(p => p.Idq.d < 0).Select(p => p.Idq.Magnitude).ToArray(),
ListResults.Where(p => p.Idq.d < 0).Select(p => p.Ldq.q).ToArray()));
dict.Add("psiM/Ld/Imax", new ListPointD(ListResults.Select(p => p.Idq.Magnitude).ToArray(), ListResults.Select(p => p.FluxLinkage_M / p.Ldq.d / p.Idq.Magnitude).ToArray()));
dict.Add("FluxLinkage(M)-mm", FluxLinkageM);
dict.Add("PhaseResistance", PhaseResistance);
double[] psid_ = new double[Count];
double[] psiq_ = new double[Count];
for (int i = 1; i < Count; i++)
{
psid_[i] = (ListResults[i].FluxLinkage_dq.d - ListResults[i - 1].FluxLinkage_dq.d) /
(ListResults[i].Idq.d - ListResults[i - 1].Idq.d);
psiq_[i] = (ListResults[i].FluxLinkage_dq.q - ListResults[i - 1].FluxLinkage_dq.q) /
(ListResults[i].Idq.q - ListResults[i - 1].Idq.q);
}
dict.Add("PsiD'(id)", new ListPointD(ListResults.Select(p => p.Idq.d).ToArray(), psid_));
dict.Add("PsiQ'(iq)", new ListPointD(ListResults.Select(p => p.Idq.q).ToArray(), psiq_));
//LinearSpline ls_psi_d = LinearSpline.Interpolate(ListResults.Select(p => p.Idq.d), ListResults.Select(p => p.FluxLinkage_dq.d));
//LinearSpline ls_psi_q = LinearSpline.Interpolate(ListResults.Select(p => p.Idq.q), ListResults.Select(p => p.FluxLinkage_dq.q));
// Build torque by angle for each
for (int i = 0; i < ListResults.Length; i++)
{
var one_step_result = ListResults[i];
// only quarter where id<0,iq>0
if (one_step_result.Idq.d >= 0 || one_step_result.Idq.q <= 0)
{
continue;
}
double Ld = one_step_result.Ldq.d;
double Lq = one_step_result.Ldq.q;
double II = one_step_result.Idq.Magnitude;
double Beta0 = one_step_result.Idq.Phase;
double psiM = one_step_result.FluxLinkage_M;
double d_wire = (Analyser.Motor.Stator as Stator3Phase).WireDiameter;
double S_wire = d_wire * d_wire / 4 * Math.PI;
String name = String.Format("Torque (Imax={0:F2}, J={1:F2})", II, II / S_wire / Math.Sqrt(2));
if (dict.ContainsKey(name))
{
continue;
}
int n = 360;
double[] x = Enumerable.Range(0, n).Select(kk => 1.0 * kk).ToArray();
double[] tt = new double[n];
for (int k = 0; k < n; k++)
{
double beta = 2.0 * Math.PI * k / n;
double id = II * Math.Cos(beta);
double iq = II * Math.Sin(beta);
tt[k] = 1.5 * pp * (psiM * iq + (Ld - Lq) * id * iq);
//double psid = ls_psi_d.Interpolate(id);
//double psiq = ls_psi_q.Interpolate(iq);
//tt[k] = 1.5 * pp * (psid * iq - psiq * id);
}
object value = new ListPointD(x, tt);
dict.Add(name, value);
}
IEnumerable <int> seq = Enumerable.Range(0, Count);
var arrI = ListResults.Where(p => p.Idq.d < 0).Select(p => p.Idq.Magnitude).ToArray();
var arrL1 = seq.Where(i => ListResults[i].Idq.d < 0).Select(i => (ListResults[i].Ldq.d + ListResults[i].Ldq.q) / 3).ToArray();
var arrL2 = seq.Where(i => ListResults[i].Idq.d < 0).Select(i => - (ListResults[i].Ldq.d - ListResults[i].Ldq.q) / 3).ToArray();
dict.Add("L1(I)", new ListPointD(arrI, arrL1));
dict.Add("L2(I)", new ListPointD(arrI, arrL2));
int Q = Analyser.Motor.Stator.Q;
int q = Q / 3 / pp / 2;
double kp = Math.Sin(Math.PI / (2 * 3)) / (q * Math.Sin(Math.PI / (2 * 3 * q)));
var stator = Analyser.Motor.Stator as Stator3Phase;
double ns = 4 / Math.PI * kp * stator.NStrands * q * pp;
var Motor = Analyser.Motor;
var rotor = Motor.Rotor as VPMRotor;
double gm = rotor.gammaMerad;
double[] arr_dmin = new double[Count];
double[] arr_dmax = new double[Count];
for (int i = 0; i < arrL1.Length; i++)
{
double mL1 = arrL1[i];
double mL2 = arrL2[i];
double a1 = mL1 / ((ns / 2 / pp) * (ns / 2 / pp) * Math.PI * Motor.Rotor.RGap * Motor.GeneralParams.MotorLength * 1e-6 * 4 * Math.PI * 1e-7);
double a2 = mL2 / (0.5 * (ns / 2 / pp) * (ns / 2 / pp) * Math.PI * Motor.Rotor.RGap * Motor.GeneralParams.MotorLength * 1e-6 * 4 * Math.PI * 1e-7);
arr_dmin[i] = 1 / (a1 + a2 * gm / (2 * Math.Sin(gm)));
arr_dmax[i] = 1 / (a1 - a2 * (Math.PI - gm) / (2 * Math.Sin(gm)));
}
dict.Add("dmin(I)", new ListPointD(arrI, arr_dmin));
dict.Add("dmax(I)", new ListPointD(arrI, arr_dmax));
return(dict);
}
public ListFilesHandler(string backend, Options options, ListResults result)
{
m_backendurl = backend;
m_options = options;
m_result = result;
}
