public MatrisBase <object> Head(MatrisBase <object> df,
int n = 5)
{
if (!df.IsValid())
{
throw new Exception(CompilerMessage.DF_INVALID_SIZE);
}
n = Math.Min(n, df.Row);
if (n <= 0 || df.Row < n)
{
throw new Exception(CompilerMessage.MAT_OUT_OF_RANGE_INDEX("satır", 1, df.Row));
}
return(df.Row == n
? df is Dataframe ? ((Dataframe)df.Copy()) : df.Copy()
: df is Dataframe dataframe
? new Dataframe(dataframe[new Range(0, n)],
dataframe.Delimiter,
dataframe.NewLine,
null,
Dataframe.GetCopyOfLabels(dataframe.GetColLabels()),
dataframe.GetRowSettings().Copy(),
dataframe.GetColSettings().Copy())
: new MatrisBase <object>(df[new Range(0, n)]));
}
public MatrisBase <object> Mul(MatrisBase <object> df,
int numberOnly = 1)
{
if (!df.IsValid())
{
throw new Exception(CompilerMessage.DF_INVALID_SIZE);
}
int nc = df.Col;
int nr = df.Row;
List <object> muls = new List <object>();
for (int c = 0; c < nc; c++)
{
muls.Add(ArrayMethods.ArrayMul(df.ColList(c, 0), 0, nr, numberOnly) ?? float.NaN);
}
return(df is Dataframe data
? new Dataframe(new List <List <object> >()
{
muls
},
data.Delimiter,
data.NewLine,
null,
Dataframe.GetCopyOfLabels(data.GetColLabels()),
null,
data.GetColSettings().Copy())
: new MatrisBase <object>(new List <List <object> >()
{
muls
}));
}
public MatrisBase <object> Set(MatrisBase <object> A,
int i,
int j,
float value,
int based = 0)
{
if (!A.IsValid())
{
throw new Exception(CompilerMessage.MAT_INVALID_SIZE);
}
if (i - based < 0 || i - based >= A.Row)
{
throw new Exception(CompilerMessage.MAT_OUT_OF_RANGE_INDEX("satır", based, A.Row - 1));
}
if (j - based < 0 || j - based >= A.Col)
{
throw new Exception(CompilerMessage.MAT_OUT_OF_RANGE_INDEX("sütun", based, A.Col - 1));
}
List <List <object> > newlis = A is Dataframe ? ((Dataframe)A.Copy()).GetValues() : A.Copy().GetValues();
newlis[i - based][j - based] = (dynamic)value;
return(A is Dataframe df
? new Dataframe(newlis,
df.Delimiter,
df.NewLine,
Dataframe.GetCopyOfLabels(df.GetRowLabels()),
Dataframe.GetCopyOfLabels(df.GetColLabels()),
df.GetRowSettings().Copy(),
df.GetColSettings().Copy())
: new MatrisBase <object>(newlis));
}
public MatrisBase <object> Abs(MatrisBase <object> A)
{
if (!A.IsValid())
{
throw new Exception(CompilerMessage.MAT_INVALID_SIZE);
}
CompilerUtils.AssertMatrixValsAreNumbers(A);
int m = A.Row;
int n = A.Col;
List <List <object> > vals = A.GetValues();
List <List <object> > newvals = new List <List <object> >();
for (int i = 0; i < m; i++)
{
newvals.Add(new List <object>());
for (int j = 0; j < n; j++)
{
newvals[i].Add((dynamic)Math.Abs(float.Parse(vals[i][j].ToString())));
}
}
return(A is Dataframe df
? new Dataframe(newvals,
df.Delimiter,
df.NewLine,
Dataframe.GetCopyOfLabels(df.GetRowLabels()),
Dataframe.GetCopyOfLabels(df.GetColLabels()),
df.GetRowSettings().Copy(),
df.GetColSettings().Copy())
: new MatrisBase <object>(newvals));
}
internal static async Task <Dataframe?> CreateDataframe(TcpConnectionService tcpConnection, CancellationToken ct)
{
var dataframe = new Dataframe(tcpConnection, ct);
var oneByteArray = await dataframe.GetNextBytes(1);
Debug.WriteLine($"First byte: {oneByteArray?[0]}");
if (oneByteArray is null)
{
return(null);
}
var bits = new BitArray(oneByteArray);
return(dataframe with
{
FIN = bits[7],
RSV1 = bits[6],
RSV2 = bits[5],
RSV3 = bits[4],
Opcode = GetOpcode(),
Fragment = oneByteArray[0] switch
{
(byte)FragmentKind.First => FragmentKind.First,
(byte)FragmentKind.Last => FragmentKind.Last,
_ => FragmentKind.None
}
});
public MatrisBase <object> Adjoint(MatrisBase <object> A)
{
if (!A.IsSquare())
{
throw new Exception(CompilerMessage.MAT_NOT_SQUARE);
}
CompilerUtils.AssertMatrixValsAreNumbers(A);
List <List <object> > adj = new List <List <object> >();
int r = A.Row;
int c = A.Col;
for (int i = 0; i < r; i++)
{
adj.Add(new List <object>());
for (int j = 0; j < c; j++)
{
adj[i].Add((dynamic)(((i + j) % 2 == 1 ? -1 : 1) * Minor(A, i, j, 0)));
}
}
return(A is Dataframe df
? new Dataframe(Transpose(new MatrisBase <object>(adj)).GetValues(),
df.Delimiter,
df.NewLine,
Dataframe.GetCopyOfLabels(df.GetRowLabels()),
Dataframe.GetCopyOfLabels(df.GetColLabels()),
df.GetRowSettings().Copy(),
df.GetColSettings().Copy())
: Transpose(new MatrisBase <object>(adj)));
}
public MatrisBase <object> RREchelon(MatrisBase <object> A)
{
// Bad dimensions
if (!A.IsValid())
{
throw new Exception(CompilerMessage.MAT_INVALID_SIZE);
}
// Zero matrix
if (A.IsZero((float)0.0))
{
return(A);
}
if (A is Dataframe df)
{
CompilerUtils.AssertMatrixValsAreNumbers(A);
Dataframe result = df.Copy();
InnerRREchelon(df, result);
return(result);
}
else
{
MatrisBase <object> result = A.Copy();
InnerRREchelon(A, result);
return(result);
}
}
public MatrisBase <object> Inverse(MatrisBase <object> A)
{
if (!A.IsSquare())
{
throw new Exception(CompilerMessage.MAT_NOT_SQUARE);
}
if (Determinant(A) == (float)0.0)
{
throw new Exception(CompilerMessage.MAT_DET_ZERO_NO_INV);
}
using MatrisBase <object> temp = Concatenate(A is Dataframe ? ((Dataframe)A.Copy()) : A.Copy(),
(dynamic) new SpecialMatricesService().Identity(A.Row),
1);
return(A is Dataframe df
? new Dataframe(RREchelon(temp)[new Range(new Index(0), new Index(temp.Row)), new Range(new Index(A.Col), new Index(temp.Col))],
df.Delimiter,
df.NewLine,
Dataframe.GetCopyOfLabels(df.GetRowLabels()),
Dataframe.GetCopyOfLabels(df.GetColLabels()),
df.GetRowSettings().Copy(),
df.GetColSettings().Copy())
: new MatrisBase <object>(vals: RREchelon(temp)[new Range(new Index(0), new Index(temp.Row)), new Range(new Index(A.Col), new Index(temp.Col))]));
}
/* Method: GenerateDataSetFromFile
* Generates a float dataset from an input file.
* The dataset is saved on the static class attribute to be used and accessed from another context.
*
* Parameters:
* - path: path to file on project structure.
* Outputs:
* - N/A
*/
public static void GenerateDataSetFromFile(string path)
{
// Reads lines from file
var lines = ReadFile(path);
var xArray = new int[lines.Length];
var yArray = new int[lines.Length];
var values = new float[lines.Length];
// Iterates and separates each line
for (int i = 0; i < lines.Length; i++)
{
var separatedValues = lines[i].Split(';');
int xCoord = int.Parse(separatedValues[0]);
int yCoord = int.Parse(separatedValues[1]);
float.TryParse(separatedValues[2], out float value);
xArray[i] = xCoord;
yArray[i] = yCoord;
values[i] = value;
}
dataset = new Dataframe(xArray, yArray, values);
visibleDataset = new Dataframe(xArray, yArray, values);
maxFilter = Mathf.CeilToInt(dataset.maxValue);
minFilter = Mathf.FloorToInt(dataset.minValue);
}
public static void ResetFilters()
{
maxFilter = dataset.maxValue;
minFilter = dataset.minValue;
visibleDataset = dataset;
newFilterApplied = true;
}
public static void FilterDataset()
{
Dataframe newDataframe = new Dataframe
{
width = dataset.width,
length = dataset.length,
depth = dataset.depth,
minValue = dataset.minValue,
maxValue = dataset.maxValue,
mean = dataset.mean
};
float [,] newValues = new float[dataset.width, dataset.length];
int xSize = dataset.values.GetLength(0);
int ySize = dataset.values.GetLength(1);
for (int i = 0; i < xSize; i++)
{
for (int j = 0; j < ySize; j++)
{
float value = dataset.values[i, j];
bool aboveMinFilter = value > minFilter / dataset.depth;
bool belowMaxFilter = value < maxFilter / dataset.depth;
newValues[i, j] = (aboveMinFilter && belowMaxFilter) ? value : 0.00f;
}
}
newDataframe.values = newValues;
visibleDataset = newDataframe;
newFilterApplied = true;
}
private void button1_Click(object sender, EventArgs e)
{
if (openFileDialog1.ShowDialog() == DialogResult.OK)
{
string dataFileName = openFileDialog1.FileName;
System.IO.StreamReader fs = System.IO.File.OpenText(openFileDialog1.FileName);
string[] token = fs.ReadLine().Split(' ');
int length = int.Parse(token[0]);
int numLabel = int.Parse(token[1]);
dataframe = new Dataframe(numLabel, length);
for (int i = 0; i < length; i++)
{
token = fs.ReadLine().Split('@');
for (int j = 0; j < numLabel; j++)
{
dataframe.Features[j, i] = double.Parse(token[j]);
}
}
}
else
{
return;
}
}
internal async Task SendPong(
Dataframe dataframe,
CancellationToken ct) =>
await ComposeFrameAndSendAsync(
dataframe.Binary,
OpcodeKind.Pong,
FragmentKind.None,
ct);
public MatrisBase <object> ToMat(Dataframe dataframe)
{
if (dataframe.IsValid() && dataframe.IsAllNumbers())
{
return(new MatrisBase <object>(dataframe.Copy().GetValues()));
}
else
{
throw new Exception(CompilerMessage.INVALID_CONVERSION_TO_MAT);
}
}
private void _read()
{
_dataframes = new List <Dataframe>();
{
var i = 0;
Dataframe M_;
do
{
M_ = new Dataframe(m_io, this, m_root);
_dataframes.Add(M_);
i++;
} while (!(M_.Finished));
}
}
private void _read()
{
_initialFrame = new InitialFrame(m_io, this, m_root);
if (InitialFrame.Header.Finished != true)
{
_trailingFrames = new List <Dataframe>();
{
var i = 0;
Dataframe M_;
do
{
M_ = new Dataframe(m_io, this, m_root);
_trailingFrames.Add(M_);
i++;
} while (!(M_.Header.Finished));
}
}
}
public MatrisBase <object> Mean(MatrisBase <object> df,
int numberOnly = 1)
{
if (!df.IsValid())
{
throw new Exception(CompilerMessage.DF_INVALID_SIZE);
}
int nc = df.Col;
int nr = df.Row;
List <object> means = new List <object>();
int pop;
for (int c = 0; c < nc; c++)
{
pop = nr - (numberOnly == 1 ? df.AmountOfNanInColumn(c) : 0);
object res = ArrayMethods.ArraySum(df.ColList(c, 0), 0, nr, numberOnly) ?? float.NaN;
if (pop == 0)
{
means.Add(float.NaN);
}
else
{
means.Add(float.IsNaN((float)res) ? res : (float)res / pop);
}
}
return(df is Dataframe data
? new Dataframe(new List <List <object> >()
{
means
},
data.Delimiter,
data.NewLine,
null,
Dataframe.GetCopyOfLabels(data.GetColLabels()),
null,
data.GetColSettings().Copy())
: new MatrisBase <object>(new List <List <object> >()
{
means
}));
}
public MatrisBase <object> Sample(MatrisBase <object> df,
int n = 5)
{
if (!df.IsValid())
{
throw new Exception(CompilerMessage.DF_INVALID_SIZE);
}
int nr = df.Row;
n = Math.Min(n, nr);
if (n <= 0 || nr < n)
{
throw new Exception(CompilerMessage.MAT_OUT_OF_RANGE_INDEX("satır", 1, nr));
}
if (nr == n)
{
return(df is Dataframe ? ((Dataframe)df.Copy()) : df.Copy());
}
else
{
List <List <object> > newList = new List <List <object> >();
List <List <object> > shuffled = new MatrisArithmeticService().Shuffle(df, 0).GetValues();
for (int i = 0; i < n; i++)
{
newList.Add(shuffled[i]);
}
return(df is Dataframe dataframe
? new Dataframe(newList,
dataframe.Delimiter,
dataframe.NewLine,
null,
Dataframe.GetCopyOfLabels(dataframe.GetColLabels()),
dataframe.GetRowSettings().Copy(),
dataframe.GetColSettings().Copy()
)
: new MatrisBase <object>(newList));
}
}
public MatrisBase <object> Round(MatrisBase <object> A,
int n = 0)
{
if (!A.IsValid())
{
throw new Exception(CompilerMessage.MAT_INVALID_SIZE);
}
CompilerUtils.AssertMatrixValsAreNumbers(A);
return(n < 0
? throw new Exception(CompilerMessage.ARG_INVALID_VALUE("n", " Sıfırdan büyük olmalı."))
: A is Dataframe df
? new Dataframe(A.Round(n).GetValues(),
df.Delimiter,
df.NewLine,
Dataframe.GetCopyOfLabels(df.GetRowLabels()),
Dataframe.GetCopyOfLabels(df.GetColLabels()),
df.GetRowSettings().Copy(),
df.GetColSettings().Copy())
: A.Round(n));
}
public MatrisBase <object> Transpose(MatrisBase <object> A)
{
if (!A.IsValid())
{
throw new Exception(CompilerMessage.MAT_INVALID_SIZE);
}
List <List <object> > result = new List <List <object> >();
for (int j = 0; j < A.Col; j++)
{
result.Add(A.ColList(j, 0));
}
return(A is Dataframe df
? new Dataframe(result,
df.Delimiter,
df.NewLine,
Dataframe.GetCopyOfLabels(df.GetColLabels()),
Dataframe.GetCopyOfLabels(df.GetRowLabels()),
df.GetRowSettings().Copy(),
df.GetColSettings().Copy())
: new MatrisBase <object>(result));
}
private TerrainData UpdateTerrainData(TerrainData td, Dataframe ds = null)
{
// updates the terrain object and sets all its properties
float[,] heights;
if (ds != null)
{
Debug.Log("Input generated map");
width = ds.width;
length = ds.length;
depth = ds.depth;
heights = ds.values;
}
else
{
heights = GenerateHeights();
// Debug.Log("Noise generated map");
}
// sets the heigthmap of the terrain
td.size = new Vector3(width, depth, length);
td.heightmapResolution = GetMapResolution(width, length);
td.SetHeights(0, 0, heights);
return(td);
}
/// <summary>
/// Create and save a dataframe with given name and values from text
/// </summary>
public async Task OnPostAddDataframe()
{
if (_frontService.CheckCmdDate(HttpContext.Session.Get <DateTime>(SessionLastCommandDate)))
{
DateTime LastCmdDate = DateTime.Now;
Dictionary <string, string> reqdict = new Dictionary <string, string>();
await _utils.ReadAndDecodeRequest(Request.Body, Encoding.Default, IgnoredParams, reqdict);
if (reqdict.ContainsKey(DfNameParam) &&
reqdict.ContainsKey(DfValsParam) &&
reqdict.ContainsKey(DfDelimParam) &&
reqdict.ContainsKey(DfNewLineParam)
)
{
Dictionary <string, Dataframe> _dict = HttpContext.Session.GetDfDict(SessionDfDict, SessionDfLabels, SessionDfSettings);
if (!HttpContext.Session.GetMatrixDict(SessionMatrisDict, SessionSeedDict).ContainsKey(reqdict[DfNameParam]))
{
if (!_dict.ContainsKey(reqdict[DfNameParam]))
{
try
{
Validations.ValidMatrixName(reqdict[DfNameParam], throwOnBadName: true);
reqdict[DfDelimParam] = _utils.FixLiterals(reqdict[DfDelimParam]);
reqdict[DfNewLineParam] = _utils.FixLiterals(reqdict[DfNewLineParam]);
reqdict[DfValsParam] = _utils.FixLiterals(reqdict[DfValsParam]);
List <string> optlist = _utils.GetOptionList(reqdict);
using Dataframe df = new Dataframe
(
_utils.StringTo2DList
(
reqdict[DfValsParam],
reqdict[DfDelimParam],
reqdict[DfNewLineParam],
true,
(int)DataframeLimits.forRows,
(int)DataframeLimits.forCols,
true,
optlist
),
optlist
);
_frontService.AddToDfDict
(
reqdict[DfNameParam],
df,
_dict
);
Dictionary <string, List <List <object> > > vals = HttpContext.Session.GetMatVals(SessionDfDict, true);
Dictionary <string, Dictionary <string, dynamic> > settings = HttpContext.Session.GetDfSettings(SessionDfSettings);
Dictionary <string, Dictionary <string, List <LabelList> > > labels = HttpContext.Session.GetDfLabels(SessionDfLabels);
_frontService.SetDfDicts(_dict, vals, labels, settings);
HttpContext.Session.Set(SessionDfDict, vals);
HttpContext.Session.SetDfLabels(SessionDfLabels, labels);
HttpContext.Session.SetDfSettings(SessionDfSettings, settings);
using CommandMessage msg = new CommandMessage(CompilerMessage.SAVED_DF(reqdict[DfNameParam]), CommandState.SUCCESS);
HttpContext.Session.SetLastMsg(
SessionLastMessage,
msg
);
_utils.DisposeDfDicts(null, labels);
vals.Clear();
labels.Clear();
settings.Clear();
}
catch (Exception err)
{
using CommandMessage msg = err.InnerException != null
? new CommandMessage(err.InnerException.Message, CommandState.ERROR)
: new CommandMessage(err.Message, CommandState.ERROR);
HttpContext.Session.SetLastMsg(
SessionLastMessage,
msg
);
}
}
else
{
using CommandMessage msg = new CommandMessage(CompilerMessage.DF_NAME_ALREADY_EXISTS(reqdict[DfNameParam]), CommandState.WARNING);
HttpContext.Session.SetLastMsg(
SessionLastMessage,
msg
);
}
}
else
{
using CommandMessage msg = new CommandMessage(CompilerMessage.MAT_NAME_ALREADY_EXISTS(reqdict[DfNameParam]), CommandState.WARNING);
HttpContext.Session.SetLastMsg(
SessionLastMessage,
msg
);
}
_utils.DisposeDfDicts(_dict, null);
_dict.Clear();
}
else
{
using CommandMessage msg = new CommandMessage(RequestMessage.REQUEST_MISSING_KEYS("AddDataframe", new string[2] { DfNameParam, DfValsParam }), CommandState.ERROR);
HttpContext.Session.SetLastMsg(
SessionLastMessage,
msg
);
}
HttpContext.Session.Set(SessionLastCommandDate, LastCmdDate);
}
else
{
using CommandMessage msg = new CommandMessage(RequestMessage.REQUEST_SPAM(HttpContext.Session.Get <DateTime>(SessionLastCommandDate)), CommandState.WARNING);
HttpContext.Session.SetLastMsg(
SessionLastMessage,
msg
);
}
}
private void button3_Click(object sender, EventArgs e)
{
dataframe = new Dataframe();
dataframe.makeRandomData(9, 500);
}
public MatrisBase <object> PseudoInverse(MatrisBase <object> A,
int side = -1)
{
if (Rank(A) != Math.Min(A.Row, A.Col))
{
throw new Exception(CompilerMessage.MAT_PSEINV_NOT_FULL_RANK);
}
if (side != -1 && side != 1)
{
throw new Exception(CompilerMessage.MAT_PSEINV_BAD_SIDE);
}
CompilerUtils.AssertMatrixValsAreNumbers(A);
string sidename = side == -1 ? "sol" : "sağ";
// Left inverse
if (side == -1)
{
try
{
return(A is Dataframe df
? new Dataframe(MatrisMul(Inverse(MatrisMul(Conjugate(A), A)), Conjugate(A)).GetValues(),
df.Delimiter,
df.NewLine,
Dataframe.GetCopyOfLabels(df.GetRowLabels()),
Dataframe.GetCopyOfLabels(df.GetColLabels()),
df.GetRowSettings().Copy(),
df.GetColSettings().Copy())
: MatrisMul(Inverse(MatrisMul(Conjugate(A), A)), Conjugate(A)));
}
catch (Exception err)
{
if (err.Message == CompilerMessage.MAT_DET_ZERO_NO_INV)
{
throw new Exception(CompilerMessage.MAT_PSEINV_DET_ZERO(sidename));
}
throw new Exception("Genelleştirilmiş ters matris hatası:\n", err);
}
}
else // Right inverse
{
try
{
return(A is Dataframe df
? new Dataframe(MatrisMul(Conjugate(A), Inverse(MatrisMul(A, Conjugate(A)))).GetValues(),
df.Delimiter,
df.NewLine,
Dataframe.GetCopyOfLabels(df.GetRowLabels()),
Dataframe.GetCopyOfLabels(df.GetColLabels()),
df.GetRowSettings().Copy(),
df.GetColSettings().Copy())
: MatrisMul(Conjugate(A), Inverse(MatrisMul(A, Conjugate(A)))));
}
catch (Exception err)
{
if (err.Message == CompilerMessage.MAT_DET_ZERO_NO_INV)
{
throw new Exception(CompilerMessage.MAT_PSEINV_DET_ZERO(sidename));
}
throw new Exception("Genelleştirilmiş ters matris hatası:\n", err);
}
}
}
public MatrisBase <object> Mode(MatrisBase <object> df,
int numberOnly = 1)
{
if (!df.IsValid())
{
throw new Exception(CompilerMessage.DF_INVALID_SIZE);
}
int nc = df.Col;
List <object> modes = new List <object>();
for (int j = 0; j < nc; j++)
{
List <object> col = df.ColList(j, 0);
Dictionary <object, int> tracker = new Dictionary <object, int>();
foreach (object val in col)
{
if (tracker.ContainsKey(val))
{
tracker[val]++;
}
else
{
tracker.Add(val, 1);
}
}
object mode = null;
object placeholder = new None();
placeholder = (df is Dataframe ? placeholder : float.NaN);
int currentmax = 0;
foreach (KeyValuePair <object, int> pair in tracker)
{
if (numberOnly == 1 && (pair.Key is None ||
pair.Key is null ||
((!float.TryParse(pair.Value.ToString(), out float res) ||
float.IsNaN(res)))))
{
continue;
}
if (pair.Value > currentmax)
{
currentmax = pair.Value;
mode = pair.Key;
}
}
modes.Add(mode ?? placeholder);
}
return(df is Dataframe dataframe
? new Dataframe(new List <List <object> >()
{
modes
},
dataframe.Delimiter,
dataframe.NewLine,
null,
Dataframe.GetCopyOfLabels(dataframe.GetColLabels()),
null,
dataframe.GetColSettings().Copy())
: new MatrisBase <object>(new List <List <object> >()
{
modes
}));
}
public MatrisBase <object> Median(MatrisBase <object> df,
int numberOnly = 1)
{
if (!df.IsValid())
{
throw new Exception(CompilerMessage.DF_INVALID_SIZE);
}
int pop;
int nr = df.Row;
int nc = df.Col;
List <object> meds = new List <object>();
if (df is Dataframe dataframe)
{
for (int j = 0; j < nc; j++)
{
if (!dataframe.IsAllNumberColumn(j, 0))
{
if (numberOnly == 1)
{
List <object> col = new List <object>();
foreach (object o in dataframe.ColList(j, 0))
{
if (o is None ||
o is null ||
((!float.TryParse(o.ToString(), out float res) ||
float.IsNaN(res))))
{
continue;
}
col.Add(o);
}
if (col.Count == 0)
{
meds.Add(float.NaN);
continue;
}
pop = nr - df.AmountOfNanInColumn(j);
col.Sort();
meds.Add((pop % 2 == 1)
? (float)col[((pop + 1) / 2) - 1]
: ((float)col[(pop / 2) - 1] + (float)col[(int)Math.Round((decimal)(pop + 1) / 2, 0) - 1]) / 2);
}
else
{
meds.Add(float.NaN);
}
}
else
{
List <object> col = dataframe.ColList(j, 0);
col.Sort();
meds.Add((nr % 2 == 1)
? (float)col[((nr + 1) / 2) - 1]
: ((float)col[(nr / 2) - 1] + (float)col[(int)Math.Round((decimal)(nr + 1) / 2, 0) - 1]) / 2);
}
}
return(new Dataframe(new List <List <object> >()
{
meds
},
dataframe.Delimiter,
dataframe.NewLine,
null,
Dataframe.GetCopyOfLabels(dataframe.GetColLabels()),
null,
dataframe.GetColSettings().Copy()));
}
else
{
for (int j = 0; j < nc; j++)
{
if (numberOnly == 1)
{
List <object> col = new List <object>();
foreach (object o in df.ColList(j, 0))
{
if (o is None ||
o is null ||
((!float.TryParse(o.ToString(), out float res) ||
float.IsNaN(res))))
{
continue;
}
col.Add(o);
}
if (col.Count == 0)
{
meds.Add(float.NaN);
continue;
}
pop = nr - df.AmountOfNanInColumn(j);
col.Sort();
meds.Add((pop % 2 == 1)
? (float)col[((pop + 1) / 2) - 1]
: ((float)col[(pop / 2) - 1] + (float)col[(int)Math.Round((decimal)(pop + 1) / 2, 0) - 1]) / 2);
}
else
{
List <object> col = df.ColList(j, 0);
col.Sort();
meds.Add((nr % 2 == 1)
? (float)col[((nr + 1) / 2) - 1]
: (float)col[(nr / 2) - 1] + (float)col[(int)Math.Round((decimal)(nr + 1) / 2, 0) - 1]);
}
}
return(new MatrisBase <object>(new List <List <object> >()
{
meds
}));
}
}
public MatrisBase <object> SDev(MatrisBase <object> df,
int usePopulation = 0,
int numberOnly = 1)
{
if (!df.IsValid())
{
throw new Exception(CompilerMessage.DF_INVALID_SIZE);
}
if (usePopulation != 0 && usePopulation != 1)
{
throw new Exception(CompilerMessage.ARG_INVALID_VALUE("usePopulation", "Örneklem için 0, popülasyon için 1 olmalı!"));
}
int nr = df.Row;
int nc = df.Col;
if (nr == 1 && usePopulation == 1)
{
usePopulation = 0;
}
List <object> means = Mean(df).RowList(1);
List <object> sdevs = new List <object>();
List <List <object> > vals = df.GetValues();
int pop;
for (int j = 0; j < nc; j++)
{
float sdev = 0;
float mean = (float)means[j];
if (float.IsNaN(mean))
{
if (numberOnly == 1)
{
sdevs.Add(0);
}
else
{
sdevs.Add(float.NaN);
}
continue;
}
for (int i = 0; i < nr; i++)
{
if (float.TryParse(vals[i][j].ToString(), out float res))
{
if (numberOnly == 1 && float.IsNaN(res))
{
continue;
}
sdev += (float)Math.Pow(res - mean, 2);
}
else
{
if (numberOnly == 1)
{
continue;
}
else
{
sdev = float.NaN;
break;
}
}
}
pop = nr - usePopulation - (numberOnly == 1 ? df.AmountOfNanInColumn(j) : 0);
if (pop == 0)
{
sdevs.Add(0);
}
else
{
sdevs.Add((float)Math.Pow(sdev * (1.0 / pop), 0.5));
}
}
return(df is Dataframe data
? new Dataframe(new List <List <object> >()
{
sdevs
},
data.Delimiter,
data.NewLine,
null,
Dataframe.GetCopyOfLabels(data.GetColLabels()),
null,
data.GetColSettings().Copy())
: new MatrisBase <object>(new List <List <object> >()
{
sdevs
}));
}
public MatrisBase <object> Shuffle(MatrisBase <object> A,
int axis = 2)
{
if (!A.IsValid())
{
throw new Exception(CompilerMessage.MAT_INVALID_SIZE);
}
int m = A.Row;
int n = A.Col;
if (m == 1 && n == 1)
{
return(A is Dataframe ? ((Dataframe)A.Copy()) : A.Copy());
}
if (axis == 0)
{
if (m == 1)
{
return(A is Dataframe ? ((Dataframe)A.Copy()) : A.Copy());
}
List <int> indices = new List <int>();
for (int c = 0; c < m; c++)
{
indices.Add(c);
}
indices = indices.OrderBy(x => Guid.NewGuid()).ToList();
List <List <object> > newvals = new List <List <object> >();
List <List <object> > vals = A.GetValues();
int i = 0;
foreach (int k in indices)
{
newvals.Add(new List <object>());
for (int j = 0; j < n; j++)
{
newvals[i].Add(vals[k][j]);
}
i++;
}
return(A is Dataframe data
? new Dataframe(newvals,
data.Delimiter,
data.NewLine,
null,
Dataframe.GetCopyOfLabels(data.GetColLabels()),
null,
data.GetColSettings().Copy(),
true)
: new MatrisBase <object>(newvals));
}
else if (axis == 1)
{
if (n == 1)
{
return(A is Dataframe ? ((Dataframe)A.Copy()) : A.Copy());
}
List <int> indices = new List <int>();
for (int c = 0; c < n; c++)
{
indices.Add(c);
}
indices = indices.OrderBy(x => Guid.NewGuid()).ToList();
List <List <object> > newvals = new List <List <object> >();
List <List <object> > vals = A.GetValues();
for (int i = 0; i < m; i++)
{
newvals.Add(new List <object>());
foreach (int k in indices)
{
newvals[i].Add(vals[i][k]);
}
}
return(A is Dataframe data
? new Dataframe(newvals,
data.Delimiter,
data.NewLine,
Dataframe.GetCopyOfLabels(data.GetRowLabels()),
null,
data.GetRowSettings().Copy(),
null,
true)
: new MatrisBase <object>(newvals));
}
else if (axis == 2)
{
if (m == 1)
{
return(Shuffle(A, 1));
}
else if (n == 1)
{
return(Shuffle(A, 0));
}
List <int> indices = new List <int>();
for (int k = 0; k < n * m; k++)
{
indices.Add(k);
}
indices = indices.OrderBy(x => Guid.NewGuid()).ToList();
List <List <object> > newvals = new List <List <object> >();
List <List <object> > vals = A.GetValues();
int c = 0;
int r = -1;
foreach (int k in indices)
{
if (c % n == 0)
{
newvals.Add(new List <object>());
r++;
}
newvals[r].Add(vals[k / n][k % n]);
c++;
}
return(A is Dataframe data
? new Dataframe(newvals,
data.Delimiter,
data.NewLine,
forceLabelsWhenNull: true)
: new MatrisBase <object>(newvals));
}
else
{
throw new Exception(CompilerMessage.ARG_INVALID_VALUE("axis", "Satır: 0, Sütun: 1, Rastgele:2 olmalı"));
}
}
public MatrisBase <object> Describe(MatrisBase <object> df,
int usePopulation = 0,
int numberOnly = 1)
{
if (!df.IsValid())
{
throw new Exception(CompilerMessage.DF_INVALID_SIZE);
}
List <object> mins = ArrayMethods.CopyList <float>(Min(df, numberOnly)[0]);
List <object> meds = ArrayMethods.CopyList <float>(Median(df, numberOnly)[0]);
List <object> maxs = ArrayMethods.CopyList <float>(Max(df, numberOnly)[0]);
List <object> mods = ArrayMethods.CopyList <float>(Mode(df, numberOnly)[0]);
List <object> meas = ArrayMethods.CopyList <float>(Mean(df, numberOnly)[0]);
List <object> sdev = ArrayMethods.CopyList <float>(SDev(df, usePopulation, numberOnly)[0]);
List <object> vars = ArrayMethods.CopyList <float>(Var(df, usePopulation, numberOnly)[0]);
int nc = df.Col;
List <List <object> > desc = new List <List <object> >();
for (int j = 0; j < nc; j++)
{
desc.Add(new List <object>()
{
mins[j],
meds[j],
maxs[j],
mods[j],
meas[j],
sdev[j],
vars[j]
}
);
}
mins.Clear();
meds.Clear();
maxs.Clear();
mods.Clear();
meas.Clear();
sdev.Clear();
vars.Clear();
List <LabelList> newcollabels = CompilerUtils.Create1DLabelListFromList("Min", "Median", "Max", "Mode", "Mean", "Sdev", "Var");
return(df is Dataframe dataframe
? new Dataframe(desc,
dataframe.Delimiter,
dataframe.NewLine,
Dataframe.GetCopyOfLabels(dataframe.GetColLabels()) ?? new List <LabelList>()
{
new LabelList(df.Col, 1, "col_", 1)
},
newcollabels,
dataframe.GetRowSettings().Copy(),
dataframe.GetColSettings().Copy(),
true
)
: new Dataframe(desc,
rowLabels: new List <LabelList>()
{
new LabelList(df.Col, 1, "col_", 1)
},
colLabels: newcollabels
));
}
