public SingleAxisShearStationSummary(
ISessionColumnCollection collection,
DataView data,
double wdbin,
double wdrosebin,
double wsbin,
ShearCalculationGridCollection gridcollection
)
{
_ef = new ExcelFile();
_ef.LimitNear += new LimitEventHandler(_ef_LimitNear);
//original data
SessionColumnType sheartype = SessionColumnType.WSAvgSingleAxisShear;
_hourShearWksht = new HourShearWorkSheet(gridcollection, _ef);
_monthHourWorksht = new WindSpeedFrequencyMonthHourWorkSheet(collection, data.Table, _ef, sheartype);
_wSWDworkSht = new WindSpeedFrequencyWDWSWorkSheet(collection, data, wdbin, wsbin, _ef, sheartype);
_wroseWksht = new WindRoseWorkSheet(collection, data, wdrosebin, _ef, sheartype);
//datarecovery worksheet
//built in order they will appear in work book
_hourShearWksht.BuildWorkSheet();
_monthHourWorksht.BuildWorkSheet();
_wSWDworkSht.BuildWorkSheet();
_wroseWksht.BuildWorkSheet();
}
public XbyYShearStationSummary(
ISessionColumnCollection collection,
DataView data,
double wdbin,
double wdrosebin,
double wsbin,
ShearCalculationGridCollection gridcollection,
List <StationSummarySheetType> whatToRun
)
{
_collection = collection;
_data = data;
_wdbin = wdbin;
_wdrosebin = wdrosebin;
_wsbin = wsbin;
_gridcollection = gridcollection;
_ef = new ExcelFile();
_ef.LimitNear += new LimitEventHandler(_ef_LimitNear);
foreach (StationSummarySheetType s in whatToRun)
{
try
{
RunReports[s].Invoke();
}
catch
{
}
}
}
public XbyYShearStationSummary(
ISessionColumnCollection collection,
DataView data,
double wdbin,
double wdrosebin,
double wsbin,
ShearCalculationGridCollection gridcollection
)
{
_collection = collection;
_data = data;
_wdbin = wdbin;
_wdrosebin = wdrosebin;
_wsbin = wsbin;
_gridcollection = gridcollection;
_ef = new ExcelFile();
_ef.LimitNear += new LimitEventHandler(_ef_LimitNear);
//original data
_shearWksht = new MonthbyHourShearWorkSheet(gridcollection, _ef);
_monthHourWorksht = new WindSpeedFrequencyMonthHourWorkSheet(collection, data.Table, _ef, SessionColumnType.WSAvgShear);
_wSWDworkSht = new WindSpeedFrequencyWDWSWorkSheet(collection, data, wdbin, wsbin, _ef, SessionColumnType.WSAvgShear);
_wroseWksht = new WindRoseWorkSheet(collection, data, wdrosebin, _ef, SessionColumnType.WSAvgShear);
_dataRecoveryWksht = new DataRecoveryWorksheet(_ef, collection, data.Table);
//built in order they will appear in work book
_shearWksht.BuildWorkSheet();
_monthHourWorksht.BuildWorkSheet();
_wSWDworkSht.BuildWorkSheet();
_wroseWksht.BuildWorkSheet();
_dataRecoveryWksht.BuildWorkSheet();
}
public HourShearWorkSheet(ShearCalculationGridCollection gridcollection, ExcelFile ef)
{
//prepare the grids
_ef = ef;
_upperAvgGrid = new Grid(new Create1byYGrid(new HourAxis(), gridcollection.UpperAvg));
_lowerAvgGrid = new Grid(new Create1byYGrid(new HourAxis(), gridcollection.LowerAvg));
_alphaGrid = new Grid(new Create1byYGrid(new HourAxis(), gridcollection.Alpha));
}
public bool CalculateWindSpeed(double shearht, out ShearCalculationGridCollection gridcollection)
{
try
{
//make sure there are axis vals set
if (_xaxis == null || _yaxis == null)
{
Console.WriteLine(" shear not calculated because no axes were provided");
gridcollection = null;
return(false);
}
//Console.WriteLine(" x axis " + _xaxis.AxisValues.Length + " y axis " + _yaxis.AxisValues.Length);
HourAxis hourAxis = null;
MonthAxis monthAxis = null;
WindDirectionAxis wdAxis = null;
//add axes to a list for easier parsing
List <IAxis> AssignedAxis = new List <IAxis>();
AssignedAxis.Add(_xaxis);
AssignedAxis.Add(_yaxis);
bool useWD = false;
foreach (IAxis a in AssignedAxis)
{
switch (a.AxisType)
{
case AxisType.Hour:
hourAxis = (HourAxis)a;
break;
case AxisType.Month:
monthAxis = (MonthAxis)a;
break;
case AxisType.WD:
wdAxis = (WindDirectionAxis)a;
useWD = true;
throw new NotImplementedException("shear by WD not yet developed");
default:
break;
}
}
// Console.WriteLine("assigned axis types");
_data.Sort = Settings.Default.TimeStampName;
DateTime t = DateTime.Now;
double missing = Settings.Default.MissingValue;
//get a date at the beginning of the dataset provided
DateTime start = DateTime.Parse(_data[2][_collection.DateIndex].ToString());
//get a list of the columns for this config sorted ascending by height
SortedDictionary <double, ISessionColumn> orderedWsCols
= _collection.GetColumnsByType(SessionColumnType.WSAvg, start, true);
if (orderedWsCols.Count == 0)
{
throw new ApplicationException("No WS Composite columns were found in MonthHourShear class. Config boundary dates may have been passed incorrectly");
}
//sort columns descending by height
orderedWsCols.Reverse();
//put the column indexes into a list for coincident values constructor
SortedDictionary <double, int> TopCols = new SortedDictionary <double, int>();
foreach (KeyValuePair <double, ISessionColumn> kv in orderedWsCols)
{
//Console.WriteLine("passed to getrows as ws idx:" + kv.Value.ColName);
TopCols.Add(kv.Key, _collection[kv.Value.ColName].ColIndex);
}
List <double> SensorHts = TopCols.Keys.ToList();
SensorHts.Sort();
//Console.WriteLine("first row after sort " + _data[1][0] + " " + _[SensorHts [1]] + " " + _data[1][SensorHts[0]]);
//pass the column list and the dataview to get only coincident rows for the columns passed
XbyYShearCoincidentRowCollection coincident
= new XbyYShearCoincidentRowCollection(_collection.DateIndex, TopCols, _data);
int wdColIndex = 0;
List <XbyYCoincidentRow> coincidentValues = new List <XbyYCoincidentRow>();
if (_collection["WDAvgComposite"] != null)
{
wdColIndex = _collection["WDAvgComposite"].ColIndex;
//Console.WriteLine("Shear.CalculateWS:wd comp index=" + wdColIndex );
coincidentValues = coincident.GetRows(wdColIndex);
//Console.WriteLine("coincident rows count " + coincidentValues.Count);
}
else
{
coincidentValues = coincident.GetRows(1);
}
//collection to hold averages at each x y point
gridcollection = new ShearCalculationGridCollection();
//get number of elements in each axis
int hour = 0;
int month = 0;
int x = _xaxis.AxisValues.Length;
int y = _yaxis.AxisValues.Length;
// Console.WriteLine("assigned axis lengths " + x + ", " + y);
if (AxisLengthsDetermined != null)
{
AxisLengthsDetermined("Assigned Alpha Grid Axis lengths " + x + " by " + y);
}
//arrays to hold upper and lower avgs at each x,y point
double[,] UpperAvgGrid = new double[x, y];
double[,] LowerAvgGrid = new double[x, y];
//list to hold avg values for each sensor grid at each x and y bin
List <double> upperWsVals = new List <double>();
List <double> lowerWSVals = new List <double>();
for (int a = 0; a < x; a++)
{
for (int j = 0; j < y; j++)
{
int TestCount = 0;
if (useWD)
{
}
else
{
if (_xaxis.AxisType == AxisType.Hour)
{
hour = a; month = j;
}
else
{
hour = j; month = a;
}
hour = (int)hourAxis.AxisValues[hour];
month = (int)monthAxis.AxisValues[month];
//Console.WriteLine("hour " + hour + ", Month " + month);
//find the row collection for this x,y point
var r = from s in coincidentValues.AsEnumerable()
where s.Date.Month == month && s.Date.Hour == hour &&
s.WD >= 0
select s;
//Console.WriteLine(month + " " + hour + " value: " + r.Count());
double useUpperWSVal;
double useLowerWSVal;
foreach (var row in r)
{
//if (month == 11)
//{
// Console.WriteLine("date " + row.Date + " upper ws " + (double)row.UpperWS);
//}
if (Double.TryParse(row.UpperWS.ToString(), out useUpperWSVal) &&
Double.TryParse(row.LowerWS.ToString(), out useLowerWSVal))
{
upperWsVals.Add(useUpperWSVal);
lowerWSVals.Add(useLowerWSVal);
}
TestCount++;
}
}
//Console.WriteLine("upper count at " + month + ", " + hour + ": " + TestCount);
//add each collection avg to the avg grids
//Console.WriteLine("lower average at " + month + ", " + hour + ": " + lowerWSVals.Average() + "/n");
if (upperWsVals.Count > 0 && lowerWSVals.Count > 0)
{
UpperAvgGrid[a, j] = upperWsVals.Average();
// Console.WriteLine( a + " by " + j + " " + upperWsVals.Count);
LowerAvgGrid[a, j] = lowerWSVals.Average();
}
else
{
UpperAvgGrid[a, j] = 0;
LowerAvgGrid[a, j] = 0;
}
upperWsVals.Clear();
lowerWSVals.Clear();
//Console.WriteLine("Upper average at " + a + ", " + hour + " "+ UpperAvgGrid[a, j]);
//Console.WriteLine("Lower average at " + month + ", " + hour + " " + LowerAvgGrid[a, j]);
}
}
gridcollection.LowerAvg = LowerAvgGrid;
gridcollection.UpperAvg = UpperAvgGrid;
//calculate each alpha value and assign to a single grid
double[,] alphaGrid = new double[x, y];
//fill alpha table
for (int a = 0; a < x; a++)
{
for (int j = 0; j < y; j++)
{
//Console.WriteLine(" x=" + a.ToString() + " y=" + j.ToString());
alphaGrid[a, j] = Math.Log(gridcollection.UpperAvg [a, j] / gridcollection.LowerAvg [a, j])
/ Math.Log(SensorHts[1] / SensorHts[0]);
//Console.WriteLine("Alpha in grid=" + alphaGrid[a, j].ToString() +
// " upper ws =" + gridcollection.UpperAvg[a, j].ToString() +
// " Lower ws =" + gridcollection.LowerAvg[a, j].ToString() +
// " upper ht " + SensorHts[1] + " lower ht " + SensorHts[0] +
// " month=" + monthAxis.AxisValues[a] + " hour=" + hourAxis.AxisValues[j]);
if (Double.IsNaN(alphaGrid[a, j]))
{
alphaGrid[a, j] = 0;
}
}
}
gridcollection.Alpha = alphaGrid;
//create a single multi-d array from the original dictionary of values
//values must stay in order
List <int> CombineCols = TopCols.Values.ToList();
//height and value of the valid ws comp at each row ordered by datetime
double[,] result = CombineSensorVals(CombineCols);
//Console.WriteLine("Rows in full data " + _data.Count + " rows in combined dataset " + result.GetLength (1));
//array to store sheared ws
List <double> ShearResult = new List <double>(result.GetLength(1));
//add colummn to dataset and capture colindex
string localcolname = shearht.ToString();
localcolname += Enum.GetName(typeof(SessionColumnType), SessionColumnType.WSAvgShear);
localcolname += x + "by" + y;
//Console.WriteLine("X by Y shear column will be named " + localcolname);
int shearIndex = AddShearColumnToTable(localcolname, shearht);
int alphaIndex = AddAlphaColumn("Alpha");
double thisAlpha;
int xVal;
int yVal;
DateTime thisDate;
double thisWD;
if (AddingShearValues != null)
{
AddingShearValues("Calculating " + shearht + "m Sheared Windspeed");
}
//loop combined values
for (int i = 0; i < result.GetLength(1); i++)
{
thisDate = (DateTime)_data[i][_collection.DateIndex];
if (useWD)
{
thisWD = (double)_data[i][wdColIndex];
}
else
{
xVal = monthAxis.ReturnAxisValue(thisDate);
yVal = hourAxis.ReturnAxisValue(thisDate);
thisAlpha = gridcollection.Alpha [xVal, yVal];
_data[i][alphaIndex] = thisAlpha;
if (result[1, i] >= 0)
{
_data[i][shearIndex] = (result[1, i] * Math.Pow((shearht / result[0, i]), thisAlpha));
}
else
{
_data[i][shearIndex] = missing;
}
}
}
_data.Table.AcceptChanges();
DateTime t_end = DateTime.Now;
TimeSpan dur = t_end - t;
//Console.WriteLine("Calculating and adding " + x + " by " + y + " shear ws takes " + dur);
if (AddedShearValues != null)
{
AddedShearValues("Shear Calculation Complete");
}
return(true);
}
catch (Exception e)
{
throw e;
}
}
public bool CalculateWindSpeed(double shearht, out ShearCalculationGridCollection grid)
{
//there is nothing here that guarantees that the view does not span multple configs
//but assumes that it does not
try
{
_data.Sort = Settings.Default.TimeStampName;
DateTime t = DateTime.Now;
double missing = Settings.Default.MissingValue;
//get a date at the beginning of the dataset provided
DateTime start = DateTime.Parse(_data[0][_collection.DateIndex].ToString());
//get a list of the columns for this config sorted ascending by height
SortedDictionary <double, ISessionColumn> orderedWsCols
= _collection.GetColumnsByType(SessionColumnType.WSAvg, start, true);
//sort columns descending by height
orderedWsCols.Reverse();
List <ISessionColumn> workCols = orderedWsCols.Values.ToList();
//put the column indexes into a list for coincident values constructor
List <int> TopCols = new List <int>();
foreach (KeyValuePair <double, ISessionColumn> kv in orderedWsCols)
{
Console.WriteLine("col name " + kv.Value.ColName);
TopCols.Add(kv.Value.ColIndex);
}
Console.WriteLine("first row after sort " + _data[0][0] + " " + _data[0][TopCols[0]] + " " + _data[0][TopCols[1]]);
//pass the column list and the dataview to get the coincident values of the columns
ICoincidentValues coincident = new CoincidentValues(TopCols, _data);
//take the average of the each of the lists of values
//add the average to a dictionary indexed by the column index
Dictionary <int, List <double> > coincidentValues = coincident.GetValues();
Dictionary <int, double> avgvals = new Dictionary <int, double>();
foreach (KeyValuePair <int, List <double> > kv in coincidentValues)
{
avgvals.Add(kv.Key, kv.Value.Average());
Console.WriteLine(_collection[kv.Key].ColName + " " + kv.Value.Count);
double ht = _collection[kv.Key].getConfigAtDate(start).Height;
}
Console.WriteLine("upper avg " + avgvals[TopCols[1]] + " lower avg " + avgvals[TopCols[0]]);
Console.WriteLine("upper ht " + orderedWsCols.Keys.ToList()[1] + " lower ht " + orderedWsCols.Keys.ToList()[0]);
//calculate alpha
Console.WriteLine(" num " + Math.Log(avgvals[TopCols[1]] / avgvals[TopCols[0]]));
Console.WriteLine(" den " + Math.Log(orderedWsCols.Keys.ToList()[1] / orderedWsCols.Keys.ToList()[0]));
double alpha = Math.Log(avgvals[TopCols[1]] / avgvals[TopCols[0]])
/ Math.Log(orderedWsCols.Keys.ToList()[1] / orderedWsCols.Keys.ToList()[0]);
Console.WriteLine("alpha=" + alpha.ToString());
//create a single multi-d array from the original dictionary of values
//values must stay in order
double[,] result = CombineSensorVals(TopCols);
List <double> ShearResult = new List <double>(result.GetLength(1));
//add colummn to dataset
string localcolname = shearht.ToString();
localcolname += Enum.GetName(typeof(SessionColumnType), SessionColumnType.WSAvgBulkShear);
Console.WriteLine("composite col will be named " + localcolname);
int shearIndex = AddBulkShearToTable(localcolname, shearht);
//apply bulk shear alpha to create sheared array values
for (int i = 0; i < result.GetLength(1); i++)
{
if (result[1, i] >= 0)
{
_data[i][shearIndex] = (result[1, i] * Math.Pow((shearht / result[0, i]), alpha));
}
else
{
_data[i][shearIndex] = missing;
}
}
_data.Table.AcceptChanges();
DateTime t_end = DateTime.Now;
TimeSpan dur = t_end - t;
Console.WriteLine("Calculating and adding bulk shear ws takes " + dur);
grid = null;
return(true);
}
catch (Exception e)
{
throw e;
}
}
public bool CalculateWindSpeed(double shearht, out ShearCalculationGridCollection gridcollection)
{
//make sure there are axis vals set
if (_xaxis == null)
{
Console.WriteLine(" shear not calculated because no axis was provided");
gridcollection = null;
return(false);
}
Console.WriteLine(" x axis " + _xaxis.AxisValues.Length);
HourAxis hourAxis = (HourAxis)_xaxis;
_data.Sort = Settings.Default.TimeStampName;
DateTime t = DateTime.Now;
double missing = Settings.Default.MissingValue;
//get a date at the beginning of the dataset provided
DateTime start = DateTime.Parse(_data[2][_collection.DateIndex].ToString());
//get a list of the columns for this config sorted ascending by height
SortedDictionary <double, ISessionColumn> orderedWsCols
= _collection.GetColumnsByType(SessionColumnType.WSAvg, start, true);
//sort columns descending by height
orderedWsCols.Reverse();
//put the column indexes into a list for coincident values constructor
SortedDictionary <double, int> TopCols = new SortedDictionary <double, int>();
foreach (KeyValuePair <double, ISessionColumn> kv in orderedWsCols)
{
TopCols.Add(kv.Key, kv.Value.ColIndex);
}
List <double> SensorHts = TopCols.Keys.ToList();
SensorHts.Sort();
//pass the column list and the dataview to get only coincident rows for the columns passed
XbyYShearCoincidentRowCollection coincident
= new XbyYShearCoincidentRowCollection(_collection.DateIndex, TopCols, _data);
int wdColIndex = _collection["WDAvgComposite"].ColIndex;
Console.WriteLine("wd comp index=" + wdColIndex);
List <XbyYCoincidentRow> coincidentValues = coincident.GetRows(wdColIndex);
Console.WriteLine("coincident rows count " + coincidentValues.Count);
//collection to hold averages at each x y point
gridcollection = new ShearCalculationGridCollection();
//get number of elements in each axis
int hour = 0;
int x = _xaxis.AxisValues.Length;
Console.WriteLine("assigned axis length 1 by " + x);
//arrays to hold upper and lower avgs at each x,y point
double[,] UpperAvgGrid = new double[1, x];
double[,] LowerAvgGrid = new double[1, x];
//list to hold avg values for each sensor grid at each x and y bin
List <double> upperWsVals = new List <double>();
List <double> lowerWSVals = new List <double>();
//only 1 element because this is a 1 by x shear
for (int a = 0; a < 1; a++)
{
for (int j = 0; j < x; j++)
{
int TestCount = 0;
//Console.WriteLine(" a " + a + " j " + j);
hour = (int)hourAxis.AxisValues[j];
//find the row collection for this x,y point
var r = from s in coincidentValues.AsEnumerable()
where s.Date.Hour == hour &&
s.WD >= 0
select s;
//Console.WriteLine(month + " " + hour + " value: " + r.Count());
double useUpperWSVal;
double useLowerWSVal;
foreach (var row in r)
{
if (Double.TryParse(row.UpperWS.ToString(), out useUpperWSVal) &&
Double.TryParse(row.LowerWS.ToString(), out useLowerWSVal))
{
upperWsVals.Add(useUpperWSVal);
lowerWSVals.Add(useLowerWSVal);
}
TestCount++;
}
if (upperWsVals.Count > 0 && lowerWSVals.Count > 0)
{
UpperAvgGrid[a, j] = upperWsVals.Average();
LowerAvgGrid[a, j] = lowerWSVals.Average();
}
else
{
UpperAvgGrid[a, j] = 0;
LowerAvgGrid[a, j] = 0;
}
upperWsVals.Clear();
lowerWSVals.Clear();
}
}
gridcollection.LowerAvg = LowerAvgGrid;
gridcollection.UpperAvg = UpperAvgGrid;
//calculate each alpha value and assign to a single grid
double[,] alphaGrid = new double[1, x];
//fill alpha table
for (int a = 0; a < 1; a++)
{
for (int j = 0; j < x; j++)
{
//Console.WriteLine(" x=" + a.ToString() + " y=" + j.ToString());
alphaGrid[a, j] = Math.Log(gridcollection.UpperAvg[a, j] / gridcollection.LowerAvg[a, j])
/ Math.Log(SensorHts[1] / SensorHts[0]);
//Console.WriteLine("Alpha in grid=" + alphaGrid[a, j].ToString() +
// " upper ws =" + gridcollection.UpperAvg[a, j].ToString() +
// " Lower ws =" + gridcollection.LowerAvg[a, j].ToString() +
// " upper ht " + SensorHts[1] + " lower ht " + SensorHts[0] +
// " month=" + monthAxis.AxisValues[a] + " hour=" + hourAxis.AxisValues[j]);
}
}
gridcollection.Alpha = alphaGrid;
//create a single multi-d array from the original dictionary of values
//values must stay in order
List <int> CombineCols = TopCols.Values.ToList();
//height and value of the valid ws comp at each row ordered by datetime
double[,] result = CombineSensorVals(CombineCols);
Console.WriteLine("Rows in full data " + _data.Count + " rows in combined dataset " + result.GetLength(1));
//array to store sheared ws
List <double> ShearResult = new List <double>(result.GetLength(1));
//add colummn to dataset and capture colindex
string localcolname = shearht.ToString();
localcolname += Enum.GetName(typeof(SessionColumnType), SessionColumnType.WSAvgSingleAxisShear);
localcolname += "1" + "by" + x;
Console.WriteLine("X by Y shear column will be named " + localcolname);
int shearIndex = AddShearColumnToTable(localcolname, shearht);
double thisAlpha;
int yVal;
DateTime thisDate;
//loop combined values
for (int i = 0; i < result.GetLength(1); i++)
{
thisDate = (DateTime)_data[i][_collection.DateIndex];
yVal = hourAxis.ReturnAxisValue(thisDate);
thisAlpha = gridcollection.Alpha[0, yVal];
if (result[0, i] > 0)
{
_data[i][shearIndex] = (result[1, i] * Math.Pow((shearht / result[0, i]), thisAlpha));
//Console.WriteLine(_data[i][shearIndex]);
}
else
{
_data[i][shearIndex] = missing;
}
}
_data.Table.AcceptChanges();
DateTime t_end = DateTime.Now;
TimeSpan dur = t_end - t;
Console.WriteLine("Calculating and adding 1 by " + x + " shear ws takes " + dur);
return(true);
}
