public void Method_Of_Bins_Test()
{
// Test Method of Bins method
// Loop through WD, TOD, Season, and WS width (0.5 and 1.0 m/s)
Continuum thisInst = new Continuum("");
string fileName = "C:\\Users\\liz_w\\Desktop\\Continuum 3 GUI Testing\\SaveFolder\\OneMetTSNotFiltWithMERRAAndMCP_1";
thisInst.Open(fileName + ".cfm");
thisInst.isTest = true;
thisInst.cboMCP_Type.SelectedIndex = 1;
Met thisMet = thisInst.GetSelectedMet("MCP");
Met.WSWD_Dist thisEst = new Met.WSWD_Dist();
Met.WSWD_Dist lastEst = new Met.WSWD_Dist();
for (int WD_ind = 0; WD_ind <= 4; WD_ind++)
{
for (int TOD_ind = 0; TOD_ind <= 1; TOD_ind++)
{
for (int seasonInd = 0; seasonInd <= 1; seasonInd++)
{
for (int WS_width_ind = 0; WS_width_ind <= 1; WS_width_ind++)
{
if (WS_width_ind == 0)
{
thisInst.txtWS_bin_width.Text = "0.5";
}
else
{
thisInst.txtWS_bin_width.Text = "1.0";
}
thisInst.cboMCPNumHours.SelectedIndex = TOD_ind;
thisInst.cboMCPNumSeasons.SelectedIndex = seasonInd;
thisInst.cboMCPNumWD.SelectedIndex = WD_ind;
thisInst.DoMCP();
thisEst = thisMet.GetWS_WD_Dist(thisInst.modeledHeight, Met.TOD.All, Met.Season.All);
Assert.AreNotEqual(thisEst.WS, lastEst.WS, "LT Estimate did not change with setting change");
lastEst = thisEst;
}
}
}
}
thisInst.Close();
}
public void Variance_Ratio_Test()
{
// Test Variance Ratio method
Continuum thisInst = new Continuum("");
string fileName = "C:\\Users\\liz_w\\Desktop\\Continuum 3 GUI Testing\\SaveFolder\\OneMetTSNotFiltWithMERRAAndMCP_1";
thisInst.Open(fileName + ".cfm");
thisInst.isTest = true;
thisInst.cboMCP_Type.SelectedIndex = 2;
Met thisMet = thisInst.GetSelectedMet("MCP");
Met.WSWD_Dist thisEst = new Met.WSWD_Dist();
Met.WSWD_Dist lastEst = new Met.WSWD_Dist();
for (int WD_ind = 0; WD_ind <= 4; WD_ind++)
{
for (int TOD_ind = 0; TOD_ind <= 1; TOD_ind++)
{
for (int seasonInd = 0; seasonInd <= 1; seasonInd++)
{
thisInst.cboMCPNumHours.SelectedIndex = TOD_ind;
thisInst.cboMCPNumSeasons.SelectedIndex = seasonInd;
thisInst.cboMCPNumWD.SelectedIndex = WD_ind;
thisInst.DoMCP();
thisEst = thisMet.GetWS_WD_Dist(thisInst.modeledHeight, Met.TOD.All, Met.Season.All);
Assert.AreNotEqual(thisEst.WS, lastEst.WS, "LT Estimate did not change with setting change");
lastEst = thisEst;
}
}
}
thisInst.Close();
}
/// <summary> Conducts wind speed estimate from Met 1 to Met 2 and vice-versa and calculates WS cross-prediction struct (WS_CrossPreds[,]) </summary>
public void DoMetCrossPred(int crossPredInd, int radiusIndex, Continuum thisInst)
{
int numWD = thisInst.metList.numWD;
int numNodes = 0;
NodeCollection nodeList = new NodeCollection();
if (WS_Pred[crossPredInd, radiusIndex].nodePath == null)
{
numNodes = 0;
}
else
{
numNodes = WS_Pred[crossPredInd, radiusIndex].nodePath.Length;
}
if (numNodes > 0)
{
WS_Pred[crossPredInd, radiusIndex].nodeWS_Ests1to2 = new double[numNodes];
WS_Pred[crossPredInd, radiusIndex].nodeSectorWS_Ests1to2 = new double[numNodes, numWD];
WS_Pred[crossPredInd, radiusIndex].nodeWS_Ests2to1 = new double[numNodes];
WS_Pred[crossPredInd, radiusIndex].nodeSectorWS_Ests2to1 = new double[numNodes, numWD];
}
Nodes[] pathOfNodes;
Model thisModel = WS_Pred[crossPredInd, radiusIndex].model;
// Get WS distributions at each site (used to calculate the cross-prediction percent error)
Met.WSWD_Dist met1Dist = met1.GetWS_WD_Dist(thisInst.modeledHeight, thisModel.timeOfDay, thisModel.season);
Met.WSWD_Dist met2Dist = met2.GetWS_WD_Dist(thisInst.modeledHeight, thisModel.timeOfDay, thisModel.season);
// Conduct cross-prediction from Met 1 to Met 2
Nodes endNode = nodeList.GetMetNode(met2);
ModelCollection.WS_Est_Struct WS_EstStr = thisInst.modelList.DoWS_Estimate(met1, endNode, WS_Pred[crossPredInd, radiusIndex].nodePath, thisModel, thisInst);
// Get sectorwise wind speed and calculate sectorwise percent error (for Met 1 predicting Met 2)
for (int WD_Ind = 0; WD_Ind < numWD; WD_Ind++)
{
WS_Pred[crossPredInd, radiusIndex].sectorWS_Ests[0, WD_Ind] = WS_EstStr.sectorWS[WD_Ind];
double met2WS = met2Dist.WS * met2Dist.sectorWS_Ratio[WD_Ind];
WS_Pred[crossPredInd, radiusIndex].percErrSector[0, WD_Ind] = (WS_EstStr.sectorWS[WD_Ind] - met2WS) / met2WS;
}
WS_Pred[crossPredInd, radiusIndex].nodeSectorWS_Ests1to2 = WS_EstStr.sectorWS_AtNodes;
double avgWS = 0;
double WR_count = 0;
// Get overall wind speed at nodes (for Met 1 predicting Met 2)
for (int nodeInd = 0; nodeInd < numNodes; nodeInd++)
{
avgWS = 0;
WR_count = 0;
Nodes thisNode = WS_Pred[crossPredInd, radiusIndex].nodePath[nodeInd];
double[] nodeWindRose = thisInst.metList.GetInterpolatedWindRose(thisModel.metsUsed, thisNode.UTMX, thisNode.UTMY, thisModel.timeOfDay, thisModel.season, thisInst.modeledHeight);
for (int WD_Ind = 0; WD_Ind < numWD; WD_Ind++)
{
avgWS = avgWS + nodeWindRose[WD_Ind] * WS_Pred[crossPredInd, radiusIndex].nodeSectorWS_Ests1to2[nodeInd, WD_Ind];
WR_count = WR_count + nodeWindRose[WD_Ind];
}
WS_Pred[crossPredInd, radiusIndex].nodeWS_Ests1to2[nodeInd] = avgWS / WR_count;
}
avgWS = 0;
WR_count = 0;
for (int WD = 0; WD < numWD; WD++)
{
avgWS = avgWS + WS_Pred[crossPredInd, radiusIndex].sectorWS_Ests[0, WD] * met2Dist.windRose[WD];
WR_count = WR_count + met2Dist.windRose[WD];
}
// Calculate avg WS estimate and overall error at Met 2
avgWS = avgWS / WR_count;
WS_Pred[crossPredInd, radiusIndex].WS_Ests[0] = avgWS;
WS_Pred[crossPredInd, radiusIndex].percErr[0] = (avgWS - met2Dist.WS) / met2Dist.WS;
// Now conduct same calculations but going from Met 2 to Met 1.
endNode = nodeList.GetMetNode(met1);
if (numNodes > 0)
{
pathOfNodes = new Nodes[numNodes];
}
else
{
pathOfNodes = null;
}
// Reverse order of nodes when going from Met 2 to Met 1
for (int i = 0; i < numNodes; i++)
{
pathOfNodes[i] = WS_Pred[crossPredInd, radiusIndex].nodePath[numNodes - 1 - i];
}
// Do WS Estimate for Met 2 predicting Met 1
WS_EstStr = thisInst.modelList.DoWS_Estimate(met2, endNode, pathOfNodes, thisModel, thisInst);
// Get sectorwise wind speed and sectorwise percent error (for Met 2 predicting Met 1)
for (int WD_Ind = 0; WD_Ind < numWD; WD_Ind++)
{
WS_Pred[crossPredInd, radiusIndex].sectorWS_Ests[1, WD_Ind] = WS_EstStr.sectorWS[WD_Ind];
WS_Pred[crossPredInd, radiusIndex].percErrSector[1, WD_Ind] = (WS_EstStr.sectorWS[WD_Ind] - met1Dist.WS * met1Dist.sectorWS_Ratio[WD_Ind])
/ (met1Dist.WS * met1Dist.sectorWS_Ratio[WD_Ind]);
}
WS_Pred[crossPredInd, radiusIndex].nodeSectorWS_Ests2to1 = WS_EstStr.sectorWS_AtNodes;
avgWS = 0;
WR_count = 0;
// Get overall wind speed at nodes (for Met 2 predicting Met 1)
for (int nodeInd = 0; nodeInd < numNodes; nodeInd++)
{
avgWS = 0;
WR_count = 0;
Nodes thisNode = pathOfNodes[nodeInd];
double[] nodeWindRose = thisInst.metList.GetInterpolatedWindRose(thisModel.metsUsed, thisNode.UTMX, thisNode.UTMY, thisModel.timeOfDay, thisModel.season, thisInst.modeledHeight);
for (int WD_Ind = 0; WD_Ind < numWD; WD_Ind++)
{
avgWS = avgWS + nodeWindRose[WD_Ind] * WS_Pred[crossPredInd, radiusIndex].nodeSectorWS_Ests2to1[nodeInd, WD_Ind];
WR_count = WR_count + nodeWindRose[WD_Ind];
}
WS_Pred[crossPredInd, radiusIndex].nodeWS_Ests2to1[nodeInd] = avgWS / WR_count;
}
avgWS = 0;
WR_count = 0;
for (int WD = 0; WD < numWD; WD++)
{
avgWS = avgWS + WS_Pred[crossPredInd, radiusIndex].sectorWS_Ests[1, WD] * met1Dist.windRose[WD];
WR_count = WR_count + met1Dist.windRose[WD];
}
// Calculate avg WS estimate and overall error at Met 1
avgWS = avgWS / WR_count;
WS_Pred[crossPredInd, radiusIndex].WS_Ests[1] = avgWS;
WS_Pred[crossPredInd, radiusIndex].percErr[1] = (avgWS - met1Dist.WS) / met1Dist.WS;
}
