public DataTable GetAllCalendarItems()
{
var codePanel = new DataTable(); //CodePanel Data
codePanel.Columns.Add
(
"Subject",
typeof(string));
codePanel.Columns.Add
(
"Location",
typeof(string));
codePanel.Columns.Add
(
"StartTime",
typeof(DateTime));
codePanel.Columns.Add
(
"EndTime",
typeof(DateTime));
codePanel.Columns.Add
(
"StartDate",
typeof(DateTime));
codePanel.Columns.Add
(
"EndDate",
typeof(DateTime));
codePanel.Columns.Add
(
"AllDayEvent",
typeof(bool));
codePanel.Columns.Add
(
"Body",
typeof(string));
ListViewContacts = new ListView();
OApp = new Application();
ONs = OApp.GetNamespace("MAPI");
OCalenderFolder = ONs.GetDefaultFolder(OlDefaultFolders.olFolderCalendar);
OutlookCalendarItems = OCalenderFolder.Items;
OutlookCalendarItems.IncludeRecurrences = true;
// DataTable CodePanel = new DataTable();
foreach (AppointmentItem item in OutlookCalendarItems)
{
DataRow row = codePanel.NewRow();
row["Subject"] = item.Subject;
row["Location"] = item.Location;
row["StartTime"] = item.Start.TimeOfDay.ToString();
row["EndTime"] = item.End.TimeOfDay.ToString();
row["StartDate"] = item.Start.Date;
row["EndDate"] = item.End.Date;
row["AllDayEvent"] = item.AllDayEvent;
row["Body"] = item.Body;
codePanel.Rows.Add(row);
}
codePanel.AcceptChanges();
foreach (DataRow dr in codePanel.Rows)
{
var lvi = new ListViewItem(dr["Subject"].ToString());
lvi.SubItems.Add(dr["Location"].ToString());
lvi.SubItems.Add(dr["StartTime"].ToString());
lvi.SubItems.Add(dr["EndTime"].ToString());
lvi.SubItems.Add(dr["StartDate"].ToString());
lvi.SubItems.Add(dr["EndDate"].ToString());
lvi.SubItems.Add(dr["AllDayEvent"].ToString());
lvi.SubItems.Add(dr["Body"].ToString());
ListViewContacts.Items.Add(lvi);
}
OApp = null;
ONs = null;
return(codePanel);
}
/// <summary>
/// LGMDPlus model visual processing
/// </summary>
/// <param name="img1"></param>
/// <param name="img2"></param>
/// <param name="t"></param>
public void LGMDPlus_Processing(byte[,,] img1, byte[,,] img2, int t)
{
float tmp_sum = 0;
float tmp_ffi = 0;
int cur_frame = t % ONs.GetLength(2);
int pre_frame = (t - 1) % ONs.GetLength(2);
int cur_spi = t % spike.Length;
float sigma, sca, localW;
//PHOTORECEPTORS
for (int y = 0; y < this.height; y++)
{
for (int x = 0; x < width; x++)
{
photoreceptors[y, x, cur_frame] = HighpassFilter(img1[y, x, 0], img2[y, x, 0]);
tmp_ffi += Math.Abs(photoreceptors[y, x, cur_frame]);
}
}
//attention
//SPATIAL LOW-PASS FILTERING
blurred = GaussBlur(photoreceptors, gauss_blur_kernel_width, gauss_blur_kernel, cur_frame);
//attention
//FFI TUNING
ffi[cur_frame] = tmp_ffi / Ncell;
ffi[cur_frame] = LowpassFilter(ffi[cur_frame], ffi[pre_frame], lp_FFI);
sigma = FFIshapesDelayCoefficient(ffi[cur_frame]);
temporalTuning(raw_tau_G, ref dyn_tau_G, ref dyn_lp_G, sigma);
dyn_bias = FFIMediation(ffi[cur_frame], W_base);
//ON/OFF MECHANISMS
for (int y = 0; y < height; y++)
{
for (int x = 0; x < width; x++)
{
ons[y, x, cur_frame] = HRplusDC_ON(ons[y, x, pre_frame], blurred[y, x]);
offs[y, x, cur_frame] = HRplusDC_OFF(offs[y, x, pre_frame], blurred[y, x]);
}
}
//SPATIOTEMPORAL PROCESSING IN DUAL-PATHWAYS
for (int y = 0; y < height; y++)
{
for (int x = 0; x < width; x++)
{
localW = 1 - BiasMat[y, x];
if (localW < W_min)
{
localW = W_min;
}
Inh_ON[y, x] = Convolution(y, x, ons, ConvK, cur_frame, pre_frame, lp_E);
Inh_OFF[y, x] = Convolution(y, x, offs, ConvK, cur_frame, pre_frame, lp_E);
//attention
//dyn_bias = FFIMediation(ffi[cur_frame], (1 - BiasMat[y, x]));
//S_on = sCellValue(ons[y, x, cur_frame], Inh_ON[y, x], dyn_bias);
//S_off = sCellValue(offs[y, x, cur_frame], Inh_OFF[y, x], dyn_bias);
S_on = sCellValue(ons[y, x, cur_frame], Inh_ON[y, x], localW * dyn_bias);
S_off = sCellValue(offs[y, x, cur_frame], Inh_OFF[y, x], localW * dyn_bias);
//S_on = sCellValue(ons[y, x, cur_frame] * BiasMat[y, x], Inh_ON[y, x], dyn_bias);
//S_off = sCellValue(offs[y, x, cur_frame] * BiasMat[y, x], Inh_OFF[y, x], dyn_bias);
scells[y, x] = SupralinearSummation(S_on, S_off);
}
}
for (int y = 0; y < height; y++)
{
for (int x = 0; x < width; x++)
{
gcells[y, x, cur_frame] = Convolving(y, x, scells, W_g);
}
}
sca = Scale(cur_frame);
for (int y = 0; y < height; y++)
{
for (int x = 0; x < width; x++)
{
gcells[y, x, cur_frame] = gCellValue(scells[y, x], gcells[y, x, cur_frame], sca);
//latency of input local excitation
gcells[y, x, cur_frame] = LowpassFilter(gcells[y, x, cur_frame], gcells[y, x, pre_frame], dyn_lp_G);
tmp_sum += gcells[y, x, cur_frame];
}
}
//MEMBRANE POTENTIAL
mp[cur_frame] = tmp_sum;
/*
* if (ffi[cur_frame] > 1)
* mp[cur_frame] /= (float)(Math.Sqrt(ffi[cur_frame]));
*/
smp[cur_frame] = SigmoidTransfer(mp[cur_frame]);
//SPIKE FREQUENCY ADAPTATION
sfa[cur_frame] = SFA_HPF(sfa[pre_frame], smp[pre_frame], smp[cur_frame]);
//SPIKING
spike[cur_spi] = Spiking(sfa[cur_frame]);
//RATE
spiRate = spikeFrequency(spike);
//Collision Recognition
if (collision == 0)
{
collision = collisionDetecting(spiRate, Tsr);
//attention
if (collision == 1)
{
activationTiming = t;
}
}
//Console.WriteLine("{0} {1:F} {2:F} {3:F} {4:F} {5} {6:F} {7:F} {8:F}", t, mp[cur_frame], smp[cur_frame], sfa[cur_frame], ffi[cur_frame], spike[cur_spi], spiRate, dyn_bias, dyn_tau_G);
Console.WriteLine("{0} {1:F} {2:F} {3:F} {4:F} {5} {6:F} {7}", t, mp[cur_frame], smp[cur_frame], sfa[cur_frame], ffi[cur_frame], spike[cur_spi], spiRate, collision);
}
/// <summary>
/// LGMD2 based visual processing
/// </summary>
/// <param name="img1"></param>
/// <param name="img2"></param>
/// <param name="t"></param>
public void LGMD_Processing(byte[,,] img1, byte[,,] img2, int t)
{
float tmp_sum = 0;
int cur_frame = t % ONs.GetLength(2);
int pre_frame = (t - 1) % ONs.GetLength(2);
int cur_spi = t % SPIKE.Length;
float tmp_ffi = 0;
float sigma, sca;
//PHOTORECEPTORS
for (int y = 0; y < height; y++)
{
for (int x = 0; x < width; x++)
{
PHOTOS[y, x, cur_frame] = HighpassFilter(img1[y, x, 0], img2[y, x, 0]);
tmp_ffi += Math.Abs(PHOTOS[y, x, cur_frame]);
}
}
/*attention!*/
//FFI TUNING
FFI[cur_frame] = tmp_ffi / Ncell;
FFI[cur_frame] = LowpassFilter(FFI[cur_frame], FFI[pre_frame], lp_FFI);
sigma = FFIshapesDelayCoefficient(FFI[cur_frame]);
temporalTuning(raw_tau_E, ref tau_E, ref lp_E, sigma);
this.dyn_bias = FFIMediation(FFI[cur_frame], W_i_low);
//dyn_bias = W_i_low;
/*the new tuning mechanism*/
//ON AND OFF RECTIFYING
for (int y = 0; y < height; y++)
{
for (int x = 0; x < width; x++)
{
ONs[y, x, cur_frame] = HRplusDC_ON(ONs[y, x, pre_frame], PHOTOS[y, x, cur_frame]);
OFFs[y, x, cur_frame] = HRplusDC_OFF(OFFs[y, x, pre_frame], PHOTOS[y, x, cur_frame]);
}
}
//SPATIOTEMPORAL PROCESSING IN DUAL-PATHWAYS
for (int y = 0; y < height; y++)
{
for (int x = 0; x < width; x++)
{
INH_ON[y, x] = Convolution(y, x, ONs, Conv_Low, cur_frame, pre_frame, lp_Large);
INH_OFF[y, x] = Convolution(y, x, OFFs, Conv_Low, cur_frame, pre_frame, lp_Large);
S_on = sCellValue(ONs[y, x, cur_frame], INH_ON[y, x], dyn_bias);
S_off = sCellValue(OFFs[y, x, cur_frame], INH_OFF[y, x], dyn_bias);
S_CELLS[y, x] = SupralinearSummation(S_on, S_off);
}
}
for (int y = 0; y < height; y++)
{
for (int x = 0; x < width; x++)
{
G_CELLS[y, x, cur_frame] = Convolving(y, x, S_CELLS, W_g);
}
}
sca = Scale(cur_frame);
for (int y = 0; y < height; y++)
{
for (int x = 0; x < width; x++)
{
G_CELLS[y, x, cur_frame] = gCellValue(S_CELLS[y, x], G_CELLS[y, x, cur_frame], sca);
//latency of input local excitation
G_CELLS[y, x, cur_frame] = LowpassFilter(G_CELLS[y, x, cur_frame], G_CELLS[y, x, pre_frame], lp_E);
tmp_sum += G_CELLS[y, x, cur_frame];
}
}
//MEMBRANE POTENTIAL
MP[cur_frame] = tmp_sum;
SMP[cur_frame] = SigmoidTransfer(MP[cur_frame]);
//SPIKE FREQUENCY ADAPTATION
SFA[cur_frame] = SFA_HPF(SFA[pre_frame], SMP[pre_frame], SMP[cur_frame]);
//SPIKING
SPIKE[cur_spi] = Spiking(SFA[cur_frame]);
//RATE
SPIKERATE = spikeFrequency(SPIKE);
Console.WriteLine("{0} {1:F} {2:F} {3:F} {4:F} {5} {6:F} {7:F} {8:F}", t, this.MP[cur_frame], this.SMP[cur_frame], this.SFA[cur_frame], this.FFI[cur_frame], this.SPIKE[cur_spi], this.SPIKERATE, this.DYNAMIC_BIAS, this.TAU_EXC);
}
