public static void Test(AUTD autd)
{
const double x = AUTD.DeviceWidth / 2;
const double y = AUTD.DeviceHeight / 2;
const double z = 150;
var center = new Vector3d(x, y, z);
var g1 = Gain.FocalPoint(center);
var focuses = new[] {
center + 30.0 * Vector3d.UnitX,
center - 30.0 * Vector3d.UnitX
};
var amps = new[] {
1.0,
1.0
};
var backend = Gain.Eigen3Backend();
var g2 = Gain.HoloGSPAT(focuses, amps, backend);
var gainMap = new Dictionary <int, Gain>
{
[0] = g1,
[1] = g2
};
var gain = Gain.Grouped(autd, gainMap);
var mod = Modulation.Sine(150); // AM sin 150 Hz
autd.Send(gain, mod);
Gain.DeleteBackend(backend);
}
public void Configure(Gain gain, float time, byte timeMask, bool illuminator, byte illuminatorMask)
{
byte[][] expected = { new byte[] { 0x17, 0x02, timeMask, (byte)gain, illuminatorMask } };
color.Configure(gain: gain, integationTime: time, illuminate: illuminator);
Assert.That(platform.GetCommands(), Is.EqualTo(expected));
}
public static void Test(AUTD autd)
{
const double x = AUTD.DeviceWidth / 2;
const double y = AUTD.DeviceHeight / 2;
const double z = 150;
autd.SilentMode = false;
var mod = Modulation.Static();
var center = new Vector3d(x, y, z);
var seq = GainSequence.Create(autd);
const int pointNum = 200;
var backend = Gain.Eigen3Backend();
for (var i = 0; i < pointNum; i++)
{
const double radius = 30.0;
var theta = 2.0 * Math.PI * i / pointNum;
var p = radius * new Vector3d(Math.Cos(theta), Math.Sin(theta), 0);
var gain = Gain.FocalPoint(center + p);
seq.AddGain(gain);
}
seq.Frequency = 1;
Console.WriteLine($"Actual frequency is {seq.Frequency}");
autd.Send(seq, mod);
Gain.DeleteBackend(backend);
}
public double GetMillivolts(Channel channel, Gain gain = Gain.Volt5, SamplesPerSecond sps = SamplesPerSecond.SPS1600) {
lock (deviceLock) {
byte[] result = new byte[2];
// Set disable comparator and set "single shot" mode
config = 0x0003 | 0x8000; // | 0x100;
config |= (ushort)SamplePerSecondMap[(int)sps];
config |= (ushort)channel;
config |= (ushort)programmableGainMap[(int)gain];
data[0] = REG_CFG;
data[1] = (byte)((config >> 8) & 0xFF);
data[2] = (byte)(config & 0xFF);
I2CDevice.Write(data);
// delay in milliseconds
//int delay = (1000.0 / SamplesPerSecondRate[(int)sps] + .1;
// int delay = 1;
Task.Delay(TimeSpan.FromMilliseconds(.5)).Wait();
I2CDevice.WriteRead(new byte[] { (byte)REG_CONV, 0x00 }, result);
//var r = (((result[0] << 8) | result[1]) >> 4);
//Debug.WriteLine(r.ToString());
return (ushort)(((result[0] << 8) | result[1]) >> 4) * programmableGain_Scaler[(int)gain] / 2048;
}
}
public override int Read(float[] buffer, int offset, int count)
{
float[] input = new float[buffer.Length];
float[] gain = new float[buffer.Length];
float[] cutoff = new float[buffer.Length];
Source.Read(input, offset, count);
Gain.Read(gain, offset, count);
Cutoff.Read(cutoff, offset, count);
for (int i = offset; i < count; i++)
{
// basic hard clipping
float x = input[i] * gain[i];
float cut = Math.Abs(cutoff[i]);
if (x < -cut)
{
buffer[i] = -cut;
}
else if (x > cut)
{
buffer[i] = cut;
}
else
{
buffer[i] = x;
}
}
return(count);
}
private ushort[] GetFullLuminosity(Gain gain, IntegrationTime time)
{
// We need to configure the device for the correct gain and integration time for this reading
this._i2cDevice.Write(new byte[] { TSL2591_CONTROL_RW, (byte)((byte)gain << 4 | (byte)time) });
try
{
// Enabled the device so that we can start a reading
this._i2cDevice.Write(new byte[] { TSL2591_ENABLE_RW, 0x03 });
try
{
// We now need to wait for the integration time to pass so that we know we have a valid reading. The specification
// states that the MAX integration time per gain step is 108ms.
System.Threading.Thread.Sleep(120 * ((byte)time + 1));
var readBuffer = new byte[4];
this._i2cDevice.WriteRead(new byte[] { TSL2591_C0DATAL_R }, readBuffer);
var visible = (ushort)((readBuffer[1] << 8) | readBuffer[0]);
var ir = (ushort)((readBuffer[3] << 8) | readBuffer[2]);
return(new ushort[] { (ushort)(visible - ir), ir });
}
finally
{
this._i2cDevice.Write(new byte[] { TSL2591_ENABLE_RW, 0x00 });
}
}
finally
{
this._i2cDevice.Write(new byte[] { TSL2591_CONTROL_RW, 0x00 });
}
}
public async Task <double> GetLux(Gain gain = Gain.Low, IntegrationTime time = IntegrationTime.Shortest)
{
await ConnectAndInitialize();
await Configure(gain, time);
Enable();
await Task.Delay((int)time);
var y = ReadRegister(Registers.Command | Registers.C0DataL, x => (ushort)((x[1] << 8) | x[0]), 2) | 0;
var luminosity = (ReadRegister(Registers.Command | Registers.C1DataL, x => (ushort)((x[1] << 8) | x[0]), 2) << 16) | y;
Disable();
var full = luminosity & 0xFFFF;
var ir = luminosity >> 16;
if ((full == 0xFFFF) | (ir == 0xFFFF))
{
return(0.0);
}
var cpl = (float)gain * (float)time / 408.0F;
return((full - ir) * (1.0f - ir / full) / cpl);
}
public override int GetHashCode()
{
int hash = 1;
if (Id != 0)
{
hash ^= Id.GetHashCode();
}
if (Player != 0)
{
hash ^= Player.GetHashCode();
}
if (PictureId != 0)
{
hash ^= PictureId.GetHashCode();
}
if (Coordinate.Length != 0)
{
hash ^= Coordinate.GetHashCode();
}
if (Gain != 0D)
{
hash ^= Gain.GetHashCode();
}
if (IsEvo != 0)
{
hash ^= IsEvo.GetHashCode();
}
if (Sharpness != 0D)
{
hash ^= Sharpness.GetHashCode();
}
return(hash);
}
public static void Test(AUTD autd)
{
const double x = AUTD.DeviceWidth / 2;
const double y = AUTD.DeviceHeight / 2;
const double z = 150.0;
autd.SilentMode = false;
var mod = Modulation.Static();
autd.Send(mod);
const double radius = 30.0;
const int size = 100;
var center = new Vector3d(x, y, z);
var stm = autd.STM();
for (var i = 0; i < size; i++)
{
var theta = 2 * AUTD.Pi * i / size;
var r = new Vector3d(Math.Cos(theta), Math.Sin(theta), 0);
var f = Gain.FocalPoint(center + radius * r);
stm.AddSTMGain(f);
}
stm.StartSTM(0.5);
Console.WriteLine("press any key to stop...");
Console.ReadKey(true);
stm.StopSTM();
stm.FinishSTM();
}
public void Configure(Gain gain, Tuple <float, byte> time, Tuple <bool, byte> illuminator)
{
byte[][] expected = { new byte[] { 0x17, 0x02, time.Item2, (byte)gain, illuminator.Item2 } };
color.Configure(gain: gain, integationTime: time.Item1, illuminate: illuminator.Item1);
Assert.That(platform.GetCommands(), Is.EqualTo(expected));
}
void Update()
{
if (Target != null)
{
_autd.Send(Gain.FocalPoint(Target.transform.position));
}
}
public double GetMillivolts(Channel channel, Gain gain = Gain.Volt5, SamplesPerSecond sps = SamplesPerSecond.SPS1600)
{
lock (deviceLock) {
byte[] result = new byte[2];
// Set disable comparator and set "single shot" mode
config = 0x0003 | 0x8000; // | 0x100;
config |= (ushort)SamplePerSecondMap[(int)sps];
config |= (ushort)channel;
config |= (ushort)programmableGainMap[(int)gain];
data[0] = REG_CFG;
data[1] = (byte)((config >> 8) & 0xFF);
data[2] = (byte)(config & 0xFF);
I2CDevice.Write(data);
// delay in milliseconds
//int delay = (1000.0 / SamplesPerSecondRate[(int)sps] + .1;
// int delay = 1;
Task.Delay(TimeSpan.FromMilliseconds(.5)).Wait();
I2CDevice.WriteRead(new byte[] { (byte)REG_CONV, 0x00 }, result);
//var r = (((result[0] << 8) | result[1]) >> 4);
//Debug.WriteLine(r.ToString());
return((ushort)(((result[0] << 8) | result[1]) >> 4) * programmableGain_Scaler[(int)gain] / 2048);
}
}
public override void Single()
{
if (GeneTestSetup.Instance.IsSimulated)
{
}
else
{
string dutAddr = MeasInfo.InstruInfoList[1].Address;
//连接串口
HWAISGCOM aisg = new HWAISGCOM();
aisg.Open(dutAddr, 9600);
//设置参数
aisg.InitDut();
aisg.SetGain(Gain.ToString());
string gain = aisg.GetGain();
if (gain != Gain.ToString())
{
DataUtils.LOGINFO.WriteLog("set aisg gain wrong");
}
aisg.SetTMAMode(SubNum, Mode);
var mode = aisg.GetTMAMode(SubNum);
if (mode != Mode)
{
DataUtils.LOGINFO.WriteLog("set aisg tma mode wrong");
}
//关闭串口
aisg.Close();
}
}
public static void Test(AUTD autd)
{
autd.SilentMode = false;
var delays = new byte[autd.NumDevices, AUTD.NumTransInDevice];
delays[0, 0] = 4;
autd.SetDelayOffset(delays, null);
var uniform = new ushort[autd.NumDevices, AUTD.NumTransInDevice];
for (var i = 0; i < autd.NumDevices; i++)
{
for (var j = 0; j < AUTD.NumTransInDevice; j++)
{
uniform[i, j] = 0xFFFF;
}
}
var burst = new byte[4000];
burst[0] = 0xFF;
var g = Gain.Custom(uniform);
var m = Modulation.Custom(burst);
autd.Send(g, m);
}
public static void Test(AUTD autd)
{
const double x = AUTD.TransSpacing * (AUTD.NumTransInX - 1) / 2.0;
const double y = AUTD.TransSpacing * (AUTD.NumTransInY - 1) / 2.0;
const double z = 150.0;
var mod = Modulation.Sine(150);
var center = new Vector3d(x, y, z);
var focuses = new[] {
center + 20.0 * Vector3d.UnitX,
center - 20.0 * Vector3d.UnitX
};
var amps = new[] {
1.0,
1.0
};
var backend = Gain.Eigen3Backend();
var gain = Gain.HoloSDP(focuses, amps, backend);
autd.Send(gain, mod);
Gain.DeleteBackend(backend);
}
protected override void EnableProperties()
{
Octaves.IsVisibleWhen(FractalType, f => f.CurrentValue != PropertiesFractalType.None);
Lacunarity.IsVisibleWhen(FractalType, f => f.CurrentValue != PropertiesFractalType.None);
Gain.IsVisibleWhen(FractalType, f => f.CurrentValue != PropertiesFractalType.None);
WeightedStrength.IsVisibleWhen(FractalType, f => f.CurrentValue != PropertiesFractalType.None);
PingPongStrength.IsVisibleWhen(FractalType, f => f.CurrentValue == PropertiesFractalType.PingPong);
}
public void SetTimingAndGain(IntegrationTimeMs timing, Gain gain)
{
Enable();
Write((Register)((byte)Register.Timing | (byte)Command.Command), (byte)((byte)timing | (byte)gain));
IntegrationTime = timing;
SensorGain = gain;
Disable();
}
public INoise GetLandFormFct()
{
INoise AnomaliesZonesFractal = new FractalFbm(new Perlin(_seed), _octaves, _frequency, enuBaseNoiseRange.ZeroToOne);
INoise AnomaliesZonesFractal_as2DNoise = new NoiseAccess(AnomaliesZonesFractal, NoiseAccess.enuDimUsage.Noise2D, true);
INoise AnomaliesZonesFractal_Bias = new Gain(AnomaliesZonesFractal_as2DNoise, _bias);
return(AnomaliesZonesFractal_Bias);
}
/// <summary>
/// Initialize a new HMC5883L device connected through I2C
/// </summary>
/// <param name="sensor">I2C Device, like UnixI2cDevice or Windows10I2cDevice</param>
/// <param name="gain">Gain Setting</param>
/// <param name="measuringMode">The Mode of Measuring</param>
/// <param name="outputRate">Typical Data Output Rate (Hz)</param>
public Hmc5883l(I2cDevice sensor, Gain gain = Gain.Gain1090, MeasuringMode measuringMode = MeasuringMode.Continuous, OutputRate outputRate = OutputRate.Rate15)
{
_sensor = sensor;
_gain = (byte)gain;
_measuringMode = (byte)measuringMode;
_outputRate = (byte)outputRate;
Initialize();
}
void Start()
{
trans = GetComponent <Transform>();
Player = trans.Find("Camera (eye)");
physicsPlayer = GetComponent <VRRigidbodyPlayer>();
playArea = GetComponent <SteamVR_PlayArea>();
gains = new Gain();
lastPlayerPos = Player.localPosition;
}
public override double GetValue(double x, double y, double z)
{
double lacunarity = Lacunarity.GetValue(x, y, z);
double gain = Gain.GetValue(x, y, z);
double offset = Offset.GetValue(x, y, z);
double frequency = Frequency.GetValue(x, y, z);
x *= frequency;
y *= frequency;
z *= frequency;
int mOctaveCount = (int)OctaveCount.GetValue(x, y, z);
double signal = 0.0;
double value = 0.0;
double weight = 1.0;
for (int currentOctave = 0; currentOctave < mOctaveCount; currentOctave++)
{
long seed = (Seed + currentOctave) & 0x7fffffff;
signal = GradientNoise.GradientCoherentNoise(x, y, z,
(int)seed, NoiseQuality);
// Make the ridges.
signal = System.Math.Abs(signal);
signal = offset - signal;
// Square the signal to increase the sharpness of the ridges.
signal *= signal;
// The weighting from the previous octave is applied to the signal.
// Larger values have higher weights, producing sharp points along the
// ridges.
signal *= weight;
// Weight successive contributions by the previous signal.
weight = signal * gain;
if (weight > 1.0)
{
weight = 1.0;
}
else if (weight < 0.0)
{
weight = 0.0;
}
// Add the signal to the output value.
value += (signal * SpectralWeights[currentOctave]);
// Go to the next octave.
x *= lacunarity;
y *= lacunarity;
z *= lacunarity;
}
return((value * 1.25) - 1.0);
}
/// <summary>
/// Constructs a new Midi Processor.
/// </summary>
/// <param name="plugin">Must not be null.</param>
public MidiProcessor(Plugin plugin)
{
_plugin = plugin;
Gain = new Gain(plugin);
Transpose = new Transpose(plugin);
// for most hosts, midi output is expected during the audio processing cycle.
SyncWithAudioProcessor = true;
}
public override int GetHashCode()
{
unchecked
{
int hashCode = Power.GetHashCode();
hashCode = (hashCode * 397) ^ Gain.GetHashCode();
return(hashCode);
}
}
public override int GetHashCode()
{
int result = 7057;
result = result * 8171 + (Sound != null ? (int)Sound.Index.Value : 0);
result = result * 8171 + Gain.GetHashCode();
result = result * 8171 + Flags;
return(result);
}
public override int GetHashCode()
{
int result = 7057;
result = result * 8171 + (int)OriginalSound.Value;
result = result * 8171 + Gain.GetHashCode();
result = result * 8171 + Flags;
return(result);
}
public void CreateFeedEntryTest()
{
string xml = "<?xml version='1.0' encoding='UTF-8'?><feed xmlns='http://www.w3.org/2005/Atom' xmlns:openSearch='http://a9.com/-/spec/opensearchrss/1.0/' xmlns:gf='http://schemas.google.com/finance/2007' xmlns:gd='http://schemas.google.com/g/2005'><id>http://finance.google.com/finance/feeds/[email protected]/portfolios</id><updated>2009-06-27T05:40:34.000Z</updated><category scheme='http://schemas.google.com/g/2005#kind' term='http://schemas.google.com/finance/2007#portfolio'/><title type='text'>Portfolio Feed</title><link rel='alternate' type='text/html' href='http://finance.google.com/finance/portfolio?action=view'/><link rel='http://schemas.google.com/g/2005#feed' type='application/atom+xml' href='http://finance.google.com/finance/feeds/default/portfolios'/><link rel='http://schemas.google.com/g/2005#post' type='application/atom+xml' href='http://finance.google.com/finance/feeds/default/portfolios'/><link rel='self' type='application/atom+xml' href='http://finance.google.com/finance/feeds/default/portfolios?positions=true&returns=true'/><openSearch:totalResults>1</openSearch:totalResults><openSearch:startIndex>1</openSearch:startIndex><openSearch:itemsPerPage>1</openSearch:itemsPerPage><entry><id>http://finance.google.com/finance/feeds/[email protected]/portfolios/1</id><updated>2009-06-27T05:40:34.000Z</updated><category scheme='http://schemas.google.com/g/2005#kind' term='http://schemas.google.com/finance/2007#portfolio'/><title type='text'>My Portfolio</title><link rel='self' type='application/atom+xml' href='http://finance.google.com/finance/feeds/default/portfolios/1'/><link rel='edit' type='application/atom+xml' href='http://finance.google.com/finance/feeds/default/portfolios/1'/><gd:feedLink href='http://finance.google.com/finance/feeds/[email protected]/portfolios/1/positions'><feed><id>http://finance.google.com/finance/feeds/[email protected]/portfolios/1/positions</id><updated>2009-06-27T05:40:34.000Z</updated><category scheme='http://schemas.google.com/g/2005#kind' term='http://schemas.google.com/finance/2007#position'/><title type='text'>My Portfolio</title><link rel='alternate' type='text/html' href='http://finance.google.com/finance/portfolio?action=view&pid=1'/><link rel='http://schemas.google.com/g/2005#feed' type='application/atom+xml' href='http://finance.google.com/finance/feeds/default/portfolios'/><openSearch:totalResults>9</openSearch:totalResults><openSearch:itemsPerPage>9</openSearch:itemsPerPage><entry><id>http://finance.google.com/finance/feeds/[email protected]/portfolios/1/positions/NASDAQ:MSFT</id><updated>2009-06-27T05:40:34.000Z</updated><category scheme='http://schemas.google.com/g/2005#kind' term='http://schemas.google.com/finance/2007#position'/><title type='text'>Microsoft Corporation</title><link rel='self' type='application/atom+xml' href='http://finance.google.com/finance/feeds/default/portfolios/NASDAQ%3AMSFT'/><link rel='edit' type='application/atom+xml' href='http://finance.google.com/finance/feeds/default/portfolios/NASDAQ%3AMSFT'/><gd:feedLink href='http://finance.google.com/finance/feeds/[email protected]/portfolios/1/positions/NASDAQ:MSFT/transactions'/><gf:positionData gainPercentage='20.82242991' return1w='0.0' return1y='0.0' return3m='0.0' return3y='0.0' return4w='0.0' return5y='0.0' returnOverall='0.0' returnYTD='0.0' shares='1000.0'><gf:costBasis><gd:money amount='1070.0' currencyCode='USD'/></gf:costBasis><gf:daysGain><gd:money amount='-440.001' currencyCode='USD'/></gf:daysGain><gf:gain><gd:money amount='22280.0' currencyCode='USD'/></gf:gain><gf:marketValue><gd:money amount='23350.0' currencyCode='USD'/></gf:marketValue></gf:positionData><gf:symbol exchange='NASDAQ' fullName='Microsoft Corporation' symbol='MSFT'/></entry><entry><id>http://finance.google.com/finance/feeds/[email protected]/portfolios/1/positions/NASDAQ:AAPL</id><updated>2009-06-27T05:40:34.000Z</updated><category scheme='http://schemas.google.com/g/2005#kind' term='http://schemas.google.com/finance/2007#position'/><title type='text'>Apple Inc.</title><link rel='self' type='application/atom+xml' href='http://finance.google.com/finance/feeds/default/portfolios/NASDAQ%3AAAPL'/><link rel='edit' type='application/atom+xml' href='http://finance.google.com/finance/feeds/default/portfolios/NASDAQ%3AAAPL'/><gd:feedLink href='http://finance.google.com/finance/feeds/[email protected]/portfolios/1/positions/NASDAQ:AAPL/transactions'/><gf:positionData gainPercentage='355.1' return1w='0.02122168053' return1y='355.1' return3m='355.1' return3y='355.1' return4w='355.1' return5y='355.1' returnOverall='355.1' returnYTD='355.1' shares='100.0'><gf:costBasis><gd:money amount='40.0' currencyCode='USD'/></gf:costBasis><gf:daysGain><gd:money amount='258.0002' currencyCode='USD'/></gf:daysGain><gf:gain><gd:money amount='14204.0' currencyCode='USD'/></gf:gain><gf:marketValue><gd:money amount='14244.0' currencyCode='USD'/></gf:marketValue></gf:positionData><gf:symbol exchange='NASDAQ' fullName='Apple Inc.' symbol='AAPL'/></entry><entry><id>http://finance.google.com/finance/feeds/[email protected]/portfolios/1/positions/NASDAQ:ACAS</id><updated>2009-06-27T05:40:34.000Z</updated><category scheme='http://schemas.google.com/g/2005#kind' term='http://schemas.google.com/finance/2007#position'/><title type='text'>American Capital Ltd.</title><link rel='self' type='application/atom+xml' href='http://finance.google.com/finance/feeds/default/portfolios/NASDAQ%3AACAS'/><link rel='edit' type='application/atom+xml' href='http://finance.google.com/finance/feeds/default/portfolios/NASDAQ%3AACAS'/><gd:feedLink href='http://finance.google.com/finance/feeds/[email protected]/portfolios/1/positions/NASDAQ:ACAS/transactions'/><gf:positionData gainPercentage='0.1045296167' return1w='0.0' return1y='0.0' return3m='0.0' return3y='0.0' return4w='0.0' return5y='0.0' returnOverall='0.0' returnYTD='0.0' shares='10000.0'><gf:costBasis><gd:money amount='28700.0' currencyCode='USD'/></gf:costBasis><gf:daysGain><gd:money amount='4500.0' currencyCode='USD'/></gf:daysGain><gf:gain><gd:money amount='3000.0' currencyCode='USD'/></gf:gain><gf:marketValue><gd:money amount='31700.0' currencyCode='USD'/></gf:marketValue></gf:positionData><gf:symbol exchange='NASDAQ' fullName='American Capital Ltd.' symbol='ACAS'/></entry><entry><id>http://finance.google.com/finance/feeds/[email protected]/portfolios/1/positions/NYSE:ING</id><updated>2009-06-27T05:40:34.000Z</updated><category scheme='http://schemas.google.com/g/2005#kind' term='http://schemas.google.com/finance/2007#position'/><title type='text'>ING Groep N.V. (ADR)</title><link rel='self' type='application/atom+xml' href='http://finance.google.com/finance/feeds/default/portfolios/NYSE%3AING'/><link rel='edit' type='application/atom+xml' href='http://finance.google.com/finance/feeds/default/portfolios/NYSE%3AING'/><gd:feedLink href='http://finance.google.com/finance/feeds/[email protected]/portfolios/1/positions/NYSE:ING/transactions'/><gf:positionData gainPercentage='0.05503634476' return1w='0.0' return1y='0.0' return3m='0.0' return3y='0.0' return4w='0.0' return5y='0.0' returnOverall='0.0' returnYTD='0.0' shares='124.0'><gf:costBasis><gd:money amount='1194.12' currencyCode='USD'/></gf:costBasis><gf:daysGain><gd:money amount='-2.48' currencyCode='USD'/></gf:daysGain><gf:gain><gd:money amount='65.72' currencyCode='USD'/></gf:gain><gf:marketValue><gd:money amount='1259.84' currencyCode='USD'/></gf:marketValue></gf:positionData><gf:symbol exchange='NYSE' fullName='ING Groep N.V. (ADR)' symbol='ING'/></entry><entry><id>http://finance.google.com/finance/feeds/[email protected]/portfolios/1/positions/NASDAQ:FORTY</id><updated>2009-06-27T05:40:34.000Z</updated><category scheme='http://schemas.google.com/g/2005#kind' term='http://schemas.google.com/finance/2007#position'/><title type='text'>Formula Systems (1985) Ltd. (ADR)</title><link rel='self' type='application/atom+xml' href='http://finance.google.com/finance/feeds/default/portfolios/NASDAQ%3AFORTY'/><link rel='edit' type='application/atom+xml' href='http://finance.google.com/finance/feeds/default/portfolios/NASDAQ%3AFORTY'/><gd:feedLink href='http://finance.google.com/finance/feeds/[email protected]/portfolios/1/positions/NASDAQ:FORTY/transactions'/><gf:positionData gainPercentage='0.03818953324' return1w='0.0' return1y='0.0' return3m='0.0' return3y='0.0' return4w='0.0' return5y='0.0' returnOverall='0.0' returnYTD='0.0' shares='130.0'><gf:costBasis><gd:money amount='919.1' currencyCode='USD'/></gf:costBasis><gf:daysGain><gd:money amount='17.55' currencyCode='USD'/></gf:daysGain><gf:gain><gd:money amount='35.1' currencyCode='USD'/></gf:gain><gf:marketValue><gd:money amount='954.2' currencyCode='USD'/></gf:marketValue></gf:positionData><gf:symbol exchange='NASDAQ' fullName='Formula Systems (1985) Ltd. (ADR)' symbol='FORTY'/></entry><entry><id>http://finance.google.com/finance/feeds/[email protected]/portfolios/1/positions/NYSE:DT</id><updated>2009-06-27T05:40:34.000Z</updated><category scheme='http://schemas.google.com/g/2005#kind' term='http://schemas.google.com/finance/2007#position'/><title type='text'>Deutsche Telekom AG (ADR)</title><link rel='self' type='application/atom+xml' href='http://finance.google.com/finance/feeds/default/portfolios/NYSE%3ADT'/><link rel='edit' type='application/atom+xml' href='http://finance.google.com/finance/feeds/default/portfolios/NYSE%3ADT'/><gd:feedLink href='http://finance.google.com/finance/feeds/[email protected]/portfolios/1/positions/NYSE:DT/transactions'/><gf:positionData gainPercentage='0.01224846894' return1w='0.0' return1y='0.0' return3m='0.0' return3y='0.0' return4w='0.0' return5y='0.0' returnOverall='0.0' returnYTD='0.0' shares='242.0'><gf:costBasis><gd:money amount='2766.06' currencyCode='USD'/></gf:costBasis><gf:daysGain><gd:money amount='14.519758' currencyCode='USD'/></gf:daysGain><gf:gain><gd:money amount='33.88' currencyCode='USD'/></gf:gain><gf:marketValue><gd:money amount='2799.94' currencyCode='USD'/></gf:marketValue></gf:positionData><gf:symbol exchange='NYSE' fullName='Deutsche Telekom AG (ADR)' symbol='DT'/></entry><entry><id>http://finance.google.com/finance/feeds/[email protected]/portfolios/1/positions/NYSE:CHN</id><updated>2009-06-27T05:40:34.000Z</updated><category scheme='http://schemas.google.com/g/2005#kind' term='http://schemas.google.com/finance/2007#position'/><title type='text'>China Fund Inc. (The)</title><link rel='self' type='application/atom+xml' href='http://finance.google.com/finance/feeds/default/portfolios/NYSE%3ACHN'/><link rel='edit' type='application/atom+xml' href='http://finance.google.com/finance/feeds/default/portfolios/NYSE%3ACHN'/><gd:feedLink href='http://finance.google.com/finance/feeds/[email protected]/portfolios/1/positions/NYSE:CHN/transactions'/><gf:positionData gainPercentage='0.03348104382' return1w='0.0' return1y='0.0' return3m='0.0' return3y='0.0' return4w='0.0' return5y='0.0' returnOverall='0.0' returnYTD='0.0' shares='244.0'><gf:costBasis><gd:money amount='4955.64' currencyCode='USD'/></gf:costBasis><gf:daysGain><gd:money amount='7.320244' currencyCode='USD'/></gf:daysGain><gf:gain><gd:money amount='165.92' currencyCode='USD'/></gf:gain><gf:marketValue><gd:money amount='5121.56' currencyCode='USD'/></gf:marketValue></gf:positionData><gf:symbol exchange='NYSE' fullName='China Fund Inc. (The)' symbol='CHN'/></entry><entry><id>http://finance.google.com/finance/feeds/[email protected]/portfolios/1/positions/NYSE:FTE</id><updated>2009-06-27T05:40:34.000Z</updated><category scheme='http://schemas.google.com/g/2005#kind' term='http://schemas.google.com/finance/2007#position'/><title type='text'>France Telecom SA (ADR)</title><link rel='self' type='application/atom+xml' href='http://finance.google.com/finance/feeds/default/portfolios/NYSE%3AFTE'/><link rel='edit' type='application/atom+xml' href='http://finance.google.com/finance/feeds/default/portfolios/NYSE%3AFTE'/><gd:feedLink href='http://finance.google.com/finance/feeds/[email protected]/portfolios/1/positions/NYSE:FTE/transactions'/><gf:positionData gainPercentage='0.02424786709' return1w='0.0' return1y='0.0' return3m='0.0' return3y='0.0' return4w='0.0' return5y='0.0' returnOverall='0.0' returnYTD='0.0' shares='420.0'><gf:costBasis><gd:money amount='9353.4' currencyCode='USD'/></gf:costBasis><gf:daysGain><gd:money amount='-42.0' currencyCode='USD'/></gf:daysGain><gf:gain><gd:money amount='226.8' currencyCode='USD'/></gf:gain><gf:marketValue><gd:money amount='9580.2' currencyCode='USD'/></gf:marketValue></gf:positionData><gf:symbol exchange='NYSE' fullName='France Telecom SA (ADR)' symbol='FTE'/></entry><entry><id>http://finance.google.com/finance/feeds/[email protected]/portfolios/1/positions/NYSE:GNK</id><updated>2009-06-27T05:40:34.000Z</updated><category scheme='http://schemas.google.com/g/2005#kind' term='http://schemas.google.com/finance/2007#position'/><title type='text'>Genco Shipping & Trading Limited</title><link rel='self' type='application/atom+xml' href='http://finance.google.com/finance/feeds/default/portfolios/NYSE%3AGNK'/><link rel='edit' type='application/atom+xml' href='http://finance.google.com/finance/feeds/default/portfolios/NYSE%3AGNK'/><gd:feedLink href='http://finance.google.com/finance/feeds/[email protected]/portfolios/1/positions/NYSE:GNK/transactions'/><gf:positionData gainPercentage='0.1024649589' return1w='0.0' return1y='0.0' return3m='0.0' return3y='0.0' return4w='0.0' return5y='0.0' returnOverall='0.0' returnYTD='0.0' shares='10.0'><gf:costBasis><gd:money amount='206.9' currencyCode='USD'/></gf:costBasis><gf:daysGain><gd:money amount='14.69999' currencyCode='USD'/></gf:daysGain><gf:gain><gd:money amount='21.2' currencyCode='USD'/></gf:gain><gf:marketValue><gd:money amount='228.1' currencyCode='USD'/></gf:marketValue></gf:positionData><gf:symbol exchange='NYSE' fullName='Genco Shipping & Trading Limited' symbol='GNK'/></entry></feed></gd:feedLink><gf:portfolioData currencyCode='USD' gainPercentage='0.8135848188' return1w='0.02122168053' return1y='355.1' return3m='355.1' return3y='355.1' return4w='355.1' return5y='355.1' returnOverall='355.1' returnYTD='355.1'><gf:costBasis><gd:money amount='49205.22' currencyCode='USD'/></gf:costBasis><gf:daysGain><gd:money amount='4327.609192' currencyCode='USD'/></gf:daysGain><gf:gain><gd:money amount='40032.62' currencyCode='USD'/></gf:gain><gf:marketValue><gd:money amount='140032.62' currencyCode='USD'/></gf:marketValue></gf:portfolioData></entry></feed>";
PortfolioFeed target = Parse(xml);
for (int i = 0; i < target.Entries.Count; i++)
{
PortfolioEntry portfolioEntry = target.Entries[i] as PortfolioEntry;
Console.WriteLine("Title: " + portfolioEntry.Title.Text);
Console.WriteLine("FeedLink: " + portfolioEntry.FeedLink.ToString());
Console.WriteLine("CurrencyCode: " + portfolioEntry.CurrencyCode);
Console.WriteLine("GainPercentage: " + portfolioEntry.GainPercentage.ToString("0.00000000%"));
Console.WriteLine("Return1Week: " + portfolioEntry.Return1Week.ToString("0.00000000%"));
Console.WriteLine("Return4Week: " + portfolioEntry.Return4Week.ToString("0.00000000%"));
Console.WriteLine("Return3Month: " + portfolioEntry.Return3Month.ToString("0.00000000%"));
Console.WriteLine("ReturnYTD: " + portfolioEntry.ReturnYTD.ToString("0.00000000%"));
Console.WriteLine("Return1Year: " + portfolioEntry.Return1Year.ToString("0.00000000%"));
Console.WriteLine("Return3Year: " + portfolioEntry.Return3Year.ToString("0.00000000%"));
Console.WriteLine("Return5Year: " + portfolioEntry.Return5Year.ToString("0.00000000%"));
Console.WriteLine("ReturnOverall: " + portfolioEntry.ReturnOverall.ToString("0.00000000%"));
CostBasis costBasis = portfolioEntry.CostBasis;
foreach (Money m in costBasis.Money)
{
Console.WriteLine("Money: Amount = " + m.Amount as string);
Console.WriteLine("Money: CurrencyCode = " + m.CurrencyCode);
}
DaysGain daysGain = portfolioEntry.DaysGain;
foreach (Money m in daysGain.Money)
{
Console.WriteLine("Money: Amount = " + m.Amount as string);
Console.WriteLine("Money: CurrencyCode = " + m.CurrencyCode);
}
Gain gain = portfolioEntry.Gain;
foreach (Money m in gain.Money)
{
Console.WriteLine("Money: Amount = " + m.Amount as string);
Console.WriteLine("Money: CurrencyCode = " + m.CurrencyCode);
}
MarketValue marketValue = portfolioEntry.MarketValue;
foreach (Money m in marketValue.Money)
{
Console.WriteLine("Money: Amount = " + m.Amount as string);
Console.WriteLine("Money: CurrencyCode = " + m.CurrencyCode);
}
}
}
/// <summary>
/// Constructs a new Midi Processor.
/// </summary>
/// <param name="plugin">Must not be null.</param>
public MidiProcessor(IVstPluginEvents pluginEvents, PluginParameters parameters)
{
Gain = new Gain(parameters.GainParameters);
Transpose = new Transpose(parameters.TransposeParameters);
// for most hosts, midi output is expected during the audio processing cycle.
SyncWithAudioProcessor = true;
pluginEvents.Opened += Plugin_Opened;
}
public async Task Configure(Gain gain, IntegrationTime time)
{
await ConnectAndInitialize();
_gain = (int)gain;
WriteRegister(Registers.Command | Registers.Oscillator, gain.ToByte());
_integrationTime = (int)time;
WriteRegister(Registers.Command | Registers.Oscillator, time.ToByte());
}
public void GainResourceGroup(Gain gain)
{
foreach (var pair in gain.GainDic)
{
if (BattleRsourceDic.ContainsKey(pair.Key))
{
BattleRsourceDic[pair.Key].GainResource(pair.Value);
}
}
}
private async void setGain(Gain gain)
{
if (!initialized)
{
await begin();
}
this.gain = gain;
byte[] WriteBuffer = new byte[] { TCS34725Params.CONTROL | TCS34725Params.COMMAND_BIT,
(byte)gain };
colorSensor.Write(WriteBuffer);
}
public Luminosity GetLuminosity(Gain gain = Gain.Low, IntegrationTime time = IntegrationTime.MS100)
{
var luminosity = this.GetFullLuminosity(gain, time);
var lux = CalculateLux(luminosity[0], luminosity[1], gain, time);
return(new Luminosity()
{
Visible = luminosity[0], IR = luminosity[1], Lux = lux, Gain = gain
});
}
/// <summary>
/// Computes activation function and its derivative
/// </summary>
/// <param name="n">int</param>
/// <param name="net">double - net</param>
/// <param name="acct">VectorHorizontal - activation matrix</param>
/// <param name="gain">VectorHorizontal - gain matrix</param>
/// <returns>FunctionRD - function result</returns>
/// <remarks>Remember that values are passed by ref to speed up</remarks>
public static FunctionRD computeFunctionDervative(ref int n, ref double net, ref Activation acct, ref Gain gain)
{
FunctionChoice function = (FunctionChoice)(int)acct.Data[0][n];
FunctionRD rd = new FunctionRD();
switch (function)
{
case FunctionChoice.LinearNeuron://for output layer
{
rd.FunctionResult = gain.Data[0][n] * net;
rd.FunctionDerivative = gain.Data[0][n];
}break;
case FunctionChoice.UnipolarNeuron:
{
rd.FunctionResult = 1 / (1 + System.Math.Exp(-gain.Data[0][n] * net));
rd.FunctionDerivative = gain.Data[0][n] * (1 - rd.FunctionResult) * rd.FunctionResult;
}break;
case FunctionChoice.BipolarNeuron://for hidden layer
{
rd.FunctionResult = System.Math.Tanh(gain.Data[0][n] * net);
rd.FunctionDerivative = gain.Data[0][n] * (1 - System.Math.Pow(rd.FunctionResult,2));
}break;
case FunctionChoice.BipolarElliotNeuron:
{
rd.FunctionResult = gain.Data[0][n] * net / (1 + gain.Data[0][n] * System.Math.Abs(net));
rd.FunctionDerivative = 1 / System.Math.Pow((gain.Data[0][n] * System.Math.Abs(net) + 1), 2);
}break;
case FunctionChoice.UnipolarElliotNeuron:
{
rd.FunctionResult = 2 * gain.Data[0][n] * net / (1 + gain.Data[0][n] * System.Math.Abs(net)) - 1;
rd.FunctionDerivative = 2 * gain.Data[0][n] / System.Math.Pow((gain.Data[0][n] * System.Math.Abs(net) + 1), 2);
}break;
default:
{
throw new NeuralNetworkError(Properties.Settings.Default.FE1);
}
}
return rd;
}
/// <summary>
/// Compute psudo hessian matrix and its gradient
/// </summary>
/// <param name="info">NetworkInfo - information about neural network</param>
/// <param name="inp">Input - input data patterns used for learn</param>
/// <param name="dout">Output - output data patterns used for learn</param>
/// <param name="topo">Topography - neural network topography</param>
/// <param name="ww">Weights - weights</param>
/// <param name="act">Activation - activation function selection</param>
/// <param name="gain">Gain - neuron gain</param>
/// <param name="iw">Index - topography indexes</param>
public void Compute(ref NetworkInfo info, ref Input inp, ref Output dout, ref Topography topo,
Weights ww, ref Activation act, ref Gain gain, ref Index iw)
{
GradientMat = MatrixMB.Zeros(info.nw, 1);
HessianMat = MatrixMB.Zeros(info.nw, info.nw);
np = info.np;//number of patterns
ni = info.ni;//number of inputs
no = info.no;//number of outputs
nw = info.nw;//number of weights
nn = info.nn;//number of neurons
nio = nn + ni - no;
zeros = ni.Zeros();
delo = MatrixMB.Zeros(1, nio + 1);
J = MatrixMB.Zeros(1, nw);
for (p = 0; p < np; p++)
{
node.Clear();
node.AddRange(inp.Data[p]);
CalculateFunctionValuesAndDerivates(ref ww, ref iw, ref topo, ref act, ref gain);
for (k = 0; k < no; k++)
{
o = nio + k;
error = dout.Data[p][k] - node[o];
J.ClearWithZeros();
s = iw.Pos(o - ni);
J.Data[0][s] = -derivates[o];
delo.ClearWithZeros();
CalculateJacobian(ref ww, ref iw, ref topo);
CalculateForHiddenLayer(ref iw, ref topo, ref ww);
if (dout[p, 0] > 0.5) J = J * ratio;
var JT = J.Transposed;
GradientMat = GradientMat + JT * error;
HessianMat = HessianMat + JT * J;
}
}
}
/// <summary>
/// Computes activation function
/// </summary>
/// <param name="n">int</param>
/// <param name="net">double - net</param>
/// <param name="acct">VectorHorizontal - activation matrix</param>
/// <param name="gain">VectorHorizontal - gain matrix</param>
/// <returns>double - function result</returns>
/// <remarks>Remember that values are passed by ref to speed up</remarks>
public static double computeFunction(ref int n,ref double net, ref Activation acct, ref Gain gain)
{
try
{
FunctionChoice function = (FunctionChoice)(int)acct.Data[0][n];
switch (function)
{
case FunctionChoice.LinearNeuron:
{
return gain.Data[0][n] * net;
}
case FunctionChoice.UnipolarNeuron:
{
return 1 / (1 + System.Math.Exp(-gain.Data[0][n] * net));
}
case FunctionChoice.BipolarNeuron:
{
return System.Math.Tanh(gain.Data[0][n] * net);
}
case FunctionChoice.BipolarElliotNeuron:
{
return gain.Data[0][n] * net / (1 + gain.Data[0][n] * System.Math.Abs(net));
}
case FunctionChoice.UnipolarElliotNeuron:
{
return 2 * gain.Data[0][n] * net / (1 + gain.Data[0][n] * System.Math.Abs(net)) - 1;
}
default:
{
throw new System.Exception(Properties.Settings.Default.FE1);
}
}
}
catch (System.Exception ex)
{
throw new NeuralNetworkError("Błąd obliczania funkcji aktywacji.", ex);
}
}
/// <summary>
/// Total error calculation
/// </summary>
/// <param name="info">NetworkInfo</param>
/// <param name="inp">ref Input - input data patterns</param>
/// <param name="dout">ref Output - output data</param>
/// <param name="topo">ref Topography - topo is network topology in the form of one vector</param>
/// <param name="ww">ref Weights weights</param>
/// <param name="act">ref Activation - type of activation function</param>
/// <param name="gain">ref Gain - strengthening the activation function</param>
/// <param name="iw">ref WeightsPointers - index pointers used for network topology stored in top in the form of one vector</param>
/// <remarks>Network error will be overriden so please save it</remarks>
public double CalculateError(ref NetworkInfo info, ref Input inp, ref Output dout, ref Topography topo,
Weights ww, ref Activation act, ref Gain gain, ref Index iw)
{
try
{
Error = 0;
for (p = 0; p < info.np; p++)
{
node.Clear();
node.AddRange(inp.Data[p]);
for (n = 0; n < info.nn; n++)
{
net = ww[iw.Pos(n)];
int from = iw.Pos(n) + 1;
int to = iw.Pos(n + 1) - 1;
for (i = from; i <= to; i++)
{
net += node[(int)topo[i]] * ww[i];
}
node.Add(ActivationFunction.computeFunction(ref n, ref net, ref act, ref gain));
}
for (k = 0; k < info.no; k++)
{
Error += System.Math.Pow((dout.Data[p][k] - node[info.nio + k]), 2);
}
}
return Error;
}
catch (System.Exception ex)
{
throw new NeuralNetworkError("Błąd uaktualnienia błędu sieci neuronowej. " + ex.Message, ex);
}
}
private bool m_CameraChangingHeight; // is camera height changing?
void Start()
{
if (!Terrain1 || !Terrain2)
{
Debug.LogError("Terrains not set!!");
enabled = false;
}
// desert dune-like ridges are created using RidgeNoise. it is scaled down a bit, and Gain applied to make ridges more pronounced
var desert = new Gain(
new RidgeNoise(23478568)
{
OctaveCount = 8
} * 0.6f, 0.4f);
// hills use a simple pink noise.
var hills = new PinkNoise(3465478)
{
OctaveCount = 5, // smooth hills (no higher frequencies)
Persistence = 0.56f // but steep (changes rapidly in the frequencies we do have)
};
// weight decides, whether a given point is hills or desert
// cached, as we'd need it to decide texture at every point
m_Weight = new Cache(new PinkNoise(346546)
{
Frequency = 0.5f,
OctaveCount = 3
}.ScaleShift(0.5f, 0.5f));
// overall heightmap blends hills and deserts
m_Generator = desert.Blend(hills, m_Weight).ScaleShift(0.5f, 0.5f);
// as changes to terrains made in playmode get saved in the editor, we need to re-generate terrains
// at start. The coroutine will set m_Move in the end, so that camera does not fly intil it's ready
#if UNITY_EDITOR
StartCoroutine(CreateMapsAtStart());
#else
m_NoiseCoord=1;
m_Move=true;
#endif
}
private void RumasterSetCarrierConfig(string cpriport, string flowdirection, string carriernumber, string enabled, string carrierid, string technology, string frequency, string axccontainer, string gain, string fsinfo,string axcContainerGroupLength,string bfPeriod,string syncmode)
{
try
{
FsInfo fsinfoData = new FsInfo();
string[] fsinfostr = fsinfo.Split(SPACER_FLAG_SEC);
if (fsinfostr.Length >= 4)
{
fsinfoData.Addr = byte.Parse(fsinfostr[0]);
fsinfoData.Hf = byte.Parse(fsinfostr[1]);
fsinfoData.Bf = byte.Parse(fsinfostr[2]);
fsinfoData.BfOffset = byte.Parse(fsinfostr[3]);
}
Gain gainData = new Gain();
string[] gainstr = gain.Split(SPACER_FLAG_SEC);
if (fsinfostr.Length >= 3)
{
gainData.GainEnable = boolDic[gainstr[0]];
gainData.GainDb = double.Parse(gainstr[1]);
gainData.GainFact = double.Parse(gainstr[2]);
}
CarrierData data = new CarrierData();
data.axcContainerGroupLength = byte.Parse(axcContainerGroupLength);
data.bfPeriod = byte.Parse(bfPeriod);
data.carrierId = byte.Parse(carrierid);
data.carrierNumber = byte.Parse(carriernumber);
data.enabled = boolDic[enabled];
data.sampleFrequency = freqDic[frequency];
data.technology = technologyDic[technology];
data.startAxcContainer = byte.Parse(axccontainer);
data.syncMode = syncModeDic[syncmode];
data.fsInfo = fsinfoData;
data.gain = gainData;
rCarrierConfig.SetCarrierConfig(cpriport, flowDirectionDic[flowdirection], data);
showCarrierData(data);
}
catch (Exception e)
{
WriteTraceText("Rumaster Set Carrier Config failed!--" + e.Message);
}
}
/// <summary>
/// Sets the sensor gain value.
/// </summary>
/// <param name="gain">Gain value.</param>
public void SetGain(Gain gain)
{
Write(Register.CRB, (byte)gain);
}
public ADS1015(Gain refVoltage = Gain.Volt33)
{
this.gain = refVoltage;
}
public static extern void SetGain(IntPtr config, Gain gain);
/// <summary>
/// Puts the sensor into initial state.
/// </summary>
/// <param name="gainLevel">Gain level configuration.</param>
public void Init(Gain gainLevel = Gain.Level6)
{
bus.Write(0x01, (byte)((byte)gainLevel << 5));
}
private void CalculateFunctionValuesAndDerivates(ref Weights ww, ref Index iw, ref Topography topo, ref Activation act, ref Gain gain)
{
derivates.Clear();
derivates.AddRange(node.Count.Zeros());
for (int n = 0; n < nn; n++)//for each neuron in network
{
net = ww[iw[n]];//calculate net sum
for (i = iw[n] + 1; i <= iw[n + 1] - 1; i++)
{
net += (node[topo[i]] * ww[i]);
}
var res = ActivationFunction.computeFunctionDervative(ref n, ref net, ref act, ref gain);//and function value and its derivative
node.Add(res.FunctionResult);//save function value for output signal from neuron
derivates.Add(res.FunctionDerivative);//save function derivative value for output signal from neuron
}
}
