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Miha Kralj
2026-02-02 13:42:47 -08:00
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lib/numerics/_index.md
+15 -29
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@@ -6,32 +6,18 @@ Basic mathematical transforms and utility functions for time series. These build
| Indicator | Full Name | Description |
| :--- | :--- | :--- |
| [ACCEL](lib/numerics/accel/Accel.md) | Acceleration | Momentum change; second derivative of price. |
| [CHANGE](lib/numerics/change/Change.md) | Percentage Change | Relative price movement over lookback period. |
| [EXPTRANS](lib/numerics/exptrans/Exptrans.md) | Exponential Transform | e^x transform for log-space conversion reversal. |
| [HIGHEST](lib/numerics/highest/Highest.md) | Rolling Maximum | Maximum value over lookback window. |
| [JERK](lib/numerics/jerk/Jerk.md) | Jerk | Rate of acceleration; third derivative of price. |
| [LINEARTRANS](lib/numerics/lineartrans/Lineartrans.md) | Linear Transform | y = ax + b scaling transformation. |
| [LOGTRANS](lib/numerics/logtrans/Logtrans.md) | Logarithmic Transform | Natural log for percentage-based analysis. |
| [LOWEST](lib/numerics/lowest/Lowest.md) | Rolling Minimum | Minimum value over lookback window. |
| [MIDPOINT](lib/numerics/midpoint/Midpoint.md) | Midrange | (Highest + Lowest) / 2 over lookback window. |
| [NORMALIZE](lib/numerics/normalize/Normalize.md) | Min-Max Normalization | Scale to [0,1] range using rolling min/max. |
| [RELU](lib/numerics/relu/Relu.md) | Rectified Linear Unit | max(0, x); neural network activation function. |
| [SIGMOID](lib/numerics/sigmoid/Sigmoid.md) | Logistic Function | 1/(1+e^-x); bounded [0,1] transform. |
| [SLOPE](lib/numerics/slope/Slope.md) | Rate of Change | First derivative; velocity of price movement. |
| [SQRTTRANS](lib/numerics/sqrttrans/Sqrttrans.md) | Square Root Transform | Variance-stabilizing transformation. |
| STANDARDIZE | Z-Score Normalization | (x - mean) / stddev; zero-mean unit-variance transform. |
| BETADIST | Beta Distribution | Continuous probability distribution defined on interval [0, 1]. |
| BINOMDIST | Binomial Distribution | Discrete probability distribution of successes in n independent trials. |
| CWT | Continuous Wavelet Transform | Analyzes time series data across different frequency scales continuously. |
| DWT | Discrete Wavelet Transform | Analyzes time series data across different frequency scales at discrete intervals. |
| EXPDIST | Exponential Distribution | Continuous probability distribution describing time between events. |
| FDIST | F-Distribution | Continuous probability distribution ratio of two chi-squared distributions. |
| FFT | Fast Fourier Transform | Efficient algorithm for computing the discrete Fourier transform and its inverse. |
| GAMMADIST | Gamma Distribution | Continuous probability distribution generalizing exponential and chi-squared. |
| IFFT | Inverse Fast Fourier Transform | Efficient algorithm for computing the inverse discrete Fourier transform. |
| LOGNORMDIST | Log-normal Distribution | Continuous probability distribution of a variable whose log is normally distributed. |
| NORMDIST | Normal Distribution | Gaussian bell-shaped probability distribution. |
| POISSONDIST | Poisson Distribution | Discrete probability distribution expressing events in fixed time interval. |
| TDIST | Student's t-Distribution | Continuous probability distribution when estimating mean of normally distributed population. |
| WEIBULLDIST | Weibull Distribution | Continuous probability distribution useful in reliability and survival analysis. |
| [ACCEL](/lib/numerics/accel/Accel.md) | Acceleration | Momentum change; second derivative of price. |
| [CHANGE](/lib/numerics/change/Change.md) | Percentage Change | Relative price movement over lookback period. |
| [EXPTRANS](/lib/numerics/exptrans/Exptrans.md) | Exponential Transform | e^x transform for log-space conversion reversal. |
| [HIGHEST](/lib/numerics/highest/Highest.md) | Rolling Maximum | Maximum value over lookback window. |
| [JERK](/lib/numerics/jerk/Jerk.md) | Jerk | Rate of acceleration; third derivative of price. |
| [LINEARTRANS](/lib/numerics/lineartrans/Lineartrans.md) | Linear Transform | y = ax + b scaling transformation. |
| [LOGTRANS](/lib/numerics/logtrans/Logtrans.md) | Logarithmic Transform | Natural log for percentage-based analysis. |
| [LOWEST](/lib/numerics/lowest/Lowest.md) | Rolling Minimum | Minimum value over lookback window. |
| [MIDPOINT](/lib/numerics/midpoint/Midpoint.md) | Midrange | (Highest + Lowest) / 2 over lookback window. |
| [NORMALIZE](/lib/numerics/normalize/Normalize.md) | Min-Max Normalization | Scale to [0,1] range using rolling min/max. |
| [RELU](/lib/numerics/relu/Relu.md) | Rectified Linear Unit | max(0, x); neural network activation function. |
| [SIGMOID](/lib/numerics/sigmoid/Sigmoid.md) | Logistic Function | 1/(1+e^-x); bounded [0,1] transform. |
| [SLOPE](/lib/numerics/slope/Slope.md) | Rate of Change | First derivative; velocity of price movement. |
| [SQRTTRANS](/lib/numerics/sqrttrans/Sqrttrans.md) | Square Root Transform | Variance-stabilizing transformation. |
| [STANDARDIZE](/lib/numerics/standardize/Standardize.md) | Z-Score Normalization | (x - mean) / stddev; zero-mean unit-variance transform. |
lib/numerics/change/Change.cs
+2 -2
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@@ -82,7 +82,7 @@ public sealed class Change : AbstractBase
else
{
double past = _buffer[0];
result = past != 0.0 ? (value - past) / past : 0.0;
result = Math.Abs(past) > 0 ? (value - past) / past : 0.0;
}
Last = new TValue(input.Time, result);
@@ -187,7 +187,7 @@ public sealed class Change : AbstractBase
past = pastValidBuffer[bufferIdx];
}
output[i] = past != 0.0 ? (current - past) / past : 0.0;
output[i] = Math.Abs(past) > 0 ? (current - past) / past : 0.0;
// Update circular buffer with current valid value for future past lookups
pastValidBuffer[bufferIdx] = current;