signalflow-ta 0.3.6

Technical analysis extension for signalflow-trading.

signalflow-ta

Technical analysis extension for signalflow-trading.

The library provides 166 technical analysis indicators organized into 8 modules: momentum, overlap, volatility, volume, trend, stat, performance, divergence. Each indicator is implemented as a standalone signalflow component class with warmup property support and (where applicable) output value normalization. Additionally, AutoFeatureNormalizer is provided for automatic normalization of Polars DataFrames.

Installation

pip install signalflow-ta

Requirements

• Python >= 3.12
• signalflow-trading >= 0.3.3
• pandas-ta >= 0.4.67b0

Usage

import signalflow.ta as ta

Features

Momentum (18 indicators)

Class	SF Name	Description	Source	Parameters
RsiMom	momentum/rsi	Relative Strength Index	core.py	["period", "normalized"]
RocMom	momentum/roc	Rate of Change	core.py	["period", "normalized", "norm_period"]
MomMom	momentum/mom	Momentum (price difference)	core.py	["period", "normalized", "norm_period"]
CmoMom	momentum/cmo	Chande Momentum Oscillator	core.py	["period", "normalized"]
StochMom	momentum/stoch	Stochastic Oscillator	oscillators.py	["k_period", "d_period", "smooth_k", "normalized"]
StochRsiMom	momentum/stochrsi	Stochastic RSI	oscillators.py	["rsi_period", "stoch_period", "k_period", "d_period", "normalized"]
WillrMom	momentum/willr	Williams %R	oscillators.py	["period", "normalized"]
CciMom	momentum/cci	Commodity Channel Index	oscillators.py	["period", "constant", "normalized", "norm_period"]
UoMom	momentum/uo	Ultimate Oscillator	oscillators.py	["fast", "medium", "slow", "fast_weight", "medium_weight", "slow_weight", "normalized"]
AoMom	momentum/ao	Awesome Oscillator	oscillators.py	["fast", "slow", "normalized", "norm_period"]
MacdMom	momentum/macd	Moving Average Convergence Divergence	macd.py	["fast", "slow", "signal", "normalized", "norm_period"]
PpoMom	momentum/ppo	Percentage Price Oscillator	macd.py	["fast", "slow", "signal", "normalized", "norm_period"]
TsiMom	momentum/tsi	True Strength Index	macd.py	["fast", "slow", "signal", "normalized", "norm_period"]
TrixMom	momentum/trix	Triple Exponential Average ROC	macd.py	["period", "signal", "normalized", "norm_period"]
AccelerationMom	momentum/acceleration	Price Acceleration (2nd derivative of log-returns)	kinematics.py	["source_col", "lag", "smooth", "normalized", "norm_period"]
JerkMom	momentum/jerk	Price Jerk (3rd derivative of log-returns)	kinematics.py	["source_col", "lag", "smooth", "normalized", "norm_period"]
AngularMomentumMom	momentum/angular_momentum	Angular Momentum (L = displacement x velocity)	kinematics.py	["source_col", "period", "ma_period", "normalized", "norm_period"]
TorqueMom	momentum/torque	Torque (rate of change of angular momentum)	kinematics.py	["source_col", "period", "ma_period", "torque_lag", "normalized", "norm_period"]

Overlap / Smoothing (25 indicators)

Class	SF Name	Description	Source	Parameters
SmaSmooth	smooth/sma	Simple Moving Average	smoothers.py	["source_col", "period", "normalized"]
EmaSmooth	smooth/ema	Exponential Moving Average	smoothers.py	["source_col", "period", "normalized"]
WmaSmooth	smooth/wma	Weighted Moving Average	smoothers.py	["source_col", "period", "normalized"]
RmaSmooth	smooth/rma	Wilder's Smoothed Moving Average	smoothers.py	["source_col", "period", "normalized"]
DemaSmooth	smooth/dema	Double Exponential Moving Average	smoothers.py	["source_col", "period", "normalized"]
TemaSmooth	smooth/tema	Triple Exponential Moving Average	smoothers.py	["source_col", "period", "normalized"]
HmaSmooth	smooth/hma	Hull Moving Average	smoothers.py	["source_col", "period", "normalized"]
TrimaSmooth	smooth/trima	Triangular Moving Average	smoothers.py	["source_col", "period", "normalized"]
SwmaSmooth	smooth/swma	Symmetric Weighted Moving Average	smoothers.py	["source_col", "period", "normalized"]
SsfSmooth	smooth/ssf	Ehlers Super Smoother Filter	smoothers.py	["source_col", "period", "poles", "normalized"]
KamaSmooth	smooth/kama	Kaufman Adaptive Moving Average	adaptive.py	["source_col", "period", "fast", "slow", "normalized"]
AlmaSmooth	smooth/alma	Arnaud Legoux Moving Average	adaptive.py	["source_col", "period", "offset", "sigma", "normalized"]
JmaSmooth	smooth/jma	Jurik Moving Average	adaptive.py	["source_col", "period", "phase", "normalized"]
VidyaSmooth	smooth/vidya	Variable Index Dynamic Average	adaptive.py	["source_col", "period", "normalized"]
T3Smooth	smooth/t3	Tillson T3	adaptive.py	["source_col", "period", "vfactor", "normalized"]
ZlmaSmooth	smooth/zlma	Zero Lag Moving Average	adaptive.py	["source_col", "period", "ma_type", "normalized"]
McGinleySmooth	smooth/mcginley	McGinley Dynamic	adaptive.py	["source_col", "period", "k", "normalized"]
FramaSmooth	smooth/frama	Fractal Adaptive Moving Average	adaptive.py	["source_col", "period", "normalized"]
Hl2Price	price/hl2	High-Low Midpoint	price.py	[]
Hlc3Price	price/hlc3	Typical Price (HLC/3)	price.py	[]
Ohlc4Price	price/ohlc4	OHLC Average	price.py	[]
WcpPrice	price/wcp	Weighted Close Price	price.py	[]
TypicalPrice	price/typical	Configurable Weighted Price	price.py	["weight_high", "weight_low", "weight_close"]
MidpointPrice	price/midpoint	Rolling Midpoint	price.py	["source_col", "period"]
MidpricePrice	price/midprice	Donchian Channel Midline	price.py	["period"]

Volatility (19 indicators)

Class	SF Name	Description	Source	Parameters
TrueRangeVol	volatility/true_range	True Range	range.py	[]
AtrVol	volatility/atr	Average True Range	range.py	["period", "ma_type"]
NatrVol	volatility/natr	Normalized ATR (% of price)	range.py	["period", "ma_type"]
BollingerVol	volatility/bollinger	Bollinger Bands	bands.py	["period", "std_dev", "ma_type", "normalized", "norm_period"]
KeltnerVol	volatility/keltner	Keltner Channels	bands.py	["period", "multiplier", "ma_type", "use_true_range", "normalized", "norm_period"]
DonchianVol	volatility/donchian	Donchian Channels	bands.py	["period", "normalized", "norm_period"]
AccBandsVol	volatility/accbands	Acceleration Bands	bands.py	["period", "normalized", "norm_period"]
MassIndexVol	volatility/mass_index	Mass Index	measures.py	["fast", "slow"]
UlcerIndexVol	volatility/ulcer_index	Ulcer Index (downside volatility)	measures.py	["period"]
RviVol	volatility/rvi	Relative Volatility Index	measures.py	["period", "std_period"]
GapVol	volatility/gaps	Gap Volatility	gaps.py	["period", "normalized", "norm_period"]
KineticEnergyVol	volatility/kinetic_energy	Kinetic Energy (KE = 1/2 v^2)	energy.py	["period", "normalized", "norm_period"]
PotentialEnergyVol	volatility/potential_energy	Potential Energy (displacement from MA)	energy.py	["period", "ma_period", "normalized", "norm_period"]
TotalEnergyVol	volatility/total_energy	Total Mechanical Energy (KE + PE)	energy.py	["period", "ma_period", "normalized", "norm_period"]
EnergyFlowVol	volatility/energy_flow	Energy Flow Rate (dE/dt)	energy.py	["period", "ma_period", "flow_lag", "normalized", "norm_period"]
ElasticStrainVol	volatility/elastic_strain	Elastic Strain (relative displacement from equilibrium)	energy.py	["period", "ma_period", "normalized", "norm_period"]
TemperatureVol	volatility/temperature	Market Temperature (kinetic energy per DOF)	energy.py	["period", "normalized", "norm_period"]
HeatCapacityVol	volatility/heat_capacity	Heat Capacity (resistance to temperature change)	energy.py	["period", "lag", "normalized", "norm_period"]
FreeEnergyVol	volatility/free_energy	Helmholtz Free Energy (E - T*S)	energy.py	["period", "entropy_bins", "normalized", "norm_period"]

Volume (16 indicators)

Class	SF Name	Description	Source	Parameters
ObvVolume	volume/obv	On Balance Volume	cumulative.py	["period", "normalized", "norm_period"]
AdVolume	volume/ad	Accumulation/Distribution Line	cumulative.py	["period", "normalized", "norm_period"]
PvtVolume	volume/pvt	Price Volume Trend	cumulative.py	["period", "normalized", "norm_period"]
NviVolume	volume/nvi	Negative Volume Index	cumulative.py	["period", "normalized", "norm_period"]
PviVolume	volume/pvi	Positive Volume Index	cumulative.py	["period", "normalized", "norm_period"]
MfiVolume	volume/mfi	Money Flow Index	oscillators.py	["period", "normalized"]
CmfVolume	volume/cmf	Chaikin Money Flow	oscillators.py	["period", "normalized", "norm_period"]
EfiVolume	volume/efi	Elder Force Index	oscillators.py	["period", "normalized", "norm_period"]
EomVolume	volume/eom	Ease of Movement	oscillators.py	["period", "scale", "normalized", "norm_period"]
KvoVolume	volume/kvo	Klinger Volume Oscillator	oscillators.py	["fast", "slow", "signal", "normalized", "norm_period"]
MarketForceVolume	volume/market_force	Market Force (F = m * a)	dynamics.py	["period", "normalized", "norm_period"]
ImpulseVolume	volume/impulse	Market Impulse (J = sum F * dt)	dynamics.py	["period", "normalized", "norm_period"]
MarketMomentumVolume	volume/market_momentum	Market Momentum (p = m * v)	dynamics.py	["period", "normalized", "norm_period"]
MarketPowerVolume	volume/market_power	Market Power (P = F * v)	dynamics.py	["period", "normalized", "norm_period"]
MarketCapacitanceVolume	volume/market_capacitance	Market Capacitance (volume absorbed per unit price change)	dynamics.py	["period", "normalized", "norm_period"]
GravitationalPullVolume	volume/gravitational_pull	Gravitational Pull (volume-weighted attraction)	dynamics.py	["period", "normalized", "norm_period"]

Trend (22 indicators)

Class	SF Name	Description	Source	Parameters
AdxTrend	trend/adx	Average Directional Index	strength.py	["period", "normalized"]
AroonTrend	trend/aroon	Aroon Indicator	strength.py	["period", "normalized"]
VortexTrend	trend/vortex	Vortex Indicator	strength.py	["period", "normalized"]
VhfTrend	trend/vhf	Vertical Horizontal Filter	strength.py	["period", "normalized"]
ChopTrend	trend/chop	Choppiness Index	strength.py	["period", "normalized"]
ViscosityTrend	trend/viscosity	Viscosity (resistance to velocity change)	physics.py	["period", "normalized", "norm_period"]
ReynoldsTrend	trend/reynolds	Reynolds Number (laminar vs turbulent regime)	physics.py	["period", "normalized", "norm_period"]
RotationalInertiaTrend	trend/rotational_inertia	Rotational Inertia (resistance to trend change)	physics.py	["period", "normalized", "norm_period"]
MarketImpedanceTrend	trend/market_impedance	Market Impedance (Z = V/I analogy)	physics.py	["period", "normalized", "norm_period"]
RCTimeConstantTrend	trend/rc_time_constant	RC Time Constant (circuit analogue)	physics.py	["period", "normalized", "norm_period"]
SNRTrend	trend/snr	Signal-to-Noise Ratio	physics.py	["period", "normalized", "norm_period"]
OrderParameterTrend	trend/order_parameter	Order Parameter (phase transition)	physics.py	["period", "normalized", "norm_period"]
SusceptibilityTrend	trend/susceptibility	Susceptibility (response to changes)	physics.py	["period", "normalized", "norm_period"]
PsarTrend	trend/psar	Parabolic SAR	stops.py	["iaf", "maxaf"]
SupertrendTrend	trend/supertrend	Supertrend	stops.py	["period", "multiplier", "normalized", "norm_period"]
ChandelierTrend	trend/chandelier	Chandelier Stop	stops.py	["period", "atr_period", "multiplier"]
HiloTrend	trend/hilo	HiLo Channel	stops.py	["period", "normalized", "norm_period"]
CkspTrend	trend/cksp	Coppock Curve	stops.py	["roc_period", "ema_period", "normalized", "norm_period"]
IchimokuTrend	trend/ichimoku	Ichimoku Kinko Hyo	detection.py	["tenkan", "kijun", "senkou", "normalized", "norm_period"]
DpoTrend	trend/dpo	Detrended Price Oscillator	detection.py	["period", "normalized", "norm_period"]
QstickTrend	trend/qstick	Qstick	detection.py	["period", "normalized", "norm_period"]
TtmTrend	trend/ttm	TTM Trend	detection.py	["length", "normalized", "norm_period"]

Statistics (62 indicators)

Class	SF Name	Description	Source	Parameters
VarianceStat	stat/variance	Rolling Variance	dispersion.py	["source_col", "period", "ddof"]
StdStat	stat/std	Rolling Standard Deviation	dispersion.py	["source_col", "period", "ddof"]
MadStat	stat/mad	Mean Absolute Deviation	dispersion.py	["source_col", "period"]
ZscoreStat	stat/zscore	Z-Score	dispersion.py	["source_col", "period"]
CvStat	stat/cv	Coefficient of Variation	dispersion.py	["source_col", "period"]
RangeStat	stat/range	Range (max - min)	dispersion.py	["source_col", "period"]
IqrStat	stat/iqr	Interquartile Range	dispersion.py	["source_col", "period"]
AadStat	stat/aad	Average Absolute Deviation	dispersion.py	["source_col", "period"]
RobustZscoreStat	stat/robust_zscore	Robust Z-Score (via MAD)	dispersion.py	["source_col", "period"]
MedianStat	stat/median	Rolling Median	distribution.py	["source_col", "period"]
QuantileStat	stat/quantile	Quantile	distribution.py	["source_col", "period", "quantile"]
PctRankStat	stat/pct_rank	Percentile Rank	distribution.py	["source_col", "period"]
MinMaxStat	stat/minmax	Min-Max Scaler	distribution.py	["source_col", "period"]
SkewStat	stat/skew	Skewness	distribution.py	["source_col", "period"]
KurtosisStat	stat/kurtosis	Kurtosis	distribution.py	["source_col", "period"]
EntropyStat	stat/entropy	Entropy	distribution.py	["source_col", "period", "bins"]
JarqueBeraStat	stat/jarque_bera	Jarque-Bera Test	distribution.py	["source_col", "period"]
ModeDistanceStat	stat/mode_distance	Distance to Mode	distribution.py	["source_col", "period"]
AboveMeanRatioStat	stat/above_mean_ratio	Ratio of Values Above Mean	distribution.py	["source_col", "period"]
EntropyRateStat	stat/entropy_rate	Entropy Rate (speed of information change)	distribution.py	["source_col", "period", "lag", "base", "normalized", "norm_period"]
HurstStat	stat/hurst	Hurst Exponent	memory.py	["source_col", "period", "min_lag"]
AutocorrStat	stat/autocorr	Autocorrelation	memory.py	["source_col", "period", "lag"]
VarianceRatioStat	stat/variance_ratio	Variance Ratio	memory.py	["source_col", "period", "lag"]
DiffusionCoeffStat	stat/diffusion_coeff	Diffusion Coefficient (D = Var / 2dt)	memory.py	["source_col", "period", "normalized", "norm_period"]
AnomalousDiffusionStat	stat/anomalous_diffusion	Anomalous Diffusion Exponent	memory.py	["source_col", "period", "tau_short", "tau_long", "normalized", "norm_period"]
MsdRatioStat	stat/msd_ratio	Mean Squared Displacement Ratio	memory.py	["source_col", "period", "tau", "normalized", "norm_period"]
SpringConstantStat	stat/spring_constant	Spring Constant (mean-reversion strength)	memory.py	["source_col", "period", "ma_period", "normalized", "norm_period"]
DampingRatioStat	stat/damping_ratio	Damping Ratio (oscillation decay)	memory.py	["source_col", "period", "ma_period", "normalized", "norm_period"]
NaturalFrequencyStat	stat/natural_frequency	Natural Frequency (dominant oscillation)	memory.py	["source_col", "period", "ma_period", "normalized", "norm_period"]
PlasticStrainStat	stat/plastic_strain	Plastic Strain (non-reversible deformation ratio)	memory.py	["source_col", "period", "ma_period", "normalized", "norm_period"]
EscapeVelocityStat	stat/escape_velocity	Escape Velocity (velocity to break from MA)	memory.py	["source_col", "period", "ma_period", "normalized", "norm_period"]
CorrelationLengthStat	stat/correlation_length	Correlation Length (autocorrelation zero-crossing)	memory.py	["source_col", "period", "max_lag", "normalized", "norm_period"]
InstAmplitudeStat	stat/inst_amplitude	Instantaneous Amplitude (Hilbert transform)	cycle.py	["source_col", "period", "normalized", "norm_period"]
InstPhaseStat	stat/inst_phase	Instantaneous Phase (Hilbert transform)	cycle.py	["source_col", "period", "normalized"]
InstFrequencyStat	stat/inst_frequency	Instantaneous Frequency (Hilbert transform)	cycle.py	["source_col", "period", "normalized", "norm_period"]
PhaseAccelerationStat	stat/phase_acceleration	Phase Acceleration (2nd derivative of phase)	cycle.py	["source_col", "period", "normalized", "norm_period"]
ConstructiveInterferenceStat	stat/constructive_interference	Constructive Interference (phase-aligned amplitude)	cycle.py	["source_col", "fast_period", "slow_period", "smooth", "normalized", "norm_period"]
BeatFrequencyStat	stat/beat_frequency	Beat Frequency (two-oscillator difference)	cycle.py	["source_col", "fast_period", "slow_period", "normalized", "norm_period"]
StandingWaveRatioStat	stat/standing_wave_ratio	Standing Wave Ratio (market resonance)	cycle.py	["source_col", "period", "swr_window", "normalized", "norm_period"]
SpectralCentroidStat	stat/spectral_centroid	Spectral Centroid (frequency center of mass)	cycle.py	["source_col", "period", "normalized", "norm_period"]
SpectralEntropyStat	stat/spectral_entropy	Spectral Entropy (frequency distribution disorder)	cycle.py	["source_col", "period", "normalized"]
CorrelationStat	stat/correlation	Correlation	regression.py	["col1", "col2", "period"]
BetaStat	stat/beta	Beta Coefficient	regression.py	["col1", "col2", "period"]
RSquaredStat	stat/rsquared	R-Squared	regression.py	["col1", "col2", "period"]
LinRegSlopeStat	stat/linreg_slope	Linear Regression Slope	regression.py	["source_col", "period"]
LinRegInterceptStat	stat/linreg_intercept	Linear Regression Intercept	regression.py	["source_col", "period"]
LinRegResidualStat	stat/linreg_residual	Linear Regression Residual	regression.py	["source_col", "period"]
RealizedVolStat	stat/realized_vol	Realized Volatility	realized.py	["source_col", "period"]
ParkinsonVolStat	stat/parkinson_vol	Parkinson Volatility	realized.py	["period"]
GarmanKlassVolStat	stat/garman_klass_vol	Garman-Klass Volatility	realized.py	["period"]
RogersSatchellVolStat	stat/rogers_satchell_vol	Rogers-Satchell Volatility	realized.py	["period"]
YangZhangVolStat	stat/yang_zhang_vol	Yang-Zhang Volatility	realized.py	["period"]
PermutationEntropyStat	stat/permutation_entropy	Permutation Entropy (ordinal pattern complexity)	complexity.py	["source_col", "period", "m", "normalized", "norm_period"]
SampleEntropyStat	stat/sample_entropy	Sample Entropy (regularity / self-similarity)	complexity.py	["source_col", "period", "m", "r_mult", "normalized", "norm_period"]
LempelZivStat	stat/lempel_ziv	Lempel-Ziv Complexity (compressibility)	complexity.py	["source_col", "period", "normalized", "norm_period"]
FisherInformationStat	stat/fisher_information	Fisher Information (distribution sharpness)	complexity.py	["source_col", "period", "bins", "normalized", "norm_period"]
DfaExponentStat	stat/dfa	DFA Exponent (detrended long-range correlations)	complexity.py	["source_col", "period", "min_box", "normalized", "norm_period"]
KLDivergenceStat	stat/kl_divergence	KL Divergence (regime deviation from baseline)	information.py	["source_col", "period", "short_period", "bins", "normalized", "norm_period"]
JSDivergenceStat	stat/js_divergence	Jensen-Shannon Divergence (symmetric regime change)	information.py	["source_col", "period", "short_period", "bins", "normalized", "norm_period"]
RenyiEntropyStat	stat/renyi_entropy	Rényi Entropy (generalized tail-sensitive entropy)	information.py	["source_col", "period", "alpha", "bins", "normalized", "norm_period"]
AutoMutualInfoStat	stat/auto_mutual_info	Auto Mutual Information (nonlinear temporal dependency)	information.py	["source_col", "period", "lag", "bins", "normalized", "norm_period"]
RelativeInfoGainStat	stat/info_gain	Relative Information Gain (distributional change rate)	information.py	["source_col", "period", "bins", "normalized", "norm_period"]

Performance (2 indicators)

Class	SF Name	Description	Source	Parameters
LogReturn	perf/log_ret	Logarithmic Returns	returns.py	["source", "period"]
PctReturn	perf/pct_ret	Percentage Returns	returns.py	["source", "period"]

Divergence (2 indicators)

Class	SF Name	Description	Source	Parameters
RsiDivergence	divergence/rsi	RSI Divergence Detector (regular & hidden)	rsi_div.py	["rsi_period", "rsi_overbought", "rsi_oversold", "pivot_window", "min_pivot_distance", "lookback", "min_divergence_magnitude"]
MacdDivergence	divergence/macd	MACD Divergence Detector (regular & hidden)	macd_div.py	["fast", "slow", "signal", "pivot_window", "min_pivot_distance", "lookback", "min_divergence_magnitude"]

Normalization

Most indicators support a normalized parameter. When normalized=True, output values are transformed to relative scales:

• Bounded indicators (RSI, Stochastic, Williams %R): scaled to [0, 1] or [-1, 1]
• Unbounded indicators (MACD, ROC, smoothers): normalized via rolling z-score
• Normalized columns receive a _norm suffix

AutoFeatureNormalizer

AutoFeatureNormalizer is an automatic normalizer for Polars DataFrames. It analyzes the statistical properties of each feature and selects the optimal normalization method.

from signalflow.ta.auto_norm import AutoFeatureNormalizer

norm = AutoFeatureNormalizer(window=256, warmup=256)
artifact = norm.fit(df)
df_normalized = norm.transform(df)
# or in one step:
df_normalized = norm.fit_transform(df)

Normalization methods:

• rolling_robust -- (x - median) / IQR
• rolling_z -- (x - mean) / std
• rolling_rank -- percentile rank within a window
• rolling_winsor -- quantile clipping (outlier resistance)
• signed_log1p -- sign(x) * log1p(|x|) (for skewed distributions)

The fit() artifact can be saved/loaded via save()/load() for reproducibility.

License

See signalflow-trading for license details.