TRIX — trix

The 1-period percentage rate of change of a triple-smoothed EMA. Useful as a momentum oscillator or trend filter; signals only significant moves.

Inputs: [real] | Options: [period] | Outputs: [trix]

Basic

RustCGoJavaPythonNode.jsWASM

use tulip_rs::indicators::trix::{Trix, TIndicatorState, Indicator};

let close = vec![81.59, 81.06, 82.87, 83.00, 83.61,
                 83.15, 82.84, 83.99, 84.55, 84.36_f64];

let (outputs, _state) = Trix::indicator(&[close.as_slice()], &[14.0], None).unwrap();
println!("{:?}", outputs[0]);

// State continuation
let partial = close[..8].to_vec();
let (outputs2, mut state) = Trix::indicator(&[partial.as_slice()], &[14.0], None).unwrap();
println!("Partial TRIX: {:?}", outputs2[0]);

let new_close = close[8..].to_vec();
let continued = state.batch_indicator(&[new_close.as_slice()], None).unwrap();
println!("Continued TRIX: {:?}", continued[0]);

#include "tulip_rs_ffi.h"

double close[] = {81.59, 81.06, 82.87, 83.00, 83.61,
                  83.15, 82.84, 83.99, 84.55, 84.36};
double options[TRIX_OPTIONS] = {14.0};
const double *inputs[TRIX_INPUTS] = {close};

/* Full computation */
CIndicatorResult r = trix_indicator(inputs, 10, options, NULL, 0);
/* r.outputs[0] -> the TRIX(14) series, length r.output_lens[0] */
tulip_ffi_result_free(r);
trix_state_free(r.state);

/* Partial computation + state continuation */
CIndicatorResult p = trix_indicator(inputs, 8, options, NULL, 0);
double new_close[] = {84.55, 84.36};
const double *new_inputs[TRIX_INPUTS] = {new_close};
CBatchResult b = trix_batch(p.state, new_inputs, 2, NULL, 0);
/* b.outputs[0] -> TRIX values for just the two new bars */
tulip_ffi_batch_result_free(b);
tulip_ffi_result_free(p);
trix_state_free(p.state);

import "github.com/me60732/tulip_rs_go/indicators"

close := []float64{81.59, 81.06, 82.87, 83.00, 83.61,
                   83.15, 82.84, 83.99, 84.55, 84.36}
options := []float64{14.0}

// Full computation — Rows are zero-copy views, valid until Close.
res, st, _ := indicators.Trix.Indicator(close, options, nil)
fmt.Println(res.Rows[0]) // TRIX(14) values
res.Close()
st.Close()

// Partial computation + state continuation.
res2, st2, _ := indicators.Trix.Indicator(close[:8], options, nil)
res2.Close() // outputs consumed or closed; state stays live
batch, _ := st2.Batch(close[8:], nil)
fmt.Println(batch.Rows[0]) // continued TRIX values
batch.Close()
st2.Close()

import org.tuliprs.*;
import org.tuliprs.indicators.Trix;

double[] close = {81.59, 81.06, 82.87, 83.00, 83.61,
                  83.15, 82.84, 83.99, 84.55, 84.36};
double[] options = {14.0};

// Full computation — output rows are zero-copy views, valid until close().
Outcome oc = Trix.indicator(new double[][] {close}, options);
try (Result res = oc.result(); State st = oc.state()) {
    for (int i = 0; i < res.numOutputs(); i++) {
        System.out.println(java.util.Arrays.toString(res.toDoubleArray(i))); // TRIX values
    }
}

// Partial computation + state continuation.
Outcome p = Trix.indicator(
    new double[][] {java.util.Arrays.copyOfRange(close, 0, 8)}, options);
try (Result pr = p.result(); State st = p.state()) {
    Result br = st.batch(
        new double[][] {java.util.Arrays.copyOfRange(close, 8, 10)});
    try (br) {
        for (int i = 0; i < br.numOutputs(); i++) {
            System.out.println(java.util.Arrays.toString(br.toDoubleArray(i))); // continued TRIX values
        }
    }
}

outputs, state = tulip_rs.indicators.trix.indicator([close], [14.0])
print(outputs[0])

import * as ti from 'tulip-rs-node';

const close = Float64Array.from([81.59, 81.06, 82.87, 83.00, 83.61,
               83.15, 82.84, 83.99, 84.55, 84.36,
               85.53, 86.54, 86.89, 87.77, 87.29]);

const [outputs, state] = ti.trix.indicator([close], [14]);
console.log('TRIX(14):', outputs[0]);

// State continuation
const [, state2] = ti.trix.indicator([close.slice(0, -5)], [14]);
const continued = state2.batchIndicator([close.slice(-5)]);
console.log('Continued TRIX:', continued[0]);

import { init } from 'tulip-rs-wasm';
import * as ti from 'tulip-rs-wasm';

await init(); // bundler resolves the WASM asset automatically

const close = [81.59, 81.06, 82.87, 83.00, 83.61,
               83.15, 82.84, 83.99, 84.55, 84.36,
               85.53, 86.54, 86.89, 87.77, 87.29];

const [outputs, state] = ti.trix.indicator([close], [14]);
console.log('TRIX(14):', outputs[0]);

// State continuation
const [, state2] = ti.trix.indicator([close.slice(0, -5)], [14]);
const continued = state2.batchIndicator([close.slice(-5)]);
console.log('Continued TRIX:', continued[0]);

Optional Outputs

RustCGoJavaPythonNode.jsWASM

trix exposes 3 optional outputs: tema, dema, ema. Pass a boolean mask as the third argument — one bool per optional output, in order.

use tulip_rs::indicators::trix::{Trix, TIndicatorState, Indicator};

let close = vec![81.59, 81.06, 82.87, 83.00, 83.61,
                 83.15, 82.84, 83.99, 84.55, 84.36_f64];

let mask = [false, false, true]; // one per optional output
let (outputs, _state) = Trix::indicator(&[close.as_slice()], &[5.0], Some(&mask)).unwrap();

let trix = &outputs[0]; // trix (primary)
let ema  = &outputs[1]; // ema (optional — requested)
// tema not requested, dema not requested

trix exposes 3 optional outputs: tema, dema, ema.

#include "tulip_rs_ffi.h"

double close[] = {81.59, 81.06, 82.87, 83.00, 83.61,
                  83.15, 82.84, 83.99, 84.55, 84.36};
double options[TRIX_OPTIONS] = {5.0};
const double *inputs[TRIX_INPUTS] = {close};

bool optional_outputs[3] = {false, false, true}; // tema, dema, ema
CIndicatorResult r = trix_indicator(inputs, 10, options, optional_outputs, 3);
/* r.outputs[0] -> trix (primary) */
/* r.outputs[1] -> tema (optional — not requested here) */
/* r.outputs[2] -> dema (optional — not requested here) */
/* r.outputs[3] -> ema (optional — requested) */
tulip_ffi_result_free(r);
trix_state_free(r.state);

trix exposes 3 optional outputs: tema, dema, ema. Pass a boolean mask as the third argument.

import "github.com/me60732/tulip_rs_go/indicators"

close := []float64{81.59, 81.06, 82.87, 83.00, 83.61,
                   83.15, 82.84, 83.99, 84.55, 84.36}
options := []float64{5.0}

mask := []bool{false, false, true} // tema, dema, ema
res, st, _ := indicators.Trix.Indicator(close, options, mask)

trix := res.Rows[0] // trix (primary)
ema  := res.Rows[1] // ema (optional — requested)
// tema not requested, dema not requested
res.Close()
st.Close()

trix exposes 3 optional outputs: tema, dema, ema. Pass a boolean mask as the third argument.

import org.tuliprs.*;
import org.tuliprs.indicators.Trix;

double[] close = {81.59, 81.06, 82.87, 83.00, 83.61,
                  83.15, 82.84, 83.99, 84.55, 84.36};
double[] options = {5.0};

boolean[] mask = {false, false, true}; // tema, dema, ema
Outcome oc = Trix.indicator(new double[][] {close}, options, mask);
try (Result res = oc.result()) {
    System.out.println(java.util.Arrays.toString(res.toDoubleArray(0))); // trix (primary)
    System.out.println(java.util.Arrays.toString(res.toDoubleArray(1))); // tema (optional — not requested here)
    System.out.println(java.util.Arrays.toString(res.toDoubleArray(2))); // dema (optional — not requested here)
    System.out.println(java.util.Arrays.toString(res.toDoubleArray(3))); // ema (optional — requested)
}
oc.state().close();

import numpy as np
import tulip_rs

close = np.array([81.59, 81.06, 82.87, 83.00, 83.61,
                  83.15, 82.84, 83.99, 84.55, 84.36], dtype=np.float64)

outputs, state = tulip_rs.indicators.trix.indicator(
    [close], [5.0],
    optional_outputs=[False, False, True],
)

trix = outputs[0]  # trix (primary)
ema  = outputs[1]  # ema (optional — requested)
# tema not requested, dema not requested

trix exposes 3 optional outputs: tema, dema, ema.

const [allOut] = ti.trix.indicator([close], [14], [true, true, true]);
const trix = allOut[0]; // primary
const tema = allOut[1]; // optional 0: tema
const dema = allOut[2]; // optional 1: dema
const ema  = allOut[3]; // optional 2: ema

The WASM API is identical to Node.js — pass the boolean mask as the third argument.

const [allOut] = ti.trix.indicator([close], [14], [true, true, true]);
const trix = allOut[0]; // primary
const tema = allOut[1]; // optional 0: tema
const dema = allOut[2]; // optional 1: dema
const ema  = allOut[3]; // optional 2: ema

SIMD

RustCGoJavaPythonNode.js

By assets — same options, N assets in parallel:

use tulip_rs::indicators::trix::{Trix, Indicator};

let a1 = vec![81.59, 81.06, 82.87, 83.00, 83.61, 83.15, 82.84, 83.99, 84.55, 84.36_f64];
let a2 = vec![72.10, 72.85, 73.40, 73.00, 74.20, 74.85, 75.10, 75.60, 76.00, 76.50_f64];
let a3 = vec![55.30, 55.80, 56.10, 56.40, 56.90, 57.20, 57.50, 57.80, 58.10, 58.40_f64];
let a4 = vec![100.1, 100.5, 101.0, 101.3, 101.8, 102.0, 102.5, 103.0, 103.3, 103.8_f64];

let inputs: [&[&[f64]; 1]; 4] = [
    &[a1.as_slice()],
    &[a2.as_slice()],
    &[a3.as_slice()],
    &[a4.as_slice()],
];

let results = Trix::indicator_by_assets::<4>(&inputs, &[14.0], None).unwrap();
for (i, asset_outputs) in results.iter().enumerate() {
    println!("Asset {}: {:?}", i + 1, asset_outputs[0]);
}

By options — same asset, N option sets in parallel:

use tulip_rs::indicators::trix::{Trix, IndicatorByOptions};

let close = vec![81.59, 81.06, 82.87, 83.00, 83.61,
                 83.15, 82.84, 83.99, 84.55, 84.36_f64];

let opts: [&[f64; 1]; 4] = [&[9.0], &[14.0], &[21.0], &[30.0]];

let results = Trix::indicator_by_options::<4>(&[close.as_slice()], &opts, None).unwrap();
for (i, opt_outputs) in results.iter().enumerate() {
    println!("Period set {}: {:?}", i + 1, opt_outputs[0]);
}

By assets — same period applied to 4 assets in parallel:

double a1[] = {81.59, 81.06, 82.87, 83.00, 83.61, 83.15, 82.84, 83.99, 84.55, 84.36};
double a2[] = {72.10, 72.85, 73.40, 73.00, 74.20, 74.85, 75.10, 75.60, 76.00, 76.50};
double a3[] = {55.30, 55.80, 56.10, 56.40, 56.90, 57.20, 57.50, 57.80, 58.10, 58.40};
double a4[] = {100.1, 100.5, 101.0, 101.3, 101.8, 102.0, 102.5, 103.0, 103.3, 103.8};

const double *asset1[TRIX_INPUTS] = {a1};
const double *asset2[TRIX_INPUTS] = {a2};
const double *asset3[TRIX_INPUTS] = {a3};
const double *asset4[TRIX_INPUTS] = {a4};
const double *const *const simd_inputs[4] = {asset1, asset2, asset3, asset4};

CSimdResult r = trix_simd_by_assets(simd_inputs, 4, 10, options, NULL, 0);
for (uintptr_t i = 0; i < r.num_results; i++) {
    /* r.outputs[i][0] -> asset i's TRIX series */
    trix_state_free(r.states[i]);
}
tulip_ffi_simd_result_free(r);

By options — same asset, 4 different periods in parallel:

static const double close[] = {81.59, 81.06, 82.87, 83.00, 83.61,
                               83.15, 82.84, 83.99, 84.55, 84.36};
#define EXPANDED_LEN (sizeof(close) / sizeof(double) * 20)
static double close_expanded[EXPANDED_LEN];
for (size_t i = 0; i < 20; i++) {
    for (size_t j = 0; j < sizeof(close) / sizeof(double); j++) {
        close_expanded[i * (sizeof(close) / sizeof(double)) + j] = close[j];
    }
}
const double *inputs[TRIX_INPUTS] = {close_expanded};

static const double o1[TRIX_OPTIONS] = {9.0};
static const double o2[TRIX_OPTIONS] = {14.0};
static const double o3[TRIX_OPTIONS] = {21.0};
static const double o4[TRIX_OPTIONS] = {30.0};
const double *const simd_opts[4] = {o1, o2, o3, o4};

CSimdResult r = trix_simd_by_options(inputs, EXPANDED_LEN, simd_opts, 4, NULL, 0);
for (uintptr_t i = 0; i < r.num_results; i++) {
    trix_state_free(r.states[i]);
}
tulip_ffi_simd_result_free(r);

By assets — same period applied to 4 assets in parallel (lane counts 2/4/8/16):

a1 := []float64{81.59, 81.06, 82.87, 83.00, 83.61, 83.15, 82.84, 83.99, 84.55, 84.36}

// Reuse the same data for assets 2–4 in this example
a2, a3, a4 := a1, a1, a1

assets := [][indicators.TrixInputs][]float64{{a1}, {a2}, {a3}, {a4}}
sim, _ := indicators.Trix.SimdByAssets(assets, []float64{14.0}, nil)
for i, lanes := range sim.Results {
    fmt.Printf("Asset %d: %v\n", i+1, lanes[0])
}
sim.Close() // frees every lane state, then the SIMD buffers

By options — same asset, 4 different periods in parallel:

close := []float64{81.59, 81.06, 82.87, 83.00, 83.61,
                   83.15, 82.84, 83.99, 84.55, 84.36}

sim2, _ := indicators.Trix.SimdByOptions(close, [][]float64{{9}, {14}, {21}, {30}}, nil)
for i, lanes := range sim2.Results {
    fmt.Printf("Period set %d: %v\n", i+1, lanes[0])
}
sim2.Close()

By assets — same period applied to 4 assets in parallel (N must be 2, 4, 8, or 16):

import org.tuliprs.*;
import org.tuliprs.indicators.Trix;

double[] a1 = {81.59, 81.06, 82.87, 83.00, 83.61, 83.15, 82.84, 83.99, 84.55, 84.36};
double[] a2 = {72.10, 72.85, 73.40, 73.00, 74.20, 74.85, 75.10, 75.60, 76.00, 76.50};
double[] a3 = {55.30, 55.80, 56.10, 56.40, 56.90, 57.20, 57.50, 57.80, 58.10, 58.40};
double[] a4 = {100.1, 100.5, 101.0, 101.3, 101.8, 102.0, 102.5, 103.0, 103.3, 103.8};

// One entry per asset; each asset lists its INPUTS series.
double[][][] assets = {{a1}, {a2}, {a3}, {a4}};
try (SimdResult sim = Trix.simdByAssets(assets, new double[] {14.0}, null)) {
    for (int i = 0; i < sim.numResults(); i++) {
        System.out.printf("Asset %d: %s%n", i + 1,
            java.util.Arrays.toString(sim.toDoubleArray(i, 0)));    }
}   // frees every lane state, then the SIMD buffers (contractual order)

By options — same asset, 4 different periods in parallel:

import org.tuliprs.*;
import org.tuliprs.indicators.Trix;

double[] close = {81.59, 81.06, 82.87, 83.00, 83.61,
                  83.15, 82.84, 83.99, 84.55, 84.36};

try (SimdResult sim = Trix.simdByOptions(new double[][] {close},
        new double[][] {{9}, {14}, {21}, {30}}, null)) {
    for (int i = 0; i < sim.numResults(); i++) {
        System.out.printf("Period set %d: %s%n", i + 1,
            java.util.Arrays.toString(sim.toDoubleArray(i, 0)));    }
}

By assets — same options, N assets in parallel (must be 2, 4, 8, or 16):

simd_inputs = [[a1], [a2], [a3], [a4]]
outputs_list, states = tulip_rs.indicators.trix.simd_by_assets(simd_inputs, [14.0])

By options — same asset, N option sets in parallel:

simd_options = [[9.0], [14.0], [21.0], [30.0]]
outputs_list, states = tulip_rs.indicators.trix.simd_by_options([close], simd_options)

By assets — same period applied to 4 assets in parallel:

const simdInputs = [[close.slice()], [close.map(v => v * 1.1)], [close.map(v => v * 0.9)], [close.map(v => v * 1.02)]];
const [results] = ti.trix.simdByAssets(simdInputs, [14]);
results.forEach((out, i) => console.log(`Asset ${i + 1}:`, out[0]));

By options — same asset, 4 different periods in parallel:

const simdOptions = [[9], [14], [21], [30]];
const [results] = ti.trix.simdByOptions([close], simdOptions);
results.forEach((out, i) => console.log(`Period ${simdOptions[i][0]}:`, out[0]));