TRVI — True Range Volatility Indicator¶
Similar to CVI but uses True Range instead of high − low. Applies an EMA to TR then outputs the percentage rate of change: (ema_now − ema_old) / ema_old × 100. More responsive to overnight gaps than CVI. Optionally emits the raw True Range series (tr) and the EMA-of-TR series (ema).
Inputs: [high, low, close] | Options: [period] | Outputs: [trvi]
Basic¶
use tulip_rs::indicators::trvi::{Trvi, Indicator, TIndicatorState};
let high = vec![82.15, 81.89, 83.03, 83.30, 83.85,
83.90, 83.33, 84.30, 84.84, 85.00_f64];
let low = vec![81.29, 80.64, 81.31, 82.65, 83.07,
83.11, 82.49, 82.30, 84.15, 84.11_f64];
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 inputs = [high.as_slice(), low.as_slice(), close.as_slice()];
let (outputs, mut state) = Trvi::indicator(&inputs, &[14.0], None).unwrap();
println!("{:?}", outputs[0]); // TRVI values
// State continuation — feed new bars without reprocessing history
let partial_high = high[..8].to_vec();
let partial_low = low[..8].to_vec();
let partial_close = close[..8].to_vec();
let (outputs2, mut state) = Trvi::indicator(&[partial_high.as_slice(), partial_low.as_slice(), partial_close.as_slice()], &[14.0], None).unwrap();
println!("{:?}", outputs2[0]);
let new_high = vec![85.20_f64];
let new_low = vec![84.50_f64];
let new_close = vec![85.00_f64];
let continued = state.batch_indicator(
&[new_high.as_slice(), new_low.as_slice(), new_close.as_slice()],
None,
).unwrap();
println!("{:?}", continued[0]);
trvi exposes 2 optional outputs: tr, ema. Pass a boolean mask as the third argument.
#include "tulip_rs_ffi.h"
double high[] = {82.15, 81.89, 83.03, 83.30, 83.85,
83.90, 83.33, 84.30, 84.84, 85.00};
double low[] = {81.29, 80.64, 81.31, 82.65, 83.07,
83.11, 82.49, 82.30, 84.15, 84.11};
double close[] = {81.59, 81.06, 82.87, 83.00, 83.61,
83.15, 82.84, 83.99, 84.55, 84.36};
double options[TRVI_OPTIONS] = {14.0}; // period
const double *inputs[TRVI_INPUTS] = {high, low, close};
/* Full computation */
CIndicatorResult r = trvi_indicator(inputs, 10, options, NULL, 0);
printf("trvi[0]: %.4f\n", r.outputs[0][0]); // outputs[0] is the primary trvi series
tulip_ffi_result_free(r);
trvi_state_free(r.state);
/* Partial computation + state continuation */
CIndicatorResult p = trvi_indicator(inputs, 8, options, NULL, 0);
double new_high[] = {85.20}, new_low[] = {84.50}, new_close[] = {85.00};
const double *new_inputs[TRVI_INPUTS] = {new_high, new_low, new_close};
CBatchResult b = trvi_batch(p.state, new_inputs, 1, NULL, 0);
printf("Continued trvi[0]: %.4f\n", b.outputs[0][0]);
tulip_ffi_batch_result_free(b);
tulip_ffi_result_free(p);
trvi_state_free(p.state);
import "github.com/me60732/tulip_rs_go/indicators"
high := []float64{82.15, 81.89, 83.03, 83.30, 83.85,
83.90, 83.33, 84.30, 84.84, 85.00}
low := []float64{81.29, 80.64, 81.31, 82.65, 83.07,
83.11, 82.49, 82.30, 84.15, 84.11}
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} // period
// Full computation — Rows are zero-copy views, valid until Close.
res, st, _ := indicators.Trvi.Indicator(high, low, close, options, nil)
fmt.Println(res.Rows[0]) // TRVI values
res.Close()
st.Close()
// Partial computation + state continuation.
res2, st2, _ := indicators.Trvi.Indicator(high[:8], low[:8], close[:8], options, nil)
res2.Close() // outputs consumed or closed; state stays live
batch, _ := st2.Batch(high[8:], low[8:], close[8:], nil)
fmt.Println(batch.Rows[0]) // continued TRVI values
batch.Close()
st2.Close()
import org.tuliprs.*;
import org.tuliprs.indicators.Trvi;
double[] high = {82.15, 81.89, 83.03, 83.30, 83.85,
83.90, 83.33, 84.30, 84.84, 85.00};
double[] low = {81.29, 80.64, 81.31, 82.65, 83.07,
83.11, 82.49, 82.30, 84.15, 84.11};
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 = Trvi.indicator(new double[][] {high, low, close}, options);
try (Result res = oc.result(); State st = oc.state()) {
System.out.println(java.util.Arrays.toString(res.toDoubleArray(0))); // TRVI values
}
// Partial computation + state continuation.
int n = 8;
Outcome p = Trvi.indicator(new double[][] {
java.util.Arrays.copyOfRange(high, 0, n),
java.util.Arrays.copyOfRange(low, 0, n),
java.util.Arrays.copyOfRange(close, 0, n)}, options);
try (Result pr = p.result(); State st = p.state()) {
Result br = st.batch(new double[][] {
java.util.Arrays.copyOfRange(high, n, 10),
java.util.Arrays.copyOfRange(low, n, 10),
java.util.Arrays.copyOfRange(close, n, 10)});
try (br) {
System.out.println(java.util.Arrays.toString(br.toDoubleArray(0))); // continued TRVI
}
}
import numpy as np
import tulip_rs
high = np.array([82.15, 81.89, 83.03, 83.30, 83.85,
83.90, 83.33, 84.30, 84.84, 85.00], dtype=np.float64)
low = np.array([81.29, 80.64, 81.31, 82.65, 83.07,
83.11, 82.49, 82.30, 84.15, 84.11], dtype=np.float64)
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.trvi.indicator([high, low, close], [14.0])
print(outputs[0]) # TRVI values
# State continuation
new_high = np.array([85.20], dtype=np.float64)
new_low = np.array([84.50], dtype=np.float64)
new_close = np.array([85.00], dtype=np.float64)
continued = state.batch_indicator([new_high, new_low, new_close])
print(continued[0])
import * as ti from 'tulip-rs-node';
const high = Float64Array.from([82.15, 81.89, 83.03, 83.30, 83.85, 83.90, 83.33, 84.30, 84.84, 85.00, 85.90, 86.58, 86.98, 88.00, 87.87]);
const low = Float64Array.from([81.29, 80.64, 81.31, 82.65, 83.07, 83.11, 82.49, 82.30, 84.15, 84.11, 84.03, 85.39, 85.76, 87.17, 87.01]);
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.trvi.indicator([high, low, close], [14]);
console.log('TRVI(14):', outputs[0]);
// State continuation
const n = high.length - 5;
const [, state2] = ti.trvi.indicator([high.slice(0, n), low.slice(0, n), close.slice(0, n)], [14]);
const continued = state2.batchIndicator([high.slice(n), low.slice(n), close.slice(n)]);
console.log('Continued TRVI:', continued[0]);
import { init } from 'tulip-rs-wasm';
import * as ti from 'tulip-rs-wasm';
await init(); // bundler resolves the WASM asset automatically
const high = [82.15, 81.89, 83.03, 83.30, 83.85, 83.90, 83.33, 84.30, 84.84, 85.00, 85.90, 86.58, 86.98, 88.00, 87.87];
const low = [81.29, 80.64, 81.31, 82.65, 83.07, 83.11, 82.49, 82.30, 84.15, 84.11, 84.03, 85.39, 85.76, 87.17, 87.01];
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.trvi.indicator([high, low, close], [14]);
console.log('TRVI(14):', outputs[0]);
// State continuation
const n = high.length - 5;
const [, state2] = ti.trvi.indicator([high.slice(0, n), low.slice(0, n), close.slice(0, n)], [14]);
const continued = state2.batchIndicator([high.slice(n), low.slice(n), close.slice(n)]);
console.log('Continued TRVI:', continued[0]);
Optional Outputs¶
trvi exposes 2 optional outputs: tr, ema. Pass a boolean mask as the third argument — one bool per optional output, in order.
use tulip_rs::indicators::trvi::{Trvi, Indicator, TIndicatorState};
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 high = close.iter().map(|x| x + 1.0).collect::<Vec<_>>();
let low = close.iter().map(|x| x - 1.0).collect::<Vec<_>>();
let mask = [true, true];
let (outputs, _state) = Trvi::indicator(
&[high.as_slice(), low.as_slice(), close.as_slice()],
&[14.0],
Some(&mask),
).unwrap();
let trvi = &outputs[0]; // trvi (primary)
let tr = &outputs[1]; // tr (optional — requested)
let ema = &outputs[2]; // ema (optional — requested)
trvi exposes 2 optional outputs: tr, ema. Pass a boolean mask as the third argument.
#include "tulip_rs_ffi.h"
double high[] = {82.15, 81.89, 83.03, 83.30, 83.85,
83.90, 83.33, 84.30, 84.84, 85.00};
double low[] = {81.29, 80.64, 81.31, 82.65, 83.07,
83.11, 82.49, 82.30, 84.15, 84.11};
double close[] = {81.59, 81.06, 82.87, 83.00, 83.61,
83.15, 82.84, 83.99, 84.55, 84.36};
double options[TRVI_OPTIONS] = {14.0}; // period
const double *inputs[TRVI_INPUTS] = {high, low, close};
bool optional_outputs[2] = {true, true}; // tr, ema
CIndicatorResult r = trvi_indicator(inputs, 10, options, optional_outputs, 2);
printf("trvi[0]: %.4f\n", r.outputs[0][0]); // primary
printf("tr[0]: %.4f\n", r.outputs[1][0]); // optional 0: tr
printf("ema[0]: %.4f\n", r.outputs[2][0]); // optional 1: ema
tulip_ffi_result_free(r);
trvi_state_free(r.state);
import "github.com/me60732/tulip_rs_go/indicators"
high := []float64{82.15, 81.89, 83.03, 83.30, 83.85,
83.90, 83.33, 84.30, 84.84, 85.00}
low := []float64{81.29, 80.64, 81.31, 82.65, 83.07,
83.11, 82.49, 82.30, 84.15, 84.11}
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} // period
mask := []bool{true, true} // tr, ema
res, st, _ := indicators.Trvi.Indicator(high, low, close, options, mask)
fmt.Println(res.Rows[0]) // trvi (primary)
fmt.Println(res.Rows[1]) // tr (optional — requested)
fmt.Println(res.Rows[2]) // ema (optional — requested)
res.Close()
st.Close()
trvi exposes 2 optional outputs: tr, ema. Pass a boolean mask as the third argument — one boolean per optional output, in order.
import org.tuliprs.*;
import org.tuliprs.indicators.Trvi;
// (high/low/close series as in the Basic tab)
boolean[] mask = {true, true}; // tr, ema
Outcome oc = Trvi.indicator(new double[][] {high, low, close}, new double[] {14.0}, mask);
try (Result res = oc.result()) {
// row 0 = trvi (primary), row 1 = tr, row 2 = ema
System.out.println(java.util.Arrays.toString(res.toDoubleArray(1))); // tr
}
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)
high = close + 1.0
low = close - 1.0
outputs, state = tulip_rs.indicators.trvi.indicator(
[high, low, close], [14.0],
optional_outputs=[True, True],
)
trvi = outputs[0] # trvi (primary)
tr = outputs[1] # tr (optional — requested)
ema = outputs[2] # ema (optional — requested)
trvi exposes 2 optional outputs: tr, ema.
The WASM API is identical to Node.js — pass the boolean mask as the third argument.
SIMD¶
By assets — same options, N assets in parallel:
use tulip_rs::indicators::trvi::{Trvi, Indicator};
let inputs: [&[&[f64]; 3]; 4] = [
&[h1.as_slice(), l1.as_slice(), c1.as_slice()],
&[h2.as_slice(), l2.as_slice(), c2.as_slice()],
&[h3.as_slice(), l3.as_slice(), c3.as_slice()],
&[h4.as_slice(), l4.as_slice(), c4.as_slice()],
];
let results = Trvi::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:
By assets — same period applied to 4 assets in parallel:
double h1[] = {82.15, 81.89, 83.03, 83.30, 83.85,
83.90, 83.33, 84.30, 84.84, 85.00};
double l1[] = {81.29, 80.64, 81.31, 82.65, 83.07,
83.11, 82.49, 82.30, 84.15, 84.11};
double c1[] = {81.59, 81.06, 82.87, 83.00, 83.61,
83.15, 82.84, 83.99, 84.55, 84.36};
double h2[10], l2[10], c2[10];
for (uintptr_t i = 0; i < 10; i++) { h2[i] = h1[i] * 1.1; l2[i] = l1[i] * 1.1; c2[i] = c1[i] * 1.1; }
double h3[10], l3[10], c3[10];
for (uintptr_t i = 0; i < 10; i++) { h3[i] = 90.0 + (double)i * 0.5 + h1[i] * 0.1;
l3[i] = 90.0 + (double)i * 0.5 + l1[i] * 0.1;
c3[i] = 90.0 + (double)i * 0.5 + c1[i] * 0.1; }
double h4[10], l4[10], c4[10];
for (uintptr_t i = 0; i < 10; i++) { h4[i] = 100.0 - (double)i * 0.3 + h1[i] * 0.05;
l4[i] = 100.0 - (double)i * 0.3 + l1[i] * 0.05;
c4[i] = 100.0 - (double)i * 0.3 + c1[i] * 0.05; }
const double *asset1[TRVI_INPUTS] = {h1, l1, c1};
const double *asset2[TRVI_INPUTS] = {h2, l2, c2};
const double *asset3[TRVI_INPUTS] = {h3, l3, c3};
const double *asset4[TRVI_INPUTS] = {h4, l4, c4};
const double *const *const simd_inputs[4] = {asset1, asset2, asset3, asset4};
double options[TRVI_OPTIONS] = {14.0}; // period
CSimdResult r = trvi_simd_by_assets(simd_inputs, 4, 10, options, NULL, 0);
for (uintptr_t i = 0; i < r.num_results; i++) {
printf("Asset %zu trvi[0]: %.4f\n", i + 1, r.outputs[i][0][0]);
trvi_state_free(r.states[i]);
}
tulip_ffi_simd_result_free(r);
By options — same asset, 4 different periods in parallel:
double high[] = {82.15, 81.89, 83.03, 83.30, 83.85,
83.90, 83.33, 84.30, 84.84, 85.00};
double low[] = {81.29, 80.64, 81.31, 82.65, 83.07,
83.11, 82.49, 82.30, 84.15, 84.11};
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 (10 * 20)
double h_exp[EXPANDED_LEN], l_exp[EXPANDED_LEN], c_exp[EXPANDED_LEN];
for (uintptr_t i = 0; i < 20; i++) {
for (uintptr_t j = 0; j < 10; j++) {
h_exp[i*10+j] = high[j]; l_exp[i*10+j] = low[j]; c_exp[i*10+j] = close[j];
}
}
const double *inputs[TRVI_INPUTS] = {h_exp, l_exp, c_exp};
double o5[] = {5.0}, o10[] = {10.0}, o14[] = {14.0}, o20[] = {20.0};
const double *const simd_opts[4] = {o5, o10, o14, o20};
CSimdResult r = trvi_simd_by_options(inputs, EXPANDED_LEN, simd_opts, 4, NULL, 0);
for (uintptr_t i = 0; i < r.num_results; i++) {
printf("Period %g: %.4f\n", simd_opts[i][0], r.outputs[i][0][0]);
trvi_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):
h1 := []float64{82.15, 81.89, 83.03, 83.30, 83.85,
83.90, 83.33, 84.30, 84.84, 85.00}
l1 := []float64{81.29, 80.64, 81.31, 82.65, 83.07,
83.11, 82.49, 82.30, 84.15, 84.11}
c1 := []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
h2, l2, c2 := h1, l1, c1
h3, l3, c3 := h1, l1, c1
h4, l4, c4 := h1, l1, c1
assets := [][indicators.TrviInputs][]float64{{h1, l1, c1}, {h2, l2, c2}, {h3, l3, c3}, {h4, l4, c4}}
sim, _ := indicators.Trvi.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:
high := []float64{82.15, 81.89, 83.03, 83.30, 83.85,
83.90, 83.33, 84.30, 84.84, 85.00}
low := []float64{81.29, 80.64, 81.31, 82.65, 83.07,
83.11, 82.49, 82.30, 84.15, 84.11}
close := []float64{81.59, 81.06, 82.87, 83.00, 83.61,
83.15, 82.84, 83.99, 84.55, 84.36}
#define EXPANDED_LEN (10 * 20)
h_exp := make([]float64, EXPANDED_LEN)
l_exp := make([]float64, EXPANDED_LEN)
c_exp := make([]float64, EXPANDED_LEN)
for i := 0; i < 20; i++ {
for j := 0; j < 10; j++ {
h_exp[i*10+j] = high[j]
l_exp[i*10+j] = low[j]
c_exp[i*10+j] = close[j]
}
}
sim2, _ := indicators.Trvi.SimdByOptions(h_exp, l_exp, c_exp, [][]float64{{5.0}, {10.0}, {14.0}, {20.0}}, 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.Trvi;
// Each entry lists one asset's input series (h1..c4 as in the C tab).
double[][][] assets = {{h1, l1, c1}, {h2, l2, c2}, {h3, l3, c3}, {h4, l4, c4}};
try (SimdResult sim = Trvi.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.Trvi;
// (high/low/close series as in the Basic tab)
try (SimdResult sim = Trvi.simdByOptions(new double[][] {high, low, close},
new double[][] {{5.0}, {10.0}, {14.0}, {20.0}}, 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 = [
[h1, l1, c1],
[h2, l2, c2],
[h3, l3, c3],
[h4, l4, c4],
]
outputs_list, states = tulip_rs.indicators.trvi.simd_by_assets(simd_inputs, [14.0])
for i, asset_outputs in enumerate(outputs_list):
print(f"Asset {i+1}: {asset_outputs[0]}")
By options — same asset, N option sets in parallel:
By assets — same period applied to 4 assets in parallel:
const simdInputs = [
[high.slice(), low.slice(), close.slice()],
[high.map(v => v * 1.1), low.map(v => v * 1.1), close.map(v => v * 1.1)],
[high.map(v => v * 0.9), low.map(v => v * 0.9), close.map(v => v * 0.9)],
[high.map(v => v * 1.02), low.map(v => v * 1.02), close.map(v => v * 1.02)],
];
const [results] = ti.trvi.simdByAssets(simdInputs, [14]);
results.forEach((out, i) => console.log(`Asset ${i + 1}:`, out[0]));
By options — same asset, 4 different periods in parallel: