TR — True Range¶
The single-bar true range: the greatest of (high-low), |high-prev_close|, |low-prev_close|.
Inputs: [high, low, close] | Options: [] | Outputs: [tr]
Basic¶
use tulip_rs::indicators::tr::{Tr, 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) = Tr::indicator(&inputs, &[], None).unwrap();
println!("{:?}", outputs[0]); // True Range 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) = Tr::indicator(&[partial_high.as_slice(), partial_low.as_slice(), partial_close.as_slice()], &[], None).unwrap();
println!("{:?}", outputs2[0]);
let new_high = vec![85.90_f64];
let new_low = vec![84.03_f64];
let new_close = vec![85.53_f64];
let continued = state.batch_indicator(
&[new_high.as_slice(), new_low.as_slice(), new_close.as_slice()],
None,
).unwrap();
println!("{:?}", continued[0]);
TR has no options (TR_OPTIONS=0); pass NULL for the options array.
#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};
const double *inputs[TR_INPUTS] = {high, low, close};
const double *options = NULL; // TR has no options
/* Full computation */
CIndicatorResult r = tr_indicator(inputs, 10, options, NULL, 0);
printf("TR[0]: %.4f\n", r.outputs[0][0]); // outputs[0] is the true range series
tulip_ffi_result_free(r);
tr_state_free(r.state);
/* Partial computation + state continuation */
CIndicatorResult p = tr_indicator(inputs, 8, options, NULL, 0);
double new_high[] = {85.90}, new_low[] = {84.03}, new_close[] = {85.53};
const double *new_inputs[TR_INPUTS] = {new_high, new_low, new_close};
CBatchResult b = tr_batch(p.state, new_inputs, 1, NULL, 0);
printf("Continued TR[0]: %.4f\n", b.outputs[0][0]);
tulip_ffi_batch_result_free(b);
tulip_ffi_result_free(p);
tr_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}
// Full computation — Rows are zero-copy views, valid until Close.
res, st, _ := indicators.Tr.Indicator(high, low, close, []float64{}, nil)
fmt.Println(res.Rows[0]) // True Range values
res.Close()
st.Close()
// Partial computation + state continuation.
res2, st2, _ := indicators.Tr.Indicator(high[:8], low[:8], close[:8], []float64{}, 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 TR values
batch.Close()
st2.Close()
import org.tuliprs.*;
import org.tuliprs.indicators.Tr;
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 = {}; // TR has no options
// Full computation — output rows are zero-copy views, valid until close().
Outcome oc = Tr.indicator(new double[][] {high, low, close});
try (Result res = oc.result(); State st = oc.state()) {
System.out.println(java.util.Arrays.toString(res.toDoubleArray(0))); // True Range values
}
// Partial computation + state continuation.
int n = 8;
Outcome p = Tr.indicator(new double[][] {
java.util.Arrays.copyOfRange(high, 0, n),
java.util.Arrays.copyOfRange(low, 0, n),
java.util.Arrays.copyOfRange(close, 0, n)});
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 TR
}
}
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.tr.indicator([high, low, close], [])
print(outputs[0]) # True Range 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.tr.indicator([high, low, close], []);
console.log('TR:', outputs[0]);
// State continuation
const n = high.length - 5;
const [, state2] = ti.tr.indicator([high.slice(0, n), low.slice(0, n), close.slice(0, n)], []);
const continued = state2.batchIndicator([high.slice(n), low.slice(n), close.slice(n)]);
console.log('Continued TR:', 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.tr.indicator([high, low, close], []);
console.log('TR:', outputs[0]);
// State continuation
const n = high.length - 5;
const [, state2] = ti.tr.indicator([high.slice(0, n), low.slice(0, n), close.slice(0, n)], []);
const continued = state2.batchIndicator([high.slice(n), low.slice(n), close.slice(n)]);
console.log('Continued TR:', continued[0]);
SIMD¶
By assets — same options, N assets in parallel:
use tulip_rs::indicators::tr::{Tr, 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 = Tr::indicator_by_assets::<4>(&inputs, &[], None).unwrap();
for (i, asset_outputs) in results.iter().enumerate() {
println!("Asset {}: {:?}", i + 1, asset_outputs[0]);
}
This indicator has no options, so by-options SIMD does not apply.
By assets — TR has no options; by-options SIMD is not provided.
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[TR_INPUTS] = {h1, l1, c1};
const double *asset2[TR_INPUTS] = {h2, l2, c2};
const double *asset3[TR_INPUTS] = {h3, l3, c3};
const double *asset4[TR_INPUTS] = {h4, l4, c4};
const double *const *const simd_inputs[4] = {asset1, asset2, asset3, asset4};
const double *options = NULL; // TR has no options
CSimdResult r = tr_simd_by_assets(simd_inputs, 4, 10, options, NULL, 0);
for (uintptr_t i = 0; i < r.num_results; i++) {
printf("Asset %zu TR[0]: %.4f\n", i + 1, r.outputs[i][0][0]);
tr_state_free(r.states[i]);
}
tulip_ffi_simd_result_free(r);
By assets — same options 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.TrInputs][]float64{{h1, l1, c1}, {h2, l2, c2}, {h3, l3, c3}, {h4, l4, c4}}
sim, _ := indicators.Tr.SimdByAssets(assets, []float64{}, 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 assets — same options applied to 4 assets in parallel (N must be 2, 4, 8, or 16):
import org.tuliprs.*;
import org.tuliprs.indicators.Tr;
// 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 = Tr.simdByAssets(assets)) {
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)
This indicator has no options, so by-options SIMD does not offer.
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.tr.simd_by_assets(simd_inputs, [])
for i, asset_outputs in enumerate(outputs_list):
print(f"Asset {i+1}: {asset_outputs[0]}")
This indicator has no options, so by-options SIMD does not apply.
By assets — 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.tr.simdByAssets(simdInputs, []);
results.forEach((out, i) => console.log(`Asset ${i + 1}:`, out[0]));
This indicator has no options, so by-options SIMD does not apply.