Keltner Channel¶
A volatility-based envelope centred on an EMA of close. The middle band is EMA(close, period); the upper band adds a multiple of Wilder ATR(period) and the lower band subtracts it. Rendered as a price overlay, the channel expands during volatile periods and contracts during quiet ones. Optionally emits the underlying ATR and raw TR series.
Inputs: [high, low, close] | Options: [period, step] | Outputs: [lower, middle, upper]
Basic¶
use tulip_rs::indicators::keltnerchannel::{KeltnerChannel, 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,
85.90, 86.58, 86.98, 88.00, 87.87_f64];
let low = vec![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_f64];
let close = vec![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_f64];
let inputs = [high.as_slice(), low.as_slice(), close.as_slice()];
let (outputs, mut state) = KeltnerChannel::indicator(&inputs, &[14.0, 2.0], None).unwrap();
println!("{:?}", outputs[0]); // lower band
println!("{:?}", outputs[1]); // middle band (EMA)
println!("{:?}", outputs[2]); // upper band
// 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) = KeltnerChannel::indicator(&[partial_high.as_slice(), partial_low.as_slice(), partial_close.as_slice()], &[14.0, 2.0], None).unwrap();
println!("{:?}", outputs2[1]);
let new_high = vec![86.54_f64];
let new_low = vec![85.39_f64];
let new_close = vec![86.53_f64];
let continued = state.batch_indicator(
&[new_high.as_slice(), new_low.as_slice(), new_close.as_slice()],
None,
).unwrap();
println!("{:?}", continued[1]); // continued middle band
#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,
85.90, 86.58, 86.98, 88.00, 87.87};
double 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};
double 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};
double options[KELTNERCHANNEL_OPTIONS] = {14.0, 2.0}; // period, step
const double *inputs[KELTNERCHANNEL_INPUTS] = {high, low, close};
/* Full computation (check r.error == C_INDICATOR_ERROR_OK in real code) */
CIndicatorResult r = keltnerchannel_indicator(inputs, 15, options, NULL, 0);
/* r.outputs[0] -> lower, r.outputs[1] -> middle, r.outputs[2] -> upper */
tulip_ffi_result_free(r);
keltnerchannel_state_free(r.state);
/* Partial computation + state continuation */
CIndicatorResult p = keltnerchannel_indicator(inputs, 8, options, NULL, 0);
double new_high[] = {86.54};
double new_low[] = {85.39};
double new_close[] = {86.53};
const double *new_inputs[KELTNERCHANNEL_INPUTS] = {new_high, new_low, new_close};
CBatchResult b = keltnerchannel_batch(p.state, new_inputs, 1, NULL, 0);
/* b.outputs[1] -> middle_band for the one new bar */
tulip_ffi_batch_result_free(b);
tulip_ffi_result_free(p);
keltnerchannel_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,
85.90, 86.58, 86.98, 88.00, 87.87}
low := []float64{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}
close := []float64{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}
options := []float64{14.0, 2.0} // period, step
// Full computation — Rows are zero-copy views, valid until Close.
res, st, _ := indicators.Keltnerchannel.Indicator(high, low, close, options, nil)
fmt.Println(res.Rows[0]) // lower band
fmt.Println(res.Rows[1]) // middle band (EMA)
fmt.Println(res.Rows[2]) // upper band
res.Close()
st.Close()
// Partial computation + state continuation.
res2, st2, _ := indicators.Keltnerchannel.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[1]) // continued middle band
batch.Close()
st2.Close()
import org.tuliprs.*;
import org.tuliprs.indicators.Keltnerchannel;
double[] 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};
double[] 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};
double[] 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};
double[] options = {14.0, 2.0}; // period, step
// Full computation — output rows are zero-copy views, valid until close().
Outcome oc = Keltnerchannel.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))); // lower band
System.out.println(java.util.Arrays.toString(res.toDoubleArray(1))); // middle band (EMA)
System.out.println(java.util.Arrays.toString(res.toDoubleArray(2))); // upper band
}
// Partial computation + state continuation.
int n = 8;
Outcome p = Keltnerchannel.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, 15),
java.util.Arrays.copyOfRange(low, n, 15),
java.util.Arrays.copyOfRange(close, n, 15)});
try (br) {
System.out.println(java.util.Arrays.toString(br.toDoubleArray(1))); // continued middle band
}
}
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,
85.90, 86.58, 86.98, 88.00, 87.87], 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,
84.03, 85.39, 85.76, 87.17, 87.01], 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,
85.53, 86.54, 86.89, 87.77, 87.29], dtype=np.float64)
outputs, state = tulip_rs.indicators.keltnerchannel.indicator(
[high, low, close], [14.0, 2.0]
)
print(outputs[0]) # lower band
print(outputs[1]) # middle band (EMA)
print(outputs[2]) # upper band
# State continuation
new_high = np.array([88.50], dtype=np.float64)
new_low = np.array([87.30], dtype=np.float64)
new_close = np.array([88.10], dtype=np.float64)
continued = state.batch_indicator([new_high, new_low, new_close])
print(continued[1]) # continued middle band
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.keltnerchannel.indicator([high, low, close], [14, 2]);
console.log('Lower:', outputs[0]);
console.log('Middle (EMA):', outputs[1]);
console.log('Upper:', outputs[2]);
// State continuation
const n = high.length - 5;
const [, state2] = ti.keltnerchannel.indicator([high.slice(0, n), low.slice(0, n), close.slice(0, n)], [14, 2]);
const continued = state2.batchIndicator([high.slice(n), low.slice(n), close.slice(n)]);
console.log('Continued middle:', continued[1]);
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.keltnerchannel.indicator([high, low, close], [14, 2]);
console.log('Lower:', outputs[0]);
console.log('Middle (EMA):', outputs[1]);
console.log('Upper:', outputs[2]);
// State continuation
const n = high.length - 5;
const [, state2] = ti.keltnerchannel.indicator([high.slice(0, n), low.slice(0, n), close.slice(0, n)], [14, 2]);
const continued = state2.batchIndicator([high.slice(n), low.slice(n), close.slice(n)]);
console.log('Continued middle:', continued[1]);
Optional Outputs¶
keltnerchannel exposes 2 optional outputs: atr, tr. Pass a boolean mask as the third argument — one bool per optional output, in order.
use tulip_rs::indicators::keltnerchannel::{KeltnerChannel, 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,
85.90, 86.58, 86.98, 88.00, 87.87_f64];
let low = vec![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_f64];
let close = vec![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_f64];
let mask = [true, false];
let (outputs, _state) = KeltnerChannel::indicator(
&[high.as_slice(), low.as_slice(), close.as_slice()],
&[14.0, 2.0],
Some(&mask),
).unwrap();
let lower = &outputs[0]; // lower (primary)
let middle = &outputs[1]; // middle (primary)
let upper = &outputs[2]; // upper (primary)
let atr = &outputs[3]; // atr (optional — requested)
// tr not requested — omitted from outputs
keltnerchannel exposes 2 optional outputs: atr, tr. Pass a boolean mask as the third argument.
keltnerchannel exposes 2 optional outputs: atr, tr. The inputs are [high, low, close] and options is [period, step].
#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,
85.90, 86.58, 86.98, 88.00, 87.87};
double 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};
double 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};
double options[KELTNERCHANNEL_OPTIONS] = {14.0, 2.0}; // period, step
const double *inputs[KELTNERCHANNEL_INPUTS] = {high, low, close};
/* Request both optional outputs (atr and tr) */
bool mask[] = {true, true};
CIndicatorResult r = keltnerchannel_indicator(inputs, 15, options, mask, 2);
/* r.outputs[0] -> lower, r.outputs[1] -> middle, r.outputs[2] -> upper,
r.outputs[3] -> atr (optional 0), r.outputs[4] -> tr (optional 1) */
tulip_ffi_result_free(r);
keltnerchannel_state_free(r.state);
// Request only atr
bool mask_atr_only[] = {true, false};
CIndicatorResult partial_r = keltnerchannel_indicator(inputs, 15, options, mask_atr_only, 2);
tulip_ffi_result_free(partial_r);
keltnerchannel_state_free(partial_r.state);
keltnerchannel exposes 2 optional outputs: atr, tr. Pass a boolean mask as the fourth argument — one bool per optional output, in order.
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,
85.90, 86.58, 86.98, 88.00, 87.87}
low := []float64{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}
close := []float64{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}
options := []float64{14.0, 2.0} // period, step
// Request atr only (skip tr)
mask := []bool{true, false}
res, st, _ := indicators.Keltnerchannel.Indicator(high, low, close, options, mask)
lower := res.Rows[0] // lower (primary)
middle := res.Rows[1] // middle (primary)
upper := res.Rows[2] // upper (primary)
atr := res.Rows[3] // atr (optional 0 — requested)
res.Close()
st.Close()
// Request both optional outputs
mask_both := []bool{true, true}
fullRes, fullSt, _ := indicators.Keltnerchannel.Indicator(high, low, close, options, mask_both)
fmt.Println(fullRes.Rows[4]) // tr (optional 1)
fullRes.Close()
fullSt.Close()
keltnerchannel exposes 2 optional outputs: atr, tr. Pass a boolean mask as the third argument — one boolean per optional output, in order.
import org.tuliprs.*;
import org.tuliprs.indicators.Keltnerchannel;
// (high/low/close series as in the Basic tab)
boolean[] mask = {true, false}; // atr, tr
Outcome oc = Keltnerchannel.indicator(new double[][] {high, low, close}, new double[] {14.0, 2.0}, mask);
try (Result res = oc.result()) {
// row 0 = lower, row 1 = middle, row 2 = upper, row 3 = atr; tr was not requested
System.out.println(java.util.Arrays.toString(res.toDoubleArray(3))); // atr
}
oc.state().close();
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,
85.90, 86.58, 86.98, 88.00, 87.87], 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,
84.03, 85.39, 85.76, 87.17, 87.01], 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,
85.53, 86.54, 86.89, 87.77, 87.29], dtype=np.float64)
outputs, state = tulip_rs.indicators.keltnerchannel.indicator(
[high, low, close], [14.0, 2.0],
optional_outputs=[True, False],
)
lower = outputs[0] # lower (primary)
middle = outputs[1] # middle (primary)
upper = outputs[2] # upper (primary)
atr = outputs[3] # atr (optional — requested)
# tr not requested — omitted from outputs
keltnerchannel exposes 2 optional outputs: atr, tr.
const [allOut] = ti.keltnerchannel.indicator([high, low, close], [14, 2], [true, true]);
const lower = allOut[0]; // primary
const middle = allOut[1]; // primary
const upper = allOut[2]; // primary
const atr = allOut[3]; // optional 0: atr
const tr = allOut[4]; // optional 1: tr
// Request only atr
const [partial] = ti.keltnerchannel.indicator([high, low, close], [14, 2], [true, false]);
The WASM API is identical to Node.js — pass the boolean mask as the third argument.
const [allOut] = ti.keltnerchannel.indicator([high, low, close], [14, 2], [true, true]);
const lower = allOut[0]; // primary
const middle = allOut[1]; // primary
const upper = allOut[2]; // primary
const atr = allOut[3]; // optional 0: atr
const tr = allOut[4]; // optional 1: tr
// Request only atr
const [partial] = ti.keltnerchannel.indicator([high, low, close], [14, 2], [true, false]);
SIMD¶
use tulip_rs::indicators::keltnerchannel::{KeltnerChannel, 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 = KeltnerChannel::indicator_by_assets::<4>(&inputs, &[14.0, 2.0], None).unwrap();
for (i, asset_outputs) in results.iter().enumerate() {
println!("Asset {}: middle={:?}", i + 1, asset_outputs[1]);
}
By options — same asset, N option sets in parallel:
use tulip_rs::indicators::keltnerchannel::{KeltnerChannel, IndicatorByOptions};
let opts: [&[f64; 2]; 4] = [&[10.0, 1.5], &[14.0, 2.0], &[20.0, 2.0], &[30.0, 2.5]];
let results = KeltnerChannel::indicator_by_options::<4>(&inputs, &opts, None).unwrap();
for (i, out) in results.iter().enumerate() {
println!("Period={} step={}: middle={:?}", opts[i][0], opts[i][1], out[1]);
}
By assets — same options applied to 4 assets in one call (N must be 2/4/8/16):
double a1_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};
double a1_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};
double a1_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 double *const asset1[KELTNERCHANNEL_INPUTS] = {a1_high, a1_low, a1_close};
double a2_high[] = {90.0, 89.5, 91.0, 91.3, 91.9, 92.0, 91.5, 92.0, 92.5, 92.8};
double a2_low[] = {89.0, 88.5, 90.0, 90.3, 90.9, 91.0, 90.5, 91.0, 91.5, 91.8};
double a2_close[] = {89.5, 89.0, 90.5, 90.8, 91.4, 91.5, 91.0, 91.5, 92.0, 92.3};
const double *const asset2[KELTNERCHANNEL_INPUTS] = {a2_high, a2_low, a2_close};
double a3_high[] = {75.0 + (double)i * 0.2 for i in 0..15}; /* simplified */
double a3_low[] = {74.0 + (double)i * 0.2 for i in 0..15};
double a3_close[] = {74.5 + (double)i * 0.2 for i in 0..15};
const double *const asset3[KELTNERCHANNEL_INPUTS] = {a3_high, a3_low, a3_close};
double a4_high[] = {85.0 - (double)i * 0.1 for i in 0..15};
double a4_low[] = {84.0 - (double)i * 0.1 for i in 0..15};
double a4_close[] = {84.5 - (double)i * 0.1 for i in 0..15};
const double *const asset4[KELTNERCHANNEL_INPUTS] = {a4_high, a4_low, a4_close};
/* simd_inputs is indexed by asset (the N=4 SIMD lanes) */
const double *const *const simd_inputs[4] = {asset1, asset2, asset3, asset4};
CSimdResult r = keltnerchannel_simd_by_assets(simd_inputs, 4, 15, options, NULL, 0);
for (uintptr_t i = 0; i < r.num_results; i++) {
/* r.outputs[i][1] -> asset i's middle */
keltnerchannel_state_free(r.states[i]);
}
tulip_ffi_simd_result_free(r);
By options — same asset, 4 different option sets in one call:
static const double options_1[KELTNERCHANNEL_OPTIONS] = {10.0, 1.5};
static const double options_2[KELTNERCHANNEL_OPTIONS] = {14.0, 2.0};
static const double options_3[KELTNERCHANNEL_OPTIONS] = {20.0, 2.0};
static const double options_4[KELTNERCHANNEL_OPTIONS] = {30.0, 2.5};
const double *const simd_opts[4] = {options_1, options_2, options_3, options_4};
CSimdResult r = keltnerchannel_simd_by_options(inputs, 15, simd_opts, 4, NULL, 0);
/* r.outputs[i] -> results for option set i */
for (uintptr_t i = 0; i < r.num_results; i++) keltnerchannel_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):
a1_high := []float64{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}
a1_low := []float64{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}
a1_close := []float64{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}
// Reuse the same data for assets 2–4 in this example
a2_high, a2_low, a2_close := a1_high, a1_low, a1_close
a3_high, a3_low, a3_close := a1_high, a1_low, a1_close
a4_high, a4_low, a4_close := a1_high, a1_low, a1_close
assets := [][indicators.KeltnerchannelInputs][]float64{{a1_high, a1_low, a1_close}, {a2_high, a2_low, a2_close}, {a3_high, a3_low, a3_close}, {a4_high, a4_low, a4_close}}
sim, _ := indicators.Keltnerchannel.SimdByAssets(assets, []float64{14.0, 2.0}, nil)
for i, lanes := range sim.Results {
fmt.Printf("Asset %d: middle=%v\n", i+1, lanes[1])
}
sim.Close() // frees every lane state, then the SIMD buffers
By options — same asset, N option sets in parallel:
high := []float64{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}
low := []float64{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}
close := []float64{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}
// Tile the series 20x so longer-period option sets have enough data
#define EXPANDED_LEN (15 * 20)
high_exp := make([]float64, EXPANDED_LEN)
low_exp := make([]float64, EXPANDED_LEN)
close_exp := make([]float64, EXPANDED_LEN)
for i := 0; i < 20; i++ {
for j := 0; j < 15; j++ {
high_exp[i*15+j] = high[j]
low_exp[i*15+j] = low[j]
close_exp[i*15+j] = close[j]
}
}
sim2, _ := indicators.Keltnerchannel.SimdByOptions(high_exp, low_exp, close_exp, [][]float64{{10.0, 1.5}, {14.0, 2.0}, {20.0, 2.0}, {30.0, 2.5}}, nil)
for i, lanes := range sim2.Results {
fmt.Printf("Period=%d step=%d: middle=%v\n", i+1, lanes[0][1], lanes[0])
}
sim2.Close()
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.Keltnerchannel;
// Each entry lists one asset's input series (h1..c4 as in the C tab).
double[][][] assets = {{a1_high, a1_low, a1_close}, {a2_high, a2_low, a2_close}, {a3_high, a3_low, a3_close}, {a4_high, a4_low, a4_close}};
try (SimdResult sim = Keltnerchannel.simdByAssets(assets, new double[] {14.0, 2.0}, null)) {
for (int i = 0; i < sim.numResults(); i++) {
System.out.printf("Asset %d: middle=%s%n", i + 1,
java.util.Arrays.toString(sim.toDoubleArray(i, 1)));
}
} // frees every lane state, then the SIMD buffers (contractual order)
By options — same asset, 4 different option sets in parallel:
import org.tuliprs.*;
import org.tuliprs.indicators.Keltnerchannel;
// (high/low/close series as in the Basic tab)
try (SimdResult sim = Keltnerchannel.simdByOptions(new double[][] {high, low, close},
new double[][] {{10.0, 1.5}, {14.0, 2.0}, {20.0, 2.0}, {30.0, 2.5}}, null)) {
for (int i = 0; i < sim.numResults(); i++) {
System.out.printf("Period=%d step=%d: middle=%s%n", i + 1,
java.util.Arrays.toString(sim.toDoubleArray(i, 1)));
}
}
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.keltnerchannel.simd_by_assets(simd_inputs, [14.0, 2.0])
for i, asset_outputs in enumerate(outputs_list):
print(f"Asset {i+1}: middle={asset_outputs[1]}")
By options — same asset, N option sets in parallel:
By assets — same options 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.keltnerchannel.simdByAssets(simdInputs, [14, 2]);
results.forEach((out, i) => console.log(`Asset ${i + 1}: middle=`, out[1]));
By options — same asset, 4 different option sets in parallel: