Aroon Oscillator¶
The difference between Aroon Up and Aroon Down. Positive values indicate bullish momentum; negative bearish.
Inputs: [high, low] | Options: [period] | Outputs: [aroonosc]
Basic¶
use tulip_rs::indicators::aroonosc::{AroonOsc, 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 inputs = [high.as_slice(), low.as_slice()];
let (outputs, mut state) = AroonOsc::indicator(&inputs, &[25.0], None).unwrap();
println!("{:?}", outputs[0]); // Aroon Oscillator values
// State continuation — feed new bars without reprocessing history
let partial_high = high[..8].to_vec();
let partial_low = low[..8].to_vec();
let (outputs2, mut state) = AroonOsc::indicator(&[partial_high.as_slice(), partial_low.as_slice()], &[25.0], None).unwrap();
println!("{:?}", outputs2[0]);
let new_high = vec![85.90_f64];
let new_low = vec![84.03_f64];
let continued = state.batch_indicator(
&[new_high.as_slice(), new_low.as_slice()],
None,
).unwrap();
println!("{:?}", continued[0]);
#include "tulip_rs_ffi.h"
#include "tulip_rs_ffi_counts.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 options[AROONOSC_OPTIONS] = {25.0}; // period
const double *inputs[AROONOSC_INPUTS] = {high, low};
/* Full computation (check r.error == C_INDICATOR_ERROR_OK in real code) */
CIndicatorResult r = aroonosc_indicator(inputs, 10, options, NULL, 0);
/* r.outputs[0] -> aroonosc, length r.output_lens[0] */
tulip_ffi_result_free(r);
aroonosc_state_free(r.state);
/* Partial computation + state continuation */
CIndicatorResult p = aroonosc_indicator(inputs, 8, options, NULL, 0);
double new_high[] = {85.90};
double new_low[] = {84.03};
const double *new_inputs[AROONOSC_INPUTS] = {new_high, new_low};
CBatchResult b = aroonosc_batch(p.state, new_inputs, 1, NULL, 0);
/* b.outputs[0] -> aroonosc for the one new bar */
tulip_ffi_batch_result_free(b);
tulip_ffi_result_free(p);
aroonosc_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}
options := []float64{25.0} // period
// Full computation — Rows is just [aroonosc], valid until Close.
res, st, _ := indicators.Aroonosc.Indicator(high, low, options, nil)
fmt.Println(res.Rows[0]) // Aroon Oscillator values
res.Close()
st.Close()
// Partial computation + state continuation.
res2, st2, _ := indicators.Aroonosc.Indicator(high[:8], low[:8], options, nil)
res2.Close() // outputs consumed or closed; state stays live
batch, _ := st2.Batch(high[8:], low[8:], nil)
fmt.Println(batch.Rows[0]) // continued Aroon Oscillator values
batch.Close()
st2.Close()
import org.tuliprs.*;
import org.tuliprs.indicators.Aroonosc;
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[] options = {25.0}; // period
// Full computation — output rows are zero-copy views, valid until close().
Outcome oc = Aroonosc.indicator(new double[][] {high, low}, options);
try (Result res = oc.result(); State st = oc.state()) {
System.out.println(java.util.Arrays.toString(res.toDoubleArray(0))); // aroonosc
}
// Partial computation + state continuation.
int n = 8;
Outcome p = Aroonosc.indicator(new double[][] {
java.util.Arrays.copyOfRange(high, 0, n),
java.util.Arrays.copyOfRange(low, 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)});
try (br) {
System.out.println(java.util.Arrays.toString(br.toDoubleArray(0))); // continued aroonosc
}
}
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)
outputs, state = tulip_rs.indicators.aroonosc.indicator([high, low], [25.0])
print(outputs[0]) # Aroon Oscillator values
# State continuation
new_high = np.array([85.30], dtype=np.float64)
new_low = np.array([84.60], dtype=np.float64)
continued = state.batch_indicator([new_high, new_low])
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 [outputs, state] = ti.aroonosc.indicator([high, low], [25]);
console.log('Aroon Oscillator:', outputs[0]);
// State continuation
const n = high.length - 5;
const [, state2] = ti.aroonosc.indicator([high.slice(0, n), low.slice(0, n)], [25]);
const continued = state2.batchIndicator([high.slice(n), low.slice(n)]);
console.log('Continued AroonOsc:', 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 [outputs, state] = ti.aroonosc.indicator([high, low], [25]);
console.log('Aroon Oscillator:', outputs[0]);
// State continuation
const n = high.length - 5;
const [, state2] = ti.aroonosc.indicator([high.slice(0, n), low.slice(0, n)], [25]);
const continued = state2.batchIndicator([high.slice(n), low.slice(n)]);
console.log('Continued AroonOsc:', continued[0]);
Optional Outputs¶
aroonosc exposes 2 optional outputs: aroon_down, aroon_up. Pass a boolean mask as the third argument — one bool per optional output, in order.
use tulip_rs::indicators::aroonosc::{AroonOsc, 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) = AroonOsc::indicator(
&[high.as_slice(), low.as_slice()],
&[25.0],
Some(&mask),
).unwrap();
let aroonosc = &outputs[0]; // aroonosc (primary)
let aroon_down = &outputs[1]; // aroon_down (optional — requested)
let aroon_up = &outputs[2]; // aroon_up (optional — requested)
aroonosc exposes 2 optional outputs: aroon_down, aroon_up. Pass a boolean mask — one bool per optional output, in header order.
#include "tulip_rs_ffi.h"
#include "tulip_rs_ffi_counts.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 options[AROONOSC_OPTIONS] = {25.0}; // period
const double *inputs[AROONOSC_INPUTS] = {high, low};
bool optional_outputs[2] = {true, true}; // aroon_down, aroon_up
CIndicatorResult r = aroonosc_indicator(inputs, 10, options, optional_outputs, 2);
/* r.outputs[0] -> aroonosc (primary), length r.output_lens[0] */
/* r.outputs[1] -> aroon_down (optional), length r.output_lens[1] */
/* r.outputs[2] -> aroon_up (optional), length r.output_lens[2] */
tulip_ffi_result_free(r);
aroonosc_state_free(r.state);
aroonosc exposes 2 optional outputs: aroon_down, aroon_up. By-options isn't offered.
close := []float64{81.59, 81.06, 82.87, 83.00, 83.61, 83.15, 82.84, 83.99, 84.55, 84.36}
high := make([]float64, len(close))
low := make([]float64, len(close))
for i := range close {
high[i] = close[i] + 1.0
low[i] = close[i] - 1.0
}
options := []float64{25.0} // period
mask := []bool{true, true} // aroon_down, aroon_up
res, _st, _ := indicators.Aroonosc.Indicator(high, low, options, mask)
aroonosc := res.Rows[0] // aroonosc (primary)
aroonDown := res.Rows[1] // aroon_down (optional — requested)
aroonUp := res.Rows[2] // aroon_up (optional — requested)
res.Close()
aroonosc exposes 2 optional outputs: aroon_down, aroon_up. Pass a boolean mask as the third argument.
import org.tuliprs.*;
import org.tuliprs.indicators.Aroonosc;
// (high/low series as in the Basic tab)
boolean[] mask = {true, true}; // aroon_down, aroon_up
Outcome oc = Aroonosc.indicator(new double[][] {high, low}, new double[] {25.0}, mask);
try (Result res = oc.result()) {
// row 0 = aroonosc (primary), row 1 = aroon_down, row 2 = aroon_up
System.out.println(java.util.Arrays.toString(res.toDoubleArray(0))); // aroonosc
}
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.aroonosc.indicator(
[high, low], [25.0],
optional_outputs=[True, True],
)
aroonosc = outputs[0] # aroonosc (primary)
aroon_down = outputs[1] # aroon_down (optional — requested)
aroon_up = outputs[2] # aroon_up (optional — requested)
aroonosc exposes 2 optional outputs: aroon_down, aroon_up.
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::aroonosc::{AroonOsc, Indicator};
let inputs: [&[&[f64]; 2]; 4] = [
&[h1.as_slice(), l1.as_slice()],
&[h2.as_slice(), l2.as_slice()],
&[h3.as_slice(), l3.as_slice()],
&[h4.as_slice(), l4.as_slice()],
];
let results = AroonOsc::indicator_by_assets::<4>(&inputs, &[25.0], 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::aroonosc::{AroonOsc, IndicatorByOptions};
let opts: [&[f64; 1]; 4] = [&[5.0], &[10.0], &[25.0], &[50.0]];
let results = AroonOsc::indicator_by_options::<4>(&inputs, &opts, None).unwrap();
for (i, out) in results.iter().enumerate() {
println!("Period {}: {:?}", opts[i][0], out[0]);
}
By assets — same option applied to 4 assets in one call (N must be 2/4/8/16):
#include "tulip_rs_ffi.h"
#include "tulip_rs_ffi_counts.h"
double a1[] = {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 a2[] = {72.10, 72.85, 73.40, 73.00, 74.20, 74.85, 75.10, 75.60, 76.00, 76.50};
double l2[] = {71.10, 71.85, 72.40, 72.00, 73.20, 73.85, 74.10, 74.60, 75.00, 75.50};
/* one [INPUTS]-long pointer array per asset */
const double *asset1[AROONOSC_INPUTS] = {a1, l1};
const double *asset2[AROONOSC_INPUTS] = {a2, l2};
const double *const *const simd_inputs[4] = {asset1, asset2, NULL, NULL}; /* N=4 lanes */
double options[AROONOSC_OPTIONS] = {25.0};
bool optional_outputs[2] = {true, true};
CSimdResult r = aroonosc_simd_by_assets(simd_inputs, 4, 10, options, optional_outputs, 2);
for (uintptr_t i = 0; i < r.num_results; i++) {
/* r.outputs[i][0] -> asset i's aroonosc, length r.output_lens[i][0] */
aroonosc_state_free(r.states[i]);
}
tulip_ffi_simd_result_free(r);
By options — same asset, N different periods in one call:
#include "tulip_rs_ffi.h"
#include "tulip_rs_ffi_counts.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};
const double *inputs[AROONOSC_INPUTS] = {high, low};
/* Tile the series 20x so longer-period option sets have enough data */
#define EXPANDED_LEN (10 * 20)
static double high_expanded[EXPANDED_LEN];
static double low_expanded[EXPANDED_LEN];
for (size_t i = 0; i < 20; i++) {
for (size_t j = 0; j < 10; j++) {
high_expanded[i * 10 + j] = high[j];
low_expanded[i * 10 + j] = low[j];
}
}
const double *expanded_inputs[AROONOSC_INPUTS] = {high_expanded, low_expanded};
static const double o5[AROONOSC_OPTIONS] = {5.0};
static const double o10[AROONOSC_OPTIONS] = {10.0};
static const double o25[AROONOSC_OPTIONS] = {25.0};
static const double o50[AROONOSC_OPTIONS] = {50.0};
const double *const simd_opts[4] = {o5, o10, o25, o50};
CSimdResult r = aroonosc_simd_by_options(expanded_inputs, EXPANDED_LEN, simd_opts, 4, NULL, 0);
for (uintptr_t i = 0; i < r.num_results; i++) aroonosc_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}
// Reuse the same data for assets 2–4 in this example
h2, l2 := h1, l1
h3, l3 := h1, l1
h4, l4 := h1, l1
assets := [][indicators.AroonoscInputs][]float64{{h1, l1}, {h2, l2}, {h3, l3}, {h4, l4}}
sim, _ := indicators.Aroonosc.SimdByAssets(assets, []float64{25.0}, nil)
for i, lanes := range sim.Results {
fmt.Printf("Asset %d: %v\n", i+1, lanes[0]) // aroonosc
}
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}
// Tile the series 20x so longer-period option sets have enough data
#define EXPANDED_LEN (10 * 20)
high_exp := make([]float64, EXPANDED_LEN)
low_exp := make([]float64, EXPANDED_LEN)
for i := 0; i < 20; i++ {
for j := 0; j < 10; j++ {
high_exp[i*10+j] = high[j]
low_exp[i*10+j] = low[j]
}
}
sim2, _ := indicators.Aroonosc.SimdByOptions(high_exp, low_exp, [][]float64{{5.0}, {10.0}, {25.0}, {50.0}}, 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.Aroonosc;
double[] a1 = {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[] a2 = {72.10, 72.85, 73.40, 73.00, 74.20, 74.85, 75.10, 75.60, 76.00, 76.50};
double[] l2 = {71.10, 71.85, 72.40, 72.00, 73.20, 73.85, 74.10, 74.60, 75.00, 75.50};
double[] a3 = {a1[0]*1.1, a1[1]*1.1, a1[2]*1.1, a1[3]*1.1, a1[4]*1.1,
a1[5]*1.1, a1[6]*1.1, a1[7]*1.1, a1[8]*1.1, a1[9]*1.1};
double[] l3 = {l1[0]*1.1, l1[1]*1.1, l1[2]*1.1, l1[3]*1.1, l1[4]*1.1,
l1[5]*1.1, l1[6]*1.1, l1[7]*1.1, l1[8]*1.1, l1[9]*1.1};
double[] a4 = {a1[0]*0.9, a1[1]*0.9, a1[2]*0.9, a1[3]*0.9, a1[4]*0.9,
a1[5]*0.9, a1[6]*0.9, a1[7]*0.9, a1[8]*0.9, a1[9]*0.9};
double[] l4 = {l1[0]*0.9, l1[1]*0.9, l1[2]*0.9, l1[3]*0.9, l1[4]*0.9,
l1[5]*0.9, l1[6]*0.9, l1[7]*0.9, l1[8]*0.9, l1[9]*0.9};
// One entry per asset; each asset lists its INPUTS series.
double[][][] assets = {{a1, l1}, {a2, l2}, {a3, l3}, {a4, l4}};
try (SimdResult sim = Aroonosc.simdByAssets(assets, new double[] {25.0}, 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))); // aroonosc
}
} // 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.Aroonosc;
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};
// Tile the series 20x so longer-period option sets have enough data
double[] high_exp = new double[200];
double[] low_exp = new double[200];
for (int i = 0; i < 20; i++) {
for (int j = 0; j < 10; j++) {
high_exp[i * 10 + j] = high[j];
low_exp[i * 10 + j] = low[j];
}
}
try (SimdResult sim = Aroonosc.simdByOptions(new double[][] {high_exp, low_exp},
new double[][] {{5.0}, {10.0}, {25.0}, {50.0}}, 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))); // aroonosc
}
}
By assets — same options, N assets in parallel (must be 2, 4, 8, or 16):
simd_inputs = [
[h1, l1],
[h2, l2],
[h3, l3],
[h4, l4],
]
outputs_list, states = tulip_rs.indicators.aroonosc.simd_by_assets(simd_inputs, [25.0])
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()],
[high.map(v => v * 1.1), low.map(v => v * 1.1)],
[high.map(v => v * 0.9), low.map(v => v * 0.9)],
[high.map(v => v * 1.02), low.map(v => v * 1.02)],
];
const [results] = ti.aroonosc.simdByAssets(simdInputs, [25]);
results.forEach((out, i) => console.log(`Asset ${i + 1}:`, out[0]));
By options — same asset, 4 different periods in parallel: