BBands — Bollinger Bands¶
Three bands plotted around a moving average. The width expands and contracts with volatility.
Inputs: [real] | Options: [period, stddev_multiplier] | Outputs: [lower, middle, upper]
Basic¶
use tulip_rs::indicators::bbands::{BBands, 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];
// options: [period, stddev_multiplier]
let (outputs, mut state) = BBands::indicator(&[close.as_slice()], &[20.0, 2.0], None).unwrap();
println!("Lower: {:?}", outputs[0]);
println!("Middle: {:?}", outputs[1]);
println!("Upper: {:?}", outputs[2]);
// State continuation — feed new bars without reprocessing history
let partial = close[..8].to_vec();
let (outputs2, mut state) = BBands::indicator(&[partial.as_slice()], &[20.0, 2.0], None).unwrap();
println!("Lower: {:?}", outputs2[0]);
println!("Middle: {:?}", outputs2[1]);
let new_close = vec![85.53_f64];
let continued = state.batch_indicator(&[new_close.as_slice()], None).unwrap();
println!("Lower continued: {:?}", 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[BBANDS_OPTIONS] = {20.0, 2.0}; // period, std_dev
const double *inputs[BBANDS_INPUTS] = {close};
/* Full computation (check r.error == C_INDICATOR_ERROR_OK in real code) */
CIndicatorResult r = bbands_indicator(inputs, 10, options, NULL, 0);
/* r.outputs[0] -> lower_band, r.outputs[1] -> middle_band, r.outputs[2] -> upper_band */
tulip_ffi_result_free(r);
bbands_state_free(r.state);
/* Partial computation + state continuation */
CIndicatorResult p = bbands_indicator(inputs, 8, options, NULL, 0);
double new_close[] = {85.53};
const double *new_inputs[BBANDS_INPUTS] = {new_close};
CBatchResult b = bbands_batch(p.state, new_inputs, 1, NULL, 0);
/* b.outputs[0] -> lower_band for the one new bar */
tulip_ffi_batch_result_free(b);
tulip_ffi_result_free(p);
bbands_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{20.0, 2.0} // period, std_dev
// Full computation — Rows are zero-copy views, valid until Close.
res, st, _ := indicators.Bbands.Indicator(close, options, nil)
fmt.Println(res.Rows[0]) // Lower band
fmt.Println(res.Rows[1]) // Middle band
fmt.Println(res.Rows[2]) // Upper band
res.Close()
st.Close()
// Partial computation + state continuation.
res2, st2, _ := indicators.Bbands.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 lower band
batch.Close()
st2.Close()
import org.tuliprs.*;
import org.tuliprs.indicators.Bbands;
double[] close = {81.59, 81.06, 82.87, 83.00, 83.61,
83.15, 82.84, 83.99, 84.55, 84.36};
double[] options = {20.0, 2.0}; // period, std_dev
// Full computation — output rows are zero-copy views, valid until close().
Outcome oc = Bbands.indicator(new double[][] {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
System.out.println(java.util.Arrays.toString(res.toDoubleArray(2))); // Upper band
}
// Partial computation + state continuation.
Outcome p = Bbands.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) {
System.out.println(java.util.Arrays.toString(br.toDoubleArray(0))); // continued lower band
}
}
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)
# options: [period, stddev_multiplier]
outputs, state = tulip_rs.indicators.bbands.indicator([close], [20.0, 2.0])
print(outputs[0]) # Lower band
print(outputs[1]) # Middle band
print(outputs[2]) # Upper band
# State continuation
new_close = np.array([85.10, 85.72], dtype=np.float64)
continued = state.batch_indicator([new_close])
print(continued[0]) # Lower continued
print(continued[1]) # Middle continued
print(continued[2]) # Upper continued
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.bbands.indicator([close], [20, 2]);
console.log('Lower:', outputs[0]);
console.log('Middle:', outputs[1]);
console.log('Upper:', outputs[2]);
// State continuation
const [, state2] = ti.bbands.indicator([close.slice(0, -5)], [20, 2]);
const continued = state2.batchIndicator([close.slice(-5)]);
console.log('Continued Lower:', 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.bbands.indicator([close], [20, 2]);
console.log('Lower:', outputs[0]);
console.log('Middle:', outputs[1]);
console.log('Upper:', outputs[2]);
// State continuation
const [, state2] = ti.bbands.indicator([close.slice(0, -5)], [20, 2]);
const continued = state2.batchIndicator([close.slice(-5)]);
console.log('Continued Lower:', continued[0]);
SIMD¶
use tulip_rs::indicators::bbands::{BBands, Indicator};
let inputs: [&[&[f64]; 1]; 4] = [
&[asset1_close.as_slice()],
&[asset2_close.as_slice()],
&[asset3_close.as_slice()],
&[asset4_close.as_slice()],
];
let results = BBands::indicator_by_assets::<4>(&inputs, &[20.0, 2.0], None).unwrap();
for (i, asset_outputs) in results.iter().enumerate() {
println!("Asset {} Lower: {:?}", i + 1, asset_outputs[0]);
println!("Asset {} Middle: {:?}", i + 1, asset_outputs[1]);
println!("Asset {} Upper: {:?}", i + 1, asset_outputs[2]);
}
By options — same asset, N option sets in parallel:
use tulip_rs::indicators::bbands::{BBands, IndicatorByOptions};
let opts: [&[f64; 2]; 4] = [&[10.0, 1.5], &[20.0, 2.0], &[30.0, 2.0], &[50.0, 2.5]];
let results = BBands::indicator_by_options::<4>(&[close.as_slice()], &opts, None).unwrap();
for (i, out) in results.iter().enumerate() {
println!("Option set {} Lower: {:?}", i + 1, out[0]);
println!("Option set {} Middle: {:?}", i + 1, out[1]);
println!("Option set {} Upper: {:?}", i + 1, out[2]);
}
By assets — same options applied to 4 assets in one call (N must be 2/4/8/16):
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 [INPUTS]-long pointer array per asset */
const double *asset1[BBANDS_INPUTS] = {a1};
const double *asset2[BBANDS_INPUTS] = {a2};
const double *asset3[BBANDS_INPUTS] = {a3};
const double *asset4[BBANDS_INPUTS] = {a4};
const double *const *const simd_inputs[4] = {asset1, asset2, asset3, asset4};
CSimdResult r = bbands_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 lower_band */
bbands_state_free(r.states[i]);
}
tulip_ffi_simd_result_free(r);
By options — same asset, 4 different periods in one call:
double o10[] = {10.0}, o20[] = {20.0}, o30[] = {30.0}, o50[] = {50.0};
const double *const simd_opts[4] = {o10, o20, o30, o50};
CSimdResult r = bbands_simd_by_options(inputs, 10, simd_opts, 4, NULL, 0);
/* r.outputs[i] -> results for option set i */
for (uintptr_t i = 0; i < r.num_results; i++) bbands_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):
close := []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 := close, close, close
assets := [][indicators.BbandsInputs][]float64{{close}, {a2}, {a3}, {a4}}
sim, _ := indicators.Bbands.SimdByAssets(assets, []float64{20.0, 2.0}, nil)
for i, lanes := range sim.Results {
fmt.Printf("Asset %d Lower: %v\n", i+1, lanes[0])
fmt.Printf("Asset %d Middle: %v\n", i+1, lanes[1])
fmt.Printf("Asset %d Upper: %v\n", i+1, lanes[2])
}
sim.Close() // frees every lane state, then the SIMD buffers
By options — same asset, N option sets in parallel:
sim2, _ := indicators.Bbands.SimdByOptions(close, [][]float64{{10.0, 1.5}, {20.0, 2.0}, {30.0, 2.0}, {50.0, 2.5}}, nil)
for i, lanes := range sim2.Results {
fmt.Printf("Option set %d Lower: %v\n", i+1, lanes[0])
fmt.Printf("Option set %d Middle: %v\n", i+1, lanes[1])
fmt.Printf("Option set %d Upper: %v\n", i+1, lanes[2])
}
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.Bbands;
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 = Bbands.simdByAssets(assets, new double[] {20.0, 2.0}, null)) {
for (int i = 0; i < sim.numResults(); i++) {
System.out.printf("Asset %d Lower: %s%n", i + 1,
java.util.Arrays.toString(sim.toDoubleArray(i, 0)));
System.out.printf("Asset %d Middle: %s%n", i + 1,
java.util.Arrays.toString(sim.toDoubleArray(i, 1)));
System.out.printf("Asset %d Upper: %s%n", i + 1,
java.util.Arrays.toString(sim.toDoubleArray(i, 2)));
}
} // frees every lane state, then the SIMD buffers (contractual order)
By options — same asset, N option sets in parallel:
import org.tuliprs.*;
import org.tuliprs.indicators.Bbands;
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 = Bbands.simdByOptions(new double[][] {close},
new double[][] {{10.0, 1.5}, {20.0, 2.0}, {30.0, 2.0}, {50.0, 2.5}}, null)) {
for (int i = 0; i < sim.numResults(); i++) {
System.out.printf("Option set %d Lower: %s%n", i + 1,
java.util.Arrays.toString(sim.toDoubleArray(i, 0)));
System.out.printf("Option set %d Middle: %s%n", i + 1,
java.util.Arrays.toString(sim.toDoubleArray(i, 1)));
System.out.printf("Option set %d Upper: %s%n", i + 1,
java.util.Arrays.toString(sim.toDoubleArray(i, 2)));
}
}
By assets — same options, N assets in parallel (must be 2, 4, 8, or 16):
simd_inputs = [
[np.array(asset1_close, dtype=np.float64)],
[np.array(asset2_close, dtype=np.float64)],
[np.array(asset3_close, dtype=np.float64)],
[np.array(asset4_close, dtype=np.float64)],
]
outputs_list, states = tulip_rs.indicators.bbands.simd_by_assets(simd_inputs, [20.0, 2.0])
for i, asset_outputs in enumerate(outputs_list):
print(f"Asset {i+1} Lower: {asset_outputs[0]}")
print(f"Asset {i+1} Middle: {asset_outputs[1]}")
print(f"Asset {i+1} Upper: {asset_outputs[2]}")
By options — same asset, N option sets in parallel:
simd_options = [[10.0, 1.5], [20.0, 2.0], [30.0, 2.0], [50.0, 2.5]]
outputs_list, states = tulip_rs.indicators.bbands.simd_by_options([close], simd_options)
for i, out in enumerate(outputs_list):
print(f"Option set {i+1} Lower: {out[0]}")
print(f"Option set {i+1} Middle: {out[1]}")
print(f"Option set {i+1} Upper: {out[2]}")
By assets — same options 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.bbands.simdByAssets(simdInputs, [20, 2]);
results.forEach((out, i) => console.log(`Asset ${i + 1} Lower:`, out[0], 'Middle:', out[1], 'Upper:', out[2]));
By options — same asset, 4 different option sets in parallel: