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::indicator;
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) = 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 new_close = vec![85.10, 85.72_f64];
let continued = state.batch_indicator(&[new_close.as_slice()], None).unwrap();
println!("Lower continued: {:?}", continued[0]);
println!("Middle continued: {:?}", continued[1]);
println!("Upper continued: {:?}", continued[2]);
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 = [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¶
By assets — same options, N assets in parallel:
use tulip_rs::indicators::bbands::indicator_by_assets;
let inputs: [&[&[f64]; 1]; 4] = [
&[asset1_close.as_slice()],
&[asset2_close.as_slice()],
&[asset3_close.as_slice()],
&[asset4_close.as_slice()],
];
let results = 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::indicator_by_options;
let opts: [&[f64; 2]; 4] = [&[10.0, 1.5], &[20.0, 2.0], &[30.0, 2.0], &[50.0, 2.5]];
let results = 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, 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]], [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: