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SMA Envelope

Three bands around a Simple Moving Average. middle = SMA(real, period), upper = SMA + SMA × (percentage / 100), lower = SMA − SMA × (percentage / 100). The envelope expands and contracts proportionally with the SMA level. Used to identify overbought/oversold conditions relative to the prevailing trend. Rendered as a price overlay.

Inputs: [real]  |  Options: [period, percentage]  |  Outputs: [lower, middle, upper]

Basic

use tulip_rs::indicators::smaenvelope::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, percentage]
let (outputs, _state) = indicator(&[close.as_slice()], &[14.0, 2.5], None).unwrap();
println!("Lower:  {:?}", outputs[0]);
println!("Middle: {:?}", outputs[1]);
println!("Upper:  {:?}", outputs[2]);

// State continuation
let (outputs2, mut state) = indicator(&[&close[..8]], &[14.0, 2.5], None).unwrap();
println!("Partial Lower:  {:?}", outputs2[0]);
println!("Partial Middle: {:?}", outputs2[1]);
println!("Partial Upper:  {:?}", outputs2[2]);

let continued = state.batch_indicator(&[&close[8..]], None).unwrap();
println!("Continued Lower:  {:?}", continued[0]);
println!("Continued Middle: {:?}", continued[1]);
println!("Continued Upper:  {:?}", 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, percentage]
outputs, state = tulip_rs.indicators.smaenvelope.indicator([close], [14.0, 2.5])
print("Lower: ", outputs[0])
print("Middle:", outputs[1])
print("Upper: ", outputs[2])

# State continuation
outputs2, state = tulip_rs.indicators.smaenvelope.indicator([close[:8]], [14.0, 2.5])
print("Partial Lower: ", outputs2[0])
print("Partial Middle:", outputs2[1])
print("Partial Upper: ", outputs2[2])

continued = state.batch_indicator([close[8:]])
print("Continued Lower: ", continued[0])
print("Continued Middle:", continued[1])
print("Continued Upper: ", continued[2])

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]);

// options: [period, percentage]
const [outputs, state] = ti.smaenvelope.indicator([close], [14, 2.5]);
console.log('SMA Envelope Lower:', outputs[0]);
console.log('SMA Envelope Middle:', outputs[1]);
console.log('SMA Envelope Upper:', outputs[2]);

// State continuation
const n = close.length - 5;
const [, state2] = ti.smaenvelope.indicator([close.slice(0, n)], [14, 2.5]);
const continued = state2.batchIndicator([close.slice(n)]);
console.log('Continued Lower:', continued[0]);
console.log('Continued Middle:', continued[1]);
console.log('Continued Upper:', continued[2]);

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];

// options: [period, percentage]
const [outputs, state] = ti.smaenvelope.indicator([close], [14, 2.5]);
console.log('SMA Envelope Lower:', outputs[0]);
console.log('SMA Envelope Middle:', outputs[1]);
console.log('SMA Envelope Upper:', outputs[2]);

// State continuation
const n = close.length - 5;
const [, state2] = ti.smaenvelope.indicator([close.slice(0, n)], [14, 2.5]);
const continued = state2.batchIndicator([close.slice(n)]);
console.log('Continued Lower:', continued[0]);
console.log('Continued Middle:', continued[1]);
console.log('Continued Upper:', continued[2]);

SIMD

By assets — same options applied to 4 assets in parallel:

use tulip_rs::indicators::smaenvelope::indicator_by_assets;

let a1 = vec![81.59, 81.06, 82.87, 83.00, 83.61, 83.15, 82.84, 83.99, 84.55, 84.36_f64];
let a2 = a1.iter().map(|x| x + 5.0).collect::<Vec<_>>();
let a3 = a1.iter().map(|x| x - 5.0).collect::<Vec<_>>();
let a4 = a1.iter().map(|x| x * 1.02).collect::<Vec<_>>();

let inputs: [&[&[f64]; 1]; 4] = [
    &[a1.as_slice()],
    &[a2.as_slice()],
    &[a3.as_slice()],
    &[a4.as_slice()],
];

let results = indicator_by_assets::<4>(&inputs, &[14.0, 2.5], None).unwrap();
for (i, asset_outputs) in results.0.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, 4 different option sets in parallel:

use tulip_rs::indicators::smaenvelope::indicator_by_options;

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 opts: [&[f64; 2]; 4] = [
    &[10.0, 2.0],
    &[14.0, 2.5],
    &[20.0, 3.0],
    &[50.0, 5.0],
];

let results = indicator_by_options::<4>(&[close.as_slice()], &opts, None).unwrap();
for (i, opt_outputs) in results.0.iter().enumerate() {
    println!("Option set {} Lower:  {:?}", i + 1, opt_outputs[0]);
    println!("Option set {} Middle: {:?}", i + 1, opt_outputs[1]);
    println!("Option set {} Upper:  {:?}", i + 1, opt_outputs[2]);
}

By assets — same options applied to N assets in parallel (must be 2, 4, 8, or 16):

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)

simd_inputs = [
    [close],
    [close + 5.0],
    [close - 5.0],
    [close * 1.02],
]
outputs_list, states = tulip_rs.indicators.smaenvelope.simd_by_assets(simd_inputs, [14.0, 2.5])
for i, out in enumerate(outputs_list):
    print(f"Asset {i + 1} Lower:  {out[0]}")
    print(f"Asset {i + 1} Middle: {out[1]}")
    print(f"Asset {i + 1} Upper:  {out[2]}")

By options — same asset, N different option sets in parallel:

simd_options = [
    [10.0, 2.0],
    [14.0, 2.5],
    [20.0, 3.0],
    [50.0, 5.0],
]
outputs_list, states = tulip_rs.indicators.smaenvelope.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.smaenvelope.simdByAssets(simdInputs, [14, 2.5]);
results.forEach((out, i) => {
    console.log(`Asset ${i + 1} Lower:`, out[0]);
    console.log(`Asset ${i + 1} Middle:`, out[1]);
    console.log(`Asset ${i + 1} Upper:`, out[2]);
});

By options — same asset, 4 different option sets in parallel:

const simdOptions = [[10, 2.0], [14, 2.5], [20, 3.0], [50, 5.0]];
const [results] = ti.smaenvelope.simdByOptions([close], simdOptions);
results.forEach((out, i) => console.log(`Option set ${i + 1}:`, out[0], out[1], out[2]));