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Average Price — avgprice

The arithmetic mean of open, high, low, and close for each bar: (O + H + L + C) / 4.

Inputs: [open, high, low, close] | Options: none | Outputs: [avgprice]

Basic

use tulip_rs::indicators::avgprice::indicator;

let open  = [81.85_f64, 81.20, 81.55, 82.91, 83.10, 83.41, 82.71, 82.70, 84.20, 84.25];
let high  = [82.15_f64, 81.89, 83.03, 83.30, 83.85, 83.90, 83.33, 84.30, 84.84, 85.00];
let low   = [81.29_f64, 80.64, 81.31, 82.65, 83.07, 83.11, 82.49, 82.30, 84.15, 84.11];
let close = [81.59_f64, 81.06, 82.87, 83.00, 83.61, 83.15, 82.84, 83.99, 84.55, 84.36];

let inputs = [open.as_slice(), high.as_slice(), low.as_slice(), close.as_slice()];
let (outputs, _) = indicator(&inputs, &[], None).unwrap();
println!("{:?}", outputs[0]);

import numpy as np
import tulip_rs

open_  = np.array([81.85, 81.20, 81.55, 82.91, 83.10, 83.41, 82.71, 82.70, 84.20, 84.25], dtype=np.float64)
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)
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)

outputs, state = tulip_rs.indicators.avgprice.indicator([open_, high, low, close], [])
print(outputs[0])

import * as ti from 'tulip-rs-node';

const open_ = [81.85, 81.20, 81.55, 82.91, 83.10, 83.41, 82.71, 82.70, 84.20, 84.25, 84.03, 85.45, 86.18, 88.00, 87.30];
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.avgprice.indicator([open_, high, low, close], []);
console.log('AvgPrice:', outputs[0]);

// State continuation
const n = high.length - 5;
const [, state2] = ti.avgprice.indicator([open_.slice(0, n), high.slice(0, n), low.slice(0, n), close.slice(0, n)], []);
const continued = state2.batchIndicator([open_.slice(n), high.slice(n), low.slice(n), close.slice(n)]);
console.log('Continued AvgPrice:', continued[0]);

import { init } from 'tulip-rs-wasm';
import * as ti from 'tulip-rs-wasm';

await init(); // bundler resolves the WASM asset automatically

const open_ = [81.85, 81.20, 81.55, 82.91, 83.10, 83.41, 82.71, 82.70, 84.20, 84.25, 84.03, 85.45, 86.18, 88.00, 87.30];
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.avgprice.indicator([open_, high, low, close], []);
console.log('AvgPrice:', outputs[0]);

// State continuation
const n = high.length - 5;
const [, state2] = ti.avgprice.indicator([open_.slice(0, n), high.slice(0, n), low.slice(0, n), close.slice(0, n)], []);
const continued = state2.batchIndicator([open_.slice(n), high.slice(n), low.slice(n), close.slice(n)]);
console.log('Continued AvgPrice:', continued[0]);

SIMD

By assets — same options, N assets in parallel:

use tulip_rs::indicators::avgprice::indicator_by_assets;

let inputs: [&[&[f64]; 4]; 4] = [
    &[o1.as_slice(), h1.as_slice(), l1.as_slice(), c1.as_slice()],
    &[o2.as_slice(), h2.as_slice(), l2.as_slice(), c2.as_slice()],
    &[o3.as_slice(), h3.as_slice(), l3.as_slice(), c3.as_slice()],
    &[o4.as_slice(), h4.as_slice(), l4.as_slice(), c4.as_slice()],
];
let results = indicator_by_assets::<4>(&inputs, &[], None).unwrap();

This indicator has no options, so by-options SIMD does not apply.

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

simd_inputs = [
    [o1, h1, l1, c1],
    [o2, h2, l2, c2],
    [o3, h3, l3, c3],
    [o4, h4, l4, c4],
]
outputs_list, states = tulip_rs.indicators.avgprice.simd_by_assets(simd_inputs, [])

This indicator has no options, so by-options SIMD does not apply.

By assets — applied to 4 assets in parallel:

const simdInputs = [
    [[...open_], [...high], [...low], [...close]],
    [open_.map(v => v * 1.1), high.map(v => v * 1.1), low.map(v => v * 1.1), close.map(v => v * 1.1)],
    [open_.map(v => v * 0.9), high.map(v => v * 0.9), low.map(v => v * 0.9), close.map(v => v * 0.9)],
    [open_.map(v => v * 1.02), high.map(v => v * 1.02), low.map(v => v * 1.02), close.map(v => v * 1.02)],
];
const [results] = ti.avgprice.simdByAssets(simdInputs, []);
results.forEach((out, i) => console.log(`Asset ${i + 1}:`, out[0]));

This indicator has no options, so by-options SIMD does not apply.