DM — Directional Movement

Raw directional movement values before smoothing. +DM captures upward movement; -DM captures downward movement.

Inputs: [high, low] | Options: [period] | Outputs: [plus_dm, minus_dm]

Basic

RustCGoJavaPythonNode.jsWASM

use tulip_rs::indicators::dm::{Dm, 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) = Dm::indicator(&inputs, &[14.0], None).unwrap();
println!("+DM: {:?}", outputs[0]);
println!('-DM: {:?}', outputs[1]);

// 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) = Dm::indicator(&[partial_high.as_slice(), partial_low.as_slice()], &[14.0], None).unwrap();
println!("+DM: {:?}", outputs2[0]);
println!('-DM: {:?}', outputs2[1]);

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!("+DM continued: {:?}", continued[0]);
println!('-DM continued: {:?}', continued[1]);

#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[DM_OPTIONS] = {14.0}; // period
const double *inputs[DM_INPUTS] = {high, low};

/* Full computation (check r.error == C_INDICATOR_ERROR_OK in real code) */
CIndicatorResult r = dm_indicator(inputs, 10, options, NULL, 0);
/* r.outputs[0] -> plus_dm, length r.output_lens[0] */
/* r.outputs[1] -> minus_dm, length r.output_lens[1] */
tulip_ffi_result_free(r);
dm_state_free(r.state);

/* Partial computation + state continuation */
CIndicatorResult p = dm_indicator(inputs, 8, options, NULL, 0);
double new_high[] = {85.90};
double new_low[]  = {84.03};
const double *new_inputs[DM_INPUTS] = {new_high, new_low};
CBatchResult b = dm_batch(p.state, new_inputs, 1, NULL, 0);
/* b.outputs[0] -> plus_dm for the one new bar */
tulip_ffi_batch_result_free(b);
tulip_ffi_result_free(p);
dm_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{14.0} // period

// Full computation — Rows is [+dm, -dm], valid until Close.
res, st, _ := indicators.Dm.Indicator(high, low, options, nil)
fmt.Println("+DM:", res.Rows[0])
fmt.Println("-DM:", res.Rows[1])
res.Close()
st.Close()

// Partial computation + state continuation.
res2, st2, _ := indicators.Dm.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("+DM continued:", batch.Rows[0])
fmt.Println("-DM continued:", batch.Rows[1])
batch.Close()
st2.Close()

import org.tuliprs.*;
import org.tuliprs.indicators.Dm;

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 = {14.0}; // period

// Full computation — output rows are zero-copy views, valid until close().
Outcome oc = Dm.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))); // +DM
    System.out.println(java.util.Arrays.toString(res.toDoubleArray(1))); // -DM
}

// Partial computation + state continuation.
int n = 8;
Outcome p = Dm.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))); // +DM continued
        System.out.println(java.util.Arrays.toString(br.toDoubleArray(1))); // -DM continued
    }
}

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.dm.indicator([high, low], [14.0])
print(outputs[0])  # Plus DM
print(outputs[1])  # Minus DM

# 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])  # Plus DM continued
print(continued[1])  # Minus DM continued

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.dm.indicator([high, low], [14]);
console.log('+DM:', outputs[0]);
console.log('-DM:', outputs[1]);

// State continuation
const n = high.length - 5;
const [, state2] = ti.dm.indicator([high.slice(0, n), low.slice(0, n)], [14]);
const continued = state2.batchIndicator([high.slice(n), low.slice(n)]);
console.log('Continued +DM:', 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.dm.indicator([high, low], [14]);
console.log('+DM:', outputs[0]);
console.log('-DM:', outputs[1]);

// State continuation
const n = high.length - 5;
const [, state2] = ti.dm.indicator([high.slice(0, n), low.slice(0, n)], [14]);
const continued = state2.batchIndicator([high.slice(n), low.slice(n)]);
console.log('Continued +DM:', continued[0]);

SIMD

RustCGoJavaPythonNode.js

By assets — same options, N assets in parallel:

use tulip_rs::indicators::dm::{Dm, 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 = Dm::indicator_by_assets::<4>(&inputs, &[14.0], None).unwrap();
for (i, asset_outputs) in results.iter().enumerate() {
    println!("Asset {} +DM: {:?}", i + 1, asset_outputs[0]);
    println!("Asset {} -DM: {:?}", i + 1, asset_outputs[1]);
}

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

use tulip_rs::indicators::dm::{Dm, IndicatorByOptions};

let opts: [&[f64; 1]; 4] = [&[7.0], &[14.0], &[21.0], &[28.0]];
let results = Dm::indicator_by_options::<4>(&inputs, &opts, None).unwrap();
for (i, out) in results.iter().enumerate() {
    println!("Period {} +DM: {:?}", opts[i][0], out[0]);
    println!("Period {} -DM: {:?}", opts[i][0], out[1]);
}

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 h1[] = {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 h2[] = {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[DM_INPUTS] = {h1, l1};
const double *asset2[DM_INPUTS] = {h2, l2};
const double *const *const simd_inputs[4] = {asset1, asset2, NULL, NULL}; /* N=4 lanes */
double options[DM_OPTIONS] = {14.0};

CSimdResult r = dm_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 plus_dm, length r.output_lens[i][0] */
    /* r.outputs[i][1] -> asset i's minus_dm, length r.output_lens[i][1] */
    dm_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[DM_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[DM_INPUTS] = {high_expanded, low_expanded};

static const double o7[DM_OPTIONS]   = {7.0};
static const double o14[DM_OPTIONS]  = {14.0};
static const double o21[DM_OPTIONS]  = {21.0};
static const double o28[DM_OPTIONS]  = {28.0};
const double *const simd_opts[4] = {o7, o14, o21, o28};

CSimdResult r = dm_simd_by_options(expanded_inputs, EXPANDED_LEN, simd_opts, 4, NULL, 0);
for (uintptr_t i = 0; i < r.num_results; i++) dm_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):

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.DmInputs][]float64{{h1, l1}, {h2, l2}, {h3, l3}, {h4, l4}}
sim, _ := indicators.Dm.SimdByAssets(assets, []float64{14.0}, nil)
for i, lanes := range sim.Results {
    fmt.Printf("Asset %d +DM: %v\n", i+1, lanes[0])
    fmt.Printf("Asset %d -DM: %v\n", i+1, lanes[1])
}
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 so longer-period option sets have enough data
expandedHigh := make([]float64, len(high)*20)
expandedLow := make([]float64, len(low)*20)
for i := 0; i < 20; i++ {
    copy(expandedHigh[i*len(high):], high)
    copy(expandedLow[i*len(low):], low)
}

sim2, _ := indicators.Dm.SimdByOptions(expandedHigh, expandedLow, [][]float64{{7.0}, {14.0}, {21.0}, {28.0}}, nil)
for i, lanes := range sim2.Results {
    fmt.Printf("Period %d +DM: %v\n", i+1, lanes[0])
    fmt.Printf("Period %d -DM: %v\n", i+1, lanes[1])
}
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.Dm;

// (h1/l1 data as in the Go tab)
double[] h2 = h1, l2 = l1; // Reuse same data for assets 2-4 in this example
double[] h3 = h1, l3 = l1;
double[] h4 = h1, l4 = l1;

double[][][] assets = {{h1, l1}, {h2, l2}, {h3, l3}, {h4, l4}};
try (SimdResult sim = Dm.simdByAssets(assets, new double[] {14.0}, null)) {
    for (int i = 0; i < sim.numResults(); i++) {
        System.out.printf("Asset %d +DM: %s%n", i + 1,
            java.util.Arrays.toString(sim.toDoubleArray(i, 0)));
        System.out.printf("Asset %d -DM: %s%n", i + 1,
            java.util.Arrays.toString(sim.toDoubleArray(i, 1)));
    }
}   // 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.Dm;

// (high/low series as in the Go tab)
double[] expandedHigh = new double[high.length * 20];
double[] expandedLow = new double[low.length * 20];
for (int i = 0; i < 20; i++) {
    System.arraycopy(high, 0, expandedHigh, i * high.length, high.length);
    System.arraycopy(low, 0, expandedLow, i * low.length, low.length);
}

try (SimdResult sim = Dm.simdByOptions(new double[][] {expandedHigh, expandedLow},
        new double[][] {{7.0}, {14.0}, {21.0}, {28.0}}, null)) {
    for (int i = 0; i < sim.numResults(); i++) {
        System.out.printf("Period %d +DM: %s%n", i + 1,
            java.util.Arrays.toString(sim.toDoubleArray(i, 0)));
        System.out.printf("Period %d -DM: %s%n", i + 1,
            java.util.Arrays.toString(sim.toDoubleArray(i, 1)));
    }
}

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.dm.simd_by_assets(simd_inputs, [14.0])
for i, asset_outputs in enumerate(outputs_list):
    print(f"Asset {i+1} +DM: {asset_outputs[0]}")
    print(f"Asset {i+1} -DM: {asset_outputs[1]}")

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

simd_options = [[7.0], [14.0], [21.0], [28.0]]
outputs_list, states = tulip_rs.indicators.dm.simd_by_options([high, low], simd_options)
for i, out in enumerate(outputs_list):
    print(f"Period {simd_options[i][0]} +DM: {out[0]}")
    print(f"Period {simd_options[i][0]} -DM: {out[1]}")

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.dm.simdByAssets(simdInputs, [14]);
results.forEach((out, i) => console.log(`Asset ${i + 1} +DM:`, out[0], '-DM:', out[1]));

By options — same asset, 4 different periods in parallel:

const simdOptions = [[7], [14], [21], [28]];
const [results] = ti.dm.simdByOptions([high, low], simdOptions);
results.forEach((out, i) => console.log(`Period ${simdOptions[i][0]} +DM:`, out[0], '-DM:', out[1]));