VWMA — Volume Weighted Moving Average¶
Moving average weighted by trading volume so that high-volume bars have more influence on the average than low-volume bars.
Inputs: [real, volume] | Options: [period] | Outputs: [vwma]
Basic¶
use tulip_rs::indicators::vwma::{Vwma, TIndicatorState, 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];
let volume = vec![5653100.0, 6447400.0, 7690900.0, 3831400.0, 4455100.0,
3798000.0, 3936200.0, 4732000.0, 4841300.0, 3915300.0_f64];
let inputs = [close.as_slice(), volume.as_slice()];
let (outputs, _state) = Vwma::indicator(&inputs, &[14.0], None).unwrap();
println!("VWMA(14): {:?}", outputs[0]);
// State continuation
let partial_close = close[..8].to_vec();
let partial_volume = volume[..8].to_vec();
let inputs2 = [partial_close.as_slice(), partial_volume.as_slice()];
let (outputs2, mut state) = Vwma::indicator(&inputs2, &[14.0], None).unwrap();
println!("Partial VWMA: {:?}", outputs2[0]);
let new_close = close[8..].to_vec();
let new_volume = volume[8..].to_vec();
let new_inputs = [new_close.as_slice(), new_volume.as_slice()];
let continued = state.batch_indicator(&new_inputs, None).unwrap();
println!("Continued VWMA: {:?}", 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 volume[] = {5653100.0, 6447400.0, 7690900.0, 3831400.0, 4455100.0,
3798000.0, 3936200.0, 4732000.0, 4841300.0, 3915300.0};
double options[VWMA_OPTIONS] = {14.0}; // period
const double *inputs[VWMA_INPUTS] = {close, volume};
/* Full computation (check r.error == C_INDICATOR_ERROR_OK in real code) */
CIndicatorResult r = vwma_indicator(inputs, 10, options, NULL, 0);
/* r.outputs[0] -> the VWMA(14) series, length r.output_lens[0] */
tulip_ffi_result_free(r);
vwma_state_free(r.state);
/* Partial computation + state continuation */
CIndicatorResult p = vwma_indicator(inputs, 8, options, NULL, 0);
double new_close[] = {84.55, 84.36};
double new_volume[] = {4841300.0, 3915300.0};
const double *new_inputs[VWMA_INPUTS] = {new_close, new_volume};
CBatchResult b = vwma_batch(p.state, new_inputs, 2, NULL, 0);
/* b.outputs[0] -> VWMA values for just the two new bars */
tulip_ffi_batch_result_free(b);
tulip_ffi_result_free(p);
vwma_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}
volume := []float64{5653100.0, 6447400.0, 7690900.0, 3831400.0, 4455100.0,
3798000.0, 3936200.0, 4732000.0, 4841300.0, 3915300.0}
options := []float64{14.0} // period
// Full computation — Rows are zero-copy views, valid until Close.
res, st, _ := indicators.Vwma.Indicator(close, volume, options, nil)
fmt.Println(res.Rows[0]) // VWMA(14) values
res.Close()
st.Close()
// Partial computation + state continuation.
res2, st2, _ := indicators.Vwma.Indicator(close[:8], volume[:8], options, nil)
res2.Close() // outputs consumed or closed; state stays live
batch, _ := st2.Batch(close[8:], volume[8:], nil)
fmt.Println(batch.Rows[0]) // continued VWMA values
batch.Close()
st2.Close()
import org.tuliprs.*;
import org.tuliprs.indicators.Vwma;
double[] close = {81.59, 81.06, 82.87, 83.00, 83.61,
83.15, 82.84, 83.99, 84.55, 84.36};
double[] volume = {5653100.0, 6447400.0, 7690900.0, 3831400.0, 4455100.0,
3798000.0, 3936200.0, 4732000.0, 4841300.0, 3915300.0};
double[] options = {14.0}; // period
// Full computation — output rows are zero-copy views, valid until close().
Outcome oc = Vwma.indicator(new double[][] {close, volume}, options);
try (Result res = oc.result(); State st = oc.state()) {
System.out.println(java.util.Arrays.toString(res.toDoubleArray(0))); // VWMA(14) values
}
// Partial computation + state continuation.
int n = 8;
Outcome p = Vwma.indicator(new double[][] {
java.util.Arrays.copyOfRange(close, 0, n),
java.util.Arrays.copyOfRange(volume, 0, n)}, options);
try (Result pr = p.result(); State st = p.state()) {
Result br = st.batch(new double[][] {
java.util.Arrays.copyOfRange(close, n, 10),
java.util.Arrays.copyOfRange(volume, n, 10)});
try (br) {
System.out.println(java.util.Arrays.toString(br.toDoubleArray(0))); // continued VWMA values
}
}
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)
volume = np.array([5653100.0, 6447400.0, 7690900.0, 3831400.0, 4455100.0,
3798000.0, 3936200.0, 4732000.0, 4841300.0, 3915300.0], dtype=np.float64)
outputs, state = tulip_rs.indicators.vwma.indicator([close, volume], [14.0])
print("VWMA(14):", outputs[0])
# State continuation
partial_close = close[:8]
partial_volume = volume[:8]
outputs2, state = tulip_rs.indicators.vwma.indicator([partial_close, partial_volume], [14.0])
new_close = close[8:]
new_volume = volume[8:]
continued = state.batch_indicator([new_close, new_volume])
print("Continued VWMA:", continued[0])
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 volume = Float64Array.from([5653100, 6447400, 7690900, 3831400, 4455100,
3798000, 3936200, 4732000, 4841300, 3915300,
6830800, 6694100, 5293600, 7985800, 4807900]);
const [outputs, state] = ti.vwma.indicator([close, volume], [14]);
console.log('VWMA(14):', outputs[0]);
// State continuation
const n = close.length - 5;
const [, state2] = ti.vwma.indicator([close.slice(0, n), volume.slice(0, n)], [14]);
const continued = state2.batchIndicator([close.slice(n), volume.slice(n)]);
console.log('Continued VWMA:', 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 volume = [5653100, 6447400, 7690900, 3831400, 4455100,
3798000, 3936200, 4732000, 4841300, 3915300,
6830800, 6694100, 5293600, 7985800, 4807900];
const [outputs, state] = ti.vwma.indicator([close, volume], [14]);
console.log('VWMA(14):', outputs[0]);
// State continuation
const n = close.length - 5;
const [, state2] = ti.vwma.indicator([close.slice(0, n), volume.slice(0, n)], [14]);
const continued = state2.batchIndicator([close.slice(n), volume.slice(n)]);
console.log('Continued VWMA:', continued[0]);
SIMD¶
By assets — same period applied to 4 assets (each with close + volume) in parallel:
use tulip_rs::indicators::vwma::{Vwma, Indicator};
let a1_close = vec![81.59, 81.06, 82.87, 83.00, 83.61, 83.15, 82.84, 83.99, 84.55, 84.36_f64];
let a1_vol = vec![5653100.0, 6447400.0, 7690900.0, 3831400.0, 4455100.0,
3798000.0, 3936200.0, 4732000.0, 4841300.0, 3915300.0_f64];
let a2_close = a1_close.iter().map(|x| x + 5.0).collect::<Vec<_>>();
let a2_vol = a1_vol.clone();
let a3_close = a1_close.iter().map(|x| x - 5.0).collect::<Vec<_>>();
let a3_vol = a1_vol.clone();
let a4_close = a1_close.iter().map(|x| x * 1.02).collect::<Vec<_>>();
let a4_vol = a1_vol.clone();
let inputs: [&[&[f64]; 2]; 4] = [
&[a1_close.as_slice(), a1_vol.as_slice()],
&[a2_close.as_slice(), a2_vol.as_slice()],
&[a3_close.as_slice(), a3_vol.as_slice()],
&[a4_close.as_slice(), a4_vol.as_slice()],
];
let results = Vwma::indicator_by_assets::<4>(&inputs, &[14.0], None).unwrap();
for (i, asset_outputs) in results.iter().enumerate() {
println!("Asset {}: {:?}", i + 1, asset_outputs[0]);
}
By options — same asset, 4 different periods in parallel:
use tulip_rs::indicators::vwma::{Vwma, IndicatorByOptions};
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 volume = vec![5653100.0, 6447400.0, 7690900.0, 3831400.0, 4455100.0,
3798000.0, 3936200.0, 4732000.0, 4841300.0, 3915300.0_f64];
let opts: [&[f64; 1]; 4] = [&[5.0], &[10.0], &[14.0], &[20.0]];
let results = Vwma::indicator_by_options::<4>(&[close.as_slice(), volume.as_slice()], &opts, None).unwrap();
for (i, opt_outputs) in results.iter().enumerate() {
println!("Period set {}: {:?}", i + 1, opt_outputs[0]);
}
By assets — same period applied to 4 assets (each with close + volume) in one call (N must be 2/4/8/16):
double a1_close[] = {81.59, 81.06, 82.87, 83.00, 83.61, 83.15, 82.84, 83.99, 84.55, 84.36};
double a1_vol[] = {5653100.0, 6447400.0, 7690900.0, 3831400.0, 4455100.0,
3798000.0, 3936200.0, 4732000.0, 4841300.0, 3915300.0};
double a2_close[] = {a1_close[0]*1.1, a1_close[1]*1.1, a1_close[2]*1.1,
a1_close[3]*1.1, a1_close[4]*1.1, a1_close[5]*1.1,
a1_close[6]*1.1, a1_close[7]*1.1, a1_close[8]*1.1,
a1_close[9]*1.1};
double a2_vol[] = {a1_vol[0]*1.1, a1_vol[1]*1.1, a1_vol[2]*1.1,
a1_vol[3]*1.1, a1_vol[4]*1.1, a1_vol[5]*1.1,
a1_vol[6]*1.1, a1_vol[7]*1.1, a1_vol[8]*1.1,
a1_vol[9]*1.1};
double a3_close[] = {a1_close[0]*0.9, a1_close[1]*0.9, a1_close[2]*0.9,
a1_close[3]*0.9, a1_close[4]*0.9, a1_close[5]*0.9,
a1_close[6]*0.9, a1_close[7]*0.9, a1_close[8]*0.9,
a1_close[9]*0.9};
double a3_vol[] = {a1_vol[0]*0.9, a1_vol[1]*0.9, a1_vol[2]*0.9,
a1_vol[3]*0.9, a1_vol[4]*0.9, a1_vol[5]*0.9,
a1_vol[6]*0.9, a1_vol[7]*0.9, a1_vol[8]*0.9,
a1_vol[9]*0.9};
double a4_close[] = {a1_close[0]*1.02, a1_close[1]*1.02, a1_close[2]*1.02,
a1_close[3]*1.02, a1_close[4]*1.02, a1_close[5]*1.02,
a1_close[6]*1.02, a1_close[7]*1.02, a1_close[8]*1.02,
a1_close[9]*1.02};
double a4_vol[] = {a1_vol[0]*1.02, a1_vol[1]*1.02, a1_vol[2]*1.02,
a1_vol[3]*1.02, a1_vol[4]*1.02, a1_vol[5]*1.02,
a1_vol[6]*1.02, a1_vol[7]*1.02, a1_vol[8]*1.02,
a1_vol[9]*1.02};
/* one [INPUTS]-long pointer array per asset */
const double *asset1[VWMA_INPUTS] = {a1_close, a1_vol};
const double *asset2[VWMA_INPUTS] = {a2_close, a2_vol};
const double *asset3[VWMA_INPUTS] = {a3_close, a3_vol};
const double *asset4[VWMA_INPUTS] = {a4_close, a4_vol};
const double *const *const simd_inputs[4] = {asset1, asset2, asset3, asset4};
CSimdResult r = vwma_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 series, length r.output_lens[i][0] */
vwma_state_free(r.states[i]);
}
tulip_ffi_simd_result_free(r);
By options — same asset, 4 different periods in one call:
double o5[] = {5.0}, o10[] = {10.0}, o14[] = {14.0}, o20[] = {20.0};
const double *const simd_opts[4] = {o5, o10, o14, o20};
CSimdResult r = vwma_simd_by_options(inputs, 10, simd_opts, 4, NULL, 0);
/* r.outputs[i] -> results for option set i (periods 5/10/14/20) */
for (uintptr_t i = 0; i < r.num_results; i++) vwma_state_free(r.states[i]);
tulip_ffi_simd_result_free(r);
By assets — same period applied to 4 assets in parallel (lane counts 2/4/8/16):
a1_close := []float64{81.59, 81.06, 82.87, 83.00, 83.61, 83.15, 82.84, 83.99, 84.55, 84.36}
a1_vol := []float64{5653100.0, 6447400.0, 7690900.0, 3831400.0, 4455100.0,
3798000.0, 3936200.0, 4732000.0, 4841300.0, 3915300.0}
// Reuse the same data for assets 2–4 in this example
a2_close, a2_vol := a1_close, a1_vol
a3_close, a3_vol := a1_close, a1_vol
a4_close, a4_vol := a1_close, a1_vol
assets := [][indicators.VwmaInputs][]float64{{a1_close, a1_vol}, {a2_close, a2_vol}, {a3_close, a3_vol}, {a4_close, a4_vol}}
sim, _ := indicators.Vwma.SimdByAssets(assets, []float64{14.0}, nil)
for i, lanes := range sim.Results {
fmt.Printf("Asset %d: %v\n", i+1, lanes[0])
}
sim.Close() // frees every lane state, then the SIMD buffers
By options — same asset, 4 different periods in parallel:
close := []float64{81.59, 81.06, 82.87, 83.00, 83.61,
83.15, 82.84, 83.99, 84.55, 84.36}
volume := []float64{5653100.0, 6447400.0, 7690900.0, 3831400.0, 4455100.0,
3798000.0, 3936200.0, 4732000.0, 4841300.0, 3915300.0}
sim2, _ := indicators.Vwma.SimdByOptions(close, volume, [][]float64{{5}, {10}, {14}, {20}}, nil)
for i, lanes := range sim2.Results {
fmt.Printf("Period set %d: %v\n", i+1, lanes[0])
}
sim2.Close()
By assets — same period applied to 4 assets in parallel (N must be 2, 4, 8, or 16):
import org.tuliprs.*;
import org.tuliprs.indicators.Vwma;
double[] a1_close = {81.59, 81.06, 82.87, 83.00, 83.61, 83.15, 82.84, 83.99, 84.55, 84.36};
double[] a1_vol = {5653100.0, 6447400.0, 7690900.0, 3831400.0, 4455100.0,
3798000.0, 3936200.0, 4732000.0, 4841300.0, 3915300.0};
double[] a2_close = {72.10, 72.85, 73.40, 73.00, 74.20, 74.85, 75.10, 75.60, 76.00, 76.50};
double[] a2_vol = {5653100.0, 6447400.0, 7690900.0, 3831400.0, 4455100.0,
3798000.0, 3936200.0, 4732000.0, 4841300.0, 3915300.0};
double[] a3_close = {55.30, 55.80, 56.10, 56.40, 56.90, 57.20, 57.50, 57.80, 58.10, 58.40};
double[] a3_vol = {5653100.0, 6447400.0, 7690900.0, 3831400.0, 4455100.0,
3798000.0, 3936200.0, 4732000.0, 4841300.0, 3915300.0};
double[] a4_close = {100.1, 100.5, 101.0, 101.3, 101.8, 102.0, 102.5, 103.0, 103.3, 103.8};
double[] a4_vol = {5653100.0, 6447400.0, 7690900.0, 3831400.0, 4455100.0,
3798000.0, 3936200.0, 4732000.0, 4841300.0, 3915300.0};
// One entry per asset; each asset lists its INPUTS series.
double[][][] assets = {{a1_close, a1_vol}, {a2_close, a2_vol}, {a3_close, a3_vol}, {a4_close, a4_vol}};
try (SimdResult sim = Vwma.simdByAssets(assets, new double[] {14.0}, null)) {
for (int i = 0; i < sim.numResults(); i++) {
System.out.printf("Asset %d: %s%n", i + 1,
java.util.Arrays.toString(sim.toDoubleArray(i, 0)));
}
} // 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.Vwma;
double[] close = {81.59, 81.06, 82.87, 83.00, 83.61,
83.15, 82.84, 83.99, 84.55, 84.36};
double[] volume = {5653100.0, 6447400.0, 7690900.0, 3831400.0, 4455100.0,
3798000.0, 3936200.0, 4732000.0, 4841300.0, 3915300.0};
try (SimdResult sim = Vwma.simdByOptions(new double[][] {close, volume},
new double[][] {{5}, {10}, {14}, {20}}, null)) {
for (int i = 0; i < sim.numResults(); i++) {
System.out.printf("Period set %d: %s%n", i + 1,
java.util.Arrays.toString(sim.toDoubleArray(i, 0)));
}
}
By assets — same period 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)
volume = np.array([5653100.0, 6447400.0, 7690900.0, 3831400.0, 4455100.0,
3798000.0, 3936200.0, 4732000.0, 4841300.0, 3915300.0], dtype=np.float64)
a1_close, a1_vol = close, volume
a2_close, a2_vol = close + 5.0, volume
a3_close, a3_vol = close - 5.0, volume
a4_close, a4_vol = close * 1.02, volume
simd_inputs = [
[a1_close, a1_vol],
[a2_close, a2_vol],
[a3_close, a3_vol],
[a4_close, a4_vol],
]
outputs_list, states = tulip_rs.indicators.vwma.simd_by_assets(simd_inputs, [14.0])
for i, out in enumerate(outputs_list):
print(f"Asset {i + 1}: {out[0]}")
By options — same asset, N different periods in parallel:
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)
volume = np.array([5653100.0, 6447400.0, 7690900.0, 3831400.0, 4455100.0,
3798000.0, 3936200.0, 4732000.0, 4841300.0, 3915300.0], dtype=np.float64)
simd_options = [[5.0], [10.0], [14.0], [20.0]]
outputs_list, states = tulip_rs.indicators.vwma.simd_by_options([close, volume], simd_options)
for i, out in enumerate(outputs_list):
print(f"Period set {i + 1}: {out[0]}")
By assets — same period applied to 4 assets in parallel:
const simdInputs = [
[close.slice(), volume.slice()],
[close.map(v => v * 1.1), volume.map(v => v * 1.1)],
[close.map(v => v * 0.9), volume.map(v => v * 0.9)],
[close.map(v => v * 1.02), volume.map(v => v * 1.02)],
];
const [results] = ti.vwma.simdByAssets(simdInputs, [14]);
results.forEach((out, i) => console.log(`Asset ${i + 1}:`, out[0]));
By options — same asset, 4 different periods in parallel: