MFI — Money Flow Index¶
A volume-weighted RSI. Values above 80 suggest overbought; below 20 oversold.
Inputs: [high, low, close, volume] | Options: [period] | Outputs: [mfi]
Basic¶
use tulip_rs::indicators::mfi::{Mfi, 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 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![1200.0, 1400.0, 1100.0, 1600.0, 1300.0,
900.0, 1500.0, 1800.0, 1000.0, 1700.0_f64];
let inputs = [high.as_slice(), low.as_slice(), close.as_slice(), volume.as_slice()];
let (outputs, mut state) = Mfi::indicator(&inputs, &[14.0], None).unwrap();
println!("{:?}", outputs[0]); // MFI values
// State continuation — feed new bars without reprocessing history
let new_high = vec![85.20_f64];
let new_low = vec![84.50_f64];
let new_close = vec![85.00_f64];
let new_volume = vec![1550.0_f64];
let continued = state.batch_indicator(
&[new_high.as_slice(), new_low.as_slice(),
new_close.as_slice(), new_volume.as_slice()],
None,
).unwrap();
println!("{:?}", continued[0]);
#include "tulip_rs_ffi.h"
const double 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 double 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 double 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 double volume[] = {5653100.0, 6447400.0, 7690900.0, 3831400.0, 4455100.0, 3798000.0,
3936200.0, 4732000.0, 4841300.0, 3915300.0, 6830800.0, 6694100.0,
5293600.0, 7985800.0, 4807900.0};
const double *inputs[MFI_INPUTS] = {high, low, close, volume};
const double options[MFI_OPTIONS] = {14.0}; // period
/* Full computation (check r.error == C_INDICATOR_ERROR_OK in real code) */
CIndicatorResult r = mfi_indicator(inputs, 15, options, NULL, 0);
/* r.outputs[0] -> the MFI series, length r.output_lens[0] */
tulip_ffi_result_free(r);
mfi_state_free(r.state);
/* Partial computation + batch continuation */
CIndicatorResult pr = mfi_indicator(inputs, 10, options, NULL, 0);
const double *rest_inputs[MFI_INPUTS] = {high + 10, low + 10, close + 10, volume + 10};
CBatchResult br = mfi_batch(pr.state, rest_inputs, 5, NULL, 0);
/* br.outputs[0] -> MFI values for just the last 5 bars */
tulip_ffi_batch_result_free(br);
tulip_ffi_result_free(pr);
mfi_state_free(pr.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}
close := []float64{81.59, 81.06, 82.87, 83.00, 83.61,
83.15, 82.84, 83.99, 84.55, 84.36}
volume := []float64{1200.0, 1400.0, 1100.0, 1600.0, 1300.0,
900.0, 1500.0, 1800.0, 1000.0, 1700.0}
options := []float64{14.0} // period
// Full computation — Rows are zero-copy views, valid until Close.
res, st, _ := indicators.Mfi.Indicator(high, low, close, volume, options, nil)
fmt.Println(res.Rows[0]) // MFI values
res.Close()
st.Close()
// Partial computation + state continuation.
res2, st2, _ := indicators.Mfi.Indicator(high[:8], low[:8], close[:8], volume[:8], options, nil)
res2.Close() // outputs consumed or closed; state stays live
batch, _ := st2.Batch(high[8:], low[8:], close[8:], volume[8:], nil)
fmt.Println(batch.Rows[0]) // continued MFI values
batch.Close()
st2.Close()
import org.tuliprs.*;
import org.tuliprs.indicators.Mfi;
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[] close = {81.59, 81.06, 82.87, 83.00, 83.61,
83.15, 82.84, 83.99, 84.55, 84.36};
double[] volume = {1200.0, 1400.0, 1100.0, 1600.0, 1300.0,
900.0, 1500.0, 1800.0, 1000.0, 1700.0};
double[] options = {14.0}; // period
// Full computation — output rows are zero-copy views, valid until close().
Outcome oc = Mfi.indicator(new double[][] {high, low, close, volume}, options);
try (Result res = oc.result(); State st = oc.state()) {
System.out.println(java.util.Arrays.toString(res.toDoubleArray(0))); // MFI values
}
// Partial computation + state continuation.
int n = 8;
Outcome p = Mfi.indicator(new double[][] {
java.util.Arrays.copyOfRange(high, 0, n),
java.util.Arrays.copyOfRange(low, 0, n),
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(high, n, 10),
java.util.Arrays.copyOfRange(low, n, 10),
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 MFI
}
}
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)
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([1200.0, 1400.0, 1100.0, 1600.0, 1300.0,
900.0, 1500.0, 1800.0, 1000.0, 1700.0], dtype=np.float64)
outputs, state = tulip_rs.indicators.mfi.indicator([high, low, close, volume], [14.0])
print(outputs[0]) # MFI values
# State continuation
new_high = np.array([85.20], dtype=np.float64)
new_low = np.array([84.50], dtype=np.float64)
new_close = np.array([85.00], dtype=np.float64)
new_volume = np.array([1550.0], dtype=np.float64)
continued = state.batch_indicator([new_high, new_low, new_close, new_volume])
print(continued[0])
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 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.mfi.indicator([high, low, close, volume], [14]);
console.log('MFI(14):', outputs[0]);
// State continuation
const n = high.length - 5;
const [, state2] = ti.mfi.indicator([high.slice(0, n), low.slice(0, n), close.slice(0, n), volume.slice(0, n)], [14]);
const continued = state2.batchIndicator([high.slice(n), low.slice(n), close.slice(n), volume.slice(n)]);
console.log('Continued MFI:', 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 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.mfi.indicator([high, low, close, volume], [14]);
console.log('MFI(14):', outputs[0]);
// State continuation
const n = high.length - 5;
const [, state2] = ti.mfi.indicator([high.slice(0, n), low.slice(0, n), close.slice(0, n), volume.slice(0, n)], [14]);
const continued = state2.batchIndicator([high.slice(n), low.slice(n), close.slice(n), volume.slice(n)]);
console.log('Continued MFI:', continued[0]);
Optional Outputs¶
mfi exposes 1 optional output: typprice. Pass a boolean mask as the third argument — one bool per optional output, in order.
use tulip_rs::indicators::mfi::{Mfi, Indicator, TIndicatorState};
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 high = close.iter().map(|x| x + 1.0).collect::<Vec<_>>();
let low = close.iter().map(|x| x - 1.0).collect::<Vec<_>>();
let volume = vec![10000.0, 12000.0, 9500.0, 11000.0, 13000.0, 9800.0, 10500.0, 12500.0, 11800.0, 10200.0_f64];
let mask = [true];
let (outputs, _state) = Mfi::indicator(
&[high.as_slice(), low.as_slice(), close.as_slice(), volume.as_slice()],
&[14.0],
Some(&mask),
).unwrap();
let mfi = &outputs[0]; // mfi (primary)
let typprice = &outputs[1]; // typprice (optional — requested)
#include "tulip_rs_ffi.h"
const double close[] = {81.59, 81.06, 82.87, 83.00, 83.61, 83.15, 82.84, 83.99, 84.55, 84.36};
const double high[] = {82.59, 82.06, 83.87, 84.00, 84.61, 84.15, 83.84, 84.99, 85.55, 85.36};
const double low[] = {80.59, 80.06, 81.87, 82.00, 82.61, 82.15, 81.84, 82.99, 83.55, 83.36};
const double volume[] = {10000.0, 12000.0, 9500.0, 11000.0, 13000.0, 9800.0, 10500.0, 12500.0,
11800.0, 10200.0};
const double *inputs[MFI_INPUTS] = {high, low, close, volume};
const double options[MFI_OPTIONS] = {14.0}; // period
bool optional_outputs[1] = {true}; // typprice
CIndicatorResult r = mfi_indicator(inputs, 10, options, optional_outputs, 1);
/* r.outputs[0] -> MFI (primary), r.outputs[1] -> typprice (optional) */
tulip_ffi_result_free(r);
mfi_state_free(r.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}
high := make([]float64, len(close))
low := make([]float64, len(close))
for i, v := range close {
high[i] = v + 1.0
low[i] = v - 1.0
}
volume := []float64{10000.0, 12000.0, 9500.0, 11000.0, 13000.0, 9800.0, 10500.0, 12500.0, 11800.0, 10200.0}
options := []float64{14.0} // period
mask := []bool{true} // typprice
// Full computation — Rows are zero-copy views, valid until Close.
res, st, _ := indicators.Mfi.Indicator(high, low, close, volume, options, mask)
fmt.Println(res.Rows[0]) // mfi (primary)
fmt.Println(res.Rows[1]) // typprice (optional — requested)
res.Close()
st.Close()
import org.tuliprs.*;
import org.tuliprs.indicators.Mfi;
double[] close = {81.59, 81.06, 82.87, 83.00, 83.61, 83.15, 82.84, 83.99, 84.55, 84.36};
double[] high = {82.59, 82.06, 83.87, 84.00, 84.61,
84.15, 83.84, 84.99, 85.55, 85.36};
double[] low = {80.59, 80.06, 81.87, 82.00, 82.61,
82.15, 81.84, 82.99, 83.55, 83.36};
double[] volume = {10000.0, 12000.0, 9500.0, 11000.0, 13000.0,
9800.0, 10500.0, 12500.0, 11800.0, 10200.0};
double[] options = {14.0}; // period
boolean[] mask = {true}; // typprice
// Full computation — output rows are zero-copy views, valid until close().
Outcome oc = Mfi.indicator(new double[][] {high, low, close, volume}, options, mask);
try (Result res = oc.result()) {
System.out.println(java.util.Arrays.toString(res.toDoubleArray(0))); // mfi (primary)
System.out.println(java.util.Arrays.toString(res.toDoubleArray(1))); // typprice (optional — requested)
}
oc.state().close();
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)
high = close + 1.0
low = close - 1.0
volume = np.array([10000.0, 12000.0, 9500.0, 11000.0, 13000.0, 9800.0, 10500.0, 12500.0, 11800.0, 10200.0], dtype=np.float64)
outputs, state = tulip_rs.indicators.mfi.indicator(
[high, low, close, volume], [14.0],
optional_outputs=[True],
)
mfi = outputs[0] # mfi (primary)
typprice = outputs[1] # typprice (optional — requested)
mfi exposes 1 optional output: typprice.
SIMD¶
By assets — same options, N assets in parallel:
use tulip_rs::indicators::mfi::{Mfi, Indicator};
let inputs: [&[&[f64]; 4]; 4] = [
&[h1.as_slice(), l1.as_slice(), c1.as_slice(), v1.as_slice()],
&[h2.as_slice(), l2.as_slice(), c2.as_slice(), v2.as_slice()],
&[h3.as_slice(), l3.as_slice(), c3.as_slice(), v3.as_slice()],
&[h4.as_slice(), l4.as_slice(), c4.as_slice(), v4.as_slice()],
];
let results = Mfi::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, N option sets in parallel:
By assets — same option applied to 4 assets in one call (N must be 2/4/8/16):
const double h1[] = {82.15, 81.89, 83.03, 83.30, 83.85, 83.90, 83.33, 84.30, 84.84, 85.00};
const double l1[] = {81.29, 80.64, 81.31, 82.65, 83.07, 83.11, 82.49, 82.30, 84.15, 84.11};
const double c1[] = {81.59, 81.06, 82.87, 83.00, 83.61, 83.15, 82.84, 83.99, 84.55, 84.36};
const double v1[] = {5653100.0, 6447400.0, 7690900.0, 3831400.0, 4455100.0, 3798000.0,
3936200.0, 4732000.0, 4841300.0, 3915300.0};
const double h2[] = {85.00, 85.50, 86.00, 86.50, 87.00, 87.50, 88.00, 88.50, 89.00, 89.50};
const double l2[] = {84.00, 84.50, 85.00, 85.50, 86.00, 86.50, 87.00, 87.50, 88.00, 88.50};
const double c2[] = {84.50, 85.00, 85.50, 86.00, 86.50, 87.00, 87.50, 88.00, 88.50, 89.00};
const double v2[] = {4500000.0, 5500000.0, 6500000.0, 4000000.0, 4500000.0, 3800000.0,
4200000.0, 5000000.0, 5100000.0, 4100000.0};
const double h3[] = {78.00, 79.00, 80.00, 81.00, 82.00, 83.00, 84.00, 85.00, 86.00, 87.00};
const double l3[] = {77.00, 78.00, 79.00, 80.00, 81.00, 82.00, 83.00, 84.00, 85.00, 86.00};
const double c3[] = {77.50, 78.50, 79.50, 80.50, 81.50, 82.50, 83.50, 84.50, 85.50, 86.50};
const double v3[] = {3500000.0, 4500000.0, 5500000.0, 3000000.0, 3500000.0, 2800000.0,
3200000.0, 4000000.0, 4100000.0, 3100000.0};
const double h4[] = {95.00, 96.00, 97.00, 98.00, 99.00, 100.00, 101.00, 102.00, 103.00, 104.00};
const double l4[] = {94.00, 95.00, 96.00, 97.00, 98.00, 99.00, 100.00, 101.00, 102.00, 103.00};
const double c4[] = {94.50, 95.50, 96.50, 97.50, 98.50, 99.50, 100.50, 101.50, 102.50, 103.50};
const double v4[] = {6500000.0, 7500000.0, 8500000.0, 6000000.0, 6500000.0, 5800000.0,
6200000.0, 7000000.0, 7100000.0, 6100000.0};
const double *const asset1[MFI_INPUTS] = {h1, l1, c1, v1};
const double *const asset2[MFI_INPUTS] = {h2, l2, c2, v2};
const double *const asset3[MFI_INPUTS] = {h3, l3, c3, v3};
const double *const asset4[MFI_INPUTS] = {h4, l4, c4, v4};
const double *const *const simd_inputs[4] = {asset1, asset2, asset3, asset4};
CSimdResult r = mfi_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 MFI series, length r.output_lens[i][0] */
mfi_state_free(r.states[i]);
}
tulip_ffi_simd_result_free(r);
By options — same asset, 4 different periods in parallel:
const double h[] = {82.15, 81.89, 83.03, 83.30, 83.85, 83.90, 83.33, 84.30, 84.84, 85.00};
const double l[] = {81.29, 80.64, 81.31, 82.65, 83.07, 83.11, 82.49, 82.30, 84.15, 84.11};
const double c[] = {81.59, 81.06, 82.87, 83.00, 83.61, 83.15, 82.84, 83.99, 84.55, 84.36};
const double v[] = {5653100.0, 6447400.0, 7690900.0, 3831400.0, 4455100.0, 3798000.0,
3936200.0, 4732000.0, 4841300.0, 3915300.0};
/* 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];
static double close_expanded[EXPANDED_LEN];
static double volume_expanded[EXPANDED_LEN];
for (size_t i = 0; i < 20; i++) {
for (size_t j = 0; j < 10; j++) {
high_expanded[i * 10 + j] = h[j];
low_expanded[i * 10 + j] = l[j];
close_expanded[i * 10 + j] = c[j];
volume_expanded[i * 10 + j] = v[j];
}
}
const double *inputs[MFI_INPUTS] = {high_expanded, low_expanded, close_expanded, volume_expanded};
static const double o7[MFI_OPTIONS] = {7.0};
static const double o14[MFI_OPTIONS] = {14.0};
static const double o21[MFI_OPTIONS] = {21.0};
static const double o28[MFI_OPTIONS] = {28.0};
const double *const simd_opts[4] = {o7, o14, o21, o28};
CSimdResult r = mfi_simd_by_options(inputs, EXPANDED_LEN, simd_opts, 4, NULL, 0);
for (uintptr_t i = 0; i < r.num_results; i++) {
/* r.outputs[i][0] -> asset i's MFI series, length r.output_lens[i][0] */
mfi_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}
c1 := []float64{81.59, 81.06, 82.87, 83.00, 83.61, 83.15, 82.84, 83.99, 84.55, 84.36}
v1 := []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
h2, l2, c2, v2 := h1, l1, c1, v1
h3, l3, c3, v3 := h1, l1, c1, v1
h4, l4, c4, v4 := h1, l1, c1, v1
assets := [][indicators.MfiInputs][]float64{{h1, l1, c1, v1}, {h2, l2, c2, v2}, {h3, l3, c3, v3}, {h4, l4, c4, v4}}
sim, _ := indicators.Mfi.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, N option sets 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}
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}
assets := [][indicators.MfiInputs][]float64{
{high, low, close, volume},
{high, low, close, volume},
{high, low, close, volume},
{high, low, close, volume},
}
opts := [][]float64{{7.0}, {14.0}, {21.0}, {28.0}}
sim, _ := indicators.Mfi.SimdByOptions(high, low, close, volume, opts, nil)
for i, lanes := range sim.Results {
fmt.Printf("Period %v: %v\n", opts[i][0], lanes[0])
}
sim.Close() // frees every lane state, then the SIMD buffers
By assets — same options applied to 4 assets in parallel (lane counts 2/4/8/16):
import org.tuliprs.*;
import org.tuliprs.indicators.Mfi;
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[] c1 = {81.59, 81.06, 82.87, 83.00, 83.61, 83.15, 82.84, 83.99, 84.55, 84.36};
double[] v1 = {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
double[] h2 = h1;
double[] l2 = l1;
double[] c2 = c1;
double[] v2 = v1;
double[] h3 = h1;
double[] l3 = l1;
double[] c3 = c1;
double[] v3 = v1;
double[] h4 = h1;
double[] l4 = l1;
double[] c4 = c1;
double[] v4 = v1;
// One entry per asset; each asset lists its INPUTS series.
double[][][] assets = {{h1, l1, c1, v1}, {h2, l2, c2, v2}, {h3, l3, c3, v3}, {h4, l4, c4, v4}};
try (SimdResult sim = Mfi.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, N different option sets in parallel:
import org.tuliprs.*;
import org.tuliprs.indicators.Mfi;
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[] 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 = Mfi.simdByOptions(new double[][] {high, low, close, volume},
new double[][] {{7.0}, {14.0}, {21.0}, {28.0}}, null)) {
for (int i = 0; i < sim.numResults(); i++) {
System.out.printf("Period %d: %s%n", i + 1,
java.util.Arrays.toString(sim.toDoubleArray(i, 0)));
}
}
By assets — same options, N assets in parallel (must be 2, 4, 8, or 16):
simd_inputs = [
[h1, l1, c1, v1],
[h2, l2, c2, v2],
[h3, l3, c3, v3],
[h4, l4, c4, v4],
]
outputs_list, states = tulip_rs.indicators.mfi.simd_by_assets(simd_inputs, [14.0])
for i, asset_outputs in enumerate(outputs_list):
print(f"Asset {i+1}: {asset_outputs[0]}")
By options — same asset, N option sets in parallel:
By assets — same period applied to 4 assets in parallel:
const simdInputs = [
[high.slice(), low.slice(), close.slice(), volume.slice()],
[high.map(v => v * 1.1), low.map(v => v * 1.1), close.map(v => v * 1.1), volume.map(v => v * 1.1)],
[high.map(v => v * 0.9), low.map(v => v * 0.9), close.map(v => v * 0.9), volume.map(v => v * 0.9)],
[high.map(v => v * 1.02), low.map(v => v * 1.02), close.map(v => v * 1.02), volume.map(v => v * 1.02)],
];
const [results] = ti.mfi.simdByAssets(simdInputs, [14]);
results.forEach((out, i) => console.log(`Asset ${i + 1}:`, out[0]));
By options — same asset, 4 different periods in parallel: