CCI — Commodity Channel Index¶
Measures how far the typical price deviates from its simple moving average, normalised by mean absolute deviation. Values above +100 suggest overbought conditions; values below -100 suggest oversold conditions.
Inputs: [high, low, close] | Options: [period] | Outputs: [cci]
Basic¶
use tulip_rs::indicators::cci::{Cci, TIndicatorState, Indicator};
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 inputs = [high.as_slice(), low.as_slice(), close.as_slice()];
let (outputs, _state) = Cci::indicator(&inputs, &[20.0], None).unwrap();
println!("CCI(20): {:?}", outputs[0]);
// State continuation
let inputs2 = [&high[..8], &low[..8], &close[..8]];
let (outputs2, mut state) = Cci::indicator(&inputs2, &[20.0], None).unwrap();
println!("Partial CCI: {:?}", outputs2[0]);
let new_inputs = [&high[8..], &low[8..], &close[8..]];
let continued = state.batch_indicator(&new_inputs, None).unwrap();
println!("Continued CCI: {:?}", continued[0]);
#include "tulip_rs_ffi.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 close[] = {81.59, 81.06, 82.87, 83.00, 83.61,
83.15, 82.84, 83.99, 84.55, 84.36};
double options[CCI_OPTIONS] = {20.0}; // period
const double *inputs[CCI_INPUTS] = {high, low, close};
/* Full computation (check r.error == C_INDICATOR_ERROR_OK in real code) */
CIndicatorResult r = cci_indicator(inputs, 10, options, NULL, 0);
tulip_ffi_result_free(r);
cci_state_free(r.state);
/* Partial computation + state continuation */
CIndicatorResult p = cci_indicator(inputs, 8, options, NULL, 0);
const double *rest_inputs[CCI_INPUTS] = {high+8, low+8, close+8};
CBatchResult b = cci_batch(p.state, rest_inputs, 2, NULL, 0);
tulip_ffi_batch_result_free(b);
tulip_ffi_result_free(p);
cci_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}
close := []float64{81.59, 81.06, 82.87, 83.00, 83.61,
83.15, 82.84, 83.99, 84.55, 84.36}
options := []float64{20.0} // period
// Full computation — Rows are zero-copy views, valid until Close.
res, st, _ := indicators.Cci.Indicator(high, low, close, options, nil)
fmt.Println(res.Rows[0]) // CCI(20) values
res.Close()
st.Close()
// Partial computation + state continuation.
res2, st2, _ := indicators.Cci.Indicator(high[:8], low[:8], close[:8], options, nil)
res2.Close() // outputs consumed or closed; state stays live
batch, _ := st2.Batch(high[8:], low[8:], close[8:], nil)
fmt.Println(batch.Rows[0]) // continued CCI values
batch.Close()
st2.Close()
import org.tuliprs.*;
import org.tuliprs.indicators.Cci;
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[] options = {20.0}; // period
// Full computation — output rows are zero-copy views, valid until close().
Outcome oc = Cci.indicator(new double[][] {high, low, close}, options);
try (Result res = oc.result(); State st = oc.state()) {
System.out.println(java.util.Arrays.toString(res.toDoubleArray(0))); // CCI(20) values
}
// Partial computation + state continuation.
int n = 8;
Outcome p = Cci.indicator(new double[][] {
java.util.Arrays.copyOfRange(high, 0, n),
java.util.Arrays.copyOfRange(low, 0, n),
java.util.Arrays.copyOfRange(close, 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)});
try (br) {
System.out.println(java.util.Arrays.toString(br.toDoubleArray(0))); // continued CCI values
}
}
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)
outputs, state = tulip_rs.indicators.cci.indicator([high, low, close], [20.0])
print("CCI(20):", outputs[0])
# State continuation
outputs2, state = tulip_rs.indicators.cci.indicator([high[:8], low[:8], close[:8]], [20.0])
continued = state.batch_indicator([high[8:], low[8:], close[8:]])
print("Continued CCI:", 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 [outputs, state] = ti.cci.indicator([high, low, close], [20]);
console.log('CCI(20):', outputs[0]);
// State continuation
const n = high.length - 5;
const [, state2] = ti.cci.indicator([high.slice(0, n), low.slice(0, n), close.slice(0, n)], [20]);
const continued = state2.batchIndicator([high.slice(n), low.slice(n), close.slice(n)]);
console.log('Continued CCI:', 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 [outputs, state] = ti.cci.indicator([high, low, close], [20]);
console.log('CCI(20):', outputs[0]);
// State continuation
const n = high.length - 5;
const [, state2] = ti.cci.indicator([high.slice(0, n), low.slice(0, n), close.slice(0, n)], [20]);
const continued = state2.batchIndicator([high.slice(n), low.slice(n), close.slice(n)]);
console.log('Continued CCI:', continued[0]);
Optional Outputs¶
cci exposes 3 optional outputs: sma, md, typprice. Pass a boolean mask as the third argument — one bool per optional output, in order.
use tulip_rs::indicators::cci::{Cci, TIndicatorState, Indicator};
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 mask = [true, true, true]; // one per optional output
let inputs = [high.as_slice(), low.as_slice(), close.as_slice()];
let (outputs, _state) = Cci::indicator(&inputs, &[20.0], Some(&mask)).unwrap();
let cci = &outputs[0]; // cci (primary)
let sma = &outputs[1]; // sma (optional — requested)
let md = &outputs[2]; // md (optional — requested)
let typprice = &outputs[3]; // typprice (optional — requested)
cci exposes 3 optional outputs: sma, md, typprice.
By assets
#include <tulip_rs_ffi.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 close[] = {81.59, 81.06, 82.87, 83.00, 83.61,
83.15, 82.84, 83.99, 84.55, 84.36};
double options[CCI_OPTIONS] = {20.0};
const double *inputs[CCI_INPUTS] = {high, low, close};
bool optional_outputs[3] = {true, true, true}; // sma, md, typprice
CIndicatorResult r = cci_indicator(inputs, 10, options,
optional_outputs, 3);
double *cci = r.outputs[0]; // primary
double *sma = r.outputs[1]; // optional 0: sma
double *md = r.outputs[2]; // optional 1: md
double *typprice = r.outputs[3]; // optional 2: typprice
tulip_ffi_result_free(r);
cci_state_free(r.state);
By options
#include <tulip_rs_ffi.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 close[] = {81.59, 81.06, 82.87, 83.00, 83.61,
83.15, 82.84, 83.99, 84.55, 84.36};
double o20[] = {20.0}, o14[] = {14.0}, o10[] = {10.0}, o5[] = {5.0};
const double *const simd_opts[4] = {o20, o14, o10, o5};
#define EXPANDED_LEN (10 * 20)
double high_exp[EXPANDED_LEN], low_exp[EXPANDED_LEN], close_exp[EXPANDED_LEN];
for (int i = 0; i < 20; i++) {
for (int j = 0; j < 10; j++) {
high_exp[i*10+j] = high[j];
low_exp[i*10+j] = low[j];
close_exp[i*10+j] = close[j];
}
}
const double *expanded_inputs[CCI_INPUTS] = {high_exp, low_exp, close_exp};
bool optional_outputs[3] = {true, true, true};
CSimdResult r = cci_simd_by_options(expanded_inputs, EXPANDED_LEN,
simd_opts, 4, optional_outputs, 3);
for (uintptr_t i = 0; i < r.num_results; i++) {
double *cci = r.outputs[i][0];
double *sma = r.outputs[i][1];
double *md = r.outputs[i][2];
double *typprice = r.outputs[i][3];
cci_state_free(r.states[i]);
}
tulip_ffi_simd_result_free(r);
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}
options := []float64{20.0} // period
// Request all optional outputs (sma, md, typprice)
res, st, _ := indicators.Cci.Indicator(high, low, close, options, []bool{true, true, true})
fmt.Println(res.Rows[0]) // cci (primary)
fmt.Println(res.Rows[1]) // "sma" (optional — requested)
fmt.Println(res.Rows[2]) // "md" (optional — requested)
fmt.Println(res.Rows[3]) // "typprice" (optional — requested)
res.Close()
st.Close()
cci exposes 3 optional outputs: sma, md, typprice. Pass a boolean mask as the third argument — one boolean per optional output, in order.
import org.tuliprs.*;
import org.tuliprs.indicators.Cci;
// (high/low/close series as in the Basic tab)
boolean[] mask = {true, true, true}; // sma, md, typprice
Outcome oc = Cci.indicator(new double[][] {high, low, close}, new double[] {20.0}, mask);
try (Result res = oc.result()) {
System.out.println(java.util.Arrays.toString(res.toDoubleArray(1))); // sma
}
oc.state().close();
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)
outputs, state = tulip_rs.indicators.cci.indicator(
[high, low, close], [20.0],
optional_outputs=[True, True, True],
)
cci = outputs[0] # cci (primary)
sma = outputs[1] # sma (optional — requested)
md = outputs[2] # md (optional — requested)
typprice = outputs[3] # typprice (optional — requested)
cci exposes 3 optional outputs: sma, md, typprice.
const [allOut] = ti.cci.indicator([high, low, close], [20], [true, true, true]);
const cci = allOut[0]; // primary
const sma = allOut[1]; // optional 0: sma
const md = allOut[2]; // optional 1: md
const typprice = allOut[3]; // optional 2: typprice
// Request only sma
const [partial] = ti.cci.indicator([high, low, close], [20], [true, false, false]);
The WASM API is identical to Node.js — pass the boolean mask as the third argument.
const [allOut] = ti.cci.indicator([high, low, close], [20], [true, true, true]);
const cci = allOut[0]; // primary
const sma = allOut[1]; // optional 0: sma
const md = allOut[2]; // optional 1: md
const typprice = allOut[3]; // optional 2: typprice
// Request only sma
const [partial] = ti.cci.indicator([high, low, close], [20], [true, false, false]);
SIMD¶
By assets — same period applied to 4 assets in parallel:
use tulip_rs::indicators::cci::{Cci, Indicator};
let h1 = vec![82.15, 81.89, 83.03, 83.30, 83.85, 83.90, 83.33, 84.30, 84.84, 85.00_f64];
let l1 = vec![81.29, 80.64, 81.31, 82.65, 83.07, 83.11, 82.49, 82.30, 84.15, 84.11_f64];
let c1 = vec![81.59, 81.06, 82.87, 83.00, 83.61, 83.15, 82.84, 83.99, 84.55, 84.36_f64];
let h2 = h1.clone(); let l2 = l1.clone(); let c2 = c1.clone();
let h3 = h1.clone(); let l3 = l1.clone(); let c3 = c1.clone();
let h4 = h1.clone(); let l4 = l1.clone(); let c4 = c1.clone();
let inputs: [&[&[f64]; 3]; 4] = [
&[h1.as_slice(), l1.as_slice(), c1.as_slice()],
&[h2.as_slice(), l2.as_slice(), c2.as_slice()],
&[h3.as_slice(), l3.as_slice(), c3.as_slice()],
&[h4.as_slice(), l4.as_slice(), c4.as_slice()],
];
let results = Cci::indicator_by_assets::<4>(&inputs, &[20.0], 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::cci::{Cci, IndicatorByOptions};
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 opts: [&[f64; 1]; 4] = [&[10.0], &[14.0], &[20.0], &[30.0]];
let inputs = [high.as_slice(), low.as_slice(), close.as_slice()];
let results = Cci::indicator_by_options::<4>(&inputs, &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 in parallel:
#include <tulip_rs_ffi.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 c1[] = {81.59, 81.06, 82.87, 83.00, 83.61, 83.15, 82.84, 83.99, 84.55, 84.36};
double h2[10], l2[10], c2[10];
for (int i = 0; i < 10; i++) { h2[i] = h1[i]*1.1; l2[i] = l1[i]*1.1; c2[i] = c1[i]*1.1; }
double h3[10], l3[10], c3[10];
for (int i = 0; i < 10; i++) { h3[i] = 90+i*0.5+h1[i]*0.1; l3[i] = 90+i*0.5+l1[i]*0.1; c3[i] = 90+i*0.5+c1[i]*0.1; }
double h4[10], l4[10], c4[10];
for (int i = 0; i < 10; i++) { h4[i] = 100-i*0.3+h1[i]*0.05; l4[i] = 100-i*0.3+l1[i]*0.05; c4[i] = 100-i*0.3+c1[i]*0.05; }
const double *const asset1[CCI_INPUTS] = {h1, l1, c1};
const double *const asset2[CCI_INPUTS] = {h2, l2, c2};
const double *const asset3[CCI_INPUTS] = {h3, l3, c3};
const double *const asset4[CCI_INPUTS] = {h4, l4, c4};
const double *const *const simd_inputs[4] = {asset1, asset2, asset3, asset4};
double options[CCI_OPTIONS] = {20.0};
CSimdResult r = cci_simd_by_assets(simd_inputs, 4, 10, options, NULL, 0);
for (uintptr_t i = 0; i < r.num_results; i++) {
printf("Asset %zu: [", i+1);
for (uintptr_t j = 0; j < r.output_lens[i][0]; j++) {
printf("%.4f", r.outputs[i][0][j]);
if (j+1 < r.output_lens[i][0]) printf(", ");
}
printf("]\n");
cci_state_free(r.states[i]);
}
tulip_ffi_simd_result_free(r);
By options — same asset, 4 different periods in parallel:
#include <tulip_rs_ffi.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 close[] = {81.59, 81.06, 82.87, 83.00, 83.61,
83.15, 82.84, 83.99, 84.55, 84.36};
double o10[] = {10.0}, o14[] = {14.0}, o20[] = {20.0}, o30[] = {30.0};
const double *const simd_opts[4] = {o10, o14, o20, o30};
#define EXPANDED_LEN (10 * 20)
double high_exp[EXPANDED_LEN], low_exp[EXPANDED_LEN], close_exp[EXPANDED_LEN];
for (int i = 0; i < 20; i++) {
for (int j = 0; j < 10; j++) {
high_exp[i*10+j] = high[j];
low_exp[i*10+j] = low[j];
close_exp[i*10+j] = close[j];
}
}
const double *expanded_inputs[CCI_INPUTS] = {high_exp, low_exp, close_exp};
CSimdResult r = cci_simd_by_options(expanded_inputs, EXPANDED_LEN,
simd_opts, 4, NULL, 0);
for (uintptr_t i = 0; i < r.num_results; i++) {
printf("Period %zu: [", simd_opts[i][0]);
for (uintptr_t j = 0; j < r.output_lens[i][0]; j++) {
printf("%.4f", r.outputs[i][0][j]);
if (j+1 < r.output_lens[i][0]) printf(", ");
}
printf("]\n");
cci_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):
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}
// Reuse the same data for assets 2–4 in this example
h2, l2, c2 := h1, l1, c1
h3, l3, c3 := h1, l1, c1
h4, l4, c4 := h1, l1, c1
assets := [][indicators.CciInputs][]float64{{h1, l1, c1}, {h2, l2, c2}, {h3, l3, c3}, {h4, l4, c4}}
sim, _ := indicators.Cci.SimdByAssets(assets, []float64{20.0}, 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:
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}
sim2, _ := indicators.Cci.SimdByOptions(high, low, close, [][]float64{{10}, {14}, {20}, {30}}, 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.Cci;
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};
// Reuse the same data for assets 2–4 in this example
double[] h2 = h1; double[] l2 = l1; double[] c2 = c1;
double[] h3 = h1; double[] l3 = l1; double[] c3 = c1;
double[] h4 = h1; double[] l4 = l1; double[] c4 = c1;
// Each entry lists one asset's input series (h1..c4 as in the C tab).
double[][][] assets = {{h1, l1, c1}, {h2, l2, c2}, {h3, l3, c3}, {h4, l4, c4}};
try (SimdResult sim = Cci.simdByAssets(assets, new double[] {20.0}, 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.Cci;
// (high/low/close series as in the Basic tab)
try (SimdResult sim = Cci.simdByOptions(new double[][] {high, low, close},
new double[][] {{10}, {14}, {20}, {30}}, 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
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)
simd_inputs = [
[high, low, close],
[high + 0.5, low + 0.5, close + 0.5],
[high - 0.5, low - 0.5, close - 0.5],
[high * 1.01, low * 1.01, close * 1.01],
]
outputs_list, states = tulip_rs.indicators.cci.simd_by_assets(simd_inputs, [20.0])
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
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)
simd_options = [[10.0], [14.0], [20.0], [30.0]]
outputs_list, states = tulip_rs.indicators.cci.simd_by_options([high, low, close], 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 = [
[high.slice(), low.slice(), close.slice()],
[high.map(v => v * 1.1), low.map(v => v * 1.1), close.map(v => v * 1.1)],
[high.map(v => v * 0.9), low.map(v => v * 0.9), close.map(v => v * 0.9)],
[high.map(v => v * 1.02), low.map(v => v * 1.02), close.map(v => v * 1.02)],
];
const [results] = ti.cci.simdByAssets(simdInputs, [20]);
results.forEach((out, i) => console.log(`Asset ${i + 1}:`, out[0]));
By options — same asset, 4 different periods in parallel: