+
+
+
+
diff --git a/src/components/graphs/LiveFingerprint.svelte b/src/components/graphs/LiveFingerprint.svelte
new file mode 100644
index 000000000..7e8fcb7ca
--- /dev/null
+++ b/src/components/graphs/LiveFingerprint.svelte
@@ -0,0 +1,60 @@
+
+
+
+
+
diff --git a/src/script/domain/Filters.ts b/src/script/domain/Filters.ts
index c9252539b..ddc1b7808 100644
--- a/src/script/domain/Filters.ts
+++ b/src/script/domain/Filters.ts
@@ -7,6 +7,7 @@ import { Readable, Subscriber, Unsubscriber, Writable, get } from 'svelte/store'
import Filter from './Filter';
import FilterTypes, { FilterType } from './FilterTypes';
import Logger from '../utils/Logger';
+import FilterGraphLimits from '../utils/FilterLimits';
class Filters implements Readable
{
constructor(private filters: Writable) {}
@@ -23,6 +24,23 @@ class Filters implements Readable {
});
}
+ public computeNormalizedOutput(values: number[]): number[] {
+ return get(this.filters).map(filter => {
+ return this.normalizeFilterResult(filter.filter(values), filter);
+ });
+ }
+
+ private normalizeFilterResult(value: number, filter: Filter): number {
+ const { min, max } = FilterGraphLimits.getFilterLimits(filter);
+ const newMin = 0;
+ const newMax = 1;
+ const existingMin = min;
+ const existingMax = max;
+ return (
+ ((newMax - newMin) * (value - existingMin)) / (existingMax - existingMin) + newMin
+ );
+ }
+
public set(filterTypes: FilterType[]) {
const newFilters = filterTypes.map(filterType =>
FilterTypes.createFilter(filterType),
diff --git a/src/script/domain/stores/Engine.ts b/src/script/domain/stores/Engine.ts
index 34002a0de..a561eefda 100644
--- a/src/script/domain/stores/Engine.ts
+++ b/src/script/domain/stores/Engine.ts
@@ -4,6 +4,7 @@
* SPDX-License-Identifier: MIT
*/
import { Readable } from 'svelte/store';
+import AccelerometerClassifierInput from '../../mlmodels/AccelerometerClassifierInput';
export type EngineData = {
isRunning: boolean;
@@ -12,6 +13,7 @@ export type EngineData = {
interface Engine extends Readable {
start(): void;
stop(): void;
+ bufferToInput(): AccelerometerClassifierInput;
}
export default Engine;
diff --git a/src/script/engine/PollingPredictorEngine.ts b/src/script/engine/PollingPredictorEngine.ts
index 0b6267043..fcd5040f4 100644
--- a/src/script/engine/PollingPredictorEngine.ts
+++ b/src/script/engine/PollingPredictorEngine.ts
@@ -63,7 +63,7 @@ class PollingPredictorEngine implements Engine {
}
}
- private bufferToInput(): AccelerometerClassifierInput {
+ public bufferToInput(): AccelerometerClassifierInput {
const bufferedData = this.getRawDataFromBuffer(
StaticConfiguration.pollingPredictionSampleSize,
);
diff --git a/src/script/mlmodels/AccelerometerClassifierInput.ts b/src/script/mlmodels/AccelerometerClassifierInput.ts
index 8e425ea35..399595454 100644
--- a/src/script/mlmodels/AccelerometerClassifierInput.ts
+++ b/src/script/mlmodels/AccelerometerClassifierInput.ts
@@ -37,6 +37,23 @@ class AccelerometerClassifierInput implements ClassifierInput {
...filters.compute(this.zs),
];
}
+
+ public getNormalizedInput(filters: Filters): number[] {
+ try {
+ const x = filters.computeNormalizedOutput(this.xs);
+ const y = filters.computeNormalizedOutput(this.ys);
+ const z = filters.computeNormalizedOutput(this.zs);
+ const result = [];
+ // Group filters together instead of axes, i.e., max - x,
+ // max - y, max - z, min - x, etc.
+ for (let i = 0; i < x.length; i++) {
+ result.push(x[i], y[i], z[i]);
+ }
+ return result;
+ } catch (err) {
+ return [];
+ }
+ }
}
export default AccelerometerClassifierInput;