Run data processor on a circular-ish buffer.

Author: microbit-carlos

main.ts

@@ -1,6 +1,9 @@
 input.onButtonPressed(Button.A, function () {
     basic.clearScreen()
 })
+testrunner.onMlEvent(TestRunnerLabels.None, function () {
+    basic.clearScreen()
+})
 testrunner.onMlEvent(TestRunnerLabels.Shake, function () {
     basic.showString("S")
 })

mlrunner/filterdataprocessor.c

@@ -13,9 +13,11 @@
 
 
 static float **input_samples = NULL;
+static float *temp_buffer = NULL;
 static int sample_dimensions = 0;
 static int sample_length = 0;
 static int sample_index = 0;
+static bool buffer_filled = false;
 static float *output_data = NULL;
 static int output_length = 0;
 static MlDataFilters_t *filters = NULL;
@@ -58,7 +60,7 @@ MldpReturn_t filterDataProcessor_init(const MlDataProcessorConfig_t* config) {
         return MLDP_ERROR_ALLOC;
     }
 
-    // Allocate for each sample dimension
+    // Allocate for each sample dimension, and the temporary buffer
     sample_dimensions = config->dimensions;
     for (int i = 0; i < sample_dimensions; i++) {
         input_samples[i] = (float*)malloc(config->samples * sizeof(float));
@@ -67,6 +69,11 @@ MldpReturn_t filterDataProcessor_init(const MlDataProcessorConfig_t* config) {
             return MLDP_ERROR_ALLOC;
         }
     }
+    temp_buffer = (float*)malloc(config->samples * sizeof(float));
+    if (temp_buffer == NULL) {
+        filterDataProcessor_deinit();
+        return MLDP_ERROR_ALLOC;
+    }
 
     // Copy the filter pointers
     memcpy(filters, config->filters, config->filter_size * sizeof(MlDataFilters_t));
@@ -86,6 +93,7 @@ void filterDataProcessor_deinit() {
         free(input_samples[i]);
     }
     free(input_samples);
+    free(temp_buffer);
     free(output_data);
     free(filters);
     input_samples = NULL;
@@ -111,6 +119,7 @@ MldpReturn_t filterDataProcessor_recordData(const float* samples, const int elem
         sample_index++;
         if (sample_index >= sample_length) {
             sample_index = 0;
+            buffer_filled = true;
         }
     }
 
@@ -120,18 +129,22 @@ MldpReturn_t filterDataProcessor_recordData(const float* samples, const int elem
 bool filterDataProcessor_isDataReady() {
     if (!initialised) return false;
 
-    return sample_index == 0;
+    return buffer_filled;
 }
 
 float* filterDataProcessor_getProcessedData() {
     if (!initialised) return NULL;
+    if (!buffer_filled) return NULL;
 
     // Run all filters and save their output to output_data
     int output_i = 0;
     for (int filter_i = 0; filter_i < filter_size; filter_i++) {
         for (int dimension_i = 0; dimension_i < sample_dimensions; dimension_i++) {
+            const int elements_left = sample_length - sample_index;
+            memcpy(temp_buffer, &input_samples[dimension_i][sample_index], elements_left * sizeof(float));
+            memcpy(&temp_buffer[elements_left], input_samples[dimension_i], sample_index * sizeof(float));
             MldpReturn_t filter_result = filters[filter_i].filter(
-                input_samples[dimension_i], sample_length,
+                temp_buffer, sample_length,
                 &output_data[output_i], filters[filter_i].out_size
             );
             if (filter_result != MLDP_SUCCESS) {

mlrunner/mldataprocessor.h

@@ -31,10 +31,10 @@ typedef struct {
 } MlDataFilters_t;
 
 typedef struct {
-    const int samples;
-    const int dimensions;
-    const int output_length;
-    const int filter_size;
+    const int samples;          // How many samples are needed to calculated the processed output
+    const int dimensions;       // How many dimensions each sample contains (e.g. x, y, z is 3 dimensions)
+    const int output_length;    // Expected number elements produced by the processed output, depends on filters
+    const int filter_size;      // How many filters in the *filters array
     const MlDataFilters_t *filters;
 } MlDataProcessorConfig_t;
 

testextension.cpp

@@ -53,9 +53,11 @@ static inline uint32_t calcTicks(uint32_t ticks_start, uint32_t ticks_end) {
 
 
 namespace testrunner {
+    static bool initialised = false;
     static ml_actions_t *actions = NULL;
     static ml_predictions_t *predictions = NULL;
-    static bool initialised = false;
+    static int ml_sample_counts_per_prediction = 0;
+    static const int ML_PREDICTIONS_PER_SECOND = 4;
     static const uint16_t ML_CODAL_TIMER_VALUE = 1;
 
     // Order is important for the outputData as set in:
@@ -119,22 +121,22 @@ namespace testrunner {
     void recordAccData(MicroBitEvent) {
         if (!initialised) return;
 
+        const Sample3D accSample = uBit.accelerometer.getSample();
         const float accData[3] = {
-            uBit.accelerometer.getX() / 1000.0f,
-            uBit.accelerometer.getY() / 1000.0f,
-            uBit.accelerometer.getZ() / 1000.0f,
+            accSample.x / 1000.0f,
+            accSample.y / 1000.0f,
+            accSample.z / 1000.0f,
         };
         MldpReturn_t recordDataResult = mlDataProcessor.recordData(accData, 3);
         if (recordDataResult != MLDP_SUCCESS) {
             DEBUG_PRINT("Failed to record accelerometer data\n");
             return;
         }
 
-        if (mlDataProcessor.isDataReady()) {
-            // Stop firing timer events while running model and resume after
-            uBit.messageBus.ignore(TEST_RUNNER_ID_TIMER, ML_CODAL_TIMER_VALUE, &recordAccData);
+        // Run model every ml_sample_counts_per_prediction samples
+        static unsigned int samplesTaken = 0;
+        if (!(++samplesTaken % ml_sample_counts_per_prediction) && mlDataProcessor.isDataReady()) {
             runModel();
-            uBit.messageBus.listen(TEST_RUNNER_ID_TIMER, ML_CODAL_TIMER_VALUE, &recordAccData, MESSAGE_BUS_LISTENER_DROP_IF_BUSY);
         }
     }
 
@@ -236,6 +238,9 @@ namespace testrunner {
             uBit.panic(TEST_RUNNER_ERROR + 11);
         }
 
+        // Using sampling period to calculate how samples have to run for the next model run
+        ml_sample_counts_per_prediction = (1000 / ML_PREDICTIONS_PER_SECOND) / samplesPeriodMillisec;
+
         const MlDataProcessorConfig_t mlDataConfig = {
             .samples = samplesLen,
             .dimensions = sampleDimensions,

testextension.ts

@@ -19,7 +19,7 @@ namespace testrunner {
     //% block="on ML event %value"
     export function onMlEvent(mlEvent: TestRunnerLabels, body: () => void): void {
         startRunning();
-        control.onEvent(TestRunnerIds.TestRunnerInference, mlEvent, body)
+        control.onEvent(TestRunnerIds.TestRunnerInference, mlEvent, body, EventFlags.DropIfBusy)
     }
 
     /**