make helper funcs inline; drop std::span for algo

examples/1_convolve_simple.cpp

@@ -9,8 +9,8 @@
 
 Sample* process_data(Samples samples)
 {
-    // Define our output buffer. SIZE is the largest size of the 'samples' buffer.
-    static Sample buffer[samples.size()];
+    // Define our output buffer.
+    static Samples buffer;
 
     // Define our filter
     constexpr unsigned int filter_size = 3;
@@ -19,7 +19,8 @@ Sample *process_data(Samples samples)
     };
 
     // Begin convolving:
-    for (int n = 0; n < samples.size() - (filter_size - 1); n++) {
+    // SIZE is the size of the sample buffer.
+    for (int n = 0; n < SIZE - (filter_size - 1); n++) {
         buffer[n] = 0;
         for (int k = 0; k < filter_size; k++)
             buffer[n] += samples[n + k] * filter[k];

examples/2_convolve_overlap_save.cpp

@@ -13,7 +13,7 @@
 
 Sample* process_data(Samples samples)
 {
-    static Sample buffer[samples.size()];
+    static Samples buffer;
 
     constexpr unsigned int filter_size = 3;
 	float filter[filter_size] = {
@@ -23,7 +23,7 @@ Sample *process_data(Samples samples)
     // Keep a buffer of extra samples for overlap-save
     static Sample prev[filter_size];
 
-    for (int n = 0; n < samples.size(); n++) {
+    for (int n = 0; n < SIZE; n++) {
         buffer[n] = 0;
 
         for (int k = 0; k < filter_size; k++) {
@@ -40,7 +40,7 @@ Sample *process_data(Samples samples)
 
     // Save samples for the next convolution run
     for (int i = 0; i < filter_size; i++)
-        prev[i] = samples[samples.size() - filter_size + i];
+        prev[i] = samples[SIZE - filter_size + i];
 
     return buffer;
 }

examples/3_fir.cpp

@@ -9,7 +9,7 @@
 
 Sample* process_data(Samples samples)
 {
-    static Sample buffer[samples.size()];
+    static Samples buffer;
 
 	// Define the filter:
 	constexpr unsigned int filter_size = 3;
@@ -21,7 +21,7 @@ Sample *process_data(Samples samples)
     // Do an overlap-save convolution
     static Sample prev[filter_size];
 
-    for (int n = 0; n < samples.size(); n++) {
+    for (int n = 0; n < SIZE; n++) {
         // Using a float variable for accumulation allows for better code optimization
         float v = 0;
 
@@ -40,7 +40,7 @@ Sample *process_data(Samples samples)
 
     // Save samples for next convolution
     for (int i = 0; i < filter_size; i++)
-        prev[i] = samples[samples.size() - filter_size + i];
+        prev[i] = samples[SIZE - filter_size + i];
 
     return buffer;
 }

examples/4_fir_pro.cpp

@@ -34,18 +34,18 @@ Sample *process_data(Samples samples)
 	static float working[buffer_size + filter_size];
 
 	// 3. Scale 0-4095 interger sample values to +/- 1.0 floats
-	for (unsigned int i = 0; i < samples.size(); i++)
+	for (unsigned int i = 0; i < SIZE; i++)
 		input[i] = (samples[i] - 2048) / 2048.f;
 
 	// 4. Compute the FIR
 	arm_fir_instance_f32 fir { filter_size, working, filter };
-	arm_fir_f32(&fir, input, output, samples.size());
+	arm_fir_f32(&fir, input, output, SIZE);
 
 	// 5. Convert float results back to 0-4095 range for output
-	for (unsigned int i = 0; i < samples.size(); i++)
+	for (unsigned int i = 0; i < SIZE; i++)
 		samples[i] = output[i] * 2048.f + 2048;
 
-    return samples.data();
+    return samples;
 }
 
 // Below taken from the CMSIS DSP Library (find it on GitHub)

examples/5_fir_differentiator.cpp

@@ -10,20 +10,20 @@
 Sample* process_data(Samples samples)
 {
     constexpr int scaling_factor = 4;
-	static Sample output[samples.size()];
+    static Samples output;
     static Sample prev = 2048;
 
     // Compute the first output value using the saved sample.
     output[0] = 2048 + ((samples[0] - prev) * scaling_factor);
 
-	for (unsigned int i = 1; i < samples.size(); i++) {
+	for (unsigned int i = 1; i < SIZE; i++) {
         // Take the rate of change and scale it.
         // 2048 is added as the output should be centered in the voltage range.
 		output[i] = 2048 + ((samples[i] - samples[i - 1]) * scaling_factor);
     }
 
 	// Save the last sample for the next iteration.
-    prev = samples[samples.size() - 1];
+    prev = samples[SIZE - 1];
 
     return output;
 }

examples/6_iir_test.cpp

@@ -1,3 +1,13 @@
+/**
+ * 6_iir_test.cpp
+ * Written by Clyne Sullivan.
+ *
+ * Implements a simple infinite impulse response (IIR) filter using an alpha
+ * parameter.
+ * To build upon this example, try setting `alpha` with a parameter knob:
+ * alpha = param1() / 4095.0
+ */
+
 Sample* process_data(Samples samples)
 {
 	constexpr float alpha = 0.7;
@@ -5,9 +15,9 @@ Sample *process_data(Samples samples)
 	static Sample prev = 2048;
 
 	samples[0] = (1 - alpha) * samples[0] + alpha * prev;
-	for (unsigned int i = 1; i < samples.size(); i++)
+	for (unsigned int i = 1; i < SIZE; i++)
 		samples[i] = (1 - alpha) * samples[i] + alpha * samples[i - 1];
-	prev = samples[samples.size() - 1];
+	prev = samples[SIZE - 1];
 
-	return samples.data();
+	return samples;
 }

examples/7_iir_echo.cpp

@@ -1,9 +1,17 @@
+/**
+ * 7_iir_echo.cpp
+ * Written by Clyne Sullivan.
+ *
+ * This filter produces an echo of the given input. There are two parameters:
+ * alpha controls the feedback gain, and D controls the echo/delay length.
+ */
+
 Sample* process_data(Samples samples)
 {
 	constexpr float alpha = 0.75;
 	constexpr unsigned int D = 100;
 
-	static Sample output[samples.size()];
+	static Samples output;
 	static Sample prev[D]; // prev[0] = output[0 - D]
 
 	// Do calculations with previous output
@@ -11,12 +19,12 @@ Sample *process_data(Samples samples)
 		output[i] = samples[i] + alpha * (prev[i] - 2048);
 
 	// Do calculations with current samples
-	for (unsigned int i = D; i < samples.size(); i++)
+	for (unsigned int i = D; i < SIZE; i++)
 		output[i] = samples[i] + alpha * (output[i - D] - 2048);
 
 	// Save outputs for next computation
 	for (unsigned int i = 0; i < D; i++)
-		prev[i] = output[samples.size() - (D - i)];
+		prev[i] = output[SIZE - (D - i)];
 
 	return output;
 }

source/stmdsp/stmdsp_code.hpp

@@ -118,22 +118,22 @@ return s;
 )cpp";
 static std::string file_header_l4 = R"cpp(
 #include <cstdint>
-#include <span>
 
 using Sample = uint16_t;
-using Samples = std::span<Sample, $0>;
+using Samples = Sample[$0];
+constexpr unsigned int SIZE = $0;
 
 Sample *process_data(Samples samples);
 extern "C" void process_data_entry()
 {
     Sample *samples;
     asm("mov %0, r0" : "=r" (samples));
-    process_data(Samples(samples, $0));
+    process_data(samples);
 }
 
-static float PI = 3.14159265358979L;
+static inline float PI = 3.14159265358979L;
 __attribute__((naked))
-auto sin(float x) {
+static inline auto sin(float x) {
     asm("vmov.f32 r1, s0;"
     "eor r0, r0;"
     "svc 1;"
@@ -142,7 +142,7 @@ asm("vmov.f32 r1, s0;"
     return 0;
 }
 __attribute__((naked))
-auto cos(float x) {
+static inline auto cos(float x) {
     asm("vmov.f32 r1, s0;"
 	"mov r0, #1;"
 	"svc 1;"
@@ -151,7 +151,7 @@ asm("vmov.f32 r1, s0;"
     return 0;
 }
 __attribute__((naked))
-auto tan(float x) {
+static inline auto tan(float x) {
     asm("vmov.f32 r1, s0;"
 	"mov r0, #2;"
 	"svc 1;"
@@ -160,24 +160,24 @@ asm("vmov.f32 r1, s0;"
     return 0;
 }
 __attribute__((naked))
-auto sqrt(float) {
+static inline auto sqrt(float) {
     asm("vsqrt.f32 s0, s0; bx lr");
     return 0;
 }
 
-auto readpot1() {
+static inline auto param1() {
     Sample s;
-asm("push {r4-r11}; eor r0, r0; svc 3; mov %0, r0; pop {r4-r11}" : "=r"(s));
+    asm("eor r0, r0; svc 3; mov %0, r0" : "=r" (s) :: "r0");
     return s;
 }
-auto readpot2() {
+static inline auto param2() {
     Sample s;
-asm("push {r4-r11}; mov r0, #1; svc 3; mov %0, r0; pop {r4-r11}" : "=r"(s));
+    asm("mov r0, #1; svc 3; mov %0, r0" : "=r" (s) :: "r0");
     return s;
 }
 
-//void puts(const char *s) {
-// 's' will already be in r0.
+//static inline void puts(const char *s) {
+//    // 's' will already be in r0.
 //    asm("push {r4-r6}; svc 4; pop {r4-r6}");
 //}
 
@@ -189,7 +189,7 @@ return s;
 static std::string file_content = 
 R"cpp(Sample* process_data(Samples samples)
 {
-    return samples.data();
+    return samples;
 }
 )cpp";