update templates to new api; open template status fix

master
Clyne 3 years ago
parent 707b24dd07
commit bf0a126e8a

1
.gitignore vendored

@ -2,3 +2,4 @@ imgui.ini
stmdspgui
stmdspgui.exe
*.o
.*

@ -87,6 +87,7 @@ void fileRenderMenu()
// Treat like new file.
fileCurrentPath.clear();
statusMessage = "Ready.";
}
}

@ -7,10 +7,10 @@
* transient response is not calculated.
*/
adcsample_t *process_data(adcsample_t *samples, unsigned int size)
Sample *process_data(Samples samples)
{
// Define our output buffer. SIZE is the largest size of the 'samples' buffer.
static adcsample_t buffer[SIZE];
static Sample buffer[samples.size()];
// Define our filter
constexpr unsigned int filter_size = 3;
@ -19,7 +19,7 @@ adcsample_t *process_data(adcsample_t *samples, unsigned int size)
};
// Begin convolving:
for (int n = 0; n < size - (filter_size - 1); n++) {
for (int n = 0; n < samples.size() - (filter_size - 1); n++) {
buffer[n] = 0;
for (int k = 0; k < filter_size; k++)
buffer[n] += samples[n + k] * filter[k];

@ -11,9 +11,9 @@
* computation.
*/
adcsample_t *process_data(adcsample_t *samples, unsigned int size)
Sample *process_data(Samples samples)
{
static adcsample_t buffer[SIZE];
static Sample buffer[samples.size()];
constexpr unsigned int filter_size = 3;
float filter[filter_size] = {
@ -21,9 +21,9 @@ adcsample_t *process_data(adcsample_t *samples, unsigned int size)
};
// Keep a buffer of extra samples for overlap-save
static adcsample_t prev[filter_size];
static Sample prev[filter_size];
for (int n = 0; n < size; n++) {
for (int n = 0; n < samples.size(); n++) {
buffer[n] = 0;
for (int k = 0; k < filter_size; k++) {
@ -40,7 +40,7 @@ adcsample_t *process_data(adcsample_t *samples, unsigned int size)
// Save samples for the next convolution run
for (int i = 0; i < filter_size; i++)
prev[i] = samples[size - filter_size + i];
prev[i] = samples[samples.size() - filter_size + i];
return buffer;
}

@ -7,9 +7,9 @@
* within the available execution time. Samples are also normalized so that they center around zero.
*/
adcsample_t *process_data(adcsample_t *samples, unsigned int size)
Sample *process_data(Samples samples)
{
static adcsample_t buffer[SIZE];
static Sample buffer[samples.size()];
// Define the filter:
constexpr unsigned int filter_size = 3;
@ -19,9 +19,9 @@ adcsample_t *process_data(adcsample_t *samples, unsigned int size)
};
// Do an overlap-save convolution
static adcsample_t prev[filter_size];
static Sample prev[filter_size];
for (int n = 0; n < size; n++) {
for (int n = 0; n < samples.size(); n++) {
// Using a float variable for accumulation allows for better code optimization
float v = 0;
@ -40,7 +40,7 @@ adcsample_t *process_data(adcsample_t *samples, unsigned int size)
// Save samples for next convolution
for (int i = 0; i < filter_size; i++)
prev[i] = samples[size - filter_size + i];
prev[i] = samples[samples.size() - filter_size + i];
return buffer;
}

@ -10,7 +10,7 @@ typedef struct
static void arm_fir_f32(const arm_fir_instance_f32 * S, float32_t * pSrc, float32_t * pDst, uint32_t blockSize);
adcsample_t *process_data(adcsample_t *samples, unsigned int size)
Sample *process_data(Samples samples)
{
// 1. Define our array sizes (Be sure to set Run > Set buffer size... to below value!)
constexpr unsigned int buffer_size = 500;
@ -34,18 +34,18 @@ adcsample_t *process_data(adcsample_t *samples, unsigned int size)
static float working[buffer_size + filter_size];
// 3. Scale 0-4095 interger sample values to +/- 1.0 floats
for (unsigned int i = 0; i < size; i++)
for (unsigned int i = 0; i < samples.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, size);
arm_fir_f32(&fir, input, output, samples.size());
// 5. Convert float results back to 0-4095 range for output
for (unsigned int i = 0; i < size; i++)
for (unsigned int i = 0; i < samples.size(); i++)
samples[i] = output[i] * 2048.f + 2048;
return samples;
return samples.data();
}
// Below taken from the CMSIS DSP Library (find it on GitHub)

@ -7,23 +7,23 @@
* A scaling factor is applied so that the output's form is more clearly visible.
*/
adcsample_t *process_data(adcsample_t *samples, unsigned int size)
Sample *process_data(Samples samples)
{
constexpr int scaling_factor = 4;
static adcsample_t output[SIZE];
static adcsample_t prev = 2048;
static Sample output[samples.size()];
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 < size; i++) {
for (unsigned int i = 1; i < samples.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[size - 1];
prev = samples[samples.size() - 1];
return output;
}

@ -1,13 +1,13 @@
adcsample_t *process_data(adcsample_t *samples, unsigned int size)
Sample *process_data(Samples samples)
{
constexpr float alpha = 0.7;
static adcsample_t prev = 2048;
static Sample prev = 2048;
samples[0] = (1 - alpha) * samples[0] + alpha * prev;
for (unsigned int i = 1; i < size; i++)
for (unsigned int i = 1; i < samples.size(); i++)
samples[i] = (1 - alpha) * samples[i] + alpha * samples[i - 1];
prev = samples[size - 1];
prev = samples[samples.size() - 1];
return samples;
return samples.data();
}

@ -1,22 +1,22 @@
adcsample_t *process_data(adcsample_t *samples, unsigned int size)
Sample *process_data(Samples samples)
{
constexpr float alpha = 0.75;
constexpr unsigned int D = 100;
static adcsample_t output[SIZE];
static adcsample_t prev[D]; // prev[0] = output[0 - D]
static Sample output[samples.size()];
static Sample prev[D]; // prev[0] = output[0 - D]
// Do calculations with previous output
for (unsigned int i = 0; i < D; i++)
output[i] = samples[i] + alpha * (prev[i] - 2048);
// Do calculations with current samples
for (unsigned int i = D; i < size; i++)
for (unsigned int i = D; i < samples.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[size - (D - i)];
prev[i] = output[samples.size() - (D - i)];
return output;
}

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