Animation: Gaussian Smooth operator for Graph Editor #105635

Merged
Christoph Lendenfeld merged 15 commits from ChrisLend/blender:graph_gauss_smooth into main 2023-03-24 12:11:33 +01:00
6 changed files with 167 additions and 0 deletions
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@ -330,6 +330,7 @@ class GRAPH_MT_slider(Menu):
layout.operator("graph.blend_to_neighbor", text="Blend to Neighbor")
layout.operator("graph.blend_to_default", text="Blend to Default Value")
layout.operator("graph.ease", text="Ease")
layout.operator("graph.gauss_smooth", text="Gauss Smooth")
class GRAPH_MT_view_pie(Menu):

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@ -392,7 +392,44 @@ void blend_to_default_fcurve(PointerRNA *id_ptr, FCurve *fcu, const float factor
move_key(&fcu->bezt[i], key_y_value);
}
}
/* ---------------- */
void get_1d_gauss_kernel(const int filter_width, const float sigma, double *kernel)

For non-static functions, I think it might be better to move the ED_anim_... prefixes.

For non-static functions, I think it might be better to move the `ED_anim_...` prefixes.
{
dr.sybren marked this conversation as resolved

You could add

BLI_assert(sigma > 0.0f);
BLI_assert(kernel_size > 0);

to document the assumptions of the code. If sigma == 0 it'll cause some nice division issues.

You could add ```c BLI_assert(sigma > 0.0f); BLI_assert(kernel_size > 0); ``` to document the assumptions of the code. If `sigma == 0` it'll cause some nice division issues.
double norm = 1.0 / (M_2_SQRTPI * sigma);

I think you can remove norm from the calculations completely. Since you normalise the end result anyway, this constant factor doesn't have an impact on the final result.

I think you can remove `norm` from the calculations completely. Since you normalise the end result anyway, this constant factor doesn't have an impact on the final result.
double sig_sq = 2.0 * sigma * sigma;

const

`const`
double sum = 0.0;
for (int i = -filter_width; i <= filter_width; i++) {
kernel[i + filter_width] = norm * exp(-i * i / sig_sq);
sum += kernel[i + filter_width];
}
/* Normalize kernel values. */
for (int i = 0; i < filter_width * 2 + 1; i++) {
kernel[i] = kernel[i] / sum;
}
}
void smooth_fcurve_segment(FCurve *fcu,
FCurveSegment *segment,
float *samples,
const float factor,
const int filter_order,
dr.sybren marked this conversation as resolved
r_kernel[i] /= sum;
```c r_kernel[i] /= sum; ```
double *kernel)
{
for (int i = segment->start_index; i < segment->start_index + segment->length; i++) {
const int sample_index = (int)(fcu->bezt[i].vec[1][0] -
fcu->bezt[segment->start_index].vec[1][0]) +
filter_order;
double filter_result = 0;
/* Apply the kernel. */
for (int j = -filter_order; j <= filter_order; j++) {
filter_result += samples[sample_index + j] * kernel[filter_order + j];
}
dr.sybren marked this conversation as resolved

segment->start_index + segment->length and fcu->bezt[segment->start_index].vec[1][0] don't change during the loop, so you can store them in a constant outside of the loop and use that instead.

`segment->start_index + segment->length` and `fcu->bezt[segment->start_index].vec[1][0]` don't change during the loop, so you can store them in a constant outside of the loop and use that instead.
fcu->bezt[i].vec[1][1] = interpf((float)filter_result, samples[sample_index], factor);
}
}
/* ---------------- */
void ease_fcurve_segment(FCurve *fcu, FCurveSegment *segment, const float factor)

This comment should swap with the line above it, as double filter_result = samples[sample_index] * kernel[0]; is already part of applying the kernel.

This comment should swap with the line above it, as `double filter_result = samples[sample_index] * kernel[0];` is already part of applying the kernel.
@ -680,6 +717,16 @@ typedef struct TempFrameValCache {
float frame, val;
} TempFrameValCache;
void sample_fcurve_segment(FCurve *fcu,
const float start_frame,
float *samples,
const int sample_count)
{
for (int i = 0; i < sample_count; i++) {
samples[i] = evaluate_fcurve(fcu, start_frame + i);
}
}
void sample_fcurve(FCurve *fcu)
{
BezTriple *bezt, *start = NULL, *end = NULL;

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@ -424,6 +424,13 @@ void blend_to_neighbor_fcurve_segment(struct FCurve *fcu,
struct FCurveSegment *segment,
float factor);
void breakdown_fcurve_segment(struct FCurve *fcu, struct FCurveSegment *segment, float factor);
void get_1d_gauss_kernel(int filter_width, const float sigma, double *kernel);
void smooth_fcurve_segment(struct FCurve *fcu,
struct FCurveSegment *segment,
float *samples,
float factor,
int filter_order,
double *kernel);
void ease_fcurve_segment(struct FCurve *fcu, struct FCurveSegment *segment, float factor);
bool decimate_fcurve(struct bAnimListElem *ale, float remove_ratio, float error_sq_max);
void blend_to_default_fcurve(struct PointerRNA *id_ptr, struct FCurve *fcu, float factor);
@ -432,6 +439,10 @@ void blend_to_default_fcurve(struct PointerRNA *id_ptr, struct FCurve *fcu, floa
*/
void smooth_fcurve(struct FCurve *fcu);
void sample_fcurve(struct FCurve *fcu);
void sample_fcurve_segment(struct FCurve *fcu,
float start_frame,
float *r_samples,
int sample_count);
/* ----------- */

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@ -116,6 +116,7 @@ void GRAPH_OT_breakdown(struct wmOperatorType *ot);
void GRAPH_OT_ease(struct wmOperatorType *ot);
void GRAPH_OT_decimate(struct wmOperatorType *ot);
void GRAPH_OT_blend_to_default(struct wmOperatorType *ot);
void GRAPH_OT_gauss_smooth(struct wmOperatorType *ot);
void GRAPH_OT_sample(struct wmOperatorType *ot);
void GRAPH_OT_bake(struct wmOperatorType *ot);
void GRAPH_OT_unbake(struct wmOperatorType *ot);

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@ -464,6 +464,7 @@ void graphedit_operatortypes(void)
WM_operatortype_append(GRAPH_OT_breakdown);
WM_operatortype_append(GRAPH_OT_ease);
WM_operatortype_append(GRAPH_OT_blend_to_default);
WM_operatortype_append(GRAPH_OT_gauss_smooth);
WM_operatortype_append(GRAPH_OT_euler_filter);
WM_operatortype_append(GRAPH_OT_delete);
WM_operatortype_append(GRAPH_OT_duplicate);

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@ -1053,3 +1053,109 @@ void GRAPH_OT_ease(wmOperatorType *ot)
}
/** \} */
/* -------------------------------------------------------------------- */
/** \name Gauss Smooth Operator
* \{ */
static void gauss_smooth_graph_keys(bAnimContext *ac,
const float factor,
const float sigma,
const int filter_width)
{
ListBase anim_data = {NULL, NULL};
ANIM_animdata_filter(ac, &anim_data, OPERATOR_DATA_FILTER, ac->data, ac->datatype);
bAnimListElem *ale;
double *kernel = MEM_callocN(sizeof(double) * (filter_width * 2 + 1), "Gauss Kernel");
get_1d_gauss_kernel(filter_width, sigma, kernel);
for (ale = anim_data.first; ale; ale = ale->next) {
FCurve *fcu = (FCurve *)ale->key_data;
ListBase segments = find_fcurve_segments(fcu);

Document what this struct contains / what it's for.

Document what this struct contains / what it's for.
LISTBASE_FOREACH (FCurveSegment *, segment, &segments) {
BezTriple left_bezt = fcu->bezt[segment->start_index];
BezTriple right_bezt = fcu->bezt[segment->start_index + segment->length - 1];
const int sample_count = (int)(right_bezt.vec[1][0] - left_bezt.vec[1][0]) +
(filter_width * 2) + 1;
float *samples = MEM_callocN(sizeof(float) * sample_count, "Smooth FCurve Op Samples");
sample_fcurve_segment(fcu, left_bezt.vec[1][0] - filter_width, samples, sample_count);
smooth_fcurve_segment(fcu, segment, samples, factor, filter_width, kernel);
MEM_freeN(samples);
}
BLI_freelistN(&segments);
ale->update |= ANIM_UPDATE_DEFAULT;
}
MEM_freeN(kernel);
ANIM_animdata_update(ac, &anim_data);
ANIM_animdata_freelist(&anim_data);
}
static int gauss_exec(bContext *C, wmOperator *op)
{
bAnimContext ac;
if (ANIM_animdata_get_context(C, &ac) == 0) {
return OPERATOR_CANCELLED;
}
const float factor = RNA_float_get(op->ptr, "factor");
const float sigma = RNA_float_get(op->ptr, "sigma");
const int filter_width = RNA_int_get(op->ptr, "filter_width");
gauss_smooth_graph_keys(&ac, factor, sigma, filter_width);
/* Set notifier that keyframes have changed. */
WM_event_add_notifier(C, NC_ANIMATION | ND_KEYFRAME | NA_EDITED, NULL);
return OPERATOR_FINISHED;
}
void GRAPH_OT_gauss_smooth(wmOperatorType *ot)
{
/* Identifiers. */
ot->name = "Gauss Smooth";
ot->idname = "GRAPH_OT_gauss_smooth";
ot->description = "Smooth the curve using a Gauss filter";
/* API callbacks. */
/* ot->invoke = fft_invoke; */
/* ot->modal = fft_modal; */
ot->exec = gauss_exec;
ot->poll = graphop_editable_keyframes_poll;
/* Flags. */
ot->flag = OPTYPE_REGISTER | OPTYPE_UNDO;
RNA_def_float_factor(ot->srna,
"factor",
1.0f,
0.0f,
FLT_MAX,
"Factor",
"How much to blend to the default value",
0.0f,
1.0f);
RNA_def_float(ot->srna,
"sigma",
2.0f,
0.001f,

Change this to:

const char *mode_str = TIP_("Gaussian Smooth");

It's using the old name now. Copying to a small fixed buffer like that can very easily overflow, but you don't need to copy at all.

Change this to: ``` const char *mode_str = TIP_("Gaussian Smooth"); ``` It's using the old name now. Copying to a small fixed buffer like that can very easily overflow, but you don't need to copy at all.
FLT_MAX,
"Sigma",
"At which frquency the factor should be applied",
0.001f,
100.0f);
RNA_def_int(ot->srna,
"filter_width",
8,
1,
64,
"Filter Width",
"How far to each side the operator will average the key values",
1,
32);
}
/** \} */