mirror of
https://github.com/kovidgoyal/kitty.git
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304 lines
9.9 KiB
C
304 lines
9.9 KiB
C
/*
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* animation.c
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* Copyright (C) 2024 Kovid Goyal <kovid at kovidgoyal.net>
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*
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* Distributed under terms of the GPL3 license.
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*/
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#include "data-types.h"
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#define ANIMATION_INTERNAL_API
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typedef struct LinearParameters {
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size_t count;
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double buf[];
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} LinearParameters;
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typedef struct StepsParameters {
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size_t num_of_buckets;
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double jump_size, start_value;
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} StepsParameters;
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static const double bezier_epsilon = 1e-7;
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static const unsigned max_newton_iterations = 4;
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static const unsigned max_bisection_iterations = 16;
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typedef struct BezierParameters {
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double ax, bx, cx, ay, by, cy, start_gradient, end_gradient, spline_samples[11];
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} BezierParameters;
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typedef double(*easing_curve)(void*, double, monotonic_t);
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typedef struct animation_function {
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void *params;
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easing_curve curve;
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double y_at_start, y_size;
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} animation_function;
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typedef struct Animation {
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animation_function *functions;
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size_t count, capacity;
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} Animation;
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#include "animation.h"
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#include "state.h"
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Animation*
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alloc_animation(void) {
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return calloc(1, sizeof(Animation));
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}
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bool
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animation_is_valid(const Animation* a) { return a != NULL && a->count > 0; }
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Animation*
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free_animation(Animation *a) {
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if (a) {
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for (size_t i = 0; i < a->count; i++) free(a->functions[i].params);
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free(a->functions);
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free(a);
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}
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return NULL;
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}
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static double
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unit_value(double x) { return MAX(0., MIN(x, 1.)); }
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static double
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linear_easing_curve(void *p_, double val, monotonic_t duration UNUSED) {
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LinearParameters *p = p_;
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double start_pos = 0, stop_pos = 1, start_val = 0, stop_val = 1;
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double *x = p->buf, *y = p->buf + p->count;
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for (size_t i = 0; i < p->count; i++) {
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if (x[i] >= val) {
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stop_pos = x[i];
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stop_val = y[i];
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if (i > 0) {
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start_val = y[i-1];
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start_pos = x[i-1];
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}
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break;
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}
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}
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if (stop_pos > start_pos) {
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double frac = (val - start_pos) / (stop_pos - start_pos);
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return start_val + frac * (stop_val - start_val);
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}
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return stop_val;
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}
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// Cubic Bezier {{{
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static double
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sample_curve_x(const BezierParameters *p, double t) {
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// `ax t^3 + bx t^2 + cx t' expanded using Horner's rule.
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return ((p->ax * t + p->bx) * t + p->cx) * t;
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}
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static double
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sample_curve_y(const BezierParameters *p, double t) {
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return ((p->ay * t + p->by) * t + p->cy) * t;
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}
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static double
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sample_derivative_x(const BezierParameters *p, double t) {
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return (3.0 * p->ax * t + 2.0 * p->bx) * t + p->cx;
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}
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static double
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solve_curve_x(const BezierParameters *p, double x, double epsilon) {
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// Given an x value, find a parametric value it came from.
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double t0 = 0.0, t1 = 0.0, t2 = x, x2 = 0.0, d2 = 0.0;
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// Linear interpolation of spline curve for initial guess.
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static const size_t num_samples = arraysz(p->spline_samples);
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double delta = 1.0 / (num_samples - 1);
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for (size_t i = 1; i < num_samples; i++) {
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if (x <= p->spline_samples[i]) {
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t1 = delta * i;
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t0 = t1 - delta;
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t2 = t0 + (t1 - t0) * (x - p->spline_samples[i - 1]) / (p->spline_samples[i] - p->spline_samples[i - 1]);
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break;
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}
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}
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// Perform a few iterations of Newton's method -- normally very fast.
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// See https://en.wikipedia.org/wiki/Newton%27s_method.
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double newton_epsilon = MIN(bezier_epsilon, epsilon);
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for (unsigned i = 0; i < max_newton_iterations; i++) {
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x2 = sample_curve_x(p, t2) - x;
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if (fabs(x2) < newton_epsilon) return t2;
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d2 = sample_derivative_x(p, t2);
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if (fabs(d2) < bezier_epsilon) break;
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t2 = t2 - x2 / d2;
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}
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if (fabs(x2) < epsilon) return t2;
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t0 = 0.0, t1 = 0.0, t2 = x, x2 = 0.0;
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// Fall back to the bisection method for reliability.
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unsigned iteration = 0;
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while (t0 < t1 && iteration++ < max_bisection_iterations) {
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x2 = sample_curve_x(p, t2);
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if (fabs(x2 - x) < epsilon) return t2;
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if (x > x2) t0 = t2;
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else t1 = t2;
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t2 = (t1 + t0) * .5;
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}
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// Failure.
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return t2;
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}
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static double
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solve_unit_bezier(const BezierParameters *p, double x, double epsilon) {
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if (x < 0.0) return 0.0 + p->start_gradient * x;
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if (x > 1.0) return 1.0 + p->end_gradient * (x - 1.0);
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return sample_curve_y(p, solve_curve_x(p, x, epsilon));
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}
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static double
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cubic_bezier_easing_curve(void *p_, double t, monotonic_t duration) {
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BezierParameters *p = p_;
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// The longer the animation, the more precision we need
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double epsilon = 1.0 / monotonic_t_to_ms(duration);
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return fabs(solve_unit_bezier(p, t, epsilon));
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}
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// }}}
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static double
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step_easing_curve(void *p_, double t, monotonic_t duration UNUSED) {
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StepsParameters *p = p_;
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size_t val_bucket = (size_t)(t * p->num_of_buckets);
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return p->start_value + val_bucket * p->jump_size;
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}
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static double
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identity_easing_curve(void *p_ UNUSED, double t, monotonic_t duration UNUSED) { return t; }
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double
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apply_easing_curve(const Animation *a, double val, monotonic_t duration) {
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val = unit_value(val);
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if (!a->count) return val;
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size_t idx = MIN((size_t)(val * a->count), a->count - 1);
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animation_function *f = a->functions + idx;
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double interval_size = 1. / a->count, interval_start = idx * interval_size;
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double scaled_val = (val - interval_start) / interval_size;
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double ans = f->curve(f->params, scaled_val, duration);
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return f->y_at_start + unit_value(ans) * f->y_size;
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}
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static animation_function*
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init_function(Animation *a, double y_at_start, double y_at_end, easing_curve curve) {
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ensure_space_for(a, functions, animation_function, a->count + 1, capacity, 4, false);
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animation_function *f = a->functions + a->count++;
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zero_at_ptr(f);
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f->y_at_start = y_at_start; f->y_size = y_at_end - y_at_start; f->curve = curve;
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return f;
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}
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static bool
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is_bezier_linear(double p1x, double p1y, double p2x, double p2y) {
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// Is linear if all four points are on the same line. P0 and P4 are fixed at (0, 0) and (1, 1) for us.
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return p1x == p1y && p2x == p2y;
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}
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void
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add_cubic_bezier_animation(Animation *a, double y_at_start, double y_at_end, double p1x, double p1y, double p2x, double p2y) {
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p1x = unit_value(p1x); p2x = unit_value(p2x);
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if (is_bezier_linear(p1x, p1y, p2x, p2y)) {
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init_function(a, y_at_start, y_at_end, identity_easing_curve);
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return;
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}
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BezierParameters *p = calloc(1, sizeof(BezierParameters));
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if (!p) fatal("Out of memory");
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// Calculate the polynomial coefficients, implicit first and last control points are (0,0) and (1,1).
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p->cx = 3.0 * p1x;
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p->bx = 3.0 * (p2x - p1x) - p->cx;
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p->ax = 1.0 - p->cx - p->bx;
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p->cy = 3.0 * p1y;
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p->by = 3.0 * (p2y - p1y) - p->cy;
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p->ay = 1.0 - p->cy - p->by;
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// Calculate gradients used for values outside the unit interval
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if (p1x > 0) p->start_gradient = p1y / p1x;
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else if (p1y == 0 && p2x > 0) p->start_gradient = p2y / p2x;
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else if (p1y == 0 && p2y == 0) p->start_gradient = 1;
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else p->start_gradient = 0;
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if (p2x < 1) p->end_gradient = (p2y - 1) / (p2x - 1);
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else if (p2y == 1 && p1x < 1) p->end_gradient = (p1y - 1) / (p1x - 1);
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else if (p2y == 1 && p1y == 1) p->end_gradient = 1;
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else p->end_gradient = 0;
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size_t num_samples = arraysz(p->spline_samples);
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double delta = 1. / num_samples;
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for (size_t i = 0; i < num_samples; i++) p->spline_samples[i] = sample_curve_x(p, i * delta);
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animation_function *f = init_function(a, y_at_start, y_at_end, cubic_bezier_easing_curve);
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f->params = p;
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}
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void
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add_linear_animation(Animation *a, double y_at_start, double y_at_end, size_t count, const double *x, const double *y) {
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const size_t sz = count * sizeof(double);
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LinearParameters *p = calloc(1, sizeof(LinearParameters) + 2 * sz);
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if (!p) fatal("Out of memory");
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p->count = count;
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double *px = p->buf, *py = px + count;
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memcpy(px, x, sz); memcpy(py, y, sz);
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animation_function *f = init_function(a, y_at_start, y_at_end, linear_easing_curve);
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f->params = p;
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}
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void
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add_steps_animation(Animation *a, double y_at_start, double y_at_end, size_t count, EasingStep step) {
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double jump_size = 1. / count, start_value = 0.;
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size_t num_of_buckets = count;
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switch (step) {
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case EASING_STEP_START: start_value = jump_size; break;
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case EASING_STEP_END: break;
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case EASING_STEP_NONE:
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jump_size = 1. / (num_of_buckets - 1);
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break;
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case EASING_STEP_BOTH:
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num_of_buckets++;
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jump_size = 1. / num_of_buckets;
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start_value = jump_size;
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break;
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}
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StepsParameters *p = malloc(sizeof(StepsParameters));
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if (!p) fatal("Out of memory");
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p->num_of_buckets = num_of_buckets; p->jump_size = jump_size; p->start_value = start_value;
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animation_function *f = init_function(a, y_at_start, y_at_end, step_easing_curve);
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f->params = p;
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}
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static PyObject*
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test_cursor_blink_easing_function(PyObject *self UNUSED, PyObject *args) {
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Animation *a = OPT(animation.cursor);
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if (!animation_is_valid(a)) {
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PyErr_SetString(PyExc_RuntimeError, "must set a cursor blink animation on the global options object first");
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return NULL;
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}
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double t, duration_s = 0.5; int only_single = 1;
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if (!PyArg_ParseTuple(args, "d|pd", &t, &only_single, &duration_s)) return NULL;
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monotonic_t duration = s_double_to_monotonic_t(duration_s);
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if (only_single) {
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animation_function f = a->functions[0];
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return PyFloat_FromDouble(f.curve(f.params, t, duration));
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}
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return PyFloat_FromDouble(apply_easing_curve(a, t, duration));
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}
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static PyMethodDef module_methods[] = {
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METHODB(test_cursor_blink_easing_function, METH_VARARGS),
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{NULL, NULL, 0, NULL} /* Sentinel */
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};
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bool init_animations(PyObject *module) {
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if (PyModule_AddFunctions(module, module_methods) != 0) return false;
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return true;
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}
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