Use sqrt() and curvature_clip for more uniform distribution.

nortikin · Nov 10, 2024 · d3877aa · d3877aa
1 parent 24fec7b
commit d3877aa
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Showing 2 changed files with 20 additions and 4 deletions.
diff --git a/nodes/curve/adaptive_plot_mk2.py b/nodes/curve/adaptive_plot_mk2.py
@@ -56,12 +56,22 @@ def update_sockets(self, context):
             default = False,
             update = update_sockets)
 
+    curvature_clip : FloatProperty(
+            name = "Curvature Clip",
+            min = 0.0,
+            default = 100.0,
+            update = updateNode)
+
     def draw_buttons(self, context, layout):
         row = layout.row(align=True)
         row.prop(self, 'by_curvature', toggle=True)
         row.prop(self, 'by_length', toggle=True)
         layout.prop(self, 'random')
 
+    def draw_buttons_ext(self, context, layout):
+        self.draw_buttons(context, layout)
+        layout.prop(self, 'curvature_clip')
+
     def sv_init(self, context):
         self.inputs.new('SvCurveSocket', "Curve")
         self.inputs.new('SvStringsSocket', "Count").prop_name = 'count'
@@ -95,6 +105,7 @@ def process(self):
                             resolution = resolution,
                             by_length = self.by_length,
                             by_curvature = self.by_curvature,
+                            curvature_clip = self.curvature_clip,
                             random = self.random,
                             seed = seed)
                 n = len(new_t)

diff --git a/utils/adaptive_curve.py b/utils/adaptive_curve.py
@@ -12,7 +12,8 @@
 from sverchok.utils.sv_logging import sv_logger
 from sverchok.utils.math import distribute_int
 from sverchok.utils.geom import CubicSpline
-from sverchok.utils.curve import SvCurveLengthSolver, CurvatureIntegral
+from sverchok.utils.integrate import TrapezoidIntegral
+from sverchok.utils.curve import SvCurveLengthSolver
 
 
 class CurvePopulationController(object):
@@ -173,7 +174,7 @@ def populate_curve_old(curve, samples_t, by_length = False, by_curvature = True,
         new_t = np.sort(new_t)
     return new_t
 
-def populate_curve(curve, n_points, resolution=100, by_length = False, by_curvature = True, random=False, seed=None):
+def populate_curve(curve, n_points, resolution=100, by_length = False, by_curvature = True, curvature_clip=100.0, random=False, seed=None):
     t_min, t_max = curve.get_u_bounds()
     factors = np.zeros((resolution,))
     ts = np.linspace(t_min, t_max, num=resolution)
@@ -182,8 +183,12 @@ def populate_curve(curve, n_points, resolution=100, by_length = False, by_curvat
         lengths = np.cumsum(np.insert(lengths, 0, 0))
         factors += lengths / lengths[-1]
     if by_curvature:
-        integral = CurvatureIntegral(curve, resolution, rescale_curvature = True)
-        factors += integral.values
+        curvatures = curve.curvature_array(ts)
+        curvatures = np.clip(curvatures, 0.0, curvature_clip)
+        integral = TrapezoidIntegral(ts, ts, np.sqrt(curvatures))
+        #integral = TrapezoidIntegral(ts, ts, curvatures)
+        integral.calc()
+        factors += integral.summands
     if not by_length and not by_curvature:
         factors = np.linspace(0.0, 1.0, num=resolution)
     factors /= factors[-1]