From ee064be0632a98ef5acac441db39a902f3a5df13 Mon Sep 17 00:00:00 2001 From: "Ilya V. Portnov" Date: Sun, 6 Oct 2024 14:43:01 +0500 Subject: [PATCH 01/14] "Prepare curves net" node: initial implementation. --- menus/full_by_data_type.yaml | 1 + nodes/curve/prepare_curves_net.py | 218 ++++++++++++++++++++++++++++++ 2 files changed, 219 insertions(+) create mode 100644 nodes/curve/prepare_curves_net.py diff --git a/menus/full_by_data_type.yaml b/menus/full_by_data_type.yaml index 3825c70b1d..97a51d0b94 100644 --- a/menus/full_by_data_type.yaml +++ b/menus/full_by_data_type.yaml @@ -319,6 +319,7 @@ - Analyze NURBS Curve: - icon_name: VIEWZOOM - SvIntersectNurbsCurvesNode + - SvPrepareCurvesNetNode - SvNurbsCurveNodesNode - SvDeconstructCurveNode - SvExMarchingSquaresNode diff --git a/nodes/curve/prepare_curves_net.py b/nodes/curve/prepare_curves_net.py new file mode 100644 index 0000000000..967a9f583f --- /dev/null +++ b/nodes/curve/prepare_curves_net.py @@ -0,0 +1,218 @@ +# This file is part of project Sverchok. It's copyrighted by the contributors +# recorded in the version control history of the file, available from +# its original location https://github.com/nortikin/sverchok/commit/master +# +# SPDX-License-Identifier: GPL3 +# License-Filename: LICENSE + +import numpy as np +import bpy +from bpy.props import FloatProperty, EnumProperty, BoolProperty + +from sverchok.node_tree import SverchCustomTreeNode +from sverchok.data_structure import updateNode, zip_long_repeat, ensure_nesting_level +from sverchok.utils.curve import SvCurve +from sverchok.utils.curve.nurbs import SvNurbsCurve +from sverchok.utils.curve.nurbs_solver_applications import adjust_curve_points +from sverchok.utils.manifolds import nearest_point_on_curve + +class SvPrepareCurvesNetNode(SverchCustomTreeNode, bpy.types.Node): + """ + Triggers: Curves Net + Tooltip: Adjust semi-intersecting curves in order to make a correct curves net + """ + bl_idname = 'SvPrepareCurvesNetNode' + bl_label = 'Prepare NURBS Curves Net' + bl_icon = 'OUTLINER_OB_EMPTY' + sv_icon = 'SV_INTERSECT_CURVES' + sv_dependencies = {'scipy'} + + t_modes = [ + ('COUNT', "By Curves Count", "Use uniform T values distribution according to curves count", 0), + ('EXPLICIT', "Explicit", "Use explicitly provided T values", 1), + ('FIT', "Nearest", "Automatically find T values for nearest points", 2) + ] + + bias_modes = [ + ('U', "Curve 1", "Curves along U direction are main, adjust curves along V direction", 0), + ('V', "Curve 2", "Curves along V direction are main, adjust curves along U direction", 1) + ] + + def update_sockets(self, context): + self.inputs['T1'].hide_safe = self.u_mode != 'EXPLICIT' + self.inputs['T2'].hide_safe = self.v_mode != 'EXPLICIT' + updateNode(self, context) + + bias : EnumProperty( + name = "Bias", + items = bias_modes, + default = 'U', + update = updateNode) + + u_mode : EnumProperty( + name = "T1 values", + items = t_modes, + default = 'COUNT', + update = update_sockets) + + v_mode : EnumProperty( + name = "T2 values", + items = t_modes, + default = 'COUNT', + update = update_sockets) + + preserve_tangents : BoolProperty( + name = "Preserve tangents", + default = False, + update = updateNode) + + def draw_buttons(self, context, layout): + layout.prop(self, 'bias') + layout.prop(self, 'u_mode') + layout.prop(self, 'v_mode') + + def sv_init(self, context): + self.inputs.new('SvCurveSocket', "Curve1") + self.inputs.new('SvCurveSocket', "Curve2") + self.inputs.new('SvStringsSocket', "T1") + self.inputs.new('SvStringsSocket', "T2") + self.outputs.new('SvCurveSocket', 'Curve1') + self.outputs.new('SvCurveSocket', 'Curve2') + self.outputs.new('SvVerticesSocket', 'Intersections') + self.outputs.new('SvStringsSocket', 'T1') + self.outputs.new('SvStringsSocket', 'T2') + self.update_sockets(context) + + def prepare_t_by_count(self, curves, n): + bounds = np.array([c.get_u_bounds() for c in curves]) + ts_min = bounds[:,0] + ts_max = bounds[:,1] + t_values = np.linspace(ts_min, ts_max, num=n).T + pts = [c.evaluate_array(t) for c, t in zip(curves, t_values)] + pts = np.array(pts) + return t_values, pts + + def prepare_t(self, mode, curves, t_values, n): + if mode == 'EXPLICIT': + target_pts = [c.evaluate_array(t) for c, t in zip(curves, t_values)] + target_pts = np.array(target_pts) + elif mode == 'COUNT': + t_values, target_pts = self.prepare_t_by_count(curves, n) + else: # FIT + raise Exception("Can't fit T values for base curves") + return t_values, target_pts + + def fit_t(self, primary_curves, primary_t_values, secondary_curves): + primary_curve_pts = [c.evaluate_array(primary_t_values[i]) for i, c in enumerate(primary_curves)] + primary_curve_pts = np.array(primary_curve_pts) + secondary_t_values = [nearest_point_on_curve(primary_curve_pts[:,i], curve, samples=100, output_points=False) for i, curve in enumerate(secondary_curves)] + secondary_t_values = np.array(secondary_t_values) + return secondary_t_values + + def prepare_uv(self, u_curves, v_curves, u_values, v_values): + if self.u_mode != 'FIT': + u_values, u_pts = self.prepare_t(self.u_mode, u_curves, u_values, len(v_curves)) + else: + u_values, u_pts = None, None + if self.v_mode != 'FIT': + v_values, v_pts = self.prepare_t(self.v_mode, v_curves, v_values, len(u_curves)) + else: + v_values, v_pts = None, None + if self.bias == 'U': + return u_values, v_values, u_pts + else: + return u_values, v_values, v_pts + + def process_single(self, u_curves, v_curves, u_values, v_values): + u_values, v_values, target_pts = self.prepare_uv(u_curves, v_curves, u_values, v_values) + if self.u_mode == 'FIT' and self.v_mode != 'FIT': + u_values = self.fit_t(v_curves, v_values, u_curves) + elif self.u_mode != 'FIT' and self.v_mode == 'FIT': + v_values = self.fit_t(u_curves, u_values, v_curves) + if target_pts is None: + if self.bias == 'U': + target_pts = [c.evaluate_array(t) for c, t in zip(u_curves, u_values)] + else: + target_pts = [c.evaluate_array(t) for c, t in zip(v_curves, v_values)] + target_pts = np.array(target_pts) + + if self.bias == 'U': + new_u_curves = u_curves + new_v_curves = [] + for i, v_curve in enumerate(v_curves): + pts = target_pts[:,i] + new_curve = adjust_curve_points(v_curve, v_values[i], pts, + preserve_tangents = self.preserve_tangents) + new_v_curves.append(new_curve) + else: + new_u_curves = [] + new_v_curves = v_curves + for i, u_curve in enumerate(u_curves): + pts = target_pts[:,i] + new_curve = adjust_curve_points(u_curve, u_values[i], pts, + preserve_tangents = self.preserve_tangents) + new_u_curves.append(new_curve) + if self.bias == 'U': + target_pts = np.transpose(target_pts, axes=(1,0,2)) + return new_u_curves, new_v_curves, target_pts, u_values, v_values + + def process(self): + if not any(socket.is_linked for socket in self.outputs): + return + + if self.u_mode == 'FIT' and self.v_mode == 'FIT': + raise Exception("Automatic T values fitting can not be enabled for both directions") + + u_curves_s = self.inputs['Curve1'].sv_get() + v_curves_s = self.inputs['Curve2'].sv_get() + u_curves_s = ensure_nesting_level(u_curves_s, 3, data_types=(SvCurve,)) + v_curves_s = ensure_nesting_level(v_curves_s, 3, data_types=(SvCurve,)) + + if self.u_mode == 'EXPLICIT': + u_values_s = self.inputs['T1'].sv_get() + u_values_s = ensure_nesting_level(u_values_s, 4) + else: + u_values_s = [[None]] + if self.v_mode == 'EXPLICIT': + v_values_s = self.inputs['T2'].sv_get() + v_values_s = ensure_nesting_level(v_values_s, 4) + else: + v_values_s = [[None]] + + u_curves_out = [] + v_curves_out = [] + pts_out = [] + u_out = [] + v_out = [] + for params in zip_long_repeat(u_curves_s, v_curves_s, u_values_s, v_values_s): + new_u_curves = [] + new_v_curves = [] + new_pts = [] + new_u_values = [] + new_v_values = [] + for u_curves, v_curves, u_values, v_values in zip_long_repeat(*params): + u_curves, v_curves, pts, u_values, v_values = self.process_single(u_curves, v_curves, u_values, v_values) + new_u_curves.append(u_curves) + new_v_curves.append(v_curves) + new_pts.append(pts) + new_u_values.append(u_values) + new_v_values.append(v_values) + u_curves_out.append(new_u_curves) + v_curves_out.append(new_v_curves) + pts_out.append(new_pts) + u_out.append(new_u_values) + v_out.append(new_v_values) + + self.outputs['Curve1'].sv_set(u_curves_out) + self.outputs['Curve2'].sv_set(v_curves_out) + self.outputs['Intersections'].sv_set(pts_out) + self.outputs['T1'].sv_set(u_out) + self.outputs['T2'].sv_set(v_out) + +def register(): + bpy.utils.register_class(SvPrepareCurvesNetNode) + + +def unregister(): + bpy.utils.unregister_class(SvPrepareCurvesNetNode) + From e7837505326c6faac1e4a9647998e1631072d7bf Mon Sep 17 00:00:00 2001 From: "Ilya V. Portnov" Date: Sun, 6 Oct 2024 15:33:45 +0500 Subject: [PATCH 02/14] Deal with nesting. --- nodes/curve/prepare_curves_net.py | 51 +++++++++++++++++++++++-------- 1 file changed, 38 insertions(+), 13 deletions(-) diff --git a/nodes/curve/prepare_curves_net.py b/nodes/curve/prepare_curves_net.py index 967a9f583f..0a1f03a008 100644 --- a/nodes/curve/prepare_curves_net.py +++ b/nodes/curve/prepare_curves_net.py @@ -7,10 +7,10 @@ import numpy as np import bpy -from bpy.props import FloatProperty, EnumProperty, BoolProperty +from bpy.props import FloatProperty, EnumProperty, BoolProperty, IntProperty from sverchok.node_tree import SverchCustomTreeNode -from sverchok.data_structure import updateNode, zip_long_repeat, ensure_nesting_level +from sverchok.data_structure import updateNode, zip_long_repeat, ensure_nesting_level, get_data_nesting_level from sverchok.utils.curve import SvCurve from sverchok.utils.curve.nurbs import SvNurbsCurve from sverchok.utils.curve.nurbs_solver_applications import adjust_curve_points @@ -29,8 +29,8 @@ class SvPrepareCurvesNetNode(SverchCustomTreeNode, bpy.types.Node): t_modes = [ ('COUNT', "By Curves Count", "Use uniform T values distribution according to curves count", 0), - ('EXPLICIT', "Explicit", "Use explicitly provided T values", 1), - ('FIT', "Nearest", "Automatically find T values for nearest points", 2) + ('FIT', "By Curves Location", "Automatically find T values for nearest points", 1), + ('EXPLICIT', "Explicit", "Use explicitly provided T values", 2) ] bias_modes = [ @@ -66,10 +66,25 @@ def update_sockets(self, context): default = False, update = updateNode) + fit_samples : IntProperty( + name = "Fit Samples", + description = "Initial number of subdivisions for search of nearest points", + default = 50, + min = 3, + update = updateNode) + def draw_buttons(self, context, layout): - layout.prop(self, 'bias') - layout.prop(self, 'u_mode') - layout.prop(self, 'v_mode') + layout.label(text='Primary curves:') + layout.prop(self, 'bias', text='') + layout.label(text='Curve 1 parameters:') + layout.prop(self, 'u_mode', text='') + layout.label(text='Curve 2 parameters:') + layout.prop(self, 'v_mode', text='') + layout.prop(self, 'preserve_tangents') + + def draw_buttons_ext(self, context, layout): + self.draw_buttons(context, layout) + layout.prop(self, 'fit_samples') def sv_init(self, context): self.inputs.new('SvCurveSocket', "Curve1") @@ -105,7 +120,7 @@ def prepare_t(self, mode, curves, t_values, n): def fit_t(self, primary_curves, primary_t_values, secondary_curves): primary_curve_pts = [c.evaluate_array(primary_t_values[i]) for i, c in enumerate(primary_curves)] primary_curve_pts = np.array(primary_curve_pts) - secondary_t_values = [nearest_point_on_curve(primary_curve_pts[:,i], curve, samples=100, output_points=False) for i, curve in enumerate(secondary_curves)] + secondary_t_values = [nearest_point_on_curve(primary_curve_pts[:,i], curve, samples=self.fit_samples, output_points=False) for i, curve in enumerate(secondary_curves)] secondary_t_values = np.array(secondary_t_values) return secondary_t_values @@ -165,6 +180,9 @@ def process(self): u_curves_s = self.inputs['Curve1'].sv_get() v_curves_s = self.inputs['Curve2'].sv_get() + input_level_u = get_data_nesting_level(u_curves_s, data_types=(SvCurve,)) + input_level_v = get_data_nesting_level(v_curves_s, data_types=(SvCurve,)) + flat_output = max(input_level_u, input_level_v) <= 2 u_curves_s = ensure_nesting_level(u_curves_s, 3, data_types=(SvCurve,)) v_curves_s = ensure_nesting_level(v_curves_s, 3, data_types=(SvCurve,)) @@ -197,11 +215,18 @@ def process(self): new_pts.append(pts) new_u_values.append(u_values) new_v_values.append(v_values) - u_curves_out.append(new_u_curves) - v_curves_out.append(new_v_curves) - pts_out.append(new_pts) - u_out.append(new_u_values) - v_out.append(new_v_values) + if flat_output: + u_curves_out.extend(new_u_curves) + v_curves_out.extend(new_v_curves) + pts_out.extend(new_pts) + u_out.extend(new_u_values) + v_out.extend(new_v_values) + else: + u_curves_out.append(new_u_curves) + v_curves_out.append(new_v_curves) + pts_out.append(new_pts) + u_out.append(new_u_values) + v_out.append(new_v_values) self.outputs['Curve1'].sv_set(u_curves_out) self.outputs['Curve2'].sv_set(v_curves_out) From 0d4a9b13cda14b1d382bf9c4f2ee9e829bf27251 Mon Sep 17 00:00:00 2001 From: "Ilya V. Portnov" Date: Sun, 6 Oct 2024 15:34:41 +0500 Subject: [PATCH 03/14] Icon. --- nodes/curve/prepare_curves_net.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/nodes/curve/prepare_curves_net.py b/nodes/curve/prepare_curves_net.py index 0a1f03a008..f7f9c51969 100644 --- a/nodes/curve/prepare_curves_net.py +++ b/nodes/curve/prepare_curves_net.py @@ -24,7 +24,7 @@ class SvPrepareCurvesNetNode(SverchCustomTreeNode, bpy.types.Node): bl_idname = 'SvPrepareCurvesNetNode' bl_label = 'Prepare NURBS Curves Net' bl_icon = 'OUTLINER_OB_EMPTY' - sv_icon = 'SV_INTERSECT_CURVES' + sv_icon = 'SV_SURFACE_FROM_CURVES' sv_dependencies = {'scipy'} t_modes = [ From 8b3838efe0a5a4079e1e9acc34e1a397fa1a2b61 Mon Sep 17 00:00:00 2001 From: "Ilya V. Portnov" Date: Sun, 6 Oct 2024 15:36:52 +0500 Subject: [PATCH 04/14] Rename parameter --- nodes/curve/prepare_curves_net.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/nodes/curve/prepare_curves_net.py b/nodes/curve/prepare_curves_net.py index f7f9c51969..1d0663e05f 100644 --- a/nodes/curve/prepare_curves_net.py +++ b/nodes/curve/prepare_curves_net.py @@ -28,7 +28,7 @@ class SvPrepareCurvesNetNode(SverchCustomTreeNode, bpy.types.Node): sv_dependencies = {'scipy'} t_modes = [ - ('COUNT', "By Curves Count", "Use uniform T values distribution according to curves count", 0), + ('COUNT', "Uniform", "Use uniform T values distribution according to curves count", 0), ('FIT', "By Curves Location", "Automatically find T values for nearest points", 1), ('EXPLICIT', "Explicit", "Use explicitly provided T values", 2) ] From 8f02dd24af0f401b7b4162f18012244ea638c9ca Mon Sep 17 00:00:00 2001 From: "Ilya V. Portnov" Date: Sun, 6 Oct 2024 16:46:16 +0500 Subject: [PATCH 05/14] Better error handling. --- utils/curve/nurbs_solver_applications.py | 6 +++++- 1 file changed, 5 insertions(+), 1 deletion(-) diff --git a/utils/curve/nurbs_solver_applications.py b/utils/curve/nurbs_solver_applications.py index 53a06d40af..790c3ca3e2 100644 --- a/utils/curve/nurbs_solver_applications.py +++ b/utils/curve/nurbs_solver_applications.py @@ -44,7 +44,11 @@ def adjust_curve_points(curve, us_bar, points, preserve_tangents=False): zeros = np.zeros((n_target_points,3)) solver.add_goal(SvNurbsCurveTangents(us_bar, zeros, relative=True)) solver.set_curve_params(len(curve.get_control_points()), curve.get_knotvector()) - return solver.solve() + problem_type, residue, curve = solver.solve_ex( + problem_types = {SvNurbsCurveSolver.PROBLEM_UNDERDETERMINED, + SvNurbsCurveSolver.PROBLEM_WELLDETERMINED} + ) + return curve def deform_curve_with_falloff(curve, length_solver, u_bar, falloff_delta, falloff_type, vector, refine_samples=30, tolerance=1e-4): """ From 6fcc91cba4aeb17d2121d43a9e0b1c61d55ebafe Mon Sep 17 00:00:00 2001 From: "Ilya V. Portnov" Date: Sun, 6 Oct 2024 18:15:01 +0500 Subject: [PATCH 06/14] Add node to menus. --- index.yaml | 1 + menus/full_nortikin.yaml | 1 + 2 files changed, 2 insertions(+) diff --git a/index.yaml b/index.yaml index e00976e494..878bb3747f 100644 --- a/index.yaml +++ b/index.yaml @@ -126,6 +126,7 @@ - SvExSurfaceBoundaryNode - --- - SvIntersectNurbsCurvesNode + - SvPrepareCurvesNetNode - SvExNearestPointOnCurveNode - SvExOrthoProjectCurveNode - SvExCurveEndpointsNode diff --git a/menus/full_nortikin.yaml b/menus/full_nortikin.yaml index cc360467f9..318395f5d5 100644 --- a/menus/full_nortikin.yaml +++ b/menus/full_nortikin.yaml @@ -537,6 +537,7 @@ - icon_name: OUTLINER_OB_CURVE - extra_menu: AdvancedObjectsPartialMenu - SvIntersectNurbsCurvesNode + - SvPrepareCurvesNetNode - SvExCastCurveNode - SvProjectCurveSurfaceNode - SvOffsetCurveMk2Node From 059f48b6a93bcbf7d70f6af51ed0b8a69814919f Mon Sep 17 00:00:00 2001 From: "Ilya V. Portnov" Date: Sun, 6 Oct 2024 18:36:24 +0500 Subject: [PATCH 07/14] Factor out logic into utils module. --- nodes/curve/prepare_curves_net.py | 93 ++++----------------------- utils/curve/prepare_curves_net.py | 101 ++++++++++++++++++++++++++++++ 2 files changed, 113 insertions(+), 81 deletions(-) create mode 100644 utils/curve/prepare_curves_net.py diff --git a/nodes/curve/prepare_curves_net.py b/nodes/curve/prepare_curves_net.py index 1d0663e05f..a6591dce33 100644 --- a/nodes/curve/prepare_curves_net.py +++ b/nodes/curve/prepare_curves_net.py @@ -13,7 +13,7 @@ from sverchok.data_structure import updateNode, zip_long_repeat, ensure_nesting_level, get_data_nesting_level from sverchok.utils.curve import SvCurve from sverchok.utils.curve.nurbs import SvNurbsCurve -from sverchok.utils.curve.nurbs_solver_applications import adjust_curve_points +from sverchok.utils.curve.prepare_curves_net import prepare_curves_net, COUNT, FIT, EXPLICIT, PRIMARY_U, PRIMARY_V from sverchok.utils.manifolds import nearest_point_on_curve class SvPrepareCurvesNetNode(SverchCustomTreeNode, bpy.types.Node): @@ -28,9 +28,9 @@ class SvPrepareCurvesNetNode(SverchCustomTreeNode, bpy.types.Node): sv_dependencies = {'scipy'} t_modes = [ - ('COUNT', "Uniform", "Use uniform T values distribution according to curves count", 0), - ('FIT', "By Curves Location", "Automatically find T values for nearest points", 1), - ('EXPLICIT', "Explicit", "Use explicitly provided T values", 2) + (COUNT, "Uniform", "Use uniform T values distribution according to curves count", 0), + (FIT, "By Curves Location", "Automatically find T values for nearest points", 1), + (EXPLICIT, "Explicit", "Use explicitly provided T values", 2) ] bias_modes = [ @@ -98,86 +98,10 @@ def sv_init(self, context): self.outputs.new('SvStringsSocket', 'T2') self.update_sockets(context) - def prepare_t_by_count(self, curves, n): - bounds = np.array([c.get_u_bounds() for c in curves]) - ts_min = bounds[:,0] - ts_max = bounds[:,1] - t_values = np.linspace(ts_min, ts_max, num=n).T - pts = [c.evaluate_array(t) for c, t in zip(curves, t_values)] - pts = np.array(pts) - return t_values, pts - - def prepare_t(self, mode, curves, t_values, n): - if mode == 'EXPLICIT': - target_pts = [c.evaluate_array(t) for c, t in zip(curves, t_values)] - target_pts = np.array(target_pts) - elif mode == 'COUNT': - t_values, target_pts = self.prepare_t_by_count(curves, n) - else: # FIT - raise Exception("Can't fit T values for base curves") - return t_values, target_pts - - def fit_t(self, primary_curves, primary_t_values, secondary_curves): - primary_curve_pts = [c.evaluate_array(primary_t_values[i]) for i, c in enumerate(primary_curves)] - primary_curve_pts = np.array(primary_curve_pts) - secondary_t_values = [nearest_point_on_curve(primary_curve_pts[:,i], curve, samples=self.fit_samples, output_points=False) for i, curve in enumerate(secondary_curves)] - secondary_t_values = np.array(secondary_t_values) - return secondary_t_values - - def prepare_uv(self, u_curves, v_curves, u_values, v_values): - if self.u_mode != 'FIT': - u_values, u_pts = self.prepare_t(self.u_mode, u_curves, u_values, len(v_curves)) - else: - u_values, u_pts = None, None - if self.v_mode != 'FIT': - v_values, v_pts = self.prepare_t(self.v_mode, v_curves, v_values, len(u_curves)) - else: - v_values, v_pts = None, None - if self.bias == 'U': - return u_values, v_values, u_pts - else: - return u_values, v_values, v_pts - - def process_single(self, u_curves, v_curves, u_values, v_values): - u_values, v_values, target_pts = self.prepare_uv(u_curves, v_curves, u_values, v_values) - if self.u_mode == 'FIT' and self.v_mode != 'FIT': - u_values = self.fit_t(v_curves, v_values, u_curves) - elif self.u_mode != 'FIT' and self.v_mode == 'FIT': - v_values = self.fit_t(u_curves, u_values, v_curves) - if target_pts is None: - if self.bias == 'U': - target_pts = [c.evaluate_array(t) for c, t in zip(u_curves, u_values)] - else: - target_pts = [c.evaluate_array(t) for c, t in zip(v_curves, v_values)] - target_pts = np.array(target_pts) - - if self.bias == 'U': - new_u_curves = u_curves - new_v_curves = [] - for i, v_curve in enumerate(v_curves): - pts = target_pts[:,i] - new_curve = adjust_curve_points(v_curve, v_values[i], pts, - preserve_tangents = self.preserve_tangents) - new_v_curves.append(new_curve) - else: - new_u_curves = [] - new_v_curves = v_curves - for i, u_curve in enumerate(u_curves): - pts = target_pts[:,i] - new_curve = adjust_curve_points(u_curve, u_values[i], pts, - preserve_tangents = self.preserve_tangents) - new_u_curves.append(new_curve) - if self.bias == 'U': - target_pts = np.transpose(target_pts, axes=(1,0,2)) - return new_u_curves, new_v_curves, target_pts, u_values, v_values - def process(self): if not any(socket.is_linked for socket in self.outputs): return - if self.u_mode == 'FIT' and self.v_mode == 'FIT': - raise Exception("Automatic T values fitting can not be enabled for both directions") - u_curves_s = self.inputs['Curve1'].sv_get() v_curves_s = self.inputs['Curve2'].sv_get() input_level_u = get_data_nesting_level(u_curves_s, data_types=(SvCurve,)) @@ -209,7 +133,14 @@ def process(self): new_u_values = [] new_v_values = [] for u_curves, v_curves, u_values, v_values in zip_long_repeat(*params): - u_curves, v_curves, pts, u_values, v_values = self.process_single(u_curves, v_curves, u_values, v_values) + res = prepare_curves_net(u_curves, v_curves, + u_values, v_values, + bias = self.bias, + u_mode = self.u_mode, + v_mode = self.v_mode, + fit_samples = self.fit_samples, + preserve_tangents = self.preserve_tangents) + u_curves, v_curves, pts, u_values, v_values = res new_u_curves.append(u_curves) new_v_curves.append(v_curves) new_pts.append(pts) diff --git a/utils/curve/prepare_curves_net.py b/utils/curve/prepare_curves_net.py new file mode 100644 index 0000000000..3306549990 --- /dev/null +++ b/utils/curve/prepare_curves_net.py @@ -0,0 +1,101 @@ +# This file is part of project Sverchok. It's copyrighted by the contributors +# recorded in the version control history of the file, available from +# its original location https://github.com/nortikin/sverchok/commit/master +# +# SPDX-License-Identifier: GPL3 +# License-Filename: LICENSE + +import numpy as np +from sverchok.utils.curve.nurbs_solver_applications import adjust_curve_points +from sverchok.utils.manifolds import nearest_point_on_curve + +COUNT = 'COUNT' +FIT = 'FIT' +EXPLICIT = 'EXPLICIT' +PRIMARY_U = 'U' +PRIMARY_V = 'V' + +def prepare_curves_net(u_curves, v_curves, + u_values, v_values, + bias = PRIMARY_U, + u_mode = COUNT, + v_mode = COUNT, + fit_samples = 50, + preserve_tangents = False): + + if u_mode == FIT and v_mode == FIT: + raise Exception("Automatic T values fitting can not be enabled for both directions") + + def prepare_t_by_count(curves, n): + bounds = np.array([c.get_u_bounds() for c in curves]) + ts_min = bounds[:,0] + ts_max = bounds[:,1] + t_values = np.linspace(ts_min, ts_max, num=n).T + pts = [c.evaluate_array(t) for c, t in zip(curves, t_values)] + pts = np.array(pts) + return t_values, pts + + def prepare_t(mode, curves, t_values, n): + if mode == EXPLICIT: + target_pts = [c.evaluate_array(t) for c, t in zip(curves, t_values)] + target_pts = np.array(target_pts) + elif mode == COUNT: + t_values, target_pts = prepare_t_by_count(curves, n) + else: # FIT + raise Exception("Can't fit T values for base curves") + return t_values, target_pts + + def fit_t(primary_curves, primary_t_values, secondary_curves): + primary_curve_pts = [c.evaluate_array(primary_t_values[i]) for i, c in enumerate(primary_curves)] + primary_curve_pts = np.array(primary_curve_pts) + secondary_t_values = [nearest_point_on_curve(primary_curve_pts[:,i], curve, samples=fit_samples, output_points=False) for i, curve in enumerate(secondary_curves)] + secondary_t_values = np.array(secondary_t_values) + return secondary_t_values + + def prepare_uv(): + nonlocal u_values, v_values + if u_mode != FIT: + u_values, u_pts = prepare_t(u_mode, u_curves, u_values, len(v_curves)) + else: + u_values, u_pts = None, None + if v_mode != FIT: + v_values, v_pts = prepare_t(v_mode, v_curves, v_values, len(u_curves)) + else: + v_values, v_pts = None, None + if bias == PRIMARY_U: + return u_values, v_values, u_pts + else: + return u_values, v_values, v_pts + + u_values, v_values, target_pts = prepare_uv() + if u_mode == FIT and v_mode != FIT: + u_values = fit_t(v_curves, v_values, u_curves) + elif u_mode != FIT and v_mode == FIT: + v_values = fit_t(u_curves, u_values, v_curves) + if target_pts is None: + if bias == PRIMARY_U: + target_pts = [c.evaluate_array(t) for c, t in zip(u_curves, u_values)] + else: + target_pts = [c.evaluate_array(t) for c, t in zip(v_curves, v_values)] + target_pts = np.array(target_pts) + + if bias == PRIMARY_U: + new_u_curves = u_curves + new_v_curves = [] + for i, v_curve in enumerate(v_curves): + pts = target_pts[:,i] + new_curve = adjust_curve_points(v_curve, v_values[i], pts, + preserve_tangents = preserve_tangents) + new_v_curves.append(new_curve) + else: + new_u_curves = [] + new_v_curves = v_curves + for i, u_curve in enumerate(u_curves): + pts = target_pts[:,i] + new_curve = adjust_curve_points(u_curve, u_values[i], pts, + preserve_tangents = preserve_tangents) + new_u_curves.append(new_curve) + if bias == PRIMARY_U: + target_pts = np.transpose(target_pts, axes=(1,0,2)) + return new_u_curves, new_v_curves, target_pts, u_values, v_values + From 59f496421a97c1877cc145b2a2da9495e736c967 Mon Sep 17 00:00:00 2001 From: "Ilya V. Portnov" Date: Sun, 6 Oct 2024 18:49:42 +0500 Subject: [PATCH 08/14] Some code documentation. --- nodes/curve/prepare_curves_net.py | 20 +++++++++--------- utils/curve/prepare_curves_net.py | 34 ++++++++++++++++++++++++++++--- 2 files changed, 41 insertions(+), 13 deletions(-) diff --git a/nodes/curve/prepare_curves_net.py b/nodes/curve/prepare_curves_net.py index a6591dce33..17fabc4b87 100644 --- a/nodes/curve/prepare_curves_net.py +++ b/nodes/curve/prepare_curves_net.py @@ -13,7 +13,7 @@ from sverchok.data_structure import updateNode, zip_long_repeat, ensure_nesting_level, get_data_nesting_level from sverchok.utils.curve import SvCurve from sverchok.utils.curve.nurbs import SvNurbsCurve -from sverchok.utils.curve.prepare_curves_net import prepare_curves_net, COUNT, FIT, EXPLICIT, PRIMARY_U, PRIMARY_V +from sverchok.utils.curve.prepare_curves_net import prepare_curves_net, UNIFORM, FIT, EXPLICIT, PRIMARY_U, PRIMARY_V from sverchok.utils.manifolds import nearest_point_on_curve class SvPrepareCurvesNetNode(SverchCustomTreeNode, bpy.types.Node): @@ -28,19 +28,19 @@ class SvPrepareCurvesNetNode(SverchCustomTreeNode, bpy.types.Node): sv_dependencies = {'scipy'} t_modes = [ - (COUNT, "Uniform", "Use uniform T values distribution according to curves count", 0), + (UNIFORM, "Uniform", "Use uniform T values distribution according to curves count", 0), (FIT, "By Curves Location", "Automatically find T values for nearest points", 1), (EXPLICIT, "Explicit", "Use explicitly provided T values", 2) ] bias_modes = [ - ('U', "Curve 1", "Curves along U direction are main, adjust curves along V direction", 0), - ('V', "Curve 2", "Curves along V direction are main, adjust curves along U direction", 1) + (PRIMARY_U, "Curve 1", "Curves along U direction are main, adjust curves along V direction", 0), + (PRIMARY_V, "Curve 2", "Curves along V direction are main, adjust curves along U direction", 1) ] def update_sockets(self, context): - self.inputs['T1'].hide_safe = self.u_mode != 'EXPLICIT' - self.inputs['T2'].hide_safe = self.v_mode != 'EXPLICIT' + self.inputs['T1'].hide_safe = self.u_mode != EXPLICIT + self.inputs['T2'].hide_safe = self.v_mode != EXPLICIT updateNode(self, context) bias : EnumProperty( @@ -52,13 +52,13 @@ def update_sockets(self, context): u_mode : EnumProperty( name = "T1 values", items = t_modes, - default = 'COUNT', + default = UNIFORM, update = update_sockets) v_mode : EnumProperty( name = "T2 values", items = t_modes, - default = 'COUNT', + default = UNIFORM, update = update_sockets) preserve_tangents : BoolProperty( @@ -110,12 +110,12 @@ def process(self): u_curves_s = ensure_nesting_level(u_curves_s, 3, data_types=(SvCurve,)) v_curves_s = ensure_nesting_level(v_curves_s, 3, data_types=(SvCurve,)) - if self.u_mode == 'EXPLICIT': + if self.u_mode == EXPLICIT: u_values_s = self.inputs['T1'].sv_get() u_values_s = ensure_nesting_level(u_values_s, 4) else: u_values_s = [[None]] - if self.v_mode == 'EXPLICIT': + if self.v_mode == EXPLICIT: v_values_s = self.inputs['T2'].sv_get() v_values_s = ensure_nesting_level(v_values_s, 4) else: diff --git a/utils/curve/prepare_curves_net.py b/utils/curve/prepare_curves_net.py index 3306549990..f8ca2d2563 100644 --- a/utils/curve/prepare_curves_net.py +++ b/utils/curve/prepare_curves_net.py @@ -9,7 +9,7 @@ from sverchok.utils.curve.nurbs_solver_applications import adjust_curve_points from sverchok.utils.manifolds import nearest_point_on_curve -COUNT = 'COUNT' +UNIFORM = 'COUNT' FIT = 'FIT' EXPLICIT = 'EXPLICIT' PRIMARY_U = 'U' @@ -18,10 +18,38 @@ def prepare_curves_net(u_curves, v_curves, u_values, v_values, bias = PRIMARY_U, - u_mode = COUNT, - v_mode = COUNT, + u_mode = UNIFORM, + v_mode = UNIFORM, fit_samples = 50, preserve_tangents = False): + """ + Adjust U- or V-curves so that each U-curve would exactly intersect each V-curve. + + Args: + * u_curves, v_curves: two lists of SvCurve instances. + * u_values, v_values: curve parameter values, at which they should + intersect. Mandatory if corresponding (u_mode or v_mode) is EXPLICIT. + * bias: PRIMARY_U or PRIMARY_V. PRIMARY_U means leave U curves as is + and adjust V curves. PRIMARY_V means adjust U curves. + * u_mode, v_mode: modes of providing curve parameter values for intersection. + Possible values are UNIFORM, FIT and EXPLICIT. UNIFORM means uniform T + values distribution; FIT means find nearest place on the curve to + corresponding point on another curve; EXPLICIT means use explicitly + provided values. u_mode and v_mode can not be set to FIT simultaneously. + * fit_samples: initial resolution parameter for finding nearest point + (for FIT mode). + * preserve_tangents: if True, preserve curve tangents while adjusting. + This may lead to error if there are too few control points on curves + being adjusted (you may need to refine curves first). + + Returns: + Tuple: + * new u_curves + * new v_curves + * intersection points + * intersection T parameter values for U curves + * intersection T parameter values for V curves + """ if u_mode == FIT and v_mode == FIT: raise Exception("Automatic T values fitting can not be enabled for both directions") From cff21dd7faa3c4b9648cf977a61bae47c403e391 Mon Sep 17 00:00:00 2001 From: "Ilya V. Portnov" Date: Sun, 6 Oct 2024 20:24:58 +0500 Subject: [PATCH 09/14] Add crop_u, crop_v parameters. --- nodes/curve/prepare_curves_net.py | 19 +++++++++++++++++++ utils/curve/prepare_curves_net.py | 15 ++++++++++++++- 2 files changed, 33 insertions(+), 1 deletion(-) diff --git a/nodes/curve/prepare_curves_net.py b/nodes/curve/prepare_curves_net.py index 17fabc4b87..45a0956bd0 100644 --- a/nodes/curve/prepare_curves_net.py +++ b/nodes/curve/prepare_curves_net.py @@ -66,6 +66,16 @@ def update_sockets(self, context): default = False, update = updateNode) + crop_u : BoolProperty( + name = "Crop U Curves", + default = False, + update = updateNode) + + crop_v : BoolProperty( + name = "Crop V Curves", + default = False, + update = updateNode) + fit_samples : IntProperty( name = "Fit Samples", description = "Initial number of subdivisions for search of nearest points", @@ -81,6 +91,8 @@ def draw_buttons(self, context, layout): layout.label(text='Curve 2 parameters:') layout.prop(self, 'v_mode', text='') layout.prop(self, 'preserve_tangents') + layout.prop(self, 'crop_u') + layout.prop(self, 'crop_v') def draw_buttons_ext(self, context, layout): self.draw_buttons(context, layout) @@ -133,12 +145,19 @@ def process(self): new_u_values = [] new_v_values = [] for u_curves, v_curves, u_values, v_values in zip_long_repeat(*params): + u_curves = [SvNurbsCurve.to_nurbs(c) for c in u_curves] + v_curves = [SvNurbsCurve.to_nurbs(c) for c in v_curves] + if any(c is None for c in u_curves): + raise Exception("Some of U curves are not NURBS curves") + if any(c is None for c in v_curves): + raise Exception("Some of V curves are not NURBS curves") res = prepare_curves_net(u_curves, v_curves, u_values, v_values, bias = self.bias, u_mode = self.u_mode, v_mode = self.v_mode, fit_samples = self.fit_samples, + crop_u = self.crop_u, crop_v = self.crop_v, preserve_tangents = self.preserve_tangents) u_curves, v_curves, pts, u_values, v_values = res new_u_curves.append(u_curves) diff --git a/utils/curve/prepare_curves_net.py b/utils/curve/prepare_curves_net.py index f8ca2d2563..fb5e8afeca 100644 --- a/utils/curve/prepare_curves_net.py +++ b/utils/curve/prepare_curves_net.py @@ -20,6 +20,8 @@ def prepare_curves_net(u_curves, v_curves, bias = PRIMARY_U, u_mode = UNIFORM, v_mode = UNIFORM, + crop_u = False, + crop_v = False, fit_samples = 50, preserve_tangents = False): """ @@ -38,6 +40,8 @@ def prepare_curves_net(u_curves, v_curves, provided values. u_mode and v_mode can not be set to FIT simultaneously. * fit_samples: initial resolution parameter for finding nearest point (for FIT mode). + * crop_u, crop_v: if True, cut off tails of U and/or V curves, which + are outside first and last intersections. * preserve_tangents: if True, preserve curve tangents while adjusting. This may lead to error if there are too few control points on curves being adjusted (you may need to refine curves first). @@ -67,7 +71,7 @@ def prepare_t(mode, curves, t_values, n): if mode == EXPLICIT: target_pts = [c.evaluate_array(t) for c, t in zip(curves, t_values)] target_pts = np.array(target_pts) - elif mode == COUNT: + elif mode == UNIFORM: t_values, target_pts = prepare_t_by_count(curves, n) else: # FIT raise Exception("Can't fit T values for base curves") @@ -95,6 +99,11 @@ def prepare_uv(): else: return u_values, v_values, v_pts + def crop(curve, t_values): + t_min = min(t_values) + t_max = max(t_values) + return curve.cut_segment(t_min, t_max) + u_values, v_values, target_pts = prepare_uv() if u_mode == FIT and v_mode != FIT: u_values = fit_t(v_curves, v_values, u_curves) @@ -125,5 +134,9 @@ def prepare_uv(): new_u_curves.append(new_curve) if bias == PRIMARY_U: target_pts = np.transpose(target_pts, axes=(1,0,2)) + if crop_u: + new_u_curves = [crop(c, u_values[i]) for i, c in enumerate(new_u_curves)] + if crop_v: + new_v_curves = [crop(c, v_values[i]) for i, c in enumerate(new_v_curves)] return new_u_curves, new_v_curves, target_pts, u_values, v_values From 20ff8d5edee3f1d3ca198604456728ece619ae76 Mon Sep 17 00:00:00 2001 From: "Ilya V. Portnov" Date: Mon, 7 Oct 2024 19:35:46 +0500 Subject: [PATCH 10/14] Node documentation. --- .../curve/prepare_curves_net_crop_off.png | Bin 0 -> 286647 bytes .../curve/prepare_curves_net_crop_on.png | Bin 0 -> 285896 bytes .../curve/prepare_curves_net_curve1_nodes.png | Bin 0 -> 151197 bytes .../prepare_curves_net_curve1_result.png | Bin 0 -> 746654 bytes .../curve/prepare_curves_net_curve2_nodes.png | Bin 0 -> 189175 bytes .../prepare_curves_net_curve2_result.png | Bin 0 -> 727598 bytes .../curve/prepare_curves_net_original.png | Bin 0 -> 152705 bytes docs/nodes/curve/prepare_curves_net.rst | 146 ++++++++++++++++++ nodes/curve/prepare_curves_net.py | 8 +- 9 files changed, 149 insertions(+), 5 deletions(-) create mode 100644 docs/assets/nodes/curve/prepare_curves_net_crop_off.png create mode 100644 docs/assets/nodes/curve/prepare_curves_net_crop_on.png create mode 100644 docs/assets/nodes/curve/prepare_curves_net_curve1_nodes.png create mode 100644 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