Searched refs:norm_distances (Results 1 – 7 of 7) sorted by relevance
/dports/devel/etl/synfig-1.2.2/synfig-studio/src/synfigapp/ |
H A D | wplistconverter.cpp | 104 norm_distances.push_back(distances[i]/distances[n-1]); in operator ()() 115 …work_out[i]=WidthPoint(norm_distances[i], widths[i], WidthPoint::TYPE_INTERPOLATE, WidthPoint::TYP… in operator ()() 163 g=widths[i]-widthpoint_interpolate(wp_prev, wp_next, norm_distances[i], false); in calculate_ek2() 221 norm_distances.clear(); in clear()
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H A D | wplistconverter.h | 57 std::vector<synfig::Real> norm_distances; variable
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/dports/graphics/synfigstudio/synfig-1.2.2/synfig-studio/src/synfigapp/ |
H A D | wplistconverter.cpp | 104 norm_distances.push_back(distances[i]/distances[n-1]); in operator ()() 115 …work_out[i]=WidthPoint(norm_distances[i], widths[i], WidthPoint::TYPE_INTERPOLATE, WidthPoint::TYP… in operator ()() 163 g=widths[i]-widthpoint_interpolate(wp_prev, wp_next, norm_distances[i], false); in calculate_ek2() 221 norm_distances.clear(); in clear()
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H A D | wplistconverter.h | 57 std::vector<synfig::Real> norm_distances; variable
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/dports/graphics/synfig/synfig-1.2.2/synfig-studio/src/synfigapp/ |
H A D | wplistconverter.cpp | 104 norm_distances.push_back(distances[i]/distances[n-1]); in operator ()() 115 …work_out[i]=WidthPoint(norm_distances[i], widths[i], WidthPoint::TYPE_INTERPOLATE, WidthPoint::TYP… in operator ()() 163 g=widths[i]-widthpoint_interpolate(wp_prev, wp_next, norm_distances[i], false); in calculate_ek2() 221 norm_distances.clear(); in clear()
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H A D | wplistconverter.h | 57 std::vector<synfig::Real> norm_distances; variable
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/dports/science/py-scipy/scipy-1.7.1/scipy/interpolate/ |
H A D | interpolate.py | 2520 indices, norm_distances, out_of_bounds = self._find_indices(xi.T) 2523 norm_distances, 2527 norm_distances, 2534 def _evaluate_linear(self, indices, norm_distances, out_of_bounds): argument 2544 for ei, i, yi in zip(edge_indices, indices, norm_distances): 2549 def _evaluate_nearest(self, indices, norm_distances, out_of_bounds): argument 2551 for i, yi in zip(indices, norm_distances)] 2558 norm_distances = [] 2567 norm_distances.append((x - grid[i]) / 2572 return indices, norm_distances, out_of_bounds
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