- ScatterPlotItem disables render cache during export
- Fixes for SVG exporter - functions.isosurface() is a bazillion times faster (API change: return value format has changed)
This commit is contained in:
Luke Campagnola
parent
3de5719011
commit
ecca8855df
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@ -45,9 +45,9 @@ data = np.abs(np.fromfunction(psi, (50,50,100)))
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print("Generating isosurface..")
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verts = pg.isosurface(data, data.max()/4.)
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verts, faces = pg.isosurface(data, data.max()/4.)
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md = gl.MeshData(vertexes=verts)
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md = gl.MeshData(vertexes=verts, faces=faces)
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colors = np.ones((md.faceCount(), 4), dtype=float)
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colors[:,3] = 0.2
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@ -73,7 +73,8 @@ class Exporter(object):
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def getSourceRect(self):
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if isinstance(self.item, pg.GraphicsScene):
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return self.item.getViewWidget().viewRect()
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w = self.item.getViewWidget()
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return w.viewportTransform().inverted()[0].mapRect(w.rect())
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else:
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return self.item.sceneBoundingRect()
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@ -36,11 +36,14 @@ class SVGExporter(Exporter):
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return
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self.svg = QtSvg.QSvgGenerator()
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self.svg.setFileName(fileName)
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self.svg.setSize(QtCore.QSize(100,100))
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#self.svg.setResolution(600)
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dpi = QtGui.QDesktopWidget().physicalDpiX()
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## not really sure why this works, but it seems to be important:
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self.svg.setSize(QtCore.QSize(self.params['width']*dpi/90., self.params['height']*dpi/90.))
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self.svg.setResolution(dpi)
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#self.svg.setViewBox()
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targetRect = QtCore.QRect(0, 0, self.params['width'], self.params['height'])
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sourceRect = self.getSourceRect()
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painter = QtGui.QPainter(self.svg)
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try:
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self.setExportMode(True)
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783
functions.py
783
functions.py
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@ -1145,342 +1145,365 @@ def isocurve(data, level):
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return lines ## a list of pairs of points
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IsosurfaceDataCache = None
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def isosurface(data, level):
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"""
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Generate isosurface from volumetric data using marching cubes algorithm.
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See Paul Bourke, "Polygonising a Scalar Field"
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(http://local.wasp.uwa.edu.au/~pbourke/geometry/polygonise/)
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(http://paulbourke.net/geometry/polygonise/)
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*data* 3D numpy array of scalar values
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*level* The level at which to generate an isosurface
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Returns an array of vertex coordinates (N, 3, 3);
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This function is SLOW; plenty of room for optimization here.
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Returns an array of vertex coordinates (Nv, 3) and an array of
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per-face vertex indexes (Nf, 3)
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"""
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## For improvement, see:
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##
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## Efficient implementation of Marching Cubes' cases with topological guarantees.
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## Thomas Lewiner, Helio Lopes, Antonio Wilson Vieira and Geovan Tavares.
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## Journal of Graphics Tools 8(2): pp. 1-15 (december 2003)
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## Precompute lookup tables on the first run
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global IsosurfaceDataCache
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if IsosurfaceDataCache is None:
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## map from grid cell index to edge index.
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## grid cell index tells us which corners are below the isosurface,
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## edge index tells us which edges are cut by the isosurface.
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## (Data stolen from Bourk; see above.)
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edgeTable = np.array([
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0x0 , 0x109, 0x203, 0x30a, 0x406, 0x50f, 0x605, 0x70c,
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0x80c, 0x905, 0xa0f, 0xb06, 0xc0a, 0xd03, 0xe09, 0xf00,
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0x190, 0x99 , 0x393, 0x29a, 0x596, 0x49f, 0x795, 0x69c,
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0x99c, 0x895, 0xb9f, 0xa96, 0xd9a, 0xc93, 0xf99, 0xe90,
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0x230, 0x339, 0x33 , 0x13a, 0x636, 0x73f, 0x435, 0x53c,
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0xa3c, 0xb35, 0x83f, 0x936, 0xe3a, 0xf33, 0xc39, 0xd30,
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0x3a0, 0x2a9, 0x1a3, 0xaa , 0x7a6, 0x6af, 0x5a5, 0x4ac,
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0xbac, 0xaa5, 0x9af, 0x8a6, 0xfaa, 0xea3, 0xda9, 0xca0,
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0x460, 0x569, 0x663, 0x76a, 0x66 , 0x16f, 0x265, 0x36c,
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0xc6c, 0xd65, 0xe6f, 0xf66, 0x86a, 0x963, 0xa69, 0xb60,
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0x5f0, 0x4f9, 0x7f3, 0x6fa, 0x1f6, 0xff , 0x3f5, 0x2fc,
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0xdfc, 0xcf5, 0xfff, 0xef6, 0x9fa, 0x8f3, 0xbf9, 0xaf0,
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0x650, 0x759, 0x453, 0x55a, 0x256, 0x35f, 0x55 , 0x15c,
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0xe5c, 0xf55, 0xc5f, 0xd56, 0xa5a, 0xb53, 0x859, 0x950,
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0x7c0, 0x6c9, 0x5c3, 0x4ca, 0x3c6, 0x2cf, 0x1c5, 0xcc ,
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0xfcc, 0xec5, 0xdcf, 0xcc6, 0xbca, 0xac3, 0x9c9, 0x8c0,
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0x8c0, 0x9c9, 0xac3, 0xbca, 0xcc6, 0xdcf, 0xec5, 0xfcc,
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0xcc , 0x1c5, 0x2cf, 0x3c6, 0x4ca, 0x5c3, 0x6c9, 0x7c0,
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0x950, 0x859, 0xb53, 0xa5a, 0xd56, 0xc5f, 0xf55, 0xe5c,
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0x15c, 0x55 , 0x35f, 0x256, 0x55a, 0x453, 0x759, 0x650,
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0xaf0, 0xbf9, 0x8f3, 0x9fa, 0xef6, 0xfff, 0xcf5, 0xdfc,
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0x2fc, 0x3f5, 0xff , 0x1f6, 0x6fa, 0x7f3, 0x4f9, 0x5f0,
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0xb60, 0xa69, 0x963, 0x86a, 0xf66, 0xe6f, 0xd65, 0xc6c,
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0x36c, 0x265, 0x16f, 0x66 , 0x76a, 0x663, 0x569, 0x460,
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0xca0, 0xda9, 0xea3, 0xfaa, 0x8a6, 0x9af, 0xaa5, 0xbac,
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0x4ac, 0x5a5, 0x6af, 0x7a6, 0xaa , 0x1a3, 0x2a9, 0x3a0,
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0xd30, 0xc39, 0xf33, 0xe3a, 0x936, 0x83f, 0xb35, 0xa3c,
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0x53c, 0x435, 0x73f, 0x636, 0x13a, 0x33 , 0x339, 0x230,
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0xe90, 0xf99, 0xc93, 0xd9a, 0xa96, 0xb9f, 0x895, 0x99c,
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0x69c, 0x795, 0x49f, 0x596, 0x29a, 0x393, 0x99 , 0x190,
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0xf00, 0xe09, 0xd03, 0xc0a, 0xb06, 0xa0f, 0x905, 0x80c,
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0x70c, 0x605, 0x50f, 0x406, 0x30a, 0x203, 0x109, 0x0 ], dtype=np.uint16)
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## Table of triangles to use for filling each grid cell.
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## Each set of three integers tells us which three edges to
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## draw a triangle between.
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## (Data stolen from Bourk; see above.)
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triTable = [
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[],
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[0, 8, 3],
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[0, 1, 9],
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[1, 8, 3, 9, 8, 1],
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[1, 2, 10],
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[0, 8, 3, 1, 2, 10],
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[9, 2, 10, 0, 2, 9],
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[2, 8, 3, 2, 10, 8, 10, 9, 8],
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[3, 11, 2],
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[0, 11, 2, 8, 11, 0],
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[1, 9, 0, 2, 3, 11],
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[1, 11, 2, 1, 9, 11, 9, 8, 11],
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[3, 10, 1, 11, 10, 3],
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[0, 10, 1, 0, 8, 10, 8, 11, 10],
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[3, 9, 0, 3, 11, 9, 11, 10, 9],
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[9, 8, 10, 10, 8, 11],
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[4, 7, 8],
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[4, 3, 0, 7, 3, 4],
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[0, 1, 9, 8, 4, 7],
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[4, 1, 9, 4, 7, 1, 7, 3, 1],
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[1, 2, 10, 8, 4, 7],
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[3, 4, 7, 3, 0, 4, 1, 2, 10],
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[9, 2, 10, 9, 0, 2, 8, 4, 7],
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[2, 10, 9, 2, 9, 7, 2, 7, 3, 7, 9, 4],
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[8, 4, 7, 3, 11, 2],
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[11, 4, 7, 11, 2, 4, 2, 0, 4],
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[9, 0, 1, 8, 4, 7, 2, 3, 11],
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[4, 7, 11, 9, 4, 11, 9, 11, 2, 9, 2, 1],
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[3, 10, 1, 3, 11, 10, 7, 8, 4],
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[1, 11, 10, 1, 4, 11, 1, 0, 4, 7, 11, 4],
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[4, 7, 8, 9, 0, 11, 9, 11, 10, 11, 0, 3],
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[4, 7, 11, 4, 11, 9, 9, 11, 10],
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[9, 5, 4],
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[9, 5, 4, 0, 8, 3],
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[0, 5, 4, 1, 5, 0],
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[8, 5, 4, 8, 3, 5, 3, 1, 5],
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[1, 2, 10, 9, 5, 4],
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[3, 0, 8, 1, 2, 10, 4, 9, 5],
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[5, 2, 10, 5, 4, 2, 4, 0, 2],
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[2, 10, 5, 3, 2, 5, 3, 5, 4, 3, 4, 8],
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[9, 5, 4, 2, 3, 11],
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[0, 11, 2, 0, 8, 11, 4, 9, 5],
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[0, 5, 4, 0, 1, 5, 2, 3, 11],
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[2, 1, 5, 2, 5, 8, 2, 8, 11, 4, 8, 5],
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[10, 3, 11, 10, 1, 3, 9, 5, 4],
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[4, 9, 5, 0, 8, 1, 8, 10, 1, 8, 11, 10],
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[5, 4, 0, 5, 0, 11, 5, 11, 10, 11, 0, 3],
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[5, 4, 8, 5, 8, 10, 10, 8, 11],
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[9, 7, 8, 5, 7, 9],
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[9, 3, 0, 9, 5, 3, 5, 7, 3],
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[0, 7, 8, 0, 1, 7, 1, 5, 7],
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[1, 5, 3, 3, 5, 7],
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[9, 7, 8, 9, 5, 7, 10, 1, 2],
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[10, 1, 2, 9, 5, 0, 5, 3, 0, 5, 7, 3],
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[8, 0, 2, 8, 2, 5, 8, 5, 7, 10, 5, 2],
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[2, 10, 5, 2, 5, 3, 3, 5, 7],
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[7, 9, 5, 7, 8, 9, 3, 11, 2],
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[9, 5, 7, 9, 7, 2, 9, 2, 0, 2, 7, 11],
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[2, 3, 11, 0, 1, 8, 1, 7, 8, 1, 5, 7],
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[11, 2, 1, 11, 1, 7, 7, 1, 5],
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[9, 5, 8, 8, 5, 7, 10, 1, 3, 10, 3, 11],
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[5, 7, 0, 5, 0, 9, 7, 11, 0, 1, 0, 10, 11, 10, 0],
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[11, 10, 0, 11, 0, 3, 10, 5, 0, 8, 0, 7, 5, 7, 0],
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[11, 10, 5, 7, 11, 5],
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[10, 6, 5],
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[0, 8, 3, 5, 10, 6],
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[9, 0, 1, 5, 10, 6],
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[1, 8, 3, 1, 9, 8, 5, 10, 6],
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[1, 6, 5, 2, 6, 1],
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[1, 6, 5, 1, 2, 6, 3, 0, 8],
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[9, 6, 5, 9, 0, 6, 0, 2, 6],
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[5, 9, 8, 5, 8, 2, 5, 2, 6, 3, 2, 8],
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[2, 3, 11, 10, 6, 5],
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[11, 0, 8, 11, 2, 0, 10, 6, 5],
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[0, 1, 9, 2, 3, 11, 5, 10, 6],
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[5, 10, 6, 1, 9, 2, 9, 11, 2, 9, 8, 11],
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[6, 3, 11, 6, 5, 3, 5, 1, 3],
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[0, 8, 11, 0, 11, 5, 0, 5, 1, 5, 11, 6],
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[3, 11, 6, 0, 3, 6, 0, 6, 5, 0, 5, 9],
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[6, 5, 9, 6, 9, 11, 11, 9, 8],
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[5, 10, 6, 4, 7, 8],
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[4, 3, 0, 4, 7, 3, 6, 5, 10],
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[1, 9, 0, 5, 10, 6, 8, 4, 7],
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[10, 6, 5, 1, 9, 7, 1, 7, 3, 7, 9, 4],
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[6, 1, 2, 6, 5, 1, 4, 7, 8],
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[1, 2, 5, 5, 2, 6, 3, 0, 4, 3, 4, 7],
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[8, 4, 7, 9, 0, 5, 0, 6, 5, 0, 2, 6],
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[7, 3, 9, 7, 9, 4, 3, 2, 9, 5, 9, 6, 2, 6, 9],
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[3, 11, 2, 7, 8, 4, 10, 6, 5],
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[5, 10, 6, 4, 7, 2, 4, 2, 0, 2, 7, 11],
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[0, 1, 9, 4, 7, 8, 2, 3, 11, 5, 10, 6],
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[9, 2, 1, 9, 11, 2, 9, 4, 11, 7, 11, 4, 5, 10, 6],
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[8, 4, 7, 3, 11, 5, 3, 5, 1, 5, 11, 6],
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[5, 1, 11, 5, 11, 6, 1, 0, 11, 7, 11, 4, 0, 4, 11],
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[0, 5, 9, 0, 6, 5, 0, 3, 6, 11, 6, 3, 8, 4, 7],
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[6, 5, 9, 6, 9, 11, 4, 7, 9, 7, 11, 9],
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[10, 4, 9, 6, 4, 10],
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[4, 10, 6, 4, 9, 10, 0, 8, 3],
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[10, 0, 1, 10, 6, 0, 6, 4, 0],
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[8, 3, 1, 8, 1, 6, 8, 6, 4, 6, 1, 10],
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[1, 4, 9, 1, 2, 4, 2, 6, 4],
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[3, 0, 8, 1, 2, 9, 2, 4, 9, 2, 6, 4],
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[0, 2, 4, 4, 2, 6],
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[8, 3, 2, 8, 2, 4, 4, 2, 6],
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[10, 4, 9, 10, 6, 4, 11, 2, 3],
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[0, 8, 2, 2, 8, 11, 4, 9, 10, 4, 10, 6],
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[3, 11, 2, 0, 1, 6, 0, 6, 4, 6, 1, 10],
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[6, 4, 1, 6, 1, 10, 4, 8, 1, 2, 1, 11, 8, 11, 1],
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[9, 6, 4, 9, 3, 6, 9, 1, 3, 11, 6, 3],
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[8, 11, 1, 8, 1, 0, 11, 6, 1, 9, 1, 4, 6, 4, 1],
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[3, 11, 6, 3, 6, 0, 0, 6, 4],
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[6, 4, 8, 11, 6, 8],
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[7, 10, 6, 7, 8, 10, 8, 9, 10],
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[0, 7, 3, 0, 10, 7, 0, 9, 10, 6, 7, 10],
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[10, 6, 7, 1, 10, 7, 1, 7, 8, 1, 8, 0],
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[10, 6, 7, 10, 7, 1, 1, 7, 3],
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[1, 2, 6, 1, 6, 8, 1, 8, 9, 8, 6, 7],
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[2, 6, 9, 2, 9, 1, 6, 7, 9, 0, 9, 3, 7, 3, 9],
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[7, 8, 0, 7, 0, 6, 6, 0, 2],
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[7, 3, 2, 6, 7, 2],
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[2, 3, 11, 10, 6, 8, 10, 8, 9, 8, 6, 7],
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[2, 0, 7, 2, 7, 11, 0, 9, 7, 6, 7, 10, 9, 10, 7],
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[1, 8, 0, 1, 7, 8, 1, 10, 7, 6, 7, 10, 2, 3, 11],
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[11, 2, 1, 11, 1, 7, 10, 6, 1, 6, 7, 1],
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[8, 9, 6, 8, 6, 7, 9, 1, 6, 11, 6, 3, 1, 3, 6],
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[0, 9, 1, 11, 6, 7],
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[7, 8, 0, 7, 0, 6, 3, 11, 0, 11, 6, 0],
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[7, 11, 6],
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[7, 6, 11],
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[3, 0, 8, 11, 7, 6],
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[0, 1, 9, 11, 7, 6],
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[8, 1, 9, 8, 3, 1, 11, 7, 6],
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[10, 1, 2, 6, 11, 7],
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[1, 2, 10, 3, 0, 8, 6, 11, 7],
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[2, 9, 0, 2, 10, 9, 6, 11, 7],
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[6, 11, 7, 2, 10, 3, 10, 8, 3, 10, 9, 8],
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[7, 2, 3, 6, 2, 7],
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[7, 0, 8, 7, 6, 0, 6, 2, 0],
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[2, 7, 6, 2, 3, 7, 0, 1, 9],
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[1, 6, 2, 1, 8, 6, 1, 9, 8, 8, 7, 6],
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[10, 7, 6, 10, 1, 7, 1, 3, 7],
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[10, 7, 6, 1, 7, 10, 1, 8, 7, 1, 0, 8],
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[0, 3, 7, 0, 7, 10, 0, 10, 9, 6, 10, 7],
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[7, 6, 10, 7, 10, 8, 8, 10, 9],
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[6, 8, 4, 11, 8, 6],
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[3, 6, 11, 3, 0, 6, 0, 4, 6],
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[8, 6, 11, 8, 4, 6, 9, 0, 1],
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[9, 4, 6, 9, 6, 3, 9, 3, 1, 11, 3, 6],
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[6, 8, 4, 6, 11, 8, 2, 10, 1],
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[1, 2, 10, 3, 0, 11, 0, 6, 11, 0, 4, 6],
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[4, 11, 8, 4, 6, 11, 0, 2, 9, 2, 10, 9],
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[10, 9, 3, 10, 3, 2, 9, 4, 3, 11, 3, 6, 4, 6, 3],
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[8, 2, 3, 8, 4, 2, 4, 6, 2],
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[0, 4, 2, 4, 6, 2],
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[1, 9, 0, 2, 3, 4, 2, 4, 6, 4, 3, 8],
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[1, 9, 4, 1, 4, 2, 2, 4, 6],
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[8, 1, 3, 8, 6, 1, 8, 4, 6, 6, 10, 1],
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[10, 1, 0, 10, 0, 6, 6, 0, 4],
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[4, 6, 3, 4, 3, 8, 6, 10, 3, 0, 3, 9, 10, 9, 3],
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[10, 9, 4, 6, 10, 4],
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[4, 9, 5, 7, 6, 11],
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[0, 8, 3, 4, 9, 5, 11, 7, 6],
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[5, 0, 1, 5, 4, 0, 7, 6, 11],
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[11, 7, 6, 8, 3, 4, 3, 5, 4, 3, 1, 5],
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[9, 5, 4, 10, 1, 2, 7, 6, 11],
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[6, 11, 7, 1, 2, 10, 0, 8, 3, 4, 9, 5],
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[7, 6, 11, 5, 4, 10, 4, 2, 10, 4, 0, 2],
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[3, 4, 8, 3, 5, 4, 3, 2, 5, 10, 5, 2, 11, 7, 6],
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[7, 2, 3, 7, 6, 2, 5, 4, 9],
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[9, 5, 4, 0, 8, 6, 0, 6, 2, 6, 8, 7],
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[3, 6, 2, 3, 7, 6, 1, 5, 0, 5, 4, 0],
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[6, 2, 8, 6, 8, 7, 2, 1, 8, 4, 8, 5, 1, 5, 8],
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[9, 5, 4, 10, 1, 6, 1, 7, 6, 1, 3, 7],
|
||||
[1, 6, 10, 1, 7, 6, 1, 0, 7, 8, 7, 0, 9, 5, 4],
|
||||
[4, 0, 10, 4, 10, 5, 0, 3, 10, 6, 10, 7, 3, 7, 10],
|
||||
[7, 6, 10, 7, 10, 8, 5, 4, 10, 4, 8, 10],
|
||||
[6, 9, 5, 6, 11, 9, 11, 8, 9],
|
||||
[3, 6, 11, 0, 6, 3, 0, 5, 6, 0, 9, 5],
|
||||
[0, 11, 8, 0, 5, 11, 0, 1, 5, 5, 6, 11],
|
||||
[6, 11, 3, 6, 3, 5, 5, 3, 1],
|
||||
[1, 2, 10, 9, 5, 11, 9, 11, 8, 11, 5, 6],
|
||||
[0, 11, 3, 0, 6, 11, 0, 9, 6, 5, 6, 9, 1, 2, 10],
|
||||
[11, 8, 5, 11, 5, 6, 8, 0, 5, 10, 5, 2, 0, 2, 5],
|
||||
[6, 11, 3, 6, 3, 5, 2, 10, 3, 10, 5, 3],
|
||||
[5, 8, 9, 5, 2, 8, 5, 6, 2, 3, 8, 2],
|
||||
[9, 5, 6, 9, 6, 0, 0, 6, 2],
|
||||
[1, 5, 8, 1, 8, 0, 5, 6, 8, 3, 8, 2, 6, 2, 8],
|
||||
[1, 5, 6, 2, 1, 6],
|
||||
[1, 3, 6, 1, 6, 10, 3, 8, 6, 5, 6, 9, 8, 9, 6],
|
||||
[10, 1, 0, 10, 0, 6, 9, 5, 0, 5, 6, 0],
|
||||
[0, 3, 8, 5, 6, 10],
|
||||
[10, 5, 6],
|
||||
[11, 5, 10, 7, 5, 11],
|
||||
[11, 5, 10, 11, 7, 5, 8, 3, 0],
|
||||
[5, 11, 7, 5, 10, 11, 1, 9, 0],
|
||||
[10, 7, 5, 10, 11, 7, 9, 8, 1, 8, 3, 1],
|
||||
[11, 1, 2, 11, 7, 1, 7, 5, 1],
|
||||
[0, 8, 3, 1, 2, 7, 1, 7, 5, 7, 2, 11],
|
||||
[9, 7, 5, 9, 2, 7, 9, 0, 2, 2, 11, 7],
|
||||
[7, 5, 2, 7, 2, 11, 5, 9, 2, 3, 2, 8, 9, 8, 2],
|
||||
[2, 5, 10, 2, 3, 5, 3, 7, 5],
|
||||
[8, 2, 0, 8, 5, 2, 8, 7, 5, 10, 2, 5],
|
||||
[9, 0, 1, 5, 10, 3, 5, 3, 7, 3, 10, 2],
|
||||
[9, 8, 2, 9, 2, 1, 8, 7, 2, 10, 2, 5, 7, 5, 2],
|
||||
[1, 3, 5, 3, 7, 5],
|
||||
[0, 8, 7, 0, 7, 1, 1, 7, 5],
|
||||
[9, 0, 3, 9, 3, 5, 5, 3, 7],
|
||||
[9, 8, 7, 5, 9, 7],
|
||||
[5, 8, 4, 5, 10, 8, 10, 11, 8],
|
||||
[5, 0, 4, 5, 11, 0, 5, 10, 11, 11, 3, 0],
|
||||
[0, 1, 9, 8, 4, 10, 8, 10, 11, 10, 4, 5],
|
||||
[10, 11, 4, 10, 4, 5, 11, 3, 4, 9, 4, 1, 3, 1, 4],
|
||||
[2, 5, 1, 2, 8, 5, 2, 11, 8, 4, 5, 8],
|
||||
[0, 4, 11, 0, 11, 3, 4, 5, 11, 2, 11, 1, 5, 1, 11],
|
||||
[0, 2, 5, 0, 5, 9, 2, 11, 5, 4, 5, 8, 11, 8, 5],
|
||||
[9, 4, 5, 2, 11, 3],
|
||||
[2, 5, 10, 3, 5, 2, 3, 4, 5, 3, 8, 4],
|
||||
[5, 10, 2, 5, 2, 4, 4, 2, 0],
|
||||
[3, 10, 2, 3, 5, 10, 3, 8, 5, 4, 5, 8, 0, 1, 9],
|
||||
[5, 10, 2, 5, 2, 4, 1, 9, 2, 9, 4, 2],
|
||||
[8, 4, 5, 8, 5, 3, 3, 5, 1],
|
||||
[0, 4, 5, 1, 0, 5],
|
||||
[8, 4, 5, 8, 5, 3, 9, 0, 5, 0, 3, 5],
|
||||
[9, 4, 5],
|
||||
[4, 11, 7, 4, 9, 11, 9, 10, 11],
|
||||
[0, 8, 3, 4, 9, 7, 9, 11, 7, 9, 10, 11],
|
||||
[1, 10, 11, 1, 11, 4, 1, 4, 0, 7, 4, 11],
|
||||
[3, 1, 4, 3, 4, 8, 1, 10, 4, 7, 4, 11, 10, 11, 4],
|
||||
[4, 11, 7, 9, 11, 4, 9, 2, 11, 9, 1, 2],
|
||||
[9, 7, 4, 9, 11, 7, 9, 1, 11, 2, 11, 1, 0, 8, 3],
|
||||
[11, 7, 4, 11, 4, 2, 2, 4, 0],
|
||||
[11, 7, 4, 11, 4, 2, 8, 3, 4, 3, 2, 4],
|
||||
[2, 9, 10, 2, 7, 9, 2, 3, 7, 7, 4, 9],
|
||||
[9, 10, 7, 9, 7, 4, 10, 2, 7, 8, 7, 0, 2, 0, 7],
|
||||
[3, 7, 10, 3, 10, 2, 7, 4, 10, 1, 10, 0, 4, 0, 10],
|
||||
[1, 10, 2, 8, 7, 4],
|
||||
[4, 9, 1, 4, 1, 7, 7, 1, 3],
|
||||
[4, 9, 1, 4, 1, 7, 0, 8, 1, 8, 7, 1],
|
||||
[4, 0, 3, 7, 4, 3],
|
||||
[4, 8, 7],
|
||||
[9, 10, 8, 10, 11, 8],
|
||||
[3, 0, 9, 3, 9, 11, 11, 9, 10],
|
||||
[0, 1, 10, 0, 10, 8, 8, 10, 11],
|
||||
[3, 1, 10, 11, 3, 10],
|
||||
[1, 2, 11, 1, 11, 9, 9, 11, 8],
|
||||
[3, 0, 9, 3, 9, 11, 1, 2, 9, 2, 11, 9],
|
||||
[0, 2, 11, 8, 0, 11],
|
||||
[3, 2, 11],
|
||||
[2, 3, 8, 2, 8, 10, 10, 8, 9],
|
||||
[9, 10, 2, 0, 9, 2],
|
||||
[2, 3, 8, 2, 8, 10, 0, 1, 8, 1, 10, 8],
|
||||
[1, 10, 2],
|
||||
[1, 3, 8, 9, 1, 8],
|
||||
[0, 9, 1],
|
||||
[0, 3, 8],
|
||||
[]
|
||||
]
|
||||
edgeShifts = np.array([ ## maps edge ID (0-11) to (x,y,z) cell offset and edge ID (0-2)
|
||||
[0, 0, 0, 0],
|
||||
[1, 0, 0, 1],
|
||||
[0, 1, 0, 0],
|
||||
[0, 0, 0, 1],
|
||||
[0, 0, 1, 0],
|
||||
[1, 0, 1, 1],
|
||||
[0, 1, 1, 0],
|
||||
[0, 0, 1, 1],
|
||||
[0, 0, 0, 2],
|
||||
[1, 0, 0, 2],
|
||||
[1, 1, 0, 2],
|
||||
[0, 1, 0, 2],
|
||||
#[9, 9, 9, 9] ## fake
|
||||
], dtype=np.ubyte)
|
||||
nTableFaces = np.array([len(f)/3 for f in triTable], dtype=np.ubyte)
|
||||
faceShiftTables = [None]
|
||||
for i in range(1,6):
|
||||
## compute lookup table of index: vertexes mapping
|
||||
faceTableI = np.zeros((len(triTable), i*3), dtype=np.ubyte)
|
||||
faceTableInds = np.argwhere(nTableFaces == i)
|
||||
faceTableI[faceTableInds[:,0]] = np.array([triTable[j] for j in faceTableInds])
|
||||
faceTableI = faceTableI.reshape((len(triTable), i, 3))
|
||||
faceShiftTables.append(edgeShifts[faceTableI])
|
||||
|
||||
## Let's try something different:
|
||||
#faceTable = np.empty((256, 5, 3, 4), dtype=np.ubyte) # (grid cell index, faces, vertexes, edge lookup)
|
||||
#for i,f in enumerate(triTable):
|
||||
#f = np.array(f + [12] * (15-len(f))).reshape(5,3)
|
||||
#faceTable[i] = edgeShifts[f]
|
||||
|
||||
|
||||
IsosurfaceDataCache = (faceShiftTables, edgeShifts, edgeTable, nTableFaces)
|
||||
else:
|
||||
faceShiftTables, edgeShifts, edgeTable, nTableFaces = IsosurfaceDataCache
|
||||
|
||||
## map from grid cell index to edge index.
|
||||
## grid cell index tells us which corners are below the isosurface,
|
||||
## edge index tells us which edges are cut by the isosurface.
|
||||
## (Data stolen from Bourk; see above.)
|
||||
edgeTable = [
|
||||
0x0 , 0x109, 0x203, 0x30a, 0x406, 0x50f, 0x605, 0x70c,
|
||||
0x80c, 0x905, 0xa0f, 0xb06, 0xc0a, 0xd03, 0xe09, 0xf00,
|
||||
0x190, 0x99 , 0x393, 0x29a, 0x596, 0x49f, 0x795, 0x69c,
|
||||
0x99c, 0x895, 0xb9f, 0xa96, 0xd9a, 0xc93, 0xf99, 0xe90,
|
||||
0x230, 0x339, 0x33 , 0x13a, 0x636, 0x73f, 0x435, 0x53c,
|
||||
0xa3c, 0xb35, 0x83f, 0x936, 0xe3a, 0xf33, 0xc39, 0xd30,
|
||||
0x3a0, 0x2a9, 0x1a3, 0xaa , 0x7a6, 0x6af, 0x5a5, 0x4ac,
|
||||
0xbac, 0xaa5, 0x9af, 0x8a6, 0xfaa, 0xea3, 0xda9, 0xca0,
|
||||
0x460, 0x569, 0x663, 0x76a, 0x66 , 0x16f, 0x265, 0x36c,
|
||||
0xc6c, 0xd65, 0xe6f, 0xf66, 0x86a, 0x963, 0xa69, 0xb60,
|
||||
0x5f0, 0x4f9, 0x7f3, 0x6fa, 0x1f6, 0xff , 0x3f5, 0x2fc,
|
||||
0xdfc, 0xcf5, 0xfff, 0xef6, 0x9fa, 0x8f3, 0xbf9, 0xaf0,
|
||||
0x650, 0x759, 0x453, 0x55a, 0x256, 0x35f, 0x55 , 0x15c,
|
||||
0xe5c, 0xf55, 0xc5f, 0xd56, 0xa5a, 0xb53, 0x859, 0x950,
|
||||
0x7c0, 0x6c9, 0x5c3, 0x4ca, 0x3c6, 0x2cf, 0x1c5, 0xcc ,
|
||||
0xfcc, 0xec5, 0xdcf, 0xcc6, 0xbca, 0xac3, 0x9c9, 0x8c0,
|
||||
0x8c0, 0x9c9, 0xac3, 0xbca, 0xcc6, 0xdcf, 0xec5, 0xfcc,
|
||||
0xcc , 0x1c5, 0x2cf, 0x3c6, 0x4ca, 0x5c3, 0x6c9, 0x7c0,
|
||||
0x950, 0x859, 0xb53, 0xa5a, 0xd56, 0xc5f, 0xf55, 0xe5c,
|
||||
0x15c, 0x55 , 0x35f, 0x256, 0x55a, 0x453, 0x759, 0x650,
|
||||
0xaf0, 0xbf9, 0x8f3, 0x9fa, 0xef6, 0xfff, 0xcf5, 0xdfc,
|
||||
0x2fc, 0x3f5, 0xff , 0x1f6, 0x6fa, 0x7f3, 0x4f9, 0x5f0,
|
||||
0xb60, 0xa69, 0x963, 0x86a, 0xf66, 0xe6f, 0xd65, 0xc6c,
|
||||
0x36c, 0x265, 0x16f, 0x66 , 0x76a, 0x663, 0x569, 0x460,
|
||||
0xca0, 0xda9, 0xea3, 0xfaa, 0x8a6, 0x9af, 0xaa5, 0xbac,
|
||||
0x4ac, 0x5a5, 0x6af, 0x7a6, 0xaa , 0x1a3, 0x2a9, 0x3a0,
|
||||
0xd30, 0xc39, 0xf33, 0xe3a, 0x936, 0x83f, 0xb35, 0xa3c,
|
||||
0x53c, 0x435, 0x73f, 0x636, 0x13a, 0x33 , 0x339, 0x230,
|
||||
0xe90, 0xf99, 0xc93, 0xd9a, 0xa96, 0xb9f, 0x895, 0x99c,
|
||||
0x69c, 0x795, 0x49f, 0x596, 0x29a, 0x393, 0x99 , 0x190,
|
||||
0xf00, 0xe09, 0xd03, 0xc0a, 0xb06, 0xa0f, 0x905, 0x80c,
|
||||
0x70c, 0x605, 0x50f, 0x406, 0x30a, 0x203, 0x109, 0x0 ]
|
||||
|
||||
## Table of triangles to use for filling each grid cell.
|
||||
## Each set of three integers tells us which three edges to
|
||||
## draw a triangle between.
|
||||
## (Data stolen from Bourk; see above.)
|
||||
triTable = [
|
||||
[],
|
||||
[0, 8, 3],
|
||||
[0, 1, 9],
|
||||
[1, 8, 3, 9, 8, 1],
|
||||
[1, 2, 10],
|
||||
[0, 8, 3, 1, 2, 10],
|
||||
[9, 2, 10, 0, 2, 9],
|
||||
[2, 8, 3, 2, 10, 8, 10, 9, 8],
|
||||
[3, 11, 2],
|
||||
[0, 11, 2, 8, 11, 0],
|
||||
[1, 9, 0, 2, 3, 11],
|
||||
[1, 11, 2, 1, 9, 11, 9, 8, 11],
|
||||
[3, 10, 1, 11, 10, 3],
|
||||
[0, 10, 1, 0, 8, 10, 8, 11, 10],
|
||||
[3, 9, 0, 3, 11, 9, 11, 10, 9],
|
||||
[9, 8, 10, 10, 8, 11],
|
||||
[4, 7, 8],
|
||||
[4, 3, 0, 7, 3, 4],
|
||||
[0, 1, 9, 8, 4, 7],
|
||||
[4, 1, 9, 4, 7, 1, 7, 3, 1],
|
||||
[1, 2, 10, 8, 4, 7],
|
||||
[3, 4, 7, 3, 0, 4, 1, 2, 10],
|
||||
[9, 2, 10, 9, 0, 2, 8, 4, 7],
|
||||
[2, 10, 9, 2, 9, 7, 2, 7, 3, 7, 9, 4],
|
||||
[8, 4, 7, 3, 11, 2],
|
||||
[11, 4, 7, 11, 2, 4, 2, 0, 4],
|
||||
[9, 0, 1, 8, 4, 7, 2, 3, 11],
|
||||
[4, 7, 11, 9, 4, 11, 9, 11, 2, 9, 2, 1],
|
||||
[3, 10, 1, 3, 11, 10, 7, 8, 4],
|
||||
[1, 11, 10, 1, 4, 11, 1, 0, 4, 7, 11, 4],
|
||||
[4, 7, 8, 9, 0, 11, 9, 11, 10, 11, 0, 3],
|
||||
[4, 7, 11, 4, 11, 9, 9, 11, 10],
|
||||
[9, 5, 4],
|
||||
[9, 5, 4, 0, 8, 3],
|
||||
[0, 5, 4, 1, 5, 0],
|
||||
[8, 5, 4, 8, 3, 5, 3, 1, 5],
|
||||
[1, 2, 10, 9, 5, 4],
|
||||
[3, 0, 8, 1, 2, 10, 4, 9, 5],
|
||||
[5, 2, 10, 5, 4, 2, 4, 0, 2],
|
||||
[2, 10, 5, 3, 2, 5, 3, 5, 4, 3, 4, 8],
|
||||
[9, 5, 4, 2, 3, 11],
|
||||
[0, 11, 2, 0, 8, 11, 4, 9, 5],
|
||||
[0, 5, 4, 0, 1, 5, 2, 3, 11],
|
||||
[2, 1, 5, 2, 5, 8, 2, 8, 11, 4, 8, 5],
|
||||
[10, 3, 11, 10, 1, 3, 9, 5, 4],
|
||||
[4, 9, 5, 0, 8, 1, 8, 10, 1, 8, 11, 10],
|
||||
[5, 4, 0, 5, 0, 11, 5, 11, 10, 11, 0, 3],
|
||||
[5, 4, 8, 5, 8, 10, 10, 8, 11],
|
||||
[9, 7, 8, 5, 7, 9],
|
||||
[9, 3, 0, 9, 5, 3, 5, 7, 3],
|
||||
[0, 7, 8, 0, 1, 7, 1, 5, 7],
|
||||
[1, 5, 3, 3, 5, 7],
|
||||
[9, 7, 8, 9, 5, 7, 10, 1, 2],
|
||||
[10, 1, 2, 9, 5, 0, 5, 3, 0, 5, 7, 3],
|
||||
[8, 0, 2, 8, 2, 5, 8, 5, 7, 10, 5, 2],
|
||||
[2, 10, 5, 2, 5, 3, 3, 5, 7],
|
||||
[7, 9, 5, 7, 8, 9, 3, 11, 2],
|
||||
[9, 5, 7, 9, 7, 2, 9, 2, 0, 2, 7, 11],
|
||||
[2, 3, 11, 0, 1, 8, 1, 7, 8, 1, 5, 7],
|
||||
[11, 2, 1, 11, 1, 7, 7, 1, 5],
|
||||
[9, 5, 8, 8, 5, 7, 10, 1, 3, 10, 3, 11],
|
||||
[5, 7, 0, 5, 0, 9, 7, 11, 0, 1, 0, 10, 11, 10, 0],
|
||||
[11, 10, 0, 11, 0, 3, 10, 5, 0, 8, 0, 7, 5, 7, 0],
|
||||
[11, 10, 5, 7, 11, 5],
|
||||
[10, 6, 5],
|
||||
[0, 8, 3, 5, 10, 6],
|
||||
[9, 0, 1, 5, 10, 6],
|
||||
[1, 8, 3, 1, 9, 8, 5, 10, 6],
|
||||
[1, 6, 5, 2, 6, 1],
|
||||
[1, 6, 5, 1, 2, 6, 3, 0, 8],
|
||||
[9, 6, 5, 9, 0, 6, 0, 2, 6],
|
||||
[5, 9, 8, 5, 8, 2, 5, 2, 6, 3, 2, 8],
|
||||
[2, 3, 11, 10, 6, 5],
|
||||
[11, 0, 8, 11, 2, 0, 10, 6, 5],
|
||||
[0, 1, 9, 2, 3, 11, 5, 10, 6],
|
||||
[5, 10, 6, 1, 9, 2, 9, 11, 2, 9, 8, 11],
|
||||
[6, 3, 11, 6, 5, 3, 5, 1, 3],
|
||||
[0, 8, 11, 0, 11, 5, 0, 5, 1, 5, 11, 6],
|
||||
[3, 11, 6, 0, 3, 6, 0, 6, 5, 0, 5, 9],
|
||||
[6, 5, 9, 6, 9, 11, 11, 9, 8],
|
||||
[5, 10, 6, 4, 7, 8],
|
||||
[4, 3, 0, 4, 7, 3, 6, 5, 10],
|
||||
[1, 9, 0, 5, 10, 6, 8, 4, 7],
|
||||
[10, 6, 5, 1, 9, 7, 1, 7, 3, 7, 9, 4],
|
||||
[6, 1, 2, 6, 5, 1, 4, 7, 8],
|
||||
[1, 2, 5, 5, 2, 6, 3, 0, 4, 3, 4, 7],
|
||||
[8, 4, 7, 9, 0, 5, 0, 6, 5, 0, 2, 6],
|
||||
[7, 3, 9, 7, 9, 4, 3, 2, 9, 5, 9, 6, 2, 6, 9],
|
||||
[3, 11, 2, 7, 8, 4, 10, 6, 5],
|
||||
[5, 10, 6, 4, 7, 2, 4, 2, 0, 2, 7, 11],
|
||||
[0, 1, 9, 4, 7, 8, 2, 3, 11, 5, 10, 6],
|
||||
[9, 2, 1, 9, 11, 2, 9, 4, 11, 7, 11, 4, 5, 10, 6],
|
||||
[8, 4, 7, 3, 11, 5, 3, 5, 1, 5, 11, 6],
|
||||
[5, 1, 11, 5, 11, 6, 1, 0, 11, 7, 11, 4, 0, 4, 11],
|
||||
[0, 5, 9, 0, 6, 5, 0, 3, 6, 11, 6, 3, 8, 4, 7],
|
||||
[6, 5, 9, 6, 9, 11, 4, 7, 9, 7, 11, 9],
|
||||
[10, 4, 9, 6, 4, 10],
|
||||
[4, 10, 6, 4, 9, 10, 0, 8, 3],
|
||||
[10, 0, 1, 10, 6, 0, 6, 4, 0],
|
||||
[8, 3, 1, 8, 1, 6, 8, 6, 4, 6, 1, 10],
|
||||
[1, 4, 9, 1, 2, 4, 2, 6, 4],
|
||||
[3, 0, 8, 1, 2, 9, 2, 4, 9, 2, 6, 4],
|
||||
[0, 2, 4, 4, 2, 6],
|
||||
[8, 3, 2, 8, 2, 4, 4, 2, 6],
|
||||
[10, 4, 9, 10, 6, 4, 11, 2, 3],
|
||||
[0, 8, 2, 2, 8, 11, 4, 9, 10, 4, 10, 6],
|
||||
[3, 11, 2, 0, 1, 6, 0, 6, 4, 6, 1, 10],
|
||||
[6, 4, 1, 6, 1, 10, 4, 8, 1, 2, 1, 11, 8, 11, 1],
|
||||
[9, 6, 4, 9, 3, 6, 9, 1, 3, 11, 6, 3],
|
||||
[8, 11, 1, 8, 1, 0, 11, 6, 1, 9, 1, 4, 6, 4, 1],
|
||||
[3, 11, 6, 3, 6, 0, 0, 6, 4],
|
||||
[6, 4, 8, 11, 6, 8],
|
||||
[7, 10, 6, 7, 8, 10, 8, 9, 10],
|
||||
[0, 7, 3, 0, 10, 7, 0, 9, 10, 6, 7, 10],
|
||||
[10, 6, 7, 1, 10, 7, 1, 7, 8, 1, 8, 0],
|
||||
[10, 6, 7, 10, 7, 1, 1, 7, 3],
|
||||
[1, 2, 6, 1, 6, 8, 1, 8, 9, 8, 6, 7],
|
||||
[2, 6, 9, 2, 9, 1, 6, 7, 9, 0, 9, 3, 7, 3, 9],
|
||||
[7, 8, 0, 7, 0, 6, 6, 0, 2],
|
||||
[7, 3, 2, 6, 7, 2],
|
||||
[2, 3, 11, 10, 6, 8, 10, 8, 9, 8, 6, 7],
|
||||
[2, 0, 7, 2, 7, 11, 0, 9, 7, 6, 7, 10, 9, 10, 7],
|
||||
[1, 8, 0, 1, 7, 8, 1, 10, 7, 6, 7, 10, 2, 3, 11],
|
||||
[11, 2, 1, 11, 1, 7, 10, 6, 1, 6, 7, 1],
|
||||
[8, 9, 6, 8, 6, 7, 9, 1, 6, 11, 6, 3, 1, 3, 6],
|
||||
[0, 9, 1, 11, 6, 7],
|
||||
[7, 8, 0, 7, 0, 6, 3, 11, 0, 11, 6, 0],
|
||||
[7, 11, 6],
|
||||
[7, 6, 11],
|
||||
[3, 0, 8, 11, 7, 6],
|
||||
[0, 1, 9, 11, 7, 6],
|
||||
[8, 1, 9, 8, 3, 1, 11, 7, 6],
|
||||
[10, 1, 2, 6, 11, 7],
|
||||
[1, 2, 10, 3, 0, 8, 6, 11, 7],
|
||||
[2, 9, 0, 2, 10, 9, 6, 11, 7],
|
||||
[6, 11, 7, 2, 10, 3, 10, 8, 3, 10, 9, 8],
|
||||
[7, 2, 3, 6, 2, 7],
|
||||
[7, 0, 8, 7, 6, 0, 6, 2, 0],
|
||||
[2, 7, 6, 2, 3, 7, 0, 1, 9],
|
||||
[1, 6, 2, 1, 8, 6, 1, 9, 8, 8, 7, 6],
|
||||
[10, 7, 6, 10, 1, 7, 1, 3, 7],
|
||||
[10, 7, 6, 1, 7, 10, 1, 8, 7, 1, 0, 8],
|
||||
[0, 3, 7, 0, 7, 10, 0, 10, 9, 6, 10, 7],
|
||||
[7, 6, 10, 7, 10, 8, 8, 10, 9],
|
||||
[6, 8, 4, 11, 8, 6],
|
||||
[3, 6, 11, 3, 0, 6, 0, 4, 6],
|
||||
[8, 6, 11, 8, 4, 6, 9, 0, 1],
|
||||
[9, 4, 6, 9, 6, 3, 9, 3, 1, 11, 3, 6],
|
||||
[6, 8, 4, 6, 11, 8, 2, 10, 1],
|
||||
[1, 2, 10, 3, 0, 11, 0, 6, 11, 0, 4, 6],
|
||||
[4, 11, 8, 4, 6, 11, 0, 2, 9, 2, 10, 9],
|
||||
[10, 9, 3, 10, 3, 2, 9, 4, 3, 11, 3, 6, 4, 6, 3],
|
||||
[8, 2, 3, 8, 4, 2, 4, 6, 2],
|
||||
[0, 4, 2, 4, 6, 2],
|
||||
[1, 9, 0, 2, 3, 4, 2, 4, 6, 4, 3, 8],
|
||||
[1, 9, 4, 1, 4, 2, 2, 4, 6],
|
||||
[8, 1, 3, 8, 6, 1, 8, 4, 6, 6, 10, 1],
|
||||
[10, 1, 0, 10, 0, 6, 6, 0, 4],
|
||||
[4, 6, 3, 4, 3, 8, 6, 10, 3, 0, 3, 9, 10, 9, 3],
|
||||
[10, 9, 4, 6, 10, 4],
|
||||
[4, 9, 5, 7, 6, 11],
|
||||
[0, 8, 3, 4, 9, 5, 11, 7, 6],
|
||||
[5, 0, 1, 5, 4, 0, 7, 6, 11],
|
||||
[11, 7, 6, 8, 3, 4, 3, 5, 4, 3, 1, 5],
|
||||
[9, 5, 4, 10, 1, 2, 7, 6, 11],
|
||||
[6, 11, 7, 1, 2, 10, 0, 8, 3, 4, 9, 5],
|
||||
[7, 6, 11, 5, 4, 10, 4, 2, 10, 4, 0, 2],
|
||||
[3, 4, 8, 3, 5, 4, 3, 2, 5, 10, 5, 2, 11, 7, 6],
|
||||
[7, 2, 3, 7, 6, 2, 5, 4, 9],
|
||||
[9, 5, 4, 0, 8, 6, 0, 6, 2, 6, 8, 7],
|
||||
[3, 6, 2, 3, 7, 6, 1, 5, 0, 5, 4, 0],
|
||||
[6, 2, 8, 6, 8, 7, 2, 1, 8, 4, 8, 5, 1, 5, 8],
|
||||
[9, 5, 4, 10, 1, 6, 1, 7, 6, 1, 3, 7],
|
||||
[1, 6, 10, 1, 7, 6, 1, 0, 7, 8, 7, 0, 9, 5, 4],
|
||||
[4, 0, 10, 4, 10, 5, 0, 3, 10, 6, 10, 7, 3, 7, 10],
|
||||
[7, 6, 10, 7, 10, 8, 5, 4, 10, 4, 8, 10],
|
||||
[6, 9, 5, 6, 11, 9, 11, 8, 9],
|
||||
[3, 6, 11, 0, 6, 3, 0, 5, 6, 0, 9, 5],
|
||||
[0, 11, 8, 0, 5, 11, 0, 1, 5, 5, 6, 11],
|
||||
[6, 11, 3, 6, 3, 5, 5, 3, 1],
|
||||
[1, 2, 10, 9, 5, 11, 9, 11, 8, 11, 5, 6],
|
||||
[0, 11, 3, 0, 6, 11, 0, 9, 6, 5, 6, 9, 1, 2, 10],
|
||||
[11, 8, 5, 11, 5, 6, 8, 0, 5, 10, 5, 2, 0, 2, 5],
|
||||
[6, 11, 3, 6, 3, 5, 2, 10, 3, 10, 5, 3],
|
||||
[5, 8, 9, 5, 2, 8, 5, 6, 2, 3, 8, 2],
|
||||
[9, 5, 6, 9, 6, 0, 0, 6, 2],
|
||||
[1, 5, 8, 1, 8, 0, 5, 6, 8, 3, 8, 2, 6, 2, 8],
|
||||
[1, 5, 6, 2, 1, 6],
|
||||
[1, 3, 6, 1, 6, 10, 3, 8, 6, 5, 6, 9, 8, 9, 6],
|
||||
[10, 1, 0, 10, 0, 6, 9, 5, 0, 5, 6, 0],
|
||||
[0, 3, 8, 5, 6, 10],
|
||||
[10, 5, 6],
|
||||
[11, 5, 10, 7, 5, 11],
|
||||
[11, 5, 10, 11, 7, 5, 8, 3, 0],
|
||||
[5, 11, 7, 5, 10, 11, 1, 9, 0],
|
||||
[10, 7, 5, 10, 11, 7, 9, 8, 1, 8, 3, 1],
|
||||
[11, 1, 2, 11, 7, 1, 7, 5, 1],
|
||||
[0, 8, 3, 1, 2, 7, 1, 7, 5, 7, 2, 11],
|
||||
[9, 7, 5, 9, 2, 7, 9, 0, 2, 2, 11, 7],
|
||||
[7, 5, 2, 7, 2, 11, 5, 9, 2, 3, 2, 8, 9, 8, 2],
|
||||
[2, 5, 10, 2, 3, 5, 3, 7, 5],
|
||||
[8, 2, 0, 8, 5, 2, 8, 7, 5, 10, 2, 5],
|
||||
[9, 0, 1, 5, 10, 3, 5, 3, 7, 3, 10, 2],
|
||||
[9, 8, 2, 9, 2, 1, 8, 7, 2, 10, 2, 5, 7, 5, 2],
|
||||
[1, 3, 5, 3, 7, 5],
|
||||
[0, 8, 7, 0, 7, 1, 1, 7, 5],
|
||||
[9, 0, 3, 9, 3, 5, 5, 3, 7],
|
||||
[9, 8, 7, 5, 9, 7],
|
||||
[5, 8, 4, 5, 10, 8, 10, 11, 8],
|
||||
[5, 0, 4, 5, 11, 0, 5, 10, 11, 11, 3, 0],
|
||||
[0, 1, 9, 8, 4, 10, 8, 10, 11, 10, 4, 5],
|
||||
[10, 11, 4, 10, 4, 5, 11, 3, 4, 9, 4, 1, 3, 1, 4],
|
||||
[2, 5, 1, 2, 8, 5, 2, 11, 8, 4, 5, 8],
|
||||
[0, 4, 11, 0, 11, 3, 4, 5, 11, 2, 11, 1, 5, 1, 11],
|
||||
[0, 2, 5, 0, 5, 9, 2, 11, 5, 4, 5, 8, 11, 8, 5],
|
||||
[9, 4, 5, 2, 11, 3],
|
||||
[2, 5, 10, 3, 5, 2, 3, 4, 5, 3, 8, 4],
|
||||
[5, 10, 2, 5, 2, 4, 4, 2, 0],
|
||||
[3, 10, 2, 3, 5, 10, 3, 8, 5, 4, 5, 8, 0, 1, 9],
|
||||
[5, 10, 2, 5, 2, 4, 1, 9, 2, 9, 4, 2],
|
||||
[8, 4, 5, 8, 5, 3, 3, 5, 1],
|
||||
[0, 4, 5, 1, 0, 5],
|
||||
[8, 4, 5, 8, 5, 3, 9, 0, 5, 0, 3, 5],
|
||||
[9, 4, 5],
|
||||
[4, 11, 7, 4, 9, 11, 9, 10, 11],
|
||||
[0, 8, 3, 4, 9, 7, 9, 11, 7, 9, 10, 11],
|
||||
[1, 10, 11, 1, 11, 4, 1, 4, 0, 7, 4, 11],
|
||||
[3, 1, 4, 3, 4, 8, 1, 10, 4, 7, 4, 11, 10, 11, 4],
|
||||
[4, 11, 7, 9, 11, 4, 9, 2, 11, 9, 1, 2],
|
||||
[9, 7, 4, 9, 11, 7, 9, 1, 11, 2, 11, 1, 0, 8, 3],
|
||||
[11, 7, 4, 11, 4, 2, 2, 4, 0],
|
||||
[11, 7, 4, 11, 4, 2, 8, 3, 4, 3, 2, 4],
|
||||
[2, 9, 10, 2, 7, 9, 2, 3, 7, 7, 4, 9],
|
||||
[9, 10, 7, 9, 7, 4, 10, 2, 7, 8, 7, 0, 2, 0, 7],
|
||||
[3, 7, 10, 3, 10, 2, 7, 4, 10, 1, 10, 0, 4, 0, 10],
|
||||
[1, 10, 2, 8, 7, 4],
|
||||
[4, 9, 1, 4, 1, 7, 7, 1, 3],
|
||||
[4, 9, 1, 4, 1, 7, 0, 8, 1, 8, 7, 1],
|
||||
[4, 0, 3, 7, 4, 3],
|
||||
[4, 8, 7],
|
||||
[9, 10, 8, 10, 11, 8],
|
||||
[3, 0, 9, 3, 9, 11, 11, 9, 10],
|
||||
[0, 1, 10, 0, 10, 8, 8, 10, 11],
|
||||
[3, 1, 10, 11, 3, 10],
|
||||
[1, 2, 11, 1, 11, 9, 9, 11, 8],
|
||||
[3, 0, 9, 3, 9, 11, 1, 2, 9, 2, 11, 9],
|
||||
[0, 2, 11, 8, 0, 11],
|
||||
[3, 2, 11],
|
||||
[2, 3, 8, 2, 8, 10, 10, 8, 9],
|
||||
[9, 10, 2, 0, 9, 2],
|
||||
[2, 3, 8, 2, 8, 10, 0, 1, 8, 1, 10, 8],
|
||||
[1, 10, 2],
|
||||
[1, 3, 8, 9, 1, 8],
|
||||
[0, 9, 1],
|
||||
[0, 3, 8],
|
||||
[]
|
||||
]
|
||||
|
||||
## translation between edge index and
|
||||
## the vertex indexes that bound the edge
|
||||
edgeKey = [
|
||||
[(0,0,0), (1,0,0)],
|
||||
[(1,0,0), (1,1,0)],
|
||||
[(1,1,0), (0,1,0)],
|
||||
[(0,1,0), (0,0,0)],
|
||||
[(0,0,1), (1,0,1)],
|
||||
[(1,0,1), (1,1,1)],
|
||||
[(1,1,1), (0,1,1)],
|
||||
[(0,1,1), (0,0,1)],
|
||||
[(0,0,0), (0,0,1)],
|
||||
[(1,0,0), (1,0,1)],
|
||||
[(1,1,0), (1,1,1)],
|
||||
[(0,1,0), (0,1,1)],
|
||||
]
|
||||
|
||||
|
||||
|
||||
facets = []
|
||||
|
||||
## mark everything below the isosurface level
|
||||
mask = data < level
|
||||
|
|
@ -1494,35 +1517,93 @@ def isosurface(data, level):
|
|||
for k in [0,1]:
|
||||
fields[i,j,k] = mask[slices[i], slices[j], slices[k]]
|
||||
vertIndex = i - 2*j*i + 3*j + 4*k ## this is just to match Bourk's vertex numbering scheme
|
||||
#print i,j,k," : ", fields[i,j,k], 2**vertIndex
|
||||
index += fields[i,j,k] * 2**vertIndex
|
||||
#print index
|
||||
#print index
|
||||
|
||||
## add facets
|
||||
for i in range(index.shape[0]): # data x-axis
|
||||
for j in range(index.shape[1]): # data y-axis
|
||||
for k in range(index.shape[2]): # data z-axis
|
||||
tris = triTable[index[i,j,k]]
|
||||
for l in range(0, len(tris), 3): ## faces for this grid cell
|
||||
edges = tris[l:l+3]
|
||||
pts = []
|
||||
for m in [0,1,2]: # points in this face
|
||||
p1 = edgeKey[edges[m]][0]
|
||||
p2 = edgeKey[edges[m]][1]
|
||||
v1 = data[i+p1[0], j+p1[1], k+p1[2]]
|
||||
v2 = data[i+p2[0], j+p2[1], k+p2[2]]
|
||||
f = (level-v1) / (v2-v1)
|
||||
fi = 1.0 - f
|
||||
p = ( ## interpolate between corners
|
||||
p1[0]*fi + p2[0]*f + i + 0.5,
|
||||
p1[1]*fi + p2[1]*f + j + 0.5,
|
||||
p1[2]*fi + p2[2]*f + k + 0.5
|
||||
)
|
||||
pts.append(p)
|
||||
facets.append(pts)
|
||||
### Generate table of edges that have been cut
|
||||
cutEdges = np.zeros([x+1 for x in index.shape]+[3], dtype=np.uint32)
|
||||
edges = edgeTable[index]
|
||||
for i, shift in enumerate(edgeShifts[:12]):
|
||||
slices = [slice(shift[j],cutEdges.shape[j]+(shift[j]-1)) for j in range(3)]
|
||||
cutEdges[slices[0], slices[1], slices[2], shift[3]] += edges & 2**i
|
||||
|
||||
## for each cut edge, interpolate to see where exactly the edge is cut and generate vertex positions
|
||||
m = cutEdges > 0
|
||||
vertexInds = np.argwhere(m) ## argwhere is slow!
|
||||
vertexes = vertexInds[:,:3].astype(np.float32)
|
||||
dataFlat = data.reshape(data.shape[0]*data.shape[1]*data.shape[2])
|
||||
|
||||
## re-use the cutEdges array as a lookup table for vertex IDs
|
||||
cutEdges[vertexInds[:,0], vertexInds[:,1], vertexInds[:,2], vertexInds[:,3]] = np.arange(vertexInds.shape[0])
|
||||
|
||||
for i in [0,1,2]:
|
||||
vim = vertexInds[:,3] == i
|
||||
vi = vertexInds[vim, :3]
|
||||
viFlat = (vi * (np.array(data.strides[:3]) / data.itemsize)[np.newaxis,:]).sum(axis=1)
|
||||
v1 = dataFlat[viFlat]
|
||||
v2 = dataFlat[viFlat + data.strides[i]/data.itemsize]
|
||||
vertexes[vim,i] += (level-v1) / (v2-v1)
|
||||
|
||||
### compute the set of vertex indexes for each face.
|
||||
|
||||
## This works, but runs a bit slower.
|
||||
#cells = np.argwhere((index != 0) & (index != 255)) ## all cells with at least one face
|
||||
#cellInds = index[cells[:,0], cells[:,1], cells[:,2]]
|
||||
#verts = faceTable[cellInds]
|
||||
#mask = verts[...,0,0] != 9
|
||||
#verts[...,:3] += cells[:,np.newaxis,np.newaxis,:] ## we now have indexes into cutEdges
|
||||
#verts = verts[mask]
|
||||
#faces = cutEdges[verts[...,0], verts[...,1], verts[...,2], verts[...,3]] ## and these are the vertex indexes we want.
|
||||
|
||||
|
||||
## To allow this to be vectorized efficiently, we count the number of faces in each
|
||||
## grid cell and handle each group of cells with the same number together.
|
||||
## determine how many faces to assign to each grid cell
|
||||
nFaces = nTableFaces[index]
|
||||
totFaces = nFaces.sum()
|
||||
faces = np.empty((totFaces, 3), dtype=np.uint32)
|
||||
ptr = 0
|
||||
#import debug
|
||||
#p = debug.Profiler('isosurface', disabled=False)
|
||||
|
||||
## this helps speed up an indexing operation later on
|
||||
cs = np.array(cutEdges.strides)/cutEdges.itemsize
|
||||
cutEdges = cutEdges.flatten()
|
||||
|
||||
return np.array(facets)
|
||||
## this, strangely, does not seem to help.
|
||||
#ins = np.array(index.strides)/index.itemsize
|
||||
#index = index.flatten()
|
||||
|
||||
for i in range(1,6):
|
||||
### expensive:
|
||||
#p.mark('1')
|
||||
cells = np.argwhere(nFaces == i) ## all cells which require i faces (argwhere is expensive)
|
||||
#p.mark('2')
|
||||
if cells.shape[0] == 0:
|
||||
continue
|
||||
#cellInds = index[(cells*ins[np.newaxis,:]).sum(axis=1)]
|
||||
cellInds = index[cells[:,0], cells[:,1], cells[:,2]] ## index values of cells to process for this round
|
||||
#p.mark('3')
|
||||
|
||||
### expensive:
|
||||
verts = faceShiftTables[i][cellInds]
|
||||
#p.mark('4')
|
||||
verts[...,:3] += cells[:,np.newaxis,np.newaxis,:] ## we now have indexes into cutEdges
|
||||
verts = verts.reshape((verts.shape[0]*i,)+verts.shape[2:])
|
||||
#p.mark('5')
|
||||
|
||||
### expensive:
|
||||
#print verts.shape
|
||||
verts = (verts * cs[np.newaxis, np.newaxis, :]).sum(axis=2)
|
||||
#vertInds = cutEdges[verts[...,0], verts[...,1], verts[...,2], verts[...,3]] ## and these are the vertex indexes we want.
|
||||
vertInds = cutEdges[verts]
|
||||
#p.mark('6')
|
||||
nv = vertInds.shape[0]
|
||||
#p.mark('7')
|
||||
faces[ptr:ptr+nv] = vertInds #.reshape((nv, 3))
|
||||
#p.mark('8')
|
||||
ptr += nv
|
||||
|
||||
return vertexes, faces
|
||||
|
||||
|
||||
|
||||
|
|
|
|||
|
|
@ -233,7 +233,7 @@ class ScatterPlotItem(GraphicsObject):
|
|||
self.bounds = [None, None] ## caches data bounds
|
||||
self._maxSpotWidth = 0 ## maximum size of the scale-variant portion of all spots
|
||||
self._maxSpotPxWidth = 0 ## maximum size of the scale-invariant portion of all spots
|
||||
self.opts = {'pxMode': True, 'useCache': True} ## If useCache is False, symbols are re-drawn on every paint.
|
||||
self.opts = {'pxMode': True, 'useCache': True, 'exportMode': False} ## If useCache is False, symbols are re-drawn on every paint.
|
||||
|
||||
self.setPen(200,200,200, update=False)
|
||||
self.setBrush(100,100,150, update=False)
|
||||
|
|
@ -664,10 +664,14 @@ class ScatterPlotItem(GraphicsObject):
|
|||
rect = QtCore.QRectF(y, x, h, w)
|
||||
self.fragments.append(QtGui.QPainter.PixmapFragment.create(pos, rect))
|
||||
|
||||
def setExportMode(self, enabled, opts):
|
||||
self.opts['exportMode'] = enabled
|
||||
|
||||
|
||||
def paint(self, p, *args):
|
||||
#p.setPen(fn.mkPen('r'))
|
||||
#p.drawRect(self.boundingRect())
|
||||
if self.opts['pxMode']:
|
||||
if self.opts['pxMode'] is True:
|
||||
atlas = self.fragmentAtlas.getAtlas()
|
||||
#arr = fn.imageToArray(atlas.toImage(), copy=True)
|
||||
#if hasattr(self, 'lastAtlas'):
|
||||
|
|
@ -681,7 +685,7 @@ class ScatterPlotItem(GraphicsObject):
|
|||
|
||||
p.resetTransform()
|
||||
|
||||
if not USE_PYSIDE and self.opts['useCache']:
|
||||
if not USE_PYSIDE and self.opts['useCache'] and self.opts['exportMode'] is False:
|
||||
p.drawPixmapFragments(self.fragments, atlas)
|
||||
else:
|
||||
for i in range(len(self.data)):
|
||||
|
|
|
|||
Loading…
Reference in New Issue
Block a user