- fixed Excellon parser to detect correctly the units and zeros for Excellon's generated by Eagle 9.3.0
- modified the initial size of the canvas on startup - modified the build file (make_win.py) to solve the issue with suddenly not accepting the version as Beta
This commit is contained in:
Marius Stanciu
Marius S
parent
b6d36bb86d
commit
71d8b2df36
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@ -20,6 +20,9 @@ CAD program, and create G-Code for Isolation routing.
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- fixed DblSided Tool crash when trying to create Alignment Drills object without a Tool diameter specified
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- fixed DblSided Tool issue when entering Tool diameter values with comma decimal separator instead of decimal dot separator
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- fixed Cutout Tool Freeform to generate cutouts with options: LR, TB. 2LR, 2TB which didn't worked previously
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- fixed Excellon parser to detect correctly the units and zeros for Excellon's generated by Eagle 9.3.0
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- modified the initial size of the canvas on startup
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- modified the build file (make_win.py) to solve the issue with suddenly not accepting the version as Beta
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15.02.2019
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@ -40,7 +40,7 @@ class VisPyCanvas(scene.SceneCanvas):
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right_padding.width_max = 0
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view = self.grid_widget.add_view(row=1, col=1, border_color='black', bgcolor='white')
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view.camera = Camera(aspect=1, rect=(-100,-100,500,500))
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view.camera = Camera(aspect=1, rect=(-25,-25,150,150))
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# Following function was removed from 'prepare_draw()' of 'Grid' class by patch,
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# it is necessary to call manually
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417
camlib.py
417
camlib.py
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@ -43,7 +43,7 @@ from rasterio.features import shapes
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from xml.dom.minidom import parseString as parse_xml_string
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from scipy.spatial import KDTree, Delaunay
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# from scipy.spatial import KDTree, Delaunay
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from ParseSVG import *
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from ParseDXF import *
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@ -3348,7 +3348,7 @@ class Excellon(Geometry):
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# Number format and units
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# INCH uses 6 digits
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# METRIC uses 5/6
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self.units_re = re.compile(r'^(INCH|METRIC)(?:,([TL])Z)?$')
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self.units_re = re.compile(r'^(INCH|METRIC)(?:,([TL])Z)?.*$')
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# Tool definition/parameters (?= is look-ahead
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# NOTE: This might be an overkill!
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@ -3968,7 +3968,6 @@ class Excellon(Geometry):
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#FlatCAMApp.App.inform.emit("Detected INLINE: %s" % str(eline))
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continue
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# Search for zeros type again because it might be alone on the line
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match = re.search(r'[LT]Z',eline)
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if match:
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@ -6551,212 +6550,212 @@ def parse_gerber_number(strnumber, int_digits, frac_digits, zeros):
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return ret_val
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def voronoi(P):
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"""
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Returns a list of all edges of the voronoi diagram for the given input points.
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"""
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delauny = Delaunay(P)
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triangles = delauny.points[delauny.vertices]
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circum_centers = np.array([triangle_csc(tri) for tri in triangles])
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long_lines_endpoints = []
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lineIndices = []
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for i, triangle in enumerate(triangles):
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circum_center = circum_centers[i]
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for j, neighbor in enumerate(delauny.neighbors[i]):
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if neighbor != -1:
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lineIndices.append((i, neighbor))
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else:
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ps = triangle[(j+1)%3] - triangle[(j-1)%3]
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ps = np.array((ps[1], -ps[0]))
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middle = (triangle[(j+1)%3] + triangle[(j-1)%3]) * 0.5
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di = middle - triangle[j]
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ps /= np.linalg.norm(ps)
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di /= np.linalg.norm(di)
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if np.dot(di, ps) < 0.0:
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ps *= -1000.0
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else:
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ps *= 1000.0
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long_lines_endpoints.append(circum_center + ps)
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lineIndices.append((i, len(circum_centers) + len(long_lines_endpoints)-1))
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vertices = np.vstack((circum_centers, long_lines_endpoints))
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# filter out any duplicate lines
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lineIndicesSorted = np.sort(lineIndices) # make (1,2) and (2,1) both (1,2)
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lineIndicesTupled = [tuple(row) for row in lineIndicesSorted]
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lineIndicesUnique = np.unique(lineIndicesTupled)
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return vertices, lineIndicesUnique
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def triangle_csc(pts):
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rows, cols = pts.shape
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A = np.bmat([[2 * np.dot(pts, pts.T), np.ones((rows, 1))],
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[np.ones((1, rows)), np.zeros((1, 1))]])
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b = np.hstack((np.sum(pts * pts, axis=1), np.ones((1))))
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x = np.linalg.solve(A,b)
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bary_coords = x[:-1]
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return np.sum(pts * np.tile(bary_coords.reshape((pts.shape[0], 1)), (1, pts.shape[1])), axis=0)
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def voronoi_cell_lines(points, vertices, lineIndices):
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"""
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Returns a mapping from a voronoi cell to its edges.
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:param points: shape (m,2)
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:param vertices: shape (n,2)
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:param lineIndices: shape (o,2)
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:rtype: dict point index -> list of shape (n,2) with vertex indices
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"""
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kd = KDTree(points)
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cells = collections.defaultdict(list)
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for i1, i2 in lineIndices:
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v1, v2 = vertices[i1], vertices[i2]
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mid = (v1+v2)/2
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_, (p1Idx, p2Idx) = kd.query(mid, 2)
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cells[p1Idx].append((i1, i2))
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cells[p2Idx].append((i1, i2))
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return cells
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def voronoi_edges2polygons(cells):
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"""
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Transforms cell edges into polygons.
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:param cells: as returned from voronoi_cell_lines
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:rtype: dict point index -> list of vertex indices which form a polygon
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"""
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# first, close the outer cells
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for pIdx, lineIndices_ in cells.items():
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dangling_lines = []
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for i1, i2 in lineIndices_:
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p = (i1, i2)
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connections = filter(lambda k: p != k and (p[0] == k[0] or p[0] == k[1] or p[1] == k[0] or p[1] == k[1]), lineIndices_)
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# connections = filter(lambda (i1_, i2_): (i1, i2) != (i1_, i2_) and (i1 == i1_ or i1 == i2_ or i2 == i1_ or i2 == i2_), lineIndices_)
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assert 1 <= len(connections) <= 2
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if len(connections) == 1:
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dangling_lines.append((i1, i2))
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assert len(dangling_lines) in [0, 2]
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if len(dangling_lines) == 2:
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(i11, i12), (i21, i22) = dangling_lines
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s = (i11, i12)
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t = (i21, i22)
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# determine which line ends are unconnected
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connected = filter(lambda k: k != s and (k[0] == s[0] or k[1] == s[0]), lineIndices_)
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# connected = filter(lambda (i1,i2): (i1,i2) != (i11,i12) and (i1 == i11 or i2 == i11), lineIndices_)
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i11Unconnected = len(connected) == 0
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connected = filter(lambda k: k != t and (k[0] == t[0] or k[1] == t[0]), lineIndices_)
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# connected = filter(lambda (i1,i2): (i1,i2) != (i21,i22) and (i1 == i21 or i2 == i21), lineIndices_)
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i21Unconnected = len(connected) == 0
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startIdx = i11 if i11Unconnected else i12
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endIdx = i21 if i21Unconnected else i22
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cells[pIdx].append((startIdx, endIdx))
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# then, form polygons by storing vertex indices in (counter-)clockwise order
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polys = dict()
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for pIdx, lineIndices_ in cells.items():
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# get a directed graph which contains both directions and arbitrarily follow one of both
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directedGraph = lineIndices_ + [(i2, i1) for (i1, i2) in lineIndices_]
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directedGraphMap = collections.defaultdict(list)
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for (i1, i2) in directedGraph:
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directedGraphMap[i1].append(i2)
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orderedEdges = []
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currentEdge = directedGraph[0]
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while len(orderedEdges) < len(lineIndices_):
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i1 = currentEdge[1]
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i2 = directedGraphMap[i1][0] if directedGraphMap[i1][0] != currentEdge[0] else directedGraphMap[i1][1]
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nextEdge = (i1, i2)
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orderedEdges.append(nextEdge)
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currentEdge = nextEdge
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polys[pIdx] = [i1 for (i1, i2) in orderedEdges]
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return polys
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def voronoi_polygons(points):
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"""
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Returns the voronoi polygon for each input point.
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:param points: shape (n,2)
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:rtype: list of n polygons where each polygon is an array of vertices
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"""
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vertices, lineIndices = voronoi(points)
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cells = voronoi_cell_lines(points, vertices, lineIndices)
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polys = voronoi_edges2polygons(cells)
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polylist = []
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for i in range(len(points)):
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poly = vertices[np.asarray(polys[i])]
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polylist.append(poly)
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return polylist
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class Zprofile:
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def __init__(self):
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# data contains lists of [x, y, z]
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self.data = []
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# Computed voronoi polygons (shapely)
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self.polygons = []
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pass
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# def plot_polygons(self):
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# axes = plt.subplot(1, 1, 1)
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#
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# plt.axis([-0.05, 1.05, -0.05, 1.05])
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#
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# for poly in self.polygons:
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# p = PolygonPatch(poly, facecolor=np.random.rand(3, 1), alpha=0.3)
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# axes.add_patch(p)
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def init_from_csv(self, filename):
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pass
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def init_from_string(self, zpstring):
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pass
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def init_from_list(self, zplist):
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self.data = zplist
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def generate_polygons(self):
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self.polygons = [Polygon(p) for p in voronoi_polygons(array([[x[0], x[1]] for x in self.data]))]
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def normalize(self, origin):
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pass
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def paste(self, path):
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"""
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Return a list of dictionaries containing the parts of the original
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path and their z-axis offset.
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"""
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# At most one region/polygon will contain the path
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containing = [i for i in range(len(self.polygons)) if self.polygons[i].contains(path)]
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if len(containing) > 0:
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return [{"path": path, "z": self.data[containing[0]][2]}]
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# All region indexes that intersect with the path
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crossing = [i for i in range(len(self.polygons)) if self.polygons[i].intersects(path)]
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return [{"path": path.intersection(self.polygons[i]),
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"z": self.data[i][2]} for i in crossing]
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# def voronoi(P):
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# """
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# Returns a list of all edges of the voronoi diagram for the given input points.
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# """
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# delauny = Delaunay(P)
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# triangles = delauny.points[delauny.vertices]
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#
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# circum_centers = np.array([triangle_csc(tri) for tri in triangles])
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# long_lines_endpoints = []
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#
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# lineIndices = []
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# for i, triangle in enumerate(triangles):
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# circum_center = circum_centers[i]
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# for j, neighbor in enumerate(delauny.neighbors[i]):
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# if neighbor != -1:
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# lineIndices.append((i, neighbor))
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# else:
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# ps = triangle[(j+1)%3] - triangle[(j-1)%3]
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# ps = np.array((ps[1], -ps[0]))
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#
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# middle = (triangle[(j+1)%3] + triangle[(j-1)%3]) * 0.5
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# di = middle - triangle[j]
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#
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# ps /= np.linalg.norm(ps)
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# di /= np.linalg.norm(di)
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#
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# if np.dot(di, ps) < 0.0:
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# ps *= -1000.0
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# else:
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# ps *= 1000.0
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#
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# long_lines_endpoints.append(circum_center + ps)
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# lineIndices.append((i, len(circum_centers) + len(long_lines_endpoints)-1))
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#
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# vertices = np.vstack((circum_centers, long_lines_endpoints))
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#
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# # filter out any duplicate lines
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# lineIndicesSorted = np.sort(lineIndices) # make (1,2) and (2,1) both (1,2)
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# lineIndicesTupled = [tuple(row) for row in lineIndicesSorted]
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# lineIndicesUnique = np.unique(lineIndicesTupled)
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#
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# return vertices, lineIndicesUnique
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#
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#
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# def triangle_csc(pts):
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# rows, cols = pts.shape
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#
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# A = np.bmat([[2 * np.dot(pts, pts.T), np.ones((rows, 1))],
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# [np.ones((1, rows)), np.zeros((1, 1))]])
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#
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# b = np.hstack((np.sum(pts * pts, axis=1), np.ones((1))))
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# x = np.linalg.solve(A,b)
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# bary_coords = x[:-1]
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# return np.sum(pts * np.tile(bary_coords.reshape((pts.shape[0], 1)), (1, pts.shape[1])), axis=0)
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#
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#
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# def voronoi_cell_lines(points, vertices, lineIndices):
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# """
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# Returns a mapping from a voronoi cell to its edges.
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#
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# :param points: shape (m,2)
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# :param vertices: shape (n,2)
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# :param lineIndices: shape (o,2)
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# :rtype: dict point index -> list of shape (n,2) with vertex indices
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# """
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# kd = KDTree(points)
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#
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# cells = collections.defaultdict(list)
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# for i1, i2 in lineIndices:
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# v1, v2 = vertices[i1], vertices[i2]
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# mid = (v1+v2)/2
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# _, (p1Idx, p2Idx) = kd.query(mid, 2)
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# cells[p1Idx].append((i1, i2))
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# cells[p2Idx].append((i1, i2))
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#
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# return cells
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#
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#
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# def voronoi_edges2polygons(cells):
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# """
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# Transforms cell edges into polygons.
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#
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# :param cells: as returned from voronoi_cell_lines
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# :rtype: dict point index -> list of vertex indices which form a polygon
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# """
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#
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# # first, close the outer cells
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# for pIdx, lineIndices_ in cells.items():
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# dangling_lines = []
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# for i1, i2 in lineIndices_:
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# p = (i1, i2)
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# connections = filter(lambda k: p != k and (p[0] == k[0] or p[0] == k[1] or p[1] == k[0] or p[1] == k[1]), lineIndices_)
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# # connections = filter(lambda (i1_, i2_): (i1, i2) != (i1_, i2_) and (i1 == i1_ or i1 == i2_ or i2 == i1_ or i2 == i2_), lineIndices_)
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# assert 1 <= len(connections) <= 2
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# if len(connections) == 1:
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# dangling_lines.append((i1, i2))
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# assert len(dangling_lines) in [0, 2]
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# if len(dangling_lines) == 2:
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# (i11, i12), (i21, i22) = dangling_lines
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# s = (i11, i12)
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# t = (i21, i22)
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#
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# # determine which line ends are unconnected
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# connected = filter(lambda k: k != s and (k[0] == s[0] or k[1] == s[0]), lineIndices_)
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# # connected = filter(lambda (i1,i2): (i1,i2) != (i11,i12) and (i1 == i11 or i2 == i11), lineIndices_)
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# i11Unconnected = len(connected) == 0
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#
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# connected = filter(lambda k: k != t and (k[0] == t[0] or k[1] == t[0]), lineIndices_)
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# # connected = filter(lambda (i1,i2): (i1,i2) != (i21,i22) and (i1 == i21 or i2 == i21), lineIndices_)
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# i21Unconnected = len(connected) == 0
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#
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# startIdx = i11 if i11Unconnected else i12
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# endIdx = i21 if i21Unconnected else i22
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#
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# cells[pIdx].append((startIdx, endIdx))
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#
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# # then, form polygons by storing vertex indices in (counter-)clockwise order
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# polys = dict()
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# for pIdx, lineIndices_ in cells.items():
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# # get a directed graph which contains both directions and arbitrarily follow one of both
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# directedGraph = lineIndices_ + [(i2, i1) for (i1, i2) in lineIndices_]
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# directedGraphMap = collections.defaultdict(list)
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# for (i1, i2) in directedGraph:
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# directedGraphMap[i1].append(i2)
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# orderedEdges = []
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# currentEdge = directedGraph[0]
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# while len(orderedEdges) < len(lineIndices_):
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# i1 = currentEdge[1]
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# i2 = directedGraphMap[i1][0] if directedGraphMap[i1][0] != currentEdge[0] else directedGraphMap[i1][1]
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# nextEdge = (i1, i2)
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# orderedEdges.append(nextEdge)
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# currentEdge = nextEdge
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#
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# polys[pIdx] = [i1 for (i1, i2) in orderedEdges]
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#
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# return polys
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#
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#
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# def voronoi_polygons(points):
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# """
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# Returns the voronoi polygon for each input point.
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#
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# :param points: shape (n,2)
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# :rtype: list of n polygons where each polygon is an array of vertices
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# """
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# vertices, lineIndices = voronoi(points)
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# cells = voronoi_cell_lines(points, vertices, lineIndices)
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# polys = voronoi_edges2polygons(cells)
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# polylist = []
|
||||
# for i in range(len(points)):
|
||||
# poly = vertices[np.asarray(polys[i])]
|
||||
# polylist.append(poly)
|
||||
# return polylist
|
||||
#
|
||||
#
|
||||
# class Zprofile:
|
||||
# def __init__(self):
|
||||
#
|
||||
# # data contains lists of [x, y, z]
|
||||
# self.data = []
|
||||
#
|
||||
# # Computed voronoi polygons (shapely)
|
||||
# self.polygons = []
|
||||
# pass
|
||||
#
|
||||
# # def plot_polygons(self):
|
||||
# # axes = plt.subplot(1, 1, 1)
|
||||
# #
|
||||
# # plt.axis([-0.05, 1.05, -0.05, 1.05])
|
||||
# #
|
||||
# # for poly in self.polygons:
|
||||
# # p = PolygonPatch(poly, facecolor=np.random.rand(3, 1), alpha=0.3)
|
||||
# # axes.add_patch(p)
|
||||
#
|
||||
# def init_from_csv(self, filename):
|
||||
# pass
|
||||
#
|
||||
# def init_from_string(self, zpstring):
|
||||
# pass
|
||||
#
|
||||
# def init_from_list(self, zplist):
|
||||
# self.data = zplist
|
||||
#
|
||||
# def generate_polygons(self):
|
||||
# self.polygons = [Polygon(p) for p in voronoi_polygons(array([[x[0], x[1]] for x in self.data]))]
|
||||
#
|
||||
# def normalize(self, origin):
|
||||
# pass
|
||||
#
|
||||
# def paste(self, path):
|
||||
# """
|
||||
# Return a list of dictionaries containing the parts of the original
|
||||
# path and their z-axis offset.
|
||||
# """
|
||||
#
|
||||
# # At most one region/polygon will contain the path
|
||||
# containing = [i for i in range(len(self.polygons)) if self.polygons[i].contains(path)]
|
||||
#
|
||||
# if len(containing) > 0:
|
||||
# return [{"path": path, "z": self.data[containing[0]][2]}]
|
||||
#
|
||||
# # All region indexes that intersect with the path
|
||||
# crossing = [i for i in range(len(self.polygons)) if self.polygons[i].intersects(path)]
|
||||
#
|
||||
# return [{"path": path.intersection(self.polygons[i]),
|
||||
# "z": self.data[i][2]} for i in crossing]
|
||||
|
||||
|
||||
def autolist(obj):
|
||||
|
|
|
|||
10
make_win.py
10
make_win.py
|
|
@ -63,8 +63,8 @@ if platform.architecture()[0] == '64bit':
|
|||
include_files=include_files,
|
||||
excludes=['scipy','pytz'],
|
||||
# packages=['OpenGL','numpy','vispy','ortools','google']
|
||||
packages=['numpy','google', 'rasterio'] # works for Python 3.7
|
||||
# packages = ['opengl', 'numpy', 'google', 'rasterio'] # works for Python 3.6.5
|
||||
# packages=['numpy','google', 'rasterio'] # works for Python 3.7
|
||||
packages = ['opengl', 'numpy', 'google', 'rasterio'] # works for Python 3.6.5 and Python 3.7.1
|
||||
|
||||
)
|
||||
else:
|
||||
|
|
@ -72,8 +72,8 @@ else:
|
|||
include_files=include_files,
|
||||
excludes=['scipy', 'pytz'],
|
||||
# packages=['OpenGL','numpy','vispy','ortools','google']
|
||||
packages=['numpy', 'rasterio'] # works for Python 3.7
|
||||
# packages = ['opengl', 'numpy', 'google', 'rasterio'] # works for Python 3.6.5
|
||||
# packages=['numpy', 'rasterio'] # works for Python 3.7
|
||||
packages = ['opengl', 'numpy', 'google', 'rasterio'] # works for Python 3.6.5 and Python 3.7.1
|
||||
|
||||
)
|
||||
|
||||
|
|
@ -84,7 +84,7 @@ print("INCLUDE_FILES", include_files)
|
|||
setup(
|
||||
name="FlatCAM",
|
||||
author="Juan Pablo Caram",
|
||||
version="Beta",
|
||||
version="8.9",
|
||||
description="FlatCAM: 2D Computer Aided PCB Manufacturing",
|
||||
options=dict(build_exe=buildOptions),
|
||||
executables=[Executable("FlatCAM.py", icon='share/flatcam_icon48.ico', base=base)]
|
||||
|
|
|
|||
Loading…
Reference in New Issue