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Minor refactor
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@ -21,7 +21,7 @@ LocationSuggestion = namedtuple("LocationSuggestion", ["x", "y", "penalty_points
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class Arrange:
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build_volume = None
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def __init__(self, x, y, offset_x, offset_y, scale=1):
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def __init__(self, x, y, offset_x, offset_y, scale= 1.0):
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self.shape = (y, x)
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self._priority = numpy.zeros((x, y), dtype=numpy.int32)
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self._priority_unique_values = []
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@ -48,7 +48,8 @@ class Arrange:
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# Only count sliceable objects
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if node_.callDecoration("isSliceable"):
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fixed_nodes.append(node_)
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# place all objects fixed nodes
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# Place all objects fixed nodes
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for fixed_node in fixed_nodes:
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vertices = fixed_node.callDecoration("getConvexHull")
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points = copy.deepcopy(vertices._points)
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@ -146,8 +147,8 @@ class Arrange:
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start_idx = start_idx_list[0][0]
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else:
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start_idx = 0
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for prio in self._priority_unique_values[start_idx::step]:
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tryout_idx = numpy.where(self._priority == prio)
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for priority in self._priority_unique_values[start_idx::step]:
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tryout_idx = numpy.where(self._priority == priority)
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for idx in range(len(tryout_idx[0])):
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x = tryout_idx[0][idx]
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y = tryout_idx[1][idx]
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@ -157,8 +158,8 @@ class Arrange:
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# array to "world" coordinates
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penalty_points = self.checkShape(projected_x, projected_y, shape_arr)
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if penalty_points != 999999:
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return LocationSuggestion(x = projected_x, y = projected_y, penalty_points = penalty_points, priority = prio)
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return LocationSuggestion(x = None, y = None, penalty_points = None, priority = prio) # No suitable location found :-(
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return LocationSuggestion(x = projected_x, y = projected_y, penalty_points = penalty_points, priority = priority)
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return LocationSuggestion(x = None, y = None, penalty_points = None, priority = priority) # No suitable location found :-(
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## Place the object.
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# Marks the locations in self._occupied and self._priority
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