forked from LeenkxTeam/LNXSDK
581 lines
17 KiB
Python
581 lines
17 KiB
Python
from .maxrects import MaxRectsBssf
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import operator
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import itertools
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import collections
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import decimal
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# Float to Decimal helper
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def float2dec(ft, decimal_digits):
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"""
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Convert float (or int) to Decimal (rounding up) with the
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requested number of decimal digits.
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Arguments:
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ft (float, int): Number to convert
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decimal (int): Number of digits after decimal point
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Return:
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Decimal: Number converted to decima
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"""
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with decimal.localcontext() as ctx:
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ctx.rounding = decimal.ROUND_UP
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places = decimal.Decimal(10)**(-decimal_digits)
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return decimal.Decimal.from_float(float(ft)).quantize(places)
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# Sorting algos for rectangle lists
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SORT_AREA = lambda rectlist: sorted(rectlist, reverse=True,
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key=lambda r: r[0]*r[1]) # Sort by area
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SORT_PERI = lambda rectlist: sorted(rectlist, reverse=True,
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key=lambda r: r[0]+r[1]) # Sort by perimeter
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SORT_DIFF = lambda rectlist: sorted(rectlist, reverse=True,
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key=lambda r: abs(r[0]-r[1])) # Sort by Diff
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SORT_SSIDE = lambda rectlist: sorted(rectlist, reverse=True,
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key=lambda r: (min(r[0], r[1]), max(r[0], r[1]))) # Sort by short side
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SORT_LSIDE = lambda rectlist: sorted(rectlist, reverse=True,
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key=lambda r: (max(r[0], r[1]), min(r[0], r[1]))) # Sort by long side
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SORT_RATIO = lambda rectlist: sorted(rectlist, reverse=True,
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key=lambda r: r[0]/r[1]) # Sort by side ratio
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SORT_NONE = lambda rectlist: list(rectlist) # Unsorted
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class BinFactory(object):
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def __init__(self, width, height, count, pack_algo, *args, **kwargs):
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self._width = width
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self._height = height
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self._count = count
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self._pack_algo = pack_algo
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self._algo_kwargs = kwargs
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self._algo_args = args
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self._ref_bin = None # Reference bin used to calculate fitness
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self._bid = kwargs.get("bid", None)
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def _create_bin(self):
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return self._pack_algo(self._width, self._height, *self._algo_args, **self._algo_kwargs)
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def is_empty(self):
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return self._count<1
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def fitness(self, width, height):
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if not self._ref_bin:
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self._ref_bin = self._create_bin()
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return self._ref_bin.fitness(width, height)
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def fits_inside(self, width, height):
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# Determine if rectangle widthxheight will fit into empty bin
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if not self._ref_bin:
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self._ref_bin = self._create_bin()
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return self._ref_bin._fits_surface(width, height)
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def new_bin(self):
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if self._count > 0:
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self._count -= 1
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return self._create_bin()
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else:
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return None
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def __eq__(self, other):
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return self._width*self._height == other._width*other._height
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def __lt__(self, other):
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return self._width*self._height < other._width*other._height
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def __str__(self):
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return "Bin: {} {} {}".format(self._width, self._height, self._count)
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class PackerBNFMixin(object):
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"""
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BNF (Bin Next Fit): Only one open bin at a time. If the rectangle
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doesn't fit, close the current bin and go to the next.
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"""
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def add_rect(self, width, height, rid=None):
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while True:
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# if there are no open bins, try to open a new one
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if len(self._open_bins)==0:
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# can we find an unopened bin that will hold this rect?
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new_bin = self._new_open_bin(width, height, rid=rid)
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if new_bin is None:
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return None
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# we have at least one open bin, so check if it can hold this rect
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rect = self._open_bins[0].add_rect(width, height, rid=rid)
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if rect is not None:
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return rect
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# since the rect doesn't fit, close this bin and try again
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closed_bin = self._open_bins.popleft()
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self._closed_bins.append(closed_bin)
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class PackerBFFMixin(object):
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"""
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BFF (Bin First Fit): Pack rectangle in first bin it fits
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"""
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def add_rect(self, width, height, rid=None):
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# see if this rect will fit in any of the open bins
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for b in self._open_bins:
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rect = b.add_rect(width, height, rid=rid)
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if rect is not None:
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return rect
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while True:
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# can we find an unopened bin that will hold this rect?
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new_bin = self._new_open_bin(width, height, rid=rid)
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if new_bin is None:
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return None
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# _new_open_bin may return a bin that's too small,
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# so we have to double-check
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rect = new_bin.add_rect(width, height, rid=rid)
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if rect is not None:
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return rect
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class PackerBBFMixin(object):
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"""
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BBF (Bin Best Fit): Pack rectangle in bin that gives best fitness
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"""
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# only create this getter once
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first_item = operator.itemgetter(0)
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def add_rect(self, width, height, rid=None):
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# Try packing into open bins
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fit = ((b.fitness(width, height), b) for b in self._open_bins)
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fit = (b for b in fit if b[0] is not None)
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try:
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_, best_bin = min(fit, key=self.first_item)
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best_bin.add_rect(width, height, rid)
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return True
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except ValueError:
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pass
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# Try packing into one of the empty bins
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while True:
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# can we find an unopened bin that will hold this rect?
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new_bin = self._new_open_bin(width, height, rid=rid)
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if new_bin is None:
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return False
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# _new_open_bin may return a bin that's too small,
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# so we have to double-check
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if new_bin.add_rect(width, height, rid):
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return True
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class PackerOnline(object):
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"""
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Rectangles are packed as soon are they are added
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"""
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def __init__(self, pack_algo=MaxRectsBssf, rotation=True):
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"""
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Arguments:
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pack_algo (PackingAlgorithm): What packing algo to use
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rotation (bool): Enable/Disable rectangle rotation
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"""
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self._rotation = rotation
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self._pack_algo = pack_algo
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self.reset()
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def __iter__(self):
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return itertools.chain(self._closed_bins, self._open_bins)
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def __len__(self):
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return len(self._closed_bins)+len(self._open_bins)
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def __getitem__(self, key):
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"""
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Return bin in selected position. (excluding empty bins)
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"""
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if not isinstance(key, int):
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raise TypeError("Indices must be integers")
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size = len(self) # avoid recalulations
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if key < 0:
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key += size
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if not 0 <= key < size:
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raise IndexError("Index out of range")
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if key < len(self._closed_bins):
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return self._closed_bins[key]
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else:
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return self._open_bins[key-len(self._closed_bins)]
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def _new_open_bin(self, width=None, height=None, rid=None):
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"""
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Extract the next empty bin and append it to open bins
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Returns:
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PackingAlgorithm: Initialized empty packing bin.
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None: No bin big enough for the rectangle was found
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"""
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factories_to_delete = set() #
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new_bin = None
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for key, binfac in self._empty_bins.items():
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# Only return the new bin if the rect fits.
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# (If width or height is None, caller doesn't know the size.)
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if not binfac.fits_inside(width, height):
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continue
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# Create bin and add to open_bins
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new_bin = binfac.new_bin()
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if new_bin is None:
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continue
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self._open_bins.append(new_bin)
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# If the factory was depleted mark for deletion
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if binfac.is_empty():
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factories_to_delete.add(key)
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break
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# Delete marked factories
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for f in factories_to_delete:
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del self._empty_bins[f]
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return new_bin
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def add_bin(self, width, height, count=1, **kwargs):
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# accept the same parameters as PackingAlgorithm objects
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kwargs['rot'] = self._rotation
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bin_factory = BinFactory(width, height, count, self._pack_algo, **kwargs)
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self._empty_bins[next(self._bin_count)] = bin_factory
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def rect_list(self):
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rectangles = []
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bin_count = 0
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for abin in self:
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for rect in abin:
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rectangles.append((bin_count, rect.x, rect.y, rect.width, rect.height, rect.rid))
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bin_count += 1
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return rectangles
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def bin_list(self):
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"""
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Return a list of the dimmensions of the bins in use, that is closed
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or open containing at least one rectangle
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"""
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return [(b.width, b.height) for b in self]
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def validate_packing(self):
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for b in self:
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b.validate_packing()
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def reset(self):
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# Bins fully packed and closed.
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self._closed_bins = collections.deque()
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# Bins ready to pack rectangles
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self._open_bins = collections.deque()
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# User provided bins not in current use
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self._empty_bins = collections.OrderedDict() # O(1) deletion of arbitrary elem
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self._bin_count = itertools.count()
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class Packer(PackerOnline):
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"""
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Rectangles aren't packed untils pack() is called
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"""
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def __init__(self, pack_algo=MaxRectsBssf, sort_algo=SORT_NONE,
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rotation=True):
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"""
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"""
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super(Packer, self).__init__(pack_algo=pack_algo, rotation=rotation)
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self._sort_algo = sort_algo
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# User provided bins and Rectangles
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self._avail_bins = collections.deque()
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self._avail_rect = collections.deque()
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# Aux vars used during packing
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self._sorted_rect = []
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def add_bin(self, width, height, count=1, **kwargs):
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self._avail_bins.append((width, height, count, kwargs))
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def add_rect(self, width, height, rid=None):
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self._avail_rect.append((width, height, rid))
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def _is_everything_ready(self):
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return self._avail_rect and self._avail_bins
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def pack(self):
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self.reset()
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if not self._is_everything_ready():
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# maybe we should throw an error here?
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return
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# Add available bins to packer
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for b in self._avail_bins:
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width, height, count, extra_kwargs = b
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super(Packer, self).add_bin(width, height, count, **extra_kwargs)
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# If enabled sort rectangles
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self._sorted_rect = self._sort_algo(self._avail_rect)
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# Start packing
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for r in self._sorted_rect:
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super(Packer, self).add_rect(*r)
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class PackerBNF(Packer, PackerBNFMixin):
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"""
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BNF (Bin Next Fit): Only one open bin, if rectangle doesn't fit
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go to next bin and close current one.
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"""
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pass
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class PackerBFF(Packer, PackerBFFMixin):
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"""
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BFF (Bin First Fit): Pack rectangle in first bin it fits
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"""
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pass
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class PackerBBF(Packer, PackerBBFMixin):
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"""
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BBF (Bin Best Fit): Pack rectangle in bin that gives best fitness
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"""
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pass
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class PackerOnlineBNF(PackerOnline, PackerBNFMixin):
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"""
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BNF Bin Next Fit Online variant
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"""
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pass
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class PackerOnlineBFF(PackerOnline, PackerBFFMixin):
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"""
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BFF Bin First Fit Online variant
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"""
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pass
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class PackerOnlineBBF(PackerOnline, PackerBBFMixin):
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"""
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BBF Bin Best Fit Online variant
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"""
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pass
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class PackerGlobal(Packer, PackerBNFMixin):
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"""
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GLOBAL: For each bin pack the rectangle with the best fitness.
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"""
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first_item = operator.itemgetter(0)
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def __init__(self, pack_algo=MaxRectsBssf, rotation=True):
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"""
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"""
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super(PackerGlobal, self).__init__(pack_algo=pack_algo,
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sort_algo=SORT_NONE, rotation=rotation)
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def _find_best_fit(self, pbin):
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"""
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Return best fitness rectangle from rectangles packing _sorted_rect list
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Arguments:
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pbin (PackingAlgorithm): Packing bin
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Returns:
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key of the rectangle with best fitness
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"""
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fit = ((pbin.fitness(r[0], r[1]), k) for k, r in self._sorted_rect.items())
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fit = (f for f in fit if f[0] is not None)
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try:
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_, rect = min(fit, key=self.first_item)
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return rect
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except ValueError:
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return None
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def _new_open_bin(self, remaining_rect):
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"""
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Extract the next bin where at least one of the rectangles in
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rem
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Arguments:
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remaining_rect (dict): rectangles not placed yet
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Returns:
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PackingAlgorithm: Initialized empty packing bin.
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None: No bin big enough for the rectangle was found
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"""
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factories_to_delete = set() #
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new_bin = None
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for key, binfac in self._empty_bins.items():
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# Only return the new bin if at least one of the remaining
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# rectangles fit inside.
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a_rectangle_fits = False
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for _, rect in remaining_rect.items():
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if binfac.fits_inside(rect[0], rect[1]):
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a_rectangle_fits = True
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break
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if not a_rectangle_fits:
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factories_to_delete.add(key)
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continue
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# Create bin and add to open_bins
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new_bin = binfac.new_bin()
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if new_bin is None:
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continue
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self._open_bins.append(new_bin)
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# If the factory was depleted mark for deletion
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if binfac.is_empty():
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factories_to_delete.add(key)
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break
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# Delete marked factories
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for f in factories_to_delete:
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del self._empty_bins[f]
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return new_bin
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def pack(self):
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self.reset()
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if not self._is_everything_ready():
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return
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# Add available bins to packer
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for b in self._avail_bins:
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width, height, count, extra_kwargs = b
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super(Packer, self).add_bin(width, height, count, **extra_kwargs)
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# Store rectangles into dict for fast deletion
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self._sorted_rect = collections.OrderedDict(
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enumerate(self._sort_algo(self._avail_rect)))
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# For each bin pack the rectangles with lowest fitness until it is filled or
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# the rectangles exhausted, then open the next bin where at least one rectangle
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# will fit and repeat the process until there aren't more rectangles or bins
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# available.
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while len(self._sorted_rect) > 0:
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# Find one bin where at least one of the remaining rectangles fit
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pbin = self._new_open_bin(self._sorted_rect)
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if pbin is None:
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break
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# Pack as many rectangles as possible into the open bin
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while True:
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# Find 'fittest' rectangle
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best_rect_key = self._find_best_fit(pbin)
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if best_rect_key is None:
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closed_bin = self._open_bins.popleft()
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self._closed_bins.append(closed_bin)
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break # None of the remaining rectangles can be packed in this bin
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best_rect = self._sorted_rect[best_rect_key]
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del self._sorted_rect[best_rect_key]
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PackerBNFMixin.add_rect(self, *best_rect)
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# Packer factory
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class Enum(tuple):
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__getattr__ = tuple.index
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PackingMode = Enum(["Online", "Offline"])
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PackingBin = Enum(["BNF", "BFF", "BBF", "Global"])
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def newPacker(mode=PackingMode.Offline,
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bin_algo=PackingBin.BBF,
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pack_algo=MaxRectsBssf,
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sort_algo=SORT_AREA,
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rotation=True):
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"""
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Packer factory helper function
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Arguments:
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mode (PackingMode): Packing mode
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Online: Rectangles are packed as soon are they are added
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Offline: Rectangles aren't packed untils pack() is called
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bin_algo (PackingBin): Bin selection heuristic
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pack_algo (PackingAlgorithm): Algorithm used
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rotation (boolean): Enable or disable rectangle rotation.
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Returns:
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Packer: Initialized packer instance.
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"""
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packer_class = None
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# Online Mode
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if mode == PackingMode.Online:
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sort_algo=None
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if bin_algo == PackingBin.BNF:
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packer_class = PackerOnlineBNF
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elif bin_algo == PackingBin.BFF:
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packer_class = PackerOnlineBFF
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elif bin_algo == PackingBin.BBF:
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packer_class = PackerOnlineBBF
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else:
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raise AttributeError("Unsupported bin selection heuristic")
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# Offline Mode
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elif mode == PackingMode.Offline:
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if bin_algo == PackingBin.BNF:
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packer_class = PackerBNF
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elif bin_algo == PackingBin.BFF:
|
|
packer_class = PackerBFF
|
|
elif bin_algo == PackingBin.BBF:
|
|
packer_class = PackerBBF
|
|
elif bin_algo == PackingBin.Global:
|
|
packer_class = PackerGlobal
|
|
sort_algo=None
|
|
else:
|
|
raise AttributeError("Unsupported bin selection heuristic")
|
|
|
|
else:
|
|
raise AttributeError("Unknown packing mode.")
|
|
|
|
if sort_algo:
|
|
return packer_class(pack_algo=pack_algo, sort_algo=sort_algo,
|
|
rotation=rotation)
|
|
else:
|
|
return packer_class(pack_algo=pack_algo, rotation=rotation)
|
|
|
|
|