def test_vol_nbin(nums):
inputs = nums
bin_cls = NumberBin
a = Fit.fit(bin_cls, 9, inputs)
expected = [bin_cls(9) for _ in range(5)]
expected[0].append(inputs[0])
expected[1].append(inputs[1])
expected[1].append(inputs[5])
expected[1].append(inputs[6])
expected[2].append(inputs[2])
expected[3].append(inputs[3])
expected[4].append(inputs[4])
assert (bin_sorter(a.bins) == bin_sorter(tuple(expected)))
def test_vol_nbin(nums):
inputs = nums
bin_cls = NumberBin
a = Fit.fit(bin_cls, 9, inputs)
expected = [bin_cls(9) for _ in range(5)]
expected[0].append(inputs[0])
expected[1].append(inputs[1])
expected[1].append(inputs[5])
expected[1].append(inputs[6])
expected[2].append(inputs[2])
expected[3].append(inputs[3])
expected[4].append(inputs[4])
assert (bin_sorter(a.bins) == bin_sorter(tuple(expected)))
def test_sort_sbin(chars, bin_size):
inputs = chars
bin_cls = SimpleBin
a = Fit.fit(bin_cls, bin_size, inputs, sort=True, sort_reversed=False)
expected = [bin_cls(bin_size) for _ in range(5)]
expected[0].append(inputs[6])
expected[0].append(inputs[5])
expected[0].append(inputs[1])
expected[1].append(inputs[2])
expected[2].append(inputs[4])
expected[3].append(inputs[3])
expected[4].append(inputs[0])
assert (bin_sorter(a.bins) == bin_sorter(tuple(expected)))
def test_wfd_sbin(chars, bin_size):
inputs = chars
bin_cls = SimpleBin
a = Fit.wfd(bin_cls, bin_size, inputs)
expected = [bin_cls(bin_size) for _ in range(5)]
expected[0].append(inputs[0])
expected[1].append(inputs[3])
expected[2].append(inputs[4])
expected[3].append(inputs[2])
expected[3].append(inputs[6])
expected[4].append(inputs[1])
expected[4].append(inputs[5])
assert (bin_sorter(a.bins) == bin_sorter(tuple(expected)))
def test_sort_rev_nbin(nums, bin_size):
inputs = nums
bin_cls = NumberBin
a = Fit.fit(bin_cls, bin_size, inputs, sort=True)
expected = [bin_cls(bin_size) for _ in range(5)]
expected[0].append(inputs[0])
expected[0].append(inputs[6])
expected[1].append(inputs[3])
expected[2].append(inputs[4])
expected[2].append(inputs[5])
expected[3].append(inputs[2])
expected[4].append(inputs[1])
assert (bin_sorter(a.bins) == bin_sorter(tuple(expected)))
def test_bin_order_worst_nbin(nums, bin_size):
inputs = nums
bin_cls = NumberBin
a = Fit.fit(bin_cls, bin_size, inputs, bin_sort=BinOrdering.worst_fit)
expected = [bin_cls(bin_size) for _ in range(5)]
expected[0].append(inputs[0])
expected[1].append(inputs[1])
expected[1].append(inputs[5])
expected[2].append(inputs[2])
expected[2].append(inputs[6])
expected[3].append(inputs[3])
expected[4].append(inputs[4])
assert (bin_sorter(a.bins) == bin_sorter(tuple(expected)))
def test_ffd_nbin(nums, bin_size):
inputs = nums
bin_cls = NumberBin
a = Fit.ffd(bin_cls, bin_size, inputs)
expected = [bin_cls(bin_size) for _ in range(5)]
expected[0].append(inputs[0])
expected[0].append(inputs[6])
expected[1].append(inputs[3])
expected[2].append(inputs[4])
expected[2].append(inputs[5])
expected[3].append(inputs[2])
expected[4].append(inputs[1])
assert (bin_sorter(a.bins) == bin_sorter(tuple(expected)) and a.method == "First Fit Decreasing (FFD)")
def test_sort_rev_nbin(nums, bin_size):
inputs = nums
bin_cls = NumberBin
a = Fit.fit(bin_cls, bin_size, inputs, sort=True)
expected = [bin_cls(bin_size) for _ in range(5)]
expected[0].append(inputs[0])
expected[0].append(inputs[6])
expected[1].append(inputs[3])
expected[2].append(inputs[4])
expected[2].append(inputs[5])
expected[3].append(inputs[2])
expected[4].append(inputs[1])
assert (bin_sorter(a.bins) == bin_sorter(tuple(expected)))
def test_sort_sbin(chars, bin_size):
inputs = chars
bin_cls = SimpleBin
a = Fit.fit(bin_cls, bin_size, inputs, sort=True, sort_reversed=False)
expected = [bin_cls(bin_size) for _ in range(5)]
expected[0].append(inputs[6])
expected[0].append(inputs[5])
expected[0].append(inputs[1])
expected[1].append(inputs[2])
expected[2].append(inputs[4])
expected[3].append(inputs[3])
expected[4].append(inputs[0])
assert (bin_sorter(a.bins) == bin_sorter(tuple(expected)))
def test_bin_order_best_sbin(chars, bin_size):
inputs = chars
bin_cls = SimpleBin
a = Fit.fit(bin_cls, bin_size, inputs, bin_sort=BinOrdering.best_fit)
expected = [bin_cls(bin_size) for _ in range(5)]
expected[0].append(inputs[0])
expected[0].append(inputs[6])
expected[1].append(inputs[1])
expected[2].append(inputs[2])
expected[3].append(inputs[3])
expected[4].append(inputs[4])
expected[4].append(inputs[5])
assert (bin_sorter(a.bins) == bin_sorter(tuple(expected)))
def test_bin_order_worst_nbin(nums, bin_size):
inputs = nums
bin_cls = NumberBin
a = Fit.fit(bin_cls, bin_size, inputs, bin_sort=BinOrdering.worst_fit)
expected = [bin_cls(bin_size) for _ in range(5)]
expected[0].append(inputs[0])
expected[1].append(inputs[1])
expected[1].append(inputs[5])
expected[2].append(inputs[2])
expected[2].append(inputs[6])
expected[3].append(inputs[3])
expected[4].append(inputs[4])
assert (bin_sorter(a.bins) == bin_sorter(tuple(expected)))
def test_ff_sbin(chars, bin_size):
inputs = chars
bin_cls = SimpleBin
a = Fit.ff(bin_cls, bin_size, inputs)
expected = [bin_cls(bin_size) for _ in range(5)]
expected[0].append(inputs[0])
expected[0].append(inputs[6])
expected[1].append(inputs[1])
expected[1].append(inputs[5])
expected[2].append(inputs[2])
expected[3].append(inputs[3])
expected[4].append(inputs[4])
assert (bin_sorter(a.bins) == bin_sorter(tuple(expected)) and a.method == "First Fit (FF)")
def test_wfd_sbin(chars, bin_size):
inputs = chars
bin_cls = SimpleBin
a = Fit.wfd(bin_cls, bin_size, inputs)
expected = [bin_cls(bin_size) for _ in range(5)]
expected[0].append(inputs[0])
expected[1].append(inputs[3])
expected[2].append(inputs[4])
expected[3].append(inputs[2])
expected[3].append(inputs[6])
expected[4].append(inputs[1])
expected[4].append(inputs[5])
assert (bin_sorter(a.bins) == bin_sorter(tuple(expected)))
def test_bin_order_best_sbin(chars, bin_size):
inputs = chars
bin_cls = SimpleBin
a = Fit.fit(bin_cls, bin_size, inputs, bin_sort=BinOrdering.best_fit)
expected = [bin_cls(bin_size) for _ in range(5)]
expected[0].append(inputs[0])
expected[0].append(inputs[6])
expected[1].append(inputs[1])
expected[2].append(inputs[2])
expected[3].append(inputs[3])
expected[4].append(inputs[4])
expected[4].append(inputs[5])
assert (bin_sorter(a.bins) == bin_sorter(tuple(expected)))
def test_nf_nbin(nums, bin_size):
inputs = nums
bin_cls = NumberBin
a = Fit.nf(bin_cls, bin_size, inputs)
expected = [bin_cls(bin_size) for _ in range(6)]
expected[0].append(inputs[0])
expected[1].append(inputs[1])
expected[2].append(inputs[2])
expected[3].append(inputs[3])
expected[4].append(inputs[4])
expected[4].append(inputs[5])
expected[5].append(inputs[6])
assert (bin_sorter(a.bins) == bin_sorter(tuple(expected)) and a.method == "Next Fit (NF)")
def test_nf_nbin(nums, bin_size):
inputs = nums
bin_cls = NumberBin
a = Fit.nf(bin_cls, bin_size, inputs)
expected = [bin_cls(bin_size) for _ in range(6)]
expected[0].append(inputs[0])
expected[1].append(inputs[1])
expected[2].append(inputs[2])
expected[3].append(inputs[3])
expected[4].append(inputs[4])
expected[4].append(inputs[5])
expected[5].append(inputs[6])
assert (bin_sorter(a.bins) == bin_sorter(tuple(expected))
and a.method == "Next Fit (NF)")
def test_ffd_nbin(nums, bin_size):
inputs = nums
bin_cls = NumberBin
a = Fit.ffd(bin_cls, bin_size, inputs)
expected = [bin_cls(bin_size) for _ in range(5)]
expected[0].append(inputs[0])
expected[0].append(inputs[6])
expected[1].append(inputs[3])
expected[2].append(inputs[4])
expected[2].append(inputs[5])
expected[3].append(inputs[2])
expected[4].append(inputs[1])
assert (bin_sorter(a.bins) == bin_sorter(tuple(expected))
and a.method == "First Fit Decreasing (FFD)")
def test_ff_sbin(chars, bin_size):
inputs = chars
bin_cls = SimpleBin
a = Fit.ff(bin_cls, bin_size, inputs)
expected = [bin_cls(bin_size) for _ in range(5)]
expected[0].append(inputs[0])
expected[0].append(inputs[6])
expected[1].append(inputs[1])
expected[1].append(inputs[5])
expected[2].append(inputs[2])
expected[3].append(inputs[3])
expected[4].append(inputs[4])
assert (bin_sorter(a.bins) == bin_sorter(tuple(expected))
and a.method == "First Fit (FF)")
def test_meth_name(bin_size):
bin_cls = SimpleBin
a = Fit.fit(bin_cls, bin_size, [], method_name="TESTING")
assert (a.method == "TESTING")
def test_start_bins_lt_one(bin_size):
a = Fit.fit(SimpleBin, bin_size, [], starting_bins=-1)
assert (a.bins == tuple([SimpleBin(bin_size)]))
def test_start(bin_size):
a = Fit.fit(SimpleBin, bin_size, [], starting_bins=2)
assert (a.bins == tuple([SimpleBin(bin_size), SimpleBin(bin_size)]))
def test_start_bins_lt_one(bin_size):
a = Fit.fit(SimpleBin, bin_size, [], starting_bins=-1)
assert (a.bins == tuple([SimpleBin(bin_size)]))
def test_replace_blank():
assert (Fit._replace_method_code(None) == "Custom")
def test_replace_blank():
assert (Fit._replace_method_code(None) == "Custom")
def test_meth_name(bin_size):
bin_cls = SimpleBin
a = Fit.fit(bin_cls, bin_size, [], method_name="TESTING")
assert (a.method == "TESTING")
def test_starting_bins_gt_max_bins(bin_size):
inputs = []
bin_cls = SimpleBin
a = Fit.fit(bin_cls, bin_size, inputs, starting_bins=10, max_open_bins=3)
assert (a.total_bins == 3)
def basic(request):
return Fit.ffd(SimpleBin, 5, "a ab d c w xx z".split())
def test_detect_method_variant():
assert (Fit._detect_method(False, False, 1, BinOrdering.best_fit,
None) == Fit._replace_method_code("bfv"))
def test_start(bin_size):
a = Fit.fit(SimpleBin, bin_size, [], starting_bins=2)
assert (a.bins == tuple([SimpleBin(bin_size), SimpleBin(bin_size)]))
def test_detect_method_variant():
assert (Fit._detect_method(False, False, 1, BinOrdering.best_fit, None) == Fit._replace_method_code("bfv"))
def basic(request):
return Fit.ffd(SimpleBin, 5, "a ab d c w xx z".split())
def test_starting_bins_gt_max_bins(bin_size):
inputs = []
bin_cls = SimpleBin
a = Fit.fit(bin_cls, bin_size, inputs, starting_bins=10, max_open_bins=3)
assert (a.total_bins == 3)
def test_repr():
a = Fit.fit(SimpleBin,1,[])
assert(a.__repr__() == "<BPResult (Total Bins: 1, Total Volume: 1, Unused Volume: 1)>")
# bin_size = random.randint(10,100)
# fit_these = [random.randint(1, bin_size) for _ in range(1000)]
# print(fit_these)
bin_size = 80
fit_these = [
26, 57, 18, 8, 45, 16, 22, 29, 5, 11, 8, 27, 54, 13, 17, 21, 63, 14, 16,
45, 6, 32, 57, 24, 18, 27, 54, 35, 12, 43, 36, 72, 14, 28, 3, 11, 46, 27,
42, 59, 26, 41, 15, 41, 68
]
# print(fit_these)
# generic_results = Fit.fit(NumberBin, bin_size, fit_these)
next_fit_results = Fit.nf(NumberBin, bin_size, fit_these)
first_fit_results = Fit.ff(NumberBin, bin_size, fit_these)
worst_fit_result = Fit.wf(NumberBin, bin_size, fit_these)
best_fit_result = Fit.bf(NumberBin, bin_size, fit_these)
# sorted_next_fit_results = Fit.nfd(NumberBin, bin_size, fit_these) # not implemented
sorted_first_fit_results = Fit.ffd(NumberBin, bin_size, fit_these)
sorted_worst_fit_result = Fit.wfd(NumberBin, bin_size, fit_these)
sorted_best_fit_result = Fit.bfd(NumberBin, bin_size, fit_these)
print_result("Next Fit", next_fit_results)
print_result("First Fit", first_fit_results)
print_result("Worst Fit", worst_fit_result)
print_result("Best Fit", best_fit_result)
# print_result("Next Fit With Sort", next_fit_results) # not implemented
def test_repr():
a = Fit.fit(SimpleBin, 1, [])
assert (a.__repr__() ==
"<BPResult (Total Bins: 1, Total Volume: 1, Unused Volume: 1)>")
