def main() -> None:
"""The big enchilada."""
blocks = []
args = parse_args(sys.argv[1:])
number_of_backwards_trends = 0
for _ in range(args.trials):
# generate a random *single* trend of length args.length
seq = random_block(args.length, random.gauss, 0, 1)
blocks = decompose_into_blocks(seq)
block = rotate_to_single_block(blocks)[0]
# and decompose it in the opposite direction
reverse_blocks = decompose_into_blocks(block, decreasing_trend)
number_of_backwards_trends += len(reverse_blocks)
if args.verbose:
print(f"seq: {seq}")
print(f"blocks: {blocks}")
print(f"trend: {block}")
print(f"backwards trends: {reverse_blocks}")
if args.verbose:
print(
f"length: {args.length}, "
f" mean backwards trends: {number_of_backwards_trends/args.trials:2.2f}"
)
else:
print(f"{number_of_backwards_trends/args.trials:2.2f}")
def main():
"""The big enchilada."""
args = parse_args(sys.argv[1:])
cumulative_numbreaks = 0
for _ in range(args.trials):
seq = random_block(args.length, random.gauss, 0, 1)
blocks = decompose_into_blocks(seq)
cumulative_numbreaks += (
len(blocks) - 1) # blocks are the fence, breaks the fenceposts
header = "average number of breaks:\t" if args.verbose else ""
print(f"{header}{cumulative_numbreaks/args.trials}")
def main():
"""The big enchilada."""
args = parse_args(sys.argv[1:])
length = args.length
trials = args.trials
numbreaks_dict = (
{}
) # numbreaks_dict{3} is the number of trials that produced 3 breaks (4 blocks)
# -- useful for graphing
numbreaks_list = (
[]
) # numbreaks_list[3] is the number of breaks produced in the fourth trial
# -- useful for statistics
for _ in range(trials):
seq = random_block(length, random.gauss, 0, 1)
blocks = decompose_into_blocks(seq)
numbreaks = len(blocks) - 1 # blocks the fences, breaks the fenceposts
numbreaks_list.append(numbreaks)
if numbreaks not in numbreaks_dict:
numbreaks_dict[numbreaks] = 0
numbreaks_dict[numbreaks] += 1
if args.verbose:
try:
print(f"mode(# of breaks), {statistics.mode(numbreaks_list)}")
except Exception:
print("no single mode")
print(f"median(# of breaks), {statistics.median(numbreaks_list)}")
print(f"mean(# of breaks), {statistics.mean(numbreaks_list)}")
print(f"variance(# of breaks), {statistics.variance(numbreaks_list)}")
print(
"q ~ variance/mean = "
+ f"{statistics.variance(numbreaks_list)/statistics.mean(numbreaks_list)}"
)
if args.verbose:
print("\nnumber of breaks\t# of trials seen\n")
for key in sorted(numbreaks_dict.keys()):
print(f"{key:15}\t\t{numbreaks_dict[key]:10}")
def main() -> None:
"""The big enchilada."""
blocks = []
args = parse_args(sys.argv[1:])
for _ in range(args.trials):
seq = random_block(args.length, random.gauss, 0, 1)
blocks = decompose_into_blocks(seq)
nbreaks = len(blocks) - 1
initial_breaks = nbreaks
rotations = 0
while nbreaks:
block_sizes = [len(block) for block in blocks]
if args.verbose:
print(f"{nbreaks} | {block_sizes}")
blocks = rotate_blocks(blocks)
rotations += 1
nbreaks = len(blocks) - 1
block_sizes = [len(block) for block in blocks]
if args.verbose:
print(f"{nbreaks} | {block_sizes}")
print(f"initial breaks: {initial_breaks}\trotations: {rotations}")
else:
print(f"{initial_breaks}\t{rotations}")
def test_decompose_into_blocks() -> None:
"""Decomposes into blocks."""
seq = [1.0, 2.0, 3.0, 1.1]
blocks = decompose_into_blocks(seq)
assert [[1.0, 2.0, 3.0], [1.1]] == blocks
def main():
"""The big enchilada."""
args = parse_args(sys.argv[1:])
seq = random_block(args.length, random.gauss, 0, 1)
blocks = decompose_into_blocks(seq)
show_blocks(blocks, args.verbose)