import math
from numbers import Number
-from typing import Generic, Iterable, List, Optional, Tuple, TypeVar
+from typing import Dict, Generic, Iterable, List, Optional, Tuple, TypeVar
-from math_utils import RunningMedian
-from text_utils import bar_graph
-
-
-T = TypeVar("T", bound=Number)
+T = TypeVar("T", int, float)
+Bound = int
+Count = int
class SimpleHistogram(Generic[T]):
-
# Useful in defining wide open bottom/top bucket bounds:
POSITIVE_INFINITY = math.inf
NEGATIVE_INFINITY = -math.inf
- def __init__(self, buckets: List[Tuple[T, T]]):
- self.buckets = {}
+ def __init__(self, buckets: List[Tuple[Bound, Bound]]):
+ from math_utils import RunningMedian
+
+ self.buckets: Dict[Tuple[Bound, Bound], Count] = {}
for start_end in buckets:
if self._get_bucket(start_end[0]) is not None:
raise Exception("Buckets overlap?!")
self.buckets[start_end] = 0
- self.sigma = 0
- self.median = RunningMedian()
- self.maximum = None
- self.minimum = None
- self.count = 0
+ self.sigma: float = 0.0
+ self.median: RunningMedian = RunningMedian()
+ self.maximum: Optional[T] = None
+ self.minimum: Optional[T] = None
+ self.count: Count = 0
@staticmethod
def n_evenly_spaced_buckets(
- min_bound: T,
- max_bound: T,
- n: int,
- ) -> List[Tuple[T, T]]:
- ret = []
+ min_bound: T,
+ max_bound: T,
+ n: int,
+ ) -> List[Tuple[int, int]]:
+ ret: List[Tuple[int, int]] = []
stride = int((max_bound - min_bound) / n)
if stride <= 0:
raise Exception("Min must be < Max")
- for bucket_start in range(min_bound, max_bound, stride):
+ imax = math.ceil(max_bound)
+ imin = math.floor(min_bound)
+ for bucket_start in range(imin, imax, stride):
ret.append((bucket_start, bucket_start + stride))
return ret
- def _get_bucket(self, item: T) -> Optional[Tuple[T, T]]:
+ def _get_bucket(self, item: T) -> Optional[Tuple[int, int]]:
for start_end in self.buckets:
if start_end[0] <= item < start_end[1]:
return start_end
all_true = all_true and self.add_item(item)
return all_true
- def __repr__(self) -> str:
+ def __repr__(self, *, width: int = 80, label_formatter: str = '%d') -> str:
+ from text_utils import bar_graph
+
+ txt = ""
max_population: Optional[int] = None
for bucket in self.buckets:
pop = self.buckets[bucket]
if pop > 0:
- last_bucket_start = bucket[0]
+ last_bucket_start = bucket[0] # beginning of range
if max_population is None or pop > max_population:
- max_population = pop
- txt = ""
+ max_population = pop # bucket with max items
if max_population is None:
return txt
- for bucket in sorted(self.buckets, key=lambda x : x[0]):
- pop = self.buckets[bucket]
+ max_label_width: Optional[int] = None
+ lowest_start: Optional[int] = None
+ highest_end: Optional[int] = None
+ for bucket in sorted(self.buckets, key=lambda x: x[0]):
start = bucket[0]
+ if lowest_start is None:
+ lowest_start = start
end = bucket[1]
+ if highest_end is None or end > highest_end:
+ highest_end = end
+ label = f'[{label_formatter}..{label_formatter}): ' % (start, end)
+ label_width = len(label)
+ if max_label_width is None or label_width > max_label_width:
+ max_label_width = label_width
+ if start == last_bucket_start:
+ break
+ assert max_label_width
+ assert lowest_start
+ assert highest_end
+
+ sigma_label = f'[{label_formatter}..{label_formatter}): ' % (
+ lowest_start,
+ highest_end,
+ )
+ if len(sigma_label) > max_label_width:
+ max_label_width = len(sigma_label)
+ bar_width = width - (max_label_width + 16)
+
+ for bucket in sorted(self.buckets, key=lambda x: x[0]):
+ start = bucket[0]
+ end = bucket[1]
+ label = f'[{label_formatter}..{label_formatter}): ' % (start, end)
+ pop = self.buckets[bucket]
bar = bar_graph(
(pop / max_population),
- include_text = False,
- width = 70,
- left_end = "",
- right_end = "")
- label = f'{start}..{end}'
- txt += f'{label:12}: ' + bar + f"({pop}) ({len(bar)})\n"
+ include_text=False,
+ width=bar_width,
+ left_end="",
+ right_end="",
+ )
+ txt += label.rjust(max_label_width)
+ txt += bar
+ txt += f"({pop/self.count*100.0:5.2f}% n={pop})\n"
if start == last_bucket_start:
break
-
- txt = txt + f'''{self.count} item(s)
-{self.maximum} max
-{self.minimum} min
-{self.sigma/self.count:.3f} mean
-{self.median.get_median()} median'''
+ txt += '-' * width + '\n'
+ txt += sigma_label.rjust(max_label_width)
+ txt += ' ' * (bar_width - 2)
+ txt += f'Σ=(100.00% n={self.count})\n'
return txt