#!/usr/bin/env python3
+# -*- coding: utf-8 -*-
+
+# © Copyright 2021-2022, Scott Gasch
+
+"""A text-based simple histogram helper class."""
import math
-from numbers import Number
+from dataclasses import dataclass
from typing import Dict, Generic, Iterable, List, Optional, Tuple, TypeVar
T = TypeVar("T", int, float)
Count = int
+@dataclass
+class BucketDetails:
+ """A collection of details about the internal histogram buckets."""
+
+ num_populated_buckets: int = 0
+ """Count of populated buckets"""
+
+ max_population: Optional[int] = None
+ """The max population in a bucket currently"""
+
+ last_bucket_start: Optional[int] = None
+ """The last bucket starting point"""
+
+ lowest_start: Optional[int] = None
+ """The lowest populated bucket's starting point"""
+
+ highest_end: Optional[int] = None
+ """The highest populated bucket's ending point"""
+
+ max_label_width: Optional[int] = None
+ """The maximum label width (for display purposes)"""
+
+
class SimpleHistogram(Generic[T]):
+ """A simple histogram."""
+
# Useful in defining wide open bottom/top bucket bounds:
POSITIVE_INFINITY = math.inf
NEGATIVE_INFINITY = -math.inf
def __init__(self, buckets: List[Tuple[Bound, Bound]]):
- from math_utils import RunningMedian
+ """C'tor.
+
+ Args:
+ buckets: a list of [start..end] tuples that define the
+ buckets we are counting population in. See also
+ :meth:`n_evenly_spaced_buckets` to generate these
+ buckets more easily.
+ """
+ from math_utils import NumericPopulation
self.buckets: Dict[Tuple[Bound, Bound], Count] = {}
for start_end in buckets:
raise Exception("Buckets overlap?!")
self.buckets[start_end] = 0
self.sigma: float = 0.0
- self.median: RunningMedian = RunningMedian()
+ self.stats: NumericPopulation = NumericPopulation()
self.maximum: Optional[T] = None
self.minimum: Optional[T] = None
self.count: Count = 0
max_bound: T,
n: int,
) -> List[Tuple[int, int]]:
+ """A helper method for generating the buckets argument to
+ our c'tor provided that you want N evenly spaced buckets.
+
+ Args:
+ min_bound: the minimum possible value
+ max_bound: the maximum possible value
+ n: how many buckets to create
+
+ Returns:
+ A list of bounds that define N evenly spaced buckets
+ """
ret: List[Tuple[int, int]] = []
stride = int((max_bound - min_bound) / n)
if stride <= 0:
return ret
def _get_bucket(self, item: T) -> Optional[Tuple[int, int]]:
+ """Given an item, what bucket is it in?"""
for start_end in self.buckets:
if start_end[0] <= item < start_end[1]:
return start_end
return None
def add_item(self, item: T) -> bool:
+ """Adds a single item to the histogram (reculting in us incrementing
+ the population in the correct bucket.
+
+ Args:
+ item: the item to be added
+
+ Returns:
+ True if the item was successfully added or False if the item
+ is not within the bounds established during class construction.
+ """
bucket = self._get_bucket(item)
if bucket is None:
return False
self.count += 1
self.buckets[bucket] += 1
self.sigma += item
- self.median.add_number(item)
+ self.stats.add_number(item)
if self.maximum is None or item > self.maximum:
self.maximum = item
if self.minimum is None or item < self.minimum:
return True
def add_items(self, lst: Iterable[T]) -> bool:
+ """Adds a collection of items to the histogram and increments
+ the correct bucket's population for each item.
+
+ Args:
+ lst: An iterable of items to be added
+
+ Returns:
+ True if all items were added successfully or False if any
+ item was not able to be added because it was not within the
+ bounds established at object construction.
+ """
all_true = True
for item in lst:
all_true = all_true and self.add_item(item)
return all_true
+ def _get_bucket_details(self, label_formatter: str) -> BucketDetails:
+ """Get the details about one bucket."""
+ details = BucketDetails()
+ for (start, end), pop in sorted(self.buckets.items(), key=lambda x: x[0]):
+ if pop > 0:
+ details.num_populated_buckets += 1
+ details.last_bucket_start = start
+ if details.max_population is None or pop > details.max_population:
+ details.max_population = pop
+ if details.lowest_start is None or start < details.lowest_start:
+ details.lowest_start = start
+ if details.highest_end is None or end > details.highest_end:
+ details.highest_end = end
+ label = f'[{label_formatter}..{label_formatter}): ' % (start, end)
+ label_width = len(label)
+ if details.max_label_width is None or label_width > details.max_label_width:
+ details.max_label_width = label_width
+ return details
+
def __repr__(self, *, width: int = 80, label_formatter: str = '%d') -> str:
+ """Returns a pretty (text) representation of the histogram and
+ some vital stats about the population in it (min, max, mean,
+ median, mode, stdev, etc...)
+ """
from text_utils import bar_graph
+ details = self._get_bucket_details(label_formatter)
txt = ""
- max_population: Optional[int] = None
- for bucket in self.buckets:
- pop = self.buckets[bucket]
- if pop > 0:
- last_bucket_start = bucket[0] # beginning of range
- if max_population is None or pop > max_population:
- max_population = pop # bucket with max items
- if len(self.buckets) == 0 or max_population is None:
+ if details.num_populated_buckets == 0:
return txt
-
- 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 is not None
- assert lowest_start is not None
- assert highest_end is not None
-
+ assert details.max_label_width is not None
+ assert details.lowest_start is not None
+ assert details.highest_end is not None
+ assert details.max_population is not None
sigma_label = f'[{label_formatter}..{label_formatter}): ' % (
- lowest_start,
- highest_end,
+ details.lowest_start,
+ details.highest_end,
)
- if len(sigma_label) > max_label_width:
- max_label_width = len(sigma_label)
- bar_width = width - (max_label_width + 16)
+ if len(sigma_label) > details.max_label_width:
+ details.max_label_width = len(sigma_label)
+ bar_width = width - (details.max_label_width + 17)
- for bucket in sorted(self.buckets, key=lambda x: x[0]):
- start = bucket[0]
- end = bucket[1]
+ for (start, end), pop in sorted(self.buckets.items(), key=lambda x: x[0]):
+ if start < details.lowest_start:
+ continue
label = f'[{label_formatter}..{label_formatter}): ' % (start, end)
- pop = self.buckets[bucket]
bar = bar_graph(
- (pop / max_population),
+ (pop / details.max_population),
include_text=False,
width=bar_width,
left_end="",
right_end="",
)
- txt += label.rjust(max_label_width)
+ txt += label.rjust(details.max_label_width)
txt += bar
txt += f"({pop/self.count*100.0:5.2f}% n={pop})\n"
- if start == last_bucket_start:
+ if start == details.last_bucket_start:
break
txt += '-' * width + '\n'
- txt += sigma_label.rjust(max_label_width)
+ txt += sigma_label.rjust(details.max_label_width)
txt += ' ' * (bar_width - 2)
- txt += f'Σ=(100.00% n={self.count})\n'
+ txt += f' pop(Σn)={self.count}\n'
+ txt += ' ' * (bar_width + details.max_label_width - 2)
+ txt += f' mean(x̄)={self.stats.get_mean():.3f}\n'
+ txt += ' ' * (bar_width + details.max_label_width - 2)
+ txt += f' median(p50)={self.stats.get_median():.3f}\n'
+ txt += ' ' * (bar_width + details.max_label_width - 2)
+ txt += f' mode(Mo)={self.stats.get_mode()[0]:.3f}\n'
+ txt += ' ' * (bar_width + details.max_label_width - 2)
+ txt += f' stdev(σ)={self.stats.get_stdev():.3f}\n'
+ txt += '\n'
return txt