9978389681

Committed 17 Jul 2024 05:02PM UTC coverage: 84.772% (-0.2%) from 84.929%

Build # 9978389681

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peekxc

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v0.3.2

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67.24

/src/splex/generics.py

## --- GENERICS --- 
import numpy as np 
import itertools as it
from numbers import Integral
from more_itertools import unique_everseen
from collections.abc import Collection

from .meta import _data_attributes
from .predicates import *

def zip_data(g: Iterable[SimplexConvertible], data: Union[bool, dict, str]) -> Iterable:
  """Converts an iterable of data-attributed simplex-like objects into a sequence of tuples (s, s_data).
  
  This function decouples data attributes (stored in __slots__ or __dict__) from an iterable of simplex-like objects
  via a zip operation, remapping key-value pairs to an dictionary per simplex. 
  """
  if isinstance(data, bool):
    if data == False: 
      yield from g
    for el in g: 
      yield (el, { attr_name : getattr(el, attr_name) for attr_name in _data_attributes(el) })
    # return zip(g, (extract_data(e) for e in g))
  elif isinstance(data, str):
    for el in g: 
      yield el, getattr(el, data) if hasattr(el, data) else None
  elif isinstance(data, Collection):
    yield from zip(g, data)
  else: 
    raise ValueError(f"Invalid data input of type '{type(data)}'")

def dim(s: Union[SimplexConvertible, ComplexLike], **kwargs) -> int:
  """Returns the dimension of a simplicial object.
  
  If _s_ has an existing method _s.dim(...)_, then that method is called with additional keyword arguments _kwargs_.

  Otherwise, the behavior of this function depends on the type-class of _s_. Namely, 
  - if _s_ is SimplexLike with dimension _p_, then _p_ is returned. 
  - if _s_ is ComplexLike, then the largest dimension _p_ of any face in _s_ is returned.
  - if _s_ is none of the above but is Sized, len(_s_) - 1 is returned. 
  """
  if hasattr(s, "dim"):
    return s.dim(**kwargs)
  else:
    if is_complex_like(s):
      return max((dim(s, **kwargs) for s in s))
    else: 
      return len(s) - 1

def boundary(s: Union[SimplexConvertible, ComplexLike], p: int = None, oriented: bool = False, **kwargs) -> Iterable['SimplexConvertible']:
  """
  Returns the boundary of a simplicial object, optionally signed.

  If _s_ has an existing method _s.boundary(p, oriented)_, then that method is called with additional keyword args _kwargs_.

  Otherwise, the behavior of this function depends on the type-class of _s_. Namely, 
  - if _s_ is SimplexLike with dimension _p_, then a generator enumerating _(p-1)_-faces of _s_ is created. 
  - if _s_ is ComplexLike, then a sparse boundary matrix whose columns represent boundary chains is returned. 
  - if _s_ is FiltrationLike, then a sparse boundary matrix whose columns represent boundary chains in filtration order is returned.
  - if _s_ is none of the above but is Sized and Iterable, all len(s)-1 combinations are returned of _s_ are returned. 

  TODO: finish this
  """
  if hasattr(s, "boundary"):
    kwargs |= dict(p=p, oriented=oriented)
    return s.boundary(**kwargs)
  return combinations(s, len(s)-1)

## NOTE: Returning an *Iterable* instead of an *Iterator* is preferred, as it allows containers to 
## return lazy- or eager-proxy objects, e.g. tree iterators or entire numpy arrays 
def faces(s: Union[SimplexConvertible, ComplexLike], p: int = None, data: bool = False, **kwargs) -> Iterable[Union[SimplexConvertible, PropertySimplexConvertible]]:
  """
  Returns the faces of a simplicial object, optionally restricted by dimension.

  If _s_ has an existing method _s.faces(p)_, then that method is called with additional keyword arguments _kwargs_. 
  
  Otherwise, the behavior of this function depends on the type-class of _s_. Namely, 
  - if _s_ is SimplexLike, then a generator enumerating _p_-combinations of _s_ is returned. 
  - if _s_ is ComplexLike, then a generator enumerating _p_-faces of _s_ (in any order) is returned. 
  - if _s_ is FiltrationLike, then a generator enumerating _p_-faces of _s_ in filtration order is returned.
  - if _s_ is none of the above but is Sized and Iterable, all combinations of _s_ of length _p+1_ are chained and returned. 
  """
  kwargs |= dict(p=p, data=data)
  if hasattr(s, "faces"):
    return s.faces(**kwargs)
  elif is_complex_like(s):
    return unique_everseen(it.chain.from_iterable([faces(f, **kwargs) for f in s])) # handles data implicitly, though faces may not store data
    # if p is None:
    #   g = iter(sset)
    # else: 
    #   g = iter(filter(lambda s: len(s) == p+1, iter(sset)))
  elif is_filtration_like(s):
    if not data:
      return (f for i,f in s)
    else:
      return ((f, dict(index=i)) for i,f in s)
  elif is_simplex_like(s): # is simplex convertible
    k = len(s)
    if p is None:
      g = it.chain.from_iterable([combinations(s, k-i) for i in reversed(range(0, k))])
    else:
      assert isinstance(p, Integral), f"Invalid type {type(p)}; dimension 'p' must be integral type"
      g = iter(combinations(s, p+1))
    return zip_data(g, data)
  else:
    raise ValueError(f"Unknown type supplied '{type(s)}'")

def card(s: Union[SimplexConvertible, ComplexLike, FiltrationLike], p: int = None, **kwargs):
  """Counts the number of _p_-dimensional simplices of a simplicial object _s_. 
  
  If _s_ has an existing method _s.card(p)_, then that method is called with additional keyword arguments _kwargs_. 

  Otherwise, the behavior of this function depends on the type-class of _s_ and whether _p_ is specified. Namely, 
   - If _s_ is _complex like_, then card(s) returns a tuple containing the number of simplices in _s_ in each dimension, and _card(s, p)_ the number of simplices in _s_ with dimension p.
  """
  if hasattr(s, "card"):
    kwargs |= dict(p=p)
    return s.card(**kwargs)
  else:
    if p is None: 
      from collections import Counter
      cc = Counter([dim(s, **kwargs) for s in faces(s, p, **kwargs)])
      return tuple(cc.values())
    else: 
      assert isinstance(p, int)
      return int(sum([1 for s in faces(s, p, **kwargs) if dim(s, **kwargs) == p]))
    

1	## --- GENERICS ---
2	import numpy as np	3✔
3	import itertools as it	3✔
4	from numbers import Integral	3✔
5	from more_itertools import unique_everseen	3✔
6	from collections.abc import Collection	3✔
7
8	from .meta import _data_attributes	3✔
9	from .predicates import *	3✔
10
11	def zip_data(g: Iterable[SimplexConvertible], data: Union[bool, dict, str]) -> Iterable:	3✔
12	"""Converts an iterable of data-attributed simplex-like objects into a sequence of tuples (s, s_data).
13
14	This function decouples data attributes (stored in __slots__ or __dict__) from an iterable of simplex-like objects
15	via a zip operation, remapping key-value pairs to an dictionary per simplex.
16	"""
17	if isinstance(data, bool):	3✔
18	if data == False:	3✔
19	yield from g	3✔
20	for el in g:	3✔
21	yield (el, { attr_name : getattr(el, attr_name) for attr_name in _data_attributes(el) })	3✔
22	# return zip(g, (extract_data(e) for e in g))
UNCOV 23	elif isinstance(data, str):	×
24	for el in g:	×
25	yield el, getattr(el, data) if hasattr(el, data) else None	×
NEW 26	elif isinstance(data, Collection):	×
NEW 27	yield from zip(g, data)	×
28	else:
UNCOV 29	raise ValueError(f"Invalid data input of type '{type(data)}'")	×
30
31	def dim(s: Union[SimplexConvertible, ComplexLike], **kwargs) -> int:	3✔
32	"""Returns the dimension of a simplicial object.
33
34	If _s_ has an existing method _s.dim(...)_, then that method is called with additional keyword arguments _kwargs_.
35
36	Otherwise, the behavior of this function depends on the type-class of _s_. Namely,
37	- if _s_ is SimplexLike with dimension _p_, then _p_ is returned.
38	- if _s_ is ComplexLike, then the largest dimension _p_ of any face in _s_ is returned.
39	- if _s_ is none of the above but is Sized, len(_s_) - 1 is returned.
40	"""
41	if hasattr(s, "dim"):	3✔
42	return s.dim(**kwargs)	3✔
43	else:
44	if is_complex_like(s):	3✔
UNCOV 45	return max((dim(s, **kwargs) for s in s))	×
46	else:
47	return len(s) - 1	3✔
48
49	def boundary(s: Union[SimplexConvertible, ComplexLike], p: int = None, oriented: bool = False, **kwargs) -> Iterable['SimplexConvertible']:	3✔
50	"""
51	Returns the boundary of a simplicial object, optionally signed.
52
53	If _s_ has an existing method _s.boundary(p, oriented)_, then that method is called with additional keyword args _kwargs_.
54
55	Otherwise, the behavior of this function depends on the type-class of _s_. Namely,
56	- if _s_ is SimplexLike with dimension _p_, then a generator enumerating _(p-1)_-faces of _s_ is created.
57	- if _s_ is ComplexLike, then a sparse boundary matrix whose columns represent boundary chains is returned.
58	- if _s_ is FiltrationLike, then a sparse boundary matrix whose columns represent boundary chains in filtration order is returned.
59	- if _s_ is none of the above but is Sized and Iterable, all len(s)-1 combinations are returned of _s_ are returned.
60
61	TODO: finish this
62	"""
UNCOV 63	if hasattr(s, "boundary"):	×
64	kwargs \|= dict(p=p, oriented=oriented)	×
65	return s.boundary(**kwargs)	×
66	return combinations(s, len(s)-1)	×
67
68	## NOTE: Returning an Iterable instead of an Iterator is preferred, as it allows containers to
69	## return lazy- or eager-proxy objects, e.g. tree iterators or entire numpy arrays
70	def faces(s: Union[SimplexConvertible, ComplexLike], p: int = None, data: bool = False, **kwargs) -> Iterable[Union[SimplexConvertible, PropertySimplexConvertible]]:	3✔
71	"""
72	Returns the faces of a simplicial object, optionally restricted by dimension.
73
74	If _s_ has an existing method _s.faces(p)_, then that method is called with additional keyword arguments _kwargs_.
75
76	Otherwise, the behavior of this function depends on the type-class of _s_. Namely,
77	- if _s_ is SimplexLike, then a generator enumerating _p_-combinations of _s_ is returned.
78	- if _s_ is ComplexLike, then a generator enumerating _p_-faces of _s_ (in any order) is returned.
79	- if _s_ is FiltrationLike, then a generator enumerating _p_-faces of _s_ in filtration order is returned.
80	- if _s_ is none of the above but is Sized and Iterable, all combinations of _s_ of length _p+1_ are chained and returned.
81	"""
82	kwargs \|= dict(p=p, data=data)	3✔
83	if hasattr(s, "faces"):	3✔
84	return s.faces(**kwargs)	3✔
85	elif is_complex_like(s):	3✔
86	return unique_everseen(it.chain.from_iterable([faces(f, **kwargs) for f in s])) # handles data implicitly, though faces may not store data	3✔
87	# if p is None:
88	# g = iter(sset)
89	# else:
90	# g = iter(filter(lambda s: len(s) == p+1, iter(sset)))
91	elif is_filtration_like(s):	3✔
UNCOV 92	if not data:	×
93	return (f for i,f in s)	×
94	else:
UNCOV 95	return ((f, dict(index=i)) for i,f in s)	×
96	elif is_simplex_like(s): # is simplex convertible	3✔
97	k = len(s)	3✔
98	if p is None:	3✔
99	g = it.chain.from_iterable([combinations(s, k-i) for i in reversed(range(0, k))])	3✔
100	else:
UNCOV 101	assert isinstance(p, Integral), f"Invalid type {type(p)}; dimension 'p' must be integral type"	×
102	g = iter(combinations(s, p+1))	×
103	return zip_data(g, data)	3✔
104	else:
UNCOV 105	raise ValueError(f"Unknown type supplied '{type(s)}'")	×
106
107	def card(s: Union[SimplexConvertible, ComplexLike, FiltrationLike], p: int = None, **kwargs):	3✔
108	"""Counts the number of _p_-dimensional simplices of a simplicial object _s_.
109
110	If _s_ has an existing method _s.card(p)_, then that method is called with additional keyword arguments _kwargs_.
111
112	Otherwise, the behavior of this function depends on the type-class of _s_ and whether _p_ is specified. Namely,
113	- If _s_ is _complex like_, then card(s) returns a tuple containing the number of simplices in _s_ in each dimension, and _card(s, p)_ the number of simplices in _s_ with dimension p.
114	"""
115	if hasattr(s, "card"):	3✔
116	kwargs \|= dict(p=p)	3✔
117	return s.card(**kwargs)	3✔
118	else:
119	if p is None:	3✔
120	from collections import Counter	3✔
121	cc = Counter([dim(s, kwargs) for s in faces(s, p, kwargs)])	3✔
122	return tuple(cc.values())	3✔
123	else:
UNCOV 124	assert isinstance(p, int)	×
UNCOV 125	return int(sum([1 for s in faces(s, p, kwargs) if dim(s, kwargs) == p]))	×
126

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