o ˷eO@sLdZddlZddlZddlZddlmZmZddlmZm Z m Z ddl m Z m Z ddlZgdZddZd d Zd d Zda Miscellaneous Helpers for NetworkX. These are not imported into the base networkx namespace but can be accessed, for example, as >>> import networkx >>> networkx.utils.make_list_of_ints({1, 2, 3}) [1, 2, 3] >>> networkx.utils.arbitrary_element({5, 1, 7}) # doctest: +SKIP 1 N) defaultdictdeque)IterableIteratorSized)chaintee)is_string_likeiterableempty_generatorflattenmake_list_of_intsis_list_of_intsmake_strgenerate_unique_nodedefault_openerdict_to_numpy_arraydict_to_numpy_array1dict_to_numpy_array2 is_iteratorarbitrary_elementconsumepairwisegroupsto_tuplecreate_random_statecreate_py_random_statePythonRandomInterface nodes_equal edges_equal graphs_equalcCsd}t|tt|tS)zvCheck if obj is string. .. deprecated:: 2.6 This is deprecated and will be removed in NetworkX v3.0. zYis_string_like is deprecated and will be removed in 3.0.Use isinstance(obj, str) instead.)warningswarnDeprecationWarning isinstancestrobjmsgr)J/var/www/ideatree/venv/lib/python3.10/site-packages/networkx/utils/misc.pyr 8s  r cCs:d}t|tt|drdSzt|WdSYdS)zReturn True if obj is iterable with a well-defined len(). .. deprecated:: 2.6 This is deprecated and will be removed in NetworkX v3.0. ziterable is deprecated and will be removed in 3.0.Use isinstance(obj, (collections.abc.Iterable, collections.abc.Sized)) instead.__iter__TF)r!r"r#hasattrlenr&r)r)r*r Fs   r cCstdtdddDS)zAReturn a generator with no members. .. deprecated:: 2.6 z:empty_generator is deprecated and will be removed in v3.0.css|]}|VqdSNr)).0ir)r)r* bsz"empty_generator..r))r!r"r#r)r)r)r*r Zsr cCsht|ttfr t|tr|S|durg}|D]}t|ttfr$t|tr*||qt||qt|S)z>Return flattened version of (possibly nested) iterable object.N)r$rrr%appendr tuple)r'resultitemr)r)r*r es  r c Cst|ts5g}|D])}d|}zt|}Wn ty#t|dw||kr-t|||q |St|D]0\}}d|}t|trHq9zt|}Wn ty[t|dw||kret||||<q9|S)a*Return list of ints from sequence of integral numbers. All elements of the sequence must satisfy int(element) == element or a ValueError is raised. Sequence is iterated through once. If sequence is a list, the non-int values are replaced with ints. So, no new list is created zsequence is not all integers: N)r$listint ValueErrornx NetworkXErrorr2 enumerate)sequencer4r0errmsgiiindxr)r)r*r ss4              r cCs@d}tj|tddt|tsdS|D] }t|tsdSqdS)zReturn True if list is a list of ints. .. deprecated:: 2.6 This is deprecated and will be removed in NetworkX v3.0. zhis_list_of_ints is deprecated and will be removed in 3.0.See also: ``networkx.utils.make_list_of_ints.`` stacklevelFT)r!r"r#r$r6r7)intlistr(r0r)r)r*rs  rcCsd}t|tt|S)zReturns the string representation of t. .. deprecated:: 2.6 This is deprecated and will be removed in NetworkX v3.0. zCmake_str is deprecated and will be removed in 3.0. Use str instead.)r!r"r#r%)xr(r)r)r*rs rcCsd}t|tttS)z|Generate a unique node label. .. deprecated:: 2.6 This is deprecated and will be removed in NetworkX v3.0. zVgenerate_unique_node is deprecated and will be removed in 3.0. Use uuid.uuid4 instead.)r!r"r#r%uuiduuid4)r(r)r)r*rs  rcCsLtdtddlm}dgdgdggdd}|tj|g}||dS) aOpens `filename` using system's default program. .. deprecated:: 2.6 default_opener is deprecated and will be removed in version 3.0. Consider an image processing library to open images, such as Pillow:: from PIL import Image Image.open(filename).show() Parameters ---------- filename : str The path of the file to be opened. zAdefault_opener is deprecated and will be removed in version 3.0. r)callopenzxdg-open)zcmd.exez/Cstart)darwinlinuxlinux2win32N)r!r"r# subprocessrGsysplatform)filenamerGcmdscmdr)r)r*rs  rc Cs.zt||WSttfyt||YSw)zPConvert a dictionary of dictionaries to a numpy array with optional mapping.)_dict_to_numpy_array2AttributeError TypeError_dict_to_numpy_array1)dmappingr)r)r*rs  rcCd}tj|tddt||S)zConvert a dict of dicts to a 2d numpy array with optional mapping. .. deprecated:: 2.8 dict_to_numpy_array2 is deprecated and will be removed in networkx 3.0. Use `dict_to_numpy_array` instead. zhdict_to_numpy_array2 is deprecated and will be removed in networkx 3.0. Use dict_to_numpy_array instead.r@rA)r!r"r#rUrYrZr(r)r)r*r  rc Csddl}|dur)t|}|D] \}}||qtt|tt|}t|}| ||f}|D]"\}} |D]\} } z ||| || | f<Wq@t yYYq@wq8|S)zYConvert a dictionary of dictionaries to a 2d numpy array with optional mapping. rN) numpysetkeysitemsupdatedictzipranger-zerosKeyError) rYrZnpskvnak1r0k2jr)r)r*rUs"  rUcCr[)zConvert a dict of numbers to a 1d numpy array with optional mapping. .. deprecated:: 2.8 dict_to_numpy_array1 is deprecated and will be removed in networkx 3.0. Use dict_to_numpy_array instead. zhdict_to_numpy_array1 is deprecated and will be removed in networkx 3.0. Use dict_to_numpy_array instead.r@rA)r!r"r#rXr\r)r)r*rr]rcCsnddl}|durt|}tt|tt|}t|}||}|D]\}}||}||||<q&|S)zJConvert a dictionary of numbers to a 1d numpy array with optional mapping.rN) r^r_r`rcrdrer-rfra)rYrZrhrirlrmrnr0r)r)r*rX$s  rXcCs8d}tj|tddt|dpt|d}t||uo|S)zReturns True if and only if the given object is an iterator object. .. deprecated:: 2.6.0 Deprecated in favor of ``isinstance(obj, collections.abc.Iterator)`` zxis_iterator is deprecated and will be removed in version 3.0. Use ``isinstance(obj, collections.abc.Iterator)`` instead.r@rA__next__next)r!r"r#r,iter)r'r( has_next_attrr)r)r*r3s rcCst|tr tdtt|S)aReturns an arbitrary element of `iterable` without removing it. This is most useful for "peeking" at an arbitrary element of a set, but can be used for any list, dictionary, etc., as well. Parameters ---------- iterable : `abc.collections.Iterable` instance Any object that implements ``__iter__``, e.g. set, dict, list, tuple, etc. Returns ------- The object that results from ``next(iter(iterable))`` Raises ------ ValueError If `iterable` is an iterator (because the current implementation of this function would consume an element from the iterator). Examples -------- Arbitrary elements from common Iterable objects: >>> nx.utils.arbitrary_element([1, 2, 3]) # list 1 >>> nx.utils.arbitrary_element((1, 2, 3)) # tuple 1 >>> nx.utils.arbitrary_element({1, 2, 3}) # set 1 >>> d = {k: v for k, v in zip([1, 2, 3], [3, 2, 1])} >>> nx.utils.arbitrary_element(d) # dict_keys 1 >>> nx.utils.arbitrary_element(d.values()) # dict values 3 `str` is also an Iterable: >>> nx.utils.arbitrary_element("hello") 'h' :exc:`ValueError` is raised if `iterable` is an iterator: >>> iterator = iter([1, 2, 3]) # Iterator, *not* Iterable >>> nx.utils.arbitrary_element(iterator) Traceback (most recent call last): ... ValueError: cannot return an arbitrary item from an iterator Notes ----- This function does not return a *random* element. If `iterable` is ordered, sequential calls will return the same value:: >>> l = [1, 2, 3] >>> nx.utils.arbitrary_element(l) 1 >>> nx.utils.arbitrary_element(l) 1 z0cannot return an arbitrary item from an iterator)r$rr8rrrs)r r)r)r*rBs ? rcCs$d}tj|tddt|dddS)z}Consume the iterator entirely. .. deprecated:: 2.6 This is deprecated and will be removed in NetworkX v3.0. zpconsume is deprecated and will be removed in version 3.0. Use ``collections.deque(iterator, maxlen=0)`` instead.r@rAr)maxlenN)r!r"r#r)iteratorr(r)r)r*rsrFcCs:t|\}}t|d}|durt|t||fSt||S)z&s -> (s0, s1), (s1, s2), (s2, s3), ...NT)rrrrdr)r cyclicrmbfirstr)r)r*rs   rcCs0tt}|D] \}}|||qt|S)aConverts a many-to-one mapping into a one-to-many mapping. `many_to_one` must be a dictionary whose keys and values are all :term:`hashable`. The return value is a dictionary mapping values from `many_to_one` to sets of keys from `many_to_one` that have that value. Examples -------- >>> from networkx.utils import groups >>> many_to_one = {"a": 1, "b": 1, "c": 2, "d": 3, "e": 3} >>> groups(many_to_one) # doctest: +SKIP {1: {'a', 'b'}, 2: {'c'}, 3: {'e', 'd'}} )rr_raaddrc) many_to_one one_to_manyrkrjr)r)r*rsrcCs0tjdtddt|ttfs|Sttt|S)aConverts lists to tuples. .. deprecated:: 2.8 to_tuple is deprecated and will be removed in NetworkX 3.0. Examples -------- >>> from networkx.utils import to_tuple >>> a_list = [1, 2, [1, 4]] >>> to_tuple(a_list) (1, 2, (1, 4)) z;to_tuple is deprecated and will be removed in NetworkX 3.0.r@rA)r!r"r#r$r3r6mapr)rDr)r)r*rsrcCspddl}|dus ||jur|jjjSt||jjr|St|tr&|j|St||jjr/|S|d}t|)aReturns a numpy.random.RandomState or numpy.random.Generator instance depending on input. Parameters ---------- random_state : int or NumPy RandomState or Generator instance, optional (default=None) If int, return a numpy.random.RandomState instance set with seed=int. if `numpy.random.RandomState` instance, return it. if `numpy.random.Generator` instance, return it. if None or numpy.random, return the global random number generator used by numpy.random. rNzW cannot be used to create a numpy.random.RandomState or numpy.random.Generator instance) r^randommtrand_randr$ RandomStater7 Generatorr8) random_staterhr(r)r)r*rs    rc@sheZdZdddZddZddZddd Zd d Zd d ZddZ ddZ ddZ ddZ ddZ dS)rNcCsRzddl}Wntyd}t|tYnw|dur$|jjj|_dS||_dS)Nrz.numpy not found, only random.random available.) r^ ImportErrorr!r" ImportWarningr~rr_rng)selfrngrhr(r)r)r*__init__s   zPythonRandomInterface.__init__cCs |jSr.rr~)rr)r)r*r~s zPythonRandomInterface.randomcCs||||jSr.r)rrmrxr)r)r*uniformszPythonRandomInterface.uniformcCs4ddl}t|j|jjr|j||S|j||SNrr^r$rr~rintegersrandintrrmrxrhr)r)r* randrangeszPythonRandomInterface.randrangecCsLddl}t|j|jjr|jdt|}||S|jdt|}||Sr)r^r$rr~rrr-r)rseqrhidxr)r)r*choice s zPythonRandomInterface.choicecCs|j||Sr.)rnormal)rmusigmar)r)r*gaussszPythonRandomInterface.gausscC |j|Sr.)rshuffle)rrr)r)r*r zPythonRandomInterface.shufflecCs|jjt||fddS)NF)sizereplace)rrr6)rrrjr)r)r*sampleszPythonRandomInterface.samplecCs<ddl}t|j|jjr|j||dS|j||dS)Nrrrr)r)r*rszPythonRandomInterface.randintcCs|jd|S)Nr)r exponential)rscaler)r)r* expovariate'sz!PythonRandomInterface.expovariatecCrr.)rpareto)rshaper)r)r* paretovariate+rz#PythonRandomInterface.paretovariater.)__name__ __module__ __qualname__rr~rrrrrrrrrr)r)r)r*rs      rcCsddl}z+ddl}||jurt|jjjWSt||jj|jjfr&t|WSt|tr.|WSWn ty8Ynw|dusA||urD|j St||j rL|St|t rV| |S|d}t |)aReturns a random.Random instance depending on input. Parameters ---------- random_state : int or random number generator or None (default=None) If int, return a random.Random instance set with seed=int. if random.Random instance, return it. if None or the `random` package, return the global random number generator used by `random`. if np.random package, return the global numpy random number generator wrapped in a PythonRandomInterface class. if np.random.RandomState or np.random.Generator instance, return it wrapped in PythonRandomInterface if a PythonRandomInterface instance, return it rNz4 cannot be used to generate a random.Random instance) r~r^rrrr$rrr_instRandomr7r8)rr~rhr(r)r)r*r:s*        rc Cs\t|}t|}z t|}t|}W||kSttfy-t|}t|}Y||kSw)aUCheck if nodes are equal. Equality here means equal as Python objects. Node data must match if included. The order of nodes is not relevant. Parameters ---------- nodes1, nodes2 : iterables of nodes, or (node, datadict) tuples Returns ------- bool True if nodes are equal, False otherwise. )r6rcr8rWfromkeys)nodes1nodes2nlist1nlist2d1d2r)r)r*rbs   rcCs|ddlm}|t}|t}d}t|D].\}}|d|d}}|ddg} |||vr6|||| } | |||<| |||<qd} t|D].\} }|d|d}}|ddg} |||vrk|||| } | |||<| |||<qI|| kr~dS|D]9\} } | D]0\} }| |vrdS| || vrdS|| | }|D]} || || krdSqqqdS)aCheck if edges are equal. Equality here means equal as Python objects. Edge data must match if included. The order of the edges is not relevant. Parameters ---------- edges1, edges2 : iterables of with u, v nodes as edge tuples (u, v), or edge tuples with data dicts (u, v, d), or edge tuples with keys and data dicts (u, v, k, d) Returns ------- bool True if edges are equal, False otherwise. r)rrr@NFT) collectionsrrcr;racount)edges1edges2rrrc1eurkdatac2rlnbrdictnbrdatalist d2datalistr)r)r*r}sF         rcCs$|j|jko|j|jko|j|jkS)aCheck if graphs are equal. Equality here means equal as Python objects (not isomorphism). Node, edge and graph data must match. Parameters ---------- graph1, graph2 : graph Returns ------- bool True if graphs are equal, False otherwise. )adjnodesgraph)graph1graph2r)r)r*r s   r r.)F)+__doc__rPrEr!rrrcollections.abcrrr itertoolsrrnetworkxr9__all__r r r r r rrrrrrrUrrXrrrrrrrrrrrr r)r)r)r*sF ! $    F    L( 7