ph lSrSSKrSSKJrJrJrJrJrJ r J r SSK J r SSK Jr "SS5rS rS rg) z Represents the network of interest. This is the primary object of PyPhi and the context of all |small_phi| and |big_phi| computation. N)cache connectivityconvertjsonifyutilsvalidateconfig) NodeLabels)is_state_by_statec"\rSrSrSrSSjr\S5r\S5r \S5r Sr \S 5r \S 5r \S 5r\S 5r\S 5r\S5r\R&"S5S5rSrSrSrSrSrSrSr\S5rSrg)NetworkaA network of nodes. Represents the network under analysis and holds auxilary data about it. Args: tpm (np.ndarray): The transition probability matrix of the network. The TPM can be provided in any of three forms: **state-by-state**, **state-by-node**, or **multidimensional state-by-node** form. In the state-by-node forms, row indices must follow the little-endian convention (see :ref:`little-endian-convention`). In state-by-state form, column indices must also follow the little-endian convention. If the TPM is given in state-by-node form, it can be either 2-dimensional, so that ``tpm[i]`` gives the probabilities of each node being ON if the previous state is encoded by |i| according to the little-endian convention, or in multidimensional form, so that ``tpm[(0, 0, 1)]`` gives the probabilities of each node being ON if the previous state is |N_0 = 0, N_1 = 0, N_2 = 1|. The shape of the 2-dimensional form of a state-by-node TPM must be ``(s, n)``, and the shape of the multidimensional form of the TPM must be ``[2] * n + [n]``, where ``s`` is the number of states and ``n`` is the number of nodes in the network. Keyword Args: cm (np.ndarray): A square binary adjacency matrix indicating the connections between nodes in the network. ``cm[i][j] == 1`` means that node |i| is connected to node |j| (see :ref:`cm-conventions`). **If no connectivity matrix is given, PyPhi assumes that every node is connected to every node (including itself)**. node_labels (tuple[str] or |NodeLabels|): Human-readable labels for each node in the network. Example: In a 3-node network, ``the_network.tpm[(0, 0, 1)]`` gives the transition probabilities for each node at |t| given that state at |t-1| was |N_0 = 0, N_1 = 0, N_2 = 1|. NchURU5uUlUlURU5uUlUl[ [UR55Ul [X0R5Ul U=(d [R"5Ul[R "U5 gN) _build_tpm_tpm _tpm_hash _build_cm_cm_cm_hashtuplerangesize _node_indicesr _node_labelsr PurviewCache purview_cacher network)selftpmcm node_labelsrs G/home/james-whalen/.local/lib/python3.13/site-packages/pyphi/network.py__init__Network.__init__<s}$(OOC$8! 4>"&.."4$-"5#34&{4F4FG*Be.@.@.BcUR$)zSnp.ndarray: The network's transition probability matrix, in multidimensional form. )rr s r$r! Network.tpmEs yyr'cJ[R"U5n[R"U[R S9 [ U5(a[R"U5nO[R"U5n[R"U5 U[R"U54$)zJValidate the TPM passed by the user and convert to multidimensional form. )check_independence) nparrayr r!r !VALIDATE_CONDITIONAL_INDEPENDENCEr rstate_by_state2state_by_nodeto_multidimensionalr np_immutablenp_hash)r!s r$rNetwork._build_tpmLst hhsm SV-U-UV S ! !66s;C--c2C 3U]]3'((r'cUR$)znp.ndarray: The network's connectivity matrix. A square binary adjacency matrix indicating the connections between nodes in the network. rr)s r$r" Network.cm_s xxr'cUc-[R"URUR45nO[R"U5n[R "U5 U[R "U54$)z^Convert the passed CM to the proper format, or construct the unitary CM if none was provided. )r-onesrr.rr2r3)r r"s r$rNetwork._build_cmhsS :$))TYY/0B"B 2EMM"%&&r'cUR$)znp.ndarray: Alias for ``cm``.r6r)s r$connectivity_matrixNetwork.connectivity_matrixvs xxr'cB[R"UR5$)z:See :func:`pyphi.connectivity.causally_significant_nodes`.)rcausally_significant_nodesr"r)s r$r?"Network.causally_significant_nodes{s66tww??r'c[U5$)(int: The number of nodes in the network.)lenr)s r$r Network.sizes4yr'c SUR-$)z2int: The number of possible states of the network.)rr)s r$ num_statesNetwork.num_statessDII~r'cUR$)zhtuple[int]: The indices of nodes in the network. This is equivalent to ``tuple(range(network.size))``. )rr)s r$ node_indicesNetwork.node_indicess !!!r'cUR$)z/tuple[str]: The labels of nodes in the network.)rr)s r$r#Network.node_labelss   r'rcp[R"UR5n[URXU5$)a6All purviews which are not clearly reducible for mechanism. Args: direction (Direction): |CAUSE| or |EFFECT|. mechanism (tuple[int]): The mechanism which all purviews are checked for reducibility over. Returns: list[tuple[int]]: All purviews which are irreducible over ``mechanism``. )rpowersetrirreducible_purviewsr")r direction mechanism all_purviewss r$potential_purviewsNetwork.potential_purviewss0~~d&8&89 #DGGY$02 2r'c4URRS$)rB)r!shaper)s r$__len__Network.__len__sxx~~b!!r'cNSRURUR5$)NzNetwork({}, cm={}))formatr!r"r)s r$__repr__Network.__repr__s#**488TWW==r'c"UR5$r)r]r)s r$__str__Network.__str__s}}r'c[U[5=(a] [R"URUR5=(a+ [R"UR UR 5$)zkReturn whether this network equals the other object. Networks are equal if they have the same TPM and CM. ) isinstancerr- array_equalr!r"r others r$__eq__Network.__eq__sI ug & . NN488UYY / . NN477EHH - r'c.URU5(+$r)rgres r$__ne__Network.__ne__s;;u%%%r'cD[URUR45$r)hashrrr)s r$__hash__Network.__hash__sT^^T]]344r'c`URURURURS.$)z*Return a JSON-serializable representation.r!r"rr#rqr)s r$to_jsonNetwork.to_jsons,88''II++   r'cUS [S0UD6$)z@Return a |Network| object from a JSON dictionary representation.r)r)cls json_dicts r$ from_jsonNetwork.from_jsons f ###r')rrrrrrr)NNN)__name__ __module__ __qualname____firstlineno____doc__r%propertyr! staticmethodrr"rr<r?rrGrJr#rmethodrTrYr]r`rgrjrnrr classmethodrx__static_attributes__rur'r$rrs'T ))$ '@@ ""!!  \\/"2#2 ">  &5 $$r'rcd^^^UUU4SjnUVs/sHoT"U5(aMUPM sn$s snf)aReturn all purviews which are irreducible for the mechanism. Args: cm (np.ndarray): An |N x N| connectivity matrix. direction (Direction): |CAUSE| or |EFFECT|. purviews (list[tuple[int]]): The purviews to check. mechanism (tuple[int]): The mechanism in question. Returns: list[tuple[int]]: All purviews in ``purviews`` which are not reducible over ``mechanism``. Raises: ValueError: If ``direction`` is invalid. cZ>TRTU5up[R"TX5$)z2Return ``True`` if purview is trivially reducible.)orderrblock_reducible)purview_fromtor"rQrRs r$ reducible'irreducible_purviews..reducibles(OOIw7 ++B::r'ru)r"rQrRpurviewsrrs``` r$rPrPs) ; $, F89W3EG8 FF Fs--cz[U5n[R"U5sSSS5 $!,(df  g=f)zConvert a JSON network to a PyPhi network. Args: filename (str): A path to a JSON file representing a network. Returns: Network: The corresponding PyPhi network object. N)openrload)filenamefs r$rxrxs" h1||A s, :)r~numpyr-rrrrrr r labelsr r!r rrPrxrur'r$rs6  LLL"B$B$JG0 r'