From 2f9c140c387868dffe5bba959f4c81776acb6c66 Mon Sep 17 00:00:00 2001 From: nicoval Date: Fri, 12 Feb 2021 13:00:13 +0100 Subject: [PATCH] corrected dcm-new to dcm_exp and same for decm --- src/NEMtropy/graph_classes.py | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/src/NEMtropy/graph_classes.py b/src/NEMtropy/graph_classes.py index 522d30a6..cc9512b6 100644 --- a/src/NEMtropy/graph_classes.py +++ b/src/NEMtropy/graph_classes.py @@ -2399,9 +2399,9 @@ def solve_tool( :param model: Available models are: - *dcm*: solves DBCM respect to the parameters *x* and "y" of the loglikelihood function, it works for uweighted directed graphs [insert ref]. - - *dcm-new*: differently from the *dcm* option, *dcm-new* considers the exponents of *x* and *y* as parameters [insert ref]. + - *dcm_exp*: differently from the *dcm* option, *dcm_exp* considers the exponents of *x* and *y* as parameters [insert ref]. - *decm*: solves DECM respect to the parameters *a_out*, *a_in*, *b_out* and *b_in* of the loglikelihood function, it is conceived for weighted directed graphs [insert ref]. - - *decm-new*: differently from the *ecm* option, *ecm_exp* considers the exponents of *a_out*, *a_in*, *b_out* and *b_in** as parameters [insert ref]. + - *decm_exp*: differently from the *decm* option, *decm_exp* considers the exponents of *a_out*, *a_in*, *b_out* and *b_in** as parameters [insert ref]. - *crema*: solves CReMa for a weighted directd graphs. In order to compute beta parameters, it requires information about the binary structure of the network. These can be provided by the user by using *adjacency* paramenter. - *crema-sparse*: alternative implementetio of *crema* for large graphs. The *creama-sparse* model doesn't compute the binary probability matrix avoing memory problems for large graphs. :type model: str @@ -2428,7 +2428,7 @@ def solve_tool( - *strengths_minor*: initial guess of each node is inversely proportional to its strength; :type initial_guess: str, optional - :param adjacency: Adjacency can be a binary method (defaults is *dcm-new*) or an adjacency matrix. + :param adjacency: Adjacency can be a binary method (defaults is *dcm_exp*) or an adjacency matrix. :type adjacency: str or numpy.ndarray, optional :param method_adjacency: If adjacency is a *model*, it is the *methdod* used to solve it. Defaults to "newton". :type method_adjacency: str, optional