Return a `list` of phi parameters for `timepoint` and `topic_id`. Parameters ---------- timepoint : int an integer with range [0, `t`) topic_id :

.. versionadded:: 0.5.0 Return a distribution of the sub topics in the document. (for only `tomotopy.models.PAModel`) Parameters ---------- normaliz

Return a distribution of the sub topics in a super topic `super_topic_id`. The returned value is a `list` that has `k2` fraction numbers indicating pr

.. versionadded:: 0.5.0 Return the `top_n` sub topics with their probabilities for the document. (for only `tomotopy.models.PAModel`)

Return the word distribution of the topic `topic_id`. The returned value is a `list` that has `len(vocabs)` fraction numbers indicating probabilities

Return the word distribution of the topic `topic_id`. The returned value is a `list` that has `len(vocabs)` fraction numbers indicating probabilities

Return the word distribution of the topic `topic_id`. The returned value is a `list` that has `len(vocabs)` fraction numbers indicating probabilities

Return the word distribution of the topic `topic_id` with `timepoint`. The returned value is a `list` that has `len(vocabs)` fraction numbers indicati

.. versionadded:: 0.6.0 Return word-topic prior for `word`. If there is no set prior for `word`, an empty list is returned. Parameters ---------- wo

the total number of iterations of training (read-only) .. versionadded:: 0.9.0

Return `True` if the topic `topic_id` is alive, otherwise return `False`. Parameters ---------- topic_id : int an integer in range [0, `k`) indic

K, the number of topics (read-only)

k1, the number of super topics (read-only)

k2, the number of sub topics (read-only)

the hyperparameter k_g (read-only)

the hyperparameter k_l (read-only)

a `list` of (label, list of probabilities of each topic belonging to the label) of the document (for only `tomotopy.models.LLDAModel` and `tomotopy.mo

parameter lambdas in the shape `[k, len(metadata_dict), l]` where `k` is the number of topics and `l` is the size of vector for multi_metadata (read-o

parameter lambdas in the shape `[k, f]` (read-only) .. warning:: Prior to version 0.11.0, there was a bug in the lambda getter, so it yielded th

the number of latent topics (read-only)

approximation : lgamma(z) ~= (z+2.5)ln(z+3) - z - 3 + 0.5 ln (2pi) + 1/12/(z + 3) - ln (z(z+1)(z+2))

approximation : lgamma(z) ~= (z+2.5)ln(z+3) - z - 3 + 0.5 ln (2pi) + 1/12/(z + 3) - ln (z(z+1)(z+2))

approximation : lgamma(z) ~= (z+2.5)ln(z+3) - z - 3 + 0.5 ln (2pi) + 1/12/(z + 3) - ln (z(z+1)(z+2))

approximation : lgamma(z) ~= (z+2.5)ln(z+3) - z - 3 + 0.5 ln (2pi) + 1/12/(z + 3) - ln (z(z+1)(z+2))

approximation : lgamma(z + a) - lgamma(z) = (z + a + 1.5) * log(z + a + 2) - (z + 1.5) * log(z + 2) - a + (1. / (z + a + 2) - 1. / (z + 2)) / 12. - lo

approximation : lgamma(z + a) - lgamma(z) = (z + a + 1.5) * log(z + a + 2) - (z + 1.5) * log(z + 2) - a + (1. / (z + a + 2) - 1. / (z + 2)) / 12. - lo

the number of alive topics (read-only)