
background_distributions

state

model

model_direct

hmm_check_t

model_ipow
 binary algorithm to compute powers of integers efficiently see Knuth, TAOCP, Vol 2, 463 uses if appropiate lookup table from struct model

model_free
 Frees the memory of a model.

model_read
 Reads in ASCII data to initialize an array of models.

model_direct_read
 Reads in a model, where the model parameters are explicit given in matrix form.

model_from_sequence_ascii
 Produces simple leftright models given sequences.

model_from_sequence
 Produces simple leftright models given sequences.

model_copy
 Copies a given model.

model_check
 Tests if all standardization requirements of model are fulfilled.

model_check_compatibility
 Tests if number of states and number of outputs in the models match.

model_check_compatibel_models
 Test if to models are compatible.

model_generate_from_sequence
 Produces a model, which generates the given sequence with probability 1.

model_generate_sequences
 Produces sequences to a given model.

model_likelihood
 Calculates the sum log( P( O  lambda ) ).

model_set_transition
 Set transition from state 'i' to state 'j' to value 'prob'.

model_print
 Writes a model in matrix format.

model_A_print
 Writes transition matrix of a model.

model_B_print
 Writes output matrix of a model.

model_Pi_print
 Writes initial allocation vector of a matrix.

model_fix_print
 Writes fix vector of a matrix.

model_A_print_transp
 Writes transposed transition matrix of a model.

model_B_print_transp
 Writes transposed output matrix of a model.

model_Pi_print_transp
 Writes transposed initial allocation vector of a matrix.

model_direct_print
 Writes a HMM in matrix format.

model_states_print
 Writes the parameters of a model sorted by states.

model_direct_clean
 Frees all memory from a model, sets the pointers to NULL and variables to zero.

model_direct_check_data
 Tests compatibility of the model components.

model_prob_distance
 Computes probabilistic distance of two models

state_clean
 Frees all memory from a state, sets the pointers to NULL and variables to zero.

get_emission_index
 Calculates the right index for emission array b of state j in model mo given an observation obs and taking the state order into account, returns 1 if state order exceeds number of so far emitted characters

update_emission_history
 Updates emission history of model mo, discarding the oldest and 'adding' the new observation by using modulo and multiplication

update_emission_history_front
 Updates emission history of model mo for backward algorithm by 'adding' observation obs to the left, (example: obs = 3 2 0 0 1 > 3 2 0 0 )

model_normalize
 Uses vector_normalize in vectorh Normalizes the transition and output probs for each state in the given model

model_add_noise
 Add a specific level of noise to the model parameters

model_apply_duration
 Allocates a new background_distributions struct and assigs the arguments to the respective fields.

model_apply_background
 Apply the background distributions to the emission probabilities of states of the model which have one specified (background_id[state_id] != kNoBackgroundDistribution).

model_alloc_background_distributions
 Allocates a new background_distributions struct and assigs the arguments to the respective fields.

model_get_uniform_background
 Calculates the background distribution for a sequence_t the calculated distribution is uniform, every state with the same order has the same background distribution.

model_distance
 Calculates the squared distance between two compatible models.

state_copy
 Copies a given state.

state_copy_to
 Copies a given state to a given destination.
Alphabetic index
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