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Methods defined here:
- __init__(self, organism, membership, ratios, config_params)
- create scoring function instance
- do_compute(self, iteration_result, ref_matrix=None)
- compute method, iteration is the 0-based iteration number
Methods inherited from ScoringFunctionBase:
- check_requirements(self)
- Give the scoring module an opportunity to check whether the
requirements to run are all met
- compute(self, iteration_result, reference_matrix=None)
- general compute method,
iteration_result is a dictionary that contains the
results generated by the scoring functions in the
current computation.
the reference_matrix is actually a hack that allows the scoring
function to normalize its scores to the range of a reference
score matrix. In the normal case, those would be the gene expression
row scores
- compute_force(self, iteration_result, reference_matrix=None)
- enforce computation, regardless of the iteration function
- gene_names(self)
- returns the gene names
- last_cached(self)
- num_clusters(self)
- returns the number of clusters
- pickle_path(self)
- returns the function-specific pickle-path
- rows_for_cluster(self, cluster)
- returns the rows for the specified cluster
- run_in_iteration(self, i)
- run_logs(self)
- returns a list of RunLog objects, giving information about
the last run of this function
- scaling(self, iteration)
- returns the quantile normalization scaling for the specified iteration
- set_score_means(self, iteration_result, matrix)
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