o Thc@sLdZddlZddlZddlmZddlmZddl m Z dgZ d ddZ dS) zUtilities for random sampling.N)check_random_state)sample_without_replacementrcCs,td}td}tddg}tt|D]}t||||<||jjdkr3td||j||jtj dd||<|dur[tj ||j dd}| d||j dnt||}t t|d srtd ||j d||j dkrtd |||j d|j dd||vrt||dd||<t|dd }t|} ||j ddkrt||dk} d|| } t|| } t|| |d } || ||dk}||}|t|}t|| j| d}||||||t|qtj|||f|t|ftdS)aGenerate a sparse random matrix given column class distributions Parameters ---------- n_samples : int, Number of samples to draw in each column. classes : list of size n_outputs of arrays of size (n_classes,) List of classes for each column. class_probability : list of size n_outputs of arrays of shape (n_classes,), default=None Class distribution of each column. If None, uniform distribution is assumed. random_state : int, RandomState instance or None, default=None Controls the randomness of the sampled classes. See :term:`Glossary `. Returns ------- random_matrix : sparse csc matrix of size (n_samples, n_outputs) irzclass dtype %s is not supportedF)copyN)shaperg?z2Probability array at index {0} does not sum to onezXclasses[{0}] (length {1}) and class_probability[{0}] (length {2}) have different length.g) n_population n_samples random_state)size)dtype)arrayrangelennpasarrayr kind ValueErrorastypeint64emptyrfillisclosesumformatinsertr flatnonzeroitemintrextend searchsortedcumsumuniformappendsp csc_matrix)r classesclass_probabilityr dataindicesindptrj class_prob_jrng index_class_0 p_nonzeronnz ind_sampleclasses_j_nonzeroclass_probability_nzclass_probability_nz_norm classes_indr6T/home/air/segue/gpt/backup/venv/lib/python3.10/site-packages/sklearn/utils/random.py_random_choice_cscs\       r8)NN) __doc__r numpyr scipy.sparsesparser$r_randomr__all__r8r6r6r6r7s