how can i find "batch_size" function? about cardio

[roman-kh]

batch_size specifies how many items should be processed in one iteration.

When you run the pipeline, it takes batch_size items from your dataset index and execute each action in the pipeline:

• load to load data fo each item in the batch
• cwt to make wavelet transform
  and so on.

See batchflow documentation and tutorials for details.

[koicu]

nice :) i solve it
and.. i have one more problem
when i run this code, this error come out

i use 'q1c' parameter not 'pu1' when i init HMM initialize parameter

thanx to your reply have a good day!

.load(fmt='wfdb', components=["signal", "annotation", "meta"], ann_ext='q1c')

Traceback (most recent call last):

File "", line 142, in
expanded = np.concatenate([expand_annotation(samp, types, length) for samp, types, length in zip(annsamp, anntype, lengths)])

File "", line 142, in
expanded = np.concatenate([expand_annotation(samp, types, length) for samp, types, length in zip(annsamp, anntype, lengths)])

File "", line 49, in expand_annotation
annot_expand[begin:end] = states[s]

KeyError: 'u'

template_ppl_inits = (
bf.Pipeline()
.init_variable("annsamps", init_on_each_run=list)
.init_variable("anntypes", init_on_each_run=list)
.init_variable("hmm_features", init_on_each_run=list)
.load(fmt='wfdb', components=["signal", "annotation", "meta"], ann_ext='q1c')
.cwt(src="signal", dst="hmm_features", scales=[4,8,16], wavelet="mexh")
.standardize(axis=-1, src="hmm_features", dst="hmm_features")
.update_variable("annsamps", bf.F(get_annsamples), mode='e')
.update_variable("anntypes", bf.F(get_anntypes), mode='e')
.update_variable("hmm_features", bf.B("hmm_features"), mode='e')
.run(batch_size=20, shuffle=False, drop_last=False, n_epochs=1, lazy=True)

)
#%%
index.drop_channels()
#%%
from cardio.pipelines import hmm_preprocessing_pipeline, hmm_train_pipeline
import warnings
warnings.filterwarnings('ignore')

pipeline = hmm_preprocessing_pipeline()
ppl_inits = (dtst >> pipeline).run()

ppl_inits = (dtst >> template_ppl_inits).run()

#lengths = [hmm_features.shape[2] for hmm_features in ppl_inits.get_variable("hmm_features")]
lengths = [hmm_features.shape[2] for hmm_features in ppl_inits.get_variable("hmm_features")]
hmm_features = np.concatenate([hmm_features[0,:,:].T for hmm_features in ppl_inits.get_variable("hmm_features")])
anntype = ppl_inits.get_variable("anntypes")
annsamp = ppl_inits.get_variable("annsamps")

expanded = np.concatenate([expand_annotation(samp, types, length) for samp, types, length in zip(annsamp, anntype, lengths)])

means, covariances = prepare_means_covars(hmm_features, expanded, states = [3, 5, 11, 14, 17, 19], num_features = 3)

transition_matrix, start_probabilities = prepare_transmat_startprob()

[Shlyankin]

KeyError: 'u'
I think, that is 'u' wave in annotations file. Standard function don't process 'u' wave. If you want to recognize 'u' waves you should rework code for this. Good luck.