@@ -503,7 +503,7 @@ def christov_segmenter(signal=None, sampling_rate=1000.):
503503 X = ss .filtfilt (b , a , signal )
504504 # 2. Moving averaging of samples in 28 ms interval for electromyogram
505505 # noise suppression a filter with first zero at about 35 Hz.
506- b = np .ones (sampling_rate / 35. ) / 35.
506+ b = np .ones (int ( sampling_rate / 35. ) ) / 35.
507507 X = ss .filtfilt (b , a , X )
508508 X , _ , _ = st .filter_signal (signal = X ,
509509 ftype = 'butter' ,
@@ -531,11 +531,11 @@ def christov_segmenter(signal=None, sampling_rate=1000.):
531531 # with first zero at about 25 Hz. It is suppressing the noise
532532 # magnified by the differentiation procedure used in the
533533 # process of the complex lead sintesis.
534- b = np .ones (sampling_rate / 25. ) / 25.
534+ b = np .ones (int ( sampling_rate / 25. ) ) / 25.
535535 Y = ss .lfilter (b , a , Y )
536536
537537 # Init
538- MM = M_th * np .max (Y [:5 * sampling_rate ]) * np .ones (5 )
538+ MM = M_th * np .max (Y [:int ( 5 * sampling_rate ) ]) * np .ones (5 )
539539 MMidx = 0
540540 M = np .mean (MM )
541541 slope = np .linspace (1.0 , 0.6 , int (sampling_rate ))
@@ -827,7 +827,7 @@ def gamboa_segmenter(signal=None, sampling_rate=1000., tol=0.002):
827827 for i in b [1 :]:
828828 if i - previous > v_300ms :
829829 previous = i
830- rpeaks .append (np .argmax (signal [i : i + v_100ms ]) + i )
830+ rpeaks .append (np .argmax (signal [int ( i ): int ( i + v_100ms ) ]) + i )
831831
832832 rpeaks = np .array (rpeaks , dtype = 'int' )
833833
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