code: def test_LearnerSCCS_confidence_intervals(self):
      def fit(clazz):
          self.setUp()
          lrn = clazz(n_lags=self.n_lags, penalized_features=[])
          coeffs, _ = lrn.fit(
              self.features, self.labels, self.censoring
          )
          p_features, p_labels, p_censoring = lrn._preprocess_data(
              self.features, self.labels, self.censoring
          )
          confidence_intervals = lrn._bootstrap(
              p_features,
              p_labels,
              p_censoring,
              np.hstack(coeffs),
              5,
              0.90,
          )
          for i, c in enumerate(coeffs):
              self.assertTrue(
                  np.all(confidence_intervals.lower_bound[i] <= c),
                  "lower bound of the confidence interval\
                                         should be <= coeffs at index %i"
                  % i,
              )
              self.assertTrue(
                  np.all(c <= confidence_intervals.upper_bound[i]),
                  "upper bound of the confidence interval\
                                         should be >= coeffs at index %i"
                  % i,
              )
          # Same with 0 lags
          n_lags = np.zeros_like(self.n_lags, dtype="uint64")
          lrn = clazz(n_lags=n_lags, penalized_features=[])
          coeffs, _ = lrn.fit(
              self.features, self.labels, self.censoring
          )
          p_features, p_labels, p_censoring = lrn._preprocess_data(
              self.features, self.labels, self.censoring
          )
          confidence_intervals = lrn._bootstrap(
              p_features,
              p_labels,
              p_censoring,
              np.hstack(coeffs),
              5,
              0.90,
          )
          for i, c in enumerate(coeffs):
              self.assertTrue(
                  np.all(confidence_intervals.lower_bound[i] <= c),
                  "lower bound of the confidence interval\
                                         should be <= coeffs at index %i"
                  % i,
              )
              self.assertTrue(
                  np.all(c <= confidence_intervals.upper_bound[i]),
                  "upper bound of the confidence interval\
                                         should be >= coeffs at index %i"
                  % i,
              )
  
      fit(ConvSCCS)
      fit(BatchConvSCCS)
      fit(StreamConvSCCS)
  
file_path: tick/tick/survival/tests/convolutional_sccs_test.py
imports: import unittest
  import numpy
  from tick.survival import SimuSCCS, ConvSCCS
  from scipy.sparse import csr_matrix
  from tick.survival.sccs import *
label_desc: Use image node_id 5 for calling the Test obj's underlying member method code with example usage: obj.test_LearnerSCCS_confidence_intervals() without return types