Cleaned up PEP8 violations.

src/main/python/org/broadinstitute/hellbender/gcnvkernel/inference/fancy_optimizers.py

@@ -249,4 +249,4 @@ def initialize_state_from_instance(self, instance: 'FancyAdamax'):
         self.get_rho_m().set_value(instance.get_rho_m().get_value())
         self.get_rho_u().set_value(instance.get_rho_u().get_value())
         if not self.disable_bias_correction:
-            self.get_res_tensor().set_value(instance.get_res_tensor().get_value())
+            self.get_res_tensor().set_value(instance.get_res_tensor().get_value())

src/main/python/org/broadinstitute/hellbender/gcnvkernel/io/io_denoising_calling.py

@@ -259,7 +259,7 @@ def _read_sample_copy_number_log_posterior(self,
             delimiter=delimiter,
             comment=comment)
         assert read_log_q_c_tc.shape == (self.denoising_calling_workspace.num_intervals,
-                                             self.denoising_calling_workspace.calling_config.num_copy_number_states)
+                                         self.denoising_calling_workspace.calling_config.num_copy_number_states)
         return read_log_q_c_tc
 
     def _read_sample_copy_number_log_emission(self,
@@ -271,9 +271,8 @@ def _read_sample_copy_number_log_emission(self,
             io_consts.default_copy_number_log_emission_tsv_filename,
             delimiter=delimiter,
             comment=comment)
-        assert read_log_emission_tc.shape ==\
-               (self.denoising_calling_workspace.num_intervals,
-                self.denoising_calling_workspace.calling_config.num_copy_number_states)
+        assert read_log_emission_tc.shape == (self.denoising_calling_workspace.num_intervals,
+                                              self.denoising_calling_workspace.calling_config.num_copy_number_states)
         return read_log_emission_tc
 
     def __call__(self):

src/main/python/org/broadinstitute/hellbender/gcnvkernel/models/commons.py

@@ -30,8 +30,7 @@ def get_normalized_prob_vector(prob_vector: np.ndarray, prob_sum_tol: float) ->
     else:
         _logger.warning("The given probability vector ({0}) is not normalized to unity within the provided "
                         "tolerance ({1}); sum = {2}. Normalization was enforced. However, please check the inputs "
-                        "for unintentional errors.".format(
-            prob_vector, prob_sum_tol, prob_sum))
+                        "for unintentional errors.".format(prob_vector, prob_sum_tol, prob_sum))
         return prob_vector / prob_sum
 
 

src/main/python/org/broadinstitute/hellbender/gcnvkernel/models/model_denoising_calling.py

@@ -784,7 +784,7 @@ def __init__(self,
         mean_mapping_error_correction_s = eps * read_depth_s * shared_workspace.average_ploidy_s
 
         denoised_copy_ratio_st = ((shared_workspace.n_st - mean_mapping_error_correction_s.dimshuffle(0, 'x'))
-                                / ((1.0 - eps) * read_depth_s.dimshuffle(0, 'x') * bias_st))
+                                  / ((1.0 - eps) * read_depth_s.dimshuffle(0, 'x') * bias_st))
 
         Deterministic(name='denoised_copy_ratio_st', var=denoised_copy_ratio_st)
 

src/main/python/org/broadinstitute/hellbender/gcnvkernel/postprocess/segment_quality_utils.py

@@ -312,4 +312,4 @@ def get_segment_quality_end(self, end_index: int, call_state: int) -> float:
                                                     self.beta_tc[end_index + 1, call_state]))
             logp = logsumexp(np.asarray(complementary_paths_unnorm_logp)) - self.log_data_likelihood
 
-        return logp_to_phred(logp)
+        return logp_to_phred(logp)

src/main/python/org/broadinstitute/hellbender/gcnvkernel/structs/metadata.py

@@ -143,8 +143,7 @@ def rectify_contig(_contig: str):
         for j, contig in enumerate(self.contig_list):
             if rectify_contig(contig) not in all_standard_contigs:
                 _logger.warning("Sample {0} has an unrecognized contig ({1}). Germline contig ploidy determination "
-                                "may not be reliable for decoy/non-standard contigs.".format(
-                    self.sample_name, contig))
+                                "may not be reliable for decoy/non-standard contigs.".format(self.sample_name, contig))
             if rectify_contig(contig) in autosomal_contigs and self.ploidy_j[j] != homo_sapiens_autosomal_contig_ploidy:
                 _logger.warning("Sample {0} has an anomalous ploidy ({1}) for contig {2}. ".format(
                                     self.sample_name, self.ploidy_j[j], contig) + general_warning_msg)

src/main/python/org/broadinstitute/hellbender/gcnvkernel/tasks/inference_task_base.py

@@ -533,8 +533,8 @@ def _update_discrete_posteriors(self):
                 # if there is a self-consistency loop and not converged ...
                 if not iters_converged and self.hybrid_inference_params.max_calling_iters > 1:
                     _logger.warning('{0} did not converge. Increase maximum calling rounds (current: {1}) '
-                                    'if this behavior persists.'.format(
-                        self.calling_task_name, self.hybrid_inference_params.max_calling_iters))
+                                    'if this behavior persists.'.format(self.calling_task_name,
+                                                                        self.hybrid_inference_params.max_calling_iters))
 
         return iters_converged