class_docstr: Compute the cosine distance between two streamlines.
class_docstr_tok: ["Compute","the","cosine","distance","between","two","streamlines","."]
docstr: Check if two features are vectors of same dimension.
  
  Basically this method exists so that we don't have to check
  inside the `dist` method (speedup).
docstr_tok: ["Check","if","two","features","are","vectors","of","same","dimension",".","Basically","this","method","exists","so","that","we","do","n't","have","to","check","inside","the","`","dist","`","method","(","speedup",")","."]
code: def are_compatible(self, shape1, shape2):
      """Check if two features are vectors of same dimension.
  
      Basically this method exists so that we don't have to check
      inside the `dist` method (speedup).
      """
      return shape1 == shape2 and shape1[0] == 1
  
file_path: dipy/doc/examples/segment_extending_clustering_framework.py
imports: import numpy
  from dipy.data import get_fnames
  from dipy.io.streamline import load_tractogram
  from dipy.tracking.streamline import Streamlines
  from dipy.viz import window, actor, colormap
  from dipy.segment.clustering import QuickBundles
  from dipy.segment.featurespeed import Feature, VectorOfEndpointsFeature
  from dipy.segment.metric import Metric, SumPointwiseEuclideanMetric
  from dipy.tracking.streamline import length
label_desc: Use image node_id 2 for calling the CosineMetric obj's underlying member method code with example usage: obj.are_compatible(shape1, shape2) and returns: unknown