code: def _scipy_triangular(self, low, high, peak):
      # Scipy triangular specifies a triangular distribution
      # from loc to loc + scale, with loc + c * scale as the
      # peak, giving:
      # loc = low, loc + scale = high, loc + c * scale = peak.
      # We invert this mapping here.
      return stats.triang(
          c=(peak - low) / (high - low), loc=low, scale=(high - low)
      )
  
imports: import numpy
  from scipy import stats
  import tensorflow.compat.v1
  import tensorflow.compat.v2
  from tensorflow_probability.python.distributions import triangular
  from tensorflow_probability.python.distributions.internal import statistical_testing
  from tensorflow_probability.python.internal import test_util
label_desc: Use image node_id 3 for calling the _TriangularTest obj's underlying member method code with example usage: obj._scipy_triangular(low, high, peak) and returns: stats