class_docstr: A strategy for floats distributed between two endpoints.
  
  The conditional distribution tries to produce values clustered
  closer to one of the ends.
class_docstr_tok: ["A","strategy","for","floats","distributed","between","two","endpoints",".","The","conditional","distribution","tries","to","produce","values","clustered","closer","to","one","of","the","ends","."]
code: def __init__(self, lower_bound, upper_bound, width):
      SearchStrategy.__init__(self)
      assert isinstance(lower_bound, float)
      assert isinstance(upper_bound, float)
      assert 0 <= lower_bound < upper_bound
      assert (
          math.copysign(1, lower_bound) == 1
      ), "lower bound may not be -0.0"
      assert width in (16, 32, 64)
      self.lower_bound = lower_bound
      self.upper_bound = upper_bound
      self.width = width
  
imports: from __future__ import absolute_import, division, print_function
  import math
  import hypothesis.internal.conjecture.floats
  import hypothesis.internal.conjecture.utils
  from hypothesis.control import assume, reject
  from hypothesis.internal.conjecture.utils import calc_label_from_name
  from hypothesis.internal.floats import float_of
  from hypothesis.strategies._internal.strategies import SearchStrategy
label_desc: Use image node_id 1 to create a new FixedBoundedFloatStrategy object from inherited base classes: SearchStrategy with example: obj = FixedBoundedFloatStrategy(lower_bound, upper_bound, width)