old_contents: """Specific hypothesis strategies that are useful for testing.
  
  It defines the following strategies:
  
  - :code:`dimension`: Represents a size or dimension e.g. for numpy arrays image
    sizes etc.
  - :code:`real`: Represents a real number in the range +/-1 million
  """
  from math import pi
  
  from hypothesis.strategies import integers, floats
  
  real = floats(min_value=-1e6, max_value=1e6)
  angle = floats(min_value=-pi, max_value=pi)
  
  dimension = integers(min_value=4, max_value=1024)
  
new_contents: """Specific hypothesis strategies that are useful for testing.
  
  It defines the following strategies:
  
  - :code:`dimension`: Represents a size or dimension e.g. for numpy arrays image
    sizes etc.
  - :code:`real`: Represents a real number in the range +/-1 million
  """
  from math import pi
  
  import numpy as np
  from hypothesis.strategies import integers, floats, tuples
  from hypothesis.extra.numpy import arrays
  
  # Basic types
  real = floats(min_value=-1e6, max_value=1e6)
  angle = floats(min_value=-pi, max_value=pi)
  dimension = integers(min_value=4, max_value=1024)
  small_dimension = integers(min_value=4, max_value=256)
  image_size = tuples(small_dimension, small_dimension)
  
  # Stylo data
  domain_values = arrays(np.float64, image_size, elements=real)
  shape_mask = arrays(np.bool_, image_size)
  
subject: Update hypothesis strategies