
from __future__ import absolute_import

# Global random number generator
import numpy as np
prng = np.random.RandomState()
# Set the error level to ignore...for example: log2(0).
np.seterr(all='ignore')
del np

from .equal import close, allclose
from .sampling import sample, _sample, _samples
from .ops import get_ops, LinearOperations, LogOperations
from .fraction import approximate_fraction
from .sigmaalgebra import sigma_algebra, is_sigma_algebra, atom_set

from . import aitchison
from . import combinatorics


from __future__ import absolute_import

# Global random number generator
import numpy as np
prng = np.random.RandomState()
# Set the error level to ignore...for example: log2(0).
np.seterr(all='ignore')
del np

from .equal import close, allclose
from .sampling import sample, _sample, _samples
from .ops import get_ops, LinearOperations, LogOperations
from .fraction import approximate_fraction
from .sigmaalgebra import sigma_algebra, is_sigma_algebra, atom_set
from .perturb import perturb_pmf

from . import aitchison
from . import combinatorics

Make perturb_pmf available in dit.math.
Make perturb_pmf available in dit.math.

  
  from __future__ import absolute_import
  
  # Global random number generator
  import numpy as np
  prng = np.random.RandomState()
  # Set the error level to ignore...for example: log2(0).
  np.seterr(all='ignore')
  del np
  
  from .equal import close, allclose
  from .sampling import sample, _sample, _samples
  from .ops import get_ops, LinearOperations, LogOperations
  from .fraction import approximate_fraction
  from .sigmaalgebra import sigma_algebra, is_sigma_algebra, atom_set
+ from .perturb import perturb_pmf
  
  from . import aitchison
  from . import combinatorics
  
Make perturb_pmf available in dit.math.
## Code Before:

from __future__ import absolute_import

# Global random number generator
import numpy as np
prng = np.random.RandomState()
# Set the error level to ignore...for example: log2(0).
np.seterr(all='ignore')
del np

from .equal import close, allclose
from .sampling import sample, _sample, _samples
from .ops import get_ops, LinearOperations, LogOperations
from .fraction import approximate_fraction
from .sigmaalgebra import sigma_algebra, is_sigma_algebra, atom_set

from . import aitchison
from . import combinatorics

## Instruction:
Make perturb_pmf available in dit.math.
## Code After:

from __future__ import absolute_import

# Global random number generator
import numpy as np
prng = np.random.RandomState()
# Set the error level to ignore...for example: log2(0).
np.seterr(all='ignore')
del np

from .equal import close, allclose
from .sampling import sample, _sample, _samples
from .ops import get_ops, LinearOperations, LogOperations
from .fraction import approximate_fraction
from .sigmaalgebra import sigma_algebra, is_sigma_algebra, atom_set
from .perturb import perturb_pmf

from . import aitchison
from . import combinatorics
