Add fallback for Numba < 0.28

Should be removed once Anaconda is updated to include Naumba >= 0.28

quantecon/game_theory/support_enumeration.py

@@ -11,11 +11,18 @@
 Tardos, and V. Vazirani eds., Algorithmic Game Theory, 2007.
 
 """
+from distutils.version import LooseVersion
 import numpy as np
 import numba
 from numba import jit
 
 
+least_numba_version = LooseVersion('0.28')
+is_numba_required_installed = True
+if LooseVersion(numba.__version__) < least_numba_version:
+ is_numba_required_installed = False
+nopython = is_numba_required_installed
+
 EPS = np.finfo(float).eps
 
 
@@ -39,6 +46,11 @@ def support_enumeration(g):
  list(tuple(ndarray(float, ndim=1)))
  List containing tuples of Nash equilibrium mixed actions.
 
+ Notes
+ -----
+ This routine is jit-complied if Numba version 0.28 or above is
+ installed.
+
  """
  return list(support_enumeration_gen(g))
 
@@ -68,7 +80,7 @@ def support_enumeration_gen(g):
  g.players[1].payoff_array)
 
 
-@jit(nopython=True) # cache=True raises _pickle.PicklingError
+@jit(nopython=nopython) # cache=True raises _pickle.PicklingError
 def _support_enumeration_gen(payoff_matrix0, payoff_matrix1):
  """
  Main body of `support_enumeration_gen`.
@@ -117,7 +129,7 @@ def _support_enumeration_gen(payoff_matrix0, payoff_matrix1):
  next_k_array(supps[0])
 
 
-@jit(nopython=True, cache=True)
+@jit(nopython=nopython, cache=True)
 def _indiff_mixed_action(payoff_matrix, own_supp, opp_supp, A, b, out):
  """
  Given a player's payoff matrix `payoff_matrix`, an array `own_supp`
@@ -270,25 +282,37 @@ def next_k_array(a):
  return a
 
 
-@jit(nopython=True, cache=True)
-def is_singular(a):
- """
- Determine whether matrix `a` is numerically singular, by checking
- its singular values.
+if is_numba_required_installed:
+ @jit(nopython=True, cache=True)
+ def is_singular(a):
+ s = numba.targets.linalg._compute_singular_values(a)
+ if s[-1] <= s[0] * EPS:
+ return True
+ else:
+ return False
+else:
+ def is_singular(a):
+ s = np.linalg.svd(a, compute_uv=False)
+ if s[-1] <= s[0] * EPS:
+ return True
+ else:
+ return False
+
+_is_singular_docstr = \
+"""
+Determine whether matrix `a` is numerically singular, by checking
+its singular values.
 
- Parameters
- ----------
- a : ndarray(float, ndim=2)
-  2-dimensional array of floats.
+Parameters
+----------
+a : ndarray(float, ndim=2)
+ 2-dimensional array of floats.
 
- Returns
- -------
- bool
-  Whether `a` is numerically singular.
+Returns
+-------
+bool
+ Whether `a` is numerically singular.
 
- """
- s = numba.targets.linalg._compute_singular_values(a)
- if s[-1] <= s[0] * EPS:
- return True
- else:
- return False
+"""
+
+is_singular.__doc__ = _is_singular_docstr