From 2f827370ec4652ec4607603d844da63e62a0b0e8 Mon Sep 17 00:00:00 2001
From: Matt McKay <mamckay@gmail.com>
Date: Thu, 14 Apr 2016 16:58:02 -0400
Subject: [PATCH 1/6] Remove optional numba installation code and make numba
 jit a strict dependancy

---
 quantecon/lss.py              |   8 +--
 quantecon/markov/gth_solve.py | 102 +++++++++++++++++-----------------
 quantecon/markov/random.py    |   8 +--
 quantecon/random/utilities.py |   9 +--
 quantecon/util/__init__.py    |   1 -
 quantecon/util/array.py       |  11 +---
 quantecon/util/external.py    |  24 --------
 7 files changed, 61 insertions(+), 102 deletions(-)
 delete mode 100644 quantecon/util/external.py

diff --git a/quantecon/lss.py b/quantecon/lss.py
index dbfc2d029..1deb600da 100644
--- a/quantecon/lss.py
+++ b/quantecon/lss.py
@@ -9,10 +9,10 @@
 import numpy as np
 from numpy.random import multivariate_normal
 from scipy.linalg import solve
+from numba import jit
 
-#-Check if Numba is Available-#
-from .util import numba_installed, jit
-
+#TODO: Should this be specified with (nopython=True?)
+@jit
 def simulate_linear_model(A, x0, v, ts_length):
     """
     This is a separate function for simulating a vector linear system of 
@@ -55,8 +55,6 @@ def simulate_linear_model(A, x0, v, ts_length):
                 x[i, t+1] += A[i, j] * x[j, t]   #Dot Product
     return x
 
-if numba_installed:
-    simulate_linear_model = jit(simulate_linear_model)
 
 class LinearStateSpace(object):
     """
diff --git a/quantecon/markov/gth_solve.py b/quantecon/markov/gth_solve.py
index 7881dd493..a8affa6a9 100644
--- a/quantecon/markov/gth_solve.py
+++ b/quantecon/markov/gth_solve.py
@@ -10,15 +10,14 @@
 import numpy as np
 from numba import jit
 
-from ..util import numba_installed, jit
-if not numba_installed:
-    try:
-        xrange
-    except:  # python3
-        xrange = range
+#TODO: Remove as we no longer officially support Python <3.5?
+try:
+    xrange
+except:  # python3
+    xrange = range
 
 
-def gth_solve(A, overwrite=False):
+def gth_solve(A, overwrite=False, use_jit=True):
     r"""
     This routine computes the stationary distribution of an irreducible
     Markov transition matrix (stochastic matrix) or transition rate
@@ -74,11 +73,11 @@ def gth_solve(A, overwrite=False):
     n = A1.shape[0]
     x = np.zeros(n)
 
-    if numba_installed:
+    if use_jit:
         _gth_solve_jit(A1, x)
         return x
 
-    # if not numba_installed
+    # if not using jit
     # === Reduction === #
     for k in xrange(n-1):
         scale = np.sum(A1[k, k+1:n])
@@ -103,46 +102,45 @@ def gth_solve(A, overwrite=False):
     return x
 
 
-if numba_installed:
-    @jit(nopython=True)
-    def _gth_solve_jit(A, out):
-        """
-        JIT complied version of the main routine of gth_solve.
-
-        Parameters
-        ----------
-        A : numpy.ndarray(float, ndim=2)
-            Stochastic matrix or generator matrix. Must be of shape n x n.
-            Data will be overwritten.
-
-        out : numpy.ndarray(float, ndim=1)
-            Output array in which to place the stationary distribution of A.
-
-        """
-        n = A.shape[0]
-
-        # === Reduction === #
-        for k in range(n-1):
-            scale = np.sum(A[k, k+1:n])
-            if scale <= 0:
-                # There is one (and only one) recurrent class contained in
-                # {0, ..., k};
-                # compute the solution associated with that recurrent class.
-                n = k+1
-                break
-            for i in range(k+1, n):
-                A[i, k] /= scale
-
-                for j in range(k+1, n):
-                    A[i, j] += A[i, k] * A[k, j]
-
-        # === Backward substitution === #
-        out[n-1] = 1
-        for k in range(n-2, -1, -1):
-            for i in range(k+1, n):
-                out[k] += out[i] * A[i, k]
-
-        # === Normalization === #
-        norm = np.sum(out)
-        for k in range(n):
-            out[k] /= norm
+@jit(nopython=True)
+def _gth_solve_jit(A, out):
+    """
+    JIT complied version of the main routine of gth_solve.
+
+    Parameters
+    ----------
+    A : numpy.ndarray(float, ndim=2)
+        Stochastic matrix or generator matrix. Must be of shape n x n.
+        Data will be overwritten.
+
+    out : numpy.ndarray(float, ndim=1)
+        Output array in which to place the stationary distribution of A.
+
+    """
+    n = A.shape[0]
+
+    # === Reduction === #
+    for k in range(n-1):
+        scale = np.sum(A[k, k+1:n])
+        if scale <= 0:
+            # There is one (and only one) recurrent class contained in
+            # {0, ..., k};
+            # compute the solution associated with that recurrent class.
+            n = k+1
+            break
+        for i in range(k+1, n):
+            A[i, k] /= scale
+
+            for j in range(k+1, n):
+                A[i, j] += A[i, k] * A[k, j]
+
+    # === Backward substitution === #
+    out[n-1] = 1
+    for k in range(n-2, -1, -1):
+        for i in range(k+1, n):
+            out[k] += out[i] * A[i, k]
+
+    # === Normalization === #
+    norm = np.sum(out)
+    for k in range(n):
+        out[k] /= norm
diff --git a/quantecon/markov/random.py b/quantecon/markov/random.py
index 4ff567897..db0cdba95 100644
--- a/quantecon/markov/random.py
+++ b/quantecon/markov/random.py
@@ -8,10 +8,11 @@
 """
 import numpy as np
 import scipy.sparse
+from numba import jit
 
 from .core import MarkovChain
 from .ddp import DiscreteDP
-from ..util import check_random_state, numba_installed, jit
+from ..util import check_random_state
 from ..random import probvec, sample_without_replacement
 
 
@@ -218,7 +219,8 @@ def random_discrete_dp(num_states, num_actions, beta=None,
     ddp = DiscreteDP(R, Q, beta, s_indices, a_indices)
     return ddp
 
-
+#TODO: Should this use (nopython=True) flag?
+@jit
 def _sa_indices(num_states, num_actions):
     L = num_states * num_actions
     s_indices = np.empty(L, dtype=int)
@@ -233,5 +235,3 @@ def _sa_indices(num_states, num_actions):
 
     return s_indices, a_indices
 
-if numba_installed:
-    _sa_indices = jit(_sa_indices)
diff --git a/quantecon/random/utilities.py b/quantecon/random/utilities.py
index 98944f01f..2883a250c 100644
--- a/quantecon/random/utilities.py
+++ b/quantecon/random/utilities.py
@@ -3,7 +3,7 @@
 """
 
 import numpy as np
-from ..util import check_random_state, numba_installed, jit
+from ..util import check_random_state
 
 #-Generating Arrays and Vectors-#
 
@@ -75,6 +75,8 @@ def _diff(r, out):
         out[i, n] = 1 - r[i, n-1]
 
 
+#TODO: Should this use (nopython=True) flag?
+@jit
 def sample_without_replacement(n, k, num_trials=None, random_state=None):
     """
     Randomly choose k integers without replacement from 0, ..., n-1.
@@ -141,8 +143,3 @@ def sample_without_replacement(n, k, num_trials=None, random_state=None):
         return result[0]
     else:
         return result
-
-if numba_installed:
-    docs = sample_without_replacement.__doc__
-    sample_without_replacement = jit(sample_without_replacement)
-    sample_without_replacement.__doc__ = docs
diff --git a/quantecon/util/__init__.py b/quantecon/util/__init__.py
index 39dcf0b0e..1bc7ef5ce 100644
--- a/quantecon/util/__init__.py
+++ b/quantecon/util/__init__.py
@@ -3,7 +3,6 @@
 """
 
 from .array import searchsorted
-from .external import jit, numba_installed
 from .notebooks import fetch_nb_dependencies
 from .random import check_random_state
 from .timing import tic, tac, toc
\ No newline at end of file
diff --git a/quantecon/util/array.py b/quantecon/util/array.py
index 17db7caac..02ebeff32 100644
--- a/quantecon/util/array.py
+++ b/quantecon/util/array.py
@@ -9,13 +9,12 @@
 """
 
 import numpy as np
-from .external import numba_installed, jit
 
 # ----------------- #
 # -ARRAY UTILITIES- #
 # ----------------- #
 
-
+@jit(nopython=True)
 def _searchsorted(a, v):
     """
     Custom version of np.searchsorted. Return the largest index `i` such
@@ -61,11 +60,3 @@ def _searchsorted(a, v):
         else:
             lo = m
     return hi
-
-if numba_installed:
-    searchsorted = jit(nopython=True)(_searchsorted)
-else:
-    def searchsorted(a, v):
-        return np.searchsorted(a, v, side='right')
-
-searchsorted.__doc__ = _searchsorted.__doc__
diff --git a/quantecon/util/external.py b/quantecon/util/external.py
deleted file mode 100644
index 6578640d8..000000000
--- a/quantecon/util/external.py
+++ /dev/null
@@ -1,24 +0,0 @@
-"""
-External Module
-===============
-
-This module is an import location for flexible dependancies on external packages such as numba
-
-Packages
---------
-  1. numba
-
-"""
-
-import warnings
-
-#-Setup Installed Indicator and Import JIT function for NUMBA-#
-
-numba_installed = True
-try:
-    from numba import jit
-except ImportError:
-    numba_installed = False
-    jit = None
-    from .common_messages import numba_import_fail_message
-    warnings.warn(numba_import_fail_message, UserWarning)

From 7096e526438abce41c975ef77d3ce6c4215296e5 Mon Sep 17 00:00:00 2001
From: Matt McKay <mamckay@gmail.com>
Date: Thu, 14 Apr 2016 16:59:07 -0400
Subject: [PATCH 2/6] Remove python27 support for xrange due to migration to
 python3.5+

---
 quantecon/markov/gth_solve.py | 11 ++---------
 1 file changed, 2 insertions(+), 9 deletions(-)

diff --git a/quantecon/markov/gth_solve.py b/quantecon/markov/gth_solve.py
index a8affa6a9..ef0ca2af7 100644
--- a/quantecon/markov/gth_solve.py
+++ b/quantecon/markov/gth_solve.py
@@ -10,13 +10,6 @@
 import numpy as np
 from numba import jit
 
-#TODO: Remove as we no longer officially support Python <3.5?
-try:
-    xrange
-except:  # python3
-    xrange = range
-
-
 def gth_solve(A, overwrite=False, use_jit=True):
     r"""
     This routine computes the stationary distribution of an irreducible
@@ -79,7 +72,7 @@ def gth_solve(A, overwrite=False, use_jit=True):
 
     # if not using jit
     # === Reduction === #
-    for k in xrange(n-1):
+    for k in range(n-1):
         scale = np.sum(A1[k, k+1:n])
         if scale <= 0:
             # There is one (and only one) recurrent class contained in
@@ -93,7 +86,7 @@ def gth_solve(A, overwrite=False, use_jit=True):
 
     # === Backward substitution === #
     x[n-1] = 1
-    for k in xrange(n-2, -1, -1):
+    for k in range(n-2, -1, -1):
         x[k] = np.dot(x[k+1:n], A1[k+1:n, k])
 
     # === Normalization === #

From c1c29c9a990d370e245d24efa152daca187f4cb0 Mon Sep 17 00:00:00 2001
From: Matt McKay <mamckay@gmail.com>
Date: Thu, 14 Apr 2016 17:04:19 -0400
Subject: [PATCH 3/6] add import statement that was missed

---
 quantecon/util/array.py | 1 +
 1 file changed, 1 insertion(+)

diff --git a/quantecon/util/array.py b/quantecon/util/array.py
index 02ebeff32..200d7ca98 100644
--- a/quantecon/util/array.py
+++ b/quantecon/util/array.py
@@ -9,6 +9,7 @@
 """
 
 import numpy as np
+from numba import jit
 
 # ----------------- #
 # -ARRAY UTILITIES- #

From bc75fc7cb6a76f11cc8f9f8e89ddfc97f0ba3ed0 Mon Sep 17 00:00:00 2001
From: Matt McKay <mamckay@gmail.com>
Date: Thu, 14 Apr 2016 17:09:42 -0400
Subject: [PATCH 4/6] add adjustment to function name

---
 quantecon/util/array.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/quantecon/util/array.py b/quantecon/util/array.py
index 200d7ca98..9b18e9ebe 100644
--- a/quantecon/util/array.py
+++ b/quantecon/util/array.py
@@ -16,7 +16,7 @@
 # ----------------- #
 
 @jit(nopython=True)
-def _searchsorted(a, v):
+def searchsorted(a, v):
     """
     Custom version of np.searchsorted. Return the largest index `i` such
     that `a[i-1] <= v < a[i]` (for `i = 0`, `v < a[0]`); if `v[n-1] <=

From f58e62505252c20b70852f547107a6d54e4f3e1a Mon Sep 17 00:00:00 2001
From: Matt McKay <mamckay@gmail.com>
Date: Thu, 14 Apr 2016 17:13:28 -0400
Subject: [PATCH 5/6] Add jit import statement

---
 quantecon/random/utilities.py | 2 ++
 1 file changed, 2 insertions(+)

diff --git a/quantecon/random/utilities.py b/quantecon/random/utilities.py
index 2883a250c..904e3dd7d 100644
--- a/quantecon/random/utilities.py
+++ b/quantecon/random/utilities.py
@@ -3,6 +3,8 @@
 """
 
 import numpy as np
+from numba import jit
+
 from ..util import check_random_state
 
 #-Generating Arrays and Vectors-#

From 59bddd5f9d42d9ecd5ae634f62a43420f9045a54 Mon Sep 17 00:00:00 2001
From: Matt McKay <mamckay@gmail.com>
Date: Fri, 15 Apr 2016 10:24:25 -0400
Subject: [PATCH 6/6] Remove #TODO statements post discussion and review

---
 quantecon/lss.py              | 1 -
 quantecon/markov/random.py    | 1 -
 quantecon/random/utilities.py | 2 --
 3 files changed, 4 deletions(-)

diff --git a/quantecon/lss.py b/quantecon/lss.py
index 1deb600da..3cc2b91a4 100644
--- a/quantecon/lss.py
+++ b/quantecon/lss.py
@@ -11,7 +11,6 @@
 from scipy.linalg import solve
 from numba import jit
 
-#TODO: Should this be specified with (nopython=True?)
 @jit
 def simulate_linear_model(A, x0, v, ts_length):
     """
diff --git a/quantecon/markov/random.py b/quantecon/markov/random.py
index db0cdba95..9fb1d055d 100644
--- a/quantecon/markov/random.py
+++ b/quantecon/markov/random.py
@@ -219,7 +219,6 @@ def random_discrete_dp(num_states, num_actions, beta=None,
     ddp = DiscreteDP(R, Q, beta, s_indices, a_indices)
     return ddp
 
-#TODO: Should this use (nopython=True) flag?
 @jit
 def _sa_indices(num_states, num_actions):
     L = num_states * num_actions
diff --git a/quantecon/random/utilities.py b/quantecon/random/utilities.py
index 904e3dd7d..2142fe089 100644
--- a/quantecon/random/utilities.py
+++ b/quantecon/random/utilities.py
@@ -76,8 +76,6 @@ def _diff(r, out):
             out[i, j] = r[i, j] - r[i, j-1]
         out[i, n] = 1 - r[i, n-1]
 
-
-#TODO: Should this use (nopython=True) flag?
 @jit
 def sample_without_replacement(n, k, num_trials=None, random_state=None):
     """