Merge pull request aimacode#190 from SnShine/addRounder

Removed truncate() and added rounder() as discussed in aimacode#183

Author: norvig

tests/test_probability.py

@@ -110,11 +110,11 @@ def test_forward_backward():
     umbrellaHMM = HiddenMarkovModel(umbrella_transition, umbrella_sensor)
 
     umbrella_evidence = [T, T, F, T, T]
-    assert truncate(forward_backward(umbrellaHMM, umbrella_evidence, umbrella_prior)) == [[0.6469, 0.3531],
+    assert rounder(forward_backward(umbrellaHMM, umbrella_evidence, umbrella_prior)) == [[0.6469, 0.3531],
                 [0.8673, 0.1327], [0.8204, 0.1796], [0.3075, 0.6925], [0.8204, 0.1796], [0.8673, 0.1327]]
 
     umbrella_evidence = [T, F, T, F, T]
-    assert truncate(forward_backward(umbrellaHMM, umbrella_evidence, umbrella_prior)) == [[0.5871, 0.4129],
+    assert rounder(forward_backward(umbrellaHMM, umbrella_evidence, umbrella_prior)) == [[0.5871, 0.4129],
                  [0.7177, 0.2823], [0.2324, 0.7676], [0.6072, 0.3928], [0.2324, 0.7676], [0.7177, 0.2823]]
 
 def test_fixed_lag_smoothing():
@@ -126,16 +126,16 @@ def test_fixed_lag_smoothing():
     umbrellaHMM = HiddenMarkovModel(umbrella_transition, umbrella_sensor)
 
     d = 2
-    assert truncate(fixed_lag_smoothing(e_t, umbrellaHMM, d, umbrella_evidence, t)) == [0.1111, 0.8889]
+    assert rounder(fixed_lag_smoothing(e_t, umbrellaHMM, d, umbrella_evidence, t)) == [0.1111, 0.8889]
     d = 5
-    assert truncate(fixed_lag_smoothing(e_t, umbrellaHMM, d, umbrella_evidence, t)) is None
+    assert fixed_lag_smoothing(e_t, umbrellaHMM, d, umbrella_evidence, t) is None
 
     umbrella_evidence = [T, T, F, T, T]
     # t = 4
     e_t = T
 
     d = 1
-    assert truncate(fixed_lag_smoothing(e_t, umbrellaHMM, d, umbrella_evidence, t)) == [0.9939, 0.0061]
+    assert rounder(fixed_lag_smoothing(e_t, umbrellaHMM, d, umbrella_evidence, t)) == [0.9939, 0.0061]
 
 
 if __name__ == '__main__':

tests/test_utils.py

@@ -113,20 +113,20 @@ def test_scalar_vector_product():
     assert scalar_vector_product(2, [1, 2, 3]) == [2, 4, 6]
 
 def test_scalar_matrix_product():
-  assert truncate(scalar_matrix_product(-5, [[1, 2], [3, 4], [0, 6]])) == [[-5, -10], [-15, -20], [0, -30]]
-  assert truncate(scalar_matrix_product(0.2, [[1, 2], [2, 3]])) == [[0.2, 0.4], [0.4, 0.6]]
+  assert rounder(scalar_matrix_product(-5, [[1, 2], [3, 4], [0, 6]])) == [[-5, -10], [-15, -20], [0, -30]]
+  assert rounder(scalar_matrix_product(0.2, [[1, 2], [2, 3]])) == [[0.2, 0.4], [0.4, 0.6]]
 
 
 def test_inverse_matrix():
-  assert truncate(inverse_matrix([[1, 0], [0, 1]])) == [[1, 0], [0, 1]]
-  assert truncate(inverse_matrix([[2, 1], [4, 3]])) == [[1.5, -0.5], [-2.0, 1.0]]
-  assert truncate(inverse_matrix([[4, 7], [2, 6]])) == [[0.6, -0.7], [-0.2, 0.4]]
-
-def test_truncate():
-  assert truncate(5.3330000300330) == 5.3330
-  assert truncate(10.234566) == 10.2346
-  assert truncate([1.234566, 0.555555, 6.010101]) == [1.2346, 0.5556, 6.0101]
-  assert truncate([[1.234566, 0.555555, 6.010101],
+  assert rounder(inverse_matrix([[1, 0], [0, 1]])) == [[1, 0], [0, 1]]
+  assert rounder(inverse_matrix([[2, 1], [4, 3]])) == [[1.5, -0.5], [-2.0, 1.0]]
+  assert rounder(inverse_matrix([[4, 7], [2, 6]])) == [[0.6, -0.7], [-0.2, 0.4]]
+
+def test_rounder():
+  assert rounder(5.3330000300330) == 5.3330
+  assert rounder(10.234566) == 10.2346
+  assert rounder([1.234566, 0.555555, 6.010101]) == [1.2346, 0.5556, 6.0101]
+  assert rounder([[1.234566, 0.555555, 6.010101],
                    [10.505050, 12.121212, 6.030303]]) == [[1.2346, 0.5556, 6.0101],
                                                           [10.5051, 12.1212, 6.0303]]
 

utils.py

@@ -243,16 +243,13 @@ def weighted_sampler(seq, weights):
 
     return lambda: seq[bisect.bisect(totals, random.uniform(0, totals[-1]))]
 
-def truncate(x, n = 4):
-    """Truncates floats, vectors, matrices to n decimal values"""
-    if isinstance(x, float):
-        return(float("{0:.{1}f}".format(x, n)))
-    elif isinstance(x, list) and isinstance(x[0], float):
-        return([float("{0:.{1}f}".format(i, n)) for i in x])
-    elif isinstance(x, list) and isinstance(x[0], list) and isinstance(x[0][0], float):
-        return([[float("{0:.{1}f}".format(i, n)) for i in row] for row in x])
+def rounder(numbers, d = 4):
+    "Round a single number, or sequence of numbers, to d decimal places."
+    if isinstance(numbers, (int, float)):
+        return round(numbers, d)
     else:
-        return x
+        constructor = type(numbers)     # Can be list, set, tuple, etc.
+        return constructor(rounder(n, d) for n in numbers)
 
 def num_or_str(x):
     """The argument is a string; convert to a number if