1 files changed, 81 insertions, 1 deletions
diff --git a/numpy/core/numeric.py b/numpy/core/numeric.py
index bb13d573e..60111e1f2 100644
--- a/numpy/core/numeric.py
+++ b/numpy/core/numeric.py
@@ -12,7 +12,7 @@ __all__ = ['newaxis', 'ndarray', 'flatiter', 'nditer', 'nested_iters', 'ufunc',
            'array_repr', 'array_str', 'set_string_function',
            'little_endian', 'require',
            'fromiter', 'array_equal', 'array_equiv',
-           'indices', 'fromfunction',
+           'indices', 'fromfunction', 'isclose',
            'load', 'loads', 'isscalar', 'binary_repr', 'base_repr',
            'ones', 'identity', 'allclose', 'compare_chararrays', 'putmask',
            'seterr', 'geterr', 'setbufsize', 'getbufsize',
@@ -2024,6 +2024,86 @@ def allclose(a, b, rtol=1.e-5, atol=1.e-8):
     y = y[~xinf]
     return all(less_equal(absolute(x-y), atol + rtol * absolute(y)))
 
+def isclose(a, b, rtol=1.e-5, atol=1.e-8, equal_nan=False):
+    """
+    Returns a boolean array where two arrays are element-wise equal within a
+    tolerance.
+
+    The tolerance values are positive, typically very small numbers.  The
+    relative difference (`rtol` * abs(`b`)) and the absolute difference
+    `atol` are added together to compare against the absolute difference
+    between `a` and `b`.
+
+    Parameters
+    ----------
+    a, b : array_like
+        Input arrays to compare.
+    rtol : float
+        The relative tolerance parameter (see Notes).
+    atol : float
+        The absolute tolerance parameter (see Notes).
+    equal_nan : bool
+        Whether to compare NaN's as equal.  If True, NaN's in `a` will be
+        considered equal to NaN's in `b` in the output array.
+
+    Returns
+    -------
+    y : array_like
+        Returns a boolean array of where `a` and `b` are equal within the
+        given tolerance. If both `a` and `b` are scalars, returns a single
+        boolean value.
+
+    See Also
+    --------
+    allclose
+
+    Notes
+    -----
+    For finite values, isclose uses the following equation to test whether
+    two floating point values are equivalent.
+
+     absolute(`a` - `b`) <= (`atol` + `rtol` * absolute(`b`))
+
+    The above equation is not symmetric in `a` and `b`, so that
+    `isclose(a, b)` might be different from `isclose(b, a)` in
+    some rare cases.
+
+    Examples
+    --------
+    >>> np.isclose([1e10,1e-7], [1.00001e10,1e-8])
+    array([True, False])
+    >>> np.isclose([1e10,1e-8], [1.00001e10,1e-9])
+    array([True, True])
+    >>> np.isclose([1e10,1e-8], [1.0001e10,1e-9])
+    array([False, True])
+    >>> np.isclose([1.0, np.nan], [1.0, np.nan])
+    array([True, False])
+    >>> np.isclose([1.0, np.nan], [1.0, np.nan], equal_nan=True)
+    array([True, True])
+    """
+    def within_tol(x, y, atol, rtol):
+        result = less_equal(abs(x-y), atol + rtol * abs(y))
+        if isscalar(a) and isscalar(b):
+            result = bool(result)
+        return result
+    x = array(a, copy=False, ndmin=1)
+    y = array(b, copy=False, ndmin=1)
+    xfin = isfinite(x)
+    yfin = isfinite(y)
+    if all(xfin) and all(yfin):
+        return within_tol(x, y, atol, rtol)
+    else:
+        # Avoid subtraction with infinite/nan values...
+        cond = zeros(broadcast(x, y).shape, dtype=bool)
+        mask = xfin & yfin
+        cond[mask] = within_tol(x[mask], y[mask], atol, rtol)
+        # Check for equality of infinite values...
+        cond[~mask] = (x[~mask] == y[~mask])
+        if equal_nan:
+            # Make NaN == NaN
+            cond[isnan(x) & isnan(y)] = True
+        return cond
+
 def array_equal(a1, a2):
     """
     True if two arrays have the same shape and elements, False otherwise.