Author: Alex Gaynor <alex.gay...@gmail.com>
Branch:
Changeset: r61645:18b9462c447b
Date: 2013-02-22 23:29 -0800
http://bitbucket.org/pypy/pypy/changeset/18b9462c447b/
Log: merged upstream
diff --git a/lib_pypy/numpypy/__init__.py b/lib_pypy/numpypy/__init__.py
--- a/lib_pypy/numpypy/__init__.py
+++ b/lib_pypy/numpypy/__init__.py
@@ -1,5 +1,6 @@
from _numpypy import *
from .core import *
+from .lib import *
import _numpypy
__all__ = _numpypy.__all__
diff --git a/lib_pypy/numpypy/core/fromnumeric.py
b/lib_pypy/numpypy/core/fromnumeric.py
--- a/lib_pypy/numpypy/core/fromnumeric.py
+++ b/lib_pypy/numpypy/core/fromnumeric.py
@@ -1290,7 +1290,9 @@
array([3, 4, 2, 3, 4, 5, 6, 7, 8, 8])
"""
- raise NotImplementedError('Waiting on interp level method')
+ if not hasattr(a, 'clip'):
+ a = numpypy.array(a)
+ return a.clip(a_min, a_max, out=out)
def sum(a, axis=None, dtype=None, out=None):
diff --git a/lib_pypy/numpypy/core/numeric.py b/lib_pypy/numpypy/core/numeric.py
--- a/lib_pypy/numpypy/core/numeric.py
+++ b/lib_pypy/numpypy/core/numeric.py
@@ -501,3 +501,34 @@
a = asarray(a)
b = asarray(b)
return a.ravel()[:,newaxis]*b.ravel()[newaxis,:]
+
+def identity(n, dtype=None):
+ """
+ Return the identity array.
+
+ The identity array is a square array with ones on
+ the main diagonal.
+
+ Parameters
+ ----------
+ n : int
+ Number of rows (and columns) in `n` x `n` output.
+ dtype : data-type, optional
+ Data-type of the output. Defaults to ``float``.
+
+ Returns
+ -------
+ out : ndarray
+ `n` x `n` array with its main diagonal set to one,
+ and all other elements 0.
+
+ Examples
+ --------
+ >>> np.identity(3)
+ array([[ 1., 0., 0.],
+ [ 0., 1., 0.],
+ [ 0., 0., 1.]])
+
+ """
+ from numpy import eye
+ return eye(n, dtype=dtype)
diff --git a/lib_pypy/numpypy/lib/__init__.py b/lib_pypy/numpypy/lib/__init__.py
new file mode 100644
--- /dev/null
+++ b/lib_pypy/numpypy/lib/__init__.py
@@ -0,0 +1,2 @@
+from .function_base import *
+from .twodim_base import *
diff --git a/lib_pypy/numpypy/lib/function_base.py
b/lib_pypy/numpypy/lib/function_base.py
new file mode 100644
--- /dev/null
+++ b/lib_pypy/numpypy/lib/function_base.py
@@ -0,0 +1,8 @@
+from _numpypy import array
+
+def average(a):
+ # This implements a weighted average, for now we don't implement the
+ # weighting, just the average part!
+ if not hasattr(a, "mean"):
+ a = array(a)
+ return a.mean()
diff --git a/lib_pypy/numpypy/lib/twodim_base.py
b/lib_pypy/numpypy/lib/twodim_base.py
new file mode 100644
--- /dev/null
+++ b/lib_pypy/numpypy/lib/twodim_base.py
@@ -0,0 +1,52 @@
+from _numpypy import zeros
+
+def eye(N, M=None, k=0, dtype=float):
+ """
+ Return a 2-D array with ones on the diagonal and zeros elsewhere.
+
+ Parameters
+ ----------
+ N : int
+ Number of rows in the output.
+ M : int, optional
+ Number of columns in the output. If None, defaults to `N`.
+ k : int, optional
+ Index of the diagonal: 0 (the default) refers to the main diagonal,
+ a positive value refers to an upper diagonal, and a negative value
+ to a lower diagonal.
+ dtype : data-type, optional
+ Data-type of the returned array.
+
+ Returns
+ -------
+ I : ndarray of shape (N,M)
+ An array where all elements are equal to zero, except for the `k`-th
+ diagonal, whose values are equal to one.
+
+ See Also
+ --------
+ identity : (almost) equivalent function
+ diag : diagonal 2-D array from a 1-D array specified by the user.
+
+ Examples
+ --------
+ >>> np.eye(2, dtype=int)
+ array([[1, 0],
+ [0, 1]])
+ >>> np.eye(3, k=1)
+ array([[ 0., 1., 0.],
+ [ 0., 0., 1.],
+ [ 0., 0., 0.]])
+
+ """
+ if M is None:
+ M = N
+ m = zeros((N, M), dtype=dtype)
+ if k >= M:
+ return m
+ if k >= 0:
+ i = k
+ else:
+ i = (-k) * M
+ m[:M-k].flat[i::M+1] = 1
+ return m
diff --git a/pypy/module/micronumpy/__init__.py
b/pypy/module/micronumpy/__init__.py
--- a/pypy/module/micronumpy/__init__.py
+++ b/pypy/module/micronumpy/__init__.py
@@ -163,9 +163,6 @@
interpleveldefs[exposed] = "interp_ufuncs.get(space).%s" % impl
appleveldefs = {
- 'average': 'app_numpy.average',
- 'identity': 'app_numpy.identity',
- 'eye': 'app_numpy.eye',
'arange': 'app_numpy.arange',
}
def setup_after_space_initialization(self):
diff --git a/pypy/module/micronumpy/app_numpy.py
b/pypy/module/micronumpy/app_numpy.py
--- a/pypy/module/micronumpy/app_numpy.py
+++ b/pypy/module/micronumpy/app_numpy.py
@@ -2,39 +2,6 @@
import _numpypy
-def average(a):
- # This implements a weighted average, for now we don't implement the
- # weighting, just the average part!
- if not hasattr(a, "mean"):
- a = _numpypy.array(a)
- return a.mean()
-
-def identity(n, dtype=None):
- a = _numpypy.zeros((n, n), dtype=dtype)
- for i in range(n):
- a[i][i] = 1
- return a
-
-def eye(n, m=None, k=0, dtype=None):
- if m is None:
- m = n
- a = _numpypy.zeros((n, m), dtype=dtype)
- ni = 0
- mi = 0
-
- if k < 0:
- p = n + k
- ni = -k
- else:
- p = n - k
- mi = k
-
- while ni < n and mi < m:
- a[ni][mi] = 1
- ni += 1
- mi += 1
- return a
-
def arange(start, stop=None, step=1, dtype=None):
'''arange([start], stop[, step], dtype=None)
Generate values in the half-interval [start, stop).
diff --git a/pypy/module/micronumpy/interp_numarray.py
b/pypy/module/micronumpy/interp_numarray.py
--- a/pypy/module/micronumpy/interp_numarray.py
+++ b/pypy/module/micronumpy/interp_numarray.py
@@ -453,13 +453,13 @@
@unwrap_spec(mode=str)
def descr_choose(self, space, w_choices, mode='raise', w_out=None):
- if w_out is not None and not isinstance(w_out, W_NDimArray):
+ if not space.is_none(w_out) and not isinstance(w_out, W_NDimArray):
raise OperationError(space.w_TypeError, space.wrap(
"return arrays must be of ArrayType"))
return interp_arrayops.choose(space, self, w_choices, w_out, mode)
def descr_clip(self, space, w_min, w_max, w_out=None):
- if w_out is not None and not isinstance(w_out, W_NDimArray):
+ if not space.is_none(w_out) and not isinstance(w_out, W_NDimArray):
raise OperationError(space.w_TypeError, space.wrap(
"return arrays must be of ArrayType"))
min = convert_to_array(space, w_min)
diff --git a/pypy/module/micronumpy/test/test_arrayops.py
b/pypy/module/micronumpy/test/test_arrayops.py
--- a/pypy/module/micronumpy/test/test_arrayops.py
+++ b/pypy/module/micronumpy/test/test_arrayops.py
@@ -99,10 +99,13 @@
def test_choose_out(self):
from _numpypy import array
a, b, c = array([1, 2, 3]), [4, 5, 6], 13
+ r = array([2, 1, 0]).choose([a, b, c], out=None)
+ assert (r == [13, 5, 3]).all()
+ assert (a == [1, 2, 3]).all()
r = array([2, 1, 0]).choose([a, b, c], out=a)
assert (r == [13, 5, 3]).all()
assert (a == [13, 5, 3]).all()
-
+
def test_choose_modes(self):
from _numpypy import array
a, b, c = array([1, 2, 3]), [4, 5, 6], 13
diff --git a/pypy/module/micronumpy/test/test_complex.py
b/pypy/module/micronumpy/test/test_complex.py
--- a/pypy/module/micronumpy/test/test_complex.py
+++ b/pypy/module/micronumpy/test/test_complex.py
@@ -382,7 +382,7 @@
def test_conjugate(self):
from _numpypy import conj, conjugate, complex128, complex64
- import _numpypy as np
+ import numpypy as np
c0 = complex128(complex(2.5, 0))
c1 = complex64(complex(1, 2))
diff --git a/pypy/module/micronumpy/test/test_module.py
b/pypy/module/micronumpy/test/test_module.py
deleted file mode 100644
--- a/pypy/module/micronumpy/test/test_module.py
+++ /dev/null
@@ -1,8 +0,0 @@
-from pypy.module.micronumpy.test.test_base import BaseNumpyAppTest
-
-
-class AppTestNumPyModule(BaseNumpyAppTest):
- def test_average(self):
- from _numpypy import array, average
- assert average(range(10)) == 4.5
- assert average(array(range(10))) == 4.5
diff --git a/pypy/module/micronumpy/test/test_numarray.py
b/pypy/module/micronumpy/test/test_numarray.py
--- a/pypy/module/micronumpy/test/test_numarray.py
+++ b/pypy/module/micronumpy/test/test_numarray.py
@@ -1188,55 +1188,6 @@
assert (array([[1,2],[3,4]]).prod(0) == [3, 8]).all()
assert (array([[1,2],[3,4]]).prod(1) == [2, 12]).all()
- def test_identity(self):
- from _numpypy import identity, array
- from _numpypy import int32, float64, dtype
- a = identity(0)
- assert len(a) == 0
- assert a.dtype == dtype('float64')
- assert a.shape == (0, 0)
- b = identity(1, dtype=int32)
- assert len(b) == 1
- assert b[0][0] == 1
- assert b.shape == (1, 1)
- assert b.dtype == dtype('int32')
- c = identity(2)
- assert c.shape == (2, 2)
- assert (c == [[1, 0], [0, 1]]).all()
- d = identity(3, dtype='int32')
- assert d.shape == (3, 3)
- assert d.dtype == dtype('int32')
- assert (d == [[1, 0, 0], [0, 1, 0], [0, 0, 1]]).all()
-
- def test_eye(self):
- from _numpypy import eye
- from _numpypy import int32, dtype
- a = eye(0)
- assert len(a) == 0
- assert a.dtype == dtype('float64')
- assert a.shape == (0, 0)
- b = eye(1, dtype=int32)
- assert len(b) == 1
- assert b[0][0] == 1
- assert b.shape == (1, 1)
- assert b.dtype == dtype('int32')
- c = eye(2)
- assert c.shape == (2, 2)
- assert (c == [[1, 0], [0, 1]]).all()
- d = eye(3, dtype='int32')
- assert d.shape == (3, 3)
- assert d.dtype == dtype('int32')
- assert (d == [[1, 0, 0], [0, 1, 0], [0, 0, 1]]).all()
- e = eye(3, 4)
- assert e.shape == (3, 4)
- assert (e == [[1, 0, 0, 0], [0, 1, 0, 0], [0, 0, 1, 0]]).all()
- f = eye(2, 4, k=3)
- assert f.shape == (2, 4)
- assert (f == [[0, 0, 0, 1], [0, 0, 0, 0]]).all()
- g = eye(3, 4, k=-1)
- assert g.shape == (3, 4)
- assert (g == [[0, 0, 0, 0], [1, 0, 0, 0], [0, 1, 0, 0]]).all()
-
def test_prod(self):
from _numpypy import array
a = array(range(1, 6))
@@ -1754,7 +1705,8 @@
from _numpypy import array
a = array([1, 2, 17, -3, 12])
assert (a.clip(-2, 13) == [1, 2, 13, -2, 12]).all()
- assert (a.clip(-1, 1) == [1, 1, 1, -1, 1]).all()
+ assert (a.clip(-1, 1, out=None) == [1, 1, 1, -1, 1]).all()
+ assert (a == [1, 2, 17, -3, 12]).all()
assert (a.clip(-1, [1, 2, 3, 4, 5]) == [1, 2, 3, -1, 5]).all()
assert (a.clip(-2, 13, out=a) == [1, 2, 13, -2, 12]).all()
assert (a == [1, 2, 13, -2, 12]).all()
diff --git a/pypy/module/test_lib_pypy/numpypy/core/test_fromnumeric.py
b/pypy/module/test_lib_pypy/numpypy/core/test_fromnumeric.py
--- a/pypy/module/test_lib_pypy/numpypy/core/test_fromnumeric.py
+++ b/pypy/module/test_lib_pypy/numpypy/core/test_fromnumeric.py
@@ -34,6 +34,20 @@
# a = array([(1, 2), (3, 4)], dtype=[('x', 'i4'), ('y', 'i4')])
# assert shape(a) == (2,)
+ def test_clip(self):
+ import numpypy as np
+ a = np.arange(10)
+ b = np.clip(a, 1, 8)
+ assert (b == [1, 1, 2, 3, 4, 5, 6, 7, 8, 8]).all()
+ assert (a == [0, 1, 2, 3, 4, 5, 6, 7, 8, 9]).all()
+ b = np.clip(a, 3, 6, out=a)
+ assert (b == [3, 3, 3, 3, 4, 5, 6, 6, 6, 6]).all()
+ assert (a == [3, 3, 3, 3, 4, 5, 6, 6, 6, 6]).all()
+ a = np.arange(10)
+ b = np.clip(a, [3,4,1,1,1,4,4,4,4,4], 8)
+ assert (b == [3, 4, 2, 3, 4, 5, 6, 7, 8, 8]).all()
+ assert (a == [0, 1, 2, 3, 4, 5, 6, 7, 8, 9]).all()
+
def test_sum(self):
# tests taken from numpy/core/fromnumeric.py docstring
from numpypy import array, sum, ones, zeros
diff --git a/pypy/module/test_lib_pypy/numpypy/core/test_numeric.py
b/pypy/module/test_lib_pypy/numpypy/core/test_numeric.py
--- a/pypy/module/test_lib_pypy/numpypy/core/test_numeric.py
+++ b/pypy/module/test_lib_pypy/numpypy/core/test_numeric.py
@@ -20,6 +20,7 @@
assert base_repr(-12, 10, 4) == '-000012'
assert base_repr(-12, 4) == '-30'
+
class AppTestRepr(BaseNumpyAppTest):
def test_repr(self):
from numpypy import array
@@ -146,10 +147,10 @@
def test_equal(self):
from _numpypy import array
from numpypy import array_equal
-
+
a = [1, 2, 3]
b = [1, 2, 3]
-
+
assert array_equal(a, b)
assert array_equal(a, array(b))
assert array_equal(array(a), b)
@@ -158,10 +159,10 @@
def test_not_equal(self):
from _numpypy import array
from numpypy import array_equal
-
+
a = [1, 2, 3]
b = [1, 2, 4]
-
+
assert not array_equal(a, b)
assert not array_equal(a, array(b))
assert not array_equal(array(a), b)
@@ -170,17 +171,17 @@
def test_mismatched_shape(self):
from _numpypy import array
from numpypy import array_equal
-
+
a = [1, 2, 3]
b = [[1, 2, 3], [1, 2, 3]]
-
+
assert not array_equal(a, b)
assert not array_equal(a, array(b))
assert not array_equal(array(a), b)
assert not array_equal(array(a), array(b))
+
class AppTestNumeric(BaseNumpyAppTest):
-
def test_outer(self):
from _numpypy import array
from numpypy import outer
@@ -192,3 +193,22 @@
[12, 15, 18]])
assert (res == expected).all()
+ def test_identity(self):
+ from _numpypy import array, int32, float64, dtype
+ from numpypy import identity
+ a = identity(0)
+ assert len(a) == 0
+ assert a.dtype == dtype('float64')
+ assert a.shape == (0, 0)
+ b = identity(1, dtype=int32)
+ assert len(b) == 1
+ assert b[0][0] == 1
+ assert b.shape == (1, 1)
+ assert b.dtype == dtype('int32')
+ c = identity(2)
+ assert c.shape == (2, 2)
+ assert (c == [[1, 0], [0, 1]]).all()
+ d = identity(3, dtype='int32')
+ assert d.shape == (3, 3)
+ assert d.dtype == dtype('int32')
+ assert (d == [[1, 0, 0], [0, 1, 0], [0, 0, 1]]).all()
diff --git a/pypy/module/test_lib_pypy/numpypy/lib/test_function_base.py
b/pypy/module/test_lib_pypy/numpypy/lib/test_function_base.py
new file mode 100644
--- /dev/null
+++ b/pypy/module/test_lib_pypy/numpypy/lib/test_function_base.py
@@ -0,0 +1,7 @@
+from pypy.module.micronumpy.test.test_base import BaseNumpyAppTest
+
+class AppTestFunctionBase(BaseNumpyAppTest):
+ def test_average(self):
+ from numpypy import array, average
+ assert average(range(10)) == 4.5
+ assert average(array(range(10))) == 4.5
diff --git a/pypy/module/test_lib_pypy/numpypy/lib/test_twodim_base.py
b/pypy/module/test_lib_pypy/numpypy/lib/test_twodim_base.py
new file mode 100644
--- /dev/null
+++ b/pypy/module/test_lib_pypy/numpypy/lib/test_twodim_base.py
@@ -0,0 +1,31 @@
+from pypy.module.micronumpy.test.test_base import BaseNumpyAppTest
+
+class AppTestFunctionBase(BaseNumpyAppTest):
+ def test_eye(self):
+ from _numpypy import int32, dtype
+ from numpypy import eye
+ a = eye(0)
+ assert len(a) == 0
+ assert a.dtype == dtype('float64')
+ assert a.shape == (0, 0)
+ b = eye(1, dtype=int32)
+ assert len(b) == 1
+ assert b[0][0] == 1
+ assert b.shape == (1, 1)
+ assert b.dtype == dtype('int32')
+ c = eye(2)
+ assert c.shape == (2, 2)
+ assert (c == [[1, 0], [0, 1]]).all()
+ d = eye(3, dtype='int32')
+ assert d.shape == (3, 3)
+ assert d.dtype == dtype('int32')
+ assert (d == [[1, 0, 0], [0, 1, 0], [0, 0, 1]]).all()
+ e = eye(3, 4)
+ assert e.shape == (3, 4)
+ assert (e == [[1, 0, 0, 0], [0, 1, 0, 0], [0, 0, 1, 0]]).all()
+ f = eye(2, 4, k=3)
+ assert f.shape == (2, 4)
+ assert (f == [[0, 0, 0, 1], [0, 0, 0, 0]]).all()
+ g = eye(3, 4, k=-1)
+ assert g.shape == (3, 4)
+ assert (g == [[0, 0, 0, 0], [1, 0, 0, 0], [0, 1, 0, 0]]).all()
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