10000 Fixed bug in numpy.piecewise() for 0-d array handling by ericsuh · Pull Request #331 · numpy/numpy · GitHub
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Fixed bug in numpy.piecewise() for 0-d array handling #331

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Fixed bug in numpy.piecewise() for 0-d array handling #331

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e553e1b
Fixed bug in numpy.piecewise()
ericsuh Jul 5, 2012
e2ad1a7
Fixed numpy.piecewise() and tests
ericsuh Jul 7, 2012
c760734
Reverted numpy.piecewise() tests to original set with regression test
ericsuh Mar 1, 2013
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Reverted numpy.piecewise() tests to original set with regression test 
Fixed one bug in fix, changed unit tests of numpy.piecewise() to be the
original set except for the addition of one regression test.

Revisions of unit tests to include spelling out undocumented assumptions
of behavior of numpy.piecewise() will come later.
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@ericsuh
ericsuh committed Mar 1, 2013
commit c7607340c6085f36db14b6329099f2384c93a639
3 changes: 2 additions & 1 deletion numpy/lib/function_base.py
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Original file line number Diff line number Diff line change
Expand Up @@ -675,7 +675,8 @@ def piecewise(x, condlist, funclist, *args, **kw):
n2 = len(funclist)
if isscalar(condlist) or \
(isinstance(condlist, np.ndarray) and condlist.ndim == 0) or \
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This changes the behavior and needs to be documented. I've also looked at the following version:

    def isscalarlike(a):
        return isscalar(a) or (isinstance(a, np.ndarray) and a.ndim == 0)

    x = asanyarray(x)
    n2 = len(funclist)
    if isscalarlike(condlist) or (x.ndim > 0 and isscalarlike(condlist[0])):
        condlist = [condlist]

Which is a bit different again, but clearer I think.

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Yeah, I suspect this change is probably fine but I haven't wrapped my head
around that complex conditional...

On Sun, Aug 18, 2013 at 5:01 PM, Charles Harris notifications@github.comwrote:

In numpy/lib/function_base.py:

@@ -674,20 +674,13 @@ def piecewise(x, condlist, funclist, _args, *_kw):
x = asanyarray(x)
n2 = len(funclist)
if isscalar(condlist) or \

  •       not (isinstance(condlist[0], list) or

  •            isinstance(condlist[0], ndarray)):

  •        (isinstance(condlist, np.ndarray) and condlist.ndim == 0) or \

This changes the behavior and needs to be documented. I've also looked at
the following version:

def isscalarlike(a):
    return isscalar(a) or (isinstance(a, np.ndarray) and a.ndim == 0)

x = asanyarray(x)
n2 = len(funclist)
if isscalarlike(condlist) or (x.ndim > 0 and isscalarlike(a[0])):
    condlist = [condlist]

Which is a bit different again, but clearer I think.

—
Reply to this email directly or view it on GitHubhttps://github.com//pull/331/files#r5831760
.

(x.ndim > 0 and condlist[0].ndim == 0):
(x.ndim > 0 and (isscalar(condlist[0]) or \
(isinstance(condlist, np.ndarray) and condlist[0].ndim == 0))):
condlist = [condlist]
condlist = [asarray(c, dtype=bool) for c in condlist]
n = len(condlist)
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166 changes: 34 additions & 132 deletions numpy/lib/tests/test_function_base.py
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Expand Up @@ -1179,150 +1179,52 @@ def test_simple(self):


class TestPiecewise(TestCase):
def test_0d(self):
# Input: scalar
x = 5

# Condition: scalar bool
y = piecewise(x, x < 7, [1])
assert(y.ndim == 0)
assert(y == 1)

# Condition: singleton list of scalar bool
y = piecewise(x, [x < 7], [1])
assert(y == 1)

# Condition: 0-d array of bool
y = piecewise(x, np.array(x < 7), [1])
assert(y == 1)

# Condition: 1-d array of bool
y = piecewise(x, np.array([x < 7]), [1])
assert(y == 1)

# Condition: singleton list of 0-d array of bool
y = piecewise(x, [np.array(x < 7)], [1])
assert(y == 1)

# Condition: singleton list of 1-d array of bool
y = piecewise(x, [np.array([x < 7])], [1])
assert(y == 1)

# Condition: scalar int
y = piecewise(x, 1, [1])
assert(y == 1)

# Condition: singleton list of int
y = piecewise(x, [1], [1])
assert(y == 1)

# Condition: 1-d list of bools
y = piecewise(x, [x < 7, x >= 7], [1, 2])
assert(y == 1)

# Condition: 1-d list of bools (test alternative)
y = piecewise(x, [x >= 7, x < 7], [1, 2])
assert(y == 2)

# Condition: 1-d list of 0-d arrays of bools
y = piecewise(x, [np.array(x < 7), np.array(x >= 7)], [1, 2])
assert(y == 1)

# Input: 0-d array
x = np.array(5)

y = piecewise(x, x < 7, [1])
assert(y.ndim == 0)
assert(y == 1)

def test_simple(self):
# Input: 1-d array
x = np.array([3,5])

# Condition: bare array of bool
y = piecewise(x, x < 7, [1])
assert_array_equal(y, [1, 1])
# Condition is single bool list
x = piecewise([0, 0], [True, False], [1])
assert_array_equal(x, [1, 0])

# Make sure callables are called
y = piecewise(x, x < 7, [(lambda x: -x)])
assert_array_equal(y, [-3, -5])
# List of conditions: single bool list
x = piecewise([0, 0], [[True, False]], [1])
assert_array_equal(x, [1, 0])

# Condition: singleton list of array of bool
y = piecewise(x, [x < 7], [1])
assert_array_equal(y, [1, 1])
# Conditions is single bool array
x = piecewise([0, 0], np.array([True, False]), [1])
assert_array_equal(x, [1, 0])

# Condition: (1,2) array of bool
y = piecewise(x, np.array([x < 7]), [1])
assert_array_equal(y, [1, 1])
# Condition is single int array
x = piecewise([0, 0], np.array([1, 0]), [1])
assert_array_equal(x, [1, 0])

# Condition: list of array of bool
y = piecewise(x, [x >= 4, x < 4], [1, 2])
assert_array_equal(y, [2, 1])
# List of conditions: int array
x = piecewise([0, 0], [np.array([1, 0])], [1])
assert_array_equal(x, [1, 0])

y = piecewise(x, [x > 7, x <= 7], [1, 2])
assert_array_equal(y, [2, 2])

y = piecewise(x, [x < 4, x >= 4], [1, 2])
assert_array_equal(y, [1, 2])
x = piecewise([0, 0], [[False, True]], [lambda x:-1])
assert_array_equal(x, [0, -1])

y = piecewise(x, np.array([x < 4, x >= 4]), [1, 2])
assert_array_equal(y, [1, 2])
x = piecewise([1, 2], [[True, False], [False, True]], [3, 4])
assert_array_equal(x, [3, 4])

def test_default(self):
# Input: scalar
x = 5
# No value specified for x[1], should be 0
x = piecewise([1, 2], [True, False], [2])
assert_array_equal(x, [2, 0])

# built-in no-match: 0
# Should set x[1] to 3
x = piecewise([1, 2], [True, False], [2, 3])
assert_array_equal(x, [2, 3])

# Condition: scalar bool
y = piecewise(x, x > 7, [1])
assert_array_equal(y, 0)

# Condition: scalar int
y = piecewise(x, 0, [1])
assert_array_equal(y, 0)

# custom no-match

y = piecewise(x, x < 7, [1, 2])
assert_array_equal(y, [1])

y = piecewise(x, x > 7, [1, 2])
assert_array_equal(y, [2])

# Condition: scalar int
y = piecewise(x, 0, [1, 2])
assert_array_equal(y, [2])

# Input: 1-d array
x = np.array([3,5])

# built-in no-match: 0

y = piecewise(x, x > 7, [1])
assert_array_equal(y, [0,0])

y = piecewise(x, x < 4, [1])
assert_array_equal(y, [1, 0])

# custom no-match

y = piecewise(x, x < 7, [1, 2])
assert_array_equal(y, [1, 1])

y = piecewise(x, x > 7, [1, 2])
assert_array_equal(y, [2, 2])

y = piecewise(x, x < 4, [1, 2])
assert_array_equal(y, [1, 2])

# Condition: list of array of bool
y = piecewise(x, [x < 4], [1, 2])
assert_array_equal(y, [1, 2])

# Condition: (1,2) array of bool
y = piecewise(x, np.array([x < 4]), [1, 2])
assert_array_equal(y, [1, 2])
def test_0d(self):
x = np.array(3)
y = piecewise(x, x > 3, [4, 0])
assert_(y.ndim == 0)
assert_(y == 0)

y = piecewise(x, [True, False], [1, 0])
assert_(y.ndim == 0)
assert_(y == 1)

class TestBincount(TestCase):
def test_simple(self):
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0