8000 FIX: array_view construction for empty arrays by jkseppan · Pull Request #5106 · matplotlib/matplotlib · GitHub
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FIX: array_view construction for empty arrays #5106

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Merged
merged 8 commits into from
Oct 2, 2015
Merged

FIX: array_view construction for empty arrays #5106

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e6b1745
Return error from array_view for numpy scalars
jkseppan Sep 20, 2015
724cb9b
Catch errors in the 1d branch of Py_affine_transform
jkseppan Sep 20, 2015
2f29bdf
Accept dimension mismatch for empty arrays
jkseppan Sep 20, 2015
c0e09d5
Assign m_arr = tmp in more cases
jkseppan Sep 21, 2015
536d175
Don't allow shape mismatches for empty arrays
jkseppan Sep 27, 2015
3965858
Add test
jkseppan Sep 27, 2015
2f5a633
Use atleast_3d instead of ensure_3d
jkseppan Sep 28, 2015
123deb5
Add a comment about _transforms
jkseppan Oct 1, 2015
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Don't allow shape mismatches for empty arrays 
Instead change callers to have empty arrays of the right shape.
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@jkseppan
jkseppan committed Sep 27, 2015
commit 536d175995bbef9fc9576b7055cd4d3afd8d581a
15 changes: 15 additions & 0 deletions lib/matplotlib/cbook.py
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Expand Up @@ -2244,6 +2244,21 @@ def _reshape_2D(X):
return X


def ensure_3d(arr):
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Do we want to make this a public function? We now have _check_1d(), _reshape_2D, and this new ensure_3d (notice the inconsistency with the case of "d/D").

Why don't we make this private, and make a new issue to unify the logic across these three functions later (if possible)?

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I would have thought that an underscore in the beginning means a function that is only called from within cbook, but clearly some underscored functions are called from elsewhere. What is the intended meaning?

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https://www.python.org/dev/peps/pep-0008/#id29

It means that it is to be treated as being for internal use only. This
gives developers the freedom to modify the API of such modules or functions
without warning or deprecation cycles. As noted later in PEP8, it is easier
to start with something as private and then make it public later, as
opposed to releasing it as public and then modifying it later.

On Mon, Sep 28, 2015 at 10:23 AM, Jouni K. Seppänen <
notifications@github.com> wrote:

In lib/matplotlib/cbook.py
#5106 (comment):

@@ -2244,6 +2244,21 @@ def _reshape_2D(X):
return X

+def ensure_3d(arr):

I would have thought that an underscore in the beginning means a function
that is only called from within cbook, but clearly some underscored
functions are called from elsewhere. What is the intended meaning?

—
Reply to this email directly or view it on GitHub
https://github.com/matplotlib/matplotlib/pull/5106/files#r40557282.

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PEP8 doesn't really say what the boundaries of internal use are, but I guess here it means internal to matplotlib. Ok, I'll change this.

"""
Return a version of arr with ndim==3, with extra dimensions added
at the end of arr.shape as needed.
"""
arr = np.asanyarray(arr)
if arr.ndim == 1:
arr = arr[:, None, None]
elif arr.ndim == 2:
arr = arr[:, :, None]
elif arr.ndim > 3 or arr.ndim < 1:
raise ValueError("cannot convert arr to 3-dimensional")
return arr


def violin_stats(X, method, points=100):
'''
Returns a list of dictionaries of data which can be used to draw a series
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6 changes: 2 additions & 4 deletions lib/matplotlib/collections.py
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Expand Up @@ -80,9 +80,7 @@ class Collection(artist.Artist, cm.ScalarMappable):
# _offsets must be a Nx2 array!
_offsets.shape = (0, 2)
_transOffset = transforms.IdentityTransform()
_transforms = []


_transforms = np.empty((0, 3, 3))
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Since you've touched it, would you mind adding a #: style docstring for what _transforms is supposed to be - this will make reviewing (and editing) this part of the code easier in the future.

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Where is this #: style documented?

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I think @pelson just means to add a normal comment explaining what the expected shape of _transfroms is and why?

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I see with git grep that there is a small number of #: comments in the code, but that's not a very easy thing to search. Does Sphinx do something special with them, or some other tool?

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Indeed it does: http://sphinx-doc.org/ext/autodoc.html#directive-autoattribute


def __init__(self,
edgecolors=None,
Expand Down Expand Up @@ -1515,7 +1513,7 @@ def __init__(self, widths, heights, angles, units='points', **kwargs):
self._angles = np.asarray(angles).ravel() * (np.pi / 180.0)
self._units = units
self.set_transform(transforms.IdentityTransform())
self._transforms = []
self._transforms = np.empty((0, 3, 3))
self._paths = [mpath.Path.unit_circle()]

def _set_transforms(self):
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5 changes: 3 additions & 2 deletions lib/matplotlib/path.py
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Expand Up @@ -24,7 +24,7 @@
from numpy import ma

from matplotlib import _path
from matplotlib.cbook import simple_linear_interpolation, maxdict
from matplotlib.cbook import simple_linear_interpolation, maxdict, ensure_3d
from matplotlib import rcParams


Expand Down Expand Up @@ -988,7 +988,8 @@ def get_path_collection_extents(
if len(paths) == 0:
raise ValueError("No paths provided")
return Bbox.from_extents(*_path.get_path_collection_extents(
master_transform, paths, transforms, offsets, offset_transform))
master_transform, paths, ensure_3d(transforms),
offsets, offset_transform))


def get_paths_extents(paths, transforms=[]):
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8 changes: 8 additions & 0 deletions lib/matplotlib/tests/test_cbook.py
A8CD
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Expand Up @@ -376,3 +376,11 @@ def test_step_fails():
np.arange(12))
assert_raises(ValueError, cbook._step_validation,
np.arange(12), np.arange(3))


def test_ensure_3d():
assert_array_equal([[[1]], [[2]], [[3]]],
cbook.ensure_3d([1, 2, 3]))
assert_array_equal([[[1], [2]], [[3], [4]]],
cbook.ensure_3d([[1, 2], [3, 4]]))
assert_raises(ValueError, cbook.ensure_3d, [[[[1]]]])
4 changes: 3 additions & 1 deletion lib/matplotlib/transforms.py
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Expand Up @@ -48,6 +48,7 @@
from sets import Set as set

from .path import Path
from .cbook import ensure_3d

DEBUG = False
# we need this later, but this is very expensive to set up
Expand Down Expand Up @@ -666,7 +667,8 @@ def count_overlaps(self, bboxes):

bboxes is a sequence of :class:`BboxBase` objects
"""
return count_bboxes_overlapping_bbox(self, [np.array(x) for x in bboxes])
return count_bboxes_overlapping_bbox(
self, ensure_3d([np.array(x) for x in bboxes]))

def expanded(self, sw, sh):
"""
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6 changes: 0 additions & 6 deletions src/numpy_cpp.h
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Expand Up @@ -448,12 +448,6 @@ class array_view : public detail::array_view_accessors<array_view, T, ND>
return 1;
}
}
if (PyArray_NDIM(tmp) > 0 && PyArray_DIM(tmp, 0) == 0) {
// accept dimension mismatch for empty arrays
Py_XDECREF(m_arr);
m_arr = tmp;
return 1;
}
if (PyArray_NDIM(tmp) != ND) {
PyErr_Format(PyExc_ValueError,
"Expected %d-dimensional array, got %d",
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0