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Stop using np.{builtin}, and fix bugs due to the previous confusion #8996

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merged 2 commits into from
Aug 6, 2017
Merged

Stop using np.{builtin}, and fix bugs due to the previous confusion #8996

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c9612cc
MAINT: Use builtin when np.{x} is builtins.{x}.
eric-wieser Aug 6, 2017
7b8883c
BUG: Use np.integer instead of int, to allow unsigned integers
eric-wieser Aug 6, 2017
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4 changes: 2 additions & 2 deletions examples/event_handling/viewlims.py
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Original file line number Diff line number Diff line change
Expand Up @@ -36,8 +36,8 @@ def __call__(self, xstart, xend, ystart, yend):
self.y = np.linspace(ystart, yend, self.height).reshape(-1, 1)
c = self.x + 1.0j * self.y
threshold_time = np.zeros((self.height, self.width))
z = np.zeros(threshold_time.shape, dtype=np.complex)
mask = np.ones(threshold_time.shape, dtype=np.bool)
z = np.zeros(threshold_time.shape, dtype=complex)
mask = np.ones(threshold_time.shape, dtype=bool)
for i in range(self.niter):
z[mask] = z[mask]**self.power + c[mask]
mask = (np.abs(z) < self.radius)
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2 changes: 1 addition & 1 deletion examples/images_contours_and_fields/contour_corner_mask.py
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Expand Up @@ -14,7 +14,7 @@
z = np.sin(0.5 * x) * np.cos(0.52 * y)

# Mask various z values.
mask = np.zeros_like(z, dtype=np.bool)
mask = np.zeros_like(z, dtype=bool)
mask[2, 3:5] = True
mask[3:5, 4] = True
mask[7, 2] = True
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2 changes: 1 addition & 1 deletion examples/images_contours_and_fields/tricontour_smooth_delaunay.py
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Expand Up @@ -75,7 +75,7 @@ def experiment_res(x, y):
ntri = tri.triangles.shape[0]

# Some invalid data are masked out
mask_init = np.zeros(ntri, dtype=np.bool)
mask_init = np.zeros(ntri, dtype=bool)
masked_tri = random_gen.randint(0, ntri, int(ntri * init_mask_frac))
mask_init[masked_tri] = True
tri.set_mask(mask_init)
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10 changes: 5 additions & 5 deletions lib/matplotlib/axes/_axes.py
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Expand Up @@ -4769,9 +4769,9 @@ def fill_between(self, x, y1, y2=0, where=None, interpolate=False,
y2 = np.ones_like(x) * y2

if where is None:
where = np.ones(len(x), np.bool)
where = np.ones(len(x), bool)
else:
where = np.asarray(where, np.bool)
where = np.asarray(where, bool)

if not (x.shape == y1.shape == y2.shape == where.shape):
raise ValueError("Argument dimensions are incompatible")
Expand Down Expand Up @@ -4930,9 +4930,9 @@ def fill_betweenx(self, y, x1, x2=0, where=None,
x2 = np.ones_like(y) * x2

if where is None:
where = np.ones(len(y), np.bool)
where = np.ones(len(y), bool)
else:
where = np.asarray(where, np.bool)
where = np.asarray(where, bool)

if not (y.shape == x1.shape == x2.shape == where.shape):
raise ValueError("Argument dimensions are incompatible")
Expand All @@ -4954,7 +4954,7 @@ def fill_betweenx(self, y, x1, x2=0, where=None,
continue

N = len(yslice)
Y = np.zeros((2 * N + 2, 2), np.float)
Y = np.zeros((2 * N + 2, 2), float)
if interpolate:
def get_interp_point(ind):
im1 = max(ind - 1, 0)
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2 changes: 1 addition & 1 deletion lib/matplotlib/colors.py
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Expand Up @@ -1443,7 +1443,7 @@ def hsv_to_rgb(hsv):
g = np.empty_like(h)
b = np.empty_like(h)

i = (h * 6.0).astype(np.int)
i = (h * 6.0).astype(int)
f = (h * 6.0) - i
p = v * (1.0 - s)
q = v * (1.0 - s * f)
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28 changes: 14 additions & 14 deletions lib/matplotlib/finance.py
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Expand Up @@ -58,27 +58,27 @@ def md5(x):
(str('year'), np.int16),
(str('month'), np.int8),
(str('day'), np.int8),
(str('d'), np.float), # mpl datenum
(str('open'), np.float),
(str('high'), np.float),
(str('low'), np.float),
(str('close'), np.float),
(str('volume'), np.float),
(str('aclose'), np.float)])
(str('d'), float), # mpl datenum
(str('open'), float),
(str('high'), float),
(str('low'), float),
(str('close'), float),
(str('volume'), float),
(str('aclose'), float)])


stock_dt_ochl = np.dtype(
[(str('date'), object),
(str('year'), np.int16),
(str('month'), np.int8),
(str('day'), np.int8),
(str('d'), np.float), # mpl datenum
(str('open'), np.float),
(str('close'), np.float),
(str('high'), np.float),
(str('low'), np.float),
(str('volume'), np.float),
(str('aclose'), np.float)])
(str('d'), float), # mpl datenum
(str('open'), float),
(str('close'), float),
(str('high'), float),
(str('low'), float),
(str('volume'), float),
(str('aclose'), float)])


def parse_yahoo_historical_ochl(fh, adjusted=True, asobject=False):
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6 changes: 3 additions & 3 deletions lib/matplotlib/mlab.py
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Expand Up @@ -3136,17 +3136,17 @@ def get_type(item, atype=int):
def get_justify(colname, column, precision):
ntype = column.dtype

if np.issubdtype(ntype, str) or np.issubdtype(ntype, bytes):
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This didn't catch unicode on python 2, but did on python 3

if np.issubdtype(ntype, np.character):
fixed_width = int(ntype.str[2:])
length = max(len(colname), fixed_width)
return 0, length+padding, "%s" # left justify

if np.issubdtype(ntype, np.int):
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This was false for ntype == np.uint8

if np.issubdtype(ntype, np.integer):
length = max(len(colname),
np.max(list(map(len, list(map(str, column))))))
return 1, length+padding, "%d" # right justify

if np.issubdtype(ntype, np.float):
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This worked correctly, but will raise a warning in numpy 1.14 if numpy/numpy#9505 is merged

if np.issubdtype(ntype, np.floating):
fmt = "%." + str(precision) + "f"
length = max(
len(colname),
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6 changes: 3 additions & 3 deletions lib/matplotlib/quiver.py
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Expand Up @@ -982,12 +982,12 @@ def _find_tails(self, mag, rounding=True, half=5, full=10, flag=50):
# If rounding, round to the nearest multiple of half, the smallest
# increment
if rounding:
mag = half * (mag / half + 0.5).astype(np.int)
mag = half * (mag / half + 0.5).astype(int)

num_flags = np.floor(mag / flag).astype(np.int)
num_flags = np.floor(mag / flag).astype(int)
mag = np.mod(mag, flag)

num_barb = np.floor(mag / full).astype(np.int)
num_barb = np.floor(mag / full).astype(int)
mag = np.mod(mag, full)

half_flag = mag >= half
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8 changes: 4 additions & 4 deletions lib/matplotlib/streamplot.py
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Expand Up @@ -599,14 +599,14 @@ def interpgrid(a, xi, yi):

Ny, Nx = np.shape(a)
if isinstance(xi, np.ndarray):
x = xi.astype(np.int)
y = yi.astype(np.int)
x = xi.astype(int)
y = yi.astype(int)
# Check that xn, yn don't exceed max index
xn = np.clip(x + 1, 0, Nx - 1)
yn = np.clip(y + 1, 0, Ny - 1)
else:
x = np.int(xi)
y = np.int(yi)
x = int(xi)
y = int(yi)
# conditional is faster than clipping for integers
if x == (Nx - 2):
xn = x
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2 changes: 1 addition & 1 deletion lib/matplotlib/tests/test_image.py
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Expand Up @@ -705,7 +705,7 @@ def test_mask_image():

ax1.imshow(A, interpolation='nearest')

A = np.zeros((5, 5), dtype=np.bool)
A = np.zeros((5, 5), dtype=bool)
A[1:2, 1:2] = True
A = np.ma.masked_array(np.ones((5, 5), dtype=np.uint16), A)

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10 changes: 5 additions & 5 deletions lib/matplotlib/tests/test_triangulation.py
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Expand Up @@ -847,7 +847,7 @@ def test_tritools():
x = np.array([0., 1., 0.5, 0., 2.])
y = np.array([0., 0., 0.5*np.sqrt(3.), -1., 1.])
triangles = np.array([[0, 1, 2], [0, 1, 3], [1, 2, 4]], dtype=np.int32)
mask = np.array([False, False, True], dtype=np.bool)
mask = np.array([False, False, True], dtype=bool)
triang = mtri.Triangulation(x, y, triangles, mask=mask)
analyser = mtri.TriAnalyzer(triang)
assert_array_almost_equal(analyser.scale_factors,
Expand Down Expand Up @@ -881,15 +881,15 @@ def power(x, a):
triang = mtri.Triangulation(x, y, triangles=meshgrid_triangles(n+1))
analyser = mtri.TriAnalyzer(triang)
mask_flat = analyser.get_flat_tri_mask(0.2)
verif_mask = np.zeros(162, dtype=np.bool)
verif_mask = np.zeros(162, dtype=bool)
corners_index = [0, 1, 2, 3, 14, 15, 16, 17, 18, 19, 34, 35, 126, 127,
142, 143, 144, 145, 146, 147, 158, 159, 160, 161]
verif_mask[corners_index] = True
assert_array_equal(mask_flat, verif_mask)

# Now including a hole (masked triangle) at the center. The center also
# shall be eliminated by get_flat_tri_mask.
mask = np.zeros(162, dtype=np.bool)
mask = np.zeros(162, dtype=bool)
mask[80] = True
triang.set_mask(mask)
mask_flat = analyser.get_flat_tri_mask(0.2)
Expand All @@ -906,7 +906,7 @@ def test_trirefine():
x, y = np.meshgrid(x, x)
x = x.ravel()
y = y.ravel()
mask = np.zeros(2*n**2, dtype=np.bool)
mask = np.zeros(2*n**2, dtype=bool)
mask[n**2:] = True
triang = mtri.Triangulation(x, y, triangles=meshgrid_triangles(n+1),
mask=mask)
Expand Down Expand Up @@ -1032,7 +1032,7 @@ def test_trianalyzer_mismatched_indices():
x = np.array([0., 1., 0.5, 0., 2.])
y = np.array([0., 0., 0.5*np.sqrt(3.), -1., 1.])
triangles = np.array([[0, 1, 2], [0, 1, 3], [1, 2, 4]], dtype=np.int32)
mask = np.array([False, False, True], dtype=np.bool)
mask = np.array([False, False, True], dtype=bool)
triang = mtri.Triangulation(x, y, triangles, mask=mask)
analyser = mtri.TriAnalyzer(triang)
# numpy >= 1.10 raises a VisibleDeprecationWarning in the following line
Expand Down
4 changes: 2 additions & 2 deletions lib/matplotlib/tri/triangulation.py
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Expand Up @@ -66,7 +66,7 @@ def __init__(self, x, y, triangles=None, mask=None):
raise ValueError('triangles min element is out of bounds')

if mask is not None:
self.mask = np.asarray(mask, dtype=np.bool)
self.mask = np.asarray(mask, dtype=bool)
if self.mask.shape != (self.triangles.shape[0],):
raise ValueError('mask array must have same length as '
'triangles array')
Expand Down Expand Up @@ -200,7 +200,7 @@ def set_mask(self, mask):
if mask is None:
self.mask = None
else:
self.mask = np.asarray(mask, dtype=np.bool)
self.mask = np.asarray(mask, dtype=bool)
if self.mask.shape != (self.triangles.shape[0],):
raise ValueError('mask array must have same length as '
'triangles array')
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2 changes: 1 addition & 1 deletion lib/matplotlib/tri/tritools.py
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Expand Up @@ -177,7 +177,7 @@ def get_flat_tri_mask(self, min_circle_ratio=0.01, rescale=True):

current_mask = self._triangulation.mask
if current_mask is None:
current_mask = np.zeros(ntri, dtype=np.bool)
current_mask = np.zeros(ntri, dtype=bool)
valid_neighbors = np.copy(self._triangulation.neighbors)
renum_neighbors = np.arange(ntri, dtype=np.int32)
nadd = -1
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4 changes: 2 additions & 2 deletions lib/mpl_toolkits/tests/test_mplot3d.py
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Expand Up @@ -343,8 +343,8 @@ def test_poly3dcollection_closed():
fig = plt.figure()
ax = fig.gca(projection='3d')

poly1 = np.array([[0, 0, 1], [0, 1, 1], [0, 0, 0]], np.float)
poly2 = np.array([[0, 1, 1], [1, 1, 1], [1, 1, 0]], np.float)
poly1 = np.array([[0, 0, 1], [0, 1, 1], [0, 0, 0]], float)
poly2 = np.array([[0, 1, 1], [1, 1, 1], [1, 1, 0]], float)
c1 = art3d.Poly3DCollection([poly1], linewidths=3, edgecolor='k',
facecolor=(0.5, 0.5, 1, 0.5), closed=True)
c2 = art3d.Poly3DCollection([poly2], linewidths=3, edgecolor='k',
Expand Down