8000 Additional cleanups by anntzer · Pull Request #7547 · matplotlib/matplotlib · GitHub
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Merged
merged 6 commits into from
Dec 5, 2016
Merged

Additional cleanups #7547

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de302f5
Call min/max directly on generator or two args.
anntzer Dec 1, 2016
46b9d47
Remove old `__cmp__` method.
anntzer Jun 28, 2016
1504540
Use reshape instead of assigning to shape.
anntzer Dec 1, 2016
3d00576
Use shorter function names (min, max, abs, conj).
anntzer Dec 1, 2016
69622dd
set/dict literals/comprehensions.
anntzer Dec 1, 2016
f1b25e6
Minor fixes following comments.
anntzer Dec 2, 2016
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Use shorter function names (min, max, abs, conj).
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@anntzer
anntzer committed Dec 4, 2016
commit 3d00576eced6fa68eb34136e457510c00521baf7
7 changes: 3 additions & 4 deletions examples/api/collections_demo.py
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Expand Up @@ -89,9 +89,8 @@

# 7-sided regular polygons

col = collections.RegularPolyCollection(7,
sizes=np.fabs(xx) * 10.0, offsets=xyo,
transOffset=ax3.transData)
col = collections.RegularPolyCollection(
7, sizes=np.abs(xx) * 10.0, offsets=xyo, transOffset=ax3.transData)
trans = transforms.Affine2D().scale(fig.dpi / 72.0)
col.set_transform(trans) # the points to pixels transform
ax3.add_collection(col, autolim=True)
Expand All @@ -109,7 +108,7 @@
offs = (0.1, 0.0)

yy = np.linspace(0, 2*np.pi, nverts)
ym = np.amax(yy)
ym = np.max(yy)
xx = (0.2 + (ym - yy)/ym)**2 * np.cos(yy - 0.4)*0.5
segs = []
for i in range(ncurves):
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4 changes: 2 additions & 2 deletions examples/api/sankey_demo_old.py
8000
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Expand Up @@ -37,11 +37,11 @@ def sankey(ax,
import matplotlib.patches as mpatches
from matplotlib.path import Path

outs = np.absolute(outputs)
outs = np.abs(outputs)
outsigns = np.sign(outputs)
outsigns[-1] = 0 # Last output

ins = np.absolute(inputs)
ins = np.abs(inputs)
insigns = np.sign(inputs)
insigns[0] = 0 # First input

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4 changes: 2 additions & 2 deletions examples/event_handling/poly_editor.py
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Expand Up @@ -70,8 +70,8 @@ def get_ind_under_point(self, event):
xy = np.asarray(self.poly.xy)
xyt = self.poly.get_transform().transform(xy)
xt, yt = xyt[:, 0], xyt[:, 1]
d = np.sqrt((xt - event.x)**2 + (yt - event.y)**2)
indseq = np.nonzero(np.equal(d, np.amin(d)))[0]
d = np.hypot(xt - event.x, yt - event.y)
indseq, = np.nonzero(d == d.min())
ind = indseq[0]

if d[ind] >= self.epsilon:
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5 changes: 2 additions & 3 deletions examples/pylab_examples/anscombe.py
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Expand Up @@ -22,7 +22,7 @@ def fit(x):
return 3 + 0.5*x


xfit = np.array([np.amin(x), np.amax(x)])
xfit = np.array([np.min(x), np.max(x)])

plt.subplot(221)
plt.plot(x, y1, 'ks', xfit, fit(xfit), 'r-', lw=2)
Expand All @@ -43,8 +43,7 @@ def fit(x):
plt.setp(plt.gca(), yticks=(4, 8, 12), xticks=(0, 10, 20))

plt.subplot(224)

xfit = np.array([np.amin(x4), np.amax(x4)])
xfit = np.array([np.min(x4), np.max(x4)])
plt.plot(x4, y4, 'ks', xfit, fit(xfit), 'r-', lw=2)
plt.axis([2, 20, 2, 14])
plt.setp(plt.gca(), yticklabels=[], yticks=(4, 8, 12), xticks=(0, 10, 20))
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2 changes: 1 addition & 1 deletion examples/pylab_examples/axes_demo.py
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Expand Up @@ -14,7 +14,7 @@

# the main axes is subplot(111) by default
plt.plot(t, s)
plt.axis([0, 1, 1.1*np.amin(s), 2*np.amax(s)])
plt.axis([0, 1, 1.1 * np.min(s), 2 * np.max(s)])
plt.xlabel('time (s)')
plt.ylabel('current (nA)')
plt.title('Gaussian colored noise')
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4 changes: 1 addition & 3 deletions examples/pylab_examples/layer_images.py
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Expand Up @@ -23,9 +23,7 @@ def func3(x, y):
# for the images their apparent extent could be different due to
# interpolation edge effects


xmin, xmax, ymin, ymax = np.amin(x), np.amax(x), np.amin(y), np.amax(y)
extent = xmin, xmax, ymin, ymax
extent = np.min(x), np.max(x), np.min(y), np.max(y)
fig = plt.figure(frameon=False)

Z1 = np.add.outer(range(8), range(8)) % 2 # chessboard
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What does np.add.outer do (it works, but I've never seen it used that way)?

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It makes the first argument a column array and the second a row array, broadcasts them and applies the ufunc.

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4 changes: 2 additions & 2 deletions examples/pylab_examples/line_collection2.py
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Expand Up @@ -13,8 +13,8 @@

# We need to set the plot limits, they will not autoscale
ax = plt.axes()
ax.set_xlim((np.amin(x), np.amax(x)))
ax.set_ylim((np.amin(np.amin(ys)), np.amax(np.amax(ys))))
ax.set_xlim(np.min(x), np.max(x))
ax.set_ylim(np.min(ys), np.max(ys))

# colors is sequence of rgba tuples
# linestyle is a string or dash tuple. Legal string values are
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11 changes: 5 additions & 6 deletions examples/pylab_examples/multi_image.py
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Expand Up @@ -7,8 +7,7 @@
from matplotlib.pyplot import figure, show, axes, sci
from matplotlib import cm, colors
from matplotlib.font_manager import FontProperties
from numpy import amin, amax, ravel
from numpy.random import rand
import numpy as np

Nr = 3
Nc = 2
Expand Down Expand Up @@ -37,12 +36,12 @@
a.set_xticklabels([])
# Make some fake data with a range that varies
# somewhat from one plot to the next.
data = ((1 + i + j)/10.0)*rand(10, 20)*1e-6
dd = ravel(data)
data = ((1 + i + j) / 10) * np.random.rand(10, 20) * 1e-6
dd = data.ravel()
# Manually find the min and max of all colors for
# use in setting the color scale.
vmin = min(vmin, amin(dd))
vmax = max(vmax, amax(dd))
vmin = min(vmin, np.min(dd))
vmax = max(vmax, np.max(dd))
images.append(a.imshow(data, cmap=cmap))

ax.append(a)
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3 changes: 1 addition & 2 deletions examples/pylab_examples/quadmesh_demo.py
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Expand Up @@ -21,8 +21,7 @@
Z = (Z - Z.min()) / (Z.max() - Z.min())

# The color array can include masked values:
Zm = ma.masked_where(np.fabs(Qz) < 0.5*np.amax(Qz), Z)

Zm = ma.masked_where(np.abs(Qz) < 0.5 * np.max(Qz), Z)

fig = figure()
ax = fig.add_subplot(121)
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2 changes: 1 addition & 1 deletion examples/pylab_examples/vline_hline_demo.py
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Expand Up @@ -10,7 +10,7 @@
def f(t):
s1 = np.sin(2 * np.pi * t)
e1 = np.exp(-t)
return np.absolute((s1 * e1)) + .05
return np.abs(s1 * e1) + .05

t = np.arange(0.0, 5.0, 0.1)
s = f(t)
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4 changes: 2 additions & 2 deletions examples/user_interfaces/embedding_in_wx3.py
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Expand Up @@ -74,7 +74,7 @@ def init_plot_data(self):
z = np.sin(self.x) + np.cos(self.y)
self.im = a.imshow(z, cmap=cm.RdBu) # , interpolation='nearest')

zmax = np.amax(z) - ERR_TOL
zmax = np.max(z) - ERR_TOL
ymax_i, xmax_i = np.nonzero(z >= zmax)
if self.im.origin == 'upper':
ymax_i = z.shape[0] - ymax_i
Expand All @@ -93,7 +93,7 @@ def OnWhiz(self, evt):
z = np.sin(self.x) + np.cos(self.y)
self.im.set_array(z)

zmax = np.amax(z) - ERR_TOL
zmax = np.max(z) - ERR_TOL
ymax_i, xmax_i = np.nonzero(z >= zmax)
if self.im.origin == 'upper':
ymax_i = z.shape[0] - ymax_i
Expand Down
34 changes: 17 additions & 17 deletions lib/matplotlib/axes/_axes.py
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Expand Up @@ -2460,7 +2460,7 @@ def stem(self, *args, **kwargs):
marker=linemarker, label="_nolegend_")
stemlines.append(l)

baseline, = self.plot([np.amin(x), np.amax(x)], [bottom, bottom],
baseline, = self.plot([np.min(x), np.max(x)], [bottom, bottom],
color=basecolor, linestyle=basestyle,
marker=basemarker, label="_nolegend_")

Expand Down Expand Up @@ -4228,8 +4228,8 @@ def hexbin(self, x, y, C=None, gridsize=100, bins=None,
if extent is not None:
xmin, xmax, ymin, ymax = extent
else:
xmin, xmax = (np.amin(x), np.amax(x)) if len(x) else (0, 1)
ymin, ymax = (np.amin(y), np.amax(y)) if len(y) else (0, 1)
xmin, xmax = (np.min(x), np.max(x)) if len(x) else (0, 1)
ymin, ymax = (np.min(y), np.max(y)) if len(y) else (0, 1)

# to avoid issues with singular data, expand the min/max pairs
xmin, xmax = mtrans.nonsingular(xmin, xmax, expander=0.1)
Expand Down Expand Up @@ -5470,10 +5470,10 @@ def pcolor(self, *args, **kwargs):

self.add_collection(collection, autolim=False)

minx = np.amin(x)
maxx = np.amax(x)
miny = np.amin(y)
maxy = np.amax(y)
minx = np.min(x)
maxx = np.max(x)
miny = np.min(y)
maxy = np.max(y)
collection.sticky_edges.x[:] = [minx, maxx]
collection.sticky_edges.y[:] = [miny, maxy]
corners = (minx, miny), (maxx, maxy)
Expand Down Expand Up @@ -5622,10 +5622,10 @@ def pcolormesh(self, *args, **kwargs):

self.add_collection(collection, autolim=False)

minx = np.amin(X)
maxx = np.amax(X)
miny = np.amin(Y)
maxy = np.amax(Y)
minx = np.min(X)
maxx = np.max(X)
miny = np.min(Y)
maxy = np.max(Y)
collection.sticky_edges.x[:] = [minx, maxx]
collection.sticky_edges.y[:] = [miny, maxy]
corners = (minx, miny), (maxx, maxy)
Expand Down Expand Up @@ -6386,7 +6386,7 @@ def _normalize_input(inp, ename='input'):
else:
labels = [six.text_type(lab) for lab in label]

for (patch, lbl) in zip_longest(patches, labels, fillvalue=None):
for patch, lbl in zip_longest(patches, labels, fillvalue=None):
if patch:
p = patch[0]
p.update(kwargs)
Expand Down Expand Up @@ -6724,7 +6724,7 @@ def csd(self, x, y, NFFT=None, Fs=None, Fc=None, detrend=None,
# pxy is complex
freqs += Fc

line = self.plot(freqs, 10 * np.log10(np.absolute(pxy)), **kwargs)
line = self.plot(freqs, 10 * np.log10(np.abs(pxy)), **kwargs)
self.set_xlabel('Frequency')
self.set_ylabel('Cross Spectrum Magnitude (dB)')
self.grid(True)
Expand Down Expand Up @@ -7227,7 +7227,7 @@ def specgram(self, x, NFFT=None, Fs=None, Fc=None, detrend=None,
Z = np.flipud(Z)

if xextent is None:
xextent = 0, np.amax(t)
xextent = 0, np.max(t)
xmin, xmax = xextent
freqs += Fc
extent = xmin, xmax, freqs[0], freqs[-1]
Expand Down Expand Up @@ -7300,7 +7300,7 @@ def spy(self, Z, precision=0, marker=None, markersize=None,
marker = 's'
if marker is None and markersize is None:
Z = np.asarray(Z)
mask = np.absolute(Z) > precision
mask = np.abs(Z) > precision

if 'cmap' not in kwargs:
kwargs['cmap'] = mcolors.ListedColormap(['w', 'k'],
Expand All @@ -7316,12 +7316,12 @@ def spy(self, Z, precision=0, marker=None, markersize=None,
y = c.row
x = c.col
else:
nonzero = np.absolute(c.data) > precision
nonzero = np.abs(c.data) > precision
y = c.row[nonzero]
x = c.col[nonzero]
else:
Z = np.asarray(Z)
nonzero = np.absolute(Z) > precision
nonzero = np.abs(Z) > precision
y, x = np.nonzero(nonzero)
if marker is None:
marker = 's'
Expand Down
12 changes: 6 additions & 6 deletions lib/matplotlib/axes/_base.py
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Expand Up @@ -1346,8 +1346,8 @@ def get_data_ratio(self):
xmin, xmax = self.get_xbound()
ymin, ymax = self.get_ybound()

xsize = max(math.fabs(xmax - xmin), 1e-30)
ysize = max(math.fabs(ymax - ymin), 1e-30)
xsize = max(abs(xmax - xmin), 1e-30)
ysize = max(abs(ymax - ymin), 1e-30)

return ysize / xsize

Expand All @@ -1359,8 +1359,8 @@ def get_data_ratio_log(self):
xmin, xmax = self.get_xbound()
ymin, ymax = self.get_ybound()

xsize = max(math.fabs(math.log10(xmax) - math.log10(xmin)), 1e-30)
ysize = max(math.fabs(math.log10(ymax) - math.log10(ymin)), 1e-30)
xsize = max(abs(math.log10(xmax) - math.log10(xmin)), 1e-30)
ysize = max(abs(math.log10(ymax) - math.log10(ymin)), 1e-30)

return ysize / xsize

Expand Down Expand Up @@ -1432,8 +1432,8 @@ def apply_aspect(self, position=None):
xmin, xmax = math.log10(xmin), math.log10(xmax)
ymin, ymax = math.log10(ymin), math.log10(ymax)

xsize = max(math.fabs(xmax - xmin), 1e-30)
ysize = max(math.fabs(ymax - ymin), 1e-30)
xsize = max(abs(xmax - xmin), 1e-30)
ysize = max(abs(ymax - ymin), 1e-30)

l, b, w, h = position.bounds
box_aspect = fig_aspect * (h / w)
Expand Down
26 changes: 7 additions & 19 deletions lib/matplotlib/contour.py
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Expand Up @@ -226,20 +226,8 @@ def clabel(self, *args, **kwargs):

def print_label(self, linecontour, labelwidth):
"Return *False* if contours are too short for a label."
lcsize = len(linecontour)
if lcsize > 10 * labelwidth:
return True

xmax = np.amax(linecontour[:, 0])
xmin = np.amin(linecontour[:, 0])
ymax = np.amax(linecontour[:, 1])
ymin = np.amin(linecontour[:, 1])

lw = labelwidth
if (xmax - xmin) > 1.2 * lw or (ymax - ymin) > 1.2 * lw:
return True
else:
return False
return (len(linecontour) > 10 * labelwidth
or (np.ptp(linecontour, axis=0) > 1.2 * labelwidth).any())

def too_close(self, x, y, lw):
"Return *True* if a label is already near this location."
Expand Down Expand Up @@ -1056,8 +1044,8 @@ def _process_args(self, *args, **kwargs):
self.levels = args[0]
self.allsegs = args[1]
self.allkinds = len(args) > 2 and args[2] or None
self.zmax = np.amax(self.levels)
self.zmin = np.amin(self.levels)
self.zmax = np.max(self.levels)
self.zmin = np.min(self.levels)
self._auto = False

# Check lengths of levels and allsegs.
Expand Down Expand Up @@ -1180,7 +1168,7 @@ def _contour_level_args(self, z, args):
if self.filled and len(self.levels) < 2:
raise ValueError("Filled contours require at least 2 levels.")

if len(self.levels) > 1 and np.amin(np.diff(self.levels)) <= 0.0:
if len(self.levels) > 1 and np.min(np.diff(self.levels)) <= 0.0:
if hasattr(self, '_corner_mask') and self._corner_mask == 'legacy':
warnings.warn("Contour levels are not increasing")
else:
Expand Down Expand Up @@ -1210,8 +1198,8 @@ def _process_levels(self):
with line contours.
"""
# following are deprecated and will be removed in 2.2
self._vmin = np.amin(self.levels)
self._vmax = np.amax(self.levels)
self._vmin = np.min(self.levels)
self._vmax = np.max(self.levels)

# Make a private _levels to include extended regions; we
# want to leave the original levels attribute unchanged.
Expand Down
2 changes: 1 addition & 1 deletion lib/matplotlib/legend_handler.py
Original file line number Diff line number Diff line change
Expand Up @@ -551,7 +551,7 @@ def create_artists(self, legend, orig_handle,
for lm, m in zip(leg_stemlines, stemlines):
self.update_prop(lm, m, legend)

leg_baseline = Line2D([np.amin(xdata), np.amax(xdata)],
leg_baseline = Line2D([np.min(xdata), np.max(xdata)],
[bottom, bottom])

self.update_prop(leg_baseline, baseline, legend)
Expand Down
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