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UnCamelCase examples.#16201

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Merged
timhoffm merged 1 commit intomatplotlib:masterfromanntzer:camelicide
Jan 13, 2020
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18 changes: 9 additions & 9 deletionsexamples/event_handling/pipong.py
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Original file line numberDiff line numberDiff line change
Expand Up@@ -126,18 +126,18 @@ def __init__(self, ax):
self.ax = ax
ax.set_ylim([-1, 1])
ax.set_xlim([0, 7])
padAx = 0
padBx = .50
padAy =padBy = .30
padBx += 6.3
pad_a_x = 0
pad_b_x = .50
pad_a_y =pad_b_y = .30
pad_b_x += 6.3

# pads
pA, = self.ax.barh(padAy, .2,
pA, = self.ax.barh(pad_a_y, .2,
height=.3, color='k', alpha=.5, edgecolor='b',
lw=2, label="Player B",
animated=True)
pB, = self.ax.barh(padBy, .2,
height=.3, left=padBx, color='k', alpha=.5,
pB, = self.ax.barh(pad_b_y, .2,
height=.3, left=pad_b_x, color='k', alpha=.5,
edgecolor='r', lw=2, label="Player A",
animated=True)

Expand DownExpand Up@@ -169,8 +169,8 @@ def __init__(self, ax):
self.on = False
self.inst = True # show instructions from the beginning
self.background = None
self.pads = [Pad(pA,padAx, padAy),
Pad(pB,padBx, padBy, 'r')]
self.pads = [Pad(pA,pad_a_x, pad_a_y),
Pad(pB,pad_b_x, pad_b_y, 'r')]
self.pucks = []
self.i = self.ax.annotate(instructions, (.5, 0.5),
name='monospace',
Expand Down
42 changes: 20 additions & 22 deletionsexamples/statistics/boxplot_demo.py
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Original file line numberDiff line numberDiff line change
Expand Up@@ -8,8 +8,8 @@
The following examples show off how to visualize boxplots with
Matplotlib. There are many options to control their appearance and
the statistics that they use to summarize the data.

"""

import matplotlib.pyplot as plt
import numpy as np
from matplotlib.patches import Polygon
Expand DownExpand Up@@ -130,23 +130,23 @@
medians = np.empty(num_boxes)
for i in range(num_boxes):
box = bp['boxes'][i]
boxX = []
boxY = []
box_x = []
box_y = []
for j in range(5):
boxX.append(box.get_xdata()[j])
boxY.append(box.get_ydata()[j])
box_coords = np.column_stack([boxX, boxY])
box_x.append(box.get_xdata()[j])
box_y.append(box.get_ydata()[j])
box_coords = np.column_stack([box_x, box_y])
# Alternate between Dark Khaki and Royal Blue
ax1.add_patch(Polygon(box_coords, facecolor=box_colors[i % 2]))
# Now draw the median lines back over what we just filled in
med = bp['medians'][i]
medianX = []
medianY = []
median_x = []
median_y = []
for j in range(2):
medianX.append(med.get_xdata()[j])
medianY.append(med.get_ydata()[j])
ax1.plot(medianX, medianY, 'k')
medians[i] =medianY[0]
median_x.append(med.get_xdata()[j])
median_y.append(med.get_ydata()[j])
ax1.plot(median_x, median_y, 'k')
medians[i] =median_y[0]
# Finally, overplot the sample averages, with horizontal alignment
# in the center of each box
ax1.plot(np.average(med.get_xdata()), np.average(data[i]),
Expand DownExpand Up@@ -193,22 +193,20 @@
# We can then use the boxplot along with this function to show these intervals.


deffakeBootStrapper(n):
deffake_bootstrapper(n):
"""
This is just a placeholder for the user's method of
bootstrapping the median and its confidence intervals.

Returns an arbitrary median and confidence intervals
packed into a tuple
Returns an arbitrary median and confidence interval packed into a tuple.
"""
if n == 1:
med = 0.1
CI = (-0.25, 0.25)
ci = (-0.25, 0.25)
else:
med = 0.2
CI = (-0.35, 0.50)

return med, CI
ci = (-0.35, 0.50)
return med, ci

inc = 0.1
e1 = np.random.normal(0, 1, size=500)
Expand All@@ -217,10 +215,10 @@ def fakeBootStrapper(n):
e4 = np.random.normal(0, 1 + 2*inc, size=500)

treatments = [e1, e2, e3, e4]
med1,CI1 =fakeBootStrapper(1)
med2,CI2 =fakeBootStrapper(2)
med1,ci1 =fake_bootstrapper(1)
med2,ci2 =fake_bootstrapper(2)
medians = [None, None, med1, med2]
conf_intervals = [None, None,CI1, CI2]
conf_intervals = [None, None,ci1, ci2]

fig, ax = plt.subplots()
pos = np.array(range(len(treatments))) + 1
Expand Down
4 changes: 2 additions & 2 deletionsexamples/statistics/customized_violin.py
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Original file line numberDiff line numberDiff line change
Expand Up@@ -60,12 +60,12 @@ def set_axis_style(ax, labels):
whiskers = np.array([
adjacent_values(sorted_array, q1, q3)
for sorted_array, q1, q3 in zip(data, quartile1, quartile3)])
whiskersMin, whiskersMax = whiskers[:, 0], whiskers[:, 1]
whiskers_min, whiskers_max = whiskers[:, 0], whiskers[:, 1]

inds = np.arange(1, len(medians) + 1)
ax2.scatter(inds, medians, marker='o', color='white', s=30, zorder=3)
ax2.vlines(inds, quartile1, quartile3, color='k', linestyle='-', lw=5)
ax2.vlines(inds,whiskersMin, whiskersMax, color='k', linestyle='-', lw=1)
ax2.vlines(inds,whiskers_min, whiskers_max, color='k', linestyle='-', lw=1)

# set style for the axes
labels = ['A', 'B', 'C', 'D']
Expand Down
8 changes: 1 addition & 7 deletionsexamples/units/basic_units.py
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Original file line numberDiff line numberDiff line change
Expand Up@@ -122,12 +122,8 @@ def __new__(cls, value, unit):
try:
subcls = type(f'TaggedValue_of_{value_class.__name__}',
(cls, value_class), {})
if subcls not in units.registry:
units.registry[subcls] = basicConverter
return object.__new__(subcls)
except TypeError:
if cls not in units.registry:
units.registry[cls] = basicConverter
return object.__new__(cls)

def __init__(self, value, unit):
Expand DownExpand Up@@ -378,6 +374,4 @@ def cos(x):
return math.cos(x.convert_to(radians).get_value())


basicConverter = BasicUnitConverter()
units.registry[BasicUnit] = basicConverter
units.registry[TaggedValue] = basicConverter
units.registry[BasicUnit] = units.registry[TaggedValue] = BasicUnitConverter()
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