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Merged
merged 7 commits into from
Jan 5, 2016
Merged

De-randomize doc builds #5769

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1856ca3
DOC: Ensure arrow demo is plotted in consistent order.
QuLogic Dec 25, 2015
800d4ad
DOC: Ensure named colours are sorted by name too.
QuLogic Dec 25, 2015
093c819
DOC: Ensure 0.98.4 what's new example is consistent.
QuLogic Dec 30, 2015
a9a0251
DOC: Remove randomness from tight layout demo.
QuLogic Dec 31, 2015
7a57fde
DOC: Sort aliased property names in listing.
QuLogic Dec 31, 2015
e9c762d
DOC: Sort replaced parameter names.
QuLogic Dec 31, 2015
8314b8b
DOC: Regularize random data in example plots.
QuLogic Dec 31, 2015
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DOC: Regularize random data in example plots. 
This ensures that the same plots are produced between builds.
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@QuLogic
QuLogic committed Jan 2, 2016
commit 8314b8b4306318ca35996d5da1ab91ed275d0897
5 changes: 3 additions & 2 deletions examples/api/filled_step.py
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@@ -1,4 +1,5 @@
import itertools
from collections import OrderedDict
from functools import partial

import numpy as np
Expand Down Expand Up @@ -174,9 +175,9 @@ def stack_hist(ax, stacked_data, sty_cycle, bottoms=None,
hatch_cycle = cycler('hatch', ['/', '*', '+', '|'])

# make some synthetic data
np.random.seed(0)
stack_data = np.random.randn(4, 12250)
dict_data = {lab: d for lab, d in zip(list(c['label'] for c in label_cycle),
stack_data)}
dict_data = OrderedDict(zip((c['label'] for c in label_cycle), stack_data))

# work with plain arrays
fig, (ax1, ax2) = plt.subplots(1, 2, figsize=(9, 4.5), tight_layout=True)
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1 change: 1 addition & 0 deletions examples/pylab_examples/boxplot_demo2.py
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Expand Up @@ -16,6 +16,7 @@
randomDists = ['Normal(1,1)', ' Lognormal(1,1)', 'Exp(1)', 'Gumbel(6,4)',
'Triangular(2,9,11)']
N = 500
np.random.seed(0)
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I would suggest adding a comment that the random seeding is only to make the example reproducible

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There are many of these in the examples without any comment; add them as well?

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There are many issues with the examples so I wouldn't expect to fix all of them but I would like to do this in new examples

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Done.

norm = np.random.normal(1, 1, N)
logn = np.random.lognormal(1, 1, N)
expo = np.random.exponential(1, N)
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3 changes: 3 additions & 0 deletions examples/pylab_examples/spectrum_demo.py
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@@ -1,6 +1,9 @@
import matplotlib.pyplot as plt
import numpy as np


np.random.seed(0)

dt = 0.01
Fs = 1/dt
t = np.arange(0, 10, dt)
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20 changes: 10 additions & 10 deletions examples/pylab_examples/system_monitor.py
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Expand Up @@ -3,23 +3,23 @@
import numpy as np


def get_memory():
def get_memory(t):
"Simulate a function that returns system memory"
return 100*(0.5 + 0.5*np.sin(0.5*np.pi*time.time()))
return 100 * (0.5 + 0.5 * np.sin(0.5 * np.pi * t))


def get_cpu():
def get_cpu(t):
"Simulate a function that returns cpu usage"
return 100*(0.5 + 0.5*np.sin(0.2*np.pi*(time.time() - 0.25)))
return 100 * (0.5 + 0.5 * np.sin(0.2 * np.pi * (t - 0.25)))


def get_net():
def get_net(t):
"Simulate a function that returns network bandwidth"
return 100*(0.5 + 0.5*np.sin(0.7*np.pi*(time.time() - 0.1)))
return 100 * (0.5 + 0.5 * np.sin(0.7 * np.pi * (t - 0.1)))


def get_stats():
return get_memory(), get_cpu(), get_net()
def get_stats(t):
return get_memory(t), get_cpu(t), get_net(t)

fig, ax = plt.subplots()
ind = np.arange(1, 4)
Expand All @@ -28,7 +28,7 @@ def get_stats():
plt.show(block=False)


pm, pc, pn = plt.bar(ind, get_stats())
pm, pc, pn = plt.bar(ind, get_stats(0))
centers = ind + 0.5*pm.get_width()
pm.set_facecolor('r')
pc.set_facecolor('g')
Expand All @@ -42,7 +42,7 @@ def get_stats():

start = time.time()
for i in range(200): # run for a little while
m, c, n = get_stats()
m, c, n = get_stats(i / 10.0)

# update the animated artists
pm.set_height(m)
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3 changes: 3 additions & 0 deletions examples/pylab_examples/xcorr_demo.py
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@@ -1,6 +1,9 @@
import matplotlib.pyplot as plt
import numpy as np


np.random.seed(0)

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Same

x, y = np.random.randn(2, 100)
fig = plt.figure()
ax1 = fig.add_subplot(211)
Expand Down