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Merged
merged 1 commit into from
Mar 25, 2019
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Doc: Update timeline example #13719

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1 change: 1 addition & 0 deletions .flake8
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Original file line number Diff line number Diff line change
Expand Up @@ -145,6 +145,7 @@ per-file-ignores =
examples/lines_bars_and_markers/span_regions.py: E402
examples/lines_bars_and_markers/stem_plot.py: E402
examples/lines_bars_and_markers/step_demo.py: E402
examples/lines_bars_and_markers/timeline.py: E402
examples/misc/agg_buffer.py: E402
examples/misc/anchored_artists.py: E501
examples/misc/contour_manual.py: E501
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138 changes: 93 additions & 45 deletions examples/lines_bars_and_markers/timeline.py
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Expand Up @@ -15,57 +15,105 @@
import matplotlib.dates as mdates
from datetime import datetime

# A list of Matplotlib releases and their dates
# Taken from https://api.github.com/repos/matplotlib/matplotlib/releases
names = ['v2.2.2', 'v2.2.1', 'v2.2.0', 'v2.1.2', 'v2.1.1', 'v2.1.0', 'v2.0.2',
'v2.0.1', 'v2.0.0', 'v1.5.3', 'v1.5.2', 'v1.5.1', 'v1.5.0', 'v1.4.3',
'v1.4.2', 'v1.4.1', 'v1.4.0']

dates = ['2018-03-17T03:00:07Z', '2018-03-16T22:06:39Z',
'2018-03-06T12:53:32Z', '2018-01-18T04:56:47Z',
'2017-12-10T04:47:38Z', '2017-10-07T22:35:12Z',
'2017-05-10T02:11:15Z', '2017-05-02T01:59:49Z',
'2017-01-17T02:59:36Z', '2016-09-09T03:00:52Z',
'2016-07-03T15:52:01Z', '2016-01-10T22:38:50Z',
'2015-10-29T21:40:23Z', '2015-02-16T04:22:54Z',
'2014-10-26T03:24:13Z', '2014-10-18T18:56:23Z',
'2014-08-26T21:06:04Z']
dates = [datetime.strptime(ii, "%Y-%m-%dT%H:%M:%SZ") for ii in dates]
try:
# Try to fetch a list of Matplotlib releases and their dates
# from https://api.github.com/repos/matplotlib/matplotlib/releases
import urllib.request
import json

url = 'https://api.github.com/repos/matplotlib/matplotlib/releases'
url += '?per_page=100'
data = json.loads(urllib.request.urlopen(url, timeout=.4).read().decode())

dates = []
names = []
for item in data:
if 'rc' not in item['tag_name'] and 'b' not in item['tag_name']:
dates.append(item['published_at'].split("T")[0])
names.append(item['tag_name'])
# Convert date strings (e.g. 2014-10-18) to datetime
dates = [datetime.strptime(d, "%Y-%m-%d") for d in dates]

except Exception:
# In case the above fails, e.g. because of missing internet connection
# use the following lists as fallback.
names = ['v2.2.4', 'v3.0.3', 'v3.0.2', 'v3.0.1', 'v3.0.0', 'v2.2.3',
'v2.2.2', 'v2.2.1', 'v2.2.0', 'v2.1.2', 'v2.1.1', 'v2.1.0',
'v2.0.2', 'v2.0.1', 'v2.0.0', 'v1.5.3', 'v1.5.2', 'v1.5.1',
'v1.5.0', 'v1.4.3', 'v1.4.2', 'v1.4.1', 'v1.4.0']

dates = ['2019-02-26', '2019-02-26', '2018-11-10', '2018-11-10',
'2018-09-18', '2018-08-10', '2018-03-17', '2018-03-16',
'2018-03-06', '2018-01-18', '2017-12-10', '2017-10-07',
'2017-05-10', '2017-05-02', '2017-01-17', '2016-09-09',
'2016-07-03', '2016-01-10', '2015-10-29', '2015-02-16',
'2014-10-26', '2014-10-18', '2014-08-26']

# Convert date strings (e.g. 2014-10-18) to datetime
dates = [datetime.strptime(d, "%Y-%m-%d") for d in dates]

##############################################################################
# Next, we'll iterate through each date and plot it on a horizontal line.
# We'll add some styling to the text so that overlaps aren't as strong.
# Next, we'll create a `~.Axes.stem` plot with some variation in levels as to
# distinguish even close-by events. In contrast to a usual stem plot, we will
# shift the markers to the baseline for visual emphasis on the one-dimensional
# nature of the time line.
# For each event, we add a text label via `~.Axes.annotate`, which is offset
# in units of points from the tip of the event line.
#
# Note that Matplotlib will automatically plot datetime inputs.

levels = np.array([-5, 5, -3, 3, -1, 1])
fig, ax = plt.subplots(figsize=(8, 5))

# Create the base line
start = min(dates)
stop = max(dates)
ax.plot((start, stop), (0, 0), 'k', alpha=.5)

# Iterate through releases annotating each one
for ii, (iname, idate) in enumerate(zip(names, dates)):
level = levels[ii % 6]
vert = 'top' if level < 0 else 'bottom'

ax.scatter(idate, 0, s=100, facecolor='w', edgecolor='k', zorder=9999)
# Plot a line up to the text
ax.plot((idate, idate), (0, level), c='r', alpha=.7)
# Give the text a faint background and align it properly
ax.text(idate, level, iname,
horizontalalignment='right', verticalalignment=vert, fontsize=14,
backgroundcolor=(1., 1., 1., .3))

# Choose some nice levels
levels = np.tile([-5, 5, -3, 3, -1, 1],
int(np.ceil(len(dates)/6)))[:len(dates)]

# Create figure and plot a stem plot with the date
fig, ax = plt.subplots(figsize=(8.8, 4), constrained_layout=True)
ax.set(title="Matplotlib release dates")
# Set the xticks formatting
# format xaxis with 3 month intervals
ax.get_xaxis().set_major_locator(mdates.MonthLocator(interval=3))

markerline, stemline, baseline = ax.stem(dates, levels,
linefmt="C3-", basefmt="k-",
use_line_collection=True)

plt.setp(markerline, mec="k", mfc="w", zorder=3)

# Shift the markers to the baseline by replacing the y-data by zeros.
markerline.set_ydata(np.zeros(len(dates)))
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This is a hack on the original purpose of stem. Not sure I like it, but OTOH, the loop before wasn't good either. At least, this needs explanation.


# annotate lines
vert = np.array(['top', 'bottom'])[(levels > 0).astype(int)]
for d, l, r, va in zip(dates, levels, names, vert):
ax.annotate(r, xy=(d, l), xytext=(-3, np.sign(l)*3),
textcoords="offset points", va=va, ha="right")

# format xaxis with 4 month intervals
ax.get_xaxis().set_major_locator(mdates.MonthLocator(interval=4))
ax.get_xaxis().set_major_formatter(mdates.DateFormatter("%b %Y"))
fig.autofmt_xdate()
plt.setp(ax.get_xticklabels(), rotation=30, ha="right")

# remove y axis and spines
ax.get_yaxis().set_visible(False)
for spine in ["left", "top", "right"]:
ax.spines[spine].set_visible(False)

# Remove components for a cleaner look
plt.setp((ax.get_yticklabels() + ax.get_yticklines() +
list(ax.spines.values())), visible=False)
ax.margins(y=0.1)
plt.show()


#############################################################################
#
# ------------
#
# References
# """"""""""
#
# The use of the following functions, methods and classes is shown
# in this example:

import matplotlib
matplotlib.axes.Axes.stem
matplotlib.axes.Axes.annotate
matplotlib.axis.Axis.set_major_locator
matplotlib.axis.Axis.set_major_formatter
matplotlib.dates.MonthLocator
matplotlib.dates.DateFormatter