8000 Backport PR #13719: Doc: Update timeline example · matplotlib/matplotlib@4c91d7d · GitHub
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Commit 4c91d7d

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jklymakMeeseeksDev[bot]
jklymak
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Backport PR #13719: Doc: Update timeline example
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‎.flake8

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examples/lines_bars_and_markers/span_regions.py: E402
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examples/lines_bars_and_markers/stem_plot.py: E402
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examples/lines_bars_and_markers/step_demo.py: E402
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examples/lines_bars_and_markers/timeline.py: E402
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examples/misc/agg_buffer.py: E402
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examples/misc/anchored_artists.py: E501
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examples/misc/contour_manual.py: E501

‎examples/lines_bars_and_markers/timeline.py

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import matplotlib.dates as mdates
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from datetime import datetime
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# A list of Matplotlib releases and their dates
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# Taken from https://api.github.com/repos/matplotlib/matplotlib/releases
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names = ['v2.2.2', 'v2.2.1', 'v2.2.0', 'v2.1.2', 'v2.1.1', 'v2.1.0', 'v2.0.2',
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'v2.0.1', 'v2.0.0', 'v1.5.3', 'v1.5.2', 'v1.5.1', 'v1.5.0', 'v1.4.3',
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'v1.4.2', 'v1.4.1', 'v1.4.0']
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dates = ['2018-03-17T03:00:07Z', '2018-03-16T22:06:39Z',
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'2018-03-06T12:53:32Z', '2018-01-18T04:56:47Z',
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'2017-12-10T04:47:38Z', '2017-10-07T22:35:12Z',
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'2017-05-10T02:11:15Z', '2017-05-02T01:59:49Z',
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'2017-01-17T02:59:36Z', '2016-09-09T03:00:52Z',
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'2016-07-03T15:52:01Z', '2 8000 016-01-10T22:38:50Z',
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'2015-10-29T21:40:23Z', '2015-02-16T04:22:54Z',
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'2014-10-26T03:24:13Z', '2014-10-18T18:56:23Z',
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'2014-08-26T21:06:04Z']
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dates = [datetime.strptime(ii, "%Y-%m-%dT%H:%M:%SZ") for ii in dates]
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try:
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# Try to fetch a list of Matplotlib releases and their dates
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# from https://api.github.com/repos/matplotlib/matplotlib/releases
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import urllib.request
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import json
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url = 'https://api.github.com/repos/matplotlib/matplotlib/releases'
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url += '?per_page=100'
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data = json.loads(urllib.request.urlopen(url, timeout=.4).read().decode())
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dates = []
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names = []
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for item in data:
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if 'rc' not in item['tag_name'] and 'b' not in item['tag_name']:
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dates.append(item['published_at'].split("T")[0])
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names.append(item['tag_name'])
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# Convert date strings (e.g. 2014-10-18) to datetime
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dates = [datetime.strptime(d, "%Y-%m-%d") for d in dates]
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except Exception:
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# In case the above fails, e.g. because of missing internet connection
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# use the following lists as fallback.
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names = ['v2.2.4', 'v3.0.3', 'v3.0.2', 'v3.0.1', 'v3.0.0', 'v2.2.3',
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'v2.2.2', 'v2.2.1', 'v2.2.0', 'v2.1.2', 'v2.1.1', 'v2.1.0',
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'v2.0.2', 'v2.0.1', 'v2.0.0', 'v1.5.3', 'v1.5.2', 'v1.5.1',
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'v1.5.0', 'v1.4.3', 'v1.4.2', 'v1.4.1', 'v1.4.0']
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dates = ['2019-02-26', '2019-02-26', '2018-11-10', '2018-11-10',
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'2018-09-18', '2018-08-10', '2018-03-17', '2018-03-16',
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'2018-03-06', '2018-01-18', '2017-12-10', '2017-10-07',
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'2017-05-10', '2017-05-02', '2017-01-17', '2016-09-09',
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'2016-07-03', '2016-01-10', '2015-10-29', '2015-02-16',
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'2014-10-26', '2014-10-18', '2014-08-26']
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# Convert date strings (e.g. 2014-10-18) to datetime
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dates = [datetime.strptime(d, "%Y-%m-%d") for d in dates]
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##############################################################################
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# Next, we'll iterate through each date and plot it on a horizontal line.
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# We'll add some styling to the text so that overlaps aren't as strong.
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# Next, we'll create a `~.Axes.stem` plot with some variation in levels as to
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# distinguish even close-by events. In contrast to a usual stem plot, we will
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# shift the markers to the baseline for visual emphasis on the one-dimensional
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# nature of the time line.
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# For each event, we add a text label via `~.Axes.annotate`, which is offset
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# in units of points from the tip of the event line.
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#
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# Note that Matplotlib will automatically plot datetime inputs.
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levels = np.array([-5, 5, -3, 3, -1, 1])
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fig, ax = plt.subplots(figsize=(8, 5))
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# Create the base line
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start = min(dates)
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stop = max(dates)
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ax.plot((start, stop), (0, 0), 'k', alpha=.5)
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# Iterate through releases annotating each one
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for ii, (iname, idate) in enumerate(zip(names, dates)):
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level = levels[ii % 6]
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vert = 'top' if level < 0 else 'bottom'
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ax.scatter(idate, 0, s=100, facecolor='w', edgecolor='k', zorder=9999)
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# Plot a line up to the text
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ax.plot((idate, idate), (0, level), c='r', alpha=.7)
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# Give the text a faint background and align it properly
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ax.text(idate, level, iname,
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horizontalalignment='right', verticalalignment=vert, fontsize=14,
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backgroundcolor=(1., 1., 1., .3))
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# Choose some nice levels
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levels = np.tile([-5, 5, -3, 3, -1, 1],
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int(np.ceil(len(dates)/6)))[:len(dates)]
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# Create figure and plot a stem plot with the date
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fig, ax = plt.subplots(figsize=(8.8, 4), constrained_layout=True)
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ax.set(title="Matplotlib release dates")
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# Set the xticks formatting
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# format xaxis with 3 month intervals
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ax.get_xaxis().set_major_locator(mdates.MonthLocator(interval=3))
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markerline, stemline, baseline = ax.stem(dates, levels,
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linefmt="C3-", basefmt="k-",
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use_line_collection=True)
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plt.setp(markerline, mec="k", mfc="w", zorder=3)
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# Shift the markers to the baseline by replacing the y-data by zeros.
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markerline.set_ydata(np.zeros(len(dates)))
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# annotate lines
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vert = np.array(['top', 'bottom'])[(levels > 0).astype(int)]
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for d, l, r, va in zip(dates, levels, names, vert):
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ax.annotate(r, xy=(d, l), xytext=(-3, np.sign(l)*3),
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textcoords="offset points", va=va, ha="right")
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# format xaxis with 4 month intervals
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ax.get_xaxis().set_major_locator(mdates.MonthLocator(interval=4))
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ax.get_xaxis().set_major_formatter(mdates.DateFormatter("%b %Y"))
66-
fig.autofmt_xdate()
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plt.setp(ax.get_xticklabels(), rotation=30, ha="right")
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# remove y axis and spines
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ax.get_yaxis().set_visible(False)
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for spine in ["left", "top", "right"]:
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ax.spines[spine].set_visible(False)
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# Remove components for a cleaner look
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plt.setp((ax.get_yticklabels() + ax.get_yticklines() +
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list(ax.spines.values())), visible=False)
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ax.margins(y=0.1)
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plt.show()
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#############################################################################
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#
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# ------------
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#
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# References
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# """"""""""
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#
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# The use of the following functions, methods and classes is shown
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# in this example:
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import matplotlib
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matplotlib.axes.Axes.stem
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matplotlib.axes.Axes.annotate
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matplotlib.axis.Axis.set_major_locator
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matplotlib.axis.Axis.set_major_formatter
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matplotlib.dates.MonthLocator
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matplotlib.dates.DateFormatter

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