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DOC: MEP12 docstrings for errorbar examples
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‎examples/statistics/errorbar_demo.py

Lines changed: 8 additions & 3 deletions
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"""Demo of the errorbar function.
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This exhibits the most basic use of of the error bar method.
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In this case, constant values are provided for both the error
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in the x- and y-directions.
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"""
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Demo of the errorbar function.
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"""
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import numpy as np
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import matplotlib.pyplot as plt
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# example data
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x = np.arange(0.1, 4, 0.5)
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y = np.exp(-x)
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plt.errorbar(x, y, xerr=0.2, yerr=0.4)
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fig, ax = plt.subplots()
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ax.errorbar(x, y, xerr=0.2, yerr=0.4)
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plt.show()

‎examples/statistics/errorbar_demo_features.py

Lines changed: 18 additions & 14 deletions
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"""
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Demo of errorbar function with different ways of specifying error bars.
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"""Demo of the different ways of specifying error bars.
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Errors can be specified as a constant value (as shown in `errorbar_demo.py`),
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or as demonstrated in this example, they can be specified by an N x 1 or 2 x N,
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where N is the number of data points.
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Errors can be specified as a constant value (as shown in
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`errorbar_demo.py`), or as demonstrated in this example, they can be
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specified by an N x 1 or 2 x N, where N is the number of data points.
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N x 1:
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Error varies for each point, but the error values are symmetric (i.e. the
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lower and upper values are equal).
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Error varies for each point, but the error values are
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symmetric (i.e. the lower and upper values are equal).
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2 x N:
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Error varies for each point, and the lower and upper limits (in that order)
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are different (asymmetric case)
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Error varies for each point, and the lower and upper limits
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(in that order) are different (asymmetric case)
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16-
In addition, this example demonstrates how to use log scale with errorbar.
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In addition, this example demonstrates how to use log
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scale with error bars.
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"""
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import numpy as np
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import matplotlib.pyplot as plt
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# example data
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x = np.arange(0.1, 4, 0.5)
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y = np.exp(-x)
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# example error bar values that vary with x-position
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error = 0.1 + 0.2 * x
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# error bar values w/ different -/+ errors
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lower_error = 0.4 * error
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upper_error = error
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asymmetric_error = [lower_error, upper_error]
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3129
fig, (ax0, ax1) = plt.subplots(nrows=2, sharex=True)
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ax0.errorbar(x, y, yerr=error, fmt='-o')
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ax0.set_title('variable, symmetric error')
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# error bar values w/ different -/+ errors that
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# also vary with the x-position
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lower_error = 0.4 * error
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upper_error = error
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asymmetric_error = [lower_error, upper_error]
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3539
ax1.errorbar(x, y, xerr=asymmetric_error, fmt='o')
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ax1.set_title('variable, asymmetric error')
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ax1.set_yscale('log')

‎examples/statistics/errorbar_limits.py

Lines changed: 43 additions & 20 deletions
Original file line numberDiff line numberDiff line change
@@ -1,50 +1,73 @@
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"""Demo of how to include upper and lower limits in error bars
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In matplotlib, errors bars can have "limits". Applying limits to the
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error bars essentially makes the error unidirectional. Because of that,
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upper and lower limits can be applied in both the y- and x-directions
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via the `uplims`, `lolims`, `xuplims`, and `xlolims` parameters,
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respectively. This parameters can be scalar or boolean arrays.
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For example, if `xlolims` is `True`, the x-error bars will only extend
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from the data towards increasing values. If `uplims` is an array filled
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with `False` except for the 3rd and 5th values, all of the y-error bars
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will be bi-directional, except the 3rd and 5th bars, which will extend
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from the data towards decreasing y-values.
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"""
2-
Demo of the errorbar function, including upper and lower limits
3-
"""
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import numpy as np
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import matplotlib.pyplot as plt
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# example data
8-
x = np.arange(0.5, 5.5, 0.5)
20+
x = np.array([0.5, 1.0, 1.5, 2.0, 2.5, 3.0, 3.5, 4.0, 4.5, 5.0])
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y = np.exp(-x)
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xerr = 0.1
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yerr = 0.2
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25+
# lower & upper limits of the error
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lolims = np.array([0, 0, 1, 0, 1, 0, 0, 0, 1, 0], dtype=bool)
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uplims = np.array([0, 1, 0, 0, 0, 1, 0, 0, 0, 1], dtype=bool)
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ls = 'dotted'
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14-
fig = plt.figure()
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ax = fig.add_subplot(1, 1, 1)
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fig, ax = plt.subplots(figsize=(7, 4))
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# standard error bars
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plt.errorbar(x, y, xerr=xerr, yerr=yerr, ls=ls)
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ax.errorbar(x, y, xerr=xerr, yerr=yerr, linestyle=ls)
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2035
# including upper limits
21-
uplims = np.zeros(x.shape)
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uplims[[1, 5, 9]] = True
23-
plt.errorbar(x, y + 0.5, xerr=xerr, yerr=yerr, uplims=uplims, ls=ls)
36+
ax.errorbar(x, y + 0.5, xerr=xerr, yerr=yerr, uplims=uplims,
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linestyle=ls)
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2539
# including lower limits
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lolims = np.zeros(x.shape)
27-
lolims[[2, 4, 8]] = True
28-
plt.errorbar(x, y + 1.0, xerr=xerr, yerr=yerr, lolims=lolims, ls=ls)
40+
ax.errorbar(x, y + 1.0, xerr=xerr, yerr=yerr, lolims=lolims,
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linestyle=ls)
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3043
# including upper and lower limits
31-
plt.errorbar(x, y + 1.5, marker='o', ms=8, xerr=xerr, yerr=yerr,
32-
lolims=lolims, uplims=uplims, ls=ls)
44+
ax.errorbar(x, y + 1.5, xerr=xerr, yerr=yerr,
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lolims=lolims, uplims=uplims,
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marker='o', markersize=8,
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linestyle=ls)
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34-
# including xlower and xupper limits
49+
# Plot a series with lower and upper limits in both x & y
50+
# constant x-error with varying y-error
3551
xerr = 0.2
3652
yerr = np.zeros(x.shape) + 0.2
3753
yerr[[3, 6]] = 0.3
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55+
# mock up some limits by modifying previous data
3856
xlolims = lolims
3957
xuplims = uplims
4058
lolims = np.zeros(x.shape)
4159
uplims = np.zeros(x.shape)
42-
lolims[[6]] = True
43-
uplims[[3]] = True
44-
plt.errorbar(x, y + 2.1, marker='o', ms=8, xerr=xerr, yerr=yerr,
45-
xlolims=xlolims, xuplims=xuplims, uplims=uplims, lolims=lolims,
46-
ls='none')
60+
lolims[[6]] = True # only limited at this index
61+
uplims[[3]] = True # only limited at this index
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63+
# do the plotting
64+
ax.errorbar(x, y + 2.1, xerr=xerr, yerr=yerr,
65+
xlolims=xlolims, xuplims=xuplims,
66+
uplims=uplims, lolims=lolims,
67+
marker='o', markersize=8,
68+
linestyle='none')
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70+
# tidy up the figure
4871
ax.set_xlim((0, 5.5))
4972
ax.set_title('Errorbar upper and lower limits')
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plt.show()

‎examples/statistics/errorbars_and_boxes.py

Lines changed: 36 additions & 15 deletions
Original file line numberDiff line numberDiff line change
@@ -1,6 +1,21 @@
1-
'''
2-
Example to create boxes from error using PatchCollection
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'''
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"""Demo on creating boxes from error bars using PatchCollection
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In this example, we snazz up a pretty standard error bar plot by adding
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a rectangle patch defined by the limits of the bars in both the x- and
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y- directions. Do this, we have to write our own custom function called
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`make_error_boxes`. Close inspection of this function will reveal the
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preferred pattern in writting functions for matplotlib:
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1. an `Axes` object is passed directly to the function
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2. the function operates on the `Axes` methods directly, not through
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the `pyplot` interface
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3. plotting kwargs that could be abbreviated are spelled out for
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better code readability in the figure (for example we use
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`facecolor` instead of `fc`)
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4. the artists returned by the `Axes` plotting methods are then
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returned by the function so that, if desired, their styles
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can be modified later (they are not modified in this example).
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"""
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import numpy as np
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import matplotlib.pyplot as plt
@@ -11,38 +26,44 @@
1126
n = 5
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1328
# Dummy data
29+
np.random.seed(10)
1430
x = np.arange(0, n, 1)
15-
y = np.random.rand(n)*5.
31+
y = np.random.rand(n) * 5.
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1733
# Dummy errors (above and below)
18-
xerr = np.random.rand(2, n)
19-
yerr = np.random.rand(2, n)
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21-
# Create figure and axes
22-
fig, ax = plt.subplots(1)
34+
xerr = np.random.rand(2, n) + 0.1
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yerr = np.random.rand(2, n) + 0.2
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2437

25-
def make_error_boxes(ax, xdata, ydata, xerror, yerror, fc='r', ec='None', alpha=0.5):
38+
def make_error_boxes(ax, xdata, ydata, xerror, yerror, facecolor='r',
39+
edgecolor='None', alpha=0.5):
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2741
# Create list for all the error patches
2842
errorboxes = []
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3044
# Loop over data points; create box from errors at each point
31-
for xc, yc, xe, ye in zip(xdata, ydata, xerror.T, yerror.T):
32-
rect = Rectangle((xc-xe[0], yc-ye[0]), xe.sum(), ye.sum())
45+
for x, y, xe, ye in zip(xdata, ydata, xerror.T, yerror.T):
46+
rect = Rectangle((x - xe[0], y - ye[0]), xe.sum(), ye.sum())
3347
errorboxes.append(rect)
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3549
# Create patch collection with specified colour/alpha
36-
pc = PatchCollection(errorboxes, facecolor=fc, alpha=alpha, edgecolor=ec)
50+
pc = PatchCollection(errorboxes, facecolor=facecolor, alpha=alpha,
51+
edgecolor=edgecolor)
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3853
# Add collection to axes
3954
ax.add_collection(pc)
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4156
# Plot errorbars
42-
ax.errorbar(xdata, ydata, xerr=xerror, yerr=yerror, fmt='None', ecolor='k')
57+
artists = ax.errorbar(xdata, ydata, xerr=xerror, yerr=yerror,
58+
fmt='None', ecolor='k')
4359

60+
return artists
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62+
63+
# Create figure and axes
64+
fig, ax = plt.subplots(1)
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4566
# Call function to create error boxes
46-
make_error_boxes(ax, x, y, xerr, yerr)
67+
_ = make_error_boxes(ax, x, y, xerr, yerr)
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4869
plt.show()

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