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Merged and improved the streamplot demonstration #8082

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08b2382
Merged the three streamplot_demo_X.py files into a single streamplot_…
tmcclintock Feb 15, 2017
4618736
Changed plt.cm.autumn to the string autumn when specifying the colorm…
tmcclintock Feb 15, 2017
fadc12c
Changed fig4 to fig3... because there was no fig3.
tmcclintock Feb 17, 2017
2d8f334
Added a space to conform to PEP8.
tmcclintock Feb 17, 2017
fc0ce67
Fixed both references to the streamplot demo in the documentation files.
tmcclintock Feb 19, 2017
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2 changes: 1 addition & 1 deletion doc/users/prev_whats_new/whats_new_1.2.rst
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Expand Up @@ -152,7 +152,7 @@ In addition to simply plotting the streamlines of the vector field,
line widths of the streamlines to a separate parameter, such as the speed or
local intensity of the vector field.

.. plot:: mpl_examples/images_contours_and_fields/streamplot_demo_features.py
.. plot:: mpl_examples/images_contours_and_fields/streamplot_demo.py


New hist functionality
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2 changes: 1 addition & 1 deletion doc/users/screenshots.rst
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Expand Up @@ -71,7 +71,7 @@ a vector field. In addition to simply plotting the streamlines, it allows you
to map the colors and/or line widths of streamlines to a separate parameter,
such as the speed or local intensity of the vector field.

.. plot:: mpl_examples/images_contours_and_fields/streamplot_demo_features.py
.. plot:: mpl_examples/images_contours_and_fields/streamplot_demo.py

This feature complements the :meth:`~matplotlib.pyplot.quiver` function for
plotting vector fields. Thanks to Tom Flannaghan and Tony Yu for adding the
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68 changes: 68 additions & 0 deletions examples/images_contours_and_fields/streamplot_demo.py
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@@ -0,0 +1,68 @@
"""
==========
Streamplot
==========

Demo of the `streamplot` function.

A streamplot, or streamline plot, is used to display 2D vector fields. This
example shows a few features of the stream plot function:
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stream plot <- streamplot?


* Varying the color along a streamline.
* Varying the density of streamlines.
* Varying the line width along a stream line.
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stream line <- streamline?

* Streamlines skipping masked regions and NaN values.
* Controlling the start points of streamlines.
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See the similar comment below (in the relevant code block).

"""
import numpy as np
import matplotlib.pyplot as plt

w = 3
Y, X = np.mgrid[-w:w:100j, -w:w:100j]
U = -1 - X**2 + Y
V = 1 + X - Y**2
speed = np.sqrt(U*U + V*V)

# Varying color along a streamline
fig0, ax = plt.subplots()
strm = ax.streamplot(X, Y, U, V, color=U, linewidth=2, cmap='autumn')
fig0.colorbar(strm.lines)

# Varying the density of streamlines
fig1, (ax1, ax2) = plt.subplots(ncols=2)
ax1.streamplot(X, Y, U, V, density=[0.5, 1])

# Varying the line width along a stream line
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I would merge this block with the previous one. I find it a bit perturbing that the previous block creates two subplots but only uses one. IMO, the two description comments may then be merged into something like:

# Varying the density of streamlines (ax1) and the line width along
# a streamline (ax2).

lw = 5*speed / speed.max()
ax2.streamplot(X, Y, U, V, density=0.6, color='k', linewidth=lw)

# Streamlines skipping masked regions and NaN values
mask = np.zeros(U.shape, dtype=bool)
mask[40:60, 40:60] = True
U[:20, :20] = np.nan
U = np.ma.array(U, mask=mask)

fig2, ax = plt.subplots()
ax.streamplot(X, Y, U, V, color='r')

ax.imshow(-mask, extent=(-w, w, -w, w), alpha=0.5,
interpolation='nearest', cmap=plt.cm.gray)

# Controlling the start points of streamlines
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# Controlling the start points of streamlines <- # Controlling the start points of the streamlines. Disclaimer: I am not a native English speaker, so please forget this comment if I am obviously wrong ;)…

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The former refers to any streamlines, while the latter is about these streamlines. More importantly, I think it should be "starting" instead of "start".

X, Y = (np.linspace(-3, 3, 100),
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Why not reuse the previous X and Y arrays? Especially if the purpose is to create similar arrays.

np.linspace(-3, 3, 100))

U, V = np.mgrid[-3:3:100j, 0:0:100j]

seed_points = np.array([[-2, 0, 1], [-2, 0, 1]])
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Any reason for changing the U, V and seed_points arrays compared to the former streamplot_demo_start_points.py script?


fig3, ax = plt.subplots()
strm = ax.streamplot(X, Y, U, V, color=U, linewidth=2,
cmap="autumn", start_points=seed_points.T)
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Being there, I would replace the double quotes with single ones (i.e. "autumn" <- 'autumn'), to be consistent with the rest of the script.

fig3.colorbar(strm.lines)

ax.plot(seed_points[0], seed_points[1], 'bo')
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@afvincent afvincent Feb 27, 2017 •
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It might be useful to add a small comment to precise that this is some kind of an helper plot. Maybe simply:

# Displaying the starting points with red symbols.

Edit: start <- starting (see @QuLogic's comment above)


ax.axis((-3, 3, -3, 3))

plt.show()
33 changes: 0 additions & 33 deletions examples/images_contours_and_fields/streamplot_demo_features.py
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29 changes: 0 additions & 29 deletions examples/images_contours_and_fields/streamplot_demo_masking.py
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28 changes: 0 additions & 28 deletions examples/images_contours_and_fields/streamplot_demo_start_points.py
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