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Merged streamline examples #8336

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Merged
merged 4 commits into from
Apr 12, 2017
Merged

Merged streamline examples #8336

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bf2b43b
Merge all figure in streamplot examples in one plot
patniharshit Mar 19, 2017
92b1196
Add gridspec to have equal aspect ratio and remove references of deleted
patniharshit Mar 23, 2017
913fdb7
Remove data regeneration
patniharshit Mar 28, 2017
d56b5ce
Update example name in docs
patniharshit Apr 10, 2017
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Remove data regeneration
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@patniharshit @dstansby
patniharshit authored and dstansby committed Apr 12, 2017
commit 913fdb7331c0b5d6ddc0ea8f07e1a19ba7585b74
25 changes: 8 additions & 17 deletions 25 ...es_contours_and_fields/streamplot_demo.py → ...es_contours_and_fields/plot_streamplot.py
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Expand Up @@ -3,14 +3,14 @@
Streamplot
==========

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

* Varying the color along a stream line.
* Varying the density of stream lines.
* Varying the line width along a stream line.
* Controlling the starting points of stream lines.
* Stream lines skipping masked regions and NaN values.
* Varying the color along a streamline.
* Varying the density of streamlines.
* Varying the line width along a streamline.
* Controlling the starting points of streamlines.
* Streamlines skipping masked regions and NaN values.
"""
import numpy as np
import matplotlib.pyplot as plt
Expand All @@ -34,7 +34,7 @@
ax1 = fig.add_subplot(gs[0, 1])
strm = ax1.streamplot(X, Y, U, V, color=U, linewidth=2, cmap='autumn')
fig.colorbar(strm.lines)
ax1.set_title('Varying color')
ax1.set_title('Varying Color')

# Varying line width along a streamline
ax2 = fig.add_subplot(gs[1, 0])
Expand All @@ -43,9 +43,6 @@
ax2.set_title('Varying Line Width')

# Controlling the starting points of the streamlines
X, Y = (np.linspace(-3, 3, 100),
np.linspace(-3, 3, 100))
U, V = np.mgrid[-3:3:100j, 0:0:100j]
seed_points = np.array([[-2, -1, 0, 1, 2, -1], [-2, -1, 0, 1, 2, 2]])

ax3 = fig.add_subplot(gs[1, 1])
Expand All @@ -59,12 +56,6 @@
ax3.axis((-w, w, -w, w))

# Create a mask
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)

mask = np.zeros(U.shape, dtype=bool)
mask[40:60, 40:60] = True
U[:20, :20] = np.nan
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