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DOC: Make abbreviation of versus consistent.
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doc/devel/MEP/MEP10.rst

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@@ -133,8 +133,8 @@ that docstring in the parsed content on the example page. These
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docstrings could easily include references to any other part of the
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documentation.
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Documentation using help() vs a browser
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---------------------------------------
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Documentation using help() vs. a browser
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----------------------------------------
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Using Sphinx markup in the source allows for good-looking docs in your
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browser, but the markup also makes the raw text returned using help()

doc/users/event_handling.rst

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@@ -519,7 +519,7 @@ Picking exercise
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Create a data set of 100 arrays of 1000 Gaussian random numbers and
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compute the sample mean and standard deviation of each of them (hint:
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numpy arrays have a mean and std method) and make a xy marker plot of
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the 100 means vs the 100 standard deviations. Connect the line
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the 100 means vs. the 100 standard deviations. Connect the line
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created by the plot command to the pick event, and plot the original
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time series of the data that generated the clicked on points. If more
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than one point is within the tolerance of the clicked on point, you
@@ -528,7 +528,7 @@ can use multiple subplots to plot the multiple time series.
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Exercise solution::
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"""
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compute the mean and stddev of 100 data sets and plot mean vs stddev.
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compute the mean and stddev of 100 data sets and plot mean vs. stddev.
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When you click on one of the mu, sigma points, plot the raw data from
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the dataset that generated the mean and stddev
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"""

doc/users/prev_whats_new/changelog.rst

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@@ -2827,7 +2827,7 @@ the `API changes <../../api/api_changes.html>`_.
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now looks correct - SC
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2007-01-11 Added Axes.xcorr and Axes.acorr to plot the cross
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correlation of x vs y or the autocorrelation of x. pylab
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correlation of x vs. y or the autocorrelation of x. pylab
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wrappers also provided. See examples/xcorr_demo.py - JDH
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2007-01-10 Added "Subplot.label_outer" method. It will set the

doc/users/prev_whats_new/whats_new_1.5.rst

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@@ -504,7 +504,7 @@ Artist-level {get,set}_usetex for text
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``````````````````````````````````````
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Add ``{get,set}_usetex`` methods to :class:`~matplotlib.text.Text` objects
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which allow artist-level control of LaTeX rendering vs the internal mathtex
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which allow artist-level control of LaTeX rendering vs. the internal mathtex
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rendering.
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examples/shapes_and_collections/line_collection.py

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@@ -19,7 +19,7 @@
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# simple example showing how it is done.
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x = np.arange(100)
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# Here are many sets of y to plot vs x
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# Here are many sets of y to plot vs. x
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ys = x[:50, np.newaxis] + x[np.newaxis, :]
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segs = np.zeros((50, 100, 2))
@@ -56,7 +56,7 @@
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N = 50
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x = np.arange(N)
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# Here are many sets of y to plot vs x
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# Here are many sets of y to plot vs. x
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ys = [x + i for i in x]
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# We need to set the plot limits, they will not autoscale

examples/statistics/barchart_demo.py

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@@ -49,7 +49,7 @@ def format_score(scr, test):
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"""
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Build up the score labels for the right Y-axis by first
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appending a carriage return to each string and then tacking on
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the appropriate meta information (i.e., 'laps' vs 'seconds'). We
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the appropriate meta information (i.e., 'laps' vs. 'seconds'). We
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want the labels centered on the ticks, so if there is no meta
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info (like for pushups) then don't add the carriage return to
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the string

examples/subplots_axes_and_figures/shared_axis_demo.py

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@@ -9,7 +9,7 @@
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Changing the axis limits on one axes will be reflected automatically
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in the other, and vice-versa, so when you navigate with the toolbar
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the axes will follow each other on their shared axes. Ditto for
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changes in the axis scaling (e.g., log vs linear). However, it is
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changes in the axis scaling (e.g., log vs. linear). However, it is
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possible to have differences in tick labeling, e.g., you can selectively
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turn off the tick labels on one axes.
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extern/agg24-svn/include/agg_span_gradient_contour.h

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@@ -2,7 +2,7 @@
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// AGG Contribution Pack - Gradients 1 (AGG CP - Gradients 1)
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// http://milan.marusinec.sk/aggcp
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//
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// For Anti-Grain Geometry - Version 2.4
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// For Anti-Grain Geometry - Version 2.4
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// http://www.antigrain.org
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//
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// Contribution Created By:
@@ -49,7 +49,7 @@ namespace agg
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int m_frame;
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double m_d1;
52-
double m_d2;
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double m_d2;
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public:
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gradient_contour() :
@@ -90,7 +90,7 @@ namespace agg
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void frame(int f ) { m_frame = f; }
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int frame() { return m_frame; }
93-
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int calculate(int x, int y, int d) const
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{
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if (m_buffer)
@@ -193,7 +193,7 @@ namespace agg
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// Setup VG Engine & Render
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agg::rendering_buffer rb;
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rb.attach(buffer ,width ,height ,width );
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agg::pixfmt_gray8 pf(rb);
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agg::renderer_base<agg::pixfmt_gray8> renb(pf );
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@@ -209,14 +209,14 @@ namespace agg
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ras.add_path(trans );
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// II. Distance Transform
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// Create Float Buffer + 0 vs infinity (1e20) assignment
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// Create Float Buffer + 0 vs. infinity (1e20) assignment
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float* image = new float[width * height];
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if (image)
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{
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for (int y = 0, l = 0; y < height; y++ )
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for (int y = 0, l = 0; y < height; y++ )
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{
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for (int x = 0; x < width; x++, l++ )
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for (int x = 0; x < width; x++, l++ )
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{
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if (buffer[l ] == 0)
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{
@@ -227,7 +227,7 @@ namespace agg
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image[l ] = float(infinity );
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}
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}
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}
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// DT of 2d
@@ -247,34 +247,34 @@ namespace agg
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if ((spanf) && (spang) && (spanr) && (spann))
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{
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// Transform along columns
250-
for (int x = 0; x < width; x++ )
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for (int x = 0; x < width; x++ )
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{
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for (int y = 0; y < height; y++ )
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for (int y = 0; y < height; y++ )
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{
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spanf[y] = image[y * width + x];
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}
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257257
// DT of 1d
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dt(spanf ,spang ,spanr ,spann ,height );
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260-
for (int y = 0; y < height; y++ )
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for (int y = 0; y < height; y++ )
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{
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image[y * width + x] = spanr[y];
263263
}
264264
}
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266266
// Transform along rows
267-
for (int y = 0; y < height; y++ )
267+
for (int y = 0; y < height; y++ )
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{
269-
for (int x = 0; x < width; x++ )
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for (int x = 0; x < width; x++ )
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{
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spanf[x] = image[y * width + x];
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}
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// DT of 1d
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dt(spanf ,spang ,spanr ,spann ,width );
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277-
for (int x = 0; x < width; x++ )
277+
for (int x = 0; x < width; x++ )
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{
279279
image[y * width + x] = spanr[x];
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}
@@ -284,9 +284,9 @@ namespace agg
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float min = sqrt(image[0] );
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float max = min;
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287-
for (int y = 0, l = 0; y < height; y++ )
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for (int y = 0, l = 0; y < height; y++ )
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{
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for (int x = 0; x < width; x++, l++ )
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for (int x = 0; x < width; x++, l++ )
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{
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image[l] = sqrt(image[l]);
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@@ -312,9 +312,9 @@ namespace agg
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{
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float scale = 255 / (max - min );
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315-
for (int y = 0, l = 0; y < height; y++ )
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for (int y = 0, l = 0; y < height; y++ )
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{
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for (int x = 0; x < width; x++ ,l++ )
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for (int x = 0; x < width; x++ ,l++ )
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{
319319
buffer[l] = int8u(int((image[l] - min ) * scale ));
320320
}
@@ -335,7 +335,7 @@ namespace agg
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result = m_buffer;
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337337
}
338-
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339339
if (spanf) { delete [] spanf; }
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if (spang) { delete [] spang; }
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if (spanr) { delete [] spanr; }

lib/matplotlib/__init__.py

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@@ -1145,8 +1145,8 @@ class rc_context:
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plt.plot(x, b)
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plt.plot(x, c)
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1148-
The 'a' vs 'x' and 'c' vs 'x' plots would have settings from
1149-
'screen.rc', while the 'b' vs 'x' plot would have settings from
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The 'a' vs. 'x' and 'c' vs. 'x' plots would have settings from
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'screen.rc', while the 'b' vs. 'x' plot would have settings from
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'print.rc'.
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A dictionary can also be passed to the context manager::

lib/matplotlib/axes/_axes.py

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@@ -4284,7 +4284,7 @@ def scatter(self, x, y, s=None, c=None, marker=None, cmap=None, norm=None,
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verts=None, edgecolors=None, *, plotnonfinite=False,
42854285
**kwargs):
42864286
"""
4287-
A scatter plot of *y* vs *x* with varying marker size and/or color.
4287+
A scatter plot of *y* vs. *x* with varying marker size and/or color.
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Parameters
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----------

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