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Fix remaining pep8 issues in tutorials.
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‎tutorials/02_intermediate/artists.py‎

Lines changed: 1 addition & 1 deletion
Original file line numberDiff line numberDiff line change
@@ -668,7 +668,7 @@ class in the matplotlib API, and the one you will be working with most
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# gridline Line2D instance
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# label1 Text instance
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# label2 Text instance
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# gridOn boolean which determines whether to draw the gridline
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# gridOn boolean which determines whether to draw the gridline
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# tick1On boolean which determines whether to draw the 1st tickline
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# tick2On boolean which determines whether to draw the 2nd tickline
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# label1On boolean which determines whether to draw the 1st tick label

‎tutorials/02_intermediate/legend_guide.py‎

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@@ -236,9 +236,11 @@
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import matplotlib.patches as mpatches
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class AnyObject(object):
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pass
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class AnyObjectHandler(object):
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def legend_artist(self, legend, orig_handle, fontsize, handlebox):
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x0, y0 = handlebox.xdescent, handlebox.ydescent
@@ -249,6 +251,7 @@ def legend_artist(self, legend, orig_handle, fontsize, handlebox):
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handlebox.add_artist(patch)
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return patch
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plt.legend([AnyObject()], ['My first handler'],
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handler_map={AnyObject: AnyObjectHandler()})
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@@ -267,6 +270,7 @@ def legend_artist(self, legend, orig_handle, fontsize, handlebox):
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from matplotlib.legend_handler import HandlerPatch
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273+
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class HandlerEllipse(HandlerPatch):
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def create_artists(self, legend, orig_handle,
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xdescent, ydescent, width, height, fontsize, trans):

‎tutorials/03_advanced/path_tutorial.py‎

Lines changed: 26 additions & 24 deletions
Original file line numberDiff line numberDiff line change
@@ -19,19 +19,20 @@
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import matplotlib.patches as patches
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verts = [
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(0., 0.), # left, bottom
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(0., 1.), # left, top
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(1., 1.), # right, top
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(1., 0.), # right, bottom
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(0., 0.), # ignored
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]
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codes = [Path.MOVETO,
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Path.LINETO,
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Path.LINETO,
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Path.LINETO,
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Path.CLOSEPOLY,
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]
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(0., 0.), # left, bottom
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(0., 1.), # left, top
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(1., 1.), # right, top
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(1., 0.), # right, bottom
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(0., 0.), # ignored
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]
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codes = [
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Path.MOVETO,
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Path.LINETO,
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Path.LINETO,
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Path.LINETO,
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Path.CLOSEPOLY,
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]
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path = Path(verts, codes)
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@@ -75,17 +76,18 @@
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# point
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verts = [
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(0., 0.), # P0
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(0.2, 1.), # P1
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(1., 0.8), # P2
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(0.8, 0.), # P3
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]
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codes = [Path.MOVETO,
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Path.CURVE4,
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Path.CURVE4,
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Path.CURVE4,
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]
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(0., 0.), # P0
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(0.2, 1.), # P1
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(1., 0.8), # P2
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(0.8, 0.), # P3
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]
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codes = [
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Path.MOVETO,
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Path.CURVE4,
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Path.CURVE4,
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Path.CURVE4,
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]
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path = Path(verts, codes)
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‎tutorials/03_advanced/transforms_tutorial.py‎

Lines changed: 16 additions & 16 deletions
Original file line numberDiff line numberDiff line change
@@ -24,11 +24,11 @@
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Coordinate Transformation Object Description
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========== ===================== ====================================================================================
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`data` ``ax.transData`` The userland data coordinate system, controlled by the xlim and ylim
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`axes` ``ax.transAxes`` The coordinate system of the :class:`~matplotlib.axes.Axes`; (0,0) is
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bottom left of the axes, and (1,1) is top right of the axes.
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`figure` ``fig.transFigure`` The coordinate system of the :class:`~matplotlib.figure.Figure`; (0,0)
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is bottom left of the figure, and (1,1) is top right of the figure.
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`display` `None` This is the pixel coordinate system of the display; (0,0) is the bottom
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`axes` ``ax.transAxes`` The coordinate system of the :class:`~matplotlib.axes.Axes`; (0, 0) is
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bottom left of the axes, and (1, 1) is top right of the axes.
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`figure` ``fig.transFigure`` The coordinate system of the :class:`~matplotlib.figure.Figure`; (0, 0)
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is bottom left of the figure, and (1, 1) is top right of the figure.
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`display` `None` This is the pixel coordinate system of the display; (0, 0) is the bottom
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left of the display, and (width, height) is the top right of the display in pixels.
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Alternatively, the identity transform
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(:class:`matplotlib.transforms.IdentityTransform()`) may be used instead of None.
@@ -87,7 +87,7 @@
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# In [15]: ax.transData.transform((5, 0))
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# Out[15]: array([ 335.175, 247. ])
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#
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# In [16]: ax.transData.transform([(5, 0), (1,2)])
90+
# In [16]: ax.transData.transform([(5, 0), (1, 2)])
9191
# Out[16]:
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# array([[ 335.175, 247. ],
9393
# [ 132.435, 642.2 ]])
@@ -170,13 +170,13 @@
170170
# In [54]: ax.transData.transform((5, 0))
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# Out[54]: array([ 335.175, 247. ])
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#
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# In [55]: ax.set_ylim(-1,2)
173+
# In [55]: ax.set_ylim(-1, 2)
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# Out[55]: (-1, 2)
175175
#
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# In [56]: ax.transData.transform((5, 0))
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# Out[56]: array([ 335.175 , 181.13333333])
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#
179-
# In [57]: ax.set_xlim(10,20)
179+
# In [57]: ax.set_xlim(10, 20)
180180
# Out[57]: (10, 20)
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#
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# In [58]: ax.transData.transform((5, 0))
@@ -189,7 +189,7 @@
189189
# ================
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#
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# After the `data` coordinate system, `axes` is probably the second most
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# useful coordinate system. Here the point (0,0) is the bottom left of
192+
# useful coordinate system. Here the point (0, 0) is the bottom left of
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# your axes or subplot, (0.5, 0.5) is the center, and (1.0, 1.0) is the
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# top right. You can also refer to points outside the range, so (-0.1,
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# 1.1) is to the left and above your axes. This coordinate system is
@@ -272,7 +272,7 @@
272272
# highlight the 1..2 stddev region with a span.
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# We want x to be in data coordinates and y to
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# span from 0..1 in axes coords
275-
rect = patches.Rectangle((1,0), width=1, height=1,
275+
rect = patches.Rectangle((1, 0), width=1, height=1,
276276
transform=trans, color='yellow',
277277
alpha=0.5)
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@@ -389,7 +389,7 @@
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# self.transData = self.transScale + (self.transLimits + self.transAxes)
390390
#
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# We've been introduced to the ``transAxes`` instance above in
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# :ref:`axes-coords`, which maps the (0,0), (1,1) corners of the
392+
# :ref:`axes-coords`, which maps the (0, 0), (1, 1) corners of the
393393
# axes or subplot bounding box to `display` space, so let's look at
394394
# these other two pieces.
395395
#
@@ -405,19 +405,19 @@
405405
# In [81]: ax.set_xlim(0, 10)
406406
# Out[81]: (0, 10)
407407
#
408-
# In [82]: ax.set_ylim(-1,1)
408+
# In [82]: ax.set_ylim(-1, 1)
409409
# Out[82]: (-1, 1)
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#
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# In [84]: ax.transLimits.transform((0,-1))
411+
# In [84]: ax.transLimits.transform((0, -1))
412412
# Out[84]: array([ 0., 0.])
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#
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# In [85]: ax.transLimits.transform((10,-1))
414+
# In [85]: ax.transLimits.transform((10, -1))
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# Out[85]: array([ 1., 0.])
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#
417-
# In [86]: ax.transLimits.transform((10,1))
417+
# In [86]: ax.transLimits.transform((10, 1))
418418
# Out[86]: array([ 1., 1.])
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#
420-
# In [87]: ax.transLimits.transform((5,0))
420+
# In [87]: ax.transLimits.transform((5, 0))
421421
# Out[87]: array([ 0.5, 0.5])
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#
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# and we can use this same inverted transformation to go from the unit

‎tutorials/colors/colormaps.py‎

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Original file line numberDiff line numberDiff line change
@@ -27,7 +27,7 @@
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perceives changes in the lightness parameter as changes in the data
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much better than, for example, changes in hue. Therefore, colormaps
2929
which have monotonically increasing lightness through the colormap
30-
will be better interpreted by the viewer. A wonderful example of
30+
will be better interpreted by the viewer. A wonderful example of
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perceptually uniform colormaps is [colorcet]_.
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Color can be represented in 3D space in various ways. One way to represent color
@@ -340,11 +340,11 @@ def plot_color_gradients(cmap_category, cmap_list):
340340
for ax, name in zip(axes, cmap_list):
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342342
# Get RGB values for colormap.
343-
rgb = cm.get_cmap(plt.get_cmap(name))(x)[np.newaxis,:,:3]
343+
rgb = cm.get_cmap(plt.get_cmap(name))(x)[np.newaxis, :, :3]
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345345
# Get colormap in CAM02-UCS colorspace. We want the lightness.
346346
lab = cspace_converter("sRGB1", "CAM02-UCS")(rgb)
347-
L = lab[0,:,0]
347+
L = lab[0, :, 0]
348348
L = np.float32(np.vstack((L, L, L)))
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350350
ax[0].imshow(gradient, aspect='auto', cmap=plt.get_cmap(name))

‎tutorials/text/text_intro.py‎

Lines changed: 1 addition & 1 deletion
Original file line numberDiff line numberDiff line change
@@ -7,7 +7,7 @@
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Matplotlib has extensive text support, including support for
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mathematical expressions, truetype support for raster and
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vector outputs, newline separated text with arbitrary
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rotations, and unicode support.
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rotations, and unicode support.
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Because it embeds fonts directly in output documents, e.g., for postscript
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or PDF, what you see on the screen is what you get in the hardcopy.

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