From bdb82e4dc2381f771ebaa74d9e2dff560b106f47 Mon Sep 17 00:00:00 2001 From: Thomas A Caswell Date: Fri, 25 Sep 2020 13:14:53 -0400 Subject: [PATCH] DOC: prefer colormap over color map Fix this across the entire codebase and docs. --- doc/api/prev_api_changes/api_changes_2.0.1.rst | 4 ++-- doc/api/prev_api_changes/api_changes_2.2.0.rst | 4 ++-- doc/devel/color_changes.rst | 14 +++++++------- doc/thirdpartypackages/index.rst | 2 +- doc/users/dflt_style_changes.rst | 18 +++++++++--------- doc/users/next_whats_new/colormap_repr.rst | 4 ++-- doc/users/prev_whats_new/changelog.rst | 4 ++-- doc/users/prev_whats_new/whats_new_2.0.0.rst | 6 +++--- .../images_contours_and_fields/image_masked.py | 2 +- examples/mplot3d/surface3d.py | 8 ++++---- examples/mplot3d/surface3d_radial.py | 2 +- lib/matplotlib/_cm.py | 4 ++-- lib/matplotlib/axes/_axes.py | 4 ++-- lib/matplotlib/collections.py | 2 +- lib/matplotlib/colorbar.py | 2 +- lib/matplotlib/colors.py | 16 ++++++++-------- lib/matplotlib/contour.py | 2 +- lib/matplotlib/image.py | 2 +- lib/matplotlib/pyplot.py | 8 ++++---- lib/matplotlib/tests/test_collections.py | 6 +++--- lib/matplotlib/tests/test_colorbar.py | 4 ++-- lib/matplotlib/tests/test_colors.py | 2 +- lib/mpl_toolkits/axes_grid1/colorbar.py | 2 +- lib/mpl_toolkits/mplot3d/axes3d.py | 2 +- tutorials/introductory/images.py | 2 +- 25 files changed, 63 insertions(+), 63 deletions(-) diff --git a/doc/api/prev_api_changes/api_changes_2.0.1.rst b/doc/api/prev_api_changes/api_changes_2.0.1.rst index 36b1c983efdf..57f149f6b3f7 100644 --- a/doc/api/prev_api_changes/api_changes_2.0.1.rst +++ b/doc/api/prev_api_changes/api_changes_2.0.1.rst @@ -55,8 +55,8 @@ line width the final patterns would not change. There is no way to restore the old behavior. -Deprecate 'Vega' color maps ---------------------------- +Deprecate 'Vega' colormaps +-------------------------- The "Vega" colormaps are deprecated in Matplotlib 2.0.1 and will be removed in Matplotlib 2.2. Use the "tab" colormaps instead: "tab10", diff --git a/doc/api/prev_api_changes/api_changes_2.2.0.rst b/doc/api/prev_api_changes/api_changes_2.2.0.rst index 52b11cc81a0e..29ed03649fd8 100644 --- a/doc/api/prev_api_changes/api_changes_2.2.0.rst +++ b/doc/api/prev_api_changes/api_changes_2.2.0.rst @@ -110,8 +110,8 @@ The ``Axes.get_axis_bgcolor``, ``Axes.set_axis_bgcolor``, The unused ``FONT_SCALE`` and ``fontd`` attributes of the `.RendererSVG` class have been removed. -color maps -~~~~~~~~~~ +colormaps +~~~~~~~~~ The ``spectral`` colormap has been removed. The ``Vega*`` colormaps, which were aliases for the ``tab*`` colormaps, have been removed. diff --git a/doc/devel/color_changes.rst b/doc/devel/color_changes.rst index 723728048e73..d36a873c7225 100644 --- a/doc/devel/color_changes.rst +++ b/doc/devel/color_changes.rst @@ -5,21 +5,21 @@ Default Color changes ********************* As discussed at length elsewhere [insert links], ``jet`` is an -empirically bad color map and should not be the default color map. +empirically bad colormap and should not be the default colormap. Due to the position that changing the appearance of the plot breaks backward compatibility, this change has been put off for far longer than it should have been. In addition to changing the default color map we plan to take the chance to change the default color-cycle on -plots and to adopt a different color map for filled plots (``imshow``, +plots and to adopt a different colormap for filled plots (``imshow``, ``pcolor``, ``contourf``, etc) and for scatter like plots. Default Heat Map Colormap ------------------------- -The choice of a new color map is fertile ground to bike-shedding ("No, +The choice of a new colormap is fertile ground to bike-shedding ("No, it should be _this_ color") so we have a proposed set criteria (via -Nathaniel Smith) to evaluate proposed color maps. +Nathaniel Smith) to evaluate proposed colormaps. - it should be a sequential colormap, because diverging colormaps are really misleading unless you know where the "center" of the data is, @@ -64,9 +64,9 @@ Default Scatter Colormap ------------------------ For heat-map like applications it can be desirable to cover as much of -the luminance scale as possible, however when color mapping markers, +the luminance scale as possible, however when colormapping markers, having markers too close to white can be a problem. For that reason -we propose using a different (but maybe related) color map to the +we propose using a different (but maybe related) colormap to the heat map for marker-based. The design parameters are the same as above, only with a more limited luminance variation. @@ -102,7 +102,7 @@ Example script Proposed Colormaps ++++++++++++++++++ -Color Cycle / Qualitative color map +Color Cycle / Qualitative colormap ----------------------------------- When plotting lines it is frequently desirable to plot multiple lines diff --git a/doc/thirdpartypackages/index.rst b/doc/thirdpartypackages/index.rst index 24329d9b5f37..0f3e553ec9d4 100644 --- a/doc/thirdpartypackages/index.rst +++ b/doc/thirdpartypackages/index.rst @@ -331,7 +331,7 @@ visualisation of data from csv files or `pandas.DataFrame`\s. Main features: - Scatter, line, density, histogram, and box plot types - Settings for the marker size, line width, number of bins of histogram, - color map (from cmocean) + colormap (from cmocean) - Save figure as editable PDF - Code of the plotted graph is available so that it can be reused and modified outside of sviewgui diff --git a/doc/users/dflt_style_changes.rst b/doc/users/dflt_style_changes.rst index 92363551a219..02cc51f49bc5 100644 --- a/doc/users/dflt_style_changes.rst +++ b/doc/users/dflt_style_changes.rst @@ -28,8 +28,8 @@ persistently and selectively revert many of these changes. -Colors, color cycles, and color maps -==================================== +Colors, color cycles, and colormaps +=================================== Colors in default property cycle -------------------------------- @@ -117,7 +117,7 @@ in your :file:`matplotlibrc` file. Colormap -------- -The new default color map used by `matplotlib.cm.ScalarMappable` instances is +The new default colormap used by `matplotlib.cm.ScalarMappable` instances is 'viridis' (aka `option D `__). .. plot:: @@ -144,7 +144,7 @@ For an introduction to color theory and how 'viridis' was generated watch Nathaniel Smith and Stéfan van der Walt's talk from SciPy2015. See `here for many more details `__ about the other alternatives and the tools used to create the color -map. For details on all of the color maps available in matplotlib see +map. For details on all of the colormaps available in matplotlib see :doc:`/tutorials/colors/colormaps`. .. raw:: html @@ -846,7 +846,7 @@ Interpolation The default interpolation method for `~matplotlib.axes.Axes.imshow` is now ``'nearest'`` and by default it resamples the data (both up and down -sampling) before color mapping. +sampling) before colormapping. .. plot:: @@ -888,16 +888,16 @@ in your :file:`matplotlibrc` file. Colormapping pipeline --------------------- -Previously, the input data was normalized, then color mapped, and then +Previously, the input data was normalized, then colormapped, and then resampled to the resolution required for the screen. This meant that the final resampling was being done in color space. Because the color -maps are not generally linear in RGB space, colors not in the color map +maps are not generally linear in RGB space, colors not in the colormap may appear in the final image. This bug was addressed by an almost complete overhaul of the image handling code. The input data is now normalized, then resampled to the correct -resolution (in normalized dataspace), and then color mapped to -RGB space. This ensures that only colors from the color map appear +resolution (in normalized dataspace), and then colormapped to +RGB space. This ensures that only colors from the colormap appear in the final image. (If your viewer subsequently resamples the image, the artifact may reappear.) diff --git a/doc/users/next_whats_new/colormap_repr.rst b/doc/users/next_whats_new/colormap_repr.rst index 077f6fca12e9..2f02f9eff978 100644 --- a/doc/users/next_whats_new/colormap_repr.rst +++ b/doc/users/next_whats_new/colormap_repr.rst @@ -2,5 +2,5 @@ IPython representations for Colormap objects ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ The `matplotlib.colors.Colormap` object now has image representations for -IPython / Jupyter backends. Cells returning a color map on the last line will -display an image of the color map. +IPython / Jupyter backends. Cells returning a colormap on the last line will +display an image of the colormap. diff --git a/doc/users/prev_whats_new/changelog.rst b/doc/users/prev_whats_new/changelog.rst index 08f034a60bde..e35878e9935e 100644 --- a/doc/users/prev_whats_new/changelog.rst +++ b/doc/users/prev_whats_new/changelog.rst @@ -1980,7 +1980,7 @@ the `API changes <../../api/api_changes.html>`_. 2008-04-20 Fix double-zoom bug. - MM -2008-04-15 Speed up color mapping. - EF +2008-04-15 Speed up colormapping. - EF 2008-04-12 Speed up zooming and panning of dense images. - EF @@ -3197,7 +3197,7 @@ the `API changes <../../api/api_changes.html>`_. a sequence of (x,y) tuples for specifying paths in collections, quiver, contour, pcolor, transforms. Fixed contour bug involving setting limits for - color mapping. Added numpy-style all() to numerix. - EF + colormapping. Added numpy-style all() to numerix. - EF 2006-06-20 Added custom FigureClass hook to pylab interface - see examples/custom_figure_class.py diff --git a/doc/users/prev_whats_new/whats_new_2.0.0.rst b/doc/users/prev_whats_new/whats_new_2.0.0.rst index fe79413d85ea..7a6bac78e97a 100644 --- a/doc/users/prev_whats_new/whats_new_2.0.0.rst +++ b/doc/users/prev_whats_new/whats_new_2.0.0.rst @@ -187,11 +187,11 @@ Improved image support ---------------------- Prior to version 2.0, matplotlib resampled images by first applying -the color map and then resizing the result. Since the resampling was +the colormap and then resizing the result. Since the resampling was performed on the colored image, this introduced colors in the output -image that didn't actually exist in the color map. Now, images are +image that didn't actually exist in the colormap. Now, images are resampled first (and entirely in floating-point, if the input image is -floating-point), and then the color map is applied. +floating-point), and then the colormap is applied. In order to make this important change, the image handling code was almost entirely rewritten. As a side effect, image resampling uses diff --git a/examples/images_contours_and_fields/image_masked.py b/examples/images_contours_and_fields/image_masked.py index 15a78f7123ce..0131c3c15874 100644 --- a/examples/images_contours_and_fields/image_masked.py +++ b/examples/images_contours_and_fields/image_masked.py @@ -45,7 +45,7 @@ # set up the Axes objects fig, (ax1, ax2) = plt.subplots(nrows=2, figsize=(6, 5.4)) -# plot using 'continuous' color map +# plot using 'continuous' colormap im = ax1.imshow(Zm, interpolation='bilinear', cmap=palette, norm=colors.Normalize(vmin=-1.0, vmax=1.0), diff --git a/examples/mplot3d/surface3d.py b/examples/mplot3d/surface3d.py index 51912ed4b3c4..d8b2f598a1d9 100644 --- a/examples/mplot3d/surface3d.py +++ b/examples/mplot3d/surface3d.py @@ -1,9 +1,9 @@ """ -====================== -3D surface (color map) -====================== +===================== +3D surface (colormap) +===================== -Demonstrates plotting a 3D surface colored with the coolwarm color map. +Demonstrates plotting a 3D surface colored with the coolwarm colormap. The surface is made opaque by using antialiased=False. Also demonstrates using the LinearLocator and custom formatting for the diff --git a/examples/mplot3d/surface3d_radial.py b/examples/mplot3d/surface3d_radial.py index c298ddc48864..185f61a6f9b1 100644 --- a/examples/mplot3d/surface3d_radial.py +++ b/examples/mplot3d/surface3d_radial.py @@ -4,7 +4,7 @@ ================================= Demonstrates plotting a surface defined in polar coordinates. -Uses the reversed version of the YlGnBu color map. +Uses the reversed version of the YlGnBu colormap. Also demonstrates writing axis labels with latex math mode. Example contributed by Armin Moser. diff --git a/lib/matplotlib/_cm.py b/lib/matplotlib/_cm.py index f51b7591ddbc..a04cb69d3e7d 100644 --- a/lib/matplotlib/_cm.py +++ b/lib/matplotlib/_cm.py @@ -54,7 +54,7 @@ def _prism_blue(x): return -1.1 * np.sin((x * 20.9) * np.pi) _prism_data = {'red': _prism_red, 'green': _prism_green, 'blue': _prism_blue} def _ch_helper(gamma, s, r, h, p0, p1, x): - """Helper function for generating picklable cubehelix color maps.""" + """Helper function for generating picklable cubehelix colormaps.""" # Apply gamma factor to emphasise low or high intensity values xg = x ** gamma # Calculate amplitude and angle of deviation from the black to white @@ -1096,7 +1096,7 @@ def _gist_heat_blue(x): return 4 * x - 3 def _gist_yarg(x): return 1 - x _gist_yarg_data = {'red': _gist_yarg, 'green': _gist_yarg, 'blue': _gist_yarg} -# This bipolar color map was generated from CoolWarmFloat33.csv of +# This bipolar colormap was generated from CoolWarmFloat33.csv of # "Diverging Color Maps for Scientific Visualization" by Kenneth Moreland. # _coolwarm_data = { diff --git a/lib/matplotlib/axes/_axes.py b/lib/matplotlib/axes/_axes.py index 4b7fbe68d85b..b458edd89c75 100644 --- a/lib/matplotlib/axes/_axes.py +++ b/lib/matplotlib/axes/_axes.py @@ -4472,7 +4472,7 @@ def hexbin(self, x, y, C=None, gridsize=100, bins=None, - If *None*, no binning is applied; the color of each hexagon directly corresponds to its count value. - - If 'log', use a logarithmic scale for the color map. + - If 'log', use a logarithmic scale for the colormap. Internally, :math:`log_{10}(i+1)` is used to determine the hexagon color. This is equivalent to ``norm=LogNorm()``. - If an integer, divide the counts in the specified number @@ -5239,7 +5239,7 @@ def imshow(self, X, cmap=None, norm=None, aspect=None, The input may either be actual RGB(A) data, or 2D scalar data, which will be rendered as a pseudocolor image. For displaying a grayscale - image set up the color mapping using the parameters + image set up the colormapping using the parameters ``cmap='gray', vmin=0, vmax=255``. The number of pixels used to render an image is set by the axes size diff --git a/lib/matplotlib/collections.py b/lib/matplotlib/collections.py index 2392d2489b51..51c6c50a0305 100644 --- a/lib/matplotlib/collections.py +++ b/lib/matplotlib/collections.py @@ -1795,7 +1795,7 @@ class PatchCollection(Collection): """ A generic collection of patches. - This makes it easier to assign a color map to a heterogeneous + This makes it easier to assign a colormap to a heterogeneous collection of patches. This also may improve plotting speed, since PatchCollection will diff --git a/lib/matplotlib/colorbar.py b/lib/matplotlib/colorbar.py index f75612b74eb0..89541378e1ae 100644 --- a/lib/matplotlib/colorbar.py +++ b/lib/matplotlib/colorbar.py @@ -136,7 +136,7 @@ *values* None or a sequence which must be of length 1 less than the sequence of *boundaries*. For each region delimited by adjacent entries in *boundaries*, the - color mapped to the corresponding value in values + colormapped to the corresponding value in values will be used. ============ =================================================== diff --git a/lib/matplotlib/colors.py b/lib/matplotlib/colors.py index 3e8226b0ce25..9429ac9d9608 100644 --- a/lib/matplotlib/colors.py +++ b/lib/matplotlib/colors.py @@ -703,14 +703,14 @@ def _init(self): raise NotImplementedError("Abstract class only") def is_gray(self): - """Return whether the color map is grayscale.""" + """Return whether the colormap is grayscale.""" if not self._isinit: self._init() return (np.all(self._lut[:, 0] == self._lut[:, 1]) and np.all(self._lut[:, 0] == self._lut[:, 2])) def _resample(self, lutsize): - """Return a new color map with *lutsize* entries.""" + """Return a new colormap with *lutsize* entries.""" raise NotImplementedError() def reversed(self, name=None): @@ -738,7 +738,7 @@ def _repr_png_(self): (_REPR_PNG_SIZE[1], 1)) pixels = self(X, bytes=True) png_bytes = io.BytesIO() - title = self.name + ' color map' + title = self.name + ' colormap' author = f'Matplotlib v{mpl.__version__}, https://matplotlib.org' pnginfo = PngInfo() pnginfo.add_text('Title', title) @@ -766,7 +766,7 @@ def color_block(color): f'{self.name} ' '' '
' @@ -795,7 +795,7 @@ class LinearSegmentedColormap(Colormap): def __init__(self, name, segmentdata, N=256, gamma=1.0): """ - Create color map from linear mapping segments + Create colormap from linear mapping segments segmentdata argument is a dictionary with a red, green and blue entries. Each entry should be a list of *x*, *y0*, *y1* tuples, @@ -858,7 +858,7 @@ def _init(self): self._set_extremes() def set_gamma(self, gamma): - """Set a new gamma value and regenerate color map.""" + """Set a new gamma value and regenerate colormap.""" self._gamma = gamma self._init() @@ -902,7 +902,7 @@ def from_list(name, colors, N=256, gamma=1.0): return LinearSegmentedColormap(name, cdict, N, gamma) def _resample(self, lutsize): - """Return a new color map with *lutsize* entries.""" + """Return a new colormap with *lutsize* entries.""" new_cmap = LinearSegmentedColormap(self.name, self._segmentdata, lutsize) new_cmap._rgba_over = self._rgba_over @@ -1006,7 +1006,7 @@ def _init(self): self._set_extremes() def _resample(self, lutsize): - """Return a new color map with *lutsize* entries.""" + """Return a new colormap with *lutsize* entries.""" colors = self(np.linspace(0, 1, lutsize)) new_cmap = ListedColormap(colors, name=self.name) # Keep the over/under values too diff --git a/lib/matplotlib/contour.py b/lib/matplotlib/contour.py index fb8eba585d65..7b6713b8e37d 100644 --- a/lib/matplotlib/contour.py +++ b/lib/matplotlib/contour.py @@ -1191,7 +1191,7 @@ def _process_colors(self): """ Color argument processing for contouring. - Note that we base the color mapping on the contour levels + Note that we base the colormapping on the contour levels and layers, not on the actual range of the Z values. This means we don't have to worry about bad values in Z, and we always have the full dynamic range available for the selected diff --git a/lib/matplotlib/image.py b/lib/matplotlib/image.py index 25cfc15f647a..0dc4449b4abc 100644 --- a/lib/matplotlib/image.py +++ b/lib/matplotlib/image.py @@ -462,7 +462,7 @@ def _make_image(self, A, in_bbox, out_bbox, clip_bbox, magnification=1.0, # would not full eliminate it and breaks a number of # tests (due to the slightly different error bouncing # some pixels across a boundary in the (very - # quantized) color mapping step). + # quantized) colormapping step). offset = .1 frac = .8 # we need to run the vmin/vmax through the same rescaling diff --git a/lib/matplotlib/pyplot.py b/lib/matplotlib/pyplot.py index a8bca37cb3f5..e177d727d142 100644 --- a/lib/matplotlib/pyplot.py +++ b/lib/matplotlib/pyplot.py @@ -2007,8 +2007,8 @@ def colormaps(): for nominal data that has no inherent ordering, where color is used only to distinguish categories - Matplotlib ships with 4 perceptually uniform color maps which are - the recommended color maps for sequential data: + Matplotlib ships with 4 perceptually uniform colormaps which are + the recommended colormaps for sequential data: ========= =================================================== Colormap Description @@ -2087,7 +2087,7 @@ def colormaps(): Colormap Description ========= ======================================================= autumn sequential linearly-increasing shades of red-orange-yellow - bone sequential increasing black-white color map with + bone sequential increasing black-white colormap with a tinge of blue, to emulate X-ray film cool linearly-decreasing shades of cyan-magenta copper sequential increasing shades of black-copper @@ -2128,7 +2128,7 @@ def colormaps(): Language software ============ ======================================================= - A set of cyclic color maps: + A set of cyclic colormaps: ================ ================================================= Colormap Description diff --git a/lib/matplotlib/tests/test_collections.py b/lib/matplotlib/tests/test_collections.py index 3159e7f2bba7..efbb71e1b95e 100644 --- a/lib/matplotlib/tests/test_collections.py +++ b/lib/matplotlib/tests/test_collections.py @@ -547,7 +547,7 @@ def test_scatter_post_alpha(): def test_scatter_alpha_array(): x = np.arange(5) alpha = x / 5 - # With color mapping. + # With colormapping. fig, (ax0, ax1) = plt.subplots(2) sc0 = ax0.scatter(x, x, c=x, alpha=alpha) sc1 = ax1.scatter(x, x, c=x) @@ -555,14 +555,14 @@ def test_scatter_alpha_array(): plt.draw() assert_array_equal(sc0.get_facecolors()[:, -1], alpha) assert_array_equal(sc1.get_facecolors()[:, -1], alpha) - # Without color mapping. + # Without colormapping. fig, (ax0, ax1) = plt.subplots(2) sc0 = ax0.scatter(x, x, color=['r', 'g', 'b', 'c', 'm'], alpha=alpha) sc1 = ax1.scatter(x, x, color='r', alpha=alpha) plt.draw() assert_array_equal(sc0.get_facecolors()[:, -1], alpha) assert_array_equal(sc1.get_facecolors()[:, -1], alpha) - # Without color mapping, and set alpha afterward. + # Without colormapping, and set alpha afterward. fig, (ax0, ax1) = plt.subplots(2) sc0 = ax0.scatter(x, x, color=['r', 'g', 'b', 'c', 'm']) sc0.set_alpha(alpha) diff --git a/lib/matplotlib/tests/test_colorbar.py b/lib/matplotlib/tests/test_colorbar.py index 8307fceb3384..c64ebcc634f7 100644 --- a/lib/matplotlib/tests/test_colorbar.py +++ b/lib/matplotlib/tests/test_colorbar.py @@ -21,10 +21,10 @@ def _get_cmap_norms(): Helper function for _colorbar_extension_shape and colorbar_extension_length. """ - # Create a color map and specify the levels it represents. + # Create a colormap and specify the levels it represents. cmap = cm.get_cmap("RdBu", lut=5) clevs = [-5., -2.5, -.5, .5, 1.5, 3.5] - # Define norms for the color maps. + # Define norms for the colormaps. norms = dict() norms['neither'] = BoundaryNorm(clevs, len(clevs) - 1) norms['min'] = BoundaryNorm([-10] + clevs[1:], len(clevs) - 1) diff --git a/lib/matplotlib/tests/test_colors.py b/lib/matplotlib/tests/test_colors.py index 97790de87617..827617c3eec6 100644 --- a/lib/matplotlib/tests/test_colors.py +++ b/lib/matplotlib/tests/test_colors.py @@ -983,7 +983,7 @@ def _azimuth2math(azimuth, elevation): def test_pandas_iterable(pd): # Using a list or series yields equivalent - # color maps, i.e the series isn't seen as + # colormaps, i.e the series isn't seen as # a single color lst = ['red', 'blue', 'green'] s = pd.Series(lst) diff --git a/lib/mpl_toolkits/axes_grid1/colorbar.py b/lib/mpl_toolkits/axes_grid1/colorbar.py index ce28ff98b3c7..97cf11c45f51 100644 --- a/lib/mpl_toolkits/axes_grid1/colorbar.py +++ b/lib/mpl_toolkits/axes_grid1/colorbar.py @@ -91,7 +91,7 @@ *values* None or a sequence which must be of length 1 less than the sequence of *boundaries*. For each region delimited by adjacent entries in *boundaries*, the - color mapped to the corresponding value in values + colormapped to the corresponding value in values will be used. ============ =================================================== diff --git a/lib/mpl_toolkits/mplot3d/axes3d.py b/lib/mpl_toolkits/mplot3d/axes3d.py index d256e6210c41..7738fd214797 100644 --- a/lib/mpl_toolkits/mplot3d/axes3d.py +++ b/lib/mpl_toolkits/mplot3d/axes3d.py @@ -1458,7 +1458,7 @@ def plot_surface(self, X, Y, Z, *args, norm=None, vmin=None, Create a surface plot. By default it will be colored in shades of a solid color, but it also - supports color mapping by supplying the *cmap* argument. + supports colormapping by supplying the *cmap* argument. .. note:: diff --git a/tutorials/introductory/images.py b/tutorials/introductory/images.py index 7b41ce0d6f37..858c3ccd262f 100644 --- a/tutorials/introductory/images.py +++ b/tutorials/introductory/images.py @@ -32,7 +32,7 @@ This turns on inline plotting, where plot graphics will appear in your notebook. This has important implications for interactivity. For inline plotting, commands in cells below the cell that outputs a plot will not affect the plot. For example, -changing the color map is not possible from cells below the cell that creates a plot. +changing the colormap is not possible from cells below the cell that creates a plot. However, for other backends, such as Qt5, that open a separate window, cells below those that create the plot will change the plot - it is a live object in memory.