r""" Annotations =========== Annotations are graphical elements, often pieces of text, that explain, add context to, or otherwise highlight some portion of the visualized data. `~.Axes.annotate` supports a number of coordinate systems for flexibly positioning data and annotations relative to each other and a variety of options of for styling the text. Axes.annotate also provides an optional arrow from the text to the data and this arrow can be styled in various ways. `~.Axes.text` can also be used for simple text annotation, but does not provide as much flexibility in positioning and styling as `~.Axes.annotate`. .. contents:: Table of Contents :depth: 3 """ ############################################################################### # .. _annotations-tutorial: # # Basic annotation # ---------------- # # In an annotation, there are two points to consider: the location of the data # being annotated *xy* and the location of the annotation text *xytext*. Both # of these arguments are ``(x, y)`` tuples: import numpy as np import matplotlib.pyplot as plt fig, ax = plt.subplots(figsize=(3, 3)) t = np.arange(0.0, 5.0, 0.01) s = np.cos(2*np.pi*t) line, = ax.plot(t, s, lw=2) ax.annotate('local max', xy=(2, 1), xytext=(3, 1.5), arrowprops=dict(facecolor='black', shrink=0.05)) ax.set_ylim(-2, 2) ############################################################################### # In this example, both the *xy* (arrow tip) and *xytext* locations # (text location) are in data coordinates. There are a variety of other # coordinate systems one can choose -- you can specify the coordinate # system of *xy* and *xytext* with one of the following strings for # *xycoords* and *textcoords* (default is 'data') # # ================== ======================================================== # argument coordinate system # ================== ======================================================== # 'figure points' points from the lower left corner of the figure # 'figure pixels' pixels from the lower left corner of the figure # 'figure fraction' (0, 0) is lower left of figure and (1, 1) is upper right # 'axes points' points from lower left corner of axes # 'axes pixels' pixels from lower left corner of axes # 'axes fraction' (0, 0) is lower left of axes and (1, 1) is upper right # 'data' use the axes data coordinate system # ================== ======================================================== # # The following strings are also valid arguments for *textcoords* # # ================== ======================================================== # argument coordinate system # ================== ======================================================== # 'offset points' offset (in points) from the xy value # 'offset pixels' offset (in pixels) from the xy value # ================== ======================================================== # # For physical coordinate systems (points or pixels) the origin is the # bottom-left of the figure or axes. Points are # `typographic points `_ # meaning that they are a physical unit measuring 1/72 of an inch. Points and # pixels are discussed in further detail in :ref:`transforms-fig-scale-dpi`. # # .. _annotation-data: # # Annotating data # ~~~~~~~~~~~~~~~ # # This example places the text coordinates in fractional axes coordinates: fig, ax = plt.subplots(figsize=(3, 3)) t = np.arange(0.0, 5.0, 0.01) s = np.cos(2*np.pi*t) line, = ax.plot(t, s, lw=2) ax.annotate('local max', xy=(2, 1), xycoords='data', xytext=(0.01, .99), textcoords='axes fraction', va='top', ha='left', arrowprops=dict(facecolor='black', shrink=0.05)) ax.set_ylim(-2, 2) ################################################################### # # .. _annotation-with-arrow: # # Annotating with arrows # ~~~~~~~~~~~~~~~~~~~~~~ # # You can enable drawing of an arrow from the text to the annotated point # by giving a dictionary of arrow properties in the optional keyword # argument *arrowprops*. # # ==================== ===================================================== # *arrowprops* key description # ==================== ===================================================== # width the width of the arrow in points # frac the fraction of the arrow length occupied by the head # headwidth the width of the base of the arrow head in points # shrink move the tip and base some percent away from # the annotated point and text # # \*\*kwargs any key for :class:`matplotlib.patches.Polygon`, # e.g., ``facecolor`` # ==================== ===================================================== # # In the example below, the *xy* point is in the data coordinate system # since *xycoords* defaults to 'data'. For a polar axes, this is in # (theta, radius) space. The text in this example is placed in the # fractional figure coordinate system. :class:`matplotlib.text.Text` # keyword arguments like *horizontalalignment*, *verticalalignment* and # *fontsize* are passed from `~matplotlib.axes.Axes.annotate` to the # ``Text`` instance. fig = plt.figure() ax = fig.add_subplot(projection='polar') r = np.arange(0, 1, 0.001) theta = 2 * 2*np.pi * r line, = ax.plot(theta, r, color='#ee8d18', lw=3) ind = 800 thisr, thistheta = r[ind], theta[ind] ax.plot([thistheta], [thisr], 'o') ax.annotate('a polar annotation', xy=(thistheta, thisr), # theta, radius xytext=(0.05, 0.05), # fraction, fraction textcoords='figure fraction', arrowprops=dict(facecolor='black', shrink=0.05), horizontalalignment='left', verticalalignment='bottom') ############################################################################### # For more on plotting with arrows, see :ref:`annotation_with_custom_arrow` # # .. _annotations-offset-text: # # Placing text annotations relative to data # ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ # Annotations can be positioned at a relative offset to the *xy* input to # annotation by setting the *textcoords* keyword argument to ``'offset points'`` # or ``'offset pixels'``. fig, ax = plt.subplots(figsize=(3, 3)) x = [1, 3, 5, 7, 9] y = [2, 4, 6, 8, 10] annotations = ["A", "B", "C", "D", "E"] ax.scatter(x, y, s=20) for xi, yi, text in zip(x, y, annotations): ax.annotate(text, xy=(xi, yi), xycoords='data', xytext=(1.5, 1.5), textcoords='offset points') ############################################################################### # The annotations are offset 1.5 points (1.5*1/72 inches) from the *xy* values. # # .. _plotting-guide-annotation: # # Advanced annotation # ------------------- # # We recommend reading :ref:`annotations-tutorial`, :func:`~matplotlib.pyplot.text` # and :func:`~matplotlib.pyplot.annotate` before reading this section. # # Annotating with boxed text # ~~~~~~~~~~~~~~~~~~~~~~~~~~ # # `~.Axes.text` takes a *bbox* keyword argument, which draws a box around the # text: fig, ax = plt.subplots(figsize=(5, 5)) t = ax.text(0.5, 0.5, "Direction", ha="center", va="center", rotation=45, size=15, bbox=dict(boxstyle="rarrow,pad=0.3", fc="lightblue", ec="steelblue", lw=2)) ############################################################################### # The arguments are the name of the box style with its attributes as # keyword arguments. Currently, following box styles are implemented. # # ========== ============== ========================== # Class Name Attrs # ========== ============== ========================== # Circle ``circle`` pad=0.3 # DArrow ``darrow`` pad=0.3 # Ellipse ``ellipse`` pad=0.3 # LArrow ``larrow`` pad=0.3 # RArrow ``rarrow`` pad=0.3 # Round ``round`` pad=0.3,rounding_size=None # Round4 ``round4`` pad=0.3,rounding_size=None # Roundtooth ``roundtooth`` pad=0.3,tooth_size=None # Sawtooth ``sawtooth`` pad=0.3,tooth_size=None # Square ``square`` pad=0.3 # ========== ============== ========================== # # .. figure:: ../../gallery/shapes_and_collections/images/sphx_glr_fancybox_demo_001.png # :target: ../../gallery/shapes_and_collections/fancybox_demo.html # :align: center # # The patch object (box) associated with the text can be accessed using:: # # bb = t.get_bbox_patch() # # The return value is a `.FancyBboxPatch`; patch properties # (facecolor, edgewidth, etc.) can be accessed and modified as usual. # `.FancyBboxPatch.set_boxstyle` sets the box shape:: # # bb.set_boxstyle("rarrow", pad=0.6) # # The attribute arguments can also be specified within the style # name with separating comma:: # # bb.set_boxstyle("rarrow, pad=0.6") # # # Defining custom box styles # ~~~~~~~~~~~~~~~~~~~~~~~~~~ # # You can use a custom box style. The value for the ``boxstyle`` can be a # callable object in the following forms: from matplotlib.path import Path def custom_box_style(x0, y0, width, height, mutation_size): """ Given the location and size of the box, return the path of the box around it. Rotation is automatically taken care of. Parameters ---------- x0, y0, width, height : float Box location and size. mutation_size : float Mutation reference scale, typically the text font size. """ # padding mypad = 0.3 pad = mutation_size * mypad # width and height with padding added. width = width + 2 * pad height = height + 2 * pad # boundary of the padded box x0, y0 = x0 - pad, y0 - pad x1, y1 = x0 + width, y0 + height # return the new path return Path([(x0, y0), (x1, y0), (x1, y1), (x0, y1), (x0-pad, (y0+y1)/2), (x0, y0), (x0, y0)], closed=True) fig, ax = plt.subplots(figsize=(3, 3)) ax.text(0.5, 0.5, "Test", size=30, va="center", ha="center", rotation=30, bbox=dict(boxstyle=custom_box_style, alpha=0.2)) ############################################################################### # See also :doc:`/gallery/userdemo/custom_boxstyle01`. Similarly, you can define a # custom `.ConnectionStyle` and a custom `.ArrowStyle`. View the source code at # `.patches` to learn how each class is defined. # # .. _annotation_with_custom_arrow: # # Customizing annotation arrows # ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ # # An arrow connecting *xy* to *xytext* can be optionally drawn by # specifying the *arrowprops* argument. To draw only an arrow, use # empty string as the first argument: fig, ax = plt.subplots(figsize=(3, 3)) ax.annotate("", xy=(0.2, 0.2), xycoords='data', xytext=(0.8, 0.8), textcoords='data', arrowprops=dict(arrowstyle="->", connectionstyle="arc3")) ############################################################################### # The arrow is drawn as follows: # # 1. A path connecting the two points is created, as specified by the # *connectionstyle* parameter. # 2. The path is clipped to avoid patches *patchA* and *patchB*, if these are # set. # 3. The path is further shrunk by *shrinkA* and *shrinkB* (in pixels). # 4. The path is transmuted to an arrow patch, as specified by the *arrowstyle* # parameter. # # .. figure:: ../../gallery/userdemo/images/sphx_glr_annotate_explain_001.png # :target: ../../gallery/userdemo/annotate_explain.html # :align: center # # The creation of the connecting path between two points is controlled by # ``connectionstyle`` key and the following styles are available. # # ========== ============================================= # Name Attrs # ========== ============================================= # ``angle`` angleA=90,angleB=0,rad=0.0 # ``angle3`` angleA=90,angleB=0 # ``arc`` angleA=0,angleB=0,armA=None,armB=None,rad=0.0 # ``arc3`` rad=0.0 # ``bar`` armA=0.0,armB=0.0,fraction=0.3,angle=None # ========== ============================================= # # Note that "3" in ``angle3`` and ``arc3`` is meant to indicate that the # resulting path is a quadratic spline segment (three control # points). As will be discussed below, some arrow style options can only # be used when the connecting path is a quadratic spline. # # The behavior of each connection style is (limitedly) demonstrated in the # example below. (Warning: The behavior of the ``bar`` style is currently not # well-defined and may be changed in the future). # # .. figure:: ../../gallery/userdemo/images/sphx_glr_connectionstyle_demo_001.png # :target: ../../gallery/userdemo/connectionstyle_demo.html # :align: center # # The connecting path (after clipping and shrinking) is then mutated to # an arrow patch, according to the given ``arrowstyle``. # # ========== ============================================= # Name Attrs # ========== ============================================= # ``-`` None # ``->`` head_length=0.4,head_width=0.2 # ``-[`` widthB=1.0,lengthB=0.2,angleB=None # ``|-|`` widthA=1.0,widthB=1.0 # ``-|>`` head_length=0.4,head_width=0.2 # ``<-`` head_length=0.4,head_width=0.2 # ``<->`` head_length=0.4,head_width=0.2 # ``<|-`` head_length=0.4,head_width=0.2 # ``<|-|>`` head_length=0.4,head_width=0.2 # ``fancy`` head_length=0.4,head_width=0.4,tail_width=0.4 # ``simple`` head_length=0.5,head_width=0.5,tail_width=0.2 # ``wedge`` tail_width=0.3,shrink_factor=0.5 # ========== ============================================= # # .. figure:: ../../gallery/text_labels_and_annotations/images/sphx_glr_fancyarrow_demo_001.png # :target: ../../gallery/text_labels_and_annotations/fancyarrow_demo.html # :align: center # # Some arrowstyles only work with connection styles that generate a # quadratic-spline segment. They are ``fancy``, ``simple``, and ``wedge``. # For these arrow styles, you must use the "angle3" or "arc3" connection # style. # # If the annotation string is given, the patch is set to the bbox patch # of the text by default. fig, ax = plt.subplots(figsize=(3, 3)) ax.annotate("Test", xy=(0.2, 0.2), xycoords='data', xytext=(0.8, 0.8), textcoords='data', size=20, va="center", ha="center", arrowprops=dict(arrowstyle="simple", connectionstyle="arc3,rad=-0.2")) ############################################################################## # As with `~.Axes.text`, a box around the text can be drawn using the *bbox* # argument. fig, ax = plt.subplots(figsize=(3, 3)) ann = ax.annotate("Test", xy=(0.2, 0.2), xycoords='data', xytext=(0.8, 0.8), textcoords='data', size=20, va="center", ha="center", bbox=dict(boxstyle="round4", fc="w"), arrowprops=dict(arrowstyle="-|>", connectionstyle="arc3,rad=-0.2", fc="w")) ############################################################################## # By default, the starting point is set to the center of the text # extent. This can be adjusted with ``relpos`` key value. The values # are normalized to the extent of the text. For example, (0, 0) means # lower-left corner and (1, 1) means top-right. fig, ax = plt.subplots(figsize=(3, 3)) ann = ax.annotate("Test", xy=(0.2, 0.2), xycoords='data', xytext=(0.8, 0.8), textcoords='data', size=20, va="center", ha="center", bbox=dict(boxstyle="round4", fc="w"), arrowprops=dict(arrowstyle="-|>", connectionstyle="arc3,rad=0.2", relpos=(0., 0.), fc="w")) ann = ax.annotate("Test", xy=(0.2, 0.2), xycoords='data', xytext=(0.8, 0.8), textcoords='data', size=20, va="center", ha="center", bbox=dict(boxstyle="round4", fc="w"), arrowprops=dict(arrowstyle="-|>", connectionstyle="arc3,rad=-0.2", relpos=(1., 0.), fc="w")) ############################################################################## # Placing Artist at anchored Axes locations # ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ # # There are classes of artists that can be placed at an anchored # location in the Axes. A common example is the legend. This type # of artist can be created by using the `.OffsetBox` class. A few # predefined classes are available in :mod:`matplotlib.offsetbox` and in # :mod:`mpl_toolkits.axes_grid1.anchored_artists`. from matplotlib.offsetbox import AnchoredText fig, ax = plt.subplots(figsize=(3, 3)) at = AnchoredText("Figure 1a", prop=dict(size=15), frameon=True, loc='upper left') at.patch.set_boxstyle("round,pad=0.,rounding_size=0.2") ax.add_artist(at) ############################################################################### # The *loc* keyword has same meaning as in the legend command. # # A simple application is when the size of the artist (or collection of # artists) is known in pixel size during the time of creation. For # example, If you want to draw a circle with fixed size of 20 pixel x 20 # pixel (radius = 10 pixel), you can utilize # `~mpl_toolkits.axes_grid1.anchored_artists.AnchoredDrawingArea`. The instance # is created with a size of the drawing area (in pixels), and arbitrary artists # can be added to the drawing area. Note that the extents of the artists that are # added to the drawing area are not related to the placement of the drawing # area itself. Only the initial size matters. # # The artists that are added to the drawing area should not have a # transform set (it will be overridden) and the dimensions of those # artists are interpreted as a pixel coordinate, i.e., the radius of the # circles in above example are 10 pixels and 5 pixels, respectively. from matplotlib.patches import Circle from mpl_toolkits.axes_grid1.anchored_artists import AnchoredDrawingArea fig, ax = plt.subplots(figsize=(3, 3)) ada = AnchoredDrawingArea(40, 20, 0, 0, loc='upper right', pad=0., frameon=False) p1 = Circle((10, 10), 10) ada.drawing_area.add_artist(p1) p2 = Circle((30, 10), 5, fc="r") ada.drawing_area.add_artist(p2) ax.add_artist(ada) ############################################################################### # Sometimes, you want your artists to scale with the data coordinate (or # coordinates other than canvas pixels). You can use # `~mpl_toolkits.axes_grid1.anchored_artists.AnchoredAuxTransformBox` class. # This is similar to # `~mpl_toolkits.axes_grid1.anchored_artists.AnchoredDrawingArea` except that # the extent of the artist is determined during the drawing time respecting the # specified transform. # # The ellipse in the example below will have width and height # corresponding to 0.1 and 0.4 in data coordinates and will be # automatically scaled when the view limits of the axes change. from matplotlib.patches import Ellipse from mpl_toolkits.axes_grid1.anchored_artists import AnchoredAuxTransformBox fig, ax = plt.subplots(figsize=(3, 3)) box = AnchoredAuxTransformBox(ax.transData, loc='upper left') el = Ellipse((0, 0), width=0.1, height=0.4, angle=30) # in data coordinates! box.drawing_area.add_artist(el) ax.add_artist(box) ############################################################################### # Another method of anchoring an artist relative to a parent axes or anchor # point is via the *bbox_to_anchor* argument of `.AnchoredOffsetbox`. This # artist can then be automatically positioned relative to another artist using # `.HPacker` and `.VPacker`: from matplotlib.offsetbox import (AnchoredOffsetbox, DrawingArea, HPacker, TextArea) fig, ax = plt.subplots(figsize=(3, 3)) box1 = TextArea(" Test: ", textprops=dict(color="k")) box2 = DrawingArea(60, 20, 0, 0) el1 = Ellipse((10, 10), width=16, height=5, angle=30, fc="r") el2 = Ellipse((30, 10), width=16, height=5, angle=170, fc="g") el3 = Ellipse((50, 10), width=16, height=5, angle=230, fc="b") box2.add_artist(el1) box2.add_artist(el2) box2.add_artist(el3) box = HPacker(children=[box1, box2], align="center", pad=0, sep=5) anchored_box = AnchoredOffsetbox(loc='lower left', child=box, pad=0., frameon=True, bbox_to_anchor=(0., 1.02), bbox_transform=ax.transAxes, borderpad=0.,) ax.add_artist(anchored_box) fig.subplots_adjust(top=0.8) ############################################################################### # Note that, unlike in `.Legend`, the ``bbox_transform`` is set to # `.IdentityTransform` by default # # .. _annotating_coordinate_systems: # # Coordinate systems for annotations # ---------------------------------- # # Matplotlib Annotations support several types of coordinate systems. The # examples in :ref:`annotations-tutorial` used the ``data`` coordinate system; # Some others more advanced options are: # # 1. A `.Transform` instance. For more information on transforms, see the # :doc:`../advanced/transforms_tutorial` For example, the # ``Axes.transAxes`` transform positions the annotation relative to the Axes # coordinates and using it is therefore identical to setting the # coordinate system to "axes fraction": fig, (ax1, ax2) = plt.subplots(nrows=1, ncols=2, figsize=(6, 3)) ax1.annotate("Test", xy=(0.5, 0.5), xycoords=ax1.transAxes) ax2.annotate("Test", xy=(0.5, 0.5), xycoords="axes fraction") ############################################################################### # Another commonly used `.Transform` instance is ``Axes.transData``. This # transform is the coordinate system of the data plotted in the axes. In this # example, it is used to draw an arrow from a point in *ax1* to text in *ax2*, # where the point and text are positioned relative to the coordinates of *ax1* # and *ax2* respectively: fig, (ax1, ax2) = plt.subplots(nrows=1, ncols=2, figsize=(6, 3)) ax1.annotate("Test1", xy=(0.5, 0.5), xycoords="axes fraction") ax2.annotate("Test2", xy=(0.5, 0.5), xycoords=ax1.transData, xytext=(0.5, 0.5), textcoords=ax2.transData, arrowprops=dict(arrowstyle="->")) ############################################################################# # 2. An `.Artist` instance. The *xy* value (or *xytext*) is interpreted as a # fractional coordinate of the bounding box (bbox) of the artist: fig, ax = plt.subplots(nrows=1, ncols=1, figsize=(3, 3)) an1 = ax.annotate("Test 1", xy=(0.5, 0.5), xycoords="data", va="center", ha="center", bbox=dict(boxstyle="round", fc="w")) an2 = ax.annotate("Test 2", xy=(1, 0.5), xycoords=an1, # (1, 0.5) of an1's bbox xytext=(30, 0), textcoords="offset points", va="center", ha="left", bbox=dict(boxstyle="round", fc="w"), arrowprops=dict(arrowstyle="->")) ############################################################################### # Note that you must ensure that the extent of the coordinate artist (*an1* in # this example) is determined before *an2* gets drawn. Usually, this means # that *an2* needs to be drawn after *an1*. The base class for all bounding # boxes is `.BboxBase` # # 3. A callable object that takes the renderer instance as single argument, and # returns either a `.Transform` or a `.BboxBase`. For example, the return # value of `.Artist.get_window_extent` is a bbox, so this method is identical # to (2) passing in the artist: fig, ax = plt.subplots(nrows=1, ncols=1, figsize=(3, 3)) an1 = ax.annotate("Test 1", xy=(0.5, 0.5), xycoords="data", va="center", ha="center", bbox=dict(boxstyle="round", fc="w")) an2 = ax.annotate("Test 2", xy=(1, 0.5), xycoords=an1.get_window_extent, xytext=(30, 0), textcoords="offset points", va="center", ha="left", bbox=dict(boxstyle="round", fc="w"), arrowprops=dict(arrowstyle="->")) ############################################################################### # `.Artist.get_window_extent` is the bounding box of the Axes object and is # therefore identical to setting the coordinate system to axes fraction: fig, (ax1, ax2) = plt.subplots(nrows=1, ncols=2, figsize=(6, 3)) an1 = ax1.annotate("Test1", xy=(0.5, 0.5), xycoords="axes fraction") an2 = ax2.annotate("Test 2", xy=(0.5, 0.5), xycoords=ax2.get_window_extent) ############################################################################### # 4. A blended pair of coordinate specifications -- the first for the # x-coordinate, and the second is for the y-coordinate. For example, x=0.5 is # in data coordinates, and y=1 is in normalized axes coordinates: fig, ax = plt.subplots(figsize=(3, 3)) ax.annotate("Test", xy=(0.5, 1), xycoords=("data", "axes fraction")) ax.axvline(x=.5, color='lightgray') ax.set(xlim=(0, 2), ylim=(1, 2)) ############################################################################### # 5. Sometimes, you want your annotation with some "offset points", not from the # annotated point but from some other point or artist. `.text.OffsetFrom` is # a helper for such cases. from matplotlib.text import OffsetFrom fig, ax = plt.subplots(figsize=(3, 3)) an1 = ax.annotate("Test 1", xy=(0.5, 0.5), xycoords="data", va="center", ha="center", bbox=dict(boxstyle="round", fc="w")) offset_from = OffsetFrom(an1, (0.5, 0)) an2 = ax.annotate("Test 2", xy=(0.1, 0.1), xycoords="data", xytext=(0, -10), textcoords=offset_from, # xytext is offset points from "xy=(0.5, 0), xycoords=an1" va="top", ha="center", bbox=dict(boxstyle="round", fc="w"), arrowprops=dict(arrowstyle="->")) ############################################################################### # Using ConnectionPatch # ~~~~~~~~~~~~~~~~~~~~~ # # `.ConnectionPatch` is like an annotation without text. While `~.Axes.annotate` # is sufficient in most situations, `.ConnectionPatch` is useful when you want # to connect points in different axes. For example, here we connect the point # *xy* in the data coordinates of ``ax1`` to point *xy* in the data coordinates # of ``ax2``: from matplotlib.patches import ConnectionPatch fig, (ax1, ax2) = plt.subplots(nrows=1, ncols=2, figsize=(6, 3)) xy = (0.3, 0.2) con = ConnectionPatch(xyA=xy, coordsA=ax1.transData, xyB=xy, coordsB=ax2.transData) fig.add_artist(con) ############################################################################### # Here, we added the `.ConnectionPatch` to the *figure* # (with `~.Figure.add_artist`) rather than to either axes. This ensures that # the ConnectionPatch artist is drawn on top of both axes, and is also necessary # when using :doc:`constrained_layout # ` for positioning the axes. # # Zoom effect between Axes # ~~~~~~~~~~~~~~~~~~~~~~~~ # # `mpl_toolkits.axes_grid1.inset_locator` defines some patch classes useful for # interconnecting two axes. # # .. figure:: ../../gallery/subplots_axes_and_figures/images/sphx_glr_axes_zoom_effect_001.png # :target: ../../gallery/subplots_axes_and_figures/axes_zoom_effect.html # :align: center # # The code for this figure is at # :doc:`/gallery/subplots_axes_and_figures/axes_zoom_effect` and # familiarity with :doc:`../advanced/transforms_tutorial` # is recommended.