简介
mpldatacursor
包可以为matplotlib
提供交互式的数据光标(弹出式注释框)。
它的典型功能是:
鼠标左键单击
图表数据元素时会弹出文本框显示最近的数据元素的坐标值。
鼠标右键单击
文本框取消显示数据光标。
- 按
d
键时切换显示\关闭数据光标。
安装
如果matplotlib版本低于3.3可以直接使用pip安装
pip install mpldatacursor
如果matplotlib版本高于3.3,虽然pip安装成功,但是运行案例时会出现AttributeError: 'ScalarFormatter' object has no attribute 'pprint_val'
错误。
通过查看源码可知:
try:
# Again, older versions of mpl
return formatter.pprint_val(x)
except AttributeError:
# 3.3.0 or later
return formatter.format_data_short(x)
通过分析,预计是因为使用了国内pip源,mpldatacursor
包还未修复该问题(pip 安装的 mpldatacursor
包版本号是0.7.1)。
因此,建议到https://github.com/joferkington/mpldatacursor
下载源码,进行源码安装(源码安装的 mpldatacursor
包版本号是0.7.dev0)。
基本应用(官方实例)解析
应用流程
mpldatacursor
包基本应用方式比较简单:
- 从
mpldatacursor
包中导入datacursor
函数。
- 应用
datacursor
函数。
包结构
查看源码可知,mpldatacursor
包的结构如下:
mpldatacursor
convenience.py
datacursor.py
pick_info.py
__init__.py
datacursor
函数定义在convenience.py
中,datacursor
函数的返回值是DataCursor
类实例。
DataCursor
类定义在datacursor.py
中。
pick_info.py
定义了一系列和弹出文本框相关的函数,供DataCursor
类调用。
datacursor函数定义
由 datacursor
函数定义可知:
datacursor
函数可以不提供参数,这样图像内所有数据元素都会应用交互式数据光标。
datacursor
函数可以指定哪些数据元素应用交互式数据光标。
def datacursor(artists=None, axes=None, **kwargs):
"""
Create an interactive data cursor for the specified artists or specified
axes. The data cursor displays information about a selected artist in a
"popup" annotation box.
If a specific sequence of artists is given, only the specified artists will
be interactively selectable. Otherwise, all manually-plotted artists in
*axes* will be used (*axes* defaults to all axes in all figures).
Parameters
-----------
artists : a matplotlib artist or sequence of artists, optional
The artists to make selectable and display information for. If this is
not specified, then all manually plotted artists in `axes` will be
used.
axes : a matplotlib axes of sequence of axes, optional
The axes to selected artists from if a sequence of artists is not
specified. If `axes` is not specified, then all available axes in all
figures will be used.
tolerance : number, optional
The radius (in points) that the mouse click must be within to select
the artist. Default: 5 points.
formatter : callable, optional
A function that accepts arbitrary kwargs and returns a string that will
be displayed with annotate. Often, it is convienent to pass in the
format method of a template string, e.g.
``formatter="{label}".format``.
Keyword arguments passed in to the `formatter` function:
`x`, `y` : floats
The x and y data coordinates of the clicked point
`event` : a matplotlib ``PickEvent``
The pick event that was fired (note that the selected
artist can be accessed through ``event.artist``).
`label` : string or None
The legend label of the selected artist.
`ind` : list of ints or None
If the artist has "subitems" (e.g. points in a scatter or
line plot), this will be a list of the item(s) that were
clicked on. If the artist does not have "subitems", this
will be None. Note that this is always a list, even when
a single item is selected.
Some selected artists may supply additional keyword arguments that
are not always present, for example:
`z` : number
The "z" (usually color or array) value, if present. For an
``AxesImage`` (as created by ``imshow``), this will be the
uninterpolated array value at the point clicked. For a
``PathCollection`` (as created by ``scatter``) this will be the
"c" value if an array was passed to "c".
`i`, `j` : ints
The row, column indicies of the selected point for an
``AxesImage`` (as created by ``imshow``)
`s` : number
The size of the selected item in a ``PathCollection`` if a size
array is specified.
`c` : number
The array value displayed as color for a ``PathCollection``
if a "c" array is specified (identical to "z").
`point_label` : list
If `point_labels` is given when the data cursor is initialized
and the artist has "subitems", this will be a list of the items
of `point_labels` that correspond to the selected artists.
Note that this is always a list, even when a single artist is
selected.
`width`, `height`, `top`, `bottom` : numbers
The parameters for ``Rectangle`` artists (e.g. bar plots).
point_labels : sequence or dict, optional
For artists with "subitems" (e.g. Line2D's), the item(s) of
`point_labels` corresponding to the selected "subitems" of the artist
will be passed into the formatter function as the "point_label" kwarg.
If a single sequence is given, it will be used for all artists with
"subitems". Alternatively, a dict of artist:sequence pairs may be given
to match an artist to the correct series of point labels.
display : {"one-per-axes", "single", "multiple"}, optional
Controls whether more than one annotation box will be shown.
Default: "one-per-axes"
draggable : boolean, optional
Controls whether or not the annotation box will be interactively
draggable to a new location after being displayed. Defaults to False.
hover : boolean, optional
If True, the datacursor will "pop up" when the mouse hovers over an
artist. Defaults to False. Enabling hover also sets
`display="single"` and `draggable=False`.
props_override : function, optional
If specified, this function customizes the parameters passed into the
formatter function and the x, y location that the datacursor "pop up"
"points" to. This is often useful to make the annotation "point" to a
specific side or corner of an artist, regardless of the position
clicked. The function is passed the same kwargs as the `formatter`
function and is expected to return a dict with at least the keys "x"
and "y" (and probably several others).
Expected call signature: `props_dict = props_override(**kwargs)`
keybindings : boolean or dict, optional
By default, the keys "d" and "t" will be bound to deleting/hiding all
annotation boxes and toggling interactivity for datacursors,
respectively. If keybindings is False, the ability to hide/toggle
datacursors interactively will be disabled. Alternatively, a dict of
the form {'hide':'somekey', 'toggle':'somekey'} may specified to
customize the keyboard shortcuts.
date_format : string, optional
The strftime-style formatting string for dates. Used only if the x or y
axes have been set to display dates. Defaults to "%x %X".
display_button: int, optional
The mouse button that will triggers displaying an annotation box.
Defaults to 1, for left-clicking. (Common options are 1:left-click,
2:middle-click, 3:right-click)
hide_button: int or None, optional
The mouse button that triggers hiding the selected annotation box.
Defaults to 3, for right-clicking. (Common options are 1:left-click,
2:middle-click, 3:right-click, None:hiding disabled)
keep_inside : boolean, optional
Whether or not to adjust the x,y offset to keep the text box inside the
figure. This option has no effect on draggable datacursors. Defaults to
True. Note: Currently disabled on OSX and NbAgg/notebook backends.
**kwargs : additional keyword arguments, optional
Additional keyword arguments are passed on to annotate.
Returns
-------
dc : A ``mpldatacursor.DataCursor`` instance
"""
官方实例源码
import matplotlib.pyplot as plt
import numpy as np
from mpldatacursor import datacursor
data = np.outer(range(10), range(1, 5))
fig, ax = plt.subplots()
lines = ax.plot(data)
ax.set_title('Click somewhere on a line')
datacursor()
plt.show()
限定仅某数据元素使用交互式光标
本实例中,有两个数据元素(artist
):line1
和line2
,datacursor(line1)
函数提供了参数line1
,因此只有line1
可以使用交互式数据光标,line2
则没有效果。
import matplotlib.pyplot as plt
import numpy as np
from mpldatacursor import datacursor
fig, ax = plt.subplots()
line1 = ax.plot([1,3])
line2 = ax.plot([1,2])
ax.set_title('Click somewhere on a line')
datacursor(line1)
plt.show()
其他官方实例功能概述
mpldatacursor
提供了大量实际案例,详见https://github.com/joferkington/mpldatacursor/tree/master/examples。不再一一分析,仅简单说明功能。
basic_single_annotation.py
:在多子图情况下,默认每个子图的数据光标是独立的,即每个子图都可以显示数据光标,相互不影响。使用datacursor(display='single')
参数后,仅在当前子图显示数据光标,其余子图显示的数据光标自动关闭。
change_popup_color.py
:提供了两个案例,一个取消了提示框的边框,一个将提示框的背景色改为白色。
hover_example.py
:将数据光标的触发方式由鼠标左键单击改为鼠标悬浮。
show_artist_labels.py
:将数据光标默认显示的坐标值改为数据元素的label
。
highlighting_example.py
:点击数据元素时,数据元素会高亮(黄色)显示。
draggable_example.py
:在一个子图中,同时显示多个数据光标。
customize_keyboard_shortcuts.py
:重新绑定数据光标快捷键。
labeled_points_example.py
:自定义数据点标签。
date_example.py
:日期数据显示。
bar_example.py
:在柱状图中,在每个柱上方鼠标悬浮触发数据光标。
总结
mpldatacursor
历史悠久,但是迟迟没有发布支持matplotlib3.3
的稳定版,建议源码安装开发版,或者使用mplcursors
包https://github.com/anntzer/mplcursors。
mpldatacursor
功能上还是挺丰富的,可以作为深入学习matplotlib
交互的案例。
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