doc_content stringlengths 1 386k | doc_id stringlengths 5 188 |
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button1(event)[source]
Process an button-1 event (add a label to a contour). Parameters
eventMouseEvent | matplotlib.blocking_input_api#matplotlib.blocking_input.BlockingContourLabeler.button1 |
button3(event)[source]
Process an button-3 event (remove a label if not in inline mode). Unfortunately, if one is doing inline labels, then there is currently no way to fix the broken contour - once humpty-dumpty is broken, he can't be put back together. In inline mode, this does nothing. Parameters
eventMouseEve... | matplotlib.blocking_input_api#matplotlib.blocking_input.BlockingContourLabeler.button3 |
pop_click(event, index=- 1)[source]
Remove a click (by default, the last) from the list of clicks. Parameters
eventMouseEvent | matplotlib.blocking_input_api#matplotlib.blocking_input.BlockingContourLabeler.pop_click |
classmatplotlib.blocking_input.BlockingInput(fig, eventslist=())[source]
Bases: object Callable for retrieving events in a blocking way. add_event(event)[source]
For base class, this just appends an event to events.
cleanup()[source]
Disconnect all callbacks.
on_event(event)[source]
Event handler; wil... | matplotlib.blocking_input_api#matplotlib.blocking_input.BlockingInput |
add_event(event)[source]
For base class, this just appends an event to events. | matplotlib.blocking_input_api#matplotlib.blocking_input.BlockingInput.add_event |
cleanup()[source]
Disconnect all callbacks. | matplotlib.blocking_input_api#matplotlib.blocking_input.BlockingInput.cleanup |
on_event(event)[source]
Event handler; will be passed to the current figure to retrieve events. | matplotlib.blocking_input_api#matplotlib.blocking_input.BlockingInput.on_event |
pop(index=- 1)[source]
Remove an event from the event list -- by default, the last. Note that this does not check that there are events, much like the normal pop method. If no events exist, this will throw an exception. | matplotlib.blocking_input_api#matplotlib.blocking_input.BlockingInput.pop |
pop_event(index=- 1)[source]
Remove an event from the event list -- by default, the last. Note that this does not check that there are events, much like the normal pop method. If no events exist, this will throw an exception. | matplotlib.blocking_input_api#matplotlib.blocking_input.BlockingInput.pop_event |
post_event()[source]
For baseclass, do nothing but collect events. | matplotlib.blocking_input_api#matplotlib.blocking_input.BlockingInput.post_event |
classmatplotlib.blocking_input.BlockingKeyMouseInput(fig)[source]
Bases: matplotlib.blocking_input.BlockingInput Callable for retrieving mouse clicks and key presses in a blocking way. post_event()[source]
Determine if it is a key event. | matplotlib.blocking_input_api#matplotlib.blocking_input.BlockingKeyMouseInput |
post_event()[source]
Determine if it is a key event. | matplotlib.blocking_input_api#matplotlib.blocking_input.BlockingKeyMouseInput.post_event |
classmatplotlib.blocking_input.BlockingMouseInput(fig, mouse_add=MouseButton.LEFT, mouse_pop=MouseButton.RIGHT, mouse_stop=MouseButton.MIDDLE)[source]
Bases: matplotlib.blocking_input.BlockingInput Callable for retrieving mouse clicks in a blocking way. This class will also retrieve keypresses and map them to mouse c... | matplotlib.blocking_input_api#matplotlib.blocking_input.BlockingMouseInput |
add_click(event)[source]
Add the coordinates of an event to the list of clicks. Parameters
eventMouseEvent | matplotlib.blocking_input_api#matplotlib.blocking_input.BlockingMouseInput.add_click |
button_add=1[source] | matplotlib.blocking_input_api#matplotlib.blocking_input.BlockingMouseInput.button_add |
button_pop=3[source] | matplotlib.blocking_input_api#matplotlib.blocking_input.BlockingMouseInput.button_pop |
button_stop=2[source] | matplotlib.blocking_input_api#matplotlib.blocking_input.BlockingMouseInput.button_stop |
cleanup(event=None)[source]
Parameters
eventMouseEvent, optional
Not used | matplotlib.blocking_input_api#matplotlib.blocking_input.BlockingMouseInput.cleanup |
key_event()[source]
Process a key press event, mapping keys to appropriate mouse clicks. | matplotlib.blocking_input_api#matplotlib.blocking_input.BlockingMouseInput.key_event |
mouse_event()[source]
Process a mouse click event. | matplotlib.blocking_input_api#matplotlib.blocking_input.BlockingMouseInput.mouse_event |
mouse_event_add(event)[source]
Process an button-1 event (add a click if inside axes). Parameters
eventMouseEvent | matplotlib.blocking_input_api#matplotlib.blocking_input.BlockingMouseInput.mouse_event_add |
mouse_event_pop(event)[source]
Process an button-3 event (remove the last click). Parameters
eventMouseEvent | matplotlib.blocking_input_api#matplotlib.blocking_input.BlockingMouseInput.mouse_event_pop |
mouse_event_stop(event)[source]
Process an button-2 event (end blocking input). Parameters
eventMouseEvent | matplotlib.blocking_input_api#matplotlib.blocking_input.BlockingMouseInput.mouse_event_stop |
pop(event, index=- 1)[source]
Remove a click and the associated event from the list of clicks. Defaults to the last click. | matplotlib.blocking_input_api#matplotlib.blocking_input.BlockingMouseInput.pop |
pop_click(event, index=- 1)[source]
Remove a click (by default, the last) from the list of clicks. Parameters
eventMouseEvent | matplotlib.blocking_input_api#matplotlib.blocking_input.BlockingMouseInput.pop_click |
post_event()[source]
Process an event. | matplotlib.blocking_input_api#matplotlib.blocking_input.BlockingMouseInput.post_event |
matplotlib.category Plotting of string "category" data: plot(['d', 'f', 'a'], [1, 2, 3]) will plot three points with x-axis values of 'd', 'f', 'a'. See Plotting categorical variables for an example. The module uses Matplotlib's matplotlib.units mechanism to convert from strings to integers and provides a tick locator,... | matplotlib.category_api |
classmatplotlib.category.StrCategoryConverter[source]
Bases: matplotlib.units.ConversionInterface staticaxisinfo(unit, axis)[source]
Set the default axis ticks and labels. Parameters
unitUnitData
object string unit information for value
axisAxis
axis for which information is being set Note axis is not ... | matplotlib.category_api#matplotlib.category.StrCategoryConverter |
staticaxisinfo(unit, axis)[source]
Set the default axis ticks and labels. Parameters
unitUnitData
object string unit information for value
axisAxis
axis for which information is being set Note axis is not used Returns
AxisInfo
Information to support default tick labeling | matplotlib.category_api#matplotlib.category.StrCategoryConverter.axisinfo |
staticconvert(value, unit, axis)[source]
Convert strings in value to floats using mapping information stored in the unit object. Parameters
valuestr or iterable
Value or list of values to be converted.
unitUnitData
An object mapping strings to integers.
axisAxis
The axis on which the converted value is ... | matplotlib.category_api#matplotlib.category.StrCategoryConverter.convert |
staticdefault_units(data, axis)[source]
Set and update the Axis units. Parameters
datastr or iterable of str
axisAxis
axis on which the data is plotted Returns
UnitData
object storing string to integer mapping | matplotlib.category_api#matplotlib.category.StrCategoryConverter.default_units |
classmatplotlib.category.StrCategoryFormatter(units_mapping)[source]
Bases: matplotlib.ticker.Formatter String representation of the data at every tick. Parameters
units_mappingdict
Mapping of category names (str) to indices (int). format_ticks(values)[source]
Return the tick labels for all the ticks at... | matplotlib.category_api#matplotlib.category.StrCategoryFormatter |
format_ticks(values)[source]
Return the tick labels for all the ticks at once. | matplotlib.category_api#matplotlib.category.StrCategoryFormatter.format_ticks |
classmatplotlib.category.StrCategoryLocator(units_mapping)[source]
Bases: matplotlib.ticker.Locator Tick at every integer mapping of the string data. Parameters
units_mappingdict
Mapping of category names (str) to indices (int). tick_values(vmin, vmax)[source]
Return the values of the located ticks give... | matplotlib.category_api#matplotlib.category.StrCategoryLocator |
tick_values(vmin, vmax)[source]
Return the values of the located ticks given vmin and vmax. Note To get tick locations with the vmin and vmax values defined automatically for the associated axis simply call the Locator instance: >>> print(type(loc))
<type 'Locator'>
>>> print(loc())
[1, 2, 3, 4] | matplotlib.category_api#matplotlib.category.StrCategoryLocator.tick_values |
classmatplotlib.category.UnitData(data=None)[source]
Bases: object Create mapping between unique categorical values and integer ids. Parameters
dataiterable
sequence of string values update(data)[source]
Map new values to integer identifiers. Parameters
dataiterable of str or bytes
Raises
TypeE... | matplotlib.category_api#matplotlib.category.UnitData |
update(data)[source]
Map new values to integer identifiers. Parameters
dataiterable of str or bytes
Raises
TypeError
If elements in data are neither str nor bytes. | matplotlib.category_api#matplotlib.category.UnitData.update |
matplotlib.cbook A collection of utility functions and classes. Originally, many (but not all) were from the Python Cookbook -- hence the name cbook. This module is safe to import from anywhere within Matplotlib; it imports Matplotlib only at runtime. classmatplotlib.cbook.CallbackRegistry(exception_handler=<function... | matplotlib.cbook_api |
matplotlib.cbook.boxplot_stats(X, whis=1.5, bootstrap=None, labels=None, autorange=False)[source]
Return a list of dictionaries of statistics used to draw a series of box and whisker plots using bxp. Parameters
Xarray-like
Data that will be represented in the boxplots. Should have 2 or fewer dimensions.
whisf... | matplotlib.cbook_api#matplotlib.cbook.boxplot_stats |
classmatplotlib.cbook.CallbackRegistry(exception_handler=<function _exception_printer>)[source]
Bases: object Handle registering, processing, blocking, and disconnecting for a set of signals and callbacks: >>> def oneat(x):
... print('eat', x)
>>> def ondrink(x):
... print('drink', x)
>>> from matplotlib.cbook... | matplotlib.cbook_api#matplotlib.cbook.CallbackRegistry |
blocked(*, signal=None)
Block callback signals from being processed. A context manager to temporarily block/disable callback signals from being processed by the registered listeners. Parameters
signalstr, optional
The callback signal to block. The default is to block all signals. | matplotlib.cbook_api#matplotlib.cbook.CallbackRegistry.blocked |
connect(signal, func)[source]
Register func to be called when signal signal is generated. | matplotlib.cbook_api#matplotlib.cbook.CallbackRegistry.connect |
disconnect(cid)[source]
Disconnect the callback registered with callback id cid. No error is raised if such a callback does not exist. | matplotlib.cbook_api#matplotlib.cbook.CallbackRegistry.disconnect |
process(s, *args, **kwargs)[source]
Process signal s. All of the functions registered to receive callbacks on s will be called with *args and **kwargs. | matplotlib.cbook_api#matplotlib.cbook.CallbackRegistry.process |
matplotlib.cbook.contiguous_regions(mask)[source]
Return a list of (ind0, ind1) such that mask[ind0:ind1].all() is True and we cover all such regions. | matplotlib.cbook_api#matplotlib.cbook.contiguous_regions |
matplotlib.cbook.delete_masked_points(*args)[source]
Find all masked and/or non-finite points in a set of arguments, and return the arguments with only the unmasked points remaining. Arguments can be in any of 5 categories: 1-D masked arrays 1-D ndarrays ndarrays with more than one dimension other non-string iterabl... | matplotlib.cbook_api#matplotlib.cbook.delete_masked_points |
matplotlib.cbook.deprecated(*args, **kwargs)[source]
[Deprecated] Notes Deprecated since version 3.4: | matplotlib.cbook_api#matplotlib.cbook.deprecated |
matplotlib.cbook.file_requires_unicode(x)[source]
Return whether the given writable file-like object requires Unicode to be written to it. | matplotlib.cbook_api#matplotlib.cbook.file_requires_unicode |
matplotlib.cbook.flatten(seq, scalarp=<function is_scalar_or_string>)[source]
Return a generator of flattened nested containers. For example: >>> from matplotlib.cbook import flatten
>>> l = (('John', ['Hunter']), (1, 23), [[([42, (5, 23)], )]])
>>> print(list(flatten(l)))
['John', 'Hunter', 1, 23, 42, 5, 23]
By: Co... | matplotlib.cbook_api#matplotlib.cbook.flatten |
matplotlib.cbook.get_sample_data(fname, asfileobj=True, *, np_load=False)[source]
Return a sample data file. fname is a path relative to the mpl-data/sample_data directory. If asfileobj is True return a file object, otherwise just a file path. Sample data files are stored in the 'mpl-data/sample_data' directory withi... | matplotlib.cbook_api#matplotlib.cbook.get_sample_data |
classmatplotlib.cbook.Grouper(init=())[source]
Bases: object A disjoint-set data structure. Objects can be joined using join(), tested for connectedness using joined(), and all disjoint sets can be retrieved by using the object as an iterator. The objects being joined must be hashable and weak-referenceable. Examples... | matplotlib.cbook_api#matplotlib.cbook.Grouper |
clean()[source]
Clean dead weak references from the dictionary. | matplotlib.cbook_api#matplotlib.cbook.Grouper.clean |
get_siblings(a)[source]
Return all of the items joined with a, including itself. | matplotlib.cbook_api#matplotlib.cbook.Grouper.get_siblings |
join(a, *args)[source]
Join given arguments into the same set. Accepts one or more arguments. | matplotlib.cbook_api#matplotlib.cbook.Grouper.join |
joined(a, b)[source]
Return whether a and b are members of the same set. | matplotlib.cbook_api#matplotlib.cbook.Grouper.joined |
remove(a)[source] | matplotlib.cbook_api#matplotlib.cbook.Grouper.remove |
matplotlib.cbook.index_of(y)[source]
A helper function to create reasonable x values for the given y. This is used for plotting (x, y) if x values are not explicitly given. First try y.index (assuming y is a pandas.Series), if that fails, use range(len(y)). This will be extended in the future to deal with more types ... | matplotlib.cbook_api#matplotlib.cbook.index_of |
matplotlib.cbook.is_math_text(s)[source]
Return whether the string s contains math expressions. This is done by checking whether s contains an even number of non-escaped dollar signs. | matplotlib.cbook_api#matplotlib.cbook.is_math_text |
matplotlib.cbook.is_scalar_or_string(val)[source]
Return whether the given object is a scalar or string like. | matplotlib.cbook_api#matplotlib.cbook.is_scalar_or_string |
matplotlib.cbook.is_writable_file_like(obj)[source]
Return whether obj looks like a file object with a write method. | matplotlib.cbook_api#matplotlib.cbook.is_writable_file_like |
matplotlib.cbook.ls_mapper={'-': 'solid', '--': 'dashed', '-.': 'dashdot', ':': 'dotted'}
Maps short codes for line style to their full name used by backends. | matplotlib.cbook_api#matplotlib.cbook.ls_mapper |
matplotlib.cbook.ls_mapper_r={'dashdot': '-.', 'dashed': '--', 'dotted': ':', 'solid': '-'}
Maps full names for line styles used by backends to their short codes. | matplotlib.cbook_api#matplotlib.cbook.ls_mapper_r |
classmatplotlib.cbook.maxdict(maxsize)[source]
Bases: dict A dictionary with a maximum size. Notes This doesn't override all the relevant methods to constrain the size, just __setitem__, so use with caution. | matplotlib.cbook_api#matplotlib.cbook.maxdict |
matplotlib.cbook.normalize_kwargs(kw, alias_mapping=None)[source]
Helper function to normalize kwarg inputs. Parameters
kwdict or None
A dict of keyword arguments. None is explicitly supported and treated as an empty dict, to support functions with an optional parameter of the form props=None.
alias_mappingdi... | matplotlib.cbook_api#matplotlib.cbook.normalize_kwargs |
matplotlib.cbook.open_file_cm(path_or_file, mode='r', encoding=None)[source]
Pass through file objects and context-manage path-likes. | matplotlib.cbook_api#matplotlib.cbook.open_file_cm |
matplotlib.cbook.print_cycles(objects, outstream=<_io.TextIOWrapper name='<stdout>' mode='w' encoding='utf-8'>, show_progress=False)[source]
Print loops of cyclic references in the given objects. It is often useful to pass in gc.garbage to find the cycles that are preventing some objects from being garbage collected.... | matplotlib.cbook_api#matplotlib.cbook.print_cycles |
matplotlib.cbook.pts_to_midstep(x, *args)[source]
Convert continuous line to mid-steps. Given a set of N points convert to 2N points which when connected linearly give a step function which changes values at the middle of the intervals. Parameters
xarray
The x location of the steps. May be empty.
y1, ..., ypa... | matplotlib.cbook_api#matplotlib.cbook.pts_to_midstep |
matplotlib.cbook.pts_to_poststep(x, *args)[source]
Convert continuous line to post-steps. Given a set of N points convert to 2N + 1 points, which when connected linearly give a step function which changes values at the end of the intervals. Parameters
xarray
The x location of the steps. May be empty.
y1, ...,... | matplotlib.cbook_api#matplotlib.cbook.pts_to_poststep |
matplotlib.cbook.pts_to_prestep(x, *args)[source]
Convert continuous line to pre-steps. Given a set of N points, convert to 2N - 1 points, which when connected linearly give a step function which changes values at the beginning of the intervals. Parameters
xarray
The x location of the steps. May be empty.
y1,... | matplotlib.cbook_api#matplotlib.cbook.pts_to_prestep |
matplotlib.cbook.report_memory(i=0)[source]
[Deprecated] Return the memory consumed by the process. Notes Deprecated since version 3.5. | matplotlib.cbook_api#matplotlib.cbook.report_memory |
matplotlib.cbook.safe_first_element(obj)[source]
Return the first element in obj. This is an type-independent way of obtaining the first element, supporting both index access and the iterator protocol. | matplotlib.cbook_api#matplotlib.cbook.safe_first_element |
matplotlib.cbook.safe_masked_invalid(x, copy=False)[source] | matplotlib.cbook_api#matplotlib.cbook.safe_masked_invalid |
matplotlib.cbook.sanitize_sequence(data)[source]
Convert dictview objects to list. Other inputs are returned unchanged. | matplotlib.cbook_api#matplotlib.cbook.sanitize_sequence |
classmatplotlib.cbook.silent_list(type, seq=None)[source]
Bases: list A list with a short repr(). This is meant to be used for a homogeneous list of artists, so that they don't cause long, meaningless output. Instead of [<matplotlib.lines.Line2D object at 0x7f5749fed3c8>,
<matplotlib.lines.Line2D object at 0x7f5749f... | matplotlib.cbook_api#matplotlib.cbook.silent_list |
matplotlib.cbook.simple_linear_interpolation(a, steps)[source]
Resample an array with steps - 1 points between original point pairs. Along each column of a, (steps - 1) points are introduced between each original values; the values are linearly interpolated. Parameters
aarray, shape (n, ...)
stepsint
Returns... | matplotlib.cbook_api#matplotlib.cbook.simple_linear_interpolation |
classmatplotlib.cbook.Stack(default=None)[source]
Bases: object Stack of elements with a movable cursor. Mimics home/back/forward in a web browser. back()[source]
Move the position back and return the current element.
bubble(o)[source]
Raise all references of o to the top of the stack, and return it. Raise... | matplotlib.cbook_api#matplotlib.cbook.Stack |
back()[source]
Move the position back and return the current element. | matplotlib.cbook_api#matplotlib.cbook.Stack.back |
bubble(o)[source]
Raise all references of o to the top of the stack, and return it. Raises
ValueError
If o is not in the stack. | matplotlib.cbook_api#matplotlib.cbook.Stack.bubble |
clear()[source]
Empty the stack. | matplotlib.cbook_api#matplotlib.cbook.Stack.clear |
empty()[source]
Return whether the stack is empty. | matplotlib.cbook_api#matplotlib.cbook.Stack.empty |
forward()[source]
Move the position forward and return the current element. | matplotlib.cbook_api#matplotlib.cbook.Stack.forward |
home()[source]
Push the first element onto the top of the stack. The first element is returned. | matplotlib.cbook_api#matplotlib.cbook.Stack.home |
push(o)[source]
Push o to the stack at current position. Discard all later elements. o is returned. | matplotlib.cbook_api#matplotlib.cbook.Stack.push |
remove(o)[source]
Remove o from the stack. Raises
ValueError
If o is not in the stack. | matplotlib.cbook_api#matplotlib.cbook.Stack.remove |
matplotlib.cbook.strip_math(s)[source]
Remove latex formatting from mathtext. Only handles fully math and fully non-math strings. | matplotlib.cbook_api#matplotlib.cbook.strip_math |
matplotlib.cbook.to_filehandle(fname, flag='r', return_opened=False, encoding=None)[source]
Convert a path to an open file handle or pass-through a file-like object. Consider using open_file_cm instead, as it allows one to properly close newly created file objects more easily. Parameters
fnamestr or path-like or ... | matplotlib.cbook_api#matplotlib.cbook.to_filehandle |
matplotlib.cbook.violin_stats(X, method, points=100, quantiles=None)[source]
Return a list of dictionaries of data which can be used to draw a series of violin plots. See the Returns section below to view the required keys of the dictionary. Users can skip this function and pass a user-defined set of dictionaries wit... | matplotlib.cbook_api#matplotlib.cbook.violin_stats |
matplotlib.cbook.warn_deprecated(*args, **kwargs)[source]
[Deprecated] Notes Deprecated since version 3.4: | matplotlib.cbook_api#matplotlib.cbook.warn_deprecated |
matplotlib.cm Builtin colormaps, colormap handling utilities, and the ScalarMappable mixin. See also Colormap reference for a list of builtin colormaps. Creating Colormaps in Matplotlib for examples of how to make colormaps. Choosing Colormaps in Matplotlib an in-depth discussion of choosing colormaps. Colormap Normal... | matplotlib.cm_api |
classmatplotlib.cm.ColormapRegistry(cmaps)[source]
Bases: collections.abc.Mapping Container for colormaps that are known to Matplotlib by name. Experimental While we expect the API to be final, we formally mark it as experimental for 3.5 because we want to keep the option to still adapt the API for 3.6 should the ne... | matplotlib.cm_api#matplotlib.cm.ColormapRegistry |
register(cmap, *, name=None, force=False)[source]
Register a new colormap. The colormap name can then be used as a string argument to any cmap parameter in Matplotlib. It is also available in pyplot.get_cmap. The colormap registry stores a copy of the given colormap, so that future changes to the original colormap in... | matplotlib.cm_api#matplotlib.cm.ColormapRegistry.register |
matplotlib.cm.get_cmap(name=None, lut=None)[source]
Get a colormap instance, defaulting to rc values if name is None. Colormaps added with register_cmap() take precedence over built-in colormaps. Parameters
namematplotlib.colors.Colormap or str or None, default: None
If a Colormap instance, it will be returned.... | matplotlib.cm_api#matplotlib.cm.get_cmap |
matplotlib.cm.register_cmap(name=None, cmap=None, *, override_builtin=False)[source]
Add a colormap to the set recognized by get_cmap(). Register a new colormap to be accessed by name LinearSegmentedColormap('swirly', data, lut)
register_cmap(cmap=swirly_cmap)
Parameters
namestr, optional
The name that can be ... | matplotlib.cm_api#matplotlib.cm.register_cmap |
classmatplotlib.cm.ScalarMappable(norm=None, cmap=None)[source]
Bases: object A mixin class to map scalar data to RGBA. The ScalarMappable applies data normalization before returning RGBA colors from the given colormap. Parameters
normmatplotlib.colors.Normalize (or subclass thereof)
The normalizing object whic... | matplotlib.cm_api#matplotlib.cm.ScalarMappable |
autoscale()[source]
Autoscale the scalar limits on the norm instance using the current array | matplotlib.cm_api#matplotlib.cm.ScalarMappable.autoscale |
autoscale_None()[source]
Autoscale the scalar limits on the norm instance using the current array, changing only limits that are None | matplotlib.cm_api#matplotlib.cm.ScalarMappable.autoscale_None |
changed()[source]
Call this whenever the mappable is changed to notify all the callbackSM listeners to the 'changed' signal. | matplotlib.cm_api#matplotlib.cm.ScalarMappable.changed |
colorbar
The last colorbar associated with this ScalarMappable. May be None. | matplotlib.cm_api#matplotlib.cm.ScalarMappable.colorbar |
get_alpha()[source]
Returns
float
Always returns 1. | matplotlib.cm_api#matplotlib.cm.ScalarMappable.get_alpha |
get_array()[source]
Return the array of values, that are mapped to colors. The base class ScalarMappable does not make any assumptions on the dimensionality and shape of the array. | matplotlib.cm_api#matplotlib.cm.ScalarMappable.get_array |
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