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import itertools import kiwisolver as kiwi import logging import numpy as np import matplotlib as mpl import matplotlib.patches as mpatches from matplotlib.transforms import Bbox _layoutboxobjnum = itertools.count() The provided code snippet includes necessary dependencies for implementing the `seq_id` function. Write a Python function `def seq_id()` to solve the following problem: Generate a short sequential id for layoutbox objects. Here is the function: def seq_id(): """Generate a short sequential id for layoutbox objects.""" return '%06d' % next(_layoutboxobjnum)
Generate a short sequential id for layoutbox objects.
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import itertools import kiwisolver as kiwi import logging import numpy as np import matplotlib as mpl import matplotlib.patches as mpatches from matplotlib.transforms import Bbox "antialiased": ["aa"], "edgecolor": ["ec"], "facecolor": ["fc"], "linestyle": ["ls"], "linewidth": ["lw"], }) The provided code snippet includes necessary dependencies for implementing the `plot_children` function. Write a Python function `def plot_children(fig, lg=None, level=0)` to solve the following problem: Simple plotting to show where boxes are. Here is the function: def plot_children(fig, lg=None, level=0): """Simple plotting to show where boxes are.""" if lg is None: _layoutgrids = fig.get_layout_engine().execute(fig) lg = _layoutgrids[fig] colors = mpl.rcParams["axes.prop_cycle"].by_key()["color"] col = colors[level] for i in range(lg.nrows): for j in range(lg.ncols): bb = lg.get_outer_bbox(rows=i, cols=j) fig.add_artist( mpatches.Rectangle(bb.p0, bb.width, bb.height, linewidth=1, edgecolor='0.7', facecolor='0.7', alpha=0.2, transform=fig.transFigure, zorder=-3)) bbi = lg.get_inner_bbox(rows=i, cols=j) fig.add_artist( mpatches.Rectangle(bbi.p0, bbi.width, bbi.height, linewidth=2, edgecolor=col, facecolor='none', transform=fig.transFigure, zorder=-2)) bbi = lg.get_left_margin_bbox(rows=i, cols=j) fig.add_artist( mpatches.Rectangle(bbi.p0, bbi.width, bbi.height, linewidth=0, edgecolor='none', alpha=0.2, facecolor=[0.5, 0.7, 0.5], transform=fig.transFigure, zorder=-2)) bbi = lg.get_right_margin_bbox(rows=i, cols=j) fig.add_artist( mpatches.Rectangle(bbi.p0, bbi.width, bbi.height, linewidth=0, edgecolor='none', alpha=0.2, facecolor=[0.7, 0.5, 0.5], transform=fig.transFigure, zorder=-2)) bbi = lg.get_bottom_margin_bbox(rows=i, cols=j) fig.add_artist( mpatches.Rectangle(bbi.p0, bbi.width, bbi.height, linewidth=0, edgecolor='none', alpha=0.2, facecolor=[0.5, 0.5, 0.7], transform=fig.transFigure, zorder=-2)) bbi = lg.get_top_margin_bbox(rows=i, cols=j) fig.add_artist( mpatches.Rectangle(bbi.p0, bbi.width, bbi.height, linewidth=0, edgecolor='none', alpha=0.2, facecolor=[0.7, 0.2, 0.7], transform=fig.transFigure, zorder=-2)) for ch in lg.children.flat: if ch is not None: plot_children(fig, ch, level=level+1)
Simple plotting to show where boxes are.
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from decimal import Decimal from numbers import Number import numpy as np from numpy import ma from matplotlib import cbook class Decimal(object): def __new__(cls: Type[_DecimalT], value: _DecimalNew = ..., context: Optional[Context] = ...) -> _DecimalT: ... def from_float(cls, __f: float) -> Decimal: ... if sys.version_info >= (3,): def __bool__(self) -> bool: ... else: def __nonzero__(self) -> bool: ... def __div__(self, other: _Decimal, context: Optional[Context] = ...) -> Decimal: ... def __rdiv__(self, other: _Decimal, context: Optional[Context] = ...) -> Decimal: ... def __ne__(self, other: object, context: Optional[Context] = ...) -> bool: ... def compare(self, other: _Decimal, context: Optional[Context] = ...) -> Decimal: ... def __hash__(self) -> int: ... def as_tuple(self) -> DecimalTuple: ... if sys.version_info >= (3, 6): def as_integer_ratio(self) -> Tuple[int, int]: ... def to_eng_string(self, context: Optional[Context] = ...) -> str: ... if sys.version_info >= (3,): def __abs__(self) -> Decimal: ... def __add__(self, other: _Decimal) -> Decimal: ... def __divmod__(self, other: _Decimal) -> Tuple[Decimal, Decimal]: ... def __eq__(self, other: object) -> bool: ... def __floordiv__(self, other: _Decimal) -> Decimal: ... def __ge__(self, other: _ComparableNum) -> bool: ... def __gt__(self, other: _ComparableNum) -> bool: ... def __le__(self, other: _ComparableNum) -> bool: ... def __lt__(self, other: _ComparableNum) -> bool: ... def __mod__(self, other: _Decimal) -> Decimal: ... def __mul__(self, other: _Decimal) -> Decimal: ... def __neg__(self) -> Decimal: ... def __pos__(self) -> Decimal: ... def __pow__(self, other: _Decimal, modulo: Optional[_Decimal] = ...) -> Decimal: ... def __radd__(self, other: _Decimal) -> Decimal: ... def __rdivmod__(self, other: _Decimal) -> Tuple[Decimal, Decimal]: ... def __rfloordiv__(self, other: _Decimal) -> Decimal: ... def __rmod__(self, other: _Decimal) -> Decimal: ... def __rmul__(self, other: _Decimal) -> Decimal: ... def __rsub__(self, other: _Decimal) -> Decimal: ... def __rtruediv__(self, other: _Decimal) -> Decimal: ... def __str__(self) -> str: ... def __sub__(self, other: _Decimal) -> Decimal: ... def __truediv__(self, other: _Decimal) -> Decimal: ... else: def __abs__(self, round: bool = ..., context: Optional[Context] = ...) -> Decimal: ... def __add__(self, other: _Decimal, context: Optional[Context] = ...) -> Decimal: ... def __divmod__(self, other: _Decimal, context: Optional[Context] = ...) -> Tuple[Decimal, Decimal]: ... def __eq__(self, other: object, context: Optional[Context] = ...) -> bool: ... def __floordiv__(self, other: _Decimal, context: Optional[Context] = ...) -> Decimal: ... def __ge__(self, other: _ComparableNum, context: Optional[Context] = ...) -> bool: ... def __gt__(self, other: _ComparableNum, context: Optional[Context] = ...) -> bool: ... def __le__(self, other: _ComparableNum, context: Optional[Context] = ...) -> bool: ... def __lt__(self, other: _ComparableNum, context: Optional[Context] = ...) -> bool: ... def __mod__(self, other: _Decimal, context: Optional[Context] = ...) -> Decimal: ... def __mul__(self, other: _Decimal, context: Optional[Context] = ...) -> Decimal: ... def __neg__(self, context: Optional[Context] = ...) -> Decimal: ... def __pos__(self, context: Optional[Context] = ...) -> Decimal: ... def __pow__(self, other: _Decimal, modulo: Optional[_Decimal] = ..., context: Optional[Context] = ...) -> Decimal: ... def __radd__(self, other: _Decimal, context: Optional[Context] = ...) -> Decimal: ... def __rdivmod__(self, other: _Decimal, context: Optional[Context] = ...) -> Tuple[Decimal, Decimal]: ... def __rfloordiv__(self, other: _Decimal, context: Optional[Context] = ...) -> Decimal: ... def __rmod__(self, other: _Decimal, context: Optional[Context] = ...) -> Decimal: ... def __rmul__(self, other: _Decimal, context: Optional[Context] = ...) -> Decimal: ... def __rsub__(self, other: _Decimal, context: Optional[Context] = ...) -> Decimal: ... def __rtruediv__(self, other: _Decimal, context: Optional[Context] = ...) -> Decimal: ... def __str__(self, eng: bool = ..., context: Optional[Context] = ...) -> str: ... def __sub__(self, other: _Decimal, context: Optional[Context] = ...) -> Decimal: ... def __truediv__(self, other: _Decimal, context: Optional[Context] = ...) -> Decimal: ... def remainder_near(self, other: _Decimal, context: Optional[Context] = ...) -> Decimal: ... def __float__(self) -> float: ... def __int__(self) -> int: ... def __trunc__(self) -> int: ... def real(self) -> Decimal: ... def imag(self) -> Decimal: ... def conjugate(self) -> Decimal: ... def __complex__(self) -> complex: ... if sys.version_info >= (3,): def __round__(self) -> int: ... def __round__(self, ndigits: int) -> Decimal: ... def __floor__(self) -> int: ... def __ceil__(self) -> int: ... else: def __long__(self) -> long: ... def fma(self, other: _Decimal, third: _Decimal, context: Optional[Context] = ...) -> Decimal: ... def __rpow__(self, other: _Decimal, context: Optional[Context] = ...) -> Decimal: ... def normalize(self, context: Optional[Context] = ...) -> Decimal: ... if sys.version_info >= (3,): def quantize(self, exp: _Decimal, rounding: Optional[str] = ..., context: Optional[Context] = ...) -> Decimal: ... def same_quantum(self, other: _Decimal, context: Optional[Context] = ...) -> bool: ... else: def quantize( self, exp: _Decimal, rounding: Optional[str] = ..., context: Optional[Context] = ..., watchexp: bool = ... ) -> Decimal: ... def same_quantum(self, other: _Decimal) -> bool: ... def to_integral_exact(self, rounding: Optional[str] = ..., context: Optional[Context] = ...) -> Decimal: ... def to_integral_value(self, rounding: Optional[str] = ..., context: Optional[Context] = ...) -> Decimal: ... def to_integral(self, rounding: Optional[str] = ..., context: Optional[Context] = ...) -> Decimal: ... def sqrt(self, context: Optional[Context] = ...) -> Decimal: ... def max(self, other: _Decimal, context: Optional[Context] = ...) -> Decimal: ... def min(self, other: _Decimal, context: Optional[Context] = ...) -> Decimal: ... def adjusted(self) -> int: ... if sys.version_info >= (3,): def canonical(self) -> Decimal: ... else: def canonical(self, context: Optional[Context] = ...) -> Decimal: ... def compare_signal(self, other: _Decimal, context: Optional[Context] = ...) -> Decimal: ... if sys.version_info >= (3,): def compare_total(self, other: _Decimal, context: Optional[Context] = ...) -> Decimal: ... def compare_total_mag(self, other: _Decimal, context: Optional[Context] = ...) -> Decimal: ... else: def compare_total(self, other: _Decimal) -> Decimal: ... def compare_total_mag(self, other: _Decimal) -> Decimal: ... def copy_abs(self) -> Decimal: ... def copy_negate(self) -> Decimal: ... if sys.version_info >= (3,): def copy_sign(self, other: _Decimal, context: Optional[Context] = ...) -> Decimal: ... else: def copy_sign(self, other: _Decimal) -> Decimal: ... def exp(self, context: Optional[Context] = ...) -> Decimal: ... def is_canonical(self) -> bool: ... def is_finite(self) -> bool: ... def is_infinite(self) -> bool: ... def is_nan(self) -> bool: ... def is_normal(self, context: Optional[Context] = ...) -> bool: ... def is_qnan(self) -> bool: ... def is_signed(self) -> bool: ... def is_snan(self) -> bool: ... def is_subnormal(self, context: Optional[Context] = ...) -> bool: ... def is_zero(self) -> bool: ... def ln(self, context: Optional[Context] = ...) -> Decimal: ... def log10(self, context: Optional[Context] = ...) -> Decimal: ... def logb(self, context: Optional[Context] = ...) -> Decimal: ... def logical_and(self, other: _Decimal, context: Optional[Context] = ...) -> Decimal: ... def logical_invert(self, context: Optional[Context] = ...) -> Decimal: ... def logical_or(self, other: _Decimal, context: Optional[Context] = ...) -> Decimal: ... def logical_xor(self, other: _Decimal, context: Optional[Context] = ...) -> Decimal: ... def max_mag(self, other: _Decimal, context: Optional[Context] = ...) -> Decimal: ... def min_mag(self, other: _Decimal, context: Optional[Context] = ...) -> Decimal: ... def next_minus(self, context: Optional[Context] = ...) -> Decimal: ... def next_plus(self, context: Optional[Context] = ...) -> Decimal: ... def next_toward(self, other: _Decimal, context: Optional[Context] = ...) -> Decimal: ... def number_class(self, context: Optional[Context] = ...) -> str: ... def radix(self) -> Decimal: ... def rotate(self, other: _Decimal, context: Optional[Context] = ...) -> Decimal: ... def scaleb(self, other: _Decimal, context: Optional[Context] = ...) -> Decimal: ... def shift(self, other: _Decimal, context: Optional[Context] = ...) -> Decimal: ... def __reduce__(self) -> Tuple[Type[Decimal], Tuple[str]]: ... def __copy__(self) -> Decimal: ... def __deepcopy__(self, memo: Any) -> Decimal: ... def __format__(self, specifier: str, context: Optional[Context] = ...) -> str: ... class Number(metaclass=ABCMeta): def __hash__(self) -> int: ... The provided code snippet includes necessary dependencies for implementing the `_is_natively_supported` function. Write a Python function `def _is_natively_supported(x)` to solve the following problem: Return whether *x* is of a type that Matplotlib natively supports or an array of objects of such types. Here is the function: def _is_natively_supported(x): """ Return whether *x* is of a type that Matplotlib natively supports or an array of objects of such types. """ # Matplotlib natively supports all number types except Decimal. if np.iterable(x): # Assume lists are homogeneous as other functions in unit system. for thisx in x: if thisx is ma.masked: continue return isinstance(thisx, Number) and not isinstance(thisx, Decimal) else: return isinstance(x, Number) and not isinstance(x, Decimal)
Return whether *x* is of a type that Matplotlib natively supports or an array of objects of such types.
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from contextlib import ExitStack from enum import Enum import functools import importlib import inspect import logging from numbers import Number import re import sys import threading import time from cycler import cycler import matplotlib import matplotlib.colorbar import matplotlib.image from matplotlib import _api from matplotlib import rcsetup, style from matplotlib import _pylab_helpers, interactive from matplotlib import cbook from matplotlib import _docstring from matplotlib.backend_bases import ( FigureCanvasBase, FigureManagerBase, MouseButton) from matplotlib.figure import Figure, FigureBase, figaspect from matplotlib.gridspec import GridSpec, SubplotSpec from matplotlib import rcParams, rcParamsDefault, get_backend, rcParamsOrig from matplotlib.rcsetup import interactive_bk as _interactive_bk from matplotlib.artist import Artist from matplotlib.axes import Axes, Subplot from matplotlib.projections import PolarAxes from matplotlib import mlab from matplotlib.scale import get_scale_names from matplotlib import cm from matplotlib.cm import _colormaps as colormaps, register_cmap from matplotlib.colors import _color_sequences as color_sequences import numpy as np from matplotlib.colors import Normalize from matplotlib.lines import Line2D from matplotlib.text import Text, Annotation from matplotlib.patches import Polygon, Rectangle, Circle, Arrow from matplotlib.widgets import Button, Slider, Widget from .ticker import ( TickHelper, Formatter, FixedFormatter, NullFormatter, FuncFormatter, FormatStrFormatter, ScalarFormatter, LogFormatter, LogFormatterExponent, LogFormatterMathtext, Locator, IndexLocator, FixedLocator, NullLocator, LinearLocator, LogLocator, AutoLocator, MultipleLocator, MaxNLocator) def get(obj, *args, **kwargs): return matplotlib.artist.get(obj, *args, **kwargs) def _copy_docstring_and_deprecators(method, func=None): if func is None: return functools.partial(_copy_docstring_and_deprecators, method) decorators = [_docstring.copy(method)] # Check whether the definition of *method* includes @_api.rename_parameter # or @_api.make_keyword_only decorators; if so, propagate them to the # pyplot wrapper as well. while getattr(method, "__wrapped__", None) is not None: decorator = _api.deprecation.DECORATORS.get(method) if decorator: decorators.append(decorator) method = method.__wrapped__ for decorator in decorators[::-1]: func = decorator(func) return func
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from contextlib import ExitStack from enum import Enum import functools import importlib import inspect import logging from numbers import Number import re import sys import threading import time from cycler import cycler import matplotlib import matplotlib.colorbar import matplotlib.image from matplotlib import _api from matplotlib import rcsetup, style from matplotlib import _pylab_helpers, interactive from matplotlib import cbook from matplotlib import _docstring from matplotlib.backend_bases import ( FigureCanvasBase, FigureManagerBase, MouseButton) from matplotlib.figure import Figure, FigureBase, figaspect from matplotlib.gridspec import GridSpec, SubplotSpec from matplotlib import rcParams, rcParamsDefault, get_backend, rcParamsOrig from matplotlib.rcsetup import interactive_bk as _interactive_bk from matplotlib.artist import Artist from matplotlib.axes import Axes, Subplot from matplotlib.projections import PolarAxes from matplotlib import mlab from matplotlib.scale import get_scale_names from matplotlib import cm from matplotlib.cm import _colormaps as colormaps, register_cmap from matplotlib.colors import _color_sequences as color_sequences import numpy as np from matplotlib.colors import Normalize from matplotlib.lines import Line2D from matplotlib.text import Text, Annotation from matplotlib.patches import Polygon, Rectangle, Circle, Arrow from matplotlib.widgets import Button, Slider, Widget from .ticker import ( TickHelper, Formatter, FixedFormatter, NullFormatter, FuncFormatter, FormatStrFormatter, ScalarFormatter, LogFormatter, LogFormatterExponent, LogFormatterMathtext, Locator, IndexLocator, FixedLocator, NullLocator, LinearLocator, LogLocator, AutoLocator, MultipleLocator, MaxNLocator) def set_loglevel(*args, **kwargs): # Ensure this appears in the pyplot docs. return matplotlib.set_loglevel(*args, **kwargs)
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from contextlib import ExitStack from enum import Enum import functools import importlib import inspect import logging from numbers import Number import re import sys import threading import time from cycler import cycler import matplotlib import matplotlib.colorbar import matplotlib.image from matplotlib import _api from matplotlib import rcsetup, style from matplotlib import _pylab_helpers, interactive from matplotlib import cbook from matplotlib import _docstring from matplotlib.backend_bases import ( FigureCanvasBase, FigureManagerBase, MouseButton) from matplotlib.figure import Figure, FigureBase, figaspect from matplotlib.gridspec import GridSpec, SubplotSpec from matplotlib import rcParams, rcParamsDefault, get_backend, rcParamsOrig from matplotlib.rcsetup import interactive_bk as _interactive_bk from matplotlib.artist import Artist from matplotlib.axes import Axes, Subplot from matplotlib.projections import PolarAxes from matplotlib import mlab from matplotlib.scale import get_scale_names from matplotlib import cm from matplotlib.cm import _colormaps as colormaps, register_cmap from matplotlib.colors import _color_sequences as color_sequences import numpy as np from matplotlib.colors import Normalize from matplotlib.lines import Line2D from matplotlib.text import Text, Annotation from matplotlib.patches import Polygon, Rectangle, Circle, Arrow from matplotlib.widgets import Button, Slider, Widget from .ticker import ( TickHelper, Formatter, FixedFormatter, NullFormatter, FuncFormatter, FormatStrFormatter, ScalarFormatter, LogFormatter, LogFormatterExponent, LogFormatterMathtext, Locator, IndexLocator, FixedLocator, NullLocator, LinearLocator, LogLocator, AutoLocator, MultipleLocator, MaxNLocator) def show(*args, **kwargs): """ Display all open figures. Parameters ---------- block : bool, optional Whether to wait for all figures to be closed before returning. If `True` block and run the GUI main loop until all figure windows are closed. If `False` ensure that all figure windows are displayed and return immediately. In this case, you are responsible for ensuring that the event loop is running to have responsive figures. Defaults to True in non-interactive mode and to False in interactive mode (see `.pyplot.isinteractive`). See Also -------- ion : Enable interactive mode, which shows / updates the figure after every plotting command, so that calling ``show()`` is not necessary. ioff : Disable interactive mode. savefig : Save the figure to an image file instead of showing it on screen. Notes ----- **Saving figures to file and showing a window at the same time** If you want an image file as well as a user interface window, use `.pyplot.savefig` before `.pyplot.show`. At the end of (a blocking) ``show()`` the figure is closed and thus unregistered from pyplot. Calling `.pyplot.savefig` afterwards would save a new and thus empty figure. This limitation of command order does not apply if the show is non-blocking or if you keep a reference to the figure and use `.Figure.savefig`. **Auto-show in jupyter notebooks** The jupyter backends (activated via ``%matplotlib inline``, ``%matplotlib notebook``, or ``%matplotlib widget``), call ``show()`` at the end of every cell by default. Thus, you usually don't have to call it explicitly there. """ _warn_if_gui_out_of_main_thread() return _get_backend_mod().show(*args, **kwargs) def figure(num=None, # autoincrement if None, else integer from 1-N figsize=None, # defaults to rc figure.figsize dpi=None, # defaults to rc figure.dpi facecolor=None, # defaults to rc figure.facecolor edgecolor=None, # defaults to rc figure.edgecolor frameon=True, FigureClass=Figure, clear=False, **kwargs ): """ Create a new figure, or activate an existing figure. Parameters ---------- num : int or str or `.Figure` or `.SubFigure`, optional A unique identifier for the figure. If a figure with that identifier already exists, this figure is made active and returned. An integer refers to the ``Figure.number`` attribute, a string refers to the figure label. If there is no figure with the identifier or *num* is not given, a new figure is created, made active and returned. If *num* is an int, it will be used for the ``Figure.number`` attribute, otherwise, an auto-generated integer value is used (starting at 1 and incremented for each new figure). If *num* is a string, the figure label and the window title is set to this value. If num is a ``SubFigure``, its parent ``Figure`` is activated. figsize : (float, float), default: :rc:`figure.figsize` Width, height in inches. dpi : float, default: :rc:`figure.dpi` The resolution of the figure in dots-per-inch. facecolor : color, default: :rc:`figure.facecolor` The background color. edgecolor : color, default: :rc:`figure.edgecolor` The border color. frameon : bool, default: True If False, suppress drawing the figure frame. FigureClass : subclass of `~matplotlib.figure.Figure` If set, an instance of this subclass will be created, rather than a plain `.Figure`. clear : bool, default: False If True and the figure already exists, then it is cleared. layout : {'constrained', 'compressed', 'tight', 'none', `.LayoutEngine`, None}, \ default: None The layout mechanism for positioning of plot elements to avoid overlapping Axes decorations (labels, ticks, etc). Note that layout managers can measurably slow down figure display. - 'constrained': The constrained layout solver adjusts axes sizes to avoid overlapping axes decorations. Can handle complex plot layouts and colorbars, and is thus recommended. See :doc:`/tutorials/intermediate/constrainedlayout_guide` for examples. - 'compressed': uses the same algorithm as 'constrained', but removes extra space between fixed-aspect-ratio Axes. Best for simple grids of axes. - 'tight': Use the tight layout mechanism. This is a relatively simple algorithm that adjusts the subplot parameters so that decorations do not overlap. See `.Figure.set_tight_layout` for further details. - 'none': Do not use a layout engine. - A `.LayoutEngine` instance. Builtin layout classes are `.ConstrainedLayoutEngine` and `.TightLayoutEngine`, more easily accessible by 'constrained' and 'tight'. Passing an instance allows third parties to provide their own layout engine. If not given, fall back to using the parameters *tight_layout* and *constrained_layout*, including their config defaults :rc:`figure.autolayout` and :rc:`figure.constrained_layout.use`. **kwargs Additional keyword arguments are passed to the `.Figure` constructor. Returns ------- `~matplotlib.figure.Figure` Notes ----- A newly created figure is passed to the `~.FigureCanvasBase.new_manager` method or the `new_figure_manager` function provided by the current backend, which install a canvas and a manager on the figure. Once this is done, :rc:`figure.hooks` are called, one at a time, on the figure; these hooks allow arbitrary customization of the figure (e.g., attaching callbacks) or of associated elements (e.g., modifying the toolbar). See :doc:`/gallery/user_interfaces/mplcvd` for an example of toolbar customization. If you are creating many figures, make sure you explicitly call `.pyplot.close` on the figures you are not using, because this will enable pyplot to properly clean up the memory. `~matplotlib.rcParams` defines the default values, which can be modified in the matplotlibrc file. """ if isinstance(num, FigureBase): if num.canvas.manager is None: raise ValueError("The passed figure is not managed by pyplot") _pylab_helpers.Gcf.set_active(num.canvas.manager) return num.figure allnums = get_fignums() next_num = max(allnums) + 1 if allnums else 1 fig_label = '' if num is None: num = next_num elif isinstance(num, str): fig_label = num all_labels = get_figlabels() if fig_label not in all_labels: if fig_label == 'all': _api.warn_external("close('all') closes all existing figures.") num = next_num else: inum = all_labels.index(fig_label) num = allnums[inum] else: num = int(num) # crude validation of num argument manager = _pylab_helpers.Gcf.get_fig_manager(num) if manager is None: max_open_warning = rcParams['figure.max_open_warning'] if len(allnums) == max_open_warning >= 1: _api.warn_external( f"More than {max_open_warning} figures have been opened. " f"Figures created through the pyplot interface " f"(`matplotlib.pyplot.figure`) are retained until explicitly " f"closed and may consume too much memory. (To control this " f"warning, see the rcParam `figure.max_open_warning`). " f"Consider using `matplotlib.pyplot.close()`.", RuntimeWarning) manager = new_figure_manager( num, figsize=figsize, dpi=dpi, facecolor=facecolor, edgecolor=edgecolor, frameon=frameon, FigureClass=FigureClass, **kwargs) fig = manager.canvas.figure if fig_label: fig.set_label(fig_label) for hookspecs in rcParams["figure.hooks"]: module_name, dotted_name = hookspecs.split(":") obj = importlib.import_module(module_name) for part in dotted_name.split("."): obj = getattr(obj, part) obj(fig) _pylab_helpers.Gcf._set_new_active_manager(manager) # make sure backends (inline) that we don't ship that expect this # to be called in plotting commands to make the figure call show # still work. There is probably a better way to do this in the # FigureManager base class. draw_if_interactive() if _REPL_DISPLAYHOOK is _ReplDisplayHook.PLAIN: fig.stale_callback = _auto_draw_if_interactive if clear: manager.canvas.figure.clear() return manager.canvas.figure The provided code snippet includes necessary dependencies for implementing the `pause` function. Write a Python function `def pause(interval)` to solve the following problem: Run the GUI event loop for *interval* seconds. If there is an active figure, it will be updated and displayed before the pause, and the GUI event loop (if any) will run during the pause. This can be used for crude animation. For more complex animation use :mod:`matplotlib.animation`. If there is no active figure, sleep for *interval* seconds instead. See Also -------- matplotlib.animation : Proper animations show : Show all figures and optional block until all figures are closed. Here is the function: def pause(interval): """ Run the GUI event loop for *interval* seconds. If there is an active figure, it will be updated and displayed before the pause, and the GUI event loop (if any) will run during the pause. This can be used for crude animation. For more complex animation use :mod:`matplotlib.animation`. If there is no active figure, sleep for *interval* seconds instead. See Also -------- matplotlib.animation : Proper animations show : Show all figures and optional block until all figures are closed. """ manager = _pylab_helpers.Gcf.get_active() if manager is not None: canvas = manager.canvas if canvas.figure.stale: canvas.draw_idle() show(block=False) canvas.start_event_loop(interval) else: time.sleep(interval)
Run the GUI event loop for *interval* seconds. If there is an active figure, it will be updated and displayed before the pause, and the GUI event loop (if any) will run during the pause. This can be used for crude animation. For more complex animation use :mod:`matplotlib.animation`. If there is no active figure, sleep for *interval* seconds instead. See Also -------- matplotlib.animation : Proper animations show : Show all figures and optional block until all figures are closed.
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from contextlib import ExitStack from enum import Enum import functools import importlib import inspect import logging from numbers import Number import re import sys import threading import time from cycler import cycler import matplotlib import matplotlib.colorbar import matplotlib.image from matplotlib import _api from matplotlib import rcsetup, style from matplotlib import _pylab_helpers, interactive from matplotlib import cbook from matplotlib import _docstring from matplotlib.backend_bases import ( FigureCanvasBase, FigureManagerBase, MouseButton) from matplotlib.figure import Figure, FigureBase, figaspect from matplotlib.gridspec import GridSpec, SubplotSpec from matplotlib import rcParams, rcParamsDefault, get_backend, rcParamsOrig from matplotlib.rcsetup import interactive_bk as _interactive_bk from matplotlib.artist import Artist from matplotlib.axes import Axes, Subplot from matplotlib.projections import PolarAxes from matplotlib import mlab from matplotlib.scale import get_scale_names from matplotlib import cm from matplotlib.cm import _colormaps as colormaps, register_cmap from matplotlib.colors import _color_sequences as color_sequences import numpy as np from matplotlib.colors import Normalize from matplotlib.lines import Line2D from matplotlib.text import Text, Annotation from matplotlib.patches import Polygon, Rectangle, Circle, Arrow from matplotlib.widgets import Button, Slider, Widget from .ticker import ( TickHelper, Formatter, FixedFormatter, NullFormatter, FuncFormatter, FormatStrFormatter, ScalarFormatter, LogFormatter, LogFormatterExponent, LogFormatterMathtext, Locator, IndexLocator, FixedLocator, NullLocator, LinearLocator, LogLocator, AutoLocator, MultipleLocator, MaxNLocator) draw_all = _pylab_helpers.Gcf.draw_all def rcdefaults(): matplotlib.rcdefaults() if matplotlib.is_interactive(): draw_all()
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from contextlib import ExitStack from enum import Enum import functools import importlib import inspect import logging from numbers import Number import re import sys import threading import time from cycler import cycler import matplotlib import matplotlib.colorbar import matplotlib.image from matplotlib import _api from matplotlib import rcsetup, style from matplotlib import _pylab_helpers, interactive from matplotlib import cbook from matplotlib import _docstring from matplotlib.backend_bases import ( FigureCanvasBase, FigureManagerBase, MouseButton) from matplotlib.figure import Figure, FigureBase, figaspect from matplotlib.gridspec import GridSpec, SubplotSpec from matplotlib import rcParams, rcParamsDefault, get_backend, rcParamsOrig from matplotlib.rcsetup import interactive_bk as _interactive_bk from matplotlib.artist import Artist from matplotlib.axes import Axes, Subplot from matplotlib.projections import PolarAxes from matplotlib import mlab from matplotlib.scale import get_scale_names from matplotlib import cm from matplotlib.cm import _colormaps as colormaps, register_cmap from matplotlib.colors import _color_sequences as color_sequences import numpy as np from matplotlib.colors import Normalize from matplotlib.lines import Line2D from matplotlib.text import Text, Annotation from matplotlib.patches import Polygon, Rectangle, Circle, Arrow from matplotlib.widgets import Button, Slider, Widget from .ticker import ( TickHelper, Formatter, FixedFormatter, NullFormatter, FuncFormatter, FormatStrFormatter, ScalarFormatter, LogFormatter, LogFormatterExponent, LogFormatterMathtext, Locator, IndexLocator, FixedLocator, NullLocator, LinearLocator, LogLocator, AutoLocator, MultipleLocator, MaxNLocator) def getp(obj, *args, **kwargs): return matplotlib.artist.getp(obj, *args, **kwargs)
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from contextlib import ExitStack from enum import Enum import functools import importlib import inspect import logging from numbers import Number import re import sys import threading import time from cycler import cycler import matplotlib import matplotlib.colorbar import matplotlib.image from matplotlib import _api from matplotlib import rcsetup, style from matplotlib import _pylab_helpers, interactive from matplotlib import cbook from matplotlib import _docstring from matplotlib.backend_bases import ( FigureCanvasBase, FigureManagerBase, MouseButton) from matplotlib.figure import Figure, FigureBase, figaspect from matplotlib.gridspec import GridSpec, SubplotSpec from matplotlib import rcParams, rcParamsDefault, get_backend, rcParamsOrig from matplotlib.rcsetup import interactive_bk as _interactive_bk from matplotlib.artist import Artist from matplotlib.axes import Axes, Subplot from matplotlib.projections import PolarAxes from matplotlib import mlab from matplotlib.scale import get_scale_names from matplotlib import cm from matplotlib.cm import _colormaps as colormaps, register_cmap from matplotlib.colors import _color_sequences as color_sequences import numpy as np from matplotlib.colors import Normalize from matplotlib.lines import Line2D from matplotlib.text import Text, Annotation from matplotlib.patches import Polygon, Rectangle, Circle, Arrow from matplotlib.widgets import Button, Slider, Widget from .ticker import ( TickHelper, Formatter, FixedFormatter, NullFormatter, FuncFormatter, FormatStrFormatter, ScalarFormatter, LogFormatter, LogFormatterExponent, LogFormatterMathtext, Locator, IndexLocator, FixedLocator, NullLocator, LinearLocator, LogLocator, AutoLocator, MultipleLocator, MaxNLocator) if (rcParams["backend_fallback"] and rcParams._get_backend_or_none() in ( set(_interactive_bk) - {'WebAgg', 'nbAgg'}) and cbook._get_running_interactive_framework()): rcParams._set("backend", rcsetup._auto_backend_sentinel) ) rcParams = RcParams() if rcParams['axes.formatter.use_locale']: locale.setlocale(locale.LC_ALL, '') The provided code snippet includes necessary dependencies for implementing the `xkcd` function. Write a Python function `def xkcd(scale=1, length=100, randomness=2)` to solve the following problem: Turn on `xkcd <https://xkcd.com/>`_ sketch-style drawing mode. This will only have effect on things drawn after this function is called. For best results, the "Humor Sans" font should be installed: it is not included with Matplotlib. Parameters ---------- scale : float, optional The amplitude of the wiggle perpendicular to the source line. length : float, optional The length of the wiggle along the line. randomness : float, optional The scale factor by which the length is shrunken or expanded. Notes ----- This function works by a number of rcParams, so it will probably override others you have set before. If you want the effects of this function to be temporary, it can be used as a context manager, for example:: with plt.xkcd(): # This figure will be in XKCD-style fig1 = plt.figure() # ... # This figure will be in regular style fig2 = plt.figure() Here is the function: def xkcd(scale=1, length=100, randomness=2): """ Turn on `xkcd <https://xkcd.com/>`_ sketch-style drawing mode. This will only have effect on things drawn after this function is called. For best results, the "Humor Sans" font should be installed: it is not included with Matplotlib. Parameters ---------- scale : float, optional The amplitude of the wiggle perpendicular to the source line. length : float, optional The length of the wiggle along the line. randomness : float, optional The scale factor by which the length is shrunken or expanded. Notes ----- This function works by a number of rcParams, so it will probably override others you have set before. If you want the effects of this function to be temporary, it can be used as a context manager, for example:: with plt.xkcd(): # This figure will be in XKCD-style fig1 = plt.figure() # ... # This figure will be in regular style fig2 = plt.figure() """ # This cannot be implemented in terms of contextmanager() or rc_context() # because this needs to work as a non-contextmanager too. if rcParams['text.usetex']: raise RuntimeError( "xkcd mode is not compatible with text.usetex = True") stack = ExitStack() stack.callback(dict.update, rcParams, rcParams.copy()) from matplotlib import patheffects rcParams.update({ 'font.family': ['xkcd', 'xkcd Script', 'Humor Sans', 'Comic Neue', 'Comic Sans MS'], 'font.size': 14.0, 'path.sketch': (scale, length, randomness), 'path.effects': [ patheffects.withStroke(linewidth=4, foreground="w")], 'axes.linewidth': 1.5, 'lines.linewidth': 2.0, 'figure.facecolor': 'white', 'grid.linewidth': 0.0, 'axes.grid': False, 'axes.unicode_minus': False, 'axes.edgecolor': 'black', 'xtick.major.size': 8, 'xtick.major.width': 3, 'ytick.major.size': 8, 'ytick.major.width': 3, }) return stack
Turn on `xkcd <https://xkcd.com/>`_ sketch-style drawing mode. This will only have effect on things drawn after this function is called. For best results, the "Humor Sans" font should be installed: it is not included with Matplotlib. Parameters ---------- scale : float, optional The amplitude of the wiggle perpendicular to the source line. length : float, optional The length of the wiggle along the line. randomness : float, optional The scale factor by which the length is shrunken or expanded. Notes ----- This function works by a number of rcParams, so it will probably override others you have set before. If you want the effects of this function to be temporary, it can be used as a context manager, for example:: with plt.xkcd(): # This figure will be in XKCD-style fig1 = plt.figure() # ... # This figure will be in regular style fig2 = plt.figure()
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from contextlib import ExitStack from enum import Enum import functools import importlib import inspect import logging from numbers import Number import re import sys import threading import time from cycler import cycler import matplotlib import matplotlib.colorbar import matplotlib.image from matplotlib import _api from matplotlib import rcsetup, style from matplotlib import _pylab_helpers, interactive from matplotlib import cbook from matplotlib import _docstring from matplotlib.backend_bases import ( FigureCanvasBase, FigureManagerBase, MouseButton) from matplotlib.figure import Figure, FigureBase, figaspect from matplotlib.gridspec import GridSpec, SubplotSpec from matplotlib import rcParams, rcParamsDefault, get_backend, rcParamsOrig from matplotlib.rcsetup import interactive_bk as _interactive_bk from matplotlib.artist import Artist from matplotlib.axes import Axes, Subplot from matplotlib.projections import PolarAxes from matplotlib import mlab from matplotlib.scale import get_scale_names from matplotlib import cm from matplotlib.cm import _colormaps as colormaps, register_cmap from matplotlib.colors import _color_sequences as color_sequences import numpy as np from matplotlib.colors import Normalize from matplotlib.lines import Line2D from matplotlib.text import Text, Annotation from matplotlib.patches import Polygon, Rectangle, Circle, Arrow from matplotlib.widgets import Button, Slider, Widget from .ticker import ( TickHelper, Formatter, FixedFormatter, NullFormatter, FuncFormatter, FormatStrFormatter, ScalarFormatter, LogFormatter, LogFormatterExponent, LogFormatterMathtext, Locator, IndexLocator, FixedLocator, NullLocator, LinearLocator, LogLocator, AutoLocator, MultipleLocator, MaxNLocator) def get_figlabels(): """Return a list of existing figure labels.""" managers = _pylab_helpers.Gcf.get_all_fig_managers() managers.sort(key=lambda m: m.num) return [m.canvas.figure.get_label() for m in managers] The provided code snippet includes necessary dependencies for implementing the `fignum_exists` function. Write a Python function `def fignum_exists(num)` to solve the following problem: Return whether the figure with the given id exists. Here is the function: def fignum_exists(num): """Return whether the figure with the given id exists.""" return _pylab_helpers.Gcf.has_fignum(num) or num in get_figlabels()
Return whether the figure with the given id exists.
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from contextlib import ExitStack from enum import Enum import functools import importlib import inspect import logging from numbers import Number import re import sys import threading import time from cycler import cycler import matplotlib import matplotlib.colorbar import matplotlib.image from matplotlib import _api from matplotlib import rcsetup, style from matplotlib import _pylab_helpers, interactive from matplotlib import cbook from matplotlib import _docstring from matplotlib.backend_bases import ( FigureCanvasBase, FigureManagerBase, MouseButton) from matplotlib.figure import Figure, FigureBase, figaspect from matplotlib.gridspec import GridSpec, SubplotSpec from matplotlib import rcParams, rcParamsDefault, get_backend, rcParamsOrig from matplotlib.rcsetup import interactive_bk as _interactive_bk from matplotlib.artist import Artist from matplotlib.axes import Axes, Subplot from matplotlib.projections import PolarAxes from matplotlib import mlab from matplotlib.scale import get_scale_names from matplotlib import cm from matplotlib.cm import _colormaps as colormaps, register_cmap from matplotlib.colors import _color_sequences as color_sequences import numpy as np from matplotlib.colors import Normalize from matplotlib.lines import Line2D from matplotlib.text import Text, Annotation from matplotlib.patches import Polygon, Rectangle, Circle, Arrow from matplotlib.widgets import Button, Slider, Widget from .ticker import ( TickHelper, Formatter, FixedFormatter, NullFormatter, FuncFormatter, FormatStrFormatter, ScalarFormatter, LogFormatter, LogFormatterExponent, LogFormatterMathtext, Locator, IndexLocator, FixedLocator, NullLocator, LinearLocator, LogLocator, AutoLocator, MultipleLocator, MaxNLocator) def gcf(): """ Get the current figure. If there is currently no figure on the pyplot figure stack, a new one is created using `~.pyplot.figure()`. (To test whether there is currently a figure on the pyplot figure stack, check whether `~.pyplot.get_fignums()` is empty.) """ manager = _pylab_helpers.Gcf.get_active() if manager is not None: return manager.canvas.figure else: return figure() The provided code snippet includes necessary dependencies for implementing the `get_current_fig_manager` function. Write a Python function `def get_current_fig_manager()` to solve the following problem: Return the figure manager of the current figure. The figure manager is a container for the actual backend-depended window that displays the figure on screen. If no current figure exists, a new one is created, and its figure manager is returned. Returns ------- `.FigureManagerBase` or backend-dependent subclass thereof Here is the function: def get_current_fig_manager(): """ Return the figure manager of the current figure. The figure manager is a container for the actual backend-depended window that displays the figure on screen. If no current figure exists, a new one is created, and its figure manager is returned. Returns ------- `.FigureManagerBase` or backend-dependent subclass thereof """ return gcf().canvas.manager
Return the figure manager of the current figure. The figure manager is a container for the actual backend-depended window that displays the figure on screen. If no current figure exists, a new one is created, and its figure manager is returned. Returns ------- `.FigureManagerBase` or backend-dependent subclass thereof
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from contextlib import ExitStack from enum import Enum import functools import importlib import inspect import logging from numbers import Number import re import sys import threading import time from cycler import cycler import matplotlib import matplotlib.colorbar import matplotlib.image from matplotlib import _api from matplotlib import rcsetup, style from matplotlib import _pylab_helpers, interactive from matplotlib import cbook from matplotlib import _docstring from matplotlib.backend_bases import ( FigureCanvasBase, FigureManagerBase, MouseButton) from matplotlib.figure import Figure, FigureBase, figaspect from matplotlib.gridspec import GridSpec, SubplotSpec from matplotlib import rcParams, rcParamsDefault, get_backend, rcParamsOrig from matplotlib.rcsetup import interactive_bk as _interactive_bk from matplotlib.artist import Artist from matplotlib.axes import Axes, Subplot from matplotlib.projections import PolarAxes from matplotlib import mlab from matplotlib.scale import get_scale_names from matplotlib import cm from matplotlib.cm import _colormaps as colormaps, register_cmap from matplotlib.colors import _color_sequences as color_sequences import numpy as np from matplotlib.colors import Normalize from matplotlib.lines import Line2D from matplotlib.text import Text, Annotation from matplotlib.patches import Polygon, Rectangle, Circle, Arrow from matplotlib.widgets import Button, Slider, Widget from .ticker import ( TickHelper, Formatter, FixedFormatter, NullFormatter, FuncFormatter, FormatStrFormatter, ScalarFormatter, LogFormatter, LogFormatterExponent, LogFormatterMathtext, Locator, IndexLocator, FixedLocator, NullLocator, LinearLocator, LogLocator, AutoLocator, MultipleLocator, MaxNLocator) def gcf(): """ Get the current figure. If there is currently no figure on the pyplot figure stack, a new one is created using `~.pyplot.figure()`. (To test whether there is currently a figure on the pyplot figure stack, check whether `~.pyplot.get_fignums()` is empty.) """ manager = _pylab_helpers.Gcf.get_active() if manager is not None: return manager.canvas.figure else: return figure() def disconnect(cid): return gcf().canvas.mpl_disconnect(cid)
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from contextlib import ExitStack from enum import Enum import functools import importlib import inspect import logging from numbers import Number import re import sys import threading import time from cycler import cycler import matplotlib import matplotlib.colorbar import matplotlib.image from matplotlib import _api from matplotlib import rcsetup, style from matplotlib import _pylab_helpers, interactive from matplotlib import cbook from matplotlib import _docstring from matplotlib.backend_bases import ( FigureCanvasBase, FigureManagerBase, MouseButton) from matplotlib.figure import Figure, FigureBase, figaspect from matplotlib.gridspec import GridSpec, SubplotSpec from matplotlib import rcParams, rcParamsDefault, get_backend, rcParamsOrig from matplotlib.rcsetup import interactive_bk as _interactive_bk from matplotlib.artist import Artist from matplotlib.axes import Axes, Subplot from matplotlib.projections import PolarAxes from matplotlib import mlab from matplotlib.scale import get_scale_names from matplotlib import cm from matplotlib.cm import _colormaps as colormaps, register_cmap from matplotlib.colors import _color_sequences as color_sequences import numpy as np from matplotlib.colors import Normalize from matplotlib.lines import Line2D from matplotlib.text import Text, Annotation from matplotlib.patches import Polygon, Rectangle, Circle, Arrow from matplotlib.widgets import Button, Slider, Widget from .ticker import ( TickHelper, Formatter, FixedFormatter, NullFormatter, FuncFormatter, FormatStrFormatter, ScalarFormatter, LogFormatter, LogFormatterExponent, LogFormatterMathtext, Locator, IndexLocator, FixedLocator, NullLocator, LinearLocator, LogLocator, AutoLocator, MultipleLocator, MaxNLocator) def gcf(): """ Get the current figure. If there is currently no figure on the pyplot figure stack, a new one is created using `~.pyplot.figure()`. (To test whether there is currently a figure on the pyplot figure stack, check whether `~.pyplot.get_fignums()` is empty.) """ manager = _pylab_helpers.Gcf.get_active() if manager is not None: return manager.canvas.figure else: return figure() The provided code snippet includes necessary dependencies for implementing the `clf` function. Write a Python function `def clf()` to solve the following problem: Clear the current figure. Here is the function: def clf(): """Clear the current figure.""" gcf().clear()
Clear the current figure.
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from contextlib import ExitStack from enum import Enum import functools import importlib import inspect import logging from numbers import Number import re import sys import threading import time from cycler import cycler import matplotlib import matplotlib.colorbar import matplotlib.image from matplotlib import _api from matplotlib import rcsetup, style from matplotlib import _pylab_helpers, interactive from matplotlib import cbook from matplotlib import _docstring from matplotlib.backend_bases import ( FigureCanvasBase, FigureManagerBase, MouseButton) from matplotlib.figure import Figure, FigureBase, figaspect from matplotlib.gridspec import GridSpec, SubplotSpec from matplotlib import rcParams, rcParamsDefault, get_backend, rcParamsOrig from matplotlib.rcsetup import interactive_bk as _interactive_bk from matplotlib.artist import Artist from matplotlib.axes import Axes, Subplot from matplotlib.projections import PolarAxes from matplotlib import mlab from matplotlib.scale import get_scale_names from matplotlib import cm from matplotlib.cm import _colormaps as colormaps, register_cmap from matplotlib.colors import _color_sequences as color_sequences import numpy as np from matplotlib.colors import Normalize from matplotlib.lines import Line2D from matplotlib.text import Text, Annotation from matplotlib.patches import Polygon, Rectangle, Circle, Arrow from matplotlib.widgets import Button, Slider, Widget from .ticker import ( TickHelper, Formatter, FixedFormatter, NullFormatter, FuncFormatter, FormatStrFormatter, ScalarFormatter, LogFormatter, LogFormatterExponent, LogFormatterMathtext, Locator, IndexLocator, FixedLocator, NullLocator, LinearLocator, LogLocator, AutoLocator, MultipleLocator, MaxNLocator) def gcf(): """ Get the current figure. If there is currently no figure on the pyplot figure stack, a new one is created using `~.pyplot.figure()`. (To test whether there is currently a figure on the pyplot figure stack, check whether `~.pyplot.get_fignums()` is empty.) """ manager = _pylab_helpers.Gcf.get_active() if manager is not None: return manager.canvas.figure else: return figure() def legend(*args, **kwargs): return gca().legend(*args, **kwargs) def figlegend(*args, **kwargs): return gcf().legend(*args, **kwargs)
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from contextlib import ExitStack from enum import Enum import functools import importlib import inspect import logging from numbers import Number import re import sys import threading import time from cycler import cycler import matplotlib import matplotlib.colorbar import matplotlib.image from matplotlib import _api from matplotlib import rcsetup, style from matplotlib import _pylab_helpers, interactive from matplotlib import cbook from matplotlib import _docstring from matplotlib.backend_bases import ( FigureCanvasBase, FigureManagerBase, MouseButton) from matplotlib.figure import Figure, FigureBase, figaspect from matplotlib.gridspec import GridSpec, SubplotSpec from matplotlib import rcParams, rcParamsDefault, get_backend, rcParamsOrig from matplotlib.rcsetup import interactive_bk as _interactive_bk from matplotlib.artist import Artist from matplotlib.axes import Axes, Subplot from matplotlib.projections import PolarAxes from matplotlib import mlab from matplotlib.scale import get_scale_names from matplotlib import cm from matplotlib.cm import _colormaps as colormaps, register_cmap from matplotlib.colors import _color_sequences as color_sequences import numpy as np from matplotlib.colors import Normalize from matplotlib.lines import Line2D from matplotlib.text import Text, Annotation from matplotlib.patches import Polygon, Rectangle, Circle, Arrow from matplotlib.widgets import Button, Slider, Widget from .ticker import ( TickHelper, Formatter, FixedFormatter, NullFormatter, FuncFormatter, FormatStrFormatter, ScalarFormatter, LogFormatter, LogFormatterExponent, LogFormatterMathtext, Locator, IndexLocator, FixedLocator, NullLocator, LinearLocator, LogLocator, AutoLocator, MultipleLocator, MaxNLocator) def gca(): return gcf().gca() The provided code snippet includes necessary dependencies for implementing the `cla` function. Write a Python function `def cla()` to solve the following problem: Clear the current axes. Here is the function: def cla(): """Clear the current axes.""" # Not generated via boilerplate.py to allow a different docstring. return gca().cla()
Clear the current axes.
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from contextlib import ExitStack from enum import Enum import functools import importlib import inspect import logging from numbers import Number import re import sys import threading import time from cycler import cycler import matplotlib import matplotlib.colorbar import matplotlib.image from matplotlib import _api from matplotlib import rcsetup, style from matplotlib import _pylab_helpers, interactive from matplotlib import cbook from matplotlib import _docstring from matplotlib.backend_bases import ( FigureCanvasBase, FigureManagerBase, MouseButton) from matplotlib.figure import Figure, FigureBase, figaspect from matplotlib.gridspec import GridSpec, SubplotSpec from matplotlib import rcParams, rcParamsDefault, get_backend, rcParamsOrig from matplotlib.rcsetup import interactive_bk as _interactive_bk from matplotlib.artist import Artist from matplotlib.axes import Axes, Subplot from matplotlib.projections import PolarAxes from matplotlib import mlab from matplotlib.scale import get_scale_names from matplotlib import cm from matplotlib.cm import _colormaps as colormaps, register_cmap from matplotlib.colors import _color_sequences as color_sequences import numpy as np from matplotlib.colors import Normalize from matplotlib.lines import Line2D from matplotlib.text import Text, Annotation from matplotlib.patches import Polygon, Rectangle, Circle, Arrow from matplotlib.widgets import Button, Slider, Widget from .ticker import ( TickHelper, Formatter, FixedFormatter, NullFormatter, FuncFormatter, FormatStrFormatter, ScalarFormatter, LogFormatter, LogFormatterExponent, LogFormatterMathtext, Locator, IndexLocator, FixedLocator, NullLocator, LinearLocator, LogLocator, AutoLocator, MultipleLocator, MaxNLocator) def figure(num=None, # autoincrement if None, else integer from 1-N figsize=None, # defaults to rc figure.figsize dpi=None, # defaults to rc figure.dpi facecolor=None, # defaults to rc figure.facecolor edgecolor=None, # defaults to rc figure.edgecolor frameon=True, FigureClass=Figure, clear=False, **kwargs ): """ Create a new figure, or activate an existing figure. Parameters ---------- num : int or str or `.Figure` or `.SubFigure`, optional A unique identifier for the figure. If a figure with that identifier already exists, this figure is made active and returned. An integer refers to the ``Figure.number`` attribute, a string refers to the figure label. If there is no figure with the identifier or *num* is not given, a new figure is created, made active and returned. If *num* is an int, it will be used for the ``Figure.number`` attribute, otherwise, an auto-generated integer value is used (starting at 1 and incremented for each new figure). If *num* is a string, the figure label and the window title is set to this value. If num is a ``SubFigure``, its parent ``Figure`` is activated. figsize : (float, float), default: :rc:`figure.figsize` Width, height in inches. dpi : float, default: :rc:`figure.dpi` The resolution of the figure in dots-per-inch. facecolor : color, default: :rc:`figure.facecolor` The background color. edgecolor : color, default: :rc:`figure.edgecolor` The border color. frameon : bool, default: True If False, suppress drawing the figure frame. FigureClass : subclass of `~matplotlib.figure.Figure` If set, an instance of this subclass will be created, rather than a plain `.Figure`. clear : bool, default: False If True and the figure already exists, then it is cleared. layout : {'constrained', 'compressed', 'tight', 'none', `.LayoutEngine`, None}, \ default: None The layout mechanism for positioning of plot elements to avoid overlapping Axes decorations (labels, ticks, etc). Note that layout managers can measurably slow down figure display. - 'constrained': The constrained layout solver adjusts axes sizes to avoid overlapping axes decorations. Can handle complex plot layouts and colorbars, and is thus recommended. See :doc:`/tutorials/intermediate/constrainedlayout_guide` for examples. - 'compressed': uses the same algorithm as 'constrained', but removes extra space between fixed-aspect-ratio Axes. Best for simple grids of axes. - 'tight': Use the tight layout mechanism. This is a relatively simple algorithm that adjusts the subplot parameters so that decorations do not overlap. See `.Figure.set_tight_layout` for further details. - 'none': Do not use a layout engine. - A `.LayoutEngine` instance. Builtin layout classes are `.ConstrainedLayoutEngine` and `.TightLayoutEngine`, more easily accessible by 'constrained' and 'tight'. Passing an instance allows third parties to provide their own layout engine. If not given, fall back to using the parameters *tight_layout* and *constrained_layout*, including their config defaults :rc:`figure.autolayout` and :rc:`figure.constrained_layout.use`. **kwargs Additional keyword arguments are passed to the `.Figure` constructor. Returns ------- `~matplotlib.figure.Figure` Notes ----- A newly created figure is passed to the `~.FigureCanvasBase.new_manager` method or the `new_figure_manager` function provided by the current backend, which install a canvas and a manager on the figure. Once this is done, :rc:`figure.hooks` are called, one at a time, on the figure; these hooks allow arbitrary customization of the figure (e.g., attaching callbacks) or of associated elements (e.g., modifying the toolbar). See :doc:`/gallery/user_interfaces/mplcvd` for an example of toolbar customization. If you are creating many figures, make sure you explicitly call `.pyplot.close` on the figures you are not using, because this will enable pyplot to properly clean up the memory. `~matplotlib.rcParams` defines the default values, which can be modified in the matplotlibrc file. """ if isinstance(num, FigureBase): if num.canvas.manager is None: raise ValueError("The passed figure is not managed by pyplot") _pylab_helpers.Gcf.set_active(num.canvas.manager) return num.figure allnums = get_fignums() next_num = max(allnums) + 1 if allnums else 1 fig_label = '' if num is None: num = next_num elif isinstance(num, str): fig_label = num all_labels = get_figlabels() if fig_label not in all_labels: if fig_label == 'all': _api.warn_external("close('all') closes all existing figures.") num = next_num else: inum = all_labels.index(fig_label) num = allnums[inum] else: num = int(num) # crude validation of num argument manager = _pylab_helpers.Gcf.get_fig_manager(num) if manager is None: max_open_warning = rcParams['figure.max_open_warning'] if len(allnums) == max_open_warning >= 1: _api.warn_external( f"More than {max_open_warning} figures have been opened. " f"Figures created through the pyplot interface " f"(`matplotlib.pyplot.figure`) are retained until explicitly " f"closed and may consume too much memory. (To control this " f"warning, see the rcParam `figure.max_open_warning`). " f"Consider using `matplotlib.pyplot.close()`.", RuntimeWarning) manager = new_figure_manager( num, figsize=figsize, dpi=dpi, facecolor=facecolor, edgecolor=edgecolor, frameon=frameon, FigureClass=FigureClass, **kwargs) fig = manager.canvas.figure if fig_label: fig.set_label(fig_label) for hookspecs in rcParams["figure.hooks"]: module_name, dotted_name = hookspecs.split(":") obj = importlib.import_module(module_name) for part in dotted_name.split("."): obj = getattr(obj, part) obj(fig) _pylab_helpers.Gcf._set_new_active_manager(manager) # make sure backends (inline) that we don't ship that expect this # to be called in plotting commands to make the figure call show # still work. There is probably a better way to do this in the # FigureManager base class. draw_if_interactive() if _REPL_DISPLAYHOOK is _ReplDisplayHook.PLAIN: fig.stale_callback = _auto_draw_if_interactive if clear: manager.canvas.figure.clear() return manager.canvas.figure The provided code snippet includes necessary dependencies for implementing the `subplot_mosaic` function. Write a Python function `def subplot_mosaic(mosaic, *, sharex=False, sharey=False, width_ratios=None, height_ratios=None, empty_sentinel='.', subplot_kw=None, gridspec_kw=None, per_subplot_kw=None, **fig_kw)` to solve the following problem: Build a layout of Axes based on ASCII art or nested lists. This is a helper function to build complex GridSpec layouts visually. See :doc:`/gallery/subplots_axes_and_figures/mosaic` for an example and full API documentation Parameters ---------- mosaic : list of list of {hashable or nested} or str A visual layout of how you want your Axes to be arranged labeled as strings. For example :: x = [['A panel', 'A panel', 'edge'], ['C panel', '.', 'edge']] produces 4 axes: - 'A panel' which is 1 row high and spans the first two columns - 'edge' which is 2 rows high and is on the right edge - 'C panel' which in 1 row and 1 column wide in the bottom left - a blank space 1 row and 1 column wide in the bottom center Any of the entries in the layout can be a list of lists of the same form to create nested layouts. If input is a str, then it must be of the form :: ''' AAE C.E ''' where each character is a column and each line is a row. This only allows only single character Axes labels and does not allow nesting but is very terse. sharex, sharey : bool, default: False If True, the x-axis (*sharex*) or y-axis (*sharey*) will be shared among all subplots. In that case, tick label visibility and axis units behave as for `subplots`. If False, each subplot's x- or y-axis will be independent. width_ratios : array-like of length *ncols*, optional Defines the relative widths of the columns. Each column gets a relative width of ``width_ratios[i] / sum(width_ratios)``. If not given, all columns will have the same width. Convenience for ``gridspec_kw={'width_ratios': [...]}``. height_ratios : array-like of length *nrows*, optional Defines the relative heights of the rows. Each row gets a relative height of ``height_ratios[i] / sum(height_ratios)``. If not given, all rows will have the same height. Convenience for ``gridspec_kw={'height_ratios': [...]}``. empty_sentinel : object, optional Entry in the layout to mean "leave this space empty". Defaults to ``'.'``. Note, if *layout* is a string, it is processed via `inspect.cleandoc` to remove leading white space, which may interfere with using white-space as the empty sentinel. subplot_kw : dict, optional Dictionary with keywords passed to the `.Figure.add_subplot` call used to create each subplot. These values may be overridden by values in *per_subplot_kw*. per_subplot_kw : dict, optional A dictionary mapping the Axes identifiers or tuples of identifiers to a dictionary of keyword arguments to be passed to the `.Figure.add_subplot` call used to create each subplot. The values in these dictionaries have precedence over the values in *subplot_kw*. If *mosaic* is a string, and thus all keys are single characters, it is possible to use a single string instead of a tuple as keys; i.e. ``"AB"`` is equivalent to ``("A", "B")``. .. versionadded:: 3.7 gridspec_kw : dict, optional Dictionary with keywords passed to the `.GridSpec` constructor used to create the grid the subplots are placed on. **fig_kw All additional keyword arguments are passed to the `.pyplot.figure` call. Returns ------- fig : `.Figure` The new figure dict[label, Axes] A dictionary mapping the labels to the Axes objects. The order of the axes is left-to-right and top-to-bottom of their position in the total layout. Here is the function: def subplot_mosaic(mosaic, *, sharex=False, sharey=False, width_ratios=None, height_ratios=None, empty_sentinel='.', subplot_kw=None, gridspec_kw=None, per_subplot_kw=None, **fig_kw): """ Build a layout of Axes based on ASCII art or nested lists. This is a helper function to build complex GridSpec layouts visually. See :doc:`/gallery/subplots_axes_and_figures/mosaic` for an example and full API documentation Parameters ---------- mosaic : list of list of {hashable or nested} or str A visual layout of how you want your Axes to be arranged labeled as strings. For example :: x = [['A panel', 'A panel', 'edge'], ['C panel', '.', 'edge']] produces 4 axes: - 'A panel' which is 1 row high and spans the first two columns - 'edge' which is 2 rows high and is on the right edge - 'C panel' which in 1 row and 1 column wide in the bottom left - a blank space 1 row and 1 column wide in the bottom center Any of the entries in the layout can be a list of lists of the same form to create nested layouts. If input is a str, then it must be of the form :: ''' AAE C.E ''' where each character is a column and each line is a row. This only allows only single character Axes labels and does not allow nesting but is very terse. sharex, sharey : bool, default: False If True, the x-axis (*sharex*) or y-axis (*sharey*) will be shared among all subplots. In that case, tick label visibility and axis units behave as for `subplots`. If False, each subplot's x- or y-axis will be independent. width_ratios : array-like of length *ncols*, optional Defines the relative widths of the columns. Each column gets a relative width of ``width_ratios[i] / sum(width_ratios)``. If not given, all columns will have the same width. Convenience for ``gridspec_kw={'width_ratios': [...]}``. height_ratios : array-like of length *nrows*, optional Defines the relative heights of the rows. Each row gets a relative height of ``height_ratios[i] / sum(height_ratios)``. If not given, all rows will have the same height. Convenience for ``gridspec_kw={'height_ratios': [...]}``. empty_sentinel : object, optional Entry in the layout to mean "leave this space empty". Defaults to ``'.'``. Note, if *layout* is a string, it is processed via `inspect.cleandoc` to remove leading white space, which may interfere with using white-space as the empty sentinel. subplot_kw : dict, optional Dictionary with keywords passed to the `.Figure.add_subplot` call used to create each subplot. These values may be overridden by values in *per_subplot_kw*. per_subplot_kw : dict, optional A dictionary mapping the Axes identifiers or tuples of identifiers to a dictionary of keyword arguments to be passed to the `.Figure.add_subplot` call used to create each subplot. The values in these dictionaries have precedence over the values in *subplot_kw*. If *mosaic* is a string, and thus all keys are single characters, it is possible to use a single string instead of a tuple as keys; i.e. ``"AB"`` is equivalent to ``("A", "B")``. .. versionadded:: 3.7 gridspec_kw : dict, optional Dictionary with keywords passed to the `.GridSpec` constructor used to create the grid the subplots are placed on. **fig_kw All additional keyword arguments are passed to the `.pyplot.figure` call. Returns ------- fig : `.Figure` The new figure dict[label, Axes] A dictionary mapping the labels to the Axes objects. The order of the axes is left-to-right and top-to-bottom of their position in the total layout. """ fig = figure(**fig_kw) ax_dict = fig.subplot_mosaic( mosaic, sharex=sharex, sharey=sharey, height_ratios=height_ratios, width_ratios=width_ratios, subplot_kw=subplot_kw, gridspec_kw=gridspec_kw, empty_sentinel=empty_sentinel, per_subplot_kw=per_subplot_kw, ) return fig, ax_dict
Build a layout of Axes based on ASCII art or nested lists. This is a helper function to build complex GridSpec layouts visually. See :doc:`/gallery/subplots_axes_and_figures/mosaic` for an example and full API documentation Parameters ---------- mosaic : list of list of {hashable or nested} or str A visual layout of how you want your Axes to be arranged labeled as strings. For example :: x = [['A panel', 'A panel', 'edge'], ['C panel', '.', 'edge']] produces 4 axes: - 'A panel' which is 1 row high and spans the first two columns - 'edge' which is 2 rows high and is on the right edge - 'C panel' which in 1 row and 1 column wide in the bottom left - a blank space 1 row and 1 column wide in the bottom center Any of the entries in the layout can be a list of lists of the same form to create nested layouts. If input is a str, then it must be of the form :: ''' AAE C.E ''' where each character is a column and each line is a row. This only allows only single character Axes labels and does not allow nesting but is very terse. sharex, sharey : bool, default: False If True, the x-axis (*sharex*) or y-axis (*sharey*) will be shared among all subplots. In that case, tick label visibility and axis units behave as for `subplots`. If False, each subplot's x- or y-axis will be independent. width_ratios : array-like of length *ncols*, optional Defines the relative widths of the columns. Each column gets a relative width of ``width_ratios[i] / sum(width_ratios)``. If not given, all columns will have the same width. Convenience for ``gridspec_kw={'width_ratios': [...]}``. height_ratios : array-like of length *nrows*, optional Defines the relative heights of the rows. Each row gets a relative height of ``height_ratios[i] / sum(height_ratios)``. If not given, all rows will have the same height. Convenience for ``gridspec_kw={'height_ratios': [...]}``. empty_sentinel : object, optional Entry in the layout to mean "leave this space empty". Defaults to ``'.'``. Note, if *layout* is a string, it is processed via `inspect.cleandoc` to remove leading white space, which may interfere with using white-space as the empty sentinel. subplot_kw : dict, optional Dictionary with keywords passed to the `.Figure.add_subplot` call used to create each subplot. These values may be overridden by values in *per_subplot_kw*. per_subplot_kw : dict, optional A dictionary mapping the Axes identifiers or tuples of identifiers to a dictionary of keyword arguments to be passed to the `.Figure.add_subplot` call used to create each subplot. The values in these dictionaries have precedence over the values in *subplot_kw*. If *mosaic* is a string, and thus all keys are single characters, it is possible to use a single string instead of a tuple as keys; i.e. ``"AB"`` is equivalent to ``("A", "B")``. .. versionadded:: 3.7 gridspec_kw : dict, optional Dictionary with keywords passed to the `.GridSpec` constructor used to create the grid the subplots are placed on. **fig_kw All additional keyword arguments are passed to the `.pyplot.figure` call. Returns ------- fig : `.Figure` The new figure dict[label, Axes] A dictionary mapping the labels to the Axes objects. The order of the axes is left-to-right and top-to-bottom of their position in the total layout.
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from contextlib import ExitStack from enum import Enum import functools import importlib import inspect import logging from numbers import Number import re import sys import threading import time from cycler import cycler import matplotlib import matplotlib.colorbar import matplotlib.image from matplotlib import _api from matplotlib import rcsetup, style from matplotlib import _pylab_helpers, interactive from matplotlib import cbook from matplotlib import _docstring from matplotlib.backend_bases import ( FigureCanvasBase, FigureManagerBase, MouseButton) from matplotlib.figure import Figure, FigureBase, figaspect from matplotlib.gridspec import GridSpec, SubplotSpec from matplotlib import rcParams, rcParamsDefault, get_backend, rcParamsOrig from matplotlib.rcsetup import interactive_bk as _interactive_bk from matplotlib.artist import Artist from matplotlib.axes import Axes, Subplot from matplotlib.projections import PolarAxes from matplotlib import mlab from matplotlib.scale import get_scale_names from matplotlib import cm from matplotlib.cm import _colormaps as colormaps, register_cmap from matplotlib.colors import _color_sequences as color_sequences import numpy as np from matplotlib.colors import Normalize from matplotlib.lines import Line2D from matplotlib.text import Text, Annotation from matplotlib.patches import Polygon, Rectangle, Circle, Arrow from matplotlib.widgets import Button, Slider, Widget from .ticker import ( TickHelper, Formatter, FixedFormatter, NullFormatter, FuncFormatter, FormatStrFormatter, ScalarFormatter, LogFormatter, LogFormatterExponent, LogFormatterMathtext, Locator, IndexLocator, FixedLocator, NullLocator, LinearLocator, LogLocator, AutoLocator, MultipleLocator, MaxNLocator) def gcf(): """ Get the current figure. If there is currently no figure on the pyplot figure stack, a new one is created using `~.pyplot.figure()`. (To test whether there is currently a figure on the pyplot figure stack, check whether `~.pyplot.get_fignums()` is empty.) """ manager = _pylab_helpers.Gcf.get_active() if manager is not None: return manager.canvas.figure else: return figure() def axes(arg=None, **kwargs): """ Add an Axes to the current figure and make it the current Axes. Call signatures:: plt.axes() plt.axes(rect, projection=None, polar=False, **kwargs) plt.axes(ax) Parameters ---------- arg : None or 4-tuple The exact behavior of this function depends on the type: - *None*: A new full window Axes is added using ``subplot(**kwargs)``. - 4-tuple of floats *rect* = ``[left, bottom, width, height]``. A new Axes is added with dimensions *rect* in normalized (0, 1) units using `~.Figure.add_axes` on the current figure. projection : {None, 'aitoff', 'hammer', 'lambert', 'mollweide', \ 'polar', 'rectilinear', str}, optional The projection type of the `~.axes.Axes`. *str* is the name of a custom projection, see `~matplotlib.projections`. The default None results in a 'rectilinear' projection. polar : bool, default: False If True, equivalent to projection='polar'. sharex, sharey : `~.axes.Axes`, optional Share the x or y `~matplotlib.axis` with sharex and/or sharey. The axis will have the same limits, ticks, and scale as the axis of the shared Axes. label : str A label for the returned Axes. Returns ------- `~.axes.Axes`, or a subclass of `~.axes.Axes` The returned axes class depends on the projection used. It is `~.axes.Axes` if rectilinear projection is used and `.projections.polar.PolarAxes` if polar projection is used. Other Parameters ---------------- **kwargs This method also takes the keyword arguments for the returned Axes class. The keyword arguments for the rectilinear Axes class `~.axes.Axes` can be found in the following table but there might also be other keyword arguments if another projection is used, see the actual Axes class. %(Axes:kwdoc)s See Also -------- .Figure.add_axes .pyplot.subplot .Figure.add_subplot .Figure.subplots .pyplot.subplots Examples -------- :: # Creating a new full window Axes plt.axes() # Creating a new Axes with specified dimensions and a grey background plt.axes((left, bottom, width, height), facecolor='grey') """ fig = gcf() pos = kwargs.pop('position', None) if arg is None: if pos is None: return fig.add_subplot(**kwargs) else: return fig.add_axes(pos, **kwargs) else: return fig.add_axes(arg, **kwargs) def delaxes(ax=None): """ Remove an `~.axes.Axes` (defaulting to the current axes) from its figure. """ if ax is None: ax = gca() ax.remove() class GridSpec(GridSpecBase): """ A grid layout to place subplots within a figure. The location of the grid cells is determined in a similar way to `~.figure.SubplotParams` using *left*, *right*, *top*, *bottom*, *wspace* and *hspace*. Indexing a GridSpec instance returns a `.SubplotSpec`. """ def __init__(self, nrows, ncols, figure=None, left=None, bottom=None, right=None, top=None, wspace=None, hspace=None, width_ratios=None, height_ratios=None): """ Parameters ---------- nrows, ncols : int The number of rows and columns of the grid. figure : `.Figure`, optional Only used for constrained layout to create a proper layoutgrid. left, right, top, bottom : float, optional Extent of the subplots as a fraction of figure width or height. Left cannot be larger than right, and bottom cannot be larger than top. If not given, the values will be inferred from a figure or rcParams at draw time. See also `GridSpec.get_subplot_params`. wspace : float, optional The amount of width reserved for space between subplots, expressed as a fraction of the average axis width. If not given, the values will be inferred from a figure or rcParams when necessary. See also `GridSpec.get_subplot_params`. hspace : float, optional The amount of height reserved for space between subplots, expressed as a fraction of the average axis height. If not given, the values will be inferred from a figure or rcParams when necessary. See also `GridSpec.get_subplot_params`. width_ratios : array-like of length *ncols*, optional Defines the relative widths of the columns. Each column gets a relative width of ``width_ratios[i] / sum(width_ratios)``. If not given, all columns will have the same width. height_ratios : array-like of length *nrows*, optional Defines the relative heights of the rows. Each row gets a relative height of ``height_ratios[i] / sum(height_ratios)``. If not given, all rows will have the same height. """ self.left = left self.bottom = bottom self.right = right self.top = top self.wspace = wspace self.hspace = hspace self.figure = figure super().__init__(nrows, ncols, width_ratios=width_ratios, height_ratios=height_ratios) _AllowedKeys = ["left", "bottom", "right", "top", "wspace", "hspace"] def update(self, **kwargs): """ Update the subplot parameters of the grid. Parameters that are not explicitly given are not changed. Setting a parameter to *None* resets it to :rc:`figure.subplot.*`. Parameters ---------- left, right, top, bottom : float or None, optional Extent of the subplots as a fraction of figure width or height. wspace, hspace : float, optional Spacing between the subplots as a fraction of the average subplot width / height. """ for k, v in kwargs.items(): if k in self._AllowedKeys: setattr(self, k, v) else: raise AttributeError(f"{k} is an unknown keyword") for figmanager in _pylab_helpers.Gcf.figs.values(): for ax in figmanager.canvas.figure.axes: if ax.get_subplotspec() is not None: ss = ax.get_subplotspec().get_topmost_subplotspec() if ss.get_gridspec() == self: ax._set_position( ax.get_subplotspec().get_position(ax.figure)) def get_subplot_params(self, figure=None): """ Return the `.SubplotParams` for the GridSpec. In order of precedence the values are taken from - non-*None* attributes of the GridSpec - the provided *figure* - :rc:`figure.subplot.*` """ if figure is None: kw = {k: mpl.rcParams["figure.subplot."+k] for k in self._AllowedKeys} subplotpars = mpl.figure.SubplotParams(**kw) else: subplotpars = copy.copy(figure.subplotpars) subplotpars.update(**{k: getattr(self, k) for k in self._AllowedKeys}) return subplotpars def locally_modified_subplot_params(self): """ Return a list of the names of the subplot parameters explicitly set in the GridSpec. This is a subset of the attributes of `.SubplotParams`. """ return [k for k in self._AllowedKeys if getattr(self, k)] def tight_layout(self, figure, renderer=None, pad=1.08, h_pad=None, w_pad=None, rect=None): """ Adjust subplot parameters to give specified padding. Parameters ---------- figure : `.Figure` The figure. renderer : `.RendererBase` subclass, optional The renderer to be used. pad : float Padding between the figure edge and the edges of subplots, as a fraction of the font-size. h_pad, w_pad : float, optional Padding (height/width) between edges of adjacent subplots. Defaults to *pad*. rect : tuple (left, bottom, right, top), default: None (left, bottom, right, top) rectangle in normalized figure coordinates that the whole subplots area (including labels) will fit into. Default (None) is the whole figure. """ if renderer is None: renderer = figure._get_renderer() kwargs = _tight_layout.get_tight_layout_figure( figure, figure.axes, _tight_layout.get_subplotspec_list(figure.axes, grid_spec=self), renderer, pad=pad, h_pad=h_pad, w_pad=w_pad, rect=rect) if kwargs: self.update(**kwargs) The provided code snippet includes necessary dependencies for implementing the `subplot2grid` function. Write a Python function `def subplot2grid(shape, loc, rowspan=1, colspan=1, fig=None, **kwargs)` to solve the following problem: Create a subplot at a specific location inside a regular grid. Parameters ---------- shape : (int, int) Number of rows and of columns of the grid in which to place axis. loc : (int, int) Row number and column number of the axis location within the grid. rowspan : int, default: 1 Number of rows for the axis to span downwards. colspan : int, default: 1 Number of columns for the axis to span to the right. fig : `.Figure`, optional Figure to place the subplot in. Defaults to the current figure. **kwargs Additional keyword arguments are handed to `~.Figure.add_subplot`. Returns ------- `~.axes.Axes` The Axes of the subplot. The returned Axes can actually be an instance of a subclass, such as `.projections.polar.PolarAxes` for polar projections. Notes ----- The following call :: ax = subplot2grid((nrows, ncols), (row, col), rowspan, colspan) is identical to :: fig = gcf() gs = fig.add_gridspec(nrows, ncols) ax = fig.add_subplot(gs[row:row+rowspan, col:col+colspan]) Here is the function: def subplot2grid(shape, loc, rowspan=1, colspan=1, fig=None, **kwargs): """ Create a subplot at a specific location inside a regular grid. Parameters ---------- shape : (int, int) Number of rows and of columns of the grid in which to place axis. loc : (int, int) Row number and column number of the axis location within the grid. rowspan : int, default: 1 Number of rows for the axis to span downwards. colspan : int, default: 1 Number of columns for the axis to span to the right. fig : `.Figure`, optional Figure to place the subplot in. Defaults to the current figure. **kwargs Additional keyword arguments are handed to `~.Figure.add_subplot`. Returns ------- `~.axes.Axes` The Axes of the subplot. The returned Axes can actually be an instance of a subclass, such as `.projections.polar.PolarAxes` for polar projections. Notes ----- The following call :: ax = subplot2grid((nrows, ncols), (row, col), rowspan, colspan) is identical to :: fig = gcf() gs = fig.add_gridspec(nrows, ncols) ax = fig.add_subplot(gs[row:row+rowspan, col:col+colspan]) """ if fig is None: fig = gcf() rows, cols = shape gs = GridSpec._check_gridspec_exists(fig, rows, cols) subplotspec = gs.new_subplotspec(loc, rowspan=rowspan, colspan=colspan) ax = fig.add_subplot(subplotspec, **kwargs) axes_to_delete = [other for other in fig.axes if other != ax and ax.bbox.fully_overlaps(other.bbox)] if axes_to_delete: _api.warn_deprecated( "3.6", message="Auto-removal of overlapping axes is deprecated " "since %(since)s and will be removed %(removal)s; explicitly call " "ax.remove() as needed.") for ax_to_del in axes_to_delete: delaxes(ax_to_del) return ax
Create a subplot at a specific location inside a regular grid. Parameters ---------- shape : (int, int) Number of rows and of columns of the grid in which to place axis. loc : (int, int) Row number and column number of the axis location within the grid. rowspan : int, default: 1 Number of rows for the axis to span downwards. colspan : int, default: 1 Number of columns for the axis to span to the right. fig : `.Figure`, optional Figure to place the subplot in. Defaults to the current figure. **kwargs Additional keyword arguments are handed to `~.Figure.add_subplot`. Returns ------- `~.axes.Axes` The Axes of the subplot. The returned Axes can actually be an instance of a subclass, such as `.projections.polar.PolarAxes` for polar projections. Notes ----- The following call :: ax = subplot2grid((nrows, ncols), (row, col), rowspan, colspan) is identical to :: fig = gcf() gs = fig.add_gridspec(nrows, ncols) ax = fig.add_subplot(gs[row:row+rowspan, col:col+colspan])
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from contextlib import ExitStack from enum import Enum import functools import importlib import inspect import logging from numbers import Number import re import sys import threading import time from cycler import cycler import matplotlib import matplotlib.colorbar import matplotlib.image from matplotlib import _api from matplotlib import rcsetup, style from matplotlib import _pylab_helpers, interactive from matplotlib import cbook from matplotlib import _docstring from matplotlib.backend_bases import ( FigureCanvasBase, FigureManagerBase, MouseButton) from matplotlib.figure import Figure, FigureBase, figaspect from matplotlib.gridspec import GridSpec, SubplotSpec from matplotlib import rcParams, rcParamsDefault, get_backend, rcParamsOrig from matplotlib.rcsetup import interactive_bk as _interactive_bk from matplotlib.artist import Artist from matplotlib.axes import Axes, Subplot from matplotlib.projections import PolarAxes from matplotlib import mlab from matplotlib.scale import get_scale_names from matplotlib import cm from matplotlib.cm import _colormaps as colormaps, register_cmap from matplotlib.colors import _color_sequences as color_sequences import numpy as np from matplotlib.colors import Normalize from matplotlib.lines import Line2D from matplotlib.text import Text, Annotation from matplotlib.patches import Polygon, Rectangle, Circle, Arrow from matplotlib.widgets import Button, Slider, Widget from .ticker import ( TickHelper, Formatter, FixedFormatter, NullFormatter, FuncFormatter, FormatStrFormatter, ScalarFormatter, LogFormatter, LogFormatterExponent, LogFormatterMathtext, Locator, IndexLocator, FixedLocator, NullLocator, LinearLocator, LogLocator, AutoLocator, MultipleLocator, MaxNLocator) def gca(): return gcf().gca() The provided code snippet includes necessary dependencies for implementing the `twinx` function. Write a Python function `def twinx(ax=None)` to solve the following problem: Make and return a second axes that shares the *x*-axis. The new axes will overlay *ax* (or the current axes if *ax* is *None*), and its ticks will be on the right. Examples -------- :doc:`/gallery/subplots_axes_and_figures/two_scales` Here is the function: def twinx(ax=None): """ Make and return a second axes that shares the *x*-axis. The new axes will overlay *ax* (or the current axes if *ax* is *None*), and its ticks will be on the right. Examples -------- :doc:`/gallery/subplots_axes_and_figures/two_scales` """ if ax is None: ax = gca() ax1 = ax.twinx() return ax1
Make and return a second axes that shares the *x*-axis. The new axes will overlay *ax* (or the current axes if *ax* is *None*), and its ticks will be on the right. Examples -------- :doc:`/gallery/subplots_axes_and_figures/two_scales`
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from contextlib import ExitStack from enum import Enum import functools import importlib import inspect import logging from numbers import Number import re import sys import threading import time from cycler import cycler import matplotlib import matplotlib.colorbar import matplotlib.image from matplotlib import _api from matplotlib import rcsetup, style from matplotlib import _pylab_helpers, interactive from matplotlib import cbook from matplotlib import _docstring from matplotlib.backend_bases import ( FigureCanvasBase, FigureManagerBase, MouseButton) from matplotlib.figure import Figure, FigureBase, figaspect from matplotlib.gridspec import GridSpec, SubplotSpec from matplotlib import rcParams, rcParamsDefault, get_backend, rcParamsOrig from matplotlib.rcsetup import interactive_bk as _interactive_bk from matplotlib.artist import Artist from matplotlib.axes import Axes, Subplot from matplotlib.projections import PolarAxes from matplotlib import mlab from matplotlib.scale import get_scale_names from matplotlib import cm from matplotlib.cm import _colormaps as colormaps, register_cmap from matplotlib.colors import _color_sequences as color_sequences import numpy as np from matplotlib.colors import Normalize from matplotlib.lines import Line2D from matplotlib.text import Text, Annotation from matplotlib.patches import Polygon, Rectangle, Circle, Arrow from matplotlib.widgets import Button, Slider, Widget from .ticker import ( TickHelper, Formatter, FixedFormatter, NullFormatter, FuncFormatter, FormatStrFormatter, ScalarFormatter, LogFormatter, LogFormatterExponent, LogFormatterMathtext, Locator, IndexLocator, FixedLocator, NullLocator, LinearLocator, LogLocator, AutoLocator, MultipleLocator, MaxNLocator) def gca(): return gcf().gca() The provided code snippet includes necessary dependencies for implementing the `twiny` function. Write a Python function `def twiny(ax=None)` to solve the following problem: Make and return a second axes that shares the *y*-axis. The new axes will overlay *ax* (or the current axes if *ax* is *None*), and its ticks will be on the top. Examples -------- :doc:`/gallery/subplots_axes_and_figures/two_scales` Here is the function: def twiny(ax=None): """ Make and return a second axes that shares the *y*-axis. The new axes will overlay *ax* (or the current axes if *ax* is *None*), and its ticks will be on the top. Examples -------- :doc:`/gallery/subplots_axes_and_figures/two_scales` """ if ax is None: ax = gca() ax1 = ax.twiny() return ax1
Make and return a second axes that shares the *y*-axis. The new axes will overlay *ax* (or the current axes if *ax* is *None*), and its ticks will be on the top. Examples -------- :doc:`/gallery/subplots_axes_and_figures/two_scales`
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from contextlib import ExitStack from enum import Enum import functools import importlib import inspect import logging from numbers import Number import re import sys import threading import time from cycler import cycler import matplotlib import matplotlib.colorbar import matplotlib.image from matplotlib import _api from matplotlib import rcsetup, style from matplotlib import _pylab_helpers, interactive from matplotlib import cbook from matplotlib import _docstring from matplotlib.backend_bases import ( FigureCanvasBase, FigureManagerBase, MouseButton) from matplotlib.figure import Figure, FigureBase, figaspect from matplotlib.gridspec import GridSpec, SubplotSpec from matplotlib import rcParams, rcParamsDefault, get_backend, rcParamsOrig from matplotlib.rcsetup import interactive_bk as _interactive_bk from matplotlib.artist import Artist from matplotlib.axes import Axes, Subplot from matplotlib.projections import PolarAxes from matplotlib import mlab from matplotlib.scale import get_scale_names from matplotlib import cm from matplotlib.cm import _colormaps as colormaps, register_cmap from matplotlib.colors import _color_sequences as color_sequences import numpy as np from matplotlib.colors import Normalize from matplotlib.lines import Line2D from matplotlib.text import Text, Annotation from matplotlib.patches import Polygon, Rectangle, Circle, Arrow from matplotlib.widgets import Button, Slider, Widget from .ticker import ( TickHelper, Formatter, FixedFormatter, NullFormatter, FuncFormatter, FormatStrFormatter, ScalarFormatter, LogFormatter, LogFormatterExponent, LogFormatterMathtext, Locator, IndexLocator, FixedLocator, NullLocator, LinearLocator, LogLocator, AutoLocator, MultipleLocator, MaxNLocator) def gcf(): """ Get the current figure. If there is currently no figure on the pyplot figure stack, a new one is created using `~.pyplot.figure()`. (To test whether there is currently a figure on the pyplot figure stack, check whether `~.pyplot.get_fignums()` is empty.) """ manager = _pylab_helpers.Gcf.get_active() if manager is not None: return manager.canvas.figure else: return figure() The provided code snippet includes necessary dependencies for implementing the `subplot_tool` function. Write a Python function `def subplot_tool(targetfig=None)` to solve the following problem: Launch a subplot tool window for a figure. Returns ------- `matplotlib.widgets.SubplotTool` Here is the function: def subplot_tool(targetfig=None): """ Launch a subplot tool window for a figure. Returns ------- `matplotlib.widgets.SubplotTool` """ if targetfig is None: targetfig = gcf() tb = targetfig.canvas.manager.toolbar if hasattr(tb, "configure_subplots"): # toolbar2 return tb.configure_subplots() elif hasattr(tb, "trigger_tool"): # toolmanager return tb.trigger_tool("subplots") else: raise ValueError("subplot_tool can only be launched for figures with " "an associated toolbar")
Launch a subplot tool window for a figure. Returns ------- `matplotlib.widgets.SubplotTool`
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from contextlib import ExitStack from enum import Enum import functools import importlib import inspect import logging from numbers import Number import re import sys import threading import time from cycler import cycler import matplotlib import matplotlib.colorbar import matplotlib.image from matplotlib import _api from matplotlib import rcsetup, style from matplotlib import _pylab_helpers, interactive from matplotlib import cbook from matplotlib import _docstring from matplotlib.backend_bases import ( FigureCanvasBase, FigureManagerBase, MouseButton) from matplotlib.figure import Figure, FigureBase, figaspect from matplotlib.gridspec import GridSpec, SubplotSpec from matplotlib import rcParams, rcParamsDefault, get_backend, rcParamsOrig from matplotlib.rcsetup import interactive_bk as _interactive_bk from matplotlib.artist import Artist from matplotlib.axes import Axes, Subplot from matplotlib.projections import PolarAxes from matplotlib import mlab from matplotlib.scale import get_scale_names from matplotlib import cm from matplotlib.cm import _colormaps as colormaps, register_cmap from matplotlib.colors import _color_sequences as color_sequences import numpy as np from matplotlib.colors import Normalize from matplotlib.lines import Line2D from matplotlib.text import Text, Annotation from matplotlib.patches import Polygon, Rectangle, Circle, Arrow from matplotlib.widgets import Button, Slider, Widget from .ticker import ( TickHelper, Formatter, FixedFormatter, NullFormatter, FuncFormatter, FormatStrFormatter, ScalarFormatter, LogFormatter, LogFormatterExponent, LogFormatterMathtext, Locator, IndexLocator, FixedLocator, NullLocator, LinearLocator, LogLocator, AutoLocator, MultipleLocator, MaxNLocator) def gca(): return gcf().gca() The provided code snippet includes necessary dependencies for implementing the `box` function. Write a Python function `def box(on=None)` to solve the following problem: Turn the axes box on or off on the current axes. Parameters ---------- on : bool or None The new `~matplotlib.axes.Axes` box state. If ``None``, toggle the state. See Also -------- :meth:`matplotlib.axes.Axes.set_frame_on` :meth:`matplotlib.axes.Axes.get_frame_on` Here is the function: def box(on=None): """ Turn the axes box on or off on the current axes. Parameters ---------- on : bool or None The new `~matplotlib.axes.Axes` box state. If ``None``, toggle the state. See Also -------- :meth:`matplotlib.axes.Axes.set_frame_on` :meth:`matplotlib.axes.Axes.get_frame_on` """ ax = gca() if on is None: on = not ax.get_frame_on() ax.set_frame_on(on)
Turn the axes box on or off on the current axes. Parameters ---------- on : bool or None The new `~matplotlib.axes.Axes` box state. If ``None``, toggle the state. See Also -------- :meth:`matplotlib.axes.Axes.set_frame_on` :meth:`matplotlib.axes.Axes.get_frame_on`
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from contextlib import ExitStack from enum import Enum import functools import importlib import inspect import logging from numbers import Number import re import sys import threading import time from cycler import cycler import matplotlib import matplotlib.colorbar import matplotlib.image from matplotlib import _api from matplotlib import rcsetup, style from matplotlib import _pylab_helpers, interactive from matplotlib import cbook from matplotlib import _docstring from matplotlib.backend_bases import ( FigureCanvasBase, FigureManagerBase, MouseButton) from matplotlib.figure import Figure, FigureBase, figaspect from matplotlib.gridspec import GridSpec, SubplotSpec from matplotlib import rcParams, rcParamsDefault, get_backend, rcParamsOrig from matplotlib.rcsetup import interactive_bk as _interactive_bk from matplotlib.artist import Artist from matplotlib.axes import Axes, Subplot from matplotlib.projections import PolarAxes from matplotlib import mlab from matplotlib.scale import get_scale_names from matplotlib import cm from matplotlib.cm import _colormaps as colormaps, register_cmap from matplotlib.colors import _color_sequences as color_sequences import numpy as np from matplotlib.colors import Normalize from matplotlib.lines import Line2D from matplotlib.text import Text, Annotation from matplotlib.patches import Polygon, Rectangle, Circle, Arrow from matplotlib.widgets import Button, Slider, Widget from .ticker import ( TickHelper, Formatter, FixedFormatter, NullFormatter, FuncFormatter, FormatStrFormatter, ScalarFormatter, LogFormatter, LogFormatterExponent, LogFormatterMathtext, Locator, IndexLocator, FixedLocator, NullLocator, LinearLocator, LogLocator, AutoLocator, MultipleLocator, MaxNLocator) def gca(): return gcf().gca() The provided code snippet includes necessary dependencies for implementing the `rgrids` function. Write a Python function `def rgrids(radii=None, labels=None, angle=None, fmt=None, **kwargs)` to solve the following problem: Get or set the radial gridlines on the current polar plot. Call signatures:: lines, labels = rgrids() lines, labels = rgrids(radii, labels=None, angle=22.5, fmt=None, **kwargs) When called with no arguments, `.rgrids` simply returns the tuple (*lines*, *labels*). When called with arguments, the labels will appear at the specified radial distances and angle. Parameters ---------- radii : tuple with floats The radii for the radial gridlines labels : tuple with strings or None The labels to use at each radial gridline. The `matplotlib.ticker.ScalarFormatter` will be used if None. angle : float The angular position of the radius labels in degrees. fmt : str or None Format string used in `matplotlib.ticker.FormatStrFormatter`. For example '%f'. Returns ------- lines : list of `.lines.Line2D` The radial gridlines. labels : list of `.text.Text` The tick labels. Other Parameters ---------------- **kwargs *kwargs* are optional `.Text` properties for the labels. See Also -------- .pyplot.thetagrids .projections.polar.PolarAxes.set_rgrids .Axis.get_gridlines .Axis.get_ticklabels Examples -------- :: # set the locations of the radial gridlines lines, labels = rgrids( (0.25, 0.5, 1.0) ) # set the locations and labels of the radial gridlines lines, labels = rgrids( (0.25, 0.5, 1.0), ('Tom', 'Dick', 'Harry' )) Here is the function: def rgrids(radii=None, labels=None, angle=None, fmt=None, **kwargs): """ Get or set the radial gridlines on the current polar plot. Call signatures:: lines, labels = rgrids() lines, labels = rgrids(radii, labels=None, angle=22.5, fmt=None, **kwargs) When called with no arguments, `.rgrids` simply returns the tuple (*lines*, *labels*). When called with arguments, the labels will appear at the specified radial distances and angle. Parameters ---------- radii : tuple with floats The radii for the radial gridlines labels : tuple with strings or None The labels to use at each radial gridline. The `matplotlib.ticker.ScalarFormatter` will be used if None. angle : float The angular position of the radius labels in degrees. fmt : str or None Format string used in `matplotlib.ticker.FormatStrFormatter`. For example '%f'. Returns ------- lines : list of `.lines.Line2D` The radial gridlines. labels : list of `.text.Text` The tick labels. Other Parameters ---------------- **kwargs *kwargs* are optional `.Text` properties for the labels. See Also -------- .pyplot.thetagrids .projections.polar.PolarAxes.set_rgrids .Axis.get_gridlines .Axis.get_ticklabels Examples -------- :: # set the locations of the radial gridlines lines, labels = rgrids( (0.25, 0.5, 1.0) ) # set the locations and labels of the radial gridlines lines, labels = rgrids( (0.25, 0.5, 1.0), ('Tom', 'Dick', 'Harry' )) """ ax = gca() if not isinstance(ax, PolarAxes): raise RuntimeError('rgrids only defined for polar axes') if all(p is None for p in [radii, labels, angle, fmt]) and not kwargs: lines = ax.yaxis.get_gridlines() labels = ax.yaxis.get_ticklabels() else: lines, labels = ax.set_rgrids( radii, labels=labels, angle=angle, fmt=fmt, **kwargs) return lines, labels
Get or set the radial gridlines on the current polar plot. Call signatures:: lines, labels = rgrids() lines, labels = rgrids(radii, labels=None, angle=22.5, fmt=None, **kwargs) When called with no arguments, `.rgrids` simply returns the tuple (*lines*, *labels*). When called with arguments, the labels will appear at the specified radial distances and angle. Parameters ---------- radii : tuple with floats The radii for the radial gridlines labels : tuple with strings or None The labels to use at each radial gridline. The `matplotlib.ticker.ScalarFormatter` will be used if None. angle : float The angular position of the radius labels in degrees. fmt : str or None Format string used in `matplotlib.ticker.FormatStrFormatter`. For example '%f'. Returns ------- lines : list of `.lines.Line2D` The radial gridlines. labels : list of `.text.Text` The tick labels. Other Parameters ---------------- **kwargs *kwargs* are optional `.Text` properties for the labels. See Also -------- .pyplot.thetagrids .projections.polar.PolarAxes.set_rgrids .Axis.get_gridlines .Axis.get_ticklabels Examples -------- :: # set the locations of the radial gridlines lines, labels = rgrids( (0.25, 0.5, 1.0) ) # set the locations and labels of the radial gridlines lines, labels = rgrids( (0.25, 0.5, 1.0), ('Tom', 'Dick', 'Harry' ))
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from contextlib import ExitStack from enum import Enum import functools import importlib import inspect import logging from numbers import Number import re import sys import threading import time from cycler import cycler import matplotlib import matplotlib.colorbar import matplotlib.image from matplotlib import _api from matplotlib import rcsetup, style from matplotlib import _pylab_helpers, interactive from matplotlib import cbook from matplotlib import _docstring from matplotlib.backend_bases import ( FigureCanvasBase, FigureManagerBase, MouseButton) from matplotlib.figure import Figure, FigureBase, figaspect from matplotlib.gridspec import GridSpec, SubplotSpec from matplotlib import rcParams, rcParamsDefault, get_backend, rcParamsOrig from matplotlib.rcsetup import interactive_bk as _interactive_bk from matplotlib.artist import Artist from matplotlib.axes import Axes, Subplot from matplotlib.projections import PolarAxes from matplotlib import mlab from matplotlib.scale import get_scale_names from matplotlib import cm from matplotlib.cm import _colormaps as colormaps, register_cmap from matplotlib.colors import _color_sequences as color_sequences import numpy as np from matplotlib.colors import Normalize from matplotlib.lines import Line2D from matplotlib.text import Text, Annotation from matplotlib.patches import Polygon, Rectangle, Circle, Arrow from matplotlib.widgets import Button, Slider, Widget from .ticker import ( TickHelper, Formatter, FixedFormatter, NullFormatter, FuncFormatter, FormatStrFormatter, ScalarFormatter, LogFormatter, LogFormatterExponent, LogFormatterMathtext, Locator, IndexLocator, FixedLocator, NullLocator, LinearLocator, LogLocator, AutoLocator, MultipleLocator, MaxNLocator) def gca(): return gcf().gca() The provided code snippet includes necessary dependencies for implementing the `thetagrids` function. Write a Python function `def thetagrids(angles=None, labels=None, fmt=None, **kwargs)` to solve the following problem: Get or set the theta gridlines on the current polar plot. Call signatures:: lines, labels = thetagrids() lines, labels = thetagrids(angles, labels=None, fmt=None, **kwargs) When called with no arguments, `.thetagrids` simply returns the tuple (*lines*, *labels*). When called with arguments, the labels will appear at the specified angles. Parameters ---------- angles : tuple with floats, degrees The angles of the theta gridlines. labels : tuple with strings or None The labels to use at each radial gridline. The `.projections.polar.ThetaFormatter` will be used if None. fmt : str or None Format string used in `matplotlib.ticker.FormatStrFormatter`. For example '%f'. Note that the angle in radians will be used. Returns ------- lines : list of `.lines.Line2D` The theta gridlines. labels : list of `.text.Text` The tick labels. Other Parameters ---------------- **kwargs *kwargs* are optional `.Text` properties for the labels. See Also -------- .pyplot.rgrids .projections.polar.PolarAxes.set_thetagrids .Axis.get_gridlines .Axis.get_ticklabels Examples -------- :: # set the locations of the angular gridlines lines, labels = thetagrids(range(45, 360, 90)) # set the locations and labels of the angular gridlines lines, labels = thetagrids(range(45, 360, 90), ('NE', 'NW', 'SW', 'SE')) Here is the function: def thetagrids(angles=None, labels=None, fmt=None, **kwargs): """ Get or set the theta gridlines on the current polar plot. Call signatures:: lines, labels = thetagrids() lines, labels = thetagrids(angles, labels=None, fmt=None, **kwargs) When called with no arguments, `.thetagrids` simply returns the tuple (*lines*, *labels*). When called with arguments, the labels will appear at the specified angles. Parameters ---------- angles : tuple with floats, degrees The angles of the theta gridlines. labels : tuple with strings or None The labels to use at each radial gridline. The `.projections.polar.ThetaFormatter` will be used if None. fmt : str or None Format string used in `matplotlib.ticker.FormatStrFormatter`. For example '%f'. Note that the angle in radians will be used. Returns ------- lines : list of `.lines.Line2D` The theta gridlines. labels : list of `.text.Text` The tick labels. Other Parameters ---------------- **kwargs *kwargs* are optional `.Text` properties for the labels. See Also -------- .pyplot.rgrids .projections.polar.PolarAxes.set_thetagrids .Axis.get_gridlines .Axis.get_ticklabels Examples -------- :: # set the locations of the angular gridlines lines, labels = thetagrids(range(45, 360, 90)) # set the locations and labels of the angular gridlines lines, labels = thetagrids(range(45, 360, 90), ('NE', 'NW', 'SW', 'SE')) """ ax = gca() if not isinstance(ax, PolarAxes): raise RuntimeError('thetagrids only defined for polar axes') if all(param is None for param in [angles, labels, fmt]) and not kwargs: lines = ax.xaxis.get_ticklines() labels = ax.xaxis.get_ticklabels() else: lines, labels = ax.set_thetagrids(angles, labels=labels, fmt=fmt, **kwargs) return lines, labels
Get or set the theta gridlines on the current polar plot. Call signatures:: lines, labels = thetagrids() lines, labels = thetagrids(angles, labels=None, fmt=None, **kwargs) When called with no arguments, `.thetagrids` simply returns the tuple (*lines*, *labels*). When called with arguments, the labels will appear at the specified angles. Parameters ---------- angles : tuple with floats, degrees The angles of the theta gridlines. labels : tuple with strings or None The labels to use at each radial gridline. The `.projections.polar.ThetaFormatter` will be used if None. fmt : str or None Format string used in `matplotlib.ticker.FormatStrFormatter`. For example '%f'. Note that the angle in radians will be used. Returns ------- lines : list of `.lines.Line2D` The theta gridlines. labels : list of `.text.Text` The tick labels. Other Parameters ---------------- **kwargs *kwargs* are optional `.Text` properties for the labels. See Also -------- .pyplot.rgrids .projections.polar.PolarAxes.set_thetagrids .Axis.get_gridlines .Axis.get_ticklabels Examples -------- :: # set the locations of the angular gridlines lines, labels = thetagrids(range(45, 360, 90)) # set the locations and labels of the angular gridlines lines, labels = thetagrids(range(45, 360, 90), ('NE', 'NW', 'SW', 'SE'))
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from contextlib import ExitStack from enum import Enum import functools import importlib import inspect import logging from numbers import Number import re import sys import threading import time from cycler import cycler import matplotlib import matplotlib.colorbar import matplotlib.image from matplotlib import _api from matplotlib import rcsetup, style from matplotlib import _pylab_helpers, interactive from matplotlib import cbook from matplotlib import _docstring from matplotlib.backend_bases import ( FigureCanvasBase, FigureManagerBase, MouseButton) from matplotlib.figure import Figure, FigureBase, figaspect from matplotlib.gridspec import GridSpec, SubplotSpec from matplotlib import rcParams, rcParamsDefault, get_backend, rcParamsOrig from matplotlib.rcsetup import interactive_bk as _interactive_bk from matplotlib.artist import Artist from matplotlib.axes import Axes, Subplot from matplotlib.projections import PolarAxes from matplotlib import mlab from matplotlib.scale import get_scale_names from matplotlib import cm from matplotlib.cm import _colormaps as colormaps, register_cmap from matplotlib.colors import _color_sequences as color_sequences import numpy as np from matplotlib.colors import Normalize from matplotlib.lines import Line2D from matplotlib.text import Text, Annotation from matplotlib.patches import Polygon, Rectangle, Circle, Arrow from matplotlib.widgets import Button, Slider, Widget from .ticker import ( TickHelper, Formatter, FixedFormatter, NullFormatter, FuncFormatter, FormatStrFormatter, ScalarFormatter, LogFormatter, LogFormatterExponent, LogFormatterMathtext, Locator, IndexLocator, FixedLocator, NullLocator, LinearLocator, LogLocator, AutoLocator, MultipleLocator, MaxNLocator) def gcf(): """ Get the current figure. If there is currently no figure on the pyplot figure stack, a new one is created using `~.pyplot.figure()`. (To test whether there is currently a figure on the pyplot figure stack, check whether `~.pyplot.get_fignums()` is empty.) """ manager = _pylab_helpers.Gcf.get_active() if manager is not None: return manager.canvas.figure else: return figure() def gci(): return gcf()._gci() def colorbar(mappable=None, cax=None, ax=None, **kwargs): if mappable is None: mappable = gci() if mappable is None: raise RuntimeError('No mappable was found to use for colorbar ' 'creation. First define a mappable such as ' 'an image (with imshow) or a contour set (' 'with contourf).') ret = gcf().colorbar(mappable, cax=cax, ax=ax, **kwargs) return ret
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from contextlib import ExitStack from enum import Enum import functools import importlib import inspect import logging from numbers import Number import re import sys import threading import time from cycler import cycler import matplotlib import matplotlib.colorbar import matplotlib.image from matplotlib import _api from matplotlib import rcsetup, style from matplotlib import _pylab_helpers, interactive from matplotlib import cbook from matplotlib import _docstring from matplotlib.backend_bases import ( FigureCanvasBase, FigureManagerBase, MouseButton) from matplotlib.figure import Figure, FigureBase, figaspect from matplotlib.gridspec import GridSpec, SubplotSpec from matplotlib import rcParams, rcParamsDefault, get_backend, rcParamsOrig from matplotlib.rcsetup import interactive_bk as _interactive_bk from matplotlib.artist import Artist from matplotlib.axes import Axes, Subplot from matplotlib.projections import PolarAxes from matplotlib import mlab from matplotlib.scale import get_scale_names from matplotlib import cm from matplotlib.cm import _colormaps as colormaps, register_cmap from matplotlib.colors import _color_sequences as color_sequences import numpy as np from matplotlib.colors import Normalize from matplotlib.lines import Line2D from matplotlib.text import Text, Annotation from matplotlib.patches import Polygon, Rectangle, Circle, Arrow from matplotlib.widgets import Button, Slider, Widget from .ticker import ( TickHelper, Formatter, FixedFormatter, NullFormatter, FuncFormatter, FormatStrFormatter, ScalarFormatter, LogFormatter, LogFormatterExponent, LogFormatterMathtext, Locator, IndexLocator, FixedLocator, NullLocator, LinearLocator, LogLocator, AutoLocator, MultipleLocator, MaxNLocator) def gci(): return gcf()._gci() The provided code snippet includes necessary dependencies for implementing the `clim` function. Write a Python function `def clim(vmin=None, vmax=None)` to solve the following problem: Set the color limits of the current image. If either *vmin* or *vmax* is None, the image min/max respectively will be used for color scaling. If you want to set the clim of multiple images, use `~.ScalarMappable.set_clim` on every image, for example:: for im in gca().get_images(): im.set_clim(0, 0.5) Here is the function: def clim(vmin=None, vmax=None): """ Set the color limits of the current image. If either *vmin* or *vmax* is None, the image min/max respectively will be used for color scaling. If you want to set the clim of multiple images, use `~.ScalarMappable.set_clim` on every image, for example:: for im in gca().get_images(): im.set_clim(0, 0.5) """ im = gci() if im is None: raise RuntimeError('You must first define an image, e.g., with imshow') im.set_clim(vmin, vmax)
Set the color limits of the current image. If either *vmin* or *vmax* is None, the image min/max respectively will be used for color scaling. If you want to set the clim of multiple images, use `~.ScalarMappable.set_clim` on every image, for example:: for im in gca().get_images(): im.set_clim(0, 0.5)
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from contextlib import ExitStack from enum import Enum import functools import importlib import inspect import logging from numbers import Number import re import sys import threading import time from cycler import cycler import matplotlib import matplotlib.colorbar import matplotlib.image from matplotlib import _api from matplotlib import rcsetup, style from matplotlib import _pylab_helpers, interactive from matplotlib import cbook from matplotlib import _docstring from matplotlib.backend_bases import ( FigureCanvasBase, FigureManagerBase, MouseButton) from matplotlib.figure import Figure, FigureBase, figaspect from matplotlib.gridspec import GridSpec, SubplotSpec from matplotlib import rcParams, rcParamsDefault, get_backend, rcParamsOrig from matplotlib.rcsetup import interactive_bk as _interactive_bk from matplotlib.artist import Artist from matplotlib.axes import Axes, Subplot from matplotlib.projections import PolarAxes from matplotlib import mlab from matplotlib.scale import get_scale_names from matplotlib import cm from matplotlib.cm import _colormaps as colormaps, register_cmap from matplotlib.colors import _color_sequences as color_sequences import numpy as np from matplotlib.colors import Normalize from matplotlib.lines import Line2D from matplotlib.text import Text, Annotation from matplotlib.patches import Polygon, Rectangle, Circle, Arrow from matplotlib.widgets import Button, Slider, Widget from .ticker import ( TickHelper, Formatter, FixedFormatter, NullFormatter, FuncFormatter, FormatStrFormatter, ScalarFormatter, LogFormatter, LogFormatterExponent, LogFormatterMathtext, Locator, IndexLocator, FixedLocator, NullLocator, LinearLocator, LogLocator, AutoLocator, MultipleLocator, MaxNLocator) def imsave(fname, arr, **kwargs): return matplotlib.image.imsave(fname, arr, **kwargs)
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from contextlib import ExitStack from enum import Enum import functools import importlib import inspect import logging from numbers import Number import re import sys import threading import time from cycler import cycler import matplotlib import matplotlib.colorbar import matplotlib.image from matplotlib import _api from matplotlib import rcsetup, style from matplotlib import _pylab_helpers, interactive from matplotlib import cbook from matplotlib import _docstring from matplotlib.backend_bases import ( FigureCanvasBase, FigureManagerBase, MouseButton) from matplotlib.figure import Figure, FigureBase, figaspect from matplotlib.gridspec import GridSpec, SubplotSpec from matplotlib import rcParams, rcParamsDefault, get_backend, rcParamsOrig from matplotlib.rcsetup import interactive_bk as _interactive_bk from matplotlib.artist import Artist from matplotlib.axes import Axes, Subplot from matplotlib.projections import PolarAxes from matplotlib import mlab from matplotlib.scale import get_scale_names from matplotlib import cm from matplotlib.cm import _colormaps as colormaps, register_cmap from matplotlib.colors import _color_sequences as color_sequences import numpy as np from matplotlib.colors import Normalize from matplotlib.lines import Line2D from matplotlib.text import Text, Annotation from matplotlib.patches import Polygon, Rectangle, Circle, Arrow from matplotlib.widgets import Button, Slider, Widget from .ticker import ( TickHelper, Formatter, FixedFormatter, NullFormatter, FuncFormatter, FormatStrFormatter, ScalarFormatter, LogFormatter, LogFormatterExponent, LogFormatterMathtext, Locator, IndexLocator, FixedLocator, NullLocator, LinearLocator, LogLocator, AutoLocator, MultipleLocator, MaxNLocator) def figure(num=None, # autoincrement if None, else integer from 1-N figsize=None, # defaults to rc figure.figsize dpi=None, # defaults to rc figure.dpi facecolor=None, # defaults to rc figure.facecolor edgecolor=None, # defaults to rc figure.edgecolor frameon=True, FigureClass=Figure, clear=False, **kwargs ): """ Create a new figure, or activate an existing figure. Parameters ---------- num : int or str or `.Figure` or `.SubFigure`, optional A unique identifier for the figure. If a figure with that identifier already exists, this figure is made active and returned. An integer refers to the ``Figure.number`` attribute, a string refers to the figure label. If there is no figure with the identifier or *num* is not given, a new figure is created, made active and returned. If *num* is an int, it will be used for the ``Figure.number`` attribute, otherwise, an auto-generated integer value is used (starting at 1 and incremented for each new figure). If *num* is a string, the figure label and the window title is set to this value. If num is a ``SubFigure``, its parent ``Figure`` is activated. figsize : (float, float), default: :rc:`figure.figsize` Width, height in inches. dpi : float, default: :rc:`figure.dpi` The resolution of the figure in dots-per-inch. facecolor : color, default: :rc:`figure.facecolor` The background color. edgecolor : color, default: :rc:`figure.edgecolor` The border color. frameon : bool, default: True If False, suppress drawing the figure frame. FigureClass : subclass of `~matplotlib.figure.Figure` If set, an instance of this subclass will be created, rather than a plain `.Figure`. clear : bool, default: False If True and the figure already exists, then it is cleared. layout : {'constrained', 'compressed', 'tight', 'none', `.LayoutEngine`, None}, \ default: None The layout mechanism for positioning of plot elements to avoid overlapping Axes decorations (labels, ticks, etc). Note that layout managers can measurably slow down figure display. - 'constrained': The constrained layout solver adjusts axes sizes to avoid overlapping axes decorations. Can handle complex plot layouts and colorbars, and is thus recommended. See :doc:`/tutorials/intermediate/constrainedlayout_guide` for examples. - 'compressed': uses the same algorithm as 'constrained', but removes extra space between fixed-aspect-ratio Axes. Best for simple grids of axes. - 'tight': Use the tight layout mechanism. This is a relatively simple algorithm that adjusts the subplot parameters so that decorations do not overlap. See `.Figure.set_tight_layout` for further details. - 'none': Do not use a layout engine. - A `.LayoutEngine` instance. Builtin layout classes are `.ConstrainedLayoutEngine` and `.TightLayoutEngine`, more easily accessible by 'constrained' and 'tight'. Passing an instance allows third parties to provide their own layout engine. If not given, fall back to using the parameters *tight_layout* and *constrained_layout*, including their config defaults :rc:`figure.autolayout` and :rc:`figure.constrained_layout.use`. **kwargs Additional keyword arguments are passed to the `.Figure` constructor. Returns ------- `~matplotlib.figure.Figure` Notes ----- A newly created figure is passed to the `~.FigureCanvasBase.new_manager` method or the `new_figure_manager` function provided by the current backend, which install a canvas and a manager on the figure. Once this is done, :rc:`figure.hooks` are called, one at a time, on the figure; these hooks allow arbitrary customization of the figure (e.g., attaching callbacks) or of associated elements (e.g., modifying the toolbar). See :doc:`/gallery/user_interfaces/mplcvd` for an example of toolbar customization. If you are creating many figures, make sure you explicitly call `.pyplot.close` on the figures you are not using, because this will enable pyplot to properly clean up the memory. `~matplotlib.rcParams` defines the default values, which can be modified in the matplotlibrc file. """ if isinstance(num, FigureBase): if num.canvas.manager is None: raise ValueError("The passed figure is not managed by pyplot") _pylab_helpers.Gcf.set_active(num.canvas.manager) return num.figure allnums = get_fignums() next_num = max(allnums) + 1 if allnums else 1 fig_label = '' if num is None: num = next_num elif isinstance(num, str): fig_label = num all_labels = get_figlabels() if fig_label not in all_labels: if fig_label == 'all': _api.warn_external("close('all') closes all existing figures.") num = next_num else: inum = all_labels.index(fig_label) num = allnums[inum] else: num = int(num) # crude validation of num argument manager = _pylab_helpers.Gcf.get_fig_manager(num) if manager is None: max_open_warning = rcParams['figure.max_open_warning'] if len(allnums) == max_open_warning >= 1: _api.warn_external( f"More than {max_open_warning} figures have been opened. " f"Figures created through the pyplot interface " f"(`matplotlib.pyplot.figure`) are retained until explicitly " f"closed and may consume too much memory. (To control this " f"warning, see the rcParam `figure.max_open_warning`). " f"Consider using `matplotlib.pyplot.close()`.", RuntimeWarning) manager = new_figure_manager( num, figsize=figsize, dpi=dpi, facecolor=facecolor, edgecolor=edgecolor, frameon=frameon, FigureClass=FigureClass, **kwargs) fig = manager.canvas.figure if fig_label: fig.set_label(fig_label) for hookspecs in rcParams["figure.hooks"]: module_name, dotted_name = hookspecs.split(":") obj = importlib.import_module(module_name) for part in dotted_name.split("."): obj = getattr(obj, part) obj(fig) _pylab_helpers.Gcf._set_new_active_manager(manager) # make sure backends (inline) that we don't ship that expect this # to be called in plotting commands to make the figure call show # still work. There is probably a better way to do this in the # FigureManager base class. draw_if_interactive() if _REPL_DISPLAYHOOK is _ReplDisplayHook.PLAIN: fig.stale_callback = _auto_draw_if_interactive if clear: manager.canvas.figure.clear() return manager.canvas.figure def gca(): return gcf().gca() def sci(im): return gca()._sci(im) def figaspect(arg): """ Calculate the width and height for a figure with a specified aspect ratio. While the height is taken from :rc:`figure.figsize`, the width is adjusted to match the desired aspect ratio. Additionally, it is ensured that the width is in the range [4., 16.] and the height is in the range [2., 16.]. If necessary, the default height is adjusted to ensure this. Parameters ---------- arg : float or 2D array If a float, this defines the aspect ratio (i.e. the ratio height / width). In case of an array the aspect ratio is number of rows / number of columns, so that the array could be fitted in the figure undistorted. Returns ------- width, height : float The figure size in inches. Notes ----- If you want to create an Axes within the figure, that still preserves the aspect ratio, be sure to create it with equal width and height. See examples below. Thanks to Fernando Perez for this function. Examples -------- Make a figure twice as tall as it is wide:: w, h = figaspect(2.) fig = Figure(figsize=(w, h)) ax = fig.add_axes([0.1, 0.1, 0.8, 0.8]) ax.imshow(A, **kwargs) Make a figure with the proper aspect for an array:: A = rand(5, 3) w, h = figaspect(A) fig = Figure(figsize=(w, h)) ax = fig.add_axes([0.1, 0.1, 0.8, 0.8]) ax.imshow(A, **kwargs) """ isarray = hasattr(arg, 'shape') and not np.isscalar(arg) # min/max sizes to respect when autoscaling. If John likes the idea, they # could become rc parameters, for now they're hardwired. figsize_min = np.array((4.0, 2.0)) # min length for width/height figsize_max = np.array((16.0, 16.0)) # max length for width/height # Extract the aspect ratio of the array if isarray: nr, nc = arg.shape[:2] arr_ratio = nr / nc else: arr_ratio = arg # Height of user figure defaults fig_height = mpl.rcParams['figure.figsize'][1] # New size for the figure, keeping the aspect ratio of the caller newsize = np.array((fig_height / arr_ratio, fig_height)) # Sanity checks, don't drop either dimension below figsize_min newsize /= min(1.0, *(newsize / figsize_min)) # Avoid humongous windows as well newsize /= max(1.0, *(newsize / figsize_max)) # Finally, if we have a really funky aspect ratio, break it but respect # the min/max dimensions (we don't want figures 10 feet tall!) newsize = np.clip(newsize, figsize_min, figsize_max) return newsize The provided code snippet includes necessary dependencies for implementing the `matshow` function. Write a Python function `def matshow(A, fignum=None, **kwargs)` to solve the following problem: Display an array as a matrix in a new figure window. The origin is set at the upper left hand corner and rows (first dimension of the array) are displayed horizontally. The aspect ratio of the figure window is that of the array, unless this would make an excessively short or narrow figure. Tick labels for the xaxis are placed on top. Parameters ---------- A : 2D array-like The matrix to be displayed. fignum : None or int or False If *None*, create a new figure window with automatic numbering. If a nonzero integer, draw into the figure with the given number (create it if it does not exist). If 0, use the current axes (or create one if it does not exist). .. note:: Because of how `.Axes.matshow` tries to set the figure aspect ratio to be the one of the array, strange things may happen if you reuse an existing figure. Returns ------- `~matplotlib.image.AxesImage` Other Parameters ---------------- **kwargs : `~matplotlib.axes.Axes.imshow` arguments Here is the function: def matshow(A, fignum=None, **kwargs): """ Display an array as a matrix in a new figure window. The origin is set at the upper left hand corner and rows (first dimension of the array) are displayed horizontally. The aspect ratio of the figure window is that of the array, unless this would make an excessively short or narrow figure. Tick labels for the xaxis are placed on top. Parameters ---------- A : 2D array-like The matrix to be displayed. fignum : None or int or False If *None*, create a new figure window with automatic numbering. If a nonzero integer, draw into the figure with the given number (create it if it does not exist). If 0, use the current axes (or create one if it does not exist). .. note:: Because of how `.Axes.matshow` tries to set the figure aspect ratio to be the one of the array, strange things may happen if you reuse an existing figure. Returns ------- `~matplotlib.image.AxesImage` Other Parameters ---------------- **kwargs : `~matplotlib.axes.Axes.imshow` arguments """ A = np.asanyarray(A) if fignum == 0: ax = gca() else: # Extract actual aspect ratio of array and make appropriately sized # figure. fig = figure(fignum, figsize=figaspect(A)) ax = fig.add_axes([0.15, 0.09, 0.775, 0.775]) im = ax.matshow(A, **kwargs) sci(im) return im
Display an array as a matrix in a new figure window. The origin is set at the upper left hand corner and rows (first dimension of the array) are displayed horizontally. The aspect ratio of the figure window is that of the array, unless this would make an excessively short or narrow figure. Tick labels for the xaxis are placed on top. Parameters ---------- A : 2D array-like The matrix to be displayed. fignum : None or int or False If *None*, create a new figure window with automatic numbering. If a nonzero integer, draw into the figure with the given number (create it if it does not exist). If 0, use the current axes (or create one if it does not exist). .. note:: Because of how `.Axes.matshow` tries to set the figure aspect ratio to be the one of the array, strange things may happen if you reuse an existing figure. Returns ------- `~matplotlib.image.AxesImage` Other Parameters ---------------- **kwargs : `~matplotlib.axes.Axes.imshow` arguments
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from contextlib import ExitStack from enum import Enum import functools import importlib import inspect import logging from numbers import Number import re import sys import threading import time from cycler import cycler import matplotlib import matplotlib.colorbar import matplotlib.image from matplotlib import _api from matplotlib import rcsetup, style from matplotlib import _pylab_helpers, interactive from matplotlib import cbook from matplotlib import _docstring from matplotlib.backend_bases import ( FigureCanvasBase, FigureManagerBase, MouseButton) from matplotlib.figure import Figure, FigureBase, figaspect from matplotlib.gridspec import GridSpec, SubplotSpec from matplotlib import rcParams, rcParamsDefault, get_backend, rcParamsOrig from matplotlib.rcsetup import interactive_bk as _interactive_bk from matplotlib.artist import Artist from matplotlib.axes import Axes, Subplot from matplotlib.projections import PolarAxes from matplotlib import mlab from matplotlib.scale import get_scale_names from matplotlib import cm from matplotlib.cm import _colormaps as colormaps, register_cmap from matplotlib.colors import _color_sequences as color_sequences import numpy as np from matplotlib.colors import Normalize from matplotlib.lines import Line2D from matplotlib.text import Text, Annotation from matplotlib.patches import Polygon, Rectangle, Circle, Arrow from matplotlib.widgets import Button, Slider, Widget from .ticker import ( TickHelper, Formatter, FixedFormatter, NullFormatter, FuncFormatter, FormatStrFormatter, ScalarFormatter, LogFormatter, LogFormatterExponent, LogFormatterMathtext, Locator, IndexLocator, FixedLocator, NullLocator, LinearLocator, LogLocator, AutoLocator, MultipleLocator, MaxNLocator) def gcf(): def text(x, y, s, fontdict=None, **kwargs): def figtext(x, y, s, fontdict=None, **kwargs): return gcf().text(x, y, s, fontdict=fontdict, **kwargs)
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from contextlib import ExitStack from enum import Enum import functools import importlib import inspect import logging from numbers import Number import re import sys import threading import time from cycler import cycler import matplotlib import matplotlib.colorbar import matplotlib.image from matplotlib import _api from matplotlib import rcsetup, style from matplotlib import _pylab_helpers, interactive from matplotlib import cbook from matplotlib import _docstring from matplotlib.backend_bases import ( FigureCanvasBase, FigureManagerBase, MouseButton) from matplotlib.figure import Figure, FigureBase, figaspect from matplotlib.gridspec import GridSpec, SubplotSpec from matplotlib import rcParams, rcParamsDefault, get_backend, rcParamsOrig from matplotlib.rcsetup import interactive_bk as _interactive_bk from matplotlib.artist import Artist from matplotlib.axes import Axes, Subplot from matplotlib.projections import PolarAxes from matplotlib import mlab from matplotlib.scale import get_scale_names from matplotlib import cm from matplotlib.cm import _colormaps as colormaps, register_cmap from matplotlib.colors import _color_sequences as color_sequences import numpy as np from matplotlib.colors import Normalize from matplotlib.lines import Line2D from matplotlib.text import Text, Annotation from matplotlib.patches import Polygon, Rectangle, Circle, Arrow from matplotlib.widgets import Button, Slider, Widget from .ticker import ( TickHelper, Formatter, FixedFormatter, NullFormatter, FuncFormatter, FormatStrFormatter, ScalarFormatter, LogFormatter, LogFormatterExponent, LogFormatterMathtext, Locator, IndexLocator, FixedLocator, NullLocator, LinearLocator, LogLocator, AutoLocator, MultipleLocator, MaxNLocator) def gcf(): class MouseButton(IntEnum): def ginput( n=1, timeout=30, show_clicks=True, mouse_add=MouseButton.LEFT, mouse_pop=MouseButton.RIGHT, mouse_stop=MouseButton.MIDDLE): return gcf().ginput( n=n, timeout=timeout, show_clicks=show_clicks, mouse_add=mouse_add, mouse_pop=mouse_pop, mouse_stop=mouse_stop)
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from contextlib import ExitStack from enum import Enum import functools import importlib import inspect import logging from numbers import Number import re import sys import threading import time from cycler import cycler import matplotlib import matplotlib.colorbar import matplotlib.image from matplotlib import _api from matplotlib import rcsetup, style from matplotlib import _pylab_helpers, interactive from matplotlib import cbook from matplotlib import _docstring from matplotlib.backend_bases import ( FigureCanvasBase, FigureManagerBase, MouseButton) from matplotlib.figure import Figure, FigureBase, figaspect from matplotlib.gridspec import GridSpec, SubplotSpec from matplotlib import rcParams, rcParamsDefault, get_backend, rcParamsOrig from matplotlib.rcsetup import interactive_bk as _interactive_bk from matplotlib.artist import Artist from matplotlib.axes import Axes, Subplot from matplotlib.projections import PolarAxes from matplotlib import mlab from matplotlib.scale import get_scale_names from matplotlib import cm from matplotlib.cm import _colormaps as colormaps, register_cmap from matplotlib.colors import _color_sequences as color_sequences import numpy as np from matplotlib.colors import Normalize from matplotlib.lines import Line2D from matplotlib.text import Text, Annotation from matplotlib.patches import Polygon, Rectangle, Circle, Arrow from matplotlib.widgets import Button, Slider, Widget from .ticker import ( TickHelper, Formatter, FixedFormatter, NullFormatter, FuncFormatter, FormatStrFormatter, ScalarFormatter, LogFormatter, LogFormatterExponent, LogFormatterMathtext, Locator, IndexLocator, FixedLocator, NullLocator, LinearLocator, LogLocator, AutoLocator, MultipleLocator, MaxNLocator) def gcf(): """ Get the current figure. If there is currently no figure on the pyplot figure stack, a new one is created using `~.pyplot.figure()`. (To test whether there is currently a figure on the pyplot figure stack, check whether `~.pyplot.get_fignums()` is empty.) """ manager = _pylab_helpers.Gcf.get_active() if manager is not None: return manager.canvas.figure else: return figure() def waitforbuttonpress(timeout=-1): return gcf().waitforbuttonpress(timeout=timeout)
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from contextlib import ExitStack from enum import Enum import functools import importlib import inspect import logging from numbers import Number import re import sys import threading import time from cycler import cycler import matplotlib import matplotlib.colorbar import matplotlib.image from matplotlib import _api from matplotlib import rcsetup, style from matplotlib import _pylab_helpers, interactive from matplotlib import cbook from matplotlib import _docstring from matplotlib.backend_bases import ( FigureCanvasBase, FigureManagerBase, MouseButton) from matplotlib.figure import Figure, FigureBase, figaspect from matplotlib.gridspec import GridSpec, SubplotSpec from matplotlib import rcParams, rcParamsDefault, get_backend, rcParamsOrig from matplotlib.rcsetup import interactive_bk as _interactive_bk from matplotlib.artist import Artist from matplotlib.axes import Axes, Subplot from matplotlib.projections import PolarAxes from matplotlib import mlab from matplotlib.scale import get_scale_names from matplotlib import cm from matplotlib.cm import _colormaps as colormaps, register_cmap from matplotlib.colors import _color_sequences as color_sequences import numpy as np from matplotlib.colors import Normalize from matplotlib.lines import Line2D from matplotlib.text import Text, Annotation from matplotlib.patches import Polygon, Rectangle, Circle, Arrow from matplotlib.widgets import Button, Slider, Widget from .ticker import ( TickHelper, Formatter, FixedFormatter, NullFormatter, FuncFormatter, FormatStrFormatter, ScalarFormatter, LogFormatter, LogFormatterExponent, LogFormatterMathtext, Locator, IndexLocator, FixedLocator, NullLocator, LinearLocator, LogLocator, AutoLocator, MultipleLocator, MaxNLocator) def gca(): return gcf().gca() def acorr(x, *, data=None, **kwargs): return gca().acorr( x, **({"data": data} if data is not None else {}), **kwargs)
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from contextlib import ExitStack from enum import Enum import functools import importlib import inspect import logging from numbers import Number import re import sys import threading import time from cycler import cycler import matplotlib import matplotlib.colorbar import matplotlib.image from matplotlib import _api from matplotlib import rcsetup, style from matplotlib import _pylab_helpers, interactive from matplotlib import cbook from matplotlib import _docstring from matplotlib.backend_bases import ( FigureCanvasBase, FigureManagerBase, MouseButton) from matplotlib.figure import Figure, FigureBase, figaspect from matplotlib.gridspec import GridSpec, SubplotSpec from matplotlib import rcParams, rcParamsDefault, get_backend, rcParamsOrig from matplotlib.rcsetup import interactive_bk as _interactive_bk from matplotlib.artist import Artist from matplotlib.axes import Axes, Subplot from matplotlib.projections import PolarAxes from matplotlib import mlab from matplotlib.scale import get_scale_names from matplotlib import cm from matplotlib.cm import _colormaps as colormaps, register_cmap from matplotlib.colors import _color_sequences as color_sequences import numpy as np from matplotlib.colors import Normalize from matplotlib.lines import Line2D from matplotlib.text import Text, Annotation from matplotlib.patches import Polygon, Rectangle, Circle, Arrow from matplotlib.widgets import Button, Slider, Widget from .ticker import ( TickHelper, Formatter, FixedFormatter, NullFormatter, FuncFormatter, FormatStrFormatter, ScalarFormatter, LogFormatter, LogFormatterExponent, LogFormatterMathtext, Locator, IndexLocator, FixedLocator, NullLocator, LinearLocator, LogLocator, AutoLocator, MultipleLocator, MaxNLocator) def gca(): return gcf().gca() def angle_spectrum( x, Fs=None, Fc=None, window=None, pad_to=None, sides=None, *, data=None, **kwargs): return gca().angle_spectrum( x, Fs=Fs, Fc=Fc, window=window, pad_to=pad_to, sides=sides, **({"data": data} if data is not None else {}), **kwargs)
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from contextlib import ExitStack from enum import Enum import functools import importlib import inspect import logging from numbers import Number import re import sys import threading import time from cycler import cycler import matplotlib import matplotlib.colorbar import matplotlib.image from matplotlib import _api from matplotlib import rcsetup, style from matplotlib import _pylab_helpers, interactive from matplotlib import cbook from matplotlib import _docstring from matplotlib.backend_bases import ( FigureCanvasBase, FigureManagerBase, MouseButton) from matplotlib.figure import Figure, FigureBase, figaspect from matplotlib.gridspec import GridSpec, SubplotSpec from matplotlib import rcParams, rcParamsDefault, get_backend, rcParamsOrig from matplotlib.rcsetup import interactive_bk as _interactive_bk from matplotlib.artist import Artist from matplotlib.axes import Axes, Subplot from matplotlib.projections import PolarAxes from matplotlib import mlab from matplotlib.scale import get_scale_names from matplotlib import cm from matplotlib.cm import _colormaps as colormaps, register_cmap from matplotlib.colors import _color_sequences as color_sequences import numpy as np from matplotlib.colors import Normalize from matplotlib.lines import Line2D from matplotlib.text import Text, Annotation from matplotlib.patches import Polygon, Rectangle, Circle, Arrow from matplotlib.widgets import Button, Slider, Widget from .ticker import ( TickHelper, Formatter, FixedFormatter, NullFormatter, FuncFormatter, FormatStrFormatter, ScalarFormatter, LogFormatter, LogFormatterExponent, LogFormatterMathtext, Locator, IndexLocator, FixedLocator, NullLocator, LinearLocator, LogLocator, AutoLocator, MultipleLocator, MaxNLocator) def gca(): def annotate( text, xy, xytext=None, xycoords='data', textcoords=None, arrowprops=None, annotation_clip=None, **kwargs): return gca().annotate( text, xy, xytext=xytext, xycoords=xycoords, textcoords=textcoords, arrowprops=arrowprops, annotation_clip=annotation_clip, **kwargs)
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from contextlib import ExitStack from enum import Enum import functools import importlib import inspect import logging from numbers import Number import re import sys import threading import time from cycler import cycler import matplotlib import matplotlib.colorbar import matplotlib.image from matplotlib import _api from matplotlib import rcsetup, style from matplotlib import _pylab_helpers, interactive from matplotlib import cbook from matplotlib import _docstring from matplotlib.backend_bases import ( FigureCanvasBase, FigureManagerBase, MouseButton) from matplotlib.figure import Figure, FigureBase, figaspect from matplotlib.gridspec import GridSpec, SubplotSpec from matplotlib import rcParams, rcParamsDefault, get_backend, rcParamsOrig from matplotlib.rcsetup import interactive_bk as _interactive_bk from matplotlib.artist import Artist from matplotlib.axes import Axes, Subplot from matplotlib.projections import PolarAxes from matplotlib import mlab from matplotlib.scale import get_scale_names from matplotlib import cm from matplotlib.cm import _colormaps as colormaps, register_cmap from matplotlib.colors import _color_sequences as color_sequences import numpy as np from matplotlib.colors import Normalize from matplotlib.lines import Line2D from matplotlib.text import Text, Annotation from matplotlib.patches import Polygon, Rectangle, Circle, Arrow from matplotlib.widgets import Button, Slider, Widget from .ticker import ( TickHelper, Formatter, FixedFormatter, NullFormatter, FuncFormatter, FormatStrFormatter, ScalarFormatter, LogFormatter, LogFormatterExponent, LogFormatterMathtext, Locator, IndexLocator, FixedLocator, NullLocator, LinearLocator, LogLocator, AutoLocator, MultipleLocator, MaxNLocator) def gca(): return gcf().gca() def arrow(x, y, dx, dy, **kwargs): return gca().arrow(x, y, dx, dy, **kwargs)
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from contextlib import ExitStack from enum import Enum import functools import importlib import inspect import logging from numbers import Number import re import sys import threading import time from cycler import cycler import matplotlib import matplotlib.colorbar import matplotlib.image from matplotlib import _api from matplotlib import rcsetup, style from matplotlib import _pylab_helpers, interactive from matplotlib import cbook from matplotlib import _docstring from matplotlib.backend_bases import ( FigureCanvasBase, FigureManagerBase, MouseButton) from matplotlib.figure import Figure, FigureBase, figaspect from matplotlib.gridspec import GridSpec, SubplotSpec from matplotlib import rcParams, rcParamsDefault, get_backend, rcParamsOrig from matplotlib.rcsetup import interactive_bk as _interactive_bk from matplotlib.artist import Artist from matplotlib.axes import Axes, Subplot from matplotlib.projections import PolarAxes from matplotlib import mlab from matplotlib.scale import get_scale_names from matplotlib import cm from matplotlib.cm import _colormaps as colormaps, register_cmap from matplotlib.colors import _color_sequences as color_sequences import numpy as np from matplotlib.colors import Normalize from matplotlib.lines import Line2D from matplotlib.text import Text, Annotation from matplotlib.patches import Polygon, Rectangle, Circle, Arrow from matplotlib.widgets import Button, Slider, Widget from .ticker import ( TickHelper, Formatter, FixedFormatter, NullFormatter, FuncFormatter, FormatStrFormatter, ScalarFormatter, LogFormatter, LogFormatterExponent, LogFormatterMathtext, Locator, IndexLocator, FixedLocator, NullLocator, LinearLocator, LogLocator, AutoLocator, MultipleLocator, MaxNLocator) def gca(): return gcf().gca() def autoscale(enable=True, axis='both', tight=None): return gca().autoscale(enable=enable, axis=axis, tight=tight)
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from contextlib import ExitStack from enum import Enum import functools import importlib import inspect import logging from numbers import Number import re import sys import threading import time from cycler import cycler import matplotlib import matplotlib.colorbar import matplotlib.image from matplotlib import _api from matplotlib import rcsetup, style from matplotlib import _pylab_helpers, interactive from matplotlib import cbook from matplotlib import _docstring from matplotlib.backend_bases import ( FigureCanvasBase, FigureManagerBase, MouseButton) from matplotlib.figure import Figure, FigureBase, figaspect from matplotlib.gridspec import GridSpec, SubplotSpec from matplotlib import rcParams, rcParamsDefault, get_backend, rcParamsOrig from matplotlib.rcsetup import interactive_bk as _interactive_bk from matplotlib.artist import Artist from matplotlib.axes import Axes, Subplot from matplotlib.projections import PolarAxes from matplotlib import mlab from matplotlib.scale import get_scale_names from matplotlib import cm from matplotlib.cm import _colormaps as colormaps, register_cmap from matplotlib.colors import _color_sequences as color_sequences import numpy as np from matplotlib.colors import Normalize from matplotlib.lines import Line2D from matplotlib.text import Text, Annotation from matplotlib.patches import Polygon, Rectangle, Circle, Arrow from matplotlib.widgets import Button, Slider, Widget from .ticker import ( TickHelper, Formatter, FixedFormatter, NullFormatter, FuncFormatter, FormatStrFormatter, ScalarFormatter, LogFormatter, LogFormatterExponent, LogFormatterMathtext, Locator, IndexLocator, FixedLocator, NullLocator, LinearLocator, LogLocator, AutoLocator, MultipleLocator, MaxNLocator) def gca(): return gcf().gca() def axhspan(ymin, ymax, xmin=0, xmax=1, **kwargs): return gca().axhspan(ymin, ymax, xmin=xmin, xmax=xmax, **kwargs)
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from contextlib import ExitStack from enum import Enum import functools import importlib import inspect import logging from numbers import Number import re import sys import threading import time from cycler import cycler import matplotlib import matplotlib.colorbar import matplotlib.image from matplotlib import _api from matplotlib import rcsetup, style from matplotlib import _pylab_helpers, interactive from matplotlib import cbook from matplotlib import _docstring from matplotlib.backend_bases import ( FigureCanvasBase, FigureManagerBase, MouseButton) from matplotlib.figure import Figure, FigureBase, figaspect from matplotlib.gridspec import GridSpec, SubplotSpec from matplotlib import rcParams, rcParamsDefault, get_backend, rcParamsOrig from matplotlib.rcsetup import interactive_bk as _interactive_bk from matplotlib.artist import Artist from matplotlib.axes import Axes, Subplot from matplotlib.projections import PolarAxes from matplotlib import mlab from matplotlib.scale import get_scale_names from matplotlib import cm from matplotlib.cm import _colormaps as colormaps, register_cmap from matplotlib.colors import _color_sequences as color_sequences import numpy as np from matplotlib.colors import Normalize from matplotlib.lines import Line2D from matplotlib.text import Text, Annotation from matplotlib.patches import Polygon, Rectangle, Circle, Arrow from matplotlib.widgets import Button, Slider, Widget from .ticker import ( TickHelper, Formatter, FixedFormatter, NullFormatter, FuncFormatter, FormatStrFormatter, ScalarFormatter, LogFormatter, LogFormatterExponent, LogFormatterMathtext, Locator, IndexLocator, FixedLocator, NullLocator, LinearLocator, LogLocator, AutoLocator, MultipleLocator, MaxNLocator) def gca(): return gcf().gca() def axline(xy1, xy2=None, *, slope=None, **kwargs): return gca().axline(xy1, xy2=xy2, slope=slope, **kwargs)
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from contextlib import ExitStack from enum import Enum import functools import importlib import inspect import logging from numbers import Number import re import sys import threading import time from cycler import cycler import matplotlib import matplotlib.colorbar import matplotlib.image from matplotlib import _api from matplotlib import rcsetup, style from matplotlib import _pylab_helpers, interactive from matplotlib import cbook from matplotlib import _docstring from matplotlib.backend_bases import ( FigureCanvasBase, FigureManagerBase, MouseButton) from matplotlib.figure import Figure, FigureBase, figaspect from matplotlib.gridspec import GridSpec, SubplotSpec from matplotlib import rcParams, rcParamsDefault, get_backend, rcParamsOrig from matplotlib.rcsetup import interactive_bk as _interactive_bk from matplotlib.artist import Artist from matplotlib.axes import Axes, Subplot from matplotlib.projections import PolarAxes from matplotlib import mlab from matplotlib.scale import get_scale_names from matplotlib import cm from matplotlib.cm import _colormaps as colormaps, register_cmap from matplotlib.colors import _color_sequences as color_sequences import numpy as np from matplotlib.colors import Normalize from matplotlib.lines import Line2D from matplotlib.text import Text, Annotation from matplotlib.patches import Polygon, Rectangle, Circle, Arrow from matplotlib.widgets import Button, Slider, Widget from .ticker import ( TickHelper, Formatter, FixedFormatter, NullFormatter, FuncFormatter, FormatStrFormatter, ScalarFormatter, LogFormatter, LogFormatterExponent, LogFormatterMathtext, Locator, IndexLocator, FixedLocator, NullLocator, LinearLocator, LogLocator, AutoLocator, MultipleLocator, MaxNLocator) def gca(): return gcf().gca() def axvspan(xmin, xmax, ymin=0, ymax=1, **kwargs): return gca().axvspan(xmin, xmax, ymin=ymin, ymax=ymax, **kwargs)
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from contextlib import ExitStack from enum import Enum import functools import importlib import inspect import logging from numbers import Number import re import sys import threading import time from cycler import cycler import matplotlib import matplotlib.colorbar import matplotlib.image from matplotlib import _api from matplotlib import rcsetup, style from matplotlib import _pylab_helpers, interactive from matplotlib import cbook from matplotlib import _docstring from matplotlib.backend_bases import ( FigureCanvasBase, FigureManagerBase, MouseButton) from matplotlib.figure import Figure, FigureBase, figaspect from matplotlib.gridspec import GridSpec, SubplotSpec from matplotlib import rcParams, rcParamsDefault, get_backend, rcParamsOrig from matplotlib.rcsetup import interactive_bk as _interactive_bk from matplotlib.artist import Artist from matplotlib.axes import Axes, Subplot from matplotlib.projections import PolarAxes from matplotlib import mlab from matplotlib.scale import get_scale_names from matplotlib import cm from matplotlib.cm import _colormaps as colormaps, register_cmap from matplotlib.colors import _color_sequences as color_sequences import numpy as np from matplotlib.colors import Normalize from matplotlib.lines import Line2D from matplotlib.text import Text, Annotation from matplotlib.patches import Polygon, Rectangle, Circle, Arrow from matplotlib.widgets import Button, Slider, Widget from .ticker import ( TickHelper, Formatter, FixedFormatter, NullFormatter, FuncFormatter, FormatStrFormatter, ScalarFormatter, LogFormatter, LogFormatterExponent, LogFormatterMathtext, Locator, IndexLocator, FixedLocator, NullLocator, LinearLocator, LogLocator, AutoLocator, MultipleLocator, MaxNLocator) def gca(): return gcf().gca() def barbs(*args, data=None, **kwargs): return gca().barbs( *args, **({"data": data} if data is not None else {}), **kwargs)
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from contextlib import ExitStack from enum import Enum import functools import importlib import inspect import logging from numbers import Number import re import sys import threading import time from cycler import cycler import matplotlib import matplotlib.colorbar import matplotlib.image from matplotlib import _api from matplotlib import rcsetup, style from matplotlib import _pylab_helpers, interactive from matplotlib import cbook from matplotlib import _docstring from matplotlib.backend_bases import ( FigureCanvasBase, FigureManagerBase, MouseButton) from matplotlib.figure import Figure, FigureBase, figaspect from matplotlib.gridspec import GridSpec, SubplotSpec from matplotlib import rcParams, rcParamsDefault, get_backend, rcParamsOrig from matplotlib.rcsetup import interactive_bk as _interactive_bk from matplotlib.artist import Artist from matplotlib.axes import Axes, Subplot from matplotlib.projections import PolarAxes from matplotlib import mlab from matplotlib.scale import get_scale_names from matplotlib import cm from matplotlib.cm import _colormaps as colormaps, register_cmap from matplotlib.colors import _color_sequences as color_sequences import numpy as np from matplotlib.colors import Normalize from matplotlib.lines import Line2D from matplotlib.text import Text, Annotation from matplotlib.patches import Polygon, Rectangle, Circle, Arrow from matplotlib.widgets import Button, Slider, Widget from .ticker import ( TickHelper, Formatter, FixedFormatter, NullFormatter, FuncFormatter, FormatStrFormatter, ScalarFormatter, LogFormatter, LogFormatterExponent, LogFormatterMathtext, Locator, IndexLocator, FixedLocator, NullLocator, LinearLocator, LogLocator, AutoLocator, MultipleLocator, MaxNLocator) def gca(): return gcf().gca() def barh( y, width, height=0.8, left=None, *, align='center', data=None, **kwargs): return gca().barh( y, width, height=height, left=left, align=align, **({"data": data} if data is not None else {}), **kwargs)
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from contextlib import ExitStack from enum import Enum import functools import importlib import inspect import logging from numbers import Number import re import sys import threading import time from cycler import cycler import matplotlib import matplotlib.colorbar import matplotlib.image from matplotlib import _api from matplotlib import rcsetup, style from matplotlib import _pylab_helpers, interactive from matplotlib import cbook from matplotlib import _docstring from matplotlib.backend_bases import ( FigureCanvasBase, FigureManagerBase, MouseButton) from matplotlib.figure import Figure, FigureBase, figaspect from matplotlib.gridspec import GridSpec, SubplotSpec from matplotlib import rcParams, rcParamsDefault, get_backend, rcParamsOrig from matplotlib.rcsetup import interactive_bk as _interactive_bk from matplotlib.artist import Artist from matplotlib.axes import Axes, Subplot from matplotlib.projections import PolarAxes from matplotlib import mlab from matplotlib.scale import get_scale_names from matplotlib import cm from matplotlib.cm import _colormaps as colormaps, register_cmap from matplotlib.colors import _color_sequences as color_sequences import numpy as np from matplotlib.colors import Normalize from matplotlib.lines import Line2D from matplotlib.text import Text, Annotation from matplotlib.patches import Polygon, Rectangle, Circle, Arrow from matplotlib.widgets import Button, Slider, Widget from .ticker import ( TickHelper, Formatter, FixedFormatter, NullFormatter, FuncFormatter, FormatStrFormatter, ScalarFormatter, LogFormatter, LogFormatterExponent, LogFormatterMathtext, Locator, IndexLocator, FixedLocator, NullLocator, LinearLocator, LogLocator, AutoLocator, MultipleLocator, MaxNLocator) def gca(): return gcf().gca() def bar_label( container, labels=None, *, fmt='%g', label_type='edge', padding=0, **kwargs): return gca().bar_label( container, labels=labels, fmt=fmt, label_type=label_type, padding=padding, **kwargs)
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from contextlib import ExitStack from enum import Enum import functools import importlib import inspect import logging from numbers import Number import re import sys import threading import time from cycler import cycler import matplotlib import matplotlib.colorbar import matplotlib.image from matplotlib import _api from matplotlib import rcsetup, style from matplotlib import _pylab_helpers, interactive from matplotlib import cbook from matplotlib import _docstring from matplotlib.backend_bases import ( FigureCanvasBase, FigureManagerBase, MouseButton) from matplotlib.figure import Figure, FigureBase, figaspect from matplotlib.gridspec import GridSpec, SubplotSpec from matplotlib import rcParams, rcParamsDefault, get_backend, rcParamsOrig from matplotlib.rcsetup import interactive_bk as _interactive_bk from matplotlib.artist import Artist from matplotlib.axes import Axes, Subplot from matplotlib.projections import PolarAxes from matplotlib import mlab from matplotlib.scale import get_scale_names from matplotlib import cm from matplotlib.cm import _colormaps as colormaps, register_cmap from matplotlib.colors import _color_sequences as color_sequences import numpy as np from matplotlib.colors import Normalize from matplotlib.lines import Line2D from matplotlib.text import Text, Annotation from matplotlib.patches import Polygon, Rectangle, Circle, Arrow from matplotlib.widgets import Button, Slider, Widget from .ticker import ( TickHelper, Formatter, FixedFormatter, NullFormatter, FuncFormatter, FormatStrFormatter, ScalarFormatter, LogFormatter, LogFormatterExponent, LogFormatterMathtext, Locator, IndexLocator, FixedLocator, NullLocator, LinearLocator, LogLocator, AutoLocator, MultipleLocator, MaxNLocator) def gca(): def broken_barh(xranges, yrange, *, data=None, **kwargs): return gca().broken_barh( xranges, yrange, **({"data": data} if data is not None else {}), **kwargs)
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from contextlib import ExitStack from enum import Enum import functools import importlib import inspect import logging from numbers import Number import re import sys import threading import time from cycler import cycler import matplotlib import matplotlib.colorbar import matplotlib.image from matplotlib import _api from matplotlib import rcsetup, style from matplotlib import _pylab_helpers, interactive from matplotlib import cbook from matplotlib import _docstring from matplotlib.backend_bases import ( FigureCanvasBase, FigureManagerBase, MouseButton) from matplotlib.figure import Figure, FigureBase, figaspect from matplotlib.gridspec import GridSpec, SubplotSpec from matplotlib import rcParams, rcParamsDefault, get_backend, rcParamsOrig from matplotlib.rcsetup import interactive_bk as _interactive_bk from matplotlib.artist import Artist from matplotlib.axes import Axes, Subplot from matplotlib.projections import PolarAxes from matplotlib import mlab from matplotlib.scale import get_scale_names from matplotlib import cm from matplotlib.cm import _colormaps as colormaps, register_cmap from matplotlib.colors import _color_sequences as color_sequences import numpy as np from matplotlib.colors import Normalize from matplotlib.lines import Line2D from matplotlib.text import Text, Annotation from matplotlib.patches import Polygon, Rectangle, Circle, Arrow from matplotlib.widgets import Button, Slider, Widget from .ticker import ( TickHelper, Formatter, FixedFormatter, NullFormatter, FuncFormatter, FormatStrFormatter, ScalarFormatter, LogFormatter, LogFormatterExponent, LogFormatterMathtext, Locator, IndexLocator, FixedLocator, NullLocator, LinearLocator, LogLocator, AutoLocator, MultipleLocator, MaxNLocator) def gca(): def clabel(CS, levels=None, **kwargs): return gca().clabel(CS, levels=levels, **kwargs)
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from contextlib import ExitStack from enum import Enum import functools import importlib import inspect import logging from numbers import Number import re import sys import threading import time from cycler import cycler import matplotlib import matplotlib.colorbar import matplotlib.image from matplotlib import _api from matplotlib import rcsetup, style from matplotlib import _pylab_helpers, interactive from matplotlib import cbook from matplotlib import _docstring from matplotlib.backend_bases import ( FigureCanvasBase, FigureManagerBase, MouseButton) from matplotlib.figure import Figure, FigureBase, figaspect from matplotlib.gridspec import GridSpec, SubplotSpec from matplotlib import rcParams, rcParamsDefault, get_backend, rcParamsOrig from matplotlib.rcsetup import interactive_bk as _interactive_bk from matplotlib.artist import Artist from matplotlib.axes import Axes, Subplot from matplotlib.projections import PolarAxes from matplotlib import mlab from matplotlib.scale import get_scale_names from matplotlib import cm from matplotlib.cm import _colormaps as colormaps, register_cmap from matplotlib.colors import _color_sequences as color_sequences import numpy as np from matplotlib.colors import Normalize from matplotlib.lines import Line2D from matplotlib.text import Text, Annotation from matplotlib.patches import Polygon, Rectangle, Circle, Arrow from matplotlib.widgets import Button, Slider, Widget from .ticker import ( TickHelper, Formatter, FixedFormatter, NullFormatter, FuncFormatter, FormatStrFormatter, ScalarFormatter, LogFormatter, LogFormatterExponent, LogFormatterMathtext, Locator, IndexLocator, FixedLocator, NullLocator, LinearLocator, LogLocator, AutoLocator, MultipleLocator, MaxNLocator) def gca(): return gcf().gca() def cohere( x, y, NFFT=256, Fs=2, Fc=0, detrend=mlab.detrend_none, window=mlab.window_hanning, noverlap=0, pad_to=None, sides='default', scale_by_freq=None, *, data=None, **kwargs): return gca().cohere( x, y, NFFT=NFFT, Fs=Fs, Fc=Fc, detrend=detrend, window=window, noverlap=noverlap, pad_to=pad_to, sides=sides, scale_by_freq=scale_by_freq, **({"data": data} if data is not None else {}), **kwargs)
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from contextlib import ExitStack from enum import Enum import functools import importlib import inspect import logging from numbers import Number import re import sys import threading import time from cycler import cycler import matplotlib import matplotlib.colorbar import matplotlib.image from matplotlib import _api from matplotlib import rcsetup, style from matplotlib import _pylab_helpers, interactive from matplotlib import cbook from matplotlib import _docstring from matplotlib.backend_bases import ( FigureCanvasBase, FigureManagerBase, MouseButton) from matplotlib.figure import Figure, FigureBase, figaspect from matplotlib.gridspec import GridSpec, SubplotSpec from matplotlib import rcParams, rcParamsDefault, get_backend, rcParamsOrig from matplotlib.rcsetup import interactive_bk as _interactive_bk from matplotlib.artist import Artist from matplotlib.axes import Axes, Subplot from matplotlib.projections import PolarAxes from matplotlib import mlab from matplotlib.scale import get_scale_names from matplotlib import cm from matplotlib.cm import _colormaps as colormaps, register_cmap from matplotlib.colors import _color_sequences as color_sequences import numpy as np from matplotlib.colors import Normalize from matplotlib.lines import Line2D from matplotlib.text import Text, Annotation from matplotlib.patches import Polygon, Rectangle, Circle, Arrow from matplotlib.widgets import Button, Slider, Widget from .ticker import ( TickHelper, Formatter, FixedFormatter, NullFormatter, FuncFormatter, FormatStrFormatter, ScalarFormatter, LogFormatter, LogFormatterExponent, LogFormatterMathtext, Locator, IndexLocator, FixedLocator, NullLocator, LinearLocator, LogLocator, AutoLocator, MultipleLocator, MaxNLocator) def gca(): def sci(im): def contour(*args, data=None, **kwargs): __ret = gca().contour( *args, **({"data": data} if data is not None else {}), **kwargs) if __ret._A is not None: sci(__ret) # noqa return __ret
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from contextlib import ExitStack from enum import Enum import functools import importlib import inspect import logging from numbers import Number import re import sys import threading import time from cycler import cycler import matplotlib import matplotlib.colorbar import matplotlib.image from matplotlib import _api from matplotlib import rcsetup, style from matplotlib import _pylab_helpers, interactive from matplotlib import cbook from matplotlib import _docstring from matplotlib.backend_bases import ( FigureCanvasBase, FigureManagerBase, MouseButton) from matplotlib.figure import Figure, FigureBase, figaspect from matplotlib.gridspec import GridSpec, SubplotSpec from matplotlib import rcParams, rcParamsDefault, get_backend, rcParamsOrig from matplotlib.rcsetup import interactive_bk as _interactive_bk from matplotlib.artist import Artist from matplotlib.axes import Axes, Subplot from matplotlib.projections import PolarAxes from matplotlib import mlab from matplotlib.scale import get_scale_names from matplotlib import cm from matplotlib.cm import _colormaps as colormaps, register_cmap from matplotlib.colors import _color_sequences as color_sequences import numpy as np from matplotlib.colors import Normalize from matplotlib.lines import Line2D from matplotlib.text import Text, Annotation from matplotlib.patches import Polygon, Rectangle, Circle, Arrow from matplotlib.widgets import Button, Slider, Widget from .ticker import ( TickHelper, Formatter, FixedFormatter, NullFormatter, FuncFormatter, FormatStrFormatter, ScalarFormatter, LogFormatter, LogFormatterExponent, LogFormatterMathtext, Locator, IndexLocator, FixedLocator, NullLocator, LinearLocator, LogLocator, AutoLocator, MultipleLocator, MaxNLocator) def gca(): return gcf().gca() def sci(im): return gca()._sci(im) def contourf(*args, data=None, **kwargs): __ret = gca().contourf( *args, **({"data": data} if data is not None else {}), **kwargs) if __ret._A is not None: sci(__ret) # noqa return __ret
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from contextlib import ExitStack from enum import Enum import functools import importlib import inspect import logging from numbers import Number import re import sys import threading import time from cycler import cycler import matplotlib import matplotlib.colorbar import matplotlib.image from matplotlib import _api from matplotlib import rcsetup, style from matplotlib import _pylab_helpers, interactive from matplotlib import cbook from matplotlib import _docstring from matplotlib.backend_bases import ( FigureCanvasBase, FigureManagerBase, MouseButton) from matplotlib.figure import Figure, FigureBase, figaspect from matplotlib.gridspec import GridSpec, SubplotSpec from matplotlib import rcParams, rcParamsDefault, get_backend, rcParamsOrig from matplotlib.rcsetup import interactive_bk as _interactive_bk from matplotlib.artist import Artist from matplotlib.axes import Axes, Subplot from matplotlib.projections import PolarAxes from matplotlib import mlab from matplotlib.scale import get_scale_names from matplotlib import cm from matplotlib.cm import _colormaps as colormaps, register_cmap from matplotlib.colors import _color_sequences as color_sequences import numpy as np from matplotlib.colors import Normalize from matplotlib.lines import Line2D from matplotlib.text import Text, Annotation from matplotlib.patches import Polygon, Rectangle, Circle, Arrow from matplotlib.widgets import Button, Slider, Widget from .ticker import ( TickHelper, Formatter, FixedFormatter, NullFormatter, FuncFormatter, FormatStrFormatter, ScalarFormatter, LogFormatter, LogFormatterExponent, LogFormatterMathtext, Locator, IndexLocator, FixedLocator, NullLocator, LinearLocator, LogLocator, AutoLocator, MultipleLocator, MaxNLocator) def gca(): def csd( x, y, NFFT=None, Fs=None, Fc=None, detrend=None, window=None, noverlap=None, pad_to=None, sides=None, scale_by_freq=None, return_line=None, *, data=None, **kwargs): return gca().csd( x, y, NFFT=NFFT, Fs=Fs, Fc=Fc, detrend=detrend, window=window, noverlap=noverlap, pad_to=pad_to, sides=sides, scale_by_freq=scale_by_freq, return_line=return_line, **({"data": data} if data is not None else {}), **kwargs)
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from contextlib import ExitStack from enum import Enum import functools import importlib import inspect import logging from numbers import Number import re import sys import threading import time from cycler import cycler import matplotlib import matplotlib.colorbar import matplotlib.image from matplotlib import _api from matplotlib import rcsetup, style from matplotlib import _pylab_helpers, interactive from matplotlib import cbook from matplotlib import _docstring from matplotlib.backend_bases import ( FigureCanvasBase, FigureManagerBase, MouseButton) from matplotlib.figure import Figure, FigureBase, figaspect from matplotlib.gridspec import GridSpec, SubplotSpec from matplotlib import rcParams, rcParamsDefault, get_backend, rcParamsOrig from matplotlib.rcsetup import interactive_bk as _interactive_bk from matplotlib.artist import Artist from matplotlib.axes import Axes, Subplot from matplotlib.projections import PolarAxes from matplotlib import mlab from matplotlib.scale import get_scale_names from matplotlib import cm from matplotlib.cm import _colormaps as colormaps, register_cmap from matplotlib.colors import _color_sequences as color_sequences import numpy as np from matplotlib.colors import Normalize from matplotlib.lines import Line2D from matplotlib.text import Text, Annotation from matplotlib.patches import Polygon, Rectangle, Circle, Arrow from matplotlib.widgets import Button, Slider, Widget from .ticker import ( TickHelper, Formatter, FixedFormatter, NullFormatter, FuncFormatter, FormatStrFormatter, ScalarFormatter, LogFormatter, LogFormatterExponent, LogFormatterMathtext, Locator, IndexLocator, FixedLocator, NullLocator, LinearLocator, LogLocator, AutoLocator, MultipleLocator, MaxNLocator) def gca(): def eventplot( positions, orientation='horizontal', lineoffsets=1, linelengths=1, linewidths=None, colors=None, alpha=None, linestyles='solid', *, data=None, **kwargs): return gca().eventplot( positions, orientation=orientation, lineoffsets=lineoffsets, linelengths=linelengths, linewidths=linewidths, colors=colors, alpha=alpha, linestyles=linestyles, **({"data": data} if data is not None else {}), **kwargs)
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from contextlib import ExitStack from enum import Enum import functools import importlib import inspect import logging from numbers import Number import re import sys import threading import time from cycler import cycler import matplotlib import matplotlib.colorbar import matplotlib.image from matplotlib import _api from matplotlib import rcsetup, style from matplotlib import _pylab_helpers, interactive from matplotlib import cbook from matplotlib import _docstring from matplotlib.backend_bases import ( FigureCanvasBase, FigureManagerBase, MouseButton) from matplotlib.figure import Figure, FigureBase, figaspect from matplotlib.gridspec import GridSpec, SubplotSpec from matplotlib import rcParams, rcParamsDefault, get_backend, rcParamsOrig from matplotlib.rcsetup import interactive_bk as _interactive_bk from matplotlib.artist import Artist from matplotlib.axes import Axes, Subplot from matplotlib.projections import PolarAxes from matplotlib import mlab from matplotlib.scale import get_scale_names from matplotlib import cm from matplotlib.cm import _colormaps as colormaps, register_cmap from matplotlib.colors import _color_sequences as color_sequences import numpy as np from matplotlib.colors import Normalize from matplotlib.lines import Line2D from matplotlib.text import Text, Annotation from matplotlib.patches import Polygon, Rectangle, Circle, Arrow from matplotlib.widgets import Button, Slider, Widget from .ticker import ( TickHelper, Formatter, FixedFormatter, NullFormatter, FuncFormatter, FormatStrFormatter, ScalarFormatter, LogFormatter, LogFormatterExponent, LogFormatterMathtext, Locator, IndexLocator, FixedLocator, NullLocator, LinearLocator, LogLocator, AutoLocator, MultipleLocator, MaxNLocator) def gca(): return gcf().gca() def fill_betweenx( y, x1, x2=0, where=None, step=None, interpolate=False, *, data=None, **kwargs): return gca().fill_betweenx( y, x1, x2=x2, where=where, step=step, interpolate=interpolate, **({"data": data} if data is not None else {}), **kwargs)
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from contextlib import ExitStack from enum import Enum import functools import importlib import inspect import logging from numbers import Number import re import sys import threading import time from cycler import cycler import matplotlib import matplotlib.colorbar import matplotlib.image from matplotlib import _api from matplotlib import rcsetup, style from matplotlib import _pylab_helpers, interactive from matplotlib import cbook from matplotlib import _docstring from matplotlib.backend_bases import ( FigureCanvasBase, FigureManagerBase, MouseButton) from matplotlib.figure import Figure, FigureBase, figaspect from matplotlib.gridspec import GridSpec, SubplotSpec from matplotlib import rcParams, rcParamsDefault, get_backend, rcParamsOrig from matplotlib.rcsetup import interactive_bk as _interactive_bk from matplotlib.artist import Artist from matplotlib.axes import Axes, Subplot from matplotlib.projections import PolarAxes from matplotlib import mlab from matplotlib.scale import get_scale_names from matplotlib import cm from matplotlib.cm import _colormaps as colormaps, register_cmap from matplotlib.colors import _color_sequences as color_sequences import numpy as np from matplotlib.colors import Normalize from matplotlib.lines import Line2D from matplotlib.text import Text, Annotation from matplotlib.patches import Polygon, Rectangle, Circle, Arrow from matplotlib.widgets import Button, Slider, Widget from .ticker import ( TickHelper, Formatter, FixedFormatter, NullFormatter, FuncFormatter, FormatStrFormatter, ScalarFormatter, LogFormatter, LogFormatterExponent, LogFormatterMathtext, Locator, IndexLocator, FixedLocator, NullLocator, LinearLocator, LogLocator, AutoLocator, MultipleLocator, MaxNLocator) def gca(): return gcf().gca() def stairs( values, edges=None, *, orientation='vertical', baseline=0, fill=False, data=None, **kwargs): return gca().stairs( values, edges=edges, orientation=orientation, baseline=baseline, fill=fill, **({"data": data} if data is not None else {}), **kwargs)
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from contextlib import ExitStack from enum import Enum import functools import importlib import inspect import logging from numbers import Number import re import sys import threading import time from cycler import cycler import matplotlib import matplotlib.colorbar import matplotlib.image from matplotlib import _api from matplotlib import rcsetup, style from matplotlib import _pylab_helpers, interactive from matplotlib import cbook from matplotlib import _docstring from matplotlib.backend_bases import ( FigureCanvasBase, FigureManagerBase, MouseButton) from matplotlib.figure import Figure, FigureBase, figaspect from matplotlib.gridspec import GridSpec, SubplotSpec from matplotlib import rcParams, rcParamsDefault, get_backend, rcParamsOrig from matplotlib.rcsetup import interactive_bk as _interactive_bk from matplotlib.artist import Artist from matplotlib.axes import Axes, Subplot from matplotlib.projections import PolarAxes from matplotlib import mlab from matplotlib.scale import get_scale_names from matplotlib import cm from matplotlib.cm import _colormaps as colormaps, register_cmap from matplotlib.colors import _color_sequences as color_sequences import numpy as np from matplotlib.colors import Normalize from matplotlib.lines import Line2D from matplotlib.text import Text, Annotation from matplotlib.patches import Polygon, Rectangle, Circle, Arrow from matplotlib.widgets import Button, Slider, Widget from .ticker import ( TickHelper, Formatter, FixedFormatter, NullFormatter, FuncFormatter, FormatStrFormatter, ScalarFormatter, LogFormatter, LogFormatterExponent, LogFormatterMathtext, Locator, IndexLocator, FixedLocator, NullLocator, LinearLocator, LogLocator, AutoLocator, MultipleLocator, MaxNLocator) def gca(): return gcf().gca() def sci(im): return gca()._sci(im) def hist2d( x, y, bins=10, range=None, density=False, weights=None, cmin=None, cmax=None, *, data=None, **kwargs): __ret = gca().hist2d( x, y, bins=bins, range=range, density=density, weights=weights, cmin=cmin, cmax=cmax, **({"data": data} if data is not None else {}), **kwargs) sci(__ret[-1]) return __ret
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from contextlib import ExitStack from enum import Enum import functools import importlib import inspect import logging from numbers import Number import re import sys import threading import time from cycler import cycler import matplotlib import matplotlib.colorbar import matplotlib.image from matplotlib import _api from matplotlib import rcsetup, style from matplotlib import _pylab_helpers, interactive from matplotlib import cbook from matplotlib import _docstring from matplotlib.backend_bases import ( FigureCanvasBase, FigureManagerBase, MouseButton) from matplotlib.figure import Figure, FigureBase, figaspect from matplotlib.gridspec import GridSpec, SubplotSpec from matplotlib import rcParams, rcParamsDefault, get_backend, rcParamsOrig from matplotlib.rcsetup import interactive_bk as _interactive_bk from matplotlib.artist import Artist from matplotlib.axes import Axes, Subplot from matplotlib.projections import PolarAxes from matplotlib import mlab from matplotlib.scale import get_scale_names from matplotlib import cm from matplotlib.cm import _colormaps as colormaps, register_cmap from matplotlib.colors import _color_sequences as color_sequences import numpy as np from matplotlib.colors import Normalize from matplotlib.lines import Line2D from matplotlib.text import Text, Annotation from matplotlib.patches import Polygon, Rectangle, Circle, Arrow from matplotlib.widgets import Button, Slider, Widget from .ticker import ( TickHelper, Formatter, FixedFormatter, NullFormatter, FuncFormatter, FormatStrFormatter, ScalarFormatter, LogFormatter, LogFormatterExponent, LogFormatterMathtext, Locator, IndexLocator, FixedLocator, NullLocator, LinearLocator, LogLocator, AutoLocator, MultipleLocator, MaxNLocator) def gca(): return gcf().gca() def hlines( y, xmin, xmax, colors=None, linestyles='solid', label='', *, data=None, **kwargs): return gca().hlines( y, xmin, xmax, colors=colors, linestyles=linestyles, label=label, **({"data": data} if data is not None else {}), **kwargs)
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from contextlib import ExitStack from enum import Enum import functools import importlib import inspect import logging from numbers import Number import re import sys import threading import time from cycler import cycler import matplotlib import matplotlib.colorbar import matplotlib.image from matplotlib import _api from matplotlib import rcsetup, style from matplotlib import _pylab_helpers, interactive from matplotlib import cbook from matplotlib import _docstring from matplotlib.backend_bases import ( FigureCanvasBase, FigureManagerBase, MouseButton) from matplotlib.figure import Figure, FigureBase, figaspect from matplotlib.gridspec import GridSpec, SubplotSpec from matplotlib import rcParams, rcParamsDefault, get_backend, rcParamsOrig from matplotlib.rcsetup import interactive_bk as _interactive_bk from matplotlib.artist import Artist from matplotlib.axes import Axes, Subplot from matplotlib.projections import PolarAxes from matplotlib import mlab from matplotlib.scale import get_scale_names from matplotlib import cm from matplotlib.cm import _colormaps as colormaps, register_cmap from matplotlib.colors import _color_sequences as color_sequences import numpy as np from matplotlib.colors import Normalize from matplotlib.lines import Line2D from matplotlib.text import Text, Annotation from matplotlib.patches import Polygon, Rectangle, Circle, Arrow from matplotlib.widgets import Button, Slider, Widget from .ticker import ( TickHelper, Formatter, FixedFormatter, NullFormatter, FuncFormatter, FormatStrFormatter, ScalarFormatter, LogFormatter, LogFormatterExponent, LogFormatterMathtext, Locator, IndexLocator, FixedLocator, NullLocator, LinearLocator, LogLocator, AutoLocator, MultipleLocator, MaxNLocator) def gca(): def loglog(*args, **kwargs): return gca().loglog(*args, **kwargs)
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from contextlib import ExitStack from enum import Enum import functools import importlib import inspect import logging from numbers import Number import re import sys import threading import time from cycler import cycler import matplotlib import matplotlib.colorbar import matplotlib.image from matplotlib import _api from matplotlib import rcsetup, style from matplotlib import _pylab_helpers, interactive from matplotlib import cbook from matplotlib import _docstring from matplotlib.backend_bases import ( FigureCanvasBase, FigureManagerBase, MouseButton) from matplotlib.figure import Figure, FigureBase, figaspect from matplotlib.gridspec import GridSpec, SubplotSpec from matplotlib import rcParams, rcParamsDefault, get_backend, rcParamsOrig from matplotlib.rcsetup import interactive_bk as _interactive_bk from matplotlib.artist import Artist from matplotlib.axes import Axes, Subplot from matplotlib.projections import PolarAxes from matplotlib import mlab from matplotlib.scale import get_scale_names from matplotlib import cm from matplotlib.cm import _colormaps as colormaps, register_cmap from matplotlib.colors import _color_sequences as color_sequences import numpy as np from matplotlib.colors import Normalize from matplotlib.lines import Line2D from matplotlib.text import Text, Annotation from matplotlib.patches import Polygon, Rectangle, Circle, Arrow from matplotlib.widgets import Button, Slider, Widget from .ticker import ( TickHelper, Formatter, FixedFormatter, NullFormatter, FuncFormatter, FormatStrFormatter, ScalarFormatter, LogFormatter, LogFormatterExponent, LogFormatterMathtext, Locator, IndexLocator, FixedLocator, NullLocator, LinearLocator, LogLocator, AutoLocator, MultipleLocator, MaxNLocator) def gca(): return gcf().gca() def magnitude_spectrum( x, Fs=None, Fc=None, window=None, pad_to=None, sides=None, scale=None, *, data=None, **kwargs): return gca().magnitude_spectrum( x, Fs=Fs, Fc=Fc, window=window, pad_to=pad_to, sides=sides, scale=scale, **({"data": data} if data is not None else {}), **kwargs)
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from contextlib import ExitStack from enum import Enum import functools import importlib import inspect import logging from numbers import Number import re import sys import threading import time from cycler import cycler import matplotlib import matplotlib.colorbar import matplotlib.image from matplotlib import _api from matplotlib import rcsetup, style from matplotlib import _pylab_helpers, interactive from matplotlib import cbook from matplotlib import _docstring from matplotlib.backend_bases import ( FigureCanvasBase, FigureManagerBase, MouseButton) from matplotlib.figure import Figure, FigureBase, figaspect from matplotlib.gridspec import GridSpec, SubplotSpec from matplotlib import rcParams, rcParamsDefault, get_backend, rcParamsOrig from matplotlib.rcsetup import interactive_bk as _interactive_bk from matplotlib.artist import Artist from matplotlib.axes import Axes, Subplot from matplotlib.projections import PolarAxes from matplotlib import mlab from matplotlib.scale import get_scale_names from matplotlib import cm from matplotlib.cm import _colormaps as colormaps, register_cmap from matplotlib.colors import _color_sequences as color_sequences import numpy as np from matplotlib.colors import Normalize from matplotlib.lines import Line2D from matplotlib.text import Text, Annotation from matplotlib.patches import Polygon, Rectangle, Circle, Arrow from matplotlib.widgets import Button, Slider, Widget from .ticker import ( TickHelper, Formatter, FixedFormatter, NullFormatter, FuncFormatter, FormatStrFormatter, ScalarFormatter, LogFormatter, LogFormatterExponent, LogFormatterMathtext, Locator, IndexLocator, FixedLocator, NullLocator, LinearLocator, LogLocator, AutoLocator, MultipleLocator, MaxNLocator) def gca(): return gcf().gca() def minorticks_off(): return gca().minorticks_off()
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from contextlib import ExitStack from enum import Enum import functools import importlib import inspect import logging from numbers import Number import re import sys import threading import time from cycler import cycler import matplotlib import matplotlib.colorbar import matplotlib.image from matplotlib import _api from matplotlib import rcsetup, style from matplotlib import _pylab_helpers, interactive from matplotlib import cbook from matplotlib import _docstring from matplotlib.backend_bases import ( FigureCanvasBase, FigureManagerBase, MouseButton) from matplotlib.figure import Figure, FigureBase, figaspect from matplotlib.gridspec import GridSpec, SubplotSpec from matplotlib import rcParams, rcParamsDefault, get_backend, rcParamsOrig from matplotlib.rcsetup import interactive_bk as _interactive_bk from matplotlib.artist import Artist from matplotlib.axes import Axes, Subplot from matplotlib.projections import PolarAxes from matplotlib import mlab from matplotlib.scale import get_scale_names from matplotlib import cm from matplotlib.cm import _colormaps as colormaps, register_cmap from matplotlib.colors import _color_sequences as color_sequences import numpy as np from matplotlib.colors import Normalize from matplotlib.lines import Line2D from matplotlib.text import Text, Annotation from matplotlib.patches import Polygon, Rectangle, Circle, Arrow from matplotlib.widgets import Button, Slider, Widget from .ticker import ( TickHelper, Formatter, FixedFormatter, NullFormatter, FuncFormatter, FormatStrFormatter, ScalarFormatter, LogFormatter, LogFormatterExponent, LogFormatterMathtext, Locator, IndexLocator, FixedLocator, NullLocator, LinearLocator, LogLocator, AutoLocator, MultipleLocator, MaxNLocator) def gca(): return gcf().gca() def minorticks_on(): return gca().minorticks_on()
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from contextlib import ExitStack from enum import Enum import functools import importlib import inspect import logging from numbers import Number import re import sys import threading import time from cycler import cycler import matplotlib import matplotlib.colorbar import matplotlib.image from matplotlib import _api from matplotlib import rcsetup, style from matplotlib import _pylab_helpers, interactive from matplotlib import cbook from matplotlib import _docstring from matplotlib.backend_bases import ( FigureCanvasBase, FigureManagerBase, MouseButton) from matplotlib.figure import Figure, FigureBase, figaspect from matplotlib.gridspec import GridSpec, SubplotSpec from matplotlib import rcParams, rcParamsDefault, get_backend, rcParamsOrig from matplotlib.rcsetup import interactive_bk as _interactive_bk from matplotlib.artist import Artist from matplotlib.axes import Axes, Subplot from matplotlib.projections import PolarAxes from matplotlib import mlab from matplotlib.scale import get_scale_names from matplotlib import cm from matplotlib.cm import _colormaps as colormaps, register_cmap from matplotlib.colors import _color_sequences as color_sequences import numpy as np from matplotlib.colors import Normalize from matplotlib.lines import Line2D from matplotlib.text import Text, Annotation from matplotlib.patches import Polygon, Rectangle, Circle, Arrow from matplotlib.widgets import Button, Slider, Widget from .ticker import ( TickHelper, Formatter, FixedFormatter, NullFormatter, FuncFormatter, FormatStrFormatter, ScalarFormatter, LogFormatter, LogFormatterExponent, LogFormatterMathtext, Locator, IndexLocator, FixedLocator, NullLocator, LinearLocator, LogLocator, AutoLocator, MultipleLocator, MaxNLocator) def gca(): def sci(im): def pcolor( *args, shading=None, alpha=None, norm=None, cmap=None, vmin=None, vmax=None, data=None, **kwargs): __ret = gca().pcolor( *args, shading=shading, alpha=alpha, norm=norm, cmap=cmap, vmin=vmin, vmax=vmax, **({"data": data} if data is not None else {}), **kwargs) sci(__ret) return __ret
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from contextlib import ExitStack from enum import Enum import functools import importlib import inspect import logging from numbers import Number import re import sys import threading import time from cycler import cycler import matplotlib import matplotlib.colorbar import matplotlib.image from matplotlib import _api from matplotlib import rcsetup, style from matplotlib import _pylab_helpers, interactive from matplotlib import cbook from matplotlib import _docstring from matplotlib.backend_bases import ( FigureCanvasBase, FigureManagerBase, MouseButton) from matplotlib.figure import Figure, FigureBase, figaspect from matplotlib.gridspec import GridSpec, SubplotSpec from matplotlib import rcParams, rcParamsDefault, get_backend, rcParamsOrig from matplotlib.rcsetup import interactive_bk as _interactive_bk from matplotlib.artist import Artist from matplotlib.axes import Axes, Subplot from matplotlib.projections import PolarAxes from matplotlib import mlab from matplotlib.scale import get_scale_names from matplotlib import cm from matplotlib.cm import _colormaps as colormaps, register_cmap from matplotlib.colors import _color_sequences as color_sequences import numpy as np from matplotlib.colors import Normalize from matplotlib.lines import Line2D from matplotlib.text import Text, Annotation from matplotlib.patches import Polygon, Rectangle, Circle, Arrow from matplotlib.widgets import Button, Slider, Widget from .ticker import ( TickHelper, Formatter, FixedFormatter, NullFormatter, FuncFormatter, FormatStrFormatter, ScalarFormatter, LogFormatter, LogFormatterExponent, LogFormatterMathtext, Locator, IndexLocator, FixedLocator, NullLocator, LinearLocator, LogLocator, AutoLocator, MultipleLocator, MaxNLocator) def gca(): def phase_spectrum( x, Fs=None, Fc=None, window=None, pad_to=None, sides=None, *, data=None, **kwargs): return gca().phase_spectrum( x, Fs=Fs, Fc=Fc, window=window, pad_to=pad_to, sides=sides, **({"data": data} if data is not None else {}), **kwargs)
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from contextlib import ExitStack from enum import Enum import functools import importlib import inspect import logging from numbers import Number import re import sys import threading import time from cycler import cycler import matplotlib import matplotlib.colorbar import matplotlib.image from matplotlib import _api from matplotlib import rcsetup, style from matplotlib import _pylab_helpers, interactive from matplotlib import cbook from matplotlib import _docstring from matplotlib.backend_bases import ( FigureCanvasBase, FigureManagerBase, MouseButton) from matplotlib.figure import Figure, FigureBase, figaspect from matplotlib.gridspec import GridSpec, SubplotSpec from matplotlib import rcParams, rcParamsDefault, get_backend, rcParamsOrig from matplotlib.rcsetup import interactive_bk as _interactive_bk from matplotlib.artist import Artist from matplotlib.axes import Axes, Subplot from matplotlib.projections import PolarAxes from matplotlib import mlab from matplotlib.scale import get_scale_names from matplotlib import cm from matplotlib.cm import _colormaps as colormaps, register_cmap from matplotlib.colors import _color_sequences as color_sequences import numpy as np from matplotlib.colors import Normalize from matplotlib.lines import Line2D from matplotlib.text import Text, Annotation from matplotlib.patches import Polygon, Rectangle, Circle, Arrow from matplotlib.widgets import Button, Slider, Widget from .ticker import ( TickHelper, Formatter, FixedFormatter, NullFormatter, FuncFormatter, FormatStrFormatter, ScalarFormatter, LogFormatter, LogFormatterExponent, LogFormatterMathtext, Locator, IndexLocator, FixedLocator, NullLocator, LinearLocator, LogLocator, AutoLocator, MultipleLocator, MaxNLocator) def gca(): return gcf().gca() def plot_date( x, y, fmt='o', tz=None, xdate=True, ydate=False, *, data=None, **kwargs): return gca().plot_date( x, y, fmt=fmt, tz=tz, xdate=xdate, ydate=ydate, **({"data": data} if data is not None else {}), **kwargs)
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from contextlib import ExitStack from enum import Enum import functools import importlib import inspect import logging from numbers import Number import re import sys import threading import time from cycler import cycler import matplotlib import matplotlib.colorbar import matplotlib.image from matplotlib import _api from matplotlib import rcsetup, style from matplotlib import _pylab_helpers, interactive from matplotlib import cbook from matplotlib import _docstring from matplotlib.backend_bases import ( FigureCanvasBase, FigureManagerBase, MouseButton) from matplotlib.figure import Figure, FigureBase, figaspect from matplotlib.gridspec import GridSpec, SubplotSpec from matplotlib import rcParams, rcParamsDefault, get_backend, rcParamsOrig from matplotlib.rcsetup import interactive_bk as _interactive_bk from matplotlib.artist import Artist from matplotlib.axes import Axes, Subplot from matplotlib.projections import PolarAxes from matplotlib import mlab from matplotlib.scale import get_scale_names from matplotlib import cm from matplotlib.cm import _colormaps as colormaps, register_cmap from matplotlib.colors import _color_sequences as color_sequences import numpy as np from matplotlib.colors import Normalize from matplotlib.lines import Line2D from matplotlib.text import Text, Annotation from matplotlib.patches import Polygon, Rectangle, Circle, Arrow from matplotlib.widgets import Button, Slider, Widget from .ticker import ( TickHelper, Formatter, FixedFormatter, NullFormatter, FuncFormatter, FormatStrFormatter, ScalarFormatter, LogFormatter, LogFormatterExponent, LogFormatterMathtext, Locator, IndexLocator, FixedLocator, NullLocator, LinearLocator, LogLocator, AutoLocator, MultipleLocator, MaxNLocator) def gca(): return gcf().gca() def psd( x, NFFT=None, Fs=None, Fc=None, detrend=None, window=None, noverlap=None, pad_to=None, sides=None, scale_by_freq=None, return_line=None, *, data=None, **kwargs): return gca().psd( x, NFFT=NFFT, Fs=Fs, Fc=Fc, detrend=detrend, window=window, noverlap=noverlap, pad_to=pad_to, sides=sides, scale_by_freq=scale_by_freq, return_line=return_line, **({"data": data} if data is not None else {}), **kwargs)
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from contextlib import ExitStack from enum import Enum import functools import importlib import inspect import logging from numbers import Number import re import sys import threading import time from cycler import cycler import matplotlib import matplotlib.colorbar import matplotlib.image from matplotlib import _api from matplotlib import rcsetup, style from matplotlib import _pylab_helpers, interactive from matplotlib import cbook from matplotlib import _docstring from matplotlib.backend_bases import ( FigureCanvasBase, FigureManagerBase, MouseButton) from matplotlib.figure import Figure, FigureBase, figaspect from matplotlib.gridspec import GridSpec, SubplotSpec from matplotlib import rcParams, rcParamsDefault, get_backend, rcParamsOrig from matplotlib.rcsetup import interactive_bk as _interactive_bk from matplotlib.artist import Artist from matplotlib.axes import Axes, Subplot from matplotlib.projections import PolarAxes from matplotlib import mlab from matplotlib.scale import get_scale_names from matplotlib import cm from matplotlib.cm import _colormaps as colormaps, register_cmap from matplotlib.colors import _color_sequences as color_sequences import numpy as np from matplotlib.colors import Normalize from matplotlib.lines import Line2D from matplotlib.text import Text, Annotation from matplotlib.patches import Polygon, Rectangle, Circle, Arrow from matplotlib.widgets import Button, Slider, Widget from .ticker import ( TickHelper, Formatter, FixedFormatter, NullFormatter, FuncFormatter, FormatStrFormatter, ScalarFormatter, LogFormatter, LogFormatterExponent, LogFormatterMathtext, Locator, IndexLocator, FixedLocator, NullLocator, LinearLocator, LogLocator, AutoLocator, MultipleLocator, MaxNLocator) def gca(): return gcf().gca() def sci(im): return gca()._sci(im) def quiver(*args, data=None, **kwargs): __ret = gca().quiver( *args, **({"data": data} if data is not None else {}), **kwargs) sci(__ret) return __ret
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from contextlib import ExitStack from enum import Enum import functools import importlib import inspect import logging from numbers import Number import re import sys import threading import time from cycler import cycler import matplotlib import matplotlib.colorbar import matplotlib.image from matplotlib import _api from matplotlib import rcsetup, style from matplotlib import _pylab_helpers, interactive from matplotlib import cbook from matplotlib import _docstring from matplotlib.backend_bases import ( FigureCanvasBase, FigureManagerBase, MouseButton) from matplotlib.figure import Figure, FigureBase, figaspect from matplotlib.gridspec import GridSpec, SubplotSpec from matplotlib import rcParams, rcParamsDefault, get_backend, rcParamsOrig from matplotlib.rcsetup import interactive_bk as _interactive_bk from matplotlib.artist import Artist from matplotlib.axes import Axes, Subplot from matplotlib.projections import PolarAxes from matplotlib import mlab from matplotlib.scale import get_scale_names from matplotlib import cm from matplotlib.cm import _colormaps as colormaps, register_cmap from matplotlib.colors import _color_sequences as color_sequences import numpy as np from matplotlib.colors import Normalize from matplotlib.lines import Line2D from matplotlib.text import Text, Annotation from matplotlib.patches import Polygon, Rectangle, Circle, Arrow from matplotlib.widgets import Button, Slider, Widget from .ticker import ( TickHelper, Formatter, FixedFormatter, NullFormatter, FuncFormatter, FormatStrFormatter, ScalarFormatter, LogFormatter, LogFormatterExponent, LogFormatterMathtext, Locator, IndexLocator, FixedLocator, NullLocator, LinearLocator, LogLocator, AutoLocator, MultipleLocator, MaxNLocator) def gca(): return gcf().gca() def quiverkey(Q, X, Y, U, label, **kwargs): return gca().quiverkey(Q, X, Y, U, label, **kwargs)
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from contextlib import ExitStack from enum import Enum import functools import importlib import inspect import logging from numbers import Number import re import sys import threading import time from cycler import cycler import matplotlib import matplotlib.colorbar import matplotlib.image from matplotlib import _api from matplotlib import rcsetup, style from matplotlib import _pylab_helpers, interactive from matplotlib import cbook from matplotlib import _docstring from matplotlib.backend_bases import ( FigureCanvasBase, FigureManagerBase, MouseButton) from matplotlib.figure import Figure, FigureBase, figaspect from matplotlib.gridspec import GridSpec, SubplotSpec from matplotlib import rcParams, rcParamsDefault, get_backend, rcParamsOrig from matplotlib.rcsetup import interactive_bk as _interactive_bk from matplotlib.artist import Artist from matplotlib.axes import Axes, Subplot from matplotlib.projections import PolarAxes from matplotlib import mlab from matplotlib.scale import get_scale_names from matplotlib import cm from matplotlib.cm import _colormaps as colormaps, register_cmap from matplotlib.colors import _color_sequences as color_sequences import numpy as np from matplotlib.colors import Normalize from matplotlib.lines import Line2D from matplotlib.text import Text, Annotation from matplotlib.patches import Polygon, Rectangle, Circle, Arrow from matplotlib.widgets import Button, Slider, Widget from .ticker import ( TickHelper, Formatter, FixedFormatter, NullFormatter, FuncFormatter, FormatStrFormatter, ScalarFormatter, LogFormatter, LogFormatterExponent, LogFormatterMathtext, Locator, IndexLocator, FixedLocator, NullLocator, LinearLocator, LogLocator, AutoLocator, MultipleLocator, MaxNLocator) def gca(): return gcf().gca() def semilogx(*args, **kwargs): return gca().semilogx(*args, **kwargs)
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from contextlib import ExitStack from enum import Enum import functools import importlib import inspect import logging from numbers import Number import re import sys import threading import time from cycler import cycler import matplotlib import matplotlib.colorbar import matplotlib.image from matplotlib import _api from matplotlib import rcsetup, style from matplotlib import _pylab_helpers, interactive from matplotlib import cbook from matplotlib import _docstring from matplotlib.backend_bases import ( FigureCanvasBase, FigureManagerBase, MouseButton) from matplotlib.figure import Figure, FigureBase, figaspect from matplotlib.gridspec import GridSpec, SubplotSpec from matplotlib import rcParams, rcParamsDefault, get_backend, rcParamsOrig from matplotlib.rcsetup import interactive_bk as _interactive_bk from matplotlib.artist import Artist from matplotlib.axes import Axes, Subplot from matplotlib.projections import PolarAxes from matplotlib import mlab from matplotlib.scale import get_scale_names from matplotlib import cm from matplotlib.cm import _colormaps as colormaps, register_cmap from matplotlib.colors import _color_sequences as color_sequences import numpy as np from matplotlib.colors import Normalize from matplotlib.lines import Line2D from matplotlib.text import Text, Annotation from matplotlib.patches import Polygon, Rectangle, Circle, Arrow from matplotlib.widgets import Button, Slider, Widget from .ticker import ( TickHelper, Formatter, FixedFormatter, NullFormatter, FuncFormatter, FormatStrFormatter, ScalarFormatter, LogFormatter, LogFormatterExponent, LogFormatterMathtext, Locator, IndexLocator, FixedLocator, NullLocator, LinearLocator, LogLocator, AutoLocator, MultipleLocator, MaxNLocator) def gca(): def semilogy(*args, **kwargs): return gca().semilogy(*args, **kwargs)
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from contextlib import ExitStack from enum import Enum import functools import importlib import inspect import logging from numbers import Number import re import sys import threading import time from cycler import cycler import matplotlib import matplotlib.colorbar import matplotlib.image from matplotlib import _api from matplotlib import rcsetup, style from matplotlib import _pylab_helpers, interactive from matplotlib import cbook from matplotlib import _docstring from matplotlib.backend_bases import ( FigureCanvasBase, FigureManagerBase, MouseButton) from matplotlib.figure import Figure, FigureBase, figaspect from matplotlib.gridspec import GridSpec, SubplotSpec from matplotlib import rcParams, rcParamsDefault, get_backend, rcParamsOrig from matplotlib.rcsetup import interactive_bk as _interactive_bk from matplotlib.artist import Artist from matplotlib.axes import Axes, Subplot from matplotlib.projections import PolarAxes from matplotlib import mlab from matplotlib.scale import get_scale_names from matplotlib import cm from matplotlib.cm import _colormaps as colormaps, register_cmap from matplotlib.colors import _color_sequences as color_sequences import numpy as np from matplotlib.colors import Normalize from matplotlib.lines import Line2D from matplotlib.text import Text, Annotation from matplotlib.patches import Polygon, Rectangle, Circle, Arrow from matplotlib.widgets import Button, Slider, Widget from .ticker import ( TickHelper, Formatter, FixedFormatter, NullFormatter, FuncFormatter, FormatStrFormatter, ScalarFormatter, LogFormatter, LogFormatterExponent, LogFormatterMathtext, Locator, IndexLocator, FixedLocator, NullLocator, LinearLocator, LogLocator, AutoLocator, MultipleLocator, MaxNLocator) def gca(): return gcf().gca() def sci(im): return gca()._sci(im) def specgram( x, NFFT=None, Fs=None, Fc=None, detrend=None, window=None, noverlap=None, cmap=None, xextent=None, pad_to=None, sides=None, scale_by_freq=None, mode=None, scale=None, vmin=None, vmax=None, *, data=None, **kwargs): __ret = gca().specgram( x, NFFT=NFFT, Fs=Fs, Fc=Fc, detrend=detrend, window=window, noverlap=noverlap, cmap=cmap, xextent=xextent, pad_to=pad_to, sides=sides, scale_by_freq=scale_by_freq, mode=mode, scale=scale, vmin=vmin, vmax=vmax, **({"data": data} if data is not None else {}), **kwargs) sci(__ret[-1]) return __ret
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from contextlib import ExitStack from enum import Enum import functools import importlib import inspect import logging from numbers import Number import re import sys import threading import time from cycler import cycler import matplotlib import matplotlib.colorbar import matplotlib.image from matplotlib import _api from matplotlib import rcsetup, style from matplotlib import _pylab_helpers, interactive from matplotlib import cbook from matplotlib import _docstring from matplotlib.backend_bases import ( FigureCanvasBase, FigureManagerBase, MouseButton) from matplotlib.figure import Figure, FigureBase, figaspect from matplotlib.gridspec import GridSpec, SubplotSpec from matplotlib import rcParams, rcParamsDefault, get_backend, rcParamsOrig from matplotlib.rcsetup import interactive_bk as _interactive_bk from matplotlib.artist import Artist from matplotlib.axes import Axes, Subplot from matplotlib.projections import PolarAxes from matplotlib import mlab from matplotlib.scale import get_scale_names from matplotlib import cm from matplotlib.cm import _colormaps as colormaps, register_cmap from matplotlib.colors import _color_sequences as color_sequences import numpy as np from matplotlib.colors import Normalize from matplotlib.lines import Line2D from matplotlib.text import Text, Annotation from matplotlib.patches import Polygon, Rectangle, Circle, Arrow from matplotlib.widgets import Button, Slider, Widget from .ticker import ( TickHelper, Formatter, FixedFormatter, NullFormatter, FuncFormatter, FormatStrFormatter, ScalarFormatter, LogFormatter, LogFormatterExponent, LogFormatterMathtext, Locator, IndexLocator, FixedLocator, NullLocator, LinearLocator, LogLocator, AutoLocator, MultipleLocator, MaxNLocator) def gca(): return gcf().gca() def sci(im): return gca()._sci(im) def spy( Z, precision=0, marker=None, markersize=None, aspect='equal', origin='upper', **kwargs): __ret = gca().spy( Z, precision=precision, marker=marker, markersize=markersize, aspect=aspect, origin=origin, **kwargs) if isinstance(__ret, cm.ScalarMappable): sci(__ret) # noqa return __ret
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from contextlib import ExitStack from enum import Enum import functools import importlib import inspect import logging from numbers import Number import re import sys import threading import time from cycler import cycler import matplotlib import matplotlib.colorbar import matplotlib.image from matplotlib import _api from matplotlib import rcsetup, style from matplotlib import _pylab_helpers, interactive from matplotlib import cbook from matplotlib import _docstring from matplotlib.backend_bases import ( FigureCanvasBase, FigureManagerBase, MouseButton) from matplotlib.figure import Figure, FigureBase, figaspect from matplotlib.gridspec import GridSpec, SubplotSpec from matplotlib import rcParams, rcParamsDefault, get_backend, rcParamsOrig from matplotlib.rcsetup import interactive_bk as _interactive_bk from matplotlib.artist import Artist from matplotlib.axes import Axes, Subplot from matplotlib.projections import PolarAxes from matplotlib import mlab from matplotlib.scale import get_scale_names from matplotlib import cm from matplotlib.cm import _colormaps as colormaps, register_cmap from matplotlib.colors import _color_sequences as color_sequences import numpy as np from matplotlib.colors import Normalize from matplotlib.lines import Line2D from matplotlib.text import Text, Annotation from matplotlib.patches import Polygon, Rectangle, Circle, Arrow from matplotlib.widgets import Button, Slider, Widget from .ticker import ( TickHelper, Formatter, FixedFormatter, NullFormatter, FuncFormatter, FormatStrFormatter, ScalarFormatter, LogFormatter, LogFormatterExponent, LogFormatterMathtext, Locator, IndexLocator, FixedLocator, NullLocator, LinearLocator, LogLocator, AutoLocator, MultipleLocator, MaxNLocator) def gca(): return gcf().gca() def stackplot( x, *args, labels=(), colors=None, baseline='zero', data=None, **kwargs): return gca().stackplot( x, *args, labels=labels, colors=colors, baseline=baseline, **({"data": data} if data is not None else {}), **kwargs)
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from contextlib import ExitStack from enum import Enum import functools import importlib import inspect import logging from numbers import Number import re import sys import threading import time from cycler import cycler import matplotlib import matplotlib.colorbar import matplotlib.image from matplotlib import _api from matplotlib import rcsetup, style from matplotlib import _pylab_helpers, interactive from matplotlib import cbook from matplotlib import _docstring from matplotlib.backend_bases import ( FigureCanvasBase, FigureManagerBase, MouseButton) from matplotlib.figure import Figure, FigureBase, figaspect from matplotlib.gridspec import GridSpec, SubplotSpec from matplotlib import rcParams, rcParamsDefault, get_backend, rcParamsOrig from matplotlib.rcsetup import interactive_bk as _interactive_bk from matplotlib.artist import Artist from matplotlib.axes import Axes, Subplot from matplotlib.projections import PolarAxes from matplotlib import mlab from matplotlib.scale import get_scale_names from matplotlib import cm from matplotlib.cm import _colormaps as colormaps, register_cmap from matplotlib.colors import _color_sequences as color_sequences import numpy as np from matplotlib.colors import Normalize from matplotlib.lines import Line2D from matplotlib.text import Text, Annotation from matplotlib.patches import Polygon, Rectangle, Circle, Arrow from matplotlib.widgets import Button, Slider, Widget from .ticker import ( TickHelper, Formatter, FixedFormatter, NullFormatter, FuncFormatter, FormatStrFormatter, ScalarFormatter, LogFormatter, LogFormatterExponent, LogFormatterMathtext, Locator, IndexLocator, FixedLocator, NullLocator, LinearLocator, LogLocator, AutoLocator, MultipleLocator, MaxNLocator) def gca(): return gcf().gca() def stem( *args, linefmt=None, markerfmt=None, basefmt=None, bottom=0, label=None, use_line_collection=_api.deprecation._deprecated_parameter, orientation='vertical', data=None): return gca().stem( *args, linefmt=linefmt, markerfmt=markerfmt, basefmt=basefmt, bottom=bottom, label=label, use_line_collection=use_line_collection, orientation=orientation, **({"data": data} if data is not None else {}))
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from contextlib import ExitStack from enum import Enum import functools import importlib import inspect import logging from numbers import Number import re import sys import threading import time from cycler import cycler import matplotlib import matplotlib.colorbar import matplotlib.image from matplotlib import _api from matplotlib import rcsetup, style from matplotlib import _pylab_helpers, interactive from matplotlib import cbook from matplotlib import _docstring from matplotlib.backend_bases import ( FigureCanvasBase, FigureManagerBase, MouseButton) from matplotlib.figure import Figure, FigureBase, figaspect from matplotlib.gridspec import GridSpec, SubplotSpec from matplotlib import rcParams, rcParamsDefault, get_backend, rcParamsOrig from matplotlib.rcsetup import interactive_bk as _interactive_bk from matplotlib.artist import Artist from matplotlib.axes import Axes, Subplot from matplotlib.projections import PolarAxes from matplotlib import mlab from matplotlib.scale import get_scale_names from matplotlib import cm from matplotlib.cm import _colormaps as colormaps, register_cmap from matplotlib.colors import _color_sequences as color_sequences import numpy as np from matplotlib.colors import Normalize from matplotlib.lines import Line2D from matplotlib.text import Text, Annotation from matplotlib.patches import Polygon, Rectangle, Circle, Arrow from matplotlib.widgets import Button, Slider, Widget from .ticker import ( TickHelper, Formatter, FixedFormatter, NullFormatter, FuncFormatter, FormatStrFormatter, ScalarFormatter, LogFormatter, LogFormatterExponent, LogFormatterMathtext, Locator, IndexLocator, FixedLocator, NullLocator, LinearLocator, LogLocator, AutoLocator, MultipleLocator, MaxNLocator) def gca(): def sci(im): def streamplot( x, y, u, v, density=1, linewidth=None, color=None, cmap=None, norm=None, arrowsize=1, arrowstyle='-|>', minlength=0.1, transform=None, zorder=None, start_points=None, maxlength=4.0, integration_direction='both', broken_streamlines=True, *, data=None): __ret = gca().streamplot( x, y, u, v, density=density, linewidth=linewidth, color=color, cmap=cmap, norm=norm, arrowsize=arrowsize, arrowstyle=arrowstyle, minlength=minlength, transform=transform, zorder=zorder, start_points=start_points, maxlength=maxlength, integration_direction=integration_direction, broken_streamlines=broken_streamlines, **({"data": data} if data is not None else {})) sci(__ret.lines) return __ret
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from contextlib import ExitStack from enum import Enum import functools import importlib import inspect import logging from numbers import Number import re import sys import threading import time from cycler import cycler import matplotlib import matplotlib.colorbar import matplotlib.image from matplotlib import _api from matplotlib import rcsetup, style from matplotlib import _pylab_helpers, interactive from matplotlib import cbook from matplotlib import _docstring from matplotlib.backend_bases import ( FigureCanvasBase, FigureManagerBase, MouseButton) from matplotlib.figure import Figure, FigureBase, figaspect from matplotlib.gridspec import GridSpec, SubplotSpec from matplotlib import rcParams, rcParamsDefault, get_backend, rcParamsOrig from matplotlib.rcsetup import interactive_bk as _interactive_bk from matplotlib.artist import Artist from matplotlib.axes import Axes, Subplot from matplotlib.projections import PolarAxes from matplotlib import mlab from matplotlib.scale import get_scale_names from matplotlib import cm from matplotlib.cm import _colormaps as colormaps, register_cmap from matplotlib.colors import _color_sequences as color_sequences import numpy as np from matplotlib.colors import Normalize from matplotlib.lines import Line2D from matplotlib.text import Text, Annotation from matplotlib.patches import Polygon, Rectangle, Circle, Arrow from matplotlib.widgets import Button, Slider, Widget from .ticker import ( TickHelper, Formatter, FixedFormatter, NullFormatter, FuncFormatter, FormatStrFormatter, ScalarFormatter, LogFormatter, LogFormatterExponent, LogFormatterMathtext, Locator, IndexLocator, FixedLocator, NullLocator, LinearLocator, LogLocator, AutoLocator, MultipleLocator, MaxNLocator) def gca(): return gcf().gca() def table( cellText=None, cellColours=None, cellLoc='right', colWidths=None, rowLabels=None, rowColours=None, rowLoc='left', colLabels=None, colColours=None, colLoc='center', loc='bottom', bbox=None, edges='closed', **kwargs): return gca().table( cellText=cellText, cellColours=cellColours, cellLoc=cellLoc, colWidths=colWidths, rowLabels=rowLabels, rowColours=rowColours, rowLoc=rowLoc, colLabels=colLabels, colColours=colColours, colLoc=colLoc, loc=loc, bbox=bbox, edges=edges, **kwargs)
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from contextlib import ExitStack from enum import Enum import functools import importlib import inspect import logging from numbers import Number import re import sys import threading import time from cycler import cycler import matplotlib import matplotlib.colorbar import matplotlib.image from matplotlib import _api from matplotlib import rcsetup, style from matplotlib import _pylab_helpers, interactive from matplotlib import cbook from matplotlib import _docstring from matplotlib.backend_bases import ( FigureCanvasBase, FigureManagerBase, MouseButton) from matplotlib.figure import Figure, FigureBase, figaspect from matplotlib.gridspec import GridSpec, SubplotSpec from matplotlib import rcParams, rcParamsDefault, get_backend, rcParamsOrig from matplotlib.rcsetup import interactive_bk as _interactive_bk from matplotlib.artist import Artist from matplotlib.axes import Axes, Subplot from matplotlib.projections import PolarAxes from matplotlib import mlab from matplotlib.scale import get_scale_names from matplotlib import cm from matplotlib.cm import _colormaps as colormaps, register_cmap from matplotlib.colors import _color_sequences as color_sequences import numpy as np from matplotlib.colors import Normalize from matplotlib.lines import Line2D from matplotlib.text import Text, Annotation from matplotlib.patches import Polygon, Rectangle, Circle, Arrow from matplotlib.widgets import Button, Slider, Widget from .ticker import ( TickHelper, Formatter, FixedFormatter, NullFormatter, FuncFormatter, FormatStrFormatter, ScalarFormatter, LogFormatter, LogFormatterExponent, LogFormatterMathtext, Locator, IndexLocator, FixedLocator, NullLocator, LinearLocator, LogLocator, AutoLocator, MultipleLocator, MaxNLocator) def gca(): return gcf().gca() def ticklabel_format( *, axis='both', style='', scilimits=None, useOffset=None, useLocale=None, useMathText=None): return gca().ticklabel_format( axis=axis, style=style, scilimits=scilimits, useOffset=useOffset, useLocale=useLocale, useMathText=useMathText)
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from contextlib import ExitStack from enum import Enum import functools import importlib import inspect import logging from numbers import Number import re import sys import threading import time from cycler import cycler import matplotlib import matplotlib.colorbar import matplotlib.image from matplotlib import _api from matplotlib import rcsetup, style from matplotlib import _pylab_helpers, interactive from matplotlib import cbook from matplotlib import _docstring from matplotlib.backend_bases import ( FigureCanvasBase, FigureManagerBase, MouseButton) from matplotlib.figure import Figure, FigureBase, figaspect from matplotlib.gridspec import GridSpec, SubplotSpec from matplotlib import rcParams, rcParamsDefault, get_backend, rcParamsOrig from matplotlib.rcsetup import interactive_bk as _interactive_bk from matplotlib.artist import Artist from matplotlib.axes import Axes, Subplot from matplotlib.projections import PolarAxes from matplotlib import mlab from matplotlib.scale import get_scale_names from matplotlib import cm from matplotlib.cm import _colormaps as colormaps, register_cmap from matplotlib.colors import _color_sequences as color_sequences import numpy as np from matplotlib.colors import Normalize from matplotlib.lines import Line2D from matplotlib.text import Text, Annotation from matplotlib.patches import Polygon, Rectangle, Circle, Arrow from matplotlib.widgets import Button, Slider, Widget from .ticker import ( TickHelper, Formatter, FixedFormatter, NullFormatter, FuncFormatter, FormatStrFormatter, ScalarFormatter, LogFormatter, LogFormatterExponent, LogFormatterMathtext, Locator, IndexLocator, FixedLocator, NullLocator, LinearLocator, LogLocator, AutoLocator, MultipleLocator, MaxNLocator) def gca(): return gcf().gca() def sci(im): return gca()._sci(im) def tricontour(*args, **kwargs): __ret = gca().tricontour(*args, **kwargs) if __ret._A is not None: sci(__ret) # noqa return __ret
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from contextlib import ExitStack from enum import Enum import functools import importlib import inspect import logging from numbers import Number import re import sys import threading import time from cycler import cycler import matplotlib import matplotlib.colorbar import matplotlib.image from matplotlib import _api from matplotlib import rcsetup, style from matplotlib import _pylab_helpers, interactive from matplotlib import cbook from matplotlib import _docstring from matplotlib.backend_bases import ( FigureCanvasBase, FigureManagerBase, MouseButton) from matplotlib.figure import Figure, FigureBase, figaspect from matplotlib.gridspec import GridSpec, SubplotSpec from matplotlib import rcParams, rcParamsDefault, get_backend, rcParamsOrig from matplotlib.rcsetup import interactive_bk as _interactive_bk from matplotlib.artist import Artist from matplotlib.axes import Axes, Subplot from matplotlib.projections import PolarAxes from matplotlib import mlab from matplotlib.scale import get_scale_names from matplotlib import cm from matplotlib.cm import _colormaps as colormaps, register_cmap from matplotlib.colors import _color_sequences as color_sequences import numpy as np from matplotlib.colors import Normalize from matplotlib.lines import Line2D from matplotlib.text import Text, Annotation from matplotlib.patches import Polygon, Rectangle, Circle, Arrow from matplotlib.widgets import Button, Slider, Widget from .ticker import ( TickHelper, Formatter, FixedFormatter, NullFormatter, FuncFormatter, FormatStrFormatter, ScalarFormatter, LogFormatter, LogFormatterExponent, LogFormatterMathtext, Locator, IndexLocator, FixedLocator, NullLocator, LinearLocator, LogLocator, AutoLocator, MultipleLocator, MaxNLocator) def gca(): return gcf().gca() def sci(im): return gca()._sci(im) def tricontourf(*args, **kwargs): __ret = gca().tricontourf(*args, **kwargs) if __ret._A is not None: sci(__ret) # noqa return __ret
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from contextlib import ExitStack from enum import Enum import functools import importlib import inspect import logging from numbers import Number import re import sys import threading import time from cycler import cycler import matplotlib import matplotlib.colorbar import matplotlib.image from matplotlib import _api from matplotlib import rcsetup, style from matplotlib import _pylab_helpers, interactive from matplotlib import cbook from matplotlib import _docstring from matplotlib.backend_bases import ( FigureCanvasBase, FigureManagerBase, MouseButton) from matplotlib.figure import Figure, FigureBase, figaspect from matplotlib.gridspec import GridSpec, SubplotSpec from matplotlib import rcParams, rcParamsDefault, get_backend, rcParamsOrig from matplotlib.rcsetup import interactive_bk as _interactive_bk from matplotlib.artist import Artist from matplotlib.axes import Axes, Subplot from matplotlib.projections import PolarAxes from matplotlib import mlab from matplotlib.scale import get_scale_names from matplotlib import cm from matplotlib.cm import _colormaps as colormaps, register_cmap from matplotlib.colors import _color_sequences as color_sequences import numpy as np from matplotlib.colors import Normalize from matplotlib.lines import Line2D from matplotlib.text import Text, Annotation from matplotlib.patches import Polygon, Rectangle, Circle, Arrow from matplotlib.widgets import Button, Slider, Widget from .ticker import ( TickHelper, Formatter, FixedFormatter, NullFormatter, FuncFormatter, FormatStrFormatter, ScalarFormatter, LogFormatter, LogFormatterExponent, LogFormatterMathtext, Locator, IndexLocator, FixedLocator, NullLocator, LinearLocator, LogLocator, AutoLocator, MultipleLocator, MaxNLocator) def gca(): return gcf().gca() def sci(im): return gca()._sci(im) def tripcolor( *args, alpha=1.0, norm=None, cmap=None, vmin=None, vmax=None, shading='flat', facecolors=None, **kwargs): __ret = gca().tripcolor( *args, alpha=alpha, norm=norm, cmap=cmap, vmin=vmin, vmax=vmax, shading=shading, facecolors=facecolors, **kwargs) sci(__ret) return __ret
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from contextlib import ExitStack from enum import Enum import functools import importlib import inspect import logging from numbers import Number import re import sys import threading import time from cycler import cycler import matplotlib import matplotlib.colorbar import matplotlib.image from matplotlib import _api from matplotlib import rcsetup, style from matplotlib import _pylab_helpers, interactive from matplotlib import cbook from matplotlib import _docstring from matplotlib.backend_bases import ( FigureCanvasBase, FigureManagerBase, MouseButton) from matplotlib.figure import Figure, FigureBase, figaspect from matplotlib.gridspec import GridSpec, SubplotSpec from matplotlib import rcParams, rcParamsDefault, get_backend, rcParamsOrig from matplotlib.rcsetup import interactive_bk as _interactive_bk from matplotlib.artist import Artist from matplotlib.axes import Axes, Subplot from matplotlib.projections import PolarAxes from matplotlib import mlab from matplotlib.scale import get_scale_names from matplotlib import cm from matplotlib.cm import _colormaps as colormaps, register_cmap from matplotlib.colors import _color_sequences as color_sequences import numpy as np from matplotlib.colors import Normalize from matplotlib.lines import Line2D from matplotlib.text import Text, Annotation from matplotlib.patches import Polygon, Rectangle, Circle, Arrow from matplotlib.widgets import Button, Slider, Widget from .ticker import ( TickHelper, Formatter, FixedFormatter, NullFormatter, FuncFormatter, FormatStrFormatter, ScalarFormatter, LogFormatter, LogFormatterExponent, LogFormatterMathtext, Locator, IndexLocator, FixedLocator, NullLocator, LinearLocator, LogLocator, AutoLocator, MultipleLocator, MaxNLocator) def gca(): def triplot(*args, **kwargs): return gca().triplot(*args, **kwargs)
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from contextlib import ExitStack from enum import Enum import functools import importlib import inspect import logging from numbers import Number import re import sys import threading import time from cycler import cycler import matplotlib import matplotlib.colorbar import matplotlib.image from matplotlib import _api from matplotlib import rcsetup, style from matplotlib import _pylab_helpers, interactive from matplotlib import cbook from matplotlib import _docstring from matplotlib.backend_bases import ( FigureCanvasBase, FigureManagerBase, MouseButton) from matplotlib.figure import Figure, FigureBase, figaspect from matplotlib.gridspec import GridSpec, SubplotSpec from matplotlib import rcParams, rcParamsDefault, get_backend, rcParamsOrig from matplotlib.rcsetup import interactive_bk as _interactive_bk from matplotlib.artist import Artist from matplotlib.axes import Axes, Subplot from matplotlib.projections import PolarAxes from matplotlib import mlab from matplotlib.scale import get_scale_names from matplotlib import cm from matplotlib.cm import _colormaps as colormaps, register_cmap from matplotlib.colors import _color_sequences as color_sequences import numpy as np from matplotlib.colors import Normalize from matplotlib.lines import Line2D from matplotlib.text import Text, Annotation from matplotlib.patches import Polygon, Rectangle, Circle, Arrow from matplotlib.widgets import Button, Slider, Widget from .ticker import ( TickHelper, Formatter, FixedFormatter, NullFormatter, FuncFormatter, FormatStrFormatter, ScalarFormatter, LogFormatter, LogFormatterExponent, LogFormatterMathtext, Locator, IndexLocator, FixedLocator, NullLocator, LinearLocator, LogLocator, AutoLocator, MultipleLocator, MaxNLocator) def gca(): return gcf().gca() def violinplot( dataset, positions=None, vert=True, widths=0.5, showmeans=False, showextrema=True, showmedians=False, quantiles=None, points=100, bw_method=None, *, data=None): return gca().violinplot( dataset, positions=positions, vert=vert, widths=widths, showmeans=showmeans, showextrema=showextrema, showmedians=showmedians, quantiles=quantiles, points=points, bw_method=bw_method, **({"data": data} if data is not None else {}))
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from contextlib import ExitStack from enum import Enum import functools import importlib import inspect import logging from numbers import Number import re import sys import threading import time from cycler import cycler import matplotlib import matplotlib.colorbar import matplotlib.image from matplotlib import _api from matplotlib import rcsetup, style from matplotlib import _pylab_helpers, interactive from matplotlib import cbook from matplotlib import _docstring from matplotlib.backend_bases import ( FigureCanvasBase, FigureManagerBase, MouseButton) from matplotlib.figure import Figure, FigureBase, figaspect from matplotlib.gridspec import GridSpec, SubplotSpec from matplotlib import rcParams, rcParamsDefault, get_backend, rcParamsOrig from matplotlib.rcsetup import interactive_bk as _interactive_bk from matplotlib.artist import Artist from matplotlib.axes import Axes, Subplot from matplotlib.projections import PolarAxes from matplotlib import mlab from matplotlib.scale import get_scale_names from matplotlib import cm from matplotlib.cm import _colormaps as colormaps, register_cmap from matplotlib.colors import _color_sequences as color_sequences import numpy as np from matplotlib.colors import Normalize from matplotlib.lines import Line2D from matplotlib.text import Text, Annotation from matplotlib.patches import Polygon, Rectangle, Circle, Arrow from matplotlib.widgets import Button, Slider, Widget from .ticker import ( TickHelper, Formatter, FixedFormatter, NullFormatter, FuncFormatter, FormatStrFormatter, ScalarFormatter, LogFormatter, LogFormatterExponent, LogFormatterMathtext, Locator, IndexLocator, FixedLocator, NullLocator, LinearLocator, LogLocator, AutoLocator, MultipleLocator, MaxNLocator) def gca(): return gcf().gca() def vlines( x, ymin, ymax, colors=None, linestyles='solid', label='', *, data=None, **kwargs): return gca().vlines( x, ymin, ymax, colors=colors, linestyles=linestyles, label=label, **({"data": data} if data is not None else {}), **kwargs)
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from contextlib import ExitStack from enum import Enum import functools import importlib import inspect import logging from numbers import Number import re import sys import threading import time from cycler import cycler import matplotlib import matplotlib.colorbar import matplotlib.image from matplotlib import _api from matplotlib import rcsetup, style from matplotlib import _pylab_helpers, interactive from matplotlib import cbook from matplotlib import _docstring from matplotlib.backend_bases import ( FigureCanvasBase, FigureManagerBase, MouseButton) from matplotlib.figure import Figure, FigureBase, figaspect from matplotlib.gridspec import GridSpec, SubplotSpec from matplotlib import rcParams, rcParamsDefault, get_backend, rcParamsOrig from matplotlib.rcsetup import interactive_bk as _interactive_bk from matplotlib.artist import Artist from matplotlib.axes import Axes, Subplot from matplotlib.projections import PolarAxes from matplotlib import mlab from matplotlib.scale import get_scale_names from matplotlib import cm from matplotlib.cm import _colormaps as colormaps, register_cmap from matplotlib.colors import _color_sequences as color_sequences import numpy as np from matplotlib.colors import Normalize from matplotlib.lines import Line2D from matplotlib.text import Text, Annotation from matplotlib.patches import Polygon, Rectangle, Circle, Arrow from matplotlib.widgets import Button, Slider, Widget from .ticker import ( TickHelper, Formatter, FixedFormatter, NullFormatter, FuncFormatter, FormatStrFormatter, ScalarFormatter, LogFormatter, LogFormatterExponent, LogFormatterMathtext, Locator, IndexLocator, FixedLocator, NullLocator, LinearLocator, LogLocator, AutoLocator, MultipleLocator, MaxNLocator) def gca(): return gcf().gca() def xcorr( x, y, normed=True, detrend=mlab.detrend_none, usevlines=True, maxlags=10, *, data=None, **kwargs): return gca().xcorr( x, y, normed=normed, detrend=detrend, usevlines=usevlines, maxlags=maxlags, **({"data": data} if data is not None else {}), **kwargs)
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from contextlib import ExitStack from enum import Enum import functools import importlib import inspect import logging from numbers import Number import re import sys import threading import time from cycler import cycler import matplotlib import matplotlib.colorbar import matplotlib.image from matplotlib import _api from matplotlib import rcsetup, style from matplotlib import _pylab_helpers, interactive from matplotlib import cbook from matplotlib import _docstring from matplotlib.backend_bases import ( FigureCanvasBase, FigureManagerBase, MouseButton) from matplotlib.figure import Figure, FigureBase, figaspect from matplotlib.gridspec import GridSpec, SubplotSpec from matplotlib import rcParams, rcParamsDefault, get_backend, rcParamsOrig from matplotlib.rcsetup import interactive_bk as _interactive_bk from matplotlib.artist import Artist from matplotlib.axes import Axes, Subplot from matplotlib.projections import PolarAxes from matplotlib import mlab from matplotlib.scale import get_scale_names from matplotlib import cm from matplotlib.cm import _colormaps as colormaps, register_cmap from matplotlib.colors import _color_sequences as color_sequences import numpy as np from matplotlib.colors import Normalize from matplotlib.lines import Line2D from matplotlib.text import Text, Annotation from matplotlib.patches import Polygon, Rectangle, Circle, Arrow from matplotlib.widgets import Button, Slider, Widget from .ticker import ( TickHelper, Formatter, FixedFormatter, NullFormatter, FuncFormatter, FormatStrFormatter, ScalarFormatter, LogFormatter, LogFormatterExponent, LogFormatterMathtext, Locator, IndexLocator, FixedLocator, NullLocator, LinearLocator, LogLocator, AutoLocator, MultipleLocator, MaxNLocator) def gca(): return gcf().gca() def xscale(value, **kwargs): return gca().set_xscale(value, **kwargs)
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from contextlib import ExitStack from enum import Enum import functools import importlib import inspect import logging from numbers import Number import re import sys import threading import time from cycler import cycler import matplotlib import matplotlib.colorbar import matplotlib.image from matplotlib import _api from matplotlib import rcsetup, style from matplotlib import _pylab_helpers, interactive from matplotlib import cbook from matplotlib import _docstring from matplotlib.backend_bases import ( FigureCanvasBase, FigureManagerBase, MouseButton) from matplotlib.figure import Figure, FigureBase, figaspect from matplotlib.gridspec import GridSpec, SubplotSpec from matplotlib import rcParams, rcParamsDefault, get_backend, rcParamsOrig from matplotlib.rcsetup import interactive_bk as _interactive_bk from matplotlib.artist import Artist from matplotlib.axes import Axes, Subplot from matplotlib.projections import PolarAxes from matplotlib import mlab from matplotlib.scale import get_scale_names from matplotlib import cm from matplotlib.cm import _colormaps as colormaps, register_cmap from matplotlib.colors import _color_sequences as color_sequences import numpy as np from matplotlib.colors import Normalize from matplotlib.lines import Line2D from matplotlib.text import Text, Annotation from matplotlib.patches import Polygon, Rectangle, Circle, Arrow from matplotlib.widgets import Button, Slider, Widget from .ticker import ( TickHelper, Formatter, FixedFormatter, NullFormatter, FuncFormatter, FormatStrFormatter, ScalarFormatter, LogFormatter, LogFormatterExponent, LogFormatterMathtext, Locator, IndexLocator, FixedLocator, NullLocator, LinearLocator, LogLocator, AutoLocator, MultipleLocator, MaxNLocator) def gca(): return gcf().gca() def yscale(value, **kwargs): return gca().set_yscale(value, **kwargs)
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from contextlib import ExitStack from enum import Enum import functools import importlib import inspect import logging from numbers import Number import re import sys import threading import time from cycler import cycler import matplotlib import matplotlib.colorbar import matplotlib.image from matplotlib import _api from matplotlib import rcsetup, style from matplotlib import _pylab_helpers, interactive from matplotlib import cbook from matplotlib import _docstring from matplotlib.backend_bases import ( FigureCanvasBase, FigureManagerBase, MouseButton) from matplotlib.figure import Figure, FigureBase, figaspect from matplotlib.gridspec import GridSpec, SubplotSpec from matplotlib import rcParams, rcParamsDefault, get_backend, rcParamsOrig from matplotlib.rcsetup import interactive_bk as _interactive_bk from matplotlib.artist import Artist from matplotlib.axes import Axes, Subplot from matplotlib.projections import PolarAxes from matplotlib import mlab from matplotlib.scale import get_scale_names from matplotlib import cm from matplotlib.cm import _colormaps as colormaps, register_cmap from matplotlib.colors import _color_sequences as color_sequences import numpy as np from matplotlib.colors import Normalize from matplotlib.lines import Line2D from matplotlib.text import Text, Annotation from matplotlib.patches import Polygon, Rectangle, Circle, Arrow from matplotlib.widgets import Button, Slider, Widget from .ticker import ( TickHelper, Formatter, FixedFormatter, NullFormatter, FuncFormatter, FormatStrFormatter, ScalarFormatter, LogFormatter, LogFormatterExponent, LogFormatterMathtext, Locator, IndexLocator, FixedLocator, NullLocator, LinearLocator, LogLocator, AutoLocator, MultipleLocator, MaxNLocator) def set_cmap(cmap): """ Set the default colormap, and applies it to the current image if any. Parameters ---------- cmap : `~matplotlib.colors.Colormap` or str A colormap instance or the name of a registered colormap. See Also -------- colormaps matplotlib.cm.register_cmap matplotlib.cm.get_cmap """ cmap = get_cmap(cmap) rc('image', cmap=cmap.name) im = gci() if im is not None: im.set_cmap(cmap) The provided code snippet includes necessary dependencies for implementing the `autumn` function. Write a Python function `def autumn()` to solve the following problem: Set the colormap to 'autumn'. This changes the default colormap as well as the colormap of the current image if there is one. See ``help(colormaps)`` for more information. Here is the function: def autumn(): """ Set the colormap to 'autumn'. This changes the default colormap as well as the colormap of the current image if there is one. See ``help(colormaps)`` for more information. """ set_cmap('autumn')
Set the colormap to 'autumn'. This changes the default colormap as well as the colormap of the current image if there is one. See ``help(colormaps)`` for more information.
171,191
from contextlib import ExitStack from enum import Enum import functools import importlib import inspect import logging from numbers import Number import re import sys import threading import time from cycler import cycler import matplotlib import matplotlib.colorbar import matplotlib.image from matplotlib import _api from matplotlib import rcsetup, style from matplotlib import _pylab_helpers, interactive from matplotlib import cbook from matplotlib import _docstring from matplotlib.backend_bases import ( FigureCanvasBase, FigureManagerBase, MouseButton) from matplotlib.figure import Figure, FigureBase, figaspect from matplotlib.gridspec import GridSpec, SubplotSpec from matplotlib import rcParams, rcParamsDefault, get_backend, rcParamsOrig from matplotlib.rcsetup import interactive_bk as _interactive_bk from matplotlib.artist import Artist from matplotlib.axes import Axes, Subplot from matplotlib.projections import PolarAxes from matplotlib import mlab from matplotlib.scale import get_scale_names from matplotlib import cm from matplotlib.cm import _colormaps as colormaps, register_cmap from matplotlib.colors import _color_sequences as color_sequences import numpy as np from matplotlib.colors import Normalize from matplotlib.lines import Line2D from matplotlib.text import Text, Annotation from matplotlib.patches import Polygon, Rectangle, Circle, Arrow from matplotlib.widgets import Button, Slider, Widget from .ticker import ( TickHelper, Formatter, FixedFormatter, NullFormatter, FuncFormatter, FormatStrFormatter, ScalarFormatter, LogFormatter, LogFormatterExponent, LogFormatterMathtext, Locator, IndexLocator, FixedLocator, NullLocator, LinearLocator, LogLocator, AutoLocator, MultipleLocator, MaxNLocator) def set_cmap(cmap): """ Set the default colormap, and applies it to the current image if any. Parameters ---------- cmap : `~matplotlib.colors.Colormap` or str A colormap instance or the name of a registered colormap. See Also -------- colormaps matplotlib.cm.register_cmap matplotlib.cm.get_cmap """ cmap = get_cmap(cmap) rc('image', cmap=cmap.name) im = gci() if im is not None: im.set_cmap(cmap) The provided code snippet includes necessary dependencies for implementing the `bone` function. Write a Python function `def bone()` to solve the following problem: Set the colormap to 'bone'. This changes the default colormap as well as the colormap of the current image if there is one. See ``help(colormaps)`` for more information. Here is the function: def bone(): """ Set the colormap to 'bone'. This changes the default colormap as well as the colormap of the current image if there is one. See ``help(colormaps)`` for more information. """ set_cmap('bone')
Set the colormap to 'bone'. This changes the default colormap as well as the colormap of the current image if there is one. See ``help(colormaps)`` for more information.
171,192
from contextlib import ExitStack from enum import Enum import functools import importlib import inspect import logging from numbers import Number import re import sys import threading import time from cycler import cycler import matplotlib import matplotlib.colorbar import matplotlib.image from matplotlib import _api from matplotlib import rcsetup, style from matplotlib import _pylab_helpers, interactive from matplotlib import cbook from matplotlib import _docstring from matplotlib.backend_bases import ( FigureCanvasBase, FigureManagerBase, MouseButton) from matplotlib.figure import Figure, FigureBase, figaspect from matplotlib.gridspec import GridSpec, SubplotSpec from matplotlib import rcParams, rcParamsDefault, get_backend, rcParamsOrig from matplotlib.rcsetup import interactive_bk as _interactive_bk from matplotlib.artist import Artist from matplotlib.axes import Axes, Subplot from matplotlib.projections import PolarAxes from matplotlib import mlab from matplotlib.scale import get_scale_names from matplotlib import cm from matplotlib.cm import _colormaps as colormaps, register_cmap from matplotlib.colors import _color_sequences as color_sequences import numpy as np from matplotlib.colors import Normalize from matplotlib.lines import Line2D from matplotlib.text import Text, Annotation from matplotlib.patches import Polygon, Rectangle, Circle, Arrow from matplotlib.widgets import Button, Slider, Widget from .ticker import ( TickHelper, Formatter, FixedFormatter, NullFormatter, FuncFormatter, FormatStrFormatter, ScalarFormatter, LogFormatter, LogFormatterExponent, LogFormatterMathtext, Locator, IndexLocator, FixedLocator, NullLocator, LinearLocator, LogLocator, AutoLocator, MultipleLocator, MaxNLocator) def set_cmap(cmap): """ Set the default colormap, and applies it to the current image if any. Parameters ---------- cmap : `~matplotlib.colors.Colormap` or str A colormap instance or the name of a registered colormap. See Also -------- colormaps matplotlib.cm.register_cmap matplotlib.cm.get_cmap """ cmap = get_cmap(cmap) rc('image', cmap=cmap.name) im = gci() if im is not None: im.set_cmap(cmap) The provided code snippet includes necessary dependencies for implementing the `cool` function. Write a Python function `def cool()` to solve the following problem: Set the colormap to 'cool'. This changes the default colormap as well as the colormap of the current image if there is one. See ``help(colormaps)`` for more information. Here is the function: def cool(): """ Set the colormap to 'cool'. This changes the default colormap as well as the colormap of the current image if there is one. See ``help(colormaps)`` for more information. """ set_cmap('cool')
Set the colormap to 'cool'. This changes the default colormap as well as the colormap of the current image if there is one. See ``help(colormaps)`` for more information.
171,193
from contextlib import ExitStack from enum import Enum import functools import importlib import inspect import logging from numbers import Number import re import sys import threading import time from cycler import cycler import matplotlib import matplotlib.colorbar import matplotlib.image from matplotlib import _api from matplotlib import rcsetup, style from matplotlib import _pylab_helpers, interactive from matplotlib import cbook from matplotlib import _docstring from matplotlib.backend_bases import ( FigureCanvasBase, FigureManagerBase, MouseButton) from matplotlib.figure import Figure, FigureBase, figaspect from matplotlib.gridspec import GridSpec, SubplotSpec from matplotlib import rcParams, rcParamsDefault, get_backend, rcParamsOrig from matplotlib.rcsetup import interactive_bk as _interactive_bk from matplotlib.artist import Artist from matplotlib.axes import Axes, Subplot from matplotlib.projections import PolarAxes from matplotlib import mlab from matplotlib.scale import get_scale_names from matplotlib import cm from matplotlib.cm import _colormaps as colormaps, register_cmap from matplotlib.colors import _color_sequences as color_sequences import numpy as np from matplotlib.colors import Normalize from matplotlib.lines import Line2D from matplotlib.text import Text, Annotation from matplotlib.patches import Polygon, Rectangle, Circle, Arrow from matplotlib.widgets import Button, Slider, Widget from .ticker import ( TickHelper, Formatter, FixedFormatter, NullFormatter, FuncFormatter, FormatStrFormatter, ScalarFormatter, LogFormatter, LogFormatterExponent, LogFormatterMathtext, Locator, IndexLocator, FixedLocator, NullLocator, LinearLocator, LogLocator, AutoLocator, MultipleLocator, MaxNLocator) def set_cmap(cmap): """ Set the default colormap, and applies it to the current image if any. Parameters ---------- cmap : `~matplotlib.colors.Colormap` or str A colormap instance or the name of a registered colormap. See Also -------- colormaps matplotlib.cm.register_cmap matplotlib.cm.get_cmap """ cmap = get_cmap(cmap) rc('image', cmap=cmap.name) im = gci() if im is not None: im.set_cmap(cmap) The provided code snippet includes necessary dependencies for implementing the `copper` function. Write a Python function `def copper()` to solve the following problem: Set the colormap to 'copper'. This changes the default colormap as well as the colormap of the current image if there is one. See ``help(colormaps)`` for more information. Here is the function: def copper(): """ Set the colormap to 'copper'. This changes the default colormap as well as the colormap of the current image if there is one. See ``help(colormaps)`` for more information. """ set_cmap('copper')
Set the colormap to 'copper'. This changes the default colormap as well as the colormap of the current image if there is one. See ``help(colormaps)`` for more information.
171,194
from contextlib import ExitStack from enum import Enum import functools import importlib import inspect import logging from numbers import Number import re import sys import threading import time from cycler import cycler import matplotlib import matplotlib.colorbar import matplotlib.image from matplotlib import _api from matplotlib import rcsetup, style from matplotlib import _pylab_helpers, interactive from matplotlib import cbook from matplotlib import _docstring from matplotlib.backend_bases import ( FigureCanvasBase, FigureManagerBase, MouseButton) from matplotlib.figure import Figure, FigureBase, figaspect from matplotlib.gridspec import GridSpec, SubplotSpec from matplotlib import rcParams, rcParamsDefault, get_backend, rcParamsOrig from matplotlib.rcsetup import interactive_bk as _interactive_bk from matplotlib.artist import Artist from matplotlib.axes import Axes, Subplot from matplotlib.projections import PolarAxes from matplotlib import mlab from matplotlib.scale import get_scale_names from matplotlib import cm from matplotlib.cm import _colormaps as colormaps, register_cmap from matplotlib.colors import _color_sequences as color_sequences import numpy as np from matplotlib.colors import Normalize from matplotlib.lines import Line2D from matplotlib.text import Text, Annotation from matplotlib.patches import Polygon, Rectangle, Circle, Arrow from matplotlib.widgets import Button, Slider, Widget from .ticker import ( TickHelper, Formatter, FixedFormatter, NullFormatter, FuncFormatter, FormatStrFormatter, ScalarFormatter, LogFormatter, LogFormatterExponent, LogFormatterMathtext, Locator, IndexLocator, FixedLocator, NullLocator, LinearLocator, LogLocator, AutoLocator, MultipleLocator, MaxNLocator) def set_cmap(cmap): """ Set the default colormap, and applies it to the current image if any. Parameters ---------- cmap : `~matplotlib.colors.Colormap` or str A colormap instance or the name of a registered colormap. See Also -------- colormaps matplotlib.cm.register_cmap matplotlib.cm.get_cmap """ cmap = get_cmap(cmap) rc('image', cmap=cmap.name) im = gci() if im is not None: im.set_cmap(cmap) The provided code snippet includes necessary dependencies for implementing the `flag` function. Write a Python function `def flag()` to solve the following problem: Set the colormap to 'flag'. This changes the default colormap as well as the colormap of the current image if there is one. See ``help(colormaps)`` for more information. Here is the function: def flag(): """ Set the colormap to 'flag'. This changes the default colormap as well as the colormap of the current image if there is one. See ``help(colormaps)`` for more information. """ set_cmap('flag')
Set the colormap to 'flag'. This changes the default colormap as well as the colormap of the current image if there is one. See ``help(colormaps)`` for more information.
171,195
from contextlib import ExitStack from enum import Enum import functools import importlib import inspect import logging from numbers import Number import re import sys import threading import time from cycler import cycler import matplotlib import matplotlib.colorbar import matplotlib.image from matplotlib import _api from matplotlib import rcsetup, style from matplotlib import _pylab_helpers, interactive from matplotlib import cbook from matplotlib import _docstring from matplotlib.backend_bases import ( FigureCanvasBase, FigureManagerBase, MouseButton) from matplotlib.figure import Figure, FigureBase, figaspect from matplotlib.gridspec import GridSpec, SubplotSpec from matplotlib import rcParams, rcParamsDefault, get_backend, rcParamsOrig from matplotlib.rcsetup import interactive_bk as _interactive_bk from matplotlib.artist import Artist from matplotlib.axes import Axes, Subplot from matplotlib.projections import PolarAxes from matplotlib import mlab from matplotlib.scale import get_scale_names from matplotlib import cm from matplotlib.cm import _colormaps as colormaps, register_cmap from matplotlib.colors import _color_sequences as color_sequences import numpy as np from matplotlib.colors import Normalize from matplotlib.lines import Line2D from matplotlib.text import Text, Annotation from matplotlib.patches import Polygon, Rectangle, Circle, Arrow from matplotlib.widgets import Button, Slider, Widget from .ticker import ( TickHelper, Formatter, FixedFormatter, NullFormatter, FuncFormatter, FormatStrFormatter, ScalarFormatter, LogFormatter, LogFormatterExponent, LogFormatterMathtext, Locator, IndexLocator, FixedLocator, NullLocator, LinearLocator, LogLocator, AutoLocator, MultipleLocator, MaxNLocator) def set_cmap(cmap): """ Set the default colormap, and applies it to the current image if any. Parameters ---------- cmap : `~matplotlib.colors.Colormap` or str A colormap instance or the name of a registered colormap. See Also -------- colormaps matplotlib.cm.register_cmap matplotlib.cm.get_cmap """ cmap = get_cmap(cmap) rc('image', cmap=cmap.name) im = gci() if im is not None: im.set_cmap(cmap) The provided code snippet includes necessary dependencies for implementing the `gray` function. Write a Python function `def gray()` to solve the following problem: Set the colormap to 'gray'. This changes the default colormap as well as the colormap of the current image if there is one. See ``help(colormaps)`` for more information. Here is the function: def gray(): """ Set the colormap to 'gray'. This changes the default colormap as well as the colormap of the current image if there is one. See ``help(colormaps)`` for more information. """ set_cmap('gray')
Set the colormap to 'gray'. This changes the default colormap as well as the colormap of the current image if there is one. See ``help(colormaps)`` for more information.
171,196
from contextlib import ExitStack from enum import Enum import functools import importlib import inspect import logging from numbers import Number import re import sys import threading import time from cycler import cycler import matplotlib import matplotlib.colorbar import matplotlib.image from matplotlib import _api from matplotlib import rcsetup, style from matplotlib import _pylab_helpers, interactive from matplotlib import cbook from matplotlib import _docstring from matplotlib.backend_bases import ( FigureCanvasBase, FigureManagerBase, MouseButton) from matplotlib.figure import Figure, FigureBase, figaspect from matplotlib.gridspec import GridSpec, SubplotSpec from matplotlib import rcParams, rcParamsDefault, get_backend, rcParamsOrig from matplotlib.rcsetup import interactive_bk as _interactive_bk from matplotlib.artist import Artist from matplotlib.axes import Axes, Subplot from matplotlib.projections import PolarAxes from matplotlib import mlab from matplotlib.scale import get_scale_names from matplotlib import cm from matplotlib.cm import _colormaps as colormaps, register_cmap from matplotlib.colors import _color_sequences as color_sequences import numpy as np from matplotlib.colors import Normalize from matplotlib.lines import Line2D from matplotlib.text import Text, Annotation from matplotlib.patches import Polygon, Rectangle, Circle, Arrow from matplotlib.widgets import Button, Slider, Widget from .ticker import ( TickHelper, Formatter, FixedFormatter, NullFormatter, FuncFormatter, FormatStrFormatter, ScalarFormatter, LogFormatter, LogFormatterExponent, LogFormatterMathtext, Locator, IndexLocator, FixedLocator, NullLocator, LinearLocator, LogLocator, AutoLocator, MultipleLocator, MaxNLocator) def set_cmap(cmap): """ Set the default colormap, and applies it to the current image if any. Parameters ---------- cmap : `~matplotlib.colors.Colormap` or str A colormap instance or the name of a registered colormap. See Also -------- colormaps matplotlib.cm.register_cmap matplotlib.cm.get_cmap """ cmap = get_cmap(cmap) rc('image', cmap=cmap.name) im = gci() if im is not None: im.set_cmap(cmap) The provided code snippet includes necessary dependencies for implementing the `hot` function. Write a Python function `def hot()` to solve the following problem: Set the colormap to 'hot'. This changes the default colormap as well as the colormap of the current image if there is one. See ``help(colormaps)`` for more information. Here is the function: def hot(): """ Set the colormap to 'hot'. This changes the default colormap as well as the colormap of the current image if there is one. See ``help(colormaps)`` for more information. """ set_cmap('hot')
Set the colormap to 'hot'. This changes the default colormap as well as the colormap of the current image if there is one. See ``help(colormaps)`` for more information.
171,197
from contextlib import ExitStack from enum import Enum import functools import importlib import inspect import logging from numbers import Number import re import sys import threading import time from cycler import cycler import matplotlib import matplotlib.colorbar import matplotlib.image from matplotlib import _api from matplotlib import rcsetup, style from matplotlib import _pylab_helpers, interactive from matplotlib import cbook from matplotlib import _docstring from matplotlib.backend_bases import ( FigureCanvasBase, FigureManagerBase, MouseButton) from matplotlib.figure import Figure, FigureBase, figaspect from matplotlib.gridspec import GridSpec, SubplotSpec from matplotlib import rcParams, rcParamsDefault, get_backend, rcParamsOrig from matplotlib.rcsetup import interactive_bk as _interactive_bk from matplotlib.artist import Artist from matplotlib.axes import Axes, Subplot from matplotlib.projections import PolarAxes from matplotlib import mlab from matplotlib.scale import get_scale_names from matplotlib import cm from matplotlib.cm import _colormaps as colormaps, register_cmap from matplotlib.colors import _color_sequences as color_sequences import numpy as np from matplotlib.colors import Normalize from matplotlib.lines import Line2D from matplotlib.text import Text, Annotation from matplotlib.patches import Polygon, Rectangle, Circle, Arrow from matplotlib.widgets import Button, Slider, Widget from .ticker import ( TickHelper, Formatter, FixedFormatter, NullFormatter, FuncFormatter, FormatStrFormatter, ScalarFormatter, LogFormatter, LogFormatterExponent, LogFormatterMathtext, Locator, IndexLocator, FixedLocator, NullLocator, LinearLocator, LogLocator, AutoLocator, MultipleLocator, MaxNLocator) def set_cmap(cmap): """ Set the default colormap, and applies it to the current image if any. Parameters ---------- cmap : `~matplotlib.colors.Colormap` or str A colormap instance or the name of a registered colormap. See Also -------- colormaps matplotlib.cm.register_cmap matplotlib.cm.get_cmap """ cmap = get_cmap(cmap) rc('image', cmap=cmap.name) im = gci() if im is not None: im.set_cmap(cmap) The provided code snippet includes necessary dependencies for implementing the `hsv` function. Write a Python function `def hsv()` to solve the following problem: Set the colormap to 'hsv'. This changes the default colormap as well as the colormap of the current image if there is one. See ``help(colormaps)`` for more information. Here is the function: def hsv(): """ Set the colormap to 'hsv'. This changes the default colormap as well as the colormap of the current image if there is one. See ``help(colormaps)`` for more information. """ set_cmap('hsv')
Set the colormap to 'hsv'. This changes the default colormap as well as the colormap of the current image if there is one. See ``help(colormaps)`` for more information.
171,198
from contextlib import ExitStack from enum import Enum import functools import importlib import inspect import logging from numbers import Number import re import sys import threading import time from cycler import cycler import matplotlib import matplotlib.colorbar import matplotlib.image from matplotlib import _api from matplotlib import rcsetup, style from matplotlib import _pylab_helpers, interactive from matplotlib import cbook from matplotlib import _docstring from matplotlib.backend_bases import ( FigureCanvasBase, FigureManagerBase, MouseButton) from matplotlib.figure import Figure, FigureBase, figaspect from matplotlib.gridspec import GridSpec, SubplotSpec from matplotlib import rcParams, rcParamsDefault, get_backend, rcParamsOrig from matplotlib.rcsetup import interactive_bk as _interactive_bk from matplotlib.artist import Artist from matplotlib.axes import Axes, Subplot from matplotlib.projections import PolarAxes from matplotlib import mlab from matplotlib.scale import get_scale_names from matplotlib import cm from matplotlib.cm import _colormaps as colormaps, register_cmap from matplotlib.colors import _color_sequences as color_sequences import numpy as np from matplotlib.colors import Normalize from matplotlib.lines import Line2D from matplotlib.text import Text, Annotation from matplotlib.patches import Polygon, Rectangle, Circle, Arrow from matplotlib.widgets import Button, Slider, Widget from .ticker import ( TickHelper, Formatter, FixedFormatter, NullFormatter, FuncFormatter, FormatStrFormatter, ScalarFormatter, LogFormatter, LogFormatterExponent, LogFormatterMathtext, Locator, IndexLocator, FixedLocator, NullLocator, LinearLocator, LogLocator, AutoLocator, MultipleLocator, MaxNLocator) def set_cmap(cmap): """ Set the default colormap, and applies it to the current image if any. Parameters ---------- cmap : `~matplotlib.colors.Colormap` or str A colormap instance or the name of a registered colormap. See Also -------- colormaps matplotlib.cm.register_cmap matplotlib.cm.get_cmap """ cmap = get_cmap(cmap) rc('image', cmap=cmap.name) im = gci() if im is not None: im.set_cmap(cmap) The provided code snippet includes necessary dependencies for implementing the `jet` function. Write a Python function `def jet()` to solve the following problem: Set the colormap to 'jet'. This changes the default colormap as well as the colormap of the current image if there is one. See ``help(colormaps)`` for more information. Here is the function: def jet(): """ Set the colormap to 'jet'. This changes the default colormap as well as the colormap of the current image if there is one. See ``help(colormaps)`` for more information. """ set_cmap('jet')
Set the colormap to 'jet'. This changes the default colormap as well as the colormap of the current image if there is one. See ``help(colormaps)`` for more information.
171,199
from contextlib import ExitStack from enum import Enum import functools import importlib import inspect import logging from numbers import Number import re import sys import threading import time from cycler import cycler import matplotlib import matplotlib.colorbar import matplotlib.image from matplotlib import _api from matplotlib import rcsetup, style from matplotlib import _pylab_helpers, interactive from matplotlib import cbook from matplotlib import _docstring from matplotlib.backend_bases import ( FigureCanvasBase, FigureManagerBase, MouseButton) from matplotlib.figure import Figure, FigureBase, figaspect from matplotlib.gridspec import GridSpec, SubplotSpec from matplotlib import rcParams, rcParamsDefault, get_backend, rcParamsOrig from matplotlib.rcsetup import interactive_bk as _interactive_bk from matplotlib.artist import Artist from matplotlib.axes import Axes, Subplot from matplotlib.projections import PolarAxes from matplotlib import mlab from matplotlib.scale import get_scale_names from matplotlib import cm from matplotlib.cm import _colormaps as colormaps, register_cmap from matplotlib.colors import _color_sequences as color_sequences import numpy as np from matplotlib.colors import Normalize from matplotlib.lines import Line2D from matplotlib.text import Text, Annotation from matplotlib.patches import Polygon, Rectangle, Circle, Arrow from matplotlib.widgets import Button, Slider, Widget from .ticker import ( TickHelper, Formatter, FixedFormatter, NullFormatter, FuncFormatter, FormatStrFormatter, ScalarFormatter, LogFormatter, LogFormatterExponent, LogFormatterMathtext, Locator, IndexLocator, FixedLocator, NullLocator, LinearLocator, LogLocator, AutoLocator, MultipleLocator, MaxNLocator) def set_cmap(cmap): """ Set the default colormap, and applies it to the current image if any. Parameters ---------- cmap : `~matplotlib.colors.Colormap` or str A colormap instance or the name of a registered colormap. See Also -------- colormaps matplotlib.cm.register_cmap matplotlib.cm.get_cmap """ cmap = get_cmap(cmap) rc('image', cmap=cmap.name) im = gci() if im is not None: im.set_cmap(cmap) The provided code snippet includes necessary dependencies for implementing the `pink` function. Write a Python function `def pink()` to solve the following problem: Set the colormap to 'pink'. This changes the default colormap as well as the colormap of the current image if there is one. See ``help(colormaps)`` for more information. Here is the function: def pink(): """ Set the colormap to 'pink'. This changes the default colormap as well as the colormap of the current image if there is one. See ``help(colormaps)`` for more information. """ set_cmap('pink')
Set the colormap to 'pink'. This changes the default colormap as well as the colormap of the current image if there is one. See ``help(colormaps)`` for more information.
171,200
from contextlib import ExitStack from enum import Enum import functools import importlib import inspect import logging from numbers import Number import re import sys import threading import time from cycler import cycler import matplotlib import matplotlib.colorbar import matplotlib.image from matplotlib import _api from matplotlib import rcsetup, style from matplotlib import _pylab_helpers, interactive from matplotlib import cbook from matplotlib import _docstring from matplotlib.backend_bases import ( FigureCanvasBase, FigureManagerBase, MouseButton) from matplotlib.figure import Figure, FigureBase, figaspect from matplotlib.gridspec import GridSpec, SubplotSpec from matplotlib import rcParams, rcParamsDefault, get_backend, rcParamsOrig from matplotlib.rcsetup import interactive_bk as _interactive_bk from matplotlib.artist import Artist from matplotlib.axes import Axes, Subplot from matplotlib.projections import PolarAxes from matplotlib import mlab from matplotlib.scale import get_scale_names from matplotlib import cm from matplotlib.cm import _colormaps as colormaps, register_cmap from matplotlib.colors import _color_sequences as color_sequences import numpy as np from matplotlib.colors import Normalize from matplotlib.lines import Line2D from matplotlib.text import Text, Annotation from matplotlib.patches import Polygon, Rectangle, Circle, Arrow from matplotlib.widgets import Button, Slider, Widget from .ticker import ( TickHelper, Formatter, FixedFormatter, NullFormatter, FuncFormatter, FormatStrFormatter, ScalarFormatter, LogFormatter, LogFormatterExponent, LogFormatterMathtext, Locator, IndexLocator, FixedLocator, NullLocator, LinearLocator, LogLocator, AutoLocator, MultipleLocator, MaxNLocator) def set_cmap(cmap): """ Set the default colormap, and applies it to the current image if any. Parameters ---------- cmap : `~matplotlib.colors.Colormap` or str A colormap instance or the name of a registered colormap. See Also -------- colormaps matplotlib.cm.register_cmap matplotlib.cm.get_cmap """ cmap = get_cmap(cmap) rc('image', cmap=cmap.name) im = gci() if im is not None: im.set_cmap(cmap) The provided code snippet includes necessary dependencies for implementing the `prism` function. Write a Python function `def prism()` to solve the following problem: Set the colormap to 'prism'. This changes the default colormap as well as the colormap of the current image if there is one. See ``help(colormaps)`` for more information. Here is the function: def prism(): """ Set the colormap to 'prism'. This changes the default colormap as well as the colormap of the current image if there is one. See ``help(colormaps)`` for more information. """ set_cmap('prism')
Set the colormap to 'prism'. This changes the default colormap as well as the colormap of the current image if there is one. See ``help(colormaps)`` for more information.
171,201
from contextlib import ExitStack from enum import Enum import functools import importlib import inspect import logging from numbers import Number import re import sys import threading import time from cycler import cycler import matplotlib import matplotlib.colorbar import matplotlib.image from matplotlib import _api from matplotlib import rcsetup, style from matplotlib import _pylab_helpers, interactive from matplotlib import cbook from matplotlib import _docstring from matplotlib.backend_bases import ( FigureCanvasBase, FigureManagerBase, MouseButton) from matplotlib.figure import Figure, FigureBase, figaspect from matplotlib.gridspec import GridSpec, SubplotSpec from matplotlib import rcParams, rcParamsDefault, get_backend, rcParamsOrig from matplotlib.rcsetup import interactive_bk as _interactive_bk from matplotlib.artist import Artist from matplotlib.axes import Axes, Subplot from matplotlib.projections import PolarAxes from matplotlib import mlab from matplotlib.scale import get_scale_names from matplotlib import cm from matplotlib.cm import _colormaps as colormaps, register_cmap from matplotlib.colors import _color_sequences as color_sequences import numpy as np from matplotlib.colors import Normalize from matplotlib.lines import Line2D from matplotlib.text import Text, Annotation from matplotlib.patches import Polygon, Rectangle, Circle, Arrow from matplotlib.widgets import Button, Slider, Widget from .ticker import ( TickHelper, Formatter, FixedFormatter, NullFormatter, FuncFormatter, FormatStrFormatter, ScalarFormatter, LogFormatter, LogFormatterExponent, LogFormatterMathtext, Locator, IndexLocator, FixedLocator, NullLocator, LinearLocator, LogLocator, AutoLocator, MultipleLocator, MaxNLocator) def set_cmap(cmap): """ Set the default colormap, and applies it to the current image if any. Parameters ---------- cmap : `~matplotlib.colors.Colormap` or str A colormap instance or the name of a registered colormap. See Also -------- colormaps matplotlib.cm.register_cmap matplotlib.cm.get_cmap """ cmap = get_cmap(cmap) rc('image', cmap=cmap.name) im = gci() if im is not None: im.set_cmap(cmap) The provided code snippet includes necessary dependencies for implementing the `spring` function. Write a Python function `def spring()` to solve the following problem: Set the colormap to 'spring'. This changes the default colormap as well as the colormap of the current image if there is one. See ``help(colormaps)`` for more information. Here is the function: def spring(): """ Set the colormap to 'spring'. This changes the default colormap as well as the colormap of the current image if there is one. See ``help(colormaps)`` for more information. """ set_cmap('spring')
Set the colormap to 'spring'. This changes the default colormap as well as the colormap of the current image if there is one. See ``help(colormaps)`` for more information.
171,202
from contextlib import ExitStack from enum import Enum import functools import importlib import inspect import logging from numbers import Number import re import sys import threading import time from cycler import cycler import matplotlib import matplotlib.colorbar import matplotlib.image from matplotlib import _api from matplotlib import rcsetup, style from matplotlib import _pylab_helpers, interactive from matplotlib import cbook from matplotlib import _docstring from matplotlib.backend_bases import ( FigureCanvasBase, FigureManagerBase, MouseButton) from matplotlib.figure import Figure, FigureBase, figaspect from matplotlib.gridspec import GridSpec, SubplotSpec from matplotlib import rcParams, rcParamsDefault, get_backend, rcParamsOrig from matplotlib.rcsetup import interactive_bk as _interactive_bk from matplotlib.artist import Artist from matplotlib.axes import Axes, Subplot from matplotlib.projections import PolarAxes from matplotlib import mlab from matplotlib.scale import get_scale_names from matplotlib import cm from matplotlib.cm import _colormaps as colormaps, register_cmap from matplotlib.colors import _color_sequences as color_sequences import numpy as np from matplotlib.colors import Normalize from matplotlib.lines import Line2D from matplotlib.text import Text, Annotation from matplotlib.patches import Polygon, Rectangle, Circle, Arrow from matplotlib.widgets import Button, Slider, Widget from .ticker import ( TickHelper, Formatter, FixedFormatter, NullFormatter, FuncFormatter, FormatStrFormatter, ScalarFormatter, LogFormatter, LogFormatterExponent, LogFormatterMathtext, Locator, IndexLocator, FixedLocator, NullLocator, LinearLocator, LogLocator, AutoLocator, MultipleLocator, MaxNLocator) def set_cmap(cmap): """ Set the default colormap, and applies it to the current image if any. Parameters ---------- cmap : `~matplotlib.colors.Colormap` or str A colormap instance or the name of a registered colormap. See Also -------- colormaps matplotlib.cm.register_cmap matplotlib.cm.get_cmap """ cmap = get_cmap(cmap) rc('image', cmap=cmap.name) im = gci() if im is not None: im.set_cmap(cmap) The provided code snippet includes necessary dependencies for implementing the `summer` function. Write a Python function `def summer()` to solve the following problem: Set the colormap to 'summer'. This changes the default colormap as well as the colormap of the current image if there is one. See ``help(colormaps)`` for more information. Here is the function: def summer(): """ Set the colormap to 'summer'. This changes the default colormap as well as the colormap of the current image if there is one. See ``help(colormaps)`` for more information. """ set_cmap('summer')
Set the colormap to 'summer'. This changes the default colormap as well as the colormap of the current image if there is one. See ``help(colormaps)`` for more information.
171,203
from contextlib import ExitStack from enum import Enum import functools import importlib import inspect import logging from numbers import Number import re import sys import threading import time from cycler import cycler import matplotlib import matplotlib.colorbar import matplotlib.image from matplotlib import _api from matplotlib import rcsetup, style from matplotlib import _pylab_helpers, interactive from matplotlib import cbook from matplotlib import _docstring from matplotlib.backend_bases import ( FigureCanvasBase, FigureManagerBase, MouseButton) from matplotlib.figure import Figure, FigureBase, figaspect from matplotlib.gridspec import GridSpec, SubplotSpec from matplotlib import rcParams, rcParamsDefault, get_backend, rcParamsOrig from matplotlib.rcsetup import interactive_bk as _interactive_bk from matplotlib.artist import Artist from matplotlib.axes import Axes, Subplot from matplotlib.projections import PolarAxes from matplotlib import mlab from matplotlib.scale import get_scale_names from matplotlib import cm from matplotlib.cm import _colormaps as colormaps, register_cmap from matplotlib.colors import _color_sequences as color_sequences import numpy as np from matplotlib.colors import Normalize from matplotlib.lines import Line2D from matplotlib.text import Text, Annotation from matplotlib.patches import Polygon, Rectangle, Circle, Arrow from matplotlib.widgets import Button, Slider, Widget from .ticker import ( TickHelper, Formatter, FixedFormatter, NullFormatter, FuncFormatter, FormatStrFormatter, ScalarFormatter, LogFormatter, LogFormatterExponent, LogFormatterMathtext, Locator, IndexLocator, FixedLocator, NullLocator, LinearLocator, LogLocator, AutoLocator, MultipleLocator, MaxNLocator) def set_cmap(cmap): """ Set the default colormap, and applies it to the current image if any. Parameters ---------- cmap : `~matplotlib.colors.Colormap` or str A colormap instance or the name of a registered colormap. See Also -------- colormaps matplotlib.cm.register_cmap matplotlib.cm.get_cmap """ cmap = get_cmap(cmap) rc('image', cmap=cmap.name) im = gci() if im is not None: im.set_cmap(cmap) The provided code snippet includes necessary dependencies for implementing the `winter` function. Write a Python function `def winter()` to solve the following problem: Set the colormap to 'winter'. This changes the default colormap as well as the colormap of the current image if there is one. See ``help(colormaps)`` for more information. Here is the function: def winter(): """ Set the colormap to 'winter'. This changes the default colormap as well as the colormap of the current image if there is one. See ``help(colormaps)`` for more information. """ set_cmap('winter')
Set the colormap to 'winter'. This changes the default colormap as well as the colormap of the current image if there is one. See ``help(colormaps)`` for more information.
171,204
from contextlib import ExitStack from enum import Enum import functools import importlib import inspect import logging from numbers import Number import re import sys import threading import time from cycler import cycler import matplotlib import matplotlib.colorbar import matplotlib.image from matplotlib import _api from matplotlib import rcsetup, style from matplotlib import _pylab_helpers, interactive from matplotlib import cbook from matplotlib import _docstring from matplotlib.backend_bases import ( FigureCanvasBase, FigureManagerBase, MouseButton) from matplotlib.figure import Figure, FigureBase, figaspect from matplotlib.gridspec import GridSpec, SubplotSpec from matplotlib import rcParams, rcParamsDefault, get_backend, rcParamsOrig from matplotlib.rcsetup import interactive_bk as _interactive_bk from matplotlib.artist import Artist from matplotlib.axes import Axes, Subplot from matplotlib.projections import PolarAxes from matplotlib import mlab from matplotlib.scale import get_scale_names from matplotlib import cm from matplotlib.cm import _colormaps as colormaps, register_cmap from matplotlib.colors import _color_sequences as color_sequences import numpy as np from matplotlib.colors import Normalize from matplotlib.lines import Line2D from matplotlib.text import Text, Annotation from matplotlib.patches import Polygon, Rectangle, Circle, Arrow from matplotlib.widgets import Button, Slider, Widget from .ticker import ( TickHelper, Formatter, FixedFormatter, NullFormatter, FuncFormatter, FormatStrFormatter, ScalarFormatter, LogFormatter, LogFormatterExponent, LogFormatterMathtext, Locator, IndexLocator, FixedLocator, NullLocator, LinearLocator, LogLocator, AutoLocator, MultipleLocator, MaxNLocator) def set_cmap(cmap): """ Set the default colormap, and applies it to the current image if any. Parameters ---------- cmap : `~matplotlib.colors.Colormap` or str A colormap instance or the name of a registered colormap. See Also -------- colormaps matplotlib.cm.register_cmap matplotlib.cm.get_cmap """ cmap = get_cmap(cmap) rc('image', cmap=cmap.name) im = gci() if im is not None: im.set_cmap(cmap) The provided code snippet includes necessary dependencies for implementing the `magma` function. Write a Python function `def magma()` to solve the following problem: Set the colormap to 'magma'. This changes the default colormap as well as the colormap of the current image if there is one. See ``help(colormaps)`` for more information. Here is the function: def magma(): """ Set the colormap to 'magma'. This changes the default colormap as well as the colormap of the current image if there is one. See ``help(colormaps)`` for more information. """ set_cmap('magma')
Set the colormap to 'magma'. This changes the default colormap as well as the colormap of the current image if there is one. See ``help(colormaps)`` for more information.
171,205
from contextlib import ExitStack from enum import Enum import functools import importlib import inspect import logging from numbers import Number import re import sys import threading import time from cycler import cycler import matplotlib import matplotlib.colorbar import matplotlib.image from matplotlib import _api from matplotlib import rcsetup, style from matplotlib import _pylab_helpers, interactive from matplotlib import cbook from matplotlib import _docstring from matplotlib.backend_bases import ( FigureCanvasBase, FigureManagerBase, MouseButton) from matplotlib.figure import Figure, FigureBase, figaspect from matplotlib.gridspec import GridSpec, SubplotSpec from matplotlib import rcParams, rcParamsDefault, get_backend, rcParamsOrig from matplotlib.rcsetup import interactive_bk as _interactive_bk from matplotlib.artist import Artist from matplotlib.axes import Axes, Subplot from matplotlib.projections import PolarAxes from matplotlib import mlab from matplotlib.scale import get_scale_names from matplotlib import cm from matplotlib.cm import _colormaps as colormaps, register_cmap from matplotlib.colors import _color_sequences as color_sequences import numpy as np from matplotlib.colors import Normalize from matplotlib.lines import Line2D from matplotlib.text import Text, Annotation from matplotlib.patches import Polygon, Rectangle, Circle, Arrow from matplotlib.widgets import Button, Slider, Widget from .ticker import ( TickHelper, Formatter, FixedFormatter, NullFormatter, FuncFormatter, FormatStrFormatter, ScalarFormatter, LogFormatter, LogFormatterExponent, LogFormatterMathtext, Locator, IndexLocator, FixedLocator, NullLocator, LinearLocator, LogLocator, AutoLocator, MultipleLocator, MaxNLocator) def set_cmap(cmap): """ Set the default colormap, and applies it to the current image if any. Parameters ---------- cmap : `~matplotlib.colors.Colormap` or str A colormap instance or the name of a registered colormap. See Also -------- colormaps matplotlib.cm.register_cmap matplotlib.cm.get_cmap """ cmap = get_cmap(cmap) rc('image', cmap=cmap.name) im = gci() if im is not None: im.set_cmap(cmap) The provided code snippet includes necessary dependencies for implementing the `inferno` function. Write a Python function `def inferno()` to solve the following problem: Set the colormap to 'inferno'. This changes the default colormap as well as the colormap of the current image if there is one. See ``help(colormaps)`` for more information. Here is the function: def inferno(): """ Set the colormap to 'inferno'. This changes the default colormap as well as the colormap of the current image if there is one. See ``help(colormaps)`` for more information. """ set_cmap('inferno')
Set the colormap to 'inferno'. This changes the default colormap as well as the colormap of the current image if there is one. See ``help(colormaps)`` for more information.
171,206
from contextlib import ExitStack from enum import Enum import functools import importlib import inspect import logging from numbers import Number import re import sys import threading import time from cycler import cycler import matplotlib import matplotlib.colorbar import matplotlib.image from matplotlib import _api from matplotlib import rcsetup, style from matplotlib import _pylab_helpers, interactive from matplotlib import cbook from matplotlib import _docstring from matplotlib.backend_bases import ( FigureCanvasBase, FigureManagerBase, MouseButton) from matplotlib.figure import Figure, FigureBase, figaspect from matplotlib.gridspec import GridSpec, SubplotSpec from matplotlib import rcParams, rcParamsDefault, get_backend, rcParamsOrig from matplotlib.rcsetup import interactive_bk as _interactive_bk from matplotlib.artist import Artist from matplotlib.axes import Axes, Subplot from matplotlib.projections import PolarAxes from matplotlib import mlab from matplotlib.scale import get_scale_names from matplotlib import cm from matplotlib.cm import _colormaps as colormaps, register_cmap from matplotlib.colors import _color_sequences as color_sequences import numpy as np from matplotlib.colors import Normalize from matplotlib.lines import Line2D from matplotlib.text import Text, Annotation from matplotlib.patches import Polygon, Rectangle, Circle, Arrow from matplotlib.widgets import Button, Slider, Widget from .ticker import ( TickHelper, Formatter, FixedFormatter, NullFormatter, FuncFormatter, FormatStrFormatter, ScalarFormatter, LogFormatter, LogFormatterExponent, LogFormatterMathtext, Locator, IndexLocator, FixedLocator, NullLocator, LinearLocator, LogLocator, AutoLocator, MultipleLocator, MaxNLocator) def set_cmap(cmap): """ Set the default colormap, and applies it to the current image if any. Parameters ---------- cmap : `~matplotlib.colors.Colormap` or str A colormap instance or the name of a registered colormap. See Also -------- colormaps matplotlib.cm.register_cmap matplotlib.cm.get_cmap """ cmap = get_cmap(cmap) rc('image', cmap=cmap.name) im = gci() if im is not None: im.set_cmap(cmap) The provided code snippet includes necessary dependencies for implementing the `plasma` function. Write a Python function `def plasma()` to solve the following problem: Set the colormap to 'plasma'. This changes the default colormap as well as the colormap of the current image if there is one. See ``help(colormaps)`` for more information. Here is the function: def plasma(): """ Set the colormap to 'plasma'. This changes the default colormap as well as the colormap of the current image if there is one. See ``help(colormaps)`` for more information. """ set_cmap('plasma')
Set the colormap to 'plasma'. This changes the default colormap as well as the colormap of the current image if there is one. See ``help(colormaps)`` for more information.
171,207
from contextlib import ExitStack from enum import Enum import functools import importlib import inspect import logging from numbers import Number import re import sys import threading import time from cycler import cycler import matplotlib import matplotlib.colorbar import matplotlib.image from matplotlib import _api from matplotlib import rcsetup, style from matplotlib import _pylab_helpers, interactive from matplotlib import cbook from matplotlib import _docstring from matplotlib.backend_bases import ( FigureCanvasBase, FigureManagerBase, MouseButton) from matplotlib.figure import Figure, FigureBase, figaspect from matplotlib.gridspec import GridSpec, SubplotSpec from matplotlib import rcParams, rcParamsDefault, get_backend, rcParamsOrig from matplotlib.rcsetup import interactive_bk as _interactive_bk from matplotlib.artist import Artist from matplotlib.axes import Axes, Subplot from matplotlib.projections import PolarAxes from matplotlib import mlab from matplotlib.scale import get_scale_names from matplotlib import cm from matplotlib.cm import _colormaps as colormaps, register_cmap from matplotlib.colors import _color_sequences as color_sequences import numpy as np from matplotlib.colors import Normalize from matplotlib.lines import Line2D from matplotlib.text import Text, Annotation from matplotlib.patches import Polygon, Rectangle, Circle, Arrow from matplotlib.widgets import Button, Slider, Widget from .ticker import ( TickHelper, Formatter, FixedFormatter, NullFormatter, FuncFormatter, FormatStrFormatter, ScalarFormatter, LogFormatter, LogFormatterExponent, LogFormatterMathtext, Locator, IndexLocator, FixedLocator, NullLocator, LinearLocator, LogLocator, AutoLocator, MultipleLocator, MaxNLocator) def set_cmap(cmap): """ Set the default colormap, and applies it to the current image if any. Parameters ---------- cmap : `~matplotlib.colors.Colormap` or str A colormap instance or the name of a registered colormap. See Also -------- colormaps matplotlib.cm.register_cmap matplotlib.cm.get_cmap """ cmap = get_cmap(cmap) rc('image', cmap=cmap.name) im = gci() if im is not None: im.set_cmap(cmap) The provided code snippet includes necessary dependencies for implementing the `viridis` function. Write a Python function `def viridis()` to solve the following problem: Set the colormap to 'viridis'. This changes the default colormap as well as the colormap of the current image if there is one. See ``help(colormaps)`` for more information. Here is the function: def viridis(): """ Set the colormap to 'viridis'. This changes the default colormap as well as the colormap of the current image if there is one. See ``help(colormaps)`` for more information. """ set_cmap('viridis')
Set the colormap to 'viridis'. This changes the default colormap as well as the colormap of the current image if there is one. See ``help(colormaps)`` for more information.
171,208
from contextlib import ExitStack from enum import Enum import functools import importlib import inspect import logging from numbers import Number import re import sys import threading import time from cycler import cycler import matplotlib import matplotlib.colorbar import matplotlib.image from matplotlib import _api from matplotlib import rcsetup, style from matplotlib import _pylab_helpers, interactive from matplotlib import cbook from matplotlib import _docstring from matplotlib.backend_bases import ( FigureCanvasBase, FigureManagerBase, MouseButton) from matplotlib.figure import Figure, FigureBase, figaspect from matplotlib.gridspec import GridSpec, SubplotSpec from matplotlib import rcParams, rcParamsDefault, get_backend, rcParamsOrig from matplotlib.rcsetup import interactive_bk as _interactive_bk from matplotlib.artist import Artist from matplotlib.axes import Axes, Subplot from matplotlib.projections import PolarAxes from matplotlib import mlab from matplotlib.scale import get_scale_names from matplotlib import cm from matplotlib.cm import _colormaps as colormaps, register_cmap from matplotlib.colors import _color_sequences as color_sequences import numpy as np from matplotlib.colors import Normalize from matplotlib.lines import Line2D from matplotlib.text import Text, Annotation from matplotlib.patches import Polygon, Rectangle, Circle, Arrow from matplotlib.widgets import Button, Slider, Widget from .ticker import ( TickHelper, Formatter, FixedFormatter, NullFormatter, FuncFormatter, FormatStrFormatter, ScalarFormatter, LogFormatter, LogFormatterExponent, LogFormatterMathtext, Locator, IndexLocator, FixedLocator, NullLocator, LinearLocator, LogLocator, AutoLocator, MultipleLocator, MaxNLocator) def set_cmap(cmap): """ Set the default colormap, and applies it to the current image if any. Parameters ---------- cmap : `~matplotlib.colors.Colormap` or str A colormap instance or the name of a registered colormap. See Also -------- colormaps matplotlib.cm.register_cmap matplotlib.cm.get_cmap """ cmap = get_cmap(cmap) rc('image', cmap=cmap.name) im = gci() if im is not None: im.set_cmap(cmap) The provided code snippet includes necessary dependencies for implementing the `nipy_spectral` function. Write a Python function `def nipy_spectral()` to solve the following problem: Set the colormap to 'nipy_spectral'. This changes the default colormap as well as the colormap of the current image if there is one. See ``help(colormaps)`` for more information. Here is the function: def nipy_spectral(): """ Set the colormap to 'nipy_spectral'. This changes the default colormap as well as the colormap of the current image if there is one. See ``help(colormaps)`` for more information. """ set_cmap('nipy_spectral')
Set the colormap to 'nipy_spectral'. This changes the default colormap as well as the colormap of the current image if there is one. See ``help(colormaps)`` for more information.
171,209
from contextlib import ExitStack import inspect import itertools import logging from numbers import Integral import numpy as np import matplotlib as mpl from matplotlib import _blocking_input, backend_bases, _docstring, projections from matplotlib.artist import ( Artist, allow_rasterization, _finalize_rasterization) from matplotlib.backend_bases import ( DrawEvent, FigureCanvasBase, NonGuiException, MouseButton, _get_renderer) import matplotlib._api as _api import matplotlib.cbook as cbook import matplotlib.colorbar as cbar import matplotlib.image as mimage from matplotlib.axes import Axes from matplotlib.gridspec import GridSpec from matplotlib.layout_engine import ( ConstrainedLayoutEngine, TightLayoutEngine, LayoutEngine, PlaceHolderLayoutEngine ) import matplotlib.legend as mlegend from matplotlib.patches import Rectangle from matplotlib.text import Text from matplotlib.transforms import (Affine2D, Bbox, BboxTransformTo, TransformedBbox) def _stale_figure_callback(self, val): if self.figure: self.figure.stale = val
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