classmatplotlib.container.ErrorbarContainer(*args, **kwargs)[source]

Bases: matplotlib.container.Container Container for the artists of error bars (e.g. created by Axes.errorbar). The container can be treated as the lines tuple itself. Additionally, you can access these and further parameters by the attributes.  Attributes

linestuple

Tuple of (data_line, caplines, barlinecols).  data_line : Line2D instance of x, y plot markers and/or line. caplines : tuple of Line2D instances of the error bar caps. barlinecols : list of LineCollection with the horizontal and vertical error ranges.
has_xerr, has_yerrbool

True if the errorbar has x/y errors.


classmatplotlib.container.StemContainer(*args, **kwargs)[source]

Bases: matplotlib.container.Container Container for the artists created in a Axes.stem() plot. The container can be treated like a namedtuple (markerline, stemlines,
baseline).  Attributes

markerlineLine2D

The artist of the markers at the stem heads.
stemlineslist of Line2D

The artists of the vertical lines for all stems.
baselineLine2D

The artist of the horizontal baseline.      Parameters

markerline_stemlines_baselinetuple

Tuple of (markerline, stemlines, baseline). markerline contains the LineCollection of the markers, stemlines is a LineCollection of the main lines, baseline is the Line2D of the baseline.


matplotlib.contour Classes to support contour plotting and labelling for the Axes class.   classmatplotlib.contour.ClabelText(x=0, y=0, text='', color=None, verticalalignment='baseline', horizontalalignment='left', multialignment=None, fontproperties=None, rotation=None, linespacing=None, rotation_mode=None, usetex=None, wrap=False, transform_rotates_text=False, *, parse_math=True, **kwargs)[source]

Bases: matplotlib.text.Text Unlike the ordinary text, the get_rotation returns an updated angle in the pixel coordinate assuming that the input rotation is an angle in data coordinate (or whatever transform set). Create a Text instance at x, y with string text. Valid keyword arguments are:
Property Description
agg_filter a filter function, which takes a (m, n, 3) float array and a dpi value, and returns a (m, n, 3) array
alpha scalar or None
animated bool
backgroundcolor color
bbox dict with properties for patches.FancyBboxPatch
clip_box unknown
clip_on unknown
clip_path unknown
color or c color
figure Figure
fontfamily or family {FONTNAME, 'serif', 'sans-serif', 'cursive', 'fantasy', 'monospace'}
fontproperties or font or font_properties font_manager.FontProperties or str or pathlib.Path
fontsize or size float or {'xx-small', 'x-small', 'small', 'medium', 'large', 'x-large', 'xx-large'}
fontstretch or stretch {a numeric value in range 0-1000, 'ultra-condensed', 'extra-condensed', 'condensed', 'semi-condensed', 'normal', 'semi-expanded', 'expanded', 'extra-expanded', 'ultra-expanded'}
fontstyle or style {'normal', 'italic', 'oblique'}
fontvariant or variant {'normal', 'small-caps'}
fontweight or weight {a numeric value in range 0-1000, 'ultralight', 'light', 'normal', 'regular', 'book', 'medium', 'roman', 'semibold', 'demibold', 'demi', 'bold', 'heavy', 'extra bold', 'black'}
gid str
horizontalalignment or ha {'center', 'right', 'left'}
in_layout bool
label object
linespacing float (multiple of font size)
math_fontfamily str
multialignment or ma {'left', 'right', 'center'}
parse_math bool
path_effects AbstractPathEffect
picker None or bool or float or callable
position (float, float)
rasterized bool
rotation float or {'vertical', 'horizontal'}
rotation_mode {None, 'default', 'anchor'}
sketch_params (scale: float, length: float, randomness: float)
snap bool or None
text object
transform Transform
transform_rotates_text bool
url str
usetex bool or None
verticalalignment or va {'center', 'top', 'bottom', 'baseline', 'center_baseline'}
visible bool
wrap bool
x float
y float
zorder float     get_rotation()[source]

Return the text angle in degrees between 0 and 360.
   set(*, agg_filter=<UNSET>, alpha=<UNSET>, animated=<UNSET>, backgroundcolor=<UNSET>, bbox=<UNSET>, clip_box=<UNSET>, clip_on=<UNSET>, clip_path=<UNSET>, color=<UNSET>, fontfamily=<UNSET>, fontproperties=<UNSET>, fontsize=<UNSET>, fontstretch=<UNSET>, fontstyle=<UNSET>, fontvariant=<UNSET>, fontweight=<UNSET>, gid=<UNSET>, horizontalalignment=<UNSET>, in_layout=<UNSET>, label=<UNSET>, linespacing=<UNSET>, math_fontfamily=<UNSET>, multialignment=<UNSET>, parse_math=<UNSET>, path_effects=<UNSET>, picker=<UNSET>, position=<UNSET>, rasterized=<UNSET>, rotation=<UNSET>, rotation_mode=<UNSET>, sketch_params=<UNSET>, snap=<UNSET>, text=<UNSET>, transform=<UNSET>, transform_rotates_text=<UNSET>, url=<UNSET>, usetex=<UNSET>, verticalalignment=<UNSET>, visible=<UNSET>, wrap=<UNSET>, x=<UNSET>, y=<UNSET>, zorder=<UNSET>)[source]

Set multiple properties at once. Supported properties are
Property Description
agg_filter a filter function, which takes a (m, n, 3) float array and a dpi value, and returns a (m, n, 3) array
alpha scalar or None
animated bool
backgroundcolor color
bbox dict with properties for patches.FancyBboxPatch
clip_box Bbox
clip_on bool
clip_path Patch or (Path, Transform) or None
color or c color
figure Figure
fontfamily or family {FONTNAME, 'serif', 'sans-serif', 'cursive', 'fantasy', 'monospace'}
fontproperties or font or font_properties font_manager.FontProperties or str or pathlib.Path
fontsize or size float or {'xx-small', 'x-small', 'small', 'medium', 'large', 'x-large', 'xx-large'}
fontstretch or stretch {a numeric value in range 0-1000, 'ultra-condensed', 'extra-condensed', 'condensed', 'semi-condensed', 'normal', 'semi-expanded', 'expanded', 'extra-expanded', 'ultra-expanded'}
fontstyle or style {'normal', 'italic', 'oblique'}
fontvariant or variant {'normal', 'small-caps'}
fontweight or weight {a numeric value in range 0-1000, 'ultralight', 'light', 'normal', 'regular', 'book', 'medium', 'roman', 'semibold', 'demibold', 'demi', 'bold', 'heavy', 'extra bold', 'black'}
gid str
horizontalalignment or ha {'center', 'right', 'left'}
in_layout bool
label object
linespacing float (multiple of font size)
math_fontfamily str
multialignment or ma {'left', 'right', 'center'}
parse_math bool
path_effects AbstractPathEffect
picker None or bool or float or callable
position (float, float)
rasterized bool
rotation float or {'vertical', 'horizontal'}
rotation_mode {None, 'default', 'anchor'}
sketch_params (scale: float, length: float, randomness: float)
snap bool or None
text object
transform Transform
transform_rotates_text bool
url str
usetex bool or None
verticalalignment or va {'center', 'top', 'bottom', 'baseline', 'center_baseline'}
visible bool
wrap bool
x float
y float
zorder float

   classmatplotlib.contour.ContourLabeler[source]

Bases: object Mixin to provide labelling capability to ContourSet.   add_label(x, y, rotation, lev, cvalue)[source]

Add contour label using Text class.
   add_label_clabeltext(x, y, rotation, lev, cvalue)[source]

Add contour label using ClabelText class.
   add_label_near(x, y, inline=True, inline_spacing=5, transform=None)[source]

Add a label near the point (x, y).  Parameters

x, yfloat

The approximate location of the label.
inlinebool, default: True

If True remove the segment of the contour beneath the label.
inline_spacingint, default: 5

Space in pixels to leave on each side of label when placing inline. This spacing will be exact for labels at locations where the contour is straight, less so for labels on curved contours.
transformTransform or False, default: self.axes.transData

A transform applied to (x, y) before labeling. The default causes (x, y) to be interpreted as data coordinates. False is a synonym for IdentityTransform; i.e. (x, y) should be interpreted as display coordinates.
   calc_label_rot_and_inline(slc, ind, lw, lc=None, spacing=5)[source]

Calculate the appropriate label rotation given the linecontour coordinates in screen units, the index of the label location and the label width. If lc is not None or empty, also break contours and compute inlining. spacing is the empty space to leave around the label, in pixels. Both tasks are done together to avoid calculating path lengths multiple times, which is relatively costly. The method used here involves computing the path length along the contour in pixel coordinates and then looking approximately (label width / 2) away from central point to determine rotation and then to break contour if desired.
   clabel(levels=None, *, fontsize=None, inline=True, inline_spacing=5, fmt=None, colors=None, use_clabeltext=False, manual=False, rightside_up=True, zorder=None)[source]

Label a contour plot. Adds labels to line contours in this ContourSet (which inherits from this mixin class).  Parameters

levelsarray-like, optional

A list of level values, that should be labeled. The list must be a subset of cs.levels. If not given, all levels are labeled.
fontsizestr or float, default: rcParams["font.size"] (default: 10.0)

Size in points or relative size e.g., 'smaller', 'x-large'. See Text.set_size for accepted string values.
colorscolor or colors or None, default: None

The label colors:  If None, the color of each label matches the color of the corresponding contour. If one string color, e.g., colors = 'r' or colors = 'red', all labels will be plotted in this color. If a tuple of colors (string, float, rgb, etc), different labels will be plotted in different colors in the order specified.
inlinebool, default: True

If True the underlying contour is removed where the label is placed.
inline_spacingfloat, default: 5

Space in pixels to leave on each side of label when placing inline. This spacing will be exact for labels at locations where the contour is straight, less so for labels on curved contours.
fmtFormatter or str or callable or dict, optional

How the levels are formatted:  If a Formatter, it is used to format all levels at once, using its Formatter.format_ticks method. If a str, it is interpreted as a %-style format string. If a callable, it is called with one level at a time and should return the corresponding label. If a dict, it should directly map levels to labels.  The default is to use a standard ScalarFormatter.
manualbool or iterable, default: False

If True, contour labels will be placed manually using mouse clicks. Click the first button near a contour to add a label, click the second button (or potentially both mouse buttons at once) to finish adding labels. The third button can be used to remove the last label added, but only if labels are not inline. Alternatively, the keyboard can be used to select label locations (enter to end label placement, delete or backspace act like the third mouse button, and any other key will select a label location). manual can also be an iterable object of (x, y) tuples. Contour labels will be created as if mouse is clicked at each (x, y) position.
rightside_upbool, default: True

If True, label rotations will always be plus or minus 90 degrees from level.
use_clabeltextbool, default: False

If True, ClabelText class (instead of Text) is used to create labels. ClabelText recalculates rotation angles of texts during the drawing time, therefore this can be used if aspect of the axes changes.
zorderfloat or None, default: (2 + contour.get_zorder())

zorder of the contour labels.    Returns
 labels

A list of Text instances for the labels.
   get_label_coords(distances, XX, YY, ysize, lw)[source]

[Deprecated] Return x, y, and the index of a label location. Labels are plotted at a location with the smallest deviation of the contour from a straight line unless there is another label nearby, in which case the next best place on the contour is picked up. If all such candidates are rejected, the beginning of the contour is chosen. Notes  Deprecated since version 3.4.
   get_label_width(lev, fmt, fsize)[source]

[Deprecated] Return the width of the label in points. Notes  Deprecated since version 3.5.
   get_text(lev, fmt)[source]

Get the text of the label.
   labels(inline, inline_spacing)[source]

   locate_label(linecontour, labelwidth)[source]

Find good place to draw a label (relatively flat part of the contour).
   pop_label(index=- 1)[source]

Defaults to removing last label, but any index can be supplied
   print_label(linecontour, labelwidth)[source]

Return whether a contour is long enough to hold a label.
   set_label_props(label, text, color)[source]

Set the label properties - color, fontsize, text.
   too_close(x, y, lw)[source]

Return whether a label is already near this location.

   classmatplotlib.contour.ContourSet(ax, *args, levels=None, filled=False, linewidths=None, linestyles=None, hatches=(None,), alpha=None, origin=None, extent=None, cmap=None, colors=None, norm=None, vmin=None, vmax=None, extend='neither', antialiased=None, nchunk=0, locator=None, transform=None, **kwargs)[source]

Bases: matplotlib.cm.ScalarMappable, matplotlib.contour.ContourLabeler Store a set of contour lines or filled regions. User-callable method: clabel  Parameters

axAxes

levels[level0, level1, ..., leveln]

A list of floating point numbers indicating the contour levels.
allsegs[level0segs, level1segs, ...]

List of all the polygon segments for all the levels. For contour lines len(allsegs) == len(levels), and for filled contour regions len(allsegs) = len(levels)-1. The lists should look like level0segs = [polygon0, polygon1, ...]
polygon0 = [[x0, y0], [x1, y1], ...]

allkindsNone or [level0kinds, level1kinds, ...]

Optional list of all the polygon vertex kinds (code types), as described and used in Path. This is used to allow multiply- connected paths such as holes within filled polygons. If not None, len(allkinds) == len(allsegs). The lists should look like level0kinds = [polygon0kinds, ...]
polygon0kinds = [vertexcode0, vertexcode1, ...]
 If allkinds is not None, usually all polygons for a particular contour level are grouped together so that level0segs = [polygon0] and level0kinds = [polygon0kinds].  **kwargs

Keyword arguments are as described in the docstring of contour.    Attributes

axAxes

The Axes object in which the contours are drawn.
collectionssilent_list of PathCollections

The Artists representing the contour. This is a list of PathCollections for both line and filled contours.
levelsarray

The values of the contour levels.
layersarray

Same as levels for line contours; half-way between levels for filled contours. See ContourSet._process_colors.     Draw contour lines or filled regions, depending on whether keyword arg filled is False (default) or True. Call signature: ContourSet(ax, levels, allsegs, [allkinds], **kwargs)
  Parameters

axAxes

The Axes object to draw on.
levels[level0, level1, ..., leveln]

A list of floating point numbers indicating the contour levels.
allsegs[level0segs, level1segs, ...]

List of all the polygon segments for all the levels. For contour lines len(allsegs) == len(levels), and for filled contour regions len(allsegs) = len(levels)-1. The lists should look like level0segs = [polygon0, polygon1, ...]
polygon0 = [[x0, y0], [x1, y1], ...]

allkinds[level0kinds, level1kinds, ...], optional

Optional list of all the polygon vertex kinds (code types), as described and used in Path. This is used to allow multiply- connected paths such as holes within filled polygons. If not None, len(allkinds) == len(allsegs). The lists should look like level0kinds = [polygon0kinds, ...]
polygon0kinds = [vertexcode0, vertexcode1, ...]
 If allkinds is not None, usually all polygons for a particular contour level are grouped together so that level0segs = [polygon0] and level0kinds = [polygon0kinds].  **kwargs

Keyword arguments are as described in the docstring of contour.       changed()[source]

Call this whenever the mappable is changed to notify all the callbackSM listeners to the 'changed' signal.
   find_nearest_contour(x, y, indices=None, pixel=True)[source]

Find the point in the contour plot that is closest to (x, y).  Parameters

x, yfloat

The reference point.
indiceslist of int or None, default: None

Indices of contour levels to consider. If None (the default), all levels are considered.
pixelbool, default: True

If True, measure distance in pixel (screen) space, which is useful for manual contour labeling; else, measure distance in axes space.    Returns

contourCollection

The contour that is closest to (x, y).
segmentint

The index of the Path in contour that is closest to (x, y).
indexint

The index of the path segment in segment that is closest to (x, y).
xmin, yminfloat

The point in the contour plot that is closest to (x, y).
d2float

The squared distance from (xmin, ymin) to (x, y).
   get_alpha()[source]

Return alpha to be applied to all ContourSet artists.
   get_transform()[source]

Return the Transform instance used by this ContourSet.
   legend_elements(variable_name='x', str_format=<class 'str'>)[source]

Return a list of artists and labels suitable for passing through to legend which represent this ContourSet. The labels have the form "0 < x <= 1" stating the data ranges which the artists represent.  Parameters

variable_namestr

The string used inside the inequality used on the labels.
str_formatfunction: float -> str

Function used to format the numbers in the labels.    Returns

artistslist[Artist]

A list of the artists.
labelslist[str]

A list of the labels.
   set_alpha(alpha)[source]

Set the alpha blending value for all ContourSet artists. alpha must be between 0 (transparent) and 1 (opaque).

   classmatplotlib.contour.QuadContourSet(ax, *args, levels=None, filled=False, linewidths=None, linestyles=None, hatches=(None,), alpha=None, origin=None, extent=None, cmap=None, colors=None, norm=None, vmin=None, vmax=None, extend='neither', antialiased=None, nchunk=0, locator=None, transform=None, **kwargs)[source]

Bases: matplotlib.contour.ContourSet Create and store a set of contour lines or filled regions. This class is typically not instantiated directly by the user but by contour and contourf.  Attributes

axAxes

The Axes object in which the contours are drawn.
collectionssilent_list of PathCollections

The Artists representing the contour. This is a list of PathCollections for both line and filled contours.
levelsarray

The values of the contour levels.
layersarray

Same as levels for line contours; half-way between levels for filled contours. See ContourSet._process_colors.     Draw contour lines or filled regions, depending on whether keyword arg filled is False (default) or True. Call signature: ContourSet(ax, levels, allsegs, [allkinds], **kwargs)
  Parameters

axAxes

The Axes object to draw on.
levels[level0, level1, ..., leveln]

A list of floating point numbers indicating the contour levels.
allsegs[level0segs, level1segs, ...]

List of all the polygon segments for all the levels. For contour lines len(allsegs) == len(levels), and for filled contour regions len(allsegs) = len(levels)-1. The lists should look like level0segs = [polygon0, polygon1, ...]
polygon0 = [[x0, y0], [x1, y1], ...]

allkinds[level0kinds, level1kinds, ...], optional

Optional list of all the polygon vertex kinds (code types), as described and used in Path. This is used to allow multiply- connected paths such as holes within filled polygons. If not None, len(allkinds) == len(allsegs). The lists should look like level0kinds = [polygon0kinds, ...]
polygon0kinds = [vertexcode0, vertexcode1, ...]
 If allkinds is not None, usually all polygons for a particular contour level are grouped together so that level0segs = [polygon0] and level0kinds = [polygon0kinds].  **kwargs

Keyword arguments are as described in the docstring of contour.


classmatplotlib.contour.ClabelText(x=0, y=0, text='', color=None, verticalalignment='baseline', horizontalalignment='left', multialignment=None, fontproperties=None, rotation=None, linespacing=None, rotation_mode=None, usetex=None, wrap=False, transform_rotates_text=False, *, parse_math=True, **kwargs)[source]

Bases: matplotlib.text.Text Unlike the ordinary text, the get_rotation returns an updated angle in the pixel coordinate assuming that the input rotation is an angle in data coordinate (or whatever transform set). Create a Text instance at x, y with string text. Valid keyword arguments are:
Property Description
agg_filter a filter function, which takes a (m, n, 3) float array and a dpi value, and returns a (m, n, 3) array
alpha scalar or None
animated bool
backgroundcolor color
bbox dict with properties for patches.FancyBboxPatch
clip_box unknown
clip_on unknown
clip_path unknown
color or c color
figure Figure
fontfamily or family {FONTNAME, 'serif', 'sans-serif', 'cursive', 'fantasy', 'monospace'}
fontproperties or font or font_properties font_manager.FontProperties or str or pathlib.Path
fontsize or size float or {'xx-small', 'x-small', 'small', 'medium', 'large', 'x-large', 'xx-large'}
fontstretch or stretch {a numeric value in range 0-1000, 'ultra-condensed', 'extra-condensed', 'condensed', 'semi-condensed', 'normal', 'semi-expanded', 'expanded', 'extra-expanded', 'ultra-expanded'}
fontstyle or style {'normal', 'italic', 'oblique'}
fontvariant or variant {'normal', 'small-caps'}
fontweight or weight {a numeric value in range 0-1000, 'ultralight', 'light', 'normal', 'regular', 'book', 'medium', 'roman', 'semibold', 'demibold', 'demi', 'bold', 'heavy', 'extra bold', 'black'}
gid str
horizontalalignment or ha {'center', 'right', 'left'}
in_layout bool
label object
linespacing float (multiple of font size)
math_fontfamily str
multialignment or ma {'left', 'right', 'center'}
parse_math bool
path_effects AbstractPathEffect
picker None or bool or float or callable
position (float, float)
rasterized bool
rotation float or {'vertical', 'horizontal'}
rotation_mode {None, 'default', 'anchor'}
sketch_params (scale: float, length: float, randomness: float)
snap bool or None
text object
transform Transform
transform_rotates_text bool
url str
usetex bool or None
verticalalignment or va {'center', 'top', 'bottom', 'baseline', 'center_baseline'}
visible bool
wrap bool
x float
y float
zorder float     get_rotation()[source]

Return the text angle in degrees between 0 and 360.
   set(*, agg_filter=<UNSET>, alpha=<UNSET>, animated=<UNSET>, backgroundcolor=<UNSET>, bbox=<UNSET>, clip_box=<UNSET>, clip_on=<UNSET>, clip_path=<UNSET>, color=<UNSET>, fontfamily=<UNSET>, fontproperties=<UNSET>, fontsize=<UNSET>, fontstretch=<UNSET>, fontstyle=<UNSET>, fontvariant=<UNSET>, fontweight=<UNSET>, gid=<UNSET>, horizontalalignment=<UNSET>, in_layout=<UNSET>, label=<UNSET>, linespacing=<UNSET>, math_fontfamily=<UNSET>, multialignment=<UNSET>, parse_math=<UNSET>, path_effects=<UNSET>, picker=<UNSET>, position=<UNSET>, rasterized=<UNSET>, rotation=<UNSET>, rotation_mode=<UNSET>, sketch_params=<UNSET>, snap=<UNSET>, text=<UNSET>, transform=<UNSET>, transform_rotates_text=<UNSET>, url=<UNSET>, usetex=<UNSET>, verticalalignment=<UNSET>, visible=<UNSET>, wrap=<UNSET>, x=<UNSET>, y=<UNSET>, zorder=<UNSET>)[source]

Set multiple properties at once. Supported properties are
Property Description
agg_filter a filter function, which takes a (m, n, 3) float array and a dpi value, and returns a (m, n, 3) array
alpha scalar or None
animated bool
backgroundcolor color
bbox dict with properties for patches.FancyBboxPatch
clip_box Bbox
clip_on bool
clip_path Patch or (Path, Transform) or None
color or c color
figure Figure
fontfamily or family {FONTNAME, 'serif', 'sans-serif', 'cursive', 'fantasy', 'monospace'}
fontproperties or font or font_properties font_manager.FontProperties or str or pathlib.Path
fontsize or size float or {'xx-small', 'x-small', 'small', 'medium', 'large', 'x-large', 'xx-large'}
fontstretch or stretch {a numeric value in range 0-1000, 'ultra-condensed', 'extra-condensed', 'condensed', 'semi-condensed', 'normal', 'semi-expanded', 'expanded', 'extra-expanded', 'ultra-expanded'}
fontstyle or style {'normal', 'italic', 'oblique'}
fontvariant or variant {'normal', 'small-caps'}
fontweight or weight {a numeric value in range 0-1000, 'ultralight', 'light', 'normal', 'regular', 'book', 'medium', 'roman', 'semibold', 'demibold', 'demi', 'bold', 'heavy', 'extra bold', 'black'}
gid str
horizontalalignment or ha {'center', 'right', 'left'}
in_layout bool
label object
linespacing float (multiple of font size)
math_fontfamily str
multialignment or ma {'left', 'right', 'center'}
parse_math bool
path_effects AbstractPathEffect
picker None or bool or float or callable
position (float, float)
rasterized bool
rotation float or {'vertical', 'horizontal'}
rotation_mode {None, 'default', 'anchor'}
sketch_params (scale: float, length: float, randomness: float)
snap bool or None
text object
transform Transform
transform_rotates_text bool
url str
usetex bool or None
verticalalignment or va {'center', 'top', 'bottom', 'baseline', 'center_baseline'}
visible bool
wrap bool
x float
y float
zorder float


get_rotation()[source]

Return the text angle in degrees between 0 and 360.


set(*, agg_filter=<UNSET>, alpha=<UNSET>, animated=<UNSET>, backgroundcolor=<UNSET>, bbox=<UNSET>, clip_box=<UNSET>, clip_on=<UNSET>, clip_path=<UNSET>, color=<UNSET>, fontfamily=<UNSET>, fontproperties=<UNSET>, fontsize=<UNSET>, fontstretch=<UNSET>, fontstyle=<UNSET>, fontvariant=<UNSET>, fontweight=<UNSET>, gid=<UNSET>, horizontalalignment=<UNSET>, in_layout=<UNSET>, label=<UNSET>, linespacing=<UNSET>, math_fontfamily=<UNSET>, multialignment=<UNSET>, parse_math=<UNSET>, path_effects=<UNSET>, picker=<UNSET>, position=<UNSET>, rasterized=<UNSET>, rotation=<UNSET>, rotation_mode=<UNSET>, sketch_params=<UNSET>, snap=<UNSET>, text=<UNSET>, transform=<UNSET>, transform_rotates_text=<UNSET>, url=<UNSET>, usetex=<UNSET>, verticalalignment=<UNSET>, visible=<UNSET>, wrap=<UNSET>, x=<UNSET>, y=<UNSET>, zorder=<UNSET>)[source]

Set multiple properties at once. Supported properties are
Property Description
agg_filter a filter function, which takes a (m, n, 3) float array and a dpi value, and returns a (m, n, 3) array
alpha scalar or None
animated bool
backgroundcolor color
bbox dict with properties for patches.FancyBboxPatch
clip_box Bbox
clip_on bool
clip_path Patch or (Path, Transform) or None
color or c color
figure Figure
fontfamily or family {FONTNAME, 'serif', 'sans-serif', 'cursive', 'fantasy', 'monospace'}
fontproperties or font or font_properties font_manager.FontProperties or str or pathlib.Path
fontsize or size float or {'xx-small', 'x-small', 'small', 'medium', 'large', 'x-large', 'xx-large'}
fontstretch or stretch {a numeric value in range 0-1000, 'ultra-condensed', 'extra-condensed', 'condensed', 'semi-condensed', 'normal', 'semi-expanded', 'expanded', 'extra-expanded', 'ultra-expanded'}
fontstyle or style {'normal', 'italic', 'oblique'}
fontvariant or variant {'normal', 'small-caps'}
fontweight or weight {a numeric value in range 0-1000, 'ultralight', 'light', 'normal', 'regular', 'book', 'medium', 'roman', 'semibold', 'demibold', 'demi', 'bold', 'heavy', 'extra bold', 'black'}
gid str
horizontalalignment or ha {'center', 'right', 'left'}
in_layout bool
label object
linespacing float (multiple of font size)
math_fontfamily str
multialignment or ma {'left', 'right', 'center'}
parse_math bool
path_effects AbstractPathEffect
picker None or bool or float or callable
position (float, float)
rasterized bool
rotation float or {'vertical', 'horizontal'}
rotation_mode {None, 'default', 'anchor'}
sketch_params (scale: float, length: float, randomness: float)
snap bool or None
text object
transform Transform
transform_rotates_text bool
url str
usetex bool or None
verticalalignment or va {'center', 'top', 'bottom', 'baseline', 'center_baseline'}
visible bool
wrap bool
x float
y float
zorder float


classmatplotlib.contour.ContourLabeler[source]

Bases: object Mixin to provide labelling capability to ContourSet.   add_label(x, y, rotation, lev, cvalue)[source]

Add contour label using Text class.
   add_label_clabeltext(x, y, rotation, lev, cvalue)[source]

Add contour label using ClabelText class.
   add_label_near(x, y, inline=True, inline_spacing=5, transform=None)[source]

Add a label near the point (x, y).  Parameters

x, yfloat

The approximate location of the label.
inlinebool, default: True

If True remove the segment of the contour beneath the label.
inline_spacingint, default: 5

Space in pixels to leave on each side of label when placing inline. This spacing will be exact for labels at locations where the contour is straight, less so for labels on curved contours.
transformTransform or False, default: self.axes.transData

A transform applied to (x, y) before labeling. The default causes (x, y) to be interpreted as data coordinates. False is a synonym for IdentityTransform; i.e. (x, y) should be interpreted as display coordinates.
   calc_label_rot_and_inline(slc, ind, lw, lc=None, spacing=5)[source]

Calculate the appropriate label rotation given the linecontour coordinates in screen units, the index of the label location and the label width. If lc is not None or empty, also break contours and compute inlining. spacing is the empty space to leave around the label, in pixels. Both tasks are done together to avoid calculating path lengths multiple times, which is relatively costly. The method used here involves computing the path length along the contour in pixel coordinates and then looking approximately (label width / 2) away from central point to determine rotation and then to break contour if desired.
   clabel(levels=None, *, fontsize=None, inline=True, inline_spacing=5, fmt=None, colors=None, use_clabeltext=False, manual=False, rightside_up=True, zorder=None)[source]

Label a contour plot. Adds labels to line contours in this ContourSet (which inherits from this mixin class).  Parameters

levelsarray-like, optional

A list of level values, that should be labeled. The list must be a subset of cs.levels. If not given, all levels are labeled.
fontsizestr or float, default: rcParams["font.size"] (default: 10.0)

Size in points or relative size e.g., 'smaller', 'x-large'. See Text.set_size for accepted string values.
colorscolor or colors or None, default: None

The label colors:  If None, the color of each label matches the color of the corresponding contour. If one string color, e.g., colors = 'r' or colors = 'red', all labels will be plotted in this color. If a tuple of colors (string, float, rgb, etc), different labels will be plotted in different colors in the order specified.
inlinebool, default: True

If True the underlying contour is removed where the label is placed.
inline_spacingfloat, default: 5

Space in pixels to leave on each side of label when placing inline. This spacing will be exact for labels at locations where the contour is straight, less so for labels on curved contours.
fmtFormatter or str or callable or dict, optional

How the levels are formatted:  If a Formatter, it is used to format all levels at once, using its Formatter.format_ticks method. If a str, it is interpreted as a %-style format string. If a callable, it is called with one level at a time and should return the corresponding label. If a dict, it should directly map levels to labels.  The default is to use a standard ScalarFormatter.
manualbool or iterable, default: False

If True, contour labels will be placed manually using mouse clicks. Click the first button near a contour to add a label, click the second button (or potentially both mouse buttons at once) to finish adding labels. The third button can be used to remove the last label added, but only if labels are not inline. Alternatively, the keyboard can be used to select label locations (enter to end label placement, delete or backspace act like the third mouse button, and any other key will select a label location). manual can also be an iterable object of (x, y) tuples. Contour labels will be created as if mouse is clicked at each (x, y) position.
rightside_upbool, default: True

If True, label rotations will always be plus or minus 90 degrees from level.
use_clabeltextbool, default: False

If True, ClabelText class (instead of Text) is used to create labels. ClabelText recalculates rotation angles of texts during the drawing time, therefore this can be used if aspect of the axes changes.
zorderfloat or None, default: (2 + contour.get_zorder())

zorder of the contour labels.    Returns
 labels

A list of Text instances for the labels.
   get_label_coords(distances, XX, YY, ysize, lw)[source]

[Deprecated] Return x, y, and the index of a label location. Labels are plotted at a location with the smallest deviation of the contour from a straight line unless there is another label nearby, in which case the next best place on the contour is picked up. If all such candidates are rejected, the beginning of the contour is chosen. Notes  Deprecated since version 3.4.
   get_label_width(lev, fmt, fsize)[source]

[Deprecated] Return the width of the label in points. Notes  Deprecated since version 3.5.
   get_text(lev, fmt)[source]

Get the text of the label.
   labels(inline, inline_spacing)[source]

   locate_label(linecontour, labelwidth)[source]

Find good place to draw a label (relatively flat part of the contour).
   pop_label(index=- 1)[source]

Defaults to removing last label, but any index can be supplied
   print_label(linecontour, labelwidth)[source]

Return whether a contour is long enough to hold a label.
   set_label_props(label, text, color)[source]

Set the label properties - color, fontsize, text.
   too_close(x, y, lw)[source]

Return whether a label is already near this location.


add_label(x, y, rotation, lev, cvalue)[source]

Add contour label using Text class.


add_label_clabeltext(x, y, rotation, lev, cvalue)[source]

Add contour label using ClabelText class.


add_label_near(x, y, inline=True, inline_spacing=5, transform=None)[source]

Add a label near the point (x, y).  Parameters

x, yfloat

The approximate location of the label.
inlinebool, default: True

If True remove the segment of the contour beneath the label.
inline_spacingint, default: 5

Space in pixels to leave on each side of label when placing inline. This spacing will be exact for labels at locations where the contour is straight, less so for labels on curved contours.
transformTransform or False, default: self.axes.transData

A transform applied to (x, y) before labeling. The default causes (x, y) to be interpreted as data coordinates. False is a synonym for IdentityTransform; i.e. (x, y) should be interpreted as display coordinates.


calc_label_rot_and_inline(slc, ind, lw, lc=None, spacing=5)[source]

Calculate the appropriate label rotation given the linecontour coordinates in screen units, the index of the label location and the label width. If lc is not None or empty, also break contours and compute inlining. spacing is the empty space to leave around the label, in pixels. Both tasks are done together to avoid calculating path lengths multiple times, which is relatively costly. The method used here involves computing the path length along the contour in pixel coordinates and then looking approximately (label width / 2) away from central point to determine rotation and then to break contour if desired.


clabel(levels=None, *, fontsize=None, inline=True, inline_spacing=5, fmt=None, colors=None, use_clabeltext=False, manual=False, rightside_up=True, zorder=None)[source]

Label a contour plot. Adds labels to line contours in this ContourSet (which inherits from this mixin class).  Parameters

levelsarray-like, optional

A list of level values, that should be labeled. The list must be a subset of cs.levels. If not given, all levels are labeled.
fontsizestr or float, default: rcParams["font.size"] (default: 10.0)

Size in points or relative size e.g., 'smaller', 'x-large'. See Text.set_size for accepted string values.
colorscolor or colors or None, default: None

The label colors:  If None, the color of each label matches the color of the corresponding contour. If one string color, e.g., colors = 'r' or colors = 'red', all labels will be plotted in this color. If a tuple of colors (string, float, rgb, etc), different labels will be plotted in different colors in the order specified.
inlinebool, default: True

If True the underlying contour is removed where the label is placed.
inline_spacingfloat, default: 5

Space in pixels to leave on each side of label when placing inline. This spacing will be exact for labels at locations where the contour is straight, less so for labels on curved contours.
fmtFormatter or str or callable or dict, optional

How the levels are formatted:  If a Formatter, it is used to format all levels at once, using its Formatter.format_ticks method. If a str, it is interpreted as a %-style format string. If a callable, it is called with one level at a time and should return the corresponding label. If a dict, it should directly map levels to labels.  The default is to use a standard ScalarFormatter.
manualbool or iterable, default: False

If True, contour labels will be placed manually using mouse clicks. Click the first button near a contour to add a label, click the second button (or potentially both mouse buttons at once) to finish adding labels. The third button can be used to remove the last label added, but only if labels are not inline. Alternatively, the keyboard can be used to select label locations (enter to end label placement, delete or backspace act like the third mouse button, and any other key will select a label location). manual can also be an iterable object of (x, y) tuples. Contour labels will be created as if mouse is clicked at each (x, y) position.
rightside_upbool, default: True

If True, label rotations will always be plus or minus 90 degrees from level.
use_clabeltextbool, default: False

If True, ClabelText class (instead of Text) is used to create labels. ClabelText recalculates rotation angles of texts during the drawing time, therefore this can be used if aspect of the axes changes.
zorderfloat or None, default: (2 + contour.get_zorder())

zorder of the contour labels.    Returns
 labels

A list of Text instances for the labels.


get_label_coords(distances, XX, YY, ysize, lw)[source]

[Deprecated] Return x, y, and the index of a label location. Labels are plotted at a location with the smallest deviation of the contour from a straight line unless there is another label nearby, in which case the next best place on the contour is picked up. If all such candidates are rejected, the beginning of the contour is chosen. Notes  Deprecated since version 3.4.


get_label_width(lev, fmt, fsize)[source]

[Deprecated] Return the width of the label in points. Notes  Deprecated since version 3.5.


get_text(lev, fmt)[source]

Get the text of the label.


locate_label(linecontour, labelwidth)[source]

Find good place to draw a label (relatively flat part of the contour).


pop_label(index=- 1)[source]

Defaults to removing last label, but any index can be supplied


print_label(linecontour, labelwidth)[source]

Return whether a contour is long enough to hold a label.


set_label_props(label, text, color)[source]

Set the label properties - color, fontsize, text.


too_close(x, y, lw)[source]

Return whether a label is already near this location.


classmatplotlib.contour.ContourSet(ax, *args, levels=None, filled=False, linewidths=None, linestyles=None, hatches=(None,), alpha=None, origin=None, extent=None, cmap=None, colors=None, norm=None, vmin=None, vmax=None, extend='neither', antialiased=None, nchunk=0, locator=None, transform=None, **kwargs)[source]

Bases: matplotlib.cm.ScalarMappable, matplotlib.contour.ContourLabeler Store a set of contour lines or filled regions. User-callable method: clabel  Parameters

axAxes

levels[level0, level1, ..., leveln]

A list of floating point numbers indicating the contour levels.
allsegs[level0segs, level1segs, ...]

List of all the polygon segments for all the levels. For contour lines len(allsegs) == len(levels), and for filled contour regions len(allsegs) = len(levels)-1. The lists should look like level0segs = [polygon0, polygon1, ...]
polygon0 = [[x0, y0], [x1, y1], ...]

allkindsNone or [level0kinds, level1kinds, ...]

Optional list of all the polygon vertex kinds (code types), as described and used in Path. This is used to allow multiply- connected paths such as holes within filled polygons. If not None, len(allkinds) == len(allsegs). The lists should look like level0kinds = [polygon0kinds, ...]
polygon0kinds = [vertexcode0, vertexcode1, ...]
 If allkinds is not None, usually all polygons for a particular contour level are grouped together so that level0segs = [polygon0] and level0kinds = [polygon0kinds].  **kwargs

Keyword arguments are as described in the docstring of contour.    Attributes

axAxes

The Axes object in which the contours are drawn.
collectionssilent_list of PathCollections

The Artists representing the contour. This is a list of PathCollections for both line and filled contours.
levelsarray

The values of the contour levels.
layersarray

Same as levels for line contours; half-way between levels for filled contours. See ContourSet._process_colors.     Draw contour lines or filled regions, depending on whether keyword arg filled is False (default) or True. Call signature: ContourSet(ax, levels, allsegs, [allkinds], **kwargs)
  Parameters

axAxes

The Axes object to draw on.
levels[level0, level1, ..., leveln]

A list of floating point numbers indicating the contour levels.
allsegs[level0segs, level1segs, ...]

List of all the polygon segments for all the levels. For contour lines len(allsegs) == len(levels), and for filled contour regions len(allsegs) = len(levels)-1. The lists should look like level0segs = [polygon0, polygon1, ...]
polygon0 = [[x0, y0], [x1, y1], ...]

allkinds[level0kinds, level1kinds, ...], optional

Optional list of all the polygon vertex kinds (code types), as described and used in Path. This is used to allow multiply- connected paths such as holes within filled polygons. If not None, len(allkinds) == len(allsegs). The lists should look like level0kinds = [polygon0kinds, ...]
polygon0kinds = [vertexcode0, vertexcode1, ...]
 If allkinds is not None, usually all polygons for a particular contour level are grouped together so that level0segs = [polygon0] and level0kinds = [polygon0kinds].  **kwargs

Keyword arguments are as described in the docstring of contour.       changed()[source]

Call this whenever the mappable is changed to notify all the callbackSM listeners to the 'changed' signal.
   find_nearest_contour(x, y, indices=None, pixel=True)[source]

Find the point in the contour plot that is closest to (x, y).  Parameters

x, yfloat

The reference point.
indiceslist of int or None, default: None

Indices of contour levels to consider. If None (the default), all levels are considered.
pixelbool, default: True

If True, measure distance in pixel (screen) space, which is useful for manual contour labeling; else, measure distance in axes space.    Returns

contourCollection

The contour that is closest to (x, y).
segmentint

The index of the Path in contour that is closest to (x, y).
indexint

The index of the path segment in segment that is closest to (x, y).
xmin, yminfloat

The point in the contour plot that is closest to (x, y).
d2float

The squared distance from (xmin, ymin) to (x, y).
   get_alpha()[source]

Return alpha to be applied to all ContourSet artists.
   get_transform()[source]

Return the Transform instance used by this ContourSet.
   legend_elements(variable_name='x', str_format=<class 'str'>)[source]

Return a list of artists and labels suitable for passing through to legend which represent this ContourSet. The labels have the form "0 < x <= 1" stating the data ranges which the artists represent.  Parameters

variable_namestr

The string used inside the inequality used on the labels.
str_formatfunction: float -> str

Function used to format the numbers in the labels.    Returns

artistslist[Artist]

A list of the artists.
labelslist[str]

A list of the labels.
   set_alpha(alpha)[source]

Set the alpha blending value for all ContourSet artists. alpha must be between 0 (transparent) and 1 (opaque).


changed()[source]

Call this whenever the mappable is changed to notify all the callbackSM listeners to the 'changed' signal.


find_nearest_contour(x, y, indices=None, pixel=True)[source]

Find the point in the contour plot that is closest to (x, y).  Parameters

x, yfloat

The reference point.
indiceslist of int or None, default: None

Indices of contour levels to consider. If None (the default), all levels are considered.
pixelbool, default: True

If True, measure distance in pixel (screen) space, which is useful for manual contour labeling; else, measure distance in axes space.    Returns

contourCollection

The contour that is closest to (x, y).
segmentint

The index of the Path in contour that is closest to (x, y).
indexint

The index of the path segment in segment that is closest to (x, y).
xmin, yminfloat

The point in the contour plot that is closest to (x, y).
d2float

The squared distance from (xmin, ymin) to (x, y).


get_alpha()[source]

Return alpha to be applied to all ContourSet artists.


get_transform()[source]

Return the Transform instance used by this ContourSet.


legend_elements(variable_name='x', str_format=<class 'str'>)[source]

Return a list of artists and labels suitable for passing through to legend which represent this ContourSet. The labels have the form "0 < x <= 1" stating the data ranges which the artists represent.  Parameters

variable_namestr

The string used inside the inequality used on the labels.
str_formatfunction: float -> str

Function used to format the numbers in the labels.    Returns

artistslist[Artist]

A list of the artists.
labelslist[str]

A list of the labels.


set_alpha(alpha)[source]

Set the alpha blending value for all ContourSet artists. alpha must be between 0 (transparent) and 1 (opaque).


classmatplotlib.contour.QuadContourSet(ax, *args, levels=None, filled=False, linewidths=None, linestyles=None, hatches=(None,), alpha=None, origin=None, extent=None, cmap=None, colors=None, norm=None, vmin=None, vmax=None, extend='neither', antialiased=None, nchunk=0, locator=None, transform=None, **kwargs)[source]

Bases: matplotlib.contour.ContourSet Create and store a set of contour lines or filled regions. This class is typically not instantiated directly by the user but by contour and contourf.  Attributes

axAxes

The Axes object in which the contours are drawn.
collectionssilent_list of PathCollections

The Artists representing the contour. This is a list of PathCollections for both line and filled contours.
levelsarray

The values of the contour levels.
layersarray

Same as levels for line contours; half-way between levels for filled contours. See ContourSet._process_colors.     Draw contour lines or filled regions, depending on whether keyword arg filled is False (default) or True. Call signature: ContourSet(ax, levels, allsegs, [allkinds], **kwargs)
  Parameters

axAxes

The Axes object to draw on.
levels[level0, level1, ..., leveln]

A list of floating point numbers indicating the contour levels.
allsegs[level0segs, level1segs, ...]

List of all the polygon segments for all the levels. For contour lines len(allsegs) == len(levels), and for filled contour regions len(allsegs) = len(levels)-1. The lists should look like level0segs = [polygon0, polygon1, ...]
polygon0 = [[x0, y0], [x1, y1], ...]

allkinds[level0kinds, level1kinds, ...], optional

Optional list of all the polygon vertex kinds (code types), as described and used in Path. This is used to allow multiply- connected paths such as holes within filled polygons. If not None, len(allkinds) == len(allsegs). The lists should look like level0kinds = [polygon0kinds, ...]
polygon0kinds = [vertexcode0, vertexcode1, ...]
 If allkinds is not None, usually all polygons for a particular contour level are grouped together so that level0segs = [polygon0] and level0kinds = [polygon0kinds].  **kwargs

Keyword arguments are as described in the docstring of contour.


matplotlib.dates                      Matplotlib provides sophisticated date plotting capabilities, standing on the shoulders of python datetime and the add-on module dateutil. By default, Matplotlib uses the units machinery described in units to convert datetime.datetime, and numpy.datetime64 objects when plotted on an x- or y-axis. The user does not need to do anything for dates to be formatted, but dates often have strict formatting needs, so this module provides many axis locators and formatters. A basic example using numpy.datetime64 is: import numpy as np

times = np.arange(np.datetime64('2001-01-02'),
                  np.datetime64('2002-02-03'), np.timedelta64(75, 'm'))
y = np.random.randn(len(times))

fig, ax = plt.subplots()
ax.plot(times, y)
  See also  Date tick labels Formatting date ticks using ConciseDateFormatter Date Demo Convert    Matplotlib date format Matplotlib represents dates using floating point numbers specifying the number of days since a default epoch of 1970-01-01 UTC; for example, 1970-01-01, 06:00 is the floating point number 0.25. The formatters and locators require the use of datetime.datetime objects, so only dates between year 0001 and 9999 can be represented. Microsecond precision is achievable for (approximately) 70 years on either side of the epoch, and 20 microseconds for the rest of the allowable range of dates (year 0001 to 9999). The epoch can be changed at import time via dates.set_epoch or rcParams["dates.epoch"] to other dates if necessary; see Date Precision and Epochs for a discussion.  Note Before Matplotlib 3.3, the epoch was 0000-12-31 which lost modern microsecond precision and also made the default axis limit of 0 an invalid datetime. In 3.3 the epoch was changed as above. To convert old ordinal floats to the new epoch, users can do: new_ordinal = old_ordinal + mdates.date2num(np.datetime64('0000-12-31'))
  There are a number of helper functions to convert between datetime objects and Matplotlib dates:
datestr2num Convert a date string to a datenum using dateutil.parser.parse.
date2num Convert datetime objects to Matplotlib dates.
num2date Convert Matplotlib dates to datetime objects.
num2timedelta Convert number of days to a timedelta object.
drange Return a sequence of equally spaced Matplotlib dates.
set_epoch Set the epoch (origin for dates) for datetime calculations.
get_epoch Get the epoch used by dates.    Note Like Python's datetime.datetime, Matplotlib uses the Gregorian calendar for all conversions between dates and floating point numbers. This practice is not universal, and calendar differences can cause confusing differences between what Python and Matplotlib give as the number of days since 0001-01-01 and what other software and databases yield. For example, the US Naval Observatory uses a calendar that switches from Julian to Gregorian in October, 1582. Hence, using their calculator, the number of days between 0001-01-01 and 2006-04-01 is 732403, whereas using the Gregorian calendar via the datetime module we find: In [1]: date(2006, 4, 1).toordinal() - date(1, 1, 1).toordinal()
Out[1]: 732401
  All the Matplotlib date converters, tickers and formatters are timezone aware. If no explicit timezone is provided, rcParams["timezone"] (default: 'UTC') is assumed. If you want to use a custom time zone, pass a datetime.tzinfo instance with the tz keyword argument to num2date, Axis.axis_date, and any custom date tickers or locators you create. A wide range of specific and general purpose date tick locators and formatters are provided in this module. See matplotlib.ticker for general information on tick locators and formatters. These are described below. The dateutil module provides additional code to handle date ticking, making it easy to place ticks on any kinds of dates. See examples below.   Date tickers Most of the date tickers can locate single or multiple values. For example: # import constants for the days of the week
from matplotlib.dates import MO, TU, WE, TH, FR, SA, SU

# tick on mondays every week
loc = WeekdayLocator(byweekday=MO, tz=tz)

# tick on mondays and saturdays
loc = WeekdayLocator(byweekday=(MO, SA))
 In addition, most of the constructors take an interval argument: # tick on mondays every second week
loc = WeekdayLocator(byweekday=MO, interval=2)
 The rrule locator allows completely general date ticking: # tick every 5th easter
rule = rrulewrapper(YEARLY, byeaster=1, interval=5)
loc = RRuleLocator(rule)
 The available date tickers are:
MicrosecondLocator: Locate microseconds.
SecondLocator: Locate seconds.
MinuteLocator: Locate minutes.
HourLocator: Locate hours.
DayLocator: Locate specified days of the month.
WeekdayLocator: Locate days of the week, e.g., MO, TU.
MonthLocator: Locate months, e.g., 7 for July.
YearLocator: Locate years that are multiples of base.
RRuleLocator: Locate using a matplotlib.dates.rrulewrapper. rrulewrapper is a simple wrapper around dateutil's dateutil.rrule which allow almost arbitrary date tick specifications. See rrule example.
AutoDateLocator: On autoscale, this class picks the best DateLocator (e.g., RRuleLocator) to set the view limits and the tick locations. If called with interval_multiples=True it will make ticks line up with sensible multiples of the tick intervals. E.g. if the interval is 4 hours, it will pick hours 0, 4, 8, etc as ticks. This behaviour is not guaranteed by default.    Date formatters The available date formatters are:
AutoDateFormatter: attempts to figure out the best format to use. This is most useful when used with the AutoDateLocator.
ConciseDateFormatter: also attempts to figure out the best format to use, and to make the format as compact as possible while still having complete date information. This is most useful when used with the AutoDateLocator.
DateFormatter: use strftime format strings.    classmatplotlib.dates.AutoDateFormatter(locator, tz=None, defaultfmt='%Y-%m-%d', *, usetex=None)[source]

Bases: matplotlib.ticker.Formatter A Formatter which attempts to figure out the best format to use. This is most useful when used with the AutoDateLocator. AutoDateFormatter has a .scale dictionary that maps tick scales (the interval in days between one major tick) to format strings; this dictionary defaults to self.scaled = {
    DAYS_PER_YEAR: rcParams['date.autoformat.year'],
    DAYS_PER_MONTH: rcParams['date.autoformat.month'],
    1: rcParams['date.autoformat.day'],
    1 / HOURS_PER_DAY: rcParams['date.autoformat.hour'],
    1 / MINUTES_PER_DAY: rcParams['date.autoformat.minute'],
    1 / SEC_PER_DAY: rcParams['date.autoformat.second'],
    1 / MUSECONDS_PER_DAY: rcParams['date.autoformat.microsecond'],
}
 The formatter uses the format string corresponding to the lowest key in the dictionary that is greater or equal to the current scale. Dictionary entries can be customized: locator = AutoDateLocator()
formatter = AutoDateFormatter(locator)
formatter.scaled[1/(24*60)] = '%M:%S' # only show min and sec
 Custom callables can also be used instead of format strings. The following example shows how to use a custom format function to strip trailing zeros from decimal seconds and adds the date to the first ticklabel: def my_format_function(x, pos=None):
    x = matplotlib.dates.num2date(x)
    if pos == 0:
        fmt = '%D %H:%M:%S.%f'
    else:
        fmt = '%H:%M:%S.%f'
    label = x.strftime(fmt)
    label = label.rstrip("0")
    label = label.rstrip(".")
    return label

formatter.scaled[1/(24*60)] = my_format_function
 Autoformat the date labels.  Parameters

locatorticker.Locator

Locator that this axis is using.
tzstr, optional

Passed to dates.date2num.
defaultfmtstr

The default format to use if none of the values in self.scaled are greater than the unit returned by locator._get_unit().
usetexbool, default: rcParams["text.usetex"] (default: False)

To enable/disable the use of TeX's math mode for rendering the results of the formatter. If any entries in self.scaled are set as functions, then it is up to the customized function to enable or disable TeX's math mode itself.
   classmatplotlib.dates.AutoDateLocator(tz=None, minticks=5, maxticks=None, interval_multiples=True)[source]

Bases: matplotlib.dates.DateLocator On autoscale, this class picks the best DateLocator to set the view limits and the tick locations.  Attributes

intervalddict

Mapping of tick frequencies to multiples allowed for that ticking. The default is self.intervald = {
    YEARLY  : [1, 2, 4, 5, 10, 20, 40, 50, 100, 200, 400, 500,
               1000, 2000, 4000, 5000, 10000],
    MONTHLY : [1, 2, 3, 4, 6],
    DAILY   : [1, 2, 3, 7, 14, 21],
    HOURLY  : [1, 2, 3, 4, 6, 12],
    MINUTELY: [1, 5, 10, 15, 30],
    SECONDLY: [1, 5, 10, 15, 30],
    MICROSECONDLY: [1, 2, 5, 10, 20, 50, 100, 200, 500,
                    1000, 2000, 5000, 10000, 20000, 50000,
                    100000, 200000, 500000, 1000000],
}
 where the keys are defined in dateutil.rrule. The interval is used to specify multiples that are appropriate for the frequency of ticking. For instance, every 7 days is sensible for daily ticks, but for minutes/seconds, 15 or 30 make sense. When customizing, you should only modify the values for the existing keys. You should not add or delete entries. Example for forcing ticks every 3 hours: locator = AutoDateLocator()
locator.intervald[HOURLY] = [3]  # only show every 3 hours
      Parameters

tzdatetime.tzinfo

Ticks timezone.
minticksint

The minimum number of ticks desired; controls whether ticks occur yearly, monthly, etc.
maxticksint

The maximum number of ticks desired; controls the interval between ticks (ticking every other, every 3, etc.). For fine-grained control, this can be a dictionary mapping individual rrule frequency constants (YEARLY, MONTHLY, etc.) to their own maximum number of ticks. This can be used to keep the number of ticks appropriate to the format chosen in AutoDateFormatter. Any frequency not specified in this dictionary is given a default value.
interval_multiplesbool, default: True

Whether ticks should be chosen to be multiple of the interval, locking them to 'nicer' locations. For example, this will force the ticks to be at hours 0, 6, 12, 18 when hourly ticking is done at 6 hour intervals.       get_locator(dmin, dmax)[source]

Pick the best locator based on a distance.
   nonsingular(vmin, vmax)[source]

Given the proposed upper and lower extent, adjust the range if it is too close to being singular (i.e. a range of ~0).
   tick_values(vmin, vmax)[source]

Return the values of the located ticks given vmin and vmax.  Note To get tick locations with the vmin and vmax values defined automatically for the associated axis simply call the Locator instance: >>> print(type(loc))
<type 'Locator'>
>>> print(loc())
[1, 2, 3, 4]

   classmatplotlib.dates.ConciseDateConverter(formats=None, zero_formats=None, offset_formats=None, show_offset=True, *, interval_multiples=True)[source]

Bases: matplotlib.dates.DateConverter   axisinfo(unit, axis)[source]

Return the AxisInfo for unit. unit is a tzinfo instance or None. The axis argument is required but not used.

   classmatplotlib.dates.ConciseDateFormatter(locator, tz=None, formats=None, offset_formats=None, zero_formats=None, show_offset=True, *, usetex=None)[source]

Bases: matplotlib.ticker.Formatter A Formatter which attempts to figure out the best format to use for the date, and to make it as compact as possible, but still be complete. This is most useful when used with the AutoDateLocator: >>> locator = AutoDateLocator()
>>> formatter = ConciseDateFormatter(locator)
  Parameters

locatorticker.Locator

Locator that this axis is using.
tzstr, optional

Passed to dates.date2num.
formatslist of 6 strings, optional

Format strings for 6 levels of tick labelling: mostly years, months, days, hours, minutes, and seconds. Strings use the same format codes as strftime. Default is ['%Y', '%b', '%d', '%H:%M', '%H:%M', '%S.%f']
zero_formatslist of 6 strings, optional

Format strings for tick labels that are "zeros" for a given tick level. For instance, if most ticks are months, ticks around 1 Jan 2005 will be labeled "Dec", "2005", "Feb". The default is ['', '%Y', '%b', '%b-%d', '%H:%M', '%H:%M']
offset_formatslist of 6 strings, optional

Format strings for the 6 levels that is applied to the "offset" string found on the right side of an x-axis, or top of a y-axis. Combined with the tick labels this should completely specify the date. The default is: ['', '%Y', '%Y-%b', '%Y-%b-%d', '%Y-%b-%d', '%Y-%b-%d %H:%M']

show_offsetbool, default: True

Whether to show the offset or not.
usetexbool, default: rcParams["text.usetex"] (default: False)

To enable/disable the use of TeX's math mode for rendering the results of the formatter.     Examples See Formatting date ticks using ConciseDateFormatter (Source code, png, pdf)    Autoformat the date labels. The default format is used to form an initial string, and then redundant elements are removed.   format_data_short(value)[source]

Return a short string version of the tick value. Defaults to the position-independent long value.
   format_ticks(values)[source]

Return the tick labels for all the ticks at once.
   get_offset()[source]

   classmatplotlib.dates.DateConverter(*, interval_multiples=True)[source]

Bases: matplotlib.units.ConversionInterface Converter for datetime.date and datetime.datetime data, or for date/time data represented as it would be converted by date2num. The 'unit' tag for such data is None or a tzinfo instance.   axisinfo(unit, axis)[source]

Return the AxisInfo for unit. unit is a tzinfo instance or None. The axis argument is required but not used.
   staticconvert(value, unit, axis)[source]

If value is not already a number or sequence of numbers, convert it with date2num. The unit and axis arguments are not used.
   staticdefault_units(x, axis)[source]

Return the tzinfo instance of x or of its first element, or None

   classmatplotlib.dates.DateFormatter(fmt, tz=None, *, usetex=None)[source]

Bases: matplotlib.ticker.Formatter Format a tick (in days since the epoch) with a strftime format string.  Parameters

fmtstr

strftime format string
tzdatetime.tzinfo, default: rcParams["timezone"] (default: 'UTC')

Ticks timezone.
usetexbool, default: rcParams["text.usetex"] (default: False)

To enable/disable the use of TeX's math mode for rendering the results of the formatter.       set_tzinfo(tz)[source]

   classmatplotlib.dates.DateLocator(tz=None)[source]

Bases: matplotlib.ticker.Locator Determines the tick locations when plotting dates. This class is subclassed by other Locators and is not meant to be used on its own.  Parameters

tzdatetime.tzinfo

     datalim_to_dt()[source]

Convert axis data interval to datetime objects.
   hms0d={'byhour': 0, 'byminute': 0, 'bysecond': 0}

   nonsingular(vmin, vmax)[source]

Given the proposed upper and lower extent, adjust the range if it is too close to being singular (i.e. a range of ~0).
   set_tzinfo(tz)[source]

Set time zone info.
   viewlim_to_dt()[source]

Convert the view interval to datetime objects.

   classmatplotlib.dates.DayLocator(bymonthday=None, interval=1, tz=None)[source]

Bases: matplotlib.dates.RRuleLocator Make ticks on occurrences of each day of the month. For example, 1, 15, 30. Mark every day in bymonthday; bymonthday can be an int or sequence. Default is to tick every day of the month: bymonthday=range(1, 32).
   classmatplotlib.dates.HourLocator(byhour=None, interval=1, tz=None)[source]

Bases: matplotlib.dates.RRuleLocator Make ticks on occurrences of each hour. Mark every hour in byhour; byhour can be an int or sequence. Default is to tick every hour: byhour=range(24) interval is the interval between each iteration. For example, if interval=2, mark every second occurrence.
   classmatplotlib.dates.MicrosecondLocator(interval=1, tz=None)[source]

Bases: matplotlib.dates.DateLocator Make ticks on regular intervals of one or more microsecond(s).  Note By default, Matplotlib uses a floating point representation of time in days since the epoch, so plotting data with microsecond time resolution does not work well for dates that are far (about 70 years) from the epoch (check with get_epoch). If you want sub-microsecond resolution time plots, it is strongly recommended to use floating point seconds, not datetime-like time representation. If you really must use datetime.datetime() or similar and still need microsecond precision, change the time origin via dates.set_epoch to something closer to the dates being plotted. See Date Precision and Epochs.  interval is the interval between each iteration. For example, if interval=2, mark every second microsecond.   set_axis(axis)[source]

   set_data_interval(vmin, vmax)[source]

[Deprecated] Notes  Deprecated since version 3.5:
   set_view_interval(vmin, vmax)[source]

[Deprecated] Notes  Deprecated since version 3.5:
   tick_values(vmin, vmax)[source]

Return the values of the located ticks given vmin and vmax.  Note To get tick locations with the vmin and vmax values defined automatically for the associated axis simply call the Locator instance: >>> print(type(loc))
<type 'Locator'>
>>> print(loc())
[1, 2, 3, 4]

   classmatplotlib.dates.MinuteLocator(byminute=None, interval=1, tz=None)[source]

Bases: matplotlib.dates.RRuleLocator Make ticks on occurrences of each minute. Mark every minute in byminute; byminute can be an int or sequence. Default is to tick every minute: byminute=range(60) interval is the interval between each iteration. For example, if interval=2, mark every second occurrence.
   classmatplotlib.dates.MonthLocator(bymonth=None, bymonthday=1, interval=1, tz=None)[source]

Bases: matplotlib.dates.RRuleLocator Make ticks on occurrences of each month, e.g., 1, 3, 12. Mark every month in bymonth; bymonth can be an int or sequence. Default is range(1, 13), i.e. every month. interval is the interval between each iteration. For example, if interval=2, mark every second occurrence.
   classmatplotlib.dates.RRuleLocator(o, tz=None)[source]

Bases: matplotlib.dates.DateLocator  Parameters

tzdatetime.tzinfo

     staticget_unit_generic(freq)[source]

   tick_values(vmin, vmax)[source]

Return the values of the located ticks given vmin and vmax.  Note To get tick locations with the vmin and vmax values defined automatically for the associated axis simply call the Locator instance: >>> print(type(loc))
<type 'Locator'>
>>> print(loc())
[1, 2, 3, 4]

   classmatplotlib.dates.SecondLocator(bysecond=None, interval=1, tz=None)[source]

Bases: matplotlib.dates.RRuleLocator Make ticks on occurrences of each second. Mark every second in bysecond; bysecond can be an int or sequence. Default is to tick every second: bysecond = range(60) interval is the interval between each iteration. For example, if interval=2, mark every second occurrence.
   classmatplotlib.dates.WeekdayLocator(byweekday=1, interval=1, tz=None)[source]

Bases: matplotlib.dates.RRuleLocator Make ticks on occurrences of each weekday. Mark every weekday in byweekday; byweekday can be a number or sequence. Elements of byweekday must be one of MO, TU, WE, TH, FR, SA, SU, the constants from dateutil.rrule, which have been imported into the matplotlib.dates namespace. interval specifies the number of weeks to skip. For example, interval=2 plots every second week.
   classmatplotlib.dates.YearLocator(base=1, month=1, day=1, tz=None)[source]

Bases: matplotlib.dates.RRuleLocator Make ticks on a given day of each year that is a multiple of base. Examples: # Tick every year on Jan 1st
locator = YearLocator()

# Tick every 5 years on July 4th
locator = YearLocator(5, month=7, day=4)
 Mark years that are multiple of base on a given month and day (default jan 1).
   matplotlib.dates.date2num(d)[source]

Convert datetime objects to Matplotlib dates.  Parameters

ddatetime.datetime or numpy.datetime64 or sequences of these

  Returns
 float or sequence of floats

Number of days since the epoch. See get_epoch for the epoch, which can be changed by rcParams["date.epoch"] (default: '1970-01-01T00:00:00') or set_epoch. If the epoch is "1970-01-01T00:00:00" (default) then noon Jan 1 1970 ("1970-01-01T12:00:00") returns 0.5.     Notes The Gregorian calendar is assumed; this is not universal practice. For details see the module docstring.
   matplotlib.dates.datestr2num(d, default=None)[source]

Convert a date string to a datenum using dateutil.parser.parse.  Parameters

dstr or sequence of str

The dates to convert.
defaultdatetime.datetime, optional

The default date to use when fields are missing in d.
   matplotlib.dates.drange(dstart, dend, delta)[source]

Return a sequence of equally spaced Matplotlib dates. The dates start at dstart and reach up to, but not including dend. They are spaced by delta.  Parameters

dstart, denddatetime

The date limits.
deltadatetime.timedelta

Spacing of the dates.    Returns
 numpy.array

A list floats representing Matplotlib dates.
   matplotlib.dates.epoch2num(e)[source]

[Deprecated] Convert UNIX time to days since Matplotlib epoch.  Parameters

elist of floats

Time in seconds since 1970-01-01.    Returns
 numpy.array

Time in days since Matplotlib epoch (see get_epoch()).     Notes  Deprecated since version 3.5.
   matplotlib.dates.get_epoch()[source]

Get the epoch used by dates.  Returns

epochstr

String for the epoch (parsable by numpy.datetime64).
   matplotlib.dates.num2date(x, tz=None)[source]

Convert Matplotlib dates to datetime objects.  Parameters

xfloat or sequence of floats

Number of days (fraction part represents hours, minutes, seconds) since the epoch. See get_epoch for the epoch, which can be changed by rcParams["date.epoch"] (default: '1970-01-01T00:00:00') or set_epoch.
tzstr, default: rcParams["timezone"] (default: 'UTC')

Timezone of x.    Returns

datetime or sequence of datetime

Dates are returned in timezone tz. If x is a sequence, a sequence of datetime objects will be returned.     Notes The addition of one here is a historical artifact. Also, note that the Gregorian calendar is assumed; this is not universal practice. For details, see the module docstring.
   matplotlib.dates.num2epoch(d)[source]

[Deprecated] Convert days since Matplotlib epoch to UNIX time.  Parameters

dlist of floats

Time in days since Matplotlib epoch (see get_epoch()).    Returns
 numpy.array

Time in seconds since 1970-01-01.     Notes  Deprecated since version 3.5.
   matplotlib.dates.num2timedelta(x)[source]

Convert number of days to a timedelta object. If x is a sequence, a sequence of timedelta objects will be returned.  Parameters

xfloat, sequence of floats

Number of days. The fraction part represents hours, minutes, seconds.    Returns

datetime.timedelta or list[datetime.timedelta]

   classmatplotlib.dates.relativedelta(dt1=None, dt2=None, years=0, months=0, days=0, leapdays=0, weeks=0, hours=0, minutes=0, seconds=0, microseconds=0, year=None, month=None, day=None, weekday=None, yearday=None, nlyearday=None, hour=None, minute=None, second=None, microsecond=None)

Bases: object The relativedelta type is designed to be applied to an existing datetime and can replace specific components of that datetime, or represents an interval of time. It is based on the specification of the excellent work done by M.-A. Lemburg in his mx.DateTime extension. However, notice that this type does NOT implement the same algorithm as his work. Do NOT expect it to behave like mx.DateTime's counterpart. There are two different ways to build a relativedelta instance. The first one is passing it two date/datetime classes: relativedelta(datetime1, datetime2)
 The second one is passing it any number of the following keyword arguments: relativedelta(arg1=x,arg2=y,arg3=z...)

year, month, day, hour, minute, second, microsecond:
    Absolute information (argument is singular); adding or subtracting a
    relativedelta with absolute information does not perform an arithmetic
    operation, but rather REPLACES the corresponding value in the
    original datetime with the value(s) in relativedelta.

years, months, weeks, days, hours, minutes, seconds, microseconds:
    Relative information, may be negative (argument is plural); adding
    or subtracting a relativedelta with relative information performs
    the corresponding arithmetic operation on the original datetime value
    with the information in the relativedelta.

weekday:
    One of the weekday instances (MO, TU, etc) available in the
    relativedelta module. These instances may receive a parameter N,
    specifying the Nth weekday, which could be positive or negative
    (like MO(+1) or MO(-2)). Not specifying it is the same as specifying
    +1. You can also use an integer, where 0=MO. This argument is always
    relative e.g. if the calculated date is already Monday, using MO(1)
    or MO(-1) won't change the day. To effectively make it absolute, use
    it in combination with the day argument (e.g. day=1, MO(1) for first
    Monday of the month).

leapdays:
    Will add given days to the date found, if year is a leap
    year, and the date found is post 28 of february.

yearday, nlyearday:
    Set the yearday or the non-leap year day (jump leap days).
    These are converted to day/month/leapdays information.
 There are relative and absolute forms of the keyword arguments. The plural is relative, and the singular is absolute. For each argument in the order below, the absolute form is applied first (by setting each attribute to that value) and then the relative form (by adding the value to the attribute). The order of attributes considered when this relativedelta is added to a datetime is:  Year Month Day Hours Minutes Seconds Microseconds  Finally, weekday is applied, using the rule described above. For example >>> from datetime import datetime
>>> from dateutil.relativedelta import relativedelta, MO
>>> dt = datetime(2018, 4, 9, 13, 37, 0)
>>> delta = relativedelta(hours=25, day=1, weekday=MO(1))
>>> dt + delta
datetime.datetime(2018, 4, 2, 14, 37)
 First, the day is set to 1 (the first of the month), then 25 hours are added, to get to the 2nd day and 14th hour, finally the weekday is applied, but since the 2nd is already a Monday there is no effect.   normalized()

Return a version of this object represented entirely using integer values for the relative attributes. >>> relativedelta(days=1.5, hours=2).normalized()
relativedelta(days=+1, hours=+14)
  Returns
Returns a dateutil.relativedelta.relativedelta object.
   propertyweeks

   classmatplotlib.dates.rrule(freq, dtstart=None, interval=1, wkst=None, count=None, until=None, bysetpos=None, bymonth=None, bymonthday=None, byyearday=None, byeaster=None, byweekno=None, byweekday=None, byhour=None, byminute=None, bysecond=None, cache=False)

Bases: dateutil.rrule.rrulebase That's the base of the rrule operation. It accepts all the keywords defined in the RFC as its constructor parameters (except byday, which was renamed to byweekday) and more. The constructor prototype is: rrule(freq)
 Where freq must be one of YEARLY, MONTHLY, WEEKLY, DAILY, HOURLY, MINUTELY, or SECONDLY.  Note Per RFC section 3.3.10, recurrence instances falling on invalid dates and times are ignored rather than coerced: Recurrence rules may generate recurrence instances with an invalid date (e.g., February 30) or nonexistent local time (e.g., 1:30 AM on a day where the local time is moved forward by an hour at 1:00 AM). Such recurrence instances MUST be ignored and MUST NOT be counted as part of the recurrence set. This can lead to possibly surprising behavior when, for example, the start date occurs at the end of the month: >>> from dateutil.rrule import rrule, MONTHLY
>>> from datetime import datetime
>>> start_date = datetime(2014, 12, 31)
>>> list(rrule(freq=MONTHLY, count=4, dtstart=start_date))
...
[datetime.datetime(2014, 12, 31, 0, 0),
 datetime.datetime(2015, 1, 31, 0, 0),
 datetime.datetime(2015, 3, 31, 0, 0),
 datetime.datetime(2015, 5, 31, 0, 0)]
  Additionally, it supports the following keyword arguments:  Parameters

dtstart -- The recurrence start. Besides being the base for the recurrence, missing parameters in the final recurrence instances will also be extracted from this date. If not given, datetime.now() will be used instead.
interval -- The interval between each freq iteration. For example, when using YEARLY, an interval of 2 means once every two years, but with HOURLY, it means once every two hours. The default interval is 1.
wkst -- The week start day. Must be one of the MO, TU, WE constants, or an integer, specifying the first day of the week. This will affect recurrences based on weekly periods. The default week start is got from calendar.firstweekday(), and may be modified by calendar.setfirstweekday().
count --
If given, this determines how many occurrences will be generated.  Note As of version 2.5.0, the use of the keyword until in conjunction with count is deprecated, to make sure dateutil is fully compliant with RFC-5545 Sec. 3.3.10. Therefore, until and count must not occur in the same call to rrule.
until --
If given, this must be a datetime instance specifying the upper-bound limit of the recurrence. The last recurrence in the rule is the greatest datetime that is less than or equal to the value specified in the until parameter.  Note As of version 2.5.0, the use of the keyword until in conjunction with count is deprecated, to make sure dateutil is fully compliant with RFC-5545 Sec. 3.3.10. Therefore, until and count must not occur in the same call to rrule.
bysetpos -- If given, it must be either an integer, or a sequence of integers, positive or negative. Each given integer will specify an occurrence number, corresponding to the nth occurrence of the rule inside the frequency period. For example, a bysetpos of -1 if combined with a MONTHLY frequency, and a byweekday of (MO, TU, WE, TH, FR), will result in the last work day of every month.
bymonth -- If given, it must be either an integer, or a sequence of integers, meaning the months to apply the recurrence to.
bymonthday -- If given, it must be either an integer, or a sequence of integers, meaning the month days to apply the recurrence to.
byyearday -- If given, it must be either an integer, or a sequence of integers, meaning the year days to apply the recurrence to.
byeaster -- If given, it must be either an integer, or a sequence of integers, positive or negative. Each integer will define an offset from the Easter Sunday. Passing the offset 0 to byeaster will yield the Easter Sunday itself. This is an extension to the RFC specification.
byweekno -- If given, it must be either an integer, or a sequence of integers, meaning the week numbers to apply the recurrence to. Week numbers have the meaning described in ISO8601, that is, the first week of the year is that containing at least four days of the new year.
byweekday -- If given, it must be either an integer (0 == MO), a sequence of integers, one of the weekday constants (MO, TU, etc), or a sequence of these constants. When given, these variables will define the weekdays where the recurrence will be applied. It's also possible to use an argument n for the weekday instances, which will mean the nth occurrence of this weekday in the period. For example, with MONTHLY, or with YEARLY and BYMONTH, using FR(+1) in byweekday will specify the first friday of the month where the recurrence happens. Notice that in the RFC documentation, this is specified as BYDAY, but was renamed to avoid the ambiguity of that keyword.
byhour -- If given, it must be either an integer, or a sequence of integers, meaning the hours to apply the recurrence to.
byminute -- If given, it must be either an integer, or a sequence of integers, meaning the minutes to apply the recurrence to.
bysecond -- If given, it must be either an integer, or a sequence of integers, meaning the seconds to apply the recurrence to.
cache -- If given, it must be a boolean value specifying to enable or disable caching of results. If you will use the same rrule instance multiple times, enabling caching will improve the performance considerably.      replace(**kwargs)

Return new rrule with same attributes except for those attributes given new values by whichever keyword arguments are specified.

   matplotlib.dates.set_epoch(epoch)[source]

Set the epoch (origin for dates) for datetime calculations. The default epoch is rcParams["dates.epoch"] (by default 1970-01-01T00:00). If microsecond accuracy is desired, the date being plotted needs to be within approximately 70 years of the epoch. Matplotlib internally represents dates as days since the epoch, so floating point dynamic range needs to be within a factor of 2^52. set_epoch must be called before any dates are converted (i.e. near the import section) or a RuntimeError will be raised. See also Date Precision and Epochs.  Parameters

epochstr

valid UTC date parsable by numpy.datetime64 (do not include timezone).


classmatplotlib.dates.AutoDateFormatter(locator, tz=None, defaultfmt='%Y-%m-%d', *, usetex=None)[source]

Bases: matplotlib.ticker.Formatter A Formatter which attempts to figure out the best format to use. This is most useful when used with the AutoDateLocator. AutoDateFormatter has a .scale dictionary that maps tick scales (the interval in days between one major tick) to format strings; this dictionary defaults to self.scaled = {
    DAYS_PER_YEAR: rcParams['date.autoformat.year'],
    DAYS_PER_MONTH: rcParams['date.autoformat.month'],
    1: rcParams['date.autoformat.day'],
    1 / HOURS_PER_DAY: rcParams['date.autoformat.hour'],
    1 / MINUTES_PER_DAY: rcParams['date.autoformat.minute'],
    1 / SEC_PER_DAY: rcParams['date.autoformat.second'],
    1 / MUSECONDS_PER_DAY: rcParams['date.autoformat.microsecond'],
}
 The formatter uses the format string corresponding to the lowest key in the dictionary that is greater or equal to the current scale. Dictionary entries can be customized: locator = AutoDateLocator()
formatter = AutoDateFormatter(locator)
formatter.scaled[1/(24*60)] = '%M:%S' # only show min and sec
 Custom callables can also be used instead of format strings. The following example shows how to use a custom format function to strip trailing zeros from decimal seconds and adds the date to the first ticklabel: def my_format_function(x, pos=None):
    x = matplotlib.dates.num2date(x)
    if pos == 0:
        fmt = '%D %H:%M:%S.%f'
    else:
        fmt = '%H:%M:%S.%f'
    label = x.strftime(fmt)
    label = label.rstrip("0")
    label = label.rstrip(".")
    return label

formatter.scaled[1/(24*60)] = my_format_function
 Autoformat the date labels.  Parameters

locatorticker.Locator

Locator that this axis is using.
tzstr, optional

Passed to dates.date2num.
defaultfmtstr

The default format to use if none of the values in self.scaled are greater than the unit returned by locator._get_unit().
usetexbool, default: rcParams["text.usetex"] (default: False)

To enable/disable the use of TeX's math mode for rendering the results of the formatter. If any entries in self.scaled are set as functions, then it is up to the customized function to enable or disable TeX's math mode itself.


classmatplotlib.dates.AutoDateLocator(tz=None, minticks=5, maxticks=None, interval_multiples=True)[source]

Bases: matplotlib.dates.DateLocator On autoscale, this class picks the best DateLocator to set the view limits and the tick locations.  Attributes

intervalddict

Mapping of tick frequencies to multiples allowed for that ticking. The default is self.intervald = {
    YEARLY  : [1, 2, 4, 5, 10, 20, 40, 50, 100, 200, 400, 500,
               1000, 2000, 4000, 5000, 10000],
    MONTHLY : [1, 2, 3, 4, 6],
    DAILY   : [1, 2, 3, 7, 14, 21],
    HOURLY  : [1, 2, 3, 4, 6, 12],
    MINUTELY: [1, 5, 10, 15, 30],
    SECONDLY: [1, 5, 10, 15, 30],
    MICROSECONDLY: [1, 2, 5, 10, 20, 50, 100, 200, 500,
                    1000, 2000, 5000, 10000, 20000, 50000,
                    100000, 200000, 500000, 1000000],
}
 where the keys are defined in dateutil.rrule. The interval is used to specify multiples that are appropriate for the frequency of ticking. For instance, every 7 days is sensible for daily ticks, but for minutes/seconds, 15 or 30 make sense. When customizing, you should only modify the values for the existing keys. You should not add or delete entries. Example for forcing ticks every 3 hours: locator = AutoDateLocator()
locator.intervald[HOURLY] = [3]  # only show every 3 hours
      Parameters

tzdatetime.tzinfo

Ticks timezone.
minticksint

The minimum number of ticks desired; controls whether ticks occur yearly, monthly, etc.
maxticksint

The maximum number of ticks desired; controls the interval between ticks (ticking every other, every 3, etc.). For fine-grained control, this can be a dictionary mapping individual rrule frequency constants (YEARLY, MONTHLY, etc.) to their own maximum number of ticks. This can be used to keep the number of ticks appropriate to the format chosen in AutoDateFormatter. Any frequency not specified in this dictionary is given a default value.
interval_multiplesbool, default: True

Whether ticks should be chosen to be multiple of the interval, locking them to 'nicer' locations. For example, this will force the ticks to be at hours 0, 6, 12, 18 when hourly ticking is done at 6 hour intervals.       get_locator(dmin, dmax)[source]

Pick the best locator based on a distance.
   nonsingular(vmin, vmax)[source]

Given the proposed upper and lower extent, adjust the range if it is too close to being singular (i.e. a range of ~0).
   tick_values(vmin, vmax)[source]

Return the values of the located ticks given vmin and vmax.  Note To get tick locations with the vmin and vmax values defined automatically for the associated axis simply call the Locator instance: >>> print(type(loc))
<type 'Locator'>
>>> print(loc())
[1, 2, 3, 4]


get_locator(dmin, dmax)[source]

Pick the best locator based on a distance.


nonsingular(vmin, vmax)[source]

Given the proposed upper and lower extent, adjust the range if it is too close to being singular (i.e. a range of ~0).


tick_values(vmin, vmax)[source]

Return the values of the located ticks given vmin and vmax.  Note To get tick locations with the vmin and vmax values defined automatically for the associated axis simply call the Locator instance: >>> print(type(loc))
<type 'Locator'>
>>> print(loc())
[1, 2, 3, 4]


classmatplotlib.dates.ConciseDateConverter(formats=None, zero_formats=None, offset_formats=None, show_offset=True, *, interval_multiples=True)[source]

Bases: matplotlib.dates.DateConverter   axisinfo(unit, axis)[source]

Return the AxisInfo for unit. unit is a tzinfo instance or None. The axis argument is required but not used.


axisinfo(unit, axis)[source]

Return the AxisInfo for unit. unit is a tzinfo instance or None. The axis argument is required but not used.


classmatplotlib.dates.ConciseDateFormatter(locator, tz=None, formats=None, offset_formats=None, zero_formats=None, show_offset=True, *, usetex=None)[source]

Bases: matplotlib.ticker.Formatter A Formatter which attempts to figure out the best format to use for the date, and to make it as compact as possible, but still be complete. This is most useful when used with the AutoDateLocator: >>> locator = AutoDateLocator()
>>> formatter = ConciseDateFormatter(locator)
  Parameters

locatorticker.Locator

Locator that this axis is using.
tzstr, optional

Passed to dates.date2num.
formatslist of 6 strings, optional

Format strings for 6 levels of tick labelling: mostly years, months, days, hours, minutes, and seconds. Strings use the same format codes as strftime. Default is ['%Y', '%b', '%d', '%H:%M', '%H:%M', '%S.%f']
zero_formatslist of 6 strings, optional

Format strings for tick labels that are "zeros" for a given tick level. For instance, if most ticks are months, ticks around 1 Jan 2005 will be labeled "Dec", "2005", "Feb". The default is ['', '%Y', '%b', '%b-%d', '%H:%M', '%H:%M']
offset_formatslist of 6 strings, optional

Format strings for the 6 levels that is applied to the "offset" string found on the right side of an x-axis, or top of a y-axis. Combined with the tick labels this should completely specify the date. The default is: ['', '%Y', '%Y-%b', '%Y-%b-%d', '%Y-%b-%d', '%Y-%b-%d %H:%M']

show_offsetbool, default: True

Whether to show the offset or not.
usetexbool, default: rcParams["text.usetex"] (default: False)

To enable/disable the use of TeX's math mode for rendering the results of the formatter.     Examples See Formatting date ticks using ConciseDateFormatter (Source code, png, pdf)    Autoformat the date labels. The default format is used to form an initial string, and then redundant elements are removed.   format_data_short(value)[source]

Return a short string version of the tick value. Defaults to the position-independent long value.
   format_ticks(values)[source]

Return the tick labels for all the ticks at once.
   get_offset()[source]


format_data_short(value)[source]

Return a short string version of the tick value. Defaults to the position-independent long value.


format_ticks(values)[source]

Return the tick labels for all the ticks at once.


matplotlib.dates.date2num(d)[source]

Convert datetime objects to Matplotlib dates.  Parameters

ddatetime.datetime or numpy.datetime64 or sequences of these

  Returns
 float or sequence of floats

Number of days since the epoch. See get_epoch for the epoch, which can be changed by rcParams["date.epoch"] (default: '1970-01-01T00:00:00') or set_epoch. If the epoch is "1970-01-01T00:00:00" (default) then noon Jan 1 1970 ("1970-01-01T12:00:00") returns 0.5.     Notes The Gregorian calendar is assumed; this is not universal practice. For details see the module docstring.


classmatplotlib.dates.DateConverter(*, interval_multiples=True)[source]

Bases: matplotlib.units.ConversionInterface Converter for datetime.date and datetime.datetime data, or for date/time data represented as it would be converted by date2num. The 'unit' tag for such data is None or a tzinfo instance.   axisinfo(unit, axis)[source]

Return the AxisInfo for unit. unit is a tzinfo instance or None. The axis argument is required but not used.
   staticconvert(value, unit, axis)[source]

If value is not already a number or sequence of numbers, convert it with date2num. The unit and axis arguments are not used.
   staticdefault_units(x, axis)[source]

Return the tzinfo instance of x or of its first element, or None


staticconvert(value, unit, axis)[source]

If value is not already a number or sequence of numbers, convert it with date2num. The unit and axis arguments are not used.


staticdefault_units(x, axis)[source]

Return the tzinfo instance of x or of its first element, or None


classmatplotlib.dates.DateFormatter(fmt, tz=None, *, usetex=None)[source]

Bases: matplotlib.ticker.Formatter Format a tick (in days since the epoch) with a strftime format string.  Parameters

fmtstr

strftime format string
tzdatetime.tzinfo, default: rcParams["timezone"] (default: 'UTC')

Ticks timezone.
usetexbool, default: rcParams["text.usetex"] (default: False)

To enable/disable the use of TeX's math mode for rendering the results of the formatter.       set_tzinfo(tz)[source]


classmatplotlib.dates.DateLocator(tz=None)[source]

Bases: matplotlib.ticker.Locator Determines the tick locations when plotting dates. This class is subclassed by other Locators and is not meant to be used on its own.  Parameters

tzdatetime.tzinfo

     datalim_to_dt()[source]

Convert axis data interval to datetime objects.
   hms0d={'byhour': 0, 'byminute': 0, 'bysecond': 0}

   nonsingular(vmin, vmax)[source]

Given the proposed upper and lower extent, adjust the range if it is too close to being singular (i.e. a range of ~0).
   set_tzinfo(tz)[source]

Set time zone info.
   viewlim_to_dt()[source]

Convert the view interval to datetime objects.


datalim_to_dt()[source]

Convert axis data interval to datetime objects.


hms0d={'byhour': 0, 'byminute': 0, 'bysecond': 0}


set_tzinfo(tz)[source]

Set time zone info.


viewlim_to_dt()[source]

Convert the view interval to datetime objects.


matplotlib.dates.datestr2num(d, default=None)[source]

Convert a date string to a datenum using dateutil.parser.parse.  Parameters

dstr or sequence of str

The dates to convert.
defaultdatetime.datetime, optional

The default date to use when fields are missing in d.


classmatplotlib.dates.DayLocator(bymonthday=None, interval=1, tz=None)[source]

Bases: matplotlib.dates.RRuleLocator Make ticks on occurrences of each day of the month. For example, 1, 15, 30. Mark every day in bymonthday; bymonthday can be an int or sequence. Default is to tick every day of the month: bymonthday=range(1, 32).


matplotlib.dates.drange(dstart, dend, delta)[source]

Return a sequence of equally spaced Matplotlib dates. The dates start at dstart and reach up to, but not including dend. They are spaced by delta.  Parameters

dstart, denddatetime

The date limits.
deltadatetime.timedelta

Spacing of the dates.    Returns
 numpy.array

A list floats representing Matplotlib dates.


matplotlib.dates.epoch2num(e)[source]

[Deprecated] Convert UNIX time to days since Matplotlib epoch.  Parameters

elist of floats

Time in seconds since 1970-01-01.    Returns
 numpy.array

Time in days since Matplotlib epoch (see get_epoch()).     Notes  Deprecated since version 3.5.


matplotlib.dates.get_epoch()[source]

Get the epoch used by dates.  Returns

epochstr

String for the epoch (parsable by numpy.datetime64).


classmatplotlib.dates.HourLocator(byhour=None, interval=1, tz=None)[source]

Bases: matplotlib.dates.RRuleLocator Make ticks on occurrences of each hour. Mark every hour in byhour; byhour can be an int or sequence. Default is to tick every hour: byhour=range(24) interval is the interval between each iteration. For example, if interval=2, mark every second occurrence.


classmatplotlib.dates.MicrosecondLocator(interval=1, tz=None)[source]

Bases: matplotlib.dates.DateLocator Make ticks on regular intervals of one or more microsecond(s).  Note By default, Matplotlib uses a floating point representation of time in days since the epoch, so plotting data with microsecond time resolution does not work well for dates that are far (about 70 years) from the epoch (check with get_epoch). If you want sub-microsecond resolution time plots, it is strongly recommended to use floating point seconds, not datetime-like time representation. If you really must use datetime.datetime() or similar and still need microsecond precision, change the time origin via dates.set_epoch to something closer to the dates being plotted. See Date Precision and Epochs.  interval is the interval between each iteration. For example, if interval=2, mark every second microsecond.   set_axis(axis)[source]

   set_data_interval(vmin, vmax)[source]

[Deprecated] Notes  Deprecated since version 3.5:
   set_view_interval(vmin, vmax)[source]

[Deprecated] Notes  Deprecated since version 3.5:
   tick_values(vmin, vmax)[source]

Return the values of the located ticks given vmin and vmax.  Note To get tick locations with the vmin and vmax values defined automatically for the associated axis simply call the Locator instance: >>> print(type(loc))
<type 'Locator'>
>>> print(loc())
[1, 2, 3, 4]


set_data_interval(vmin, vmax)[source]

[Deprecated] Notes  Deprecated since version 3.5:


set_view_interval(vmin, vmax)[source]

[Deprecated] Notes  Deprecated since version 3.5:


tick_values(vmin, vmax)[source]

Return the values of the located ticks given vmin and vmax.  Note To get tick locations with the vmin and vmax values defined automatically for the associated axis simply call the Locator instance: >>> print(type(loc))
<type 'Locator'>
>>> print(loc())
[1, 2, 3, 4]


classmatplotlib.dates.MinuteLocator(byminute=None, interval=1, tz=None)[source]

Bases: matplotlib.dates.RRuleLocator Make ticks on occurrences of each minute. Mark every minute in byminute; byminute can be an int or sequence. Default is to tick every minute: byminute=range(60) interval is the interval between each iteration. For example, if interval=2, mark every second occurrence.


classmatplotlib.dates.MonthLocator(bymonth=None, bymonthday=1, interval=1, tz=None)[source]

Bases: matplotlib.dates.RRuleLocator Make ticks on occurrences of each month, e.g., 1, 3, 12. Mark every month in bymonth; bymonth can be an int or sequence. Default is range(1, 13), i.e. every month. interval is the interval between each iteration. For example, if interval=2, mark every second occurrence.


matplotlib.dates.num2date(x, tz=None)[source]

Convert Matplotlib dates to datetime objects.  Parameters

xfloat or sequence of floats

Number of days (fraction part represents hours, minutes, seconds) since the epoch. See get_epoch for the epoch, which can be changed by rcParams["date.epoch"] (default: '1970-01-01T00:00:00') or set_epoch.
tzstr, default: rcParams["timezone"] (default: 'UTC')

Timezone of x.    Returns

datetime or sequence of datetime

Dates are returned in timezone tz. If x is a sequence, a sequence of datetime objects will be returned.     Notes The addition of one here is a historical artifact. Also, note that the Gregorian calendar is assumed; this is not universal practice. For details, see the module docstring.


matplotlib.dates.num2epoch(d)[source]

[Deprecated] Convert days since Matplotlib epoch to UNIX time.  Parameters

dlist of floats

Time in days since Matplotlib epoch (see get_epoch()).    Returns
 numpy.array

Time in seconds since 1970-01-01.     Notes  Deprecated since version 3.5.


matplotlib.dates.num2timedelta(x)[source]

Convert number of days to a timedelta object. If x is a sequence, a sequence of timedelta objects will be returned.  Parameters

xfloat, sequence of floats

Number of days. The fraction part represents hours, minutes, seconds.    Returns

datetime.timedelta or list[datetime.timedelta]