doc_content stringlengths 1 386k | doc_id stringlengths 5 188 |
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set_params(nbins=None)[source]
Set parameters within this locator. | matplotlib.ticker_api#matplotlib.ticker.FixedLocator.set_params |
tick_values(vmin, vmax)[source]
Return the locations of the ticks. Note Because the values are fixed, vmin and vmax are not used in this method. | matplotlib.ticker_api#matplotlib.ticker.FixedLocator.tick_values |
classmatplotlib.ticker.FormatStrFormatter(fmt)[source]
Bases: matplotlib.ticker.Formatter Use an old-style ('%' operator) format string to format the tick. The format string should have a single variable format (%) in it. It will be applied to the value (not the position) of the tick. Negative numeric values will use... | matplotlib.ticker_api#matplotlib.ticker.FormatStrFormatter |
classmatplotlib.ticker.Formatter[source]
Bases: matplotlib.ticker.TickHelper Create a string based on a tick value and location. staticfix_minus(s)[source]
Some classes may want to replace a hyphen for minus with the proper unicode symbol (U+2212) for typographical correctness. This is a helper method to perform ... | matplotlib.ticker_api#matplotlib.ticker.Formatter |
staticfix_minus(s)[source]
Some classes may want to replace a hyphen for minus with the proper unicode symbol (U+2212) for typographical correctness. This is a helper method to perform such a replacement when it is enabled via rcParams["axes.unicode_minus"] (default: True). | matplotlib.ticker_api#matplotlib.ticker.Formatter.fix_minus |
format_data(value)[source]
Return the full string representation of the value with the position unspecified. | matplotlib.ticker_api#matplotlib.ticker.Formatter.format_data |
format_data_short(value)[source]
Return a short string version of the tick value. Defaults to the position-independent long value. | matplotlib.ticker_api#matplotlib.ticker.Formatter.format_data_short |
format_ticks(values)[source]
Return the tick labels for all the ticks at once. | matplotlib.ticker_api#matplotlib.ticker.Formatter.format_ticks |
get_offset()[source] | matplotlib.ticker_api#matplotlib.ticker.Formatter.get_offset |
locs=[] | matplotlib.ticker_api#matplotlib.ticker.Formatter.locs |
set_locs(locs)[source]
Set the locations of the ticks. This method is called before computing the tick labels because some formatters need to know all tick locations to do so. | matplotlib.ticker_api#matplotlib.ticker.Formatter.set_locs |
classmatplotlib.ticker.FuncFormatter(func)[source]
Bases: matplotlib.ticker.Formatter Use a user-defined function for formatting. The function should take in two inputs (a tick value x and a position pos), and return a string containing the corresponding tick label. get_offset()[source]
set_offset_string(ofs)[s... | matplotlib.ticker_api#matplotlib.ticker.FuncFormatter |
get_offset()[source] | matplotlib.ticker_api#matplotlib.ticker.FuncFormatter.get_offset |
set_offset_string(ofs)[source] | matplotlib.ticker_api#matplotlib.ticker.FuncFormatter.set_offset_string |
classmatplotlib.ticker.IndexLocator(base, offset)[source]
Bases: matplotlib.ticker.Locator Place a tick on every multiple of some base number of points plotted, e.g., on every 5th point. It is assumed that you are doing index plotting; i.e., the axis is 0, len(data). This is mainly useful for x ticks. Place ticks eve... | matplotlib.ticker_api#matplotlib.ticker.IndexLocator |
set_params(base=None, offset=None)[source]
Set parameters within this locator | matplotlib.ticker_api#matplotlib.ticker.IndexLocator.set_params |
tick_values(vmin, vmax)[source]
Return the values of the located ticks given vmin and vmax. Note To get tick locations with the vmin and vmax values defined automatically for the associated axis simply call the Locator instance: >>> print(type(loc))
<type 'Locator'>
>>> print(loc())
[1, 2, 3, 4] | matplotlib.ticker_api#matplotlib.ticker.IndexLocator.tick_values |
classmatplotlib.ticker.LinearLocator(numticks=None, presets=None)[source]
Bases: matplotlib.ticker.Locator Determine the tick locations The first time this function is called it will try to set the number of ticks to make a nice tick partitioning. Thereafter the number of ticks will be fixed so that interactive navig... | matplotlib.ticker_api#matplotlib.ticker.LinearLocator |
set_params(numticks=None, presets=None)[source]
Set parameters within this locator. | matplotlib.ticker_api#matplotlib.ticker.LinearLocator.set_params |
tick_values(vmin, vmax)[source]
Return the values of the located ticks given vmin and vmax. Note To get tick locations with the vmin and vmax values defined automatically for the associated axis simply call the Locator instance: >>> print(type(loc))
<type 'Locator'>
>>> print(loc())
[1, 2, 3, 4] | matplotlib.ticker_api#matplotlib.ticker.LinearLocator.tick_values |
view_limits(vmin, vmax)[source]
Try to choose the view limits intelligently. | matplotlib.ticker_api#matplotlib.ticker.LinearLocator.view_limits |
classmatplotlib.ticker.Locator[source]
Bases: matplotlib.ticker.TickHelper Determine the tick locations; Note that the same locator should not be used across multiple Axis because the locator stores references to the Axis data and view limits. MAXTICKS=1000
nonsingular(v0, v1)[source]
Adjust a range as needed... | matplotlib.ticker_api#matplotlib.ticker.Locator |
MAXTICKS=1000 | matplotlib.ticker_api#matplotlib.ticker.Locator.MAXTICKS |
nonsingular(v0, v1)[source]
Adjust a range as needed to avoid singularities. This method gets called during autoscaling, with (v0, v1) set to the data limits on the axes if the axes contains any data, or (-inf, +inf) if not. If v0 == v1 (possibly up to some floating point slop), this method returns an expanded inter... | matplotlib.ticker_api#matplotlib.ticker.Locator.nonsingular |
raise_if_exceeds(locs)[source]
Log at WARNING level if locs is longer than Locator.MAXTICKS. This is intended to be called immediately before returning locs from __call__ to inform users in case their Locator returns a huge number of ticks, causing Matplotlib to run out of memory. The "strange" name of this method da... | matplotlib.ticker_api#matplotlib.ticker.Locator.raise_if_exceeds |
set_params(**kwargs)[source]
Do nothing, and raise a warning. Any locator class not supporting the set_params() function will call this. | matplotlib.ticker_api#matplotlib.ticker.Locator.set_params |
tick_values(vmin, vmax)[source]
Return the values of the located ticks given vmin and vmax. Note To get tick locations with the vmin and vmax values defined automatically for the associated axis simply call the Locator instance: >>> print(type(loc))
<type 'Locator'>
>>> print(loc())
[1, 2, 3, 4] | matplotlib.ticker_api#matplotlib.ticker.Locator.tick_values |
view_limits(vmin, vmax)[source]
Select a scale for the range from vmin to vmax. Subclasses should override this method to change locator behaviour. | matplotlib.ticker_api#matplotlib.ticker.Locator.view_limits |
classmatplotlib.ticker.LogFormatter(base=10.0, labelOnlyBase=False, minor_thresholds=None, linthresh=None)[source]
Bases: matplotlib.ticker.Formatter Base class for formatting ticks on a log or symlog scale. It may be instantiated directly, or subclassed. Parameters
basefloat, default: 10.
Base of the logarithm... | matplotlib.ticker_api#matplotlib.ticker.LogFormatter |
base(base)[source]
Change the base for labeling. Warning Should always match the base used for LogLocator | matplotlib.ticker_api#matplotlib.ticker.LogFormatter.base |
format_data(value)[source]
Return the full string representation of the value with the position unspecified. | matplotlib.ticker_api#matplotlib.ticker.LogFormatter.format_data |
format_data_short(value)[source]
Return a short string version of the tick value. Defaults to the position-independent long value. | matplotlib.ticker_api#matplotlib.ticker.LogFormatter.format_data_short |
label_minor(labelOnlyBase)[source]
Switch minor tick labeling on or off. Parameters
labelOnlyBasebool
If True, label ticks only at integer powers of base. | matplotlib.ticker_api#matplotlib.ticker.LogFormatter.label_minor |
set_locs(locs=None)[source]
Use axis view limits to control which ticks are labeled. The locs parameter is ignored in the present algorithm. | matplotlib.ticker_api#matplotlib.ticker.LogFormatter.set_locs |
classmatplotlib.ticker.LogFormatterExponent(base=10.0, labelOnlyBase=False, minor_thresholds=None, linthresh=None)[source]
Bases: matplotlib.ticker.LogFormatter Format values for log axis using exponent = log_base(value). | matplotlib.ticker_api#matplotlib.ticker.LogFormatterExponent |
classmatplotlib.ticker.LogFormatterMathtext(base=10.0, labelOnlyBase=False, minor_thresholds=None, linthresh=None)[source]
Bases: matplotlib.ticker.LogFormatter Format values for log axis using exponent = log_base(value). | matplotlib.ticker_api#matplotlib.ticker.LogFormatterMathtext |
classmatplotlib.ticker.LogFormatterSciNotation(base=10.0, labelOnlyBase=False, minor_thresholds=None, linthresh=None)[source]
Bases: matplotlib.ticker.LogFormatterMathtext Format values following scientific notation in a logarithmic axis. | matplotlib.ticker_api#matplotlib.ticker.LogFormatterSciNotation |
classmatplotlib.ticker.LogitFormatter(*, use_overline=False, one_half='\x0crac{1}{2}', minor=False, minor_threshold=25, minor_number=6)[source]
Bases: matplotlib.ticker.Formatter Probability formatter (using Math text). Parameters
use_overlinebool, default: False
If x > 1/2, with x = 1-v, indicate if x should b... | matplotlib.ticker_api#matplotlib.ticker.LogitFormatter |
format_data_short(value)[source]
Return a short string version of the tick value. Defaults to the position-independent long value. | matplotlib.ticker_api#matplotlib.ticker.LogitFormatter.format_data_short |
set_locs(locs)[source]
Set the locations of the ticks. This method is called before computing the tick labels because some formatters need to know all tick locations to do so. | matplotlib.ticker_api#matplotlib.ticker.LogitFormatter.set_locs |
set_minor_number(minor_number)[source]
Set the number of minor ticks to label when some minor ticks are labelled. Parameters
minor_numberint
Number of ticks which are labelled when the number of ticks is below the threshold. | matplotlib.ticker_api#matplotlib.ticker.LogitFormatter.set_minor_number |
set_minor_threshold(minor_threshold)[source]
Set the threshold for labelling minors ticks. Parameters
minor_thresholdint
Maximum number of locations for labelling some minor ticks. This parameter have no effect if minor is False. | matplotlib.ticker_api#matplotlib.ticker.LogitFormatter.set_minor_threshold |
set_one_half(one_half)[source]
Set the way one half is displayed. one_halfstr, default: r"frac{1}{2}"
The string used to represent 1/2. | matplotlib.ticker_api#matplotlib.ticker.LogitFormatter.set_one_half |
use_overline(use_overline)[source]
Switch display mode with overline for labelling p>1/2. Parameters
use_overlinebool, default: False
If x > 1/2, with x = 1-v, indicate if x should be displayed as $overline{v}$. The default is to display $1-v$. | matplotlib.ticker_api#matplotlib.ticker.LogitFormatter.use_overline |
classmatplotlib.ticker.LogitLocator(minor=False, *, nbins='auto')[source]
Bases: matplotlib.ticker.MaxNLocator Determine the tick locations for logit axes Place ticks on the logit locations Parameters
nbinsint or 'auto', optional
Number of ticks. Only used if minor is False.
minorbool, default: False
Indica... | matplotlib.ticker_api#matplotlib.ticker.LogitLocator |
nonsingular(vmin, vmax)[source]
Adjust a range as needed to avoid singularities. This method gets called during autoscaling, with (v0, v1) set to the data limits on the axes if the axes contains any data, or (-inf, +inf) if not. If v0 == v1 (possibly up to some floating point slop), this method returns an expanded i... | matplotlib.ticker_api#matplotlib.ticker.LogitLocator.nonsingular |
set_params(minor=None, **kwargs)[source]
Set parameters within this locator. | matplotlib.ticker_api#matplotlib.ticker.LogitLocator.set_params |
tick_values(vmin, vmax)[source]
Return the values of the located ticks given vmin and vmax. Note To get tick locations with the vmin and vmax values defined automatically for the associated axis simply call the Locator instance: >>> print(type(loc))
<type 'Locator'>
>>> print(loc())
[1, 2, 3, 4] | matplotlib.ticker_api#matplotlib.ticker.LogitLocator.tick_values |
classmatplotlib.ticker.LogLocator(base=10.0, subs=(1.0,), numdecs=4, numticks=None)[source]
Bases: matplotlib.ticker.Locator Determine the tick locations for log axes Place ticks on the locations : subs[j] * base**i Parameters
basefloat, default: 10.0
The base of the log used, so ticks are placed at base**n.
... | matplotlib.ticker_api#matplotlib.ticker.LogLocator |
base(base)[source]
Set the log base (major tick every base**i, i integer). | matplotlib.ticker_api#matplotlib.ticker.LogLocator.base |
nonsingular(vmin, vmax)[source]
Adjust a range as needed to avoid singularities. This method gets called during autoscaling, with (v0, v1) set to the data limits on the axes if the axes contains any data, or (-inf, +inf) if not. If v0 == v1 (possibly up to some floating point slop), this method returns an expanded i... | matplotlib.ticker_api#matplotlib.ticker.LogLocator.nonsingular |
set_params(base=None, subs=None, numdecs=None, numticks=None)[source]
Set parameters within this locator. | matplotlib.ticker_api#matplotlib.ticker.LogLocator.set_params |
subs(subs)[source]
Set the minor ticks for the log scaling every base**i*subs[j]. | matplotlib.ticker_api#matplotlib.ticker.LogLocator.subs |
tick_values(vmin, vmax)[source]
Return the values of the located ticks given vmin and vmax. Note To get tick locations with the vmin and vmax values defined automatically for the associated axis simply call the Locator instance: >>> print(type(loc))
<type 'Locator'>
>>> print(loc())
[1, 2, 3, 4] | matplotlib.ticker_api#matplotlib.ticker.LogLocator.tick_values |
view_limits(vmin, vmax)[source]
Try to choose the view limits intelligently. | matplotlib.ticker_api#matplotlib.ticker.LogLocator.view_limits |
classmatplotlib.ticker.MaxNLocator(nbins=None, **kwargs)[source]
Bases: matplotlib.ticker.Locator Find nice tick locations with no more than N being within the view limits. Locations beyond the limits are added to support autoscaling. Parameters
nbinsint or 'auto', default: 10
Maximum number of intervals; one l... | matplotlib.ticker_api#matplotlib.ticker.MaxNLocator |
default_params={'integer': False, 'min_n_ticks': 2, 'nbins': 10, 'prune': None, 'steps': None, 'symmetric': False} | matplotlib.ticker_api#matplotlib.ticker.MaxNLocator.default_params |
set_params(**kwargs)[source]
Set parameters for this locator. Parameters
nbinsint or 'auto', optional
see MaxNLocator
stepsarray-like, optional
see MaxNLocator
integerbool, optional
see MaxNLocator
symmetricbool, optional
see MaxNLocator
prune{'lower', 'upper', 'both', None}, optional
see MaxNLo... | matplotlib.ticker_api#matplotlib.ticker.MaxNLocator.set_params |
tick_values(vmin, vmax)[source]
Return the values of the located ticks given vmin and vmax. Note To get tick locations with the vmin and vmax values defined automatically for the associated axis simply call the Locator instance: >>> print(type(loc))
<type 'Locator'>
>>> print(loc())
[1, 2, 3, 4] | matplotlib.ticker_api#matplotlib.ticker.MaxNLocator.tick_values |
view_limits(dmin, dmax)[source]
Select a scale for the range from vmin to vmax. Subclasses should override this method to change locator behaviour. | matplotlib.ticker_api#matplotlib.ticker.MaxNLocator.view_limits |
classmatplotlib.ticker.MultipleLocator(base=1.0)[source]
Bases: matplotlib.ticker.Locator Set a tick on each integer multiple of a base within the view interval. set_params(base)[source]
Set parameters within this locator.
tick_values(vmin, vmax)[source]
Return the values of the located ticks given vmin and... | matplotlib.ticker_api#matplotlib.ticker.MultipleLocator |
set_params(base)[source]
Set parameters within this locator. | matplotlib.ticker_api#matplotlib.ticker.MultipleLocator.set_params |
tick_values(vmin, vmax)[source]
Return the values of the located ticks given vmin and vmax. Note To get tick locations with the vmin and vmax values defined automatically for the associated axis simply call the Locator instance: >>> print(type(loc))
<type 'Locator'>
>>> print(loc())
[1, 2, 3, 4] | matplotlib.ticker_api#matplotlib.ticker.MultipleLocator.tick_values |
view_limits(dmin, dmax)[source]
Set the view limits to the nearest multiples of base that contain the data. | matplotlib.ticker_api#matplotlib.ticker.MultipleLocator.view_limits |
classmatplotlib.ticker.NullFormatter[source]
Bases: matplotlib.ticker.Formatter Always return the empty string. | matplotlib.ticker_api#matplotlib.ticker.NullFormatter |
classmatplotlib.ticker.NullLocator[source]
Bases: matplotlib.ticker.Locator No ticks tick_values(vmin, vmax)[source]
Return the locations of the ticks. Note Because the values are Null, vmin and vmax are not used in this method. | matplotlib.ticker_api#matplotlib.ticker.NullLocator |
tick_values(vmin, vmax)[source]
Return the locations of the ticks. Note Because the values are Null, vmin and vmax are not used in this method. | matplotlib.ticker_api#matplotlib.ticker.NullLocator.tick_values |
classmatplotlib.ticker.PercentFormatter(xmax=100, decimals=None, symbol='%', is_latex=False)[source]
Bases: matplotlib.ticker.Formatter Format numbers as a percentage. Parameters
xmaxfloat
Determines how the number is converted into a percentage. xmax is the data value that corresponds to 100%. Percentages are ... | matplotlib.ticker_api#matplotlib.ticker.PercentFormatter |
convert_to_pct(x)[source] | matplotlib.ticker_api#matplotlib.ticker.PercentFormatter.convert_to_pct |
format_pct(x, display_range)[source]
Format the number as a percentage number with the correct number of decimals and adds the percent symbol, if any. If self.decimals is None, the number of digits after the decimal point is set based on the display_range of the axis as follows:
display_range decimals sample
>50 ... | matplotlib.ticker_api#matplotlib.ticker.PercentFormatter.format_pct |
classmatplotlib.ticker.ScalarFormatter(useOffset=None, useMathText=None, useLocale=None)[source]
Bases: matplotlib.ticker.Formatter Format tick values as a number. Parameters
useOffsetbool or float, default: rcParams["axes.formatter.useoffset"] (default: True)
Whether to use offset notation. See set_useOffset. ... | matplotlib.ticker_api#matplotlib.ticker.ScalarFormatter |
format_data(value)[source]
Return the full string representation of the value with the position unspecified. | matplotlib.ticker_api#matplotlib.ticker.ScalarFormatter.format_data |
format_data_short(value)[source]
Return a short string version of the tick value. Defaults to the position-independent long value. | matplotlib.ticker_api#matplotlib.ticker.ScalarFormatter.format_data_short |
get_offset()[source]
Return scientific notation, plus offset. | matplotlib.ticker_api#matplotlib.ticker.ScalarFormatter.get_offset |
get_useLocale()[source]
Return whether locale settings are used for formatting. See also ScalarFormatter.set_useLocale | matplotlib.ticker_api#matplotlib.ticker.ScalarFormatter.get_useLocale |
get_useMathText()[source]
Return whether to use fancy math formatting. See also ScalarFormatter.set_useMathText | matplotlib.ticker_api#matplotlib.ticker.ScalarFormatter.get_useMathText |
get_useOffset()[source]
Return whether automatic mode for offset notation is active. This returns True if set_useOffset(True); it returns False if an explicit offset was set, e.g. set_useOffset(1000). See also ScalarFormatter.set_useOffset | matplotlib.ticker_api#matplotlib.ticker.ScalarFormatter.get_useOffset |
set_locs(locs)[source]
Set the locations of the ticks. This method is called before computing the tick labels because some formatters need to know all tick locations to do so. | matplotlib.ticker_api#matplotlib.ticker.ScalarFormatter.set_locs |
set_powerlimits(lims)[source]
Set size thresholds for scientific notation. Parameters
lims(int, int)
A tuple (min_exp, max_exp) containing the powers of 10 that determine the switchover threshold. For a number representable as \(a \times 10^\mathrm{exp}\) with \(1 <= |a| < 10\), scientific notation will be used... | matplotlib.ticker_api#matplotlib.ticker.ScalarFormatter.set_powerlimits |
set_scientific(b)[source]
Turn scientific notation on or off. See also ScalarFormatter.set_powerlimits | matplotlib.ticker_api#matplotlib.ticker.ScalarFormatter.set_scientific |
set_useLocale(val)[source]
Set whether to use locale settings for decimal sign and positive sign. Parameters
valbool or None
None resets to rcParams["axes.formatter.use_locale"] (default: False). | matplotlib.ticker_api#matplotlib.ticker.ScalarFormatter.set_useLocale |
set_useMathText(val)[source]
Set whether to use fancy math formatting. If active, scientific notation is formatted as \(1.2 \times 10^3\). Parameters
valbool or None
None resets to rcParams["axes.formatter.use_mathtext"] (default: False). | matplotlib.ticker_api#matplotlib.ticker.ScalarFormatter.set_useMathText |
set_useOffset(val)[source]
Set whether to use offset notation. When formatting a set numbers whose value is large compared to their range, the formatter can separate an additive constant. This can shorten the formatted numbers so that they are less likely to overlap when drawn on an axis. Parameters
valbool or fl... | matplotlib.ticker_api#matplotlib.ticker.ScalarFormatter.set_useOffset |
classmatplotlib.ticker.StrMethodFormatter(fmt)[source]
Bases: matplotlib.ticker.Formatter Use a new-style format string (as used by str.format) to format the tick. The field used for the tick value must be labeled x and the field used for the tick position must be labeled pos. | matplotlib.ticker_api#matplotlib.ticker.StrMethodFormatter |
classmatplotlib.ticker.SymmetricalLogLocator(transform=None, subs=None, linthresh=None, base=None)[source]
Bases: matplotlib.ticker.Locator Determine the tick locations for symmetric log axes. Parameters
transformSymmetricalLogTransform, optional
If set, defines the base and linthresh of the symlog transform. ... | matplotlib.ticker_api#matplotlib.ticker.SymmetricalLogLocator |
set_params(subs=None, numticks=None)[source]
Set parameters within this locator. | matplotlib.ticker_api#matplotlib.ticker.SymmetricalLogLocator.set_params |
tick_values(vmin, vmax)[source]
Return the values of the located ticks given vmin and vmax. Note To get tick locations with the vmin and vmax values defined automatically for the associated axis simply call the Locator instance: >>> print(type(loc))
<type 'Locator'>
>>> print(loc())
[1, 2, 3, 4] | matplotlib.ticker_api#matplotlib.ticker.SymmetricalLogLocator.tick_values |
view_limits(vmin, vmax)[source]
Try to choose the view limits intelligently. | matplotlib.ticker_api#matplotlib.ticker.SymmetricalLogLocator.view_limits |
classmatplotlib.ticker.TickHelper[source]
Bases: object axis=None
create_dummy_axis(**kwargs)[source]
set_axis(axis)[source]
set_bounds(vmin, vmax)[source]
[Deprecated] Notes Deprecated since version 3.5:
set_data_interval(vmin, vmax)[source]
[Deprecated] Notes Deprecated since version 3.5: ... | matplotlib.ticker_api#matplotlib.ticker.TickHelper |
axis=None | matplotlib.ticker_api#matplotlib.ticker.TickHelper.axis |
create_dummy_axis(**kwargs)[source] | matplotlib.ticker_api#matplotlib.ticker.TickHelper.create_dummy_axis |
set_axis(axis)[source] | matplotlib.ticker_api#matplotlib.ticker.TickHelper.set_axis |
set_bounds(vmin, vmax)[source]
[Deprecated] Notes Deprecated since version 3.5: | matplotlib.ticker_api#matplotlib.ticker.TickHelper.set_bounds |
set_data_interval(vmin, vmax)[source]
[Deprecated] Notes Deprecated since version 3.5: | matplotlib.ticker_api#matplotlib.ticker.TickHelper.set_data_interval |
set_view_interval(vmin, vmax)[source]
[Deprecated] Notes Deprecated since version 3.5: | matplotlib.ticker_api#matplotlib.ticker.TickHelper.set_view_interval |
matplotlib.tight_bbox Helper module for the bbox_inches parameter in Figure.savefig. matplotlib.tight_bbox.adjust_bbox(fig, bbox_inches, fixed_dpi=None)[source]
Temporarily adjust the figure so that only the specified area (bbox_inches) is saved. It modifies fig.bbox, fig.bbox_inches, fig.transFigure._boxout, and f... | matplotlib.tight_bbox_api |
matplotlib.tight_bbox.adjust_bbox(fig, bbox_inches, fixed_dpi=None)[source]
Temporarily adjust the figure so that only the specified area (bbox_inches) is saved. It modifies fig.bbox, fig.bbox_inches, fig.transFigure._boxout, and fig.patch. While the figure size changes, the scale of the original figure is conserved.... | matplotlib.tight_bbox_api#matplotlib.tight_bbox.adjust_bbox |
matplotlib.tight_bbox.process_figure_for_rasterizing(fig, bbox_inches_restore, fixed_dpi=None)[source]
A function that needs to be called when figure dpi changes during the drawing (e.g., rasterizing). It recovers the bbox and re-adjust it with the new dpi. | matplotlib.tight_bbox_api#matplotlib.tight_bbox.process_figure_for_rasterizing |
matplotlib.tight_layout Routines to adjust subplot params so that subplots are nicely fit in the figure. In doing so, only axis labels, tick labels, axes titles and offsetboxes that are anchored to axes are currently considered. Internally, this module assumes that the margins (left margin, etc.) which are differences ... | matplotlib.tight_layout_api |
matplotlib.tight_layout.auto_adjust_subplotpars(fig, renderer, nrows_ncols, num1num2_list, subplot_list, ax_bbox_list=None, pad=1.08, h_pad=None, w_pad=None, rect=None)[source]
[Deprecated] Return a dict of subplot parameters to adjust spacing between subplots or None if resulting axes would have zero height or width... | matplotlib.tight_layout_api#matplotlib.tight_layout.auto_adjust_subplotpars |
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