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DOC: Update docstring to numpy format for last few functions in transforms (#9309)
* DOC: Update docstring to numpy format for last few functions * DOC: fix syntax for arguments, add class links, improve wording. * DOC: Update link to class in local file
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lib/matplotlib/transforms.py

Lines changed: 68 additions & 26 deletions
Original file line numberDiff line numberDiff line change
@@ -2866,31 +2866,33 @@ def _revalidate(self):
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def nonsingular(vmin, vmax, expander=0.001, tiny=1e-15, increasing=True):
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'''
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"""
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Modify the endpoints of a range as needed to avoid singularities.
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*vmin*, *vmax*
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the initial endpoints.
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*tiny*
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threshold for the ratio of the interval to the maximum absolute
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Parameters
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----------
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vmin, vmax : float
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The initial endpoints.
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expander : float, optional, default: 0.001
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Fractional amount by which *vmin* and *vmax* are expanded if
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the original interval is too small, based on *tiny*.
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tiny : float, optional, default: 1e-15
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Threshold for the ratio of the interval to the maximum absolute
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value of its endpoints. If the interval is smaller than
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this, it will be expanded. This value should be around
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1e-15 or larger; otherwise the interval will be approaching
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the double precision resolution limit.
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increasing : bool, optional, default: True
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If True, swap *vmin*, *vmax* if *vmin* > *vmax*.
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Returns
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-------
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vmin, vmax : float
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Endpoints, expanded and/or swapped if necessary.
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If either input is inf or NaN, or if both inputs are 0 or very
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close to zero, it returns -*expander*, *expander*.
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"""
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*expander*
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fractional amount by which *vmin* and *vmax* are expanded if
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the original interval is too small, based on *tiny*.
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*increasing*: [True | False]
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If True (default), swap *vmin*, *vmax* if *vmin* > *vmax*
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Returns *vmin*, *vmax*, expanded and/or swapped if necessary.
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If either input is inf or NaN, or if both inputs are 0 or very
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close to zero, it returns -*expander*, *expander*.
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'''
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if (not np.isfinite(vmin)) or (not np.isfinite(vmax)):
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return -expander, expander
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@@ -2918,25 +2920,65 @@ def nonsingular(vmin, vmax, expander=0.001, tiny=1e-15, increasing=True):
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def interval_contains(interval, val):
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"""
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Check, inclusively, whether an interval includes a given value.
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Parameters
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----------
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interval : sequence of scalar
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A 2-length sequence, endpoints that define the interval.
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val : scalar
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Value to check is within interval.
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Returns
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-------
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bool
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Returns true if given val is within the interval.
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"""
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a, b = interval
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return a <= val <= b or a >= val >= b
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def interval_contains_open(interval, val):
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"""
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Check, excluding endpoints, whether an interval includes a given value.
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Parameters
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----------
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interval : sequence of scalar
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A 2-length sequence, endpoints that define the interval.
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val : scalar
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Value to check is within interval.
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Returns
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-------
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bool
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Returns true if given val is within the interval.
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"""
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a, b = interval
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return a < val < b or a > val > b
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def offset_copy(trans, fig=None, x=0.0, y=0.0, units='inches'):
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'''
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"""
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Return a new transform with an added offset.
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args:
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trans is any transform
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kwargs:
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fig is the current figure; it can be None if units are 'dots'
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x, y give the offset
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units is 'inches', 'points' or 'dots'
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'''
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Parameters
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----------
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trans : :class:`Transform` instance
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Any transform, to which offset will be applied.
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fig : :class:`~matplotlib.figure.Figure`, optional, default: None
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Current figure. It can be None if *units* are 'dots'.
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x, y : float, optional, default: 0.0
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Specifies the offset to apply.
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units : {'inches', 'points', 'dots'}, optional
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Units of the offset.
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Returns
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-------
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trans : :class:`Transform` instance
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Transform with applied offset.
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"""
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if units == 'dots':
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return trans + Affine2D().translate(x, y)
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if fig is None:

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