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More edits to Normalize docstrings.
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lib/matplotlib/colors.py

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@@ -914,29 +914,28 @@ class Normalize:
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A class which, when called, linearly normalizes data into the
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``[0.0, 1.0]`` interval.
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"""
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def __init__(self, vmin=None, vmax=None, clip=False):
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"""
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Parameters
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----------
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vmin : float
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vmax : float
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clip : bool
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vmin, vmax : float or None
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If *vmin* and/or *vmax* is not given, they are initialized from the
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minimum and maximum value, respectively, of the first input
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processed; i.e., ``__call__(A)`` calls ``autoscale_None(A)``.
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clip : bool, default: False
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If ``True`` values falling outside the range ``[vmin, vmax]``,
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are mapped to 0 or 1, whichever is closer, and masked values are
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set to 1. If ``False`` masked values remain masked.
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set to 1. If ``False`` masked values remain masked.
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Clipping silently defeats the purpose of setting the over, under,
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and masked colors in a colormap, so it is likely to lead to
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surprises; therefore the default is ``clip=False``.
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Notes
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-----
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If neither *vmin* or *vmax* are given, they are initialized from the
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minimum and maximum value respectively of the first input
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processed. That is, ``__call__(A)`` calls ``autoscale_None(A)``.
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Returns 0 if::
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vmin==vmax
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Clipping silently defeats the purpose of setting the over, under, and
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masked colors in a colormap, so it is likely to lead to surprises;
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therefore the default is ``clip=False``.
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Returns 0 if ``vmin == vmax``.
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"""
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self.vmin = _sanitize_extrema(vmin)
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self.vmax = _sanitize_extrema(vmax)
@@ -954,7 +953,7 @@ def process_value(value):
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result : masked array
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Masked array with the same shape as *value*.
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is_scalar : bool
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``True`` if *value* is a scalar.
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Whether *value* is a scalar.
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Notes
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-----

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