@@ -213,7 +213,6 @@ def __str__(self):
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return "{}(base={}, nonpositive={!r})" .format (
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type (self ).__name__ , self .base , "clip" if self ._clip else "mask" )
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- @_api .rename_parameter ("3.8" , "a" , "values" )
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def transform_non_affine (self , values ):
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# Ignore invalid values due to nans being passed to the transform.
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with np .errstate (divide = "ignore" , invalid = "ignore" ):
@@ -250,7 +249,6 @@ def __init__(self, base):
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def __str__ (self ):
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return f"{ type (self ).__name__ } (base={ self .base } )"
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- @_api .rename_parameter ("3.8" , "a" , "values" )
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def transform_non_affine (self , values ):
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return np .power (self .base , values )
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@@ -362,7 +360,6 @@ def __init__(self, base, linthresh, linscale):
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self ._linscale_adj = (linscale / (1.0 - self .base ** - 1 ))
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self ._log_base = np .log (base )
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- @_api .rename_parameter ("3.8" , "a" , "values" )
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def transform_non_affine (self , values ):
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abs_a = np .abs (values )
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with np .errstate (divide = "ignore" , invalid = "ignore" ):
@@ -390,7 +387,6 @@ def __init__(self, base, linthresh, linscale):
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self .linscale = linscale
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self ._linscale_adj = (linscale / (1.0 - self .base ** - 1 ))
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- @_api .rename_parameter ("3.8" , "a" , "values" )
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def transform_non_affine (self , values ):
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abs_a = np .abs (values )
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with np .errstate (divide = "ignore" , invalid = "ignore" ):
@@ -472,7 +468,6 @@ def __init__(self, linear_width):
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"must be strictly positive" )
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self .linear_width = linear_width
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- @_api .rename_parameter ("3.8" , "a" , "values" )
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def transform_non_affine (self , values ):
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return self .linear_width * np .arcsinh (values / self .linear_width )
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@@ -488,7 +483,6 @@ def __init__(self, linear_width):
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super ().__init__ ()
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self .linear_width = linear_width
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- @_api .rename_parameter ("3.8" , "a" , "values" )
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def transform_non_affine (self , values ):
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return self .linear_width * np .sinh (values / self .linear_width )
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@@ -589,7 +583,6 @@ def __init__(self, nonpositive='mask'):
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self ._nonpositive = nonpositive
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self ._clip = {"clip" : True , "mask" : False }[nonpositive ]
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- @_api .rename_parameter ("3.8" , "a" , "values" )
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def transform_non_affine (self , values ):
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"""logit transform (base 10), masked or clipped"""
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with np .errstate (divide = "ignore" , invalid = "ignore" ):
@@ -613,7 +606,6 @@ def __init__(self, nonpositive='mask'):
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super ().__init__ ()
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self ._nonpositive = nonpositive
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- @_api .rename_parameter ("3.8" , "a" , "values" )
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def transform_non_affine (self , values ):
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"""logistic transform (base 10)"""
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return 1.0 / (1 + 10 ** (- values ))
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