Misc package¶
Various miscellaneous code required by ConKit
-
deprecate
(version, msg=None)[source]¶ Decorator to deprecate Python classes and functions
Parameters: Examples
Enable
DeprecationWarning
messages to be displayed.>>> import warnings >>> warnings.simplefilter('default')
Decorate a simple Python function without additional message
>>> @deprecate('0.0.0') ... def sum(a, b): ... return a + b >>> sum(1, 2) deprecated.py:34: DeprecationWarning: sum has been deprecated and will be removed in version 0.0.0! warnings.warn(message, DeprecationWarning) 3
Decorate a simple Python function with additional message
>>> @deprecate('0.0.1', msg='Use XXX instead!') ... def sum(a, b): ... return a + b >>> sum(2, 2) deprecated.py:34: DeprecationWarning: sum has been deprecated and will be removed in version 0.0.0! - Use XXX instead! warnings.warn(message, DeprecationWarning) 4
Decorate an entire Python class
>>> @deprecate('0.0.2') ... class Obj(object): ... pass >>> Obj() deprecated.py:34: DeprecationWarning: Obj has been deprecated and will be removed in version 0.0.2! warnings.warn(message, DeprecationWarning) <__main__.Obj object at 0x7f8ee0f1ead0>
Decorate a Python class method
>>> class Obj(object): ... def __init__(self, v): ... self.v = v ... @deprecate('0.0.3') ... def mul(self, other): ... return self.v * other.v >>> Obj(2).mul(Obj(3)) deprecated.py:34: DeprecationWarning: mul has been deprecated and will be removed in version 0.0.3! warnings.warn(message, DeprecationWarning) 6
Decorate a Python class staticmethod
>>> class Obj(object): ... @staticmethod ... @deprecate('0.0.4') ... def sub(a, b): ... return a - b >>> Obj.sub(2, 1) deprecated.py:34: DeprecationWarning: sub has been deprecated and will be removed in version 0.0.4! warnings.warn(message, DeprecationWarning) 1
Decorate a Python class classmethod
>>> class Obj(object): ... CONST = 5 ... @classmethod ... @deprecate('0.0.5') ... def sub(cls, a): ... return a - cls.CONST >>> Obj().sub(5) deprecated.py:34: DeprecationWarning: sub has been deprecated and will be removed in version 0.0.5! warnings.warn(message, DeprecationWarning) 0
-
normalize
(data, vmin=0, vmax=1)[source]¶ Apply a Feature scaling algorithm to normalize the data
This normalization will bring all values into the range [0, 1]. This function allows range restrictions by values
vmin
andvmax
.\[{X}'=\frac{(X-X_{min})(vmax-vmin)}{X_{max}-X_{min}}\]Parameters: Returns: The normalized data
Return type: