![]() ![]() If the length of ‘funclist’ is one more than the length of ‘condlist’, then that will be the default value when the condition is False.įunclist: It is a list of callables. The function will consider only those values from ‘funclist’ for which the corresponding value in ‘condlist’ is True. The ‘condlist’ size should be the same as the size of the parameter ‘funclist’. The syntax of the piecewise function in the numpy library is: numpy.piecewise(x, condlist, funclist, *args, **kw) Parameters :Ĭondlist: It is a list of boolean arrays. #Piecewise linear function codeInstead of defining a complete function, we can reduce the entire function code to a single line using NumPy’s piecewise function. If we were to define the piecewise function for the above example using a user defined function, then the python code used would be: ![]() If input value is 5, then the function value would be ( 10 – 5 ), which is 5.įor input value 11, the function value would be ( 2*(11) + 3 ), which is 25. If the input value is -10, then the function value would be (10)^2, which is 100. So, for example, if the value of x lies between 0 and 10 where 10 is exclusive, then the sub-function ( 10 – x ) would be applied to it.Īnd if the value of x would be greater than or equal to 10, then the sub-function ( 2x + 3 ) would be applied to it. If x is negative, then the sub-function x^2 would be applied to it. It has been defined over three intervals – ![]() Here, we have defined a piecewise function ‘f(x)’ in the above image. Let us understand with the help of an example. Depending on the interval in which the input value lies, a sub-function is defined for it. It is a function which has different sub functions.įor each interval, a sub-function is defined. Piecewise functions are those functions in mathematics which behave differently with different input values. Using numpy piecewise for multi dimensional array. ![]()
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