How to transform a np.array into a function?

Question

I have the following np.array which describes a rectangular wave. I would like to transform it into a callable function with a continuous argument. The np.array is:

import matplotlib.pyplot as plt
import numpy as np
from numpy.random import seed
from numpy.random import rand


def piecewise_control( off_times,amp_inj, period_inj ):

   def select(T):
       
       return lambda t: (-T/2 <= t) & (t < T/2)

   def pulse_train(t, at, shape):
       
       return np.sum(shape(t - at[:,np.newaxis]), axis=0)



   for i in range(1,len(off_times)):

     off_times[i] += off_times[i-1]  + period_inj

 
  
   return  amp_inj*pulse_train(t,off_times,shape=select(period_inj))               


t=np.linspace(0,100,10000)
off_times = 10*rand(10)
period_inj = 1
amp_inj = 1 

control = piecewise_control(  off_times,amp_inj, period_inj )

plt.plot(t,control)
plt.show()

This answer inspired me.

The plot is the following:

The question is: can we transform the array control into a function with a continuous argument?

Of course if we did:

def ccontrol(t, control):
      return control[t]

unfortunately we would get a function which only depends on integers.

@Tarik sorry I removed that word because it was misleading. I want something callable just as a function like sint(t). — Siderius
– Siderius, Commented Apr 30, 2021 at 10:09
Which array do you want to transform into a function? Can you provide the function signature (arguments) and the expected return? — Tarik
– Tarik, Commented Apr 30, 2021 at 21:06
@Tarik the array is control which is defined via the function piecewise_control. I would like to have this array just as a callable function defined for each argument. I thought that an interpolation technique or a dense output would have been a key point. — Siderius
– Siderius, Commented May 2, 2021 at 13:47

ForceBru · Accepted Answer · 2021-05-02 13:52:48Z

3

You can subclass numpy.ndarray and implement the __call__ method:

import numpy as np

class MyArray(np.ndarray):
    def __call__(self, idx):
        return self[idx]

control = np.random.rand(100)
control_view = control.view(MyArray)

print(control_view(5), control[5])

For interpolation you can use scipy.interpolate. In fact, interpolation routines can return functions that you can call with any input, not necessarily integers.

answered May 2, 2021 at 13:52

ForceBru

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3 Comments

Siderius Over a year ago

Your solution gives the same output of my ccontrol function.

ForceBru Over a year ago

@Siderius, right, but it's a callable array, as opposed to a separate function. Now that you edited the question saying you need to call this function with floating-point numbers, scipy.interpolate does exactly that.

אלימלך שרייבר Over a year ago

wrapping the index with int(): return self[int(idx)] would do the trick here. (zero-order interpolation)

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