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"""
RC.py

Implements a Reservoir Computer (RC), also known as an Echo State Network (ESN),
for modeling and predicting nonlinear dynamical systems.

Key features:
- Fixed, sparse reservoir with random weights
- Only the output weights are trained via ridge regression
- Suitable for chaotic systems like Lorenz, Rössler, Mackey-Glass

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# sample names
name_01 = "Ria Arora"
name_02 = "John Mathew Appleseed"
name_03 = "Kumar Anurag"

# for getting indices of name-initials
def get_initals_index(name):
    initials_index_list = [0]
    for i,v in enumerate(name):
        if v == ' ':

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## Bitwise NOT(~) in Python

a = 12
print ("Bitwise NOT on 12 = ",~a)

'''
[1] Bitwise NOT on Positive Numbers (in Python):

a = 12

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from time import sleep
import threading 
import time

class RepeatedTimer(object):
  def __init__(self, interval, function, *args, **kwargs):
    self._timer = None
    self.interval = interval
    self.function = function
    self.args = args

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def int_to_en(num):
    d = { 0 : 'zero', 1 : 'one', 2 : 'two', 3 : 'three', 4 : 'four', 5 : 'five',
          6 : 'six', 7 : 'seven', 8 : 'eight', 9 : 'nine', 10 : 'ten',
          11 : 'eleven', 12 : 'twelve', 13 : 'thirteen', 14 : 'fourteen',
          15 : 'fifteen', 16 : 'sixteen', 17 : 'seventeen', 18 : 'eighteen',
          19 : 'nineteen', 20 : 'twenty',
          30 : 'thirty', 40 : 'forty', 50 : 'fifty', 60 : 'sixty',
          70 : 'seventy', 80 : 'eighty', 90 : 'ninety' }
    k = 1000
    m = k * 1000

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Enter any number: 156
Prime Factors of a:  [2, 2, 3, 13]

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number = int(input("Enter the no that you want to search in list: "))

l = [1,2,3,1,5,44,1,1,-10,1,1]

number_index = -1


print("All occurences (index position) of a number in list:")
for i in range(l.count(number)):
    if i == 0:

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from scipy.stats import chi2_contingency
from scipy.stats import chi2

def chi_test():
    '''
    Output
    1. stat: Float
    2. dof : Integer
    3. p_val: Float
    4. res: String

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from scipy import stats
import math

def poisson():
    '''
    output: ans : Float
    '''
    #Write your code here
    #Assign the probability value to the variable ans
    #Round off to 2 decimal places

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from scipy import stats

def binomial():
    '''
    output: ans : Float
    '''
    #Write your code here
    #Assign the probability value to the variable ans
    #Round off to 2 decimal places
    n = 4