random variable from probabilites and outcomes in python using numpy

I am new to python and coding in general. i want use a numpy function to randomly select a value from a vector of lottery outcomes depending on another vector that captures the probability weights, that were generated from a probability weighting function.

This is the code I used so far that works without problem

 import numpy as np
 # calculate probability weighting function
 p = np.arange(0.01, 1, 0.001, dtype = float)  
 p = p.transpose()
 
 alpha = input("alpha = ") 
 alpha = float(alpha)
 alpha = np.zeros((1, len(p))) + alpha # vector of same length as p with all entries being 0.5

 def w(alpha, p):
     return np.exp(-(-np.log(p))**alpha) # probability weighting function
 w = w(alpha, p)

 # calculate inverse of probability weighting function: p = exp(-log^2(w))
 def P(w):
    return np.exp(np.log2(w))
 probability_of_winning = P(w)
 probability_of_winning = np.round([probability_of_winning], decimals=2) # rounds to 2 decimal points
 probability_of_winning_in_percent = probability_of_winning * 100

 probability_of_losing = 1 - probability_of_winning
 probability_of_losing_in_percent = probability_of_losing * 100

 # calculate best outcome of lottery
 E = input("endownment/ expected value of lottery = ") # endownment & expected value of lottery
 E = float(E)
 E = np.zeros((1, len(p))) + E
   
 b = input("worst outcome of lottery is = ") # worst outcome of lottery 
 b = float(b)
 b = np.zeros((1, len(p))) + b

 def A(E, b, probability_of_winning):
     return (E - b * (1 - probability_of_winning)) / probability_of_winning
 a = A(E, b, probability_of_winning)    
 a = np.round([A(E, b, probability_of_winning)], decimals=2)

I than created two matrixes to have the coresponding outcomes and probabilities for losing or winning the lottery in the colums

 # matrix for probability of winning/ losing the lottery in colums
 array_probabilities = (probability_of_winning_in_percent, probability_of_losing_in_percent) 
 matrix_of_probabilities = np.vstack(array_probabilities).T.squeeze()
 # matrix for outcoms of winning/ losing the lottery in colums
 a=a.squeeze() # reduce size of dimensions of a 
 array_outcomes = (a, b)
 matrix_of_outcomes = np.vstack(array_outcomes).T

then I separeted the rows to receive the outcome and probability pairs for each lottery

 lottery_outcome_pairs = np.vsplit(matrix_of_outcomes, len(p))
 lottery_probability_pairs = np.vsplit(matrix_of_probabilities, len(p))

then I wanted to use the numpy function np.random.choice to generate randomly outcomes form the lottery_outcome_vector given the weights of the lottery_probability_pairs with:

 ralizations = np.random.choice(lottery_outcome_pairs, 5, p = lottery_probability_pairs)

however here i receive the following error:

  ValueError: a must be 1-dimensional

how can I fix my code? thank you very much in advance