test.py

from re import A
import torch
import numpy as np
from collections import Counter
from channel import Channel
# def myfun(data):
#     tempdata = data
#     tempdata[1] = 0
#     return tempdata
# a = torch.tensor([1,1,0,0,0,1,1,0,0,1])
# index = torch.nonzero(a).squeeze()
# n = len(index)
# print(index,n)
# a[index[-1]] = 0
# print(a)
# b = myfun(a.clone())
# print(b,a)
# c = b.tolist()
# print(c)
# print(c == set(c), c)
# a = {1:0, 5:0, 6:1, 9:2}
# min_set = min(a.values())
# xxx = a.keys()
# a = list(range(11))
# a.remove(9)
# print(a)


# alive = torch.tensor([1,0,0,1,1])
# alive = alive.view(1,1,5)
# alive = alive.expand(1, 5, 5).unsqueeze(-1)
# print(alive, alive.transpose(1,2))

# # check for np.nonzero function
# x = np.array([[1,0,1,1,1,0,0,1,0,1]])
# print(x[np.nonzero(x)])
# print(np.nonzero(x.squeeze()))

# # check for non-alive, return an empty array 
# a = np.array([0,0,0])
# print(type(np.nonzero(a.squeeze())[0]))
# print(type(np.nonzero(a.squeeze())[0].tolist()))

# # check channel
# alive = np.array([0,0,0,0,0,0])
# mychannel = Channel()
# a,b,c = mychannel.send(alive)
# print(a)

# # check empty list iter
# a = [] 
# for x in a:
#     print('efeef')

# # check loop return 
# def loopfunction():
#     x = 100
#     while x >0:
#         x -= 1
#         return 100
# print(loopfunction())

# a = []
# for x in range(10):
#     b = []
#     for y in range(5):
#         b.append(y)
#     a.extend(b)
# print(a)
class myclass():
    def __init__(self,qq) -> None:
        self.data = 9.9
        self.qq = qq
    def myfun(self):
        tempdata = self.data
        for x in [1,2,3,4]:
            print(tempdata,self.data)
            tempdata -= 1
            self.qq -= 1
            print(self.qq)
        print(id(tempdata) == id(self.data))
y = 100
mymine = myclass(y)
for x in [1,2,3]:
    mymine.myfun()
print(y)
a = 100.0
b = a
print(id(a) == id(b))