How can I configure j-easy/easy-random for Bidirectional association? For example,
Parent contains Set<Child> Child has reference to Parent
In Set<Child>, every child instance should refer to the same object of the composing Parent. However, currently new instance of Parent is created for every Child in Set<Child>
I have two matrices (1 and 2) which I multiply, resulting in the concordance matrix (c).
I need to randomize one of theses matrices 1000 times and them compare the number of times the value of these concordance matrices were higher than the first comparation.
# Exemple:
mat1 <- matrix(rbinom(222, 1, 0.5),nrow=74,ncol=3) # habitat
mat2 <- matrix(rbinom(592, 1, 0.5),nrow=74,ncol=8) # modular
tmat1 <- t(mat1)
# Multipying the tranposed matrix 1 by matrix 2:
c <- tmat1%*%mat2 # concordance matrix c
resu <- matrix(NA,nrow=3,ncol=8) # creating the matrix to fill with the results of values higher than c
for(r in 1:1000) {
mat3 <- apply(mat1,1,sample) # randomizing matrix 1, maintaining the number of intercations by nodes
cc <- mat3%*%mat2 # multiplying these matrices
for (i in 1:dim(c)[1]){ # rows
for(j in 1:dim(c)[2]){ # columns
if(cc[i]>=c[j]){ #
resu[i,j] <- sum(cc[i]>=c[j]) # filling the matrix with the number of times cc was higher then c
}
}
}
}
But the result is wrong: it is resulting in a matrix with correct number of rows (3) and columns (8) but all fill out by 1.
Each element has to be a different number of times the concordance was higher in cc[i] than c[j].
Any thoughts, please?
Here is my attempt; a slightly-modified Fisher-Yates algorithm. I am not sure how to make sure it's random though.
const shuffleWithoutMovingFalsies = array => {
const newArray = [...array];
const getRandomValue = (i, N) => ~~(Math.random() * (N - i) + i);
newArray.forEach((elem, i, arr, j = getRandomValue(i, arr.length)) => arr[i] && arr[j] && ([arr[i], arr[j]] = [arr[j], arr[i]]));
return newArray;
}
const array = [1, 2, null, 3, null, null, 4, 5, 6, null];
const shuffledArray = shuffleWithoutMovingFalsies(array);
console.log(shuffledArray);All I did was add arr[i] && arr[j] && as a check to make sure both elements about to be swapped are NOT falsy.
Pseudocode Example:
Random function: (1 to 5, results less than 100, results must equal 100 when all random numbers are
added).
Showmessage:
Number 1 = 35
Number 2 = 15
Number 3 = 10
Number 4 = 20
Number 5 = 20
I am trying to efficiently add an integer column to a dataframe, where the integer is any number, i, from 0 to N, where i is not in the set R. The set r in R for every row is obtained by a mapping from the value of the first column, word1, to a set, K. Every value in word1 has a map to a set of values within R.
word1 | word2 | word3
Idaho New York <rand integer based on word 1 map>
I'm trying to do this without a UDF. This is the psuedo-code I've landed on but I really don't know if this is even possible with PySpark. I'm stuck in how to generate a random integer within a range that excludes values. Normally, I'd generate random values until a value meeting the condition is met. But I think I'd need to move any while loop into a udf, which I'm trying to avoid.
df_expanded = df.withColumn('word3', rand() where rand() not in map(col('word1')))
Here is how I'd write it in a udf, but this is very slow.
def get_sample(all_ii, word):
# the set of integers to exclude
s = iid[word]
# all_ii, set, has all possible integers in a range
a = all_ii - s
if len(a): return random.sample(a, 1)[0]
return ''
I need to know if we have a array of scale and shape parameters and want to generate n (it could be 10^6 for instance) gamma random variables for each elements of pair scale and shape parameters array but without a loop or for, then what can we do? Is there any trick because apparently there is no way at least in matlab helps? thanks in advance...
I'm trying to get an output that looks like that:
12:15
07:55
02:20
04:35
I managed to get the following output:
2020-07-03 03:53:32
2020-07-20 08:01:15
2020-07-29 10:04:11
2020-07-07 07:17:24
2020-07-20 12:13:32
by using this code:
import datetime
import time
import random
MINTIME = datetime.datetime(2020,7,1,0,0,0)
MAXTIME = datetime.datetime(2020,7,31,0,0,0)
mintime_ts = int(time.mktime(MINTIME.timetuple())) #convert date into int
maxtime_ts = int(time.mktime(MAXTIME.timetuple())) #convert date into int
for RECORD in range(100):
random_ts = random.randint(mintime_ts, maxtime_ts)
RANDOMTIME = datetime.datetime.fromtimestamp(random_ts)
print(RANDOMTIME)
So, basically I have two issues. The first is I want to get the time in format of (hh:mm) only. The second is that I want the step to be 5 minutes (something like 14:50 or 04:35 .. etc).
Thanks