crossover | 🎯 A Crosshair Overlay for any screen | Game Engine library
kandi X-RAY | crossover Summary
kandi X-RAY | crossover Summary
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Currently covering the most popular Java, JavaScript and Python libraries. See a Sample of crossover
crossover Key Features
crossover Examples and Code Snippets
Lines of Code : 16License : Permissive (MIT License)
Copydef crossover(p1, p2):
''' Performing uniform crossover. Alpha is the flag
that determines which gene of each chromosome is choosen
to be inherited by the offspring. Maultiply the alpha value
with each gene of every chromosome of both the par Community Discussions
Trending Discussions on crossover
QUESTION
I have a list, lprobs. Each list element is a simple vector of probabilities (P[Z≥z]) under different parameter values (defined below in kvec).
When comparing these probabilities, the lower parameter value initially always has a lower probability when z>=2. Then there is a "crossover" at some value of z where the lower parameter value begins yielding a higher probability. I need to determine the the z value and probability when these crossovers occur for all combinations of k values.
The following plot may help visualize this:
The black (k = 0.01) is the easiest example to point out: I need to find the z value and P(Z=z) when P(Z=z) for k = 0.01 crosses over with k = 0.25, 0.5, 0.75, 1.0 (somewhere after z > 300). If there is not a crossover by the maximum z value (defined in the below code by cutoff), it should return NA (i.e. when comparing k values of 0.01 and 0.25).
I have tried several for loops and manually finding these values, but I have not found an elegant solution to systematically record the z value and probability for each crossover. The actual data are much larger.
The desired result would be as below (though open to suggestions, doesn't have to be exactly this), where z_val and prob_z identify the specific z value and probability of each crossover event:
ANSWER
Answered 2022-Mar-09 at 20:47I believe you can do something like this:
QUESTION
I have a serious problem merging Take profit and Stop loss in one script.
I'm using this script for TP https://kodify.net/tradingview/orders/percentage-profit/
and this one for SL https://kodify.net/tradingview/orders/percentage-stop/
I came up with the below script which doesn't look to SL. Hence, the order will remain open until TP % is reached. I need your help to fix it and activate SL same as TP.
...ANSWER
Answered 2021-Aug-06 at 17:41Here you go, with couple of additions
QUESTION
I have a PRM file that is a kind of text file. I want to change some characters in it. For example, " md = minf; " to "md = maxf;" and "ls = 1" to "ls = 3". Can you guide me on how can I change it? I don't know how can I use WriteLines function in this situation?
...ANSWER
Answered 2022-Mar-02 at 00:04linn <- c("begin_pop = \\p1\\;", " beginfounder;", " male [n = 20, pop = \\hp\\];", " female [n = 400, pop = \\hp\\];", " endfounder;", " ls = 1;", " pmp = 0.5;", " ng = 10;", " md = minf;", " sr = 0.5;", " dr = 0.3;", " sd = ebv /h;", " cd = ebv /l;", " ebvest = true_av;", " begpop;", " ld /maft 0.1;", "\t crossover;", " data;", " stat;", " genotype/gen 8 9 10;", " endpop;", "end_pop;")
gsub("\\b(ls\\s*=\\s*)1", "\\1 3",
gsub("\\b(md\\s*=\\s*)minf", "\\1maxf", linn))
# [1] "begin_pop = \\p1\\;" " beginfounder;"
# [3] " male [n = 20, pop = \\hp\\];" " female [n = 400, pop = \\hp\\];"
# [5] " endfounder;" " ls = 3;"
# [7] " pmp = 0.5;" " ng = 10;"
# [9] " md = maxf;" " sr = 0.5;"
# [11] " dr = 0.3;" " sd = ebv /h;"
# [13] " cd = ebv /l;" " ebvest = true_av;"
# [15] " begpop;" " ld /maft 0.1;"
# [17] "\t crossover;" " data;"
# [19] " stat;" " genotype/gen 8 9 10;"
# [21] " endpop;" "end_pop;"
QUESTION
I'm running a multi-objective optimisation with Pymoo (0.5.0) using NSGA-III and within my population of new candidates some of the generated candidates have nan parameters. This results in my evaluate function (which is a call to a neural network) returning nan. The optimisation is running and producing desired results but I'd like to know why some of the candidate parameters are nan. Here is the code for the problem.
Problem setup:
...ANSWER
Answered 2021-Oct-08 at 10:38The nan arise because the limits for your parameters 11, 12 and 12 are equal (-1 and -1 in all cases).
If you look at the code for the polynomial mutation (real_pm), you have the following lines:
QUESTION
My table in snowflake has a column with string values. The string has comma and slash. I need to list only the values before first comma or slash. I used snowflake SPLIT function, with that i could only get rid of either of one (comma or slash but not both) character.
...ANSWER
Answered 2022-Feb-03 at 01:04A simple regex should help:
QUESTION
I have a strategy in tradingview that enters every time this condition is true, but I only need to enter the second occurrence of this condition
...ANSWER
Answered 2022-Jan-30 at 21:25You can use a counter for that. Increase it when your condition becomes true, check if it is 2, enter position and reset your counter for next order.
Here is an example that enters and exits position whenever a MACD cross takes place the second time.
QUESTION
I'm fresh student and soon I will have to finish project. But I'm stuck! I do learn JS but I can't understand how to make something. So this is what I need to make.
I have select elements with some options. Some divs with select are hidden and I want to show them when someone click on 1st select some option example "Veliki servis". (Want to remove class hidden from #filteri #ulja.) I tried and I am tired now.
Hope will get answer soon so I can analyze.
...ANSWER
Answered 2022-Jan-29 at 12:51Here is a compact way of achieving your objective:
QUESTION
I have this code in my account and it works fine but I can not publish it. I'm having a very hard time converting this script to the version 4 or 5.
...ANSWER
Answered 2022-Jan-18 at 09:31It's not a v4 indicator, it's written in Pine v1, hence why it works without specifying the version at the beginning. Migration guides from earlier Pine versions to the newer ones can be found in the User Manual.
Working v5 code:
QUESTION
ANSWER
Answered 2022-Jan-05 at 19:39We can full_join the dataset with itself by the same day of week, month and year. Here is a dplyr approach.
QUESTION
I'm not entirely familiar with all the terminology, so please excuse any errors on that part. I decided to write a program that uses an evolutionary (?) algorithm to go from a random string of characters to a target string.
It works fine, but I noticed something that I don't understand. If I use 'asexual' reproduction, i.e. each string clones itself and then mutates with some probability, the convergence to the solution is much slower, and sometimes doesn't converge at all, but gets trapped, at say an average fitness of ~0.8. This doesn't make sense to me, since the mutation should make it trend towards the optimum, right?
However, if I instead use crossover, e.g. I pick two parents and do a uniform mix of characters and then like normal mutate the child with some probability the convergence is not only practically guaranteed, it is also orders of magnitude faster. I don't think this can explained solely by the fact that the child gets to "mutate more" since both its parents are also mutated in the previous generation.
Could someone please explain the role of crossover, and why it allows for much faster convergence in algorithms such as these?
...ANSWER
Answered 2021-Dec-20 at 11:38The role of crossover in genetic algorithms is to spread the beneficial mutations of population members that let them achieve a high fitness value to more members of the population.
The key is that only the fit members of the population crossover with each other and thereby spread beneficial mutations to more members of the population with the intent that the offespring (/new members) might also benefit from the mutation of the parent. Thereby crossover leads to a spreading of mutations that lead to a higher fitness value spread throughout the population - leading to your observed faster convergence.
Take for example a neural network that plays a jump and run video game and is optimized with a genetic algorithm. One member might have received a high fitness score through a mutation that makes him jump over obstacles. Another member might have received a high fitness score through a mutation that makes him collect lifes on the map. Crossing over fit parent members spreads the beneficial mutations faster than if the rest of the population would need to learn these fitness increasing mutations itself by chance.
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