conditional-statements

问题 I have a dataset as follows: library(data.table) DT <- structure(list(State_Ab = c("MD", "MD", "MD", "MD", "MD", "MD", "MD", "MD", "MD", "MD", "MD", "MD", "MD", "MD"), County = c("Baltimore", "Baltimore", "Baltimore", "Baltimore", "Baltimore", "Baltimore", "Baltimore", "Baltimore", "Baltimore", "Baltimore", "Baltimore", "Baltimore", "Baltimore", "Baltimore"), year = c(1994, 1994, 1998, 1998, 2000, 2000, 2004, 2004, 2006, 2006, 2010, 2010, 2016, 2016), Population = c(140942, 219673, 235413,

问题 I have data as follows: library(data.table) DT <- structure(list(State_Ab = c("VA", "VA", "VA", "VA", "VA", "VA", "VA", "VA", "VA", "VA", "VA", "VA", "VA", "VA", "VA", "VA", "VA", "VA", "VA", "VA", "VA", "VA", "VA", "VA", "VA", "VA", "VA", "VA", "VA", "VA", "VA", "VA", "VA", "VA", "VA", "VA", "VA", "VA", "VA", "VA", "VA", "VA", "VA", "VA", "VA", "VA"), year = c(1995, 1995, 1995, 1995, 1999, 1999, 1999, 1999, 2001, 2001, 2001, 2001, 2005, 2005, 2005, 2005, 2007, 2007, 2007, 2007, 2011, 2011,

问题 For numpy we have threshold = 3 a = np.array([1,2,3,4,5,6]) a[a>=3] = 199 # a is [1, 2, 199, 199, 199, 199] How to write a similar code in tensorflow 2 b = tf.Variable(a) Thanks. 回答1: Sure, you can use tf.where to conditionally set values: b = tf.Variable(a) tf.where(b >= 3, 199, b) # <tf.Tensor: shape=(6,), dtype=int64, numpy=array([ 1, 2, 199, 199, 199, 199])> 来源： https://stackoverflow.com/questions/65449671/conditional-assignment-of-tf-variable-in-tensorflow-2

问题 For numpy we have threshold = 3 a = np.array([1,2,3,4,5,6]) a[a>=3] = 199 # a is [1, 2, 199, 199, 199, 199] How to write a similar code in tensorflow 2 b = tf.Variable(a) Thanks. 回答1: Sure, you can use tf.where to conditionally set values: b = tf.Variable(a) tf.where(b >= 3, 199, b) # <tf.Tensor: shape=(6,), dtype=int64, numpy=array([ 1, 2, 199, 199, 199, 199])> 来源： https://stackoverflow.com/questions/65449671/conditional-assignment-of-tf-variable-in-tensorflow-2

问题 This solution Automate Seed as a Vector Instead of an Integer in R library(forecast) SEED_vector <- c(1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19) arima_order_results = data.frame() for (my_seed in SEED_vector){ set.seed(my_seed) ar1 <- arima.sim(n = 10, model=list(ar=0.2, order = c(1, 0, 0)), sd = 1) ar2 <- auto.arima(ar1, ic ="aicc") arima_order = arimaorder(ar2) arima_order = t(as.data.frame(arima_order)) # Print the arima order. print(arima_order) # This line of code is just if you

问题 This solution Automate Seed as a Vector Instead of an Integer in R library(forecast) SEED_vector <- c(1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19) arima_order_results = data.frame() for (my_seed in SEED_vector){ set.seed(my_seed) ar1 <- arima.sim(n = 10, model=list(ar=0.2, order = c(1, 0, 0)), sd = 1) ar2 <- auto.arima(ar1, ic ="aicc") arima_order = arimaorder(ar2) arima_order = t(as.data.frame(arima_order)) # Print the arima order. print(arima_order) # This line of code is just if you

问题 This solution Automate Seed as a Vector Instead of an Integer in R library(forecast) SEED_vector <- c(1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19) arima_order_results = data.frame() for (my_seed in SEED_vector){ set.seed(my_seed) ar1 <- arima.sim(n = 10, model=list(ar=0.2, order = c(1, 0, 0)), sd = 1) ar2 <- auto.arima(ar1, ic ="aicc") arima_order = arimaorder(ar2) arima_order = t(as.data.frame(arima_order)) # Print the arima order. print(arima_order) # This line of code is just if you

问题 This solution Automate Seed as a Vector Instead of an Integer in R library(forecast) SEED_vector <- c(1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19) arima_order_results = data.frame() for (my_seed in SEED_vector){ set.seed(my_seed) ar1 <- arima.sim(n = 10, model=list(ar=0.2, order = c(1, 0, 0)), sd = 1) ar2 <- auto.arima(ar1, ic ="aicc") arima_order = arimaorder(ar2) arima_order = t(as.data.frame(arima_order)) # Print the arima order. print(arima_order) # This line of code is just if you

问题 Currently, I see behavior like this: render() { const list = []; return ( <div> { list.length && <div>List rendered</div> } </div> ) } My expected is nothing rendered with that condition, but string "0" rendered (string "0" is list.length ). I don't know why. Anybody can help me explain this case to React? 回答1: That's basically the way, short-circuit evaluation is designed: As logical expressions are evaluated left to right, they are tested for possible "short-circuit" evaluation using the

问题 I've tried to come up with a simple solution to the followig problem. Here is the minimum working example: data <- data.frame(subject = c('Math', 'English', 'French', 'English'), grade = c(1, 3, 5, 4)) I want a function that compares Enlish grades and returns a logical vector that has TRUE for the row with the highest english grade, and FALSE for all other rows. In this case [1] FALSE FALSE FALSE TRUE . 回答1: We can get the max 'grade' per 'subject' with ave compare it with the 'grade' to get