for-loop

问题 I have a raster stack and 100 points. For each raster I want to extract the value and do so using three different scales/buffers. First, here are three rasters combined into a stack library(raster) # Make rasters and combine into stack set.seed(123) r1 = raster(ncol=1000, nrow=1000, xmn=0, xmx=1000, ymn=0, ymx=1000) values(r1) = round(runif(ncell(r1),1,100)) r2 = raster(ncol=1000, nrow=1000, xmn=0, xmx=1000, ymn=0, ymx=1000) values(r2) = round(seq(1:ncell(r1))) r3 = raster(ncol=1000, nrow

问题 I have a raster stack and 100 points. For each raster I want to extract the value and do so using three different scales/buffers. First, here are three rasters combined into a stack library(raster) # Make rasters and combine into stack set.seed(123) r1 = raster(ncol=1000, nrow=1000, xmn=0, xmx=1000, ymn=0, ymx=1000) values(r1) = round(runif(ncell(r1),1,100)) r2 = raster(ncol=1000, nrow=1000, xmn=0, xmx=1000, ymn=0, ymx=1000) values(r2) = round(seq(1:ncell(r1))) r3 = raster(ncol=1000, nrow

问题 I have the following code: for(int sentenceCounter = 0; sentenceCounter < sentences.length; sentenceCounter++) { double score = 0; String[] sentence = sentences[sentenceCounter].split(" "); for (int titleCounter = 0; titleCounter < titles.length; titleCounter++) { for (int wordCounter = 0; wordCounter < sentence.length; wordCounter++) { if (titles[titleCounter].equals(sentence[wordCounter])) { if(titleCounter == 0) { score += titleValue * hundred / 100; sentenceScore.put(sentenceCounter,

问题 I have the following code: for(int sentenceCounter = 0; sentenceCounter < sentences.length; sentenceCounter++) { double score = 0; String[] sentence = sentences[sentenceCounter].split(" "); for (int titleCounter = 0; titleCounter < titles.length; titleCounter++) { for (int wordCounter = 0; wordCounter < sentence.length; wordCounter++) { if (titles[titleCounter].equals(sentence[wordCounter])) { if(titleCounter == 0) { score += titleValue * hundred / 100; sentenceScore.put(sentenceCounter,

问题 I have output data from a piece of equipment. Unfortunately the output data is not organized very well, and I have been writing a code in R to break it down. Essentially the data is a separate list of information (basic descriptive information, and raw data for two different measurements A and B for each time interval) for each subject pasted into one long document. For example: Date: 01/01/2016 Time: 12:00:00 Subject: Subject1 A: 1: 1 2 4 1 2: 2 1 2 3 3: 1 0 2 7 B: 1: 2 3 0 1 2: 4 1 1 2 3: 3

问题 I have output data from a piece of equipment. Unfortunately the output data is not organized very well, and I have been writing a code in R to break it down. Essentially the data is a separate list of information (basic descriptive information, and raw data for two different measurements A and B for each time interval) for each subject pasted into one long document. For example: Date: 01/01/2016 Time: 12:00:00 Subject: Subject1 A: 1: 1 2 4 1 2: 2 1 2 3 3: 1 0 2 7 B: 1: 2 3 0 1 2: 4 1 1 2 3: 3

问题 I am creating a loop in order to append continuously values from user input to a dictionary but i am getting this error: AttributeError: 'dict' object has no attribute 'append' This is my code so far: for index, elem in enumerate(main_feeds): print(index,":",elem) temp_list = index,":",elem li = {} print_user_areas(li) while True: n = (input('\nGive number: ')) if n == "": break else: if n.isdigit(): n=int(n) print('\n') print (main_feeds[n]) temp = main_feeds[n] for item in user: user['areas

问题 I hope this is not trivial but I am wondering the following: If I have a specific folder with n csv files, how could I iteratively read all of them, one at a time, and perform some calculations on their values? For a single file, for example, I do something like this and perform some calculations on the x array: import csv import os directoryPath=raw_input('Directory path for native csv file: ') csvfile = numpy.genfromtxt(directoryPath, delimiter=",") x=csvfile[:,2] #Creates the array that

问题 I am reading log files in my python code which contains some nested json data. I have a nested for loop containing 4 for-loops from which values of certain keys are extracted and appended to a dataframe. The nested for-loop is taking too much time and I saw from other answers that multiprocessing is the way to go for nested for-loops but did not find an example for json data. What is the best approach for this ? Below is my code to extract data from log files and into dataframes.

问题 I am trying to use a loop for iterating through two lists. Unfortunately, the second for loop does not work: it only checks the first item within the list, but not with rest. Could you please tell me why? Thanks Lists: low_cars_engines=['Audi', 'Bentley', 'Bugatti', 'Porsche', 'Skoda'] low_planes_engines=['Pratt & Whitney','Rolls-Royce','GE Aviation'] I would like to add two more columns (Cars and Planes) to my original dataset based on if statements: if an object from list 'Engine to check'