normalization

问题 Is it possible to normalize this table in R based on the last column(samples) samples = number of sequenced genomes. So I want to get a normalised distribution of all the genes in all the conditions. Simplified example of my data: I tried: dat1 <- read.table(text = " gene1 gene2 gene3 samples condition1 1 1 8 120 condition2 18 4 1 118 condition3 0 0 1 75 condition4 32 1 1 130", header = TRUE) dat1<-normalize(dat1, method = "standardize", range = c(0, 1), margin = 1L, on.constant = "quiet")

来源： https://stackoverflow.com/questions/52619663/android-room-efficient-way-to-transform-json-result-into-db-object

来源： https://stackoverflow.com/questions/52619663/android-room-efficient-way-to-transform-json-result-into-db-object

来源： https://stackoverflow.com/questions/11176603/how-to-avoid-browsers-unicode-normalization-when-submitting-a-form-with-unicode

来源： https://stackoverflow.com/questions/46977761/creating-z-score-grouped-by-column-value-in-r

问题 I'm trying to normalize a string in ColdFusion. I want to use the Java class java.text.Normalizer for this, as CF doesn't have any similar functions as far as I know. Here's my current code: <cfset normalizer = createObject( "java", "java.text.Normalizer" ) /> <cfset string = "äéöè" /> <cfset string = normalizer.normalize(string, createObject( "java", "java.text.Normalizer$Form" ).NFD) /> <cfset string = ReReplace(string, "\\p{InCombiningDiacriticalMarks}+", "") /> <cfoutput>#string#<

问题 I have a 2D numpy array "signals" of shape (100000, 1024). Each row contains the traces of amplitude of a signal, which I want to normalise to be within 0-1. The signals each have different amplitudes, so I can't just divide by one common factor, so I was wondering if there's a way to normalise each of the signals so that each value within them is between 0-1? Let's say that the signals look something like [[0,1,2,3,5,8,2,1],[0,2,5,10,7,4,2,1]] and I want them to become [[0.125,0.25,0.375,0

问题 I have a 2D numpy array "signals" of shape (100000, 1024). Each row contains the traces of amplitude of a signal, which I want to normalise to be within 0-1. The signals each have different amplitudes, so I can't just divide by one common factor, so I was wondering if there's a way to normalise each of the signals so that each value within them is between 0-1? Let's say that the signals look something like [[0,1,2,3,5,8,2,1],[0,2,5,10,7,4,2,1]] and I want them to become [[0.125,0.25,0.375,0

问题 I am getting a type error as "TypeError: string indices must be integers" in the following code. import pandas as pd import json from pandas.io.json import json_normalize full_json_df = pd.read_json('data/world_bank_projects.json') json_nor = json_normalize(full_json_df, 'mjtheme_namecode') json_nor.groupby('name')['code'].count().sort_values(ascending=False).head(10) Output: TypeError Traceback (most recent call last) <ipython-input-28-9401e8bf5427> in <module>() 1 # Find the top 10 major

问题 I was wondering if there is a built in normalisation function in flutter. That works like this List<int> array = [-105,24,66,-50,-49,2] //Normalises to get numbers between -1 and 1 List<double> normalised = array.normalise(-1,1) 回答1: I'm afraid there isn't one, but I've made what you're looking for manually: import 'dart:math'; List<int> array = [-105, 24, 66, -50, -49, 2]; final lower = array.reduce(min); final upper = array.reduce(max); final List<double> normalized = []; array.forEach(