histogram

问题 I have used the code hist(x, probability=TRUE) which gives me a y-axis from 0 to 2 with the name density. I dont get what this means. Does it integrate to 1, sum to 1, or what is the y-value equal to? The documentation says "freq = NULL, probability = !freq" but that does not make sense to me. If I dont use probability=TRUE I get Frequency on the y-axis, but the shape of the plot is the same. 回答1: You can save your histogram to a variable and take a look at it. x=rnorm(1000) h<-hist(x) h

问题 I would like to know how one is able to fit any distribution to a given set of data using the method of MLEs. As a particular example, could anyone suggest a working code that would give the correct results for the MLEs for $\theta$ and $\beta$ when the generalised Lindley distribution described in https://rivista-statistica.unibo.it/article/viewFile/6836/7039 is applied to the data: 5.1, 6.3, 10.8, 12.1, 18.5, 19.7, 22.2, 23, 30.6, 37.3, 46.3, 53.9, 59.8, 66.2 on pg. 156? How can this then

问题 Suppose that based on my my previous question I have equalized the histogram of an image now the question is how to apply this new equalized histogram on the image? I mean what is the algorithm to get the new image from the new equalized histogram? I have seen a code about this in the net. It is evident that the last for loops, shown in this photo, are for applying the equalized histogram on the image matrix. But I don't understand the algorithm used. Again note that it's a college assignment

问题 I have a couple of questions, and i tried but i couldn't solve it. Let me help. This is the question. There is an unknown histogram, and I want to guess the histogram(Not exact histogram is okay). I got some information about histogram. Given Information: min, max, size, mean, percentile(25%, 50%, 75%) I want to know how i can get the graph satisfying those conditions. Why this code doesn't work?? Thank you. -----------This is what i tried------------- import pandas as pd import numpy as np

问题 I'm using OpenCV combined with C++ to get the histogram (using calcHist function) of the image in BGR, which is converted from grayscale with GRAY2BGR. The weird thing here is that histogram seems to count all pixels except... white ones (255, 255, 255). What can be the case? Of course I can convert it in HSV and look up for S = 0 to detect white pixels (I hope it'll work, haven't tested it yet) but why the heck should I do so when I've the histogram counted already? Do you have any ideas? PS

问题 I have a set of data that I transpose to get the data groups into rows and have place holder values (for my case, series of mass values) in columns. My next goal is to draw histograms for each row that contains the same character as shown below: mz 902.4 909.4 915.3 n 0.6 0.3 1.4 n.1 0.4 0.3 1.3 n.2 0.3 0.2 1.1 n.3 0.2 0.2 1.3 n.4 0.4 0.3 1.4 DCIS 0.3 1.6 DCIS.1 0.3 1.2 DCIS.2 1.1 DCIS.3 0.2 1.2 DCIS.4 0.2 1.3 DCIS.5 0.2 0.1 1.5 br_1 0.5 0.4 1.4 br_1.1 0.2 1.3 br_1.2 0.5 0.2 1.4 br_1.3 0.5 0

问题 I have a directory with 10000 .root files (each looks like hists11524_blinded.root or hists9899_blinded.root ) in it and need to run some macros for my data analysis purposes. However, I don't need all of the files (just 4000 out of all) to be in the directory. I have a list of needed runs (these 4000 numbers) in thebest.txt file . This file is also in that directory with histograms. I want to delete the files which are not needed for the processing before running macros by using the info

问题 I read this article http://www.r-bloggers.com/comparing-hist-and-cut-r-functions/ and tested hist() to be faster than cut() by ~4 times on my PC. My script loops through cut() many times so the time-saving would be significant. I thus tried to switch to the speedier function but am having difficulties getting the exact output as per cut() . From the sample code below: data <- rnorm(10, mean=0, sd=1) #generate data my_breaks <- seq(-6, 6, by=1) #create a vector that specifies my break points

问题 I have a set of images and i want to create a histogram over the hue values from each image. Therfore i created an array with length 180. In every cell i add 1 if the hue value is in the image. In the end i have the array with the occurence of each hue value, but when i use numpy.hist, the y-axis are the hue values and the x-axis are the occurence. But i want it the other way round. Here is my code: path = 'path' sub_path = 'subpath' sumHueOcc = np.zeros((180, 1), dtype=int) print("sumHue

问题 I have following code that was given to me, but I am not sure at all as to what the logic here is. The idea, I believe, is that this will histogram/quantize my data. Here is the code: The input: x = 180.*rand(1,1000); %1000 points from 0 to 180 degrees. binWidth = 20; %I want the binWidth to be 20 degrees. The main function: % ------------------------------------------------------------------------- % Compute the closest bin center x1 that is less than or equal to x % ------------------------