histogram

问题 Here is an example data set: structure(list(Age = c(6L, 7L, 5L, 6L, 7L, 9L,6L, 7L, 5L, 6L, 7L, 9L,6L, 7L, 5L, 6L, 7L, 9L), Year = c(2011, 2011, 2011, 2011, 2011, 2011, 2011, 2011, 2011, 2011, 2011, 2011, 2011, 2011, 2011, 2011, 2011, 2011 )), .Names = c("Age", "Year"), row.names = c(NA, 6L), class = "data.frame") I am trying to create a legend that will show the three components that I list in my geom_vline command below. I've read several examples on s.overflow but nothing seems to be

问题 I have to do the following - 1) find pixels belonging to intensity-level-0 to intensity-level-255 and store them in 256 arrays 2) redistribute pixels from one intensity level to another intensity level so that all the 256 levels have equal pixels. This is the algorithm of a bigger problem I'm trying to solve and I'm stuck here as I don't know how to manipulate the cell array elements. I'll be having 256 cells in the cell array and I've to compare and redistribute elements belonging to

问题 I am learning to visualize tensor via tensorboard, however, I don't know how to interpret chart in Histogram tab. I used below code to visualize: sess = tf.Session() tf.summary.histogram('test', tf.constant([1, 1, 2, 2, 3, 4, 4, 4, 4])) summary = tf.summary.merge_all() train_writer = tf.summary.FileWriter('../tmp/train', sess.graph) for i in range(10): sum = sess.run(summary) train_writer.add_summary(sum, i) I got this chart from tensorboard: Histogram mode: offset Histogram mode: overlay I

问题 Using ggplot2 it is very easy to create stacked histograms: library(ggplot2) ggplot(data = iris, aes(x = Sepal.Length, fill = Species)) + geom_histogram(colour = 'white') ggplot(data = iris, aes(x = Sepal.Length, fill = Species)) + geom_histogram(colour = 'white', position = 'fill') I would like to know how to create both histograms using only R base graphics . 回答1: You can generate both plots with barplot() , based on a frequency table of Species and Sepal.Length . # Create frequency table

问题 I'm tyring to implement (I know there's a custom function for achieving it) the grayscale image histogram in Matlab, so far I've tried: function h = histogram_matlab(imageSource) openImage = rgb2gray(imread(imageSource)); [rows,cols] = size(openImage); histogram_values = [0:255]; for i = 1:rows for j = 1:cols p = openImage(i,j); histogram_values(p) = histogram_values(p) + 1; end end histogram(histogram_values) However when I call the function, for example: histogram_matlab('Harris.png') I

问题 Consider the following d <- read.table(text=" class num married type 1 0.0 63530 23067 A 2 2.5 27061 16601 A 3 3.5 29938 19332 B 4 4.5 33076 24112 A 5 5.6 45759 32405 A 6 6.5 72794 61234 A 7 8.0 153177 107089 A 8 10.8 362124 267303 A 9 13.5 551051 334578 A 10 15.5 198634 181530 A 11 2.5 52710 10450 B 12 7.0 123177 98076 B 13 8.0 262524 105331 B 14 13.5 301031 127690 B 15 15.5 103634 49887 B ") p <- ggplot(d) + geom_histogram(aes(x=class,weight=num,fill=type), binwidth=6,alpha=.4) + geom

问题 Consider the following d <- read.table(text=" class num married type 1 0.0 63530 23067 A 2 2.5 27061 16601 A 3 3.5 29938 19332 B 4 4.5 33076 24112 A 5 5.6 45759 32405 A 6 6.5 72794 61234 A 7 8.0 153177 107089 A 8 10.8 362124 267303 A 9 13.5 551051 334578 A 10 15.5 198634 181530 A 11 2.5 52710 10450 B 12 7.0 123177 98076 B 13 8.0 262524 105331 B 14 13.5 301031 127690 B 15 15.5 103634 49887 B ") p <- ggplot(d) + geom_histogram(aes(x=class,weight=num,fill=type), binwidth=6,alpha=.4) + geom

问题 I have two sets of different sizes that I'd like to plot on the same histogram. However, since one set has ~330,000 values and the other has about ~16,000 values, their frequency histograms are hard to compare. I'd like to plot a histogram comparing the two sets such that the y-axis is the % of occurrences in that bin. My code below gets close to this, except that rather than having the individual bin values sum to 1.0, the integral of the histogram sums to 1.0 (this is because of the normed

问题 I have some x and y data, with which I would like to generate a 3D histogram, with a color gradient (bwr or whatever). I have written a script which plot the interesting values, in between -2 and 2 for both x and y abscesses: import numpy as np import numpy.random import matplotlib.pyplot as plt # To generate some test data x = np.random.randn(500) y = np.random.randn(500) XY = np.stack((x,y),axis=-1) def selection(XY, limitXY=[[-2,+2],[-2,+2]]): XY_select = [] for elt in XY: if elt[0] >

问题 I have jpegs on a webpage. I would like to perform client-side equalization (contrast stretching) on these images without browser plugins. I would also accept a solution for histogram equalization. I currently use a poor approximation with a combination of two CSS filters (-webkit-filter: contrast() brightness()). I am hoping to be able to accomplish this with something like processing.js or pixastic. 回答1: I do not know of a library that contains an efficient histogram equalization method