histogram

I had load buffered image and need to plot histogram? please suggest me next steps to to plot RGB histogram. if it can done using jai please suggest me the way to do it. I hadtried alot and also googled alot but dint found any right solution. here is how i had load my image please provide me next steps BufferedImage image= ImageIO.read(new File("C:\\Images\\Sunset.jpg")); ParameterBlock pb = new ParameterBlock(); int[] bins = { 256 }; double[] low = { 0.0D }; double[] high = { 256.0D }; pb.addSource(image); pb.add(null); pb.add(1); pb.add(1); pb.add(bins); pb.add(low); pb.add(high); RenderedOp

I am trying to have ggplot2 show one line of a histogram as a different color than the rest. In this I have been successful; however, ggplot is using the default colors when a different set are specified. I am sure there is an error in my code, but I am unable to determine where it is. The data and code are below: create data library(ggplot2) set.seed(71185) dist.x <- as.data.frame(round(runif(100000, min= 1.275, max= 1.725), digits=2)) colnames(dist.x) <- 'sim_con' start histogram ggplot(dist.x, aes(x = sim_con)) + geom_histogram(colour = "black", aes(fill = ifelse(dist.x$sim_con==1.55,

I have an array A which I am trying to put into 10 bins. Here is what I've done. A = range(1,94) hist = np.histogram(A, bins=10) np.digitize(A, hist[1]) But the output has 11 bins, not 10, with the last value (93) placed in bin 11, when it should have been in bin 10. I can fix it with a hack, but what's the most elegant way of doing this? How do I tell digitize that the last bin in hist[1] is inclusive on the right - [ ] instead of [ )? The output of np.histogram actually has 10 bins; the last (right-most) bin includes the greatest element because its right edge is inclusive (unlike for other

I have a pandas dataframe like the following: df = pd.DataFrame({ 'a_wood' : np.random.randn(100), 'a_grassland' : np.random.randn(100), 'a_settlement' : np.random.randn(100), 'b_wood' : np.random.randn(100), 'b_grassland' : np.random.randn(100), 'b_settlement' : np.random.randn(100)}) and I want to create histograms of this data with every dataframe header in one subplot. fig, ax = plt.subplots(2, 3, sharex='col', sharey='row') m=0 for i in range(2): for j in range(3): df.hist(column = df.columns[m], bins = 12, ax=ax[i,j], figsize=(20, 18)) m+=1 For that the previous code works perfectly but

I am using Python (3.4) Jupyter Notebook. I tried to plot a histogram with label using the code below. %matplotlib notebook import matplotlib.pyplot as plt import matplotlib import numpy as np bins = np.linspace(0, 1.0, 40) plt.hist(good_tests, bins, alpha = 0.5, color = 'b' , label = 'good') plt.show() But the label 'good' doesn't show at all. Did I miss anything? Thanks! you need to add a legend. See legend for details. plt.legend() 来源： https://stackoverflow.com/questions/41213346/python-matplotlib-label-in-histogram

came across this seemingly new package - skimr, which looks pretty nifty, and was trying it out and looks like I'm missing some package installation. Skim works fine except that it doesn't print the histogram, it is supposed to print for numeric variables. I am merely trying the examples given in the documentation. Link to skimr documentation here - https://github.com/ropenscilabs/skimr#skimr this is the code I'm using devtools::install_github("hadley/colformat") devtools::install_github("ropenscilabs/skimr") library(skimr) a<-skim(mtcars) dim(a) View(a) instead of histograms being printed, I