histogram

I'd like to have a weights option in seaborn distplot, similar to that in numpy histogram. Without this option, the only alternative would be to apply the weighting to the input array, which could result in an impractical size (and time). vlasisva You can provide weights by passing them to the underlying matplotlib's histogram function using the hist_kws argument, as: sns.distplot(..., hist_kws={'weights': your weights array}, ...) Take note though, that the weights will be passed only to the underlying histogram; neither the kde, nor the fit functions of the distplot will be affected. 来源：

I want to make a histogram of every column of a matrix, but I want the bins to be logarithmic and also normalized. And after I create the histogram I want to make a fit on it without showing the bars. This is what I have tried: y=histogram(x,'Normalized','probability'); This gives me the histogram normalized, but I don't know how to make the bins logarithmic. There are two different ways of creating a logarithmic histogram: Compute the histogram of the logarithm of the data. This is probably the nicest approach, as you let the software decide on how many bins to create, etc. The x-axis now

I am creating a hsv histogram from an image like below. - (void)processImageWithHsv:(Mat&)image; { Mat image_hsv; cvtColor(image, image_hsv, CV_BGR2HSV); int hbins = 50, sbins = 60; int histSize[] = {hbins, sbins}; float hranges[] = { 0, 360 }; float sranges[] = { 0, 256 }; const float* ranges[] = { hranges, sranges }; MatND hist; int channels[] = {0, 1}; calcHist( &image_hsv, 1, channels, Mat(), // do not use mask hist, 2, histSize, ranges, true, // the histogram is uniform false ); double maxVal = 0; minMaxLoc(hist, 0, &maxVal, 0, 0); // ???: HOW Convert this information to colour value }

I have a dataset with 3-hourly precipitation amounts for the month of January in the period 1977-1983 (see attachment). However, I want to generate precipitation data for the period 1984-1990 based upon these data. Therefore, I was wondering if it would be possible to create a custom made probability density function of the precipitation amounts (1977-1983) and from this, generate random numbers (precipitation data) for the desired period (1984-1990). Is this possible in Matlab and could someone help me by doing so? Thanks in advance! A histogram will give you an estimate of the PDF -- just

I've tried to search for an answer, but can't seem to find the right one that does the job for me. I have a dataset ( data ) with two variables: people's ages ( age ) and number of awards ( awards ) My objective is to plot the number of awards against age in R. FYI, a person can have multiple awards and people can have the same age. I tried to plot a histogram and barplot, but the problem with that is that it counts the number of observations instead of summing the number of awards. A sample dataset: age <- c(21,22,22,25,30,34,45,26,37,46,49,21) awards <- c(0,3,2,1,0,0,1,3,1,1,1,1) data <-

I want to group an histogram rowstacked in gnuplot similar to this image: I have these 2 files where the data from the histogram comes from: #Round-robin Input West-Virginia ChicagoI ChicagoII California 1500 28 25 28 19 3000 30 24 25 21 4500 28 28 25 19 6000 34 25 23 18 #Min-makespan Input West-Virginia ChicagoI ChicagoII California 1500 34 20 30 17 3000 33 30 21 16 4500 31 23 38 9 6000 42 21 38 0 plot for [i=2:5] 'cloudusage-roundrobin.dat' using i:xtic(1), \ for [i=2:5] 'cloudusage-minmakespan.dat' using i:xtic(1) 1 - My plot instruction stack both histograms, instead of having them side-by