Find QuantilesJames J Balamuta
R= range H= highest value L= lowest value The range is the easiest measure of variability to calculate. To find the range, follow these steps: Order all values in your data set from low to high. Subtract the lowest value from the highest value. ...
(); int numBinsY = histogram->GetNbinsY(); if ( zAxisNormOption == kNormByQuantiles ) { std::vector<double> binContents; for ( int iBinX = 1; iBinX <= numBinsX; ++iBinX ) { for ( int iBinY = 1; iBinY <= numBinsY; ++iBinY ) { binContents.push_back(histogr...
abs(array - values).argmin(axis=-1) return array[indices] image = plt.imread('example_3_band_image.jpg') print(image.shape) # should be (nrows, ncols, 3) quantiles = np.linspace(0, 255, num=2 ** 2, dtype=np.uint8) quantiled_image = find_nearest(quantiles, image) print(quant...
(2) the actual differential PSI value is represented as quantiles of a log-normal distribution (Additional file 1: Fig. S10). The mean and variance of the log-normal distribution, along with quantiles of the original ∆PSI values, are stored. The first step is lossless while the second ...
segmented_rfm['r_quartile'] = segmented_rfm['recency'].apply(RScore, args=('recency',quantiles,)) segmented_rfm['f_quartile'] = segmented_rfm['frequency'].apply(FMScore, args=('frequency',quantiles,)) segmented_rfm['m_quartile'] = segmented_rfm['monetary_value'].apply(FMScore, args=...
FINDis designed for problems in which we have two biological conditions , each with a certain number of Hi-C replicates . FINDis based on the simple idea that the establishment of a chromatin loop between two loci and , a "mountain shape" structure should be formed (due to the spatial de...
Find outliers based on quantilesdataSeries
quantiles = quantiles.to_dict() Create a segmented RFM table segmented_rfm = rfmTable The lowest recency, highest frequency and monetary amounts are our best customers. def RScore(x,p,d): if x <= d[p][0.25]: return 1 elif x <= d[p][0.50]: ...