correlation

问题 Log polar transform is commonly used in image with phase correlation using Fourier transform for estimating rotation and translation etc. However, I am little confusing how to apply it in audio signal. I am trying to estimate time shift between two audio signal through log polar transform (LPT) and phase correlation. I applied LPT using https://en.wikipedia.org/wiki/Log-polar_coordinates in audio signal and plotter using matlab with polar(theta,rho), until here, there is no problem, problem

问题 I have a correlation matrix like so a b c a 1 0.5 0.3 b 0.5 1 0.7 c 0.3 0.7 1 And I want to transform this into a dataframe where the columns are like this: Letter1 letter2 correlation a a 1 a b 0.5 a c 0.3 b a 0.5 b b 1 . . . . . . Is there a pandas command to allow me to do this? Thanks in advance And a follow up to this, can I assign a value to the letters in Letter1 like so: Value1 Letter1 Value2 letter2 correlation 1 a 1 a 1 1 a 2 b 0.5 1 a 3 c 0.3 2 b 1 a 0.5 2 b 2 b 1 . . . . . . . . .

问题 I have a correlation matrix like so a b c a 1 0.5 0.3 b 0.5 1 0.7 c 0.3 0.7 1 And I want to transform this into a dataframe where the columns are like this: Letter1 letter2 correlation a a 1 a b 0.5 a c 0.3 b a 0.5 b b 1 . . . . . . Is there a pandas command to allow me to do this? Thanks in advance And a follow up to this, can I assign a value to the letters in Letter1 like so: Value1 Letter1 Value2 letter2 correlation 1 a 1 a 1 1 a 2 b 0.5 1 a 3 c 0.3 2 b 1 a 0.5 2 b 2 b 1 . . . . . . . . .

问题 I am plotting various correlation matrices with a different number of columns using seaborn. For the sake of eye-candy, I'd like to have all correlation matrices to have the same cell size. Unfortunately, I am not able to parameterize seaborn to do so. Here is a minimal example: from string import ascii_letters import numpy as np import pandas as pd import seaborn as sns import matplotlib.pyplot as plt # Generate two random dataset rs = np.random.RandomState(42) d1 = pd.DataFrame(data=rs

问题 Is there a way to calculate the normalized cross correlation of two arrays in OpenCV (C++)? http://local.wasp.uwa.edu.au/~pbourke/miscellaneous/correlate/ I have a CvMat and I want to get a correlation matrix of all the cols. I saw cvCalcCovarMatrix but I can't see a way to normalize it to get the correlation. Thanks 回答1: You should use cvMatchTemplate() with method=CV_TM_CCORR_NORMED . 来源： https://stackoverflow.com/questions/4621844/cross-correlation-of-two-arrays-in-opencv

问题 Is there a way to calculate the normalized cross correlation of two arrays in OpenCV (C++)? http://local.wasp.uwa.edu.au/~pbourke/miscellaneous/correlate/ I have a CvMat and I want to get a correlation matrix of all the cols. I saw cvCalcCovarMatrix but I can't see a way to normalize it to get the correlation. Thanks 回答1: You should use cvMatchTemplate() with method=CV_TM_CCORR_NORMED . 来源： https://stackoverflow.com/questions/4621844/cross-correlation-of-two-arrays-in-opencv

问题 I've got too many features in a data frame. I'm trying to plot ONLY the features which are correlated over a certain threshold, let's say over 80%, and show those in a heatmap. I put some code together, and it runs, but I still see some white lines, which have no data, and thus no correlation. Also, I'm seeing things that are well under 80% correlation. Here is the code that I tried. import seaborn c = newdf.corr() plt.figure(figsize=(10,10)) seaborn.heatmap(c, cmap='RdYlGn_r', mask = (np.abs

问题 I am using Python library scipy to calculate Pearson's correlation for two float arrays. The returned value for coefficient is always 1.0, even if the arrays are different. For example: [-0.65499887 2.34644428] [-1.46049758 3.86537321] I am calling the routine in this way: r_row, p_value = scipy.stats.pearsonr(array1, array2) The value of r_row is always 1.0. What am I doing wrong? 回答1: Pearson's correlation coefficient is a measure of how well your data would be fitted by a linear regression

问题 I would like to calculate the correlation coefficient of 2 sound samples using AForge 2.2.5 . I've read from here the formula to calculate Cross Correlation. And here I've read about the formula to calculate the correlation coefficient. This is currently what I have: Prior to calling CrossCorrelation(), FFT has been performed. static Complex[] CrossCorrelation(Complex[] ffta, Complex[] fftb) { var conj = ffta.Select(i => new Complex(i.Re, -i.Im)).ToArray(); for (int a = 0; a < conj.Length; a+

问题 I would like to calculate the correlation coefficient of 2 sound samples using AForge 2.2.5 . I've read from here the formula to calculate Cross Correlation. And here I've read about the formula to calculate the correlation coefficient. This is currently what I have: Prior to calling CrossCorrelation(), FFT has been performed. static Complex[] CrossCorrelation(Complex[] ffta, Complex[] fftb) { var conj = ffta.Select(i => new Complex(i.Re, -i.Im)).ToArray(); for (int a = 0; a < conj.Length; a+