DescriptionX vs logx.png English: This is a linear regression onto log(x) on the unit interval. The Pearson correlation coefficient r = 0.866. The blue...
This is exactly the same plot as X_vs_logx.png but with the y-axis restricted (which amplifies the difference between log(x) and its linear regression). watson...
log(x) on the interval [.2,1] in blue. Its regression in red. Compare to watson (talk) 21:42, 19 September 2010 (UTC) I, the copyright holder of this...
nan_to_num(iny,0) logx=np.log10(inx) logy=np.log10(iny) logx2=np.log10(outx) #m,b = np.polyfit(logx, logy, 1) coef = np.polyfit(logx,logy,order1) poly1d_fn...
fit_log_poly(inx, iny, outx): logx=np.log10(inx) logy=np.log10(iny) logx2=np.log10(outx) #m,b = np.polyfit(logx, logy, 1) coef = np.polyfit(logx,logy,6) poly1d_fn...
nan_to_num(iny,0) logx=np.log10(inx) logy=np.log10(iny) logx2=np.log10(outx) #m,b = np.polyfit(logx, logy, 1) coef = np.polyfit(logx,logy,order1) poly1d_fn...
