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The Bode phase plot is the graph of the phase, commonly expressed in degrees, of the argument function ((=)) as a function of . The phase is plotted on the same logarithmic ω {\displaystyle \omega } -axis as the magnitude plot, but the value for the phase is plotted on a linear vertical axis.
Matplotlib (portmanteau of MATLAB, plot, and library [3]) is a plotting library for the Python programming language and its numerical mathematics extension NumPy.It provides an object-oriented API for embedding plots into applications using general-purpose GUI toolkits like Tkinter, wxPython, Qt, or GTK.
The following MATLAB code will plot the root locus of the closed-loop transfer function as varies using the described manual method as well as the rlocus built-in function: % Manual method K_array = ( 0 : 0.1 : 220 ). ' ; % .' is a transpose.
Magnitude transfer function of a bandpass filter with lower 3 dB cutoff frequency f 1 and upper 3 dB cutoff frequency f 2 Bode plot (a logarithmic frequency response plot) of any first-order low-pass filter with a normalized cutoff frequency at =1 and a unity gain (0 dB) passband.
# set terminal svg enhanced size 875 1250 fname "Times" fsize 25 set terminal postscript enhanced portrait dashed lw 1 "Helvetica" 14 set output "bode.ps" # ugly part of something G(w,n) = 0 * w * n + 100000 # 1 / (sqrt(1 + w**(2*n))) dB(x) = 0 + x + 100000 # 20 * log10(abs(x)) P(w) = w * 0 + 200 # -atan(w)*180/pi # Gridlines set grid # Set x axis to logarithmic scale set logscale x 10 set ...
The code is kind of kludgy, but makes a good output. Generated in gnuplot with the script below (save as butterworth_bode_plot.plt and then open in gnuplot). Then it was postprocessed with Inkscape. See Wikipedia graph-making tips. Many orders on one plot: Image:Butterworth orders.png
Ridgeline plot: Several line plots, vertically stacked and slightly overlapping. Q–Q plot : In statistics, a Q–Q plot (Q stands for quantile) is a graphical method for diagnosing differences between the probability distribution of a statistical population from which a random sample has been taken and a comparison distribution.
The test functions used to evaluate the algorithms for MOP were taken from Deb, [4] Binh et al. [5] and Binh. [6] The software developed by Deb can be downloaded, [ 7 ] which implements the NSGA-II procedure with GAs, or the program posted on Internet, [ 8 ] which implements the NSGA-II procedure with ES.