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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.
A log–log plot of y = x (blue), y = x 2 (green), and y = x 3 (red). Note the logarithmic scale markings on each of the axes, and that the log x and log y axes (where the logarithms are 0) are where x and y themselves are 1. Comparison of linear, concave, and convex functions when plotted using a linear scale (left) or a log scale (right).
A base-10 log scale is used for the Y-axis of the bottom left graph, and the Y-axis ranges from 0.1 to 1000. The top right graph uses a log-10 scale for just the X-axis, and the bottom right graph uses a log-10 scale for both the X axis and the Y-axis. Presentation of data on a logarithmic scale can be helpful when the data:
The linear–log type of a semi-log graph, defined by a logarithmic scale on the x axis, and a linear scale on the y axis. Plotted lines are: y = 10 x (red), y = x (green), y = log(x) (blue). In science and engineering, a semi-log plot/graph or semi-logarithmic plot/graph has one axis on a logarithmic scale, the other on a linear scale.
Example and code for Python using the matplotlib library; ChernoffFace package in Python using the matplotlib library; Function ChernoffFace in Wolfram Language (Mathematica) at Wolfram Function Repository; Example code for MATLAB using Statistics and Machine Learning Toolbox. "Mapping Quality of Life with Chernoff Faces", Joseph G. Spinelli ...
import math import matplotlib.pyplot as plt import numpy as np def main (u: float, points = 200, iterations = 1000, nlim = 20, limit = False, title = True): """ Args: u:float ikeda parameter points:int number of starting points iterations:int number of iterations nlim:int plot these many last points for 'limit' option.
Both axes are in logarithmic scale The roofline model is an intuitive visual performance model used to provide performance estimates of a given compute kernel or application running on multi-core , many-core , or accelerator processor architectures , by showing inherent hardware limitations, and potential benefit and priority of optimizations .
The graph of the logistic map + = is the plane curve that plots the relationship between and +, with (or x) on the horizontal axis and + (or f (x)) on the vertical axis. The graph of the logistic map looks like this, except for the case r = 0: