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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.
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.
In comparison, MATLAB boasts a large number of additional toolboxes, notably Simulink, whereas NumPy is intrinsically integrated with Python, a more modern and complete programming language. Moreover, complementary Python packages are available; SciPy is a library that adds more MATLAB-like functionality and Matplotlib is a plotting package ...
using DynamicalSystems, PyPlot PyPlot. using3D # parameters and initial conditions N = 5 F = 8.0 u₀ = F * ones (N) u₀ [1] += 0.01 # small perturbation # The Lorenz-96 model is predefined in DynamicalSystems.jl: ds = Systems. lorenz96 (N; F = F) # Equivalently, to define a fast version explicitly, do: struct Lorenz96 {N} end # Structure for size type function (obj:: Lorenz96 {N})(dx, x, p ...
A rug plot of 100 data points appears in blue along the x-axis. (The points are sampled from the normal distribution shown in gray. The other curves show various kernel density estimates of the data.)
A stem-and-leaf plot of prime numbers under 100 shows that the most frequent tens digits are 0 and 1 while the least is 9. A stem-and-leaf display or stem-and-leaf plot is a device for presenting quantitative data in a graphical format, similar to a histogram, to assist in visualizing the shape of a distribution.
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.
Partial autocorrelation function of Lake Huron's depth with confidence interval (in blue, plotted around 0). In time series analysis, the partial autocorrelation function (PACF) gives the partial correlation of a stationary time series with its own lagged values, regressed the values of the time series at all shorter lags.