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Plot contour lines. Call signature: contour( [X,Y,]Z,[levels],**kwargs) contour and contourf draw contour lines and filled contours, respectively. Except as noted, function signatures and return values are the same for both versions. Parameters: X, Yarray-like, optional. The coordinates of the values in Z.
Contour plots in Python with matplotlib: Easy as X-Y-Z. Feb 24, 2020 • A quick tutorial on generating great-looking contour plots quickly using Python/matplotlib.
20 maj 2019 · import matplotlib.pyplot as plt import numpy as np x = [-3,-2,-1,0,1,2,3] y = [1,2] z = np.array([7,5,6,5,1,0,9,5,3,8,3,1,0,4]) X, Y = np.meshgrid(x, y) print (X.shape, Y.shape) # (2, 7) (2, 7) Both have same shape Z = z.reshape(X.shape) # Use either X or Y to define shape fig = plt.figure() ax1 = plt.contourf(X, Y, Z) plt.colorbar(ax1) plt.show()
21 kwi 2020 · The matplotlib.pyplot.contour() are usually useful when Z = f(X, Y) i.e Z changes as a function of input X and Y. A contourf() is also available which allows us to draw filled contours. Syntax: matplotlib.pyplot.contour([X, Y, ] Z, [levels], **kwargs)
Matplotlib contour plots are powerful tools for visualizing three-dimensional data on a two-dimensional plane. This article will dive deep into the world of matplotlib contour plots, exploring their various features, customization options, and practical applications.
Here’s an example of how to create a publication-quality contour plot: import matplotlib.pyplot as plt import numpy as np x = np.linspace(-5, 5, 100) y = np.linspace(-5, 5, 100) X, Y = np.meshgrid(x, y) Z = np.sin(np.sqrt(X**2 + Y**2)) fig, ax = plt.subplots(figsize=(8, 6)) levels = np.linspace(-1, 1, 15) contour = ax.contourf(X, Y, Z, levels ...
Plot contour lines. See contour . import matplotlib.pyplot as plt import numpy as np plt . style . use ( '_mpl-gallery-nogrid' ) # make data X , Y = np . meshgrid ( np . linspace ( - 3 , 3 , 256 ), np . linspace ( - 3 , 3 , 256 )) Z = ( 1 - X / 2 + X ** 5 + Y ** 3 ) * np . exp ( - X ** 2 - Y ** 2 ) levels = np . linspace ( np . min ( Z ), np ...
