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20 maj 2019 · i'm looking for the best way to create a contour plot using a numpy meshgrid. I have excel data in columns simplyfied looking like this: x data values: -3, -2, -1, 0, 1, 2 ,3, -3, -2, -1, 0, 1, 2, 3. y data values: 1, 1, 1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 2, 2. z data values: 7 , 5, 6, 5, 1, 0, 9, 5, 3, 8, 3, 1, 0, 4.
Use np.meshgrid to create matrices \(X\) and \(Y\) of \(x\) and \(y\) values respectively. Compute matrix \(Z\) of values \(z_{j,i} = f(x_i,y_j)\). Plot the result with plt.contour and specify the number of contour lines. Add a color bar and other figure properties.
In this comprehensive guide, we will explore the best way to create a 2D contour plot using a numpy meshgrid in Python. We will cover various aspects of contour plots, including their applications, the necessary tools, and numerous code examples to demonstrate different use cases.
A contour plot can be created with the plt.contour function. It takes three arguments: a grid of x values, a grid of y values, and a grid of z values. The x and y values represent positions on the plot, and the z values will be represented by the contour levels.
24 kwi 2013 · As has been noted on the matplotlib user list, these functions obey different conventions: pcolormesh expects the x and y values to specify the corners of the individual pixels, while contour expects the centers of the pixels. What is the best way to make these behave consistently?
Comparison of a contour plot of irregularly spaced data interpolated on a regular grid versus a tricontour plot for an unstructured triangular grid. Since contour and contourf expect the data to live on a regular grid, plotting a contour plot of irregularly spaced data requires different methods.
29 lut 2024 · With NumPy’s meshgrid function, you can easily create matrices that define the coordinates for a 2D grid. This is ideal for computing functions of two variables efficiently. Here’s an example: import numpy as np x = np.linspace (-5, 5, 11) y = np.linspace (-5, 5, 11) X, Y = np.meshgrid (x, y) Output:
