Evaluate a Hermite series at points x with multidimensional coefficient array in Python

Evaluate a Hermite series at points x with multidimensional coefficient array in Python

To evaluate a Hermite series at points x with a multidimensional coefficient array using NumPy, you can use the hermeval function. Here's how you can do it:

  1. Ensure you have numpy installed.
  2. Use the hermeval function, which evaluates the Hermite series at the specified points.

The following example demonstrates how you can use a multidimensional coefficient array to evaluate a Hermite series:

import numpy as np def evaluate_hermite_series(coefs, x): """ Evaluate the Hermite series at points x using the given coefficient array. """ return np.hermeval(x, coefs) def main(): # Define a 2D coefficient array, for example: coefs = np.array([[1, 2, 3], [3, 2, 1]]) # Define evaluation points x = np.array([0, 0.5, 1]) # Evaluate result = evaluate_hermite_series(coefs, x) print("Evaluation Results:") print(result) if __name__ == "__main__": main()

The result will contain the evaluation of the Hermite series for each set of coefficients at each point in x.

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