and screenshot. Thank you so much!
- Using Python Provide The Solution Code In Text And Screenshot Thank You So Much 1 (86.55 KiB) Viewed 24 times
Using PYTHON, provide the solution code in text and screenshot. Thank you so much!
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Using PYTHON, provide the solution code in text and screenshot. Thank you so much!
Using PYTHON, provide the solution code in text
and screenshot. Thank you so much!
Create a Linear Spline function. The code should take as input, 1D arrays x and fx, that consist of the data point locations, x, and dependent variable values, fx at those x locations. The function should return the coefficients of the linear spline. Thus, a call to the function could look like: coeffs = Linear Spline(x, fx) = You may use np.linalg.solve in this function. Note, this function should be able to take any length x and any length fx and produce the coefficients for a linear spline. This should not be just hard coded to provide the coefficients for the sample data below. a x = np.array([3.0, 4.5, 7.0, 9.01) fx = np.array([2.5, 1.0, 2.5, 0.5))
and screenshot. Thank you so much!
Create a Linear Spline function. The code should take as input, 1D arrays x and fx, that consist of the data point locations, x, and dependent variable values, fx at those x locations. The function should return the coefficients of the linear spline. Thus, a call to the function could look like: coeffs = Linear Spline(x, fx) = You may use np.linalg.solve in this function. Note, this function should be able to take any length x and any length fx and produce the coefficients for a linear spline. This should not be just hard coded to provide the coefficients for the sample data below. a x = np.array([3.0, 4.5, 7.0, 9.01) fx = np.array([2.5, 1.0, 2.5, 0.5))