Buckets:
| Module file not meant for execution. | |
| --- Running Galerkin (Least Squares) Example --- | |
| ...evaluating matrix... | |
| (0,0) | |
| (0,1) | |
| (0,2) | |
| (1,1) | |
| (1,2) | |
| (2,2) | |
| A: | |
| Matrix([[1, 1/2, 1/3], [1/2, 1/3, 1/4], [1/3, 1/4, 1/5]]) | |
| b: | |
| Matrix([[sqrt(pi)*erf(1)/2], [1/2 - exp(-1)/2], [-exp(-1)/2 + sqrt(pi)*erf(1)/4]]) | |
| coeff: [-18 + 3*exp(-1) + 12*sqrt(pi)*erf(1), -63*sqrt(pi)*erf(1) - 6*exp(-1) + 96, -90 + 60*sqrt(pi)*erf(1)] | |
| approximation: x**2*(-90 + 60*sqrt(pi)*erf(1)) + x*(-63*sqrt(pi)*erf(1) - 6*exp(-1) + 96) - 18 + 3*exp(-1) + 12*sqrt(pi)*erf(1) | |
| Galerkin coefficients: [-18 + 3*exp(-1) + 12*sqrt(pi)*erf(1), -63*sqrt(pi)*erf(1) - 6*exp(-1) + 96, -90 + 60*sqrt(pi)*erf(1)] | |
| Galerkin approximation: x**2*(-90 + 60*sqrt(pi)*erf(1)) + x*(-63*sqrt(pi)*erf(1) - 6*exp(-1) + 96) - 18 + 3*exp(-1) + 12*sqrt(pi)*erf(1) | |
| f: exp(-x**2) | |
| u: x**2*(-90 + 60*sqrt(pi)*erf(1)) + x*(-63*sqrt(pi)*erf(1) - 6*exp(-1) + 96) - 18 + 3*exp(-1) + 12*sqrt(pi)*erf(1) | |
| --- Galerkin Example Finished --- | |
| --- Running Interpolation Example --- | |
| ...evaluating matrix... | |
| (0,0) | |
| (0,1) | |
| (0,2) | |
| (1,0) | |
| (1,1) | |
| (1,2) | |
| (2,0) | |
| (2,1) | |
| (2,2) | |
| A: | |
| Matrix([[1, 0, 0], [1, 0.500000000000000, 0.250000000000000], [1, 1, 1]]) | |
| b: | |
| Matrix([[1.00000000000000], [6.12323399573677e-17], [-1.00000000000000]]) | |
| coeff: [1.00000000000000, -2.00000000000000, -4.44089209850063e-16] | |
| approximation: -4.44089209850063e-16*x**2 - 2.0*x + 1.0 | |
| Interpolation coefficients: [1.00000000000000, -2.00000000000000, -4.44089209850063e-16] | |
| Interpolation approximation: -4.44089209850063e-16*x**2 - 2.0*x + 1.0 | |
| f: cos(pi*x) | |
| u: -4.44089209850063e-16*x**2 - 2.0*x + 1.0 | |
| --- Interpolation Example Finished --- | |
| --- Running Regression Example --- | |
| (...evaluating matrix...) | |
| B: | |
| [[10. 5. ] | |
| [ 5. 3.51851852]] | |
| d: | |
| [5.67128182 2.83564091] | |
| coeff: [0.56712818 0. ] | |
| approximation: 0.567128181961771 | |
| Regression coefficients: [0.56712818 0. ] | |
| Regression approximation: 0.567128181961771 | |
| f: sin(pi*x) | |
| u: 0.567128181961771 | |
| Traceback (most recent call last): | |
| File "/root/finite_difference/src/approx/approx1D.py", line 413, in <module> | |
| comparison_plot( | |
| File "/root/finite_difference/src/approx/approx1D.py", line 324, in comparison_plot | |
| plt.plot(xcoor, approx, '-') | |
| File "/dolfinx-env/lib/python3.12/site-packages/matplotlib/pyplot.py", line 3838, in plot | |
| return gca().plot( | |
| ^^^^^^^^^^^ | |
| File "/dolfinx-env/lib/python3.12/site-packages/matplotlib/axes/_axes.py", line 1777, in plot | |
| lines = [*self._get_lines(self, *args, data=data, **kwargs)] | |
| ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ | |
| File "/dolfinx-env/lib/python3.12/site-packages/matplotlib/axes/_base.py", line 297, in __call__ | |
| yield from self._plot_args( | |
| ^^^^^^^^^^^^^^^^ | |
| File "/dolfinx-env/lib/python3.12/site-packages/matplotlib/axes/_base.py", line 494, in _plot_args | |
| raise ValueError(f"x and y must have same first dimension, but " | |
| ValueError: x and y must have same first dimension, but have shapes (601,) and (1,) | |
Xet Storage Details
- Size:
- 2.99 kB
- Xet hash:
- 1011fe653922acffc643dd41e4b8e0dab75091f8715c204ee84d92693b334b7b
·
Xet efficiently stores files, intelligently splitting them into unique chunks and accelerating uploads and downloads. More info.