diff --git a/SFEM/README.md b/SFEM/README.md index cd7d21846b99e7fb086f2f9f8621f3f98b13fc11..31681396082b1ba661fa0a9501887f1e9bb407ba 100644 --- a/SFEM/README.md +++ b/SFEM/README.md @@ -54,18 +54,21 @@ Instructions for Debian/Ubuntu based workstations are as follows. * [generateRF.py](./generateRF/generateRF.py): * The RF is defined from the mean and standard deviation of the variables as well as from their correlation following for example for a 2-dimension RF: - * meanX = np.array([0.5,10]) # mean of variables - * stdX = np.array([0.05,0.1]) # std of variables - * rho = 0.2 - * R0_XY = np.array([[1, rho], [rho, 1]]) + * ```meanX = np.array([0.5,10])``` # mean of variables + * ```stdX = np.array([0.05,0.1])``` # std of variables + * ```rho = 0.2``` + * ```R0_XY = np.array([[1, rho], [rho, 1]])``` #covariance matrix * And from a the correlation lengths along the 3 direction - * lc = [15., 15., 15.] # correlation length + * ```lc = [15., 15., 15.]``` # correlation length * The number of RFs to be generated follows from * Nsim =10 * The Random fields will be generated at the spatial points defined in terms of their coordinates. * The script tries to read a file in ```mechDir+'/GPData'```, where ```mechDir``` is the working directory, describing the list of spatial points. One example of points coordinates can be found in [rnnRF/GPData/coordinate_P_ZZ_OnPhysical_11.csv](./rnnRF/GPData/coordinate_P_ZZ_OnPhysical_11.csv) stored following 3 coordinates, point number and point volume (for a FE simulation) - * The random field number ```X``` is saved in tge file ```mechDir+'/randomFields'/RandField_X.csv```, where ```mechDir``` is the working directory. The number of columns is the dimension of the random variable and the number of lines the number of spatial points. One example of generated 2-dimension RF can be found in [rnnRF/randomFields/RandField_0.csv](./rrnnRF/randomFields/RandField_0.csv). - * The random field number ```X``` along with the spatial points coordinates is saved in file ```mechDir+'/randomFields'/RandField_And_GP_X.csv```, where ```mechDir``` is the working directory. The number of columns is the dimension of the random variable plus the 3 spatial coordinates and the number of lines the number of spatial points. One example of generated 2-dimension RF can be found in [rnnRF/randomFields/RandField_And_GP_0.csv](./rrnnRF/randomFields/RandField_And_GP_0.csv). + * The random field number ```X``` is saved in tge file ```mechDir+'/randomFields/RandField_X.csv'```, where ```mechDir``` is the working directory. The number of columns is the dimension of the random variable and the number of lines the number of spatial points. One example of generated 2-dimension RF can be found in [rnnRF/randomFields/RandField_0.csv](./rnnRF/randomFields/RandField_0.csv). + * The random field number ```X``` along with the spatial points coordinates is saved in file ```mechDir+'/randomFields/RandField_And_GP_X.csv'```, where ```mechDir``` is the working directory. The number of columns is the dimension of the random variable plus the 3 spatial coordinates and the number of lines the number of spatial points. One example of generated 2-dimension RF can be found in [rnnRF/randomFields/RandField_And_GP_0.csv](./rnnRF/randomFields/RandField_And_GP_0.csv). + * The variable ```recomputePDF=True``` forces the evaluation of the spectral density matrix, which will be saved in ```mechDir+'/randomFields/H_pdf.dat'``` + * The variable ```recomputePDF=False``` reads the spectral density matrix already saved in ```mechDir+'/randomFields/H_pdf.dat'``` +* [plotRF.py](./generateRF/plotRF.py): ### cellRF