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authorGravatar Edoardo Zoni <59625522+EZoni@users.noreply.github.com> 2022-12-02 20:20:17 -0800
committerGravatar GitHub <noreply@github.com> 2022-12-02 20:20:17 -0800
commit2857ca08a97b3a8f82d902480816acac0b9614d6 (patch)
tree5999a62464445e491eeb81a96444f48c0fa41125 /Examples/Tests/PythonWrappers/PICMI_inputs_2d.py
parent3b6a467d1b7dd79ce90b02048dd1c6a0db7b138d (diff)
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Clean up examples folders (#3545)
* Clean up examples folders * Use `snake_case` names * Rename `nci_corrector` as `nci_fdtd_stability`
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-rwxr-xr-xExamples/Tests/PythonWrappers/PICMI_inputs_2d.py295
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diff --git a/Examples/Tests/PythonWrappers/PICMI_inputs_2d.py b/Examples/Tests/PythonWrappers/PICMI_inputs_2d.py
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-#!/usr/bin/env python3
-
-import matplotlib.pyplot as plt
-from mpl_toolkits.axes_grid1.axes_divider import make_axes_locatable
-import numpy as np
-
-from pywarpx import picmi
-
-# Number of time steps
-max_steps = 100
-
-# Grid
-nx = 128
-nz = 128
-
-# Domain
-xmin = 0.e-6
-zmin = 0.e-6
-xmax = 50.e-6
-zmax = 50.e-6
-
-# Cell size
-dx = (xmax - xmin) / nx
-dz = (zmax - zmin) / nz
-
-# Domain decomposition
-max_grid_size_x = 64
-max_grid_size_z = 64
-
-# PML
-nxpml = 10
-nzpml = 10
-field_boundary = ['open', 'open']
-
-# Spectral order
-nox = 8
-noz = 8
-
-# Guard cells
-nxg = 8
-nzg = 8
-
-# Initialize grid
-grid = picmi.Cartesian2DGrid(number_of_cells = [nx,nz],
- lower_bound = [xmin,zmin],
- upper_bound = [xmax,zmax],
- lower_boundary_conditions = field_boundary,
- upper_boundary_conditions = field_boundary,
- guard_cells = [nxg,nzg],
- moving_window_velocity = [0.,0.,0],
- warpx_max_grid_size_x = max_grid_size_x,
- warpx_max_grid_size_y = max_grid_size_z)
-
-# Initialize field solver
-solver = picmi.ElectromagneticSolver(grid=grid, cfl=0.95, method='PSATD',
- stencil_order = [nox,noz],
- divE_cleaning = 1,
- divB_cleaning = 1,
- pml_divE_cleaning = 1,
- pml_divB_cleaning = 1,
- warpx_psatd_update_with_rho = True)
-
-# Initialize diagnostics
-diag_field_list = ["E", "B"]
-field_diag = picmi.FieldDiagnostic(name = 'diag1',
- grid = grid,
- period = 10,
- write_dir = '.',
- warpx_file_prefix = 'Python_wrappers_plt',
- data_list = diag_field_list)
-
-# Initialize simulation
-sim = picmi.Simulation(solver = solver,
- max_steps = max_steps,
- verbose = 1,
- particle_shape = 'cubic',
- warpx_current_deposition_algo = 'direct',
- warpx_particle_pusher_algo = 'boris',
- warpx_field_gathering_algo = 'energy-conserving',
- warpx_use_filter = 1)
-
-# Add diagnostics to simulation
-sim.add_diagnostic(field_diag)
-
-# Write input file to run with compiled version
-sim.write_input_file(file_name = 'inputs_2d')
-
-# Whether to include guard cells in data returned by Python wrappers
-include_ghosts = 1
-
-# Compute min and max of fields data
-def compute_minmax(data):
- vmax = np.abs(data).max()
- vmin = -vmax
- return vmin, vmax
-
-# Plot fields data either in valid domain or in PML
-def plot_data(data, pml, title, name):
- fig, ax = plt.subplots(nrows = 1, ncols = 1, gridspec_kw = dict(wspace = 0.5), figsize = [6,5])
- cax = make_axes_locatable(ax).append_axes('right', size='5%', pad='5%')
- lw = 0.8
- ls = '--'
- if pml:
- # Draw PMLs and ghost regions
- ax.axvline(x = 0 , linewidth = lw, linestyle = ls)
- ax.axvline(x = 0+nxg , linewidth = lw, linestyle = ls)
- ax.axvline(x = -nxpml , linewidth = lw, linestyle = ls)
- ax.axvline(x = nx , linewidth = lw, linestyle = ls)
- ax.axvline(x = nx-nxg , linewidth = lw, linestyle = ls)
- ax.axvline(x = nx+nxpml, linewidth = lw, linestyle = ls)
- ax.axhline(y = 0 , linewidth = lw, linestyle = ls)
- ax.axhline(y = 0+nzg , linewidth = lw, linestyle = ls)
- ax.axhline(y = -nzpml , linewidth = lw, linestyle = ls)
- ax.axhline(y = nz , linewidth = lw, linestyle = ls)
- ax.axhline(y = nz-nzg , linewidth = lw, linestyle = ls)
- ax.axhline(y = nz+nzpml, linewidth = lw, linestyle = ls)
- # Annotations
- ax.annotate('PML', xy = (-nxpml//2,nz//2), rotation = 'vertical', ha = 'center', va = 'center')
- ax.annotate('PML', xy = (nx+nxpml//2,nz//2), rotation = 'vertical', ha = 'center', va = 'center')
- ax.annotate('PML', xy = (nx//2,-nzpml//2), rotation = 'horizontal', ha = 'center', va = 'center')
- ax.annotate('PML', xy = (nx//2,nz+nzpml//2), rotation = 'horizontal', ha = 'center', va = 'center')
- ax.annotate('PML ghost', xy = (nxg//2,nz//2), rotation = 'vertical', ha = 'center', va = 'center')
- ax.annotate('PML ghost', xy = (-nxpml-nxg//2,nz//2), rotation = 'vertical', ha = 'center', va = 'center')
- ax.annotate('PML ghost', xy = (nx-nxg//2,nz//2), rotation = 'vertical', ha = 'center', va = 'center')
- ax.annotate('PML ghost', xy = (nx+nxpml+nxg//2,nz//2), rotation = 'vertical', ha = 'center', va = 'center')
- ax.annotate('PML ghost', xy = (nx//2,nzg//2), rotation = 'horizontal', ha = 'center', va = 'center')
- ax.annotate('PML ghost', xy = (nx//2,-nzpml-nzg//2), rotation = 'horizontal', ha = 'center', va = 'center')
- ax.annotate('PML ghost', xy = (nx//2,nz-nzg//2), rotation = 'horizontal', ha = 'center', va = 'center')
- ax.annotate('PML ghost', xy = (nx//2,nz+nzpml+nzg//2), rotation = 'horizontal', ha = 'center', va = 'center')
- # Set extent and sliced data
- extent = np.array([-nxg-nxpml, nx+nxpml+nxg, -nzg-nzpml, nz+nzpml+nzg])
- else:
- # Draw ghost regions
- ax.axvline(x = 0 , linewidth = lw, linestyle = ls)
- ax.axvline(x = nx, linewidth = lw, linestyle = ls)
- ax.axhline(y = 0 , linewidth = lw, linestyle = ls)
- ax.axhline(y = nz, linewidth = lw, linestyle = ls)
- # Annotations
- ax.annotate('ghost', xy = (-nxg//2,nz//2), rotation = 'vertical', ha = 'center', va = 'center')
- ax.annotate('ghost', xy = (nx+nxg//2,nz//2), rotation = 'vertical', ha = 'center', va = 'center')
- ax.annotate('ghost', xy = (nx//2,-nzg//2), rotation = 'horizontal', ha = 'center', va = 'center')
- ax.annotate('ghost', xy = (nx//2,nz+nzg//2), rotation = 'horizontal', ha = 'center', va = 'center')
- # Set extent and sliced data
- extent = np.array([-nxg, nx+nxg, -nzg, nz+nzg])
- X = data[:,:].transpose()
- # Min and max for colorbar
- vmin, vmax = compute_minmax(X)
- # Display data as image
- im = ax.imshow(X = X, origin = 'lower', extent = extent, vmin = vmin, vmax = vmax, cmap = 'seismic')
- # Add colorbar to plot
- fig.colorbar(im, cax = cax)
- # Set label for x- and y-axis, set title
- ax.set_xlabel('x')
- ax.set_ylabel('z')
- ax.set_title(title)
- # Set plot title
- suptitle = 'PML in (x,z), 4 grids 64 x 64'
- plt.suptitle(suptitle)
- # Save figure
- figname = 'figure_' + name + '.png'
- fig.savefig(figname, dpi = 100)
-
-# Initialize fields data (unit pulse) and apply smoothing
-def init_data(data):
- impulse_1d = np.array([1./4., 1./2., 1./4.])
- impulse = np.outer(impulse_1d, impulse_1d)
- data[nx//2-1:nx//2+2,nz//2-1:nz//2+2] = impulse
-
-# Initialize inputs and WarpX instance
-sim.initialize_inputs()
-sim.initialize_warpx()
-
-# Get fields data using Python wrappers
-import pywarpx.fields as pwxf
-
-Ex = pwxf.ExFPWrapper(include_ghosts = include_ghosts)
-Ey = pwxf.EyFPWrapper(include_ghosts = include_ghosts)
-Ez = pwxf.EzFPWrapper(include_ghosts = include_ghosts)
-Bx = pwxf.BxFPWrapper(include_ghosts = include_ghosts)
-By = pwxf.ByFPWrapper(include_ghosts = include_ghosts)
-Bz = pwxf.BzFPWrapper(include_ghosts = include_ghosts)
-F = pwxf.FFPWrapper(include_ghosts = include_ghosts)
-G = pwxf.GFPWrapper(include_ghosts = include_ghosts)
-Expml = pwxf.ExFPPMLWrapper(include_ghosts = include_ghosts)
-Eypml = pwxf.EyFPPMLWrapper(include_ghosts = include_ghosts)
-Ezpml = pwxf.EzFPPMLWrapper(include_ghosts = include_ghosts)
-Bxpml = pwxf.BxFPPMLWrapper(include_ghosts = include_ghosts)
-Bypml = pwxf.ByFPPMLWrapper(include_ghosts = include_ghosts)
-Bzpml = pwxf.BzFPPMLWrapper(include_ghosts = include_ghosts)
-Fpml = pwxf.FFPPMLWrapper(include_ghosts = include_ghosts)
-Gpml = pwxf.GFPPMLWrapper(include_ghosts = include_ghosts)
-
-# Initialize fields data in valid domain
-init_data(Ex)
-init_data(Ey)
-init_data(Ez)
-init_data(Bx)
-init_data(By)
-init_data(Bz)
-init_data(F)
-init_data(G)
-
-# Advance simulation until last time step
-sim.step(max_steps)
-
-# Plot E
-plot_data(Ex, pml = False, title = 'Ex', name = 'Ex')
-plot_data(Ey, pml = False, title = 'Ey', name = 'Ey')
-plot_data(Ez, pml = False, title = 'Ez', name = 'Ez')
-
-# Plot B
-plot_data(Bx, pml = False, title = 'Bx', name = 'Bx')
-plot_data(By, pml = False, title = 'By', name = 'By')
-plot_data(Bz, pml = False, title = 'Bz', name = 'Bz')
-
-# F and G
-plot_data(F, pml = False, title = 'F', name = 'F')
-plot_data(G, pml = False, title = 'G', name = 'G')
-
-# Plot E in PML
-plot_data(Expml[:,:,0], pml = True, title = 'Exy in PML', name = 'Exy')
-plot_data(Expml[:,:,1], pml = True, title = 'Exz in PML', name = 'Exz')
-plot_data(Expml[:,:,2], pml = True, title = 'Exx in PML', name = 'Exx')
-plot_data(Eypml[:,:,0], pml = True, title = 'Eyz in PML', name = 'Eyz')
-plot_data(Eypml[:,:,1], pml = True, title = 'Eyx in PML', name = 'Eyx')
-plot_data(Eypml[:,:,2], pml = True, title = 'Eyy in PML', name = 'Eyy') # zero
-plot_data(Ezpml[:,:,0], pml = True, title = 'Ezx in PML', name = 'Ezx')
-plot_data(Ezpml[:,:,1], pml = True, title = 'Ezy in PML', name = 'Ezy') # zero
-plot_data(Ezpml[:,:,2], pml = True, title = 'Ezz in PML', name = 'Ezz')
-
-# Plot B in PML
-plot_data(Bxpml[:,:,0], pml = True, title = 'Bxy in PML', name = 'Bxy')
-plot_data(Bxpml[:,:,1], pml = True, title = 'Bxz in PML', name = 'Bxz')
-plot_data(Bxpml[:,:,2], pml = True, title = 'Bxx in PML', name = 'Bxx')
-plot_data(Bypml[:,:,0], pml = True, title = 'Byz in PML', name = 'Byz')
-plot_data(Bypml[:,:,1], pml = True, title = 'Byx in PML', name = 'Byx')
-plot_data(Bypml[:,:,2], pml = True, title = 'Byy in PML', name = 'Byy') # zero
-plot_data(Bzpml[:,:,0], pml = True, title = 'Bzx in PML', name = 'Bzx')
-plot_data(Bzpml[:,:,1], pml = True, title = 'Bzy in PML', name = 'Bzy') # zero
-plot_data(Bzpml[:,:,2], pml = True, title = 'Bzz in PML', name = 'Bzz')
-
-# Plot F and G in PML
-plot_data(Fpml[:,:,0], pml = True, title = 'Fx in PML', name = 'Fx')
-plot_data(Fpml[:,:,1], pml = True, title = 'Fy in PML', name = 'Fy')
-plot_data(Fpml[:,:,2], pml = True, title = 'Fz in PML', name = 'Fz')
-plot_data(Gpml[:,:,0], pml = True, title = 'Gx in PML', name = 'Gx')
-plot_data(Gpml[:,:,1], pml = True, title = 'Gy in PML', name = 'Gy')
-plot_data(Gpml[:,:,2], pml = True, title = 'Gz in PML', name = 'Gz')
-
-# Check values with benchmarks (precomputed from the same Python arrays)
-def check_values(benchmark, data, rtol, atol):
- passed = np.allclose(benchmark, np.sum(np.abs(data[:,:])), rtol = rtol, atol = atol)
- assert(passed)
-
-rtol = 5e-08
-atol = 1e-12
-
-# E
-check_values(1013263608.6369569, Ex[:,:], rtol, atol)
-check_values(717278256.7957529 , Ey[:,:], rtol, atol)
-check_values(717866566.5718911 , Ez[:,:], rtol, atol)
-# B
-check_values(3.0214509313437636, Bx[:,:], rtol, atol)
-check_values(3.0242765102729985, By[:,:], rtol, atol)
-check_values(3.0214509326970465, Bz[:,:], rtol, atol)
-# F and G
-check_values(3.0188584528062377, F[:,:], rtol, atol)
-check_values(1013672631.8764204, G[:,:], rtol, atol)
-# E in PML
-check_values(364287936.1526477 , Expml[:,:,0], rtol, atol)
-check_values(183582352.20753333, Expml[:,:,1], rtol, atol)
-check_values(190065766.41491824, Expml[:,:,2], rtol, atol)
-check_values(440581907.0828975 , Eypml[:,:,0], rtol, atol)
-check_values(178117294.05871135, Eypml[:,:,1], rtol, atol)
-check_values(0.0 , Eypml[:,:,2], rtol, atol)
-check_values(430277101.26568377, Ezpml[:,:,0], rtol, atol)
-check_values(0.0 , Ezpml[:,:,1], rtol, atol)
-check_values(190919663.2167449 , Ezpml[:,:,2], rtol, atol)
-# B in PML
-check_values(1.0565189315366146 , Bxpml[:,:,0], rtol, atol)
-check_values(0.46181913800643065, Bxpml[:,:,1], rtol, atol)
-check_values(0.6849858305343736 , Bxpml[:,:,2], rtol, atol)
-check_values(1.7228584190213505 , Bypml[:,:,0], rtol, atol)
-check_values(0.47697332248020935, Bypml[:,:,1], rtol, atol)
-check_values(0.0 , Bypml[:,:,2], rtol, atol)
-check_values(1.518338068658267 , Bzpml[:,:,0], rtol, atol)
-check_values(0.0 , Bzpml[:,:,1], rtol, atol)
-check_values(0.6849858291863835 , Bzpml[:,:,2], rtol, atol)
-# F and G in PML
-check_values(1.7808748509425263, Fpml[:,:,0], rtol, atol)
-check_values(0.0 , Fpml[:,:,1], rtol, atol)
-check_values(0.4307845604625681, Fpml[:,:,2], rtol, atol)
-check_values(536552745.42701197, Gpml[:,:,0], rtol, atol)
-check_values(0.0 , Gpml[:,:,1], rtol, atol)
-check_values(196016270.97767758, Gpml[:,:,2], rtol, atol)