Reorganize Tools/ into subfolders, in prevision of LibEnsemble scripts (#908)

* reorganize Tools/ into subfolders, in prevision of LibEnsemble scripts

* Oops, also need to let git know some files have been deleted

* caps for consistency

* few paths to fix

1 files changed, 0 insertions, 290 deletions

diff --git a/Tools/plot_parallel.py b/Tools/plot_parallel.py
deleted file mode 100644
index 6a14ddab4..000000000
--- a/Tools/plot_parallel.py
+++ /dev/null
@@ -1,290 +0,0 @@
-# Copyright 2019 David Grote, Maxence Thevenet
-#
-# This file is part of WarpX.
-#
-# License: BSD-3-Clause-LBNL
-
-import os
-import glob
-import matplotlib
-import sys
-import argparse
-import yt
-yt.funcs.mylog.setLevel(50)
-import numpy as np
-import matplotlib.pyplot as plt
-
-'''
-This script loops over all WarpX plotfiles in a directory and, for each
-plotfile, saves an image showing the field and particles.
-
-Requires yt>3.5 and Python3
-
-It can be run serial:
-
-> python plot_parallel.py --path <path/to/plt/files> --serial
-
-or parallel
-
-> mpirun -np 32 python plot_parallel.py --path <path/to/plt/files>
-
-When running parallel, the plotfiles are distributed as evenly as possible
-between MPI ranks.
-
-This script also proposes options to plot quantities over all timesteps.
-That quantity from of all plotfiles is gathered to rank 0, and the evolution
-is plotted. The default operation is the max of a specified field.
-For example, " --plot_evolution Ey" will plot the max of Ey.
-Also, "--plot_particle_evolution species" for the given species, will plot the RMS x versus the average z.
-
-To get help, run
-> python plot_parallel --help
-'''
-
-# Parse command line for options.
-parser = argparse.ArgumentParser()
-parser.add_argument('--path', default=None,
-                    help='path to plotfiles, defaults to diags/plotfiles. Plotfiles names must be plt?????')
-parser.add_argument('--image_dir', default=None,
-                    help='path where images are placed, defaults to diags/plotfiles or path if specified.')
-parser.add_argument('--plotlib', default='yt',
-                    choices=['yt','matplotlib'],
-                    help='Plotting library to use')
-parser.add_argument('--field', default='Ez',
-                    help='Which field to plot, e.g., Ez, By, jx or rho. The central slice in y is plotted')
-parser.add_argument('--pjump', default=20,
-                    help='When plotlib=matplotlib, we plot every pjump particle')
-parser.add_argument('--vmax', type=float, default=None,
-                    help='If specified, the colormap will have bounds [-vmax, vmax]')
-parser.add_argument('--slicewidth', default=10.e-6,
-                    help='Only particles with -slicewidth/2<y<slicewidth/2 are plotted')
-parser.add_argument('--serial', action='store_true', default=False,
-                    help='Specifies running in serial, avoiding the import of MPI')
-parser.add_argument('--species', dest='pslist', nargs='+', type=str, default=None,
-                    help='Species to be plotted, e.g., " --species beam plasma_e ". By default, all species in the simulation are shown')
-parser.add_argument('--plot_evolution', type=str, default=None,
-                    help='Quantity to plot the evolution of across all data files')
-parser.add_argument('--plot_particle_evolution', type=str, default=None,
-                    help='Will plot the RMS x versus average z of the particles in the given species')
-args = parser.parse_args()
-
-path = args.path
-image_dir = args.image_dir
-plotlib = args.plotlib
-vmax = args.vmax
-plot_evolution = args.plot_evolution
-plot_particle_evolution = args.plot_particle_evolution
-
-if path is None:
-    path = 'diags/plotfiles'
-if image_dir is None:
-    image_dir = path
-
-# Sanity check
-if int(sys.version[0]) != 3:
-    print('WARNING: Parallel analysis was only tested with Python3')
-
-matplotlib.rcParams.update({'font.size': 14})
-pscolor = ['r','g','b','k','m','c','y','w']
-pssize = 1.
-# For 2D data, plot 2D array.
-# For 3D data, plot central x-z slice.
-yt_slicedir = {2:2, 3:1}
-
-# Get list of particle species.
-def get_species(a_file_list):
-    # if user-specified, just return the user list
-    if args.pslist is not None:
-        return args.pslist
-    # otherwise, loop over all plotfiles to get particle species list
-    psset = set()
-    for filename in a_file_list:
-        ds = yt.load( filename )
-        for ps in ds.particle_types:
-            if ps == 'all':
-                continue
-            psset.add(ps)
-    pslist = list(psset)
-    pslist.sort()
-    return pslist
-
-def plot_snapshot(filename):
-    print( filename )
-    # Load plotfile
-    ds = yt.load( filename )
-    # Get number of dimension
-    dim = ds.dimensionality
-
-    # Plot field colormap
-    if plotlib == 'matplotlib':
-        plt.figure(figsize=(12,7))
-        # Read field quantities from yt dataset
-        all_data_level_0 = ds.covering_grid(level=0,left_edge=ds.domain_left_edge, dims=ds.domain_dimensions)
-        F = all_data_level_0['boxlib', args.field].v.squeeze()
-        if dim == 3:
-            F = F[:,int(F.shape[1]+.5)//2,:]
-        extent = [ds.domain_left_edge[dim-1], ds.domain_right_edge[dim-1],
-                  ds.domain_left_edge[0], ds.domain_right_edge[0]]
-        # Plot field quantities with matplotlib
-        plt.imshow(F, aspect='auto', extent=extent, origin='lower')
-        plt.colorbar()
-        plt.xlim(ds.domain_left_edge[dim-1], ds.domain_right_edge[dim-1])
-        plt.ylim(ds.domain_left_edge[0], ds.domain_right_edge[0])
-        if vmax is not None:
-            plt.clim(-vmax, vmax)
-    if plotlib == 'yt':
-        # Directly plot with yt
-        if dim==2: aspect = ds.domain_width[0]/ds.domain_width[1]
-        if dim==3: aspect = ds.domain_width[2]/ds.domain_width[0]
-        sl = yt.SlicePlot(ds, yt_slicedir[dim], args.field, aspect=aspect)
-        if vmax is not None:
-            sl.set_zlim(-vmax, vmax)
-
-    # Plot particle quantities
-    for ispecies, pspecies in enumerate(pslist):
-        if pspecies in [x[0] for x in ds.field_list]:
-            if plotlib == 'matplotlib':
-                # Read particle quantities from yt dataset
-                ad = ds.all_data()
-                xp = ad[pspecies, 'particle_position_x'].v
-                if dim == 3:
-                    yp = ad[pspecies, 'particle_position_y'].v
-                    zp = ad[pspecies, 'particle_position_z'].v
-                    select = yp**2<(args.slicewidth/2)**2
-                    xp = xp[select] ; yp = yp[select] ; zp = zp[select]
-                if dim == 2:
-                    zp = ad[pspecies, 'particle_position_y'].v
-                # Select randomly one every pjump particles
-                random_indices = np.random.choice(xp.shape[0], int(xp.shape[0]/args.pjump))
-                if dim == 2:
-                    xp=xp[random_indices] ; zp=zp[random_indices]
-                if dim == 3:
-                    xp=xp[random_indices] ; yp=yp[random_indices] ; zp=zp[random_indices]
-                plt.scatter(zp,xp,c=pscolor[ispecies],s=pssize, linewidth=pssize,marker=',')
-            if plotlib == 'yt':
-                # Directly plot particles with yt
-                sl.annotate_particles(width=(args.slicewidth, 'm'), p_size=pssize,
-                                      ptype=pspecies, col=pscolor[ispecies])
-    # Add labels to plot and save
-    iteration = int(filename[-5:])
-    image_file_name = os.path.join(image_dir, 'plt_%s_%s_%05d.png'%(args.field, plotlib, iteration))
-    if plotlib == 'matplotlib':
-        plt.xlabel('z (m)')
-        plt.ylabel('x (m)')
-        plt.title('%s at iteration %d, time = %e s'%(args.field, iteration, ds.current_time))
-        plt.savefig(image_file_name, bbox_inches='tight', dpi=300)
-        plt.close()
-    if plotlib == 'yt':
-        sl.annotate_grids()
-        sl.save(image_file_name)
-
-# Compute the evolved quantity from plotfile filename
-def get_evolution_quantity(filename, quantity_name):
-    # Load plotfile
-    ds = yt.load( filename )
-    # Get number of dimension
-    dim = ds.dimensionality
-    # Read field quantities from yt dataset
-    all_data_level_0 = ds.covering_grid(level=0,left_edge=ds.domain_left_edge, dims=ds.domain_dimensions)
-    F = all_data_level_0['boxlib', quantity_name].v.squeeze()
-    zwin = (ds.domain_left_edge[dim-1]+ds.domain_right_edge[dim-1])/2
-    quantity = np.amax(F)
-    return zwin, quantity
-
-def plot_evolved_quantity(zwin_arr, maxF_arr):
-    plt.figure()
-    plt.plot(zwin_arr, maxF_arr)
-    plt.xlabel('z (m)')
-    plt.ylabel('%s (S.I.)'%plot_evolution)
-    plt.title('Field max evolution')
-    plt.savefig(os.path.join(image_dir, 'max_%s_evolution.pdf'%plot_evolution), bbox_inches='tight')
-
-# Compute the evolved particle quantity from plotfile filename
-def get_particle_evolution_quantity(filename, species):
-    # Load plotfile
-    ds = yt.load( filename )
-    dim = ds.dimensionality
-    ad = ds.all_data()
-    x = ad[species, 'particle_position_x']
-    if dim == 2:
-        z = ad[species, 'particle_position_y']
-    else:
-        z = ad[species, 'particle_position_z']
-    return np.mean(z), np.std(x)
-
-def plot_particle_evolved_quantity(zbar, xstd):
-    plt.figure()
-    plt.plot(zbar, xstd)
-    plt.xlabel('ave z (m)')
-    plt.ylabel('rms x (m)')
-    plt.title('%s evolution'%plot_particle_evolution)
-    plt.savefig(os.path.join(image_dir, '%s_evolution.pdf'%plot_particle_evolution), bbox_inches='tight')
-
-def reduce_evolved_quantity(z, q):
-    if size > 1:
-        global_z = np.empty_like(z)
-        global_q = np.empty_like(q)
-        comm_world.Reduce(z, global_z, op=MPI.MAX)
-        comm_world.Reduce(q, global_q, op=MPI.MAX)
-        return global_z, global_q
-    else:
-        return z, q
-
-### Analysis ###
-
-# Get list of plotfiles
-file_list = glob.glob(os.path.join(path, 'plt?????'))
-file_list.sort()
-nfiles = len(file_list)
-
-# Get list of particle speciess to plot
-pslist = get_species(file_list);
-
-rank = 0
-size = 1
-if not args.serial:
-    try:
-        from mpi4py import MPI
-        comm_world = MPI.COMM_WORLD
-        rank = comm_world.Get_rank()
-        size = comm_world.Get_size()
-    except ImportError:
-        pass
-
-if rank == 0:
-    print('number of MPI ranks: %d'%size)
-    print('Number of plotfiles: %s'%nfiles)
-    print('list of species: ', pslist)
-
-if plot_evolution is not None:
-    # Fill with a value less than any possible value
-    zwin = np.full(nfiles, np.finfo(float).min)
-    quantity = np.full(nfiles, np.finfo(float).min)
-if plot_particle_evolution is not None:
-    # Fill with a value less than any possible value
-    zbar = np.full(nfiles, np.finfo(float).min)
-    xstd = np.full(nfiles, np.finfo(float).min)
-
-# Loop over files, splitting plotfile list among MPI ranks
-# - plot field snapshot
-# - store window position and field max in arrays
-for count, filename in enumerate(file_list):
-    if count%size != rank:
-        continue
-
-    plot_snapshot( filename )
-    if plot_evolution is not None:
-        zwin[count], quantity[count] = get_evolution_quantity( filename, plot_evolution )
-    if plot_particle_evolution is not None:
-        zbar[count], xstd[count] = get_particle_evolution_quantity(filename, plot_particle_evolution)
-
-if plot_evolution is not None:
-    zwin, quantity = reduce_evolved_quantity(zwin, quantity)
-    if rank == 0:
-        plot_evolved_quantity(zwin, quantity)
-
-if plot_particle_evolution is not None:
-    zbar, xstd = reduce_evolved_quantity(zbar, xstd)
-    if rank == 0:
-        plot_particle_evolved_quantity(zbar, xstd)
-